東華大學圖書館 |

Strategical Planning and Impacts Analysis of Prescribed Fire in Forest Fire Management /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Strategical Planning and Impacts Analysis of Prescribed Fire in Forest Fire Management // Jianzhou Qi.
Author:	Qi, Jianzhou,
Description:	1 electronic resource (140 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
Contained By:	Dissertations Abstracts International86-03A.
Subject:	Wildlife management. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31490857
ISBN:	9798384085386

Strategical Planning and Impacts Analysis of Prescribed Fire in Forest Fire Management /
Qi, Jianzhou,

Strategical Planning and Impacts Analysis of Prescribed Fire in Forest Fire Management /Jianzhou Qi. - 1 electronic resource (140 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: A.

Wildfire risk, increasingly affected by evolving climatic conditions, requires strategic intervention. Prescribed burning, as a primary method, offers numerous benefits, such as reducing fuel loads and mitigating wildfire severity. However, it also presents substantial side effects and risks, including the potential for escaped fires and adverse impacts on air quality. This project seeks to refine the implementation and optimization of prescribed burns through a comprehensive analytical approach, addressing both the benefits and potential risks to develop more effective and sustainable prescribed burning strategies.We initiated our study with a systematic review of the literature on optimization and decision models for prescribed burning, analyzing 471 academic papers published in the last 20 years. Our study identifies four main types of models: Spatial-Allocation, Spatial-Extent, Temporal-only, and Spatial-Temporal. We observe a growing number of studies on modeling prescribed burning, primarily due to the expansion in spatial-allocation and spatial-temporal models. There is also an increase in complexity as the models consider more elements affecting the prescribed burning effectiveness. We identify the essential components for optimization models, including stakeholders, decision variables, objectives, and influential factors, to enhance model practicality. The review also examines solution techniques, such as integer programming in spatial allocation, stochastic dynamic programming in probabilistic models, and multi-objective programming in balancing trade-offs. These techniques' strengths and limitations are discussed to help researchers adapt methods to specific challenges in prescribed burning optimization. Additionally, we investigate general assumptions in the models and challenges in relaxation to enhance practicality. For example, the assumption was made for static burning conditions and flat topography. After a thorough review of existing prescribed burning models and the identification of research gaps, we conducted a detailed study on the risks associated with escaped fires during prescribed burns, aiming to enhance their cost-effectiveness. We introduced a decision-analytical model that evaluates strategic decisions of prescribed burning. This model considers the risks of escaped fires and suggests solutions for determining optimal coverage and expected costs. By applying our model to a 2021 Oregon case, we determined that every dollar spent on prescribed burning cuts expected costs by $6, albeit with an additional $0.23 for suppressing escaped fires. The ideal burn coverage was 59% more than the existing level, leading to a 63% reduction in costs. In this framework, 15% of the expected costs go towards escaped fire suppression, equivalent to 5% of Oregon's 2021 fire management expenditure.In the last phase, we conducted a study to analyze the impact of prescribed burning PM2.5 emissions, focusing on strategic planning to minimize total net fires PM2.5 emission costs. Although prescribed burning can effectively mitigate PM2.5 emissions from wildfires, it emits a considerable amount of hazardous emissions, especially during the smoldering phase. Specifically, we developed an optimization model that quantifies both the implementation costs of prescribed burning and the social costs of PM2.5 emissions from prescribed burning and wildfires. Applying this model to Oregon in 2021, we demonstrated that prescribed burning can effectively reduce wildfire emissions and the associated social costs by 65.30%, with an estimated benefit-cost ratio of 4.35. The total net cost can be reduced by 25.68% at the optimal prescribed burning extent, which requires a 15.65% increase in the acreage compared to what was actually implemented. However, our case study also showed that exceeding this optimal extent significantly raises net costs due to the social costs of elevated PM2.5 emissions from prescribed burning. Over-implementation leads to a proportional increase in adverse health outcomes, ultimately outweighing the benefits.

