Research Article Twelve-Year Trends of PM and Visibility ...sese.nuist.edu.cn/TeacherFiles/file/20170820/... · twelve-year trends of PM 10 and visibility in Hefei during the period

Research ArticleTwelve-Year Trends of PM10 and Visibility inthe Hefei Metropolitan Area of China

Lin Huang Mindong Chen and Jianlin Hu

Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution ControlJiangsu Engineering Technology Research Center of Environmental Cleaning MaterialsCollaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and Engineering Nanjing University of Information Science and Technology219 Ningliu Road Nanjing Jiangsu 210044 China

Correspondence should be addressed to Jianlin Hu hu jianlin126com

Received 12 November 2015 Accepted 18 January 2016

Academic Editor Renate Forkel

Copyright copy 2016 Lin Huang et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

China has been experiencing severe air pollution and previous studies havemostly focused onmegacities and a few hot spot regionsHefei the provincial capital city of Anhui province has a population of near 5 million in its metropolitan area but its air quality hasnot been reported in literature In this study daily PM

10and visibility data in 2001ndash2012 were analyzed to investigate the air quality

status as well as the twelve-year pollution trends in Hefei The results reveal that Hefei has been suffering high PM10pollution and

low visibility during the study period The annual average PM10concentrations are 2sim3 times of the Chinese Ambient Air Quality

Standard PM10shows fluctuating variation in 2001ndash2007 and has a slightly decreasing trend after 2008The annual average visibility

range is generally lower than 7 km and shows a worsening trend from 2001 to 2006 followed by an improving trend from 2007 to2012 Wind speed precipitation and relative humidity have negative effects on PM

10concentrations in Hefei while temperature

could positively or negatively affect PM10 The results provide a general understanding of the status and long-term trends of PM

10

pollution and visibility in a typical second-tier city in China

1 Introduction

Particulate matter (PM) is a pollutant of great environmentalconcern due to its tight correlation with health conditionsof people [1ndash5] and the climate of the earth [6ndash8] PM isactually a complex mixture of extremely small particles andliquid droplets with chemical components of sulfate nitrateammonium elemental carbon organic chemicals metalsand so forth [9] the emissions of which originate from bothanthropogenic and natural sources [6 10 11] Based on theaerodynamic diameter of particles PM is classified intoPM25

(PM with an aerodynamic diameter le25 120583m) PM10

(PM with an aerodynamic diameter le10 120583m) and TSP (totalsuspended particles PM with an aerodynamic diameterle100 120583m) [12]

Visibility usually refers to the horizontal distance atwhich the contrast between a target and its sky backgroundequals the threshold of human eyes [13] Visibility canbe significantly associated with air quality as it could be

decreased by air pollutants via light scattering and absorptionby fine particles in the atmosphere [13ndash15] Thus visibilitycan be taken as a highly relevant visual indicator of airpollution level [16] China has been experiencing severe airpollution in recent decades resulting from the rapid industrialdevelopment and urbanization Many studies have reportedthe high PM pollution levels and the degradation of visibilitydue to the worsening air quality in China [13 16ndash18]

Analysis on long-term changing trends of PM pollutionand visibility is an important approach to evaluate the overallimpact on air quality at local regional continental andglobal scales [13 19] In China the relevant studies have beenfocused on the megacities [20ndash24] and some hot spot regionssuch as the North China Plain [14 23 25ndash27] the YangtzeRiver Delta region [17 18 28 29] and the Pearl River Deltaregion [16 30] Few studies on PM pollution and visibilityover a specific second-tier city such as Hefei have beencarried out and therefore long-term changing trends of PM

10

pollution and visibility remain unknown in these areas

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2016 Article ID 4810796 9 pageshttpdxdoiorg10115520164810796

2 Advances in Meteorology

Hefei Shanghai

Guangzhou

Beijing

Xirsquoan

Figure 1 Location of Hefei city as marked by the red rectangle

The government of China started routinely monitoringPM10 sulfur dioxide (SO

2) and nitrogen dioxide (NO

2) in

Hefei in June 2000 Routinemeasurement of PM25

was intro-duceduntil January 2013 andno routinemeasurement of TSPwas available in Hefei Therefore long-term trends analysisis only feasible for PM

10in Hefei In this study analysis of

twelve-year trends of PM10and visibility in Hefei during the

period of 2001ndash2012 was performed The study investigatedthe general patterns of PM

10and visibility trends in Hefei

over the recent twelve-year period by analyzing the seasonaland annual behavior of PM

10and visibility In addition the

meteorological factors that may affect PM10

pollution andvisibility were also examined The results provide a generalunderstanding of the long-term PM

10pollution and visibility

characteristics which can be served as a basic data supportfor local government to further mitigate the environmentpollution and to improve air quality control plans for the city

2 Materials and Methods

21 Study Areas Hefei (center 1171910158403710158401015840 314410158405510158401015840) is thecapital city of Anhui province located in the east center ofChina about 1000 km south to the national capital city ofBeijing and 450 km west to the city of Shanghai (Figure 1)Hefei is the largest city and the political economic andcultural center ofAnhui provinceHefei has a total populationof about 8 million and near 5 million inhabitants reside in itsmetropolitan area in 2012 [31] Hefei has a GDP of 416 billionChinese currency ranked number 1 in Anhui province andnumber 31 in China in 2012 [31] The main industry includesmachinery electronics chemistry steel textile and cigaretteindustries Hefei has been identified by The Economist inthe December 2012 as worldrsquos number 1 fastest growingmetropolitan economy (httpwwweconomistcomnode21567579)

22 Data Source Daily air pollution index (API) and themajor pollutant data during June 2000 to January 2013 inHefei were downloaded from the website of the Ministry of

