ACS ES&T Air最新文献

This study estimates ground-level fine particulate matter (PM_2.5) concentrations using geostationary satellites-derived Aerosol Optical Depth (AOD) and radiance measurements and meteorological parameters from the High-Resolution Rapid Refresh (HRRR) model, with AirNow PM_2.5 measurements over the contiguous United States (CONUS). A Deep Neural Network (DNN) was adopted and compared with other machine learning (ML) models (i.e., Random Forest and Light Gradient-Boosting Machine) to estimate surface PM_2.5 concentrations. The DNN model (without the tropospheric emissions: monitoring of pollution (TEMPO); 1 year) estimated PM_2.5 with an interquartile range (IQR) of 4.32 μg/m³, and outperformed ML models, with up to 44.68% better index of agreement (IOA) and 45.28% smaller relative root-mean-square error (rRMSE), particularly in high PM_2.5 cases. The hourly estimated PM_2.5 closely matched the observed PM_2.5 in both temporal trend and spatial distribution across the eastern CONUS. ML modeling was further enhanced to include TEMPO Level 1b (L1b) data. The DNN model with TEMPO improved performance, with an 8% higher R² and a 25% lower rRMSE than the DNN model without TEMPO. The more significant improvement was seen during high smoke events using the TEMPO data. For the first time, we demonstrate the use of TEMPO L1b spectrally resolved radiances data to capture high PM_2.5 concentrations during the wildfire events, enhancing our understanding of PM_2.5 dynamics. This study provides a framework to integrate data from multiple geostationary satellites with HRRR model outputs to estimate surface air quality at high temporal resolution.

This study provides enhanced PM_2.5 monitoring estimated through deep neural networks, particularly during wildfire events, and supporting public health responses.

Inhaling smoke PM_2.5 can lead to acute health effects like asthma and lung irritation, making it essential to estimate smoke exposure on short time scales. Epidemiological studies that assess these effects need daily, fire-specific ground-level PM_2.5 data, and missing emission information can lead to underestimates. This paper presents a method to estimate daily fire-specific PM_2.5 smoke concentrations in the western United States from 2007 to 2019. Our model uses fire characteristics (e.g., fuel type, fire size, and distance) and updated fire emission inputs in an atmospheric dispersion model to simulate where smoke travels and at what concentration. We then apply a Bayesian time-series model to ground-based EPA monitors to isolate the smoke-specific portion of total PM_2.5, accounting for meteorology and season. This approach allows us to assess spatial variation in smoke exposure and investigate the role of fire attributes. For example, Lindon, UT experienced 398 fires with modest average concentrations (∼2 μg m³), while Carson City, NV saw fewer fires (177) but more intense exposures (∼6 μg m³, max 159 μg m³). These contrasts highlight the value of linking fire characteristics to daily exposure in health studies and underscore the need to consider transported smoke in fire management strategies.

Submicron particles (PM₁) play a crucial role in air quality and human health. This study investigates the influence of long-range transport (LRT) on urban aerosol levels in Leipzig, Germany, using high-resolution aerosol mass spectrometry measurements at two sites: an urban traffic site (Eisenbahnstrasse, Eiba) and a rural background site (Melpitz), located ∼50 km apart. The sites were analyzed during winter 2017 under two dominant wind regimes: East and West. These sites were directly linked to each other, which was supported by cross-correlation analysis, with a typical time lag of −2 h in East and +4 h in West. Eastern winds brought higher concentrations (Melpitz: 35.50 μg m^–3, Eiba: 37.47 μg m^–3), while Western winds led to cleaner conditions. After being corrected for time lag, the Urban Increment (UI) was estimated, showing that during Eastern wind, only ∼9% of PM₁ mass measured at Eiba was attributed to urban sources, highlighting the dominant contribution of regionally transported aerosol. Furthermore, source apportionment of organic aerosol (OA) identified five major factors─three primary OA and two oxygenated OA─at both sites. The findings underscore the significant role of regional pollution in shaping urban air quality and the need for cross-border emission reduction strategies.

The findings of this study highlight the issue of long-range transport (LRT) aerosols from Eastern Europe and their impact on urban air quality in Eastern Germany.

