Development of an integrated policy making tool for assessing air quality and human health benefits of air pollution control

Efficient air quality management is critical to protect public health from the adverse impacts of air pollution. To evaluate the effectiveness of air pollution control strategies, the US Environmental Protection Agency （US EPA） has developed the Software for Model Attainment Test-Community Edition （SMAT-CE） to assess the air quality attainment of emission reductions, and the Environmental Benefits Mapping and Analysis Program- Community Edition （BenMAP-CE） to evaluate the health and economic benefits of air quality improvement respectively. Since scientific decision-making requires timely and coherent information, developing the linkage between SMAT-CE and BenMAP-CE into an integrated assessment platform is desirable. To address this need, a new module linking SMAT-CE to BenMAP-CE has been developed and tested. The new module streamlines the assessment of air quality and human health benefits for a proposed air pollution control strategy. It also implements an optimized data gridding algorithm which significantly enhances the computational efficiency without compro- mising accuracy. The performance of the integrated software package is demonstrated through a case study that evaluates the air quality and associated economic benefits of a national-level control strategy of PM2.5. The results of the case study show that the proposed emission reduction reduces the number of nonattainment sites from 379 to 25 based on the US National Ambient Air Quality Standards, leading to more than USS334billion ofeconomic benefits annually from improved public health. The integration of the science-based software tools in this study enhances the efficiency of developing effective and optimized emission control strategies for policy makers.

Design and demonstration of a next-generation air quality attainment assessment system for PM_(2.5)and O_3

Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test-Community Edition （SMAT-CE） is developed for demonstrating attainment of air quality standards of O3 and PM2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards （NAAQS） shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM2.5 and 8-hour O3 for a proposed emission control policy.

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling（RSM） methodology and serves as a visualization and analysis tool（VAT） for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S.demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias 〈 2% and assisting in air quality policy making in near real time.

A case study of development and application of a streamlined control and response modeling system for PM_(2.5)attainment assessment in China

This article describes the development and application of a streamlined air control and response modeling system with a novel response surface modeling-linear coupled fitting method and a new module to provide streamlined model data for PM_（2.5） attainment assessment in China.This method is capable of significantly reducing the dimensions required to establish a response surface model,as well as capturing more realistic response of PM_（2.5） to emission changes with a limited number of model simulations.The newly developed module establishes a data link between the system and the Software for Model Attainment Test—Community Edition（SMAT-CE）,and has the ability to rapidly provide model responses to emission control scenarios for SMAT-CE using a simple interface.The performance of this streamlined system is demonstrated through a case study of the Yangtze River Delta（YRD） in China.Our results show that this system is capable of reproducing the Community Multi-Scale Air Quality（CMAQ） model simulation results with maximum mean normalized error 〈 3.5%.It is also demonstrated that primary emissions make a major contribution to ambient levels of PM_（2.5） in January and August（e.g.,more than50%contributed by primary emissions in Shanghai）,and Shanghai needs to have regional emission control both locally and in its neighboring provinces to meet China＇s annual PM_（2.5）National Ambient Air Quality Standard.The streamlined system provides a real-time control/response assessment to identify the contributions of major emission sources to ambient PM_（2.5）（and potentially O_3 as well） and streamline air quality data for SMAT-CE to perform attainment assessments.

Enhancement of the polynomial functions response surface model for real-time analyzing ozone sensitivity

Quantification of the nonlinearities between ambient ozone(O3)and the emissions of nitrogen oxides(NOx)and volatile organic compound(VOC)is a prerequisite for an effective O3 control strategy.An Enhanced polynomial functions Response Surface Model(Epf-RSM)with the capability to analyze O3-NOx-VOC sensitivities in real time was developed by integrating the hill-climbing adaptive method into the optimized Extended Response Surface Model(ERSM)system.The Epf-RSM could single out the best suited polynomial function for each grid cell to quantify the responses of O3 concentrations to precursor emission changes.Several comparisons between Epf-RSM and pf-ERSM(polynomial functions based ERSM)were performed using out-of-sample validation,together with comparisons of the spatial distribution and the Empirical Kinetic Modeling Approach diagrams.The comparison results showed that Epf-RSM effectively addressed the drawbacks of pf-ERSM with respect to overfitting in the margin areas and high biases in the transition areas.The O3 concentrations predicted by Epf-RSM agreed well with Community Multi-scale Air Quality simulation results.The case study results in the Pearl River Delta and the north-western area of the Shandong province indicated that the O3 formations in the central areas of both the regions were more sensitive to anthropogenic VOC in January,April,and October,while more NOx-sensitive in July.

Development and case study of a new-generation model-VAT for analyzing the boundary conditions influence on atmospheric mercury simulation

Atmospheric models are essential tools to study the behavior of air pollutants. To interpret the complicated atmospheric model simulations, a new-generation Model Visualization and Analysis Tool （Model-VAT） has been developed for scientists to analyze the model data and visualize the simulation results. The Model-VAT incorporates analytic functions of conventional tools and enhanced capabilities in flexibly accessing, analyzing, and comparing simulated results from multi-scale models with diflbrent map projections and grid resolutions. The performance of the Model-VAT is demonstrated by a case study of investigating the influence of boundary conditions （BCs） on the ambient Hg formation and transport simulated by the CMAQ model over the Pearl River Delta （PRD） region. The alternative BC options are taken from （1） default time-independent profiles, （2） outputs from a CMAQ simulation of a larger nesting domain, and （3） concentration files from GEOS-Chem （re-gridded and re-projected using the Model-VAT）. The three BC inputs and simulated ambient concentrations and deposition were compared using the Model-VAT. The results show that the model simulations based on the static BCs （default profile） underestimates the Hg concentrations by --6.5%, dry depositions by -9.4%, and wet depositions by --43.2% compared to those of the model-derived （e. g. GEOS-Chem or nesting CMAQ） BCs. This study highlights the importance of model nesting approach and demonstrates that the innovative functions of Model-VAT enhances the efficiency of analyzing and comparing the model results from various atmospheric model simulations.