Exposure inequality assessment for PM2.5 and the potential association with environmental health in Beijing

Fine particulate matter (PM2.5) pollution exposure has an adverse impact on public health, and some vulnerable social groups suffer from unfair exposure. Few studies have been conducted to estimate and to compare the exposure and inequality of different residential demographics at multiple time scales. This study assessed the exposures level of age and education subgroups on the whole city and the exposure inequalities of these subgroups within a concentration interval area for PM2.5 pollution at multiple time scales in Beijing in 2015. The potential association of PM2.5 with cancer morbidity was also explored through spatial analysis. Comparing the model performance of the ordinary kriging (OK) interpolation method with that of the land use regression (LUR) model method, the OK method was applied to estimate the PM2.5 concentrations at 1 km resolution. The exposure and inequality assessments for PM2.5 pollution were conducted by calculating the population-weighted exposure level and the inequality index, respectively. The spatial correlation of PM2.5 with cancer morbidity was investigated by spatial autocorrelation and grey correlation degree analysis. Overall, for the highest 1-h concentration, older people (age >= 60) and residents with tertiary education were the most disproportionately exposed to PM2.5. For the higher PM2.5 concentration during the annual average, spring, autumn and winter periods, exposures to PM2.5 were disproportionately high for children (age <= 4) and residents with primary or secondary education. Moreover, exposures to PM2.5 were disproportionately low for the illiterate due to their geographical distribution characteristics. Additionally, the spatial distribution of cancer morbidity was similar to the spatial pattern of PM2.5, manifesting a potential spatial association between PM2.5 and cancer morbidity. These findings provide scientific support for air pollution exposure assessments and environmental epidemiology. (C) 2018 Elsevier B.V. All rights reserved.