Dominant role of emission reduction in PM<sub>2.5</sub> air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis

Abstract

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.

Environmental Effective Assessment of Control Measures Implemented by Clean Air Action Plan (2013–2017) in Beijing, China

“…Dust sources were controlled to a certain extent during the implementation of the CAAP. However, this pollution source emission type has a large base and it is difficult to control [28]. It is Atmosphere 2020, 11, 189 7 of 12 necessary to further improve management and control actions.…”

Exploring 2016–2017 surface ozone pollution over China: source contributions and meteorological influences

“…In particular, 2016 and 2017 witnessed the most severe surface ozone pollution in record over most Chinese cities. The summertime surface MDA8 ozone levels in 2016-2017 averaged over the major Chinese cities increased by about 20 % compared to 2013-2014 , despite the fact that the Chinese Action Plan on Air Pollution Prevention and Control implemented in 2013 has significantly reduced anthropogenic emissions of nitrogen oxides (NO x = NO + NO 2 ) and alleviated winter haze pollution (Cheng et al, 2019;. Exploring source attributions to surface ozone in China is therefore critical to understanding the recent ozone increase and to reexamining the air pollution control strategy.…”

China's emission control strategies have suppressed unfavorable influences of climate on wintertime PM<sub>2.5</sub> concentrations in Beijing since 2002

“…The underestimate of sulfate by models and the overestimate of BC in Beijing have been well documented in previous studies (Cheng et al, 206;Gao et al, 2016aGao et al, , 2018aSong et al, 2018), attributed to missing reaction pathways and aging and deposition treatments in models (Song et al, 2019). Several heterogeneous reaction pathways for sulfate formation have been proposed, including the oxidation of SO 2 by NO 2 , transitionmetal-catalyzed O 2 , or H 2 O 2 in aerosol water and by NO 2 or O 2 on aerosol surfaces (Cheng et al, 2016;He et al, 2014;Hung et al, 2018;Li et al, 2018). More recently, Song et al (2019) proposed that the heterogeneous production of hydroxymethanesulfonate (HMS) from the reaction of SO 2 and formaldehyde could be an important chemical mechanism for wintertime haze in China.…”