Table 1The bottom and upper limit of API values and correspond-ing PM

10concentrations

API PM10concentrations (120583gmminus3)

119868bottom 119868upper 119862bottom 119862upper0 50 0 5050 100 50 150100 200 150 350200 300 350 420300 400 420 500400 500 500 600

Environmental Protection of the Peoplersquos Republic of ChinaData Center (httpdatacentermepgovcn) Multiple siteshave been built up inHefei (4 sites in 2000 and then graduallyexpanded to 9 sites with the expansion of the city by 2010)The monitoring sites are all located in the urban area Eventhough ambient concentrations of PM

10 NO2 and SO

2

have been routinely monitored at multiple sites the datawebsite only publishes city-average API values (averagedover all sites) The complete data in 2001ndash2012 were thereforeanalyzed in this study Daily API values were estimated basedon the ambient concentrations of PM

10 NO2 and SO

2

First sub-API (ie API of one specific pollutant) values wereestimated for PM

10 NO2 and SO

2 respectively and then the

maximum sub-API value was determined as the daily APIand the associated pollutant was determined as the majorpollutant In Hefei PM

10was the major pollutants on all the

pollution days in 2001ndash2012 (httpdatacentermepgovcnreportair dailyair dairy aqijsp) Therefore daily PM

10

mass concentrations were converted back from API valuesusing the following

119862 = (119868 minus 119868bottom) times119862upper minus 119862bottom119868upper minus 119868bottom

+ 119862bottom (1)

where 119862 is the PM10

concentration and 119868 is the API value119868upper and 119868bottom are the upper and bottom limit values for 119868(ie 119868bottom le 119868 lt 119868upper) 119862upper and 119862bottom are the upperand bottom limit concentrations corresponding to 119868upper and119868bottom Table 1 shows the values of 119868bottom 119868upper 119862bottom and119862upper

The meteorological observation data in 2001ndash2012 wereobtained from the National Climate Data Center (NCDC)(ftpftpncdcnoaagovpubdatanoaa) The meteorologi-cal data includes hourly surface observations of air temper-ature dew point temperature wind speed wind directionprecipitation Relative humidity was estimated using the tem-perature and dew point temperature Hourly meteorologicalparameters then were averaged to daily values to investigatetheir correlations to daily PM

10and visibility

3 Results and Discussion

31 PM10 Trends Figure 2(a) displays the long-term trends ofthe PM

10concentrations inHefei during the period from2001

to 2012 The statistical results for each year were computed

Advances in Meteorology 3

0

100

200

300

400

500

600

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

PM10

(120583g m

minus3)

Maximum value

75th percentile

Median value25th percentile

Average value

Standard deviation

Minimum value

(a)

30

120

90

60

150

180

210

240

300

270

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

PM10

(120583g m

minus3)

Best 20 PM10 rate = 052120583gm3 yearAverage PM10 rate = 024 120583gm3 yearWorst 20 PM10 rate = minus118 120583gm3 year

(b)

Figure 2 (a) Statistical box chart of long-term trends for the PM10concentration in Hefei during the period from 2001 to 2012 The range of

the box represents the interquartile range of the data (b)The worst 20 and 50 and best 20 region-average PM10concentration trends in

Hefei during the period from 2001 to 2012 Dotted lines are the linear regression curves of the corresponding trend lines

using the individual daily data The annual average concen-trations of PM

10show fluctuating variation in 2001ndash2007 and

slightly decrease after 2008 with an overall increasing trendof 024120583gmminus3 per year (Figure 2(b)) The minimum PM

10

annual average concentration is 93 plusmn 41 120583gmminus3 observed in2005 and the maximum is 126 plusmn 55 120583gmminus3 observed in 2008The annual average PM

10concentrations are 2sim3 times of

Grade I Chinese Ambient Air Quality Standard for annualaverage PM

10(40 120583gmminus3) [32] underscoring serious air

pollution status in Hefei The minimum PM10concentration

values for the twelve years ranged from 9 to 23120583gmminus3 witha low deviation magnitude however the maximum valuesrevealed a significant annual variation with no clear trendduring this period The maximum PM

10concentration was

248120583gmminus3 in 2001 and then concentration value drasticallyincreased to 470 120583gmminus3 in 2002 followed by a continuousdecrease from 2004 to 2007 The concentration went back to506120583gmminus3 in 2008 and showed a zigzag behavior after thatThe maximum PM

10in Hefei is 230120583gmminus3 in 2012 which

is the lowest value during the twelve years but is 4 times ofGrade I Chinese Ambient Air Quality Standard for 24-houraverage PM

10(50 120583gmminus3) [32]

Figure 2(b) shows the worst 20 and 50 and best 20average PM

10concentration trends inHefei during the period

from 2001 to 2012 Dotted lines are the linear regressioncurves of the corresponding trend lines An increasing trendis found for the best 20 PM

10concentrations at the rate of

052120583gmminus3 per year A similar but relatively smaller trend is

found for the average PM10concentrations of 024120583gmminus3 per

year However the worst 20 PM10concentration exhibited a

declining trend of 118 120583gmminus3 per year It should be noted thatthe trends are not statistically significant as the correlationcoefficients (1198772) are all below 015 for the three trendsThere-fore overall the PM

10pollution situation has not been signifi-

cantly improved during these years in Hefei Considering thehigh PM

10levels further legislation efforts will be expected

to inhibit PM pollution and improve air quality in HefeiFigure 3 shows the frequency distribution of daily PM

10

concentrations in Hefei in each year during 2001ndash2012 in fiveconcentration ranges 0ndash50 50ndash100 100ndash150 150ndash200 andgt200120583gmminus3 PM

