Please wait a minute...

Frontiers of Environmental Science & Engineering

Front. Environ. Sci. Eng.    2016, Vol. 10 Issue (5) : 9     https://doi.org/10.1007/s11783-016-0853-y
RESEARCH ARTICLE |
Space view of the decadal variation for typical air pollutants in the Pearl River Delta (PRD) region in China
Zifeng WANG1,Min SHAO2,*(),Liangfu CHEN1,*(),Minghui TAO1,Liuju ZHONG3,Duohong CHEN3,Meng FAN1,Yang WANG1,Xinhui WANG1
1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China
2. College of Environmental Sciences and Engineering, Peking University, Beijing 100876, China
3. Guangdong Environmental Monitoring Center, Guangzhou 510308, China
Download: PDF(3907 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Guide   
Abstract

Spatial and temporal trends of the typical pollutants in PRD viewed from space.

Comparisons of the satellite retrievals with the collocated in situ data are given.

Among different MCs, the control measures applied in PRD are the most effective.

The unique HCHO trends imply significant contribution from the biogenic origins.

The Pearl River Delta (PRD) is one of the most industrialized, urbanized and populated regions in China, and thus has been long suffering from severe air pollutions. Space data provide a unique perspective for investigating the atmospheric environment at a regional scale. By utilizing multiple satellite retrievals from 2005 to 2013, this study presented, for the first time, the spatial patterns and temporal trends of typical air pollutants over PRD and its vicinity. As viewed from space, aerosol optical depth (AOD), NO2 and SO2 all had their higher values at the central part of PRD, and showed clear descending gradients as moving to the outskirt of this region. As to the inter-annual variation, all these pollutants had decreasing trends in PRD during the study period, which generally agreed with the relevant in situ measurements. However, the satellite retrievals differed from ground measurements when addressing NO2 and SO2 in the vicinity of PRD. This work also provides the inter-comparison among PRD and three other metropolitan clusters in China: PRD had relatively high AOD, moderate NO2 and low SO2 levels, and it was the only region achieving the effective reduction of NO2 and SO2 during last decade. Unlike the previous three pollutants, HCHO observed by satellite showed very special patterns: it had a relatively homogeneous spatial distribution over both of PRD and its vicinity, and presented an opposite increasing trend from 2005 to 2010. Moreover, PRD had the highest HCHO level among all the metropolitan clusters, hinting a considerable contribution of biogenic origins of HCHO in PRD.

Keywords The Pearl River Delta (PRD)      Satellite monitoring      Regional air quality      Long-term trend      HCHO     
This article is part of themed collection: Understanding the processes of air pollution formation (Responsible Editors: Min SHAO, Shuxiao WANG & Armistead G. RUSSELL)
PACS:     
Fund: 
Corresponding Authors: Min SHAO,Liangfu CHEN   
Issue Date: 20 June 2016
 Cite this article:   
Zifeng WANG,Min SHAO,Liangfu CHEN, et al. Space view of the decadal variation for typical air pollutants in the Pearl River Delta (PRD) region in China[J]. Front. Environ. Sci. Eng., 2016, 10(5): 9.
