Characteristics of pollutants and their correlation to … · 2020. 7. 31. · pendence on wind, providing information on regional pollu-tion characteristics. ... (Ran et al., 2009;

Atmos. Chem. Phys., 11, 4353–4369, 2011www.atmos-chem-phys.net/11/4353/2011/doi:10.5194/acp-11-4353-2011© Author(s) 2011. CC Attribution 3.0 License.

AtmosphericChemistry

and Physics

Characteristics of pollutants and their correlation to meteorologicalconditions at a suburban site in the North China Plain

W. Y. Xu1, C. S. Zhao1, L. Ran1, Z. Z. Deng1, P. F. Liu1, N. Ma1, W. L. Lin 2, X. B. Xu2, P. Yan2, X. He3, J. Yu4,*,W. D. Liang4, and L. L. Chen4

1Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China2Key Laboratory for Atmospheric Chemistry, Centre for Atmosphere Watch and Services, Chinese Academy ofMeteorological Sciences, China Meteorological Administration, Beijing, China3Aviation Meteorological Center, Air Traffic Management Bureau, Civil Aviation Administration of China, Beijing, China4Wuqing Meteorological Bureau of Tianjin, China* now at: Tanggu Meteorological Bureau of Tianjin, China

Received: 11 December 2010 – Published in Atmos. Chem. Phys. Discuss.: 2 March 2011Revised: 29 April 2011 – Accepted: 2 May 2011 – Published: 11 May 2011

Abstract. North China Plain (NCP) is one of the mostdensely populated regions in China and has experiencedenormous economic growth in the past decades. Its regionaltrace gas pollution has also become one of the top environ-mental concerns in China. Measurements of surface tracegases, including O3, NOx, SO2 and CO were carried outwithin the HaChi (Haze in China) project at Wuqing Me-teorology Station, located between 2 mega-cities (Beijingand Tianjin) in the NCP, from 9 July 2009 to 21 January2010. Detailed statistical analyses were made in order to pro-vide information on the levels of the measured air pollutantsand their characteristics. Gaseous air pollutant concentra-tions were also studied together with meteorological data andsatellite data to help us better understand the causes of theobserved variations in the trace gases during the field cam-paign. In comparison to measurements from other rural andbackground stations in the NCP, relatively high concentra-tions were detected in Wuqing, presumably due to regionalmixing and transport of pollutants. Local meteorology haddeterministic impacts on air pollution levels, which have tobe accounted for when evaluating other effects on pollutantconcentrations. Trace gas concentrations showed strong de-pendence on wind, providing information on regional pollu-tion characteristics. O3 mixing ratio also showed clear de-pendencies on temperature and relative humidity.

Correspondence to:C. S. Zhao([email protected])

1 Introduction

Economic reforms since 1978 have brought rapid develop-ments for China. With them came increased emissions ofair pollutants, environmental problems and health concerns,caused by industries, power plants, vehicles and other needsfor combustion of fuel (Kan and Chen, 2004; Hao and Wang,2005; Shao et al., 2006).

Carbon monoxide (CO), nitrogen oxides (NOx) and sul-phur dioxide (SO2) are all trace gases in the atmosphereand primary pollutants emitted from anthropogenic activi-ties (Kato and Akimoto, 1994; Streets and Waldhoff, 2000).Emitted mainly by combustion sources and having relativelylonger atmospheric lifetime, CO is also an ideal tracer foranthropogenic pollution, facilitating the interpretation of theconcentrations of other pollutants (Parrish et al., 1993, 1998;Wang et al., 1996, 1997; Jaffe et al., 1997). NOx, however,has a very short lifetime and is mainly emitted through fos-sil fuel burning. Additionally, CO and NOx are precursorsof ozone (O3), which is the most important secondary pol-lutant in the atmosphere (Jenkin et al., 2000). O3 is a majorcomponent of photochemical smog, and can be hazardous tovegetation, materials and human health (PORG, 1997). SO2is also an important trace gas. Its oxidation can lead to aciddeposition and also contributes to the formation of sulphateaerosols (Meagher et al., 1978; Saxena and Seigneur, 1987),which in turn will have impacts on the solar radiation andphotochemistry (Dickerson et al., 1997). SO2 levels are typ-ically very high, especially in North China, where domesticheating during winter largely relies on coal combustion.

Published by Copernicus Publications on behalf of the European Geosciences Union.

http://creativecommons.org/licenses/by/3.0/

4354 W. Y. Xu et al.: Characteristics of pollutants in the North China Plain

Mega-cities in China commonly suffer from severe air pol-lution (Ran et al., 2009; Liu et al., 2009). Neighbouring re-gions, especially downwind regions, are typically envelopedby regional pollution. One of the most severely polluted ar-eas in the world is the North China Plain (NCP) region (vanDonkelaar et al., 2010), in which there are two of the mostheavily populated mega-cities in China, Beijing and Tian-jin. Concerns were raised during preparation for the 2008Summer Olympic Games in Beijing and numerous studieshave been done since then (e.g., Xu et al., 2005; Ding etal., 2008; Lin et al., 2008, 2009; Wang et al., 2009). It wasfound that, since winter 2007, there were improvements inthe overall combustion efficiency (Wang et al., 2010). Chanet al. (2008) reported decreasing trends for the concentra-tions of SO2 (from 120 µg m−3 to 50 µg m−3) and CO (from3.3 mg m−3 to 2.0 mg m−3) in Beijing for the period of 1998to 2005, while NO2 emissions did not vary. Nevertheless,pollution events still often occurred in urban and surround-ing areas. For example, a maximum 1-h O3 mixing ratio of286 ppbv was reported in a mountainous area north of Bei-jing and attributed to a polluted plume from urban Beijing(Wang et al., 2006). Such pollution episodes are commonlycaused by both the emissions of primary pollutants and theaccompanied weather conditions.

Regional and local scale meteorology influences pollutionin different ways. Large scale weather patterns determine at-mospheric stability, large scale circulations, temperature ad-vection, humidity and cloud formation, which all have greatimpacts on the mixing scale of various pollutants and the for-mation of secondary air pollutants. Recent research revealsthat synoptic pressure patterns and their evolution are themain causes of regional air pollution processes in the NCP(Chen et al., 2008). High pressure and successive low pres-sure systems were associated with the formation of air pol-lution, and pressure systems with strong gradients led to de-creases of the Air Pollution Index (API). Modelling studiesalso confirmed that summertime high pressure systems canturn the East China Plains into a “basin” of ozone pollution(Zhao et al., 2009). Since emissions are almost constant dur-ing a given season, it is the meteorological pattern that deter-mines whether heavy pollution can form on a regional scale.Local meteorological parameters are not always consistentwith those on a larger scale, but they also have substantialinfluence on air pollution. In fact, there are several local me-teorological factors that can affect both regional and localconcentrations of pollutants. Wind speed can alter the dis-persion state of the atmosphere (Prosmitis et al., 2003; Ulaset al., 2006; Jones et al., 2010), while wind directions pro-vide information on the transport of pollutants (Lin et al.,2008). In regard to chemical reactions and transformations,temperature, solar radiation and humidity conditions are themost crucial factors (Korsog and Wolff, 1991; Greene et al.,1999). However, no clear linear relationships could be foundbetween meteorological parameters (i.e., wind speed, ultra-violet radiation, or temperature) and the concentration of pol-

lutants (Liu et al., 1994). Moreover, vertical distribution ofpollutants can be modified by local circulations (Chen et al.,2009). Thus, it becomes highly necessary for setting up airquality management strategies, to know the relationships be-tween meteorological factors and trace gases concentrations.

In recent years, in-situ measurements of atmospheric tracegas pollutants in the NCP were mostly made at rural sites(Gao et al., 2005; Lin et al., 2008, 2009; Wang et al., 2006,2008) or in central Beijing (Tang et al., 2009). Few obser-vations were made in between the city clusters. The interac-tions between the metropolitan areas are still unknown. Forthis study, we set up an observation site at a suburban site inbetween Beijing and Tianjin, designed to acquire more infor-mation on regional transport of pollutants between the twomega-cities by analysing the relationship between meteoro-logical parameters (i.e. wind speed, wind direction, tempera-ture, humidity, etc.) and local pollutant concentrations.

2 Data and methodology

2.1 Site

The measurements were done at the Wuqing MeteorologicalStation (39◦22′58.8′′ N 117◦1′1.2′′ E, 7.4 m a.s.l.). Wuqingis a suburban district, situated in between Beijing and Tian-jin, the two heavily populated megacity centres (about 80 kmto Beijing and 30 km to Tianjin) and surrounded by HebeiProvince, as shown in Fig. 1. The Wuqing Meteorologi-cal Station is located east of large areas of farm fields, westof groups of small factories and northwest of the centre ofWuqing district, Tianjin. Further down to the southeast ofWuqing is the industrial zone of Tianjin, called Tianjin Bin-hai Industrial Area, and the city of Beijing is to the north-western side. Traffic flow near the site is on a very low level,compared to the centres of metropolitans, and there are nolarge emission sources in the surrounding areas nearby. Un-like rural sites that are situated to the north of Beijing, suchas Shangdianzi (SDZ) GAW station or Miyun ObservationSite, Wuqing lies inside the polluted region, but is relativelyclean, compared to the neighbouring mega-cities. Thus allthe above mentioned criteria make Wuqing highly represen-tative of the overall pollution level of the polluted NCP re-gion and a favourable spot for observing transport of air pol-lutants.

2.2 Trace gas measurements

A set of commercial trace gas instruments (Thermo Envi-ronmental Instruments Inc., USA C-series) has been used tocontinuously monitor various trace gases. Surface O3 wasmeasured with a UV photometric analyser (TE 49C), COwith a gas filter correlation analyser (TE 48C), NOx witha chemiluminescence analyser (TE 42CTL) and SO2 with apulsed UV fluorescence analyser (TE 43CTL), from 9 July2009 to 21 January 2010. All the instruments were housed in

Atmos. Chem. Phys., 11, 4353–4369, 2011 www.atmos-chem-phys.net/11/4353/2011/

W. Y. Xu et al.: Characteristics of pollutants in the North China Plain 4355

Fig. 1. Location of the campaign site (Wuqing Meteorology Sta-tion).

an air-conditioned container, with a relatively constant tem-perature. For CO, zero checks are automatically executed ev-ery 6 h; for the other primary gases, multipoint calibrationsand daily zero/span checks were performed according to US-EPA recommendations on quality assurance and quality con-trol, using a dynamic gas calibrator (TE 146C) in combina-tion with a zero air supplier (TE111) and a set of standardreference gas mixtures (National Institute of Metrology, Bei-jing, China). The O3 analyser was calibrated respectively inthe beginning and at the end of the observation, using an O3calibrator (TE 49CPS). Results suggest that the linear driftduring the observation period was less than 0.5 % and couldbe ignored.