10concentrations in the range of 50ndash100

and 100ndash150 120583gmminus3 dominatemost days of a year accountingfor approximately 70 of all days in a year The number ofdays with PM

10concentration less than 100120583gmminus3 shows

an increasing trend during 2008 to 2012 indicating a slightimprovement in air quality since 2008 The days with thePM10

concentration over 200120583gmminus3 only account for lessthan 10 of the total days over all the years except 2002 and2008 and show no clear trend

To learn more about the temporal variations of PM10 the

data are divided into four seasonal groups Each season isdefined as spring (March to May) summer (June to August)fall (September to November) and winter (December toFebruary) Figure 4 presented the seasonal variations forPM10

concentration in Hefei during 2001ndash2012 Of all thetwelve years summer has the lowest PM

10concentrations


0306090

120150180210240270300330360

Day

s

Year20

12

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

gt200

150ndash200100ndash150

50ndash1000ndash50

Figure 3 Frequency distribution of daily PM10

concentration inHefei during the period from2001 to 2012Note PM

10concentration

unit 120583gmminus3

among all seasons with the lowest standard deviation variedin the range of 71 plusmn 18 (2005) to 104 plusmn 45 (2008) 120583gmminus3 Theother three seasons have similar PM

10concentrations with

the 12-yearmean values of 114plusmn14 (spring) 114plusmn11 (fall) and112 plusmn 11 (winter) 120583gmminus3 respectively Higher dilution dueto warmer temperature and mixing layer and higher removaldue to more precipitation in summer are the main driver ofrelatively clean PM

10status in summer In addition to the

effects of meteorological conditions additional emissions inother seasons (such as agricultural biomass burning in thespring and fall [8] residential house heating and fireworksduring the Chinese New Year [33]) also contribute to thedifference among the seasons Even though the summerconcentrations are the lowest still the concentrations areseveral times higher than Grade I Chinese Ambient AirQuality Standard The relatively weak seasonal variationespecially among spring fall and winter is not consistentfrom the seasonal pattern in other cities [34] suggesting thepollution sources and processes are different in Hefei

32 Visibility Trends Long-term trend of visibility in Hefeihas been analyzed for the period of 2001ndash2012 and the annualstatistical results are shown in Figure 5(a)The annual averagevisibility is less than 7 km in all the years except 2001 and2004 The best visibility is found in 2001 with the highestvalue of 232 km and the average value of 86 kmThe visibilityshows a worsening trend from 2001 to 2007 In 2007 thehighest visibility is 117 km and the lowest value is only07 km with an average one of 56 km The mean visibilitypresents a slightly increasing trend by 95 on average since2007 In 2012 the average visibility can reach 61plusmn25 km andthe lowest value is 12 km The highest visibility shows a cleardegradation trends from 2001 (232 km) to 2012 (120 km)

020406080

100120140160180200220240

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

SpringSummer

FallWinter

PM10

(120583g m

minus3)

Figure 4 Seasonal variations of PM10concentration inHefei during

2001ndash2012 The error bars indicated the standard deviation for theaverage PM

10concentration value in each season every year

The general visibility situation is very serious and continuousand effective pollution control strategy is necessary to coun-teract the degradation of atmospheric visibility

The worst 20 and 50 and best 20 region-averagevisibility trends in Hefei during 2001ndash2012 are shown inFigure 5(b) Dashed lines are the linear regression curves ofthe corresponding trend lines Similar decreasing trends arefound over the twelve years with the rates of 001 008 and013 km per year which were observed for the worst 20 and50 and best 20 average visibility respectively However itis encouraging to notice slight increasing trends in generalsince 2006 or 2007 for the three groups of data

The trends of annual percentages () of visibility forlower than 5 km and higher than 10 km in Hefei during 2001ndash2012 are shown in Figure 6 The percentage of visibility lowerthan 5 km is in the range of 219ndash427 with an overallincreasing rate of 114 per year while that of visibility higherthan 10 km is in the range of 38ndash353 with an overalldecreasing rate of 151 per year However it is worthy tonotice that there is a breaking point for both trends in 2006similar to the visibility trends in Figure 5 The percentagelower than 5 km visibility before 2006 exhibits a significantlyincreasing trend with the rate of 304 per year whileafter 2006 a decreasing trend is observed with a decliningrate of 109 per year The percentage higher than 10 kmvisibility before 2006 exhibits a fluctuating behavior witha decreasing rate of 377 per year and in contrast after2006 a steady increasing trend with a high 1198772 value of0917 and a changing rate of 091 per year is obtained Thedecreasing trend in PM

10after 2008 and the increasing trend

in visibility after 2006 are consistent with the air controlprograms that have been implemented during the 11th five-year plan (2006ndash2010) as suggested by other studies [13 15]


0

5

10

15

20

25

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

Visib

ility

(km

)

(a)

2

4

6

8

10

12

16

14

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Visib

ility

(km

)

Worst 20 visibility rate = minus001 kmyearAverage visibility rate = minus008 kmyearBest 20 visibility rate = minus013 kmyear

(b)

Figure 5 (a) Statistical box chart of long-term trends for the visibility in Hefei during the period from 2001 to 2012 The range of the boxrepresents the interquartile range of the data (b) The worst 20 and 50 and best 20 region-average visibility trends in Hefei during theperiod from 2001 to 2012 Dashed lines are the linear regression curves of the corresponding trend lines

20

25

30

35

40

45

50

Visi

bilit

y (

)

0

5

10

15

20

25

30

35

40

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Linear trend (2001ndash2006)304 per year R2 = 0564

