Burden of typical diseases attributed to the sources of PM2.5-bound toxic metals in Beijing: An integrated approach to source apportionment and QALYs

Abstract

PM2.5-bound toxic metals (TMs) are derived from various sources, and they can cause many adverse health effects on the human body. To effectively reduce the disease burden of TMs by controlling the relative sources, an integrated approach of quality-adjusted life years (QALYs) and source-apportionment (positive matrix factorization, PMF) was proposed and applied to some typical diseases induced by TMs in 2017 in Beijing. The estimation included two parts; first, the number of potentially affected people was calculated based on the source mass contribution from PMF and the inhalation unit risk of TMs; second, the QALYs lost per affected person was calculated based on the disease duration, expected years of life lost (EYLL) and quality of life (QoL) for both affected people and the general population. The results showed that QALYs lost per person for renal cancer (17.3 QALYs), pneumonia (14.4 QALYs), lung cancer (14.2 QALYs), skin cancer (12.7 QALYs) and diabetes mellitus (12.6 QALYs) were higher than those for other diseases. Combined with PMF, the source contributions to the overall burden of typical diseases from the TMs followed the order of coal combustion (50.2%) > vehicle emissions (24.4%) > fuel oil combustion (11.4%) > Cr-related industry (10.9%) > resuspended dust (3.0%). The rank was further compared with that assessed for noncancer and cancer risks, and we verified the reasonability of the QALYs method. For seasonal contributions to coal combustion, winter and spring had the highest contributions, which coincided with the fact that coal was the main fuel for heating in Beijing. The QALYs lost attributed to TMs for coal combustion decreased by 49.1% from 2016 to 2017, which may indicate an effective policy associated with coal control. Overall, the integrated approach was successfully employed for estimating the disease burden induced by TMs from each source and was an effective solution to identify the control rank of sources for TM reduction. Keywords: PM2.5, Toxic metals, QALYs, Positive matrix factorization, Coal combustion