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At least 55 records · Page 3

Benchmarking greenhouse gas emissions from US wastewater treatment for targeted reduction

Here, in this study, to assess the national climate impact of wastewater treatment and inform decarbonization, we assembled a comprehensive greenhouse gas inventory of 15,863 facilities in the contiguous USA. Considering location and treatment configurations, we modelled on-site CH 4 , N 2 O and CO 2 production and emissions associated with energy, chemical inputs and solids disposal. Using Monte Carlo simulations, we estimated median national emissions at 47 million tonnes of CO 2 equivalent per year, with on-site process CH 4 and N 2 O emissions exceeding current government estimates by 41%. Treatment configurations with anaerobic digesters are responsible for 16 million tonnes of CO 2 equivalent per year of fugitive methane, outweighing benefits achieved through on-site electricity generation. Systems designed for nutrient removal have the highest greenhouse gas emissions intensity, attributable to energy requirements and N 2 O production, demonstrating current trade-offs between meeting water quality and climate objectives. We analysed key sensitivities and included a geospatial analysis to highlight the scale and distribution of opportunities for reducing life cycle greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

Nitrate loading projection is sensitive to freeze-thaw cycle representation

Climate change can have substantial impacts on nitrogen runoff, which is a major cause of eutrophication, harmful algal blooms, and hypoxia in freshwaters and coastal regions. We examined responses of nitrate loading to climate change in the Upper Mississippi River Basin (UMRB) with an enhanced Soil and Water Assessment Tool with physically based Freeze-Thaw cycle representation (SWAT-FT), as compared with the original SWAT model that employs an empirical equation. Driven by future climate projections from five General Circulation Models (GCMs) from 1960 to 2099 under the Representative Concentrations Pathways (RCP) 8.5 scenario, we analyzed changes in riverine nitrate loadings, as well as terrestrial surface and subsurface contributions of the UMRB in the 21st century relative to the baseline period of 1960–1999. By the end of the 21st century, the original SWAT model predicted about a 50% increase in riverine nitrate loadings which is nearly twice as much as that estimated by SWAT-FT (ca. 25%). Such a large difference in projected nitrate changes can potentially mislead mitigation strategies that aim to reduce nitrogen runoff from the UMRB. Further analysis shows that the difference between the original SWAT model and SWAT-FT led to substantial discrepancies in the spatial distribution of surface and subsurface nitrate loadings in the UMRB. In general, SWAT-FT predicted more nitrate leaching for northwestern parts of the UMRB which are more sensitive to freeze-thaw cycle, mainly because SWAT-FT simulated less frequent frozen soils. This study highlights the importance of using physically based freeze-thaw cycle representation in water quality modeling. Design of future nitrogen runoff reduction strategies should include careful assessment of effects that land management has on the freeze-thaw cycles to provide reliable projection of water quality under climate change.

Wang, Qianfeng↗

Health and air pollutant emission impacts of net zero CO2 by 2050 scenarios from the energy modeling forum 37 study

Carbon dioxide and non-greenhouse gas air pollutants are emitted from many of the same sources. Decarbonization actions thus typically yield air pollutant emission reductions, resulting in significant air quality benefits. Although several studies have highlighted this connection, including in the context of net zero carbon emission targets, substantial uncertainty remains regarding how alternative technological pathways to this goal will affect the spatial distribution and magnitude of air pollutants. Comprehensive multi-model and multi-scenario analyzes are needed to explore the relative impacts of alternative pathways. Here, our study begins to address this gap by leveraging the results from the recent Energy Modeling Forum 37 inter-model comparison exercise on U.S. decarbonization pathways. Comparing the results of the six teams who submitted air pollutant emissions suggests that strategies that target net zero U.S. carbon emissions would yield significant reductions in many air pollutants, and that this finding is generally robust across pathways. However, some energy sources, such as biomass and fossil fuels with carbon capture, will emit air pollutants and can potentially influence the magnitude, spatial distribution, and even sign of localized air pollutant emission changes. In the second part of this analysis, a simplified air quality and health impacts screening model is used to evaluate the air quality impacts in 2035 of sectoral emission changes from the three models that provided sectoral detail. Relative to a reference scenario, a net zero pathway is estimated to reduce fine particulate matter concentrations across the contiguous U.S., with health benefits from reduced mortality ranging from $\$$65 billion to $\$$250 billion in 2035 alone (2023$\$$s). These benefits would be expected to grow over time as the net zero trajectory becomes more stringent. Both the magnitude of potential benefits and the substantial variation of the projections across models underscore the need for an EMF-like inter-model comparison exercise focused on air quality.

