Liao Kuo-Jen, Hou Xiangting
a Department of Environmental Engineering , Texas A&M University-Kingsville , Kingsville , TX , USA.
J Air Waste Manag Assoc. 2015 Jun;65(6):732-42. doi: 10.1080/10962247.2015.1014073.
Developing regional air quality management strategies is a difficult task because formation of air pollutants is interdependent and air quality at different locations may have different responses to emissions from common sources. We developed an optimization-based model, OPtimal integrated Emission Reduction Alternatives (OPERA), which allows for identifications of least-cost control strategies for attaining multipollutant air quality targets at multiple locations simultaneously. To implement OPERA, first, sensitivities of air quality to precursor emission changes are quantified. Second, cost functions of emission reductions are estimated using a cost analysis tool that includes a pool of available control measures. The third step is to determine desired reductions in concentrations of air pollutants. The last step is to identify the optimal control strategies by minimizing costs of emission controls using the sensitivities of air pollutants to emission changes, cost functions, and constraints for feasible emission reduction ratios. A case study that investigates ozone and PM2.5 air quality in the summer of 2007 for five major cities in the eastern United States is presented in this paper. The results of the OPERA calculations show that reductions in regional NOx and VOC as well as local primary PM2.5 emissions were more cost-effective than SO2 controls for decreasing ozone and total PM2.5 concentrations in the summer of 2007. This was because reductions in SO2 emissions would only decrease PM2.5 concentrations, and reductions in primary PM2.5 emissions were more cost-effective than SO2 emission controls.
We developed an optimization-based model, OPtimal integrated Emission Reduction Alternatives (OPERA), which allows for identification of least-cost emission control strategies for attaining multipollutant air quality targets at multiple locations simultaneously. A major strength of OPERA is its flexibility, which allows for changes in air quality regulations, involving agencies, study regions, and so on, to be readily incorporated. Overall, it has been demonstrated that OPERA is useful in developing least-cost emission control strategies for achieving multipollutant air quality targets at multiple locations simultaneously and could be useful for policymakers developing integrated air quality management plans.
制定区域空气质量管理策略是一项艰巨的任务，因为空气污染物的形成相互依存，而且不同地点的空气质量对共同来源排放的反应可能不同。我们开发了一种基于优化的模型——最优综合减排方案（OPERA），该模型能够确定以最低成本实现多个地点多污染物空气质量目标的控制策略。为了实施OPERA，首先要量化空气质量对前体排放变化的敏感性。其次，使用包含一系列可用控制措施的成本分析工具估算减排成本函数。第三步是确定空气污染物浓度的期望降幅。最后一步是利用空气污染物对排放变化的敏感性、成本函数以及可行减排率的约束条件，通过最小化排放控制成本来确定最优控制策略。本文给出了一个案例研究，调查了2007年夏季美国东部五个主要城市的臭氧和PM2.5空气质量。OPERA计算结果表明，2007年夏季，减少区域氮氧化物和挥发性有机物以及本地一次PM2.5排放，比控制二氧化硫排放对于降低臭氧和总PM2.5浓度更具成本效益。这是因为减少二氧化硫排放只会降低PM2.5浓度，而减少一次PM2.5排放比控制二氧化硫排放更具成本效益。
我们开发了一种基于优化的模型——最优综合减排方案（OPERA），该模型能够确定以最低成本实现多个地点多污染物空气质量目标的排放控制策略。OPERA的一个主要优势在于其灵活性，能够轻松纳入空气质量法规、相关机构、研究区域等方面的变化。总体而言，已证明OPERA在制定以最低成本实现多个地点多污染物空气质量目标的排放控制策略方面很有用，并且可能对制定综合空气质量管理计划的政策制定者有用。
