Comparison between two air quality index systems in study of urban air pollution in China and its socio-economic determinants

doi:10.7523/j.issn.2095-6134.2020.01.006

Abstract

Abstract: Since the environmental quality in metropolitan areas has significant impact on public health and everyday life of urban residents, it is of great importance to provide scientific information about the urban air pollutant concentration, which has gained much concern from both the governmental authorities and the scientific fields. This study illustrated the urban air quality of 113 sample cities in China by the comparison between the aggregate air quality index (AAQI) and the air quality index (AQI) and then depicted its spatial differentiation based on spatial interpolation. Furthermore, this study analyzed the influential factors behind the air quality variations among these cities by employing panel data models. The results indicated that the urban air quality showed a significant agglomeration feature at the national scale, with North China retaining the highest values both in terms of AAQI and AQI. From temporal perspective, the urban air quality reported a desirable trend nationwide from 2014 to 2016. Results from the regression models indicated that the urban air quality was affected by geographical locations, socioeconomic factors, and environmental regulations, among which urbanization level and industrial structure were reported to be the important socioeconomic factors exerting more significant impacts on the urban air quality. We suggest that more efforts should be devoted to develop comprehensive indices for evaluation of the urban air quality and to explore new avenues to improve urban air quality from industrialization and urbanization perspectives.

Key words: AAQI (aggregate air quality index), key environmental protection cities, spatiotemporal characteristics, influential factors

CLC Number:

X321
F129.9

ZHANG Xiaoping, LIN Meihan. Comparison between two air quality index systems in study of urban air pollution in China and its socio-economic determinants[J]. , 2020, 37(1): 39-50.

