大气可吸入颗粒物中多环芳烃的健康风险预测模型

Predictive Modeling on the Risk Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) in PM_(10)

通过对河北省40个采样点的大气可吸入颗粒物(PM10)中16种多环芳烃(PAHs)污染物的环境浓度以及其所致的苯并(a)芘等效毒性(BEQ)进行分析,发现大气可吸入颗粒物中PAHs污染物随季节变换而发生变化,且在低温冬季时,各PAHs环境浓度和所致BEQ均高于其他季节;日常仅监测苯并(a)芘(BaP),苯并(k)荧蒽(BkF)和稠二萘(CHR)的环境浓度,即可对大气可吸入颗粒物中PAHs污染物所致BEQ带来的健康风险进行评价,缩减了日常监测的工作量和运算过程,提高了效率.

16 polycyclic aromatic hydrocarbons （PAHs） in PM10 （the particulate matter（≤10μm） gathering from 40 sample points in Hebei province were determined by GC/MS. Through the analysis of the concentration and benzo（a） pyrene equivalent toxicity （BEQ） of the PAHs pollutions, we concluded that the distribution characters of PAHs in four seasons were different from each other, and the concentrations of PAHs and BEQ in winter all were quite more than those of the others probably because of the rela- tively low temperature and the heating system. In addition, we create a predictive modeling by factor mathematic method using three factors such as benzo（a） pyrene （BaP）,benzo（k） fluorathene （BkF） and chrysene （CHR）. This modeling could greatly reduce the workload of routine monitor and the arithmetic process, leading to the efficient prediction.