 URL:  
http://journal.hep.com.cn/fese/EN/10.1007/s11783-016-0853-y
http://journal.hep.com.cn/fese/EN/Y2016/V10/I5/9
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Zifeng WANG
Min SHAO
Liangfu CHEN
Minghui TAO
Liuju ZHONG
Duohong CHEN
Meng FAN
Yang WANG
Xinhui WANG
Fig.1  Information of study areas, including the land use and topography of Guangdong, as well as the detailed surface of PRD based on the true-color satellite image
Fig.2  Spatial distributions of satellite retrieved AOD (a), NO2 VCD (b), SO2 VCD (c) and HCHO VCD (d) in Guangdong Province (with PRD highlighted by red boundary) averaged for 2005–2013
Fig.3  2005 to 2013 mean values and standard errors of satellite retrievals of AOD, NO2, SO2 and HCHO, as well as the relevant in-situ measurements of PM10, NO2 and SO2 for (a) PRD and each of its cities, and (b) Vic-PRD and each of its cities, respectively
Fig.4  Annual mean distributions of the satellite retrieved AOD, NO2, SO2 and HCHO (a-d, respectively) in PRD in 2005 (left panels) and in 2013 (middle panels), as well as their relative difference (right panels)
parameter* region year
2005 2006 2007 2008 2009 2010 2011 2012 2013
AOD PRD 0.70 0.69 0.66 0.57 0.56 0.62 0.61 0.64 0.51
Vic-PRD 0.60 0.58 0.62 0.48 0.51 0.51 0.55 0.53 0.41
Guangdong 0.62 0.60 0.62 0.50 0.52 0.54 0.56 0.56 0.43
NO2 VCD PRD 8.62 8.41 8.83 7.73 7.35 7.15 7.55 6.48 7.38
Vic-PRD 3.02 3.01 3.42 3.02 3.14 3.07 3.55 3.03 2.59
Guangdong 4.56 4.49 4.85 4.28 4.27 4.13 4.60 3.93 3.71
SO2 VCD PRD 0.48 0.47 0.38 0.42 0.27 0.36 0.27 0.14 0.19
Vic-PRD 0.16 0.12 0.10 0.19 0.09 0.14 0.15 0.10 0.11
Guangdong 0.24 0.25 0.17 0.25 0.16 0.23 0.19 0.10 0.18
HCHO VCD PRD 12.61 13.36 13.98 13.10 14.35 15.25 13.55 14.77 13.36
Vic-PRD 11.66 12.65 13.19 12.90 13.10 15.03 11.82 12.85 10.48
Guangdong 12.07 13.05 13.69 13.22 13.62 15.55 12.46 13.60 11.47
PM10 PRD 66.7 66.3 67.6 63.8 58.4 57.7 60.1 57.6 69.9
Vic-PRD 57.2 58.0 59.6 54.5 49.6 50.8 49.3 42.6 50.7
Guangdong 61.0 62.0 63.0 58.5 53.4 53.7 54.0 50.0 60.0
NO2 PRD 38.7 42.8 42.4 40.0 39.3 40.2 38.3 36.1 41.0
Vic-PRD 20.8 19.1 17.4 16.3 18.4 17.8 17.8 17.6 20.2
Guangdong 28.0 29.0 28.1 26.5 27.4 27.4 27.0 26.0 30.0
SO2 PRD 34.1 38.2 35.7 30.9 27.6 25.9 23.3 19.1 21.1
Vic-PRD 21.3 23.3 21.5 20.2 19.2 18.7 17.8 14.1 16.6
Guangdong 27.0 30.0 28.0 23.0 23.0 22.0 20.0 17.0 19.0
Tab.1  Annual mean values of AOD, NO2 VCD, SO2 VCD, HCHO VCD, as well as those of in situ PM10, NO2, SO2 for PRD, Vic-PRD and Guangdong Province
PRD vicinity
meana Stdb R2c rated pe mean Std R2 rate p
AOD 0.62 0.06 0.46 −2.2% 0.31 0.41 0.04 0.62 −2.6% 0.06
PM10in-situ 63.11 4.75 0.11 −0.8% 52.46 5.36 0.68 −2.8% 0.06
NO2VCD 7.72 0.76 0.69 −2.7% 0.06 3.10 0.27 0.05
NO2in-situ 39.88 2.08 0.17 18.36 1.42 0.02
SO2VCD 0.33 0.12 0.86 −8.5% 0.06 0.13 0.03 0.10
SO2in-situ 28.43 6.71 0.89 −6.8% 0.06 19.17 2.80 0.82 −4.3% 0.06
Tab.2  Basic information of variation trends of the satellite retrieved AOD, NO2 VCD and SO2, as well as that of the in-situ measurements of PM10, NO2 and SO2 in PRD and Vic-PRD over the period of 2005 to 2013
Fig.5  Normalized inter-annual variations of satellite retrievals and relevant in-situ measurements of aerosol (a), NO2 (b) and SO2(c), in both PRD (upper panel) and Vic-PRD (bottom panel) from 2005 to 2013. The emission amount of SO2 and NOx, as well as the total energy consumption in Guangdong Province is also presented (d)
Fig.6  Variation trends of satellite retrieved AOD, NO2, SO2 and HCHO in different cities in PRD (e.g., Guangzhou, Zhongshan, Zhaoqing, and Shenzhen) and in Vic PRD (e.g., Shaoguan and Yunfu)
Fig.7  Same as Figure 6 but among PRD and other metropolitan clusters (MCs), namely Beijing-Tianjin-Hebei (JJJ), Yangtze River Delta (YRD) and Cheng-Yu (CY) regions
