Co-benefits of peaking carbon dioxide emissions on air quality and health, a case of Guangzhou, China.

Cities play a key role in making carbon emission reduction targets achievable and tackling air pollution. Using Guangzhou city as a case, this paper explored the air quality and health co-benefits of peaking carbon dioxide emissions under three scenarios and developed an integrated assessment framework by combining a local air pollutant emission inventory, an atmospheric chemistry transport model, and a health assessment model. The results showed that SO2, PM10, and PM2.5 could achieve larger emission reductions than NH3, VOCs, and NOx among all the scenarios we examined. Under the enhanced peaking scenario with the most stringent mitigation strategies, Guangzhou could meet the local ambient air quality standard for PM2.5 (34 µg/m3), with the most reduction observed in the annual average PM2.5 concentration (28.4%) and related premature deaths (17.08%), compared with the base year 2015. We also identified hotspot grids, which were areas with high concentrations of carbon emissions, high concentrations of air pollution and poor air quality in Guangzhou. Our analysis highlighted the importance of promoting peaking carbon dioxide emission for the improvement of air quality and public health at the city level.

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, PM2.5, 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, PM2.5, and PM10 (46.0% for SO2, 15.2% for NO2, 9.4% for PM2.5, 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, PM2.5, 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.

A new method of hotspot analysis on the management of CO2 and air pollutants, a case study in Guangzhou city, China.

Emission inventory plays an important role in designing effective emission control strategies. Currently, there is unbalanced development of CO2 and air pollutant emission inventories in China and the spatial information of both cannot be obtained simultaneously, which prevents a collaborative control strategy. In this study, we developed a unified emission inventory including both CO2 and air pollutants, then utilized spatial mapping methods to identify the co-hotspots of both CO2 and air pollutants at a high spatial resolution (1 × 1 km2). We applied Guangzhou city as a case study to illustrate the method. The results showed that CO2 and air pollutants were mainly emitted from the stationary combustion sector and the transportation sector. These two sectors contributed 95 %, 67 %, and 93 % to total CO2, SO2, and NOx emissions, respectively. Up to 86 %, 86 %, 66 %, and 72 % of total CO2, SO2, NOx, and PM2.5 emissions were attributed to the top 10 % emission grids with 1 × 1 km2 resolution. However, our results showed high emission grids were not surrounded by other high emissions grids for all types of emissions analyzed in this study. The co-hotspot analysis enables accurate identification of high-emission grids, which helps environment managers to prioritize resource allocation when designing control strategies. Our study underscores the importance of managing CO2 and air pollutants simultaneously at the city level.