The spatiotemporal inhomogeneity of pollutant concentrations and its dependence on regional weather conditions in a coastal city of China
Hourly data for sulfur dioxide (SO2), nitrogen oxides (NOx), and inhalable particulate matter (PM10) over a 33-month period from a network of air quality monitoring stations across Qingdao, a major coastal city in eastern China, along with surface and upper-air meteorological data, are used to characterize the spatiotemporal variability of these pollutants in the region and the role of meteorological conditions play in pollution episodes. Large differences in the concentrations of all three pollutants are found between densely populated or industrial areas and suburban commercial or residential or coastal tourist areas, but the differences are relatively small between older and newer parts of the residential-commercial areas and between old and newly developed industrial areas. Wavelet analyses revealed a strong seasonal cycle for all three pollutants, introseasonal variability with a periodicity depending on pollutant and location, and diurnal and a semi-diurnal variability with season-dependent amplitude and phase. Low wind speed is found to be the leading factor for pollution buildup in the region. These results may prove useful for urban planning and development and implementation of effective air pollution control strategies for other coastal regions with economic development similar to Qingdao.
KeywordsAir pollution Coastal city air pollution Air pollution meteorology Sulfur dioxide (SO2) Nitrogen oxides (NOx) Particulate matter (PM10)
This paper is supported by the Center of Engineering Technology for Ecological Carbon Sequestration and Trapping Utilization in Shandong, China. The authors (Zhou and Yu) gratefully acknowledge the support of the Center for Global Change & Earth Observations during their time as visiting scholars to Michigan State University, USA. We appreciated the Environmental Protection Department of Shandong Province for the air quality data and University of Wyoming for the sounding data and surface data in Qingdao.
- Huang, L., Wang, C., Wang, J., & Yu, P. (2001). Research on the time series analysis forecast method for air pollution in Qingdao. Journal of Ocean University of Qingdao, 31(1), 14–20 (In Chinese). https://doi.org/10.3969/j.issn.1672-5174.2001.01.002.Google Scholar
- Huang, R., Guo, L., Yan, M., & Yu, S. (2015). Relationship between air quality and meteorological conditions from 2006 to 2012 in Qingdao. Journal of Meteorology and Environment, 31(2), 37–43 (In Chinese). https://doi.org/10.3969/j.issn.1673-503X.2015.02.006.Google Scholar
- Jia, Z. (2016). Analysis on Pollution Characteristics of Nitrogen Oxides near the Arterial Traffic in Qingdao City. Journal of EMCC, 26(5), 83–85. https://doi.org/10.13358/j.issn.1008-813x.2016.05.22.Google Scholar
- Kassomenos, P. A., Kelessis, A., Petrakakis, M., Zoumakis, N., Christides, T., & Paschalidou, A. K. (2012). Air quality assessment in a heavily-polluted urban Mediterranean environment through air quality indices. Ecological Indicators, 18, 259–268. https://doi.org/10.1016/j.ecolind.2011.11.021.CrossRefGoogle Scholar
- Li, B., & Qu, W. J. (2008). PM10 pollution characteristic and transportation analysis of Qingdao in 2007. China Meteorological Society 2008 annual meeting of the atmospheric environmental monitoring branch prediction and control of pollutants, 449–461. http://www.cnki.net.
