Istanbul, one of the mega cities in the world located between Asia and Europe, has suffered from severe air pollution problems due to rapid population growth, traffic and industry. Atmospheric levels of PAHs and PCBs were investigated in Istanbul at 22 sampling sites during four different sampling periods using PUF disk passive air samplers and spatial and temporal variations of these chemicals were determined. Soil samples were also taken at the air sampling sites. At all sites, the average ambient air Σ15PAH and Σ41PCB concentrations were found as 85.6 ± 68.3 ng m−3 and 246 ± 122 pg m−3, respectively. Phenanthrene and anthracene were the predominant PAHs and low molecular weight congeners dominated the PCBs. The PAH concentrations were higher especially at urban sites close to highways. However, the PCBs showed moderately uniform spatial variations. Except four sites, the PAH concentrations were increased with decreasing temperatures during the sampling period, indicating the contributions of combustion sources for residential heating, while PCB concentrations were mostly increased with the temperature, probably due to enhanced volatilization at higher temperatures from their sources. The results of the Factor Analysis represented the impact of traffic, petroleum, coal/biomass and natural gas combustion and medical waste incineration plants on ambient air concentrations. A similar spatial distribution trend was observed in the soil samples. Fugacity ratio results indicated that the source/sink tendency of soil for PAHs and PCBs depends on their volatility and temperature; soil generally acts as a source for lighter PAHs and PCBs particularly in higher temperatures while atmospheric deposition is a main source for higher molecular weight compounds in local soils. Toxicological effect studies also revealed the severity of air and soil pollution especially in terms of PAHs in Istanbul.

Because people spend most of their time indoors, the characterization of indoor air quality is important for exposure assessment. Unfortunately, indoor air data are scarce, leading to a major data gap in risk assessment. In this study, PM2.5 concentrations in both indoor and outdoor air were simultaneously measured using on-line particulate counters in 13 households in Haidian, Beijing for both heating and non-heating seasons. A bimodal distribution of PM2.5 concentrations suggests rapid transitions between polluted and non-polluted situations. The PM2.5 concentrations in indoor and outdoor air varied synchronously, with the indoor variation lagging. The lag time in the heating season was longer than that in the non-heating season. The particle sizes in indoor air were smaller than those in ambient air in the heating season and vice versa in the non-heating season. PM2.5 concentrations in indoor air were generally lower than those in ambient air except when ambient concentrations dropped sharply to very low levels or there were internal emissions from cooking or other activities. The effectiveness of an air cleaner to reduce indoor PM2.5 concentrations was demonstrated. Non-linear regression models were developed to predict indoor air PM2.5 concentrations based on ambient data with lag time incorporated. The models were applied to estimate the overall population exposure to PM2.5 and the health consequences in Haidian. The health impacts would be significantly overestimated without the indoor exposure being taken into consideration, and this bias would increase as the ambient air quality improved in the future.

Based on the 12-hour PM2.5 samples collected in an urban site of Beijing, sixteen PM2.5-bound Polycyclic Aromatic Hydrocarbons (PAHs) were measured to investigate the characteristics and potential source regions of particulate PAHs in Beijing. The study period included the summer period in July–August 2014, the APEC source control period during the Asia-Pacific Economic Cooperation (APEC) meeting in the first half of November 2014, and the heating period in the second half of November 2014. Compared to PM2.5, sum of 16 PM2.5-bound PAHs exhibited more significant seasonal variation with the winter concentration largely exceeding the summer concentration. Temperature appeared to be the most crucial meteorological factor during the summer and heating periods, while PM2.5-bound PAHs showed stronger correlation with relative humidity and wind speed during the APEC source control period. Residential heating significantly increased the concentrations of higher-ring-number (≥4) PAHs measured in PM2.5 fraction. Potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analysis as well as the (3 + 4) ring/(5 + 6) ring PAH ratio analysis revealed the seasonal difference in the potential source area of PM2.5-bound PAHs in Beijing. Southern Hebei was the most likely potential source area in the cold season. Using black carbon (BC) and carbon monoxide (CO) as the PAH tracers, regional residential, transportation and industry emissions all contributed to the PAH pollution in Beijing.

Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM2.5 and CO2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM2.5 concentrations with a maximum concentration above 100 μg m−3 at the building rooftop. The above-ground “hotspots” would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant “hotspots” into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed.