Measured ambient concentrations were recorded as 1-minaverage mixing ratios by volume (ppbv). When analysing thestatistical variability, diurnal cycle of trace gases and temper-ature/relative humidity(RH) dependency of ozone, 1-h aver-aged data were used; while for the calculations of trace gaswind dependency, 1-h moving averaged gas concentrationswere employed to equalizing the sampling frequency.

2.3 Determination of trace gas exceedance and HighPollution Days (HPD)

To evaluate the overall pollution level at Wuqing, an ex-ceedance standard was set up as the average trace gas levelplus one standard deviation. For O3, the exceedance levelwas calculated using only the data before the 1 October 2009,while for the primary gas pollutants, only the data after thatdate were used in the determination of the exceedance stan-dard. Calculated exceedance standards for CO, NO, NO2,NOx, SO2 and O3 were respectively 3878, 80, 52, 43, 128and 68 ppbv. The hours with 1-h averaged measurementsexceeding the defined standard were defined as exceedancehours, when total daily exceedance hours reached over 3 h,the day was determined as a High Pollution Day (HPD)in respect to the exceeding trace gas. Monthly exceedance

hour frequency is obtained by dividing the monthly total ex-ceedance hours by the number of hours with valid measure-ments. Similarly HPD frequency is the ratio of monthly to-tal HPDs to the number of days with valid measurements.Monthly Mean Exceedance Amount (MEA) was calculatedas:

MEA=1

hExceedance

∑(mExceedance−mStandard), (1)

Where mExeedanceis the measured 1-h mean mixing ratiowithin a certain month that exceeded the above defined stan-dard (mStandard), andhExceedanceis the monthly total numberof exceedance hours.

2.4 Meteorological data

Meteorological variables were obtained by an AutomaticWeather Station installed at the Wuqing Meteorological Sta-tion. Wind parameters are observed at 10 m height, whiletemperature, pressure and moisture information are collectedat 1.5 m height. The moving averages of wind speed andwind direction were calculated over a span of 2 h, since fluc-tuations in wind directions are less representative of trans-ports from those directions. Average wind speed is calcu-lated both using arithmetic and vector mean methods. Thearithmetic mean wind speed WSa is greater than the vectormean WSv. The more consistent the wind direction, the moreWSv tends towards WSa. Thus when analysing the wind de-pendency of various pollutants, only the data with relativelycontinuous wind directions will be considered, using a cri-terion of WSv/WSa> 0.95. 2-h moving averaged wind datawere used for the wind frequency rose, without taking intoaccount the continuity of wind directions. Wind directionsin this work are referred to as the directions the winds arecoming from. NCEP FNL (Final) Operational Global Anal-ysis data from 9 July 2009 to 21 January 2010 were used tosupplement the analysis of regional weather patterns.

2.5 Evaluation of trace gas wind dependency

To determine the effect of wind speed and wind direction onvarious trace gas concentrations, two methods have been ap-plied. In the first method, wind speed and wind direction aredivided into bins of 0.5 m s−1 × 10◦. Trace gas concentra-tions (60-min moving averaged) are sorted into those bins,with the aid of simultaneous meteorological data. Samplesin each bin were averaged and plotted on wind dependencemaps, to display the overall variations of trace gas levels indifferent wind directions and with varying wind speeds. Toavoid the influence of seasonal variations, wind dependencemaps are separately drawn for different seasons.

The above method still only provides information on theaverage variation. Data in each bin may show large variabil-ity, due to other factors that also influence the pollutant con-centrations. To be able to quantify the degree of influence, a

www.atmos-chem-phys.net/11/4353/2011/ Atmos. Chem. Phys., 11, 4353–4369, 2011


second method is applied. Similar to the above, 60-min mov-ing averaged gas pollutant concentrations were first dividedaccording to seasons into 3 parts, respectively representingsummer (15 July–31 August 2009), fall (1 September–30November 2009) and winter (1 December 2009–21 January2010). Then for each season, the 25th and 75th percentilesof the given gas species were calculated. Trace gas concen-trations below the 25th percentile value are defined as “rel-atively clean” and concentrations above the 75th percentilevalue as “relatively polluted”. According to different windspeed and direction, data are ordered into bins, this time witha resolution of 1 m s−1× 45◦. In each bin two frequencies arecalculated as follows:

f75 (Gas, Season, WS, WD)

=n([Gas]iSeason, iWS, iWD> 75 percentile[Gas]iSeason)

n([Gas]iSeason, iWS, iWD)(2)

f25(Gas, Season, WS, WD)

=n([Gas]iSeason, iWS, iWD < 25 percentile[Gas]iSeason)

n([Gas]iSeason, iWS, iWD), (3)

where iSeason=summer, fall, winter; iWS= 0–1, 1–2,. . . ,12–13 m s−1; iWD = S, SW, W, NW, N, NE, E, SE;n(condition) is the number of data samples fulfilling theconditions given in the parentheses. Calculations were per-formed for CO, SO2, NOx, O3.

f75 reflects the ratio of data in a given bin that exceedsthe overall 75th percentile gas concentration in a certain sea-son, representing a probability of occurrence of the “rela-tively polluted” state under a particular wind direction andwind speed. Similarly,f25 can be interpreted as the proba-bility of the “relatively clean” state to occur under given winddirection and wind speed.

To quantify how much each wind direction contributes tothe concentration level of various trace gases, it is inaccu-rate to simply subtract the average concentrations of all thebins by a background concentration, due to large standarddeviations on both sides. But with the result of the secondmethod, we can determine by how much a certain wind di-rection and wind speed increases the occurrence probabil-ity of the “relatively polluted” state. As it will be shown inSect. 3.5.1, winds from the north show the lowest frequencyof polluted conditions, thus is determined as a background.The frequency increment (or probability increment) of the“relatively polluted” state is calculated as:

1f75= f75(iGas, iSeason, iWS, iWD)

−f75(iGas, iSeason, iWS,N), (4)

representing how much a certain wind direction and windspeed increases or decreases the occurrence frequency of pol-luted conditions.

2.6 Satellite data

Four satellite datasets were used provide a view of the re-gional distribution of pollutants in the NCP region. Mea-surements of Pollution in the Troposphere (MOPITT),Ozone Measuring Instrument (OMI) and Moderate Resolu-tion Imaging Spectroradiometer (MODIS) are instrumentsmounted on NASA’s EOS Terra spacecraft. The MODIS in-strument is also operating on NASA’s EOS Aqua Spacecraft.MOPITT is designed to measure global distributions of car-bon monoxide (CO) in the troposphere, providing data oncea day. Horizontal resolutions can reach up to 22km, verticalresolution up to 3 km. Level 2 Version 4 CO surface mixingratio data of 1 March 2009 to 28 February 2010 were aver-aged into 0.25◦ × 0.25◦ grids in this study. From OMI, NO2and SO2 columns can be retrieved, with nadir view pointreaching the resolution of 13× 24 km. The OMI instrumenthas several cross-track anomalies, which were ruled out forboth datasets. Level 2 OMI NO2 tropospheric column of theperiod mentioned above was interpolated and averaged into0.25◦ × 0.25◦ grids. Due to reduced OMI sensitivity to SO2in the Planetary Boundary Layer (PBL), Level 2 OMI SO2PBL column amount product can be used only under optimalviewing conditions, which require radiative cloud fraction


4050

50

50

50

60

6060

60

60

70

70

70

70

70

80

Wuqing

(a1)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

1440

1450

1460

1460

1470 1480

1490

Wuqing

(b1)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

3040

3060

3080

3100

3120

Wuqing

(c1)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

130

130

140

150

150

160

160

170170

Wuqing

(a2)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

143014401450

146014701480

14901500

1500

1510

1520 Wuqing

(b2)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

29402960

29803000

30203040306030803100

3120

Wuqing

(c2)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

140

150

160

170

180

180

190

190

200

200

210

210

220

230

240

240

Wuqing

(a3)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

13801390

1400141014201430144014501460

1470

1470

1480

1480

1490

1490

1500

1510

1520

1520

Wuqing

(b3)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

28202840286028802900

2920294029602980

3000302030403060

Wuqing

(c3)

100° 105° 110° 115° 120° 125° 130° 135° 30°

35°

40°

45°

50°

Fig. 2. Average Geopotential Height Field (white lines) and Wind Field (black vectors) for 1000 hPa, 850 hPa and 700 hPa (indicatedrespectively bya, b, c) for summer (9 July 2009–31 August 2009), fall (1 September 2009–30 November 2009) and winter (1 December2009–21 January 2009) (numbered as 1, 2, 3) from NCEP FNL (Final) Operational Global Analysis data. The magenta star marks thelocation of the observation site.

ahead of the trough, and thus the dominant wind direction inthe NCP region turns with altitude from NNW to WNW.

In winter, the continental cold high-pressure system be-comes stronger, and the WPSH is pushed further to the southonto the ocean; wind field is similar to that in fall, but the en-hanced high-pressure system resulted in higher average windspeeds in the NCP region.

For the whole measurement period, the lowest surfacepressure was accompanied by the highest surface temper-ature, which occurred in July, with a monthly mean of1002.3 hPa and 299.5 K; while the highest monthly meansurface pressure, 1028.7 hPa, was observed along with thelowest mean surface temperature, 265.1 K, in January. Themonthly mean RH ranged from 59 % to 77 %, with a maxi-mum value in August and a minimum in January.

Figure 3 shows wind roses for summer, fall and winter. Foreach wind rose, the frequency of wind direction is given re-spectively for 4 wind speed ranges: 0–3 m s−1, 3–6 m s−1, 6–9 m s−1, >9 m s−1, using the wind speed and direction dataat 10 m height. In summer, SW wind dominates, especiallyfor wind speeds between 3–6 m s−1; generally wind speed is

low; occasional NW and SE wind may occur, but mostly withwind speed under 3 m s−1. SW wind still frequently occursin fall when the wind speed is below 3 m s−1. Stronger windsmostly come from NNW, also now and then from the ENEdirection. In winter, NNW winds with wind speed between3–9 m s−1 are dominant. Wind speeds above 9 m s−1 alsooccur under NNW directions, which are consistent with thesynoptic wind field. Wind speeds below 3 m s−1 have rela-tively higher frequencies under W to NW and NE directions,but may also be of SW and SE directions from time to time.

