at SciVerse ScienceDirect

Atmospheric Environment 76 (2013) 11e20Contents lists availableAtmospheric Environment

journal homepage: www.elsevier .com/locate/atmosenvEmission trends and source characteristics of SO2, NOx, PM10 andVOCs in the Pearl River Delta region from 2000 to 2009Qing Lu a,b, Junyu Zheng a,b,*, Siqi Ye a,b, Xingling Shen a,b, Zibing Yuan b,c, Shasha Yin a,b

a School of Environmental Science and Engineering, South China University of Technology, University Town, Guangzhou 510006, PR Chinab Pearl River Delta Atmospheric Environmental Research Joint Laboratory, Guangzhou 510006, PR ChinacAtmospheric Research Center, Fok Ying Tung Graduate School, Hong Kong University of Science and Technology, Nansha IT Park,Guangzhou 511458, PR China

h i g h l i g h t s< PRD emission trends were characterized and validated from 2000e2009.< Variations in source characteristics were investigated and analyzed.< SO2 emission began to decrease from 2005, while PM10 emission decreased from 2007.< NOx and VOCs emissions exhibited upward trends during 2000e2009.< Immediate control is needed on marine emission source in the PRD region.a r t i c l e i n f o

Article history:Received 6 March 2012Received in revised form22 October 2012Accepted 27 October 2012

Keywords:Emission estimationSource contributionControl policySatellite dataGround observations* Corresponding author. B4-514, School of Environeering, South China University of Technology, SoutGuangzhou 510006, PR China. Tel./fax: 86 20 39380

E-mail address: zheng.junyu@gmail.com (J. Zheng

1352-2310/$ e see front matter 2012 Elsevier Ltd.http://dx.doi.org/10.1016/j.atmosenv.2012.10.062a b s t r a c t

Emission trends and variations in source contributions of SO2, NOx, PM10 and VOCs in the Pearl RiverDelta (PRD) region from 2000 to 2009 were characterized by using a dynamic methodology, taking intoaccount the economic development, technology penetration, and emission control. The results indicatedthat SO2 emissions increased rapidly during 2000e2005 but decreased significantly afterward. NOxemissions went up consistently during 2000e2009 except for a break point in 2008. PM10 emissionsincreased by 76% during 2000e2007 but started to decrease slightly in the following years. VOCsemissions presented continuous increase during the study period. Power plants and industrial sourceswere consistently the largest SO2 and PM10 emission contributors. The on-road mobile source was thelargest emission contributor for VOCs and NOx emissions with decreasing contributions. The NOxcontribution from power plants and industrial sources kept increasing. Worthy of mention is that thenon-road mobile source is becoming an important SO2 and NOx contributor in this region. Comparisonswith satellite data, ground observations and national trends indicated that emission trends developed inthis study were reasonable. Implications for future air pollution control policies were discussed.

2012 Elsevier Ltd. All rights reserved.1. Introduction

The PRD region, located in the southern coast of China, coverscities of Guangzhou, Shenzhen, Zhuhai, Foshan, Dongguan, Zhong-shan, Jiangmen, Huizhou and Zhaoqing (see Fig. 1). Benefited fromthe implementation of Chinas reform and opening-up policies, thePRD region has experienced rapid economic growth, with thesurgingGrossDomestic Product (GDP)by280%, fuel consumptionby150% and the population of passenger cars by 530% (GDPBS, 2001enmental Science and Engi-h Campus, University Town,021.).

All rights reserved.2010), respectively, from 2000 to 2009 (Figs. 2 and 8). However,these dramatic growths have caused serious, complex and regionalair pollution problems (Zhang et al., 2008; Zheng et al., 2010). Themonitoring data showed that the annual average number of hazedays was over 100 and the observed highest ozone concentrationwas up to 0.45 mg m3 in the region (GDEMC and HKEPD, 2005e2010; Deng et al., 2008), and the ozone background concentrationsincreased by an average rate of 0.55 ppbv yr1 during 1994e2007(Wang et al., 2009a). These findings indicated that air pollutioncontrol in this region is challenging.

In order to improve air quality in the PRD region, both nationaland local government agencies have made great efforts to formu-late and issue various control measures and policies in the pastdecade. These policies and control measures were summarized in

mailto:zheng.junyu@gmail.comhttp://crossmark.dyndns.org/dialog/?doi=10.1016/j.atmosenv.2012.10.062&domain=pdfwww.sciencedirect.com/science/journal/13522310www.elsevier.com/locate/atmosenvhttp://dx.doi.org/10.1016/j.atmosenv.2012.10.062http://dx.doi.org/10.1016/j.atmosenv.2012.10.062http://dx.doi.org/10.1016/j.atmosenv.2012.10.062

Fig. 1. The location of the PRD region and air quality monitoring stations.

Table 1Emission source categorization in the PRD region.

Category Sub-category

Power plantsIndustrial sourcesIndustrial solvent useOn-road mobile sources Heavy duty gasoline passenger cars

Heavy duty diesel passenger carsLight duty gasoline passenger carsLight duty diesel passenger carsHeavy duty gasoline trucksHeavy duty diesel trucksLight duty gasoline trucksLight duty diesel trucksBusesTaxies

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e2012Table S-1 in the Supplementary Material. These measures alreadyhelped alleviate regional air pollution problems to some extent.However, the monitoring data indicated that primary pollutantconcentrations still remained at high levels, and secondary ozoneand haze pollution episodes frequently happened (GDEMC andHKEPD, 2005e2010). Therefore, further control measures andpolicies are still needed in order to significantly improve the airquality in the PRD region.

Due to the dramatic economic growth, the adjustment of energystructure, and implementation of emission control measures, it isexpected that source characteristics in this region have greatlychanged during the past ten years. In the meantime, the effec-tiveness and roles of implemented control measures and policieshave yet to be reviewed or assessed in a systematic and scientificmanner. In order to guide future control policy formulation, there isa need for analyzing emission trends of primary pollutants (SO2,NOx, PM10 and VOCs) and identifying variations in source charac-teristics in the PRD region.

