Study On Rapid Evaluation Technology Of Air Pollution Control Measures Using Response Surface Model

Currently China's air pollution has changed from local and single urban air pollution to regional and compound air pollution,which has an impact on urban environmental air quality,atmospheric visibility,and public health.It caused a huge impact and aroused widespread concern from the media and the public.With the development and implementation of a series of comprehensive air pollution prevention and control measures such as the“Blue Sky Defense War”,“14th Five-Year Plan for Air Pollution Prevention and Control”and“Air Quality Attainment Plan”,the focus of attention is on whether these policy measures can achieve air quality goals,which also relies on the establishment of air quality model.However,the existing models generally have problems such as long calculation cycle,slow fitting speed,and low emission inventory simulation performance.It is difficult for fast decision-making support;on the other hand,how to establish a set of technical methods applicable to the rapid assessment of multi-regional and differentiated control measures through model improvement,so that the policy measures can reflect the principles of fairness and efficiency as much as possible,is also a problem to be solved in this study.It is of great practical significance to develop rapid response support technology for atmospheric environmental management decision-making.In this study,a statistical method was used to develop a response surface model based on the polynomial function regression method(pf-ERSM),and a rapid response relationship between pollutant emission reduction and PM_2.5 concentration was established.Based on this method,air quality improvement effects under different emission reduction measures in Jiangsu Province are evaluated,and the feasibility and control strategy of using response surface model to fit ozone concentration were discussed,which provided technical support for improving the level of atmospheric environmental management decision-making.(1)The surface response model of air pollution prevention and control in Jiangsu Province was constructed and verified.It is proposed to use the polynomial function regression method(pf-ERSM)to establish the response relationship between pollutant emission reduction and concentration.Based on the massive CMAQ simulation experiment and mathematical statistical deduction mechanism,Response Surface Model(RSM)was established for Jiangsu.Under the external verification scenario of CMAQ,all error-related parameters of the simulation results and the RSM fitting results were below 1%,indicating that the RSM fitting results were close to the CMAQ model simulation,and the response surface model can quickly obtain reliable emission control results.It can meet the requirements of quickly simulation of different pollutants in 13cities in Jiangsu Province.(2)The significance of incorporating regional exogenous impacts into the model for assessing the actual emission reduction effect was clarified.In the baseline scenario,CMAQ model was used to simulate the emission control of all regions outside Jiangsu Province,and RSM model was used to simulate the regional emission control of Jiangsu Province.It was found that the sum of the simulation results of the internal and external sources separated by the“zero setting method”was in good agreement with the simulation results of the baseline scenario.After the superposition of external influences,the PM_2.5 concentration in Jiangsu Province was greatly reduced,which is in line with the actual emission reduction expectation.(3)The importance of optimizing and improving the resolution of emission inventory for the simulation accuracy of the model was analyzed.The study established a complete set of 2017 Jiangsu high-resolution emission inventory,optimized and redistributed the VOCs species spectrum of the emission inventory,and relocated the spatial distribution of emissions from key industries such as electricity,steel,chemical,building materials,mobile and non-point sources.Such corrections were made to optimize the performance of the model simulation.With the verification of CMAQ model,it was found that the standard deviation and average error between the simulation results and the daily observation values in four typical months were close to each other,indicating the variation range of daily error was small.The model simulation was stable and the result was reliable.(4)The accessibility of air quality targets under different control measures were studied using the rapid response surface model system.Under the basic control scenario based on the national and Jiangsu Province's"13th Five-Year"emission reduction requirements,the results showed that the province's average annual PM_2.5concentration will decline by 11.1%,with the highest decline of 12.1%in Wuxi and Changzhou,and with the smallest decline of 10%in Lianyungang.Under balanced control scenarios,with the emission reduction ratios of all research areas being rised by 5%,10%,and20%,the province's average PM_2.5 concentration was declined by 14.0%,16.8%,and22.8%,but neither scenario can meet the air quality improvement requirements.The simulation results of differentiated management and control measures show that,under the external source compliance scenario,the PM_2.5 decline rate in Jiangsu Province can reach 28.9%in 2020 compared with 2015,which can meet the requirements of the binding assessment targets.