3.2 Distributions of pollutants in the NCP

The NCP is a complex polluted region, consisting mainlyof 2 mega-cities (Beijing and Tianjin) and Hebei Province,which encircles the two metropolitan areas. Though variouspollutants show high values in the NCP region, they are re-gionally differently distributed. Figure 4a shows the annual(1 March 2009 to 1 March 2010) average 550 nm AOD distri-bution obtained from MODIS MOD04 and MYD04 dataset.Contour lines of considerably higher AOD values are closedaround densely populated inner city areas of Beijing, Tianjin,



5000 10000

30

210

60

240

90270

120

300

150

330

180

0(a)

10000 20000

30

210

60

240

90270

120

300

150

330

180

0(b)

2500 5000

30

210

60

240

90270

120

300

150

330

180

0(c)

0~3 m/s

3~6 m/s

6~9 m/s

>9 m/s

Fig. 3. Wind frequency rose for summer (9 July 2009–31 August 2009), fall (1 September 2009–30 November 2009) and winter (1 December2009–21 January 2009).

0.2 0.2

0.2

0.20.2

0.2

0.2

0.2

0.2

0.2

0.3

0.30.3

0.3

0.3

0.3

0.3

0.3

0.3

0.3

0.4

0.4

0.4

0.4

0.4

0.5

0.50.5

0.5

0.50.6

0.60.6

0.6

0.6

0.6

0.6

0.6

0.6

0.60.6

0.7

0.7

0.7

0.7

0.7

0.7

0.7

0.8

Handan Jinan

TaiyuanShijiazhuang

BaodingTianjin

TangshanBeijing

Datong

Wuqing

Miyun SDZ GAW

Mt. Tai

(a)

112.5° E 115.0° E 117.5° E 120.0° E

37.5° N

40.0° N

42.5° N

MO

DIS

AO

D

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9200

250

250

300

300

350

350

350

400

400

400

400

400

450

450

450

450

500

500500

550

Handan Jinan

TaiyuanShijiazhuang

BaodingTianjin

TangshanBeijing

Datong

Wuqing

Miyun SDZ GAW

Mt. Tai

(b)

112.5° E 115.0° E 117.5° E 120.0° E

37.5° N

40.0° N

42.5° N

Sur

face

CO

(ppb

)

0

100

200

300

400

500

600

1.5

2

2

2

2

2 2.5

2.5

2.5

2.5

3

3Handan Jinan

TaiyuanShijiazhuang

BaodingTianjin

TangshanBeijing

Datong

Wuqing

Miyun SDZ GAW

Mt. Tai

(c)

112.5° E 115.0° E 117.5° E 120.0° E

37.5° N

40.0° N

42.5° N

SO

2 P

BL

Col

umn

Am

ount

(D.U

.)

0.5

1

1.5

2

2.5

3

3.5

4

5

55

5

5

5

10

10

10 15

15

15

15

20

20

20

20

20

20

2525

25

25

25

25

30

30

Handan Jinan

TaiyuanShijiazhuang

BaodingTianjin

TangshanBeijing

Datong

Wuqing

Miyun SDZ GAW

Mt. Tai

(d)

112.5° E 115.0° E 117.5° E 120.0° E

37.5° N

40.0° N

42.5° N

NO

2 T

ropo

sphe

ric C

olum

n A

mou

nt

(101

5 mol

ec⋅c

m−

2 )

5

10

15

20

25

30

Fig. 4. 1 March 2009–1 March 2010 average distribution of(a) 550 nm AOD (MODIS L2, resolution: 0.1◦ × 0.1◦); (b) CO SurfaceMixing Ratio (MOPITT L2 Version 4, resolution: 0.25◦ × 0.25◦); (c) SO2 Planetary Boundary Layer Column Amount (OMI L2, reso-lution: 0.5◦ × 0.5◦); (d) NO2 Tropospheric Column Amount (OMI L2, resolution: 0.25◦ × 0.25◦) in NCP region.

Shijiazhuang, etc., suggesting severe anthropogenic aerosolpollution. Wuqing is situated between the high AOD centresof Beijing (0.80) and Tianjin (0.94), with a mean AOD of0.65, representing a suburban background state in the NCPregion.

Carbon monoxide surface mixing ratio derived by MO-PITT (Fig. 4b) reveals more severe CO pollution in the south-ern part of the NCP region. A clear high centre of CO tothe ENE direction of Wuqing, where Tangshan is located,was also clearly noted. Interestingly, the belt from Beijing toTianjin shows relatively lower CO concentrations, implyingthat traffic is not a major source to atmospheric CO over theNCP region.

Mean SO2 PBL column amount distribution from OMImainly reflects summertime conditions, due to data filter-ing. As displayed in Fig. 4c, regional high concentrationsare found to the east of Wuqing and two other high centresare respectively in the SW (Handan) and S (Northeast Jinan)direction. Column amounts in Beijing and Wuqing are at theregional background pollution level.

NO2 is short-lived, and therefore its tropospheric columnprovides insight into the emission sources. Although trans-portation plays only a secondary role in the emission ofNOx in China (Zhang et al., 2009), Hao and Wang (2005)pointed out that in Beijing, 74 % of ground NOx originatesfrom vehicular emissions, while power plants and industrial



0

100

200

NO

(pp

bv)

1h NO 24h moving mean NO

0

50

100

NO

2 (p

pbv)

1h NO

224h moving mean NO

2

0

100

O3

(ppb

v)

1h O

324h moving mean O

3

100

200

OX (

ppbv

)

1h O

X24h moving mean O

X

3

6

9

CO

(pp

mv)

1h CO 24h moving mean CO

15 01Aug 15 01Sep 15 01Oct 15 01Nov 15 01Dec 15 01Jan 15 0

50

100

SO

2 (p

pbv)

1h SO

224h moving mean SO

2

Fig. 5. 1-h average and 24-hour moving average NO, NO2, O3, Ox, CO, SO2 mixing ratio time series.

processes only contribute 15 %. The NO2 distribution, asshown in Fig. 4d, reveals strong local pollution in Beijing,Tianjin, Shijiazhuang and Handan; while Tianjin, which iscloser to our site, seems to suffer more severe NO2 pollu-tion than Beijing. Though Wuqing itself does not experienceheavy traffic flows, it is surrounded by severe regional NO2pollution, leading to locally higher concentrations, despiterelatively low local emissions.

3.3 Variability of O 3, NOx, CO and SO2

24-h moving average time series and 1-h data of NO, NO2,O3, Ox, CO and SO2 mixing ratios are shown in Fig. 5. Ingeneral, NOx (NO + NO2), CO and SO2 concentration lev-els are lower during summer than in fall and winter, whilefor O3, concentrations are highest during summer, due toseasonal variations of photochemical O3 formation relatedto UV radiation, temperature, etc. There are several rea-sons behind such seasonal variations. First of all, the mixinglayer height is generally lower in winter than that in summer.The shallower mixing layer is the principal contributor to thehigher concentrations of primary emitted gaseous pollutantsin winter. Secondly, domestic heating starts in the NCP re-gion in November and ends in March. During this period,more combustion of coal leads to higher emissions of SO2,NOx and CO. Thirdly, photochemistry is most active duringsummer, accelerating the transformation of primary gaseouspollutants, whereas in winter, weaker photochemical reac-tions cannot remove the gases as quick as in the warmer sea-sons from the atmosphere. Another cause might be the mete-orological pattern in winter, which often favours of accumu-lation of pollutants. As was shown in Fig. 2, the NCP regionis often dominated by a cold high pressure system with low

surface wind speeds, sometimes also accompanied by sur-face temperature inversion. Those conditions are favourablefor the formation of haze or fog, and usually lead to highlevels of NOx, CO and SO2 due to weak diffusion. Hazydays appear frequently in the NCP region during winter sea-son. Only when Wuqing is behind a trough and Siberian airmoves southward accompanied by high wind speed, do re-gional pollutants get diluted or advected away.

A statistical analysis on the trace gas measurements andobservations from other sites is summarized in Table 1.Mean daytime CO mixing ratio at Wuqing in JA (Julyand August) is 1.1 ppmv (1100 ppbv), which is 500 ppbvhigher than the daytime mean CO level at Miyun (40◦29′ N,116◦46.45′ E, 152 m a.s.l.) in JJA 2006 (Wang et al., 2008).The all-day mean CO, 1.2 ppmv, is respectively 800 and400 ppbv higher than the CO level at Mt. Tai (36◦15′ N,117◦06′ E, 1534 m a.s.l) in JA 2003 (Gao et al., 2005) andSDZ (40◦39′ N, 117◦07′ E, 293.9 m a.s.l.) in JA 2006 (Menget al., 2009). In DJ (December and January), mean CO canreach 2.4± 2.1 ppmv, while monthly mean CO at SDZ dur-ing May 2005 to December 2006 did not exceed 900 ppbv.Seasonal mean SO2 concentrations in Wuqing range from5.7± 6.3 (JA) to 28.5± 6.3 ppbv (DJ), while monthly meanSO2 at SDZ during 2003–2006 vary between 0.1–15.2 ppbv.NOx ranges from 20.4± 12.2 ppbv in JA to 80.8± 65.5 ppbvin DJ, NO2 from 17.9± 8.5 to 35.1± 18.2 ppbv. 2004–2006 July–January monthly mean NO2 at SDZ ranges from5.2 ppbv in July to 19.2 ppbv in December (Lin et al., 2008).In contrast, Mt. Cimone, Italy station reported a mean NOxof 1.15± 0.8 ppbv for June 2000 (Fisher et al., 2003), whichrepresents a continental background NOx level of Europe. Itcan be concluded that primary gas pollutant concentrations atour site are much higher than those reported from clean rural



Table 1. Mean trace gas levels for different seasons and different time of day (using hourly averaged data) and comparisons with literaturedata.