The main objectives of this paper are to characterize emissiontrends of primary pollutants from 2000 to 2009 and to assess theimpacts of control measures on source characteristics in the PRDregion. A dynamic methodology, by considering economic devel-opment, technology penetration, and emission control, was used toestimate the emissions. The reliability of this analysis was validatedby comparing emission trends with the satellite data and groundobservations.MotorcyclesNon-road mobile sources Marine

Agriculture machineryConstruction machineryAirportRailroad

Non-industrial solvent use Personal domestic productArchitecture surface coating

Biomass burningResidential fuel consumption2. Data and methods

2.1. Methods for estimating emissions

Emission sources in eight major categories and twenty five sub-categories were considered in this study, as listed in Table 1. Thecategorization was based on the source classification in theGuangdong-Hong Kong air pollution emission inventory handbook(HG-JWGSDEP, 2008) and Zheng et al. (2009). Due to the absence ofdetailed source-based activity data from 2000 to 2009, a top-downapproach was used in this study.

By referring to the technology-based methodology for analyzingnational emission trends (Lu et al., 2010; Zhang et al., 2007; Leiet al., 2011), in this study, a dynamic approach, consideringeconomic development, technology penetration, and emissioncontrol, was used to characterize the emission trends in the PRD

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e20 13region. The emissions were estimated for different years by theEquation (1) below:

En Xi;k;l

Ai;k;l;nXm

Xi;k;l;m;nEFk;l;m;n

Xj

hZj1 hj

i(1)

Where i, k, l, m, n, j represent the city, emission source, the fuel orproduct type, the technology type, the year, control technology,respectively. E represents regional emissions of SO2, NOx, PM10 orVOCs, A stands for the activity level (such as fuel consumption ormaterial production), Xm is for the proportion of fuel or productionfor a sector that is consumed or produced by technology m. Z is theproportion of the control technology j, hj is the removal efficiency ofcontrol technology j. EF is the emission factor. SO2 emission factorsof fuel combustion sources can be calculated by Equation (2):

EF 2 S 1 SR (2)

Where S and SR represent the sulfur contents and sulfur retentionin ash, respectively. Besides, emissions from on-road mobile sour-ces were estimated by Equation (3):

En Xi

Pi;n Mi;n EFi;n

(3)

Where, i, n represent the vehicle class, the year, respectively. P is thevehicle population, M is the annual mileages traveled. Detailedmethods for estimating emissions from different sources weredescribed in previous studies (Che et al., 2009) and summarized inTable S-2 in the Supplementary Material. Table S-2 also listed thedata sources by sectors.2.2. Activity data and emission factors

2.2.1. Activity data processingGenerally, estimating a long term emission trend is much more

challenging than just developing an annual emission inventory, dueto the limitation of the availability, consistency and accuracy inactivity data and emission factors (Zhang et al., 2007). In this study,we referred much on official statistics for most activity data (e.g.,fuel consumption, vehicle population, product output, as shown inTable S-2 in the Supplementary Material). However, these datasources were either lack of detailed activity data for some emissionsources or inconsistent among different years, or missing for someyears or emission sources, therefore, surrogate data have to be usedwith certain level of data processing. Detailed activity data pro-cessing for power plants, industrial combustion sources and on-road mobile sources were presented in the following sections.

The activity data of power plants and industrial combustionsources at city level were collected from official statistical reports(BSPRD, 2001e2010). However, in order to reduce the effects ofdata gaps on emission trends, we mainly considered three majorfuel types including coal, fuel oil and natural gas consumed inpower plants and industrial combustion sources for all cities duringthe study period. Since electricity generation has strong associationwith power plant fuel consumptions, we used the electricitygeneration data to estimate the missing fuel consumption data bytaking into account changes in fuel structures and improvements infuel efficiency in power plants. The gross industrial output valuesavailable in the Guangdong Statistical Yearbook (GDPBS, 2001e2010) were used as conversion factors to estimate the missingdata in industrial combustion sources, by considering the variationin energy intensity.

For on-road mobile sources, 11 vehicle types were consideredincluding eight types of passenger cars and trucks (gross weight:heavy or light duty, fueled by diesel or gasoline), buses, taxis andmotorcycles. However, numbers of passenger cars and trucks weretypically collected by gross weight without differentiation of fueltypes in current official statistical yearbooks. In view of this, weconducted a survey and reviewed previous studies (Che et al., 2009)to estimate the ratios of gasoline to diesel vehicles with differentgross vehicle weights, and then calculated the numbers of eighttypes of passenger cars and trucks based on the above ratios.

2.2.2. Determination of emission factors and control efficienciesEmission factors and control efficiencies are greatly influenced

by control measures, control technologies and emission standards.In the past ten years, great efforts have been made to reduceprimary air pollutant emissions, such as desulfurization for powerplants and industrial sources and upgraded emission standards formotor vehicles. In order to reflect the possible impacts from thesemeasures, dynamic emission factors and control efficiencies indifferent years or cities were used to estimate the emission trends.In the following paragraphs, we introduced the approach todetermine emission factors and control efficiencies for three majorsources across years, including power plants, industrial sources andon-road mobile sources.

Emission factors of on-road mobile sources were typically esti-mated by using mobile emission estimation models with inputs ofvehicle technology distribution, fuel types, fuel economy andannual mileage traveled (He et al., 2005). Due to the lack of detailedfleet and technology information from 2000 to 2009, emissionfactors cannot be estimated by mobile emission estimation modelsfor each year. In this study, we utilized the International VehicleEmission (IVE) Model (UCR, 2008) to estimate 2007-based motorvehicle mission factors in the PRD region with the use of PRD localemission rates, vehicle emission standards, local ambient condi-tions and other local data. The emission factors for other years wereestimated based upon 2007-based emission factors by taking intoaccount the schedule of upgrading vehicle emission standards(including National 0, I, II and III) in the PRD region, the differencebetween vehicle emission factors under different emission stan-dards, and the vehicle numbers by types and years.

Emission factors and control efficiencies of power plants andindustrial sources were traditionally determined by the fuel prop-erty, combustion equipment and removal technology. The regionalaverage sulfur content (S) of coal were 0.89% in 2000 (Chen, 2001)and 0.80% in 2009 (PGGDP, 2010). Since no reliable data wereavailable, interpolation values were used to calculate the averagesulfur content (S) in each year during 2000e2009 (Lu et al., 2010).SO2 removal efficiencies of power plants and industrial sourceswere derived from Equation (4), due to lack of emission controltechnology distribution and penetration data from 2000 to 2009

hn Rn=Rn En (4)

Where R is the regional SO2 removal amount from a specificemission source, E is the pollutant discharge amount, h is theaverage removal efficiency of SO2 control technology, n is the year.The related data were collected from emission source census data,official statistical reports (EPBGDP, 2001e2009; NBSC, 2003e2009)and power plant industrial reports (CAEPI-CDDRBK, 2008, 2009,2010). PM10 removal efficiencies were collected from the Environ-ment Statistical Bulletin of Guangdong Province (EPBGDP, 2001e2009) and national studies (Zhang et al., 2006). Annual averageremoval efficiencies trends were shown in Figs. 4, 5 and 9 andFig. S-4 in the Supplementary material.

