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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Weak influence of anthropogenic emissions on aerosol, cloud, and rain in the wet season of the Amazon rainforest

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations ( N d ) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

Wang, Xuemei [University of Leeds (United Kingdom)↗
DOE OSTI2022

Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations

In 2015 and 2016, atmospheric transport modeling challenges were conducted in the context of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) verification, however, with a more limited scope with respect to emission inventories, simulation period and number of relevant samples (i.e., those above the Minimum Detectable Concentration (MDC)) involved. Therefore, a more comprehensive atmospheric transport modeling challenge was organized in 2019. Stack release data of Xe-133 were provided by the Institut National des Radioéléments/IRE (Belgium) and the Canadian Nuclear Laboratories/CNL (Canada) and accounted for in the simulations over a three (mandatory) or six (optional) months period. Best estimate emissions of additional facilities (radiopharmaceutical production and nuclear research facilities, commercial reactors or relevant research reactors) of the Northern Hemisphere were included as well. Model results were compared with observed atmospheric activity concentrations at four International Monitoring System (IMS) stations located in Europe and North America with overall considerable influence of IRE and/or CNL emissions for evaluation of the participants’ runs. Participants were prompted to work with controlled and harmonized model set-ups to make runs more comparable, but also to increase diversity. It was found that using the stack emissions of IRE and CNL with daily resolution does not lead to better results than disaggregating annual emissions of these two facilities taken from the literature if an overall score for all stations covering all valid observed samples is considered. A moderate benefit of roughly 10% is visible in statistical scores for samples influenced by IRE and/or CNL to at least 50% and there can be considerable benefit for individual samples. Effects of transport errors, not properly characterized remaining emitters and long IMS sampling times (12–24 h) undoubtedly are in contrast to and reduce the benefit of high-quality IRE and CNL stack data. Complementary best estimates for remaining emitters push the scores up by 18% compared to just considering IRE and CNL emissions alone. Despite the efforts undertaken the full multi-model ensemble built is highly redundant. An ensemble based on a few arbitrary runs is sufficient to model the Xe-133 background at the stations investigated. The effective ensemble size is below five. An optimized ensemble at each station has on average slightly higher skill compared to the full ensemble. However, the improvement (maximum of 20% and minimum of 3% in RMSE) in skill is likely being too small for being exploited for an independent period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

China's Contribution to Arctic Black Carbon Declined From 2009 to 2022

Black carbon (BC) aerosol is an important driver of Arctic warming, and China used to be a major contributor to the Arctic BC burden through long-range atmospheric transport. Here we show that China's contribution declined significantly from 2009 to 2022, primarily due to reductions in domestic BC emissions following the implementation of clean air policies. Global chemistry-transport model simulations indicate a relative decline of ∼3% yr −1 ( p < 0.05) in China's Arctic BC contribution, exceeding the decrease rate in the underlying emission inventory. Sensitivity simulations further suggest that climate change-induced shifts in atmospheric transport may have amplified this decline. Observations of aerosol absorption coefficients (σ ap ) at Arctic background observatories revealed steeper declines in σ ap when modeled China-to-total BC ratios were higher. Moreover, σ ap correlated positively with modeled BC from China, with stronger relationships as the modeled China-to-total BC ratios increased. Together, these results provide robust evidence that China's emission reductions have diminished its role in Arctic BC, contributing an estimated 0.02 W m −2 decrease in the direct radiative effect during the Arctic haze season.

GEOS-chem model↗
DOE OSTI2021

A New Field Instrument for Leaf Volatiles Reveals an Unexpected Vertical Profile of Isoprenoid Emission Capacities in a Tropical Forest

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and moderately high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 52 tropical tree species, revealing moderate consistency in EC within taxonomic groups. We highlight priorities in leaf volatiles research that require field-portable detection systems. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol VI m -2 leaf s -1 . We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An evaluation of global organic aerosol schemes using airborne observations

