PM2.5 concentrations in a typical residential apartment in Beijing and immediately outside of the building were measured simultaneously during heating and non-heating periods. The objective was to quantitatively explore the relationship between indoor and outdoor PM2.5 concentrations. A statistical method for predicting indoor PM2.5 concentrations was proposed. Ambient PM2.5 concentrations were strongly affected by meteorological conditions, especially wind directions. A bimodal distribution was identified during the heating season due to the frequent and rapid transition between severe pollution events and clean days. Indoor PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations but with 1–2 h delay, and the differences can be explained by ambient meteorological features, such as temperature, humidity, and wind direction. These results indicate the potential to incorporate indoor exposure features to the regional air quality model framework and to more accurately estimate the epidemiological relationship between human mortality and air pollution exposure.

This study provides the first estimate of dry deposition fluxes of criteria air pollutants (SO2 and NOx) across the Three Northern Regions Shelter Forest (TNRSF) region in Northern China and their long-term trends from 1982 to 2010 using the inferential method. Dry deposition velocities of SO2 and NOx increased in many places of the TNRSF up to 118.2% for SO2 and 112.1% for NOx over the last three decades due to the increased vegetation coverage over the TNRSF. The highest atmospheric deposition fluxes of SO2 and NOx were found in the Central-North China region, followed by the Northeast and the Northwest China regions of the TNRSF. A total of 820,000 t SO2 and 218,000 t NOx was estimated to be removed from the atmosphere through dry deposition process over the TNRSF from 1982 to 2010. About 50% of the total removal occurred in the Central-North China region. The estimated total SO2 and NOx dry deposition fluxes from 1982 to 2010 between a TNRSF site in this region and an adjacent farmland outside the TNRSF showed that the fluxes of these two chemicals at the TNRSF site were the factors of 2–3 greater than their fluxes in the farmland.

Pollution adversely affects vegetation; however, its impact on phenology and leaf morphology is not satisfactorily understood yet. We analyzed associations between pollutants and phenological data of birch, hazel and horse chestnut in Munich (2010) along with the suitability of leaf morphological parameters of birch for monitoring air pollution using two datasets: cumulated atmospheric concentrations of nitrogen dioxide and ozone derived from passive sampling (short-term exposure) and pollutant information derived from Land Use Regression models (long-term exposure). Partial correlations and stepwise regressions revealed that increased ozone (birch, horse chestnut), NO2, NOx and PM levels (hazel) were significantly related to delays in phenology. Correlations were especially high when rural sites were excluded suggesting a better estimation of long-term within-city pollution. In situ measurements of foliar characteristics of birch were not suitable for bio-monitoring pollution. Inconsistencies between long- and short-term exposure effects suggest some caution when interpreting short-term data collected within field studies.

Few studies have evaluated the effects of ambient air pollution and temperature in triggering out-of-hospital coronary deaths (OHCDs) in China. We evaluated the associations of air pollution and temperature with daily OHCDs in Shanghai, China from 2006 to 2011. We applied an over-dispersed generalized additive model and a distributed lag nonlinear model to analyze the effects of air pollution and temperature, respectively. A 10 μg/m3 increase in the present-day PM10, PM2.5, SO2, NO2 and CO were associated with increases in OHCD mortality of 0.49%, 0.68%, 0.88%, 1.60% and 0.08%, respectively. A 1 °C decrease below the minimum-mortality temperature corresponded to a 3.81% increase in OHCD mortality on lags days 0–21, and a 1 °C increase above minimum-mortality temperature corresponded to a 4.61% increase over lag days 0–3. No effects were found for in-hospital coronary deaths. This analysis suggests that air pollution, low temperature and high temperature may increase the risk of OHCDs.

Lichens, symbioses of fungi and algae and/or cyanobacteria, have the remarkable ability to uptake and accumulate semivolatile organic compounds (SVOC) from air, including polycyclic aromatic hydrocarbons (PAHs), but the mechanism of accumulation is still unknown. Understanding these mechanisms is critical to standardize the use of lichens as environmental bioindicators and to further integrate them in air monitoring networks. Through a series of experiments we show that gas phase PAHs easily cross lichen's surface and accumulate in the photosynthetic algal layer of lichens. Once accumulated, they remain in the algal layer and not within the fungus hyphae, or adhered to lichen's surface, as it was previously supposed to happen. Additionally, when lichens are washed, gas phase PAHs still remain in the algal layer. Our results reveal that lichens may be utilized as bioindicators of gas phase PAHs, overcoming current limitations of air monitoring.

