Skip to main content

Advertisement

SpringerLink
Log in

An evaluation of air quality modeling over the Pearl River Delta during November 2006

  • Original Paper
  • Published:
Meteorology and Atmospheric Physics Aims and scope Submit manuscript

Abstract

In this paper, we evaluate the performance of several air quality models using the Pearl River Delta (PRD) region, including the Nested Air Quality Prediction Modeling System (NAQPMS), the Community Multiscale Air Quality (CMAQ) model, and the Comprehensive Air Quality Model with extensions (CAMx). All three model runs are based on the same meteorological fields generated by the Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) and the same emission inventories. The emission data are processed by the Sparse Matrix Operator Kernel Emissions (SMOKE) model, with the inventories generated from the Transport and Chemical Evolution over the Pacific/Intercontinental Chemical Transport Experiment Phase B (TRACE-P/INTEX-B) and local emission inventory data. The results show that: (1) the meteorological simulation of the MM5 model is reasonable compared with the observations at the regional background and urban stations. (2) The models have different advantages at different stations. The CAMx model has the best performance for SO2 simulation, with the lowest mean normalized bias (MNB) and mean normalized error (MNE) at most of the Guangzhou stations, while the CMAQ model has the lowest normalized mean square error (NMSE) value for SO2 simulation at most of the other PRD urban stations. The NAQPMS model has the best performance in the NO2 simulation at most of the Guangzhou stations. (3) The model performance at the Guangzhou stations is better than that at the other stations, and the emissions may be underestimated in the other PRD cities. (4) The PM10 simulation has the best model measures of FAC2 (fraction of predictions within a factor of two of the observations) (average 53–56%) and NMSE (0.904–1.015), while the SO2 simulation has the best concentration distribution compared with the observations, according to the quantile–quantile (Q–Q) plots.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • An X, Zhu T, Wang Z, Li C, Wang Y (2007) A modeling analysis of a heavy air pollution episode occurred in Beijing. Atmos Chem Phys 7:3103–3114. doi:10.5194/acp-7-3103-2007

    Article  Google Scholar 

  • Binkowski FS, Roselle SJ (2003) Models-3 community multiscale air quality (CMAQ) model aerosol component 1. Model description. J Geophys Res Atmos 108(D6):4183. doi:10.1029/2001JD001409

    Article  Google Scholar 

  • Byun DW, Ching JKS (1999) Science algorithms of the EPA Models-3 Community Multi-scale Air Quality (CMAQ) Modeling System. EPA/600/R-99/030. National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC. Available online at: http://www.epa.gov/AMD/CMAQ/000_cover_exec.pdf

  • Byun D, Schere KL (2006) Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. Appl Mech Rev 59(1–6):51–77

    Article  Google Scholar 

  • Chan CK, Yao XH (2008) Air pollution in mega cities in China. Atmos Environ 42(1):1–42

    Article  Google Scholar 

  • Chang JC, Hanna SR (2004) Air quality model performance evaluation. Meteorol Atmos Phys 87:167–196

    Article  Google Scholar 

  • Chen XL, Feng YR, Li JN, Lin WS, Fan SJ, Wang AY, Fong SK, Lin H (2009) Numerical simulations on the effect of sea-land breezes on atmospheric haze over the Pearl River Delta region. Environ Model Assess 14(3):351–363

    Article  Google Scholar 

  • Cheng SY, Chen DS, Li JB, Wang HY, Guo XR (2007) The assessment of emission-source contributions to air quality by using a coupled MM5-ARPS-CMAQ modeling system: a case study in the Beijing metropolitan region, China. Environ Model Softw 22(11):1601–1616

    Article  Google Scholar 

  • Colle BA, Westrick KJ, Mass CF (1999) Evaluation of MM5 and Eta-10 precipitation forecasts over the Pacific Northwest during the cool season. Weather Forecast 14:137–156

    Article  Google Scholar 

  • Cruickshank TS (2008) CMAQ sensitivity to winter-time ground surface albedo. In: Proceedings of the 7th Annual Community Modeling and Analysis (CMAS) Conference: Model Evaluation and Analysis, Chapel Hill, NC, October 2008

