Ambient air pollution ranks high among the risk factors that increase the global burden of disease. Previous studies focused on assessing mortality risk and were sparsely performed in populous developing countries with deteriorating environments. We conducted a time-series study to evaluate the air pollution-associated years of life lost (YLL) and mortality risk and to identify potential modifiers relating to the season and demographic characteristics. Using linear (for YLL) and Poisson (for mortality) regression models and controlling for time-varying factors, we found that an interquartile range (IQR) increase in a three-day average cumulative (lag 0–2 day) concentrations of PM2.5, PM10, NO2 and SO2 corresponded to increases in YLL of 12.09 (95% confidence interval [CI]: 2.98–21.20), 13.69 (95% CI: 3.32–24.07), 26.95 (95% CI: 13.99–39.91) and 24.39 (95% CI: 8.62–40.15) years, respectively, and to percent increases in mortality of 1.34% (95% CI: 0.67–2.01%), 1.56% (95% CI: 0.80–2.33%), 3.36% (95% CI: 2.39–4.33%) and 2.39% (95% CI: 1.24–3.55%), respectively. Among the specific causes of death, cardiovascular and respiratory diseases were positively associated with gaseous pollutants (NO2 and SO2), and diabetes was positively correlated with NO2 (in terms of the mortality risk). The effects of air pollutants were more pronounced in the cool season than in the warm season. The elderly (>65 years) and females were more vulnerable to air pollution. Studying effect estimates and their modifications by using YLL to detect premature death should support implementing health risk assessments, identifying susceptible groups and guiding policy-making and resource allocation according to specific local conditions.

We developed a novel indicator, daily excessive concentration hours (DECH), to explore the acute mortality impacts of ambient fine particulate matter pollution (PM2.5) in Hong Kong. The DECH of PM2.5 was calculated as daily concentration-hours >25 μg/m3. We applied a generalized additive models to quantify the association between DECH and mortality with adjustment for potential confounders. The results showed that the DECH was significantly associated with mortality. The excess mortality risk for an interquartile range (565 μg/m3*hours) increase in DECH of PM2.5 was 1.65% (95% CI: 1.05%, 2.26%) for all natural mortality at lag 02 day, 2.01% (95% CI: 0.82%, 3.21%) for cardiovascular mortality at lag 03 days, and 1.41% (95% CI: 0.34%, 2.49%) for respiratory mortality at lag 2 day. The associations remained consistent after adjustment for gaseous air pollutants (daily mean concentration of SO2, NO2 and O3) and in alternative model specifications. When compared to the mortality burden of daily mean PM2.5, DECH was found to be a relatively conservative indicator. This study adds to the evidence by showing that daily excessive concentration hours of PM2.5 might be a new predictor of mortality in Hong Kong.

The development of reliable measures of exposure to traffic-related air pollution is crucial for the evaluation of the health effects of transportation. Land-use regression (LUR) techniques have been widely used for the development of exposure surfaces, however these surfaces are often highly sensitive to the data collected. With the rise of inexpensive air pollution sensors paired with GPS devices, we witness the emergence of mobile data collection protocols. For the same urban area, can we achieve a ‘universal’ model irrespective of the number of locations and sampling visits? Can we trade the temporal representation of fixed-point sampling for a larger spatial extent afforded by mobile monitoring? This study highlights the challenges of short-term mobile sampling campaigns in terms of the resulting exposure surfaces. A mobile monitoring campaign was conducted in 2015 in Montreal; nitrogen dioxide (NO2) levels at 1395 road segments were measured under repeated visits. We developed LUR models based on sub-segments, categorized in terms of the number of visits per road segment. We observe that LUR models were highly sensitive to the number of road segments and to the number of visits per road segment. The associated exposure surfaces were also highly dissimilar.

Evidence supporting an inverse association between maternal exposure to air pollutants and foetal growth has been accumulating. However, the findings from Asian populations are limited, and the question of critical windows of exposure remains unanswered. We examined whether maternal exposure to air pollutants, in particular exposure during the first trimester (an important period of placental development), was associated with foetal growth in Japanese term infants. From the Japan Perinatal Registry Network database, we received birth data for 29,177 term singleton births in western Japan (Kyushu-Okinawa Districts) between 2005 and 2010. Exposure was expressed in terms of average concentrations of air pollutants (ozone, suspended particulate matter, nitrogen dioxide, and sulphur dioxide), as measured at the nearest monitoring stations to the respective delivery hospitals of the pregnant women, during the entire pregnancy and each trimester. As proxy markers of foetal growth restriction, we used small for gestational age (SGA), and adverse birth weight (low birth weight in addition to SGA). For pollutant exposure during the entire pregnancy, we did not observe the association with SGA and adverse birth weight. In the single-trimester model for the first trimester, however, we found a positive association between ozone exposure, and SGA (odds ratio [OR] per 10 ppb increase = 1.07, 95% confidence interval [CI] = 1.01–1.12) and adverse birth weight (OR = 1.07; 95% CI = 1.01–1.14). This association persisted in the multi-trimester model, and no association for exposure during the second or third trimester was observed. Exposure to other pollutants during each trimester was not associated with these outcomes. In conclusion, maternal exposure to ozone during the first trimester was independently associated with an elevated risk of poor foetal growth.