Carbonyls and small organic acids are ubiquitous in indoor and outdoor atmospheres; carbonyls also have significant health implications. In this study, we validate a rapid, simple, and cost-effective method for carbonyl and small organic acids quantification by ultraviolet–visible (UV–vis) spectroscopy detection after derivatizing the C═O moiety with 2,4-dinitrophenylhydrazine (DNPH). The spectroscopic method is benchmarked against accurate mass speciation by using high-performance liquid chromatography coupled to high-resolution mass spectrometry (HPLC-HRMS). Complex natural mixtures relevant to indoor and outdoor air quality were examined: electronic (e-) cigarette aerosols from nicotine and cannabinoid sources, woodsmoke aerosols, and secondary organic aerosols from limonene ozonolysis. The spectroscopy method measured the UV–vis absorption of quinoidal ions, formed from DNPH hydrazones in alkaline solution, at 530 nm (A₅₃₀). A significant correlation was established between the two methods across a range of aerosol mass and chemical compositions tested, resulting in a recommended calibration factor (CF) of ∼5.16–5.34 × 10^–5 (M cm), where C_carbonyls (M) = A₅₃₀ × CF (M cm) × path length^–1 (cm^–1). The calibration factors, determined via two approaches─(1) by measuring the effective molar absorptivity of quinoidal ions produced from eight carbonyl-DNPH and acid-DNPH calibration standards, and (2) empirically from the correlation data without assumptions, were in good agreement with one another. The simple UV–vis spectroscopic method was a robust total carbonyl quantification method for multiple aerosol systems of environmental interest, which has utility in functional group apportionment, teaching laboratories, student projects, and preliminary screenings of carbonyl-related toxicity prior to more-detailed analyses.

Cloud droplets are known to effectively chemically process water-soluble organic compounds. Field measurements clearly show that concentrations of organic compounds measured in cloudwater can deviate significantly from predictions made with Henry’s law, with high enrichments measured for less water-soluble organic compounds. Several processes are suspected to be the cause of the observed enrichments, but the key process has not yet been elucidated. Here, we use the bulk-interface partitioning approach to predict enrichment coefficients (q) of organic compounds in cloud droplets. A predictive equation is derived as a function of the bulk-interface partition coefficients (K_p) and octanol–water partition coefficients (K_ow). The calculated enrichments are compared to measured q values from different field campaigns. The results show that the predicted values follow the same trend and absolute values as the measurements. Highly water-soluble compounds have small enrichments, with values around 1, while less soluble compounds have very high enrichments of up to >10³. A sensitivity study is performed for the range of K_ow values obtained from different models, and for the range of measurements for different measurement conditions. The results of the sensitivity study show that the q measurements and predictions lie within the same range, thus showing that bulk-interface partitioning can be a good predictor for organic enrichments in cloudwater.

This study presents a new approach describing the deviations of organic concentrations in cloudwater from Henry’s law using bulk-interface partitioning. This approach provides a simple but accurate estimation of the enrichment of various organic compounds in cloud droplets.

The agricultural sector significantly contributes to atmospheric pollution, impacting air quality through activities such as tillage, planting, fertilizer application, harvesting, crop residue burning, and grain handling. The outcome of this work is the documentation of the emission inventory of particulates (PM₁₀ and PM_2.5) and gaseous emissions (SO₂, CO, NO_x, NH₃, and volatile organic compounds (VOCs)) from the agricultural industry, particularly crop production. Further, the emissions of elemental carbon (EC), organic carbon (OC), and polycyclic aromatic hydrocarbons (PAHs), which are part of particulate matter (PM), were calculated along with greenhouse gases (CO₂, CH₄, and N₂O) coming from the agricultural sector for 2021, with projections for 2051. Total greenhouse gas emissions in 2021 were 408 Tg, while PM₁₀ and PM_2.5 emissions were approximately 2.5 and 1.1 Tg, respectively. The health impact of primary agricultural PM_2.5 was quantified, revealing an estimated approximately 4 million disability-adjusted life years (DALYs) and 0.13 million deaths attributable to these emissions in 2021. The findings highlight the urgent need to reduce emissions at their source and ensure sustainable agricultural practices. This study provides critical data for policymakers to address air quality and health challenges. Furthermore, the developed emission inventory will serve as a valuable resource for researchers conducting air quality modeling and environmental impact assessments.