Gases Location Time All-day Daytime (11:00–17:00) Night time (23:00–5:00)

Mean Std Max Mean Std Max Mean Std Max

CO (ppmv) Wuqing JA(2009) 1.2 0.6 4.3 1.1 0.5 3.7 1.3 0.7 4.3Wuqing SON(2009) 1.5 1.4 8.9 1.3 1.4 8.2 1.5 1.3 7.8Wuqing DJ(2009–2010) 2.4 2.1 9.4 1.8 1.8 8.7 2.5 2.2 9.4Miyun JJA (2006)a – – – 0.6 – – – – –Mt. Tai All-day mean(2003): JA: 0.42 ppbv, ON: 0.36 ppbvb

SDZJA (2006)b ∼ 0.7 – – – – – – – –Annual (2006)b 0.74 0.56 3.9 – – – – – –

SO2 (ppbv) Wuqing JA 5.7 6.3 66.1 5.7 5.6 28.3 5.9 6.9 64.4Wuqing SON 15.7 15.4 137.7 18.6 20.0 137.7 13.7 12.6 76.5Wuqing DJ 28.5 22.8 114.2 30.3 26.7 112.4 26.0 21.3 114.2

SDZ Aug(2003)-Dec(2006) monthly mean: 0.1–15.2 ppbvc

NO2 (ppbv) Wuqing JA 17.9 8.5 59.7 12.2 4.9 29.7 21.4 9.6 59.7Wuqing SON 30.1 15.8 95.1 25.5 17.9 95.1 30.0 12.4 63.2Wuqing DJ 35.1 18.2 90.4 30.9 20.0 89.2 35.3 16.2 71.6

SDZ 2004–2006 July–January monthly mean: 5.2–19.2 ppbvd

NOx (ppbv) Wuqing JA 20.4 12.2 113.5 13.3 5.6 36.9 23.4 13.0 96.4Wuqing SON 49.5 43.0 274.4 33.7 31.1 194.0 48.7 38.1 224.6Wuqing DJ 80.8 65.5 268.5 50.6 40.1 195.0 85.2 67.9 252.7

O3 (ppbv) Wuqing JA 45.2 32.5 194.0 64.1 28.3 194.0 23.9 17.3 76.8Wuqing SON 16.1 17.6 87.7 33.5 21.1 87.7 7.6 8.5 45.6Wuqing DJ 10.1 9.4 39.3 15.6 10.2 39.3 8.0 8.4 30.2Miyun JA (2006)a – – – 50.0 – – – – –

SDZ All-day mean (2004-2006): JA: 32.3 ppbv, SON: 27.5 ppbv, DJ: 19.0 ppbvd

a Wang et al. (2008),b Gao et al. (2005),c Meng et al. (2009),d Lin et al. (2008).

or background areas. Nevertheless, their concentrations aremostly on a moderate level during summertime, but due toseasonal variations in solar radiation and temperatures, thereverse is true for O3. O3 concentrations are the highest inJA and the lowest in DJ. Mean summertime ozone concen-trations are 45.2± 32.5 ppbv, while mean wintertime O3 fallsto 10.1± 9.4 ppbv. For the Miyun site, an average daytimeO3 of 50 ppbv during JA 2006 was reported (Wang et al.,2008), while the mean O3 level at the SDZ GAW station wasfound to be 32 ppbv, 28 ppbv, and 19 ppbv for JA, SON, andDJ (2004–2006), respectively (Lin et al., 2008). Comparedwith the ozone level at Wuqing (45, 16, 10 ppbv respectivelyfor JA/SON/DJ), those two sites show lower concentrationsduring summer, but at SDZ, O3 is higher during fall and win-ter. A plausible reason is that during low O3 productivityseasons, ozone in Wuqing is consumed more by primary gaspollutants than in SDZ.

Maximum values of CO, SO2, NO2 and NOx show thatpollution episodes in summer could result in surface concen-trations higher than 4 ppmv, 66 ppbv, 59 ppbv, and 96 ppbv,

respectively, which are all above exceedance standards (seeSect. 2.3). All maximum values of the primary pollutantswere observed during the night, mostly due to PBL pro-cesses and weak chemical consumption during night time.O3, as a secondary gaseous pollutant, is only produced dur-ing daytime under sufficient UV radiation; hence maximumvalues were normally observed during daytime, reaching upto 194 ppbv. Mean daytime O3 concentrations in summer are64 ppbv, while for night time, O3 is consumed by NOx, andmean mixing ratio is reduced to ca. 24 ppbv, but a maximumnight time O3 of 77 ppbv was also observed, which indicatesthat considerable portion of O3, produced in extremely se-vere episodes, could not even be consumed during night time.Photochemistry is still very active in early fall, with decreas-ing temperature and UV radiation flux, photochemistry grad-ually weakens. During wintertime, surface O3 mixing rationever exceeded 39.3 ppbv, while the mean daytime O3 con-centration was around 15.6 ppbv.

Overall, Wuqing is in the regionally polluted NCP re-gion, gaseous pollution levels are much higher than those at



Table 2. Monthly exceedance hour frequency, High Pollution Day (HPD) frequency and Mean Exceeded Amount (MEA) of CO, NO, NO2and O3 (calculation method given in Sect. 2.3).

Month Exceedance Hour/HPD Frequency (%) MEA(ppbv)

CO NO NO2 O3 SO2 CO NO NO2 O3 SO2

Jul 0.4/0 0/0 0/0 30.7/87.0 0/0 83.0 0 0 19.7 0.0Aug 0.6/0 0/0 0.5/0 19.0/54.8 0.4/0 274.6 0 5.9 20.5 18.7Sep 0.4/0 0.4/0 3.2/10.0 5.9/30 0.3/0 858.7 7.6 5.8 6.4 1.5Oct 7.1/12.9 4.4/16.1 9.4/16.1 1.5/3.2 1.8/6.5 1381.2 24.7 7.4 5.6 13.2Nov 13.8/23.3 12.0/36.7 18.0/36.7 0/0 15.6/40 1295.0 34.3 10.1 0 9.3Dec 18.8/38.7 23.9/61.3 17.4/35.5 0/0 21.4/51.6 1132.5 41.4 10.6 0 15.7Jan 28.5/47.6 18.9/42.9 19.7/38.1 0/0 26.2/52.4 1716.4 25.0 7.0 0 18.3

clean background stations. But from satellite observations,Wuqing is relatively clean compared to city centres. Themeasurement results are representative of the average pol-lution level in the NCP region.

To evaluate the severity of different gas pollutions, ex-ceedance hour and HPD frequency of the different gasspecies have been calculated for each month, along with theMEA (Table 2, method given in Sect. 2.3). In summer, O3is the major gaseous pollutant, with 87 % of the days and30.7 % of the total hours exceeding the standards in July.In October, ozone episodes still appeared, but with signif-icantly shorter exceedance frequency and MEA. NO2 andNOx pollution episodes gradually gained in frequency andintensity from July to January. During November–January,HPDs of NO2 take up more than a third of the days; withthe longest exceedance time in January (19.7 %) and largestmean exceeded amount in December (10.6 ppbv). NO ex-ceedances generally are more frequent and stronger thanNO2 exceedances during November–January, with the high-est frequency (61.3 % of all days and 23.9 % of total hours)and largest MEA (41.4 ppbv) in December. Only October-January experienced CO and SO2 HPDs, with HPD occur-rence frequencies ranging from 12.9 to 47.6 % and from6.5 to 52.4, respectively, with MEAs ranging from 1.4 to1.7 ppmv and from 9.3 to 18.3, respectively. Main gaseouspollutants are O3 in summer and NO2 during winter, which issimilar to the pollution characteristics of Beijing (Chan andYao, 2008).

3.4 Diurnal variations of trace gases and wind speed

Figure 6 shows the diurnal variations of CO, SO2, NO,NO2, NOx, O3 mixing ratio and wind speed during summer(15 July 2009–31 August 2009), fall (1 September 2009–30November 2009) and winter (1 December 2009–21 January2010).

CO shows a morning peak at 09:00 a.m. and an eveningpeak at 09:00 p.m., low during daytime and high duringnight-time. The traffic in Wuqing is relatively sparse, es-pecially during nighttime, thus CO emissions from vehicle

0

2

4

6

8

CO

(pp

mv)

(a1) (a2) (a3)

0

20

40

60

80

SO

2(p

pb

v)

(b1) (b2) (b3)

0

50

100

150

NO

(pp

bv)

(c1) (c2) (c3)

0

20

40

60

80

NO

2(p

pb

v)

(d1) (d2) (d3)

0

50

100

150

200

250

NO

X(p

pb

v)

(e1) (e2) (e3)

0

50

100

O3

(pp

bv)

(f1)

Hour

(f2)

Hour

(f3)

01 04 07 10 13 16 19 220

2

4

6

8

Local Time

Win

d V

elo

city

(m⋅s

−1)

(g1)

01 04 07 10 13 16 19 22

Local Time

(g2)

01 04 07 10 13 16 19 22

Local Time

(g3)

Fig. 6. Diurnal variation of CO(a), SO2 (b), NO (c), NO2 (d), NOx(e) and O3 (f) mixing ratio during summer (1), fall (2) and winter(3). The blue cross represents the mean value, while the red barstands for the median value. The black boxes and whiskers denotethe 5, 25, 75 and 95th percentiles.

exhaust mostly occur during daytime. In fall and winter, do-mestic heating could result in higher CO emissions duringnight-time. Aside from the variation in emissions, this di-urnal pattern is high probably caused by the diurnal varia-tion of the PBL height and wind speed. Zhang et al. (2006)used sounding measurements of a suburban site of Beijing



to determine the PBL height in autumn. Results show thatin autumn, the PBL height starts increasing after 07:00 a.m.,reaching a maximum around 02:00–03:00 p.m. and starts todecrease afterwards until 09:00 p.m. It can be assumed thatin a vast plain region, the boundary layer characteristics aresimilar. The evening peak of CO is weaker during summer,because the collapse of the boundary layer might be later intime compared with fall and winter. In summer, wind speeddecreases after 06:00 p.m. and reaches its lowest value aftermidnight, whereas in fall and winter, a low has been reachedalready at 08:00 and 07:00 p.m. (Fig. 6g1–g3), favouring theaccumulation of gases.

SO2 shows a slightly different pattern from that of CO.With the rise of the boundary layer, SO2 gains in concen-tration reaching a peak at 09:00–11:00 a.m., then decreasesuntil 05:00 p.m. A weak late evening peak can be seen be-tween 09:00–12:00 p.m., which is more significant in winterthan in summer. The same phenomenon has been observedat the SDZ GAW station and at Gucheng, a rural site south-west of Beijing (Lin et al., 2008, 2009), with a peak aroundnoon. The increase of SO2 concentration with the develop-ment of the boundary layer suggests that the upper air maycontain higher concentrations of SO2 than the near surfacelayer. Stronger turbulence will cause stronger vertical mix-ing, thus leading to increased mixing ratios. Lin et al. (2008)pointed out that possible sources could be tall chimneys offactories and power plants.

