Canute Hyandye and I.B.katega GIS -Journal of Environmental Science and Engineering,Vol4,No9,2010

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Volume 4, Number 9, September 2010 (Serial Number 34)

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Journal of Environmental Science and Engineering

Volume 4, Number 9, September 2010 (Serial Number 34)

Contents

Aquatic Environment 1 Radiation-Chemical Situation of the Waters of the Middle Reach of the River Yenisei (Russian

Federation) L. Bondareva and A. Zhizhaev

12 Hydraulic Properties of Rocky Mountain First-Order Alluvial Systems and Diurnal Water-Level Fluctuations in Riparian Vegetation: An Analysis in Hay Creek, Whitetail Basin, Montana W.D. Weight and K. Chandler

24 Discussion on Irrigation Development and Its Investment Focus in Tanzania Q.F. Shuai, J.Z. Xu, X.P. Liang, G.M. Kalinga and J. Kayumbe

Environmental Ecology and Biotechnology 32 Natural Barriers to Eco-environmental Vulnerability in a Complex Ecosystem

C.B. Hyandye and I.B. Katega 40 Study on the Sulfur Nutrition of the Sugarcane and Balance of Sulfur in Soil for Sugarcane

Planting Areas H.W. Tan, L.Q. Zhou, R.L. Xie and M.F. Huang

Environment Monitoring and Pollution Control 44 Characterization of Suspended Solids and Heavy Metal Distributions during First Flush in

Highway Runoff W.C. Liu, W.Z. Huang and A.Y. Yang

51 Brownfield Phytoremediation of Heavy Metals Using Brassica and Salix Supplemented with EDTA: Results of the First Growing Season F.E. Pitre, T.I. Teodorescu and M. Labrecque

Environmental Assessment 60 Iron Reduction and Adsorption on Shewanella Putrefaciens nearby Landfills in Northwest

Florida P.K. Subramaniam, L. Martin, P. Grasel, K. Tawfiq and G. Chen

70 Temporal Changes on Pollutants Associated with Sewage Sludge S.M. Al-Muzaini and T.E. Al-Obied

79 Traffic Emission Control: A Knowledge Based Approach K.M. Rajeev, P. Manoranjan and R. Santosh

Sept. 2010, Volume 4, No.9 (Serial No.34) Journal of Environmental Science and Engineering, ISSN 1934-8932, USA

Radiation-Chemical Situation of the Waters of the Middle Reach of the River Yenisei (Russian Federation)

L. Bondareva1 and A. Zhizhaev2

1. Siberian Federal University, Krasnoyarsk 660041, Russia

2. Institute Chemistry and Chemical Technology SBRAS, Krasnoyarsk 660036, Russia

Received: June 8, 2010 / Accepted: July 5, 2010 / Published: September 20, 2010.

Abstract: The results of monitoring the radiation-chemical situation in the middle reach of the Yenisei River located in the nearest zone of the influence of the Mining and Chemical Combine of Rosatom have been described in the paper. Using different physico-chemical methods, it has been found that uranium and tritium content in the water exceeds the background values of the flood plain of the River Yenisei. It has been shown that a wide range of radionuclides of different genesis flows into the waters of the Yenisei River. It has been demonstrated that radionuclides are transported by the water flow in the form of molecular solution or with suspended matter. In this case, the suspended matter consists of pelitic finely dispersed mineral particles, plant and organic detritus and living biological objects (for example, worms). It has been shown that the main contribution to radionuclide and metal accumulation is made by humic substances covering the particles of the suspended matter and actively participating in the formation of complexes with radionuclides and heavy metals. As a result of this work, the artificial radionuclide inflow into the ecosystem of the River Yenisei has been evidenced. Key words: Artificial radionuclides, Yenisei River, mass transfer, water suspension.

1. Introduction

There is a Mining and Chemical Combine of Rosatom (MCC) on the left bank of the Yenisei, 50 km downstream from Krasnoyarsk. MCC includes radiochemical facilities and nuclear reactors. The production facilities of the plant are located on both banks of the River Yenisei and connected by a tunnel under the river bed. Since 1958, MCC has used water for cooling industrial reactors to produce weapon-grade - 238Pu. The river water after passing through the cooling system of the reactors has been brought back to the River Yenisei. In the discharges a significant amount of radionuclides has been indicated which form due to neutrons activating the admixtures (solid suspensions and dissolved substances) contained in the river water. Two once-through reactors were

Corresponding author: L. Bondareva (1965- ), female,

Ph.D., senior researcher, associate professor, main research fields: radioecology, migration radionuclides in fresh water, ecosystems. E-mail: [email protected].

taken out of service in 1992, therefore, the reactivity level in the effluents discharged from the MCC area decreased. The last reactor with a closed circuit which is to be stopped in 2010 has been operating till nowadays.

The ecosystem of the River Yenisei contains a significant amount of artificial radionuclides due to a fifty years’ activity of MCC [1]. In particular, the increased level of radioisotope content in the bottom sediments and flood plain soils [1, 2] and radionuclide distribution regarding migration forms both in the nearest zone of the MCC influence [3, 4], and at a considerable distance from the discharge point including the estuary of the River Yenisei have been shown [5].

The analysis of the data available in literature on studying the content and distribution of radionuclides with regard to the components of the Yenisei flood plain shows that there is only fragmentary non- systemic evidence on the total content of radionu-


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clides, and there is almost no information concerning their immobilization states. The most studied are the bottom sediments and flood plains of the River Yenisei. These studies were mainly carried out in the periods of the active operation of the reactors, namely, in 1972-1991 [6]. There is a number of papers on the mathematical simulation analysis of the radionclide behavior in the system “water-suspensions-bottom sediments of the River Yenisei”. However, the models described were obtained for the data of the radiation monitoring in 1972-1992 [7, 8].

The main aims of the current study have been: (1) to study the contemporary radiation- chemical situation of the middle reach of the River Yenisei; (2) to study the material composition of water suspensions in the nearest zone of the MCC influence which transport radionuclides and heavy metals.

2. Materials and Methods

2.1 Study Area

A great part of the population of the Krasnoyarsk Region lives on the banks of the River Yenisei. The Yenisei is one of the biggest rivers in the world: its longitude from the conflux of the Big Yenisei and Little Yenisei to the Kara Sea is 3,487 km (from the headstreams of the Little Yenisei-4287 km, from the headstreams of the Big Yenisei-4123 km). The conflux of the Big and Little Yenisei, near the town Kyzyl is considered to be the geographical center of Asia. Starting in the south of in the mountain deserts of Mongolia, the River Yenisei over almost 3,000 km flows to the north across different latitudinal geographical zones and inflows into the Arctic Ocean, forming an estuary up to 30 km wide. The length is bigger than that of the rivers Danube (2,857 km); Mississippi (3,770 km); Indus (3,180 km). The Yenisei is the most full-flowing river of Russia with an annual watershed yield 624 km3. The average water discharge in the estuary is 19,800 m³/sec, the maximal one is up to 190,000 m³/sec. As to the basin area (2,580 thousand kmІ), the Yenisei is the second river in Russia (after the

river Ob) and the seventh in the world. The River Yenisei is the nominal boundary between the West and East Siberia. There are three hydroelectric power stations on the Yenisei and tributaries. The river water is highly transparent (up to 3 meters) and has low mineralization (the mean value is 54 mg/L) as well as high oxygen concentration. The flow speed and the river width vary significantly: from 1.5 to 12-15 km/h and from 0.2-0.5 km to 3-5 km. In the upper reaches of the river bed there are glacial boulder beds and cobble deposits which in the middle reach change into sandy gravel and sandy-clayish ones in the lower current of the river near the inflow into the Arctic Ocean.

The operation of the greatest hydropower stations results in constant mixing of water layers. Due to this, at a big distance down from the hydropower station the water temperature almost doesn’t change with the depth of the water flow. In early July, the water temperature in the area near the Krasnoyarsk city and 100-150 km downstream is 10 ℃, and in the late July-August 15-17 ℃. The river ecosystem is an oligotrophic one with rich river fauna, there being more than 500 species of algae and diatoms [9].

The investigations were carried out in the middle reach of the River Yenisei at the site 15 km (from the inflow of the Plosky stream (0 km) to the village Bolshoy Balchug (15 km)) (Fig. 1).

At the water discharge Q=4085 m3/s at the given

Fig. 1 Review scheme of the study area. Sampling points: “0 km”- 56°27′05′′N, 93°36′31′′E; “2 km”- 56°23′18′′N, 93°37′13′′E, “5 km”- 56°23′40′′N, “15 km”- 56°27′05′′N, 93°42′22′′E.


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site the depth of the river and current speed are determined to be H≈7 m, v=1.25-1.8 m/s, correspondingly. The stream with technogenic admixtures propagates along the right bank of the river not more than 0.1 of the width of the river, i.e. along the flood plain where the river flow speed and the width are several times less.

2.2 Sampling Technique

Water samples were taken every month in summer-autumn low-water during several years. The samples were taken in the upper layer of the stream (0-10 cm) into plastic bottles of 25 L. The samples to be studied were taken along the right bank, at a distance of 40-60 m from the edge of the river bank. Controls were taken at a distance of 500 m from the edge of the left bank, on the main waterway characterized by the highest current speed and the biggest depth.

2.3 Preparation of Samples

2.3.1 Ultra-Filtration of Suspensions Just after sampling 1 L of the sample was

ultra-filtered successively through acetate-cellulose membrane filters Millipore (with a diameter of 47 mm), the pore size being 5, 1, 0.45 and 0.2 μm to separate suspensions and fractionate them according to the pore size. The precipitates on the filters were dried till air-dried state and the morphology and particle composition were studied with an electron microscope. The precipitate was also studied to determine gross elemental composition by size fractions.

2.3.2 Preparation for the Analysis of Uranium and Tritium Content

Another part of the sample (100 mL) was separated from suspended particles by filtering through acetate-cellulose membrane filters Millipore (diameter 47 mm), the pore size being 0.2 μm, to analyze the filtrate for determining uranium and tritium content.

To determine tritium, the filtrates obtained were mixed with the scintillation cocktail Ultima Gold AB at a ratio sample:cocktail = 8:12. Before taking measure-

ments the mixture was kept for 48 hours in the dark at a temperature 4 ℃ for the system stabilization.

To determine uranium, an aliquot (10 mL) of each filtrate was conserved by adding HNO3 at a ratio of 1 mL of the concentrated acid per 1 L of the sample.

2.3.3 Concentration of Radionuclides The biggest remaining part of the sample was

concentrated following the technique suggested by Bondareva and co-workers [10]. For this purpose, 20 mL of pure HNO3, the solution of 241Am (NO3)3 (with the content of 241Am - 12 Bq/sample) and 5 mL of the Fe(III) solution (CFe= 5 mg/mL) were added to the sample (20 L) in a transparent polyethylene bottle. It was carefully mixed and allowed to stay overnight for equilibration. Then, the solution of NH4OH (25 %) was added to the sample up to рН 8-9. Then, 1 mL of KMnO4 solution (60 g/L) was added and just after mixing, 0.2 mL of MnCl2 solution (40 g/L) was finally added. The resulting solution was carefully mixed once again and left for 24 hours for precipitation. After that, the bigger part of the liquid phase was eliminated by decantation. The remaining liquid was separated from the precipitate by filtering through the paper filter, its pore diameter being 3.5 μm. The precipitate on the filter was put into a special polyethylene vessel-“denta”-and analyzed with a gamma-spectrometer. The chemical yield of 241Am was about 95%.

2.3.4 Studying the Filters with the Precipitates The filters Millipore, used for the ultra-filtration,

were pre-dried at t = 35 ℃ to obtain constant weight (for 48 h). After filtering the filters were also dried up to constant weight and, then, weighed. A segment comprising about 25% of the total filter area was cut from the dried filters. The segment was dissolved in H2O2 in the presence of HNO3 for three hours until the complete cessation of the reaction. In case of the presence of undissolved fragments, after diluting with distilled water the solution was separated from suspensions by centrifuging (6000 rpm, during 15 min) and the liquid was separated from the precipitate by decantation.


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2.4 Sample Analysis

2.4.1 Gamma-Spectroscopy A part of the original sample without any filtering

was poured into the vessel Marinelli (1 L) and the content of gamma-radiating radionuclides in the original sample was measured with the gamma spectrometer Canberra (USA) with a high purity germanium detector. Similarly, the concentrates and filtrates obtained were analyzed.

2.4.2 Determination of the Tritium Content Tritium content in the samples was determined with

the liquid-scintillation spectrometer Tri-Carb 2800 (USA).

2.4.3 ICP-MS Uranium and other elements in filtrates and solutions

obtained after dissolving the filters in Н2О2 at heating were determined by the method of mass-spectrometry with an inductively coupled plasma (ICP-MS) using the quadrupole mass spectrometer Agilent 7500а (Agilent Technologies, USA). The samples were 125-times diluted with HNO3 solution (0.3 mass.%) in deionized water.

Deionized water was obtained using the water purification system Direct-Q 3 UV (Millipore, France). The resistance of the purified water was equal to 18.2 megoohm. Commercial nitrogen acid of analytic grade was additionally purified by subdistillation (below the boiling temperature) using the installation DuoPure (Milestone, Italy).

2.4.4 Electron Microscopy Electron-microscopic studies were carried out using

the electron scanning microscope ТМ-1000 (Hitachi, Japan), with the X-ray spectral energy-dispersive analyzer SwiftED (Oxford Instrument Analytical, England) when taking images in back-scattered electrons with the accelerating voltage of 15 kV in the low vacuum regime.

The studies were carried out without any preliminary sputtering of conducting coatings over the samples. The filters with the suspensions separated by ultra-filtration were directly fixed with a double-sided

adhesive conductive carbon tape on the specimen mount and placed into the chamber of the electron microscope. Micrographs scanned in back-scattered electrons were collected into a separate file and were subjected to standard digital processing to increase the image sharpness and contrast. Spectral analysis of some sections of the sample (selected particles, characteristic details) was made.

3. Results and Discussion

3.1 Radionuclide Content in the Water of the River Yenisei in the Middle Reach of MCC

The most widely spread indicator of the background radiation of water sources is the total uranium content, its value being normalized and controlled by environmental services. In waters uranium is present in the molecular solution - in the form of uranyl-carbonate complex anions. The river water contains on the average 600 ng/L of dissolved uranium. Despite the fact that the main natural transporting agent - water - transports uranium in a negligible amount, one can’t exclude the situation of local uranium transport in considerable quantity.

The results of the water sample analysis of the River Yenisei concerning the total uranium content are given in Table 1.

The evidence presented reveals that the uranium content in the mouth of the Plosky stream, “0 km”, is 6-9 times higher than the background uranium values,

Table 1 Results of determining uranium content in the water of the Yenisei River (sampling in 2006-2009).

Concentration of uranium (μg/L) Control “0 km” “2 km”

May-June 0.18±0.03 1.70±0.04 0.85±0.06 July 0.24±0.05 2.00±0.05 1.10±0.04 August 0.18±0.04 1.10±0.03 1.30±0.05 September 0.32±0.05 2.70±0.02 1.10±0.05

Table 2 Ratio of uranium isotopes in the water samples collected at the sampling site “0 km”.

238U/235U 238U/234U 236U/234U 2007 2008 2007 2008 2007 2008 119±3 120±3 1.3×104 0.8×104 ~0.2 ~0.1


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characteristic of the River Yenisei. Isotopic analysis of some water samples was carried out. The results obtained are shown in Table 2.

It is known that natural uranium consists of a mixture of three isotopes: 238U-99.2739% (T1/2=4.468×109 years), 235U-0.7024% (T1/2= 7.038×108 years) and 234U-0.0057% (T1/2= 2.455×105 years). Independent of high migration ability of uranium for the latter two, unlike other isotope pairs, the geographical constancy of the ratio 238U/235U = 137.88 is relevant [11, 12]. In the water samples of the River Yenisei (at the sampling site “0 km”) the ratio 238U/235U amounts to 119-120. Moreover, an artificial uranium isotope 236U (Т1/2= 2.39×107 years) was also found, its ratio to the isotope 234U being 236U/234U ~0.1-0.2. Thus, one can argue that the increased uranium content in the River Yenisei water is due to the operation of MCC.

The increased tritium content can be another indicator of discharging artificial radionuclides into the water of the Yenisei. Therefore, the tritium content was determined in the collected water samples. The results are presented in Table 3.

As it can be seen from the results presented, the tritium content at the sampling site “0 km” is 15-20 as high as that of the background tritium content, obtained as a result of long-term monitoring and characteristic of the River Yenisei (4±2 Bq/L) [13].

To confirm the technogenic origin of tritium in the water samples, controls were taken to determine gamma-radiating radionuclide content. As a result, it was found that the water under study contains a significant amount of artificial radionuclides (Table 4).

Radionuclide content in natural sources is known to be ultra low, and pre-concentration methods are most frequently used to determine these radionuclides. For this purpose, either the techniques allowing one to separate the desired elements from the main matrix are used sorption on adsorbents or sedimentation in the suspensions of the corresponding compounds [14, 15] or one can employ the techniques eliminating the main

Table 3 Average tritium content in the water samples of the Yenisei River, (distance downstream from the discharge sites of the MCP territory), 2002-2009.

Concentration tritium (Bq/L) Region average min max

control 4.5 4 6 “0 km” 85 35 200 “2 km” 25 17 39 “5 km” 11 9 15 “15 km” 8 5 11

Table 4 Average radionuclide content in the Yenisei River water, the site “0 km” (2006-2009).

Concentration radionuclides (Bq/L) average min max

24Na 256 114 481 51Сr 4.97 1.39 11.8 54Mn 0.37 0.07 0.8 76As 5.7 1.2 19 85Sr 0.35 0.07 0.8 99Mo 0.6 1.61 27.3 137Cs 0.22 0.03 0.54 239Np 9.22 1.61 27.3

Table 5 Average radionuclide content in the Yenisei River water, the site “0 km”, after preconcentration (2006-2009).

Concentration radionuclides (Bq/L)

average min max 24Na 1.39 0.6 2.5 46Sc 0.11 0.02 0.47 51Cr 2.86 0.47 10.7 54Mn 0.35 0.02 0.9 59Fe 0.08 0.01 0.16 60Co 0.09 0.02 0.13 65Zn 0.04 0.02 0.13 76As 8.72 0.7 18.4 85Sr 0.01 <MDA 0.03 99Mo 0.04 0.01 0.93 103Ru 0.02 <MDA 0.03 106Ru 0.05 0.03 0.08 124Sb 0.01 0.01 0.02 131I 0.03 <MDA 0.05 133I 0.82 0.16 1.6 137Cs 0.07 0.03 0.14 141Ce 0.03 0.02 0.05 144Ce 0.08 0.04 0.13 239Np 11.31 1.54 29.5

MDA - minimum detective activity.


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Matrix, e.g., concentration by evaporation [16]. Use was made of a technique which allows one to precipitate radionuclides with various physico-chemical properties (Table 5).

The results obtained enabled one to separate the isolated radionuclides, when precipitating Fe(III) oxyhydroxide and dioxide of manganese MnO2 on the suspension, into two groups: (1) radionuclides with a variable oxidation rate (e.g., 76As) and (2) radionuclides with a constant oxidation rate.

Thus, the Yenisei River water contains a great variety of artificial radionuclides which differ in their half-life period, the nature of origin and physico-chemical properties (e.g., with the variable or constant oxidation rate in non-equilibrium environment conditions).

3.2 Material Composition of the Water Suspensions

As a result of ultra-filtration, it was found that the main part of the suspended particles (up to 90%) was concentrated in the pelitic fraction >5 μm. The filters with the suspensions were fixed on the specimen mount with the help of the conducting double-sided adhesive carbon type and placed into the electron microscope chamber. The scanned micrographs in the back-scattered electrons were collected into a separate file and subjected to standard digital processing to improve the image sharpness and contrast. The precipitate was found to contain particles of quartz, mica and iron-containing minerals (limonitic and magnetic iron), mainly, with the size not exceeding 10-15 μm. Also, the precipitate revealed the presence of a considerable amount of various biological objects (diatoms, annelids, plant spores, etc.). All the mineral particles and biota were covered with a layer of fine limonitic-clayish particles. Spectral analysis of some parts of the sample (selected particles, characteristic details) was carried out. The primary determination of the diatoms was made according to a reference book [17]. The suspended matter contains a large colony of diatoms, for example, Meridian circulare, some

cyclotellas and opyphoros, Cyclotella vor. Jacutca. Fig. 2 presents a great amount of algae among quartz

and mica debris: a colony of Meridian circulare, diatoms, some cyclotellas and opyphoros. At the right top one can see a calcite plate. Fig. 3 shows Cyclotella vor. Jacutca which is frequently found in the samples among quartz and mica debris. The diameter of the silicate skeleton gaps is of the order of 90 nm.

Fig. 2 Material composition of the water suspensions (separated by the ultra-filtration method). The fraction ≥ 5 μm. Magnification power of ×1000.

Fig. 3 Material composition of the water suspensions (separated by the ultra-filtration method). The fraction ≥ 5 μm. Magnification power of ×2000.

Cyclotella vor.

Cyclotella vor.

Opephora martui

Quartz

Diatoma

Calcite

Opephora

Cyclotella vor.

Meridian


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Fig. 4 Energy-dispersive X-ray spectrum. Fraction ≥ 5 μm. Magnification × 10000. Magnetic iron microsphere, the size is about 5.3 μm.

Fig. 5 Energy-dispersive X-ray spectrum. Fraction ≥ 5 μm. Magnification × 3000. Silicate microsphere, the size is about 12 μm.

Figs. 4 and 5 present the results of X-ray spectral analysis of single particles. A magnetic iron microsphere with a diameter of about 5.3 μm and iron content of higher than 60% is given in Fig. 4. Fig. 5 shows a silicate microsphere with a diameter of about 12-15 μm. The latter two particles could be the result of industrial activity: heat power plants or coal boilers as the particles of such morphology and composition are characteristic of coal ash.

The fraction with the size of “5-1 μm” uniformly covers the filter surface with a layer of fine particles. The brown-colour precipitate consists mainly of mineral components (calcite, clays, clayish minerals,

quartz and gypsum debris). The color is due to iron compounds. However, there are diatoms of a definite species and size (of about 4.7 μm across) (e.g., Diatoma vulgaric), whose valves consist mainly of silicon oxide (higher than 80%).

The fraction “1-0.2 μm” uniformly covers the filter surface with a layer of fine particles of the micron and submicron size, they are mainly aluminosilicate compounds having various structure and composition, limonite, calcite and gypsum. The precipitate colour is light-brown. The fraction has rather uniform material composition.

The material composition of the solid suspensions in


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the Yenisei River water generally corresponds to the inorganic composition of the rocks and their hypergenesis products forming the river bed and banks. Sometimes, the admixture of particles having technogenic origin (ash wastes from boilers) is observed.

The material composition of the suspensions correlates with the composition of the river bed sediments, in particular, that of the River Yenisei and consists of fine quartz and alumosilicate debris, detritus. Also, various clays and clayish minerals are present, in particular, micaceous alumosilicates and titaniumsilicates.

3.3 Artificial Radionuclide and Metal Distribution According to Granulometric Fractions

3.3.1 Artificial Radionuclides Without going into the details of the ion-molecular

equilibrium, it may be considered that in the river water radionuclides are present in the dissolved form, as well as on the surface of or inside suspended fine solid particles which are considerably different in their size and the nature of origin.

The fine particles of a suspended organomineral sol actively adsorb heavy elements from the solution; as a result, dynamic equilibrium is established characterizing the radionuclide mobility. Considering the heavy particle sedimentation and artificial radionuclide redistribution in the surface layer of the Yenisei River water between the liquid and the solid phases, as well as between the particles of various sizes, one could trace the radionuclide and metal transport peculiarities downstream from the discharge point to determine a possible accumulating agent.

To determine the influence of the particles of various sizes on the radionuclide transport, samples of the suspended substance were taken from the sampling sites “0 km” and “2 km” and further fractionated by the ultra-filtration method. The results are the following.

At the sampling site “0 km”, when the time of the discharge contact with the river water was insignificant,

the radionuclides 3H, 24Na, 60Co, 239Np and also, 99Mo (~90%) were mainly presented as a fraction <0.2 μm (filtrate). These can be both free ions in the molecular solution (e.g., 24Na+), and molecules or sorbed ions in colloid particles which managed to pass through a 0.2 μm filter. The solid phase is mainly presented by 46Sc, 214Bi, 103Ru, with the last two isotopes being in the most coarse fraction (more than 90% of them). 85Sr and 131I have less uniform phase distribution. 76As is almost absent in the most coarse fraction (≥5 μm).

In the samples taken “2 km” downstream, there is a decrease of the total activity, first of all, due to the coarse particle sedimentation. The radionuclide redistribution according to the size fractions was found: almost the whole amount of 60Co is concentrated in the fraction with the size of ≥1μm, a considerable amount of 214Bi is transformed into a solution (the fraction<0.2 μm), almost 40% of 99Mo and up to 70% of 24Na are transformed into the fraction of 1-0.2μm. With the total background level decrease, there appear natural radionuclides 212Pb and 234Th in the solid phase as well as 65Zn in the solution.

The element distribution between the two compartments is determined by their physico-chemical affinity to the matrix components and transport parameters regulating the apparent equilibrium in the system. Exchange reactions inside and between the compartments are essential in establishing the dynamic equilibrium, with its establishing time depending on the environmental conditions [18]. Regarding the adaptation of natural systems to radioactive contamination, the most interesting is the revealed total or partial natural immobilization of 60Co, 99Mo, 24Na in the influence zone of the Mining and Chemical Combine.

3.3.2 Metals The results of the total elemental analysis of the

suspension fragments by the methods of ICP-MS showed that “2 km” downstream from the discharge point of the Mining and Chemical Combine there was a considerable redistribution of the elements according


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to the size fractions of the suspended substance. Thus, if at the site “0 km”, in addition to the fragments ≥5 μm, a considerable contribution to the mass transport of metals is made by the fragments of the suspended substance with the size of 5-1 μm, then, at the point 2 km downstream the fragments ≥5 μm dominate with some contribution of the fragments with the size of 0.45-0.2 μm.

The MCC components as well as biological objects are known to be able to accumulate artificial radionuclides and metals due to a great complex-forming ability [19]. Therefore, when entering the water flow, metals and radionuclides interact with the organic suspension constituent rather quickly, forming stable complex compounds with certain components of this suspension. In this connection, the complexes formed are either deposited on the surface of the bed sediments or transported to considerable distances by the water flow as soluble compounds or a suspension.

Moreover, clayish minerals are known to have layered structure with a similar interlayer space through which ions and molecules of substances containing heavy metals and radionuclides of a definite radius can migrate [20]. Depending on the physico-chemical peculiarities of the interacting components, the metals and radionuclides can, first of all, be sorbed on the inner surface of the layered structure with the formation of bonds with a mineral constituent [21], thus, contributing into the metal and radionuclide accumulation; and they are able to easily migrate through the interlayer space [22-24]. For example, ions Cs+ migrate in the interlayer space better than other alkali metals [18].

Taking into consideration the correlation between the radionuclide and metal content in the organic substance suspension and clayish minerals [25], the authors made the following assumption. At the sampling site “0 km” the element content (of metals and some nonmetals) of the size fraction of 1-5 μm dominates, and this is likely to be connected with the

affinity of the elements being determined to the components of geochemical structures of the considered suspended substance fraction. 2 km downstream quite another type of distribution is observed. Since the discharge water is intensively mixed with the main stream of the River Yenisei, the suspended particles are mixed, as well. At some distance, dominating are the particles transported by the main river flow. At the same time, there are various processes resulting in the artificial radionuclide redistribution according to the size fractions. The suspended substance fragments with the particle size greater than 5 μm possess high capacity to sorb metals and artificial radionuclides. In such a case, sorption can be physical or with the formation of chemical bonds between the interacting components. Surface phenomena at the interaction interface of the two compartments (mineral- aqueous medium) are known to be caused by the water molecule adsorption and formation of a hydrate aqua film on the surface. The hydration degree of the clayish particles is mainly determined by the influence of cations-compensators which are located on the surface of the solid particles. The cations-compensators actively attach water molecules to their surface. This results in weakening the bonds between the cations and the surface in the aqueous medium, thus, a number of the cations are removed from the solid particles. The cations remaining on the surface are considered to form an adsorption layer and the removed cations create a diffusion layer. In this connection, the negatively charged surface of the solid particles and the adsorption and diffusion cation layers compensating its charge form a double electric layer of the particle. The double electric layer structure is not constant, but changes with time under the influence of the environmental conditions [26].

Moreover, with humic substances having developed surfaces with a great number of reactive functional groups, the accumulating capacity of the suspension particles increases due to the formation of stable


10

complex compounds with metals dissolved in the water flow [27]. In the case when the particle surface is entirely or to a great extent free from organic substances (e.g., particles with the size of 1-0.2 μm), the authors observed the following. In spite of clayish minerals having high sorption capacity, both on the surface and in the interlayer space, technogenic radionuclude accumulation on clayish minerals is negligible. Thus, the authors made several assumptions that the main contribution into the accumulation and transport of technogenic radionuclides, and, consequently, of metals entering the water flow together with the radionuclides, is made by complex formation with organic substances covering the particle surface of the suspended substance with the size ≥5 μm.

4. Conclusions

The Yenisei River water in the influence zone of the Mining and Chemical Combine contains considerable amounts of artificial radionuclides and heavy metals of various genesis.

The suspended substance of the water flow consists of pelitic finely dispersed mineral particles, plant and biogenic detritus and living biological objects (for example, worms).

The main mass transport forms of artificial radionuclides and metals entering the water flow can be both free ions in the molecular solution (e.g., 24Na+) and molecules or sorbed ions in colloid particles with the size less than 200 nm, and suspension, as well.