Linear trend (2001ndash2006)minus377 per year R2 = 0276


lt5kmgt10km

Overall linear trend (lt5km) = 114 per year R2 = 0346


Overall linear trend (gt10km) = minus151 per year R2 = 0613

Figure 6 Annual region-average percentages () of visibility lowerthan 5 km (left 119910-axis) and higher than 10 km (right 119910-axis) in Hefeiduring 2001ndash2012 Black dashed lines and blue dotted lines are thelinear regression curves of the corresponding trend lines splitted byyear 2006 (the red short dashed line)

However more effective control programs are further neededto keep improving the air quality and visibility in Hefei

33 PM10 and Visibility versus Meteorological Factors Themeteorological conditions are key factors determining thestatus of the PM pollution and visibility Figure 7 displays thePM10

concentrations and visibility values in different cate-gories of meteorological parameters of air temperature windspeed wind direction precipitation and relative humidityin Hefei from 2001 through 2012 The daily averages of thefive meteorological parameters are first divided into eightcategories and PM

10concentrations and visibility values are

sorted into the eight categories correspondingly and then themean and standard deviation values are calculated for PM

10

and visibility in each category The PM10

follows a clear ldquonrdquoshape with the temperature with the PM

10concentration

increasing with temperature when temperature is lower than12∘C and PM

10concentration reaches a peak point of approx-

imately 120 120583gmminus3 at around 12∘C then PM10concentration

decreases with temperature The visibility shows somewhatan inverse correlation with temperature with a decreasingtrend indicating the degradation effect of particles on vis-ibility The effects of temperature on PM

10concentrations

are complicated On one hand vertical mixing which dilutesparticles in the boundary layer is affected by the change intemperature and wind with height In general vertical mixingis stronger in hot seasons when temperature is also higher[35] On the other hand temperature affects the chemicalformation of particles Higher temperature accelerates thereactions to form more products that can partition intoparticulate phase (positive) but meanwhile the productstend to remain in their gaseous phase when temperature


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

minus5 5 10 15 20 25 30 350Air temperature (∘C)

VisibilityPM10

(a)

Wind speed (ms)

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

1 2 3 4 5 6 70

VisibilityPM10

(b)

0

20

40

60

80

100

120

140

160

180

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

Wind direction (deg)

Visibility

0 45 90 135 180 225 270 315

PM10

(c)

Precipitation (mmday)

020406080100120140160

20

468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

gt50

0ndash05

05

ndash1

1ndash3

3ndash5

5ndash10

10

ndash20

20

ndash50

VisibilityPM10

(d)

50 55 60 65 70 75 80 85 90 95 100Relative humidity ()

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

VisibilityPM10

(e)

Figure 7 Effects of meteorological factors on PM10

concentration and visibility in Hefei during 2001ndash2012 (a) air temperature (b) windspeed (c) wind direction (d) precipitation and (e) relative humidity


Table 2 Multiple regression statistics for visibility to temperature relative humidity and PM10concentraitons

(a)

Regression statisticsMultiple 119877 0691198772 047Adjusted 1198772 047Std error 136Observations 4586

(b)

Coefficients Std error 119905 stat 119875 value Lower 95 Upper 95Intercept 1146 014 8007 000 1118 1174Temperature 004 000 1820 000 003 004RH minus009 000 minus5737 000 minus009 minus008PM10

minus001 000 minus3426 000 minus002 minus001

is too high (negative) [36] Therefore the results in Hefeiindicate that the positive effect of temperature on particulatedominates when temperature is lower than 12∘C and thenegative effects become more important when temperatureis higher than 12∘C

PM10

concentration decreases with the wind speed andvisibility increases with the wind speed Calm winds prohibitthe transport of pollutants and favor the accumulation of PMleading to higher PM

10concentrations and worse visibility

[15] In terms ofwind direction effect the PM10concentration

is the highest under the southeast winds followed by the eastwinds The PM

10concentrations are similar under the rest of

wind directions This phenomenon is likely due to the moreindustries located in cities east to Hefei such as Marsquoanshanand Nanjing In winter the prevailing wind direction is north(northwest north and northeast winds) accounting for 55of total winds and the prevailing wind direction in summeris east (northeast east and southeast winds) accountingfor 59 of total winds The fact that the prevailing windsin summer are associated with higher PM

10concentrations

while the high temperatures in summer lead to decreasein PM

10concentrations (Figure 7(a)) confirms the negative

effect of temperature in summer that is discussed previouslyThevisibility trend indicates that visibility is generally the bestwhen the wind is from the southwest and is the worst whenthe wind is from the north

PM10

decrease when the precipitation and the relativehumidity increase Washout effect by precipitation is themain removal process of PM

10[6 37] Stronger precipitation

leads to more washout of PM and thus lower ambient PMconcentrations High relative humidity can significantly alterthe particle properties Some particles such as sulfates accu-mulate water and grow to larger sizes at which they are moreefficient to deposit [15] Previous study in Shanghai also foundsimilar correlation between PM

10and relative humidity [38]

The visibility also shows decreasing trends with increasingprecipitation rate and relative humidity which is consistentwith other studies [39]

PM10

can directly affect visibility by scattering andabsorption light Multiple linear regression analysis was

conducted for visibility to PM10

and the meteorologicalparameters When excluding the wind speed wind directionand precipitation in the analysis the multiple regressioncorrelation coefficient (multiple 119877) is the greatest and thestatistical results are shown in Table 2 In Hefei visibility isnegatively correlated to both RH and PM

10 The fact that

visibility is negatively correlated to PM10

but meanwhilevisibility and PM

10are both negatively correlated with RH

is presumably due to the synthesized effects by other factorssuch as particle sources hygroscopicity and hygroscopicgrowth rate of particles versus loss by depositionThe analysisof PM

10and visibility to the meteorological parameters

in Figure 7 is rather qualitative More studies are neededto quantify the relationships between PM