Chemical transport models have historically struggled to accurately simulate the magnitude and variability of observed organic aerosol (OA), with previous studies demonstrating that models significantly underestimate observed concentrations in the troposphere. In this study, we explore two different model OA schemes within the standard GEOS-Chem chemical transport model and evaluate the simulations against a suite of 15 globally distributed airborne campaigns from 2008 to 2017, primarily in the spring and summer seasons. These include the ATom, KORUS-AQ, GoAmazon,FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC campaigns and provide broad coverage over a diverse set of atmospheric composition regimes – anthropogenic, biogenic, pyrogenic and remote. The schemes include significant differences in their treatment of the primary and secondary components of OA – a “simple scheme” that models primary OA (POA) as non-volatile and takes a fixed-yield approach to secondary OA (SOA) formation and a “complex scheme” that simulates POA as semi-volatile and uses a more sophisticated volatility basis set approach for non-isoprene SOA, with an explicit aqueous uptake mechanism to model isoprene SOA. Despite these substantial differences, both the simple and complex schemes perform comparably across the aggregate dataset in their ability to capture the observed variability (with an R2 of 0.41 and 0.44, respectively). The simple scheme displays greater skill in minimizing the overall model bias (with a normalized mean bias of 0.04 compared to 0.30 for the complex scheme). Across both schemes, the model skill in reproducing observed OA is superior to previous model evaluations and approaches the fidelity of the sulfate simulation within the GEOS-Chem model. However,there are significant differences in model performance across different chemical source regimes, classified here into seven categories.Higher-resolution nested regional simulations indicate that model resolution is an important factor in capturing variability in highly localized campaigns, while also demonstrating the importance of well-constrained emissions inventories and local meteorology, particularly over Asia. Our analysis suggests that a semi-volatile treatment of POA is superior to anon-volatile treatment. It is also likely that the complex scheme parameterization overestimates biogenic SOA at the global scale. While this study identifies factors within the SOA schemes that likely contribute to OA model bias (such as a strong dependency of the bias in the complex scheme on relative humidity and sulfate concentrations), comparisons with the skill of the sulfate aerosol scheme in GEOS-Chem indicate the importance of other drivers of bias, such as emissions, transport and deposition, that are exogenous to the OA chemical scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The Foundational Industry Energy Dataset: Unit-level Characterization and Derived Energy Estimates for Industrial Facilities in 2017

The Foundational Industry Energy Dataset (FIED) addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization by facility. Each facility is identified by a unique registryID, based on the U.S. Environmental Protection Agency (EPA) Facility Registry Service, and includes its coordinates and other geographic identifiers. Energy-using units are characterized by design capacity, as well as their estimated energy use, greenhouse gas emissions, and physical throughput using 2017 data from the EPA's National Emissions Inventory and Greenhouse Gas Reporting Program. An overview of the derivation methods is provided in a separate technical report which will be linked after publication. The Python code used to compile the dataset is available in a GitHub repository. An updated 2020 version is under development.

Array↗
DOE OSTI2022

A System for Standardizing and Combining U.S. Environmental Protection Agency Emissions and Waste Inventory Data

The U.S. Environmental Protection Agency (USEPA) provides databases that agglomerate data provided by companies or states reporting emissions, releases, wastes generated, and other activities to meet statutory requirements. These databases, often referred to as inventories, can be used for a wide variety of environmental reporting and modeling purposes to characterize conditions in the United States. Yet, users are often challenged to find, retrieve, and interpret these data due to the unique schemes employed for data management, which could result in erroneous estimations or double-counting of emissions. To address these challenges, a system called Standardized Emission and Waste Inventories (StEWI) has been created. The system consists of four python modules that provide rapid access to USEPA inventory data in standard formats and permit filtering and combination of these inventory data. When accessed through StEWI, reported emissions of carbon dioxide to air and ammonia to water are reduced approximately two- and four-fold, respectively, to avoid duplicate reporting. StEWI will greatly facilitate the use of USEPA inventory data in chemical release and exposure modeling and life cycle assessment tools, among other things. To date, StEWI has been used to build the recent USEEIO model and the baseline electricity life cycle inventory database for the Federal LCA Commons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Global methane emissions from coal mining to continue growing even with declining coal production

