Per- and polyfluoroalkyl substances (PFAS) have become a target of rigorous scientific research due to their ubiquitous nature and adverse health effects. However, there are still gaps in knowledge about their environmental fate and health implications. More attention is needed for remote locations with source exposures. This study focuses on assessing PFAS exposure in Gustavus, a small Alaska community, located near a significant PFAS source from airport operations and fire training sites. Residential water (n = 25) and serum (n = 40) samples were collected from Gustavus residents and analyzed for 39 PFAS compounds. In addition, two water samples were collected from the previously identified PFAS source near the community. Fourteen distinct PFAS were detected in Gustavus water samples, including 6 perfluorinated carboxylic acids (PFCAs), 7 perfluorosulfonic acids (PFSAs), and 1 fluorotelomer sulfonate (FTS). ΣPFAS concentrations in residential drinking water ranged from not detected to 120 ng/L. High ΣPFAS levels were detected in two source samples collected from the Gustavus Department of Transportation (14,600 ng/L) and the Gustavus Airport (228 ng/L), confirming these two locations as a nearby major source of PFAS contamination. Seventeen PFAS were detected in serum and ΣPFAS concentrations ranged from 0.0170 to 13.1 ng/mL (median 0.0823 ng/mL). Perfluorooctanesulfonic acid (PFOS) and perfluorohexanesulfonic acid (PFHxS) were the most abundant PFAS in both water and serum samples and comprised up to 70% of ΣPFAS concentrations in these samples. Spearman's correlation analysis revealed PFAS concentrations in water and sera were significantly and positively correlated (r = 0.495; p = 0.0192). Our results confirm a presence of a significant PFAS source near Gustavus, Alaska and suggest that contaminated drinking water from private wells contributes to the overall PFAS body burden in Gustavus residents.

This study reports seasonal variations of meteorological parameters, atmospheric dust and dust-borne heavy metals concentrations measured, over a period of two years, next to two major airports (Dubai International Airport and Abu Dhabi International Airport) in the Gulf Cooperation Council (GCC) region. On-line monitoring stations were installed at each location next to dust samplers used to frequently collect PM2.5 and PM10 on Teflon filters for metal analysis. Clear seasonal variation in meteorological parameters were identified. The particulate matter concentrations depicted from the two locations were continuously monitored. The PM2.5 concentration ranged from 50 to 100 μg/m³ on normal days but reached 350–400 μg/m³ per day during mild storms. The PM10 levels ranged between 100 and 250 μg/m³ during normal days and spiked to 750 μg/m³ during mild storms. Energy Dispersive X-Ray Analysis (EDS) revealed the presence of significant amounts of alkali and alkaline earth metals, which pose potential harm to aircraft engines. ICP analysis showed the presence of heavy and toxic metals in concentrations that may pose harm to human health. Bulk sand samples from Abu Dhabi sites showed chemical similarities to the atmospheric dust samples. The concentrations of heavy metals, PM2.5, and PM10 are at levels that require further monitoring due to their impact on human health. The two years meteorological monitoring, with the seasonal variations, provided additional regional data in the Arabian Gulf. Furthermore, the study concluded that Sand and Dust storms (SDS) occur more frequently at the northern Arabian Gulf compared to its southern region. The chemical correlation between atmospheric dust and regional desert sand suggests the localized origin of the smaller dust particles that may form by breaking apart of the ground sand grains. As a result of the ongoing urbanization in the region, it is essential to collect additional data from various locations for a longer period of time.

In this study, the effects of descent flight path angle (between 1.25° and 4.25°) on aircraft gaseous emissions (carbon monoxide, total hydrocarbons and nitrogen oxides) are explored using actual flight data from aircraft flight data recording system and emissions indices from the International Civil Aviation Organization. All emissions parameters are corrected to flight conditions using Boeing Fuel Flow Method2, where the ambient air pressure, temperature and humidity data are obtained from long-term radiosonde data measured close to the arrival airport. The main findings highlight that the higher the flight path angle, the higher the emission indices of CO and HC, whereas the lower the emissions index of NOx and fuel consumption. Furthermore, during a descent, a heavier aircraft tends to emit less CO and HC, and more NOx. For a five-tonne aircraft mass increase, the average change in emissions indices are found to be −4.1% and −5.7% (CO), −5.4% and −8.2% (HC), and +1.1% and +1.6% (NOx) for high and low flight path angle groups, respectively. The average emissions indices for CO, HC and NOx during descent are calculated to be 24.5, 1.7 and 5.6 g/kg of fuel, whereas the average emissions for descending from 32,000 ft (9.7 km) and 24,000 ft (7.3 km) are calculated to be 7–8 kg (CO), ∼0.5 kg (HC) and ∼3 kg (NOx).