10pollution and

visibility and meteorological conditions in Hefei

4 Conclusions

Twelve-year daily PM10

and visibility data in 2001ndash2012 inHefei were analyzed Overall Hefei has been suffering seriousPM10pollution during these years The annual average PM

10

concentrations are 2sim3 times of the Chinese Ambient AirQuality Standard and the extreme daily PM

10concentrations

are over 4 times of the standard An overall worsening trendis revealed for annual average and the best 20PM

10concen-

trations even though the worst 20 PM10

(ie the extremePM10

pollution) shows a decreasing trend Unlike othercities PM

10in Hefei has a relatively weak seasonal variation

among spring fall andwinter but has lower concentrations insummerThe annual average visibility range is generally lowerthan 7 km indicating serious viability degradation in HefeiMoreover visibility exhibits an overall worsening patternthrough the period Detailed analysis reveals that the annualaverage concentrations of PM

10show fluctuating variation in

2001ndash2007 and slightly decrease after 2008 and the visibilityshows a worsening trend from 2001 to 2006 followed by asteadily improved trend from 2007 to 2012 indicating a grad-ually improved trend after the 11th five-year plan Howeverit is necessary to implement more effective control programs


in order to keep improving the air quality and visibility inHefei Wind speed precipitation and relative humidity havea negative effect on PM

10concentrations while temperature

has a negative effect on PM10

when it is above 12∘C and hasa positive effect when it is lower than 12∘C Precipitation andrelative humidity also have a negative effect on visibility

This study reports the long-term trends of PM10

andvisibility for the first time in the Hefei metropolitan area andprovides a general understanding of the status and trendsof PM

10pollution and visibility in a typical second-tier city

in China More studies are still needed in this area suchas field measurement and modeling studies to investigatethe chemical and physical properties of particles during PMpollution events source apportionment studies of PM andvisibility to reveal the contributions of different sources to PMand visibility modeling studies of regional transport of PMand its precursors and effects of meteorological conditionchange on the year-to-year variability of PM concentrationsThese studies will provide necessary scientific support fordeveloping local and regional emission mitigation programsaround the Hefei metropolitan area

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

Thiswork is financially supported by the Startup Fund forTal-ent at Nanjing University of Information Science and Tech-nology (NUIST) under Grant no 2243141501009 the NaturalScience Foundation of China (21577065) International STCooperation Program of China (2014DFA90780) a Signifi-cant Research Plan ofNationalNatural Science Foundation ofChina (91543115) and the Priority Academic ProgramDevel-opment of Jiangsu Higher Education Institutions (PAPD)

References

[1] R D Brook S Rajagopalan C A Pope et al ldquoParticulatematter air pollution and cardiovascular disease an update tothe scientific statement from the American Heart AssociationrdquoCirculation vol 121 no 21 pp 2331ndash2378 2010

[2] DW Dockery C A Pope X Xu et al ldquoAn association betweenair pollution and mortality in six US citiesrdquo The New EnglandJournal of Medicine vol 329 no 24 pp 1753ndash1759 1993

[3] O Laurent J Hu L Li et al ldquoSources and contents ofair pollution affecting term low birth weight in Los AngelesCounty California 2001ndash2008rdquo Environmental Research vol134 pp 488ndash495 2014

[4] A Seaton D Godden W MacNee and K Donaldson ldquoPartic-ulate air pollution and acute health effectsrdquoThe Lancet vol 345no 8943 pp 176ndash178 1995

[5] B Ostro J Hu D Goldberg et al ldquoAssociations of mortalitywith long-term exposures to fine and ultrafine particles speciesand sources results from the California teachers study cohortrdquoEnvironmental Health Perspectives 2015

[6] E Ahmed K-H Kim Z-H Shon and S-K Song ldquoLong-termtrend of airborne particulate matter in Seoul Korea from 2004to 2013rdquo Atmospheric Environment vol 101 pp 125ndash133 2015

[7] J Fan L R Leung P J DeMott et al ldquoAerosol impacts onCalifornia winter clouds and precipitation during CalWater2011 local pollution versus long-range transported dust (vol 14pg 81 2014)rdquo Atmospheric Chemistry and Physics vol 14 no 6pp 3063ndash3064 2014

[8] A J Ding C B Fu X Q Yang et al ldquoIntense atmospheric pol-lution modifies weather a case of mixed biomass burning withfossil fuel combustion pollution in eastern Chinardquo AtmosphericChemistry and Physics vol 13 no 20 pp 10545ndash10554 2013

[9] J Hu H Zhang S-H Chen et al ldquoPredicting primary PM25and PM01 trace composition for epidemiological studies inCaliforniardquo Environmental Science amp Technology vol 48 no 9pp 4971ndash4979 2014

[10] J Hu H Zhang S Chen et al ldquoIdentifying PM25 and PM01sources for epidemiological studies in Californiardquo Environmen-tal Science amp Technology vol 48 no 9 pp 4980ndash4990 2014

[11] J Hu C J Howard F Mitloehner P G Green and M JKleeman ldquoMobile source and livestock feed contributions toregional ozone formation in central Californiardquo EnvironmentalScience amp Technology vol 46 no 5 pp 2781ndash2789 2012

[12] J D Herner J Aw O Gao D P Chang and M J KleemanldquoSize and composition distribution of airborne particulatematter inNorthern California Imdashparticulatemass carbon andwater-soluble ionsrdquo Journal of the Air amp Waste ManagementAssociation vol 55 no 1 pp 30ndash51 2005

[13] J J Deng K Du K Wang C-S Yuan and J Zhao ldquoLong-term atmospheric visibility trend in Southeast China 1973ndash2010rdquo Atmospheric Environment vol 59 pp 11ndash21 2012