We investigated the association between hourly differences in air pollution and asthma exacerbation in Korea using asthma-related emergency department data and verified seasonality and demographic modifiers with an hourly temporal resolution. We applied time-stratified case-crossover adjusted for weather and influenza; the lag was stratified as 1–6, 7–12, 13–18, 19–24, 25–48, and49–72 h. Odds ratios (95% confidence interval) per interquartile range increase were 1.05 (1.00–1.11) after 1–6 h for PM10–2.5 and 1.10 (1.04–1.16) after 19–24 h for O3. Effect size was 1.14 (1.06–1.22) at a 1–6 h lag in spring for PM10–2.5, and 1.25 (1.03–1.51) at a 25–48 h lag in winter for O3. O3 effects were age- and low socio-economic status-modified at a 7–12 h lag [1.25 (1.04–1.51)]. Increased PM10–2.5 and O3 increased the risk of asthma exacerbation; the effect of PM10–2.5 was most immediate.

The validity of using the Air Pollution Index (API) to assess health impacts of air pollution and potential modification by individual characteristics on air pollution effects remain uncertain. We applied distributed lag non-linear models (DLNMs) to assess associations of daily API, specific pollution indices for PM10, SO2, NO2 and the weighted combined API (APIw) with mortality during 2003–2011 in Guangzhou, China. An increase of 10 in API was associated with a 0.88% (95% confidence interval (CI): 0.50, 1.27%) increase of non-accidental mortality at lag 0–2 days. Harvesting effects appeared after 2 days’ exposure. The effect estimate of API over lag 0–15 days was statistically significant and similar with those of pollutant-specific indices and APIw. Stronger associations between API and mortality were observed in the elderly, females and residents with low educational attainment. In conclusion, the API can be used to communicate health risks of air pollution.

Tropospheric ozone concentrations have been rising across Asia, and will continue to rise during the 21st century. Ozone affects rice yields through reductions in spikelet number, spikelet fertility, and grain size. Moreover, ozone leads to changes in rice grain and straw quality. Therefore the breeding of ozone tolerant rice varieties is warranted. The mapping of quantitative trait loci (QTL) using bi-parental populations identified several tolerance QTL mitigating symptom formation, grain yield losses, or the degradation of straw quality. A genome-wide association study (GWAS) demonstrated substantial natural genotypic variation in ozone tolerance in rice, and revealed that the genetic architecture of ozone tolerance in rice is dominated by multiple medium and small effect loci. Transgenic approaches targeting tolerance mechanisms such as antioxidant capacity are also discussed. It is concluded that the breeding of ozone tolerant rice can contribute substantially to the global food security, and is feasible using different breeding approaches.

We propose three estimation strategies (local, remote and mixed) for ultrafine particles (UFP) at three sites in an urban air pollution monitoring network. Estimates are obtained through Gaussian process regression based on concentrations of gaseous pollutants (NOx, O3, CO) and UFP. As local strategy, we use local measurements of gaseous pollutants (local covariates) to estimate UFP at the same site. As remote strategy, we use measurements of gaseous pollutants and UFP from two independent sites (remote covariates) to estimate UFP at a third site. As mixed strategy, we use local and remote covariates to estimate UFP. The results suggest: UFP can be estimated with good accuracy based on NOx measurements at the same location; it is possible to estimate UFP at one location based on measurements of NOx or UFP at two remote locations; the addition of remote UFP to local NOx, O3 or CO measurements improves models' performance.

Few studies on size-specific health effects of particulate matter have been conducted in Asia. We examined the association between both fine and coarse particles (PM2.5 and PM10−2.5) and mortality across 11 East Asian cities from 4 countries (Korea, Japan, Taiwan, and China). We performed a two-stage analysis: we generated city-specific estimates using a time-series analysis with a generalized additive model (Quasi-Poisson distribution), and estimated the overall effects by conducting a meta-analysis. Each 10−μg/m3 increase in PM2.5 (lag01) was associated with an increase of 0.38% (95% confidence interval = 0.21%–0.55%) in all causes mortality, 0.96% (0.46%–1.46%) in cardiovascular mortality, and 1% (0.23%–1.78%) in respiratory mortality. Each 10−μg/m3 increase in PM10−2.5 (lag01) was associated with cardiovascular mortality (0.69%, [0.05%–1.33%]), although this association attenuated after controlling for other pollutants, especially PM2.5. Increased mortality was associated with increasing PM2.5 and PM10−2.5 concentrations over 11 East Asian cities.