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Analysis of atmospheric SO2 in Sichuan-Chongqing region based on OMI data

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Abstract

The Sichuan-Chongqing region is the leader and growth pole of economic development in western China. With the rapid development of economy and unique geographical environment, high concentration of sulfur dioxide air pollution has existed for a long time in Sichuan-Chongqing area. Based on 10 years of remote sensing data, this paper studies the temporal and spatial distribution characteristics, stability, and influencing factors of sulfur dioxide in this area. Based on potential sources, the impact of surrounding areas on sulfur dioxide in Sichuan and Chongqing is analyzed. The results shows that the spatial distribution of sulfur dioxide in the Sichuan-Chongqing region is higher in the southeast and lower in the west. The Midwest region has low fluctuation and good stability. The time distribution shows obvious seasonal regularity. The concentration of sulfur dioxide is affected by socio-economic factors and natural factors. In this study, it is found that the distribution of sulfur dioxide is closely related to PM2.5, which provides an important reference for the comprehensive management of air pollution. The OMI data effectively reflects the distribution and change of atmospheric sulfur dioxide in the Sichuan-Chongqing region, and provides certain ideas for air pollution control in the Sichuan-Chongqing region and other regions in China.

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source areas in different seasons from 2015 to 2019

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Data availability

The SO2 satellite data in this study comes from NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) (https://disc.gsfc.nasa.gov). The temperature, precipitation, DEM, and other meteorological data used in this article are all from the Resource Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn). The NDVI data comes from the MOD13Q1 vegetation index data of NASA LARDS, The relevant social factor data comes from the Sichuan Provincial Bureau of Statistics and the Chongqing Municipal Statistics Information Network, and the wind direction data comes from the China Weather Network (https://www.weather.com.cn/).

References

  • Angelevska, B., Atanasova, V., & Andreevski, I. (2021). Urban air quality guidance based on measures categorization in road transport. Civil Engineering Journal, 7(2), 253-267. https://doi.org/10.28991/cej-2021-03091651

  • Cetin, M., Onac, A. K., Sevik, H., et al. (2019). Temporal and regional change of some air pollution parameters in Bursa. Air Quality, Atmosphere and Health, 12, 311–316. https://doi.org/10.1007/s11869-018-00657-6

    Article  CAS  Google Scholar 

  • Cetin, S. (2016a). Change of air quality in Kastamonu City in terms of particulate matter and CO2 amount. Oxidation Communications, 39(4), 3394–3401.

  • Carslaw, K. S., Lee, L. A., Reddington, C. L., Pringle, K. J., Rap, A., Forster, P. M., Mann, G. W., Spracklen, D. V., Woodhouse, M. T., Regayre, L. A., Pierce, J. R. (2013). Large contribution of natural aerosols to uncertainty in indirect forcing. Nature 503, 67e71. https://doi.org/10.1038/nature12674

  • Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, J. A., Hansen, J. E., Hofmann, D. J. (1992). Climate forcing by anthropogenic aerosols. Science, 255, 423e430. https://doi.org/10.1126/science.255.5043.423

  • Kilicoglu, C., Cetin, M., Aricak, B., & Sevik, H. (2020). (2020) Site selection by using the multi-criteria technique—A case study of Bafra. Turkey. Environ Monit Assess, 192, 608. https://doi.org/10.1007/s10661-020-08562-1

    Article  Google Scholar 

  • Gibergans-Baguena, C. Hervada-Sala, E. Jarauta-Bragulat, E., et al. (2020). The quality of urban air in Barcelona: A new approach applying compositional data analysis methods. Emerging Science Journal, 4(02), 2610–9182. https://doi.org/10.28991/esj-2020-01215

  • Cao, D. M. (2013). SO2 pollution, hazards and control technology in my country. Environmental Science Guide, 23, 73–72. https://doi.org/10.13623/j.cnki.hkdk.2013.02.031

  • Eisinger, M., Burrows, J. P. (1998). Tropospheric sulfur dioxide observed by the ERS-2GOME instrument [J]. Geophysical Research Letters, 25(22), 7177–7180. https://doi.org/10.1029/1998GL900128

  • Gao, Y., Sun, R. G., Chen, Z., Zang, Q. D. (2018). Study on the temporal and spatial distribution of SO2 concentration in the atmosphere of Chongqing City [J]. Journal of Guizhou Normal University (Natural Science Edition), 36(06), 20–27. https://doi.org/10.16614/j.gznuj.zrb.2018.06.006

  • Guo, X. M. (2016). Observational simulation research on the air quality and climatic characteristics of Sichuan Basin and the effect of large topography [D], Nanjing University of Information Science and Technology

  • Huang, Y. Y., Yang, D., Feng, L. (2019). The temporal and spatial changes of vegetation coverage in Ningxia from 2000 to 2016 and their driving forces [J]. Journal of Ecology, 38(08), 2515–2523. https://doi.org/10.13292/j.1000-4890.2019.08.016

  • Jiang, J. (2012), China’s atmospheric SO2 concentration monitoring and emission estimation based on OMI satellite data and numerical simulation [D]. Nanjing Normal University.