Depending on the interaction time of the compartments under study (water, suspended substance), there occurs the redistribution of artificial radionuclides and metals according to the size fractions of the suspension. In addition to this, the main contribution into the radionuclide and metal accumulation is made by complex formation with the humic substances located on the surface of the particles with the size ≥ 5 μm.

Regarding natural system adaptation to radioactive

contamination, of the greatest interest is the revealed complete or partial natural immobilization of 60Co, 99Mo, 24Na in the influence zone of the Mining and Chemical Combine.

Long-term monitoring confirms the data on artificial radionuclides entering the Yenisei River water which are likely to be connected with the activity profile of the industrial enterprises located on the banks of the studied area of the river bed.

Acknowledgments

The work was supported by RFBR, grant 08-05-00137 and RFBR Siberia 09-05-98002.

Special thanks were given to my beloved husband, who died in April 2010-Georgi Denicovich.

References [1] A. Bolsunovsky, L. Bondareva, Actinides and other

radionuclides in sediments and submerged plants of the Yenisei River, Journal of Alloys and Compounds 444-445 (2007) 495-499.

[2] A. Bolsunovsky, Artificial radionuclides in aquatic plants of the Yenisei River in the area affected by effluents of a Russian plutonium complex, Aquatic Ecology 38 (2004) 57-62.

[3] L.G. Bondareva, A.Y. Bolsunovsky, Investigation of occurrence forms of technogenic radionuclides 60Co, 137Cs, 152Eu, 241Am in the bed silt of the River Yenisei, Radiochemistry 49 (2008) 475-479

[4] A.Y. Bolsunovsky, V.O. Tcherkezyan, K.V. Barsukova, B.F. Myasoyedov, Investigation of high-activity soil samples and hot particles in the Yenisei river alluvial land, Radiochemistry 42 (2000) 560-564.

[5] Y.V. Kuznetsov, Y.A. Revenko, M.K. Leguin, On the estimate of the Yenisei river contribution into the total radioactive contamination of the Kara Sea, Radio- chemistry 36 (1994) 546-553.

[6] S.M. Vakulovsky, E.G. Tertyshnik, A.I. Kabanov, Radionuclide transport in the River Yenisei, Nuclear Energy 105 (2008) 285-291.

[7] Y.A. Platovskikh, I.V. Sergeyev, Y.V. Kuznetsov, V.K. Leguin, A.E. Shyshlov, Mathematical modeling and analysis of radionuclide behaviour in the system Krasnoyarsk Mining and Chemical Plant- the Yenisei-the Kara Sea, Nuclear Energy 95 (2003) 457-466.

[8] V.M. Belolipetsky, S.N. Genova, Mathematical modeling of hydro-physical mechanisms of radionuclide migration in river systems, in: V.F. Shabanov, A.G. Degermendgy


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(Eds.), Distribution and Migration Regularities of Radionuclide Migration in the River-Valley of the Yenisei, Publishing House of SB RAS, Novosibirsk, branch “GEO”, 2004, pp. 161-202.

[9] I.I. Gitelson, N.S. Abrosov, M.I. Gladyshev, The main hydrological and hydrobiological characteristics of the Yenisei River, in: E.T. Degens, S .Kempe, A.S. Naidu Mitt. Geol.-Palãont (Eds.), Transport of Carbon and Minerals in Major World Rivers, Lakes Ans Estuaries, Part 5 Inst. Univ. Hamburg Heft 66, 1988, pp. 43-46.

[10] L. Bondareva, A. Bolsunovsky, A. Trapeznikov, A. Degermendgy, New process for transuranide preconcentration in water samples from the Yenisei River, Doklady Chemistry 423 (2008) 311-313.

[11] G.R. Tilton, Isotopic composition and distribution of lead, uranium, and thorium in a precambrian granite, Bull. Geol. Soc. Am. 66 (1956) 1131-1148

[12] J.N. Rosholt, B.R. Doe, M. Tatsumoto, Evolution of the isotopic composition of uranium and thorium in soil profiles, Bull. Geol. Soc. Am. 77 (1966) 987-1004.

[13] A.Y. Bolsunovsky, L.G. Bondareva, Tritium in surface waters of the Yenisei River basin, J. Environ. Radioactivity 66 (2003) 285-294.

[14] K. Grasshoff, M.G. Ehrhadt, K. Kremling, The analysis of natural radionuclides in seawater, Methods of Seawater Analysis, Ch. 13, Verlag Chemie Weinheim, 1999.

[15] H.D. Livingston, D.R. Mann, V.T. Bowen, Methods for Marine Radioactivity Studies II, IAEA, Vienna, 1975, pp. 69-76.

[16] S.M. Vakulovsky (Ed.), Methodological Guide for Determination of Radioactive Water Pollution, Gidrometeoizdat, Moscow, 1986, p. 360 (in Russia).

[17] G.D. Levadnaya, Microphytobentos of the river Yenisei- Novosibirsk: Nauka, 1986, p. 288. (in Russia).

[18] E.K. Duursma, J. Carroll, Environmental Compartments:

Equilibria and Assessment of Processes between Air, Water, Sediments and Biota, Springer Verlag, Heidelberg, 1996, p. 280.

[19] T.A. Zotina, A.Y. Bolsunovsky, L.G. Bondareva, Accumulation of 241Am by suspended matter, diatoms and aquatic weeds of the Yenisei River, J. Environ. Radioactivity 101 (2010) 148-152.

[20] E.K. Duursma, C. Hoede, Theoretical, experimental and field studies concentration molecular diffusion of radioisotopes in sediments and suspended solid particles of the sea, Part A: Theories and mathematical calculations, Neth. J. Sea Res. 3 (1967) 423-457.

[21] K.O. Adebowale, I.E. Unuabonah, B.I. Olu-Owolabi, The effect of some operating variables on the adsorption of lead and cadmium ions on kaolinite clay, J. Hazardous Material 134 (2006) 130-139.

[22] B. Subramanian, G. Gupta, Adsorption of trace elements from poultry litter by montmorillonite clay, J. of Hazardous Materials 128 (2006) 80-83.

[23] A. Kaya, Ö.A. Hakan, Adsorption of zinc from aqueous solutions to bentonite, J. of Hazardous Materials 126 (2005) 183-189.

[24] M. Tuzen, E. Melek, M. Soylak, Celtic clay as sorbent for separation-preconcentration of metal ions from environmental samples, J. Hazardous Materials 136 (2006) 597-603.

[25] J.D. Milliman, Organic matter content in U.S. Atlantic continental slope sediments: decoupling the grain-size factor, Deep-Sea Res. 41 (1994) 797-808.

[26] V.N. Shvanov, V.T. Frolov, E.I. Sergeyeva e, Systematika i klassifikacia ocadochnih porod i ih analogov, S-Pb.: Nedra, 1998, p. 352. (in Russia).

[27] P. Zhou, H. Yan, B. Gu, Metal complexation by humic substances in seawater, Chemosphere 58 (2005) 1327-1337.


Hydraulic Properties of Rocky Mountain First-Order Alluvial Systems and Diurnal Water-Level Fluctuations

in Riparian Vegetation: An Analysis in Hay Creek,

Whitetail Basin, Montana

W.D. Weight1 and K. Chandler2 1. Department of Mathematics, Engineering, and Computer Science, Carroll College, Helena, MT 59625, USA

2. Montana Bureau of Mines and Geology, Billings, MT 59625, USA


Abstract: The hydrogeology of first-order streams have been evaluated from 2007 to 2009 as part of the Whitetail Basin Watershed Restoration Project in Hay Creek Canyon located 25 km north of Whitehall Montana, USA. An in-depth study of the riparian area hydrogeology started in the fall of 2007 with the installation of more than 40 hand-augered deeper (> 1 m) wells to complement preexisting driven metal pipe piezometers (± 1 m) installed in four first-order drainages. Two zones within the shallow alluvial systems were identified. This paper presents the results of a concentrated study conducted in the Hay Creek drainage within the two zones. Data loggers placed in some of the wells led to a gradual understanding of the water-level patterns in different vegetative types (Douglas Fir, Aspen, Willow-Alder, and Grass-Sagebrush) over the various seasons. The deeper water-level responses change from seasonal patterns to strongly diurnal during summer months. Diurnal patterns continue until leaves drop from riparian vegetation. This was expected, however, the Douglas fir trees show the same pattern. Near the end of the study a full year of water-level data showing the seasonal behavior changes were collected. Resaturation of the upper zone occurs in the fall with sources of recharge coming from up-drainage. A detailed evaluation of water-level responses from up-drainage to down-drainage piezometers occurs in a “wave-like” resaturation phenomenon that allows one to estimate the bulk hydraulic conductivity of the “alluvial system” aquifer using principles of Darcy’s Law. The methods used to evaluate the hydraulic properties and seasonal water-level patterns are presented. Key words: Riparian areas, hydrogeology, first-order streams, diurnal, water-level patterns, aquifer properties, prescribed fire, conifer encroachment.

1. Introduction

Riparian areas are commonly defined as a transition zone between upland terrestrial ecosystems and aquatic ecosystems [1]. Riparian areas around the world have been heavily modified by human expan-sion and development. Restoration of functioning riparian areas can result in improved stream water quality, depending on the level of human impact. In lightly impacted

Corresponding author: W.D. Weight (1954- ), male,

professor, Ph.D., main research fields: professional engineer, hydrogeology and ground water. E-mail: weightwillis @gmail.com.

drainages, changes in land manage-ment can allow native communities to recover [2].

Restoration strategies for riparian areas often include modification of woody plant populations. This topic has been extensively studied with mixed results. Early studies suggested planting woody species in riparian areas to re-form “natural” riparian systems with stable stream banks, shaded waters, and buffer zones for floodwaters [2]. Conversely, it has been well documented that woody riparian vegetation use considerable amounts of shallow groundwater through evapotranspiration [3, 4]. Recent studies conclude that

Hydraulic Properties of Rocky Mountain First-Order Alluvial Systems and Diurnal Water-Level Fluctuations in Riparian Vegetation: An Analysis in Hay Creek, Whitetail Basin, Montana

13

reduction of woody plants in riparian areas can increase stream flows, thus providing better water quality for aquatic species [5].

Significant changes in riparian area vegetation have resulted from fire management policies. Fire suppre- ssion over the last 100 years has allowed successional changes in forests and riparian areas of the northwest [6]. Natural periodic burning of riparian areas regenerated species such as Populus tremuloides (quaking aspen) [7] and Salix bebbianna (Bebbs willow) while reducing fire intolerant species like Juniperus scopulorum (Rocky Mountain Juniper) and Pseudotsuga menziesii (Douglas Fir). This anthropogenic change has allowed the fire intolerant conifer species to expand their range into riparian areas once dominated by fire regenerating species. Aspen is a successional intermediate specie that is shade intolerant, therefore without natural fire cycles, it exhibits declining suckering and regeneration patterns as conifer encroachment occurs.

Eventually, the mature deciduous plants die out and the site becomes dominated by conifers [8]. Forbs and grasses are gradually replaced by shade tolerant shrubs and conifers during this process [9]. Studies suggest that succession to conifer dominated riparian areas may reduce stream flows. This reduction may be a function of differential water use by various riparian species [10], or it may be a function of differences in infiltration of precipitation. Recent studies show canopy interception and sublimation of snow precipitation is greater in conifer sites than aspen sites [11]. Greater snowpack in aspen dominated riparian areas can lead to greater infiltration rates and increased soil moisture.

Re-establishing native plant communities through prescribed burns may be a way to increase flows in mountain streams as part of watershed level management. Water flow increases have been recorded as the result of prescribed burns of woody vegetation in primary drainages of Montana [5] and in southwest Idaho [12]. A basic understanding of the proposed

treatment area shallow groundwater system and the water use by different riparian species is central to determining riparian area management practices that optimize water quality and quantity.


2.1 Study Objectives

The Whitetail Watershed Restoration Project is a multi-agency collaboration to evaluate the effects of woody vegetation reduction using prescribed fire. Treatment areas were established in two first-order drainages of the Whitetail Creek watershed north of Whitehall, Montana and paired with two other unburned first-order drainages as control drainages (Fig. 1). Piezometer transects and continuous water-level recorders were set up in the four study areas to record hydrologic measurements for two years prior to applying the burn treatment. Hay Creek was treated with prescribed fire September 18, 2004 and the Little Whitetail Creek drainage was treated April 19-20, 2005 [13]. The prescribed burns in the Whitetail basin drainages failed to reach the desired treatment levels due to weather conditions, therefore, more than 40 additional hand-augered deeper wells (>1 m) were drilled to gain a better understanding of the surface-water/groundwater interactions among the riparian vegetation.

Characteristics common to all four drainages were

I‐90Whitehall, MT

N

11 miles

Hay Creek Study Area

Pony Creek Study Area

0.2 Miles

0.5 miles

Missoula

Butte

Base Map from Montana NRIS Fig. 1 Location of the four first-order tributaries of the Whitetail Creek drainage in southwestern Montana and the reaches where well transects and deeper wells were placed [13].


14

discovered, but more intensive field exercises were conducted in Hay Creek to refine the principles presented. Hay Creek was the most accessible “burned” drainage and became the focus of a more detailed study. The objectives of this paper are to (1) describe the hydrogeology of first-order drainages (common to the four drainages studied) with examples from Hay Creek and Little Whitetail Creek, (2) show quantification of the differences in water use by various riparian species on a daily and seasonal basis, and (3) demonstrate how water-level changes from upstream to downstream well transects can be used to estimate alluvial hydraulic properties.

2.2 Physical Characteristics

Hay Creek flows eastward and is located approximately 6 km south of the northward pair of burned and unburned drainages, which includes Little Whitetail Creek. Hay Creek has surface water flow year around in certain reaches of the study area. South facing slopes are vegetated with conifers, sages, and grasses. North facing slopes are predominately forested with mature stands of Douglas Fir. The riparian areas vary from mixed stands of aspens and conifers, brushy areas of willows and alders, and open areas of grass and sagebrush. Most of the aspen stands include encroaching conifers. The location of the metal piezometers transects and shallow wells used for groundwater level measurements and sampling are shown in Fig. 2.

The geology of the upstream end of Hay Creek consists of granodioritic rocks Cretaceous in age (Kgd) [14]. Large granitic boulders line the ridges and litter the forests. Just below piezometer transect line 1, there is a surface geologic contact where the bedrock changes to grayish-green andesite of the Elkhorn Mountain Volcanics, also Cretaceous in age (Kem) [14]. This contact gives rise to a spring named the “step spring” (Fig. 2). The alluvium downstream from this contact contains many angular boulders of andesite that make shallow well installation more difficult.

Fig. 2 Distribution of piezometers and shallow wells in the Hay Creek drainage study area.

2.3 Methods of Installing Piezometers and Wells

Metal piezometers (2.5 cm in diameter) were initially installed at five transect locations in each of the four drainages two years prior to the burn treatments. Each transect consists of three black metal pipes perforated with hand-sawn slots in the bottom 20 cm and driven into the riparian alluvium. The trouble with this method is that no sub-surface descriptions of the sediments were made and the depths were arbitrarily chosen. Guidance of the range scientists installing these piezometers was to place a piezometer on either side of the channel where riparian vegetation first appeared. They also believed that herbaceous vegetation derived their water from the upper meter of soil and from surface-water flow. Most of the metal piezometers were installed to depths less than 1.0 to 1.5 m below the surface. Water levels in many of the metal piezometers were dry by mid-to-late summer and during fall months, or have frozen water in the winter.

Additional wells were drilled (hand-augered) to gain a better understanding of the hydrogeology of the alluvial sediments and to determine whether deeper groundwater existed. Some of these were installed to depths of 3.5 m (the limit of the auger) for the purpose of collecting water-level and water chemistry information year around. Well construction typically consisted of 2.5 cm diameter PVC schedule 40 pipe; fitted with top and bottom caps, hand-sawn screens in


15

the desired interval, that were gravel-packed with 10-20 sieve size silica sand, and sealed up to the surface with bentonite grouting. In addition to the 2.5-cm wells, several 5-cm wells were installed to perform aquifer testing that would accommodate the 12-volt submersible pumps. The wells were installed as deep as possible using a 8.9-cm diameter AMS soil sampling auger. Detailed well logs were recorded for each borehole. Water-level data were collected at monthly intervals followed by continuous monitoring once diurnal and other seasonal patterns were indentified.

Four vegetation “type” sites were selected for more intensive study at Hay Creek line 3 (Fig. 2). Shallow wells were installed to collect riparian vegetation water use information at sites classified as Douglas Fir, Willow-Alder, Grass-Sagebrush, and Aspen. The well sites were chosen by visually locating areas with homogeneous woody vegetation of the desired type. All of the vegetation “type” site wells were installed in the same general area of the Hay Creek drainage to minimize differences in climatic conditions, elevation, geology, and site exposure. The distance from upstream fir site well HC 3-6 to downstream site well HC 2-2A is approximately 370 m, with 18.6 m of elevation change.

2.4 Equipment Installation Methods

The vegetation-type site wells were periodically equipped with Solinst Levelogger (Model 3001, 10 m/30 ft calibrated range) pressure transducers to record water levels every 20 minutes. The transducers were suspended near the bottom of each well with nylon cord. A Baro-logger transducer was suspended in HC 3-7 approximately 0.5 m below the top of the casing to record the barometric pressure changes.

Bucket dams were installed on the streams and springs for flow measurements in the study area. These were constructed using short lengths of 7.6 cm PVC pipes sealed into dams created from rocks, natural sediments, and bentonite granules. Periodic resealing

of the pipes was necessary due to debris clogging and disturbance by domestic and wild grazing animals.

Short-term pumping tests and sieve analyses were conducted to estimate the aquifer properties of the shallow alluvial deposits of Hay Creek. The pumping- test set-up in Hay Creek consisted of a pressure transducer connected to the pump discharge line in pumping well HC 3-1C and pressure transducers in observation wells HC 3-1A and HC 3-1D. The pressure transducers were set to record levels every 30 seconds. The 12-volt submersible sampling pump was powered by a connection to an automobile battery. A gate valve was installed on the discharge line to control the pumping rate. The pumping rate was monitored by timed filling of a graduated pitcher and recorded as mL/s.

Approximately 2 kg of aquifer materials were collected from the production zones of new wells on Hay Creek line 3 for sieve analysis and estimates of bulk porosity. The material was then dried in a drying oven at 100.0 ℃ for 12-15 hrs. The dried aquifer material was divided into three replicates for sieve analyses. Sieve sizes of 3/8, No. 4, 6, 10, 20, 40, 60, 100, and 200 meshes were used with a SS-15 8-inch sieve shaker. The sieves were shaken for 10 minutes and the trapped material from each sieve was weighed with a digital balance to the nearest 0.01 gram. The sieve analyses results were then used to calculate the hydraulic conductivities for the aquifer materials of each borehole using the Hazen Method [15, 16].


3.1 Well Logs

The installation of the deeper wells using the soil sampling auger provided important information about the aquifer materials. Most of the aquifer materials in the four drainages were classified as poorly sorted silty-sands and gravels. Most of the well logs show silt and clay layers 1 to 1.5 meters below the surface. The clay material commonly included muscovite flakes with minor amounts of coarse sand and gravel. These


16

layers often act as confining units and clearly define the saturated zones during the dry summer months. An illustration of the one of the developed cross-sections from the study area is shown in Fig. 3.

Well-log information also shed light on why so many of the driven metal pipe piezometers were dry during the summer months. The upper coarse-grained zone drains and dries out during the summer months when there is little precipitation. During the fall and spring when the drainages rehydrate, from increased precipitation a snow melt, wells completed in the gravels below the clayey layers often exhibit water-levels well above the clayey layers indicating strong upward gradients. Tree roots were also found below the confining layers to depths in excess of 2 m in several boreholes providing information about rooting depths and the ability of riparian vegetation to obtain daily water requirements during the summer months. Regarding the placement of many wells, it was discovered that if a 2-meter pry bar could be thrust in repeatedly and maneuvered to a depth of 1 m, it would make a good candidate for drilling to a deeper depth, usually being stopped by coarser material or bedrock.

3.2 Aquifer Properties

3.2.1 Sieve Sample Results Samples of the aquifer materials were collected for

sieve analysis at the Montana Tech Rock Laboratory in Butte Montana. Fig. 4 shows a plot of the sieve analyses for wells in the study area. The curves are characteristic of poorly sorted materials [15, 16]. The sieve analysis plots were used to determine the d10 and d60 particle sizes for determining the uniformity coefficient (Cu) and for use in determining the hydraulic conductivity (K) using the Hazen Method as described in Ref. [15].

Hazen Method Equation K = C (d10)2 (1) A Hazen coefficient for sorting and grain size (C) of

80 was selected for the medium to coarse poorly sorted aquifer materials [16]. Uniformity coefficients (Cu) less than 4 are common to well sorted materials and

3‐3 3‐4

3‐2A

3‐2

3‐1A

3‐1

3‐1B

Creek

Hay Creek

Med –Coarse Sand

Fine Sand

Dark Clay

Brown Soil

Silty Sand

Volcanic Ash

0 6.1 12.2 18.3 24.4 30.5 36.6 42.7 48.8

1634.1

1633.4

1632.8

1634.7

Elevation

Fig. 3 Geologic cross-section from well data collected near transect 3 in Hay Creek. Y-axis indicates elevation above sea level and the X-axis is horizontal distance in meters. The view is looking upstream.

Fig. 4 Sieve analyses of aquifer materials from the deeper boreholes in Hay Creek (HC) and Little Whitetail Creek (LWC).

poorly sorted materials have uniformity coefficients greater than 6 [15]. The samples were typically poorly sorted silty sands and gravels, having uniformity coefficients greater than 9. The resulting hydraulic conductivities calculated are somewhat low for sands and gravels. The results from the sieve analyses are presented in Table 1.

3.2.2 Total Porosity Results

Samples of the aquifer materials from the boreholes of wells LWC 3-1D and HC 3-1C were tested for total porosity in the rock mechanics lab at Montana Tech in Butte Montana. These two wells represented the sites of where pumping tests were conducted. For this analysis, water was assumed to have a density of 1.0


17

Table 1 Summary of sieve analyses values used to calculate hydraulic conductivities using the Hazen Method.

Location Hazen Method hydraulic conductivities

Well d10 (cm) d60 (cm) Cu K (cm/s) K (m/day)

HC 3-1B 0.010 0.167 17 0.009 7.6 HC 3-1C 0.014 0.166 12 0.016 13.7 HC 3-1D 0.017 0.169 10 0.023 19.8 HC-A1 0.018 0.153 9 0.025 21.3 HC 3-7 0.018 0.234 13 0.026 22.9 LWC 3-1C 0.018 0.162 9 0.027 23.2 LWC 3-1D (Lower) 0.010 0.132 13 0.009 8.2

LWC 3-1D (Upper) 0.011 0.142 13 0.011 9.1

HC Average 0.015 0.178 12 0.020 17.1 LWC Average 0.013 0.145 12 0.016 13.4

Table 2 Total porosity analyses of aquifer materials.

Sample Sample Saturated Sample dry

Mass water

Total porosity

location volume (mL) mass (g) mass (g) lost (g) percent by

volume LWC 3-1D 790 1630.5 1412.4 218.1 27.6%

HC 3-1C 1600 3228.6 2745.9 482.7 30.2%

g/mL. The results of this analysis are presented in Table 2.

The porosity values determined from this analysis fall in the range for mixed sand and gravel, 10-35% [17]. The calculated porosity values may differ from the actual porosity of the aquifer materials in-situ due to the disturbance and mixing of the materials from the boring action and saturation activities in the lab.

3.2.3 Aquifer Test Results Two short-term pumping tests were conducted to

help define the shallow aquifer properties. The test in Hay Creek was run in June of 2008 and the Little Whitetail Creek test was run in November of 2008. The test results were analyzed using Cooper-Jacob time-drawdown plots [18] created in Microsoft Excel, and using various pumping test models with AQTESOLV 4.0 [19] (Fig. 5).

The results from this modeling using five different solutions are presented in Table 3. Model solution choices of unconfined and leaky were selected based

Fig. 5 Theis model fit of time-drawdown data plotted in AQTESOLV 4.0 from the Hay Creek pumping test. Table 3 Aquifer test results from Observation Well HC 3-1D analyzed using AQTESOLV 4.0.

Model simulated T S Specific Hydraulic

(m²/day) yield conductivity (m/day)

Theis, unconfined 42.0 0.0275 0.0275 14.0 Neuman, unconfined 38.4 0.0177 0.0167 12.8 Moench, unconfined 37.5 0.0242 0.1 12.5 Tartakovsky-Neuman, unconfined 45.6 0.0254 0.01284 15.2

Hantush-Jacob, Leaky 42.0 0.0275 NA 14.0 Average values 41.1 0.0244 0.0393 13.7

on the stratigraphy of the materials established from the well logs. Most of the model solutions simulated fit the data well. An estimate of 3 m was used for the saturated thickness.

3.2.4 Wave-Like Water-Level Trends in Estimating Aquifer Properties

One of the first interesting trends noticed in the water-level data was the differences in the rate of summer water-level decline in the wells of Hay Creek near transect 3. It was determined that wells on the north side of the creek had a greater rate of decline than the wells on the south side of the creek. The wells on

10.1

10 100 0.001

0.01

0.1

1.

Time (min) C

orre

cted

Dis

plac

emen

t (ft)

Obs. Wells

HC 31DAquifer Model

UnconfinedSolution

Theis

ParametersT =0.3179ft2/minS =0.0275Kz/Kr =0.5542B =10ft


18

the north side of the creek, with south facing exposure, are located in grass and sagebrush whereas the wells on the south side are all located in woody riparian vegetation and the edge of the forested north facing slope (Fig. 6).

Initially, it was hypothesized this discrepancy in rate of decline may be caused by the differences in water storage between north and south facing slopes. This idea was based on assumptions that the water table roughly followed the topography of the land surface. The original conceptual model of this area was that groundwater entered the riparian area with flow from both sides following the topography and then flowed down the drainage along the axis of the riparian system. Analysis of the surveyed water-level elevations showed that the potentiometric surface generated from the water-level data show the groundwater flow entering the riparian area from the south and continuing northward to some undetermined point (Fig. 7). There is clearly more woody vegetation on the south side of the drainage and if transpiration was the main factor in water-table decline, then the south side should show an accelerated decline. This was not the case.

Water-level data from Hay Creek line 3 to below line 2 were used to generate the chart shown in Fig. 8. The water-levels were “normalized” at the starting date to show the differences in summer decline rates and the timing of aquifer rehydration in the fall from increased precipitation. The wells selected for this comparison are all deeper wells more or less centered in the drainage bottom. The upstream well, HC 3-1A, shows the earliest response to recovering water levels in the fall. HC G1 which is approximately 67 m downstream responded in a similar fashion. The last well to respond to the fall recovery was HC 2-2A. This trend in fall recovery was detected when diurnal cycle data were being analyzed and it was noted that the upstream wells were showing strong recovery while the downstream wells showed a water-level decline. There is over a two-month lag time between the detected fall recovery at line 3 and the recovery

Fig. 6 Water-level trends in late summer in wells on north and south sides of Hay Creek near transect 3.

3‐33‐4

3‐2

3‐1B

Creek

Hay Creek

3‐2A

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0 6.1 12.2 18.3 24.4 30.5 36.6 42.7 48.8

1634.1

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Fig. 7 Water-level surfaces from the shallower system in blue and the deeper system in brown. Y-axis indicates elevation above sea level and the x-axis is horizontal distance in meters. The view is looking upstream.

Fig. 8 Changes in water-levels in Hay Creek wells from line 3 downstream to line 2 showing the summer decline and the fall water-level recovery. The arrows mark the onset of fall recovery.


19

response at line 2 well approximately 317 m downstream. The fall water-level recovery in the riparian aquifer appears to start upstream and proceed downstream in a “wave-like” fashion. A similar trend was recorded in the wells of the Little Whitetail Creek study area.

3.2.5 Discussion The timing of the “wave-like” aquifer saturation

response from upstream to downstream with time can be viewed as a seepage velocity (Eq. 2) using the principles of Darcy’s Law [20]. By using the known hydraulic gradient, estimating the effective porosity (from the laboratory total porosity results), and algebraically manipulating Eq. 2 into Eq. 3, the bulk hydraulic conductivity of the alluvial aquifer materials can be estimated.

(2)

Where, K = hydraulic conductivity, ηe=effective porosity, δh = change in head, δl = flow path length

(3)

Where, all terms have been previously described. Using an estimated effective porosity between 20 to 25%, the bulk hydraulic conductivity of the alluvial aquifer materials of Hay Creek and Little Whitetail Creek were estimated to be 22 to 28 m/day and 16 to 19 m/day respectively. These values provide an estimate of a larger volume of the alluvial aquifer and compare reasonably well with the hydraulic estimates using the traditional sieve and aquifer testing methodologies described above.

3.3 Riparian Vegetation Water Level Results

3.3.1 Diurnal Cycles in Water Levels Diurnal cycles in groundwater levels were observed

in the deeper wells of Hay Creek and Little Whitetail Creek. The area at Hay Creek line 3 was selected as the site for a focused study of the water use by riparian vegetation. Water-levels were recorded using Solinst Levelogger pressure transducers and corrected for barometric pressure changes using pressure data recorded with a Solinst Barologger [21]. The

transducers were configured to record data every 20 minutes, but hourly data were used in the analysis. Fig. 9 displays a typical plot of the baro-corrected data showing diurnal water-level cycles over a 4-day period. The linear fit to the data was used to “slope correct” the data for long-term trends, in this case, a decline of 0.0013 ft/hr. Slope correction was used to evaluate the amplitude of the cycle when comparing data from different vegetation type sites over one time period, or for comparing traces from the same vegetation site during different time periods.

