Method Of Human Health Risk Assessment Of Pollution Source In Regional Atmospheric Environment

Atmospheric particulate matter(PM) is major pollutant in China in latest years.The PM is serious harm to human health and the sources are complex. In order to develop some control strategies for PM pollution effectively, it is necessary that identifying the pollution sources and obtaining the contribution rates of each pollution source accurately. Receptor model is one of the most important tool in source apportionment study. There is a issue that the results of source apportionment are pollutants concentration contribution rates not rates of influencing degree of pollutants on people’s health. In this paper, the health risk effect of pollution source to human in the atmospheric environment was assessed by health risk assessment combined with receptor model and AERMOD model. In addition, receptor models of sources unknown need large number of samples and receptor models of sources known need reasonable and accurate source profile to ensure the source apportionment results validity and reliability. However, those requirements are difficult to meet. To solve the above problems, some research work carried out as follows:(1) The method of the normal distribution based data expansion for receptor data was established by the producer of normal school random number based on the data of 75 days receptor data in Stockton in 2000. The reasonability of the method was verified by positive matrix factorization(PMF) and principal component analysis(PCA) model. The results showed that the data obtained from the method not only could meet the requirement of unknown receptor models for amount of receptor data,but also could accurately reflect the pollution responded by measured data. The data expansion rationality was mainly influenced by the scope and amount of expansion of the receptor data. The best-case scenario was 0.5 times of the standard deviation of each chemical composition and six of the expansion data respectively. The data with the characteristic of tremendous change which was caused of the variation of source and/or meteorological condition were marked in time series of each chemicalcomposition by 53 h algorithm. The estimate data of the marked data were also provided. In this paper, removing and replacing by estimate data were applied to reduce the effect of marked data to source apportionment results. In order to obtain reasonable results, the relative error(RE) values between original data and estimate data whether were more than 80% decided removing marked data or replacing by estimate data in actual work.(2) The reasonability of source profiles replacement method was proved by distribution, correlation and source apportionment results between replaceable source profiles and measured source profile. The source apportionment results wrer obtained by chemical mass balance(CMB) model based on the data of metallic elements in inhalation particle matter(PM10) at Lanzhou University in 2010. The comparable results showed that the method of source profiles replacement was rational and feasible.The health risks contribution rates of the sources contributing to metallic elements in PM10 at Lanzhou University to the population was calculated according to the source apportionment results and combining health risk assessment method. The results were as follows: the concentration contribution rates by CMB model ranked from high to low as vehicle exhaust dust(43.4%), urban fugitive dust(29.9%), coal fly ash(21.5%), construction cement dust(1.2%) and metal smelt dust(0.7%); the non-carcinogen hazard index contribution rates ranked from high to low as urban fugitive dust(87.7%), vehicle exhaust dust(5.9%), coal fly ash(3.0%), metal smelt dust(2.5%) and construction cement dust(0.9%); the carcinogenic risk contribution rates ranked from high to low as urban fugitive dust(97.1%), vehicle exhaust dust(1.7%), coal fly ash(0.5%), metal smelt dust(0.5%) and construction cement dust(0.2%). Apparently, the concentration contribution rates were very different from non-carcinogen hazard index contribution rates and carcinogenic risk contribution rates. It was true that source with the most concentration contribution was not the one most affected to human health and the influence of source with the least concentration contribution on human health was not to be overlooked.(3) A health risk assessment method of pollutants from fixed sources was developed by applying AERMOD model in the health risk assessment. The method could directly forecast the health risks of toxic pollutants from source by some exposure pathway. The reliability of the established method was validated by comparing with the results of traditional method. The health risk of polycyclicaromatic hydrocarbons(PAHs) in PM10 in heating and non-heating seasons was calculated respectively by using the established method, in combination with the data of sources and traditional health risk assessment method as well as the measured data of PAHs. Then the contribution rates of the health risk caused by the three fire power plants to the health risk at the receptor point were calculated. The results showed that the contribution rates were not associated with gender and age, but were associated with time period and risk types. The contribution rates in the non-heating seasons were greater than those in heating seasons, and the contribution rates of the carcinogenic risk index were greater than those of the cancer risk value.Metal elements in PM10 in Lanzhou university and PAHs in PM10 by the Lanzhou three fire power plants were used to verify the established methods rationality separately. Those methods were also could used in health risk assessment of other pollutants from other sources.