There is limited evidence showing the mortality effects of temperature variability (TV) on cardiovascular diseases. The joint effects between TV and air pollutants are also less well-established. This study aims to assess the effect modification of TV-cardiovascular mortality by air pollutants in three Chinese cities (Beijing, Nanjing and Chengdu). Data of daily mortality, air pollutants and meteorological factors from 2008 to 2011 was collected from each city. TV was calculated as the standard deviation of daily maximum and minimum temperatures over exposure days. The city-specific effect estimates of TV on cardiovascular mortality were calculated using a quasi-Poisson regression model, adjusting for potential confounders (e.g., seasonality and temperature). An interaction term of TV and a three-level air pollutants stratum indicator was included in the models. Effect modifications by air pollutants were assessed by comparing the estimates of TV's effect between pollutant stratums and calculating the corresponding 95% confidential interval of the differences. Multivariate meta-analysis was conducted to obtain the pooled estimates. The data showed that TV was associated with increased risk of cardiovascular mortality, especially for longer TV exposure days (0–8 days, TV08). This association was still observed after adjusting for air pollutants on current day or the previous two days. Stronger estimates were observed in females, but no significant difference between males and females was detected, indicating the absence of evidence of effect modification by gender. Estimates of TV-cardiovascular mortality varied across two season periods (warm and cool season) and age groups, but the evidence of effect modification by age and seasons was absent. Regarding the effect modification of TV-cardiovascular mortality association by air pollutants, a significant effect modification was identified for PM10, but not for NO2 and SO2 in the whole population for all TV exposure days. This finding also persisted in subgroups, specifically in females and the elderly.

Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic annual ruderal plant and native to Northern America, but now also spreading across Europe. Air pollution and climate change will not only affect plant growth, pollen production and duration of the whole pollen season, but also the amount of allergenic encoding transcripts and proteins of the pollen. The objective of this study was to get a better understanding of transcriptional changes in ragweed pollen upon NO2 and O3 fumigation. This will also contribute to a systems biology approach to understand the reaction of the allergenic pollen to air pollution and climate change. Ragweed plants were grown in climate chambers under controlled conditions and fumigated with enhanced levels of NO2 and O3. Illumina sequencing and de novo assembly revealed significant differentially expressed transcripts, belonging to different gene ontology (GO) terms that were grouped into biological process and molecular function. Transcript levels of the known Amb a ragweed encoding allergens were clearly up-regulated under elevated NO2, whereas the amount of allergen encoding transcripts was more variable under elevated O3 conditions. Moreover transcripts encoding allergen known from other plants could be identified. The transcriptional changes in ragweed pollen upon elevated NO2 fumigation indicates that air pollution will alter the transcriptome of the pollen. The changed levels of allergenic encoding transcripts may have an influence on the total allergenic potential of ragweed pollen.

A large eddy simulation (LES) model coupled with O3-NOx-VOC chemistry is implemented to simulate the coupled effects of emissions, mixing and chemical pre-processing within an idealised deep (aspect ratio = 2) urban street canyon under a weak wind condition. Reactive pollutants exhibit significant spatial variations in the presence of two vertically aligned unsteady vortices formed in the canyon. Comparison of the LES results from two chemical schemes (simple NOx-O3 chemistry and a more comprehensive Reduced Chemical Scheme (RCS) chemical mechanism) shows that the concentrations of NO2 and Ox inside the street canyon are enhanced by approximately 30–40% via OH/HO2 chemistry. NO, NOx, O3, OH and HO2 are chemically consumed, while NO2 and Ox (total oxidant) are chemically produced within the canyon environment. Within-canyon pre-processing increases oxidant fluxes from the canyon to the overlying boundary layer, and this effect is greater for deeper street canyons (as found in many traditional European urban centres) than shallower (lower aspect ratio) streets. There is clear evidence of distinct behaviours for emitted chemical species and entrained chemical species, and positive (or negative) values of intensities of segregations are found between pairs of species with similar (or opposite) behaviour. The simplified two-box model underestimated NO and O3 levels, but overestimated NO2 levels for both the lower and upper canyon compared with the more realistic LES-chemistry model. This suggests that the segregation effect due to incomplete mixing reduces the chemical conversion rate of NO to NO2. This study reveals the impacts of nonlinear O3-NOx-VOC photochemical processes in the incomplete mixing environment and provides a better understanding of the pre-processing of emissions within canyons, prior to their release to the urban boundary layer, through the coupling of street canyon dynamics and chemistry.

