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At least 883 records · Page 49

Recovery of Oxpure 612C-50 Coconut Carbon Particles Using Bump Arrays

Cyanide is used to leach gold from crushed ore (solid matrix) into a gold cyanide solution. The gold is extracted from the cyanide solution by adsorption onto activated carbon. The gold extraction process occurs when the activated coconut carbon is placed into tanks that contain the gold cyanide solution either in a batch process or into a continuous flow circuit. The coconut carbon is then removed from the solution for gold recovery. The use of the mesofluidic separation system (a deterministic lateral displacement system) can significantly reduce costs and waste generated from the process of removing the coconut carbon from the solution. In the coconut carbon recovery process used at many gold mines in Nevada, the gold is attached to carbon particles that are still in the cyanide liquor. The mesofluidic system can rapidly remove the gold bearing carbon particles from the cyanide liquor quickly and with no operating costs. The benefits include: • Reduce operational costs related to filtration and hydro-cyclones • Reduced acid usage for the elution gold stripping phase as only 25% of the fluids will follow the carbon particles to the final express lane when two mesofluidic systems are used in series This alternative particle removal techniques would be advantageous. A promising technique for removing larger particles from slurries is mesofluidic separation, similar to deterministic lateral displacement arrays or “bump” arrays [1] but operates at much larger flow rates. As described by Pease, et al. [2], “Bump arrays in deterministic lateral displacement devices separate large particles from small particles using arrays of staggered posts. Large particles, defined as those with radii larger than the distance between the edge of a post and the stagnation streamline from the next downstream post, must bump toward one side of the device, whereas particles smaller than this distance slalom from entrance to exit without net lateral displacement.” Unlike filters or sieves, the posts in the arrays that cause separation do not block or occlude particle flow but work because particles go around the posts. Unlike hydrocyclones separation, separation is not driven by particle density, because gravitational forces are unimportant to mesofluidic separation. Burns, et al., and Pease, et al., have shown that particles may be separated from complex suspensions, under turbulent flow conditions, and at industrially important flow rates [3-5]. They have also recently shown that mesofluidic devices may be arranged in series to increase separation performance [6]. In this paper, we evaluate the mesofluidic system for the separation of commercial OxPure GR 612 Charred Coconut shell particles as a proof of principle test for the rapid separation using the 1500 micron cut mesofluidic separator. We first describe the experimental system and conditions. We then present the experimental results. [1] Huang, L.R., E.C. Cox, R.H. Austin, J.C. Sturm. 2004. Continuous particle separation through deterministic lateral displacement. Science, 304, 987–990. https://doi.org/10.1126/science.1094567. [2] Pease L.F., J.A. Bamberger, C.A. Burns, and M.J. Minette. 2021. Large Particle Separation from Non-Newtonian Slurries using Bump Arrays. In Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting FEDSM2021-65904, V003T08A023. New York, New York: ASME. doi:10.1115/FEDSM2021-65904 [3] Burns C.A., T.G. Veldman, J. Serkowski, R.C. Daniel, X.-Y. Yu, M.J. Minette, L.F. Pease. 2021. Mesofluidic separation versus dead-end filtration. Separation and Purification Technology, 254, 117256. https://doi.org/10.1016/j.seppur.2020.117256. [4] Pease L.F., J.E. Serkowski, T.G. Veldman, J. Williams, X.-Y. Yu, M.J. Minette, J.A. Bamberger, C.A. Burns. 2021. Can Bump Arrays Separate Particles from Turbulent Flows?. In Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting FEDSM2021-67696, V003T08A024. New York, New York: ASME. doi:10.11

mesofluidic separation, slurry, bump array↗

Monitoring changes in human activity during the COVID-19 shutdown in Las Vegas using infrasound microbarometers

While studies of urban acoustics are typically restricted to the audio range, anthropogenic activity also generates infrasound (<20 Hz, roughly at the lower end of the range of human hearing). Shutdowns related to the COVID-19 pandemic unintentionally created ideal conditions for the study of urban infrasound and low frequency audio (20–500 Hz), as closures reduced human-generated ambient noise, while natural signals remained relatively unaffected. An array of infrasound sensors deployed in Las Vegas, NV, provides data for a case study in monitoring human activity during the pandemic through urban acoustics. The array records a sharp decline in acoustic power following the temporary shutdown of businesses deemed nonessential by the state of Nevada. This decline varies spatially across the array, with stations close to McCarran International Airport generally recording the greatest declines in acoustic power. Further, declines in acoustic power fluctuate with the time of day. As only signals associated with anthropogenic activity are expected to decline, this gives a rough indication of periodicities in urban acoustics throughout Las Vegas. This study's results reflect the city's response to the pandemic and suggest spatiotemporal trends in acoustics outside of shutdowns.