This paper presents projections of global methane emissions from coal mining under different coal extraction scenarios and with increasing mining depth through 2100. The paper proposes an updated methodology for calculating fugitive emissions from coal mining, which accounts for coal extraction method, coal rank, and mining depth and uses evidence-based emissions factors. A detailed assessment shows that coal mining-related methane emissions in 2010 were higher than previous studies show. This study also uses a novel methodology for calculating methane emissions from abandoned coal mines and represents the first estimate of future global methane emissions from those mines. The results show that emissions from abandoned mines increase faster than those from active ones. Using coal production data from six integrated assessment models, this study shows that by 2100 methane emissions from active underground mines increase by a factor of 4, while emissions from abandoned mines increase by a factor of 8. Abandoned mine methane emissions continue through the century even with aggressive mitigation actions.

coal mine methane, abandoned coal mine methane, em↗
DOE OSTI2020

Stable Methane Isotopologues From Northern Lakes Suggest That Ebullition Is Dominated by Sub‐Lake Scale Processes

Abstract Stable isotopes have emerged as popular study targets when investigating emission of methane (CH 4 ) from lakes. Yet little is known on how isotopic patterns conform to variations in emission magnitudes—a highly relevant question. Here, we present a large multiyear data set on stable isotopes of CH 4 ebullition (bubbling) from three small adjacent subarctic lakes. The δ 13 C‐CH 4 and δD‐CH 4 range from −78.4‰ to −53.1‰ and from −369.8‰ to −218.8‰, respectively, and vary greatly among the lakes. The signatures suggest dominant hydrogenotrophic methanogenesis, particularly in the deep zones, but there are also signals of seemingly acetoclastic production in some high fluxing shallow areas, possibly fueled by in situ vegetation, but in‐sediment anaerobic CH 4 oxidation cannot be ruled out as an alternative cause. The observed patterns, however, are not consistent across the lakes. Neither do they correspond to the spatiotemporal variations in the measured bubble CH 4 fluxes. Patterns of acetoclastic and hydrogenotrophic production plus oxidation demonstrate that gains and losses of sediment CH 4 are dominated by sub‐lake scale processes. The δD‐CH 4 in the bubbles was significantly different depending on measurement month, likely due to evaporation effects. On a larger scale, our isotopic data, combined with those from other lakes, show a significant difference in bubble δD‐CH 4 between postglacial and thermokarst lakes, an important result for emission inventories. Although this characteristic theoretically assists in source partitioning studies, most hypothetical future shifts in δD‐CH 4 due to high‐latitude lake area or production pathway are too small to lead to atmospheric changes detectable with current technology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Southern Ocean Sulfate Aerosol Sources Quantified From Sulfur Isotopes in Antarctic Ice Cores

The Southern Ocean has emerged as a key region for constraining aerosol-climate interactions due to its relatively low anthropogenic influence. Sulfate is an important aerosol over the Southern Ocean, and models suggest dimethyl sulfide (DMS) is the largest source of sulfate during summer. However, sulfur isotopes of sulfate (δ 34 S(SO 4 2− )) in Antarctic ice cores suggest a significant contribution from a previously unexplained non-DMS source. Here we show that the fractional contribution from passive volcanic degassing (f volc ) explains observed δ 34 S(SO 4 2− ), and that a global chemical transport model underestimates f volc across Antarctica. Underestimated f volc implies that the model mischaracterizes sulfate sources in this important region. The discrepancy between observed and modeled sulfate sources can be reconciled by increasing passive volcanic sulfur degassing emissions and decreasing DMS emissions. Our results imply that current biases in emissions inventories could bias assessments of aerosol-cloud interactions in the Southern Ocean region and globally.