Initial comparisons of the data collected at HC 3-6, a Fir site and HC A1, an Aspen site, showed a definite difference in the amplitude of the diurnal cycles of water-levels. To create a zero reference point from which a comparison could be made, the “slope-corrected” data points were reduced to deviation from the average level for each data set. When plotted on a common axis, the traces for each site were compared for amplitude of cycle as well as timing of each cycle (Fig. 10). The data for HC 3-6 in Fig. 10 show a change in the water-level trend during the first three cycles. “Slope correcting” the data works best for short time intervals, and therefore future comparison charts were constructed using four-day time periods.

The data recorded in the Fir site clearly showed greater diurnal water-level fluctuations than the data

Fig. 9 Water-levels for HC 3-6, a Fir site July 2008. The trace shows clear diurnal cycling and a declining trend in the water- level. The slope of the linear decline line was used to “slope correct” the data.


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Fig. 10 Aspen and Fir site diurnal cycle comparison August 2008. This comparison between HC 3-6 Fir site and HC A1 Aspen site in August 2008 shows greater diurnal water level cycles at the Fir site.

from the aspen site. The question then was if this response was site specific, or if it was a function of the vegetation type. Second locations for fir and aspen type sites were then selected and wells installed. Water-level diurnal cycles from the new fir well site HC 3-7 tracked very closely to the original fir well HC 3-6. The diurnal cycles from the new aspen site HC 2-2A resulted in a pattern more similar in magnitude to the fir sites than to the pattern from the first aspen site. This suggests the location of monitoring stations may be site specific.

Water-levels were also recorded in Hay Creek HC 3-4, a willow/alder site and in HC G2, a grass and sage, such as are common on the south facing side of Hay Creek near line 3. The rooting depths of the grass and sage vegetation did not extend deep enough (1.5 m) to detect any diurnal patterns, while it was determined that the well in the willow/alder site HC 3-4 showed very confusing signal noise. After replacing the faulty datalogger in HC 3-4 with a new one, a strong diurnal cycling pattern was clearly evident during the summer and fall months. In fact, the diurnal cycling at HC 3-4, a willow/alder site, had the greatest amplitude of the recorded cycles from the different vegetation “type” sites (Fig. 11). It is also important to note that the cycling recorded in the aspen site HC 2-2A was of similar magnitude to cycles recorded in the fir sites.

Fig. 11 Hay Creek water-level cycles 9/16/-9/19/2008. The water levels during a four-day period in September 2008 show diurnal cycles at the Aspen, Willow/Alder, and the Fir sites. The Willow/Alder site HC 3-4 showed the highest amplitude per cycle.

3.3.2 Seasonal Water-Level Patterns After discovering the diurnal nature of water-level

patterns during the summer, the question was what happens during the winter and spring? To determine the answer, water-levels were collected with pressure transducers from May 2008 until March of 2009. This allowed for comparisons of seasonal changes in the diurnal cycles at each site. The results of the levels recorded in the Grass/Sage site HC G2 failed to show a connection to the surface; therefore, soil moisture may be a controlling factor to plant growth here.

Seasonal changes in the cycles at HC 3-6 Fir site, HC 2-2A Aspen site, and HC 3-4 Willow/Alder site could be detected by comparing four-day periods each month for several months. The data collected in HC 3-4 after the faulty pressure transducer was replaced in early September are presented in Fig. 12. The water-levels have been “slope corrected” and rescaled arbitrarily on the vertical axis for comparison purposes. The strong cycling in September is all but gone by November after leaf senescence and temperatures have cooled. The diurnal cycling decreases as fall progresses into the winter season. The fluctuations in the October and November data do not seem to be related to diurnal cycling and may be the result of precipitation or


21

temperature changes. The data presented in Fig. 12 showed a similar response at the Aspen site.

The seasonal patterns observed at the Willow/Alder and aspen sites were somewhat expected in that leaf senescence in the fall and leaf development in the spring would result in different patterns of water use than in the summer. A question remained as to what evergreen conifers did. Do they take more water during the winter and in the spring?

The water-level data for the HC 3-6 Fir site are the most extensive within the study area and a monthly diurnal cycle comparison chart for April 2008 through January 2009 is presented in Fig. 13. The trend of decreasing cycle amplitude with seasonal changes was found to be similar to the other sites in the fall season (Fig. 12), but this data set also includes the spring seasonal trend. One notes that the greatest diurnal cycle amplitude occurs in August. The various four-day periods were all selected about the 20th of each month. There is a decrease in diurnal cycling at the Fir site during the fall months at the same time and at the same magnitude as in the other vegetation type sites. Previous studies show a decrease on conifer water use with the seasonal changes in the fall [22, 23]. The erratic behavior of the data for May could be the result of precipitation, increased spring-time soil moisture, and the abundance of surface-water at this site. The data collected from HC 3-6 show the clearest and most consistent diurnal cycling measured in the study area.

3.3.3 Discussion The initial understanding of the nature of the shallow

alluvial aquifer and its interaction with surface water and riparian vegetation was based upon metal piezometers driven into the sediments at a depth of approximately 1 meter. This network was placed by non-geoscientists and the placement and depths were based upon the appearance of vegetation on either side of the stream channel.

The combination of shallow piezometers and deeper wells at HC line 3 provided information about the shallow (0.3-1.5 m) and deeper (>1.5 m) components

1.15

1.2

1.25

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1.45

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7:00

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19:00

1:00

7:00

13:00

19:00

1:00

7:00

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19:00

September 16‐19October 16‐19November 16‐19

Fig. 12 HC 3-4 Willow/Alder site slope corrected water-levels. Water-levels in the Willow/Alder site HC 3-4 show diurnal cycles diminishing in the fall and into the winter.

Fig. 13 HC 3-6 slope corrected water-levels. Hay Creek Fir site HC 3-6 four-day levels for April 2008 to January 2009 show the increase in diurnal cycling in the warmer months.

of the riparian area alluvial aquifer. The shallow piezometer water levels had slightly different trends than the water levels for the deeper wells. The water-levels in the deeper system receded below the


22

shallow system allowing the shallow system to dry during the summer. This may be due to the heavy clay soils above and below the shallow silty gravels and sands of the shallow system at a depth of approximately 1 meter. The surface stream channel appears to be isolated from the deeper system near line 3 in Hay Creek.

Data collected during August and September showed the greatest amplitude diurnal cycles and the clearest patterns. This is most likely because the shallow component of the aquifer had dried, and soil moisture levels were low [24]. There is also less change in the daily weather conditions in the late summer months. The diurnal cycles recorded in the months of May and June were erratic and weak. This was most likely caused by high levels of soil moisture, precipitation events, availability of surface-water, and variable weather conditions.

The amount of available soil moisture for riparian vegetation use appears to greatly impact the amplitude of the diurnal cycles in the shallow groundwater levels. Fig. 10 shows a comparison of the water-level cycles measured in an Aspen site to water-level cycles measured in a Douglas Fir site. This figure appears to indicate fir trees have a greater water use than aspens, but the differences in the amplitude of the diurnal cycle may be a product of the soil moisture available to the plants. In a location with ample soil moisture, plants need less water from the deeper saturated zone. The wells at the two different sites are each approximately 3 m deep, but soils at the fir site were “powder dry” below the 0.5 m of frost encountered during installation of the well on March 21st, 2008. The dry gravelly soil and tree roots encountered in the borehole continued down to a depth greater than 1.7 m. The Fir site was observed to have very little snow in the winter months, and was most often bare. The Aspen site on the other hand would typically have a deep 0.3 m layer of crusty snow and ice for most of the winter. The Aspen site used for this comparison is located near a dry stream channel in an area with high soil moisture in the fall

and spring. The charts displaying the diurnal cycles during

four-day periods of each month over several months all indicate that the woody riparian vegetation uses less water as the days shorten and the temperatures decrease. This was observed at all sites and there was no indication that the conifers continued to use water at a greater rate than the deciduous trees in the fall and winter months. Considerable diurnal cycling in the Aspen and the Willow/Alder sites was detected after fall leaf loss. This water-level cycling may be the result of photosynthesis by chloroplasts in the bark of the deciduous plants [25].

4. Conclusions

Four first-order drainages were equipped with metal piezometers to measure their water levels for two years prior to treating two of the drainages with prescribed fire as part of a land management tool. The piezometers were placed by non-geoscientists, who based their locations on the proximity of an existing channel and the distribution of riparian vegetation. The depths were based on a prevailing belief that herbaceous vegetation derives their moisture from the upper 1 meter of soil, the assumed approximate rooting depths.

Over 40 wells were hand-augered to depths in excess of 1 m to learn of a more complex subsurface stratigraphy and encountered riparian roots below 2 m. Aquifer properties were estimated using traditional methods of sieve testing and aquifer testing yielding alluvial hydraulic conductivities in the 8 to 23 m/d range. The timing of the “wave-like” rehydration of the alluvial channel in the fall season provided a seepage velocity from which a bulk hydraulic conductivity of 16 to 28 m/d was derived for the two drainages studies. This new method compared well with the traditional methods and provided an estimate representing a greater volume of aquifer material.

Water-level data were collected on a 20-minute interval for most of a year in several vegetation types. Diurnal patterns in water use by riparian vegetation


23

were discovered during the summer months. Slope corrections and normalizing the data from the average data-set position allowed a comparison of different vegetation types. It was found that there was no indication that the conifers continued to use water at a greater rate than the deciduous trees in the fall and winter months. Spring patterns were complicated as a result of precipitation, increased spring-time soil moisture, and the abundance of surface-water.

Acknowledgments

Funding support came from a US Department of Agriculture (USDA) NRI grant. Prescribed fire project cooperators include the following: Bureau of Land management (BLM), USDA Forest Service, Jefferson River Montana Watershed Council, Montana Fish Wildlife and Parks, Montana Bureau of Mines and Geology, Utah State University (Mark Brunson), Montana State University (Clayton Marlow and students), Montana Tech of the University of Montana, local ranchers, and Carroll College.

References [1] C.N. Goodwin, C.P. Hawkins, J.L. Kershner, Riparian

restoration in the western United States: overview and perspective, Restoration Ecology 4 (1997) 4-14.

[2] National Research Council, Riparian Areas Functions and Strategies for Management, National Academy Press, Washington, DC, 2002.

[3] P.L. Nagler, R.L. Scott, C. Westenburg, J.R. Cleverly, E.P. Glenn, A.R. Huete, Evapotranspiration on western U.S. riversestimated using the ehanced vegetation index from MODIS and data from eddy covariance and Bowen ratio flux towers, Remote Sensing of Environment 97 (2005) 337-351.

[4] J.J. Butler, G.J. Kluitenerg, D.O. Whittemore, A field investigation of phreatophyte-induced fluctuations in the water table, Water Resources Research 43 (2007) 1-12.

[5] C.B. Marlow, D. Durham, R. Tucker, V. Shea, J. Walker, Effect of watershed forest structure on herbaceous riparian community recovery, in. AWRA 2008 Summer Specialty Conference, Virginia Beach, Virginia: AWRA, 2008.

[6] M.J. Power, C. Whitlock, P. Bartlein, L.R. Stevens, Fire and vegetation history during the last 3800 years in northwestern Montana, Geomorphology 75 (2006) 420-436.

[7] A.E. Hessel, L.J. Graumlich, Interactive effects of human activities, herbivory and fire on quaking aspen (Populus tremuloides) age structurs in western Wyoming, Journal of Biogeography 29 (2002) 889-902.

[8] D.L. Bartos, Landscape dynamics of aspen and conifer forests, in: USDA Forest Service Proceedings RMRS-P-18, Rocky Mountain Research Station, Logan, UT, 2001, pp. 3-14.

[9] R.K. Hermann, D.P. Lavendar (n.d.), Pseudotsuga menziesii (Mirb.) Franco, Douglas-Fir, available online at: http://www.na.fs.fed.us/pubs/silvics_manual/volume_1/pseudotsuga/menziesii.htm.

[10] G.F. Gifford, W. Humphries, R.A. Jaynes, A preliminary quantification of the impacts of aspen to conifer succession on water yield within the Colorado River Basin, II. modeling results, Water Resources Bulletin 20 (1984) 181-186.

[11] E.M. La Malfa, A.J. Leffler, R.J. Ryel, Differential snowpack accumulation and soil water dynamics in aspen and conifer communities: implication for water yield, in: Western Snow Conference, 75th Annual Meeting, Omnipress, Madison, WI, 2007, pp. 171-174.

[12] G.N. Flerchinger, P.E. Clark, in: First Interagency Conference on Research in the Watersheds, 2003, pp. 631-636.

[13] K.M. Chandler, The hydrogeology of riparian areas in the Whitehall Basin, M.S. Thesis, Montana Tech of the University of Montana, Butte, MT, 2009.

[14] R.S. Lewis, Geologic map of the Butte Montana 1 x 2 degree quadrangle, Montana Bureau of Mines and Geology Map Series 363 (1998).

[15] C.W. Fetter, Applied Hydrogeology (4th ed.), Upper Saddle River, New Jersey: Prentice-Hall, Inc., 2001.

[16] W.D. Weight, J.L. Sonderegger, Manual of Applied Field Hydrology, McGraw-hill, New York, 2001.

[17] R.J. Sterrett (Ed.), Groundwater and Wells (3rd ed.), New Brighton, MN: Johnson Screen, a Weatherford Company, 2007.

[18] P.A. Domencio, F.W. Schwartz, Physical and Chemical Hydrogeology (2nd ed.), John Wiley & Sons, Inc., New York, 1998.

[19] Hydro Solve, Inc., available online at: http://www. aqtesolv.com.

[20] W.D. Weight, Hydrogeology Field Manual (2nd ed.), McGraw-Hill Publishing, Professional Book group, Inc., New York, 2008..

[21] Available online at: http://www.solinst.com. [22] D.R. Young, I.C. Burke, D.H. Knight, Water relations of

high-elevation phreatophytes in Wyoming, American Midland Naturalist 2 (1985) 384-392.

[23] W.K. Smith, D.R. Young, G.A. Carter, J.L. Hadley, G.M. McNaughton, Autumn stomatal closure in six conifer sprecies of the central Rocky Mountains, Oecologia (Berlin) 63 (1984) 237-242.

[24] L.K. Lautz, Estimating groundwater evapotranspiration rates using diurnal water-table fluctuations in a semi-arid riparian zone, Hydrogeology Journal 16 (2008) 483-497.

[25] N.V. DeByle, R.P. Winokur, Aspen: ecology and management in the western United States, Vols. General Technical Report RM-119, Fort Collins, Colorado: United States Department of Agriculture, Forest Service, 1985.


Discussion on Irrigation Development and Its Investment Focus in Tanzania

Q.F. Shuai1, J.Z. Xu1, X.P. Liang1, G.M. Kalinga2 and J. Kayumbe2 1. Chinese Senior Agricultural Experts Group in Tanzania for the Project of Aiding Africa, Qianjiang 433100, China

2. Irrigation and Technical Services Division, the Ministry of Water and Irrigation, Maji Ubungo P.O.Box 35066, Tanzania


Abstract: This paper describes the significance of irrigation on economy development and the status of irrigation development in Tanzania, analyzing the potential and advantages of irrigation development in this country, combined with the major initiatives and experiences which can learn from in the recent 30 years of rural water conservancy in China. Then it discusses the next investment focus on irrigation development for Tanzanian. Key words: Tanzania, irrigation, development potential, investment focus.

Preface

According to the two governments exchange of letters between China and Tanzania, irrigation expert Mr Shuai and Mr Liang and agronomist Mr Xu were dispatched to Tanzania in August 2009 as one of 100 senior agricultural experts for aiding Africa. Mr Shuai and Mr Liang worked in the Irrigation and Technical Services Division, Ministry of Water and Irrigation. Mr Xu worked in the Crop Promotion Services, Ministry of Agriculture Food Security and Cooperative. Mr G.M. Kalinga and Mr J. Kayumbe are Tanzanian counterpart in this cooperation project. Up to now we have worked together in Tanzania for nearly one year. During this period we have completed the investigation of

Corresponding author: Q.F. Shuai (1956- ), male, P. Eng.,

research fields: irrigation development and water resources. E-mail: [email protected].

J.Z. Xu (1962- ), male, senior agronomist, research fields: soil and crops. E-mail: [email protected].

X.P. Liang (1965- ), male, senior engineer, research fields: irrigation development. E-mail: [email protected].

G.M. Kalinga (1956- ), male, BSc., Civil, MSc, Irr. Engr., research fields: water and irrigation development. E-mail: [email protected].

J. Kayumbe (1957- ), male, principal agr. officer, BSc. Agr., research fields: water and irrigation development. E-mail: [email protected].

irrigation and mission of the Fourth JIR (Joint Implementation Review) for the Agricultural Sector Development Program (ASDP), participated in the preparation of the National Irrigation Master Plan and revision of the National Irrigation Policy, also conducted a preliminary study on the National Irrigation Development Strategy. In short, we did a series of related works in consultation on policy and planning, academic guidance and technical training in territories of irrigation and agriculture. In this article, we want to discuss how to develop irrigated agriculture and its investment focus in Tanzania with our profundity understanding.

1. The Significance of Irrigation to Economic Development in Tanzania

1.1 The Concept of Irrigation and Its Connotation

The concept of irrigation is different in Tanzania and China, but in the point of view by actual operation, its connotation is similar as rural water conservancy in China. Their mission are impoundment, regulation, distribution and use of agricultural water resources through engineering means and combined with


25

agricultural technology measures to soil dressing, expansion of land use, improve the ability to withstand floods and droughts, and promote the benign cycle of ecological environment in order to achieve high and stable yield for the development of rural economy. The term of irrigation involves hydraulics, civil engineering, soil science, agriculture, hydrology, meteorology, agricultural machinery, agricultural economics and other disciplines.

1.2 Irrigation Can Increase Crop Yield

Tanzania irrigation practice shows that (a) where functioning irrigators organizations are in place, the irrigation schemes have been improved, and productivity increases (paddy) of 200% to 300% over unimproved traditional irrigation schemes. (b) for maize produced in developed irrigation schemes, yield and farm income increased by 100% to 200% over rain-fed cultivation, and up to 700% increases were observed in some locations due to the ongoing drought; for example: in Siha District, rain-fed yields of maize ranged from 0.2-0.7 t/ha, while under developed irrigation 3.5-4.5 t/ha were recorded. It is clear that irrigation development can significantly reduce key crop production risks associated with unreliable rainfall and hence raise farmer incomes. With developed/improved irrigation infrastructure and water management, paddy yields on an average can increase from 1.8 tones per hectare to 4.5 tones per hectare.

1.3 Irrigation Can Improve the Living Quality for Farmers

According to the Fourth JIR of national Agricultural Sector Development Programme, irrigation has made some significant progress. Beneficiaries in functioning irrigation schemes reported numerous benefits and impacts on their lives as a direct result of improved incomes facilitated by irrigation. Those benefits and impacts are: increased employment, improved housing, ability to pay school fees and medical treatment, and household food security. As a major outcome in

FY2008/2009, about 43,000 additional farmers have been able to achieve improved crop production. This has resulted in numerous tangible benefits to more than 200,000 people.

1.4 Irrigation Can Improve Ecological Environment

In addition to compliance with the ESMF (environmental and social management framework), the Strategic Environmental and Social Assessment was proposed to be done to fully examine all of the potential environmental and social issues that would be associated with the National Irrigation Master Plan (NIMP) and the National Irrigation Policy (NIP) and to evaluate and compare the impacts against those of alternative options; assess the legal and institutional aspects relevant to the issues and impacts; and to recommend broad measures to strengthen environmental and social management of irrigation development in Tanzania within an integrated and holistic water resources management approach that takes into account the entire range of environmental and social issues at the national and trans-boundary (international) levels.

1.5 Irrigation Can Promote the Development of Socio-economic

Irrigation practice is one of the effective means in increasing and stabilizing food and cash crop production and productivity for curbing food shortages and increasing export of cash crop and its products. In this regard, a concise plan and implementation for the development of irrigation infrastructure is pertinent. Water is a central and basic natural resource, which sustains life and provides for various social and economic needs including irrigated agriculture. It is considered as a key factor in the socio-economic development and the fight against poverty. The social and economic circumstances prevailing today have increased the competition in water demands by all users and thus created a threat in its sustainability. It therefore entails integrated planning, development and


26

management in support of food security and poverty reduction, as well as environmental safeguards amongst others.

2. The Status of Irrigation Development in Tanzania

2.1 The Level of Development Is Not High, Crop Yield Is Generally Low

The level of irrigation development in Tanzania is still very low resulting into marginal use of the potential available for irrigation development. The agricultural practice in this country is mainly rained and affected by the vagaries of weather. This invariably has subsequently subjected crop production to be generally low. The agriculture sector contributes 25.7% of Tanzania’s GDP and about 30.9% of its export earnings, while employ over 70% of work-force, accordingly the sector continues to drive economic growth in the country. Despite of its importance, agriculture is very much affected by inadequacy, seasonality and unreliability of rainfall and periodic droughts. It is for this reason that irrigation is considered necessary for providing protection against drought, a means stabilizing crop production and assurance of household food security [1].

2.2 The Overall Level of Agriculture Is Low, Green Revolution Faces Challenges

The overall level of national agricultural productivity is low, 6.3 million hectares of cultivated land has been used in only 5% of the irrigated area about 315,000 hectares. Traditional forms of irrigation, improved and modern-type multiple, but not the formation of scale and system, the average land area of 0.2 to 2.0 ha. Degree of mechanization is low, 70% of the farmers use the traditional manual labor, 20% use animal power farming, only 10% of farmers use tractors farming. In the last two years, the 120 national irrigation projects and 148 construction projects in feasibility study were completed.

Since the dependency on rain-fed agriculture has led to low production and productivity, reliance of the country on irrigated agriculture is inevitable to achieve the green revolution for increased crop production. However, there are crucial constraints facing the irrigation sector, which the government shall address so as to realize the envisaged targets. The considerable challenges include inadequate funding, lack of coordination, inadequate technical and land insecurity.

2.3 Irrigation Has a Long History, Continuee to Strengthen Institutional Building [2]

The use of irrigation in Tanzania dates back from the Iron Age and traditional irrigation systems have long been of considerable importance in various parts of the country. In 1930 modern irrigation was introduced in the Tanganyika through establishment of the Tanganyika Planting Company Ltd. (TPC) at Arusha Chini, Kilimanjaro. In 1948 a 1,000 hectare Kilangali rice irrigation farm in Morogoro Region was established by the Department of Agriculture. In 1953 a Royal Commission was established to examine possible measures to improve the living standards of the people in East Africa. The commission proposed that a single Water Department of the Ministry of Agriculture in Tanganyika become Water Development and Irrigation Division (WD&ID).

In 1964 WD&ID was transferred to the Ministry of Lands, Settlements and Water Development (MLSWD). During this period most of the development funds were allocated to state farms whereby only eight percent (8%) was allocated for expansion of traditional irrigation. In 1968 the irrigation section was established in the Ministry of Agriculture with its staff posted mostly to the Regional Administrations to work under the Regional Agricultural Development Officers (RADOs). In 1973 WD&ID was shifted from the MLSWD to the Ministry of Water Development and Power. Shortly afterwards in 1975, the responsibility for irrigation reverted to the Ministry of Agriculture, which had no capacity for the


27

task and WD&ID was disbanded with most of its staff remaining with the Ministry of Water and Power. In the same year the Irrigation Division was initiated.

The restructuring of the Ministry of Agriculture that took place in 1987 reduced the Division of Irrigation to a section, led by an Assistant Commissioner in a newly formed Division of Agriculture and Livestock Development. This went on until 2002 when the Irrigation Section was elevated to a Division of Irrigation and Technical Services with three sections. In March 2008, the Division of Irrigation and Technical Services was transferred to the newly formed Ministry of Water and Irrigation. Meanwhile, the new ministry has also set up irrigation management and technical services units in seven zones of the country.

2.4 There Are Difficulties in Irrigation Development and More Restrictive Factors

These constraints include: (1) inadequate fund for irrigation investments; (2) low capacity and participation of private sector in irrigation development; (3) low level of irrigation skills of the farmers; (4) low production and inefficient marketing systems to absorb the produce from irrigation farming; (5) inadequate institutional capacity at national-level with respect to planning, implementation and sustainable management of irrigation development in Tanzania; (6) inadequate capacity of institutions at Local Government Authority level (LGA) to handle irrigation investments, implementation and sustainable management; (7) low irrigation water use efficiency; (8) ineffective and inefficient control of irrigation water which limits the application of the principles of Water Markets and Socio-Economic Mobility of Water use permit; (9) lack of legal and regulatory framework for irrigation development; (10) lack of proper agricultural land use and management plans; (11) inadequate irrigation production support services that is supported by research and technical innovation;

(12) inadequate farm power for various farm operations; (13) inadequate data base for irrigation development; (14) inadequate attention to drainage; (15) inadequate storage of water for irrigation; (16) competing demand for water with other users such as hydropower, domestic use, livestock and wild life; and (17) changes in river flow patterns as a result of catchment degradation and climatic changes.

2.5 Water Resources Is Abundant, Opportunity of Development Is Unprecedented

The development of irrigation sector has an unprecedented opportunity to facilitate the Tanzania agriculture sector to be transformed from subsistence to a modern and highly commercial sector. Tanzania is also committed to the Millennium Development Goals (MDGs) as internationally agreed targets for reducing poverty, hunger, diseases, illiteracy, environmental degradation and discrimination against women by 2015.

This country has high potential of surface as well as ground water resources. There are 5 lakes with more than 1,000 square kilometers and 17 large rivers across the country. The area of lakes and wetlands is 5.8% of the total land. Since the low-lying east, central and western high, the river in the eastern flows into Indian Ocean, Lake Victoria into Mediterranean Sea through Nile River, Lake Tanganyika into Atlantic Ocean through Congo River, Lake Nyasa (Malawi) into Indian Ocean through Zambezi River. Sample survey shows that Tanzania has 94.5 million hectares of land, 44 million hectares of arable land, of which 29.4 million hectares are suitable for irrigation.

For the purpose of effective management, planning and development of the water resources, the country is divided into nine water basins namely: Rufiji, Pangani, Ruvuma, Wami/Ruvu, Internal Drainage, Lake Rukwa, Lake Nyasa, Lake Tanganyika and Lake Victoria. These basins hold all the surface and groundwater in the country for all uses of water, including irrigation.


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3. The Major Initiatives and Experiences in China in Recent 30 Years

3.1 The Major Initiatives in Early Phase of Reform and Opening

(1) Reform responsibility of irrigation management, to address the problems in responsibility of water facilities maintenance not implemented and effective attenuation; (2) Reform water fee and diversification. (3) Increase investment in rural water by “work for the dole” and the national comprehensive agricultural development; (4) Restore and strengthen the primary water service system through establishment of rural water points and other measures; (5) Accelerate the pace of Rural Drinking Water Supply.

3.2 The Major Initiatives in Medium Term of Reform and Opening

(1) Establishment and development of the system “labor accumulation”; (2) Take water-saving irrigation as a revolutionary measure; (3) Strengthen the work of rural drinking and resovle the difficulties in rural water supply through implementation of the National Program of “Eight-seven” Crucial Anti-Poverty; (4) To strengthen international cooperation and exchanges in this period.

3.3 The Major Initiatives in Recent Term of Reform and Opening

(1) To explore and establish new mechanisms for farmland water conservancy construction; (2) Reform deeply management system of pumping station in the state-owned large and medium irrigation; (3) Transfer system of property rights in small rural water conservancy; (4) Conduct pilot reform on participation of the water user in management and establishment of water users associations in different regions; (5) Take reform into depth by new ideas of water control and the livelihood of water conservancy.

3.4 The Results Has Been Brought Recently by Reform and Opening

Chinese irrigation has played an important role in protecting national food security under the conditions without increase the total amount of water. The agricultural productivity have been greatly enhanced to withstand drought and other disasters, reaching one mu per capita farmer offering high and stable yield farmland. The country reached 66 million hectares of irrigated area, of which effective irrigation area increased from 48 million hectares to 57 million hectares. Water-saving irrigation area was 39 million hectares, the coverage of water-saving irrigation for more than 60%. The rural water services and support capabilities were improved so that agricultural production and living conditions of farmers continue to arise. National grain production increased from 3.2 million ton to 5.2 million ton with amplitude of 57%.

3.5 The Experiences Can Learn from in Rural Water Development of China

(1) Government-led is the key. (2) Increase investment is the guarantee. (3) Farmers participate is the prerequisite. (4) Co-ordination of urban and rural areas is the direction. (5) Deepen reform is the driving force. (6) Institutional development is the foundation. (7) Learn from foreign experiences is a shortcut. The practice shows that rural water conservancy has an important strategic position in the national economy; it has become not only an important part of overall national strength, but also important material foundation of future economic and social development in China, and the important part of construction of new socialist countryside [3].

4. Potential and Advantages of Irrigation Development in Tanzania

4.1 Potential Is Great for Irrigation Development

In response to this, Tanzania launched the National Irrigation Master Plan (NIMP) in 2002 which identified a total irrigation development potential of 29.4 million hectares, representing 44 million hectares of arable land 67% in the country, of which 2.3 million


29

hectares are classified as high potential; 4.8 million hectares as medium potential; and 22.3 million hectares as low potential. However, only 310,745 hectares are provided with improved irrigation infrastructure as of June 2009, representing 6.3 million hectares cultivated area 5%. The classification of irrigation development potential area was made by superimposing three assessment maps indicating potential levels on water resources, land resources, and socio-economic aspects like improvement of roads infrastructure and increase in the demand of irrigation by stakeholders. The grain yield increased from 4.2 tons/ha to 7.8 tons/ha in the demonstration area, if the irrigated area develops up to 200 million hectares, the national income will increase 6 trillion shillings, equivalent to 4.28 billion U.S. dollars [4].