Air pollutants↗

A systematic review of machine learning in groundwater monitoring

With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.

AI/ML↗

Susceptibility of new soil organic carbon to mineralization during dry-wet cycling in soils from contrasting ends of a precipitation gradient

The persistence of soil organic carbon (SOC) is influenced by soil physicochemical properties, organic matter quality, and climatic conditions that govern its vulnerability to microbial activity. We compared the susceptibility of newly formed SOC to mineralization in two soils (Andosols) that developed under contrasting precipitation regimes. Soil from the high rainfall region (‘high rain ’) had higher SOC and lower iron concentrations than soils exposed to less rainfall (‘low rain ’). We amended soils with 13 C-labeled carbohydrates and measured the amount of substrate-derived SO 13 C mineralized when exposed to dry-wet cycling following months-long incubations. We hypothesized that susceptibility would differ due to iron content and mineralogy, initial SOC, substrate solubility (cellulose versus glucose amendment), and microbial substrate use efficiency (SUE). We found that SO 13 C was less susceptible to dry-wet cycling when more 13 C was assimilated into microbial biomass and co-localized with mineral surfaces than when co-localized with existing organo-mineral surfaces, according to microscale NanoSIMS imaging. Considerably less SO 13 C was susceptible to mineralization in the ferrihydrite-rich (low SOC) low rain soil than the leached (high SOC) high rain soil when C was added as either glucose (7.3-fold less C mineralized) or cellulose (15.2-fold less). Additionally, the SUE of glucose was comparable to cellulose in low rain soil where SO 13 C was less water soluble and coprecipitated with ferrihydrite, and used half as efficiently as cellulose in high rain soil. Our results show that the susceptibility of newly formed SOC to mineralization is modified by the effects of bioavailability on microbial metabolism and the availability of mineral surfaces for forming new organo-mineral complexes.

21 NanoSIMS↗

Online detection of airborne nanoparticle composition with mass spectrometry: Recent advances, challenges, and opportunities

Airborne nanoparticles are receiving growing attention due to their impacts on human health, air quality, and climate. Additionally, there are increasing applications of aerosol-based nanotechnology. Real-time measurement of airborne nanoparticle composition is challenging due to their small masses and the difficulties in effectively separating them from larger particles. Custom-built instruments based on mass spectrometry have been developed for nanoparticle composition, including thermal desorption-based, laser-based, and solution-based techniques. They have significantly promoted the understanding of airborne nanoparticles in the last two decades. However, they are affected by molecular fragmentation, lack of mass-resolving power, incomplete species detection, and difficulties in directly comparing to gas-phase measurements. Recent developments in atmospheric mass spectrometry provide possible solutions. Here, this review presents the potential application of these new advances to real-time measurements of the molecular nanoparticle composition and discusses the associated challenges. Such measurements present opportunities for a more comprehensive view of airborne nanoparticles and their impacts.

