噪声污染
环境卫生
空气污染
弱势群体
社会经济地位
环境科学
污染
多项式logistic回归
噪音(视频)
逻辑回归
地理
人口
统计
计算机科学
医学
数学
降噪
经济增长
图像(数学)
生物
人工智能
经济
有机化学
化学
生态学
作者
Dong Liu,Mei‐Po Kwan,Zihan Kan,Yang Liu
标识
DOI:10.1016/j.socscimed.2023.116040
摘要
Although exposure to air/noise pollution and greenspace has been found to significantly affect people's physical and mental health outcomes, there is still a lack of knowledge on what built-environment and socioeconomic factors are significantly associated with people's tri-exposure to air/noise pollution and greenspace. This study analyzes the associations between built-environment and socioeconomic factors and the tri-exposure to greenspace and air/noise pollution in Hong Kong. Based on individual-level activity data, real-time GPS trajectories, and exposure data collected by portable sensors as well as remote sensing satellite imagery, we employ multinomial logistic regression to determine the socioeconomic and built-environment factors that are significantly associated with the type of participants' tri-exposure at the grid cell level. The results show that higher transit nodal accessibility, building density, building height and land-use mix are significantly associated with a higher likelihood of being disadvantaged in terms of tri-exposure to air/noise pollution and greenspace. While more advantageous tri-exposures are significantly related to higher median monthly household income and sky view factor. Old high-rise high-density neighborhoods are more likely to be triply disadvantaged with low greenspace exposure but high air pollution and noise pollution exposure. The findings provide policymakers with critical reference in terms of addressing the inequalities in the tri-exposure outcomes.
科研通智能强力驱动
Strongly Powered by AbleSci AI