ACS ES&T Air最新文献

Commercial HVAC systems intended to mitigate indoor air pollution are operated based on standards that exclude aerosols with smaller diameters, such as ultrafine particles (UFPs, D_p ≤ 100 nm), which dominate a large proportion of indoor and outdoor number-based particle size distributions. UFPs generated from occupant activities or infiltrating from the outdoors can be recirculated and accumulate indoors when they are not successfully filtered by an air handling unit. Monitoring UFPs in real occupied environments is vital to understanding these source and mitigation dynamics, but capturing their rapid transience across multiple locations can be challenging due to high-cost instrumentation. This 9-month field measurement campaign pairs four medium-cost diffusion charger sensors with volumetric airflow rates modulated and monitored in a cloud-based building automation system of an open-plan living laboratory office and dedicated air handling unit to evaluate spatiotemporal particle number and surface area concentrations and migration trends. Particle number flux rates reveal that an estimated daily median of 8 × 10¹³ UFPs enter the air handling unit from the outdoors. Switching from a MERV14 to a HEPA filter reduces the number of UFPs supplied to the room by tens of trillions of UFPs daily, increasing the median filtration efficiency from 40% to 96%. These results demonstrate the efficacy of an optimal air handling unit’s performance to improve indoor air quality, while highlighting UFP dynamics that are not accounted for in current filtration standards nor in occupant-centered HVAC control. Scalable sensor development can popularize UFP monitoring and allow for future UFP integration within building control and automation platforms. The framework established for this campaign can be used to evaluate particle fluxes considering different analytes.

Current filtration standards exclude ultrafine particles, which dominate particle number size distributions. This field campaign establishes a framework using multinodal ultrafine particle and airflow rate monitoring to evaluate concentrations and migration trends in a high-performance building.

Commercial HVAC systems intended to mitigate indoor air pollution are operated based on standards that exclude aerosols with smaller diameters, such as ultrafine particles (UFPs, D_p ≤ 100 nm), which dominate a large proportion of indoor and outdoor number-based particle size distributions. UFPs generated from occupant activities or infiltrating from the outdoors can be recirculated and accumulate indoors when they are not successfully filtered by an air handling unit. Monitoring UFPs in real occupied environments is vital to understanding these source and mitigation dynamics, but capturing their rapid transience across multiple locations can be challenging due to high-cost instrumentation. This 9-month field measurement campaign pairs four medium-cost diffusion charger sensors with volumetric airflow rates modulated and monitored in a cloud-based building automation system of an open-plan living laboratory office and dedicated air handling unit to evaluate spatiotemporal particle number and surface area concentrations and migration trends. Particle number flux rates reveal that an estimated daily median of 8 × 10¹³ UFPs enter the air handling unit from the outdoors. Switching from a MERV14 to a HEPA filter reduces the number of UFPs supplied to the room by tens of trillions of UFPs daily, increasing the median filtration efficiency from 40% to 96%. These results demonstrate the efficacy of an optimal air handling unit's performance to improve indoor air quality, while highlighting UFP dynamics that are not accounted for in current filtration standards nor in occupant-centered HVAC control. Scalable sensor development can popularize UFP monitoring and allow for future UFP integration within building control and automation platforms. The framework established for this campaign can be used to evaluate particle fluxes considering different analytes.

Epidemiological studies typically model wildfire smoke exposure by predicting outdoor fine particulate matter (PM_2.5) concentrations, overlooking indoor environments where people spend most of their time. This discrepancy can lead to exposure misclassification for wildfire smoke and other air pollutants. We developed a machine learning (ML) model for estimating daily indoor and outdoor PM_2.5 concentrations in British Columbia, Canada, using an ensemble of nonparametric ML algorithms during the 2022 and 2023 wildfire seasons. For model training, we included daily PM_2.5 concentrations collected at 44 care facilities equipped with low-cost air quality sensors colocated indoors and outdoors. Model predictors for both indoor and outdoor PM_2.5 at the facilities included outdoor PM_2.5 and meteorological data from Canada’s National Air Pollution Surveillance Program and Purple Air sensors. The indoor and outdoor models were evaluated with cross validation and then used to compare exposure-response relationships for asthma inhaler dispensations, as an indicator of population respiratory health. Ensemble models accurately predicted PM_2.5 indoors (RMSE = 3.29 μg/m³; R² = 0.71) and outdoors (RMSE = 3.80 μg/m³; R² = 0.78). For the out-of-sample validation set (2023 wildfire season), the indoor model had a lower RMSE than the outdoor one (RMSE_Indoor = 6.65 μg/m³ vs RMSE_Outdoor = 9.64 μg/m³). The effect estimates for the relationship between indoor PM_2.5 and inhaler dispensations were higher than that for outdoor PM_2.5. These results suggest that population-scale indoor PM_2.5 exposure assessment is feasible for wildfire smoke epidemiology research, and that using outdoor estimates may bias the true relationship toward the null.