Diurnal variations of NOx concentrations are under thestrong influence of its emission characteristics, but it seemsto be affected by boundary layer processes as well. The diur-nal variation pattern of NOx resembles to that of CO, withenhanced morning (08:00 a.m.) and evening (07:00 p.m.)peaks, due to the combined effect of daytime traffic emis-sions and PBL variations. As mentioned before, local trafficis relatively sparse, thus rush hour peaks are unpronounced.Apart from the above mentioned factors, NO, NO2 diurnalchanges are also determined by photochemistry, particularlyin summer. In summer NO is rapidly converted to NO2,showing only a weak morning peak; while in winter, NOdominates because its oxidization is slow and incomplete,thus the evening peak was observed more clearly. NO2, how-ever, shows a stronger evening peak in all seasons. The pat-tern is almost the same, with slightly higher concentrationsin winter.

On average, O3 peaks were observed at 02:00–04:00 p.m.in all seasons. In seasons with weak photochemistry, diur-nal patterns are flat, with only weak enhancements duringdaytime. Late afternoon peaks (around 05:00 p.m.) are of-ten accompanied by south-westerly winds. Median ampli-tudes of O3 in summer, fall and winter were respectively 83,34 and 19 ppbv with peaking time being 04:00, 03:00 and02:00 p.m. In cooler seasons, O3 peaks could be the resultof regional mixing or transport, which may also occur duringnight-time.

3.5 Influence of meteorology on reactive gases

3.5.1 Dependence of gas pollutant concentrationson wind

Figure 7 shows the wind speed and wind direction depen-dence map of reactive gas concentrations for summer, falland winter. The shaded contours indicate the trace gas con-centrations for varying wind speeds (radial distance) andwind directions (radial direction). The dashed black linestands for the relative mean gas concentrations of each winddirection, while the solid black line is the relative frequencyof all wind directions.

As mentioned before, the prevailing surface wind direc-tion is SW in summer for Wuqing; wind speeds are typicallyrather low. CO (Fig. 7a1–a3) is a relatively well mixed tracegas. In Wuqing, average concentrations below 1 ppmv couldonly be detected in the N-W sector and under southerly winddirections, when wind speed exceeded 4 m s−1. In the SWand NE directions, CO concentrations were high under lowwind speeds (


0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(a1)

0.5 1 1.5 2

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(b1)

5 10 15

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(c1)

20 40 60

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(d1)

20 40 60 80 100 120 140

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(e1)

50 100 150

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(a2)

1 2 3

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(b2)

10 20 30 40

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(c2)

50 100 150

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(d2)

20 40 60

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(e2)

40 60 80

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(a3)

CO(ppmv)2 4 6

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(b3)

SO2(ppbv)

20 40 60

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(c3)

NOX(ppbv)

50 100 150 200

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(d3)

O3(ppbv)

5 10 15 20 25

0

10 m/s 30

210

60

240

90270

120

300

150

330

180

0(e3)

OX(ppbv)

30 40 50 60 70

Fig. 7. Wind Dependency map of CO(a), SO2 (b), NOx (c), O3 (d) and Ox (e) mixing ratio for summer (1), fall (2) and winter (3). Windspeeds are shown from 0 to 10 m s−1 (radial distance). The dashed black line shows relative mean gas concentration, while the solid blackline is the relative frequency of occurrence versus wind direction both on a scale of 0 to 1.

CO mixing ratio was more representative of a regional back-ground concentration.

As discussed in Sect. 3.2, SO2 distributions vary withseason, mainly due to domestic heating and slow chemi-cal transformations in winter (Lin et al., 2011). In sum-mer (Fig. 7b1), SO2 mixing ratios were generally low. Rel-atively higher SO2 concentrations came with local surfacewinds from SW-SE, which conforms well with the averagesummertime distribution of OMI SO2 PBL column. Whilethe S-SE sector showed trends of increasing SO2 mixing ra-tio with wind speed, the SW sector followed the increase-decrease-increase pattern with increasing wind speeds; thedecrease was found at 4 m s−1. In fall (Fig. 7b2), SO2 wasmore evenly distributed among the wind directions; the NWsector showed the lowest and the SW sector the highest con-centrations. In winter (Fig. 7b3), SO2 concentrations werethe highest under NE wind directions; winds from the southalso displayed SO2 mixing ratios between 30 and 50 ppbv,while the NW and W wind mostly brought down fresh non-SO2-polluted air. Local SO2 concentrations in Wuqing arerepresentative of the regional SO2 standards and also displaythe seasonal variation in its source locations.

For trace gases with short lifetimes, such as NOx, it canbe assumed that in-situ measured trace gas mainly stems

from local emissions, while the contribution of sources inthe surrounding regions is weak. Under such an assump-tion, concentrations should show a simple decreasing trendwith increasing wind speed to a background level. Such arelationship between NOx and wind speed was observed aswell as modelled in earlier studies (Aldrin and Haff, 2005;Carslaw et al., 2006). In this study, relatively high NOx val-ues (Fig. 7c1–c3) in Wuqing were confined to wind speedbelow 2 m s−1. Since NOx levels are dominated by localsources and reactions, its concentration is readily dilutedand concentrations generally decreased with increasing windspeed, with a mean background value around 10 ppbv. In theSE sector, relatively high NOx values persisted throughoutall wind speeds, showing a decreasing trend after reachinga peak at 1 m s−1. This indicates not only the existence ofadjacent emission sources, which is most likely the vehicleexhaust in the centre of Wuqing district, but also transportfrom farther away sources, such as the Tianjin Municipality.OMI NO2 tropospheric column confirms the fact by showinga large area of elevated NO2 columns SE to Wuqing. TheSW sector also revealed NOx at a significantly higher level,especially when accompanied by mild winds. Various fac-tors could have contributed to such a result. Since there areno obvious high concentrations of NO2 visible on the OMI



NO2 distribution in the SW direction of Wuqing, the mostprobable factor would be the synoptic condition associatedwith mild south-westerly wind, which is favourable for theaccumulation of pollutants.

As shown in the wind dependency maps (Fig. 7d1–d3),for all wind directions, O3 concentrations were generally lowunder slow winds, because high NO accumulation consumedO3 through chemical reactions. In summer and fall, high O3was found under W-S wind directions. Summertime mea-surements conducted by Ran et al. (2011) show high iso-prene concentrations, also accompanied by winds from theW-S sector, which may be the reason for the high O3 forma-tion and transport. In winter, O3 production becomes veryweak and local NOx pollution is severe, which consumes lo-cal O3, when fresh NW air is transported to Wuqing underfairly high wind speed, O3 concentrations rose up to back-ground levels in winter.

The “potential ozone” Ox (O3 + NO2) is used as an esti-mate of the total atmospheric oxidant (Lin et al., 2008). Insummer (Fig. 7e1), Ox was highest in the SW sector underhigh wind speeds. For the E-SE-S sector, Ox increases withrising wind speed, but decreases again after reaching a peakat 3.5 m s−1, which suggests that high wind speed can diluteboth primary pollutants and secondary formed ones. In fall(Fig. 7e2), Ox was high when low winds from the SE direc-tion dominated, which was mainly caused by local NOx ac-cumulation (see Fig. 7c2). High Ox were also detected underhigh winds from the SW direction, which is in favour of O3production and transport. In winter (Fig. 7e3), Ox generallydecreased with increasing wind speed. High concentrationswere found under low winds from the SW and NE direction,while the lowest concentrations were observed when strongwinds came from E.

3.5.2 Dependence of pollution frequency on wind

To avoid the large standard deviation in calculating the av-erage gas concentration under given wind directions andwind speeds, the occurrence frequency of gas concentrationsreaching above the 75th percentile (f75) or below the 25thpercentile (f25) is utilized to respectively evaluate the oc-currence probability of the “relatively polluted” state or the“relatively clean” state (see Sect. 2.5 for detailed descrip-tion). Figure 8 reveals howf75 andf25 of different speciesvary with wind direction and wind speed, respectively for JA,SON and DJ.

For primary gaseous pollutants,f75 generally decreaseswith increasing wind speed, whilef25 increases with ris-ing wind speed. This is a simple consequence of lowerpollution levels being associated with greater mixing anddilution at higher wind speeds. A rise in the frequencyof CO pollution incidents can be clearly seen in the NEand E directions,f75(CO) shows an increase after 3 m s−1

and 5 m s−1, respectively, whilef25(CO) simultaneously de-creases. Summertimef25(SO2) is very low and displays

no significant variations with either wind direction or windspeed, whilef75(SO2) is evidently higher under E-SE-S-SWwinds and shows either increasing trends with wind speed (E-SE) or very weak decreasing trends(S-SW). In fall and win-ter,f25(SO2) gains significantly with increasing wind speedunder NW-N winds, whilef75(SO2) is similar to that of sum-mertime. Results for NOx are very consistent with those ofCO; only the increasing/decreasing rate off25/f75 is higher.In the S-SW sector,f25(NOx) stays low with increasing windspeed, indicating that this sector is seldom NOx clear.

Compared with the primary pollutants,f25 and f75 ofO3 show reversed trends with wind speed. Typically, a de-creasing trend off25(O3) can be noted with increasing windspeed, especially during fall and winter, while forf75(O3)the opposite is true. However, there are exceptions under cer-tain wind directions. In summer, onlyf75(O3) in the S-SWdirections increases with wind speed, while in other direc-tions, occurrence frequency of “relatively polluted” states re-main at very low levels.f25(O3), however, only increasedslowly with easterly wind, in other directions, the occur-rence frequency of ozone polluted states decreases with windspeed. The reason that high ozone days appear frequentlyunder S-SW winds has already been stated in the previoussection. For N-NW winds, the frequency of O3 concentra-tion falling between the 25th and 75th percentiles increaseswith wind speed, indicating that higher wind speeds are morelikely to transport air with background O3 concentrations toWuqing. In fall and winter, the only exception is seen in theE sector, wheref75(O3) first increases then decreases withrising wind speed. The decrease inf75(O3) might be causedby elevated NOx concentrations (or decreasedf25(NOx)) inthe E sector.