4.2 The Government Is Focusing on Importance of Irrigation

According to national development and poverty reduction strategies (NSGRP), within the framework of national organizations focusing on economic growth and poverty reduction, growth rate in 2010 will reach 10%. The importance of irrigation development has been increasingly recognized by the government of Tanzania. The strategic objective of “Tanzania Development Vision 2025” is consistent, high-growth common prosperity, high quality of life, peace, stability and unity, good governance, quality education and international competitiveness. Tanzania is also committed to achieving the Millennium Development Goals (MDGs) as the internationally agreed in 2015 to reduce poverty, hunger, disease, illiteracy, environmental degradation and discrimination against women objectives.

The gvernment is now giving high priority to irrigation development which is emphasized within the National Policy Frameworks. The Government is also giving high priority to the management of the nation’s water resources. This offers strong synergies with irrigation development.

4.3 Knowledge of Irrigation Is Gradually Increased

Tanzania’s agricultural development must take the road of irrigated agriculture, and irrigated agriculture must develop water-saving irrigation. This is the consensus of the Tanzanian water sector. Because water is the foundation of life and environmental factors, it plays a central role in economic and social development activities. Water involved in all areas of human life, including family, livestock, fisheries, wildlife, industry, energy, entertainment and other socio-economic activities. With safe and clean water would raise the standard of living, while water scarcity will lead to serious health risks, and lead to declining living standards and life expectancy. Water has a key role in Tanzania for food security, improve family health, living environment and poverty alleviation.

4.4 The Investment Environment Is Improving for Irrigation

Government of Tanzania formed the Ministry of Water and Irrigation in March 2008. The development program in this water sector has four components, namely: (1) water resource management; (2) rural water supply and sanitation services; (3) Urban water supply and sewage services; (4) sectors strengthening and capacity building. The Ministry of Water and Irrigation has submitted “National Irrigation Policy” been revised this year and the government would promulgate it very soon. The formulation of the national irrigation policy will guide the nationwide implementation of irrigation schemes, to ensure that land and water resources optimization, to improve agricultural production and productivity, effective in promoting food security and poverty reduction goals.

4.5 Irrigation Inputs Is Gradually Strengthened

According to the field survey, 5.5% annual increased in irrigated area nearly three years, of which 2009 is the largest year, as 21,500 hectares. This year 94 irrigation schemes started construction, of which 4 dams commanding 625 ha of irrigated area have been


30

completed. The capacity building of national water sector was taken with a large-scale, 200 technical staff who all have certificates, diplomas and qualifications. It is reported that construction of irrigation are 1428 key projects up to year 2025 by the “National Irrigation Development Planning”, then the irrigated area will be 760,000 hectares, of which add newly irrigated area of 450,000 hectares that need to invest 1.5 billion U.S. dollars.

5. Discussion on Next Investment Focus of Irrigation Development in Tanzania

Through analysis above and discussed in two sides of experts, it is known that the next focus to invest irrigation development in Tanzania will be:

5.1 The Planning and Construction on Systemic Irrigation Projects

We should abandon the idea to grasp only single project and establish the concept of system engineering. The reason why China built effective irrigation, the main thing is effective in the complete planning system and a series of planning works. In Tanzania, there are no such planning to establish a sound body, let alone planning system, resulting in water resources development schemes were piecemeal, comprehensive benefits not to be played. From now on the government in national, regional and district levels should establish appropriate irrigation planning agency to make short, medium, long-term system planning for different sub-basin or area. The projects under planning can be invested, otherwise outside project can not. Do not wait for years go off and then conduct raids, make the planning year-round, to ensure the continuity and rationality of planning, and to guarantee the implementation of the plan by laws.

5.2 Build Several Large-scale Demonstration Irrigation Schemes

The first is to choose a good basis region as a demonstration model (see Fig. 1) for irrigation system

Fig. 1 Kituani Mwenzae irrigation scheme in Lushoto District, Tanga Region.

engineering in design and management for reform program in large-scale irrigation, to stimulate the whole country to carry out extensive building of large-scale irrigation schemes. Many of problems will be resolved for such as long-standing nature of irrigation management unit been unclear, irrational institutions, mechanisms and imperfect body, institutions absence, extensive management, poor funding, engineering aging, effective attenuation. It will play a positive role in promoting them and promoting sustainable agricultural development in Tanzania.

5.3 Establish a National Irrigation Data Monitoring System

To build a system for monitoring irrigation data in the country means that a national system for monitoring irrigation data should be established in different region of the country, for that the Ministry of Water and Irrigation must set up a center of processing data. Also, each basin unit and region need to establish a monitoring station for field water demand, water using, river water flow, rainfall and other parts of irrigation-related basic data, and then provide technical services for the national irrigation construction and development.

5.4 Support Cooperation in Irrigation Between China and Tanzania

It is important to carry out South-south Cooperation


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in irrigation between China and Tanzania for irrigation development. According to the mission and target framed by the “National Irrigation Master Plan”, work out a concrete implementation scheme, including annual projects, scale of investment and regional mission etc. In order to ensure implementation of the plan and irrigation development in Tanzania, the author suggested that dispatch 20 or 25 Chinese technicians to here through South-south Cooperation to facilitate carrying out of irrigation cooperation activities in seven (7) irrigation zones of Tanzania for a period of 5 years [5].

5.5 Training Technology Team of Irrigation in Whole Country

Existence of the institutional set up with qualified personnel with different disciplines related to irrigation such as irrigation engineers, soil scientists, water resources engineers, economists, mechanical engineers, hydrologists, land surveyors, agronomists, sociologists, environmentalist, and irrigation technicians. However, the number of personnel is inadequate.

To ensure rapid development of irrigation, we should create a perfect technology team of irrigation. At present irrigation technology is limited in Tanzania, lack of technical information, lower technical services. So from now on, we should determine to cultivate and foster a strong focus on irrigation technology service team, in addition to the relevant institutions to open irrigation professionals, but also establish a national training center for irrigation, vigorously training in-service officers, extensive irrigation technology to carry out international exchange activities, supporting formation of the corresponding technical services,

development of specific irrigation project evaluation, improved standard of technical service system to meet the need of continuous development of the national irrigation project in urgent.

6. Conclusions

It provides a good foundation that Tanzania’s abundant water resources, favorable natural conditions and state ownership of land for the development of irrigated agriculture. Generally speaking, agriculture and irrigation development in Tanzania has a great potential. However, there are many limiting factors, so the challenges are also great. Agricultural assistance around the world to Tanzania has a long history, both achievements and problems exist. The territory of irrigation is needed to be more explored. If we can change traditional concepts, transform methods, and avoid weaknesses, constantly updating ideas, identify the investment priorities, we must obtain a multiplier effect of irrigation development in Tanzania.

References [1] A Statistical Analysis of the 2000/01, Final Food Crop

Production Forecast for Food Security, Tanzania. [2] Agriculture, Performance and Strategies for Sustainable

Growth, Tanzania. [3] S.J. Gong, Q.F. Shuai, Exploration to establish long term

mechanism in water management organizations of grass roots level, Water Resources Development Research 3 (2009) 50-53.

[4] Q.F. Shuai, Discussion on the adjustment practice of water resources protection with development of local economy, Journal of Environmental Science and Engineering 2 (2008) 75-78.

[5] Q.F. Shuai, Enlightenments to Innovate Rural Water Control for China from Present Utilization of Water Resource in Nigeria, Water Resources Development Research 10 (2007) 49-53.


Natural Barriers to Eco-environmental Vulnerability in a Complex Ecosystem

C.B. Hyandye and I.B. Katega Department of Environmental Planning, Institute of Rural Development Planning (IRDP) P.O.Box 138, Dodoma Tanzania


Abstract: Natural features such as mountain ranges, steep slopes and vegetation prevent human movement from one habitat to another. They prevent the ecological harm from natural phenomenon like erosion and landslide. Forests destruction has brought about deterioration of ecological environment such as increasing soil and water losses. RS (Remote Sensing) and GIS (Geographic Information System) technology have enhanced the eco-environment assessment procedure using eco-environment quality index tool. This paper presents results of the research on the investigation of the potentials of different landscapes on the complex ecosystem of Makeng Village in Fujian Province to act as natural barrier to eco-environmental vulnerability. Vulnerability factors analysed were soil erosion, vegetation cover, land use types, slope and elevation. To see how one factor acts as natural barrier eco-environment stressors, factor maps were overlaid in pairs using ArcGIS 9.2 software and the matrix statistics exported for analysis in Microsoft Excel. The results showed steep slopes naturally limit human activities, growth of big trees and increase soil erosion. Flat and gentle slopes are less vulnerable to erosion. Elevation is among natural barriers to human activities. Human activities decrease with increasing elevation, hence making the eco-environment naturally stable/undisturbed. In this study, eco-vulnerability to erosion decreases with increasing vegetation cover. Key words: Eco-environment vulnerability, natural barriers, ecosystem, GIS.

1. Introduction

The eco-environment problems have attracted a lot of attention in recent years [1]. Rapid economic growth in some developing countries has resulted in widespread and severe environmental degradation, including increasing air, water and land pollutions [2]. Recently, destruction of forest vegetation has brought about deterioration of the ecological environment such as increasing soil and water losses and decreasing biodiversity [3]. The degree of eco-vulnerability varies despite the fact that the same geographical location may be receiving pressure from the same stressor. The ecological vulnerability to a certain stressor can be

Corresponding author: C.B. Hyandye (1977- ), male, master, main research fields: ecological environment evaluation, GIS, remote sensing and energy. E-mail: [email protected].

I.B. Katega (1960- ), male. Ph.D., main research fields: environmental planning and management. E-mail: [email protected].

defined as the susceptibility of the ecosystem to be changed as a consequence of that stressor [4]. Vulnerability is the degree to which a system is likely to experience harm as a result of exposure to perturbations or stress or the degree to which a person, organism, environment or system is likely to be caused harm by an activity [5]. Natural features such as mountain ranges, big rivers, steep slopes, natural vegetation may prevent human movement from one habitat to another, or prevent the ecological harm from natural phenomenon like erosion and landslides. Such natural features are called geographical barriers [5].

Tree roots help to bind and hold soil and rock particles together and thus prevent soil erosion or rock fall on steep slopes. Generally, rock fall happens on the sides of a steep mountain with little vegetation cover, but can also involve cliffs, caves, or arches. Small rockfalls are fairly common, but huge rock falls are rare


33

because of the amount of force needed to move tons of rock in question. Earthquakes can produce enough energy to cause large and small rock falls to disintegrate, move and fall. It is already known that tree and grass roots increase the shear strength of soils at particular eco-environment. When the amount of shear stress is higher than the shear strength, something has got to give. However, a quick movement, like an earthquake, acts as a trigger. It provides just enough energy to overcome the last bit of friction and allow gravity to pull everything down [6].

Geographic information system (GIS) is a modern information technique with powerful functions of storing, disposing, spatial analysis and visualizing [7-9]. RS and GIS technology have enhanced the eco-environment assessment procedure using eco-environment quality index tool [10]. For example, researchers use a series of eco-environmental attributes extracted from remotely sensed imagery and/or other auxiliary datasets, alongside with statistical methods such as Principal Component Analysis (PCA), the Analytic Hierarchy Process (AHP), or the Grey System Assessment Model (GSAM), to synthetically evaluate the ecological and spatial distribution characteristics of eco-environment [11]. With the rapid development of GIS and computer technology, it was widely applied in research fields of natural resources, environment management and their evaluations [12].

Moreover, spatial methods have proved to be useful for characterizing landscape features and dynamics. In addition, advancement in Remote Sensing, Geographic Information System (GIS) and numerical modeling techniques are crucial in developing powerful tools for eco-environment assessment procedures [13].

The study area under consideration currently is dominated by valleys and hill slopes. Hill slopes are the surfaces upon which humankind resides and engages in various economic activities [14]. Different activities like underground and surface mining, agriculture, construction, and forestry are taking place in the study area and hence contributing to the eco-vulnerability of

its ecosystem. Hillslopes comprise the land to be managed, the sites upon which forestry, agriculture, urban construction, and other human activities must be carried in harmony with natural processes [15].

The objective of this paper was to present the findings of the investigation about the potential of different landscapes on the complex ecosystem to act as a natural barrier to eco-environmental vulnerability. The vulnerability factors under the current analysis were soil erosion, vegetation cover, land use types, slope and elevation. Knowing the factors that lead to natural resistance of an ecosystem to eco-vulnerability is important in making decision of the magnitude required by the management at different zones within a complex ecosystem.


2.1 Description of the Study Area

The study area is found in Makeng village located between longitude 117° 2' 30"-117° 6' 04" East, and 25° 0'0"- 25° 3'30" North. The area is found in Xinluo district in Longyan city, Fujian province. This mining area is situated in the South East of Longyan basin (Fig.

Fig. 1 Location of the study area.


34

1). It is about 15 km away from Longyan city. The landform is complex, composed of monotonous mountains and valleys. The highest point is Tianshang’ ao on the northeast (1069 m). The lowest elevation is found in the Makeng Village in the southwest with elevation of 420 m. The main river in Makeng mining is Xi Ma River, flowing from the south to the north where it enters the Longyan basin.

The area lies in subtropical, monsoon climate characterized by warm and humid climatic conditions. There are no extreme temperatures in both summer and winter owing to its geographical position. Average annual temperature is about 19.9 ℃. The hottest month is July (38.1 ℃) whilst (delete, while) January (-5.6 ℃) is the coldest month. The average annual rainfall is about 1692 mm. The rains start in mid May, through June, July and August. Worth noting the rains in July and August are associated with typhoons. The total sun illumination is about 1979.1 hours per year. The geological formation and weather conditions allows some economic activities in the area namely iron mining, agriculture, forestry, settlement, road transportation and industry.

2.2 Data Types

2.2.1 Primary Data DEM (Digital Elevation Model), satellite images

(TM (Thematic Mapper) and ETM (Enterprise Technology Management)), soil type map, population statistics were the main primary data used in this research. The primary remote sensing images data were obtained from the “3S” (GPS, GIS and RS) laboratory in the school of environment of China University of

Table 1 Types of Remote Sensing images data.

Satellite ID & Instrument Acquisition date Resolution Landsat-5,TM 10 1992-10-20 30.00 m Landsat-5, TM 10 1998-12-08 25.00 m Landsat-7, ETM+7 2001-11-22 28.50 m Landsat-5, TM 10 2004-10-05 25.00 m Landsat-5, TM 10 2007-09-12 25.00 m

Soil types and DEM data were already available in the above mentioned laboratory.

Geosciences. Table 1 summarizes the RS data information.

2.2.2 Secondary Data Soil types were digitized from the existing soil types

map. Soil erosion maps in each year were prepared by performing GIS weighted overlay of slope, land use, vegetation types and soil type maps. Vegetation cover and landuse maps were derived from the TM10 and ETM+7 data through image classification. The land use classification was done according to American Planning Association-Land based classification standard [16]. All maps were georeferenced using UTM projection in which WGS 84 spheroid and WGS 84 datum were specified.

2.3 Assessment of Natural Barriers for Eco-environmental Vulnerability

The main method used for analysis of the influence of natural barriers to eco-vulnerability was the overlay method in ArcGIS 9.2 software. After overlaying the pairs of maps of interest, the statistics of the two layers matrix were extracted, exported to Ms Excel for manipulation, summarization and graphical presentation. The pairs of layers used in overlay were slope and land use, elevation and land use as well as vegetation cover and soil erosion. In order to assess the overall situation in eco-environmental vulnerability of the whole area under the influence of the natural barriers, an integrated eco-vulnerability index map with classes of vulnerability grades was prepared. The index map was used to show the distribution of eco-vulnerability grades on different landscapes based on elevation and time.


3.1 Distribution and Limitation of Land Use Types on Natural Landscapes

Different factor maps were used (overlaid) in combination to show how one factor influences the other. For example, how slope grades affect the distribution of land use types and eventually the gener-


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Fig. 2 A graph showing land use types on different slope grades.

al eco-vulnerability of the study area. The combination of factor maps used for analysis was slope and land use, land use and elevation, and soil erosion intensity and vegetation cover.

3.1.1 Influence of Slope on Land Use Slope grade determines the type of land use. Steep

slopes can not support big trees, and are always characterised by thin soil layer which support small plants like grasses. Fig. 2 shows that 74.67% of the land located on 0-2 degree is covered by forests. However, the forest land-cover percentage covered by forest decreases continuously from 5-15, 15-25 and >25 degree. Shrubs and agricultural land dominated the lands on 5-15 and 15-25, and to a small extent on the >25degree slopes. However, some unexpected results were found on the >25 degree slope land where 28.17% of the land is the urban land use type. The later can be explained by the presence of features like roads, up-and-down the study area and some iron mining and pre-processing industry and constructions on the steep edges of the mountains.

From these results, if slope was the only natural factor considered in contributing to eco-vulnerability, then the lands on 0-2 degree slope would be the most stable zone.

3.1.2 Influence of Elevation on Land Use The results shown in Fig. 3 conform to what was

observed in the field. Agriculture was largely carried on low lands (370-500 m) and 700-900 m altitudes whilst less agriculture activities were observed on 500-700 m altitudes. The result of the analysis (Fig. 3) shows that forest land (42.69%) and farm/grassland (36.43%) occupied upper altitudes (900-1100 m).

Clearly shown also is the fact that urban/built- up-land do not have much variation across the elevations. Generally, it ranges between 7.3% to 17.01% on the 900-1100 m and 370-500 m altitude respectively. The lands on altitudes 500-700 m are less forested and are more of shrublands (32.63%) and farmland (23.11%). This land use distribution observed was typically due to the nature of the area. On the 500-700m elevations, there were steep slopes of river valleys and/or mountains where big trees were not supported. Aspect also acted as a natural factor that influenced the existence of forest trees or shrubs in the altitudes. In addition, it was observed that forest trees hold soils in place firmly more than shrubs and grasses. Note: If the farmland and grassland could be separated as different classes during image classification, maybe better results would be obtained during the analysis.


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Elevation(m)

Land area(%)

Forest land

Shrubland

Farm/Grassland

Barrenland

Urban/Built-up-land

Fig. 3 A graph showing land use types on different elevation grades.

3.2 Influence of Vegetation Cover on Soil Erosion Intensity

Vegetation and land use are clearly important factors controlling intensity and the frequency of overland flow and surface wash erosion [17]. In addition, soil erosion mapping is an important aspect of the monitoring environment changes [18]. On the earth surface, when erosion occurs under natural environmental condition, it is called natural erosion. If human activities speed them up, and cause movements and loosening of surface soil, it is referred to as soil erosion. Soil erosion is an appearance fastened to move and lose soil by human activities in natural erosion [19]. Under normal circumstances it is expected that, the more the vegetation cover, the less the occurrence of soil erosion and vice versa. If vegetation cover was to be taken as a single natural barrier of eco-environmental vulnerability, then the areas with much vegetation would be more ecologically stable. Wind erosion happens when soils that have been cleared of plants are exposed to high-velocity wind [6]. On the other hand, plant density is much important than just the percentage of the area covered by those plants.

From Fig. 4, it was evident that vegetation type was an important natural barrier to eco-environmental vulnerability. The general trend in Fig. 4 is that soil

erosion intensity increases from left to right, except for a minor variation under agricultural land.

The current results show that evergreen conifers protect the soil more from erosion than deciduous plants which in period of the year they have no (shade off leaves). Most of the land under shrubs (SHRU) is under medium soil erosion whilst areas dominated by grasses (GRA) were under high erosion. Expected results were found for the land area under the non-vegetated land (NV) in which most of the area was under high and highest erosion intensity grades. The findings make sense because it is easy for erosion agents (water and wind) to detach soil particles in the non-vegetated areas than areas under dense vegetation which were covered by evergreen conifers (EC) and deciduous plants (DP). It can be noted in Fig. 4 that the area under AGRL has less erosion than FP. This could be due to the fact that plants under FP (mainly rice) are closely planted during growing season. Since rice is grown on heavy soils (clays) and on flat lands (Fig. 2), these areas are less affected by erosion.

3.3 General Vulnerability Distribution on Elevation Grades

The study area terrain was “V” shaped, the central part being the lowest in elevation. The eastern and western parts are higher than the central parts. From the


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y g yp

0

200

400

600

800

1000

EC DP SHRU GRA FP NV

Vegetation Types

Area(Ha)

Lowest

Low

Medium

High

Highest

EC=Evergreen Conifers, DP=Deciduous Plants, SHRU=Shrubs, GRA=Grasses, FP=Farm Plants, NV=Non-vegetated land.

Fig. 4 Soil erosion intensity under different vegetation types in 2007.

results the elevation (delete, is) was directly and inversely proportional to the vulnerability grades. Taking the year 2004 for example, the percentage of land accounted for heavy vulnerability was inversely proportional to elevation. However, vulnerability decreased with altitude, from 15.22%, 7.09%, 0.39% to 0.00% on elevations of between 373-500 m, 500-700 m, 700-900 m, and 900-1120 m respectively. The slight and light vulnerability grades follow similar trend as heavy vulnerability shown in Fig. 5.

The reason for the above observed trend was due to the fact that human activities that put eco-environment into stress like agriculture (paddy fields), iron and cement industries, settlement, and roads are concentrated on low elevations (373-500 m), and their intensity decreases with altitude.

Note: Only one big industry-Taibaolin was located on elevations above 500 m in the area. The areas between elevations 700-900 m (delete, high) have less human activities; and most of the land in these elevations was covered by both thick and less dense vegetations and grasslands. These areas are found in the northeast, east and west zones of the study area. In this study, the highest elevation was found in Tianshan’ao (900-1120 m), the top of the area had flat to gentle slopes, free from human activities and largely covered by vegetation. As a result, the land percentage characterized with the lowest vulnerability (0.00%) and the highest potential vulnerability (82.22%) was

found in the highest elevations. The potential vulnerability had a direct proportional relationship with elevation as from 500 to 1120 m, whereby it increased from 33.17%, 73.36% to 82.22% across the elevation ranges as shown in Fig. 5.

3.4 General Eco-vulnerability and Vegetation Cover

Nine factors were put into consideration during this study. They include both natural and human induced eco-environment stressors. Slope, population density and elevation parameters did not change during the vulnerability analysis. In this paper only a few selected natural barriers were discussed namely (slope, elevation, vegetation types). Soil erosion intensity was a function of land cover and land use changes for each particular year in the study. Hence; it can be concluded that land use and vegetation cover changes were the main driving forces for the eco-environmental vulnerability in the study area. Consider Fig. 6 showing land use types in terms of land percentage occupied under each year of investigation.

Figs. 6 and 7 showed a close relationship between decrease in vegetation cover and increase in heavy eco-vulnerability. Although Fig. 7 shows that in 1998, the environment was a bit resilient, where the percentage of land area under heavy vulnerability decreased to 0.89% compared with 6.61% in 1992; the area occupied by heavy vulnerability increases continuously from 1998 to 2007.This increase in heavy


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cent

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Fig. 5 Distribution of vulnerability grades along the elevation ranges in 2004.

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Fig. 6 A graph showing land use change trends against time in the study area.

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24.4

3

30.2

1

12.5

9

7.74

13.3

0

13.8

9

25.6

0

6.61

0.89 2.

24

4.76

9.34

22.5

9

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

1992 1998 2001 2004 2007Years

Land

Per

cent

age

Potential

Slight

Light

Medial

Heavy

Fig. 7 Eco-environmental vulnerability grades dynamics expressed in percentage of land they cover against time.


39

vulnerability has a close link with the decrease in forest cover shown in Fig. 6.

5. Conclusions

In this study natural stability of an eco-environment is a function of many natural factors such as vegetation cover, elevation and slope. It is hereby concluded that the named factors naturally regulated and limited some natural processes like soil erosion and landslides. They also limited the intensity of human like cultivation and construction. Vegetation cover plays a great role as natural barrier to eco-environmental vulnerability. In environmental rehabilitation programs great emphasis should be on increasing the number of trees and vegetation cover as they not only stabilize the lands in different elevation but also on different slope grades. Mapping the degree of eco-environmental vulnerability and influencing factors is crucial before making decisions about the level and type of management to be employed in that eco-environment.

Acknowledgments

This research was funded by China Scholarship Council. The author is grateful to China Center for Remote Sensing-Beijing and Makeng Mining Company for providing reliable data which made this research successful. The author is also feel indebted to everyone who supported me in one way or the other.

References [1] Z. Shi, H.Y. Li, Application of artificial neural network

approach and remotely sensed imagery for regional eco-environmental quality evaluation, Journal of Environ Monit Assess 128 (2007) 217-229.

[2] W.Y. Niu, W.M. Harris, China: the forecast of its environmental situation in the 21st century, Journal of Environmental Management 2 (1996) 101-114.

[3] Y.L. Qiao, Y. Wang, J.Y. Tang, Study of remote sensing monitoring of dynamic change of the Loess Plateau forest resources, Journal of Advances in Space Research 3 (2004) 302-306.

[4] P. Ibarra, Ecological Vulnerability to Forest Fires: an Evaluation Model, available online at: http://www. fire.uni-freiburg.de/sevilla-2007/contributions/doc/SESIONES_TEMATICAS/ST1/Ibarra_et_al_SPAIN.pdf(2007).

[5] Dictionary of Environment & Ecology, Fifth edition, P.H. Collin, Bloomsbury Publishing Plc 38 Soho Square, London W1D 3HB (2004).

[6] D.W. Linda, Environmental Science Demystified, McGRAW-HILL, 2005, p. 215.

[7] C.O. Gregory, D.C. Ohn, Using multiple logistic regression and GIS technology to predict landslide hazard in Northeast Kansas, USA. Eng. Geol. 69 (2003) 331-343.

[8] K. Charnpratheep, Q. Zhou, B. Garner, Preliminary landfill site screening using fuzzy geographical information systems, Waste Manage. Res. 2 (1997) 197-215.

[9] D. Thirumalaivasan, M. Karmegam, K. Venugopal, AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS, Environ. Model. Software 18 (2003) 645-656.

[10] Z.W. Li, G.M. Zeng, H. Zhang, The integrated eco-environment assessment of the red soil hilly region based on GIS-a case study in Changsha City, China. Ecol. Model 3-4 (2007) 540-546.

[11] R. Aspinall, D. Pearson, Integrated geographical assessment of environmental condition in water catchments: linking landscape ecology, environmental modelling and GIS, Journal of Environmental Management 59 (2000) 299-319.

[12] H.X. Lan, C.H. Zhou, L.J. Wang, Landslide hazard spatial analysis and prediction using GIS in the Xiaojiang watershed, Yunnan, China. Eng. Geol. 76 (2004) 109-128.

[13] X. Zhang, S. Dong, W. Yin, GIS grid calculation method application in urban eco-environment assessment-a case study of Longxi County in Gansu Province, in: China Proceedings of SPIE-The International Society for Optical Engineering, 2005, pp. 1-10.

[14] J.T. Terrence, F.H. Richard, Geomorphology and Reclamation of Disturbed Lands, Academic Press, INC. 1987, p. 75.

[15] T. Dunne, L.B. Leopord, Water in Environmental Planning: San Francisco, W.H. Freeman and Co., 1978, pp. 818.

[16] J.R. Anderson, E. Hardy, J. Roach, Witmer, A land-use and land-cover classification system for use with remote sensor data, Washington: U.S. Geological Survey, Professional paper#964, 1976, p. 28.

[17] European Environment Agency-EEA, Assessment and Reporting on Soil Erosion: Background and Workshop Report, 2003, p. 30, ISBN: 92-9167-519-9.

[18] Z.X. Zhang, Mountain Soil Erosion Mapping in Central Tibet Using Remote Sensing and GIS, Paper presented at the 4th International Symposium on High Mountain Remote Sensing Cartography, Karlstad - Kiruna - Tromsø, August 19-29, 1996.

[19] H.D. Fost, The Principle of Soil Science, Agricultural Press, Beijing, China (Dec. 1984).


Study on the Sulfur Nutrition of the Sugarcane and Balance of Sulfur in Soil for Sugarcane Planting Areas

H.W. Tan, L.Q. Zhou, R.L. Xie and M.F. Huang Guangxi Academy of Agricultural Sciences, Nanning 530007, Guangxi, China


Abstract: Areas of planting sugarcane are located in subtropical and tropical parts of Guangxi. These areas are characterized by high temperature, heavy rainfall and nutrients leaching. It results in strong decomposition of soil mineral and a low cation exchange capacity (CEC), low organic matter, and low phosphorus (P), potassium (K) and sulfur (S) in soils. In about 30% of the soils in the planting sugarcane regions the total sulfur and the plant-available sulfur are under 150 mg/kg and 12 mg/kg, respectively. The sulfur nutrition is usually supplied insufficiently for sugarcane growth. The total sulfur of and available sulfur are under the medium level in nearly 50% of the soils in the planting sugarcane regions. Therefore, with the improvement of production of the sugarcane, the sulfur soil nutrition will influence and limit sugarcane yield. After application of sulfur fertilizer, available stem, single stem weight increased 5.77%-9.43% of sugarcane yield than without the treatment. It still can improve the cane sugar and fibre content. And the sugarcane can obtain better economic benefits to use the sulfur phosphorus ammonium; it is 18.2-20.23 with output/input (VCR) to use the sulfur fertilizer. Amount of sugarcane absorption sulfur reaches 44.1-67 kg/ha. The treatment with no sulfur fertilizer annual sulfur nutrient lose will be 23.67 kg/ha because sugarcane yield uptake from the field. Key words: Sugarcane, sulfer nutrition, soil, balance of sulfer.

1. Introduction

Guangxi is located in the southwest of China, belonging to tropical and subtropical monsoon climate district, the temperature and rainfall are relatively high, the soil is weathered and leached strongly, the phosphorus, potassium, sulfur and cation exchange capacity (CEC) are relatively low in the soil [1]. In recent years, sugarcane yield increased in a large amount and the reduction of the sulfur fertilizer applied on sugarcane [2, 3]. So, it is necessary to study the effect of sulfur on sugarcane for sustainable sugarcane production development in Guangxi.

