Transboundary Air-Pollution Transport in the Czech-Polish Border Region between the Cities of Ostrava and Katowice.

OBJECTIVE: The Czech Hydrometeorological Institute (CHMI) estimated the transboundary transport of air pollution between the Czech Republic and Poland by assessing relationships between weather conditions and air pollution in the area as part of the "Air Quality Information System in the Polish-Czech border of the Silesian and Moravian-Silesian region" project (http://www.air-silesia.eu). Estimation of cross-border transport of pollutants is important for Czech-Polish negotiations and targeted measures for improving air quality. METHODS: Direct measurement of PM10 and sulphur dioxide (SO2) concentrations and the direction and wind speed from measuring stations in the vicinity of the Czech-Polish state border in 2006-2012. RESULTS: Taking into account all the inaccuracies, simplifications and uncertainties, by which all of the measurements are affected, it is possible to state that the PM10 transboundary transport was greater from the direction of Poland to the Czech Republic, rather than the other way around. Nevertheless, the highest share of the overall PM10 concentration load was recorded on days with a vaguely estimated airflow direction. This usually included days with changing wind direction or days with a distinct wind change throughout the given day. A changeable wind is most common during low wind speeds. It can be assumed that during such days with an ambiguous daily airflow, the polluted air saturated with sources on both sides of the border moves from one country to the other. Therefore, we could roughly ascribe an equal level of these concentrations to both the Czech and Polish side. CONCLUSIONS: PM10 transboundary transport was higher from Poland to the Czech Republic than from the opposite direction, despite the predominant air flow from the Czech Republic to Poland.

Predictions of PFAS regional-scale atmospheric deposition and ambient air exposure.

Per- and polyfluoroalkyl substances (PFAS) are a large class of human-made compounds that have contaminated the global environment. One environmental entry point for PFAS is via atmospheric emission. Air releases can impact human health through multiple routes, including direct inhalation and contamination of drinking water following air deposition. In this work, we convert the reference dose (RfD) underlying the United States Environmental Protection Agency's GenX drinking water Health Advisory to an inhalation screening level and compare to predicted PFAS and GenX air concentrations from a fluorochemical manufacturing facility in Eastern North Carolina. We find that the area around the facility experiences ~15 days per year of GenX concentrations above the inhalation screening level we derive. We investigate the sensitivity of model predictions to assumptions regarding model spatial resolution, emissions temporal profiles, and knowledge of air emission chemical composition. Decreasing the chemical specificity of PFAS emissions has the largest impact on deposition predictions with domain-wide total deposition varying by as much as 250 % for total PFAS. However, predicted domain-wide mean and median air concentrations varied by <18 % over all scenarios tested for total PFAS. Other model features like emission temporal variability and model spatial resolution had weaker impacts on predicted PFAS deposition.

Impacts of combined exposure to formaldehyde and PM2.5 at ambient concentrations on airway inflammation in mice.

Asthma is a respiratory disease that can be exacerbated by certain environmental factors. Both formaldehyde (FA) and PM2.5, the most common indoor and outdoor air pollutants in mainland China, are closely associated with the onset and development of asthma. To date, however, there is very little report available on whether there is an exacerbating effect of combined exposure to FA and PM2.5 at ambient concentrations. In this study, asthmatic mice were exposed to 1 mg/m3 FA, 1 mg/kg PM2.5, or a combination of 0.5 mg/m3 FA and 0.5 mg/kg PM2.5, respectively. Results demonstrated that both levels of oxidative stress and inflammation were significantly increased, accompanied by an obvious decline in lung function. Further, the initial activation of p38 MAPK and NF-κB that intensified the immune imbalance of asthmatic mice were found to be visibly mitigated following the administration of SB203580, a p38 MAPK inhibitor. Noteworthily, it was found that combined exposure to the two at ambient concentrations could significantly worsen asthma than exposure to each of the two alone at twice the ambient concentration. This suggests that combined exposure to formaldehyde and PM2.5 at ambient concentrations may have a synergistic effect, thus causing more severe damage in asthmatic mice. In general, this work has revealed that the combined exposure to FA and PM2.5 at ambient concentrations can synergistically aggravate asthma via the p38 MAPK pathway in mice.

The impact of power plant emission variability and fuel switching on the air quality of Kuwait.

Power plant emissions have a significant impact on air quality, and a frequent assumption made in estimating impacts is to assume annual or monthly average emission rates. This study investigates the impact, on predicted ambient concentrations, of assuming annual average emissions, compared to resolving emissions on an hourly basis (base case). A case study of emissions from power plants in Kuwait, for the year 2014, is presented. In Kuwait, power plants operate on a mix of natural gas, gas oil, crude oil, and heavy fuel oil, and the type of fuel used varies on an hourly basis. Because of this fuel variability, a fuel switching strategy was also simulated in this work, replacing high sulfur fuels with natural gas during hours with high predicted SO2 concentrations. Emissions estimates were combined with an air quality dispersion model to simulate the temporal variability and spatial dispersion of sulfur dioxide (SO2) and nitrogen dioxide (NO2) in Kuwait, for a one-year episode. The results indicate that emission averaging and fuel switching operations result in lower area-wide annual maximum SO2 concentrations compared to the base case (1747 µg/m3, 1063 µg/m3, 616 µg/m3 for base case, annual average emissions and fuel switching scenarios, respectively). The number of receptor sites recording daily exceedances of the SO2 standard for annual average emissions were one seventh of those predicted for hourly averaged emissions and 92% lower for the fuel switching scenario. For NO2, while the overall number of exceedances of air quality criteria was much lower than for SO2, the numbers of exceedances were also predicted to be lower using annual averaged emissions compared to the base case. These results document the importance of using emission estimates that capture hourly variability over annually averaged emissions, particularly in locations such as Kuwait where multiple fuels are used in power production.

Estimation of personal ozone exposure using ambient concentrations and influencing factors.

Evidence is limited regarding whether ambient monitoring can properly represent personal ozone exposure. We conducted a longitudinal panel study to measure personal exposure to ozone using real-time personal ozone monitors. Corresponding ambient ozone concentrations and possible influencing factors (meteorological conditions and activity patterns) were also collected. We used linear mixed-effect models to analyze personal-ambient ozone concentration associations and possible influencing factors. Ambient ozone concentrations were around two to three times higher than personal ozone (43.1 µg/m3 on average) and their correlations were weak with small slopes (0.35) and marginal R square (RM2) values (0.24). Larger RM2 values were found under high temperature (>29.5 °C), low humidity (<62.1%), good ventilation conditions (>4 h) and for individuals spent longer time outdoors (>0.6 h). In final model, personal ozone exposure was positively associated with ambient concentrations and ventilation conditions, but inversely correlated with ambient temperature and humidity. The models explained >50% of personal ozone concentration variabilities. Our results highlight that ambient ozone concentration alone is not a suitable surrogate for individual exposure assessment. Meteorological conditions (temperature and humidity) and activity patterns (windows opening and outdoor activities) that affecting personal ozone exposure should be taken into account.