NOx and PM10 emission factors of power plants and industrialsources were obtained from field investigations conducted onmajor point emission sources in the PRD region (HKEPD, 2011) and

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e2014the emission source census data in 2007 and 2009, with consid-ering the effect of policy implementation on emissions. The NOxand PM10 emission factors trends of power plants and industrialsources used in this study were shown in Fig. S-1 in theSupplementary Material. With respect to VOCs emission factors,although field investigations of key VOCs-related industries likeprinting, wood furniture manufacturing, shoemaking, paint andcoating manufacturing, and others were conducted in the PRDRegion, VOCs-related control and process technology variationsduring the study period were not available, emission factors wereassumed to be fixed in this study. Detailed emission factors of majoremission sources were summarized in Tables S-3e6 in theSupplementary Material.3. Results and discussion

3.1. Emission trends in the PRD region

SO2, NOx, PM10 and VOCs emission trends from anthropogenicsources in the PRD region from 2000 to 2009 were shown in Fig. 2.SO2 emissions increased rapidly from 2000 to 2005 with totalemissions increased by 72% while the GDP increased by 120%,mainly driven by the rapid growth of fossil fuel consumptionwithout strict SO2 control. In response to the implementation ofSO2 control measures for power plants and industrial sectors, SO2emissions decreased significantly after 2005 and nearly halved in2009, compared to 2005, indicating the effectiveness of controlmeasures adopted by governments in recent years. This trend wasbasically consistent with Chinese national SO2 trends, in which thenational SO2 emissions increased by 53% from 2000 to 2006 andbegan to decrease after 2006 (Lu et al., 2010).

Emission trends of NOx and PM10 exhibited similar patterns asshown in Fig. 2. During 2000e2009, the GDP in the PRD regionincreased by 282%, while NOx and PM10 emissions increased by96% and 66%, respectively. NOx emissions in the PRD region kepta consistent growth from 2000 to 2009, with lower growth ratesin recent years, while PM10 emissions kept increasing from 2000to 2007 with annual growth rates from 2% (in 2006) to 13% (in2005), but slightly declined after 2007. The reason for differencesin growth rates between emissions and GDP may be the imple-mentation of a series of control measures on vehicles, powerplants and industrial boilers by national and local governmentagencies in recent years, and the increased GDP contributions ofnon-production sector, from 44% in 2001 to 50% in 2009 (GDPBS,0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

val

ue

GDP Fuel consumption SO2 NOx PM VOCs

Fig. 2. Trends in pollutant emissions, GDP and fuel consumption (All data arenormalized to the year 2000).2001e2010). In comparison with national NOx and PM10 emissiontrends, similar upward trend was also identified in the nationalNOx emissions with an increase of 55% during 2001e2006 (Zhanget al., 2009), while the growth rates of PM10 emissions in the PRDregion increased faster than that in the national trend during2000e2005 (Zhang et al., 2009), probably due to the more rapidlyincreasing GDP in this region.

VOCs emissions remained steadily increasing with annualgrowth rates ranging from 2% to 10%. The stable growth can beattributed to the significant increase of vehicle population and theincreasing use of industrial solvent arising from rapid economicdevelopment. Compared to other three primary pollutants, fluc-tuations of VOCs emission growth rates were much smaller. Thiswas probably because most of VOCs emission control measures orpolicies were targeted on vehicle source with less focus on otheremission sources. Additionally, the VOCs emission trend in the PRDregionwas similar to the national onewith an upward trend (Zhanget al., 2009).3.2. Variations in source characteristics

In this section, we discussed variations in source characteristicsof SO2, NOx, PM10 and VOCs during the past decade and identifiedpossible impacts of policies and control measures on source char-acteristics. Besides, differences in source contributions between thePRD region and the whole China were analyzed.

3.2.1. SO2 emissionsFig. 3 presented variations in SO2 source contributions from

2000 to 2009. Apparently, although power plants and industrialsources showed declining trends in contributions, they were stillmajor contributors, accounting for 92% in 2000 and 82% in 2009. Inaddition, the contribution of non-road mobile sources showed anupward trend, accounting for 6% in 2000 and 15% in 2009 of PRDregional SO2 emissions. The PRD regional SO2 source characteristicswere similar to national ones, in which power plants and industrialsources were major contributors with around 90% of total nationalSO2 emissions since 2000 (Lu et al., 2010).

Figs. 4 and 5 showed the SO2 emission trends and related datafor power plants and industrial sources. Generally, SO2 emissions ofboth power plants and industrial sources shared similar upwardtrends from 2000 to 2005, together with energy consumption,electricity generation and the number of large industrial enter-prises. However, although electricity generation and the number of0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Power plants Industrial sources

On-road mobile sources Non-road mobile sources

Biomass burning Residential fuel consumption

Fig. 3. Contribution trends of SO2 by categories (All data are normalized to the year2000).

0

10

20

30

40

50

60

70

80

0.0

0.5

1.0

1.5

2.0

2.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

SO2

rem

oval

eff

icie

ncie

s (%

)

Nor

mal

ized

val

ue

SO emission Energy consumption

Electricity generation SO removal efficiencies

Fig. 4. Trends in SO2 emission from power plants and related activity data (All dataexcept SO2 removal efficiencies are normalized to the year 2000).

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Marine Airport

Agriculture machinery Consturction machinery

Railroad Freight transfer volumes in ports

Fig. 6. Trends in SO2 emission from marine (non-road) source and related activity data(All data are normalized to the year 2000).

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e20 15large industrial enterprises kept increasing after 2005, the energyconsumption clearly dropped after 2007, and SO2 emissions fromboth power plants and industrial sources decreased significantly.Installing and operating flue gas desulfurization (FGD) facilities inpower plants and large industrial boilers were main reasons for therapid decrease of SO2 emissions. Such decreasing may also beattributed to the implementation of control measures like shuttingdown of small and high-emitting power generation units andindustrial boilers, limiting fuel sulfur contents and increasing theproportion of clean energy consumption (PGGDP, 2004). As shownin Figs. 4 and 5, there were higher removal efficiencies in powerplants than industrial source, this was mainly because FGD deviceswere required to install in all power plants with strict supervision,while only required in larger industrial boilers for industrial sour-ces, which led to relatively low removal efficiencies for industrialsources on average.

