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Visibility characteristics and the impacts of air pollutants and meteorological conditions over Shanghai, China

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Abstract

In China, visibility condition has become an important issue that concerns both society and the scientific community. In order to study visibility characteristics and its influencing factors, visibility data, air pollutants, and meteorological data during the year 2013 were obtained over Shanghai. The temporal variation of atmospheric visibility was analyzed. The mean value of daily visibility of Shanghai was 19.1 km. Visibility exhibited an obvious seasonal cycle. The maximum and minimum visibility occurred in September and December with the values of 27.5 and 7.7 km, respectively. The relationships between the visibility and air pollutant data were calculated. The visibility had negative correlation with NO2, CO, PM2.5, PM10, and SO2 and weak positive correlation with O3. Meteorological data were clustered into four groups to reveal the joint contribution of meteorological variables to the daily average visibility. Usually, under the meteorological condition of high temperature and wind speed, the visibility of Shanghai reached about 25 km, while visibility decreased to 16 km under the weather type of low wind speed and temperature and high relative humid. Principle component analysis was also applied to identify the main cause of visibility variance. The results showed that the low visibility over Shanghai was mainly due to the high air pollution concentrations associated with low wind speed, which explained the total variance of 44.99 %. These results provide new knowledge for better understanding the variations of visibility and have direct implications to supply sound policy on visibility improvement in Shanghai.

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References

  • Brimblecombe, P. (1981). Long term trends in London fog. Science of the Total Environment, 22, 19–29.

    Article  Google Scholar 

  • Brown, K. W., Sarnat, J. A., Suh, H. H., Coull, B. A., & Koutrakis, P. (2009). Factors influencing relationships between personal and ambient concentrations of gaseous and particulate pollutants. Science of the Total Environment, 407, 3754–3765.

    Article  CAS  Google Scholar 

  • Chan, C. K., & Yao, X. (2008). Air pollution in mega cities in China. Atmospheric Environment, 42, 1–42.

    Article  CAS  Google Scholar 

  • Chang, D., Song, Y., & Liu, B. (2009). Visibility trends in six megacities in China 1973–2007. Atmospheric Research, 94, 161–167.

    Article  Google Scholar 

  • Che, H., Zhang, X., Li, Y., Zhou, Z., & Chen, Z. (2006). Relationship between horizontal extinction coefficient and PM10 concentration in Xian, China, during 1980–2002. China Particuology, 4, 327–329.

    Article  Google Scholar 

  • China Environmental Protection Ministry. (2012). GB3095-2012 Ambient air quality standards in China. Ministry of Environmental Protection and General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China.

  • Deng, J., Wang, T., Jiang, Z., Xie, M., Zhang, R., Huang, X., & Zhu, J. (2011). Characterization of visibility and its affecting factors over Nanjing, China. Atmospheric Research, 101, 681–691.

    Article  CAS  Google Scholar 

  • Dominick, D., Juahir, H., Latif, M. T., Zain, S. M., & Aris, A. Z. (2012). Spatial assessment of air quality patterns in Malaysia using multivariate analysis. Atmospheric Environment, 60, 172–181.

    Article  CAS  Google Scholar 

  • Du, K., Mu, C., Deng, J., & Yuan, F. (2013). Study on atmospheric visibility variations and the impacts of meteorological parameters using high temporal resolution data: an application of environmental internet of things in China. International Journal of Sustainable Development & World Ecology, 20, 238–247.

    Article  Google Scholar 

  • Feng, J. L., Chan, C. K., Fang, M., Hu, M., He, L. Y., & Tang, X. Y. (2006). Characteristics of organic matter in PM2.5 in Shanghai. Chemosphere, 64, 1393–1400.

    Article  CAS  Google Scholar 

  • Goyal, P., Kumar, A., & Mishra, D. (2014). The impact of air pollutants and meteorological variables on visibility in Delhi. Environmental Modeling and Assessment, 19, 127–138.

    Article  Google Scholar 

  • Kim, H. S., Huh, J. B., Hopke, P. K., Holsen, T. M., & Yi, S. M. (2007). Characteristics of the major chemical constituents of PM2.5 and smog events in Seoul, Korea in 2003 and 2004. Atmospheric Environment, 41, 6762–6770.