Altogether, results are very consistent with those from thewind dependency map (Fig. 7). To summarize and quantifythe effect of pollutant emission sources distributed in differ-ent wind directions on local trace gas concentrations, a back-groundf75 is subtracted from those lying in each wind di-rection under various wind speeds. Through comparison andanalyses, such a background value was determined as thef75values observed under northerly winds. Therefore, thef75values under wind direction N are subtracted from thef75values corresponding to all other directions (see Eq. (4) inSect. 2.5), to obtain the frequency increment1f . It shouldbe noted that, under very low wind speeds (


0

50

100 (a1) (a2)

f25

(CO) f75

(CO) f25

(SO2) f

75(SO

2) f

25(NO

X) f

75(NO

X) f

25(O

3) f

75(O

3)

(a3)

0

50

100 (b1) (b2) (b3)

0

50

100 (c1) (c2) (c3)

0

50

100 (d1)

Fre

qu

ency

(%)

(d2) (d3)

0

50

100 (e1) (e2) (e3)

0

50

100 (f1) (f2) (f3)

0

50

100 (g1) (g2) (g3)

0 1 2 3 4 5 6 70

50

100 (h1)

0 2 4 6 8 10 12

(h2)

Wind Speed (m/s)0 2 4 6 8 10 12

(h3)

Fig. 8. Variation of frequency(f25 andf75) with wind speed (WS) and wind direction (WD).(a–h) represent S, SW, W, NW, N, NE, E, SE,respectively, while (1–3) stand for summer, fall and winter. Calculation methods are given in Sect. 2.5.

increases again to a maximum value. Especially in summer,high E-SE wind can elevate occurrence frequencies of SO2pollution by up to 82 %. S-SW wind also has remarkableimpacts at 2–4 m s−1. For NOx, calm winds from nearlyall wind directions can decreasef75(NOx), but for higherwind speeds, the effect of easterly winds is more pronounced,with 1f75(NOx) reaching 51 %. For summertime O3, S-SWwinds contribute the most (max. 76 %) to increasing the fre-quency of O3 pollution events, the higher the wind speed, thegreater the frequency increment. In fall and winter, O3 con-centrations drop to a very low level, due to weakened pho-tochemistry and consumption by high NO concentrations.Thus f75(O3) does not represent the frequency of O3 pol-lution, but rather the frequency of O3 being at backgroundlevel (unconsumed by NO). Hence, in the N sector, wheref75(NOx) is very low,f75(O3) display high values. This isthe reason that1f75(O3) in fall and winter are often nega-tive. With E winds,1f75(O3) have very high negative val-ues, due to severe O3 depletion by NO. It can be noted that,1f75(O3) does not show significant variations with differentwind directions when wind speeds were low, which is proba-bly due to the nonlinear relationship of ozone to its precursorgases.

3.5.3 Dependence of ozone on temperature and relativehumidity

Atmospheric temperature is the average kinetic energy ofmolecules in the air; it directly affects the frequency of colli-sion between molecules, on which chemical reactions rely. Italso has direct impact on the mechanism pathway of O3 (e.g.,H-abstraction versus OH addition, Atkinson, 1990) genera-tion and strong correlation with stagnant, sunny (high UVradiation) atmospheric conditions (Jacob et al., 1993). In-directly, temperature may influence the decomposition rateof PAN and the emission of VOCs, which further compli-cates the relationship between temperature and O3. Sucha relationship has been studied for various locations; gen-erally, the relationship of daily O3 concentration to tem-perature is nonlinear, O3 concentrations appear to show nodependence on temperature below 294–300 K, but they be-come strongly dependent on temperature above 305 K (NRC,1991). Other studies suggest that O3 increases approximatelylinearly with temperature, with a slope in the range of 2–8 ppb K−1 (Steiner et al., 2010).

Figure 9 shows observed daily maximum O3 values in re-lation with daily maximum temperatures. The figure alsomarks the exceedance standard for O3 (horizontal red dashed



Table 3. Wind Speed (WS) and Wind Direction (WD) distribution of frequency increment1f . Calculation methods are given in Sect. 2.5.

Trace Wind 1f75 (%)

Gas (m s−1) Summer (15 Jul–31 Aug 2009) Fall (1 Sep–30 Nov 2009) Winter (1 Dec 2009–21 Jan 2010)

S SW W NW NE E SE S SW W NW NE E SE S SW W NW NE E SE

CO

0–1 −8.1 −3.0 −7.1 −18.8 1.8 −1.0 3.6 −17.7 −6.6 −10.3 −17.7 −0.9 −7.7 −12.5 −22.0 −15.5 −14.2 −10.3 −2.6 −6.6 −16.41−2 4.4 21.6 −0.1 −8.5 18.6 18.7 3.1 −10.7 9.3 −6.5 −7.2 11.2 2.9 −12.5 −11.6 −4.1 −6.4 −3.4 10.7 0.0 −11.92−3 12.5 44.0 17.3 5.0 18.6 34.2 54.0 0.7 25.3 10.9 1.7 12.9 15.3 25.0 −3.4 4.0 0.4 −3.7 4.8 1.6 −2.43–4 3.4 22.1 0.0 0.4 13.8 29.1 40.6 0.3 2.6 0.0 0.0 8.7 11.2 18.8 0.0 1.1 0.0 0.0 2.1 0.4 0.04–5 0.0 15.5 0.0 0.0 36.6 10.3 0.0 0.0 0.0 0.0 0.0 19.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.05–6 – 0.0 – 0.0 – 11.6 – – 0.0 – 0.0 – 0.0 – – 0.0 – 0.0 – 0.0 –6–7 – – – 0.0 – 26.1 – – – – 0.0 – 0.0 – – – – 0.0 – 0.0 –

SO2

0–1 10.7 12.9 9.1 −4.7 5.3 −0.2 4.3 0.3 2.1 2.2 −7.9 2.9 −2.5 −3.1 −2.2 −4.8 −5.2 −4.9 0.1 3.8 −2.01–2 31.4 35.7 27.2 9.0 16.6 13.5 6.9 2.3 12.2 5.4 −1.3 13.3 −1.2 −4.2 −4.6 0.6 −5.0 −5.9 7.5 −0.5 −5.72–3 37.2 43.5 40.4 14.7 10.4 34.5 44.7 12.8 31.1 25.3 7.8 9.0 23.9 29.3 1.6 3.3 5.7 −3.3 5.1 −1.7 4.03–4 43.9 37.8 −1.0 6.0 3.7 49.3 59.3 26.2 21.8 5.1 0.8 9.4 22.4 18.3 1.1 2.5 0.0 0.0 8.5 0.0 0.04–5 26.0 39.5 −22.8 −11.2 2.7 62.7 48.0 2.2 11.3 0.0 0.2 1.2 17.4 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.05–6 – −1.3 – −7.4 – 20.7 – – 0.0 – 0.0 – 7.4 – – 0.0 – 0.0 – 7.4 –6–7 – – – −13.1 – 81.9 – – – – 0.0 – 39.4 – – – – 0.0 – 15.8 –

NOx

0–1 −5.6 5.4 0.1 −4.6 −0.8 −9.3 −8.3 −18.4 −9.3 −3.9 −14.3 −0.1 −9.7 −9.5 −12.9 −4.7 0.0 −6.1 −2.0 0.5 −4.11–2 8.9 26.4 18.7 15.6 10.9 4.4 14.4 −4.9 8.2 11.8 6.5 12.4 −1.0 1.3 0.8 6.8 6.2 11.3 11.0 7.6 3.22–3 9.0 40.5 43.1 28.3 5.4 24.8 50.9 −0.1 11.3 11.9 1.9 −3.1 1.2 21.9 0.6 1.9 2.5 0.6 0.0 0.5 2.23–4 28.5 21.6 16.0 21.8 6.7 25.2 50.6 1.7 1.6 0.8 0.4 0.0 0.0 9.3 0.0 0.0 0.0 0.0 0.0 0.0 0.04–5 0.0 10.7 8.8 12.7 0.0 3.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.05–6 – 0.0 – 2.9 – 7.4 – – 0.0 – 0.0 – 0.0 – – 0.0 – 0.0 – 0.0 –6–7 – – – 1.0 – 29.7 – – – – 0.0 – 0.0 – – – – 0.0 – 0.0 –

O3

0–1 −0.6 −0.1 1.0 2.1 0.8 1.3 3.8 5.6 0.3 3.0 −0.7 1.3 0.5 3.6 1.7 −3.2 −1.3 −2.8 −3.1 −5.5 −0.91–2 5.0 4.1 0.6 7.5 4.4 0.2 7.3 5.6 −5.3 −6.6 −5.3 −7.0 −4.3 1.5 10.1 −5.3 −9.5 −6.4 −4.2 −6.2 −1.62–3 10.8 13.8 8.3 5.5 3.3 7.7 7.1 23.7 7.6 −7.2 −8.1 −10.5 1.3 −9.5 16.8 −2.4 −12.3 −11.9 −15.5 −3.5 −21.53–4 32.9 42.7 8.3 −0.2 6.8 5.2 −0.2 21.7 23.1 27.0 −28.0 −9.6 −15.3 −25.6 0.3 2.9 13.7 −32.6 −3.8 −33.1 −48.84–5 75.9 45.8 0.0 0.0 4.5 3.0 0.0 58.1 44.6 55.0 −18.7 32.5 −20.0 30.2 19.5 14.9 19.5 −24.0 7.3 −49.7 −1.75–6 – 56.3 – 0.0 – 0.0 – – 44.9 – −23.2 – −42.1 – – 18.0 – −9.8 – −55.8 –6–7 – – – 0.0 – 0.0 – – – – −12.4 – −63.3 – – – – 4.3 – −81.4 –

260 270 280 290 300 3100

20

40

60

80

100

120

140

160

180

200

Daily Maximum Temperature (K)

Dai

ly M

axim

um

O3

Mix

ing

Rat

io (

pp

bv)

Summer Daily Max. O3

Autumn Daily Max. O3

Winter Daily Max. O3

Max.O3=7.9×Max.Temp.−2305.3(r:0.87)

RH(%)

0

10

20

30

40

50

60

70

80

90

100

Fig. 9. Dependence of daily maximum ozone concentrations ondaily maximum temperature and current RH (RH at the occurrencetime of the ozone peak). Round dots stand for summer time data,triangles for fall data and squares for winter data; colours show cur-rent relative humidity. The horizontal red dashed line stands for theO3 exceedance standard defined in Sect. 2.3; the vertical red dashedline, stands for the temperature cut-off, under which there has beenno ozone exceedance detected; the magenta dashed line shows a re-gression between daily maximum temperature and daily maximumozone above the temperature cut off.

line) and the temperature value (vertical red dashed line),below which O3 never exceeded given standards. It canbe noted that, for atmospheric temperatures greater than294 K, O3 concentrations increased almost linearly with tem-perature, with a slope of 7 ppb K−1, but when atmospherictemperatures sank under 294 K, ozone concentrations keptbelow the exceedance level. For temperatures lower than289∼291 K, O3 concentrations were not dependent on tem-perature, but on other meteorological parameters. It shouldbe noted that the observed correlation between daily maxi-mum O3 and temperature cannot be attributed solely to tem-perature dependence of chemical reaction rates because dailymaximum temperature is highly dependent on the intensityof solar radiation, which the major driver of photochemicalO3 production.