Fig. 6 showed SO2 emission contributions and related activitydata trends for non-road mobile sources. Among non-road mobilesources, marine was the largest SO2 contributor, accounting for 8%of total emissions on average and the contribution increased by 12%per year. This was similar to the trend of freight transfer volumes inports, arising from well-developed river systems and the rapid0

10

20

30

40

50

60

70

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

SO2

rem

oval

eff

icie

ncie

s (%

)

Nor

mal

ized

val

ue

SO emission Energy consumption

Large industrial enterprises SO removal efficiencies

Fig. 5. Trends in SO2 emission from industrial sources and related activity data (Alldata except SO2 removal efficiencies are normalized to the year 2000). Note: Largeindustrial enterprises refers to those with the annual main business income over 20million RMB.development of waterway and marine transportation industries inthis region. However, limited control measures were targeted onnon-road mobile sources in this region at present.

3.2.2. NOx emissionsFig. 7 showed variations of NOx source contributions from 2000

to 2009. Obviously, on-road mobile source was the largestcontributor, although its contribution presented a decreasing trend,from 41% in 2000 to 38% in 2009. In addition, power plants andindustrial sources also made great contributions to NOx emissions.Contributions of power plants fluctuated around 24e28% from2000 to 2009 while contributions of industrial sources increasedslightly, from 17% in 2000 and 20% in 2009. The most significantincrease was the non-road mobile source with doubled emissionsand its contribution reaching 14% in 2009. In comparison withnational NOx source characteristics (Ohara et al., 2007), the largestNOx contributor was the on-road mobile source in the PRD region,while nationally it was power plant source.

Fig. 8 showed trends in NOx emissions from on-road mobilesources and vehicle population from 2000 to 2009. The vehiclepopulation increased much faster than NOx emissions after 2005,0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Power plants Industrial sources

On-road mobile sources Non-road mobile sources

Biomass burning Residential fuel consumption

Fig. 7. Contribution trends of NOx by categories (All data are normalized to the year2000).

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0.5

1.0

1.5

2.0

2.5

3.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

veh

icle

pop

ulat

ion

Nor

mal

ized

em

issi

on

Number of passenger cars Number of trucks NOx emission

Fig. 8. Trends in NOx emission from on-road mobile sources and vehicle population(All data are normalized to the year 2000).

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Marine Airport

Agriculture machinery Consturction machinery

Railroad Freight transfer volumes in ports

Fig. 10. Trends in NOx emission from marine (non-road) source and related activitydata (All data are normalized to the year 2000).

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e2016due to upgraded motor vehicle emission standards, such as theNational II implemented in 2005 and National III implemented in2008 (PGGDP, 2009b). Additionally, measures like phase-out ofhigh-emitting vehicles together with the popularization of cleanfuel vehicles such as gas vehicles, hybrid vehicles and electricvehicles (PGGDP, 2004) have also contributed to the reduced NOxemission growth rates under the pressure of rapid vehicle pop-ulation growth.

Fig. 9 showed the relationship between NOx emission trends andrelated data of power plants from 2000 to 2009. There were similarincreasing trends in NOx emissions from power plants to those inenergy consumption and electricity generation before 2005.However, both NOx emissions and energy consumption dropped in2006 while they resumed to decline after 2007. This may beprobably because the deadline of shutting down small-scalethermal power units was at the end of year 2005 (PGGDP, 2004),resulting in the improvement of fuel efficiency and the reduced fuelconsumption and NOx emission in 2006. Similar phenomenon wasfound in industrial sources and details were provided in theSupplementary Material (Fig. S-4).

Except for three largest contributors, non-road mobile sourcewas becoming an important NOx contributor in the PRD regionduring the study period. Among non-road mobile sources, asshown in Fig. 10, marine was the major contributor, accounting for69% of total non-road mobile sources emission on average with an20

30

40

50

60

70

80

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

PM

10re

mov

al e

ffic

ienc

ies

(%)

Nor

mal

ized

val

ue

NOx emission Energy consumption

Electricity generation PM emission

PM removal efficiencies

Fig. 9. Trends in NOx and PM10 emissions from power plants and related activity data(All data except PM10 removal efficiencies are normalized to the year 2000).increasing trend from 62% to 72%, indicating marine source wasbecoming one of major NOx emission sources in this region.

3.2.3. PM10 emissionsFig. 11 showed variations in PM10 source contributions from

2000 to 2009. Power plants and industrial sources were majorcontributors, with average contributions of 37% and 32%, respec-tively. The contribution of industrial sources presented a relativelyrapid growing trend (29% in 2000 and 36% in 2009), while thecontribution of power plants kept relatively steady (34% in 2000and 38% in 2009). Besides, biomass burning and on-road mobilesources were important PM10 contributors. There were similarPM10 source characteristics in the PRD region, in comparison withnational ones, in which power plants and industrial sourcescontributed nearly 70% of total national PM10 emissions in 2000and 2005 (Lei et al., 2011).

Fig. 9 showed the relationship between PM10 emission trendsand related data of power plants from 2000 to 2009. PM10 emis-sions from power plants presented similar increasing trends withthose in energy consumption and electricity generation before2005. However, both PM10 emissions and energy consumptiondropped in 2006 while they resumed to decline after 2007. This canbe attributed to the measures of closing small and high-emit power0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Power plants Industrial sources

On-road mobile sources Non-road mobile sources

Biomass burning Residential fuel consumption

Fig. 11. Contribution trends of PM10 by categories (All data are normalized to the year2000).

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Power plants Industrial sourcesIndustrial solvent use On-road mobile sourcesNon-road mobile sources Non-industrial solvent useBiomass burning Residential fuel consumption

Fig. 13. Contribution trends of VOCs by categories (All data are normalized to the year2000).

