Objective vs. Perceived Air Pollution as a Factor of Housing Pricing: A Case Study of the Greater Haifa Metropolitan Area

2010 ◽  
Vol 18 (1) ◽  
pp. 99-122 ◽  
Author(s):  
Bella Berezansky ◽  
Boris Portnov ◽  
Boaz Barzilai
Keyword(s):  
Air Pollution ◽  
Metropolitan Area

scholarly journals Understanding Air Pollution from Induced Traffic during and after the Construction of a New Highway: Case Study of Highway 25 in Montreal

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Md. Shohel Reza Amin ◽  
Umma Tamima ◽  
Luis Amador Jimenez
Keyword(s):  
Air Pollution ◽  
Metropolitan Area ◽  
Road Network ◽  
Traffic Density ◽  
Air Contaminants ◽  
Construction Period ◽  
Close Vicinity ◽  
The Road ◽  
On The Road

This study demonstrates through a case study that detailed analyses, even after the construction of a project, are feasible using current technologies and available data. A case study of highway 25 is used to illustrate the method and verify the levels of air contaminants from additionally induced traffic during and after the construction of highway. Natural traffic growth was removed from the effect of observed gas emissions by comparing observed levels on other further locations in the same metropolitan area. This study estimates air pollution from the additional traffic during and after the construction of A-25 extension project. NO2 levels were spatially interpolated during peak and off-peak hour traffic and traffic density simulated on the road network for four scenarios. Comparing the four scenarios, it was found that levels of NO2 concentrations were reduced at neighbor areas due to less traffic during the construction period. Levels of NO2 after the construction were higher than those in 2008. The simulated traffic density for four scenarios revealed that traffic density was significantly increased on both arterial and access roads within the close vicinity of the extension project during and after its construction.

Turbulence permitting air pollution simulation for the Stuttgart metropolitan area - A winter case study

2021 ◽  
Author(s):  
Thomas Schwitalla ◽  
Kirsten Warrach-Sagi ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer
Keyword(s):  
Air Pollution ◽  
Urban Space ◽  
Metropolitan Area ◽  
Complex Dynamics ◽  
Hot Spot ◽  
Vertical Mixing ◽  
Urban Canopy ◽  
Model System ◽  
Emission Data

<p>Currently a strong discussion is ongoing in Germany and Europe whether to ban vehicles from downtown areas in order to lower particle concentrations of e.g. PM<sub>10</sub> and NO<sub>2</sub>. As often only few measurements exist inside city centers, little to nothing is known about the horizontal and vertical distributions of air pollutants. Within the EU demonstration project Open Forecast (https://open-forecast.eu/), we applied the WRF-Chem model system version 4.0.3 in order to close this knowledge gap. We zoom in the urban area of Stuttgart, a hot spot of air pollution in Germany. The outermost domain with convection-permitting resolution of 1.25 km encompasses parts of Central Europe in order to provide boundary conditions for the inner two domains.</p><p>The model system was improved in many ways, e.g., with respect to the representation of land cover, urban canopy, and soil properties, which turned out to be key for an acceptable performance. Furthermore, we developed a sophisticated infrastructure to ingest the required high-resolution emission data, which turned out to be very challenging.</p><p>We show that this model approach is likely the best means to understand and to predict air pollution, as the distribution of their constituents depends strongly and simultaneously on the vertical mixing by turbulence, the mesoscale circulation in the complex urban environment, and orographic environment.</p><p>The model system was operated and investigated for a case study of January 21, 2019 during which an alert with respect to the exceedance of PM<sub>10</sub> was issued. We present the simulations of meteorological variables as well as PM<sub>10</sub> and NO<sub>2</sub> and show the complexity of their distribution in the nighttime stable and daytime shallow boundary layer in dependence of the temporal variability of the traffic in the Stuttgart metropolitan area.</p><p>To the best of our knowledge, the results reveal for the first time the complex dynamics of air pollution in complex urban space of Stuttgart at a very high spatial and temporal resolution that cannot currently be achieved with measurements.</p>

Comprehensive Pricing Model of Urban Traffic Air Pollution Based on Bi-Level Programming

2012 ◽  
Vol 253-255 ◽  
pp. 1913-1917
Author(s):  
Ze Bin Zhao
Keyword(s):  
Air Pollution ◽  
Negative Impact ◽  
Urban Traffic ◽  
Vehicle Speed ◽  
Pricing Model ◽  
The Sustainable Development ◽  
Transport Services ◽  
Relationship Model ◽  
The Relationship

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.

scholarly journals Association between Green Space Structure and the Prevalence of Asthma: A Case Study of Toronto

2021 ◽  
Vol 18 (11) ◽  
pp. 5852
Author(s):  
Yuping Dong ◽  
Helin Liu ◽  
Tianming Zheng
Keyword(s):  
Air Pollution ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Chronic Inflammatory Disease ◽  
Space Structure ◽  
Tree Diversity ◽  
Underlying Mechanisms ◽  
Index Tree

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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