English

ISBN: 9798384085386Subjects--Topical Terms:

571816
Wildlife management.
Subjects--Index Terms:

Burn strategy

Strategical Planning and Impacts Analysis of Prescribed Fire in Forest Fire Management /
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520 $a Wildfire risk, increasingly affected by evolving climatic conditions, requires strategic intervention. Prescribed burning, as a primary method, offers numerous benefits, such as reducing fuel loads and mitigating wildfire severity. However, it also presents substantial side effects and risks, including the potential for escaped fires and adverse impacts on air quality. This project seeks to refine the implementation and optimization of prescribed burns through a comprehensive analytical approach, addressing both the benefits and potential risks to develop more effective and sustainable prescribed burning strategies.We initiated our study with a systematic review of the literature on optimization and decision models for prescribed burning, analyzing 471 academic papers published in the last 20 years. Our study identifies four main types of models: Spatial-Allocation, Spatial-Extent, Temporal-only, and Spatial-Temporal. We observe a growing number of studies on modeling prescribed burning, primarily due to the expansion in spatial-allocation and spatial-temporal models. There is also an increase in complexity as the models consider more elements affecting the prescribed burning effectiveness. We identify the essential components for optimization models, including stakeholders, decision variables, objectives, and influential factors, to enhance model practicality. The review also examines solution techniques, such as integer programming in spatial allocation, stochastic dynamic programming in probabilistic models, and multi-objective programming in balancing trade-offs. These techniques' strengths and limitations are discussed to help researchers adapt methods to specific challenges in prescribed burning optimization. Additionally, we investigate general assumptions in the models and challenges in relaxation to enhance practicality. For example, the assumption was made for static burning conditions and flat topography. After a thorough review of existing prescribed burning models and the identification of research gaps, we conducted a detailed study on the risks associated with escaped fires during prescribed burns, aiming to enhance their cost-effectiveness. We introduced a decision-analytical model that evaluates strategic decisions of prescribed burning. This model considers the risks of escaped fires and suggests solutions for determining optimal coverage and expected costs. By applying our model to a 2021 Oregon case, we determined that every dollar spent on prescribed burning cuts expected costs by $6, albeit with an additional $0.23 for suppressing escaped fires. The ideal burn coverage was 59% more than the existing level, leading to a 63% reduction in costs. In this framework, 15% of the expected costs go towards escaped fire suppression, equivalent to 5% of Oregon's 2021 fire management expenditure.In the last phase, we conducted a study to analyze the impact of prescribed burning PM2.5 emissions, focusing on strategic planning to minimize total net fires PM2.5 emission costs. Although prescribed burning can effectively mitigate PM2.5 emissions from wildfires, it emits a considerable amount of hazardous emissions, especially during the smoldering phase. Specifically, we developed an optimization model that quantifies both the implementation costs of prescribed burning and the social costs of PM2.5 emissions from prescribed burning and wildfires. Applying this model to Oregon in 2021, we demonstrated that prescribed burning can effectively reduce wildfire emissions and the associated social costs by 65.30%, with an estimated benefit-cost ratio of 4.35. The total net cost can be reduced by 25.68% at the optimal prescribed burning extent, which requires a 15.65% increase in the acreage compared to what was actually implemented. However, our case study also showed that exceeding this optimal extent significantly raises net costs due to the social costs of elevated PM2.5 emissions from prescribed burning. Over-implementation leads to a proportional increase in adverse health outcomes, ultimately outweighing the benefits.
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650 4 $a Computer science. $3 523869
650 4 $a Forestry. $3 895157
650 4 $a Wildlife conservation. $2 fast $3 542165
650 4 $a Sustainability. $3 1029978
653 $a Burn strategy
653 $a Fire behavior
653 $a Fuel reduction
653 $a Prescribed fires
653 $a Risk assessment
653 $a Wildfire mitigation
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690 $a 0478
690 $a 0984
690 $a 0640
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710 2 $a State University of New York at Buffalo. $b Industrial and Systems Engineering. $e degree granting institution. $3 3823858
720 1 $a Zhuang, Jun $e degree supervisor.
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