School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China.
School of Mathematics and Statistics, Shaoguan University, Shaoguan 512005, China.
Int J Environ Res Public Health. 2023 Jan 4;20(2):921. doi: 10.3390/ijerph20020921.
Although economic growth brings abundant material wealth, it is also associated with serious PM pollution. Decoupling PM emissions from economic development is important for China's long-term sustainable development. In this paper, the generalized Divisia index method (GDIM) is extended by introducing innovation indicators to investigate the main drivers of PM pollution in China and its four subregions from 2008 to 2017. Afterwards, a GDIM-based decoupling index is developed to examine the decoupling states between PM emissions and economic growth and to identify the main factors leading to decoupling. The obtained results show that: (1) Innovation input scale and GDP are the main drivers for increases in PM emissions, while innovation input PM intensity, emission intensity, and emission coefficient are the main reasons for reductions in PM pollution. (2) China and its four subregions show general upward trends in the decoupling index, and their decoupling states turn from weak decoupling to strong decoupling. (3) Innovation input PM intensity, emission intensity, and emission coefficient contribute largely to the decoupling of PM emissions. Overall, this paper provides valuable information for mitigating haze pollution.
尽管经济增长带来了丰富的物质财富，但也伴随着严重的 PM 污染。在中国实现长期可持续发展的过程中，将 PM 排放与经济发展脱钩至关重要。本文通过引入创新指标，扩展了广义 Divisia 指数法（GDIM），以研究 2008 年至 2017 年中国及其四个子区域的 PM 污染的主要驱动因素。随后，基于 GDIM 开发了一个脱钩指数，以检验 PM 排放与经济增长之间的脱钩状态，并确定导致脱钩的主要因素。研究结果表明：（1）创新投入规模和 GDP 是 PM 排放增加的主要驱动因素，而创新投入 PM 强度、排放强度和排放系数是 PM 污染减少的主要原因。（2）中国及其四个子区域的脱钩指数均呈总体上升趋势，其脱钩状态由弱脱钩转变为强脱钩。（3）创新投入 PM 强度、排放强度和排放系数对 PM 排放的脱钩贡献较大。总的来说，本文为缓解雾霾污染提供了有价值的信息。