58 GEOSCIENCES↗

Temperature uncertainty modelling with proxy structural data as geostatistical constraints for well siting: an example applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural geology information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aims of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations. The data used to support the modelling are measured temperatures and structural proxies from 3D geologic modelling (distance to fault, distance to fault intersections and terminations, Coulomb stress change and dilation tendency), the latter considered ‘secondary’ data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally-likely temperature models (i.e. realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: V prior and entropy. V prior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because of the dipping ellipsoid shape created and that the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e. linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g. dilation v. distance to fault termination) should be used given the specific geothermal system. In general, V prior from local varying mean results identify locations that are close to high values for the structural proxies: areas with higher probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comparison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

15 GEOTHERMAL ENERGY↗

geothermal_osr (Energy Predictor for Geothermal Open Source Reservoir) [SWR-22-23]

This is a repository with the tools developed for predicting energy produced at Open-Source Reservoir (OSR). It includes both simulation data for OSR, as well as Jupyter notebooks for training and evaluating prediction models. OSR was constructed based on the data from Brady Hot Springs reservoir (Nevada, USA) but has a number of sufficiently modified characteristics and does not disclose any sensitive data.

Duplyakin, Dmitry↗

NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]

NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.

Egerer, Ulrike↗

Established Regulatory Limits for Surface Water and Groundwater

The regulatory limits for surface water and groundwater contained in this database comprise chemical-specific preliminary remediation goals (PRGs) based on potential Applicable or Relevant and Appropriate Requirements (ARARs). These values should be used in conjunction with PRGs based on risk assessment to ensure that the PRGs for a site meet the residual risk requirements for protection of human health and the environment in the National Oil and Hazardous Substance Pollution Contingency Plan (NCP). In some cases, the values presented in this database may be To-Be-Considered (TBC) Guidance because these values are superseded by site-specific state requirements. ARARs are available for the Federal government, California, Georgia, Illinois, Kentucky, New Jersey, New Mexico, Nevada, New York, Ohio, South Carolina, Tennessee, Washington, and Wisconsin. The dataset provides maximum contaminant levels for drinking water and water quality criteria for fresh and marine environments based on acute and chronic exposures. Users can select ARAR sources, drinking water standards and water quality standards, individual chemicals, and retrieve results in tabular or spreadsheet formats for analysis. ARARs are derived from authoritative sources, including federal and state government agencies. The dataset supports environmental risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against promulgated standards. This structured approach ensures a robust evaluation of environmental risks tailored to regulatory needs.

Stewart, Debra [Oak Ridge National Laboratory (ORN↗

Detecting Rain–Snow-Transition Elevations in Mountain Basins Using Wireless Sensor Networks

Here, to provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins.

54 ENVIRONMENTAL SCIENCES↗

Response of U.S. West Coast Mountain Snowpack to Local Sea Surface Temperature Perturbations: Insights from Numerical Modeling and Machine Learning

Sea surface temperature (SST) significantly modulates the precipitation and temperature over land, with important consequences on land surface processes such as snowpack. Compared to the impact of remote SST, the effect of nearshore/local SST is less well understood. In this study, the impact of local SST on the mountain snowpack of the U.S. West Coast is investigated using two 6-km regional climate simulations driven by the same lateral boundary conditions but with time-varying versus time-invariant and warmer local SSTs during 2003–15. Results show that local SST warming leads to warmer winter with more precipitation over the mountains. Meanwhile, the removal of SST temporal variability results in reduced temperature variability but increased precipitation variability. As a result, winter snow accumulation decreases by ~200 mm per season in the Cascade Mountains in the north but increases by ~100 mm per season in the Sierra Nevada in the south. Such a dipole response results from the competing effects of precipitation and temperature change at different elevations and are amplified by the enhanced atmospheric river moisture transport. To further delineate the relative contributions of different meteorological factors to the snowpack response, two neural network models were developed to predict the snow behaviors at seasonal and monthly scales. These models reveal the dominant influence of the total amount and the average temperature of precipitation on the snowpack response. Furthermore, these findings highlight the sensitivity of mountain snowpack to local SST in the western United States and underscore the importance of local SST and atmospheric rives to accurate snowpack estimations for water management.