Residential woodsmoke is an under-regulated source of fine particulate matter (PM2.5), often surpassing mobile and industrial emissions in rural communities in North America and elsewhere. In the province of British Columbia (BC), Canada, many municipalities are hesitant to adopt stricter regulations for residential wood burning without empirical evidence that smoke is affecting local air quality. The objective of this study was to develop a retrospective algorithm that uses 1-h PM2.5 concentrations and daily temperature data to identify smoky days in order to prioritise communities by smoke impacts. Levoglucosan measurements from one of the smokiest communities were used to establish the most informative values for three algorithmic parameters: the daily standard deviation of 1-h PM2.5 measurements; the daily mean temperature; and the daytime-to-nighttime ratio of PM2.5 concentrations. Alternate parameterizations were tested in 45 sensitivity analyses. Using the most informative parameter values on the most recent two years of data for each community, the number of smoky days ranged from 5 to 277. Heat maps visualizing seasonal and diurnal variation in PM2.5 concentrations showed clear differences between the higher- and lower-ranked communities. Some communities were sensitive to one or more of the parameters, but the overall rankings were consistent across the 45 analyses. This information will allow stakeholder agencies to work with local governments on implementing appropriate intervention strategies for the most smoke-impacted communities.

Under global change organisms are exposed to multiple, potentially interacting stressors. Especially interactions between successive stressors are poorly understood and recently suggested to depend on their timing of exposure. We particularly need studies assessing the impact of exposure to relevant stressors at various life stages and how these interact. We investigated the single and combined impacts of a heat wave (mild [25 °C] and extreme [30 °C]) during the egg stage, followed by successive exposure to esfenvalerate (ESF) and a heat wave during the larval stage in damselflies. Each stressor caused mortality. The egg heat wave and larval ESF exposure had delayed effects on survival, growth and lipid peroxidation (MDA). This resulted in deviations from the prediction that stressors separated by a long time interval would not interact: the egg heat wave modulated the interaction between the stressors in the larval stage. Firstly, ESF caused delayed mortality only in larvae that had been exposed to the extreme egg heat wave and this strongly depended upon the larval heat wave treatment. Secondly, ESF only increased MDA in larvae not exposed to the egg heat wave. We found little support for the prediction that when there is limited time between stressors, synergistic interactions should occur. The intermediate ESF concentration only caused delayed mortality when combined with the larval heat wave, and the lowest ESF concentrations only increased oxidative damage when followed by the mild larval heat wave. Survival selection mitigated the interaction patterns between successive stressors that are individually lethal, and therefore should be included in a predictive framework for the time-scale dependence of the outcome of multistressor studies with pollutants. The egg heat wave shaping the interaction pattern between successive pesticide exposure and a larval heat wave highlights the connectivity between the concepts of ‘heat-induced pesticide sensitivity’ and ‘pesticide-induced heat sensitivity’.

A warming climate is anticipated to increase the future heat-related total mortality in urban areas. However, little evidence has been reported for cause-specific mortality or nonurban areas. Here we assessed the impact of climate change on heat-related total and cause-specific mortality in both urban and rural counties of Jiangsu Province, China, in the next five decades. To address the potential uncertainty in projecting future heat-related mortality, we applied localized urban- and nonurban-specific exposure response functions, six population projections including a no population change scenario and five Shared Socioeconomic Pathways (SSPs), and 42 temperature projections from 21 global-scale general circulation models and two Representative Concentration Pathways (RCPs). Results showed that projected warmer temperatures in 2016–2040 and 2041–2065 will lead to higher heat-related mortality for total non-accidental, cardiovascular, respiratory, stroke, ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes occurring annually during May to September in Jiangsu Province, China. Nonurban residents in Jiangsu will suffer from more excess heat-related cause-specific mortality in 2016–2065 than urban residents. Variations across climate models and RCPs dominated the uncertainty of heat-related mortality estimation whereas population size change only had limited influence. Our findings suggest that targeted climate change mitigation and adaptation measures should be taken in both urban and nonurban areas of Jiangsu Province. Specific public health interventions should be focused on the leading causes of death (stroke, IHD, and COPD), whose health burden will be amplified by a warming climate.