Corresponding author: H.W. Tan (1961- ), male, professor, research fields: plant nutrition and ecology. E-mail: [email protected].

L.Q. Zhou (1964- ), male, professor, research fields: soil science and environment. E-mail: [email protected].

R.L. Xie (1965- ), male, professor, research fields: soil and fertilizer. E-mail: [email protected].

M.F. Huang (1954- ), female, professor, research field: soil chemical. E-mail: [email protected].


The duration of field experiments was 2002 to 2006 year. The variety of used sugarcane was Taitang series No.22. Plant density was 5000 buds/ha. Plot area was 33.3 square meters. The soil type included red soil, lateritic soil, laterite and limestone soil. The following treatments were designed:

(1) CK (NPK); (2) 30 kg S (DAPS1, DAP) (including sulfur

phosphorus ammonium 15.7-41.8-0-17.6S); (3) 60 kg S (DAPS2, DAP) (including sulfur

phosphorus ammonium 15.7-41.8-0-17.6S), this is OPT and OPT is optimum practice treatment;

(4) S1 (SSPS1) 30 S; (5) S2 (SSPS2) 60 S. SSP is the superphosphate. The fertilizers rate (kg/ha)

was: N=N 337.5; K=K2O 337.5; P=P2O5 150; S1=S 30; S2=S 60; Mg=MgO 30. Four replications were used


41

for each trial. The sulfur content was determined in precipitation

collected annually from the precipitators set in the fields and in the soil. Ca(H2PO4)2 was used as extracting solution to extract soil available sulfur, which was determined photometrically after reaction with sulfuric acid barium. The total soil sulfur was determined photometrically after boiling the soil samples in HNO3-HClO4. The determination of sucrose, it is to use polarimetry. The determination of reducing sugar, it is to use the filin-iodine volumetric procedure. The determination of fiber, it is to use the method of acid-detergent fiber.


The 301 soil samples were collected in Guangxi sugarcane planting areas. The results of analysis showed the soil can be divided into three groups depending on the total sulfur levels: low (<150 mg/kg), mid (150-300 mg/kg) and high (>300 mg/kg), which accounted for 30%, 51% and 19% in paddy field respectively, and for upland the corresponding data were 32%, 50% and 18%, respectively. The upland soil could be also divided into three groups depending on available sulfur: low (<12 mg/kg), mid (12-24 mg/kg) and high (12-24 mg/kg), which accounted for 31%, 52% and 17% in Paddy field respectively. For upland the corresponding data were 35%, 48% and 17% respectively (see Table 1). Therefore, relatively large part of sugarcane planting areas in Guangxi showed deficiency of sulfur.

Application of sulfur fertilizer influenced on agro-properties of sugarcane (Table 2). The optimum practice treatment, DAPS2 (+S) increased sugarcane milliable stalks to 8,700 plant/ha (12.1% more than the treatment without sulfur fertilizer) and a single stalk weight to 120 grams (10.6% more than the treatment without sulfur fertilizer.

The experimental results showed that the DAPS1 treatment (application of 30 kg of S/ha) increased sugarcane yield 5.77% on average (Table 3) while

application 60 kg of S/ha (DAPS2) increased sugarcane yield by 9.43% on average. Besides, the effect of sulfur with phosphorus ammonium is better than super calcium phosphate.

Application of sulfur fertilizer increased the quality of sugarcane. As shown in Table 4, sucrose was increased by 0.06% and the fibre by 0.17%, while

Table 1 The sulfur in soil of sugarcane planting areas in Guangxi.

Soil Sulfur in soil Low (%) Mid (%) High

(%) Average (mg/kg)

Available sulfur(mg/kg) 31 52 17 17.7 Paddy

field Total sulfur(mg/kg) 30 51 19 250.0

Available sulfur(mg/kg) 35 48 17 16.3

Upland Total sulfur(mg/kg) 32 50 18 208.0

Table 2 Agricultural properties of sugarcane.

Item CK(-S) SSPS1 DAPS1 SSPS2 DAPS2(OPT)

Milliable stalk (plant/hectare) 72,000 79,831 79,222 80,400 80,700

Height of plant (cm) 293.0 285.7 289.1 283.2 291.0Diameter of stalk (cm) 2.7 2.6 2.7 2.6 2.7 Single stalk weight (g) 1130 1139 1141 1151 1250

OPT is optimum practice treatment. Table 3 Effect of application various kinds of sulfur fertilizer on sugarcane.

Sugarcane Increasing yield Average Field experiments 12

(kg/ha) 5,781 –7,350 6,565.5** DAPS1 than CK Increased yield (%) 5.27 --6.27 5.77

(kg/ha) 10,471 –10,894 10,682** DAPS2 than CK Increased yield (%) 8.93 --9.93 9.43

(kg/ha) 5,380 –6,540 5,960** SSP1 than CK Increased yield (%) 4.91 --5.58 5.25

(kg/ha) 8,880 –10,400 9,640** SSP2 than CK Increased yield (%) 7.57 --9.48 8.53

F=27.51, LSD0.05=186.64, LSD0.01=255.13; ** is reached the level of LSD0.01.

Table 4 The results of analysis on quality of sugarcane.

Treatment OPT(+S,DAPS2) CK(-S,NPK) Sucrose (%) 14.64 14.58 Fibre (%) 12.44 12.27 Reduce candies (%) 2.15 2.20


42

candies were reduced by 0.05% in plants treated with sulfur fertilizer in comparison to the plants without sulfur fertilizer.

The economic benefits of application sulfur fertilizer on sugarcane are shown in Table 5. The treatments with DAPS1 and DAPS2 increased sugarcane average output value/hectare of 266.38 USD and 391.16 USD than the treatments with without S respectively. Per kg sulfur fertilizer increased income more than 6.50 US dollar.

The results shown in Table 6 showed that better economic benefits can be achieved by application of sulfur in superphosphate than sulfur in diammonium phosphate. The results of field experiments indicated that application of 1 USD in case of using this fertilizer (DAPS or SSPS) could result in the income of 18.83-20.23 USD in Guangxi sugarcane production.

The sulfur content increases in leaf and stalk of sugarcane plants after applied sulfur fertilizer (Table 7). The application of sulfur fertilizer could promote the absorption of sulfur by sugarcane, promoting the growth of sugarcane and increasing cane yield. There was no significant difference between fertilizers. Absorption of S by sugarcane was increased with the increase of sulfur amount and it reached 29.02-48.07 kg/ha as shown in Table 8.

The rain was collected from 12 field experimental sites. The average yearly rainfall was 1379 mm. The rainwater contained on average 17.4 kg of S/ha. In the first quarter (January-March) the rainfall was 327 mm with sulfur of 1.22 kg/ha; in the second quarter (April-June) the rainfall was 562 mm with sulfur of 8.70 kg/ha; in the third quarter (July-September) the rainfall was 401 mm with sulfur of 6.96 kg/ha and in the fourth quarter (October-December) the rainfall was 289 mm with sulfur of 0.52 kg/ha. Sugarcane absorbed only 5.22 kg of S/ha from rainwater, accounting for 30% of total rainwater contained sulfur.

Sugarcane stems uptake more sulfur from soil than leaves. The application sulfur nutrient of leaf is one of important measure that the sugarcane applies fertilizer.

Table 5 Economic benefits of application sulfur fertilizer on sugarcane.

Treatment Increase the output value than CK (US$/ha)

Each kg S increases the output value(US$)

DAPS1 266.38 8.88

SSPS1 241.88 8.06

DAPS2 433.48 7.22

SSPS2 391.16 6.52

Price (US$/kg): Sugarcane=0.04, S=0.29. 1US$=6.90RMB.

Table 6 Economic benefits of application different sulfur fertilizer on sugarcane.

Treatments CK (-S) SSPS1 DAPS1 SSPS2 DAPS2 Output value (US$/ha) 3337.83 3513.77 3669.42 3501.59 3654.35

Increase income than CK (US$/ha)

/ 175.94 331.59 163.77 316.52

VCR / 20.23 19.06 18.83 18.2

Price: (US $/kg): Sugarcane =0.04. VCR is value: cost ratio. Table 7 Influence of application S fertilizer S content of sugarcane leaf and stem (%).

Treatments CK(-S) DAPS1 DAPS2 SSPS1 SSPS2

Leaf 0.041 0.069 0.062 0.063 0.064

Stem 0.022 0.033 0.037 0.034 0.038 Table 8 Influence of application sulfur fertilizer on sugarcane absorption S (kg of S/ha).

Treatments CK(-S) DAPS1 DAPS2 SSPS1 SSPS2 Absorption S ( kg S/hectare) 29.02 47.30 48.07 47.80 47.01

Table 9 Balance of treatments with S and without S on sugarcane (kg/ha ).

Treatments OPT(+S) CK(-S)

Sugarcane stem uptake S (kg/ha) 43.36 25.03

Sugarcane leaf uptake S(kg/ha) 4.71 3.99

Application fertilizer bring S (kg/ha) 45.00

Rainfall brings S(kg/ha) 5.22 5.22

Sulfur nutrient balance(kg/ha) 0.15 -23.80

From nutrient balance analysis, there were surplus of sulfur nutrient that OPT treatment applied sulfur fertilizer, and the treatment without application sulfur fertilizer, sulfur nutrient lose 25.03 kg/ha for one year because sugarcane stem uptake sulfur nutrient from soil as shown in Table 9.


43

4. Conclusions

The treatment with sulfur fertilizer resulted in increased sugarcane milliable stalk and single weight. Application of 30 kg/ha of sulfur fertilizer increased an average sugarcane yield by 5.77%, while 60 kg/ha of sulfur fertilizer resulted in an increase of average sugarcane yield by 9.43%. The effect of sulfur phosphorus ammonium was better than super calcium phosphate. Sucrose and fibre contents were increased while applied the sulfur fertilizer. Application of sulfur fertilizer can bring economic benefit, with 18.20- 20.23 of output/input (VCR). The sulfur content in sugarcane leaf was higher than that in the stalk, sugarcane could uptake sulfur 29.02-48.07 kg/ha. The treatment without sulfur fertilizer resulted in annual sulfur nutrient loss of

23.80 kg/ha because sugarcane absorbed it from soil.

References [1] H.W. Tan, L.Q. Zhou, R.L. Xie, M.F. Huang, Farmland

nutrient cycle and nutrient balance in Guangxi, nutrient balances and nutrient cycling in agro-ecosystems, International Potash Institute P.O. Box 1609, CH-4001, Basel, Switzerland, 2003, pp. 241-250.

[2] H.W. Tan, Economic balance of crops and fruits production by K, Mg and S fertilizers application in subtropical red acid soil of Guangxi Province, China, TROPICS, Vol.13, No.4, March 2004, pp. 287-291.

[3] S. Dowdle, S. Portch, A systematic approach for determining soil nutrient constrains and establishing balanced fertilizer recommendations for sustained high yields, Proceedings of the International Symposium on Balanced Fertilization, November 1988, Beijing, China, pp. 8-12.


Characterization of Suspended Solids and Heavy Metal Distributions during First Flush in Highway Runoff

W.C. Liu, W.Z. Huang and A.Y. Yang Department of Civil and Disaster Prevention Engineering, National United University, Miaoli 36003, Taiwan

Received: June 9, 2010 / Accepted: August 3, 2010 / Published: September 20, 2010.

Abstract: Nonpoint source pollution has gradually received attention during stormwater flush in highway runoff. The understanding the pollutant characteristics will be critical issue to treat these types of pollution. In the present study, two monitoring stations were selected to measure hydrology and to take sampling during first flushing events at the Zhong-Shan freeway and East-West expressway in the Miaoli County, Taiwan. The results of monitoring stations in 2007 storm events found that normally the peak concentrations of total suspended solids (TSS) and heavy metals occurred at the initial stormwater and then the concentrations decreased when the measured time elapsed. The highest and lowest heavy metal concentrations were Fe and Ni, respectively, during the stormwater. Particle size distribution (PSD) mostly ranged from 12 μm and 96 μm at two measured sites. The event mean concentrations (EMCs) and loadings of TSS and heavy metals were also correlated with total runoff and total rainfall. Key words: Suspended solids, heavy metal, first flush, runoff, highway, Miaoli.

1. Introduction

In general, the pollutant concentrations decline over time, which has the tendency to produce greater emission rates at the beginning of runoff. This phenomenon is called “first flush”. The existence of first flush can affect the choice of the best management practices (BMPs). The decline in concentration is sometimes off-set by an increasing run off rate as a storm progresses. The first flush resulting in runoff significantly produces the water quality deterioration in receiving water bodies.

Stormwater has been identified as a major pollution source for many urban waters [1-7]. Rainfall generated runoff from highway surfaces often contains

Corresponding author: W.C. Liu (1963- ), male, Ph.D.,

professor, main research fields: environmental hydraulic and computational fluid dynamics. E-mail: [email protected].

W.Z. Huang (1985- ), male, graduate student, main research fields: environmental mechanics and field measure. E-mail: [email protected].

A.Y. Yang (1985- ), female, main research fields: groundwater modeling and field measurement. E-mail: [email protected].

significant loads of metal elements, particulate and dissolved solids, and organic compositions. These anthropogenic constituents are generated mainly from traffic activities, vehicular wear, fluid leakage, pavement degradation, roadway maintenance and atmospheric deposition [8-11]. For example, tire and pavement interaction abrades materials and results in the main source of solids [12]. Pavement contributes 40-50% and tires accounts for 20-30% of solids production [13]. Metals elements can not be degraded in the environment and compose an important class of persistent constituents. They can partition into dissolved and particulate fractions as the function of pH, average pavement residence time and nature and quantity of solids present.

Furumai et al. [14] conducted continuous runoff quality monitoring for one month at urban highway drainage. They concluded that particle-bound heavy metals (Zn, Pb, and Cu) accounted for more significant pollutant loads than soluble fractions. Their content decreased with increasing total suspended soils concentration in runoff samples. Kayhanian et al. [15]


45

collected and analyzed the four-year highway runoff data. The results revealed that pollutant concentrations from urban highways were higher than those found from nonurban highways. No direct linear correlation was found between highway runoff pollutant event mean concentrations and annual average daily traffic. Kim et al. [16] monitored at six southern California highway sites during stormwater runoff to measure total captured gross pollutants. They found that the gross pollutants were 90% vegetation and 10% litter. Approximately 50% of the litter was composed of biogradable materials. Crabtree et al. [17] collected the nonurban highway at six sites during and used to identify ranges of pollutant concentrations in highway runoff, relationships between runoff concentration/ loads and both highway and environmental factors, drainage system treatment efficiencies, and impacts on receiving waters. Kayhanian et al. [6] used the multiple linear regression analyses to evaluate the impact of various measured sites and storm event variables on California highway runoff constituent event mean concentrations. They found parameters to have significant impacts on highway runoff constituent event mean concentrations include: total event rainfall, cumulative seasonal rainfall, antecedent dry period, contributing drainage area, and annual average daily traffic. Surrounding land use and geographic regions were also determined to have a significant influence on runoff quality. Eckley and Branfireun [18] studied the mercury mobilization in stormwater runoff. They found that mercury concentrations were highest at the beginning of the hydrograph and were predominately particulate bound. Almost 50% of the total mercury load was transported during the first minutes of runoff.

Accurate knowledge of the quantity and quality of runoff is required to evaluate the effects of runoff on the environment and to develop appropriate mitigation technologies. In the present study, a comprehensive measurement was conducted from highway constructions in the Miaoli County, Taiwan to characterize the quantity and quality of first flushing

runoff. The regression relationships of the event mean concentrations (EMCs) and loadings of total suspended solids (TSS) and heavy metals correlated with total runoff and total rainfall were established.


2.1 Research Site and Sample Collection

Stormwater runoff characterization data used in this study were collected from the Zhong-Shan freeway (ZS) and East-West expressway (EW) in the Miaoli County (Fig. 1), Taiwan covering annual average daily traffic of over 25,000 vehicles/day and 90,000 vehicles/day, respectively.

The drainage systems of highway (Fig. 2) serve as the locations taking water sampling and to measure water volume with huge bucket. Therefore, the runoff during the storm events can be calculated. Tipping bucket rain gage was established near the highway to measure rainfall. The measured sites were so small that there was very little delay between the peak rainfall and peak runoff.

Water sampling collection began immediately after the beginning of runoff, usually 5 minutes intervals during the half-hour. After the half-hour, the samples were collected in every 10 minutes. After one hour, the samples were collected in every 20 minutes until the end of storm event. The water samples were periodically taken to the laboratory and all were analyzed with 8 hours of collection.

Fig. 1 Monitoring locations in Miaoli County of Taiwan.


46

Fig. 2 Drainage systems of East-West expressway (upper panel) and Zhong-Shan freeway (lower panel).

2.2 Sample Analysis

Water quality parameters analyzed in the laboratory for all runoff samples included: turbidity, conductivity, turbidity, total suspended solids (TSS), heavy metals (iron, lead, cadmium, nickel, zinc, and copper), and particle size analysis. We employed a Mastersizer laser particle size analyzer to determine the particle size distribution. This instrument uses light diffraction technique.

2.3 Determination of Event Mean Concentration

The pollutant concentrations washed off from nonpoint sources are quantified with event mean concentrations (EMCs). The classical EMC was used to determine the mass loading to receiving waters as shown in Eq. (1):

EMC (mg / L) = 1 1

( ) ( ) / ( )t T t T

t t

C t q t q t= =

= =

⋅⎡ ⎤⎢ ⎥⎣ ⎦∑ ∑ (1)

Wher ( )C t = pollutant concentration, ( )q t = runoff flow rate discharged at time t , and T is the period of the storm. The equation can also be used to portion of the storm by applying the appropriate integration limits [19]. EMCs are generally adopted to characterize stormwater loadings and can be multiplied by runoff volume to estimate the mass discharge [20,21].


3.1 Characteristics of Pollutants

Six storm events were monitored at two sites in

highway. Table 1 summarizes the characteristics of the events and sites including measured stations, event date, antecedent dry days (ADD), total rainfall, and total runoff. Fig. 3 shows the appearance concentration at the East-West expressway, with good views to present the first flush effect.

Figs. 4 and 5 present the example of pollution- graphs observed on August 18th at the East-West expressway and Zhong-Shan freeway, respectively. In general, the initial washed-off concentrations were higher and decreased with time elapsed. Concentration Table 1 Characteristics of the storm events at the East-West expressway (EW) and Zhong-Shan freeway (ZS). Measured station

Event date(in 2007)

ADD (day)

Total rainfall (mm)

Total runoff (L)

EW-1 May 18 11 5.00 1627.5 EW-2 May 22 1 4.50 1577.5 EW-3 Aug. 7 2 2.15 472.5 EW-4 Aug. 17 2 1.5 835.2 EW-5 Aug. 18 0 4.17 1617.7 EW-6 Sep. 17 10 2.72 869.7 ZS-1 May 22 1 4.50 269.5 ZS-2 Aug. 18 1 4.18 117.5

Fig. 3 Appearance concentrations at the East-West expressway.


47

0

40

80

120

160

200

TSS (

mg/

L)

0

20

40

60

80

Flow

(L/

min)

8

4

0

Inte

nsity

(m

m/h

r)

20070818 TSSFlow

0 40 80 120Time (min)

0

40

80

120

160

200

Turb

idity

0

100

200

300

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duct

ivity

(us

/cm

)

20070818 TurbidityConductivity

0 20 40 60 80 100

Time (min)

0

1

2

3

4

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cent

ratio

n (m

g/L)

20070818 PbFeCuCdZnNi

Fig. 4 Hydrographs and pollution-graphs on August 18th, 2007 at the East-West expressway.

reduction happens whenever a particular quantity of pollutant mixes with a large runoff volume. The dilution in stormwater occurs as a continuous and varies with rainfall rate. Among the heavy metals, Fe exhibits highest concentration during the storm events. The reason that causes the spike in Fe concentration after 100 minutes is the sudden input of nonpoint source from vehicles. Concentrations of poll utants in runoff often are higher at the beginning of runoff events.

In general, stormwater treatment systems are established to capture the initial runoff from storms and

0

20

40

60

80

TSS (

mg/

L)

0

4

8

12

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(L/

min)

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20070818 TSSFlow

0 40 80 120Time (min)

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ductivity

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cent

ratio

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g/L)

20070818 PbFeCuCdZnNi

Fig. 5 Hydrographs and pollution-graphs on August 18th, 2007 at the Zhong-Shan freeway.

remove and treat the runoff that contains the highest concentration of pollutants. The measured results suggested that TSS and Fe are the dominant pollutants. They should have the priority to be removed with BMPs and/or stormwater treatment systems.

3.2 Calculation of EMCs and Loadings

The EMCs were determined using Eq. (1) and summarized in Table 2. The EMCs ranged from 1.7 to 120.6 mg/L for TSS, 0.21×10-2 to 4.87×10-2 mg/L for Pb, 0.28 to 1.28 mg/L for Fe, 0.26×10-2 to 2.58×10-2


48

Table 2 Calculated EMCs at the East-West expressway (EW) and Zhong-Shan freeway (ZS).

EMC (mg/L) Measured station

Event date (in 2007) TSS Pb (×10-2) Fe Cu (×10-2) Cd (×10-2) Zn (×10-1) Ni (×10-2)

EW-1 May 18 120.6 -- -- -- -- -- -- EW-2 May 22 41.0 -- -- -- -- -- -- EW-3 August 7 46.2 2.19 0.28 1.55 0.39 1.73 1.16 EW-4 August 17 64.7 0.79 0.46 0.26 0.23 0.87 0.41 EW-5 August 18 29.3 0.53 0.71 0.61 0.16 0.44 0.07 EW-6 September 17 102.6 0.21 1.28 1.84 0.15 1.95 0.40 ZS-1 May 22 9.5 -- -- -- -- -- -- ZS-2 August 18 1.7 4.87 0.49 2.58 0.65 2.15 0.91

“- -” represents no measurements.

Table 3 Calculated loadings at the East-West expressway (EW) and Zhong-Shan freeway (ZS).

EMC (mg/min) Measured station

Event date (in 2007) TSS Pb (×10-2) Fe Cu (×10-2) Cd (×10-2) Zn (×10-1) Ni (×10-2)

EW-1 May 18 5.9 -- -- -- -- -- -- EW-2 May 22 1.1 -- -- -- -- -- -- EW-3 August 7 235.6 11.18 1.43 7.90 1.97 8.81 5.93 EW-4 August 17 577.9 0.39 4.14 2.38 2.09 7.74 6.36 EW-5 August 18 589.7 10.66 14.22 12.25 10.24 2.06 1.43 EW-6 September 17 1364.5 2.85 17.00 23.42 1.94 25.97 5.36 ZS-1 May 22 22.7 -- -- -- -- -- -- ZS-2 August 18 2.5 6.87 10.69 11.34 2.18 3.03 0.03

“- -” represents no measurements.

for Cu, 0.15×10-2 to 0.65×10-2 mg/L for Cd, 0.044 to 0.215 mg/L for Zn, and 0.07×10-2 to 1.16×10-2 mg/L for Ni. The wide distributions of EMCs depended upon the total rainfall and rainfall intensity owing to the dilution effect during storm events. The ADD and average rainfall intensity did not present consistent correlation with the EMC value.

Table 3 illustrates the loadings during the storm events. It shows that the pollutant loadings ranged from 1.1 to 1364.5 mg/min for TSS, 0.39×10-2 to 11.18×10-2 mg/min for Pb, 1.43 to 17.0 mg/min for Fe, 2.38×10-2 to 23.42×10-2 mg/min for Cu, 1.94×10-2 to 10.24×10-2 mg/min for Cd, 0.021 to 2.60 mg/min for Zn, and 0.03×10-2 to 6.36×10-2 mg/min for Ni. The highest and lowest pollutant loadings among the heavy metals are Fe and Ni, respectively and the second high loadings is Zn.

3.3 Regression of Washoff Pollutants and Hydrological Data

Irish et al. [21] collected the stormwater data from an expressway in the Austin Texas area and developed linear regression models for predicting loads for a number of constituents commonly found in highway runoff. In this study, the deterministic stormwater quality models were established to address the rate at which pollutants are washed from the highway and that a simple exponential function describes concentrations and loadings. The relationship between hydrological data and TSS concentration during the storm events is shown in Fig. 6. The relationships between total runoff and TSS of EMC as well as total rainfall and TSS loadings are given in Eqs. (2) and (3):

0.00148.03 TROTSSC e ⋅= ⋅ , 2 0.41R = (2)

1.5412563 TRFTSSL e− ⋅= ⋅ , 2 0.51R = (3)

Where, TSSC = TSS concentration of EMC (mg/L),

TSSL = TSS loadings (mg/min), TRO= total rrunoff (L),

TRF = total rainfall (mm), and 2R = coefficient of determination.

The regression equations between washoff heavy


49

Fig. 6 Regression of total runoff and TSS of EMC as well as total rainfall and TSS loadings.

Table 4 Regression equations of heavy metal.

Heavy metal Regression equation 32 100.0342 TRO

PbC e−− × ⋅= ⋅ , 2 0.53R =

Pb 0.77980.00393 TRF

PbL e ⋅= ⋅ , 2 0.45R = 45 100.3958 TRO

FeC e−× ⋅= ⋅ , 2 0.21R =

Fe 0.55611.3375 TRF

FeL e ⋅= ⋅ , 2 0.42R = 49.6 100.0219 TRO

CuC e−− × ⋅= ⋅ , 2 0.33R =

Cu 0.4270.026 TRFCuL e ⋅= ⋅ , 2 0.36R =

31.53 100.0141 TROCdC e

−− × ⋅= ⋅ , 2 0.39R = Cd

0.3580.00984 TRFCdL e ⋅= ⋅ , 2 0.36R =

31.0 100.2787 TROZnC e

−− × ⋅= ⋅ , 2 0.76R = Zn

0.5453.203 TRFZnL e− ⋅= ⋅ , 2 0.44R =

31.86 100.0178 TRONiC e

−− × ⋅= ⋅ , 2 0.90R = Ni 1.4561.10 TRF

NiL e− ⋅= ⋅ , 2 0.57R =

metals and hydrological data can be summarized and listed in Table 4. It is revealed that the best regression results depended on coefficient of determination appear in heavy metal Ni. We can use these equations to estimate the EMCs and loadings of pollutants if the total rainfall and total runoff are measured.

3.4 Particle Size Distribution

Particles in highway runoff contain various sorbed pollutants, and many BMPs are selected for particle removal efficiency, which makes particle size distribu-

Fig. 7 PSD at the East-West expressway (upper panel) and Zhong-Shan freeway (lower panel).

tion a crucial BMP design parameter. Li et al. [22] quantified particles between 2 and 1000 μm in diameter for three rainfall events during rainy season at three highway sites in west Los Angles. In order to comprehend the particle size distribution (PSD), the water samples during the storm events were collected and determined with Mastersizer laser particle size analyzer. Fig. 7 presents the PSD in highway runoff. It showed that the PSD at the measured stations ranged from 1 μm to 192 μm and 80% PSD was occupied in the range of 12 μm and 96 μm. These two measured stations revealed a similar pattern in PSD.

4. Conclusions

This study was performed for understanding the pollutant characteristics and estimating the EMCs and loadings during the storm events in highway runoff of Taiwan. The measured results reveal that EMCs ranged from 1.7 to 120.6 mg/L for TSS, 0.21×10-2 to 4.87×10-2 mg/L for Pb, 0.28 to 1.28 mg/L for Fe, 0.26×10-2 to 2.58×10-2 mg/L for Cu, 0.15×10-2 to 0.65×10-2 for Cd, 0.044 to 0.215 mg/L for Zn, and 0.07×10-2 to 1.16×10-2

0

10

20

30

40

50

60

70

80

90

100

1 2 2 3 4 6 8 12 16 24 32 48 64 96 128 192

particle diameter(μm)

perc

ent p

assi

ng(%

)

individual

cumulative curve

0

10

20

30

40

50

60

70

80

90

100

1 2 2 3 4 6 8 12 16 24 32 48 64 96 128 192

particle diameter(μm)

perc

ent p

assi

ng(%

)

individual

cumulative curve


50

mg/L for Ni. The wide distributions of EMCs depended upon the total rainfall and rainfall intensity because of the dilution effect during storm events. The pollutant loadings ranged from 1.1 to 1364.5 mg/min for TSS, 0.39×10-2 to 11.18×10-2 mg/min for Pb, 1.43 to 17.0 mg/min for Fe, 2.38×10-2 to 23.42×10-2 mg/min for Cu, 1.94×10-2 to 10.24×10-2 mg/min for Cd, 0.021 to 2.60 mg/min for Zn, and 0.03×10-2 to 6.36×10-2 mg/min for Ni. The highest and lowest pollutant loadings among the heavy metals are Fe and Ni, respectively. The particle size distributions ranged from 1 μm to 192 μm.The regression equations between washoff pollutants and hydrological data were also established and revealed that a simple exponential function could be applied to calculate the EMCs and loadings for TSS and heavy metals. The study will inform the decision making on the need for the provision of appropriate treatment of highway runoff. This will also contribute to the sustainable management of the highway road network in Taiwan.

Acknowledgments

The project, under which this study was conducted, was support by National Science Council, Taiwan, under Grant number NSC 96-2815-C-239-004-E. The financial support is highly appreciated. We also thank to Dr. C. Y. Chiu who kindly allowed us to use his laboratory for measuring heavy metals in Academia Sinica.

References [1] A.P. Davis, M. Shokouhian, S. Ni, Loading estimates of

lead, cadmium, and zinc in urban runoff from specific sources, Chemosphere 44 (2001) 997-1009.

