Dataset Information

Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China.

ABSTRACT: Urban traffic pollution, which is strongly influenced by the complex urban morphology, has posed a great threat to human health. In this study, we performed a high-resolution simulation of traffic pollution in a typical city block in Baoding, China, based on the Parallelized Large-eddy simulation Model (PALM), to examine the distribution patterns of traffic-related pollutants and explore their relationship with urban morphology. Based on the model results, we conducted a multi-linear regression (MLR) analysis and found that the distribution of air pollutants inside the city block was dominated by both traffic emissions and urban morphology, which explained about 70% of the total variance in spatial distribution of air pollutants. Excluding the contribution of emissions, over 50% of the total variance can still be explained by the urban morphology. Among these urban morphological factors, the key factors determining the spatial distribution of air pollution are "Distance from the road" (DR), "Building Coverage Ratio" (BCR) and "Aspect Ratio" (H/W) of the street canyon. Specifically, urban areas with lower Aspect Ratio, lower BCR and larger DR are less affected by traffic pollution. Compiling these individual factors, we developed a complex Urban Morphology Pollution Index (UMPI). Each unit increase in UMPI is associated with a one percent increase of nearby traffic pollution contribution. This index can help urban planners to semi-quantitatively evaluate building groups which tend to trap or ventilate traffic pollution and thus help to reduce human exposure to street canyon level pollution through either traffic emission control or urban morphology amelioration.

SUBMITTER: Zhou J

PROVIDER: S-EPMC9408171 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China.

Zhou Jingcheng J Liu Junfeng J Xiang Songlin S Zhang Yizhou Y Wang Yuqing Y Ge Wendong W Hu Jianying J Wan Yi Y Wang Xuejun X Liu Ying Y Ma Jianmin J Wang Xilong X Tao Shu S

International journal of environmental research and public health 20220822 16

Urban traffic pollution, which is strongly influenced by the complex urban morphology, has posed a great threat to human health. In this study, we performed a high-resolution simulation of traffic pollution in a typical city block in Baoding, China, based on the Parallelized Large-eddy simulation Model (PALM), to examine the distribution patterns of traffic-related pollutants and explore their relationship with urban morphology. Based on the model results, we conducted a multi-linear regression ...[more]

PMID: 36012070

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Project description:Introduction: Many studies have reported the association between air pollution and human health based on regulatory air pollution monitoring data. However, because regulatory monitoring networks were not designed for epidemiological studies, the collected data may not provide sufficient spatial contrasts for assessing such associations. Our goal was to develop a monitoring design supplementary to the regulatory monitoring network in Seoul, Korea. This design focused on the selection of 20 new monitoring sites to represent the variability in PM2.5 across people's residences for cohort studies. Methods: We obtained hourly measurements of PM2.5 at 37 regulatory monitoring sites in 2010 in Seoul, and computed the annual average at each site. We also computed 313 geographic variables representing various pollution sources at the regulatory monitoring sites, 31,097 children's homes from the Atopy Free School survey, and 412 community service centers in Seoul. These three types of locations represented current, subject, and candidate locations. Using the regulatory monitoring data, we performed forward variable selection and chose five variables most related to PM2.5. Then, k-means clustering was applied to categorize all locations into several groups representing a diversity in the spatial variability of the five selected variables. Finally, we computed the proportion of current to subject location in each cluster, and randomly selected new monitoring sites from candidate sites in the cluster with the minimum proportion until 20 sites were selected. Results: The five selected geographic variables were related to traffic or urbanicity with a cross-validated R² value of 0.69. Clustering analysis categorized all locations into nine clusters. Finally, one to eight new monitoring sites were selected from five clusters. Discussion: The proposed monitoring design will help future studies determine the locations of new monitoring sites representing spatial variability across residences for epidemiological analyses.

Project description:Background The association between fine particulate matter and cardiovascular disease has been convincingly demonstrated. The role of traffic-related air pollutants is less clear. To better understand the role of traffic-related air pollutants in cardiovascular disease development, we examined associations between NO2, carotid atherosclerotic plaque, and cardiometabolic disorders associated with cardiovascular disease. Methods and Results Cross-sectional analyses were conducted among 2227 patients (62.9±13.8 years; 49.5% women) from the Stroke Prevention and Atherosclerosis Research Centre (SPARC) in London, Ontario, Canada. Total carotid plaque area measured by ultrasound, cardiometabolic disorders, and residential locations were provided by SPARC medical records. Long-term outdoor residential NO2 concentrations were generated by a land use regression model. Associations between NO2, total carotid plaque area, and cardiometabolic disorders were examined using multiple regression models adjusted for age, sex, smoking, and socioeconomic status. Mean NO2 was 5.4±1.6 ppb in London, Ontario. NO2 was associated with a significant increase in plaque (3.4 mm2 total carotid plaque area per 1 ppb NO2), exhibiting a linear dose-response. NO2 was also positively associated with triglycerides, total cholesterol, and the ratio of low- to high-density lipoprotein cholesterol (P<0.05). Diabetes mellitus mediated the relationship between NO2 and total carotid plaque area (P<0.05). Conclusions Our results demonstrate that even low levels of traffic-related air pollutants are linked to atherosclerotic plaque burden, an association that may be partially attributable to pollution-induced diabetes mellitus. Our findings suggest that reducing ambient concentrations in cities with NO2 below current standards would result in additional health benefits. Given the billions of people exposed to traffic emissions, our study supports the global public health significance of reducing air pollution.

Dataset Information

Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China.

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Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China.

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