Uncertainty assessment of PM2.5 probability mapping by using spatio-temporal indicator kriging
MEI Yang1, ZHANG Wen-ting2,3, YANG Yong2,3, ZHAO Yu1, LI Lu-lu1
1. Zhenhai Urban Planning and Survey Research Insitute of Ningbo, Ningbo 315200, China; 2. College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China; 3. Key Laboratory of Arable Land Conservation, Middle and Lower Reaches of Yangtse River, Ministry of Agriculture, Wuhan 430070, China
Abstract：As a new indicator of the air pollution, PM2.5 is attracting more and more attentions from the society and academia. In China, with the rapid industrialization and urbanization, part of region is experiencing severe air pollution problems. Thus, understanding the spatio-temporal (ST) variation and trends of air pollution is a key element of an improved understanding of the underlying physical mechanisms and the implementation of the most risk assessment and environmental policy in the region. However, most of existing studies merely focused on the change of concentration, and the probability of PM2.5 exceeding ones certain concentration is rarely studied. Within this context, a method of ST Indicator Kriging (STIK) based on a non-separable ST semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations monitored during 2014 in Shandong Province, China were used as the experimental dataset. Spatial auto-correlation extent of PM2.5 was more than 100km, and the temporal auto-correlation range was about 3days. We also found that 7% of the place in Shandong province in 2014maintains probability of attaining excellent air quality larger than 0.8, 34% of the place in Shandong province in 2014 maintains the probability of attaining slight polluted air quality larger than 0.8, and only 1% of the place in Shandong province in 2014 maintains the probability of attainting severe polluted air quality larger than 0.8. Spatially, the probability of attaining slight polluted air quality in the eastern coastal was significantly higher than that of in Midwest; temporally, the air quality in summer was obviously better than those of in other seasons.
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MEI Yang, ZHANG Wen-ting, YANG Yong, ZHAO Yu, LI Lu-lu. Uncertainty assessment of PM2.5 probability mapping by using spatio-temporal indicator kriging. CHINA ENVIRONMENTAL SCIENCECE, 2018, 38(1): 35-43.
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