[2] J. German, G. Svensson, Metal content and particle size distribution of stream sediments and street sweeping waste, Water Science and Technology 46 (2002) 191-198.

[3] J. Vaze, F.H.S. Chiew, Nutrient loads associated with different sediment sizes in urban stormwater and surface pollutants, Journal of Environmental Engineering, ASCE 130 (2004) 391-396.

[4] Y. Li, S.L. Lau, M. Kayhanian, M.K. Stenstrom, First flush and natural aggregation of particles in highway runoff, Water Science and Technology 54 (2006) 21-27.

[5] H. Shirasuna, T. Fukushima, K. Matsushige, A. Lmai, N. Ozaki, Runoff and loads of nutrients and heavy metals from an urbanized area, Water Science and Technology 53 (2006) 203-213.

[6] M. Kayhanian, C. Suverkropp, A. Ruby, K. Tsay, Characterization and prediction of highway runoff constituent event mean concentration, Journal of Environmental Management 85 (2007) 279-295.

[7] B. Crabtree, P. Dempsey, I. Johnson, M. Whitehead, The development of an ecological approach to manage the pollution risk from highway runoff, Water Science and Technology 59 (2009) 549-555.

[8] J.J. Sansalone, S.G. Buchberger, Characterization of solid and metal distributions in urban highway stormwater, Water Science and Technology 36 (1997) 155-160.

[9] N.R. Thomson, E.A. Mcbean, W. Snodgrass, I.B. Monstrenko, Highway stormwater runoff quality: development of surrogate parameter relationships, Water, Air, and Soil Pollution 94 (1997) 307-347.

[10] M. Legret, C. Pagotto, Evaluation of pollutant loadings in the runoff waters from a major rural highway, Science of the Total Environment 235 (1999) 143-150.

[11] S.B. Grant, N.R. Pise, P.R. Reeves, M. Matsumoto, A. Wistrom, L. Moussa, S. Bay, M. Kayhanian, A review of the contaminants and toxicity associated with particles in stormwater runoff, Report CTSW-RT-03-059, California Department of Transportation, Sacramento, California, 2003.

[12] W. Muschack, Pollution of street run-off by traffic and local conditions, Science of the Total Environment 93 (1990) 419-431.

[13] N.K. Kobriger, A. Geinopolos, Sources and migration of highway runoff pollutants, Research Report FHWA/ RD-84/059, Department of Transportation, Federal Highway Administration, Washington, D.C., 1984.

[14] H. Furumai, H. Balmer, M. Boller, Dynamic behavior of suspended pollutants and particle size distribution in highway runoff, Water Science and Technology 46 (2002) 413-418.

[15] M. Kayhanian, A. Singh, C. Suverkropp, S. Borroum, Impact of annual average daily traffic on highway runoff pollutant concentrations, Journal of Environmental Engineering, ASCE 129 (2003) 975-990.

[16] L.H. Kim, M. Kayhanian, M.K. Stenstrom, Event mean concentration and loading of litter from highways during storm, Science of the Total Environment 330 (2004) 101-113.

[17] B. Crabtree, F. Moy, W. Whitehead, A. Roe, Monitoring pollutants in highway runoff, Water and Environment Journal 20 (2006) 287-294.

[18] C.S. Eckley, B. Branfireun, Simulated rain events on an urban roadway to understand the dynamics of mercury mobilization in stormwater runoff, Water Research 43 (2009) 3636-3646.

[19] L.H. Kim, S.O. Ko, S. Jeong, J. Yoon, Characteristics of washed-off pollutants and dynamic EMCs in parking lots and bridges during a storm, Science of the Total Environment 376 (2007) 178-184.

[20] D.L. Corwin, P.J. Vaughan, Modeling nonpoint source pollutants in the vadose zone with GIS, Environmental Science and Technology 31 (1997) 2157-2175.

[21] L.B. Irish, M.E. Barrett, J.F.Jr. Malina, R.J. Charbeneau, Use of regression models for analyzing highway storm-water loads, Journal of Environmental Engineering, ASCE 124 (1998) 987-993.

[22] Y. Li, S.L. Lau, M. Kayhanian, M.K. Stenstrom, Particle size distribution in highway runoff, Journal of Environ- mental Engineering, ASCE 131 (2005) 1267-1276.


Brownfield Phytoremediation of Heavy Metals Using Brassica and Salix Supplemented with EDTA: Results of

the First Growing Season

F.E. Pitre, T.I. Teodorescu and M. Labrecque Institut de recherche en biologie végétale, Montreal Botanical Garden, 4101 Sherbrooke East, Montreal, Quebec, Canada, H1X 2B2

Received: June 22, 2010 / Accepted: August 3, 2010 / Published: September 20, 2010. Abstract: A phytoremediation field trial was established on a site contaminated with Cu, Pb and Zn in the City of Montreal (Canada) using Brassica juncea, Salix miyabeana and Salix viminalis. The study compared metal content in plant tissues of each species at the end of the first growing season and assessed the effects of EDTA as a chelating agent to increase availability of metals for the plants. Brassica juncea accumulated more metals (Cu, Pb and Zn) in aerial parts than in roots, whereas the willows accumulated Cu and Pb mainly in roots and Zn in aerial parts (mostly in leaves). EDTA increased metal transfer in Brassica but had no effect on the two willow species. After one growing season, the total biomass yield of Brassica juncea was higher than that of the willows, and consequently, total metal accumulation by the plants was also greater. However, the high yield of willows over several years may make them more successful in brownfield phytoremediation. Key words: Soil, metals, phytoremediation, willows, mustard, bioaccumulation, metals.

1. Introduction

In the province of Quebec (Canada), heavy metals represent the second greatest industrial contaminant, after petroleum products [1]. In many urban areas of the province, industrial activities have polluted thousands of sites which could be decontaminated and reconverted into parks or green spaces. According to the Quebec Ministry of the Environment [2], more than 1,350 contaminated sites have been enumerated in the Montreal region. Only 54% have been restored by traditional methods, which generally involve the excavation, transport and containment of the contaminated soil. The average cost of restoring sites

Corresponding author: M. Labrecque (1957- ), male, M.

Sc., research fields: ecophysiology, phytotechnologies. E-mail: [email protected].

T.I. Teodorescu (1947- ), male, Ing. Ag., M. Sc., research field: agronomy. E-mail: [email protected].

F. Pitre (1978- ), male, Ph.D., research fields: ecophysiology, phytotechnologies and genomics. E-mail: [email protected].

with organic contamination can be more than $1 million (CAD) per hectare, and double in the case of inorganic contamination.

To reduce restoration costs, biological, plant-based soil decontamination technologies are considered to be a good alternative [3-8]. Such phytoremediation technologies are based on the capacity of some plant species to accumulate, translocate, stabilise, concentrate or treat contaminants in their tissues. Compared to traditional methods, phytoremediation is less expensive, can be carried out on large surfaces, causes less environmental disturbances and benefits from greater public acceptance [9, 10]. However, treatment is lengthy (several years), and the methodologies appropriate for each type of contamination-require refinement. Nonetheless, phytoremediation is becoming an increasingly popular alternative, and several studies and pilot projects are underway [11].

Brownfield Phytoremediation of Heavy Metals Using Brassica and Salix Supplemented with EDTA: Results of the First Growing Season

52

Plant selection is an essential element of phytoremediation. A number of “hyper accumulating” species (e.g., Thlaspi caerulescens) have been shown to concentrate large quantities of trace metals in their tissues, although producing low above ground biomasss yield [12]. Brassica juncea (Indian mustard) is often used in phytoremediation because of its capacity to accumulate metals and its high biomass production [13]. However, the management of an annual herbaceous species implies a number of additional costs. The genus Salix includes more than 350 species worldwide [14] and meets a number of criteria essential for plants to be used in phytoremediation [15]: tolerance to metal toxicity, high biomass production and perennial growth habit [16]. The efficiency of willows in short rotation intensive plantation for removing heavy metals from wastewater sludge has been also reported in previous studies by our group [6, 17-20] as well as by a number of others [21-23].

The availability of metals for plants depends on the nature of each metal, soil metal concentration, and also metal solubility in the soil solution, as well as the plant species themselves. For instance, lead solubility is affected by soil pH, i.e., it decreases at pH< 6.0 [24, 25]. The chelating agent EDTA (ethylene dinitrilo tetraacetic acid) was used successfully to increase the availability of metals for a number of plants species [13, 26]. Recently, Zaier et al. [27] showed that treatment of the soil with EDTA increased metal accumulation in Brassica juncea.

The main objective of this study is to compare the accumulation of three metals (Cu, Pb and Zn) by two willow species (Salix viminalis and Salix miyabeana) and one herbaceous species (Brassica juncea) at the end of their first growing season, with and without the addition of the chelating agent EDTA.


2.1 Site Description

The study was carried out on a contaminated site

Table 1 Characteristics of the soil studied in the experiment.

Units Value Sand % 63 Silt % 27 Clay % 10 Texture Sandy Loam Organic matter % 3.7 pH 8.3 P available kg/ha 69.4 K available kg/ha 360 Ca available kg/ha 12024 Mg available kg/ha 449 Cu mg/kg 417 Pg mg/kg 857 Zn mg/kg 899 EC mEq/100 g 27

located south west of the City of Montreal (45°47' N, 73°58' W). Until the end of 1960s, industrial use of the site by a railroad company (Canadian Pacific) strongly impacted soil conditions. The soil is a sandy loam (63% sand, 27% silt and 10% clay) with a high pH (8.3), low organic matter content, low available P and K and very rich in Ca (Table 1). Three metals are over the limits established by the Quebec Ministry of the Environment of Quebec for industrial use: Cu (416.8 mg/kg), Pb (857 mg/kg), and Zn (899.4 mg/kg).

2.2 Pant Material and Experimental Design

The experimental site was ploughed to a depth of 15 to 20 cm in the fall and the following spring the soil was prepared for plantation. One annual (Brassica juncea L.) and two perennial willow shrubs (Salix miyabeana SX67 and Salix viminalis L.) were selected for planting based on their suspected phytoremediation potential. The experimental design was comprised of six blocks (replicates). Each block was divided into 4 plots, further divided into three smaller plots (2 m2) into which one of the three species was randomly allocated. These plots were then split into two equal subplots; EDTA was randomly applied on one subplot (EDTA) but not on the other (Ctl). B. juncea seeds were sown and then thinned to obtain a density of nine plants per m² (i.e. per subplot). Salix sp. cuttings were


53

planted at nine plants per m² (i.e. per subplot). The study area represented a total of about 600 m2.

At the beginning of the growing season and according to agronomic standards, willows were fertilized with 25 g P2O5 and 15.5 g N per plant, while B. juncea received 3.2 g P2O5 and 2 g N per plant. In the treated subplots, a solution of EDTA was applied at a concentration of 1.88 mmol/kg of soil, one week prior to sampling. Throughout the experiment, the site was manually weeded and irrigated as needed.

2.3 Sampling and Analyses

Prior to the experiment, the soil was sampled and characterised (Table 1). Three samples were collected at the 0-20 cm horizon within each plot, then a composite sample was made and sent for analyses. Tissue samples were taken at the end of the first growing season (10 weeks after sowing for Brassica juncea and 22 weeks after planting for S. miyabeana and S. viminalis). To measure metal content in the plant tissues, two plants per subplot (n= 24 samples/species) were harvested randomly within the experiment for each tissue. Roots were thoroughly washed under tap water before drying. The plant samples were dried at 70 ℃ to constant weight. Dried tissue samples were ground up and passed through a 0.375 mm mesh. Chemical analyses of soil were conducted by a commercial laboratory (Agri-Direct, Boucherville Canada) using usual methods as recommended by the Conseil de production végétale du Québec [28]. Briefly, soil texture was determined by granulometric analysis [29]. P, K, Ca, and Mg were extracted by Mehlich-3 digestion and determined using Inductively Coupled Plasma emission (ICP). Dry soil material was digested by HCl and HNO3 and metal contents were determined by ICP spectrometry [30]. Metal contents were calculated, taking into account tissue metal concentration and average biomass production measured for each species. The transfer coefficients were determined for each metal by calculating the ratios between the metal

concentrations in each plant, relative to soil metal content.

2.4 Statistical Analyses

Analyses of variance (three-way ANOVA) were performed to compare growth and metal concentrations and contents, followed by multiple comparisons of means with Tukey’s HSD post hoc test using a significance level of 0.05, using SAS [31].


3.1 Growth

The three species planted on the contaminated site grew well during the first year following their establishment (Table 2). Significant differences in dry biomass were found between species. Total aboveground biomass of Brassica was significantly higher than that of both willow species after one year of growth. However, this was mainly due to the high fruit (seeds) biomass produced by the Indian mustard, which accounted for almost half of its total biomass; willows produced no fruit (Table 2). On the contrary, willows had higher foliar and root biomass while stem biomass was similar to that of Brassica. In all tissues, biomass did not differ significantly between the two Salix species. Application of EDTA had no impact on growth parameters for B. juncea, S. miyabeana or S. viminalis (Table 2).

The willows’ good growth performance and biomass yield at the end of the season do not adequately reflect their potential productivity. Salix sp. require at least three years after planting to develop their root system and reach full biomass production potential.

In this study, the production of above ground biomass was around 4-5 t/ha dry mass for Brassica and only 1-1.5 t/ha dry mass for the willows. Moreover, while production of above ground biomass in Brassica could reach 18 t/ha dry mass per year [32]. Salix miyabeana and S. viminalis can usually achieve 20 t/ha dry mass annually on production cycles of 3-4 years [18-20].


54

Table 2 Mean biomasses (DW) of three species at the end of first growing season.

Organ Brassica juncea

Salix miyabeana

Salix viminalis

Leaves (g-1) 10.7 a 14.1 b 20.2 b Fruits (g-1) 46.2 n. d. n. d. Stems (g-1) 25.2 a 25.4 a 36.1 a Total Biomass (g-1) 82.1 b 39.5 a 56. 2 a Roots (g-1) 5.1 a 14.6 b 16.4 b

Significant difference (p<0.05) between species without EDTA (CTL) are presented with lower case letters.

3.2 Phytoremediation of Metals

The three plant species absorbed copper, lead and zinc from the contaminated soil effectively as shown by the high metals contents in the tissues analysed (Tables 3, 4, 5). Chemical analyses highlighted differences in the capacity of each species to extract and accumulate metals, and the results for each metal are presented and discussed separately.

3.2.1 Copper B. juncea was the most efficient species in

accumulating copper. In the majority of tissues analysed, Cu concentration and content were significantly higher in Brassica than in the willows (Table 3). Application of EDTA significantly increased accumulation of Cu in all above ground parts of Brassica. However, treatment with EDTA had no impact on willows (Table 3). With or without EDTA, the highest concentration of Cu was found in the leaves of B. juncea, followed by those of S. viminalis and S. miyabeana (Table 3). Without EDTA, S. miyabeana accumulated more Cu in stem biomass than the other two species. Higher Cu concentration and content in willows were found in leaves and aerial parts (stems and branches) but concentration and content were significantly higher only in the leaves of S. viminalis. The three species had similar concentrations of Cu in their roots, but absolute content was significantly higher in the Salix species. No visible symptoms of toxicity were observed on any of the three species studied. Similar results were obtained by Kuzovkina et al. [23], who screened five Salix species and observed

no effect on growth and respiration related to Cu and Cd, but reported damage at high levels of treatment (25 µM for 21 days). The high pH of the soil (8.3) in this field experiment possibly decreased the availability of Cu, thus avoiding toxicity [33].

3.2.2 Lead Lead concentration and content were significantly

higher in all tissues of B. juncea than in Salix, irrespective of EDTA application (Table 4). Pb content showed the same pattern as Cu, i.e. most Pb was found in aerial tissues, with generally higher levels in B. juncea. However, the three species accumulated similar quantities in their roots. Zaier et al. [27] also showed that B. juncea has a higher metal transfer capacity when grown with EDTA. The two willow species absorbed comparable quantities of Pb, except for their foliar contents, which were significantly higher in the leaves of S. viminalis (Table 4). Treatment with EDTA significantly increased Pb concentration and contents in leaves, stems and above ground biomass of the species studied, as well as in fruits for B. juncea. Treatment with EDTA did not alter concentration or content of Pb in roots of any of the species.

3.2.3 Zinc The two willow species accumulated zinc most

effectively. For all tissues analysed, Zn concentration and content were significantly higher in S. miyabeana and S. viminalis than in B. juncea (Table 5). In stems of S. viminalis, Zn concentration and content were higher than in stems of B. juncea and S. miyabeana. The greatest values of Zn concentration and content were in above ground biomass of S. viminalis, followed by S. miyabeana and of B. juncea. Application of EDTA did not significantly modify Zn in willow tissues, but increased its content and concentration in B. juncea leaves and fruits (Table 5), which is similar to results reported by Zaier et al. [27]. Zn root concentrations were similar in all three species in untreated soil. However, B. juncea grown in EDTA-treated soil had higher root Zn concentration than willow, while absolute content was not affected. On the contrary, the


55

Table 3 Cu concentrations and content in different tissues of the three species untreated (CTL) or treated with EDTA.

Brassica juncea Salix miyabeana Salix viminalis

CTL EDTA CTL EDTA CTL EDTA

Leaves

Concentration (µg/g) 31.7 c 91.3 C 12.6 a 16.0 A 17. 6 b 19.9 B

Content (µg) 291 ab 876 B* 196 a 199 A 372 b 379 A

Fruits

Concentration (µg/g) 10.5 a 42.2 A n. d. n. d. n. d. n. d.

Content (µg) 462 a 17,701 A n. d. n. d. n. d. n. d.

Stems

Concentration (µg/g) 9.6 a 28.8 B* 13.0 b 13.9 A 9.7 a 9.6 A

Content (µg) 222 a 642 B* 371 a 317 A 366 a 324 A

Total Biomass

Concentration (µg/g) 51.7 b 162.2 B* 25.6 a 29.9 A 27.3 a 29.5 A

Content (µg) 3924 b 11,994 B* 1141 a 1055 AB 1612 a 1555 A

Roots

Concentration (µg/g) 162.8 a 191.9 A 128.6 a 92 A 146.4 a 122.9 A

Content (µg) 1012 a 899 A 2045 b 1359 AB 2476 b 2018 B Significant differences (p<0.05) between species without EDTA (CTL) are presented with lower case letters and treatment with EDTA are presented with upper case letters. Bold lettering denotes a significant effect of EDTA. * indicates a statistically significant interaction between B. juncea and EDTA. Table 4 Pb concentrations and content in different tissues of the three species untreated (CTL) or treated with EDTA.

Brassica juncea Salix myiabeana Salix viminalis


Leaves

Concentration (µg/g) 58.6 b 120.8 B 9.2 a 15.8 A 9.3 a 15.0 A

Content (µg) 519 b 1168 B 143a 175 A 189 a 258A

Fruits

Concentration (µg/g) 5.6 a 29.4 A n. d. n. d. n. d. n. d.

Content (µg) 279 a 1158 A n. d. n. d. n. d. n. d.

Stems

Concentration (µg/g) 9.6 b 28 B 3.0 a 3.4 A 1.7 a 2.5 a

Content (µg) 186 b 51 B 78 a 84 A 50 a 67 A

Total Biomass

Concentration (µg/g) 73.7 b 178.3 B* 12.1 a 19.2 A 10.9 a 17.5 A*

Content (µg) 5345 b 12,689 B 542 a 642 A 608 a 813 A

Roots

Concentration (µg/g) 393.1 b 460.5 B 170.4 a 98.9 A 128.5 a 153.5 A

Content (µg) 2024 a 2165 A 3016 a 1472 A 2168 a 2270 A Significant differences (p<0.05) between species without EDTA (CTL) are presented with lower case letters and treatment with EDTA are presented with upper case letters. Bold lettering denotes a significant effect of EDTA. * indicates a statistically significant interaction between B. juncea, S. viminalis and EDTA.


56

Table 5 Zn concentrations and content in different tissues of the three species untreated (CTL) or treated with EDTA.

Brassica juncea Salix myiabeana Salix viminalis


Leaves Concentration (µg/g) 347.8 a 517.6 A* 1,487 b 1,495 B 1,629 b 1,487 B Content (µg) 3301 a 5,600 A 23,030 b 20,269 B 34,351 b 29,128 B Fruits Concenrtation (µg/g) 128.8 a 209.6 A n. d. n. d. n. d. n. d. Content (µg) 5,503 a 9,094 A n. d. n. d. n. d. n. d. Stems Concentration (µg/g) 211.3 a 270.7 A 208.4 a 184.6 A 333.3 b 336.6 B Content (µg) 4,837 a 6,210 A 5,833 a 4,333 A 12,588 b 11,762 B Total Biomass Concentration (µg/g) 687.9 a 997.8 A 1695 b 1679 B 1962 c 1824 C Content (µg) 51,894 a 78,642 A 73,561 a 62,277 A 115,482 b 98,943 B Roots Concentration (µg/g) 455.8 a 596.1 B 243.1 a 197.8 A 305.3 a 307.1 A Content (µg) 2445 a 2,736 A 3,858 ab 2,822 AB 4,958 b 4,656 B Significant differences (p<0.05) between species without EDTA (CTL) are presented with lower case letters and treatment with EDTA are presented with upper case letters. Bold lettering denotes a significant effect of EDTA. * indicates a statistically significant interaction between B. juncea and EDTA.

two willow species accumulated significantly more Zn than B. juncea. As shown in Table 4, Pb concentrations and content in different tissues of the three species untreated (CTL) or treated with EDTA.

A number of interactions (Tables 3, 4, 5) observed between the species and the application of EDTA suggested that Brassica juncea was more affected by the addition of the chelating agent than the two Salix species. The Salix species were not affected by EDTA, but the application of a similar chelating agent, EDDS, has been shown to be effective in increasing heavy metal uptake by five other Salix species [34].

3.3 Metal Transfer Coefficients

Coefficients of transfer of metals from soil to plant can be used to characterize the capacity of a plant to accumulate metals. It has been reported that coefficients for Cu vary from 0.1 to 1, for Pb from 0.01 to 01, and for Zn from 1 to 10 [35]. Based on our results in Brassica and Salix, we calculated that Cu and Pb were below these limits (0.29 to 0.85 for Pb and 1.27 to 2.52 for Zn) while the transfer coefficients for B.

juncea with regard to Cu and Pb, but lower than S.miyabeana and S. viminalis for Zn. Similar values were reported by Zaier et al. [27] in Brassica napus where the application of EDTA did not significantly improve the transfer coefficient.

Generally, metal distribution in different plant parts varied according to species, type of metal and treatment applied. Analysis of the relative metal concentration in above ground biomass these components (leaves, fruits and stems) highlighted that the three metals are found mainly in the leaves (Tables 3, 4, 5). Of the total metal quantities found in above ground biomass in B. juncea on all plots (CTL or EDTA-treated), its leaves contained 58.5% of Cu, 73.5% of Pb and 51.5% of Zn. Metal concentrations in the leaves of the two willow species were even more significant. Cu, Pb and Zn were concentrated in willow leaves in proportions of 58.5%, 82% and 85.5% respectively, of the total of metals in aerial biomass. This pattern of concentration has been confirmed in several studies [15, 36, 37], which showed that Zn rapidly accumulates in the leaves. The values presented


57

Table 6 Transfer coefficients from soil to plant for the three metals studied in response to treatment with EDTA.

Brassica juncea Salix miyabeana Salix viminalis CTL EDTA CTL EDTA CTL EDTA Cu Total plant concentration (mg/kg) 214.6 354.2 154.2 121.9 173.7 152.4 Transfer coefficient 0.51 0.85 0.37 0.29 0.42 0.37 Pb Total plant concentration (mg/kg) 466. 8 638.8 182.6 118.1 139.4 171.0 Transfer coefficient 0.54 0.74 0.21 0.14 0.16 0.20 Zn Total plant concentration (mg/kg) 1143.8 1593.9 1938.4 1877.2 2267.7 2131.2 Transfer coefficient 1.27 1.77 2.16 2.09 2.52 2.37

here are higher than those reported by Vervaeke et al. [38] who found only moderate metal (Cd, Cu, Pb, Zn) is uptaken by Salix viminalis cv. Orm. These results suggest that Brassica juncea accumulates more Cu and Pb, but Salix miyabeana and Salix viminalis are more adapted to the accumulation of Zn.

Total metal accumulation in the plant and relative accumulation of metals in aboveground biomass and in roots showed that in all cases Brassica juncea accumulated more Cu, Pb and Zn in above ground tissues. On the contrary, willows accumulated more metals in their roots. Generally, treatment with EDTA increased the availability of metals in the soil but did not affect the distribution of metals in the plant (leaves, stems) which is rather specific to each plant, similar results were reported by Dushenkov et al. [39], Vandecasteele et al. [40] and Walter et al. [41].

4. Conclusions

The results of this study present the phytoremediation capabilities of three species at the end of their first season of growth, with and without EDTA. Although Brassica juncea produced more biomass than willow, we hypothesize that long-term productivity of Salix viminalis and Salix miyabeana will be higher than that of Brassica juncea because of willow’s perennial growth and tree-like morphology. These two species of willow are fast growing perennials generally planted at high density (20 000 plants/ha). Studies have shown that above ground willow biomass can be harvested in

a repetitive way (annually or at 2-3 years) over more than twenty years [20]. It was also showed that metal extraction capacities can be maintained even after five years [16]. This suggests there is great potential for long-term metal accumulation in willow biomass. While these three species are effective for the phytoremediation of metal contaminated soil, they are not classified as “hyper accumulating”. The conventional limits for plants to be considered hyper accumulating are 1000 mg/kg for Cu and Pb of 10000 mg/kg for Zn [42, 43]. The metal concentrations accumulated in this experiment are not of this order (Table 6). Nonetheless, the high biomass production of Salix sp. allowed them to accumulate large quantities of metals, suggesting great potential as a phytoremediation tool.

Acknowledgments

This project received financial support from the Fonds des priorités gouvernementales en sciences et technologies (FPGST-E) of the Quebec Ministry of Environment, Inspec-Sol Inc. and the Montréal Centre of Excellence in Brownfields Remediation (MCEBR). The authors would like to express their gratitude to Christine Galipeau and Stéphane Daigle for their help with settings, samplings, analyses and statistics.

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[23] Y.A. Kuzovkina, M. Knee, M.F. Quigley, Cadmium and copper uptake and translocation in five willow (Salix L.) species, Intern. J. of Phytorem. 6 (2004) 269-287.

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[27] H. Zaier, T. Ghnaya, K.B. Rejeb, A. Lakhdar, S. Rejeb, F. Jemal, Effects of EDTA on phytoextraction of heavy metals (Zn, Mn and Pb) from sludge-amended soil with Brassica napus, Biores. Tech. 101 (2010) 3978-3983.

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[30] U.S. Environmental Protection Agency, Method 200.7. Inductively coupled plasma-atomic emission spectrome- tric method for trace element analysis of water and waste, Methods for Chemical Analysis of Water and Wastes, 1983, EPA-600/4-79-020.

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er and zinc in shoot tissues of a range of Salix species, Biomass. Bioenerg. 12 (1997) 115-120.

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[42] M.M. Lasat, N.S. Pence, D.F. Garvin, S.D. Ebbs, L.V. Kochian, Molecular physiology of zinc transport in the Zn hyperaccumulator Thlaspi caerulescens, J. Exp. Botany 51 (2000) 71-79.

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Iron Reduction and Adsorption on Shewanella

Putrefaciens nearby Landfills in Northwest Florida

P.K. Subramaniam1, L. Martin2, P. Grasel2, K. Tawfiq1and G. Chen1

1. Department of Civil and Environmental Engineering, FAMU-FSU College of Engineering, Tallahassee, Florida 32310, USA

2. Florida Department of Environmental Protection, Tallahassee, Florida 32399, USA


Abstract: In Northwest Florida, the soil is mainly covered by poorly drained sandy soil of Myakka, which is characterized by a subsurface accumulation of humus and Al and Fe oxides. When organic rich landfill leachate is leaked to the iron rich soils, ferrous iron is released with the oxidation of organic compounds in the leachate. In this research, we investigated the activities of S. putrefaciens in reducing iron oxide in the iron rich soil of Northwest Florida with landfill leachate serving as the carbon source. S. putrefaciens had similar maximum specific growth rate and half saturation coefficients for all the leachate and soil samples. The average maximum specific growth rate was 0.008 hr-1 and the average half saturation coefficient was 243.8 mg/L. Averagely, 2.2 mg ferrous iron was generated per mg COD consumed. In addition, adsorption of reduced ferrous iron on S. putrefaciens was further characterized. Ferrous iron adsorption on S. putrefaciens was a kinetic process, which increased with the increase of the reaction time. Equilibrium ferrous iron adsorption on S. putrefaciens can be reached after three hours. Ferrous iron had linear adsorption isotherms on S. putrefaciens for the pH range of 5 to 9. Key words: Ferrous iron, S. putrefaciens, reduction, adsorption.

1. Introduction

Groundwater is an important source of drinking water, which can be easily contaminated with iron in Northwest Florida owing to the high iron content in the soil [1]. Although iron is an essential mineral for human health, its presence in groundwater above a certain level makes the water unusable mainly for aesthetic considerations such as discoloration, metallic

Corresponding author: G. Chen (1969- ), male, assistant

professor, research fields: soil contamination remediation, solid waste management, subsurface transport. E-mail: [email protected].

P.K. Subramaniam (1982- ), male, Ph.D. candidate, research fields: soil contamination remediation, solid waste management. E-mail: [email protected].

L. Martin (1947- ), male, research fields: solid waste management, soil contamination remediation. E-mail: [email protected].

