Grant: Discovery Grants Program - Individual
University of Regina
$65,000.00
An optimization-based vulnerability and risk analysis approach for supporting air and waste management under multiple umcertainties
FY 2011-12
Summary
Air and waste management systems are complicated with many uncertain parameters and their interrelations that present in terms of multiple uncertainties, while the related decision problems are of interactive, dynamic and multiobjective features. These lead to difficulties in clarifying the related vulnerabilities, impacts, risks and liabilities under a variety of system conditions and policy scenarios. Consequently, the objectives of this proposed research is to develop an optimization-based vulnerability and risk analysis approach for air and waste management under multiple uncertainties; this entails (a) analysis of complexities in air and waste management systems, (b) development of inexact optimization techniques under multiple uncertainties, (c) advancement of optimization-based vulnerability and risk analysis approaches, and (d) incorporation of the developed inexact optimization techniques and vulnerability/risk analysis approaches within a general decision-support framework. Advanced inexact optimization methodologies will be developed for addressing various forms of complexities that exist in air and waste management systems. Based on the optimization analysis, a set of vulnerability/risk assessment methods will be further developed for analyzing the comprehensive effects of human interventions on the vulnerability of receptor systems as well as the compound risks caused by multiple environmental concerns. The developed technologies will then be applied to air and waste management within a western Canada context. The proposed study will provide technical and methodological supports for tackling challenges of vulnerability/risk analysis in relation to air and waste management. It will facilitate comprehensive consideration of factors that are related to the decisions of environmental management and risk analysis. Applications of the proposed techniques to Canadian cases will help industries and governments to improve their effectiveness in managing environmental problems. Besides, a number of graduate and undergraduate students will be trained through participation in the proposed research. The trained students will fill a pressing need for environmental management professionals in various sectors.
Program
Discovery Grants Program - Individual
Recipient
Location
Saskatchewan, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
183609-2009
Name nom
Huang, Guo(Gordon)
Department département
Engineering, Faculty of
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2011
Competition year année de concours
2009
Award amount
65000
Program id
RGPIN
Program nane en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1062
Committee name en
Civil Engineering - B
Committee name fr
Génie civil - B
Area of application code
400
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Environment
Area of application fr
Environnement
Research subject code
1500
Research subject group en
Environmental engineering
Research subject group fr
Génie de l'environnement
Research subject en
Environmental engineering
Research subject fr
Génie de l'environnement
Partie
3
Nb partie
5
Application title
An optimization-based vulnerability and risk analysis approach for supporting air and waste management under multiple umcertainties
Keyword
NSERC
Application summary
Air and waste management systems are complicated with many uncertain parameters and their interrelations that present in terms of multiple uncertainties, while the related decision problems are of interactive, dynamic and multiobjective features. These lead to difficulties in clarifying the related vulnerabilities, impacts, risks and liabilities under a variety of system conditions and policy scenarios. Consequently, the objectives of this proposed research is to develop an optimization-based vulnerability and risk analysis approach for air and waste management under multiple uncertainties; this entails (a) analysis of complexities in air and waste management systems, (b) development of inexact optimization techniques under multiple uncertainties, (c) advancement of optimization-based vulnerability and risk analysis approaches, and (d) incorporation of the developed inexact optimization techniques and vulnerability/risk analysis approaches within a general decision-support framework. Advanced inexact optimization methodologies will be developed for addressing various forms of complexities that exist in air and waste management systems. Based on the optimization analysis, a set of vulnerability/risk assessment methods will be further developed for analyzing the comprehensive effects of human interventions on the vulnerability of receptor systems as well as the compound risks caused by multiple environmental concerns. The developed technologies will then be applied to air and waste management within a western Canada context. The proposed study will provide technical and methodological supports for tackling challenges of vulnerability/risk analysis in relation to air and waste management. It will facilitate comprehensive consideration of factors that are related to the decisions of environmental management and risk analysis. Applications of the proposed techniques to Canadian cases will help industries and governments to improve their effectiveness in managing environmental problems. Besides, a number of graduate and undergraduate students will be trained through participation in the proposed research. The trained students will fill a pressing need for environmental management professionals in various sectors.