[14] J L Hu YWang Q Ying and H Zhang ldquoSpatial and temporalvariability of PM25 and PM10 over the North China Plain andthe Yangtze River Delta Chinardquo Atmospheric Environment vol95 pp 598ndash609 2014

[15] M Lin J Tao C-Y Chan et al ldquoRegression analyses betweenrecent air quality and visibility changes in megacities at fourhaze regions in Chinardquo Aerosol and Air Quality Research vol12 no 6 pp 1049ndash1061 2012

[16] X J Deng X Tie D Wu et al ldquoLong-term trend of visibilityand its characterizations in the Pearl River Delta (PRD) regionChinardquo Atmospheric Environment vol 42 no 7 pp 1424ndash14352008

[17] K Huang G Zhuang Y Lin et al ldquoHow to improve the airquality overmegacities in China pollution characterization andsource analysis in Shanghai before during and after the 2010World ExpordquoAtmospheric Chemistry and Physics vol 13 no 12pp 5927ndash5942 2013

[18] Z Cheng S Wang J Jiang et al ldquoLong-term trend of hazepollution and impact of particulate matter in the Yangtze RiverDelta Chinardquo Environmental Pollution vol 182 pp 101ndash1102013

[19] J Hu H Zhang Q Ying S-H Chen F Vandenberghe andM J Kleeman ldquoLong-term particulate matter modeling forhealth effect studies in Californiamdashpart 1 model performanceon temporal and spatial variationsrdquoAtmospheric Chemistry andPhysics vol 15 no 6 pp 3445ndash3461 2015

[20] C K Chan and X Yao ldquoAir pollution in mega cities in ChinardquoAtmospheric Environment vol 42 no 1 pp 1ndash42 2008

[21] K B He F Yang Y Ma et al ldquoThe characteristics of PM25 inBeijing Chinardquo Atmospheric Environment vol 35 no 29 pp4959ndash4970 2001


[22] W Huang J Tan H Kan et al ldquoVisibility air quality and dailymortality in Shanghai Chinardquo Science of the Total Environmentvol 407 no 10 pp 3295ndash3300 2009

[23] X G Liu J Li Y Qu et al ldquoFormation and evolutionmechanism of regional haze a case study in the megacityBeijing Chinardquo Atmospheric Chemistry and Physics vol 13 no9 pp 4501ndash4514 2013

[24] Y Sun Q Jiang Z Wang et al ldquoInvestigation of the sourcesand evolution processes of severe haze pollution in Beijing inJanuary 2013rdquo Journal of Geophysical Research Atmospheres vol119 no 7 pp 4380ndash4398 2014

[25] DChang Y Song andB Liu ldquoVisibility trends in sixmegacitiesin China 1973ndash2007rdquo Atmospheric Research vol 94 no 2 pp161ndash167 2009

[26] X J Zhao P S Zhao J Xu et al ldquoAnalysis of a winter regionalhaze event and its formation mechanism in the North ChinaPlainrdquo Atmospheric Chemistry and Physics vol 13 no 11 pp5685ndash5696 2013

[27] Y R Yang X G Liu Y Qu et al ldquoCharacteristics and formationmechanism of continuous hazes in China a case study duringthe autumn of 2014 in the North China Plainrdquo AtmosphericChemistry and Physics vol 15 no 14 pp 8165ndash8178 2015

[28] J J Deng T Wang Z Jiang et al ldquoCharacterization of visibilityand its affecting factors over Nanjing Chinardquo AtmosphericResearch vol 101 no 3 pp 681ndash691 2011

[29] LGaoG Jia R Zhang et al ldquoVisual range trends in theYangtzeRiver Delta Region of China 1981ndash2005rdquo Journal of the Air ampWasteManagement Association vol 61 no 8 pp 843ndash849 2011

[30] G Peng X Wang Z Wu et al ldquoCharacteristics of particulatematter pollution in the Pearl River Delta region China anobservational-based analysis of two monitoring sitesrdquo Journalof Environmental Monitoring vol 13 no 7 pp 1927ndash1934 2011

[31] China NBoSo China City Statistical Yearbook 2012 ChinaStatistics Press Beijing China 2013

[32] MEP China National Ambient Air Quality Standards MEPBeijing China 2012

[33] Q Jiang Y L Sun Z Wang and Y Yin ldquoAerosol compositionand sources during the Chinese Spring Festival fireworkssecondary aerosol and holiday effectsrdquo Atmospheric Chemistryand Physics vol 15 no 11 pp 6023ndash6034 2015

[34] Y Wang Q Ying J Hu and H Zhang ldquoSpatial and temporalvariations of six criteria air pollutants in 31 provincial capitalcities in China during 2013-2014rdquo Environment Internationalvol 73 pp 413ndash422 2014

[35] Y Miao X-M Hu S Liu et al ldquoSeasonal variation of localatmospheric circulations and boundary layer structure in theBeijing-Tianjin-Hebei region and implications for air qualityrdquoJournal of Advances in Modeling Earth Systems vol 7 no 4 pp1602ndash1626 2015

[36] X-M Hu Y ZhangM Z Jacobson and C K Chan ldquoCouplingand evaluating gasparticle mass transfer treatments for aerosolsimulation and forecastrdquo Journal of Geophysical Research DAtmospheres vol 113 no 11 2008

[37] D J Nowak S Hirabayashi A Bodine and R Hoehn ldquoMod-eled PM

25removal by trees in ten US cities and associated

health effectsrdquo Environmental Pollution vol 178 pp 395ndash4022013

[38] H Zhang Y Wang J Hu Q Ying and X Hu ldquoRelationshipsbetween meteorological parameters and criteria air pollutantsin three megacities in Chinardquo Environmental Research vol 140pp 242ndash254 2015

