Abstract
Given the critical roles of nitrates and sulfates in fine particulate matter (PM2.5) formation, we examined spatiotemporal associations between PM2.5 and sulfur dioxide (SO2) as well as nitrogen dioxide (NO2) in China by taking advantage of the in situ observations of these three pollutants measured from the China national air quality monitoring network for the period from 2015 to 2018. Maximum covariance analysis (MCA) was applied to explore their possible coupled modes in space and time. The relative contribution of SO2 and NO2 to PM2.5 was then quantified via a statistical modeling scheme. The linear trends derived from the stratified data show that both PM2.5 and SO2 decreased significantly in northern China in terms of large values, indicating a fast reduction of high PM2.5 and SO2 loadings therein. The statistically significant coupled MCA mode between PM2.5 and SO2 indicated a possible spatiotemporal linkage between them in northern China, especially over the Beijing–Tianjin–Hebei region. Further statistical modeling practices revealed that the observed PM2.5 variations in northern China could be explained largely by SO2 rather than NO2 therein, given the estimated relatively high importance of SO2. In general, the evidence-based results in this study indicate a strong linkage between PM2.5 and SO2 in northern China in the past few years, which may help to better investigate the mechanisms behind severe haze pollution events in northern China.
Highlights
Concentrations of fine particulate matter in China have decreased prominently during the time period of 2013–2018 due to the implementation of the air pollution prevention and control action plan [1,2,3]
It shows that PM2.5 and SO2 decreased markedly during the study time period, especially in northern China, where significant decreasing trends were observed
In contrast to the trends estimated from all data value averages, trends estimated from large values were even more salient in northern China, indicating the effectiveness of clean air actions in reducing high loadings of PM2.5 and SO2 therein
Summary
Concentrations of fine particulate matter (denoted as PM2.5 ) in China have decreased prominently during the time period of 2013–2018 due to the implementation of the air pollution prevention and control action plan [1,2,3]. Many previous studies have evaluated the spatial and temporal variations of PM2.5 concentrations in China in terms of either trend estimation or spatial clustering analysis. Similar effects were revealed in Reference [1], but with more spatial details, as the PM2.5 inflection time was identified at each grid pixel. Their results indicate that performing trend analysis on stratified data
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