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Kuang, Chongai

Publications and source records attributed to Kuang, Chongai.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Tethered Balloon Observations of Vertically Resolved Aerosol Size Distributions during the U.S. DOE ARM CoURAGE and BNF Campaigns

This dataset contains vertically resolved aerosol particle number size distributions measured using a miniature Scanning Electrical Mobility Spectrometer (mSEMS) deployed aboard the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Tethered Balloon System (TBS) during the 2025 Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) and Bankhead National Forest (BNF) field campaigns. The mSEMS measured aerosol size distributions over approximately 10–300 nm during repeated TBS vertical profiles through the atmospheric boundary layer. The dataset provides measurements of particle number size distributions as a function of particle diameter, altitude, and time and supports investigation of aerosol vertical structure, elevated ultrafine and Aitken-mode particle layers, boundary-layer evolution, and residual-layer processes.

ARM↗
DOE OSTI2025

OpenCRUMS USA: An Open Machine Learning Framework for Characterizing Variability in Aerosol Reanalysis Data

Advances in artificial intelligence (AI) have called for exploring how these techniques can be used for exploring patterns in large climate datasets. To that regard, the U.S. Department of Energy AI for Earth System Predictability (AI4ESP) supported a pilot initiative called the Open Classification of Regimes in the Southeast USA (OpenCRUMS USA) project to explore how AI can be used to characterize modes of spatial variability in large climate datasets. For this study, we focus on comparing two methods for characterizing the modes of spatial variability of surface aerosol concentration over the Houston region: empirical orthogonal functions (EOFs) and layerwise relevance propagation (LRP) applied to a convolutional neural network (CNN) classifier. We show that EOF analysis typically attributes spatial variability modes that span all of southeast Texas, prohibiting the attribution of spatial variability to localized regions. However, using LRP on the CNN classifier resolves the explanatory parameters at a finer spatial resolution than EOFs. This allows for the attribution of the spatial variability of surface aerosols to local regions of organic carbon which was not possible using EOFs. In addition, the LRP analysis also suggests that synoptic-scale transport of dust is most prevalent during anticyclonic and pretrough synoptic conditions as categorized by self-organizing maps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coastal-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) Science Plan

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations regarding the impacts of climate change and associated mitigation and adaptation measures. Earth system (climate and weather) models have not yet been adapted to provide accurate predictions of climate and weather variability within cities, nor do they provide well-tested representations of the impacts of urban systems on the atmospheric environment. These limitations are largely due to limited field data available for testing and development of these models. We will deploy the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first Mobile Facility (AMF1) to the mid-Atlantic region surrounding the city of Baltimore for the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE). This deployment will create a four-node regional atmospheric observatory network including Baltimore and its three primary surrounding environments – rural, urban, and bay. CoURAGE investigators will study the interactions among the Earth’s surface, the atmospheric boundary layer, aerosols and atmospheric composition, clouds, radiation, and precipitation at each site, and examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. This study will determine the degree to which Baltimore’s atmospheric environment depends on interactive feedbacks in the atmospheric system and the degree to which conditions in Baltimore depend on the surrounding environment. Some topics of interest include how urban land management exacerbates heat waves, the impact of regional mesoscale winds (nocturnal jet, bay breeze) on urban air pollution and cloud cover, and the impact of the urban heat island and aerosol production on heavy precipitation events. Understanding this integrated coast-urban-rural system quantitatively and with good accuracy and precision is critical to informing climate adaptation and mitigation efforts in the city of Baltimore. The understanding gained should be applicable to many similar coastal, mid-latitude urban centers. Another important objective of CoURAGE is to improve the representation of the climate of coastal cities in Earth systems models (ESMs). CoURAGE investigators will use the observations to test current ESMs, identify weaknesses and work towards improved simulations of this complex environment. The ARM core facility will be deployed in the city of Baltimore, complementing the Baltimore Social-Environmental Collaborative (BSEC), a DOE urban integrated field laboratory (UIFL). Ancillary sites will be deployed to rural Maryland northwest of Baltimore, and to the southern end of Kent Island within Chesapeake Bay. The fourth node will be a long-term atmospheric observatory operated in Beltsville, Maryland by Howard University and the Maryland Department of the Environment. Measurements will be conducted for one year, starting in December of 2024. There will be two intensive operational periods (IOPs), one in summer and one in winter, when the ancillary sites will be enhanced with additional balloon launches, tethered balloon system (TBS) operation, and added atmospheric composition measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chemical Insights into the Molecular Composition of Organic Aerosols in the Urban Region of Houston, Texas