[39] I Gultepe and J A Milbrandt ldquoProbabilistic parameterizationsof visibility using observations of rain precipitation rate relativehumidity and visibilityrdquo Journal of Applied Meteorology andClimatology vol 49 no 1 pp 36ndash46 2010

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


Hefei Shanghai

Guangzhou

Beijing

Xirsquoan

Figure 1 Location of Hefei city as marked by the red rectangle

The government of China started routinely monitoringPM10 sulfur dioxide (SO

2) and nitrogen dioxide (NO

2) in

Hefei in June 2000 Routinemeasurement of PM25

was intro-duceduntil January 2013 andno routinemeasurement of TSPwas available in Hefei Therefore long-term trends analysisis only feasible for PM

10in Hefei In this study analysis of

twelve-year trends of PM10and visibility in Hefei during the

period of 2001ndash2012 was performed The study investigatedthe general patterns of PM

10and visibility trends in Hefei

over the recent twelve-year period by analyzing the seasonaland annual behavior of PM

10and visibility In addition the

meteorological factors that may affect PM10

pollution andvisibility were also examined The results provide a generalunderstanding of the long-term PM

10pollution and visibility

characteristics which can be served as a basic data supportfor local government to further mitigate the environmentpollution and to improve air quality control plans for the city

2 Materials and Methods

21 Study Areas Hefei (center 1171910158403710158401015840 314410158405510158401015840) is thecapital city of Anhui province located in the east center ofChina about 1000 km south to the national capital city ofBeijing and 450 km west to the city of Shanghai (Figure 1)Hefei is the largest city and the political economic andcultural center ofAnhui provinceHefei has a total populationof about 8 million and near 5 million inhabitants reside in itsmetropolitan area in 2012 [31] Hefei has a GDP of 416 billionChinese currency ranked number 1 in Anhui province andnumber 31 in China in 2012 [31] The main industry includesmachinery electronics chemistry steel textile and cigaretteindustries Hefei has been identified by The Economist inthe December 2012 as worldrsquos number 1 fastest growingmetropolitan economy (httpwwweconomistcomnode21567579)

22 Data Source Daily air pollution index (API) and themajor pollutant data during June 2000 to January 2013 inHefei were downloaded from the website of the Ministry of

Table 1The bottom and upper limit of API values and correspond-ing PM

10concentrations

API PM10concentrations (120583gmminus3)

119868bottom 119868upper 119862bottom 119862upper0 50 0 5050 100 50 150100 200 150 350200 300 350 420300 400 420 500400 500 500 600

Environmental Protection of the Peoplersquos Republic of ChinaData Center (httpdatacentermepgovcn) Multiple siteshave been built up inHefei (4 sites in 2000 and then graduallyexpanded to 9 sites with the expansion of the city by 2010)The monitoring sites are all located in the urban area Eventhough ambient concentrations of PM

10 NO2 and SO

2

have been routinely monitored at multiple sites the datawebsite only publishes city-average API values (averagedover all sites) The complete data in 2001ndash2012 were thereforeanalyzed in this study Daily API values were estimated basedon the ambient concentrations of PM

10 NO2 and SO

2

First sub-API (ie API of one specific pollutant) values wereestimated for PM

10 NO2 and SO

2 respectively and then the

maximum sub-API value was determined as the daily APIand the associated pollutant was determined as the majorpollutant In Hefei PM

10was the major pollutants on all the

pollution days in 2001ndash2012 (httpdatacentermepgovcnreportair dailyair dairy aqijsp) Therefore daily PM

10

mass concentrations were converted back from API valuesusing the following

119862 = (119868 minus 119868bottom) times119862upper minus 119862bottom119868upper minus 119868bottom

+ 119862bottom (1)

where 119862 is the PM10

concentration and 119868 is the API value119868upper and 119868bottom are the upper and bottom limit values for 119868(ie 119868bottom le 119868 lt 119868upper) 119862upper and 119862bottom are the upperand bottom limit concentrations corresponding to 119868upper and119868bottom Table 1 shows the values of 119868bottom 119868upper 119862bottom and119862upper

The meteorological observation data in 2001ndash2012 wereobtained from the National Climate Data Center (NCDC)(ftpftpncdcnoaagovpubdatanoaa) The meteorologi-cal data includes hourly surface observations of air temper-ature dew point temperature wind speed wind directionprecipitation Relative humidity was estimated using the tem-perature and dew point temperature Hourly meteorologicalparameters then were averaged to daily values to investigatetheir correlations to daily PM

10and visibility

3 Results and Discussion

31 PM10 Trends Figure 2(a) displays the long-term trends ofthe PM

10concentrations inHefei during the period from2001

to 2012 The statistical results for each year were computed


0

100

200

300

400

500

600

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

PM10

(120583g m

minus3)

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

(a)

30

120

90

60

150

180

210

240

300

270

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

PM10

(120583g m

minus3)


(b)







10







10concentration was




10(50 120583gmminus3) [32]













10










10concentrations


0306090

120150180210240270300330360

Day

s

Year20

12

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

gt200


50ndash1000ndash50



10concentration

unit 120583gmminus3







020406080

100120140160180200220240

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

SpringSummer

FallWinter

PM10

(120583g m

minus3)










0

5

10

15

20

25

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

Visib

ility

(km

)

(a)

2

4

6

8

10

12

16

14

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Visib

ility

(km

)


(b)


20

25

30

35

40

45

50

Visi

bilit

y (

)

0

5

10

15

20

25

30

35

40

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011




lt5kmgt10km










10



10concentration





10concentrations



020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40


VisibilityPM10

(a)

Wind speed (ms)

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

1 2 3 4 5 6 70

VisibilityPM10

(b)