  • Demerjian KL, Schere KL, Peterson JT (1980) Theoretical estimates of actinic (spherically integrated) flux and photolytic rate constants of atmospheric species in the lower troposphere. Adv Environ Sci Tech 10:369–459

    Google Scholar 

  • Deng XJ, Tie XX, Zhou XJ, Wu D, Zhong LJ, Tan HB, Li F, Huang XY, Bi XY, Deng T (2008) Effects of Southeast Asia biomass burning on aerosols and ozone concentrations over the Pearl River Delta (PRD) region. Atmos Environ 42(36):8493–8501

    Article  Google Scholar 

  • ENVIRON (2002) User’s guide to the Comprehensive Air Quality Modeling System with Extensions (CAMx), version 4.4.. ENVIRON International Corporation, Novato, CA, pp 10, 16, 29, 30, 38–40

  • Feng YR, Wang AY, Wu D, Xu XD (2007) The influence of tropical cyclone Melor on PM10 concentrations during an aerosol episode over the Pearl River Delta region of China: numerical modeling versus observational analysis. Atmos Environ 41(21):4349–4365

    Article  Google Scholar 

  • Guangdong Provincial Environmental Protection Monitoring Centre (GDEMC), Hong Kong Environmental Protection Department (HKEPD) (2007) Pearl River Delta regional air quality monitoring network: a report of monitoring results in 2006, pp 1–15. http://www.epd.gov.hk/epd/english/resources_pub/publications/files/PRD_2006_report_en.pdf

  • Guangdong Provincial Environmental Protection Monitoring Centre (GDEMC), Hong Kong Environmental Protection Department (HKEPD) (2009) Pearl River Delta regional air quality monitoring network: a report of monitoring results for the period between January and June 2009, pp 1–10. http://www.epd.gov.hk/epd/english/resources_pub/publications/files/PRD2009_1-6e.pdf

  • Gery MW, Whitten GZ, Killus JP, Dodge MC (1989) A photochemical kinetics mechanism for urban and regional scale computer modeling. J Geophys Res Atmos 94(D10):12.925–12.956

    Article  Google Scholar 

  • Grell GA, Dudhia J, Stauffer DR (1994) A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Technical Note NCAR/TN-398+ STR. National Center for Atmospheric Research (NCAR), Boulder, CO

  • Houyoux MR, Vukovich JM (1999) Updates to the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System and Integration with Models-3. Environmental Programs MCNC, North Carolina Supercomputing Center, 3021 Cornwallis Road, Research Triangle Park, NC, 27709–2889

  • Huang MY, Wang ZF, He DY, Xu HY, Zhou L (1995) Modeling studies on sulfur deposition and transport in East Asia. Water Air Soil Pollut 85(4):1921–1926

    Article  Google Scholar 

  • Li J, Wang ZF, Akimoto H, Gao C, Pochanart P, Wang X (2007) Modeling study of ozone seasonal cycle in lower troposphere over east Asia. J Geophys Res 112(D22S25). doi:10.1029/2006JD008209

  • Lo JCF, Lau AKH, Chen F, Fung JCH, Leung KKM (2007) Urban modification in a mesoscale model and the effects on the local circulation in the Pearl River Delta region. J Appl Meteor Climatol 46:457–476

    Article  Google Scholar 

  • Madronich S (2002) Tropospheric Ultraviolet and Visible (TUV) Radiation Model. National Center for Atmospheric Research (NCAR), Boulder, CO. Home page at: http://www.acd.ucar.edu/TUV/

  • Padro J, den Hartog G, Neumann HH (1991) An investigation of the ADOM dry deposition module using summertime O3 measurements above a deciduous forest. Atmos Env Part A General Topics 25(8):1689–1704

    Article  Google Scholar 

  • Seinfeld JH, Pandis SN (1998) Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & Sons, Inc., New York

    Google Scholar 

  • Strader R, Lurmann F, Pandis SN (1999) Evaluation of secondary organic aerosol formation in winter. Atmos Environ 33:4849–4863

    Article  Google Scholar 

  • Streets DG, Bond TC, Carmichael GR, Fernandes SD, Fu Q, He D, Klimont Z, Nelson SM, Tsai NY, Wang MQ, Woo J-H, Yarber KF (2003) An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. J Geophys Res 108(D21):8809. doi:10.1029/2002JD003093