Jongebloed, Ursula A. [Univ. of Washington, Seattl↗
DOE OSTI2024

Observational evidence for Criegee intermediate oligomerization reactions relevant to aerosol formation in the troposphere

Criegee intermediates are reactive intermediates that are implicated in transforming the composition of Earth’s troposphere and in the formation of secondary organic aerosol, impacting Earth’s radiation balance, air quality and human health. Yet, direct identification of their signatures in the field remains elusive. Here, from particulate and gas-phase mass-spectrometric measurements in the Amazon rainforest, we identify sequences of masses consistent with the expected signatures of oligomerization of the CH 2 OO Criegee intermediate, a process implicated in ozonolysis-driven aerosol formation. In this study, we assess the potential contributions of oligomerization through laboratory ozonolysis experiments, direct kinetic studies of Criegee intermediate reactions, and high-level theoretical calculations. Global atmospheric models built on these kinetics results indicate that Criegee intermediate chemistry may play a larger role in altering the composition of Earth’s troposphere than is captured in current atmospheric models, especially in areas of high humidity. However, the models still capture only a relatively small fraction of the observed signatures, suggesting considerable underestimates of Criegee intermediate concentrations and reactivity and/or the dominance of other, presently uncharacterized, oxidation mechanisms. Resolving the remaining uncertainties in emission inventories and the effects of atmospheric water vapour on key chemical reactions will be required to definitively assess the role of Criegee intermediate oligomerization reactions.

58 GEOSCIENCES↗
DOE OSTI2023

Measurement, reporting and Verification (MRV) of non-CO 2 greenhouse gases: International Best Practices and Suggestions for China

Measurement, Reporting, and Verification (MRV) is a systematic approach to tracking and documenting greenhouse gas (GHG) emissions and emission reductions. MRV can be used across all sectors and for all GHGs to track emissions patterns, evaluate programs, and promote transparency. As methane and other short-lived climate pollutants become critical to mitigating near-term climate change impacts, MRV systems become critical in improving emission inventories; facilitating the development of climate change policies and targets, and tracking and demonstrating progress towards sustainable development. This report focuses on current sectoral issues – including the emerging roles for satellites and remote sensing technologies - and international best practices in MRV policies and programs for non-carbon dioxide (CO 2 ) GHGs including methane, nitrous oxide (N 2 O), and hydrofluorocarbons (HFCs) in specific sectors. Based on international best practices and a review of China’s current MRV system, we offer suggestions for a possible path forward for developing and implementing a stronger non-CO 2 MRV system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Exploration of oxidative chemistry and secondary organic aerosol formation in the Amazon during the wet season: explicit modeling of the Manaus urban plume with GECKO-A

The GoAmazon 2014/5 field campaign took place in Manaus, Brazil, and allowed the investigation of the interaction between background-level biogenic air masses and anthropogenic plumes. We present in this work a box model built to simulate the impact of urban chemistry on biogenic secondary organic aerosol (SOA) formation and composition. An organic chemistry mechanism is generated with the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to simulate the explicit oxidation of biogenic and anthropogenic compounds. A parameterization is also included to account for the reactive uptake of isoprene oxidation products on aqueous particles. The biogenic emissions estimated from existing emission inventories had to be reduced to match measurements. The model is able to reproduce ozone and NO x for clean and polluted situations. The explicit model is able to reproduce background case SOA mass concentrations but does not capture the enhancement observed in the urban plume. The oxidation of biogenic compounds is the major contributor to SOA mass. A volatility basis set (VBS) parameterization applied to the same cases obtains better results than GECKO-A for predicting SOA mass in the box model. The explicit mechanism may be missing SOA-formation processes related to the oxidation of monoterpenes that could be implicitly accounted for in the VBS parameterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Implications of reduced-complexity aerosol thermodynamics on organic aerosol mass concentration and composition over North America