P. Grasel (1949- ), male, research fields: hydrogeology, subsurface geology. E-mail: [email protected].

K. Tawfiq (1955- ), male, professor, research fields: soil mechanics, hydrology, constitutive modeling, numerical analysis. E-mail: [email protected].

taste, odor, turbidity, staining of laundry and plumbing fixtures [2]. Nearby landfills of Northwest Florida, landfill leachate is being blamed for elevated levels of iron and arsenic, especially iron observations in the groundwater monitoring wells downgradient of unlined C&D landfills [3]. It is suspected that the geomicrobial iron reduction processes are responsible for the observed iron release in the groundwater nearby these landfills [3].

In Northwest Florida, the soil is mainly covered by a poorly drained sandy soil of Myakka. Myakka is a spodosol, acid soil characterized by a subsurface accumulation of humus and Al and Fe oxides [4-6]. Although Myakka soil series is widely extensive in the State of Florida, it can hardly be seen in any other states. When organic rich landfill leachate is leaked to the iron rich soil, organic compounds in the leachate are oxidized by intrinsic microorganisms to carbon dioxide and water and electrons are freed, which are picked up

Iron Reduction and Adsorption on Shewanella Putrefaciens nearby Landfills in Northwest Florida

61

by the iron oxide. Consequently, iron oxide is reduced to ferrous iron. Once released to the groundwater, iron exists in the form of ferrous iron owing to the low oxygen content in the groundwater. Specifically, elevated levels of iron concentrations have been observed in the percolation of lysimeters amended with high organic matter content at Leon County Landfill [3].

Currently, the bacterial family of Shewanella has been evidenced to be able to conserve energy for growth with the structure Fe(III) bound in smectite clay as the sole electron acceptor [7-9]:

−+ ++=++ OH8Fe4COOH3OFe2OCH 222322 (1)

This is a very important discovery since most of the iron on earth exists in the form of silicate mineral or iron oxide. Besides Shewanella, other organisms that can obtain the energy for growth by oxidizing organic compounds coupled with Fe(III) reduction have also been identified, including Geobacter metallireducens [10, 11] and Desulfuromonas acetoxidans [12]. In addition, it has also been reported that hydrogen and formate oxidation can be coupled to the dissimilatory reduction of Fe(III) or Mn(IV) by Alteromonas putrefaciens [13].

Among the iron-reducing strains, Shewanella is highly versatile in the use of terminal electron acceptors, which include oxygen, fumarate, nitrate, nitrite, trimethylamine N-oxide, dimethyl sulfoxide, sulfite, thiosulfate, and elemental sulfur, as well as solid mineral oxides such as hydrous ferric oxide (including goethite and hematite), manganese oxide, chromium oxide and uranium oxide [14, 15]. It is believed that the dissimilatory reduction of Fe(III) by Shewanella in the iron rich soil is the dominating mechanism for iron release to the groundwater [8, 16, 17]. The ability of Shewanella to utilize iron oxide as the terminal electron acceptor, i.e., dissimilatory iron reduction, has been extensively studied. Most importantly, the genes involved in the dissimilatory iron reduction have been identified, which encode cytosolic membrane proteins as well as periplasmic and outer membrane proteins. These proteins are

responsible for the inferred path of direct electron transfer from the cytoplasm to an insoluble extracellular substrate [18-21]. Since iron reduction happens outside the cells, there is a great chance for the produced ferrous iron to accumulate on the outside cell surfaces [22]. In addition, it is suggested a reactive continuum exists in natural iron oxide assemblages, which determines the Shewanella activity [23]. In this research, we investigated the activities of S. putrefaciens in reducing iron oxide from the iron rich soil of Northwest Floridian with landfill leachate serving as the carbon source as well as adsorption of reduced ferrous iron on S. putrefaciens cell surfaces. Ferrous release was found to increase with carbon consumption and ferrous iron adsorption on S. putrefaciens was found to increase with the increase of the reaction time. In addition, adsorption of ferrous iron on S. putrefaciens was favored with the increase of pH. This research will provide guidelines for landfill leachate management in terms of iron release in the groundwater. Although this research is based on Northwest Florida, results from this study can be applied beyond local and landfill perspective to any iron rich soil.


2.1 Soil Collection and Characterization

The soil used for this research was collected from four landfills located in Northwest Florida, including Franklin County Landfill, Quincy-Byrd Landfill (Gadsden County), Baker Landfill (Okaloosa County), and Santa Rosa Central Landfill (Santa Rosa County). Soil samples were collected 1 to 3 feet below the surface, 100 to 300 feet away from the landfills. The collected soil samples were immediately placed in a Styrofoam cooler and sealed. All the soil samples were delivered to the laboratory immediately and stored under refrigeration at 4 ℃ until usage in the experiments. To assess the soil iron content, soil samples were first partially thawed and placed in an anaerobic chamber with a maintained H2-N2


62

atmosphere. The samples were then ground and the weighed samples were placed in a glass reaction vessel and purged with CO2-scrubbed air, after which the samples were acidified with hot, 5% perchloric acid to dissolve carbonate precipitates such as siderite, calcite, aragonite, and carbonate forms of green-rust. Evolved CO2 gas was carried to the coulometer cell containing a CO2-sensitive ethanolamine solution and quantitatively titrated. The samples were then reacted with 0.25 M hydroxylamine (NH2OH) hydrochloride in 0.25 N HCl and incubated at 60 ℃ for 2 hours for iron extraction [24, 25]. Following the extraction, soil iron content was determined using spectrophotometric analysis techniques by reacting Fe(III) with the thiocyanate ion to form a highly colored complex:

(aq)][Fe(SCN)(aq)6SCN(aq)Fe 36

3 −−+ =+ (2) Because the thiocyanate complex is colored red, it

absorbs at 447 nm on the absorption spectrum. For this research, extracted iron was reacted with 1.5 M KSCN and the Fe(III) concentration was measured using a spectrophotometer at the wavelength of 447 nm (Shimadzu UV-1650 PC).

2.2 S. Putrefaciens Cultivation and Identification

S. putrefaciens was cultured using the sampled soil as the innocula under anaerobic conditions in an anaerobic chamber. 250 mL Teflon-sealed serum bottles equipped with CO2 entrapping devices were used for the culturing. The serum bottles contained 100 mL mineral salts media that had a composition of KH2PO4, 160 mg/L; K2HPO4, 420 mg/L; Na2HPO4, 50 mg/L; NH4Cl, 40 mg/L; MgSO4⋅7H2O, 50 mg/L; CaCl2, 50mg/L; FeCl3⋅6H2O, 0.5 mg/L; MnSO4⋅4H2O, 0.05 mg/L; H3BO3, 0.1 mg/L; ZnSO4⋅7H2O, 0.05 mg/L; and (NH4)6Mo7O24, 0.03 mg/L. Glucose at a concentration of 0.2 g/L and Fe2(SO4)3⋅7H2O at a concentration of 500 mg/L were added to serve as the carbon source and electron acceptor to stimulate S. putrefaciens growth. Resazurin (1 mg/L) was added as a redox indicator to indicate contamination by molecular oxygen and cysteine (3.0 g/L) was added to reduce the trace amount of oxygen remaining in the media after

autoclaving. The media pH was adjusted to 7.0 with 0.1 M NaOH. The headspace of the serum bottles was pressurized with ultra-pure nitrogen and the serum bottles were capped with butyl rubber septa and crimped with an aluminum seal. The inoculated serum bottles were put into a rotary-shaker (150 rpm at 35 ℃) in the dark for at least 1 week until the formation of black precipitate at the bottom and on the wall of the serum bottles was observed. Then 10 mL enriched culture was transferred into 100 mL fresh culture media amended with 0.2 g/L glucose and 500 mg/L Fe2(SO4)3⋅7H2O for the second phase culture enrichment. After the fourth phase enrichment was completed, bacterial cells were harvested by centrifugation (6000 g, 15 min) and washed twice with a fresh electrolyte solution under an extra-pure nitrogen atmosphere. The electrolyte solution was prepared using analytical reagent-grade NaCl and nano-pure de-ionized water (NPDI, Barnstead, Dubuque, IA) at a concentration of 10-5 M and adjusted to pH 7. The concentrated cells were then re-suspended in a serum bottle containing fresh, electrolyte solution (10-5 M NaCl) to give a final concentration of approximately 5×109 cells/mL.

S. putrefaciens was identified based on polymerase chain reaction (PCR) analysis. Upon verification of the PCR reaction by viewing the gel bands, the PCR samples were purified using a QIAGEN QIAquick- spin PCR purification kit. After the purification, the samples were amplified and the resulted sequences were compared with the database of the National Center for Biotechnology Information (NCBI) based on the strands that have been previously identified as S. putrefaciens. The strains whose DNA codes matched the codes of S. putrefaciens were selected and enriched for further experiments.

2.3 Iron Reduction Experiments

Laboratory iron reduction experiments were conducted using 100 g collected soil samples reacting with landfill leachate collected from corresponding landfills in the presence of S. putrefaciens (5 mL stock


63

solution at a concentration of 5 × 109 cells/mL). To mimic the real scenarios of iron reduction in the subsurface soil, the landfill leachate was diluted to COD around 50 mg/L. All of the experiments were performed in 250 mL Teflon-sealed serum bottles equipped with CO2 entrapping devices. The headspace of the serum bottles was pressurized with ultra-pure nitrogen. As a control, sampled soil was reacted with corresponding leachate in the absence of S. putrefaciens. Throughout the course of the experiments, chemical oxygen demand (COD) and ferrous iron concentrations were monitored by analyzing the extracted samples using a syringe. To investigate the effect of pH on iron reduction and release, above experiments were repeated under controlled pH conditions. For this part of research, the initial pH of the solution was adjusted to pH of 5, 6, 7, 8 and 9 using 1 M HCl or 1 M NaOH. During the experiments, pH was monitored by a pH probe mounted through the butyl rubber septa and was adjusted to maintain the desired value by adding 1 M HCl or NaOH using a syringe. COD measurements followed the standard method using a Hach DR5000 Spectrophotometer. For ferrous iron quantification, 1,10-Phenanthroline Method was utilized. In the presence of 1,10-phenanthroline (C12H8N2⋅H2O), ferrous iron formed a stable, orange-colored complex with the reagent:

++++ +=+ 3H]Fe(ph)3(ph)H(aq)Fe 23

2 (3) For this experiment, 0.0125 M 1,10-phenanthroline

was used and ferrous iron concentrations were quantified using the spectrophotometer (Shimadzu UV-1650 PC) at a wavelength of 520 nm.

2.4 Iron Adsorption Experiments

Ferrous iron adsorption on S. putrefaciens was carried out in autoclaved (121 ℃ and 1 atm for 20 min) high-density polyethylene centrifuge tubes in an anaerobic chamber in a nitrogen environment. S. putrefaciens was first harvested by centrifugation at 6000 g for 15 min after growth in the minimal salts media. The cell pellets were then washed and

re-suspended in the electrolyte solution to make a bacterial solution. The mass of the bacterial cells was quantified using ATP assay [26]. To investigate the kinetic adsorption of ferrous iron on S. putrefaciens, a series of centrifuge tubes containing ferrous iron chloride at concentrations of 0.25, 2.0, 3.5, 10.0, 15.0, and 30.0 mg/L as Fe2+ and 0.1 g S. putrefaciens (including blank controls) (sealed with Teflon-lined screw caps and pressurized with ultra-pure nitrogen) were agitated on a Wrist Action Shaker (Burrel Scientic, Model 75) for up to 24 hrs. The suspensions were then centrifuged at 6000 g for 15 min, after which ferrous iron concentrations in the supernatant were measured. The amount of ferrous iron adsorbed on S. putrefaciens was obtained using the following equation:

MV)CC(

q ei ⋅−= (4)

Where, q is the amount of ferrous iron adsorbed onto S. putrefaciens (mg/g), Ci and Ce are the initial and equilibrium ferrous iron concentrations in the solution (mg/L), V is the volume of the aqueous phase (L), and M is the mass of S. putrefaciens (g).

To investigate the effect of pH on adsorption of ferrous iron on S. putrefaciens, a series of centrifuge tubes containing ferrous iron chloride at concentrations of 0.25, 2.0, 3.5, 10.0, 15.0, and 30.0 mg/L as Fe2+ and 0.1 g S. putrefaciens (including blank controls), adjusted with 1 M HCl or 1 M NaOH to pH of 5, 6, 7, 8 and 9 (sealed with Teflon-lined screw caps and pressurized with ultra-pure nitrogen) were agitated on the Wrist Action Shaker until equilibrium was reached, which was determined based on the results of above kinetic adsorption experiments. The suspensions were then centrifuged and quantified for ferrous iron adsorption.


3.1 Soil Characterization and S. Putrefaciens Identification

The soil samples were characterized based on sieve analysis and were identified as loamy or fine sand.


64

Based on sieve analysis, all the soil samples exhibited a poor grading, i.e., the soil particles were in general similar in size range. The finest particles were screened out by sieve 200 (~ 75μm). Santa Rosa County samples had the highest percentage fines of 6.01%. Gadsden County samples were determined to have the lowest percentage fines of 0.53%. Franklin County and Okaloosa County samples had medium values of 1.31% and 4.12% respective. The soil iron content for all the samples ranged from 39.4 mg/g (Franklin County) to 119.9 mg/g (Okaloosa County). The average iron content was 77.1 mg/g. It should be noted that only reducible iron contributes to the quantified iron content. There was a general trend that the soil iron content increased with the increase of percentage of finer particles. This is due to the increase in surface area available for iron accumulation.

In the iron rich soil, S. putrefaciens played an important role in the cycling of carbon, trace metals, and nutrients. S. putrefaciens has the potential to oxidize complex sedimentary organic matter to carbon dioxide with Fe(III) serving as the sole electron acceptor. In northwest Florida, owing to the high iron content in the soil, Fe(III) would serve as the dominating electron acceptor. In this research, S. putrefaciens was identified by means of PCR analysis from the culture cultivated from the soil samples. PCR analyses indicated that the excised Fe(III)-reducing band contained a single polypeptide with an apparent molecular mass of 91 kDa. The 91-kDa heme-containing protein identified the strain as S. putrefaciens.

3.2 Iron Reduction Experiment Modeling

Landfill leachate collected from Okaloosa County had the highest COD value (2400 mg/L), followed by Santa Rosa County (1500 mg/L), Gadsden County (1000 mg/L) and Franklin County (450 mg/L). For this research, the collected landfill leachate was diluted to around 50 mg/L. With the proceeding of the experiments, COD values decreased for all the landfill

leachate investigated (Fig. 1). After 20 days’ reaction, 50% to 60% of the organic content of landfill leachate was decomposed. With the decomposition of leachate, ferrous iron release was observed, which linearly increased with the decomposition of the leachate (Fig. 2). The average ferrous iron production was 2.2 mg per mg COD consumed. Okaloosa County had the most ferrous iron production, followed by Santa Rosa County, Gadsden County and Franklin County. If S. putrefaciens growth is coupled with organic substrate depletion, Monod-type kinetics can be assumed to describe S. putrefaciens growth [27]:

SKSX

Y1

dtdS

s

m

+μ

−= (5)

SKbX

SKSX

dtdX

ss

m

+−

+μ

= (6)

Where S is the organic substrate concentration, which is usually expressed in terms of COD (mg/L); μm

Time (day)

0 5 10 15 20

CO

D (m

g/L)

0

10

20

30

40

50

60

Okaloosa CountySanta Rosa CountyQuincy CountyFranklin County

Fig. 1 Landfill leachate organic compound decomposition.

COD Consumption (mg/l)

0 5 10 15 20 25

Fe2+

(mg/

l)

0

10

20

30

40

50

60

Okaloosa CountySanta Rosa CountyGadsden CountyFranklin County

Fig. 2 Fe2+ release as a function of landfill leachate COD consumption.


65

is the maximum specific growth rate (hr-1); X is the S. putrefaciens concentration (g/L); t is the elapsed time (hr); Y is the growth yield coefficient (g biomass per g substrate); Ks is the half-saturation coefficient (g/L); and b is the S. putrefaciens decay coefficient (hr-1). By ignoring the decay rate coefficient, Y can be used to estimate the S. putrefaciens production based on organic substrate depletion, such that:

SXY

ΔΔ

−= (7)

)SS(YXX 00 −+= (8) By substituting Eq. (8) into Eq. (5), substrate

depletion can be expressed as:

SK

)]SS(YX[SY1

dtdS

s

00m

+−+μ

−= (9)

Organic substrate depletion by S. putrefaciens with the soil structure Fe(III) serving as the electron acceptor was simulated by means of non-linear regression of simplex optimization of least squares against Eq. (9). S. putrefaciens had similar maximum half saturation coefficient values for all the soil samples and the average half saturation coefficient was 243.8 mg/L (284.9 mg/L for Okaloosa, 216.5 mg/L for Santa Rosa, 234.9 mg/L for Quincy and 238.8 mg/L for Franklin). The similar half saturation coefficient values indicated that S. putrefaciens had similar affinity to the organic components. Similarly, specific growth rate and growth yield coefficient values were also in a similar range. The average maximum specific growth rate was 0.008 hr-1 (0.0105 hr-1 for Okaloosa, 0.0078 hr-1 for Santa Rosa, 0.0074 hr-1 for Quincy and 0.0068 hr-1 for Franklin) and the average yield coefficient was 0.173 mg/g (0.141 mg/mg for Okaloosa, 0.116 mg/mg for Santa Rosa, 0.178 mg/mg for Quincy and 0.252 mg/mg for Franklin). Based on the soil analysis, the iron content was 119.9 mg/g, 83.2 mg/g, 68.8 mg/g and 39.4 mg/g respectively for Okaloosa County soil, Santa Rosa County soil, Gadsden County soil and Franklin soil. Thus, the iron content was not the limiting factor during iron reduction. The variation in maximum specific growth rate among different landfill leachate and soil samples was attributed to variable concentrations of easily degradable organic

compounds of the leachate. Okaloosa landfill leachate had the highest COD value and consequently most easily degradable organic compound content, thus S. putrefaciens had the greatest maximum specific growth rate among these samples.

3.3 Ferrous Iron Adsorption

Metal-reducing bacteria which use solid substrates such as Fe(III) as the terminal electron acceptor for anaerobic respiration must be able to transport the electrons across the outer membrane between large particulate metal oxides (e.g., Fe2O3) and the electron transport chain in the cytoplasmic membrane [28]. As confirmed by bioelectrochemical method, S. putrefaciens had approximately 80% of the membrane-bound cytochromes localized in its outer membrane when grown under anaerobic conditions [29, 30]. This cytochrome distribution plays a key role in the ability to mediate Fe(III) reduction during anaerobic respiration [31]. With the production of ferrous iron, ferrous iron may accumulate on the outside cell surfaces [32]. The accumulation of ferrous iron on S. putrefaciens surfaces interferes the electron transport across the outer membrane between large particulate metal oxides (e.g., Fe2O3) and the electron transport chain in the cytoplasmic membrane. This is evidenced that with more ferrous iron adsorbed on the bacterial surface, the activities of S. putrefaciens decreased accordingly after 10 days.

Time (min)

0 50 100 150 200 250

Sor

bed

Fe2+

(mg/

g)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0.25 mg/l2.0 mg/l3.5 mg/l10.0 mg/l15.0 mg/l30.0 mg/l

Fig. 3 Ferrous iron kinetic adsorption on S. putrefaciens.


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Fig. 4 Ferrous iron release as a function of pH.

Results of ferrous iron kinetic adsorption at concentrations of 0.25, 2.0, 3.5, 10.0, 15.0, and 30.0 mg/L were presented in Fig. 3. Ferrous iron adsorption on S. putrefaciens increased with the increase of the reaction time and more ferrous irons were adsorbed for higher initial solution ferrous iron values. Based on the kinetic investigation, it was found that ferrous iron adsorption reached the maximum value and became stable after 200 minutes. The results demonstrated that equilibrium was reached after three hours’ of adsorption reaction for most cases.

Effect of pH on ferrous iron release and equilibrium adsorption on S. putrefaciens was further investigated. It was demonstrated that pH had an obvious effect of iron reduction and release (Fig. 4). For all the soil samples, a low pH favored iron reduction and release. This is because that according to Eq. (1), iron reduction

consumes alkalinity in the solution. Again, Okaloosa County had the most ferrous iron production, followed by Santa Rosa County, Gadsden County and Franklin County. Based on the speciation analysis, ferrous iron does not precipitate in the pH range of 5 to 9 under anaerobic conditions (Fig. 5). Therefore, the effect of precipitation on ferrous iron adsorption on S. putrefaciens was minimal. Ferrous iron had linear isotherms on S. putrefaciens under the pH range investigated for this research (Fig. 6). It was found that high pH favored ferrous iron adsorption on S. putrefaciens. From isotherm experiments, the average partition coefficient was found to be 0.035 L/g, 0.039 L/g, 0.050 L/g, 0.059 L/g and 0.073 L/g for pH of 5.0, 6.0, 7.0, 8.0 and 9.0 respectively. Ferrous iron competes with H+ for adsorption on S. putrefaciens. With the increase of pH, less H+ is available competing


67

Fig. 5 Ferrous iron speciation as a function of pH.

Fe2+ (mg/l)

0 5 10 15 20 25 30

Sor

bed

Fe2+

(mg/

g)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

pH = 5.0pH = 6.0pH = 7.0 pH = 8.0pH = 9.0

Fig. 6 Ferrous iron adsorption on S. putrefaciens as a function of pH.

with ferrous iron, thus more ferrous iron is able to adsorb on S. putrefaciens. It should be noted that above observation was possible only under the condition that effect of ferrous iron precipitation can be ignored.

The driving force of ferrous iron adsorption on S. putrefaciens was the attractive electrostatic interactions. The ζ potential of S. putrefaciens was found to be -24.2 ± 0.4 mV as estimated by means of electrophoretic mobility measurements based on dynamic light scattering (Zetasizer 3000HAS, Malvern Instruments Ltd., Malvern, UK). During the ζ potential measurements, S. putrefaciens was suspended in the sterilized electrolyte solution (10-5 M NaCl) at a concentration of 5×109 cells/mL. The negative ζ potential indicated that S. putrefaciens was negatively charged, which supported the attractive electrostatic

interactions with positively charged ferrous iron. The chemical structure of S. putrefaciens was further analyzed using infrared spectroscopy to gain insight into the surface properties of S. putrefaciens. The surfaces of S. putrefaciens were found to be dominated by functional groups of carboxylic acids (RCOO-) (1600 cm-1) (32.6%) and carbonyl groups (CH3CO-) (1320 cm-1) (47.8%), which were responsible for the negative charges.

4. Conclusions

Laboratory iron reduction experiments were conducted using soil samples reacting with landfill leachate collected from corresponding landfills in the presence of S. putrefaciens. After 20 days’ reaction, 50% to 60% of the organic content of landfill leachate was decomposed. With the decomposition of leachate, ferrous iron release was observed, which linearly increased with the decomposition of the leachate. Organic substrate depletion by S. putrefaciens with the soil structure Fe(III) serving as the electron acceptor was simulated with Monod Equation by means of non-linear regression of simplex optimization of least squares against equation. S. putrefaciens had similar maximum half saturation coefficient values for all the soil samples and the average half saturation coefficient was 243.8 mg/L. Similarly, specific growth rate and growth yield coefficient values were also in a similar range. Ferrous iron adsorption on S. putrefaciens was further investigated in an anaerobic chamber in a nitrogen environment. Ferrous iron adsorption on S. putrefaciens increased with the increase of the reaction time and more ferrous irons were adsorbed for higher initial solution ferrous iron values. Based on the kinetic investigation, it was found that ferrous iron adsorption reached the maximum value and became stable after 200 minutes. The results demonstrated that equilibrium was reached after three hours’ of adsorption reaction for most cases. Effect of pH on ferrous iron release and equilibrium adsorption on S. putrefaciens was further inssvestigated. It was demonstrated that pH had an


68

obvious effect of iron reduction and release. For all the soil samples, a low pH favored iron reduction and release and a high pH favored ferrous iron adsorption on S. putrefaciens.

Acknowledgements

The work was supported by Hinkley Center for Solid and Hazardous Waste Management through Grant No. UF-EIES-0632020-FSU to Florida State University.

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[8] J.E. Kostka, D.D. Dalton, H. Skelton, S. Dollhopf, J.W. Stucki, Growth of iron(III)-reducing bacteria on clay minerals as the sole electron acceptor and comparison of growth yields on a variety of oxidized iron forms, Appl. Environ. Microbiol. 68 (2002) 6256-6262.

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[14] H.H. Hau, A. Gilbert, D. Coursolle, J.A. Gralnick, Mechanism and consequences of anaerobic respiration of cobalt by Shewanella oneidensis strain MR-1, Appl. Environ. Microbiol. 74 (2008) 6880-6886.

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Temporal Changes on Pollutants Associated with Sewage Sludge

S.M. Al-Muzaini and T.E. Al-Obied

Environment Sciences Department, Kuwait Institute for Scientific Research, Safat 13100, Kuwait

Received: May 18, 2010 / Accepted: July 8, 2010 / Published: September 20, 2010.

Abstract: A field survey was carried out to collect monthly samples from sewage sludge beds. The samples were collected from three sewage treatment plants namely; Jahra, Rekka, and Um Al-Hayman; over 12 months’ period started from January and ended by December 2002, 2004 and 2006 to assess the temporal changes on the pollutants associated with sewage sludge. The collected samples were analyzed for organic matters, nutrients and heavy metals. It was observed that the quantities of organic matter, organic carbon and nutrients were varied in a wide range of values. The levels of heavy metals were generally below than reported by the Kuwait Environment Public Authority Limits for application of dry sludge. Temporal changes in the levels of heavy metals and other pollutants may be affected by temporal variation in the level of heavy metals, nutrients and organic matters in the influent of wastewater or in the efficiency of the treatment involved. Key words: Heavy metals, treatment plant, municipal treatment, contamination, Kuwait.

1. Introduction

Over 4000 m3/d of sewage sludge (5% dry matter) is generated daily in Kuwait [1]. The Kuwait Ministry of Public works estimates that the volume of sewage sludge will exceed current production after expansion in sewage treatment plants. At present, sewage sludge produced in sewage treatment plants is thickened and dried by drying beds before land disposal. Though more than 85% of wastewater of the sewage treatment plant in Kuwait is received from domestic use, industrial wastes contribute a substantial amount of heavy metals and organic matters to sewage sludge. About 15% of the sewage treatment plants influent wastewater comes from industrial sources, mainly light industries [2]. Several studies suggested that the reuse of sewage sludge on land can have major economic

Corresponding author: S.M. Al-Muzaini (1983- ), male, professor, research fields: sanitary and environmental engineering. E-mail: [email protected] or [email protected].

T.E. Al-Obeid (1993- ), male, professional researcher, research field: control technology of wastewater. E-mail: [email protected].

advantages compared with other available disposal routes like disposal to landfill sites [3]. The application of sewage sludge to agricultural land or its use for land reclamation is an attractive disposal method [4], since sewage sludge is a beneficial source of organic material and could improve soil quality [5, 6]. The application of sewage sludge to land may help to slow down the decline in organic matter in soils leading to improvement in water holding capacity, porosity and aggregate stability. The main value of sewage sludge as a fertilizer lies in its nitrogen and phosphorous contents. In fact, applying sewage sludge to soil will release nitrogen to plant over a period of several years and yet will retain it against leaching. Considerable amount of research has been conducted on the sewage sludge from wastewater treatment plants. It showed that the produced sewage sludge is an excellent soil amendment and chemical fertilizer substitute in addition to that it is environmental and economically desirable means. However, the presence of heavy metals and organic matters in sewage sludge can restrict its agriculture use, or land application.


71

2. Contamination of Sewage Sludge

Kind of heavy metals in sewage sludge depend on the type and degree of industrialization [7]. Heavy metals levels are increasingly becoming an important factor in considering sludge treatment, disposal and reuse, [8, 9]. Application of sewage sludge to land can increase metal concentration and other toxic contents, which may accumulate in soil and contaminate crops, groundwater, and food chains. This raises a concern that contamination of heavy metals and other pollutants outweigh benefits in land [9]. This is indeed a problem which must always be addressed when sewage sludge is applied to land [10]. Of these metals that may double their contents in soil are Hg, Ag, and Cu in short time [11-13]. Papadopoulos [14] reported that Cu, Ni and Zn are phototoxic at high concentration. Therefore, there is a health risk that heavy metals contents in sewage sludge may accumulate in soil due to excess use of dry sewage sludge [15].