Our study highlights the importance of assessing indoor air quality during wildfires. We developed machine learning models to estimate indoor and outdoor PM_2.5 in a region with high wildfire activity, highlighting indoor exposure is more strongly associated with acute respiratory health outcomes than outdoor exposure.

Since 2013, stringent clean air initiatives have significantly reduced atmospheric pollutant emissions in China, improving air quality and altering the spatiotemporal patterns of pollution. Utilizing fine particulate matter (PM_2.5) and its chemical composition data from 2000 to 2023, we observed a reduction in the disparity of PM_2.5 concentrations between urban and nonurban areas. This reduction is linked to stricter emission controls in urban areas and the relocation of some emission sources to nonurban areas. However, the specific chemical constituents of PM_2.5 and the driving factors behind these changes remain to be fully elucidated. By analyzing the proportions of PM_2.5 components in major cities such as Beijing, Shanghai, and Guangzhou and their surrounding nonurban areas, we found that the narrowing gap in PM_2.5 concentrations between urban and nonurban regions is associated with the convergence of the organic matter (OM) proportions in both areas. This convergence results from varying emission reduction strategies tailored to the distinct characteristics of urban and nonurban pollution sources in China. Coordinated governance between urban and nonurban areas should be considered, along with the implementation of integrated control and mitigation measures for multiple pollutants to further enhance air quality in China.

Quantifying changes in the properties of smoke aerosols under varying conditions is important for understanding the health and environmental impacts of exposure to smoke. Smoke composition, aerosol liquid water content, effective density (ρ_eff), and other properties can change significantly as smoke travels through areas under different ambient conditions and over time. During this study, we measured changes in smoke composition and physical properties due to oxidative aging and exposure to humidity. We found that smoke aging led to SOA formation and increases in ratios of organic carbon to elemental carbon. Aerosol liquid water content increased with increasing relative humidity (RH), and aged smoke took up more water than fresh smoke at all humidity levels, likely due to a combination of changes in aerosol surface polarity at low and medium RH and increases in surface area with aging at high RH. Growth factors ranged from 1.06 ± 0.08 for fresh smoke at low RH to 1.32 ± 0.08 for aged smoke at high RH. Oxidative aging and exposure to humidity led to increases in ρ_eff. For 100 nm particles, ρ_eff ranged from ∼1.2 for fresh smoke at low RH to ∼1.6 for aged smoke at high RH. Results from these experiments suggest that exposure to humidity leads to smoke restructuring and compaction and/or changes in surface chemistry.

Quantifying changes in the properties of smoke aerosols under varying conditions is important for understanding the health and environmental impacts of exposure to smoke. Smoke composition, aerosol liquid water content, effective density (ρ_eff), and other properties can change significantly as smoke travels through areas under different ambient conditions and over time. During this study, we measured changes in smoke composition and physical properties due to oxidative aging and exposure to humidity. We found that smoke aging led to SOA formation and increases in ratios of organic carbon to elemental carbon. Aerosol liquid water content increased with increasing relative humidity (RH), and aged smoke took up more water than fresh smoke at all humidity levels, likely due to a combination of changes in aerosol surface polarity at low and medium RH and increases in surface area with aging at high RH. Growth factors ranged from 1.06 ± 0.08 for fresh smoke at low RH to 1.32 ± 0.08 for aged smoke at high RH. Oxidative aging and exposure to humidity led to increases in ρ_eff. For 100 nm particles, ρ_eff ranged from ∼1.2 for fresh smoke at low RH to ∼1.6 for aged smoke at high RH. Results from these experiments suggest that exposure to humidity leads to smoke restructuring and compaction and/or changes in surface chemistry.