Atmospheric organic aerosol (OA) mass concentrations can be affected by water uptake through its impact on the gas–particle partitioning of semi-volatile compounds. Current chemical transport models (CTMs) neglect this process. We have implemented the Binary Activity Thermodynamics model coupled to a volatility basis set partitioning scheme in the GEOS-Chem CTM, providing an efficient reduced-complexity OA model that predicts relative-humidity-dependent mixing and partitioning thermodynamics, while limiting the impact on computational efficiency. We provide a quantitative assessment of this water-sensitive OA treatment, focusing on a subdomain over North America. The updated OA scheme predicts a spatiotemporal mean enhancement in surface-level OA mass concentration of 145 % for January 2019 and 76 % for July 2019 compared to GEOS-Chem's most advanced OA scheme. The temporal mean surface-level OA organic mass concentration can increase by up to ∼590 % for January 2019 and ∼280 % for July 2019, with the greatest enhancements occurring over the ocean. The updated OA scheme also quantifies the OA-associated water content. The simulations show how different OA precursors and related OA surrogates contribute and respond to water uptake, including that due to changes in temperature and relative humidity over the diurnal cycle in selected winter and summer months. These results are independent of future CTM improvements involving updates to chemical reaction schemes and emission inventories. Our water-sensitive OA scheme allows for a better representation of the seasonal and regional variations in OA mass concentration in CTMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Airborne flux measurements of ammonia over the southern Great Plains using chemical ionization mass spectrometry

Abstract. Ammonia (NH3) is an abundant trace gas in the atmosphere and an important player in atmospheric chemistry, aerosol formation and the atmosphere–surface exchange of nitrogen. The accurate determination of NH3 emission rates remains a challenge, partly due to the propensity of NH3 to interact with instrument surfaces, leading to high detection limits and slow response times. In this paper, we present a new method for quantifying ambient NH3, using chemical ionization mass spectrometry (CIMS) with deuterated benzene cations as reagents. The setup aimed at limiting sample–surface interactions and achieved a 1σ precision of 10–20 pptv and an immediate 1/e response rate of < 0.4 s, which compares favorably to the existing state of the art. The sensitivity exhibited an inverse humidity dependence, in particular in relatively dry conditions. Background of up to 10 % of the total signal required consideration as well, as it responded on the order of a few minutes. To showcase the method's capabilities, we quantified NH3 mixing ratios from measurements obtained during deployment on a Gulfstream I aircraft during the HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems) field campaign in rural Oklahoma during May 2016. Typical mixing ratios were 1–10 parts per billion by volume (ppbv) for the boundary layer and 0.1–1 ppbv in the lower free troposphere. Sharp plumes of up to tens of ppbv of NH3 were encountered as well. We identified two of their sources as a large fertilizer plant and a cattle farm, and our mixing ratio measurements yielded upper bounds of 350 ± 50 and 0.6 kg NH3 h−1 for their respective momentary source rates. The fast response of the CIMS also allowed us to derive vertical NH3 fluxes within the turbulent boundary layer via eddy covariance, for which we chiefly used the continuous wavelet transform technique. As expected for a region dominated by agriculture, we observed predominantly upward fluxes, implying net NH3 emissions from the surface. The corresponding analysis focused on the most suitable flight, which contained two straight-and-level legs at ∼ 300 m above ground. We derived NH3 fluxes between 1 and 11 mol km−2 h−1 for these legs, at an effective spatial resolution of 1–2 km. The analysis demonstrated how flux measurements benefit from suitably arranged flight tracks with sufficiently long straight-and-level legs, and it explores the detrimental effect of measurement discontinuities. Following flux footprint estimations, comparison to the NH3 area emissions inventory provided by the U.S. Environmental Protection Agency indicated overall agreement but also the absence of some sources, for instance the identified cattle farm. Our study concludes that high-precision CIMS measurements are a powerful tool for in situ measurements of ambient NH3 mixing ratios, and even allow for the airborne mapping of the air–surface exchange of NH3.

58 GEOSCIENCES↗
DOE OSTI2022

Airborne flux measurements of ammonia over the Southern Great Plains using chemical ionization mass spectrometry

