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Three years of measurement of PM2.5 with 5-min time resolution was conducted from 2005 to 2007 in urban and rural environments in Beijing to study the seasonal and diurnal variations in PM2.5 concentration. Pronounced seasonal variation was observed in the urban area, with the highest concentrations typically observed in the winter and the lowest concentrations generally found in the summer. In the rural area, the maximum in PM2.5 concentration usually appeared during the spring, followed by a second maximum in the summer, while the minimum generally occurred in the winter. Significant diurnal variations in PM2.5 concentration were observed in both urban and rural areas. In the urban area, the PM2.5 concentration displays a bimodal pattern, with peaks between 7:00 and 8:00 a.m. and between 7:00 and 11:00 p.m. The minimum generally appears around noon. The morning peak is attributed to enhanced anthropogenic activity during rush hours. The decreases of boundary layer height and wind speed in the afternoon companying with increased source activity during the afternoon rush hour result in the highest PM2.5 concentration during evening hours. In the rural area, the PM2.5 concentration shows a unimodal pattern with a significant peak between 5:00 and 11:00 p.m. The seasonal and diurnal variations in PM2.5 concentration in the urban area are mostly dominated by the seasonal and diurnal variability of boundary layer and source emissions. The year-to-year variability of rainfall also has an important influence on the seasonal variation of PM2.5 in the urban area. The seasonal and diurnal wind patterns are more important factors for PM2.5 variation in the rural area. Southerly winds carry pollutants emitted in southern urban areas northward and significantly enhance the PM2.5 concentration level in the rural area. [Copyright &y& Elsevier]

Volatile organic compounds (VOCs) play key roles in the formation of particulate matter (PM) and oxidants and hence enhance the summertime air pollution. With data analysis from various field observations (urban station: Haidian, HD; suburb station: Changping, CP; regional background station: Shangdianzi, SDZ) in June 2011, we found that the mean O 3 concentrations throughout the observation period can be arranged in order: SDZ＞CP＞HD. The mean PM concentrations can be arranged in order: HD＞CP＞SDZ. The mean concentration of total VOCs at HD was close to that at CP, but much higher than that at SDZ. Oxygenated volatile organic compounds (OVOCs) made the largest portion of VOCs (~40%) at the three stations, followed by alkanes and alkenes. Good positive correlations between the concentrations of PM and O x (=O 3 ＋NO 2) at high air temperature (≥30 °C at HD and CP; ≥28 °C at SDZ) and low RH (≤60%) were found in the daytime (07:00–18:00 LT). However, the PM concentrations were partly negatively correlated with O x at lower temperatures (≤26 °C at HD and CP; ≤22 °C at SDZ) and higher RH (≥80%). The PM concentrations were found either positively (HD and CP) or negatively (SDZ) correlated with aromatics at high temperature and low RH. The aging degree of air masses at the three stations can be arranged in order: SDZ＞CP＞HD. This can qualitatively explain the different PM−aromatics correlations. Our data suggested the other groups of VOCs may promote the increase of PM concentrations unless the PM levels become higher than 140 μg m−3 under humid conditions. This study confirms the importance of VOCs in the formation of summertime PM and oxidants over Beijing. Image 1 • Parallel photochemical formations of PM and O 3 caused positive PM-O x correlations. • Positive PM-aromatics correlations were found at HD and CP, but negative at SDZ. • OVOCs made the largest portion of VOCs (~40%) in the high ozone episode. • VOCs may promote the increase of summertime PM concentrations under humid conditions. [ABSTRACT FROM AUTHOR]

Surface particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) and column-integrated aerosol optical depth (AOD) exhibits substantial diurnal, daily, and yearly variabilities that are regionally dependent. The diversity of these temporal variabilities in urban and rural areas may imply the inherent mechanisms. A novel time-series analysis tool developed by Facebook, Prophet, is used to investigate the holiday, seasonal, and inter-annual patterns of PM2.5 and AOD at a rural station (RU) and an urban station (UR) in Beijing. PM2.5 shows a coherent decreasing tendency at both stations during 2014–2018, consistent with the implementation of the air pollution action plan at the end of 2013. RU is characterized by similar seasonal variations of AOD and PM2.5, with the lowest values in winter and the highest in summer, which is opposite that at UR with maximum AOD, but minimum PM2.5 in summer and minimum AOD, but maximum PM2.5 in winter. During the National Day holiday (1–7 October), both AOD and PM2.5 holiday components regularly shift from negative to positive departures, and the turning point generally occurs on October 4. AODs at both stations steadily increase throughout the daytime, which is most striking in winter. A morning rush hour peak of PM2.5 (7:00–9:00 local standard time (LST)) and a second peak at night (23:00 LST) are observed at UR. PM2.5 at RU often reaches minima (maxima) at around 12:00 LST (19:00 LST), about four hours later (earlier) than UR. The ratio of PM2.5 to AOD (η) shows a decreasing tendency at both stations in the last four years, indicating a profound impact of the air quality control program. η at RU always begins to increase about 1–2 h earlier than that at UR during the daytime. Large spatial and temporal variations of η suggest that caution should be observed in the estimation of PM2.5 from AOD. [ABSTRACT FROM AUTHOR]

Visibility can be used as a highly relevant visual indicator of the air pollution level. Published data on the correlations between visibility and health outcomes are very limited in China, and the health effects of slight haze on the human body have not been clarified. A semi-parametric generalized additive model (GAM) was used to assess the acute health effects of visibility on respiratory–cardiovascular mortality in Beijing, China. The correlation between visibility and PM 2.5 as well as the contributions of PM 2.5 to the health effects of visibility were analysed. Stratification model was employed to investigate the health effects of slight haze. The mortality risk of impaired visibility on the current exposure day peaked and was statistically significant for all the mortality outcomes. Every 1 km decrease in visibility corresponded to a 0.78% (95% CI: 0.62–0.95%) increase in total respiratory mortality and 0.54% (95% CI: 0.45–0.61%) increase in total cardiovascular mortality. Older people (age ≥65) were at a higher risk than the younger age group under impaired visibility. PM 2.5 had a negative logarithmic relationship relative to visibility. After adjustment for PM 2.5 , the risk estimates for both respiratory and cardiovascular mortality reduced. Short-term exposure to low visibility was significantly associated with increased respiratory and cardiovascular mortality in Beijing. The health risk of impaired visibility was particularly high, even in slight haze. The hazardous effects of visibility can be partially attributed to the effects of PM 2.5. These results can provide useful reference for relevant agencies to determine whether an adjustment to the haze warning level is warranted. Our findings indicate that visibility can be used as an alternative indicator for air quality assessments if air pollution data are insufficient or not available, particularly in developing countries. Image 1 • Studies on association between visibility and health outcomes are rare in China. • Exposure to impaired visibility is significantly related to increased mortality. • Health effects of impaired visibility can be partially explained by PM 2.5. • Health risk of impaired visibility is intense, even in slight haze. [ABSTRACT FROM AUTHOR]