Evaluating the Impact of Air Pollution on Health of Individuals Using a Dynamic Approach (Case Study: Tehran City)

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using NARX method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

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The Impact of Green Space Changes on Air Pollution and Microclimates: A Case Study of the Taipei Metropolitan Area

Sustainability ◽

10.3390/su6128827 ◽

2014 ◽

Vol 6 (12) ◽

pp. 8827-8855 ◽

Cited By ~ 26

Author(s):

Hsiao-Lan Liu ◽

Yu-Sheng Shen

Keyword(s):

Air Pollution ◽

Metropolitan Area ◽

Green Space ◽

The Impact

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Understanding the impact of vehicular emissions on air pollution from the perspective of regional transport: A case study of the Beijing-Tianjin-Hebei region in China

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.147304 ◽

2021 ◽

Vol 785 ◽

pp. 147304

Author(s):

Jianlei Lang ◽

Xiaoyu Liang ◽

Shengyue Li ◽

Ying Zhou ◽

Dongsheng Chen ◽

...

Keyword(s):

Air Pollution ◽

Vehicular Emissions ◽

Regional Transport ◽

The Impact

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Applying Social Science to Bring Resident Stakeholders into Pollution Governance: A Rural Environmental Justice Public Health Case Study

Journal of Applied Social Science ◽

10.1177/19367244211001751 ◽

2021 ◽

pp. 193672442110017

Author(s):

Sherrie M. Steiner ◽

Jordan M. Marshall ◽

Atefeh Mohammadpour ◽

Aaron W. Thompson

Keyword(s):

Air Pollution ◽

Social Science ◽

Pollution Monitoring ◽

Monitoring Method ◽

Air Pollution Monitoring ◽

Direct Exposure ◽

Cancer Clusters ◽

Governance Process ◽

The Impact

The purpose of this engaged public sociology study was to use social science to bring resident stakeholders into the process of governing pollution production in a rural community. The community has cancer clusters. Residents have concerns about direct exposure to pollution production in their neighborhood by a steel recycling plant that has been cited numerous times for environmental violations. The facility has been under voluntary remediation since 2009, but neighborhood residents were marginalized from the governance process. This case study details how social science was used to bring neighborhood residents’ concerns about direct exposure to toxic air pollution into remediation governance. A curricula-as-research model was developed to provide an engagement framework that guided the case study as it progressed through a series of six stages over five years. The principal investigator maintained this collaboration by integrating the project into courses, securing small grants, developing an affordable air pollution monitoring method, and convening multiple community meetings. The air monitoring results are analyzed and discussed. Finally, the impact of the case study on the company, the state environmental management agency, local government, the nonprofit partner, and residents’ sense of human agency is evaluated.

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Time series modeling of air pollution and its association with season and climate variables in istanbul, turkey

10.21203/rs.3.rs-27820/v4 ◽

2020 ◽

Author(s):

hazem al-najjar ◽

Nadia Al-Rousan ◽

Ismail A. Elhaty

Keyword(s):

Air Pollution ◽

Time Series ◽

Feature Selection ◽

Air Pollutants ◽

Time Series Modeling ◽

Climate Variables ◽

Different Seasons ◽

The Impact ◽

Nonlinear Autoregressive

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using Nonlinear AutoregRessive network with eXogenous inputs (NARX) method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

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Itinerant nationalisms and fracturing narratives: Incorporating regional dimensions of memory into peacebuilding

Memory Studies ◽

10.1177/1750698018800749 ◽

2018 ◽

Vol 13 (6) ◽

pp. 1183-1199

Author(s):

Andrea Purdeková

Keyword(s):

Nation Building ◽

Great Lakes Region ◽

National Context ◽

Dynamic Approach ◽

Cross Border ◽

Memory Work ◽

Multiple Levels ◽

Operational Action ◽

The Impact

While conflict is often understood across multiple levels, including its regional dimension, peacebuilding and memory work are rarely put in conversation at this level. The article explores regional dimensions of memory and argues that these open a novel and analytically productive lens on the nature and legacy of cross-border conflict and can bolster peacebuilding approaches. Taking the key case study of the Great Lakes Region of Africa, and specifically the regionalizing dimensions of the Rwandan genocide, the article investigates the impact of two very different regional dimensions of memory on social cohesion. First, the article considers the more intuitive ways in which grievances that extend across borders and fractured regional memories continue to fuel conflict. Second, and pushing beyond this, the article considers the ways in which returning diaspora deploys memory born in the wider region in attempts at nation-building. The article thus deploys a dynamic approach to memory, exploring mobile memories and the ways in which regional experiences are carried and deployed back in a national context. Overall, the article urges us to extend regional lens beyond the study of conflict roots and operational action to the study of postconflict peacebuilding and commemoration.

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Establishment of Regional Concentration–Duration–Frequency Relationships of Air Pollution: A Case Study for PM2.5

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17041419 ◽

2020 ◽

Vol 17 (4) ◽

pp. 1419 ◽

Cited By ~ 1

Author(s):

Hone-Jay Chu ◽

Muhammad Zeeshan Ali

Keyword(s):

Air Pollution ◽

Air Quality ◽

Spatial Pattern ◽

Frequency Of Occurrence ◽

Efficient Design ◽

Annual Frequency ◽

And Control ◽

Relationship Of ◽

The Impact

Poor air quality usually leads to PM2.5 warnings and affects human health. The impact of frequency and duration of extreme air quality has received considerable attention. The extreme concentration of air pollution is related to its duration and annual frequency of occurrence known as concentration–duration–frequency (CDF) relationships. However, the CDF formulas are empirical equations representing the relationship between the maximum concentration as a dependent variable and other parameters of interest, i.e., duration and annual frequency of occurrence. As a basis for deducing the extreme CDF relationship of PM2.5, the function assumes that the extreme concentration is related to the duration and frequency. In addition, the spatial pattern estimation of extreme PM2.5 is identified. The regional CDF identifies the regional extreme concentration with a specified duration and return period. The spatial pattern of extreme air pollution over 8 h duration shows the hotspots of air quality in the central and southwestern areas. Central and southwestern Taiwan is at high risk of exposure to air pollution. Use of the regional CDF analysis is highly recommended for efficient design of air quality management and control.

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