Wang Shaogu, Cheng Shunqi, Qi Xinhua
School of Geography, Fujian Normal University, Fuzhou, China.
Front Public Health. 2020 Nov 16;8:551300. doi: 10.3389/fpubh.2020.551300. eCollection 2020.
In China, severe haze is a major public health concern affecting residents' health and well-being. This study used hourly air quality monitoring data from 285 cities in China to analyze the effect of green coverage (GC) and other economic variables on the incremental PM concentration (ΔPM) during peak hours. To detect possible non-linear and interaction effect between predictive variables, a kernel-based regularized least squares (KRLS) model was used for empirical analysis. The results show that there was considerable heterogeneity between cities regarding marginal effect of GC on ΔPM, which could potentially be explained by different seasons, latitude, urban maintenance expenditure (UE), real GDP per capita (PG), and population density (PD). Also described in this study, in cities with high UE, the growth of GC, PG, and PD always remain a positive impact on mitigation of haze pollution. This shows that government expenditure on urban maintenance can reduce or mitigate the environmental pollution from economic development. In addition, the influence of other urban elements on air quality had also been analyzed so that different combinations of mitigation policies are proposed for different regions in this study to meet the mitigation targets.
在中国，严重雾霾是影响居民健康和福祉的重大公共卫生问题。本研究使用了中国285个城市的每小时空气质量监测数据，分析了绿化覆盖率（GC）和其他经济变量对高峰时段PM浓度增量（ΔPM）的影响。为了检测预测变量之间可能存在的非线性和交互效应，采用了基于核的正则化最小二乘（KRLS）模型进行实证分析。结果表明，不同城市之间绿化覆盖率对ΔPM的边际效应存在显著差异，这可能是由不同季节、纬度、城市维护支出（UE）、人均实际国内生产总值（PG）和人口密度（PD）造成的。本研究还表明，在城市维护支出较高的城市中，绿化覆盖率、人均实际国内生产总值和人口密度的增长始终对减轻雾霾污染具有积极影响。这表明政府在城市维护方面的支出可以减少或减轻经济发展带来的环境污染。此外，本研究还分析了其他城市因素对空气质量的影响，从而针对不同地区提出了不同的减排政策组合，以实现减排目标。