0

20

40

60

80

100

120

140

160

180

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)


Visibility

0 45 90 135 180 225 270 315

PM10

(c)


020406080100120140160

20

468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

gt50

0ndash05

05

ndash1

1ndash3

3ndash5

5ndash10

10

ndash20

20

ndash50

VisibilityPM10

(d)


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

VisibilityPM10

(e)





(a)


(b)




PM10







10concentrations




PM10






PM10




10 The fact that







10pollution and


4 Conclusions



10


10concentrations


10concen-


(ie the extremePM10

















Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0

100

200

300

400

500

600

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

PM10

(120583g m

minus3)

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

(a)

30

120

90

60

150

180

210

240

300

270

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

PM10

(120583g m

minus3)


(b)







10







10concentration was




10(50 120583gmminus3) [32]













10










10concentrations


0306090

120150180210240270300330360

Day

s

Year20

12

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

gt200


50ndash1000ndash50



10concentration

unit 120583gmminus3







020406080

100120140160180200220240

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

SpringSummer

FallWinter

PM10

(120583g m

minus3)










0

5

10

15

20

25

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

Visib

ility

(km

)

(a)

2

4

6

8

10

12

16

14

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Visib

ility

(km

)


(b)


20

25

30

35

40

45

50

Visi

bilit

y (

)

0

5

10

15

20

25

30

35

40

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011




lt5kmgt10km










10



10concentration





10concentrations



020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40


VisibilityPM10

(a)

Wind speed (ms)

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

1 2 3 4 5 6 70

VisibilityPM10

(b)

0

20

40

60

80

100

120

140

160

180

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)


Visibility

0 45 90 135 180 225 270 315

PM10

(c)


020406080100120140160

20

468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

gt50

0ndash05

05

ndash1

1ndash3

3ndash5

5ndash10

10

ndash20

20

ndash50

VisibilityPM10

(d)


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

VisibilityPM10

(e)





(a)


(b)




PM10







10concentrations




PM10






PM10




10 The fact that







10pollution and


4 Conclusions



10


10concentrations


10concen-


(ie the extremePM10

















Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0306090

120150180210240270300330360

Day

s

Year20

12

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

gt200


50ndash1000ndash50



10concentration

unit 120583gmminus3







020406080

100120140160180200220240

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

SpringSummer

FallWinter

PM10

(120583g m

minus3)










0

5

10

15

20

25

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

Visib

ility

(km

)

(a)

2

4

6

8

10

12

16

14

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Visib

ility

(km

)


(b)


20

25

30

35

40

45

50

Visi

bilit

y (

)

0

5

10

15

20

25

30

35

40

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011




lt5kmgt10km










10



10concentration





10concentrations



020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40


VisibilityPM10

(a)

Wind speed (ms)

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

1 2 3 4 5 6 70

VisibilityPM10

(b)

0

20

40

60

80

100

120

140

160

180

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)


Visibility

0 45 90 135 180 225 270 315

PM10

(c)


020406080100120140160

20

468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

gt50

0ndash05

05

ndash1

1ndash3

3ndash5

5ndash10

10

ndash20

20

ndash50

VisibilityPM10

(d)


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

VisibilityPM10

(e)





(a)


(b)




PM10







10concentrations




PM10






PM10




10 The fact that







10pollution and


4 Conclusions



10


10concentrations


10concen-


(ie the extremePM10

















Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0

5

10

15

20

25

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Maximum value

75th percentile


Average value

Standard deviation

Minimum value

Visib

ility

(km

)

(a)

2

4

6

8

10

12

16

14

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Visib

ility

(km

)


(b)


20

25

30

35

40

45

50

Visi

bilit

y (

)

0

5

10

15

20

25

30

35

40

Year

2012

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011




lt5kmgt10km










10



10concentration





10concentrations



020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40


VisibilityPM10

(a)

Wind speed (ms)

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

1 2 3 4 5 6 70

VisibilityPM10

(b)

0

20

40

60

80

100

120

140

160

180

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)


Visibility

0 45 90 135 180 225 270 315

PM10

(c)


020406080100120140160

20

468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

gt50

0ndash05

05

ndash1

1ndash3

3ndash5

5ndash10

10

ndash20

20

ndash50

VisibilityPM10

(d)


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

VisibilityPM10

(e)





(a)


(b)




PM10







10concentrations




PM10






PM10




10 The fact that







10pollution and


4 Conclusions



10


10concentrations


10concen-


(ie the extremePM10

















Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40


VisibilityPM10

(a)

Wind speed (ms)

020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

1 2 3 4 5 6 70

VisibilityPM10

(b)

0

20

40

60

80

100

120

140

160

180

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)


Visibility

0 45 90 135 180 225 270 315

PM10

(c)


020406080100120140160

20

468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

gt50

0ndash05

05

ndash1

1ndash3

3ndash5

5ndash10

10

ndash20

20

ndash50

VisibilityPM10

(d)


020406080100120140160180200

2468

1012141618202224262830

Visib

ility

(km

)

PM10

(120583g m

minus3)

minus20

minus40

VisibilityPM10

(e)





(a)


(b)




PM10







10concentrations




PM10






PM10




10 The fact that







10pollution and


4 Conclusions



10


10concentrations


10concen-


(ie the extremePM10

















Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



(a)


(b)




PM10







10concentrations




PM10






PM10




10 The fact that







10pollution and


4 Conclusions



10


10concentrations


10concen-


(ie the extremePM10

















Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in












Acknowledgments


References




















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in










Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

Documents

Research Article Twelve-Year Trends of PM and Visibility ...sese.nuist.edu.cn/TeacherFiles/file/20170820/... · twelve-year trends of PM 10 and visibility in Hefei during the period