Research On Inverse Modeling Of SO₂ And NO_x Emissions Coupled With Air Quality Model Using Adaptive Nudging Scheme And Its Application On Regulation Of Surrounding Emission Sources

Air pollution emission inventory is an important input data of air quality model. The uncertainty of emission inventory is a primary source of error in air quality forecasts and also has a great effect on regulation of air pollution sources. Indirect estimation methods of emission sources such as inverse model of sources is one of important research direction on the quantitative calculation of discharge capacity of pollutant and the law of temporal and spatial variation for emission sources. And the pollution emission inventory of higher resolution and multiple emission parameters is provided to air quality models using the inverse models of sources. Inverse of high resolution and multi-scale emission inventory which has seasonal variation characteristics derived from the simple, reliable, accurate and adaptive nudging scheme is one of important approach to enhance the level of air quality forecasts.The main aim of the paper is 1) to analyze simulation effect of the nudging-based inverse model and theoretical progress by simulated test in different region, season and weather conditions in China; 2) to evaluate the long-term objectivity of improving of the level of air quality forecasts by the above inverse model; 3) to study the impact of improved simulation of meteorological element field, application of observation data with different spatial resolutions and improved retrieval data of tropospheric SO₂ and NO₂ from OMI/Aura satellite(OMI SO₂ and OMI NO₂) with high resolution on correction effect of inverse model and improving of the level of air quality forecasts; 4) to evaluate the impact of different controlling situation of emission sources in different regions in north of China to air quality in Beijing, to compute contribution rate of different physical and chemical processes in the above controlling situation, to find the key controlling region of surrounding emission sources and to provide the scientific basis for service guarantee of air quality forecasts in Beijing and regulation of surrounding emission sources during the 2008 Olympic Games.The following are the main conclusions and results:(1) In this paper, the applicability of multi-scale and corrected emission inventory in different region, season and weather conditions in China using the nudging-based inverse modeling approach and the long-term objectivity of improving of the level of air quality forecasts by using the corrected emission inventory were evaluated quantitatively. The result of long-term simulation test showed that 1) the inverse model of SO₂ and NOX sources using adaptive nudging scheme is suitable for different region, season and weather conditions in China; 2) predictions of SO₂ and NO₂ concentrations in January, April, August, and October using the emission estimations derived from the nudging technique showed remarkable improvements over those based on the original emission data which is from Streets 2000; 3) the accurate relatively and multi-scale emission inventory which has seasonal variation characteristics is obtained by using the nudging-based inverse modeling approach; 4) the error field in the emission data can be reduced effectively through an inverse modeling procedure using observed air pollution levels, and using the improved emissions led to significant improvement in the forecasts of SO₂ and NO₂ concentrations in all seasons. 5) using the improved emissions of SO₂ and NOX indirectly effect hourly forecasts of PM10 and O3 and maximum forecasts of O3 in a day and the forecasting effect of PM10 and O3 is improved through the nudging-based inverse modeling approach.(2) Comparison of the impact of simulation of meteorological element field using MM5 and WRF models to correction effect of inverse model and improving of the level of air quality forecasts was given. Emphasis was placed on the discussion of impact of improved simulation of Planet Boundary Layer (PBL) height and relative humidity using WRF model on correction effect of inverse model of SO₂ and NOX sources. The results indicated that improved simulation of PBL height and relative humidity has certain influence on improvement in the tend prediction of SO₂ and NO₂ concentrations, and can reduce obviously the forecasting error. In comparison with the impact of improved simulation of meteorological element field, correction effect of emission inventory on improvement in the tend prediction of SO₂ and NO₂ concentrations and reduction of forecasting error is more effective.(3) The effect of observation information density of SO₂ and NO₂ concentrations on correction effect of inverse model and improving of the level of air quality forecasts was simulated by using the observed data of SO₂ and NO₂ concentrations with different resolution. The important effect of dense observational data of SO₂ and NO₂ concentrations in north of China on correction effect of inverse model and improving of the level of air quality forecasts was analyzed emphatically. The result showed that the forecasting error of SO₂ and NO₂ concentrations can be reduced effectively through the inverse modeling procedure using dense observational data with higher resolution. The dense observational data with higher resolution in north of China is extremely significant for correction effect of inverse model and improvement in tend prediction of SO₂ and NO₂ concentrations, especially for the forecasts of SO₂ concentration.(4) The impact of surrounding emission sources to the level of SO₂ and NO₂ concentrations in Beijing by using the improved retrieval data of OMI SO₂ and OMI NO₂ with high resolution was evaluated. And application of OMI SO₂ and OMI NO₂ data to correction effect of inverse model and improving of the level of air quality forecasts was discussed emphatically. The results revealed that 1) the spatial distribution characteristics of OMI SO₂ and OMI NO₂ column densities is in accordance with that of observational data of SO₂ and NO₂ concentrations in winter or summer. And OMI SO₂ and OMI NO₂ column densities are applicable to variational processing by means of observational data of SO₂ and NO₂ concentrations on the ground in north of China; 2) from the spatial distribution characteristics of OMI SO₂ and OMI NO₂ column densities which corrected by variational method, the conclusion was obtained that surrounding emission sources in southwest and southeast area have a great effect on the level of SO₂ and NO₂ concentrations in Beijing; 3) the tend prediction and the level of NO₂ concentration are improved obviously using revised emission inventory of NO₂ source by OMI NO₂ data with high resolution, which corrected by variational method; 4) it has a certain reference and actual application value in improvement of emission inventory of NO₂ source in north of China and Beijing and improving of the forecast of NO₂ concentration around Olympic gymnasiums.(5) The impact of different controlling situation of emission sources in different regions in north of China to air quality in Beijing and contribution rate of different physical and chemical processes in the above controlling situation were evaluated and computed, based on improved simulation of meteorological element field using WRF model and relatively accurate emission of SO₂ and NOX sources with high resolution, which are corrected by using the nudging-based inverse modeling approach. The results of control and sensitivity tests showed that 1) the main transport channels of impact of surrounding emission sources to air quality in Beijing are southwest and southeast area of Beijing. Among two main affected zone, southwest area has the most significant influence, the next is southeast area. And emission sources in northwest region have an influence on the levels of SO₂ and PM10 concentrations in Beijing to some extent. Among three main pollutants, emission sources in southwest area have the most significant influence on the level of SO₂ concentration in Beijing, the next is PM10 concentration, the least is NO₂ concentration. And the impact of surrounding emission sources to O3 concentration in Beijing is relatively small; 2) the regulation schemes of SO₂ and NOX emission sources around Beijing need consider characteristics of wind field structure at that time. The main regulation object is upwind emission sources. The key regulation area is southwest and southeast region around Beijing, the next is northwest region. As breeze and static wind blowing, the local emission sources are the key of regulation; 3) when emission of SO₂ and NOX sources in southwest region is controlled, decreasing amplitude of SO₂, NO₂ and PM10 concentrations in Beijing and adjacent area from south to north form the zonal distribution characteristics. And the decreasing ratio of PM10 concentration in the zonal distribution area has diurnal change. 4) as the grade of air pollution in summer in Beijing is third-level or above, the decreasing ratio of SO₂ and PM10 concentrations changes simultaneously with the decreasing ratio of emission of SO₂ and NOX sources in main upwind area of Beijing (southwest and southeast regions). 5) the regulation effect of surrounding emission sources in southwest area is superior to that in southeast area. Regulation of emission sources in southwest area of Beijing is very important for improving air quality in Beijing during the 2008 Olympic Games.