    Article  Google Scholar 

  • Streets DG, Zhang Q, Wang LT, He KB, Hao JM, Wu Y, Tang YH, Carmichael GR (2006) Revisiting China’s CO emissions after the Transport and Chemical Evolution over the Pacific (TRACE-P) mission: synthesis of inventories, atmospheric modeling, and observations. J Geophys Res Atmos 111(D14306). doi:10.1029/2006JD007118

  • Tesche TW, Morris R, Tonnesen G, McNally D, Boylan J, Brewer P (2006) CMAQ/CAMx annual 2002 performance evaluation over the eastern US. Atmos Environ 40(26):4906–4919

    Article  Google Scholar 

  • Walcek CJ, Aleksic NM (1998) A simple but accurate mass conservative, peak-preserving, mixing ratio bounded advection algorithm with FORTRAN code. Atmos Environ 32:3863–3880

    Article  Google Scholar 

  • Wang ZF, Sha WM, Ueda H (2000) Numerical modeling of pollutant transport and chemistry during a high-ozone event in northern Taiwan. Tellus B 52(5):1189–1205

    Article  Google Scholar 

  • Wang ZF, Maeda T, Hayashi M, Hsiao L-F, Liu K-Y (2001) A nested air quality prediction modeling system for urban and regional scales: application for high-ozone episode in Taiwan. Water Air Soil Pollut 130:391–396

    Article  Google Scholar 

  • Wang ZF, Akimoto H, Uno I (2002) Neutralization of soil aerosol and its impact on the distribution of acid rain over east Asia: observations and model results. J Geophys Res 107(D19):4389

    Article  Google Scholar 

  • Wang XM, Carmichael G, Chen DL, Tang YH, Wang TJ (2005) Impacts of different emission sources on air quality during March 2001 in the Pearl River Delta (PRD) region. Atmos Environ 39(29):5227–5241

    Article  Google Scholar 

  • Wang Z-F, Xie F-Y, Wang X-Q, An J-L, Zhu J (2006a) Development and application of nested air quality prediction modeling system. Chin J Atmos Sci 30:778–790 (in Chinese)

    Google Scholar 

  • Wang ZF, Li J, Wang XQ, Pochanart P, Akimoto H (2006b) Modeling of regional high ozone episode observed at two mountain sites (Mt. Tai and Huang) in East China. J Atmos Chem 55(3):253–272

    Article  Google Scholar 

  • Wang W, Ren LH, Zhang YH, Chen JH, Liu HJ, Bao LF, Fan SJ, Tang DG (2008) Aircraft measurements of gaseous pollutants and particulate matter over Pearl River Delta in China. Atmos Environ 42(25):6187–6202

    Article  Google Scholar 

  • Wang XM, Chen F, Wu ZY, Zhang MG, Tewari M, Guenther A, Wiedinmyer C (2009a) Impacts of weather conditions modified by urban expansion on surface ozone: comparison between the Pearl River Delta and Yangtze River Delta regions. Adv Atmos Sci 26(5):962–972

    Article  Google Scholar 

  • Wang ZF, Wu QZ, Gbaguidi AE, Yan PZ, Zhang W, Wang W, Tang X (2009b) Ensemble air quality multi-model forecast system for Beijing (EMS-Beijing): model description and preliminary application. J Nanjing University Inform Sci Technol: Natural Science Edition 1(1):19–26 (in Chinese)

    Google Scholar 

  • Wu QZ, Wang ZF, Xu WS, Huang JP, Gbaguidi A (2010a) Multi-model simulation of PM10 during the 2008 Beijing Olympic Games: effectiveness of emission restrictions. Acta Scientiae Circumstantiae 30(9):1739–1748 (in Chinese)

    Google Scholar 

  • Wu QZ, Wang ZF, Gbaguidi A, Tang X, Zhou W (2010b) Numerical study of the effect of traffic restriction on air quality in Beijing. SOLA 6A:17–20. doi:10.2151/sola.6A-005

    Article  Google Scholar 

  • Wu QZ, Wang ZF, Gbaguidi A, Gao C, Li LN, Wang W (2011) A numerical study of contributions to air pollution in Beijing during CAREBeijing-2006. Atmos Chem Phys 11:5997–6011. doi:10.5194/acp-11-5997-2011