54 ENVIRONMENTAL SCIENCES↗

Building Parameters in Las Vegas

Csv files for 132 NUDAPT-defined building parameters for census tracts in Las Vegas, Nevada along with a reference shapefile

Sweet, Levi↗

Preliminary RAM-RODD results for the MUSiC subcritical configurations

The Measurement of Uranium Subcritical and Critical (MUSiC) was performed at the DOE’s National Criticality Experiments Research Center (NCERC) located in the Nevada National Security Site (NNSS). The measurement utilized the Rocky Flats shells to perform benchmark measurements of similar highly enriched uranium (HEU) systems that span a wide range of reactivities. The Rocky Flats (RF) shells are 93.16% U-235 enriched metal hemishells that can be stacked concentrically. Ten configurations were measured with effective multiplication factors spanning between deeply subcritical (~ 0.64) through delayed critical. Details of the measured configurations are listed in Table 1. This unique set of measurements with its large span of reactivies is being used to determine the range over which neutron noise techniques such as Feynman variance-to-mean, Rossi-alpha, and pulsed neutron source techniques can be accurately employed for a bare HEU system. The results of the measurements will be published as a benchmark in The International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The results will support the growing amount of subcritical benchmark data, such as the SCRaP measurements, that is available to the community. The measurements were performed using several different detector systems for the purposes of cross-validation and obtaining detector independent results. Four detector systems were deployed, three by the NCERC team and one from the University of Michigan. The detector systems included a Neutron Multiplicity Array Detector (NoMAD) system (similar to the MC-15), four small volume 0.635 cm (Ø) × 7.59 cm 3 He detectors (ideal for measuring prompt neutron decay constants due to their fast recovery speed), the Rossi Alpha Measurements – Rapid Organic (n, γ) Discrimination Detector (RAM-RODD), and the Organic Scintillator Array (OSCAR). RAM-RODD is an array of eight 5.08 cm (Ø) × 5.08 cm EJ-309 organic scintillator detectors. OSCAR is a University of Michigan system and is an array of twelve 5.08 cm (Ø) × 5.08 cm stilbene detectors. Details of measurements performed with OSCAR will be discussed in a separate talk. The focus of this work is preliminary results obtained by RAM-RODD for the 8 subcritical configurations. Additional details on the measurements and on the setup and deployment of RAM-RODD will be discussed. Preliminary neutron noise analysis results including Rossi-alpha and Feynman-alpha will also be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

2005 Tahoe Regional Household Travel Survey

The 2005 Tahoe Regional Household Travel Survey is a comprehensive survey of the travel patterns of households in the Tahoe Basin region of California and Nevada. The survey was conducted for the Tahoe Regional Planning Agency over a four-month period, from June through September 2005. This collection contains two sets of travel data: 1) a survey of 1,220 permanent households within the Tahoe Basin region and 2) a subset survey of 125 seasonal households within the same area. The permanent resident dataset contains information about 2,732 household members, 2,471 vehicles, and 11,048 trips made during a 24-hour period. The seasonal resident subset features 726 trip observations and information about 229 household members and 185 vehicles. The survey relied on the willingness of study area residents to 1) provide demographic information about their household, its members, and its vehicles and 2) document all travel for each household member, regardless of age, over an assigned 24-hour period. During the recruitment phase, respondents were asked to provide detailed household information, including permanent or seasonal resident status, number of household occupants, type of dwelling unit, number of vehicles available to household members, as well as the year, body type, and fuel type of each vehicle. Survey participants received mailed travel logs to aid in documenting travel information for the 24-hour assessment period. Respondents were instructed to record their mode of transportation, trip purpose, number of passengers, departure and arrival times, activities at each trip destination, ride fare, and parking costs. Demographic information for this study includes age, gender, income, education, and employment status.

1Hz data↗

2005 Washoe County Travel Characteristics Study

The primary objective of the 2005 Washoe County Travel Characteristics Study was to document travel behavior data characteristics of regional households in Washoe County, Nevada, in order to update the regional transportation model. The household travel survey, which was conducted from October through November, was one of several surveys conducted in the fall of 2005 for the Regional Transportation Commission (RTC) of Washoe County, with the other surveys focusing on documenting transit usage, visitor travel behavior, and external travel through the region. The data collected were drawn from 1,174 households within the RTC planning area and contain information about 2,679 household members, 2,138 vehicles, and 11,077 unlinked trips. The household travel survey entailed the collection of activity and travel information for all household members regardless of age during a specific 24-hour period. The survey relied on the willingness of regional households to 1) provide demographic information about their household, its members, and its vehicles and 2) have all household members record all travel and activity for a specific 24-hour period, including address information for all locations visited, trip purpose, mode, and travel times.

