AI Applied to Air Pollution and Environmental Health: A Case Study on Hypothesis Generation

2021 ◽  
pp. 195-222
Author(s):  
Colin Bellinger ◽  
Mohomed Shazan Mohomed Jabbar ◽  
Osnat Wine ◽  
Charlene Nielsen ◽  
Jesus Serrano-Lomelin ◽  
...  
2011 ◽  
Vol 111 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Michelle L. Bell ◽  
Luis A. Cifuentes ◽  
Devra L. Davis ◽  
Erin Cushing ◽  
Adriana Gusman Telles ◽  
...  

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 236
Author(s):  
Ha Na You ◽  
Myeong Ja Kwak ◽  
Sun Mi Je ◽  
Jong Kyu Lee ◽  
Yea Ji Lim ◽  
...  

Environmental pollution is an important issue in metropolitan areas, and roadside trees are directly affected by various sources of pollution to which they exhibit numerous responses. The aim of the present study was to identify morpho-physio-biochemical attributes of maidenhair tree (Ginkgo biloba L.) and American sycamore (Platanus occidentalis L.) growing under two different air quality conditions (roadside with high air pollution, RH and roadside with low air pollution, RL) and to assess the possibility of using their physiological and biochemical parameters as biomonitoring tools in urban areas. The results showed that the photosynthetic rate, photosynthetic nitrogen-use efficiencies, and photochromic contents were generally low in RH in both G. biloba and P. occidentalis. However, water-use efficiency and leaf temperature showed high values in RH trees. Among biochemical parameters, in G. biloba, the lipid peroxide content was higher in RH than in RL trees, but in P. occidentalis, this content was lower in RH than in RL trees. In both species, physiological activities were low in trees planted in areas with high levels of air pollution, whereas their biochemical and morphological variables showed different responses to air pollution. Thus, we concluded that it is possible to determine species-specific physiological variables affected by regional differences of air pollution in urban areas, and these findings may be helpful for monitoring air quality and environmental health using trees.


2012 ◽  
Vol 253-255 ◽  
pp. 1913-1917
Author(s):  
Ze Bin Zhao

In order to reduce the negative impact of urban traffic air pollution, this paper firstly analyzes the relationship between urban traffic air pollution and vehicle speed, after providing the relationship model, the paper establishes a comprehensive pricing model of urban traffic air pollution based on bi-level programming, the model considers the traffic air pollution pricing, and includes the factors of congestion pricing, bus fee, pricing revenue redistribution on improvement of public transport services and the expansion of road capacity. The case study shows that the implementation of comprehensive pricing of urban traffic air pollution can reduce traffic pollution and unreasonable traffic flow, which is conducive to the sustainable development of the city.


Author(s):  
Yuping Dong ◽  
Helin Liu ◽  
Tianming Zheng

Asthma is a chronic inflammatory disease that can be caused by various factors, such as asthma-related genes, lifestyle, and air pollution, and it can result in adverse impacts on asthmatics’ mental health and quality of life. Hence, asthma issues have been widely studied, mainly from demographic, socioeconomic, and genetic perspectives. Although it is becoming increasingly clear that asthma is likely influenced by green spaces, the underlying mechanisms are still unclear and inconsistent. Moreover, green space influences the prevalence of asthma concurrently in multiple ways, but most existing studies have explored only one pathway or a partial pathway, rather than the multi-pathways. Compared to greenness (measured by Normalized Difference Vegetation Index, tree density, etc.), green space structure—which has the potential to impact the concentration of air pollution and microbial diversity—is still less investigated in studies on the influence of green space on asthma. Given this research gap, this research took Toronto, Canada, as a case study to explore the two pathways between green space structure and the prevalence of asthma based on controlling the related covariates. Using regression analysis, it was found that green space structure can protect those aged 0–19 years from a high risk of developing asthma, and this direct protective effect can be enhanced by high tree diversity. For adults, green space structure does not influence the prevalence of asthma unless moderated by tree diversity (a measurement of the richness and diversity of trees). However, this impact was not found in adult females. Moreover, the hypothesis that green space structure influences the prevalence of asthma by reducing air pollution was not confirmed in this study, which can be attributed to a variety of causes.


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