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e20 17generation units, restricting coal-fired power plants, and encour-aging the use of hydro-electric power and natural gas (PGGDP,2004, 2009a). Similar trends were found in industrial sources anddetails were provided in the Supplementary Material (Fig. S-4). Itwas noteworthy that the emissions of PM10 did not decline signif-icantly as the one of SO2 did. Generally, the two trends weresupposed to be consistent since the installation of desulphurizationsystem may lead to enhanced PM removal efficiency (Zhao et al.,2008). In our case, the slight inconsistency might be attributed tothe following reasons: (1) since the real removal efficiencies weredetermined by not only the technology itself but also the operatingconditions and managements (Zhang, 2005), the removal efficien-cies of PM10 were lower than that of SO2 control, partly due to lackof strict supervision and management since currently PM10 emis-sion has not been taken into national evaluation index system yet;(2) the wide use of low sulfur coals in power plants and majorindustrial sectors in recent years also led to the large amount of SO2emission reductions. The monitoring data showed that thedecreasing rates of SO2 and PM10 concentrations from 2005 to 2009were 19% and 9% respectively (GDEMC and HKEPD, 2005e2010),indicating the PM10 emission trend developed in this study wasreasonable, though there was inevitable uncertainty.

Fig. 12 showed trends in PM10 emission from the biomassburning source from 2000 to 2009. Biomass burning includeddomestic biofuel combustion, field burning of crop residues andforest fire (He et al., 2011). The PM10 emission from biomassburning showed a relatively steady trend, but its contributionsdecreased rapidly, from 23% in 2000 to 13% in 2009.

It must be pointed out that road dust and construction sourceswere important PM10 emission contributors in the PRD region.However, due to the lack of detailed activity data and local emissionfactors, analysis of PM10 emission trends from road dust andconstruction sources were not made in this study. Further investi-gations and studieswere needed for these two sources in the future.

3.2.4. VOCs emissionsFig. 13 showed variations in VOCs source contributions from

2000 to 2009. Obviously, the on-road mobile source was the largestVOCs contributor, accounting for 57% of PRD regional VOCs emis-sions on average with a slight declining trend from 58% to 53%,followed by the industrial solvent use source which accounted for24% of regional total emissions on average, with an increasing trendfrom 18% to 33% during the ten years. VOCs emission contributionsof both non-industrial solvent use and biomass burning sources0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

Domestic biofuel combustion Field burning of crop residues Forest fire

Fig. 12. Trends in PM10 emission from biomass burning (All data are normalized to theyear 2000).presented declining trends, from 10% to 7% and 12% to 5% respec-tively; while contributions from power plants, non-road mobilesources and industrial sources kept quite stable during the studyperiod.

Fig. 14 showed VOCs emission contributions from on-roadmobile sources by vehicle types from 2000 to 2009. Apparently,motorcycles and passenger cars were major vehicle types for VOCsemissions, accounting for 56% and 29% of regional on-road mobilesources emission on average, respectively. The number of motor-cycles decreased by 7% from 2005 to 2009, due to the restriction orprohibition on motorcycles within urban areas in most cities of thePRD region (Che et al., 2011), with its contributions decreasing from57% in 2005 to 45% in 2009. The number of passenger car increasedby 530% during the ten years, while its emission contribution justincreased from 17% in 2000 to 41% in 2009, due to the imple-mentation of more strict vehicle emission standards.

As shown in Fig. 13, the VOCs emission from the industrialsolvent use source has tripled during the ten years. Although someVOCs-related industrial sectors were equipped with VOCs gath-ering and treatment devices (e.g., activated carbon/water adsorp-tion, catalytic combustion), the removal efficiency still remained at0

1

2

3

4

5

6

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

veh

icle

pop

ulat

ion

Nor

mal

ized

em

issi

on

Motorcycles Passenger carsTrucks BusesTaxies Number of motorcyclesNumber of passenger cars

Fig. 14. Trends in VOCs emission from on-road mobile sources and vehicle population(All data are normalized to the year 2000).

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e2018a low level at present due to the limitation of control technology,ineffective operation, or less supervision.3.3. Comparison with satellite data and ground observations

In order to validate the reliability of emission trend analysis, NOxand PM10 emissions trends were compared with satellite data, andSO2, NOx and PM10 emission trends were compared with groundobservations, depending on data availability. Since the PRDRegional Air Quality Monitoring Network was established in 2005,and started to operate in the next half year in 2005 (Zheng et al.,2010), in order to keep the consistency of ground observationdata used for comparison and to make the comparison scientificallysound, in this study, we only utilized 2005e2009 ground obser-vations for comparisons. The NO2 column concentrations used inthis study were data products by the Institute of EnvironmentalPhysics (IUP), University of Bremen, from GOME (2000e2002) andSCIAMACHY (2003e2009) satellites, using the Differential OpticalAbsorption Spectroscopy-Method (DOAS) (Richter et al., 2005). Thespatial resolutions of GOME and SCIAMACHY are 0.5 0.5 and0.125 0.125, respectively. The dry surface extinction coefficient(SECdry) data with 2-km resolution were used to compare withPM10 emission trends in this study. The SECdry data were retrievedfromMODIS aerosol optical depth (AOD) data acquired fromNASAsGoddard Earth Sciences Distributed Active Archive Center, usingthe aerosol retrieval algorithms developed by Li et al. (2003), withvertical distribution correction and relative humidity correction (Liet al., 2005). The domain for retrieved satellite datawas the same asthe emission domain used in this study.

Fig. 15 showed trends in NOx emissions and satellite-based NO2column concentrations from 2000 to 2009. Generally, trends in NOxemissions and satellite-based NO2 column concentrations pre-sented broad agreement in temporal evolution. Both presentedcontinuous growths (from 2000 to 2004, increased by 55% and 82%,respectively; from 2005 to 2007, increased by 13% and 9%, respec-tively) except that emission in 2008 showed a slight drop. Thegrowth rates of emissions were lower than those of satelliteobservations during 2000e2004, similar to the situation over China(Zhang et al., 2007). However, the large discrepancy betweenemission trends and satellite observations in 2004e2005 can beattributed to the uncertainty in emission estimates, variability inmeteorology, NOx injection height, and the increasing trend ofsulfate aerosols (Zhang et al., 2007). As shown in Fig. 15, there wasa good agreement between NOx emissions and ground observations0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

NOx emissions Satellite-based NO columns

NOx ground observations

Fig. 15. Trends in NOx emissions, satellite-based NO2 column concentrations, andground NO2 concentrations (All data are normalized).during 2005e2009, indicating the reasonability of NOx emissiontrend developed in this study.