1 Zhong L, Louie P K, Zheng Z, Yuan Z, Yue D, Ho J W K, Lau A K H. Science-policy interplay: air quality management in the Pearl River Delta Region and Hong Kong. Atmospheric Environment, 2013, 76: 3–10
https://doi.org/10.1016/j.atmosenv.2013.03.012
2 Nie W, Wang T, Wang W X, Wei X L, Liu Q. Atmospheric concentrations of particulate sulfate and nitrate in Hong Kong during 1995–2008: impact of local emission and super-regional transport. Atmospheric Environment, 2013, 76: 43–51
https://doi.org/10.1016/j.atmosenv.2012.07.001
3 Yuan Z B, Yadav V, Turner J R, Louie P K K, Lau A K H. Longterm trends of ambient particulate matter emission source contributions and the accountability of control strategies in Hong Kong over 1998–2008. Atmospheric Environment, 2013, 76: 21–31
https://doi.org/10.1016/j.atmosenv.2012.09.026
4 Lu Q, Zheng J Y, Ye S Q, Shen X L, Yuan Z B, Yin S S. Emission trends and source characteristics of SO2, NOx, PM10 and VOCs in the Pearl River Delta region from 2000 to 2009. Atmospheric Environment, 2013, 76: 11–20
https://doi.org/10.1016/j.atmosenv.2012.10.062
5 Wang X, Chen W, Chen D, Wu Z, Fan Q. Long-term trends of fine particulate matter and chemical composition in the Pearl River Delta Economic Zone (PRDEZ), China. Frontiers of Environmental Science and Engineering, 2016, 10(1): 53–62
https://doi.org/10.1007/s11783-014-0728-z
6 Martin R V. Satellite remote sensing of surface air quality. Atmospheric Environment, 2008, 42(34): 7823–7843
https://doi.org/10.1016/j.atmosenv.2008.07.018
7 Hoff R M, Christopher S A. Remote sensing of particulate pollution from space: have we reached the Promised Land. Journal of the Air & Waste Management Association, 2009, 59(6): 645–675
8 Zhang L. Intercontinental transport of air pollution. Frontiers of Environmental Science and Engineering, 2010, 4(1): 20–29
https://doi.org/10.1007/s11783-010-0014-7
9 Streets D G, Canty T, Carmichael G R, de Foy B, Dickerson R R, Duncan B N, Edwards D P, Haynes J A, Henze D K, Houyoux M R, Jacob D J, Krotkov N A, Lamsal L N, Liu Y, Lu Z, Martin R V, Pfister G G, Pinder R W, Salawitch R J, Wecht K J. Emissions estimation from satellite retrievals: a review of current capability. Atmospheric Environment, 2013, 77: 1011–1042
https://doi.org/10.1016/j.atmosenv.2013.05.051
10 Massie S T, Torres O, Smith S J. Total ozone mapping spectrometer (TOMS) observations of increases of Asian aerosol in winter from 1979 to 2000. Journal of Geophysical Research, 2004, 109(D18): D18211
https://doi.org/10.1029/2004JD004620
11 Yoon J, Burrows J P, Vountas M, von Hoyningen-Hueue W. Changes in atmospheric aerosol loadings retrieved from space-based measurements during the past decade. Atmospheric Chemistry and Physics, 2014, 14(13): 6881–6902
https://doi.org/10.5194/acp-14-6881-2014
12 Wang Y, Zhang Y, Hao J. Review on the applications of tropospheric emissions spectrometer to air-quality research: perspectives for China. Frontiers of Environmental Science and Engineering, 2010, 4(1): 12–19
https://doi.org/10.1007/s11783-010-0012-9
13 Zhang Q, Streets D G, He K, Wang Y, Richter A, Burrows J P, Uno I, Jang C J, Chen D, Yao Z, Lei Y. NOx emissions trends for China, 1995–2004: the view from the ground and the view from space. Journal of Geophysical Research, 2007, 112(D22): D22306
https://doi.org/10.1029/2007JD008684
14 Itahashi S, Uno I, Yumimono K, Irie H, Osada K, Ogata K, Fukushima H, Wang Z, Ohara T.Interannual variation in the fine-mode MODIS aerosol optical depth and its relationship to the changes in sulfur dioxide emissions in China between 2000 and 2010. Atmospheric Chemistry and Physics, 2012, 12(5): 2631–2640