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.

A quantitative knowledge of the fate of deicing chemicals in the subsurface can be provided by joint analysis of lab experiments with numerical simulation models. In the present study, published experimental data of microbial degradation of the deicing chemical propylene glycol (PG) under flow conditions in soil columns were simulated inversely to receive the parameters of degradation. We evaluated different scenarios of an advection-dispersion model including different terms for degradation, such as zero order, first order and inclusion of a growing and decaying biomass for their ability to explain the data. The general break-through behavior of propylene glycol in soil columns can be simulated well using a coupled model of solute transport and degradation with growth and decay of biomass. The susceptibility of the model to non-unique solutions was investigated using systematical forward and inverse simulations. We found that the model tends to equifinal solutions under certain conditions.

Civil aircraft emissions during landing and takeoff (LTO) are important air pollutant sources, but have been given insufficient attention in China. Accurate estimation of these emissions is limited by a lack of important parameters, such as detailed flight information and the dynamic time in climb and approach modes during LTO that are dependent on mixing layer height (MLH). We developed a flight-time/flight-height relationship using real-time height information in Aircraft Meteorological Data Relay data, and then calculated the actual time for each flight in those two modes based on the actual MLH from meteorological observation. Hourly emissions of civil aircraft were then estimated based on the database of each flight. Total emissions of NOx, CO, SO2, HC and PM from LTO cycles of domestic flights in China during 2015 were 37.78 Gg, 30.25 Gg, 12.00 Gg, 2.38 Gg and 0.75 Gg, respectively. Substantial monthly, daily and hourly variations of emissions due to the flight schedule as well as MLH were calculated. Large differences were found between the new estimation and emissions calculated based on traditional method. Compared with the emissions estimated based on default parameter obtained from International Civil Aviation Organization, the average difference of annual emission among airports with new estimation for various pollutants was approximately 30.3% in climb mode and 81.4% in approach mode; compared with the emissions estimated based on the method proposed by China National Guide, the average difference of annual emission among airports were 37.4% (NOx), 8.4% (CO), 73.1% (HC) and 58.1% (PM) during LTO process. The monthly airport-specific emissions per LTO were also proposed. These can provide necessary and meaningful support for the revision of the values in National Guide.

In this study, the measurement of volatile organic compounds (VOCs) was conducted at Beijing Capital International Airport (ZBAA) and a background reference site in four seasons of 2015. Total concentrations of VOCs were 72.6 ± 9.7, 65.5 ± 8.7, 95.8 ± 11.0, and 79.2 ± 10.8 μg/m3 in winter, spring, summer, and autumn, respectively. The most abundant specie was toluene (10.1%–17.4%), followed by benzene, ethane, isopentane, ethane, acetylene, and n-butane. Seasonal variations of VOCs were analyzed, and it was found that the highest concentration occurring in summer, while the lowest in spring. For the diurnal variation, the concentration of VOCs in the daytime (9:00–15:00) was less than that at night (15:00–21:00) obviously. Ozone Formation Potential (OFP) was calculated by using Maximum Incremental Reactivity (MIR) method. The greatest contribution to OFP from alkenes and aromatics, which accounted for 27.3%–51.2% and 36.6%–58.6% of the total OFP. The WRF-CMAQ model was used to simulate the impact of airport emissions on the surrounding area. The results indicated that the maximum impact of VOCs emissions and all sources emissions at the airport on O3 was 0.035 and −23.8 μg/m3, respectively. Meanwhile, within 1 km from the airport, the concentration of O3 around the airport was greatly affected by airport emitted.

