Skip to main content
Log in

Using Bayesian optimization method and FLEXPART tracer model to evaluate CO emission in East China in springtime

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

Carbon monoxide (CO) is of great interest as a restriction factor for pollutants related to incomplete combustions. This study attempted to evaluate CO emission in East China using the analytical Bayesian inverse method and observations at Mount Hua in springtime. The mixing ratio of CO at the receptor was calculated using 5-day source-receptor relationship (SRR) simulated by a Lagrangian Particle Dispersion Model (FLEXPART) and CO emission flux. The stability of the inversion solution was evaluated on the basis of repeated random sampling simulations. The inversion results demonstrated that there were two city cluster regions (the Beijing–Tianjin–Hebei region and the low reaches of the Yangtze River Delta) where the difference between a priori (Intercontinental Chemical Transport Experiment-Phase B, INTEX-B) and a posteriori was statistically significant and the a priori might underestimate the CO emission flux by 37 %. A correction factor (a posteriori/a priori) of 1.26 was suggested for CO emission in China in spring. The spatial distribution and magnitude of the CO emission flux were comparable to the latest regional emission inventory in Asia (REAS2.0). Nevertheless, further evaluation is still necessary in view of the larger uncertainties for both the analytical inversion and the bottom-up statistical approaches.

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

Access this article

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Jacob DJ, Crawford JH, Kleb MM, Connors VS, Bendura RJ, Raper JL, Sachse GW, Gille JC, Emmons L, Heald CL (2003) Transport and chemical evolution over the pacific (TRACE-P) aircraft mission: design, execution, and first results. J Geophys Res 108(D20):9000

    Article  Google Scholar 

  • Jaffe D, Anderson T, Covert D, Kotchenruther R, Trost B, Danielson J, Simpson W, Berntsen T, Karlsdottir S, Blake D (1999) Transport of Asian air pollution to North America. Geophys Res Lett 26(6):711–714

    Article  CAS  Google Scholar 

  • Kondo, Y., N. Oshima, M. Kajino, R. Mikami, N. Moteki, N. Takegawa, R. L. Verma, Y. Kajii, S. Kato, and A. Takami (2011), Emissions of black carbon in East Asia estimated from observations at a remote site in the East China Sea, Journal of Geophysical Research, 116(D16201), doi:10.1029/2011JD015637

  • Kopacz M, Jacob D, Fisher J, Logan J, Zhang L, Megretskaia I, Yantosca R, Singh K, Henze D, Burrows J (2010) Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES), Atmos. Chem Phys 10(3):855–876

    CAS  Google Scholar 

  • Liang Q, Jaeglé L, Jaffe DA, Weiss-Penzias P, Heckman A, Snow JA (2004) Long-range transport of Asian pollution to the northeast Pacific: seasonal variations and transport pathways of carbon monoxide. J Geophys Res 109(D23):16. doi:10.1029/2003JD004402

    Google Scholar 

  • Menke W (1984) Geophysical data analysis: Discrete inverse theory. Academic, New York

    Google Scholar 

  • 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 period 1980–2020. Atmos Chem Phys 7(16):4419–4444

    Article  CAS  Google Scholar 

  • Palmer PI, Jacob DJ, Jones DB, Heald CL, Yantosca RM, Logan JA, Sachse GW, Streets DG (2003) Inverting for emissions of carbon monoxide from Asia using aircraft observations over the western Pacific. J Geophys Res 108(D21):8828

    Article  Google Scholar 

  • Pan XL, Yan P, Tang J, Ma JZ, Wang ZF, Gbaguidi A, and Sun YL (2009) Observational study of influence of aerosol hygroscopic growth on scattering coefficient over rural area near Beijing mega-city. Atmos Chem Phys 9:7519–7530

    Google Scholar 

  • Pan XL, Kanaya Y, Wang ZF, Liu Y, Pochanart P, Akimoto H, Sun YL, Dong HB, Li J, Irie H, and Takigawa M (2011) Correlation of black carbon aerosol and carbon monoxide in the high-altitude environment of Mt. Huang in Eastern China. Atmos Chem Phys 11:9735–9747. doi:10.5194/acp-11-9735-2011

    Google Scholar 

  • Pan XL, Kanaya Y, Wang ZF, Taketani F, Tanimoto H, Irie H, Takashima H, Inomata H (2012) Emission ratio of carbonaceous aerosols observed near crop residual burning sources in a rural area of the Yangtze River Delta Region, China. J Geophys Res: Atmosphere 117(D22)

  • Pan XL, Kanaya Y, Wang ZF, Komazaki Y, Taketani F, Akimoto H, Pochanart P (2013) Variations of carbonaceous aerosols from open crop residue burning with transport and its implication to estimate their lifetimes. Atmos Environ 74:301–310

    Google Scholar 

  • Seibert P, Frank A (2004) Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode. Atmos Chem Phys 4(1):51–63

    Article  CAS  Google Scholar 

  • Stohl A, Forster C, Frank A, Seibert P, Wotawa G (2005) Technical note: the Lagrangian particle dispersion model FLEXPART version 6.2. Atmos Chem Phys Discuss 5(4):4739–4799

    Article  Google Scholar 

  • Stohl A, Seibert P, Arduini J, Eckhardt S, Fraser P, Greally B, Lunder C, Maione M, Mühle J, O’Doherty S (2009) An analytical inversion method for determining regional and global emissions of greenhouse gases: sensitivity studies and application to halocarbons. Atmos Chem Phys 9:1597–1620

    Article  CAS  Google Scholar 

  • Stohl A, Kim J, Li S, O’Doherty S, Mühle J, Salameh P, Saito T, Vollmer M, Wan D, Weiss R (2010) Hydrochlorofluorocarbon and hydrofluorocarbon emissions in East Asia determined by inverse modeling. Atmos Chem Phys 10:3545–3560

    Article  CAS  Google Scholar 

  • Tang X, Zhu J, Wang ZF, Wang M, Gbaguidi A, Li J, Shao M, Tang GQ, Ji DS (2013) Inversion of CO emissions over Beijing and its surrounding areas with ensemble Kalman filter. Atmos Environ 81:1–11

    Article  Google Scholar 

  • Tanimoto H, Sawa Y, Yonemura S, Yumimoto K, Matsueda H, Uno I, Hayasaka T, Mukai H, Tohjima Y, Tsuboi K (2008) Diagnosing recent CO emissions and ozone evolution in East Asia using coordinated surface observations, adjoint inverse modeling, and MOPITT satellite data. Atmos Chem Phys 8(14):3867–3880

    Article  CAS  Google Scholar 

  • Zhang Q, Streets DG, Carmichael GR et al (2009) Asian emissions in 2006 for the NASA INTEX-B mission. Atmos Chem Phys 9(14):5131–5153

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors would like to thank all the researchers who contributed to the field measurements, and we gratefully acknowledge Dr. K. Yamaji for the helpful comments and suggestions. This work was supported by the Global Environment Research Fund (S-7, C-081, B-051) from the Ministry of the Environment, Japan.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to X. L. Pan.

Additional information

Responsible editor: Michael Matthies

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Figure 1

(DOC 32 kb)

Supplementary Figure 2

(DOC 500 kb)

Supplementary Figure 3

(DOC 88 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pan, X.L., Kanaya, Y., Wang, Z.F. et al. Using Bayesian optimization method and FLEXPART tracer model to evaluate CO emission in East China in springtime. Environ Sci Pollut Res 21, 3873–3879 (2014). https://doi.org/10.1007/s11356-013-2317-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-013-2317-2

Keyword