Oxidative aging and exposure to humidity lead to changes in the physical properties of smoke particles. We measured changes in composition, aerosol liquid water content, and effective density for fresh and aged smoke at three humidity levels.

Prescribed fire is applied across the United States as a fuel treatment to manage the impact of wildfires and restore ecosystems. While the recent application of prescribed fire has largely been confined to the southeastern US, the increase in catastrophic wildfires has accelerated the growth of prescribed fire more broadly. To effectively achieve wildfire risk reduction benefits, which includes reducing the amount of smoke emitted, the area treated by prescribed fire must come into contact with a subsequent wildfire. In this study, we applied timely and consistent geospatially resolved data sets of prescribed fires and wildfires to estimate the rate at which an area treated by prescribed fire encounters a subsequent wildfire. We summarize these encounter rates across time intervals, prescribed fire treatment area, and number of previous prescribed fires and by region. On all U.S. Forest Service lands across the Conterminous US (CONUS) 6.2% of prescribed fire treated area from 2003-2022 encountered a subsequent wildfire in 2004-2023. Encounter rates were highest in western US forests, which tend to be more impacted by wildfire than the eastern US, and lower in the eastern US. Encounter rates increased with treatment area in the southeastern US but were relatively flat in the northwest. For the CONUS, encounter rates increased with longer time intervals, associated with diminished potential for reducing wildfire severity, between prescribed fire and the subsequent wildfire area burned. Our results provide timely information on prescribed fire and wildfire interactions that can be leveraged to optimize analyses of the trade-offs between prescribed fire and wildfire.

Gas-phase organic acids are ubiquitous in the atmosphere with mixing ratios of several species, such as formic acid and acetic acid, often as high as several parts per billion by volume (ppbv). Organic acids are produced via photochemical reactions and are also directly emitted from various sources, including combustion, microbial activity, vegetation, soils, and ruminants. We present measurements of gas-phase formic, acetic, propionic, pyruvic, and pentanoic acids from a site near Boise, Idaho, in August 2019 made by iodide-adduct chemical ionization mass spectrometry (CIMS). The site is adjacent to a major interstate highway and beyond the urban/suburban core is surrounded by national forests to the north and northeast and by farmland to the west and south. Maximum mixing ratios of formic, acetic, propionic, and pentanoic acid were typically near 10, 3, 0.4, and 0.2 ppbv, respectively. Observed daytime concentrations of these acids were mostly consistent with other studies, but concentrations were persistently the highest at night between 20:00 to 8:00 (local standard time). Such elevated nighttime concentrations are unlike most other reported organic acid measurements. Although there were times when organic acid concentrations were enhanced by mobile source emissions, the organic acid concentrations appear to be mainly controlled by noncombustion surface primary emissions. Source apportionment by positive matrix factorization (PMF) supports the importance of significant noncombustion, nonphotochemical emissions. Two agricultural surface sources were identified and estimated to contribute to greater than half of total observed concentrations of formic and acetic acid. In contrast to the other measured organic acids, but in agreement with all other reported measurements in the literature, pyruvic acid concentrations peaked during the daytime and were largely controlled by photochemistry.

Sulfur-containing volatile organic compounds emitted during wildfire events, such as dimethyl sulfide, are known to form secondary aerosols containing inorganic sulfate (SO₄ ^2-) and surfactant-like organic compounds; however, little is known about the fate of sulfur in other emitted reduced organosulfur species. This study aimed to determine the sulfurous product distribution resulting from the nighttime oxidation of thiophene as a model system. Ion chromatography (IC) and aerosol mass spectrometry (a mini aerosol mass spectrometer, mAMS) were used to constrain the proportions of sulfurous compounds produced under wildfire-relevant conditions ([NO₂]/[O₃] = 0.1). With constraints from IC, results indicated that the sulfurous particle mass consisted of 30.3 ± 6.6% SO₄ ^2-, while mAMS fractionation attributed 24.5 ± 1.6% of total sulfate signal to SO₄ ^2-, 15.4 ± 1.9% to organosulfates, and 60.1 ± 0.9% to sulfonates. Empirical formulas of organosulfur products were identified as C1-C8 organosulfates and sulfonates using complementary mass spectrometry techniques. This study highlights the nighttime oxidation of thiophene and its derivatives as a source of SO₄ ^2- and particulate organosulfur compounds, which have important implications for the atmospheric sulfur budget and aerosol/droplet physical and chemical properties.