In summer, high RH and low RH both were accompa-nied by relatively lower daily maximum O3 mixing ratios,while RH between 40 % and 60 % often appeared with highO3 mixing ratios. A reasonable explanation would be thathigh RH is often associated with cloudy and rainy days insummer, thus weak UV radiation might reduce ozone pro-ductivity; while low RH in summer are mostly associatedwith northerly wind from the inland, bringing down freshless polluted air with low ozone precursor concentrations.It is also evident that, in winter, maximum O3 concentra-tions were higher under low relative humidity, which mayhave two reasons. Firstly, low relative humidity often oc-curs when the NCP region was controlled by a high pressureridge, mostly resulting in clear days with strong radiation,



thus promoting some photochemical reactions. Secondly,the above mentioned weather system was mostly accompa-nied by NW winds, which brought down fresh air with lowprecursor gas concentrations, thus the produced O3 was notdepleted by high local NO concentrations. Also, high pres-sure systems with downdrafts may bring down ozone rich airfrom the upper level.

4 Conclusions

Measurements of surface trace gases at Wuqing from the pe-riod 9 July 2009–21 January 2010 and ancillary data wereused to study the characteristics of pollution in the NorthChina Plain and the impact of meteorology on local trace gasconcentrations.

Annual mean distributions of trace gases and AOD re-veal the currently highly polluted state of the NCP. Wuqingin comparison to the neighbouring mega-cities (Beijing andTianjin) is relatively clean. The lack of significant local emis-sion sources and the location of Wuqing determine that thesite is highly representative of the regional pollution state.

Mixing ratios of gaseous pollutants were on a significantlyhigher level than rural stations to the north of Beijing citycentre (Miyun, Wang et al., 2008; SDZ, Gao et al., 2005;Meng et al., 2009; Lin et al., 2008]. Mean daytime O3varied between 64.1 (JA) and 15.6 (DJ) ppbv. CO, SO2,NO2, NOx, however, showed reversed seasonality, with thelowest values in JA, respectively being 1.2 ppmv, 5.7 ppbv,17.9 ppbv and 20.4 ppbv, and the highest values in DJ, reach-ing 2.4 ppmv, 28.5 ppbv, 35.1 ppbv and 80.8 ppbv, respec-tively. Major gaseous pollutants at Wuqing are O3 in summerand NOx in winter.

Mean diurnal patterns of primary gaseous pollutants arehigh probably determined by boundary layer processes (vari-ations of mixing height, vertical turbulence and horizontalwind velocity) and emission characteristics, showing morn-ing and evening peaks. For NOx, it is primarily the resultof rush hour emissions in combination with photochemistry;while for CO, it is more a boundary layer effect. SO2 showedan early noon peak and an insignificant evening peak, proba-bly caused by emission sources outside the nocturnal bound-ary layer. Further research on the vertical profile of SO2 or itsvertical flux is required. Secondary gas pollutant, O3, peakedbetween 02:00 to 04:00 p.m. on average.

Wind speed and wind direction showed deterministic im-pacts on trace gas pollution levels, providing information onregional pollution characteristics. Generally, high concen-trations of relatively long-lived gaseous pollutants came withwind directions from SW-SE and NE with very high frequen-cies. Short-lived gases, such as NOx, mainly displayed highconcentrations under calm winds, but also suggested trans-port form the SE. O3 showed low concentrations under calmwinds, which were accompanied by high NOx. High concen-trations of O3 were found under high wind speed, in wind

conditions with low levels of NOx. The S-SW directionsespecially showed high concentrations of O3 and high oc-currence frequency of O3 pollution during summer, proba-bly due to the high isoprene concentrations associated withthose wind directions. No transport of plumes from Beijingto Wuqing was detected, since air associated with NW windswere mostly clean, especially under large wind speeds.

Temperature is another meteorological factor that influ-ences O3 concentrations. For atmospheric temperatureshigher than 294 K, the O3 concentration increased linearlywith temperature and frequently exceeded the defined stan-dard, particularly at temperatures over 300 K; for air tem-peratures lower than 294 K, the O3 concentration showed nocorrelation with temperature and no O3 exceedance was ob-served. For temperatures beneath 289∼291 K, O3 concentra-tions depended on other meteorological parameters insteadof the temperature. This temperature limit is 9 K lower thanthat proposed by the NRC (1991).

Overall, this study provides important information on thepollution state and the characteristics of various gas pollu-tants. CO and SO2 are closely related to aerosol pollution,O3 influences the aging of atmospheric aerosols and SO2 lev-els may have great impacts on aerosol hygroscopicity, opticalproperties and CCN activations.

Acknowledgements.We gratefully thank the staff of the WuqingMeteorological Station for their logistic support. Funds forthis research were provided by the National Natural ScienceFoundation of China Project 40875001 and 40775074, the 973Program (2011CB403402), and the Basic Research Fund ofChinese Academy of Meteorological Sciences (2008Z011).

Edited by: D. Covert

References

Aldrin, M. and Haff, I. H.: Generalised additive modelling of airpollution, traffic volume and meteorology, Atmos. Environ., 39,2145–2155, 2005.

Atkinson R.: Gas-phase tropospheric chemistry of organic com-pounds: A review, Atmos. Environ., 24A, 1–41, 1990.

Carslaw, D. C., Beevers, S. D., Ropkins, K., and Bell, M. C.: De-tecting and quantifying aircraft and other on-airport contributionsto ambient nitrogen oxides in the vicinity of a large internationalairport, Atmos. Environ., 40, 5424–5434, 2006.

Chan, C. K. and Yao, X.: Air pollution in mega cities in China,Atmos. Environ., 42(1), 1–42, 2008.

Chen, Y., Zhao, C., Zhang, Q., Deng, Z., and Huang, M.: Aircraftstudy of Mountain Chimney Effect of Beijing, China, J. Geo-phys. Res., 114, D08306,doi:10.1029/2008JD010610, 2009.

Chen, Z. H., Cheng, S. Y., Li, J. B., Guo, X. R., Wang, W. H., andChen, D. S.: Relationship between atmospheric pollution pro-cesses and synoptic pressure patterns in northern China, Atmos.Environ., 42(24), 6078–6087, 2008.

Dickerson, R. R., Kondragunta, S., Stenchikov, G., Civerolo, K. L.,Doddridge, B. G., and Holben, B. N.: The Impact of Aerosols on


http://dx.doi.org/10.1029/2008JD010610


Solar Ultraviolet Radiation and Photochemical Smog, Science,278(5339), 827–830,doi:10.1126/science.278.5339.827, 1997.

Ding, A. J., Wang, T., Thouret, V., Cammas, J.-P., and Ndlec, P.:Tropospheric ozone climatology over Beijing: analysis of air-craft data from the MOZAIC program, Atmos. Chem. Phys., 8,1–13,doi:10.5194/acp-8-1-2008, 2008.

Fischer, H., Kormann, R., Klüpfel, T., Gurk, Ch., K̈onigstedt, R.,Parchatka, U., M̈uhle, J., Rhee, T. S., Brenninkmeijer, C. A. M.,Bonasoni, P., and Stohl, A.: Ozone production and trace gas cor-relations during the June 2000 MINATROC intensive measure-ment campaign at Mt. Cimone, Atmos. Chem. Phys., 3, 725–738,doi:10.5194/acp-3-725-2003, 2003.

Gao, J., Wang, T., Ding, A. J., and Liu, C. B.: Observationalstudy of ozone and carbon monoxide at the summit of mount Tai(1534 m a.s.l.) in central-eastern China, Atmos. Environ., 39(26),4779–4791, 2005.

Greene, J. S., Kalkstein, L. S., Ye, H., and Smoyer, K.: Relation-ships between synoptic climatology and atmospheric pollution at4 US cities, Theor. Appl. Climatol., 62, 163–174, 1999.

Hao, J. M. and Wang, L. T.: Improving urban air quality in China:Beijing case study, J. AirWaste Manage. Assoc., 55, 1298–1305,2005.

Jacob, D. J., Logan, J. A., Yevich, R. M., Gardner, G. M., Spi-vakovsky, C. M., Wofsy, S. C., Munger, J. W., Sillman, S.,Prather, M. J., Rodgers, M. O., Westberg, H., and Zimmerman,P. R.: Simulation of Summertime Ozone over North America, J.Geophys. Res., 98, 14797–14816, 1993.

Jaffe, D. A., Mahura, A., Kelley, J., Atkins, J., Novelli, P. C., andMerrill, J.: Impact of Asian emissions on the remote North Pa-cific atmosphere: interpretation of CO data from Shemya, Guam,Midway, and Mauna Loa, J. Geophys. Res., 101, 2037–2048,1997.

Jenkin, M. E. and Clemitshaw, K. C.: Ozone and other secondaryphotochemical pollutants chemical processes governing the for-mation in the planetary boundary layer, Atmos. Environ., 34,2499–2577, 2000.

Jones, A. M., Harrison, R. M., and Baker, J.: The wind speed de-pendence of the concentrations of airborne particulate matter andNOx, Atmos. Environ., 44(13), 1682–1690, 2010.

Kan, H. and Chen, B.: Particulate air pollution in urban areas ofShanghai, China: health-based economic assessment, Sci. TotalEnviron., 322, 71–79, 2004.

Kato, N. and Akimoto, H.: Anthropogenic emissions of SO2 andNOx in Asia: Emission inventories, Atmos. Environ., 26(19),2997–3017, 1994.

