Estimation of economic costs of air pollution caused by motor vehicles in Iran (Isfahan)

Soleimani, Mozhgan; Nematollah, Akbari; Saffari, Babak; Haghshenas, Hosein

doi:10.1007/s11356-021-13504-6

Cited by 6 publications

(3 citation statements)

References 75 publications

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“…Its prominence as one of the prominent cities in Iran is notable and warrants scholarly acknowledgment (Soleimani, Akbari et al 2021). Isfahan, a prominent urban center, grapples with a multitude of air pollution concerns, predominantly stemming from the presence of significant industrial sectors such as steel production, oil refineries, and petrochemical facilities.…”

Section: -1-study Area Descriptionmentioning

confidence: 99%

Using Artificial Neural Network for Forecasting PM2.5 Levels in a Prominent Industrial and Historically Significant Urban Center in Iran: Evaluating Health Implications

bardshahi,

Jaafarzadeh,

Tabatabaie

et al. 2023

Preprint

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There has been a scarcity of comprehensive studies that aim to predict both the levels of PM2.5 particles and their corresponding impacts on human health. To fill this gap, we developed an artificial neural network model and AirQ+ software to predict PM2.5 concentrations and assess their associated health effects. The ANN model utilized five distinct input parameters, specifically wind velocity, wind orientation, atmospheric temperature, relative moisture content, and PM2.5 levels, observed within the time frame of 2018 to 2019. The concealed stratum comprised a total of ten neurons, in addition to the presence of an output layer. The MLP neural network demonstrated strong correlations at each stage: 0.908 (training), 0.910 (validation), 0.914 (testing), and 0.907 overall. The RMSE was determined as 6.52 µg/m3 when evaluating the neural network, thus indicating the notable predictive precision exhibited by the multilayer perceptron (MLP) neural network when forecasting the concentration of PM2.5 particles. The AirQ+ software, created by the World Health Organization (WHO), was employed to assess the magnitude and consequences of PM2.5 concentrations. The average concentration of PM2.5 particles throughout the duration of the study was recorded as 26.5 μg/m3, which exceeds the recommended limit provided by the WHO by a factor of 5.3. The study estimated the proportions and numbers of deaths attributed to various conditions. Specifically, chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD), lung cancer (LC), stroke, and all-cause mortality accounted for approximately 11.67%, 15.02%, 13.25%, 15.225%, and 9.45% respectively. The estimated number of deaths were 19,195 for all causes, 10,063 for COPD, 564 for IHD, and 1,063 for lung cancer. The findings of this investigation demonstrate a high degree of reliability in the methodologies utilized. Through the utilization of these approaches, individuals in positions of authority and responsibility can aptly evaluate the cost-benefit analysis, leading to a reduction in human casualties and mitigating the economic burdens on society.

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Section: -1-study Area Descriptionmentioning

confidence: 99%

Using Artificial Neural Network for Forecasting PM2.5 Levels in a Prominent Industrial and Historically Significant Urban Center in Iran: Evaluating Health Implications

bardshahi,

Jaafarzadeh,

Tabatabaie

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Then, health endpoints were evaluated using the value of a statistical life approach . Finally, the monetary value of each unit of pollution was calculated based on the annual emissions of each pollutant into the air (Soleimani et al, 2021;. The five stages of this Calculation are shown in Figure2.…”

Section: Calculation Of Monetary Value Of Time and Monetary Value Of ...mentioning

confidence: 99%

“…Wang et al, 2015). While in this study, the cost of each emission unit for car and bus modes has been estimated using epidemiological studies and health impact assessment (Soleimani, Akbari, Saffari, & Haghshenas, 2021. The willingness to pay method has been also used to calculate the economic cost of the health effects of air pollution.…”

Section: Introductionmentioning

confidence: 99%

Determining urban tolls based on two pricing schemes by considering emission of pollution (Case study: Isfahan, Iran)

Soleimani

Nematollah

Saffari

et al. 2022

Preprint

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The problem of traffic congestion and the environmental issues related to air pollution are among the essential problems of urban management that metropolitan cities are trying to mitigate. Given that the contribution of motor vehicles to air pollution is significant, both goals are achieved by managing urban transport. Among the various methods of travel demand management, congestion pricing is a very efficient measure. In this study, it is tried to simultaneously increase the efficiency of the transportation network and reduce the environmental effects by using a bi-level model for the multi-modal network. For this purpose, the upper-level model includes minimization of the objective function, i.e., pollution emission costs, and overall commuting cost. The lower level also has a transportation network model that provides the condition of user equilibrium. Two pricing schemes, including cordon-based and link-based pricing, are used to investigate and assist policymakers. The genetic and Frank-Wolfe algorithms have been used to solve the bi-level programming model. The proposed algorithm is also applied for a real network in Isfahan-Iran. The results of the proposed model for different pricing strategies were compared. According to the results, both pricing schemes mitigate traffic congestion and pollution, and the demand was shifted from the private car mode to public transportation. However, link-based pricing provides better performance than cordon-based pricing. According to the results, if there are conditions of link-based pricing, this scheme can reduce pollution and increase tolls revenue.JEL Classification: R41, O18, R48, C61, C63, Q53

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Exploring the potential of third-generation microalgae bio-alcohol and biodiesel in arresting particulate smoke emissions and greenhouse gases using CART

Jacob

Ashok

Lawrence

et al. 2022

Environ Sci Pollut Res

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Estimation of economic costs of air pollution caused by motor vehicles in Iran (Isfahan)

Cited by 6 publications

References 75 publications

Using Artificial Neural Network for Forecasting PM2.5 Levels in a Prominent Industrial and Historically Significant Urban Center in Iran: Evaluating Health Implications

Using Artificial Neural Network for Forecasting PM2.5 Levels in a Prominent Industrial and Historically Significant Urban Center in Iran: Evaluating Health Implications

Determining urban tolls based on two pricing schemes by considering emission of pollution (Case study: Isfahan, Iran)

Exploring the potential of third-generation microalgae bio-alcohol and biodiesel in arresting particulate smoke emissions and greenhouse gases using CART

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