A framework for investigating the air quality variation characteristics based on the monitoring data: Case study for Beijing during 2013-2016

In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors (i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations (MC) of PM2.5, SO2, NO2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6% and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions (25.8%similar to 46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation (IMCV) of PM2.5 and NO2. For different pollution periods, gradually increase of frequency of S-1 (PM2.5, 0 similar to 75 mu g/m(3)) made S-1 become the largest contributor (28.8%) to the MC of PM2.5 in 2016, it had a negative contribution (-13.1%) to the IMCV of PM2.5; obvious decreases of frequencies of heavily polluted and severely polluted dominated (44.7% and 39.5%) the IMCV of PM2.5. For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease (22.5%similar to 62.5%), and those decrease contributed most to the IMCV of PM2.5 (143.3%), SO2 (72.0%), NO2 (55.5%) and CO (190.3%); the west airflow had negative influences to the IMCV of PM2.5, NO2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy. (C) 2019 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.