Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis
Authors: Cheng Jing , Su Jingping , Cui Tong , Li Xiang , Dong Xin , Sun Feng , Yang Yanyan , Tong Dan , Zheng Yixuan , Li Yanshun , Li Jinxiang , Zhang Qiang , He Kebin 
Published: May 2019

Abstract. In 2013, China's government published the Air Pollution Prevention and
Control Action Plan (APPCAP) with a specific target for Beijing, which aims
to reduce annual mean PM2.5 concentrations in Beijing to
60 µg m−3 in 2017. During 2013–2017, the air quality in
Beijing was significantly improved following the implementation of various
emission control measures locally and regionally, with the annual mean
PM2.5 concentration decreasing from 89.5 µg m−3 in 2013
to 58 µg m−3 in 2017. As meteorological conditions were more
favourable to the reduction of air pollution in 2017 than in 2013 and 2016,
the real effectiveness of emission control measures on the improvement of air
quality in Beijing has frequently been questioned. In this work, by combining a detailed bottom-up emission inventory over
Beijing, the MEIC regional emission inventory and the WRF-CMAQ (Weather
Research and Forecasting Model and Community Multiscale Air Quality) model, we
attribute the improvement in Beijing's PM2.5 air quality in 2017
(compared to 2013 and 2016) to the following factors: changes in
meteorological conditions, reduction of emissions from surrounding regions,
and seven specific categories of local emission control measures in Beijing.
We collect and summarize data related to 32 detailed control measures
implemented during 2013–2017, quantify the emission reductions associated
with each measure using the bottom-up local emission inventory in 2013,
aggregate the measures into seven categories, and conduct a series of CMAQ
simulations to quantify the contribution of different factors to the
PM2.5 changes. We found that, although changes in meteorological conditions partly explain
the improved PM2.5 air quality in Beijing in 2017 compared to 2013 (3.8 µg m−3,
12.1 % of total), the rapid decrease in
PM2.5 concentrations in Beijing during 2013–2017 was dominated by local
(20.6 µg m−3, 65.4 %) and regional (7.1 µg m−3,
22.5 %) emission reductions. The seven categories of
emission control measures, i.e. coal-fired boiler control,
clean fuels in the residential sector, optimize industrial structure,
fugitive dust control, vehicle emission control,
improved end-of-pipe control, and integrated treatment of VOCs,
reduced the PM2.5
concentrations in Beijing by 5.9, 5.3, 3.2, 2.3, 1.9, 1.8, and 0.2 µg m−3,
respectively, during 2013–2017. We also found
that changes in meteorological conditions could explain roughly 30 % of
total reduction in PM2.5 concentration during 2016–2017 with more
prominent contribution in winter months (November and December). If the
meteorological conditions in 2017 had remained the same as those in 2016,
the annual mean PM2.5 concentrations would have increased from
58 to 63 µg m−3, exceeding the
target established in the APPCAP. Despite the remarkable impacts from
meteorological condition changes, local and regional emission reductions
still played major roles in the PM2.5 decrease in Beijing during
2016–2017, and clean fuels in the residential sector, coal-fired boiler control,
and optimize industrial structure were the three most effective local measures
(contributing reductions of 2.1, 1.9, and 1.5 µg m−3,
respectively). Our study confirms the effectiveness of clean air actions in
Beijing and its surrounding regions and reveals that a new generation of
control measures and strengthened regional joint emission control measures
should be implemented for continued air quality improvement in Beijing
because the major emitting sources have changed since the implementation of
the clean air actions.