Assessing the impact of clean air action on air quality trends in Beijing using a machine learning technique

Research output: Contribution to journalArticle

Authors

  • Jing Cheng
  • Qiang Zhang
  • Kebin He
  • Shuxiao Wang

Colleges, School and Institutes

External organisations

  • Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
  • Department of Environmental Sciences/Center of Excellence in Environmental Studies, King Abdulaziz University
  • State Key Joint Laboratory of Environment, Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China

Abstract

A 5-year Clean Air Action Plan was implemented in 2013 to reduce air pollutant emissions and improve ambient air quality in Beijing. Assessment of this action plan is an essential part of the decision-making process to review its efficacy and to develop new policies. Both statistical and chemical transport modelling have been previously applied to assess the efficacy of this action plan. However, inherent uncertainties in these methods mean that new and independent methods are required to support the assessment process. Here, we applied a machine-learning-based random forest technique to quantify the effectiveness of Beijing's action plan by decoupling the impact of meteorology on ambient air quality. Our results demonstrate that meteorological conditions have an important impact on the year-to-year variations in ambient air quality. Further analyses show that the PM 2.5 mass concentration would have broken the target of the plan (2017 annual PM 2.5 <60 μg m -3) were it not for the meteorological conditions in winter 2017 favouring the dispersion of air pollutants. However, over the whole period (2013-2017), the primary emission controls required by the action plan have led to significant reductions in PM 2.5/span PM 10/NO 2, SO 2, and CO from 2013 to 2017 of approximately 34 %, 24 %, 17 %, 68 %, and 33 %, respectively, after meteorological correction. The marked decrease in PM 2.5 and SO 2 is largely attributable to a reduction in coal combustion. Our results indicate that the action plan has been highly effective in reducing the primary pollution emissions and improving air quality in Beijing. The action plan offers a successful example for developing air quality policies in other regions of China and other developing countries.

Details

Original languageEnglish
Pages (from-to)11303-11314
Number of pages12
JournalAtmospheric Chemistry and Physics
Volume19
Issue number17
Publication statusPublished - 6 Sep 2019

ASJC Scopus subject areas