https://doi.org/10.5194/acp-12-2631-2012
15 Wang S, Xing J, Chatani S, Hao J, Klimont Z, Cofala J, Amann M. Verification of anthropogenic emissions of China by satellite and ground observations. Atmospheric Environment, 2011, 45(35): 6347–6358
https://doi.org/10.1016/j.atmosenv.2011.08.054
16 Lu Z, Zhang Q, Streets D G. Sulfur dioxide and primary carbonaceous aerosol emissions in China and India, 1996–2010. Atmospheric Chemistry and Physics, 2011, 11(18): 9839–9864
https://doi.org/10.5194/acp-11-9839-2011
17 De Smedt I, Stavrakou T, Müller J F, van der A R J, Van Roozendael M. van der A and Van Roozendael. Trend detection in satellite observations for formaldehyde tropospheric columns. Geophysical Research Letters, 2010, 37(18): L18808 doi:10.1029/2010GL044245
18 Zhang Y, 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. Regional ozone pollution and observation-based approach for analyzing ozone-precursor relationship during the PRIDE-PRD 2004 campaign. Atmospheric Environment, 2008, 42(25): 6203–6218
https://doi.org/10.1016/j.atmosenv.2008.05.002
19 Lo J C F, Lau A K H, Fung J C H, Chen F. Investigation of enhanced cross-city transport and trapping of air pollutants by coastal and urban land-sea breeze circulations. Journal of Geophysical Research, 2006, 111: D14104
20 Wu D, Tie X X, Li C C, Ying Z M, Lau A K H, Huang J. An extremely low visibility event over the Guangzhou region: a case study. Atmospheric Environment, 2005, 39(35): 6568–6577
https://doi.org/10.1016/j.atmosenv.2005.07.061
21 Zheng J Y, Zhang L J, Che W W, Zheng Z Y, Yin S S. A highly resolved temporal and spatial air pollutant emission inventory for the Pearl River Delta region, China and its uncertainty assessment. Atmospheric Environment, 2009, 43(32): 5112–5122
https://doi.org/10.1016/j.atmosenv.2009.04.060
22 GDPBS (Guangdong Provincial Bureau of Statistic). 2006–2015. Guangdong Statistical Year books from 2006 to 2015. Available at: (in Chinese)
23 Kaufman Y J, Tanré D, Remer L A, Vermote E F, Chu A, Holben B N. Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. Journal of Geophysical Research, 1997, 102(D14): 17051–17067
https://doi.org/10.1029/96JD03988
24 Tanré D, Kaufman Y J, Herman M, Mattoo S. Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiances. Journal of Geophysical Research, 1997, 102(D14): 16971–16988
https://doi.org/10.1029/96JD03437
25 Remer L A, Kaufman Y J, Tanré D, Mattoo S, Chu D A, Martins J V, Li R R, Ichoku C, Levy R C, Kleidman R G, Eck T F, Vermote E, Holben B N. The MODIS aerosol algorithm, products, and validation. Journal of the Atmospheric Sciences, 2005, 62(4): 947–973
https://doi.org/10.1175/JAS3385.1
26 Abdou W A, Diner D J, Martonchik J V, Bruegge C J, Kahn R A, Gaitley B J, Crean K A, Remer L A, Holben B. Comparison of coincident multiangle imaging spectroradiometer and moderate resolution imaging spectroradiometer aerosol optical depths over land and ocean scenes containing aerosol robotic network sites. Journal of Geophysical Research, 2005, 110(D10): D10S07
https://doi.org/10.1029/2004JD004693
27 Levelt P F, van den Oord G H J, Dobber M R, Malkki A, Visser H, de Vries J, Stammes P, Lundell J O, Saari H. The ozone monitoring instrument. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(5): 1093–1101
https://doi.org/10.1109/TGRS.2006.872333
28 Boersma K F, Eskes H J, Veefkind J P, Brinksma E J. van der A R J, Sneep M, van den Oord G H J,, Levelt P F, Stammes P, Gleason J F, Bucsela E J. Near-real time retrieval of tropospheric NO2 from OMI. Atmospheric Chemistry and Physics, 2007, 6(6): 2013–2128