Molecular functional groups, such as organosulfates (CHOS) and organonitrates (CHNO) are important tracers for field observations of secondary organic aerosols (SOA). While CHOS and CHNO are prevalent in the atmosphere, there is a lack of knowledge regarding daily and day- and night-time variations in these species in the urban atmosphere. Meteorological factors such as wind speed/direction, relative humidity (RH), and temperature can influence the formation of CHOS/CHNO. To investigate these trends, we utilized multimodal chemical imaging and advanced high resolution mass spectrometry techniques to acquire particle speciation and molecular formulas (MFs) associated with day and night sampling periods. Back trajectory analyses revealed the oceanic influence of southern wind airmasses in later June sampling periods with organic fractions <10%. Conversely, northern winds in early June sampling periods contributed to the episodic emergence of extremely low volatile organics (ELVOCs) and organic factions up to 41%. The observed unique MFs to June 3 (223 MFs) and to June 4 (144 MFs) were largely found to be of biogenic rather than anthropogenic origin. Finally, our findings reveal episodic prevalence and temporal distribution of SOA constituents across the urban region of Houston, Texas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aerosol‐Correlated Cloud Activation for Clean Conditions in the Tropical Atlantic Boundary Layer During LASIC

Abstract Aerosol measurements during the DOE ARM Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign were used to quantify the differences between clean and smoky cloud condensation nuclei (CCN) budgets. Accumulation‐mode particles accounted for ∼70% of CCN at supersaturations <0.3% in clean and smoky conditions. Aitken‐mode particles contributed <20% and sea‐spray‐mode particles <10% at supersaturations <0.3%, but at supersaturations >0.3% Aitken particles contributions increased to 30%–40% of clean CCN. For clean conditions, the Hoppel minimum diameter was correlated to the accumulation‐mode number concentration, indicating aerosol‐correlated cloud activation was controlling the lower diameter cutoff for which particles serve as CCN. For smoky conditions, the contributions of Aitken particles increase and the correlation of cloud activation to accumulation‐mode particles is masked by the lower‐hygroscopicity smoke. These results provide the first multi‐month in situ quantitative constraints on the role of aerosol number size distributions in controlling cloud activation in the tropical Atlantic boundary layer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Boundary-Layer Gradients in New Particle Formation Field Campaign Report

Atmospheric new particle formation (NPF) followed by growth of the particles to ~50-150 nm is estimated to account for over 50% of the particles that can activate cloud droplets. As such, NPF and the subsequent growth plays a critical role in our ability to understand how aerosols affect cloud life cycle, properties, and processes and more generally the Earth’s radiative balance. NPF and growth is known to occur throughout the troposphere including in both the boundary layer and the free troposphere. The majority of NPF and growth observations, however, come from surface-based measurements within the boundary layer. Measurements of the vertical distribution of NPF and growth are sparse and thus insufficient to test many of the hypotheses that attempt to explain connections between NPF and boundary-layer transport and meteorology. The purpose of this campaign was to investigate the vertical distribution of NPF and growth at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns

Abstract. A large part of the uncertainty in climate projections comes from uncertain aerosol properties and aerosol–cloud interactions as well as the difficulty in remotely sensing them. The southeastern Atlantic functions as a natural laboratory to study biomass-burning smoke and to constrain this uncertainty. We address these gaps by comparing the Weather Research and Forecasting with Chemistry Community Atmosphere Model (WRF-CAM5) to the multi-campaign observations ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing), and LASIC (Layered Atlantic Smoke Interactions with Clouds) in the southeastern Atlantic in August 2017 to evaluate a large range of the model's aerosol chemical properties, size distributions, processes, and transport, as well as aerosol–cloud interactions. Overall, while WRF-CAM5 is able to represent smoke properties and transport, some key discrepancies highlight the need for further analysis. Observations of smoke composition show an overall decrease in aerosol mean diameter as smoke ages over 4–12 d, while the model lacks this trend. A decrease in the mass ratio of organic aerosol (OA) to black carbon (BC), OA:BC, and the OA mass to carbon monoxide (CO) mixing ratio, OA:CO, suggests that the model is missing processes that selectively remove OA from the particle phase, such as photolysis and heterogeneous aerosol chemistry. A large (factor of ∼2.5) enhancement in sulfate from the free troposphere (FT) to the boundary layer (BL) in observations is not present in the model, pointing to the importance of properly representing secondary sulfate aerosol formation from marine dimethyl sulfide and gaseous SO2 smoke emissions. The model shows a persistent overprediction of aerosols in the marine boundary layer (MBL), especially for clean conditions, which multiple pieces of evidence link to weaker aerosol removal in the modeled MBL than reality. This evidence includes several model features, such as not representing observed shifts towards smaller aerosol diameters, inaccurate concentration ratios of carbon monoxide and black carbon, underprediction of heavy rain events, and little evidence of persistent biases in modeled entrainment. The average below-cloud aerosol activation fraction (NCLD/NAER) remains relatively constant in WRF-CAM5 between field campaigns (∼0.65), while it decreases substantially in observations from ORACLES (∼0.78) to CLARIFY (∼0.5), which could be due to the model misrepresentation of clean aerosol conditions. WRF-CAM5 also overshoots an observed upper limit on liquid cloud droplet concentration around NCLD= 400–500 cm−3 and overpredicts the spread in NCLD. This could be related to the model often drastically overestimating the strength of boundary layer vertical turbulence by up to a factor of 10. We expect these results to motivate similar evaluations of other modeling systems and promote model development to reduce critical uncertainties in climate simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Measurements of aerosol microphysical and chemical properties in the central Arctic atmosphere during MOSAiC

The Arctic environment is transforming rapidly due to climate change. Aerosols’ abundance and physicochemical characteristics play a crucial, yet uncertain, role in these changes due to their influence on the surface energy budget through direct interaction with solar radiation and indirectly via cloud formation. Importantly, Arctic aerosol properties are also changing in response to climate change. Despite their importance, year-round measurements of their characteristics are sparse in the Arctic and often confined to lower latitudes at Arctic land-based stations and/or short high-latitude summertime campaigns. Here, we present unique aerosol microphysics and chemical composition datasets collected during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, in the central Arctic. These datasets, which include aerosol particle number concentrations, size distributions, cloud condensation nuclei concentrations, fluorescent aerosol concentrations and properties, and aerosol bulk chemical composition (black carbon, sulfate, nitrate, ammonium, chloride, and organics) will serve to improve our understanding of high-Arctic aerosol processes, with relevance towards improved modelling of the future Arctic (and global) climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-ACE: Aerosol Characterization Experiment Field Campaign Report

An objective for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) is to provide high-temporal-and-spatial resolution observations of convective clouds in the Houston region, over a broad range of environmental and aerosol regimes (Jensen et al. 2022). The TRACER siting strategy was to deploy the first ARM Mobile Facility (AMF1), with its full suite of cloud, aerosol, precipitation, and atmospheric state measurement capabilities, in a region that experiences the full diversity of aerosol properties from the Houston domain including rural, urban, and industrial atmospheric aerosol environments (see Figure 1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-VOC: Speciated Volatile Organic Compounds at the Tracking Aerosol Convection Interactions Experiment Field Campaign Report