Fig. 16 showed trends in PM10 emissions and satellite-basedSECdry values from 2000 to 2009. Basically, PM10 emissions andsatellite-based SECdry values presented similar patterns in temporalevolution, both of which increased at almost the same rates from2000 to 2004 except that the SECdry value dropped in 2002.Another discrepancy occurred during 2004e2006 when PM10emissions continued to grow but the satellite data started todecline slightly. Both emissions and the SECdry values presenteddownward trends from 2007 to 2009. In comparison, a generaldownward trend in PM10 emissions but an upward trend in AODwas observed over the whole China in 2004e2009 (Lin et al.,2010). The complex relationship between PM10 emissions and thesatellite data was probably because the AOD generally has a closerassociation with PM2.5 than with PM10 (Lin et al., 2010). Besides,there was a good agreement between PM10 emission trend andground observations during 2005e2009. These results indicatedthat PM10 emission trend developed in this study was reasonable,to some extent.

Fig. 17 showed trends in SO2 emission from 2000 to 2009 andground observations from 2005 to 2009. There was a very goodagreement between emission and ground observations, bothshowing significant downward trends after 2005. The big discrep-ancy in 2005 might be attributed to the fact that the PRD regionalmonitoring network started the trial operation in the next half yearof 2005, which may not be able to represent regional averaged SO2concentrations over the whole year.

3.4. Implication for air pollution control policy

The implementation of control policies andmeasures did reduceSO2 and PM10 emissions in the PRD region, as shown in this study.However, concentrations of primary and secondary pollutants stillremain at high levels at present, indicating the importance ofimplementing further control measures in this region. In thissection, policy implications for future air pollution control werediscussed based upon the identification of emission trends and thecharacterization of source contributions from this study.

Although significant reductions in SO2 emissions were made inthe past decade, strict control and management of SO2 emissions isstill needed (Xu et al., 2009; Xu, 2011) for further decreasing SO2concentrations and effectively controlling fine particulate pollu-tions, a commonly concerned air pollution issue in China. This0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

PM10 emissions Satellite-based SECdry values

PM10 ground observations

Fig. 16. Trends in PM10 emissions, satellite-based SECdry values, and ground PM10concentrations (All data are normalized).

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Nor

mal

ized

em

issi

on

SO emissions SO ground observations

Fig. 17. Trends in SO2 emissions and ground SO2 concentrations (All data arenormalized).

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e20 19study showed the effectiveness of current SO2 control measures onpower plants and industrial sources. These measures should befurther promoted under strict supervision and be targeted on othersources. Specially, marine sources became the third SO2 contributorwith an increasing trend but fewmeasures have been implementedin the past decade, lowering sulfur contents in fuel of ships orvessels or installing SO2 control devices is one of top priorities forreducing marine SO2 emissions in the next few years.

Upgrading motor vehicle emission standards and phasing outhigh-emitting vehicles alleviated the growth of NOx emissions in thePRD region, to some extent. However, this study showed that NOxemission still presented an upward trend from 2000 to 2009.National Ministry of Environmental Protection (MEP) listed NOxcontrol as a top priority during the national Twelfth-Five plan. Interms ofNOx source characteristics in thePRD region from this study,priority measures for reducing NOx emissions in this region mayinclude the wide use of low NOx burners and flue gas denitrificationtechnology on power plants and industrial sources, furtherupgrading vehicle emission standards, control of non-road mobilesources especially the marine source. It must be pointed out thatcautions need to be taken in reducing NOx emissions since there arecomplicated non-linear relationships in NOx/VOC ratios for ozoneformation in the PRD region (Zhang et al., 2008). Previous studies(Wanget al., 2009b; Zhanget al., 2008) showed that ozone formationwas typically under VOC-limited regime in urban areas of the PRDregion, while most likely under NOx-limited regime in surroundingrural areas. This implies that reducing NOx emissions withoutsimultaneously controlling VOCs emissions with proper ratios, viceversa, may lead to elevated ozone concentrations in this region.

Although power plants and large-scale industrial boilers havebeen equipped with particulate matter control devices in recentyears, the regional PM10 emission still remained at relatively highlevel. Such control devices should be further installed inmiddle andsmall-scale industrial sources. Biomass burning and heavy-dutydiesel vehicles are important PM10 emission contributors in thisregion, more strict control measures should be taken on thesesources. Road and construction dust sources made large contribu-tions to PM10 emission in the PRD region, but have not beeneffectively controlled. Future work should enhance the control ofdust sources and extend target areas to both urban and ruralregions.

VOCs emissions kept consistently increasing from 2000 to 2009in the PRD region though restrictingmotorcycles in urban areas andupgrading motor vehicle emission standards helped reduce VOCsemissions from vehicles, to some extent. VOCs is an importantprecursor for formations of ozone and secondary organic aerosol(SOA). Thus, controlling VOCs emissions is critical to significantlyalleviate ozone and fine particulate pollutions in this region. Basedupon this study, VOCs emissions from industrial solvent use sourcegrew rapidly, implying that control of VOCs emissions from thissource in the PRD region is of great importance in the future. Inaddition, control of vehicle emissions should still be on the toppriority in reducing VOCs emissions in this region, since vehiclesource is expected to be still the largest VOCs contributor withrapidly increasing vehicle population in the next five or ten years.

4. Summary and conclusions

Emission trends and variations in source contributions of SO2,NOx, PM10 and VOCs in the PRD region from 2000 to 2009 werecharacterized by using a dynamic approach. The emission trendresults showed that SO2 emissions increased rapidly during 2000e2005 but decreased significantly afterward. NOx emissions went upconsistently during 2000e2009 except for a break point in 2008.PM10 emissions increased by 76% during 2000e2007 but started todecrease slightly in the following years, and VOCs emissions pre-sented a continuous increase during the study period. The sourcecharacterization results showed that power plants and industrialsources were consistently the largest contributors to SO2 and PM10emissions, the on-roadmobile sourcewas the largest NOx and VOCscontributor, and industrial solvent use source was becoming animportant VOCs emission source. Worthy of attention is that non-road mobile sources gradually become important SO2 and NOxemission contributors in the PRD region, which need immediatecontrol actions on them.

In order to validate the emission trends, comparisons withsatellite data and ground observations were made, where appli-cable. The results showed that emission trends presented broadagreements with the satellite data and ground observations, indi-cating that emission trendsdeveloped in this studywere reasonable.

Acknowledgments

This work was supported by National Natural Science Founda-tion of China-Guangdong (NSFC-GD) Key Project (U1033001),International Technology Cooperation Plan of Guangdong Province(2011B050300006) and The Fundamental Research Funds for theCentral Universities, South China University of Technology(2011ZZ0009).

Appendix A. Supplementary material

Supplementary material related to this article can be foundonline at http://dx.doi.org/10.1016/j.atmosenv.2012.10.062.