The spatiotemporal variability of ambient volatile organic compounds (VOCs) in Tehran, Iran, is not well understood. Here we present the design, methods, and results of the Tehran Study of Exposure Prediction for Environmental Health Research (Tehran SEPEHR) on ambient concentrations of benzene, toluene, ethylbenzene, p-xylene, m-xylene, and o-xylene (BTEX). To date, this is the largest study of its kind in a low- and middle-income country and one of the largest globally. We measured BTEX concentrations at five reference sites and 174 distributed sites identified by a cluster analysis method. Samples were taken over 25 2-weeks at five reference sites (to be used for temporal adjustments) and over three 2-week campaigns in summer, winter, and spring at 174 distributed sites. The annual median (25th–75th percentile) for benzene, the most carcinogenic of the BTEX species, was 7.8 (6.3–9.9) μg/m3, and was higher than the national and European Union air quality standard of 5 μg/m3 at approximately 90% of the measured sites. The estimated annual mean concentrations of BTEX were spatially highly correlated for all pollutants (Spearman rank coefficient 0.81–0.98). In general, concentrations and spatial variability were highest during the summer months, most likely due to fuel evaporation in hot weather. The annual median of benzene and total BTEX across the 35 sites in the Tehran regulatory monitoring network (7.7 and 56.8 μg/m3, respectively) did a reasonable job of approximating the 144 city-wide sites (7.9 and 58.7 μg/m3, respectively). The annual median concentrations of benzene and total BTEX within 300 m of gas stations were 9.1 and 67.3 μg/m3, respectively, and were higher than sites outside this buffer. We further found that airport did not affect annual BTEX concentrations of sites within 1 km. Overall, the observed ambient concentrations of toxic VOCs are a public health concern in Tehran.

Exposure models are needed to evaluate the chronic health effects of ambient ultrafine particles (<0.1 μm) (UFPs). We developed a land use regression model for ambient UFPs in Toronto, Canada using mobile monitoring data collected during summer/winter 2010–2011. In total, 405 road segments were included in the analysis. The final model explained 67% of the spatial variation in mean UFPs and included terms for the logarithm of distances to highways, major roads, the central business district, Pearson airport, and bus routes as well as variables for the number of on-street trees, parks, open space, and the length of bus routes within a 100 m buffer. There was no systematic difference between measured and predicted values when the model was evaluated in an external dataset, although the R² value decreased (R² = 50%). This model will be used to evaluate the chronic health effects of UFPs using population-based cohorts in the Toronto area.

In this study, the positive matrix factorization (PMF) source apportionment model was employed to quantify the contributions of airport activities to particle number concentrations (PNCs) at Amsterdam Schiphol. Time-resolved particle number size distributions in parallel with the concentrations of auxiliary variables, including gaseous pollutants (NOₓ and CO), black carbon, PM₂.₅ mass, and number of arrivals/departures were measured for 32 sampling days over a 6-month period near Schiphol airport to be used in the model. PMF results revealed that airport activities, cumulatively, accounted for around 79.3% of PNCs and our model segregated them into three major groups: (i) aircraft departures, (ii) aircraft arrivals, and (iii) ground service equipment (GSE) (with some contributions of local road traffic, mostly from airport parking lots). Aircraft departures and aircraft arrivals showed mode diameters <20 nm and contributed, respectively, to 46.1% and 26.7% of PNCs. The factor GSE/local road traffic, with a mode diameter of around 60–80 nm, accounted for 6.5% of the PNCs. Road traffic related mainly to the surrounding freeways was characterized with a mode diameter of 30–40 nm; this factor contributed to 18.0% of PNCs although its absolute PNCs was comparable with that of areas heavily impacted by traffic emissions. Lastly, urban background with a mode diameter at 150–225 nm, had a minimal contribution (2.7%) to PNCs while dominating the particle volume/mass concentrations with a contribution of 58.2%. These findings illustrate the dominant role of the airport activities in ambient PNCs in the surrounding areas. More importantly, the quantification of the contributions of different airport activities to PNCs is a useful tool to better control and limit the increased PNCs near the airports that could adversely impact the health of the adjacent urban communities.