  • Kang, C. Y., Zhao, J., Song, G. F. (2019). Temporal and spatial changes of SO2 in the global atmospheric boundary layer from 2005 to 2017 [J]. China Environmental Science, 39(10), 4033–4042.

  • Li, R., Li, J. W., Liu, Z. J., et al. (2016). Satellite remote sensing study of the correlation between Chinese aerosol optical thickness, NO2 and SO2. Chinese Science Bulletin, 61, 2524–2535. https://doi.org/10.1360/N972016-00149

  • Lee, C., Martin, R. V., Van Donkelaar, A. et al. (2011). SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, space-based (SCIAMACHY and OMI) observations [J]. Journal of Geophysical Research Atmospheres, 116(D6), D06307.https://doi.org/10.1029/2010JD014758

  • Alsaidi, L. R., Abdulkareem, M. N., et al. (2020). Traffic congestion: Shift from private car to public transportation. Civil Engineering Journal, 6(8), 1547–1554. https://doi.org/10.28991/cej-2020-03091566

    Article  Google Scholar 

  • Li, C., Joiner, J., Krotkov, N. A., et al. (2013). A fast and sensitive new satellite SO2 retrieval algorithm based on principal component analysis: Application to the ozone monitoring instrument [J]. Geophysical Research Letters, 70(23), 6317–6318. https://doi.org/10.1002/2013GL058134

  • Lin, H. J. (2011). Preliminary discussion on the chemical characteristics of atmospheric precipitation in three typical regions of Sichuan [D]. Sichuan Agricultural University.

    Google Scholar 

  • Li, F. S., Ju, T. Z., Ma, C., et al. (2019). Absorption aerosol in Gansu province based on satellite remote sensing [J]. China Environmental Science, 39(10), 4082–4092. https://doi.org/10.19674/j.cnki.issn1000-6923.2019.0476

  • Li, Y. M. (2018). Discussion on the function of urban landscaping on air pollution prevention and control [J] Agriculture and Technology, 38(20), 222. CNKI:SUN:NYYS.0.2018-20-202

  • Lu, M., Li, Y. J. (2002). Study on the absorption and purification ability of some garden plants on air pollutants [J] Journal of Shandong Institute of Civil Engineering and Architecture, 02,45-49. CNKI:SUN:SDJG.0.2002-02-008

  • Ceti, M., Sevi, H., & Saat, A. (2017). Indoor air quality: The samples of Safranbolu Bulak Mencilis Cave. Fresenius Environmental Bulletin., 26(10), 5965–5970.

    Google Scholar 

  • Meng, X. Y., Wang, P. C., Wang, G. C., et al. (2009). Winter SO2 changes and transport characteristics in Beijing and its surrounding areas [J]. Climatic and Environmental Research, 14(03), 309–317.

    Google Scholar 

  • Cetin, M. (2016b). A change in the amount of CO2 at the center of the examination halls: Case study of Turkey. Studies on Ethno-Medicine, 10(2), 146–155.

    Article  Google Scholar 

  • Sunyer, J., et al. (2003). The association of daily sulfur dioxide air pollution levels with hospital admissions for cardiovascular diseases in Europe (the Aphea-II study). European Heart Journal, 24, 752–760.

    Article  CAS  Google Scholar 

  • Sevik, H., Cetin, M., Ozel, H. B., Ozel, S., Zeren Cetin, I. (2020). Changes in heavy metal accumulation in some edible landscape plants depending on traffic density. Environ Monit Assess. Jan 2;192(2):78. https://doi.org/10.1007/s10661-019-8041-8. PMID: 31899536

  • Sevik, H., Cetin, M., Ozel, H. B., Akarsu, H., Zeren Cetin, I. (2019). Analyzing of usability of tree-rings as biomonitors for monitoring heavy metal accumulation in the atmosphere in urban area: A case study of cedar tree (Cedrus sp.). Environmental Monitoring and Assessment Dec 10;192(1):23. https://doi.org/10.1007/s10661-019-8010-2. PMID: 31820113.

