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Optimal deployment of emissions reduction technologies for construction equipment
Muhammad Ehsanul Bari1, Josias Zietsman, Luca Quadrifoglio
1Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77840, USA. ehsanulbarihome@yahoo.com
Journal of the Air & Waste Management Association (1995)
|July 15, 2011
Summary
This study developed an optimization model for cost-effective emissions reduction in construction equipment. The model identifies optimal technology mixes for maximum emissions reduction and fuel savings within budget constraints.
Area of Science:
- Environmental Engineering
- Operations Research
- Mechanical Engineering
Background:
- Nonroad construction equipment contributes significantly to air pollution in nonattainment and near-nonattainment counties.
- Cost-effective deployment of emissions reduction technologies is crucial for meeting air quality standards.
- Existing models may not fully capture the multiobjective nature of technology deployment balancing cost, emissions, and fuel savings.
Purpose of the Study:
- To develop a multiobjective optimization model for deploying emissions reduction technologies on nonroad construction equipment.
- To determine the optimal mix of technologies for maximum emissions reduction and fuel savings within a specified budget.
- To evaluate the cost-effectiveness and sensitivity of different technology deployment strategies.
Main Methods:
- Developed a multiobjective optimization model with a weighted objective function for emissions reduction and fuel savings.
- Programmed the model using C++ and ILOG-CPLEX for general applicability.
- Applied the model to a Texas Department of Transportation construction equipment fleet, representing hydrogen enrichment (X), selective catalytic reduction (Y), and fuel additive (Z) technologies.
Main Results:
- Identified optimal technology mixes for varying budget amounts, maximizing oxides of nitrogen (NO(x)) reductions and combined benefits.
- Demonstrated a high benefit-cost ratio at lower budget levels, with diminishing returns at higher budgets.
- The Pareto front provided decision-makers with noninferior optimal combinations of NO(x) reductions and fuel savings for given budgets.
Conclusions:
- The developed optimization model effectively guides the cost-effective deployment of emissions reduction technologies for construction equipment.
- Budgetary constraints significantly influence the selection and mix of technologies for optimal environmental and economic benefits.
- The model offers a valuable tool for policymakers and fleet managers to achieve air quality goals efficiently.