Burning coal for winter heating has been considered a major contributor to northern China's winter haze, with the district heating boilers holding the balance. However a decade of intensive efforts on district heating boilers brought few improvements to northern China's winter air quality, arousing a speculation that the household heating stoves mainly in rural area rather than the district heating boilers mainly in urban area dominate coal emissions in winter. This implies an extreme underestimation of rural household coal consumption by the China Energy Statistical Yearbooks (CESYs), although direct evidence supporting this speculation is lacking. A village energy survey campaign was launched to gather the firsthand information on household coal consumption in the rural areas of two cities, Baoding (in Hebei province) and Beijing (the capital of China). The survey data show that the rural raw coal consumption in Baoding (5.04 × 103 kt) was approximately 6.5 times the value listed in the official CESY 2013 and exceeded the rural total of whole Hebei Province (4668 kt), revealing a huge amount of raw coal missing from the current statistical system. More importantly, rural emissions of particulate matter (PM) and SO2 from raw coal, which had never been included in widely distributing environmental statistical reports, were found higher than those from industrial and urban household sectors in the two cities in 2013, which highlights the importance of rural coal burning in creating northern China's heavy haze and helps to explain why a number of modeling predictions on ambient pollutant concentrations based on normal emission inventories were more bias-prone in winter season than in other seasons. We therefore recommend placing greater emphasis on the “missing” rural raw coal to help China in its long-term ambition to achieve clean air in the context of rapid economic development.

Seasonal patterns of birth outcomes have been observed worldwide, and there was increasing evidence that ambient temperature played as a trigger of adverse birth outcomes, such as preterm birth (PTB), low birth weight (LBW), and stillbirth. To systematically review updated epidemiological evidence about the relationship between temperature exposure during pregnancy and PTB, LBW, and stillbirth, we searched for related studies published in English from electronic databases and references of identified papers. We only included original articles that directly reported the effects of prenatal temperature exposure on birth outcomes. The characteristics and main findings of included studies were examined. A total of 36 epidemiological studies were finally included in this review. Most of these studies focused on PTB and LBW, while less attention has been paid to stillbirth that was relatively rare in the occurrence. Several designs including ecological (e.g., descriptive and time-series) and retrospective cohort studies (e.g., case-crossover and time-to-event) were applied to assess temperature effects on birth outcomes. Temperature metrics and exposure windows varied greatly in these investigations. Exposure to high temperature was generally found to be associated with PTB, LBW, and stillbirth, while several studies also reported the adverse impact of low temperature on birth outcomes of PTB and LBW. Despite no conclusive causality demonstrated, the current evidence for adverse effect on birth outcomes was stronger for heat than for cold. In summary, the evidence linking birth outcomes with ambient temperature was still very limited. Consequently, more related studies are needed worldwide and should be conducted in diversified climate zones, so as to further ascertain the association between temperature and birth outcomes. Future studies should focus on more sophisticated study designs, more accurate estimation of temperature exposure during pregnancy, and more efficient methods to find out the exposure windows, as well as cold-related effects on birth outcomes.

Chlorinated and brominated polycyclic aromatic hydrocarbons (Cl/Br-PAHs) are emerging semi-volatile organic pollutants in haze-associated particulate matter (PM). Their gas–particle phase partitioning and distribution among PM fractions have not been clarified. Clarification would increase understanding of atmospheric behavior and health risks of Cl/Br-PAHs. In this study, samples of the gas phase and 4 PM phases (aerodynamic diameters (dae) > 10 μm, 2.5–10 μm, 1.0–2.5 μm, and <1.0 μm) were collected simultaneously during haze events in Beijing and analyzed. Normalized histogram distribution indicated that the Cl/Br-PAHs tended to adhere to fine particles. Over 80% of the Cl-PAHs and 70% of the Br-PAHs were associated with fine PM (dae < 2.5 μm). The gas–particle phase partitioning and PM distribution of Cl/Br-PAHs when heating of buildings was required, which was associated with haze events, were obviously different from those when heating was not required. The relationship between the logarithmic geometric mean diameters of the Cl/Br-PAH congeners and reciprocal of the temperature (1/T) suggested that low air temperatures during the heating period could lead to high proportions of Cl/Br-PAHs in the fine particles. Increased coal burning during the heating period also contributed to high Cl/Br-PAH loads in the fine particles.