References

Bureau of Statistics of Guangzhou/Shenzhen/Zhuhai/Foshan/Jiangmen/Dongguan/Zhongshan/Huizhou/Zhaoqing, Guangdong Province (Ed.) (BSPRD), 2001e2010.Guangzhou/Shenzhen/Zhuhai/Foshan/Jiangmen/Dongguan/Zhongshan/Huiz-hou/Zhaoqing Statistical Yearbook 2001e2010. China Statistics Press, Beijing (inChinese).

Che, W.W., Zheng, J.Y., Zhong, L.J., 2009. Mobile source emission characteristics andcontributions in the Pearl River Delta region. Research of Environment Sciences22 (4), 456e461 (in Chinese).

Che, W.W., Zheng, J.Y., Wang, S.S., Zhong, L.J., Lau, A., 2011. Assessment of motorvehicle emission control policies using Model-3/CMAQ model for the PearlRiver Delta region, China. Atmospheric Environment 45 (9), 1740e1751.

Chen, P., 2001. China Coal Properties, Classification and Utilization. ChemicalIndustry Press, Beijing (in Chinese).

Committee of Desulfurization and Dust Removal of Boiler Kiln of China Associationof Environmental Protection Industry (CAEPI-CDDRBK), 2008. An overview ofthe development in power plants desulfurization and denitrification industryin 2007. China Environmental Protection Industry 6, 18e21 (in Chinese).

http://dx.doi.org/10.1016/j.atmosenv.2012.10.062

Q. Lu et al. / Atmospheric Environment 76 (2013) 11e2020Committee of Desulfurization and Dust Removal of Boiler Kiln of China Associationof Environmental Protection Industry (CAEPI-CDDRBK), 2009. An overview ofthe development in power plants desulfurization and denitrification industryin 2008. China Environmental Protection Industry 7, 8e19 (in Chinese).

Committee of Desulfurization and Dust Removal of Boiler Kiln of China Associationof Environmental Protection Industry (CAEPI-CDDRBK), 2010. An overview ofthe development in power plants desulfurization and denitrification industryin 2009. China Environmental Protection Industry 6, 17e20 (in Chinese).

Deng, X.J., Tie, X.X., Wu, D., Zhou, X.J., Bi, X.Y., Tan, H.B., Li, F., Jiang, C.L., 2008. Long-term trend of visibility and its characterizations in the Pearl River Delta (PRD)region, China. Atmospheric Environment 42 (7), 1424e1435.

Environmental Protection Bureau of Guangdong Province (EPBGDP), 2001e2009.Environment Statistical Bulletin of Guangdong Province (2001e2009). Availableat: http://www.gdep.gov.cn/zlkz/ (2012/02/15).

Guangdong Provincial Bureau of Statistic (Ed.) (GDPBS), 2001e2010. GuangdongStatistical Yearbook 2001e2010. China Statistics Press, Beijing (in Chinese).

Guangdong Provincial Environmental Protection Monitoring Centre (GDEMC), Envi-ronmental Protection Department of Hong Kong (HKEPD), 2005e2010. PearlRiver Delta Regional Air Quality Monitoring Network Report (in Chinese). Avail-able at: http://www.gdep.gov.cn/hjjce/hjxt/201010/t20101021_114994.html(2012/04/09).

He, K.B., Huo, H., Zhang, Q., He, D.Q., An, F., Wang, M., Walsh, M.P., 2005. Oilconsumption and CO2 emissions in Chinas road transport: current status,future trends, and policy implications. Energy Policy 33 (12), 1499e1507.

He, M., Zheng, J.Y., Yin, S.S., Zhang, Y.Y., 2011. Trends, temporal and spatial char-acteristics, and uncertainty in biomass burning emissions in the Pearl RiverDelta, China. Atmospheric Environment 45 (24), 4051e4059.

Hong Kong Environmental Protection Department (HKEPD), 2011. Reports ofFeasibility Study on Major Industrial Air Pollution Sources in the Pearl RiverDelta Region (Report).

Hong Kong-Guangdong Joint Working Group on Sustainable Development andEnvironmental Protection (HG-JWGSDEP), 2008. Pearl River Delta Regional AirQuality Management Plan Mid-term Review Report. http://www.legco.gov.hk/yr07-08/chinese/panels/ea/papers/ea0128cb1-666-4-ec.pdf.

Lei, Y., Zhang, Q., He, K.B., Streets, D.G., 2011. Primary anthropogenic aerosolemission trends for China, 1990e2005. Atmospheric Chemistry and Physics 11,931e954.

Li, C.C., Mao, J.T., Lau, K.H.A., Chen, J.C., Yuan, Z.B., Liu, X.Y., Zhu, A.H., Liu, G.Q., 2003.Characteristics of distribution and seasonal variation of aerosol optical depth ineasternChinawithMODISProducts.Chinese ScienceBulletin48 (22), 2488e2495.

Li, C.C., Mao, J.T., Lau, K.H.A., Yuan, Z.B., Wang, M.H., Liu, X.Y., 2005. Application ofMODIS satellite products to the air pollution research in Beijing. Science inChina Series D Earth Sciences 48 (Suppl. II), 209e219.

Lin, J.T., Nielsen, C.P., Zhao, Y., Lei, Y., Liu, Y., Mcelroy, M.B., 2010. Recent changes inparticulate air pollution over China observed from space and the ground:effectiveness of emission control. Environmental Science & Technology 44,7771e7776.

Lu, Z., Streets, D.G., Zhang, Q.,Wang, S., Carmichael, G.R., Cheng, Y.F., Wei, C., Chin, M.,Diehl, T., Tan, Q., 2010. Sulfur dioxide emissions in China and sulfur trends in EastAsia since 2000. Atmospheric Chemistry and Physics 10, 6311e6331.

National Bureau of Statistics of China (Ed.) (NBSC), 2003e2009. Yangtze River Delta& Pearl River Delta and Hong Kong & Macao Special Administrative Region andTaiwan Statistical Yearbook 2003e2009. China Statistics Press, Beijing (inChinese).

Ohara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X., Hayasaka, T., 2007.An Asian emission inventory of anthropogenic emission sources for the period1980e2020. Atmospheric Chemistry and Physics 7, 4419e4444.

Peoples Government of Guangdong Province (PGGDP), 2004. Outline Plan of theEnvironmental Protection in the Pearl River Delta Region During 2004e2020.Available at: http://www.gzepb.gov.cn/zwgk/gs/fzgh/200810/t20081010_54234.htm (2011/10/11).