Data on particulate matter of diameter <2.5 μm (PM2.5) in the city of Chongqing were first announced in 2013. We wished to assess the effects of pollutants on asthmatic children in Chongqing, China. Daily numbers of hospital visits because of asthma attacks in children aged 0–18 years in 2013 were collected from the Children's Hospital of Chongqing Medical University. Data on pollutants were accessed from the nine air quality-monitoring stations in Chongqing. A time-stratified case–crossover design was applied and conditional logistic regression was undertaken to analyze the data. We found that short-term exposure to PM10, PM2.5, sodium dioxide, nitrogen and carbon monoxide could trigger hospital visits for asthma in children. Nitrogen dioxide had an important role, whereas ozone had no effect.

Both air pollution and meteorological factors in metropolitan areas increased emergency department (ED) visits from people with chronic obstructive pulmonary disease (COPD). Few studies investigated the associations between air pollution, meteorological factors, and COPD-related health disorders in Asian countries. This study aimed to investigate the relationship between the environmental factors and COPD-associated ED visits of susceptible elderly population in the largest Taiwanese metropolitan area (Taipei area, including Taipei city and New Taipei city) between 2000 and 2013. Data of air pollutant concentrations (PM10, PM2.5, O3, SO2, NO2 and CO), meteorological factors (daily temperature, relative humidity and air pressure), and daily COPD-associated ED visits were collected from Taiwan Environmental Protection Administration air monitoring stations, Central Weather Bureau stations, and the Taiwan National Health Insurance database in Taipei area. We used a case-crossover study design and conditional logistic regression models with odds ratios (ORs), and 95% confidence intervals (CIs) for evaluating the associations between the environmental factors and COPD-associated ED visits. Analyses showed that PM2.5, O3, and SO2 had significantly greater lag effects (the lag was 4 days for PM2.5, and 5 days for O3 and SO2) on COPD-associated ED visits of the elderly population (65–79 years old). In warmer days, a significantly greater effect on elderly COPD-associated ED visits was estimated for PM2.5 with coexistence of O3. Additionally, either O3 or SO2 combined with other air pollutants increased the risk of elderly COPD-associated ED visits in the days of high relative humidity and air pressure difference, respectively. This study showed that joint effect of urban air pollution and meteorological factors contributed to the COPD-associated ED visits of the susceptible elderly population in the largest metropolitan area in Taiwan. Government authorities should review existing air pollution policies, and strengthen health education propaganda to ensure the health of the susceptible elderly population.

The limited spatial coverage of the air pollution data available from regulatory air quality monitoring networks hampers national-scale epidemiological studies of air pollution. The present study aimed to develop a national-scale exposure prediction model for estimating annual average concentrations of PM10 and NO2 at residences in South Korea using regulatory monitoring data for 2010. Using hourly measurements of PM10 and NO2 at 277 regulatory monitoring sites, we calculated the annual average concentrations at each site. We also computed 322 geographic variables in order to represent plausible local and regional pollution sources. Using these data, we developed universal kriging models, including three summary predictors estimated by partial least squares (PLS). The model performance was evaluated with fivefold cross-validation. In sensitivity analyses, we compared our approach with two alternative approaches, which added regional interactions and replaced the PLS predictors with up to ten selected variables. Finally, we predicted the annual average concentrations of PM10 and NO2 at 83,463 centroids of residential census output areas in South Korea to investigate the population exposure to these pollutants and to compare the exposure levels between monitored and unmonitored areas. The means of the annual average concentrations of PM10 and NO2 for 2010, across regulatory monitoring sites in South Korea, were 51.63 μg/m3 (SD = 8.58) and 25.64 ppb (11.05), respectively. The universal kriging exposure prediction models yielded cross-validated R2s of 0.45 and 0.82 for PM10 and NO2, respectively. Compared to our model, the two alternative approaches gave consistent or worse performances. Population exposure levels in unmonitored areas were lower than in monitored areas. This is the first study that focused on developing a national-scale point wise exposure prediction approach in South Korea, which will allow national exposure assessments and epidemiological research to answer policy-related questions and to draw comparisons among different countries.