- Li, D. P., Cheng, X. H., Yu, Y. T., Cao, H. W., Li, D., & Xu, S. Q. (2010). Effects of meteorological factors on air quality above the third grade pollution in Beijing. Journal of Meteorology and Environment, 26(3), 7–13. https://doi.org/10.3969/j.issn.1673-503X.2010.03.002.Google Scholar
- Li, T., Zhao, T., Yang, X., Wang, H., & Li, C. (2014). Inter-decadal variations in the seasonality of haze over Shandong province in recent 53 years. Ecology & Environmental Sciences, 23(9), 1432–1437. https://doi.org/10.16258/j.cnki.1674-5906.2014.09.011.Google Scholar
- Lian, L. S., Gao, J., & Shu, J. (2011). Urban air pollution feature and its relationship with meteorologic factors—a case of Jinan and Qingdao. Environmental Pollution & Control, 33(5), 22–26 (In Chinese). https://doi.org/10.15985/j.cnki.1001-3865.2011.05.009.Google Scholar
- Lopez, R. E., Thomas, V., et al. (2008). The quality of growth: fiscal policies for better results. The World Bank: Washington, D. C.Google Scholar
- Nan, Z., & Jun, S. (2006). An analysis of the factor of influence on industrial layout in Qingdao. The Planner, 22(S2), 46–48. https://doi.org/10.3969/j.issn.1006-0022.2006.z2.013.Google Scholar
- Qiang, Z., Guoxing, L., Lei, Z., & Xiaochuan, P. (2015). Burden of disease due to ambient air pollution: a review of recent studies. Journal of Environment & Health, 32(1), 85–90. https://doi.org/10.16241/j.cnki.1001-5914.2015.01.027.Google Scholar
- Qin, J. J., Wang, J., & Cheng, J. G. (2010). A typical air pollution event caused by external source transport during 2008 in Qingdao, Shandong province. Journal of Meteorology and Environment, 26(6), 35–39 http://www.cnki.com.cn/Article/CJFDTotal-LNQX201006007.htm.Google Scholar
- Shen, G. (2012). Sources apportionment of PM10 and PM2.5 in five cities in China. Tianjin Medical University, 1. http://www.cnki.net.
- Tang, G., Zhang, J., Zhu, X., Song, T., Münkel, C., Hu, B., Schäfer, K., Liu, Z., Zhang, J., Wang, L., Xin, J., Suppan, P., & Wang, Y. (2016). Mixing layer height and its implications for air pollution over Beijing, China. Atmospheric Chemistry and Physics, 16, 2459–2475. https://doi.org/10.5194/acp-16-2459-2016.CrossRefGoogle Scholar
- Wang, J., Qiu, C., Liu, B. H., Cao, J., Wang, D., & Dong, X. (2013). Characteristics of air quality and the correlation between API and meteorological elements in major cities of Shandong province. Ecology & Environmental Sciences, 22(4), 644–649. https://doi.org/10.16258/j.cnki.1674-5906.2013.04.021.Google Scholar
- Wei, Y. X., Tong, Y. Q., Yin, Y., & Chen, K. (2009). The variety of main air pollutants concentration and its relationship with meteorological condition in Nanjing City. Transactions of Atmospheric Sciences, 32(3), 451–457. https://doi.org/10.13878/j.cnki.dqkxxb.2009.03.014.Google Scholar
- Wen, Q. (2008). Research on the analysis method and model construction of tourism seasonality—take Qingdao as an example. Ocean University of China, 50–65. https://doi.org/10.7666/d.y1337099.
- Wen, L. J. (2011). Causes and elimination methods of traffic jam in second tier cities in China. Journal of Shanghai Urban Management, 19(1), 52–56. https://doi.org/10.3969/j.issn.1674-7739.2011.01.013.Google Scholar
- Wu, H., Zhang, C. Y., Wang, J., Xuan, Z. F., Chu, C. J., Feng, Y. C., & Xu, H. (2013). Comparative study on pollution characteristics and source apportionment of PM10 and PM2.5 in Qingdao. Research of Environmental Sciences, 26(6), 583–589. https://doi.org/10.13198/j.res.2013.06.4.wuh.011.Google Scholar
- Yang, Y., & Gao, H. (2008). Dynamics of ozone and its precursors in the atmosphere and their pollution characteristics in Qingdao, Shandong province. Journal of Meteorology and Environment, 24(2), 1–5. https://doi.org/10.3969/j.issn.1673-503X.2008.02.001.Google Scholar
- Zhou, N., & Song, J. (2006). An analysis of the factor of influence on industrial layout in Qingdao. Planners, 22(S2), 46–48. https://doi.org/10.3969/j.issn.1006-0022.2006.z2.013.Google Scholar
- Zhu, Y., Sabaliauskas, K., Liu, X., Meng, H., Gao, H., Jeong, C. H., Evans, G. J., & Yao, X. (2014). Comparative analysis of new particle formation events in less and severely polluted urban atmosphere. Atmospheric Environment, 98, 655–664. https://doi.org/10.1016/j.atmosenv.2014.09.043.CrossRefGoogle Scholar