47 OTHER INSTRUMENTATION↗

Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms

Atmospheric chemical reactions play an important role in air quality and climate change. While the structure and dynamics of individual chemical reactions are fairly well understood, the emergent properties of the entire atmospheric chemical system, which can involve many different species that participate in many different reactions, are not well described. In this work, we leverage graph-theoretic techniques to characterize patterns of interaction (“motifs”) in three different representations of gas-phase atmospheric chemistry, termed “chemical mechanisms.” These widely used mechanisms, the master chemical mechanism, the GEOS-Chem mechanism, and the Super-Fast mechanism, vary dramatically in scale and application, but they all generally aim to simulate the abundance and variability of chemical species in the atmosphere. This motif analysis quantifies the fundamental patterns of interaction within the mechanisms, which are directly related to their construction. For example, the gas-phase chemistry in the very small Super-Fast mechanism is entirely composed of bimolecular reactions, and its motif distribution matches that of an individual bimolecular reaction well. The larger and more complex mechanisms show emergent motif distributions that differ strongly from any specific reaction type, consistent with their complexity. The proposed motif analysis demonstrates that while these mechanisms all have a similar design goal, their higher-order structure of interactions differs strongly and thus provides a novel set of tools for exploring differences across chemical mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Crust Formation Controls Evaporation Kinetics of Secondary Organic Aerosols

Gas-particle partitioning is critical for the evolution of secondary organic aerosols (SOA) in the atmosphere. SOA particles evaporate more slowly than expected at nearly size-independent rates, but the underlying mechanism remains controversial. Here, in this study, we apply kinetic multilayer modeling to simulate evaporation of α-pinene SOA, demonstrating that surface crust formation, emerging from accumulation of low-volatility compounds at the particle surface, leads to slow evaporation and reduced size dependence of the evaporation rate. While evaporation induced by decomposition of oligomers would naturally lead to size-independent evaporation rates, we observe and simulate nearly size-independent slow evaporation of polyethylene glycol mixture particles containing polymeric species that do not decompose, confirming the relevance of composition-dependent diffusivity for size-independent, slow evaporation. Slow evaporation of limonene SOA was also observed in environmental chamber experiments, and model simulations demonstrate strong surface crust formation with bulk diffusivity being depressed by up to 5 orders of magnitude compared to the inner bulk. We present experimental evidence using a surface-based mass spectrometry technique that shows that the particle surface becomes enriched in high molecular weight compounds upon evaporation of monomers. Our findings imply that viscous surface crusts may also limit the growth and chemical transformation of SOA particles, influencing their impacts on air quality and climate.

heterogeneous chemistry↗

Wildland Urban Interface (WUI) Emissions: Laboratory Measurement of Aerosol and Trace Gas from Combustion of Manufactured Building Materials

Wildfires are increasing in intensity and more often threatening the wildland urban interface (WUI) where buildings and homes coexist with the natural environment. WUI emissions have not been as well-studied as emissions from vegetation. Thus, there is a need to quantify the emissions of building materials used in home construction under flaming and smoldering conditions to study their impacts to human health, visibility, air quality, and climate. Here, in a controlled laboratory setting, we quantify emissions of aerosols and trace gases including formaldehyde, particulate matter, and black carbon. We focus on the combustion of traditional single-source wood-based construction fuels. Our results indicate that, similar to natural fuels, the aerosol optical properties were more related to combustion conditions than the fuel type. Overall, we observed significant variability in the gas and particle emissions. Consistent trends include high formaldehyde (HCHO) and carbon monoxide (CO) emissions for smoldering conditions and higher carbon dioxide (CO 2 ), nitrogen oxides (NO x ), and black carbon for flaming conditions. Finally, these observations highlight the need to better characterize emissions for materials in the built environment to assess large-scale climate and human health impacts of fires at the WUI.

54 ENVIRONMENTAL SCIENCES↗

Predicting Liquid–Liquid Phase Separation of Submicrometer Proxies for Atmospheric Secondary Aerosol

