Research Center of the Central China Economic Development, Nanchang University, Nanchang, 330031, China; School of Economics and Management, Nanchang University, Nanchang, 330031, China.
Research Center of the Central China Economic Development, Nanchang University, Nanchang, 330031, China; School of Economics and Management, Nanchang University, Nanchang, 330031, China.
J Environ Manage. 2023 Dec 1;347:118991. doi: 10.1016/j.jenvman.2023.118991. Epub 2023 Sep 26.
In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM data of 223 prefecture-level and above cities in China mainland during 2004-2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development.
近年来，中国在取得诸多经济奇迹的同时，也饱受严重空气污染的困扰。频发的雾霾天气严重制约了中国的可持续发展。为了研究社会经济因素对中国城市雾霾的非线性门槛效应，本研究基于 STIRPAT 理论，利用中国内地 2004-2016 年 223 个地级及以上城市的遥感反演 PM 数据，构建了空间计量平滑转移自回归回归（STAR）模型。本研究采用拟极大似然估计对 ARAR-STAR 模型进行估计，并通过蒙特卡罗模拟验证参数估计的准确性，证明了本研究构建的 ARAR-STAR 模型具有稳健性。研究结果表明：经济发展水平、人口密度、先进产业结构、能源消耗、对外开放等社会经济因素与雾霾污染之间存在复杂的空间非线性关系。在空间影响下，社会经济因素对雾霾减排的影响具有复杂的异质性，存在着从高到低的经济发展水平的平滑过渡。本文构建的同时具有个体固定效应和时间固定效应的 ARAR-STAR 模型，扩展了现有空间面板非线性模型的形式，丰富和实现了空间面板平滑转移门槛模型在环境领域的应用。这不仅为中国尽快实现“污染减排与碳减排协同增效”提供政策建议，也为中国应对全球气候变化、推动全球可持续发展做出贡献。