Despite decades of ongoing mitigation efforts, ozone (O₃) levels remain persistently high in Houston, TX. For a high O₃ episode observed during the NASA Tracking Aerosol Convection Interactions ExpeRiment-Air Quality (TRACER-AQ) campaign, we use a high-resolution large-eddy simulation (LES) within the Weather Research and Forecasting model coupled with Chemistry (WRF-LES-Chem) to investigate temporal and spatial variations in O₃ formation regimes over the region. By leveraging improved simulations of O₃ and its precursors by LES, compared to the mesoscale WRF model, we derive and compare two O₃ sensitivity indicators: the formaldehyde-to-nitrogen dioxide ratio (FNR) and the ratio of radical loss via NO_X reactions to total primary radical production (L_N/Q). Specifically, we use L_N/Q to inform the threshold for FNR, the latter being a more commonly used and accessible indicator, although it is subject to significant uncertainties. We demonstrate that O₃ production in the Houston urban area transitions from a nearly homogeneous early morning VOC-limited regime to a NO_X-limited regime by midday. Using the L_N/Q indicator, we identify that a range of 0.6 < FNR < 1.8 falls in the transition zone of O₃ formation regime. The high-resolution modeling of O₃ formation and the FNR range developed in this LES study offers valuable insight for assessing future air quality and improving the understanding of atmospheric chemistry that underpins pollution control in Houston.

The oil sands (OS) region in Canada hosts one of the world’s largest unconventional crude oil deposits in the form of bitumen, which, when extracted, generates substantial tailings/wastewater that are stored in on-site ponds. Naphthenic acid fractional compounds (NAFCs), a complex mixture of alkyl-substituted acyclic and cycloaliphatic organic acids, are natural bitumen components known for their ecological toxicity and are concentrated during the extraction process into tailings ponds, where they are assumed to remain confined to the aqueous phase. Here, we quantify the emissions of up to 275 NAFCs to the atmosphere from a tailings pond and from facility-wide operations at major OS facilities. The results indicate that, despite the absence of NAFC air emissions in inventories, large quantities are emitted to the atmosphere, likely originating from surface photochemical and/or biodegradation processes. Emission rates across entire operations ranged from 3509 to 7286 kg h^–1, translating to annual emissions of 1163–2660 tonnes from both primary and secondary sources. The findings imply that NAFC air emissions may serve as a key pathway for these chemicals to enter the environment, potentially impacting downwind ecosystems.

Harmful chemicals called NAFCs found in bitumen were thought to remain in tailings ponds water. However, this study shows that large amounts─up to 2660 tonnes per year─escape into the atmosphere from Oil Sands operations

We present the seasonal variations of enhancement ratios (ERs, i.e., ΔNO_x/ΔCO₂ and ΔCO/ΔCO₂) as a function of distance from highways in the San Francisco Bay Area, using observations from the Berkeley Environmental Air Quality and CO₂ Network (BEACO₂N) at 40 locations. The spatial patterns exhibit exponential distance-decay relationships, with higher NO_x and CO ERs near highways and more uniform ERs at distances beyond 3 km. These patterns are used to infer emission factors (EFs) for transportation and residential buildings. BEACO₂N-derived EFs for CO (7.8 ± 0.6 ppbv/ppmv) and NO_x (1.0 ± 0.02 ppbv/ppmv) from transportation agree with inventory estimates. In contrast, the residential NO_x EF (0.15 ± 0.01 ppbv/ppmv) is four times lower than inventory estimates, and the residential CO EF (4.3 ± 0.3 ppbv/ppmv) is 33% lower than the California state inventory estimate.

Reactive oxygen species (ROS) play a central role in the chemical aging of organic aerosols and adverse aerosol health effects upon respiratory deposition. Previous research has shown that biogenic secondary organic aerosols (SOA) form ROS, including hydroxyl radicals and superoxide, via reactions of reactive compounds, including organic hydroperoxides and alcohols in the aqueous phase. However, the influence of oxidative aging and the SOA oxidation state on the ROS yield has not been systematically investigated. In this study, we quantify ROS yields in d-limonene SOA and β-caryophyllene SOA generated via ^•OH and ^•Cl oxidation in an oxidation flow reactor at equivalent atmospheric aging times ranging from 4 h to 22 days. We quantify radical formation using electron paramagnetic resonance spectroscopy combined with a spin-trapping technique and characterize the molecular composition of the SOA samples with high-resolution mass spectrometry. We observe maximum radical formation at an oxygen-to-carbon ratio (O/C) of ∼0.5. Thereafter, we observe a >90% decrease in radical yield as the O/C increases to 1.2 for both d-limonene SOA and β-caryophyllene SOA. Similarly, the radical yield in d-limonene and β-caryophyllene SOA is reduced by >80% after on-filter photoirradiation. Peroxide yields are found to decrease with increasing O/C values and irradiation, suggesting that the aging-induced fragmentation and/or photolysis of hydroperoxides contribute to a decrease of radical formation in aged SOA.