High concentration of heavy metals in soil may increase and impair the plants growth. These heavy metals could have detrimental effects on the human health when he consumes crops which contain high concentration of heavy metals [16]. Spanjers [17] pointed out that no matter how the sewage sludge is disposed; the contaminated sewage sludge can lead to the inputs and spreading of pollutants in the environment. Therefore, the quality of sewage sludge itself, particularly with respect to heavy metals concentration will limit final disposal options, [9]. An experimental study was done by Abdullah [18] showed that, the sewage sludge produced in Kuwait is rich in heavy metals. They indicated that the concentration of heavy metals depend on the contribution of industrial wastewater to the sewage plants. In another study was conducted by Al-Muzaini [1] reported that toxicity of heavy metals in the sewage sludges were found fluctuating between high and low level demanding exhaustive study to be conducted covering all sewage treatment plants in Kuwait, considering time changing and plants operation. Samhan and Ghobrial [19]

suggested that a comprehensive study should be conducted to have a better understanding regarding heavy metals in sewage sludge and it should take temporal changes into consideration. Al-Enezi et al. [20] showed that heavy metal such as Cd, Cr, Cu, Hg, Ni, Pb, and Zn were present in Kuwaiti sewage sludge for samples collected from Ardyia sewage treatment plant. The study recommended that extensive researches should be conducted on the dried sewage sludge in the wastewater treatment plants in Kuwait to know more about heavy metals and their toxic constituents. Regional Organization for Protection of Marine Environment ROPME [21] reported that, in Kuwait sewage sludge contained a substance amount of organic matters and heavy metals. Adoption of innovative options will lead to less sewage sludge volume but of high quality [22]. Knowing sludge properties is very important [23]. Christen [24] argued that the sewage treatment plants should develop more advance methods to treat sewage sludge in order to produce a sludge that does not contain harmful materials as heavy metals, at the same time, the produced sewage sludge could be used as a soil amendment. In fact, more research programs were implemented to evaluate a range of innovative treatment technologies to identify the best technology to produce good sludge quality. Spicer [25, 26] stressed that sludge can provide organic matters and improve water retention and soil productivity over the long term. However, Kuchenritherm et al. [27] pointed out that an environmental management system can help sludge programs build success. The better new physical/chemical and biological processes can reduce sewage sludge of heavy metals, and organic matters [28, 29]. Rosenblum et al. [30] stated that sewage sludge management program helped to improve sewage sludge quality for effective usage [27, 31]. Dessoff [32] and Bastian et al. [33] reviewed several options to deal with sewage sludge application. However, the selection of any option depends on sewage sludge characteristics. It was observed that


72

heavy metals in sewage sludge cause problems and have been indentified such as Cd [11], Cu, and Zn [34]. Therefore, metals should be studied in more detail knowledge to show if the level vary through year after year due to the temporal changes. For Kuwait it is important to know the level of heavy metals in sewage sludge. Limited information published does not allow for a detailed consideration of temporal changes in heavy metals, organic matters and nutrients of sewage sludge produced in Kuwait. This study was undertaken to determine the level of heavy metals, nutrients and organic matters in the sewage sludge produced at three sewage treatment plants including: Jahra, Rekka and Um Al-Hayman. The change in concentration of heavy metals, nutrients and organic matters due to temporal changes are presented and likely to cause environmental health problems.


3.1 Site Investigations

The investigation was performed at the three sewage treatment plants (Jahra, Rekka and Um Al-Hayman). Fig 1. shows the locations of sewage treatment plants with respect to the city of Kuwait. The Jahra sewage treatment plant was built in 1982 to serve the western, eastern and northern cities of Kuwait. The Jahra treatment plant was designed to treat 70,000 m3/d of sewage. The treatment process consists of screening grit removal, extended aeration, secondary setting, chlorination, filtration and final chlorination. Sludge from primary, secondary aeration, and clarifier’s tanks are partially pumped to aeration tanks to help reactivate the bacteria in aeration tanks. The rest of the sludge is pumped and thickened before being dried on open sludge sand beds [2]. The Rekka sewage treatment plant

Fig. 1 Location of sewage treatment plants.


73

was put into use in 1982. It collects the sewage wastewater from coastal cities. The plant was commissioned in 1982 and presently handles 120,000 m3/d of sewage. Modifications were made on the designed capacity to increase treatment to 180,000 m3/d. The treatment processes at the Rekka plant consists of screening, grit chambers, extended aeration tanks, secondary clarifiers and chlorination. Part of the sludge from primary, secondary, and clarifier’s tanks is pumped directly to the aeration tanks to help in the oxidation processes. The rest of sludge is transferred to thickener tanks and then to the sludge dry sand beds [2]. The Um Al-Hayman sewage treatment plant is designed as a tertiary treatment plant. It receives sewage wastewater from the south cities of Kuwait City. The physical and chemical processes produce the final reclaimed water by filtration and disinfections. The design and construction of the plant took place in the late nineties. The Um Al-Hayman plant was started by early 2001 with a design capacity of 10,000 m3/d. The plant receives about 6,000 m3/d of sewage. A portion of sludge produced by primary setting, oxidation ditches and secondary clarifiers is sent to the oxidation ditches to reactive the biomass and to increase the growth of bacteria. The rest of the sludge is conveyed to thickeners. Thickened sludge is pumped to the sludge drying beds.

3.2 Samples Collection Procedures

The sampling locations were selected to cover the entire sludge drying beds. The selected beds were divided into quarters. One grab samples from the center of each quarter was collected. Then, the samples were combined to form a pooled grab sample of the total bed area. All sampling equipments were made of polyethylene and used once and discarded. The bed selection was based on information collected from the sewage treatment plant managers. The samples were collected, packed and shipped to the laboratories for analysis. One sample from each sewage treatment plant was collected per month, for twelve months to account

for variable environmental operational and climatic conditions. The analysis of sewage sludge was done according to the Standard Methods [35].

3.3 Analysis of Sewage Sludge

Total organic carbon (TOC), total organic material (TOM), and total volatile materials (TVM) were determined by TOC-5000 analyzer, shimadzu, Japan. Nitrate, phosphorous, and potassium were measured using spectrophotometer, analyzer made by Hach, USA. Metals concentrations were determined by atomic absorption spectrophotometer, AS (Varian, USA). Unpreserved samples were used for the analysis employing DR-50000 analyzer and Hatch instrument. However, the digested samples were used for the analysis of heavy metals. The digestion procedure was followed by putting 50 mL of a sample in a digestion tube, 10 mL of HNO3 (69%) was added, and then sample was heated for one hour at 70 ℃ in digestion hood. The sample was cool to room temperature before filtration. After filtration, the sample was collected for determined of heavy metal concentrations. This analysis yields the contents of heavy metal elements in the solution [35]. Eleven toxic inorganic metals, cadium (Cd), chromium (Cr), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), molybdenum (Mo), nickel (Ni), lead (Pb), vanadium (V) and zinc (Zn) are chosen for the present study. These metals have reported hazardous to the public health [36].


4.1 Organic Matters and Nutrients

Sludge samples collected from Jahra, Rekka, and Um Al-Hayman sewage treatment plants 2002, 2004, and 2006 were analyzed for organic matters and nutrients. The results of the organic matters and nutrients presented in Table 1. The quantities varied in a wide range of values. The level of organic matters ranged for TOC (2-20%), TOM (38-60%), and TVM (28-58%). From Table 1, the values were varied in a


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Table 1 Levels of sewage sludge from three sewage treatment plants organic matter and nutrient.

Sewage treatment plants

Jahra plant Rekka plant Um Al-Hayman plant Parameter 2002 2004 2006 2002 2004 2006 2002 2004 2006 Organic matter TOC (mg/L) 3 20 19 2 17 15 12 18 18 TOM (%) 46 56 55 42 57 55 38 60 57 TVM (%) 48 50 28 49 52 28 53 58 24 Nutrient Potassium (mg/L) 25 16 54 31 14 55 30 21 48 Phosphorous (mg/L) 3 6 5 4 5 2 4 5 5 Nitrogen (mg/L) 0.04 0.06 0.05 0.05 0.06 0.05 0.04 0.05 0.04

TOC: Total organic carbon. TOM: Total organic matter. TVM: Total volatile matte

wide range of between the three sewage treatment plants for the years 2002, 2004, and 2006. There was marked variations in the TOC values from sewage plant to another sewage plant. The lowest TOC value was recorded at Um Al-Hayman sewage treatment plant for year 2002. However, Jahra Sewage plant recorded the highest value of TOC in year 2004 and 2006. In turn, the lowest amount of organic carbon among the investigated sludge (2%) accompanied high values of TOM and TVM, at 38% and 53% respectively. In contrast, increase in the concentrations of TOC accompanied increase in TOM and TVM values for the years 2002 and 2006 as reported [37]. The highest TVM content of 58% was found in sludge of Umm Al-Hayman sewage plant year 2004. The variation in the values of organic matters were due to the type and the source of sewage wastewater coming to the plants [38]. Analysis for TOM and TVM content in sewage sludge revealed that all tests organic matters were several times higher than the values of TOC. This is due to their natural diversified of chemical compositions and among other things by the degree of urbanization and industrialization of given area [37]. Wilson et al. [39] claimed that VOM have been detected in sewage sludge by a number of researchers. Their present may cause risk to human and to the environment. Among the numerous elements present in sewage sludge, nutrients are undoubtedly the most

important to provide nutrient matters. The potassium (K) values ranged from 14 to 55 mg/L, for phosphorous (P) values ranged from 2 to 6 mg/L, but for nitrogen (N) ranged from 0.04 to 0.06 mg/L. The data in Table 1 shows there were no marked variation in the concentration of K, P, and N between sewage plants. However, the decrease in the most cases the availability of N contents of the digested sewage sludge is relatively low, but the effect on soil will exist for considerable period of time due to the slow rate. Also, the difference in the values of K, P and N of sewage sludge were depended entirely upon its sources and processes of sewage treatment plants. This indicates that concentrations of sewage sludge contents is changing with time. In fact, the year 2004 has recorded the highest concentrations of both organic and nutrients.

4.2 Heavy Metals

The values of heavy metals namely, Cd, Cr, Co, Cu, Fe, Pb, Mn, Mo, Ni, V and Zn are given in Table 2. Among the general concern of heavy metals in the sewage sludge getting into the human food chain are Cd, Cu, Cr, Ni, Zn and Pb, while Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were selected for their toxicity to terrestrial plants [11]. But Cd was selected for its tendency to accumulate in the edible parts of terrestrial plants [40]. While Cd, Cu, Pb and Zn were selected for


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Table 2 Levels of heavy metals in sewage sludge from the three sewage treatment plants.

Jahra Plant Rekka Plant Um AL-Hayman Plant Heavy Metals 2002 2004 2006 2002 2004 2006 2002 2004 2006 Cd 0.1 0.1 0.12 0.1 0.1 0.53 0.01 0.02 0.05 Cr 7.10 0.30 13.70 2.20 0.34 1.14 5.0 0.30 6.96 Co 0.1 0.2 0.05 0.30 0.2 0.05 0.30 0.2 0.06 Cu 1.90 7.70 8.32 2.70 5.50 6.10 2.80 5.20 5.30 Fe 68.60 46.50 96.7 117.5 104.0 118.30 56.90 67.40 95.6 Pb 8.20 0.30 0.52 13.75 6.80 0.91 9.60 0.30 0.56 Mn 7.20 1.70 2.80 6.70 1.50 3.30 9.10 1.93 2.50 Mo 7.50 0.3 0.30 12.80 0.3 0.20 4.0 0.3 0.38 Ni 21.50 0.33 0.54 17.80 0.4 0.42 21.0 0.60 0.36 V 0.05 0.10 0.61 0.3 0.18 0.88 0.3 0.20 0.99 Zn 10.60 10.80 10.30 8.40 3.00 7.80 10.50 7.70 9.48

All reading in mg/kg of soli.

the potential effect on the marine ecosystem [41]. Of the metals that may double their content in soil and toxic to certain livestock is Cu [12, 13]. But, while Cd, and Pb are food chain contaminants [29]. Over the seasons 2002, 2004, and 2006 in which samples of sewage sludge were collected and analyzed. The level of heavy metals were ranged for Cd (0.1-0.53) mg/kg, Cr (0.3-13.7) mg/kg, Co (0.1-0.3) mg/kg, Cu (1.9-7.7) mg/kg, Fe (46.5-117.5) mg/kg, Pb (0.3-13.7) mg/kg, Mn (1.5-9.1) mg/kg, Mo (0.2-0.8) mg/kg, Ni (0.33-21.5) mg/kg, V (0.05-0.88) mg/kg, and Zn (5.5-30.0) mg/kg. Results show variation in the level of the same elements within different years and sewage treatment plants. Data presented in Table 2 showed the significant differences between the investigated sewage sludge samples. It must be stressed that differences in the levels of heavy metals in sewage sludge reflected overall composition of heavy metals in sewage wastewater. It was noticed that the sewage sludge from Rekka sewage plant recorded the highest concentration of heavy metals among sewage treatment plants but not exceeding Kuwait Standard of Admissible concentration of heavy metal elements (Table 3). However, in the spite of the wide range of the concentration of heavy metals found in the samples collected from three sewage treatment plants at

Table 3 Maximum permissible levels of heavy metals in sewage sludge.

Ceiling concentration (mg/kg dry weight)

Metals Range in Kuwait (A) KEPA (B) WEP (C )

Cd 0.01-0.53 85 39 Cr 0.3-13.70 3000 1200 Co 0.05-0.30 150 NA Cu 1.9-8.32 4300 1500 Fe 46.5-118.3 NA NA Pb 0.3-13.75 840 300 Mn 1.50-9.10 NA NA Mo 0.20-12.80 75 NA Ni 0.33-21.50 420 420 V 0.05-0.99 NA NA Zn 3.0-10.8 7500 NA

A= This study. B= KEPA [42] (Kuwait Environment Public Authority). C=WEF [44] (Water Environment Federation), US.

different times of years, they are much lower than by either Kuwaiti Standards or US Water Environment Federation [42]. The findings were expected due to lower numbers of industries in Kuwait compared to other countries [19]. According to Table 2, the total concentration of heavy metals in the sewage sludge generally were low in year 2006 and high in year 2004. This is due to temporal changes and also can be attributed to the degree of urbanization and industrialization. The latter factor was to a large extent responsible for heavy metals contents which may


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sometime exceed the admissible concentrations thus limiting the agricultural use of sewage sludge. Results also show variation in the level of the same element within the different seasons and sewage treatment plants. Increasing the level of some elements in the year 2002 than other years are being due to the increasing rate of industrial discharges to sewage treatment plants, in addition to variation of the quantity and quality of industrial wastewater wastes. However, with respect to the concentration of heavy metals in the mechanical biological sewage treatment plants, they were always found low compared with dewatering sewage sludge [1]. One would assume that mechanical dewatering processes may help to concentrate heavy metals. From Table 2, it is noted that the level of cobat was the lowest compared to the other metals, while iron levels in sewage sludge recorded the highest among heavy metals. However, the level of iron in 2006 was highest than the previous years. The concentration of cadmium in 2006 was higher at Rekka sewage treatment plant than they were in the years 2000 and 2004. The increase in the concentration of cadmium could have been partially caused by oil activities near the Rekka sewage treatment plant. However, the level of chromium in the year 2006 was higher than the previous years in the three sewage treatment plants. The increase in chromium concentration might be due to oil spillage. The concentration of nickel measured in 2002 was higher than the levels recorded in 2004 and 2006. However, the levels of vanadium found higher in 2006 than in 2002 and 2004. This contamination can be attributed to oil spillage and industrial waste. Ni and V are considered to be the largest trace metals constituents of crude oil, as a result, their presence in sewage sludge may indicate direct input from oil pollutants. Table 2 shows copper levels present in sewage sludge plants for the years 2002, 2004 and 2006. However, the level of copper in 2006 was higher than in the previous years (Table 2). The increase in this level might be due to oil sources.

Levels of lead, manganese, molybdenum and zinc in sludge were higher in the year 2002 than they were during 2004 and 2006. It is clear indication that heavy metals do not show any significant differences during 2004 and 2006, with the exception of marked increase in the concentration of these metals in 2002. The levels of Cd, Cr, Co, Cu, Fe, Pb, Mn, Mo, Ni, V and Zn in Kuwait’s sludge reflect their presence in the raw wastewater. All heavy metals were within the recommended level by Kuwaiti authority. However, results indicated that the level of industrialization in Kuwait is increasing and illegal dumping of industrial wastewater and oil waste is becoming uncontrolled [20]. It must be stressed that the differences in the level of heavy metals in sewage sludge reflects the variation in the overall composition of heavy metals in sewage wastewater due to industrial discharged that year.

5. Conclusions

Sewage sludge samples collected from Jahra, Rekka and Um Al-Hayman wastewater treatment plants in 2002, 2004, and 2006 were analyzed for organic matters, nutrients and heavy metals. The quantities of organic matter, organic carbon and nutrients were varied in a wide range of values. The lowest values of organic matter and organic carbon were 24% and 38% respectively, but volatile organic matter was 24%. However, the highest value of organic and organic carbon were 60% and 20 mg/L, but for volatile matter, the highest value was 58%. Nutrients such as K, P, and N were present in sewage sludge and they ranged for K (14-54) mg/L, for P (2-6) mg/L and for N (0.04-0.06) mg/L. The content of heavy metals in sewage sludge were determined and they were Cd, Cr, Co, Cu, Fe, Pb, Mn, Mo, Ni, V and Zn. Their concentration were ranging from 0.1 mg/kg (Cd) to about 117.5 mg/kg (Fe). The data shows variation in the level of heavy metals in sewage sludge collected from the three sewage treatment plants (Jahra, Rekka and Um Al-Hayman) at different time of the years. Temporal variation in


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sludge metal levels may be affected by temporal variation in the levels of heavy metals in the influent wastewater or in the efficiency of treatment involved [19, 43]. Base on the results of heavy metals presented in Table 3. Rekka sewage sludge recorded the highest contents of heavy metals, whereas Um Al-Hayman sludge recorded the lowest. These differences in metal levels among the three sludge may results from the contributions of industrial discharges and temporal effects. Moreover, the concentrations show a pronounced yearly variation, the highest year is 2004 and lowest is 2002. It is believed that this behavior is due to the climatec changes. However, levels of most metals in the three sludge were lower than their levels in sludge from United States. Before application three sewage sludge locally, characteristics of local soil should be studied thoroughly and environmental parameters should be taken into consideration.

Acknowledgements

The author would like to thank Kuwait Institute for Scientific Research for their support. This work was conducted within the project entitled “Assessment of Toxic Effect of Environmental Pollutants Associated with Sewage, EMOO24C”. The author wishes to extend his thanks to the Ministry of Public Works for their help and support. Personnel from project team are acknowledged for their excellent work and Noof S. Al-Muzaini for typing this paper.

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[12] J. Eriksson, Concentration of 61 trace elements ins sewage sludge for manure mineral fertilizer, precipitation and in soil, and crop Stockholm, Sewdish Environmental Protection Agency, Report No. 5154, 2001.

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plants, in: Proceedings of the First Regional Conferences on Sewage Sludge Technology and Management, Kuwait, 15-17, Dec. 2003, pp. 25-35.

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[44] WEF, Land Application of Sewage Sludge, Alexandria, Virginia, USA, 1994.


Traffic Emission Control: A Knowledge Based Approach

K.M. Rajeev1, P. Manoranjan2 and R. Santosh3 1. Centre for Transportation Systems (CTRANS), Indian Institute of Technology, Roorkee 247 667, India

2. Civil Engineering Department & Centre for Transportation Systems (CTRANS), Indian Institute of Technology, Roorkee 247 667,

India

3. Department of Management Studies, Indian Institute of Technology, Roorkee 247 667, India


Abstract: At present the entire world is under the risk of severe environmental problems, due to the expansion of industries, urban population and commercial activities, the city like Delhi (India) faces transportation, environmental and economic challenges. Such type of situations demand the addition of knowledge based layer to help the operators to be familiar with exact traffic problem and give the best choice of strategic control actions to the city. In current situation there is a necessity to build systematic, knowledge based tool to analyze and manage the recent or potential air quality issues and traffic noise issues. The paper comprises the creation of knowledge from the information which is extracted from the various data by using knowledge based modules (spreadsheets, database, software, etc.) and some management, optimization models. Such type of knowledge based management tool may act as a Decision Support System (DSS) which will be very supportive in traffic control system. The technology of knowledge-based systems may facilitate in designing and executing suitable knowledge structures to formulate conceptual models for traffic analysis and management and to use such approach for on-line strategic traffic management operations. Key words: Knowledge management, KM tools, traffic congestion, environmental pollution.

1. Introduction

Due to globalization, the local environmental problems have changed into international environmental pollution issue. Environmental problems have now become some of the most important issues worldwide. The idea of knowledge-based systems was developed at the end of the 1970. Today, it is important to develop knowledge management tools to support the analysis of transport infrastructure. Therefore, it is necessary to develop a knowledge based system which can ease the traffic

Corresponding author: K.M. Rajeev (1982- ), male, research scholar, research fields: transport-environment interaction, application of knowledge management in transport related environmental problems. E-mail: [email protected].

P. Manoranjan (1965- ), male, professor, research fields: travel demand modeling, public transport, transport environment interaction. E-mail: [email protected].

R. Santosh (1965- ), male, associate professor, research fields: knowledge management, human resource management, organizational behavior. E-mail: [email protected].

congestions problem in urban cities and ultimately helpful in the reduction of environmental problems and travel time.

In present time the balance between the sustainable transportation and traffic congestion is a big challenge to the developers and operators of the urban transportation network. Therefore, in the solution of this problem, the cost-benefit analysis has also flourished and is becoming a important tool in the process of decision-making [1]. After the emergence of knowledge based system concept, many other applications came in picture like DENDRAL [2], MYCIN [3], and PROSPECTOR [4]. With the help of the application of knowledge oriented approach, the users can get the explanatory answer of his question from the system. Thus the user can understood the role played by different pieces of domain knowledge existing in the particular model, which will be helpful for him to implement any action.


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2. Objective

The objectives of the study is to develop a knowledge based framework for Decision Support System (DSS) to help analyze the environmentally various sensitive zones of the city and to help in taking decision for various traffic situations and to assess the monitored & survey based data that would be very useful for noise and air quality management.

3. Methodology of the Study

This paper is mainly explaining the adopted framework of Integrated Air Quality Management and Noise Pollution Management (Figs. 1 and 2).

Fig. 1 explicates about Integrated Air Quality Management for Delhi city. Air quality of any city generally depends on the number of vehicles running on the road in that particular city and number of industries established in that city. But it is clear from various studies that transport vehicles play very important role in bad air quality. Bad air quality has various impacts on people health, climate change, natural flora and fauna and biodiversity. In present scenario there is a need of Integrated Air Quality Management which can be achieved only by the incorporation of knowledge based management (creation of knowledge, sharing of knowledge, conversion of explicit knowledge into tacit knowledge etc.), policy based management (traffic management), monitoring of concentration of various pollutants at different locations, integration of public transport vehicles), technical management (better fuel quality, vehicles with pollution control device etc.) and legal management (fuel standards, emission standards etc.). These various management options can help in sustaining better air quality for a city.

In present days because of increasing number of vehicles worldwide, traffic noise pollution has become an international issue. Fig. 2 elaborates about Noise Pollution Management. Nowadays traffic noise is going to be a challenging problem for any metro city. With the help of proposed management alternatives, it

is possible for a city to uphold the better traffic noise pollution management. During the operation of traffic noise control, diverse management alternatives play significant role like noise standards for various prescribed zones, green mufflering and environmental knowledge based management tools. To control the traffic noise, there is a requirement of environmental knowledge based management systems like internalization of knowledge, externalization of knowledge, socialization of knowledge, combination of knowledge and development of public knowledge from technology knowledge.

4. Application of Study Methodology

The above methodology is basically focused towards the transport related environmental problems of Delhi:

(1) Air Pollution: Air quality is an emerging problem as a principal motivation for improving Delhi’s transportation system. The levels of air pollutants in Delhi are often several times higher than the ambient standards set by the Central Pollution. The total population of Delhi is about 13,782,976, which spread over 1483 square km. Delhi has nearly 4,183,609 vehicles on the road which is comparatively higher than the vehicles of any other mega city. In Delhi the motor vehicles are the main contributor in air pollution. (2) Noise Pollution: Traffic noise pollution is considered as one of the significant source of noise pollution that adversely affects the human health [5-7]. This is gradually commanding attention by public at large in urban areas. The recognition of noise as an environmental problem and its adverse impact on both community and occupational environment is rapidly growing. The problem of noise pollution is only because of increasing traffic volume, industrialization and commercial activities.

(3) Vehicle Growth: A majority of motor vehicles in India are concentrated in urban centers and Delhi itself, which contains around 1.4% of the Indian population, accounts for more than 7% of all motor vehicles in the country. There are already more than 2.6 million


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Fig. 1 Integrated Air Quality Management.

Fig. 2 Noise pollution management.

Various Management Options

Policy Based Management Traffic management Involvement of Public Transport

Systems Integration of Public Transport

Systems Monitoring Land use pattern Industrial zoning Residential zone

Technical Management Fuel quality Cleaner technology Production of vehicles

with effective control device

Legal Management Fuel standards Emission standards Industrial compliance

Awareness

KM Based Management Creation of environmental Knowledge Sharing of Environmental knowledge Utilization of environmental knowledge Internalization of Environmental knowledge

Impacts Impact on human health Impact on climate Impact on flora & fauna Impact on biodiversity

Various Sources Vehicles

Industries

Integrated Air Quality Management

Air Quality

KM Based Management Creation of environmental Knowledge Sharing of Environmental knowledge Utilization of environmental knowledge Internalization of Environmental knowledge

Policy Based Management Proper Traffic management Involvement of Public Transport

Systems Monitoring Industrial zoning Residential zone Commercial zone Silence zone

Technical Management Control on source Control on path Use of noise absorbing materials Using ear plugs & muffs

Green mufflering

Legal Management Noise standards for

various zones Awareness

Noise Pollution Management

Impact on human being

Different Sources Road traffic noise Rail noise Aircraft noise Industrial noise Neighbors noise

Noise Quality


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registered motor vehicles in Delhi and about 600 vehicles are being registered everyday. Traffic composition in India is of a mixed nature. In Delhi it is expected that population will become double by 2020 and vehicle stock will become 3.7 times in that same period [8]. Fig. 3 shows the expected increase in vehicular stock in Delhi.

(4) Transport Network: The transport system of Delhi consists of a well developed transport network system based on ring and radial pattern, large fleet of buses (DTC & CNG) and a suburban rail system including MRTS. The majority share of Delhi commuters is met by road based transport systems. There has been a major improvement in transport infrastructure in recent years in terms of flyovers, road widening, new roads development and development of metro rail corridors along major routes of travel in the city. Due to continuous increase in population employment opportunities and number of vehicles, there is a constant increase in demand over the years and infrastructure has not grown in adequate proportions making the existing network system function beyond its capacity. This has led to serious traffic problems of congestion, delays, safety, traffic pollution and system management.

(5) Urbanization: Urbanization is explained by Kingsley Davis as process of switch from spread out pattern of human settlements to one of concentration in urban centers [9]. It is a finite process, a cycle through which a nation pass as they evolve from agrarian to

Fig. 3 Expected increase in vehicular stock in Delhi, source: [8].

industrial society [10]. India’s urban population is growing at an average rate of around 3 percent per annum. In India the growth of urban population has been extremely fast during this century.

5. Sustainable Approach

The urban population of the world as a whole has been expanding at the rate of nearly 3 percent per year, presumably faster than the existing world population growth rate. Roughly, half of the global population lives in cities [11]. In present time nearly 30 percent India’s population lives in urban areas. Current trends of urbanization, as inspired by better quality of life, are posing multiple stresses on our environment and human population. Coupled with rapid urbanization, each city consists of a number of supporting systems. Transport is one of them, which provides mobility, flexibility and accessibility to urban people. For all practical purposes, a sustainable transport system must offer mobility and approachability to all urban residents in safe, risk-free and eco-friendly mode of transport. In such a complex situation, linkages between environments, modes of public/private motorized transport, non-motorized transport and safety must be given sufficient consideration.

6. DSS Framework

Due to the expansion of the road network and the growth of vehicles, the Delhi traffic control has installed traffic signals at short distances. There are more than 700 signalized intersections located all over Delhi to control traffic operations and ensure smooth flow of traffic. But these signalized intersections have led to excessive time and fuel consumption for all vehicle trips. To overcome such type of problems, there is a need to incorporate KM based DSS to provide real time management system to cater to changing traffic needs. The proposed Decision Support System (DSS) is going to be a better alternative to solve traffic problems like congestion, delays, pollution management. It will also help in the creation of knowledge


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Fig. 4 Framework of Decision Support System.

and awareness among people. With the help of this DSS, the traffic controller can analyze the various transport-environmental problems and develop decision for the same. The corresponding Expert System is showing in Fig. 4. In the first phase of the study a general understanding of the problem is developed. This is carried out at various locations of Delhi, the capital of India, where data are collected with the objective of development of data model.

The developed data sheet generates information which is further with help of knowledge base (spreadsheets, documents & software) and other applicable models viz. optimization, management/operation converted into knowledge base tools. This KM based Decision Support System support in better air & noise pollution management. It also helps in the creation of public awareness and public knowledge. With the help of this DSS, the various decisions can be taken for a city by traffic ccontroller in

diverse transport related problems like congestion and environmental problems.

7. Conclusions

On the basis of above study, it is concluded that (1) KM promotes the use of information technology

in the government not only as a tool for the management and decision support system but also to re-engineer the process of the government to provide a more efficient, transparent, accountable and responsive government to its citizens.

(2) It will accelerate the use of Knowledge Based Information Technology in schools, colleges and other educational institutions with a view to providing skills and environmental knowledge to the youth so as to render them fit for employment in transport sector.

(3) For metro city like Delhi, there is a prerequisite of a systematic, accessible knowledge base for air & noise quality management.

Analysis of data

Implementation

Policy-making & decision making

Knowledge

Information

Knowledge base Spread sheets, data base, documents, other software

MODELS Optimization Management Operation

Air Pollution data Noise pollution data

OUTPUTS Improved air quality management Improved noise pollution management Public awareness Creation of public knowledge Problem analysis Decision support

Management options

Data collection

Wisdom


84

(4) From the discussed approach, it is possible to develop air and noise quality management plan in coming year.

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application of knowledge management to support the sustainable analysis of urban transportation infrastructure, Department of Civil Engineering, University of Toronto, Toronto, ON M5S 1A4, Canada, 2005.

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[7] I.D. Williams, I.S. Mc Creae, Road traffic nuisance in residential and commercial areas, Sci. Tot. Environ. 169 (1995) 75-82.

[8] D. Anjana, J. Parikh, Energy conversion and management: transport scenarios in two metropolitan cities in India, Energy Policy 45 (1997) 2603-2625.

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[11] J. Peterson, Global population projection through the 21st century, Ambio 13 (1984) 141.

Documents

Canute Hyandye and I.B.katega GIS -Journal of Environmental Science and Engineering,Vol4,No9,2010