Development and application of an adjoint version for a multi-phase air quality model

点击翻译按钮获取中文摘要

Mathematical models play an increasingly significant role in shaping our understanding of air pollution, and in identifying possible solutions for reducing it to acceptable levels. Scientists, regulators, and policymakers use air quality models to gain insight and make informed decisions about the quality of air and ways that it can be impacted by human activities. An important method that is often used for such purposes is sensitivity analysis. Sensitivity analysis tools can provide answers to the main question with respect to air pollution: how air quality will be affected by changes in emissions? Sophisticated mathematical tools have been developed to calculate sensitivity information in air quality models. Some of these methods are source-based and provide detailed sensitivity information about emission sources. Others are receptor-based and are, therefore, deemed to be ideal for addressing policy questions. In this project, the goal is to develop one group of such receptor-based tools, referred to as an adjoint, for a widely used air quality model. It is intended to use the developed adjoint model for various applications that include: 1) improved air quality forecasting, 2) developing better estimation of emission inventories that are used in the models, 3) design of optimal pollution control strategies for reaching air quality objectives and cost-benefit analysis, and 4) quantitative evaluation of inter-provincial, trans-border, and intercontinental transport of pollution.