1Hz data↗

Blodgett Forest CA Warming Experiment Soil Gas Well Data March 2014 to June 2017

These are soil gas data from the whole soil profile warming experiment at the University of California Blodgett Forest Research Station, in the Sierra Nevada foothills near Georgetown, CA at 1370 m above sea level. Mean annual precipitation is 1774 mm with most of it occurring from November through April and mean annual temperature is about 12.5°C . The experiment is in a thinned 80-year-old stand of mixed conifers including ponderosa pine (Pinus ponderosa), sugar pine (Pinus lambertiana), incense cedar (Calodefrus decurrens), white fir (Abies concolor), and douglas fir (Pseudotsuga menziesii). The soils are Holland series: fine-loamy, mixed, superactive, mesic Ultic Haploxeralfs of granitic origin with thick, >5 cm O horizons, minimal carbonates , and a pH that ranges from 5.6 to 6.5. The warming experiment warms the top meter of the soil profile to +4°C above ambient. These data include depth-resolved measurements of CO2 concentrations, 13CO2, apparent respiration quotients, soil temperature, and soil moisture (VWC). These data can be used to model CO2 production rates across the soil profile or to track how the sources and processes contributing to soil respiration change seasonally and with warming.

13C↗

Data from : "Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter". Blodgett warming experiment

This dataset contains data used for the paper: Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biology and Biochemistry 156, 108185. doi:10.1016/j.soilbio.2021.108185On April 2018 (after 4.5 years of warming), we collected O-horizon (organic horizon) material and soil core down to 90 cm depth from a whole-soil warming experiment in a mixed-coniferous temperate forest, located at the University of California Blodgett experimental forest in the foothills of the Sierra Nevada, CA USA. The goal was to assess how 4.5 years of +4 °C whole-soil warming affected the quantity and quality of soil organic matter. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This dataset contains a compressed (.zip) archive of the data used for this manuscript. The dataset includes files in .xlsx format, which can be accessed and processed using MS Excel or R. Carbon and nitrogen concentrations, as well as stable carbon isotope composition ((δ13C) and solvent extractable lipid biomarker (alkanoic acids and alkanes) data are provided as processed data files. Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy data are provided as raw output and processed data files.The dataset files "Blodgett_warming_Data" and "Blodgett_warming_raw_data.xlsx" were updated on July 7, 2021. The following updates were made: (1) specification of the units of measurements in the dataset (the unit of measurement was missing in some parameters) and (2) the column name "pulled depth" was changed to "pooled depth" in the updated data files.

54 ENVIRONMENTAL SCIENCES↗

Blodgett Forest CA Warming Experiment phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers data 2018 from: "Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil".

This data package contains phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers data used for the paper: “Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil”. SOIL, https://doi.org/10.5194/soil-2021-14.On April 2018 (after 4.5 years of warming), we collected soil cores down to 90 cm depth from the whole soil profile warming experiment at the University of California Blodgett Forest Research Station, in the Sierra Nevada foothills near Georgetown, CA at 1370 m above sea level. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This data package includes a file in .csv format and a file in .xlsx format, which can be accessed and processed using MS Excel or R. Phospholipid fatty acid and branched glycerol dialkyl glycerol tetraethers concentrations are provided as processed data files.

54 ENVIRONMENTAL SCIENCES↗

Benzene polycarboxylic acids, lignin and hydrolysable lipids data from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: "Rapid loss of complex polymers and pyrogenic carbon in subsoils under whole soil warming"

This data package contains benzene polycarboxylic acids, lignin and hydrolysable lipids data used for the paper: “Rapid loss of subsoil plant-derived polymers and pyrogenic carbon with whole-soil warming”.On April 2018 (after 4.5 years of warming), we collected soil cores down to 90 cm depth from the whole soil profile warming experiment at the University of California Blodgett Forest Research Station, in the Sierra Nevada foothills near Georgetown, CA at 1370 m above sea level. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth. This data package includes a file in .csv format and a file in .xlsx format, which can be accessed and processed using MS Excel or R. Benzene polycarboxylic acid, lignin and hydrolysable lipid concentrations are provided as processed data files.The aim of the measurements was to assess how +4°C of whole-soil warming for 4.5 years will affect structurally complex polymeric compounds at different soil depths. The research was supported by Swiss National Science Foundation (SNF) project 172744 (DEEP C) and U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under contract number DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Data used for Figure 3 of the Nature Reviews Earth and Environment (NREE) paper: "A low-to-no snow future and its impacts on water resources in the western United States

In order to synthesize western United States snowpack projections, this dataset contains the results of 18 peer-review journal articles over three periods of interest (2025-2049, 2050-2074, and 2075-2099) and over 4 mountain ranges (Cascades, Sierra Nevada, Rockies, Wasatch/Uinta) in addition to western-US wide projections. Distinction is made by model type (Earth System Models, bias-corrected statistically downscaled Earth System Models, and regional climate models). RCP4.5 and RCP8.5 emission scenarios are considered. Percent snow water equivalent (SWE) loss considers 1 April, peak SWE and/or seasonal SWE. Heterogeneity in projected snowpack changes exists across mountain ranges and for different modeling approaches, but generally indicate agreement in decreases by the end of the century.

54 ENVIRONMENTAL SCIENCES↗