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A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area

This study examines the L.A.-Long Beach Metro area concerning the future risk of the PM(2.5) concentration increase. Population expansion, economic growth, and temperature increase are incorporated to estimate the probability of the magnitude of PM(2.5) emission increase. Three possible sectors for...

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Detalles Bibliográficos
Autores principales: He, Bowen, Guan, Qun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124696/
https://www.ncbi.nlm.nih.gov/pubmed/34064536
http://dx.doi.org/10.3390/ijerph18094905
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author He, Bowen
Guan, Qun
author_facet He, Bowen
Guan, Qun
author_sort He, Bowen
collection PubMed
description This study examines the L.A.-Long Beach Metro area concerning the future risk of the PM(2.5) concentration increase. Population expansion, economic growth, and temperature increase are incorporated to estimate the probability of the magnitude of PM(2.5) emission increase. Three possible sectors for the reduction of PM(2.5) emissions are considered: ocean-going vessels, refineries, and electricity-generating units. The decision of how best to allocate emissions-reduction efforts among these three sectors is analyzed using a quantitative and qualitative decision-analysis framework. For quantitative analysis, Expected Monetary Value (EMV) and Expected Utility (EU) methods are used to select the optimal sector to invest in. Based on the EMV calculation, the refineries sector is 3.5 times and 6.4 times more worthy of investment compared to the electricity-generating units and the ocean-going vessels sector, respectively. For the qualitative analysis, three criteria (investment efficiency, implementation difficulty, time to become effective) are considered in the decision-making process and sensitivity analysis is conducted to inform the ocean-going vessel sector is the optimal alternative for all possible scenarios. The refineries sector is more preferred than the electricity-generating units sector when the implementation difficulty’s weight is smaller than 50%. This study provides a valuable risk and decision analysis framework for analyzing the air pollution problem associated with the future PM(2.5) concentration increase caused by three risk factors: population growth, economic growth, and climate change.
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spelling pubmed-81246962021-05-17 A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area He, Bowen Guan, Qun Int J Environ Res Public Health Article This study examines the L.A.-Long Beach Metro area concerning the future risk of the PM(2.5) concentration increase. Population expansion, economic growth, and temperature increase are incorporated to estimate the probability of the magnitude of PM(2.5) emission increase. Three possible sectors for the reduction of PM(2.5) emissions are considered: ocean-going vessels, refineries, and electricity-generating units. The decision of how best to allocate emissions-reduction efforts among these three sectors is analyzed using a quantitative and qualitative decision-analysis framework. For quantitative analysis, Expected Monetary Value (EMV) and Expected Utility (EU) methods are used to select the optimal sector to invest in. Based on the EMV calculation, the refineries sector is 3.5 times and 6.4 times more worthy of investment compared to the electricity-generating units and the ocean-going vessels sector, respectively. For the qualitative analysis, three criteria (investment efficiency, implementation difficulty, time to become effective) are considered in the decision-making process and sensitivity analysis is conducted to inform the ocean-going vessel sector is the optimal alternative for all possible scenarios. The refineries sector is more preferred than the electricity-generating units sector when the implementation difficulty’s weight is smaller than 50%. This study provides a valuable risk and decision analysis framework for analyzing the air pollution problem associated with the future PM(2.5) concentration increase caused by three risk factors: population growth, economic growth, and climate change. MDPI 2021-05-04 /pmc/articles/PMC8124696/ /pubmed/34064536 http://dx.doi.org/10.3390/ijerph18094905 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
He, Bowen
Guan, Qun
A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area
title A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area
title_full A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area
title_fullStr A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area
title_full_unstemmed A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area
title_short A Risk and Decision Analysis Framework to Evaluate Future PM(2.5) Risk: A Case Study in Los Angeles-Long Beach Metro Area
title_sort risk and decision analysis framework to evaluate future pm(2.5) risk: a case study in los angeles-long beach metro area
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124696/
https://www.ncbi.nlm.nih.gov/pubmed/34064536
http://dx.doi.org/10.3390/ijerph18094905
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