Formation of secondary organic aerosol (SOA) is responsible for the growth of particles into cloud condensation nuclei (CCN)-relevant sizes and accounts for a substantial fraction of aerosol mass in the troposphere. Despite its wide abundance and importance, capturing SOA in regional and climate models is still challenging due to complex chemical transformations involved in production of SOA. Oxidation products of biogenic hydrocarbons, such as isoprene, monoterpenes, and sesquiterpenes account for the largest fraction of SOA mass over the continents. As such, biogenic SOA is an important source of continental CCN, and has been recently shown to nucleate ice in the deposition mode. To better account for the processes involved in SOA formation in global and regional climate models, we need better measurements of sources and transformations of volatile organic compounds (VOCs), the precursors to SOA formation in the atmosphere. Understanding aerosol-deep convection interactions is an important science driver of the Tracking Aerosol Convection Interactions Experiment (TRACER), requiring a characterization of the critical controls on aerosol properties and processes, and how those properties and processes vary spatially and temporally in the Houston area. In that environment, the atmospheric photo-oxidative chemistry that drives the evolution and transformation of aerosol properties and processes is strongly impacted by the emission of VOCs, which have both anthropogenic (e.g., industrial, urban, transportation, biomass burning) and biogenic (e.g., marine) sources in the region. Understanding (and disentangling) the complex role of VOCs in such a heterogenous region requires high-time-resolution, speciated VOC measurements that are spatially resolved. To meet these measurement requirements, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s time-of-flight proton transfer reaction-mass spectrometer (ToF-PTR-MS) was deployed during the TRACER intensive operational period (IOP) from June to September, 2022 at the ancillary site (ANC), which was sited to provide a characterization of the rural atmospheric environment in contrast to the main site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic warming by abundant fine sea salt aerosols from blowing snow

Abstract The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. However, the mechanisms of sea salt aerosol production remain unclear. Sea salt aerosols are typically thought to be relatively large in size but low in number concentration, implying that their influence on cloud condensation nuclei population and cloud properties is generally minor. Here we present observational evidence of abundant sea salt aerosol production from blowing snow in the central Arctic. Blowing snow was observed more than 20% of the time from November to April. The sublimation of blowing snow generates high concentrations of fine-mode sea salt aerosol (diameter below 300 nm), enhancing cloud condensation nuclei concentrations up to tenfold above background levels. Using a global chemical transport model, we estimate that from November to April north of 70° N, sea salt aerosol produced from blowing snow accounts for about 27.6% of the total particle number, and the sea salt aerosol increases the longwave emissivity of clouds, leading to a calculated surface warming of +2.30 W m −2 under cloudy sky conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ARM FY2024 Aerosol Operations Plan

The Atmospheric Radiation Measurement user facility (ARM) deploys a suite of aerosol and trace gas (further mentions of aerosols will assume inclusion of trace gases) instrumentation at each of ARM's observatories. ARM currently deploys five Aerosol Observing Systems, one each at: Southern Great Plains (SGP); Eastern North Atlantic (ENA); ARM Mobile Fabilities (AMFI 1, 2, and 3). Aerosol measurements at ARM’s North Slope of Alaska (NSA) observatory have historically been made by the National Oceanic and Atmospheric Administration (NOAA) and provided to ARM through a collaboration. As ARM’s support for aerosol instrumentation increases, it is important for ARM to communicate plans and priorities for aerosol measurements to the community to maximize the benefit and planning around scientific activities and to advance confidence in ARM’s aerosol measurements. ARM will develop a yearly aerosol operations plan for the upcoming fiscal year (October 1-September 30) starting with FY24. This plan will be open and available through the ARM aerosol instrument webpages and will include: Review of the previous activities since the last plan (in this case, 2018); Planned activities and their priorities for the upcoming FY; Calibration timing and efforts; Planned activities for data products and value-added products (VAP).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