Air Pollution Modeling

Yadav, Ravi; Trivedi, P. R.; Sahu, L. K.; Beig, Gufran

doi:10.1007/978-981-15-3481-2_3

Cited by 2 publications

(2 citation statements)

References 39 publications

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“…These models are used for different purposes, such as event forecasting and long-term planning in air quality management (Itahashi, 2021). Additionally, modeling can be used to assess the air quality of urban areas, considering factors like toxic levels and variations in pollutant levels (Yadav et al, 2020). Furthermore, deep learning frameworks, such as the temporal sliding long short-term memory extended model (TS-LSTME), have been proposed to predict air quality in the following 24 hours.…”

Section: Type Of Air Pollution Modelsmentioning

confidence: 99%

“…Extensive research has established strong associations between air pollution exposure and respiratory diseases, cardiovascular disorders, cancer, neurological disorders, developmental effects, diabetes, immune system dysfunction, and skin health issues (Rice et al, 2021). Air pollution has significant impacts on human health, including respiratory and cardiovascular diseases, as well as neurological and immune dysfunctions (Yadav et al, 2020;Dominski et al, 2021;Kuppala, 2021). It is also associated with adverse effects on the developing fetus, such as low birth weight and stillbirth (Toledo de Almeida Albuquerque et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Air Pollution: A Review of Its Impacts on Health and Ecosystems, and Analytical Techniques for Their Measurement and Modeling

Mekuria

2023

J ENVIRON INFORM LET

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Air pollution is a significant global problem that affects human health and the natural environment. This research article aims to provide a comprehensive review of the impacts of air pollution on health and ecosystems and present various analytical techniques used for its measurement and modeling. The study uses a systematic review method to identify and evaluate research articles that deal with air pollution, its impacts on health and ecosystems, analytical techniques, and modeling that are only available in English and published between 2012 and 2023. The findings outlined in this article contribute to an enhanced understanding of the detrimental effects of air pollution and provide insights into effective monitoring and mitigation strategies. In conclusion, by implementing effective policies, adopting clean technologies, promoting sustainable practices, and raising awareness, we can mitigate the impacts of air pollution and create a healthier and more sustainable future.

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Section: Type Of Air Pollution Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Air Pollution: A Review of Its Impacts on Health and Ecosystems, and Analytical Techniques for Their Measurement and Modeling

Mekuria

2023

J ENVIRON INFORM LET

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Assessment of meteorological settings on air quality modeling system—a proposal for UN-SDG and regulatory studies in non-homogeneous regions in Brazil

Silva

Pimentel

Duda

et al. 2022

Environ Sci Pollut Res

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Air quality models are essential tools to meet the United Nations Sustainable Development Goals (UN-SDG) because they are effective in guiding public policies for the management of air pollutant emissions and their impacts on the environment and human health. Despite its importance, Brazil still lacks a guide for choosing and setting air quality models for regulatory purposes. Based on this, the current research aims to assess the combined WRF/CALMET/CALPUFF models for representing SO2 dispersion over non-homogeneous regions as a regulatory model for policies in Brazilian Metropolitan Regions to satisfy the UN-SDG. The combined system was applied to the Rio de Janeiro Metropolitan Region (RJMR), which is known for its physiographic complexity. In the rst step, the WRF model was evaluated against surface-observed data. The local circulation was underestimated, while the prevailing observational winds were well-represented. In the second step, it was veri ed that all CALMET three meteorological con gurations performed better for the most frequent wind speed classes, so that the largest SO2 concentrations errors occurred during light winds. Among the meteorological settings in WRF/CALMET/CALPUFF, the joined use of observed and modeled meteorological data yielded the best results for the dispersion of pollutants. This result emphasizes the relevance of meteorological data composition in complex regions with unsatisfactory monitoring given the inherent limitations of prognostic models and the excessive extrapolation of observed data that can generate distortions of reality. This research concludes with the proposal of the WRF/CALMET/CALPUFF air quality regulatory system as a supporting tool for policies in the Brazilian Metropolitan Regions in the framework of the UN-SDG, particularly in non-homogeneous regions where steady-state Gaussian models are not applicable.

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Air Pollution Modeling

Cited by 2 publications

References 39 publications

Air Pollution: A Review of Its Impacts on Health and Ecosystems, and Analytical Techniques for Their Measurement and Modeling

Air Pollution: A Review of Its Impacts on Health and Ecosystems, and Analytical Techniques for Their Measurement and Modeling

Assessment of meteorological settings on air quality modeling system—a proposal for UN-SDG and regulatory studies in non-homogeneous regions in Brazil

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