Liquid–liquid phase separation (LLPS) of atmospheric aerosols can significantly impact climate, air quality, and human health. However, their complex composition, small size, and history-dependent properties result in great uncertainty in the modeling of aerosol phase state and atmospheric processes. Herein, using cryogenic transmission electron microscopy (cryo-TEM), we examined model submicron aerosols composed of organic compounds and ammonium sulfate, and established a parameterization for the separation relative humidity (SRH) that accounts for chemical composition, particle size, and equilibration time. We evaluated different variables that describe chemical composition: O/C ratio, partition coefficient, solubility, molar mass, and polarizability. The O/C ratio fits the SRH of micrometer droplets best, and by using a scaling factor to translate the micrometer SRH parameterization to submicron aerosols, we incorporate the effects of size and equilibration time. The measured scaling factor for the submicron mean SRH (30nm – 1μm, 20 min equilibration times) is 0.80, the factor becomes 1 with equilibration time over 1 hour, and is equal to 0, meaning that SRH is absent, when the aerosol dry diameter is smaller than 30 nm. Furthermore, our parameterization will aid in universal SRH modeling, potentially leading to more accurate predictions of aerosol mass, optical properties, hygroscopicity, and heterogeneous chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Near-canopy horizontal concentration heterogeneity of semivolatile oxygenated organic compounds and implications for 2-methyltetrols primary emissions

Semivolatile oxygenated organic compounds (SV-OVOCs) are important atmospheric species, in particular for the production and chemistry of atmospheric particulate matter and related impacts on air quality and climate. In this study, SV-OVOCs were collected in the horizontal plane of the roughness layer over the tropical forest in the central Amazon during the wet season of 2018. A sampler mounted to a copter-type, hovering unmanned aerial vehicle was used. Underlying the collection region, a plateau forest transitioned into a slope forest across several hundred meters. The concentrations of pinonic and pinic acids, which are monoterpene oxidation products, had no statistical difference over the two forests. By comparison, across the study period, differences in the concentration of 2-methyltetrols, which are products of isoprene oxidation, ranged from -70% to +480% over the two forests. The chemical lifetime of 2-methyltetrols in the atmosphere is sufficiently long that heterogeneity in the isoprene emission rate from the two forests followed by atmospheric oxidation does not explain the concentration heterogeneity of 2-methyltetrols. Standing waves and local meteorology also cannot account for the heterogeneity. Of the possibilities considered, the most plausible explanation is the direct emission from the forest of 2-methyltetrols produced through biological processes within the plants. Under this explanation, the rate of direct SV-OVOC emissions should be modulated by forest type and related environmental stressors. Direct emissions of SV-OVOCs should be more broadly considered for constraining and improving models of atmospheric composition, transport, and chemistry over tropical forests.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Haze processing of atmospheric particles during wintertime in the Indo-Gangetic Plains

The impacts of haze on visibility, air quality, and climate are not well quantified due to a lack of understanding of the evolution of the mixing state and phase state of atmospheric particles during haze processing. The variability of the mixing state of atmospheric particles contributes significantly to uncertainties associated with the estimated aerosol radiative forcing. We collected particle samples in January 2018 from the highly polluted Indo-Gangetic plain during hazy conditions to study haze-processed particles. Single particle analysis using multi-modal micro-spectroscopy techniques revealed an abundance (40–70% by number) of potassium-rich sulfate particles from biomass-burning influenced smoke. Tilted view imaging showed that most of the organic particles that had inorganic potassium and sulfate inclusions were liquid-like while those without inclusions were more semi-solid. High-resolution mass spectrometry analysis revealed a significant presence of organosulfates and nitroxy-organosulfates in the morning samples (24%) compared to the afternoon samples (9%), despite higher relative humidity in the afternoon. Overall, our results highlight the significant contribution of both organic and inorganic sulfate to the total particulate sulfur budget during haze processing in winter, when anthropogenic emissions such as household burning, agricultural burning, and vehicular emissions are major contributors to particle mass.

