Analyzing the phased changes of socioeconomic drivers to carbon dioxide and particulate matter emissions in the Yangtze River Delta. (July 2022)

• Record Type: Journal Article
• Authors: Lin, Huaxing; Jiang, Ping
• Is Part Of: Ecological indicators. Volume 140(2022)
• Publication Date: 2022-07
• Subjects: Climate change -- Air pollution -- Environmental collaborative governance -- Spatial Durbin error model -- Urban agglomeration; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.109044
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Data used in the study are collected from 41 cities in Yangtze River Delta from 2005 to 2017. The spatial Durbin error model is utilized for analyzing the local and spillover effects. The phased panel is employed to observe the periodical impact changes of the drivers. Three key drivers identified can significantly realize the collaborative governance. Abstract: Enhancing the environmental collaborative governance to reduce carbon dioxide (CO2 ) and particulate matter (PM2.5 ) emissions is an important and significant low-carbon green growth strategy in China. However, few studies have explored the periodical positive and negative impact changes of the drivers in interannual phases on both CO2 and PM2.5 emissions hitherto. With the panel data in the Yangtze River Delta urban agglomeration (YRDUA) from 2005 to 2017, here we analyzed the annual evolution characters of CO2 and PM2.5 emissions and the 10 socioeconomic drivers to these emissions. The spatial Durbin error model (SDEM) by the overall panel was developed to examine the socioeconomic drivers that can synergistically affect CO2 and PM2.5 emissions. Moreover, SDEM by the phased panel was employed to observe the periodical positive and negative impact changes of the drivers. The results reveal that, the drivers that can significantly realize the collaborative governance are normalized difference vegetation index (NDVI), energy intensity (EI), and fixed asset investment (FAI). Main results include: Every 1% increase in the NDVI can reduce CO2 emissions by 0.276% and PM2.5 concentration by 0.223%; every 1% increase in EI can increase CO2 emissions by 0.024% and PM2.5 concentration by 0.003%; and every 1% increase in FAI can increase CO2 emissions by 0.049% and PM2.5 concentration by 0.018%. Increased greening levels, reduced energy intensity, and reduced investment in fixed assets can significantly alleviate CO2 and PM2.5 emissions in the YRD. Furthermore, the phased panel estimation shows that after 2013, the positive impact of economic growth on CO2 and PM2.5 emissions weakens gradually. Similarly, the positive impact of technological upgrading on CO2 emissions begins to diminish, the rise in urbanization still increases CO2 emissions, and the PM2.5 pollution weakens after 2013. Increased traffic loads lead to an increase in PM2.5 emissions, and its effect is gradually enhanced in the later stage. In addition, the positive effect of FAI on CO2 emissions increases gradually and aggravates PM2.5 pollution as well. Therefore, this study suggests that the environmental collaborative governance should focus on reforming the clean energy structure; accelerating the green transformation of industrial structure; and promoting the low-carbon industrial system, energy system, and lifestyle.