Ammonia (NH 3 ) is an abundant trace gas in the atmosphere and an important player in atmospheric chemistry, aerosol formation and the atmosphere-surface exchange of nitrogen. It is recognized as a major source of aerosol pollution, and it may limit the formation of cloud nuclei in remote or cold parts of the atmosphere. For soil and plants, NH 3 -mediated nitrogen can act as a harmful pollutant or as a desirable nutrient, mostly in natural and agricultural settings, respectively. Agriculture is also the main source of atmospheric NH 3 via volatilization from fertilizers and manure processing in livestock farming. The accurate determination of NH 3 emission rates remains a challenge, partly due to the propensity of NH 3 to interact with instrument surfaces leading to high detection limits and slow response times. In this paper, we present a new method for quantifying ambient NH 3 , using chemical ionization mass spectrometry (CIMS) with deuterated benzene cations as reagents. The setup aimed at limiting sample-surface interactions and achieved a 1-σ precision of 10–20 pptv and an immediate 1/e response rate < 0.4 s, which compares favorably to the existing state of the art. The sensitivity exhibited an inverse humidity dependence, in particular in relatively dry conditions. Background of up to 10 % of the total signal required consideration as well, as it responded on the order of a few minutes. To showcase the method’s capabilities, we quantified NH3 mixing ratios from measurements obtained during deployment on a Gulfstream I aircraft during the HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems) field campaign in rural Oklahoma during May 2016. Typical mixing ratios were 1–10 parts per billion by volume (ppbv) for the boundary layer and 0.1–1 ppbv in the lower free troposphere. Sharp plumes of up to 10s of ppbv of NH3 were encountered as well. We identified two of their sources as a large fertilizer plant and a cattle farm, and our mixing ratio measurements yielded upper bounds of 350 ± 50 and 0.6 kg NH 3 h –1 for their respective momentary source rates. The fast response of the CIMS also allowed us to derive vertical NH 3 fluxes within the turbulent boundary layer via eddy covariance, for which we chiefly used the continuous wavelet transform technique. As expected for a region dominated by agriculture, we observed predominantly upward fluxes, implying net NH 3 emissions from surface. The corresponding analysis focused on the most suitable flight, which contained two straight-and-level legs at ~300 m above ground. We derived NH 3 fluxes between –4 and 18 mol km –2 h –1 for these legs, at an effective spatial resolution of 1–2 km. The analysis demonstrated how flux measurements benefit from suitably arranged flight tracks with sufficiently long straight-and-level legs, and explores the detrimental effect of measurement discontinuities. Following flux footprint estimations, comparison to the NH 3 area emissions inventory provided by the US Environmental Protection Agency indicated overall agreement, but also the absence of some sources, for instance the identified cattle farm. Our study concludes that high-precision CIMS measurements are a powerful tool for in-situ measurements of ambient NH 3 mixing ratios, and even allow for the airborne mapping of the air-surface exchange of NH 3 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud condensation nuclei concentrations derived from the CAMS reanalysis

Determining number concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, and a process key for aerosol–cloud interactions (ACI). However, due to sparse coverage of in situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source as well as temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN numbers is one of the goals for quantifying ACI processes and achieving uncertainty-reduced estimates of their associated radiative forcing. Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models. The emitted aerosols in CAMSRA are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Furthermore, the reanalysis interpolates for cases of poor or missing retrievals and thus allows for a full spatiotemporal quantification of CCN numbers. The derived CCN dataset captures the general trend and spatial and temporal distribution of total CCN number concentrations and CCN from different aerosol species. A brief evaluation with ground-based in situ measurements demonstrates the improvement of the modelled CCN over the sole use of AOD as a proxy for CCN as the overall correlation coefficient improved from 0.37 to 0.71. However, we find the modelled CCN from CAMSRA to be generally high biased and find a particular erroneous overestimation at one heavily polluted site which emphasises the need for further validation. The CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1, Block, 2023), which is now freely available to users, features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years 2003–2021 with daily frequency. This dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry–meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM 2.5 ). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O 3 , sulfate, nitrate, ammonium, elemental carbon, tropospheric O 3 residual, and column nitrogen dioxide (NO 2 ). For example, the mean biases have been reduced by more than 10 W m –2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O 3 . However, relatively large biases still exist for cloud predictions, some PM 2.5 species, and PM 10 that warrant follow-up studies to better understand those issues. The impacts of chemistry–meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O 3 , nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM 2.5 by 3.1 % (up to 27.8 %), 4.2 % (up to 16.2 %), 6.6 % (up to 50.9 %), 5.8 % (up to 46.6 %), and 8.6 % (up to 49.1 %), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

58 GEOSCIENCES↗