| Emission inventories are the basic data for studying the mechanism of air pollution formation and air quality management,making the reliability and accuracy of emission inventories crucial.There are still large uncertainties in emission inventories.Existing emission inventory evaluation studies only analyzed one or several factors affecting the quality of the inventory,and cannot comprehensively assess the quality of the emissions inventory Quantitative uncertainty analysis is one of the important methods of inventory evaluation,but the lack of input parameter uncertainty information limited its application.Therefore,based on extensive literature researches and expert consultation,this study determined the emission inventory quality assessment indicators.Combined with expert judgment and AHP,the emission inventory quality assessment indicator system was established based on the comprehensive assessment method.In order to verify the applicability of the system,this study took the 2017 regional emission inventory of Guangdong Province as a case study,and analyzed its quality from different perspectives by various methods.Finally,the evaluation result of the regional inventory was obtained by using the quality assessment indicator system of the emission inventory.Then the key factors affecting the quality of regional emission inventory was analyzed,and suggestions for future improvement of emission inventory was proposed.In addition,based on the extensive collection of emission factors,a data set of emission factor uncertainty was constructed to provide data support for quantitative analysis of inventory uncertainty.The main conclusions are as follows(1)The emission inventory quality assessment index system was divided into four levels from top to bottom,covering four assessment contents,16 first-level and 35 second-level assessment indexes.The evaluation content includes data sources and quality,fineness,rationality and standardization,etc.Data quality focused on the evaluation of data source reliability and data representativeness.Fineness focused on the evaluation of estimation methods,source classification,spatiotemporal resolution and point sourcing rates.The rationality of the results was mainly measured from the total amount,source structure,spatiotemporal characteristics and uncertainty.The standardization of report was to evaluate the inventory compilation,component integrity and document management(2)Through the collection of 35453 emission factors based on tests or other authoritative sources,a data set containing 478 emission factor uncertainty information was constructed.In general,there was great uncertainty in PM and VOCs emission factors.The emission factor uncertainty of PM from non-road mobile source,dust source and process source was large.The uncertainty of VOCs emission factors of solvent-use source and process source was great Therefore,in order to reduce the uncertainty of emission factors,it is necessary to carry out more experimental research on the emission of PM and VOCs,especially for the emission sources with large uncertainty(3)The quantitative uncertainty ranges of SO2,NOx,CO,PM10,PM2.5,BC,OC,VOCs,and NH3 in the 2017 regional inventory of Guangdong Province were-17%?20%,-25%?28%,-30%?39%,-45%?60%,-43%?62%,-53%?116%,-54%?160%,-34%?50%,and-50%?86%,respectively.Due to the optimization of estimation methods and the application of localization parameters,inventory uncertainty was reduced compared with the results in 2012 The sensitivity analysis result showed that the mobile source,process source,solvent-use source,dust source and biomass combustion source had a great impact on the overall uncertainty of emission(4)The quality assessment score of the 2017 regional emission inventory of Guangdong Province was 0.83,indicating that the overall quality of the emission inventory was good.This showed that the data source of the emission inventory was more reliable,and the documentation work process was more standardized.The degree of fineness was moderate,and the results could describe the characteristics of pollutant emissions more accurately.But there were still some problems that could be optimized.It was found that the data quality of the emission factors and related parameters impacted the evaluation score.Therefore,it is recommended to conduct local investigations on the pollutant emission and control efficiency of the enterprise,and formulate corresponding sampling standards,and quantify the uncertainty of the measured emission factors,in order to improve the reliability and representativeness of the emission factors.The first quality assessment index system of air pollutant emission inventory in China was constructed in this study,which not only successfully realized the comprehensive assessment of the quality of regional emission inventory in Guangdong Province,but also provided suggestions for future improvement of emission inventory and reference for the comprehensive assessment of emission inventory quality.In addition,the emission factor uncertainty data set not only provided data support for the application of quantitative uncertainty analysis,but guided the future key emission source test as well. |
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