Peoples Government of Guangdong Province (PGGDP), 2009a. Prevention andControl Measures of Air Pollution in the Pearl River Delta Region of GuangdongProvince. Available at: http://www.gdep.gov.cn/zcfg/zxfg/201008/t20100809_82410.html (2011/04/09).

Peoples Government of Guangdong Province (PGGDP), 2009b. The ImplementationPlan of Vehicle Exhaust Pollution Control in Guangdong Province. Available at:http://www.gdepb.gov.cn/flfg/dfxfg/201007/t20100713_76038.html (2011/10/20).

Peoples Government of Guangdong Province (PGGDP), 2010. The Clean Air ActionPlan of the Pearl River Delta Region of Guangdong Province. Available at: http://www.gdepb.gov.cn/wrfz/dqfz/xgwj/201003/P020100308608490907835.pdf(2011/02/03).

Richter, A., Burrows, J.P., N, H., Granier, C., Niemeier, U., 2005. Increase intropospheric nitrogen dioxide over China observed from space. Nature 437,129e132.

University of California at Riverside (UCR), 2008. IVE Model Users Manual Version2.0. Available at: http://www.issrc.org/ive/ (2012/6/15).

Wang, T., Wei, X.L., Ding, A.J., Poon, C.N., Lam, K.S., Li, Y.S., Chan, L.Y., Anson, M.,2009a. Increasing surface ozone concentrations in the background atmosphereof southern China, 1994e2007. Atmospheric Chemistry and Physics Discussions9 (16), 10429e10455.

Wang, X., Zhang, Y., Hu, Y., Zhou, W., Lu, K., Zhong, L., Zeng, L., Shao, M., Hu, M.,Russell, A.G., 2009b. Process analysis and sensitivity study of regional ozoneformation over the Pearl River Delta, China, during the PRIDE-PRD2004campaign using the CMAQ model. Atmospheric Chemistry and Physics 9,26833e26880.

Xu, Y., Williams, H.R., Socolow, H.R., 2009. Chinas rapid deployment of SO2scrubbers. Energy & Environmental Science 2, 459e465.

Xu, Y., 2011. Improvement in the operation of SO2 scrubbers in Chinas coal powerplants. Environmental Science & Technology 45, 380e385.

Zhang, Q., Klimont, Z., Street, D.G., Huo, H., He, K.B., 2006. Development ofanthropogenic emissions models and emission inventory in 2001 of particulatematters in China. Progress in Natural Science 16 (2), 223e231 (in Chinese).

Zhang, Q., Streets, D.G., He, K.B., Wang, Y.X., Richter, A., Burrows, J.P., Uno, I.,Jang, C.J., Chen, D., Yao, Z.L., Lei, Y., 2007. NOx emission trend for China, 1995e2004: the view from the ground and the view from space. Journal ofGeophysical Research-Part D-Atmospheres 112, D22306.

Zhang, Y.H., Su, H., Zhong, L.J., Cheng, Y.F., Zeng, L.M., Wang, X.S., Xiang, Y.R.,Wang, J.L., Gao, D.F., Shao, M., Fan, S.J., Liu, S.C., 2008. Regional ozone pollutionand observation-based approach for analyzing ozoneeprecursor relationshipduring the PRIDE-PRD2004 campaign. Atmospheric Environment 42 (25),6203e6218.

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., Yao, Z.L., 2009.Asian emissions in 2006 for the NASA INTEX-B mission. Atmospheric Chemistryand Physics 9, 5131e5153.

Zhang, Q., 2005. Study on Regional Fine PM Emissions and Modeling in China. Ph.D.thesis, Tsinghua University, China, Beijing (in Chinese).

Zhao, Y., Wang, S.X., Duan, L., Lei, Y., Cao, P.F., Hao, J.M., 2008. Primary air pollutantemissions of coal-fired power plants in China: current status and futureprediction. Atmospheric Environment 42 (36), 8442e8452.

Zheng, J.Y., Zhang, L.J., Che, W.W., Zheng, Z.Y., Yin, S.S., 2009. A highly resolvedtemporal and spatial air pollutant emission inventory for the Pearl River Deltaregion, China and its uncertainty assessment. Atmospheric Environment 43(32), 5112e5122.

Zheng, J.Y., Zhong, L.J., Wang, T., Louie, P.K.K., Li, Z.C., 2010. Ground-level ozone in thePearl River Delta region: analysis of data from a recently established regional airquality monitoring network. Atmospheric Environment 44 (6), 814e823.

http://www.gdep.gov.cn/zlkz/http://www.gdep.gov.cn/hjjce/hjxt/201010/t20101021_114994.htmlhttp://www.legco.gov.hk/yr07-08/chinese/panels/ea/papers/ea0128cb1-666-4-ec.pdfhttp://www.legco.gov.hk/yr07-08/chinese/panels/ea/papers/ea0128cb1-666-4-ec.pdfhttp://www.gzepb.gov.cn/zwgk/gs/fzgh/200810/t20081010_54234.htmhttp://www.gzepb.gov.cn/zwgk/gs/fzgh/200810/t20081010_54234.htmhttp://www.gdep.gov.cn/zcfg/zxfg/201008/t20100809_82410.htmlhttp://www.gdep.gov.cn/zcfg/zxfg/201008/t20100809_82410.htmlhttp://www.gdepb.gov.cn/flfg/dfxfg/201007/t20100713_76038.htmlhttp://www.gdepb.gov.cn/wrfz/dqfz/xgwj/201003/P020100308608490907835.pdfhttp://www.gdepb.gov.cn/wrfz/dqfz/xgwj/201003/P020100308608490907835.pdfhttp://www.issrc.org/ive/

Emission trends and source characteristics of SO2, NOx, PM10 and VOCs in the Pearl River Delta region from 2000 to 20091. Introduction2. Data and methods2.1. Methods for estimating emissions2.2. Activity data and emission factors2.2.1. Activity data processing2.2.2. Determination of emission factors and control efficiencies

3. Results and discussion3.1. Emission trends in the PRD region3.2. Variations in source characteristics3.2.1. SO2 emissions3.2.2. NOx emissions3.2.3. PM10 emissions3.2.4. VOCs emissions

3.3. Comparison with satellite data and ground observations3.4. Implication for air pollution control policy

4. Summary and conclusionsAcknowledgmentsAppendix A. Supplementary materialReferences