Schizophrenia is a devastating neuropsychiatric disorder with increasing concern. Limited studies have been conducted to assess the relationship between short-term exposure to ambient air pollution and schizophrenia attacks. This study aimed to investigate the associations between short-term air pollution exposure and schizophrenia outpatient visits based on a time-series study performed in China. Daily data of schizophrenia outpatient admissions and air pollution from 1 October 2010 to 31 December 2013 were collected in Xi'an, a heavily-polluted city in China. We utilized a time-series Poisson regression model to examine the associations between short-term air pollution and schizophrenia outpatient visits with different lag days. A total of 34,865 outpatient-visits for schizophrenia were identified. A 10 μg/m³ increase of PM₁₀, SO₂, and NO₂ concentrations corresponded to 0.289% (95% Cl: 0.118%, 0.460%), 1.374% (95% Cl: 0.723%, 2.025%), and 1.881% (95% Cl: 0.957%, 2.805%) elevation in outpatient-visits for schizophrenia at lag 0, and the associations appeared to be stronger, although not statistically significantly, in females and in middle and older age adults (40 and over). The most significant associations were observed on the concurrent day in different lag models. In conclusion, short-term exposure to ambient air pollution (PM₁₀, SO₂, and NO₂) can be associated with increased risk of daily outpatient visits for schizophrenia, which may contribute to the further understanding of the potential adverse effects of air pollution in schizophrenia and other neuropsychiatric disorders.

The influence of air pollutants originating from the Chinese region on air quality over South Korea has been a major concern for policymakers. To investigate the inter-annual trends of the long-distance transport of air pollutants from China to South Korea, multi-year trend analysis was carried out for Aerosol Optical Depth (AOD, as a proxy of particulate matter), and CO (a water-insoluble air pollutant) and SO₂ (a partially water-soluble air pollutant), over three regions in Northeast Asia. Air pollutants are typically long-range transported from the highly polluted parts of China to South Korea through the Yellow Sea. Taking advantage of this geographical merit, we carried out the multi-year trend analysis with a special focus on the Yellow Sea region. Decreasing trends of about 5–10%, 13–17% and 55–61% during the last decade were observed in surface CO, AOD and tropospheric SO₂ columns over the North China Plain (NCP), Yellow Sea (YS), and South Korea (SK), respectively. Such decreasing trends were also found consistently during the last three, five, and seven years, indicating that the changes in pollution levels are likely in response to recent policy measures taken by the Chinese and Korean governments to improve air quality over the regions. Due to these efforts, the amounts of air pollutants transported from China to South Korea are expected to decrease in future years, to the likely rates of 1.50 ppb yr⁻¹, 0.05 DU yr⁻¹, and 0.56 μg m⁻³ yr⁻¹ over the YS region for CO, SO₂, and PM₂.₅, respectively. Given the ambitious plans recently announced by the Chinese government for the 21st meeting of Conference of Parties (COP21) and its co-control effects, the suggested percentage rates may even be conservative numbers. This analysis is expected to provide South Korean policymakers with valuable information to establish new air pollution policies in South Korea.

In this study, various remote sensing data, modeling data and emission inventories were integrated to analyze the tempo-spatial distribution of biomass burning in mainland Southeast Asia and its effects on the local ambient air quality from 2001 to 2016. Land cover changes have been considered in dividing the biomass burning into four types: forest fires, shrubland fires, crop residue burning and other fires. The results show that the monthly average number of fire spots peaked at 34,512 in March and that the monthly variation followed a seasonal pattern, which was closely related to precipitation and farming activities. The four types of biomass burning fires presented different tempo-spatial distributions. Moreover, the monthly Aerosol Optical Depth (AOD), concentration of particulate matter with a diameter less than 2.5 μm (PM₂.₅) and carbon monoxide (CO) total column also peaked in March with values of 0.62, 45 μg/m³ and 3.25 × 10¹⁸ molecules/cm², respectively. There are significant correlations between the monthly means of AOD (r = 0.74, P < 0.001), PM₂.₅ concentration (r = 0.88, P < 0.001), and CO total column (r = 0.82, P < 0.001) and the number of fire spots in the fire season. We used Positive Matrix Factorization (PMF) model to resolve the sources of PM₂.₅ into 3 factors. The result indicated that the largest contribution (48%) to annual average concentration of PM₂.₅ was from Factor 1 (dominated by biomass burning), followed by 27% from Factor 3 (dominated by anthropogenic emission), and 25% from Factor 2 (long-range transport/local nature source). The annually anthropogenic emission of CO and PM₂.₅ from 2001 to 2012 and the monthly emission from the Emission Database for Global Atmosphere Research (EDGAR) were consistent with PMF analysis and further prove that biomass burning is the dominant cause of the variation in the local air quality in mainland Southeast Asia.

Ambient fine particulate matter (PM2.5) pollution has been implicated in the development of hypertensive disorders of pregnancy. However, evidence on the effects of PM2.5-derived chemical constituents on gestational blood pressure (BP) is limited, and the potential mechanisms underlying the association remain unclear. In this study, we repeated three consecutive 72-h personal air sampling and BP measurements in 215 pregnant women for 590 visits during pregnancy. Individual PM2.5 exposure level was assessed by gravimetric method and 28 PM2.5 chemical constituents were analyzed by ED-XRF method. Plasma biomarkers of endothelial function and inflammation were measured using multiplexed immunoassays. Robust multiple linear regression models were used to estimate the associations among personal PM2.5 exposure and chemical constituents, BP changes (compared with pre-pregnancy BP) and plasma biomarkers. Mediation analyses were performed to evaluate underlying potential pathways. Result showed that exposure to PM2.5 was significantly associated with increases in systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial pressure (MAP) in the early second trimester. Meanwhile, elevated concentration of lead (Pb) constituent in PM2.5 was significant associated with increases in DBP and MAP after adjusting for PM2.5 total mass. PM2.5 and Pb constituent also presented positive associations with plasma biomarkers of endothelial function (ET-1, E-selectin, ICAM-1) and inflammation (IL-1β, IL-6, TNFα) significantly. After multiple adjustment, elevated ET-1 and IL-6 were significantly correlated with increased gestational BP, and respectively mediated 1.24%–25.06% and 7.01%–10.69% of the increased BP due to PM2.5 and Pb constituent exposure. In conclusion, our results suggested that personal exposure to PM2.5 and Pb constituent were significantly associated with increased BP during pregnancy, and the early second trimester might be the sensitive window of PM2.5 exposure. The endothelial dysfunction and elevated inflammation partially mediated the effect of PM2.5 and Pb constituent on BP during pregnancy.