Mathai, Susan [Pacific Northwest National Laborato↗

Air quality and public health co-benefits of 100% renewable electricity adoption and electrification pathways in Los Angeles

To demonstrate how a mega city can lead in decarbonizing beyond legal mandates, the city of Los Angeles (LA) developed science-based, feasible pathways towards utilizing 100% renewable energy for its municipally-owned electric utility. Aside from decarbonization, renewable energy adoption can lead to co-benefits such as improving urban air quality from reductions in combustion-related emissions of oxides of nitrogen (NO x ), primary fine particulate matter (PM 2.5 ) and others. Herein, we quantify changes to air pollutant concentrations and public health from scenarios of 100% renewable electricity adoption in LA in 2045, alongside aggressive electrification of end-use sectors. Our analysis suggests that while ensuring reliable electricity supply, reductions in emissions of air pollutants associated with the 100% renewable electricity scenarios can lead to 8% citywide reductions of PM 2.5 concentration while increasing ozone concentration by 5% relative to a 2012 baseline year, given identical meteorology conditions. The combination of these concentration changes could result in net monetized public health benefits (driven by avoided deaths) of up to $\$$1.4 billion in year 2045 in LA, results potentially replicable for other city-scale decarbonization scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

54 ENVIRONMENTAL SCIENCES↗

The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA)

To explore the various couplings across space, time and between ecosystems in a consistent manner, atmospheric modeling is moving away from the fractured limited-scale modeling strategy of the past towards a unification of the range of scales inherent in the Earth System. This paper describes the forward-looking MUlti-Scale Infrastructure for Chemistry and Aerosols (MUSICA), which is intended to become the next generation community infrastructure for research involving atmospheric chemistry and aerosols. MUSICA will be developed collaboratively by the National Center for Atmospheric Research (NCAR) and university and government researchers, with the goal of serving the international research and applications communities. The capability of unifying various spatio-temporal scales, coupling to other Earth System components and process-level modularization will allow advances in both fundamental and applied research in atmospheric composition, air quality and climate and is also envisioned to become a platform that addresses the needs of policy makers and stakeholders.

Pfister, Gabriele G.↗

Distributed Renewables for Arctic Energy: A Case Study

Alaska is a vast state that stretches into the Arctic Circle. Roughly 140,000 people in the state are dependent on isolated electric grids, traditionally burning expensive fossil fuels. This has negative impacts on air quality and climate. As the climate warms, fuel supply chains and traditional ways of life are threatened. Renewable electric sources offer a clean, resilient alternative with less volatile costs, but there are a variety of technical, social, economic, and political challenges to developing renewable energy systems in remote Arctic communities. Examples include harsh operating conditions, lack of local technical and managerial capacity, complex funding mechanisms, and glacial permitting processes. In this study, we interview one group of communities that are interested in adding renewable energy to their systems to understand the needs and challenges they face, and then another group that has successfully installed renewable energy, to understand how they overcame such challenges and the lessons they learned. Notable results include the importance of local buy-in, education, and technical involvement, procuring external funding sources, inter-community collaboration, installing bespoke systems, and working with reliable equipment suppliers. The goal of this report is to orient and inspire Arctic communities that want to begin their renewable transition, by providing helpful examples and points of contact.

17 WIND ENERGY↗

Chicago Energy Efficiency Planning and Analysis and Integrated Retrofit Strategy Validation in Single-Family Homes

In June 2020, the project team comprised of Elevate and the National Renewable Energy Laboratory (NREL), with advisory roles from the City of Chicago and Commonwealth Edison, initiated a three-year project with the U.S. Department of Energy to inform communitywide energy planning at a local scale and validate advanced retrofit packages that achieve at least 50% energy savings in existing homes. The project team has characterized Chicago’s single-family and 2-4 unit housing stock and energy use using the ResStock™ modeling tool, and with that information developed advanced whole home energy retrofit packages for single family and 2-4 unit homes that can reduce energy use by at least 50% and support climate, air quality, and other goals. This report presents an analysis of the technical potential of applying these retrofit packages at a City-wide scale, and a roadmap for rapidly scaling up retrofit programs to improve Chicago’s housing stock and target investments in the neighborhoods that need it most. The main goals of the analysis are to: 1) develop a Chicago-specific single-family and 2-4 unit building retrofit prioritization strategy; 2) identify opportunities for beneficial electrification in communities and home types that stand to benefit most; and 3) assess costs and savings potential for retrofit investments at a household and city scale, in terms of energy use, bill impacts, carbon emissions, and other outcomes.

14 SOLAR ENERGY↗