    Article  CAS  Google Scholar 

  • Li, W. J., Shao, L. Y., & Buseck, P. R. (2010). Haze types in Beijing and the influence of agricultural biomass burning. Atmospheric Chemistry and Physics, 10, 8119–8130.

    Article  CAS  Google Scholar 

  • Lin, M., Tao, J., Chan, C. Y., Cao, J. J., Zhang, Z. S., Zhu, L. H., & Zhang, R. J. (2012a). Regression analyses between recent air quality and visibility changes in megacities at four haze regions in China. Aerosol and Air Quality Research, 12, 1049–1061.

    CAS  Google Scholar 

  • Lin, M., Chan, I. N., Chan, C. Y., Engling, G., & Bloss, W. (2012b). Implications of regional surface ozone increases on visibility degradation in Southeast China. Tellus Series B, 64, 19625.

    Article  Google Scholar 

  • Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28, 129–136.

    Article  Google Scholar 

  • Louie, P. K. K., Chow, J. C., Chen, L. W. A., Watson, J. G., Leung, G., & Sin, D. W. M. (2005). PM2.5 chemical composition in Hong Kong: urban and regional variations. Science of the Total Environment, 338, 267–281.

    Article  CAS  Google Scholar 

  • Mayer, H. (1999). Air pollution in cities. Atmospheric Environment, 33, 4029–4037.

    Article  CAS  Google Scholar 

  • Meng, Z. Y., Jiang, X. M., Yan, P., Lin, W. L., Zhang, H. D., & Wang, Y. (2007). Characteristics and sources of PM2.5 and carbonaceous species during winter in Taiyuan, China. Atmospheric Environment, 41, 6901–6908.

    Article  CAS  Google Scholar 

  • Park, R. J., Jacob, D. J., Kumar, N., & Yantosca, R. M. (2006). Regional visibility statistics in the United States: natural and transboundary pollution influences, and implications for the regional haze rule. Atmospheric Environment, 40, 5405–5423.

    Article  CAS  Google Scholar 

  • Pudasainee, D., Sapkota, B., Shrestha, M. L., Kaga, A., Kondo, A., & Inoue, Y. (2006). Ground level ozone concentrations and its association with NOX and meteorological parameters in Kathmandu valley, Nepal. Atmospheric Environment, 40, 8081–8087.

    Article  CAS  Google Scholar 

  • Sabetghadam, S., Ahmadi-Givi, F., & Golestani, Y. (2012). Visibility trends in Tehran during 1958–2008. Atmospheric Environment, 62, 512–520.

    Article  CAS  Google Scholar 

  • Saini, R., Satsangi, G. S., & Taneja, A. (2008). Concentrations of surface O3, NO2 and CO during winter seasons at a semi-arid region—Agra, India. Indian Journal of Radio & Space Physics, 37, 121–130.

    CAS  Google Scholar 

  • Singh, K. P., Malik, A., & Sinha, S. (2005). Water quality assessment and apportionment of pollution sources of Gomti River (India) using multivariate statistical techniques—a case study. Analytica Chimica Acta, 538, 355–374.

    Article  CAS  Google Scholar 

  • Song, F., Shin, J. Y., Jusino-Atresino, R., & Gao, Y. (2011). Relationships among the springtime ground-level NOX, O3 and NO3 in the vicinity of highways in the US East Coast. Atmospheric Pollution Research, 2, 374–383.

    CAS  Google Scholar 

  • Statheropoulos, M., Vassilliadis, N., & Pappa, A. (1998). Principal component and canonical correlation analysis for examining air pollution and meteorological data. Atmospheric Environment, 32, 1087–1095.

    Article  CAS  Google Scholar 

  • Stranger, M., Potgieter–Vermaak, S. S., & Van Grieken, R. (2009). Particulate matter and gaseous pollutants in residences in Antwerp, Belgium. Science of the Total Environment, 407, 1182–1192.

    Article  CAS  Google Scholar 

  • Tao, J., Zhang, L. M., Engling, G., Zhang, R. J., Yang, Y. H., Cao, J. J., Zhu, C. S., Wang, Q. Y., & Luo, L. (2013). Chemical composition of PM2.5 in an urban environment in Chengdu, China: importance of springtime dust storms and biomass burning. Atmospheric Research, 122, 270–283.

