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We develop a new inversion method which is suitable for linear and nonlinear emission source (ES) modeling, based on the three-dimensional decoupled direct (DDM-3D) sensitivity analysis module in the Community Multiscale Air Quality (CMAQ) model and the three-dimensional variational (3DVAR) data assimilation technique. We established the explicit observation operator matrix between the ES and receptor concentrations and the background error covariance (BEC) matrix of the ES, which can reflect the impacts of uncertainties of the ES on assimilation. Then we constructed the inversion model of the ES by combining the sensitivity analysis with 3DVAR techniques. We performed the simulation experiment using the inversion model for a heavy haze case study in the Beijing–Tianjin–Hebei (BTH) region during 27–30 December 2016. Results show that the spatial distribution of sensitivities of SO2 and NOx ESs to their concentrations, as well as the BEC matrix of ES, is reasonable. Using an a posteriori inversed ES, underestimations of SO2 and NO2 during the heavy haze period are remarkably improved, especially for NO2. Spatial distributions of SO2 and NO2 concentrations simulated by the constrained ES were more accurate compared with an a priori ES in the BTH region. The temporal variations in regionally averaged SO2 , NO2 , and O3 modeled concentrations using an a posteriori inversed ES are consistent with in situ observations at 45 stations over the BTH region, and simulation errors decrease significantly. These results are of great significance for studies on the formation mechanism of heavy haze, the reduction of uncertainties of the ES and its dynamic updating, and the provision of accurate "virtual" emission inventories for air-quality forecasts and decision-making services for optimization control of air pollution. [ABSTRACT FROM AUTHOR]

Abstract: An emission pre-processing tool is generally needed to transform a bulk annual emission inventory into gridded, temporal (monthly, weekly, and hourly), and speciated emissions in order to use complex air quality models such as the Community Multi-scale Air Quality (CMAQ) model to assess control strategies, forecast air quality, and investigate pollution formation and transport processes. To support the regional air quality modeling in the Pearl River Delta (PRD), we developed an emission pre-processing system, Sparse Matrix Operator Kernel Emissions-PRD (SMOKE-PRD), based on the U.S. Environmental Protection Agency (USEPA)/SMOKE model. This paper introduces the methods and procedures for adapting the SMOKE model to the PRD regional bulk emissions. These include the compilation of the PRD local source-class clarification codes, the incorporation of the PRD local emission inventory, and the updating of spatial, temporal, and chemical speciation information. The SMOKE-PRD system was evaluated, and a case study on ozone simulation was conducted to demonstrate the applicability of the SMOKE-PRD system. Results show that the model can properly simulate temporal variations, spatial patterns, and peak values of O3 concentrations in the PRD region, suggesting the SMOKE-PRD system was successfully localized and can be used to provide model-ready emissions for regional air quality modeling in the PRD region. This work can be extended for adapting the SMOKE model to process emissions for modeling use in other regions of China. [Copyright &y& Elsevier]

Abstract: In recent decades, the Pearl River Delta (PRD) region located in south China has been experiencing severe air pollution, arising from the rapid increase in industry and motor vehicles. As a major contributing source to VOCs and NOx emissions, control of vehicular emissions plays a very important role in improving regional air quality. By taking 2015 as a target year, this paper assessed the impacts of five possible motor vehicle emission control measures and a combined policy scenario on ambient air quality in the PRD region, with the use of the Model-3/CMAQ (Community Multi-scale Air Quality) model. The results show: (1) an overall decreasing pattern in SO2, NO2 and PM10 concentrations was found in central-south metropolitan areas of the PRD region for all measures, but increased O3 concentrations may occur in these areas as well. The exception to this is that a slight decrease was observed for the cases of motorcycle restriction and introduction of HEV; (2) upgrading to National IV emission standards is the most effective individual measure and can reduce daily averaged NO2 and PM10 concentrations by 11.7ppbV and 21.3μgm−3, respectively; but involves an increase (at maximum) of 10.3ppbV in O3 concentration. Evaluation of the combined scenario indicates that solely controlling motor vehicle emissions is not sufficient to improve PRD regional air quality significantly. O3 and PM10 concentrations under the same VOC/NOx reduction ratios exhibit differently at different locations, suggesting that integrated and location-specific pollution control strategies, considering co-control of multi-pollutants, are needed in this region in order to decrease primary and secondary pollutant concentrations simultaneously. [Copyright &y& Elsevier]