    Article  Google Scholar 

  • Zaveri RA, Peters LK (1999) A new lumped structure photochemical mechanism for large-scale applications. J Geophys Res 104(D23):30387–30415

    Article  Google Scholar 

  • Zhang MG, Uno I, Zhang RJ, Han ZW, Wang ZF, Pu YF (2006) Evaluation of the Models-3 Community Multi-scale Air Quality (CMAQ) modeling system with observations obtained during the TRACE-P experiment: comparison of ozone and its related species. Atmos Environ 40(26):4874–4882

    Article  Google Scholar 

  • Zhang Q, Streets DG, He KB, Wang YX, Richter A, Burrows JP, Uno I, Jang CJ, Chen D, Yao ZL, Lei Y (2007) NOx emission trends for China, 1995–2004: the view from the ground and the view from space. J Geophys Res Atmos 112(D22306). doi:10.1029/2007JD008684

  • Zhang YH, Hu M, Zhong LJ, Wiedensohler A, Liu SC, Andreae MO, Wang W, Fan SJ (2008) Regional integrated experiments on air quality over Pearl River Delta 2004 (PRIDE-PRD2004): overview. Atmos Environ 42(25):6157–6173

    Article  Google Scholar 

  • Zhang Q, Streets DG, Carmichael GR, He KB, Huo H, Kannari A, Klimont Z, Park IS, Reddy S, Fu JS, Chen D, Duan L, Lei Y, Wang LT, Yao ZL (2009) Asian emissions in 2006 for the NASA INTEX-B mission. Atmos Chem Phys 9(14):5131–5153

    Article  Google Scholar 

  • Zheng JY, Zhang LJ, Che WW, Zheng ZY, Yin SS (2009) A highly resolved temporal and spatial air pollutant emission inventory for the Pearl River Delta region, China and its uncertainty assessment. Atmos Environ 43(32):5112–5122

    Article  Google Scholar 

  • Zhou W, Wang X, Zhou TJ, Li CY, Chan JCL (2007a) Interdecadal variability of the relationship between the East Asian winter monsoon and ENSO. Meteorol Atmos Phys 98:283–293. doi:10.1007/s00703-007-0263-6

    Article  Google Scholar 

  • Zhou W, Li CY, Wang X (2007b) Possible connection between Pacific oceanic interdecadal pathway and East Asian winter monsoon. Geophys Res Lett 34(L01701). doi:10.1029/2006GL027809

  • Zhou W, Chan JCL, Chen W, Ling J, Pinto JG, Shao YP et al (2009) Synoptic-scale controls of persistent low temperature and icy weather over southern China in January 2008. Mon Wea Rev 137:3978–3991. doi:10.1175/2009MWR2952.1

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National High Technology Research and Development Program of China (No. 2010AA012305) and Hong Kong ECF project 9211008.

Author information

Authors and Affiliations

  1. College of Global Change and Earth System Science, Beijing Normal University, Beijing, China

    Qizhong Wu

  2. LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Zifa Wang & Huansheng Chen

  3. Graduate University of Chinese Academy of Sciences, Beijing, China

    Huansheng Chen

  4. Guy Carpenter Asia–Pacific Climate Impact Center, School of Energy and Environment, City University of Hong Kong, Hong Kong, China

    Qizhong Wu, Wen Zhou & Mark Wenig

Authors
  1. Qizhong Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zifa Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huansheng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wen Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mark Wenig
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wen Zhou.

Additional information

Responsible editor: S. Trini Castelli.

Electronic supplementary material

Appendices

Appendices

The normalized mean square error (NMSE): \( {\text{NMSE}} = \frac{{\overline{{\left( {C_{o} - C_{p} } \right)^{2} }} }}{{C_{o} \times C_{p} }} \)

FAC2 (fraction of predictions within a factor of two of the observations) = fraction of data that satisfies: \( 0.5 \le \frac{{C_{p} }}{{C_{o} }} \le 2 \)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wu, Q., Wang, Z., Chen, H. et al. An evaluation of air quality modeling over the Pearl River Delta during November 2006. Meteorol Atmos Phys 116, 113–132 (2012). https://doi.org/10.1007/s00703-011-0179-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00703-011-0179-z

Keywords

Search

Navigation