The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai, China.
College of Transportation Engineering, Tongji University, Shanghai, China.
Front Public Health. 2021 Dec 24;9:791575. doi: 10.3389/fpubh.2021.791575. eCollection 2021.
Previous studies have paid little attention to the spatial heterogeneity of residents' marginal willingness to pay (MWTP) for clean air at a city level. To fill this gap, this study adopts a geographically weighted regression (GWR) model to quantify the spatial heterogeneity of residents' MWTP for clean air in Shanghai. First, Shanghai was divided into 218 census tracts and each tract was the smallest research unit. Then, the impacts of air pollutants and other built environment variables on housing prices were chosen to reflect residents' MWTP and a GWR model was used to analyze the spatial heterogeneity of the MWTP. Finally, the total losses caused by air pollutants in Shanghai were estimated from the perspective of housing market value. Empirical results show that air pollutants have a negative impact on housing prices. Using the marginal rate of transformation between housing prices and air pollutants, the results show Shanghai residents, on average, are willing to pay 50 and 99 Yuan/m to reduce the mean concentration of PM and NO by 1 μg/m, respectively. Moreover, residents' MWTP for clean air is higher in the suburbs and lower in the city center. This study can help city policymakers formulate regional air management policies and provide support for the green and sustainable development of the real estate market in China.
先前的研究很少关注城市层面居民对清洁空气的边际意愿支付（MWTP）的空间异质性。为了填补这一空白，本研究采用地理加权回归（GWR）模型来量化上海居民对清洁空气的 MWTP 的空间异质性。首先，将上海划分为 218 个普查区，每个普查区都是最小的研究单元。然后，选择空气污染物和其他建成环境变量对房价的影响来反映居民的 MWTP，并使用 GWR 模型来分析 MWTP 的空间异质性。最后，从住房市场价值的角度估算上海因空气污染物造成的总损失。实证结果表明，空气污染物对房价有负向影响。通过房价与空气污染物之间的边际转换率，可以得出上海居民平均愿意支付 50 元和 99 元，以分别将 PM 和 NO 的平均浓度降低 1μg/m。此外，居民对清洁空气的 MWTP 在郊区较高，在市中心较低。本研究可以帮助城市政策制定者制定区域性的空气管理政策，并为中国房地产市场的绿色和可持续发展提供支持。
