Research On Indigenized Characterization Factors Of PM_2.5 Health Impact For Life Cycle Impact Assessment In China

Life Cycle Assessment(LCA)is an international standard method for systematically and quantitatively describing the whole process resource consumption and pollutant emissions of products or processes and evaluating their environmental loads and potential impacts.Life Cycle Assessment mainly includes four steps:objective and scope definition,life cycle inventory analysis,Life Cycle Impact Assessment(LCIA)and result interpretation.LCIA is the core step that affects the accuracy of LCA results.Characterization Factors are essential element of the LCIA model,which convert the results of life cycle inventory analysis into environmental,health,and resource impact results.For example,Characterization Factors of PM2.5 health impact are used to convert life cycle air pollutant emissions of research object into human health impact.In China,human health loss caused by ambient PM2.5 is an important part of LCA results,which is not only significantly different from other countries,but also has significant regional and seasonal specificity within the region.However,the characterization factors of PM2.5 health impact used in the current mainstream LCIA models are all from the global model,lacking consideration of the actual situation and spatial and temporal differences in China.resulting in high uncertainty of PM2.5 health impact in LCA research in China.Therefore,it is the significance to improve the regional adaptability of LCIA model and improve the accuracy of LCA evaluation in China by constructing indigenized characterization factors of PM2.5 health impact with spatial and temporal specificity.Based on the current situation of air pollutant emissions,background PM2.5 concentration and population exposure characteristics in China,this paper used indigenized research methods and data to construct the monthly indigenized characterization factors of PM2.5 health impact in China and its provincial administrative regions.Firstly,the atmospheric chemical transport model GEOS-Chem was used to simulate the PM2.5 concentration under standard and sensitive scenarios.Combined with the emission inventory,population exposure parameters and other data,the indigenized PM2.5 intake fraction that can reflect the relationship between PM2.5 precursors(NH3,SO2,NOx and primary PM2.5)emissions and human PM2.5 inhalation was constructed.Secondly,the human relative health risk was assessed using PM2.5 exposure response model GEMM including the Chinese cohort study.Combined with the data of disease mortality and damage factor,the indigenized PM2.5 health effect factors that can reflect the relationship between human PM2.5 inhalation and human health damage was constructed.Thirdly,based on PM2.5 intake fraction and PM2.5 health effect factors,indigenized characterization factors of PM2.5 health impact were constructed.And based on characterization factors of PM2.5 health impact,the human health impact was analyzed from the perspective of regional synergy and PM2.5 precursors in China.Finally,this paper applied the indigenized characterization factors of PM2.5 health impact to the LCA study of China’s electricity production,and analyzed PM2.5 attributable health impact caused by different electricity production modes.The results show that the indigenized characterization factors of PM2.5 health impact constructed by indigenized methods and data have significant regional and seasonal specificity in China.In the northeastern and western border provinces of China with cleaner air and smaller population density,the characterization factors corresponding to the four PM2.5 precursors are generally smaller,while the larger characterization factors corresponding to the four PM2.5 precursors are located in different provinces of China.Among them,the characterization factors corresponding to primary PM2.5 is the largest among the four PM2.5 precursors,and the maximum value is located in Tianjin,reaching 7704.93 DALYs/kton emis.The maximum characterization factors corresponding to NH3,SO2 and NOx are located in Shanghai,Sichuan and Chongqing,respectively.In most provinces,the characterization factors corresponding to NH3 and primary PM2.5 showed seasonal specificity of high in winter and low in summer,while NOx was the opposite,and the seasonal specificity of SO2 was not obvious.Therefore,considering the above regional and seasonal specificity in LCA studies can further improve the accuracy of the research results in China.By comparing with the existing research,it is found that the characterization factors of PM2.5 health impact in the current mainstream LCIA model seriously underestimated the human health damage caused by PM2.5,affecting the reliability of LCA research results in China.In addition,research results of characterization factors also bring enlightenment to the prevention and control of air pollution:in most provinces,the PM2.5 attributable human health loss is mainly affected by the inter-regional transmission of PM2.5 precursors.It is necessary to formulate inter-provincial cooperation and regional differentiated PM2.5 precursors prevention and control policies to effectively reduce human health loss caused by PM2.5.Through LCA study on electricity production in China,compared with the mainstream LCIA model,the indigenized characterization factors constructed in this paper can more objectively and detailedly reveal the life cycle PM2.5 attributable health loss of different electricity production modes.The results show that the PM2.5 attributable health loss caused by three different electricity production modes of coal-fired power,wind power and solar photovoltaic are quite different among provinces,months and electricity production modes.At the same time,it is found that the application of indigenized characterization factors have a significant impact on LCA research results.This case study confirmed the necessity of using indigenized characterization factors of PM2.5 health impact and considering regional and seasonal differences in LCA studies in China.