Effectiveness of SO2 emission control policy on power plants in the Yangtze River Delta, China-post-assessment of the 11th Five-Year Plan

Why did air quality experience little improvement during the COVID-19 lockdown in megacities, northeast China?

To inhibit the COVID-19 (Coronavirus disease 2019) outbreak, unprecedented nationwide lockdowns were implemented in China in early 2020, resulting in a marked reduction of anthropogenic emissions. However, reasons for the insignificant improvement in air quality in megacities of northeast China, including Shenyang, Changchun, Jilin, Harbin, and Daqing, were scarcely reported. We assessed the influences of meteorological conditions and changes in emissions on air quality in the five megacities during the COVID-19 lockdown (February 2020) using the WRF-CMAQ model. Modeling results indicated that meteorology contributed a 14.7% increment in Air Quality Index (AQI) averaged over the five megacities, thus, the local unfavorable meteorology was one of the causes to yield little improved air quality. In terms of emission changes, the increase in residential emissions (+15%) accompanied by declining industry emissions (-15%) and transportation (-90%) emissions resulted in a slight AQI decrease of 3.1%, demonstrating the decrease in emissions associated with the lockdown were largely offset by the increment in residential emissions. Also, residential emissions contributed 42.3% to PM_2.5 concentration on average based on the Integrated Source Apportionment tool. These results demonstrated the key role residential emissions played in determining air quality. The findings of this study provide a scenario that helps make appropriate emission mitigation measures for improving air quality in this part of China.

The climate impact on atmospheric stagnation and capability of stagnation indices in elucidating the haze events over North China Plain and Northeast China

In this study, the spatial pattern and temporal evolution of PM_2.5 over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM_2.5 shows clear decreasing trends over time, but the seasonal mean PM_2.5 as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.

The effects of emission trading system on corporate innovation and productivity-empirical evidence from China's SO2 emission trading system

Emission trading system is a significant market-based environmental regulation tool worldwide. This study fills existing knowledge gap on whether ETSs have "weak" and "strong" version of Porter hypothesis effects in China, by examining the effects of the Chinese SO₂ emission trading on corporate innovation and productivity. Using the micro-data of domestic-listed manufacturing companies from 2004 to 2015, this study regarded China's SO₂ emission trading system as a quasi-natural experiment by applying a difference-in-difference framework to eliminate endogenous problems. It was found that the SO₂ emission trading system significantly promoted corporate innovation but did not have a significant effect on corporate productivity. The cause analysis showed that suboptimal institutional context and lack of corporate dynamic response led to the failure of strong Porter hypothesis effect. In addition, small- and medium-sized enterprises and non-state-owned enterprises gained greater innovation compensation effects of the emission trading system. This research believed that, the design, institutional context, and market incentives of emission trading systems need to be improved from the top down, to achieve the dual goal of environmental sustainability and economic growth.

Effects of air pollution control measures on air quality improvement in Guangzhou, China

The ambient air quality of Guangzhou in 2016 has significantly improved since Guangzhou and its surrounding cities implemented a series of air pollution control measures from 2014 to 2016. This study not only estimated the effects of meteorology and emission control measures on air quality improvement in Guangzhou but also assessed the contributions of emissions reduction from various sources through the combination of observation data and simulation results from Weather Research and Forecasting - Community Multiscale Air Quality (WRF-CMAQ) modeling system. Results showed that the favorable meteorological conditions in 2016 alleviated the air pollution. Compared to change in meteorology, implementing emission control measures in Guangzhou and surrounding cities was more beneficial for air quality improvement, and it could reduce the concentrations of SO₂, NO₂, PM_2.5, PM₁₀, and O₃ by 9.7 μg m^-3 (48.4%), 9.2 μg m^-3 (17.7%), 7.7 μg m^-3 (14.6%), 9.7 μg m^-3 (13.4%), and 12.0 μg m^-3 (7.7%), respectively. Furthermore, emission control measures that implemented in Guangzhou contributed most to the concentration reduction of SO₂, NO₂, PM_2.5, and PM₁₀ (46.0% for SO₂, 15.2% for NO₂, 9.4% for PM_2.5, and 9.1% for PM₁₀), and it increased O₃ concentration by 2.4%. With respect to the individual contributions of source emissions reduction, power sector emissions reduction showed the greatest contribution in reducing the concentrations of SO₂, NO₂, PM_2.5, and PM₁₀ due to the implementation of Ultra-Clean control technology. As for O₃ mitigation, VOCs product-related source emissions reduction was most effective, and followed by transportation source emissions reduction, while the reductions of power sector, industrial boiler, and industrial process source might not be as effective. Our findings provide scientific advice for the Guangzhou government to formulate air pollution prevention and control policies in the future.