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

Abstract

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 PM_2.5, 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%~46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation (IMCV) of PM_2.5 and NO₂. For different pollution periods, gradually increase of frequency of S-1 (PM_2.5, 0~75 μg/m³) made S-1 become the largest contributor (28.8%) to the MC of PM_2.5 in 2016, it had a negative contribution (-13.1%) to the IMCV of PM_2.5; obvious decreases of frequencies of heavily polluted and severely polluted dominated (44.7% and 39.5%) the IMCV of PM_2.5. For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease (22.5%~62.5%), and those decrease contributed most to the IMCV of PM_2.5 (143.3%), SO₂ (72.0%), NO₂ (55.5%) and CO (190.3%); the west airflow had negative influences to the IMCV of PM_2.5, 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.

Keywords: Air quality variations; Airflow directions; Beijing; Monitoring data analysis; Pollution periods.