Korsog, P. E. and Wolff, G. T.: An examination of troposphericozone trends in the northeastern U.S. (1973–1983) using a robuststatistical method, Atmos. Environ., 25B, 47–57, 1991.

Li, C. C., Mao, J .T., Lau, K. H. A., Chen, J. C., Yuan, Z. B., Liu, X.Y., Zhu, A. H., and Liu, G. Q.: Characteristics of distribution andseasonal variation of aerosol optical depth in eastern China withMODIS products, Chinese Sci. Bull., 48(22), 2488–2495, 2003.

Lin, W., Xu, X., Zhang, X., and Tang, J.: Contributions ofpollutants from North China Plain to surface ozone at theShangdianzi GAW Station, Atmos. Chem. Phys., 8, 5889–5898,doi:10.5194/acp-8-5889-2008, 2008.

Lin, W., Xu, X., Ge, B., and Zhang, X.: Characteristics of gaseouspollutants at Gucheng, a rural site southwest of Beijing, J. Geo-phys. Res., 114, D00G14,doi:10.1029/2008JD010339, 2009.

Lin, W., Xu, X., Ge, B., and Liu, X.: Gaseous pollutants inBeijing urban area during the heating period 2007–2008: vari-ability, sources, meteorological and chemical impacts, Atmos.Chem. Phys. Discuss., 11, 6919–6956,doi:10.5194/acpd-11-6919-2011, 2011.

Liu, C. M., Huang, C. Y., Shieh, S. L., and Wu, C. C.: Importantmeteorological parameters for ozone episodes experienced in theTaipei Basin, Atmos. Environ., 28(24), 159–173, 1994.

Liu, P., Zhao, C., Zhang, Q., Deng, Z., Huang, M., Ma, X., and Tie,X.: Aircraft study of aerosol vertical distributions over Beijingand their optical properties, Tellus B, 61, 756–767, 2009.

Meagher, J. F., Stockburger, L., Bailey, E. M., and Huff, O.: Theoxidation of sulfur dioxide to sulfate aerosols in the plume ofa coal-fired power plant, Atmos. Environ., 12(11), 2197–2203,1978.

Meng, Z. Y., Xu, X. B., Yan, P., Ding, G. A., Tang, J., Lin, W.L., Xu, X. D., and Wang, S. F.: Characteristics of trace gaseouspollutants at a regional background station in Northern China,Atmos. Chem. Phys., 9, 927–936,doi:10.5194/acp-9-927-2009,2009.

NRC (National Research Council): Rethinking the ozone problemin urban and regional air pollution, National Academy Press,Washington, DC, 1991.

OMSO2Readme file: available at:http://so2.umbc.edu/omi/omidocs.html, last accessed: 3 November 2010.

Parrish, D. D., Holloway, J. S., Trainer, M., Murphy, P. C., Forbes,G. L. and Fehsenfeld, F. C.: Export of North-American ozonepollution to the North–Atlantic ocean, Science, 259 (5100),1436–1439, 1993.

Parrish, D. D., Trainer, M., Holloway, J. S., Yee, J. E., Warshawsky,M. S. and Fehsenfeld, F. C.: Relationships between ozone andcarbon monoxide at surface sites in the North Atlantic region, J.Geophys. Res., 103, 13357–13376, 1998.

PORG: Ozone in the United Kingdom. Fourth Report of the UKPhotochemical Oxidants Review Group, Department of the En-vironment, Transport and the Regions, London, 1997

Prosmitis, A. B., Diapouli, E., and Chaloulakou, S. N.: Organic andelemental carbon particulate continuous field measurements inthe Athens urban area, 8th International Conference on Environ-mental Science and Technology, Lernos Island, Greece, 2003.

Ran, L., Zhao, C., Geng, F., Tie, X., Tang, X., Peng, L., Zhou,G., Yu, Q., Xu, J., and Guenther, A.: Ozone photochemi-cal production in urban Shanghai, China: Analysis based onground level observations, J. Geophys. Res., 114, D15301,doi:10.1029/2008JD010752, 2009.

Ran, L., Zhao, C. S., Xu, W. Y., Lu, X. Q., Han, M., Lin, W.L., Yan, P., Xu, X. B., Deng, Z. Z., Ma, N., Liu, P. F., Yu, J.,Liang, W. D., and Chen, L. L.: VOC reactivity and its effecton ozone production during the HaChi summer campaign, At-mos. Chem. Phys. Discuss., 11, 8595–8623,doi:10.5194/acpd-11-8595-2011, 2011.

Saxena, P. and Seigneur, C.: On the oxidation of SO2 to sulfate inatmospheric aerosols, Atmos. Environ., 21(4), 807–812, 1987.

Shao, M., Tang, X., Zhang, Y., and Li, W.: City clusters in China:air and surface water pollution, Front. Ecol. Environ., 4(7), 353–361, 2006.

Steiner, A. L., Davis, A. J., Sillman, S., Owen, R. C., Michalak,A. M. and Fiore, A. M.: Observed suppression of ozone for-mation at extremely high temperatures due to chemical and bio-


http://dx.doi.org/10.1126/science.278.5339.827http://dx.doi.org/10.5194/acp-8-1-2008http://dx.doi.org/10.5194/acp-3-725-2003http://dx.doi.org/10.5194/acp-8-5889-2008http://dx.doi.org/10.1029/2008JD010339http://dx.doi.org/10.5194/acpd-11-6919-2011http://dx.doi.org/10.5194/acpd-11-6919-2011http://dx.doi.org/10.5194/acp-9-927-2009http://so2.umbc.edu/omi/omi_docs.htmlhttp://so2.umbc.edu/omi/omi_docs.htmlhttp://dx.doi.org/10.1029/2008JD010752http://dx.doi.org/10.5194/acpd-11-8595-2011http://dx.doi.org/10.5194/acpd-11-8595-2011


physical feedbacks, P. Natl. Acad. Sci., 107(46), 19685–19690,doi:10.1073/pnas.1008336107, 2010.

Streets, D. G. and Waldhoff, S. T.: Present and future emissions ofair pollutants in China: SO2, NOx, and CO, Atmos. Environ.,34(3), 363–374, 2000.

Tang, G., Li, X., Wang, Y., Xin, J., and Ren, X.: Surface ozone trenddetails and interpretations in Beijing, 2001–2006, Atmos. Chem.Phys., 9, 8813–8823,doi:10.5194/acp-9-8813-2009, 2009.

Ulas, I., Mete, T., and Orhan, Y.: Analysis of major photochemi-cal pollutants with meteorological factors for high ozone days inIstanbul, Turkey, Water Air Soil Pollut., 175, 335–359, 2006.

van Donkelaar, A., Martin, R. V., Brauer, M., Kahn, R., Levy, R.,Verduzco, C., and Villeneuve, P. J.: Global estimates of am-bient fine particulate matter concentrations from satellite-basedaerosol optical depth: Development and application, EnvironHealth Perspect, 118, 847–855,doi:10.1289/ehp.0901623, 2010.

Wang, T., Carroll, M. A., Alber, G. M., Owens, K. R., Duderstadt,K. A., Markevitch, A., Parrish, D. D., Holloway, J., Fehsenfeld,F. C., Forbes, G. and Ogren, J.: Groundbased measurements ofNOx and total reactive oxidized Nitrogen (NOy) at Sable Island,Nova Scotia during the NARE 1993 Summer Intensive. J. Geo-phys. Res., 101, 28947–28960, 1996.

Wang, T., Lam, K. S., Chan, L. Y., Carroll, M. A., and Lee, A. S. Y.:Trace gas measurements in coastal Hong Kong during the PEM-WESWEST (B), J. Geophys. Res., 102, 28575–28588, 1997.

Wang, T., Ding, A., Gao, J., Wu, W. S., and America, N.: Strongozone production in urban plumes from Beijing, China, Geo-phys. Res. Lett., 33, 1–5, 2006.

Wang, Y., McElroy, M. B., Munger, J. W., Hao, J., Ma, H., Nielsen,C. P., and Chen, Y.: Variations of O3 and CO in summertimeat a rural site near Beijing, Atmos. Chem. Phys., 8, 6355–6363,doi:10.5194/acp-8-6355-2008, 2008.

Wang, Y., Hao, J., McElroy, M. B., Munger, J. W., Ma, H., Chen,D., and Nielsen, C. P.: Ozone air quality during the 2008 BeijingOlympics: effectiveness of emission restrictions, Atmos. Chem.Phys., 9, 5237–5251,doi:10.5194/acp-9-5237-2009, 2009.

Wang, Y., Munger, J. W., Xu, S., McElroy, M. B., Hao, J., Nielsen,C. P., and Ma, H.: CO2 and its correlation with CO at a rural sitenear Beijing: implications for combustion efficiency in China,Atmos. Chem. Phys., 10, 8881–8897,doi:10.5194/acp-10-8881-2010, 2010.

Xu, X. D., Zhou, X. J., and Shi, X. H.: Spatial structure andscale feature of the atmospheric pollution source impact of cityagglomeration, Science in China Series D – Earth Science 48(Suppl. II), 1–24, 2005.

Zhao, C., Wang, Y., and Zeng, T.: East China Plains: A “Basin”of Ozone Pollution, Environ. Sci. Technol., 43(6), 1911–1915,2009.

Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H.,Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., Chen,D., Duan, L., Lei, Y., Wang, L. T., and Yao, Z. L.: Asian emis-sions in 2006 for the NASA INTEX-B mission, Atmos. Chem.Phys., 9, 5131–5153,doi:10.5194/acp-9-5131-2009, 2009.

Zhang, X., Cai, X. H., and Chai, F. H.: Structures and Character-istics of the Atmospheric Boundary Layer over Beijing Area inAutumn, Acta Scientiarum Naturalium Universitatis Pekinensis,42(2), 220–225, 2006.

http://dx.doi.org/10.5194/acp-9-8813-2009http://dx.doi.org/10.1289/ehp.0901623http://dx.doi.org/10.5194/acp-8-6355-2008http://dx.doi.org/10.5194/acp-9-5237-2009http://dx.doi.org/10.5194/acp-10-8881-2010http://dx.doi.org/10.5194/acp-10-8881-2010http://dx.doi.org/10.5194/acp-9-5131-2009

Documents

Characteristics of pollutants and their correlation to … · 2020. 7. 31. · pendence on wind, providing information on regional pollu-tion characteristics. ... (Ran et al., 2009;