  • Shen, S. T., Yi, M. J., Dai, H. X., et al. (2020). Analysis of PM2.5 transport path and potential source contribution in Bengbu city [J]. Journal of Hefei University of Technology (Natural Science), 43(4):543–551. CNKI:SUN:HEFE.0.2020–04–018

  • Ucun Ozel, H., Ozel, H. B., Cetin, M. et al. (2019). Base alteration of some heavy metal concentrations on local and seasonal in Bartin River. Environmental Monitoring and Assessment 191, 594 .https://doi.org/10.1007/s10661-019-7753-0

  • Wang, L., et al. (2018). Associations between short-term exposure to ambient sulfur dioxide and increased cause-specific mortality in 272 Chinese cities. Environment International, 117, 33–39.

    Article  CAS  Google Scholar 

  • Wang, N. (2017). Spatial and temporal changes of air pollutants in the main urban area of Chongqing and analysis of influencing factors [D]. Chongqing Normal University.

    Google Scholar 

  • Wang, G. C., Wang, D. Q., Chen, Z. L. (2016). PM2.5 pollution characteristics and transport paths and potential source areas during severe pollution in Beijing in winter [J]. China Environmental Science, 36(7):1931–1937. doi:CNKI:SUN:ZGHJ.0.2016–07–002

  • Xiao Y, Tian Y Z, Xu W X, et al. ( 2017) Spatial and temporal distribution characteristics of air quality in China in the past 10 years [J]. Journal of Ecoenvironment, 26(2): 243–252.2. https://doi.org/10.16258/j.cnki.1674-5906.2017.02.009

  • Yang, K., Krotkov, N. A., Krueger, A. J., et al. (2007). Retrieval of large volcanic SO2 columns from the Aura Ozone Monitoring Instrument: Comparison and limitations [J]. Journal of Geophysical Research Atmospheres, 112(D27):1–17. https://doi.org/10.1029/2007JD008825

  • Yang, F., Feng, X., Ruan, L., et al. (2014). Research on the correlation between water tree branches and ultra-low frequency dielectric loss based on Pearson’s correlation coefficient method [J]. High Voltage Apparatus, 50(06):21–25+31. https://doi.org/10.13296/j.1001-1609.hva.2014.06.004

  • Yang, F. M., He, K. B. (2002). The chemical composition of fine particulate PM2.5 in Beijing’s atmosphere. [J]. Journal of Tsinghua University (Natural Science Edition), 42 (12) https://doi.org/10.16511/j.cnki.qhdxxb.2002.12.012

  • Zhang, X. Y., et al. (2021). Long-term ambient SO2 concentration and its exposure risk across China inferred from OMI observations from 2005 to 2018. Atmospheric Research, 247, 105105. https://doi.org/10.1016/j.atmosres.2020.105150

    Article  CAS  Google Scholar 

  • Zhao, H. L., Zhang, D. D., Huang, S., et al. (2019). Analysis of the relationship between the density of ground flashes and lightning failures in Hainan Province based on Pearson’s correlation coefficient [J]. High Voltage Apparatus, 55(08):186–192. https://doi.org/10.13296/j.1001-1609.hva.2019.08.026.

  • Zhang, Y. J., Ge, J. T., Xu, M., et al. (2020). Spatiotemporal dynamic distribution and influence analysis of HCHO column concentration in troposphere of Guangdong province [J]. Acta Scientiae Circumstantiae, 40(8):2869–2881. https://doi.org/10.13671/j.hjkxxb.2020.0104

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Acknowledgements

Most sincere thanks to NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) (https://disc.gsfc.nasa.gov), Resource Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn), NASA LARDS, Sichuan Provincial Bureau of Statistics and the Chongqing Municipal Statistics Information Network, and China Weather Network (https://www.weather.com.cn/) for providing the data sources.

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Authors and Affiliations

  1. College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730070, China

    Ruirui Huang, Tianzhen Ju, Jiale Duan, Jiachen Fan, Zhuohong Liang & Tunyang Geng

  2. Gansu Industry Polytechnic College, Tianshui, 730070, China

    Huiping Dong

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  1. Ruirui Huang
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Correspondence to Tianzhen Ju.

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Huang, R., Ju, T., Dong, H. et al. Analysis of atmospheric SO2 in Sichuan-Chongqing region based on OMI data. Environ Monit Assess 193, 849 (2021). https://doi.org/10.1007/s10661-021-09638-2

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