References

[1] Kanchan A K G A. A review on air quality indexing system[J]. Asian Journal of Atmospheric Environment, 2015, 9(2):101-113.
[2] Hu J, Ying Q, Wang Y, et al. Characterizing multi-pollutant air pollution in China:comparison of three air quality indices[J]. Environment International, 2015, 84:17-25.
[3] Kumar A, Goyal P. Forecasting of Air Quality Index in Delhi using neural network based on principal component analysis[J]. Pure and Applied Geophysics, 2013, 170(4):711-722.
[4] Gorai A K, Kanchan, Upadhyay A, et al. Design of fuzzy synthetic evaluation model for air quality assessment[J]. Environment Systems & Decisions, 2014, 34(3):456-469.
[5] Sicard P, Lesne O, Alexandre N, et al. Air quality trends and potential health effects-Development of an aggregate risk index[J]. Atmospheric Environment, 2011, 45(5):1145-1153.
[6] Bishoi B, Prakash A, Jain V K. A comparative study of air quality index based on factor analysis and US-EPA methods for an urban environment[J]. Aerosol and Air Quality Research, 2009, 9(1):1-17.
[7] Cairncross E K, John J, Zunckel M. A novel air pollution index based on the relative risk of daily mortality associated with short-term exposure to common air pollutants[J]. Atmospheric Environment, 2007, 41(38):8442-8454.
[8] Khanna N. Measuring environmental quality:an index of pollution[J]. Ecological Economics, 2000, 35(2):191-202.
[9] Kyrkilis G, Chaloulakou A, Kassomenos P A. Development of an aggregate air quality index for an urban mediterranean agglomeration:relation to potential health effects[J]. Environment International, 2007, 33(5):670-676.
[10] Stieb D M, Burnett R T, Smith-Doiron M, et al. A new multipollutant, no-threshold air quality health index based on short-term associations observed in daily time-series analyses[J]. Journal of the Air & Waste Management Association, 2008, 58(3):435-450.
[11] Swamee P K, Tyagi A. Formation of an air pollution index[J]. Journal of the Air & Waste Management Association, 1999, 49(1):88-91.
[12] Cheng W L, Kuo Y C, Lin P L, et al. Revised air quality index derived from an entropy function[J]. Atmospheric Environment, 2004, 38(3):383-391.
[13] Sheng N, Tang U W. The first official city ranking by air quality in China:a review and analysis[J]. Cities, 2016, 51:139-149.
[14] Gong Z, Zhang X. Assessment of urban air pollution and spatial spillover effects in China:cases of 113 key environmental protection cities[J]. Journal of Resources and Ecology, 2017, 8(6):584-594.
[15] Chen W, Tang H, Zhao H. Urban air quality evaluations under two versions of the national ambient air quality standards of China[J]. Atmospheric Pollution Research, 2016, 7(1):49-57.
[16] Xiang H E, Lin Z, Liu H, et al. Analysis of the driving factors of PM_2.5 in Jiangsu province based on grey correlation model[J]. Acta Geographica Sinica, 2016,71(7):1119-1129(in Chinese).
[17] Li X, Zhang M, Wang S, et al. Variation characteristics and influencing factors of air pollution index in China[J]. Environmental Science, 2012, 33(6):1936-1943(in Chinese).
[18] Kassomenos P, Kotroni V, Kallos G. Analysis of climatological and air quality observations from Greater Athens Area[J]. Atmospheric Environment, 1995, 29(24):3671-3688.
[19] Tai A P K, Mickley L J, Jacob D J. Correlations between fine particulate matter (PM_2.5) and meteorological variables in the United States:implications for the sensitivity of PM_2.5 to climate change[J]. Atmospheric Environment, 2010, 44(32):3976-3984.
[20] Tian S, Pan Y, Liu Z, et al. Size-resolved aerosol chemical analysis of extreme haze pollution events during early 2013 in urban Beijing, China[J]. Journal of Hazardous Materials, 2014, 279:452-460.
[21] Lin X, Dai W. Spatiotemporal evolution of urban air quality and socioeconomic driving forces in China[J]. Journal of Geographical Sciences, 2016, 26(11):1533-1549.
[22] Ma L, Zhang X. The spatial effect of China's haze pollution and the impact from economic change and energy structure[J]. China Industrial Economics, 2014(4):19-31(in Chinese).
[23] Wang F, Dong S, Mao Q, et al. Analysis of the environment-pollution bias of industrial structure in areas along the Yellow River in Ningxia and Inner Mongolia[J]. Resources Science, 2014, 36(3):620-631(in Chinese).
[24] Wang S, Hao J. Air quality management in China:issues, challenges, and options[J]. Journal of Environmental Sciences, 2012, 24(1):2-13.
[25] Huo J W, Yang D G, Wang F, et al. Analysis of the relationship between population structure and CO₂ emissions in Xinjiang based on Granger causality and the ridge regression[J]. Journal of University of Chinese Academy of Sciences, 2015, 32(3):333-341(in Chinese).
[26] Zhao J, Chen S, Wang H, et al. Quantifying the impacts of socio-economic factors on air quality in Chinese cities from 2000 to 2009[J]. Environmental Pollution, 2012, 167(1):148-154.
[27] Zhu X D, He C F, Li Q, et al. Influence of local government competition and environmental regulations on Chinese urban air quality[J]. China population, resources and environment, 2018, 28(6):103-110(in Chinese).
[28] Shi M J, Li Y J, Zhang X L, et al. Will the haze control target of Beijing-Tianjin-Hebei region be realized? An assessment based on environmental carrying capacity[J]. China population, resources and environment, 2017, 27(9):66-75(in Chinese).
[29] Liu Q L, Wang Q, Li P. Regional distribution changes of pollution-intensive industries in China[J], Ecological economy, 2012, 28(1):107-112(in Chinese).
[30] Jeffrey S J, Carter J O, Moodie K B, et al. Using spatial interpolation to construct a comprehensive archive of Australian climate data[J]. Environmental Modelling & Software, 2001, 16(4):309-330.
[31] Oliver M A, Webster R. Kriging:a method of interpolation for geographical information systems[J]. International Journal of Geographical Information Systems, 1990, 4(3):313-332.