    Article  CAS  Google Scholar 

  • Tsai, Y. I. (2005). Atmospheric visibility trends in an urban area in Taiwan 1961–2003. Atmospheric Environment, 39, 5555–5567.

    Article  CAS  Google Scholar 

  • Wan, J. M., Lin, M., Chan, C. Y., Zhang, Z. S., Engling, G., Wang, X. M., Chan, I. N., & Li, S. Y. (2011). Change of air quality and its impact on atmospheric visibility in central-western Pearl River Delta. Environmental Monitoring and Assessment, 172, 339–351.

    Article  CAS  Google Scholar 

  • Watson, J. G. (2002). Critical review discussion-visibility: Science and regulation. Journal of the Air & Waste Management, 52, 973–999.

    Article  Google Scholar 

  • WHO (World Health Organization). (2006). Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide 2006, summary of risk assessment. WHO Regional Office for Europe, Copenhagen, 20 pages.

  • Wichmann, J., Lind, T., Nilsson, M. A. M., & Bellander, T. (2010). PM2.5, soot and NO2 indoor–outdoor relationships at homes, pre-schools and schools in Stockholm, Sweden. Atmospheric Environment, 44, 4536–4544.

    Article  CAS  Google Scholar 

  • Xu, L. L., Chen, X. Q., Chen, J. S., Zhang, F. W., He, C., Zhao, J. P., & Yin, L. Q. (2012). Seasonal variations and chemical compositions of PM2.5 aerosol in the urban area of Fuzhou, China. Atmospheric Research, 104, 264–272.

    Article  Google Scholar 

  • Xue, D., & Yin, J. Y. (2014). Meteorological influence on predicting surface SO2 concentration from satellite remote sensing in Shanghai, China. Environmental Monitoring and Assessment, 186, 2895–2906.

    Article  CAS  Google Scholar 

  • Zhang, Q. H., Zhang, J. P., & Xue, H. W. (2010). The challenge of improving visibility in Beijing. Atmospheric Chemistry and Physics, 10, 7821–7827.

    Article  CAS  Google Scholar 

  • Zhang, F. W., Xu, L. L., Chen, J. S., Yu, Y. K., Niu, Z. C., & Yin, L. Q. (2012). Chemical compositions and extinction coefficients of PM2.5 in peri-urban of Xiamen, China, during June 2009–May 2010. Atmospheric Research, 106, 150–158.

    Article  CAS  Google Scholar 

  • Zhao, H., Che, H., Zhang, X., Ma, Y., Wang, Y., Wang, H., & Wang, Y. (2013a). Characteristics of visibility and particulate matter (PM) in an urban area of Northeast China. Atmospheric Pollution Research, 4, 427–434.

    CAS  Google Scholar 

  • Zhao, W., Cheng, J., Li, D., Duan, Y., Wei, H., Ji, R., & Wang, W. (2013b). Urban ambient air quality investigation and health risk assessment during haze and non-haze periods in Shanghai, China. Atmospheric Pollution Research, 4, 275–281.

    CAS  Google Scholar 

  • Zhou, J., Zhang, R., Cao, J., Chow, J. C., & Watson, J. G. (2012). Carbonaceous and ionic components of atmospheric fine particles in Beijing and their impact on atmospheric visibility. Aerosol and Air Quality Research, 12, 492–502.

    CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by the Project of National Natural Science Foundation of China (41404024) and partially by the Young Teachers Training and Supporting Plan in Shanghai Universities (2014–2016) and Laboratory Technician Team Building Program in Shanghai Universities (B.60-E108-14-101).

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Authors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China

    Dan Xue, Chengfan Li & Qian Liu

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  1. Dan Xue
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  2. Chengfan Li
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  3. Qian Liu
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Correspondence to Dan Xue.

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Xue, D., Li, C. & Liu, Q. Visibility characteristics and the impacts of air pollutants and meteorological conditions over Shanghai, China. Environ Monit Assess 187, 363 (2015). https://doi.org/10.1007/s10661-015-4581-8

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