High reduction of ozone and particulate matter during the 2016 G-20 summit in Hangzhou by forced emission controls of industry and traffic

Abstract

Many regions in China experience air pollution episodes because of the rapid urbanization and industrialization over the past decades. Here we analyzed the effect of emission controls implemented during the G-20 2016 Hangzhou summit on air quality. Emission controls included a forced closure of highly polluting industries, and limiting traffic and construction emissions in the cities and surroundings. Particles with aerodynamic diameter lower than 2.5 µm (PM) and ozone (O) were measured. We also simulated air quality using a forecast system consisting of the two-way coupled Weather Research and Forecast and Community Multi-scale Air Quality (WRF-CMAQ) model. Results show PM and ozone levels in Hangzhou during the G-20 Summit were considerably lower than previous to the G-20 Summit. The predicted concentrations of ozone were reduced by 25.4%, whereas the predicted concentrations of PM were reduced by 56%.

Modeling diurnal variation of surface PM<sub>2.5</sub> concentrations over East China with WRF-Chem: impacts from boundary-layer mixing and anthropogenic emission

“…The highest surface PM 2.5 concentrations appear in winter and the lowest in summer, and the highest and lowest surface PM 2.5 concentrations of a day often occur in the evening and afternoon, respectively (e.g., Gong et al, 2007;Fu et al, 2008;Hu et al, 2014;Z. F. Wang et al, 2014;Chen et al, 2015;Geng et al, 2015;Li et al, 2015;Xie et al, 2015;Zhang and Cao, 2015;Chen et al, 2016). Moreover, modeling analysis can help understand the chemical and physical processes affecting aerosol formation and evolution (e.g., Ying et al, 2009;Zhang et al, 2010;Liao et al, 2014;Cheng et al, 2016;Yang et al, 2016;Zhao et al, 2017).…”

Counteractive effects of regional transport and emission control on the formation of fine particles: a case study during the Hangzhou G20 summit

“…During the 2008 Olympic Games and the 2014 APEC summit, similar control measures were taken in Beijing and the surrounding areas to achieve a good level of air quality. During the 2008 Olympic period, the decrease in PM 2.5 mass was mainly due to the reduction of SIAs, whilst an unexpected PM 2.5 increase during the emission control period may have been related to poor weather conditions such as transport from the south and a small amount of precipitation (Li et al, 2013). In addition, the contribution of SIAs increased during this period, while the opposite was noted for organics during haze development, indicating that NO x emission control should be a priority for improving air quality in Chinese megacities (Pan et al, 2016).…”

“…As for sulfate, the gas-phase oxidation of SO 2 by OH radicals is its main formation pathway, although the heterogeneous uptake of SO 2 on pre-existing particles or in cloud droplets with oxidation by H 2 O 2 , O 3 , NO 2 , and metal ions is also important for sulfate formation (Cheng et al, 2016;Khoder, 2002;Sander and Seinfeld, 1976). Both gas-phase and heterogeneous reactions have been found to be responsible for the increase of fine particles, which ultimately leads to the occurrence of haze (Li et al, 2013;Pan et al, 2016;Wang et al, 2010). The secondary formation of SIAs has been found to be related to heterogeneous aqueous reactions and is largely dependent on the ambient humidity (Wang et al, 2012).…”

Residential emissions predicted as a major source of fine particulate matter in winter over the Yangtze River Delta, China

“…To design eff e emission control strategies, critical information is needed about the contributions of diff ent sources and regions. Investigation of the impacts of emission control policies on air quality using computational atmospheric models is essential (Xing et al 2011;Gao and Zhang et al 2012;Sun et al 2016;Liu et al 2016;Li et al 2017). For instance, the Community Multiscale Air Quality model system (Eder and Yu 2006) has been widely applied to predict the eff of emission control measures on air quality in China, especially for several large international events such as the 2008 Beijing Olympics (Xing et al 2011;Gao and Zhang et al 2012), the 2014 Beijing Asia-Pacifi Economic Cooperation Summit, (Sun et al 2016;Liu et al 2016), and the 2016 G20 Hangzhou Summit (Li et al 2017).…”

“…Investigation of the impacts of emission control policies on air quality using computational atmospheric models is essential (Xing et al 2011;Gao and Zhang et al 2012;Sun et al 2016;Liu et al 2016;Li et al 2017). For instance, the Community Multiscale Air Quality model system (Eder and Yu 2006) has been widely applied to predict the eff of emission control measures on air quality in China, especially for several large international events such as the 2008 Beijing Olympics (Xing et al 2011;Gao and Zhang et al 2012), the 2014 Beijing Asia-Pacifi Economic Cooperation Summit, (Sun et al 2016;Liu et al 2016), and the 2016 G20 Hangzhou Summit (Li et al 2017). Wang et al (2014a) studied the contributions of diffent source sectors to PM 2.5 in southern Hebei during the 2013 severe episode by the Community Multiscale Air Quality model with a brute-force method (BFM), in which a series of sensitivity simulations were performed, each with one emission sector eliminated and the diff ences between the results from the sensitivity and baseline simulations being attributed to the emission eliminated (Burr et al 2011).…”