29 Boersma K F, Eskes H J, Brinksma E J. Error analysis for tropospheric NO2 retrieval from space. Journal of Geophysical Research, 2004, 109(D4): D04311
https://doi.org/10.1029/2003JD003962
30 Chance K, Palmer P I, Spurr R J D, Martin R V, Kurosu T P, Jacob D J. Satellite observations of formaldehyde over North America from GOME. Geophysical Research Letters, 2000, 27(21): 3461–3464
https://doi.org/10.1029/2000GL011857
31 Krotkov N A, Carn S A, Krueger A J, Bhartia P K, Kai Yang. Band residual difference algorithm for retrieval of SO2 from the Aura Ozone Monitoring Instrument (OMI). IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(5): 1259–1266
https://doi.org/10.1109/TGRS.2005.861932
32 Krotkov N A, McClure B, Dickerson R R, Carn S A, Li C, Bhartia P K, Yang K, Krueger A J, Li Z, Levelt P F, Chen H, Wang P, Lu D. Validation of SO2 retrievals from the ozone monitoring instrument over NE China. Journal of Geophysical Research, 2008, 113(D16): D16S40
https://doi.org/10.1029/2007JD008818
33 De Smedt I, Muller J F, Stavrakou T, van der A R, Eskes H, Van Roozendael M. Twelve years of global observations of formaldehyde in the troposphere using GOME and SCIAMACHY sensors. Atmospheric Chemistry and Physics, 2008, 8(16): 4947–4963
https://doi.org/10.5194/acp-8-4947-2008
34 Abad G GLiu X, Chance K, Wang H, Kurosu T P, Suleiman R. Updated smithsonian astrophysical observatory ozone monitoring instrument (SAO OMI) formaldehyde retrieval. Atmospheric Measurement Techniques, 2014, 8(1): 19–32
https://doi.org/10.5194/amt-8-19-2015
35 GDEPA (Guangdong Environmental Protection Agency). 2005–2014. Environment Statistical Bulletin of Guangdong (2005 to 2014). Available at: (in Chinese)
36 Rutkowska A. Properties of the Cox–Stuart test for trend in application to hydrological series: the simulation study. Communications in Statistics– Simulation and Computation, 2015, 44(3): 565–579
https://doi.org/10.1080/03610918.2013.784988
37 Kanakidou M, Seinfeld J H, Pandis S N, Barnes I, Dentener F J, Facchini M C, Van Dingenen R, Ervens B, Nenes A, Nielsen C J, Swietlicki E, Putaud J P, Balkanski Y, Fuzzi S, Horth J, Moortgat G K, Winterhalter R, Myhre C E L, Tsigaridis K, Vignati E, Stephanou E G, Wilson J. Organic aerosol and global climate modelling: a review. Atmospheric Chemistry and Physics, 2005, 5(4): 1053–1123
https://doi.org/10.5194/acp-5-1053-2005
38 Parrish D D, Ryerson T B, Mellqvist J, Johansson J, Fried A, Richter D, Walega J G, Washenfelder R A, de Gouw J A, Peischl J, Aikin K C, McKeen S A, Frost G J, Fehsenfeld F C, Herndon S C. Primary and secondary sources of formaldehyde in urban atmospheres: Houston Texas region. Atmospheric Chemistry and Physics, 2012, 12(7): 3273–3288
https://doi.org/10.5194/acp-12-3273-2012
39 Qu W J, Arimoto R, Zhang Y X, Zhao C H, Wang Y Q, Sheng L F, Fu G. Spatial distribution and interannual variation of surace PM10 concentrations over eighty-six Chinese cities. Atmospheric Chemistry and Physics, 2010, 10(12): 5641–5662
https://doi.org/10.5194/acp-10-5641-2010
40 Barnaba F, Putaud J P, Gruening C, dell’Acqua A, Dos Santos S. Annual cycle in collocated in situ, total-column, and height-resolved aerosol observations in the Po Valley (Italy): implications for ground-level particulate matter mass concentration estimation from remote sensing. Journal of Geophysical Research, 2010, 115(D19): D19209
https://doi.org/10.1029/2009JD013002
Related articles from Frontiers Journals
[1] Xuemei WANG,Weihua CHEN,Duohong CHEN,Zhiyong WU,Qi Fan. Long-term trends of fine particulate matter and chemical composition in the Pearl River Delta Economic Zone (PRDEZ), China[J]. Front. Environ. Sci. Eng., 2016, 10(1): 53-62.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed