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Fine particulate matter (PM 2.5 ) exposure has been linked to numerous adverse health effects, with some disadvantaged subgroups bearing a disproportionate exposure burden. Few studies have been conducted to estimate the exposure and inequality of different subgroups due to a lack of adequate characterization of disparities in exposure to air pollutants in urban areas, and a mechanistic understanding of the causes of these exposure inequalities. Based on a long-term series of PM 2.5 concentrations, this study analyzed the spatial and temporal characteristics of PM 2.5 in 31 provincial capital cities of China from 2000 to 2016 using the coefficient of variation and trend analyses. A health risk assessment of human exposure to PM 2.5 from 2000 to 2016 was then undertaken. A cumulative population-weighted average concentration method was applied to investigate exposures and inequality for education level, job category, age, gender and income population subgroups. The relationships between socioeconomic factors and PM 2.5 exposure concentrations were quantified using the geographically and temporally weighted regression model (GTWR). Results indicate that the PM 2.5 concentrations in most of the capital cities in the study experienced an increasing trend at a rate of 0.98 μg m -3 per year from 2000 to 2016. The proportion of the population exposed to high PM 2.5 (above 35 μg m -3 ) increased annually, mainly due to the increase of population migrating into north, east, south and central China. The higher educated, older, higher income and urban secondary industry share (SIS) subgroups suffered from the most significant environmental inequality, respectively. The per capita GDP, population size, and the share of the secondary industry played an essential role in unequal exposure to PM 2.5 .

Concurrent indoor-outdoor fine particulate matter (PM 2.5 ) measurements were conducted at urban, suburban, and rural sites in Harbin, a megacity in the northeast of China. Chemical constituents of indoor-outdoor PM 2.5 were determined. Infiltration factors (F INF ) of all sites were calculated according to the indoor to outdoor (I/O) ratios of PM 2.5 based on the regression analysis. Linear discriminant analysis (LDA) is applied to determine the indoor-outdoor relationship. Secondary organic carbon (SOC) was calculated on the basis of organic carbon to elemental carbon (OC/EC) ratios. The mean concentrations of indoor and outdoor PM 2.5 were 166.4 ± 32.5 μg/m 3 and 228.4 ± 83.7 μg/m 3 , respectively, during the heating period. OC/EC and potassium ion to elemental carbon (K + /EC) ratios verified that biomass was an important source in Harbin especially for rural sites. The nitrate to sulfate (NO 3 - /SO 4 2- ) ratio indicates the higher contribution of traffic emissions in urban sites. Cr was the only species that exceeded the guidelines of WHO 2002, which was mainly emitted from coal and oil combustion. SOC/OC and NO 3 - /SO 4 2- ratios, and ion-balanced acidity (the ratio of cation to anion, R +/- ) showed a large urban-rural and indoor-outdoor difference. The highest SOC/OC ratio was found at urban sites, up to 38.3% for indoors. SOC/OC ratios and R +/- values of indoor environments were higher, which is attributed to the conducive condition of forming the secondary pollutants during the heating period. The results of LDA indicated that the distributions of the chemical components of PM 2.5 at three sites were statistically dissimilar. Graphical abstract.

Recently, ground ozone has become one major airborne pollutant and the frequency of ozone-induced pollution episodes has increased rapidly across China. However, due to the lack of long-term observation data, relevant research on the characteristics and influencing factors of urban ozone concentrations remains limited. Based on ground ozone observation data during 2006-2016, we quantified the causality influence of individual meteorological factors on ozone concentrations in Beijing using a convergent cross mapping (CCM) method. The result indicated that the influence of each meteorological factor on ozone concentrations varied significantly across seasons and years. At the inter-annual scale, all-year meteorological influences on ozone concentrations were much more stable than seasonal meteorological influences. At the seasonal scale, meteorological influences on ozone concentrations were stronger in spring and autumn. Amongst multiple individual factors, temperature was the key meteorological influencing factor for ozone concentrations in all seasons except winter, when wind, humidity and SSD exerted major influences on ozone concentrations. In addition to temperature, air pressure was another meteorological factor that exerted strong influences on ozone concentrations. At both the inter-annual and seasonal scale, the influence of temperature and humidity on ozone concentrations was generally stable whilst that of other factors experienced large variations. Different from PM 2.5 , meteorological influences on ozone concentrations were relatively weak in summer, when ozone concentrations were the highest in Beijing. Given the generally stable meteorological influences on ozone concentrations and human-induced emissions of VOCs and NO x across seasons, warming induced notable increase in summertime biogenic emissions of VOCs and NO x can be a major driver for the increasing ozone pollution episodes. This research provides useful references for understanding long-term meteorological influences on ozone concentrations in mega cities in China., (Copyright © 2018 Elsevier Ltd. All rights reserved.)