A methodological frame for assessing benzene induced leukemia risk mitigation due to policy measures

The study relies on the development of a methodology for assessing the determinants that comprise the overall leukemia risk due to benzene exposure and how these are affected by outdoor and indoor air quality regulation. An integrated modeling environment was constructed comprising traffic emissions, dispersion models, human exposure models and a coupled internal dose/biology-based dose–response risk assessment model, in order to assess the benzene imposed leukemia risk, as much as the impact of traffic fleet renewal and smoking banning to these levels. Regarding traffic fleet renewal, several “what if” scenarios were tested. The detailed full-chain methodology was applied in a South-Eastern European urban setting in Greece and a limited version of the methodology in Helsinki. Non-smoking population runs an average risk equal to 4.1·10−5 compared to 23.4·10−5 for smokers. The estimated lifetime risk for the examined occupational groups was higher than the one estimated for the general public by 10–20%. Active smoking constitutes a dominant parameter for benzene-attributable leukemia risk, much stronger than any related activity, occupational or not. From the assessment of mitigation policies it was found that the associated leukemia risk in the optimum traffic fleet scenario could be reduced by up to 85% for non-smokers and up to 8% for smokers. On the contrary, smoking banning provided smaller gains for (7% for non-smokers, 1% for smokers), while for Helsinki, smoking policies were found to be more efficient than traffic fleet renewal. The methodology proposed above provides a general framework for assessing aggregated exposure and the consequent leukemia risk from benzene (incorporating mechanistic data), capturing exposure and internal dosimetry dynamics, translating changes in exposure determinants to actual changes in population risk, providing a valuable tool for risk management evaluation and consequently to policy support. ► A comprehensive exposure analysis is greatly facilitated by the thorough use of measurement data and modeling tools. ► Incorporation of internal dose metrics contributes to significant refinement of exposure assessment. ► Similar community policies have completely different effect with respect to different countries/cities.