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Integrated Approach to Investigating Historic Cemeteries

Ground-penetrating radar (GPR) and terrestrial laser scanning (TLS) surveys were conducted at a historic cemetery at Cape Canaveral Air Force Station, Florida, U.S., in order to confirm the presence of burials corresponding to grave markers and detect potential unmarked burials. Noise in the GPR data from surface features and subtle terrain differences must be addressed to determine the extent of anomalies of interest. We use singular value decomposition (SVD) to isolate and remove energy from GPR data. SVD allows one to remove unwanted signals that traditional processing techniques cannot. With SVD filtering, we resolve an anomaly adjacent to confirmed burials otherwise overprinted by unwanted signal. The migration of SVD-filtered data produces more distinct, spatially constrained point reflectors. Ground elevation is derived from georeferenced TLS data and compared to that from airborne laser scanning (ALS) to highlight subtle terrain that can assist data interpretation. TLS elevations show a subtle modern mound over the burial plot where ALS elevations show a depression. The targets of interest are approximately 20–30 cm higher in elevation if a topographic correction is performed using TLS versus ALS. In archaeological applications, a notable change is often recorded at the sub-meter scale. The combined approach presented here better resolves geophysical response of buried features and their positions in the ground relative to each other.

Downs, Christine (ORCID:0000000237229381)↗

Wildfire Smoke Adjustment Factors for Low-Cost and Professional PM 2.5 Monitors with Optical Sensors

Air quality monitors using low-cost optical PM 2.5 sensors can track the dispersion of wildfire smoke; but quantitative hazard assessment requires a smoke-specific adjustment factor (AF). This study determined AFs for three professional-grade devices and four monitors with low-cost sensors based on measurements inside a well-ventilated lab impacted by the 2018 Camp Fire in California (USA). Using the Thermo TEOM-FDMS as reference, AFs of professional monitors were 0.85 for Grimm mini wide-range aerosol spectrometer, 0.25 for TSI DustTrak, and 0.53 for Thermo pDR1500; AFs for low-cost monitors were 0.59 for AirVisual Pro, 0.48 for PurpleAir Indoor, 0.46 for Air Quality Egg, and 0.60 for eLichens Indoor Air Quality Pro Station. We also compared public data from 53 PurpleAir PA-II monitors to 12 nearby regulatory monitoring stations impacted by Camp Fire smoke and devices near stations impacted by the Carr and Mendocino Complex Fires in California and the Pole Creek Fire in Utah. Camp Fire AFs varied by day and location, with median (interquartile) of 0.48 (0.44–0.53). Adjusted PA-II 4-h average data were generally within ±20% of PM 2.5 reported by the monitoring stations. Adjustment improved the accuracy of Air Quality Index (AQI) hazard level reporting, e.g., from 14% to 84% correct in Sacramento during the Camp Fire.

47 OTHER INSTRUMENTATION↗

Omega-3 fatty acids attenuate cardiovascular effects of short-term exposure to ambient air pollution

Background: Exposure to air pollution is associated with elevated cardiovascular risk. Evidence shows that omega-3 polyunsaturated fatty acids (omega-3 PUFA) may attenuate the adverse cardiovascular effects of exposure to fine particulate matter (PM 2.5 ). However, it is unclear whether habitual dietary intake of omega-3 PUFA protects against the cardiovascular effects of short-term exposure to low-level ambient air pollution in healthy participants. In the present study, sixty-two adults with low or high dietary omega-3 PUFA intake were enrolled. Blood lipids, markers of vascular inflammation, coagulation and fibrinolysis, and heart rate variability (HRV) and repolarization were repeatedly assessed in 5 sessions separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily PM 2.5 and maximum 8-h ozone (O 3 ) concentrations were obtained from nearby air quality monitoring stations. Linear mixed-effects models were used to assess the associations between air pollutant concentrations and cardiovascular responses stratified by the omega-3 intake levels. Results: The average concentrations of ambient PM 2.5 and O 3 were well below the U.S. National Ambient Air Quality Standards during the study period. Significant associations between exposure to PM 2.5 and changes in total cholesterol, von Willebrand factor (vWF), tissue plasminogen activator, D-dimer, and very-low frequency HRV were observed in the low omega-3 group, but not in the high group. Similarly, O 3 -associated adverse changes in cardiovascular biomarkers (total cholesterol, high-density lipoprotein, serum amyloid A, soluable intracellular adhesion molecule 1, and vWF) were mainly observed in the low omega-3 group. Lag-time-dependent biphasic changes were observed for some biomarkers. Conclusions: This study demonstrates associations between short-term exposure to PM 2.5 and O 3 , at concentrations below regulatory standard, and subclinical cardiovascular responses, and that dietary omega-3 PUFA consumption may provide protection against such cardiovascular effects in healthy adults.

59 BASIC BIOLOGICAL SCIENCES↗

The influence of dietary intake of omega-3 polyunsaturated fatty acids on the association between short-term exposure to ambient nitrogen dioxide and respiratory and cardiovascular outcomes among healthy adults

Background: Short-term exposure to ambient nitrogen dioxide (NO 2 ) is associated with adverse respiratory and cardiovascular outcomes. Supplementation of omega-3 polyunsaturated fatty acids (PUFA) has shown protection against exposure to fine particulate matter. This study aims to investigate whether habitual omega-3 PUFA intake differentially modify the associations between respiratory and cardiovascular responses and short-term exposure to ambient NO 2 . Methods: Sixty-two healthy participants were enrolled into low or high omega-3 groups based on their habitual omega-3 PUFA intake. Each participant was repeatedly assessed for lung function, blood lipids, markers of coagulation and fibrinolysis, vascular function, and heart rate variability (HRV) in up to five sessions, each separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily ambient NO 2 concentrations were obtained from an area air quality monitoring station on the day of outcome assessment (Lag0), 4 days prior (Lag1-4), as well as 5-day moving average (5dMA). The associations between short-term exposure to NO 2 and the measured indices were evaluated using linear mixed-effects models stratified by omega-3 levels and adjusted by covariates including relative humidity and temperature. Results: The average concentration of ambient NO 2 during the study periods was 5.3±3.8 ppb which was below the National Ambient Air Quality Standards (NAAQS). In the high omega-3 group, an interquartile range (IQR) increase in short-term NO 2 concentrations was significantly associated with increased lung function [e.g. 1.2% (95%CI: 0.2%, 2.2%) in FVC at lag1, 2.6% (95%CI: 0.4%, 4.8%) in FEV1 at 5dMA], decreased blood lipids [e.g. -2.6% (95%CI: -4.4%, -0.9%) in total cholesterol at lag2, -3.1% (95%CI: -6.1%, 0.0%) in HDL at 5dMA, and -3.1% (95%CI: -5.5%, -0.7%) in LDL at lag2], improved vascular function [e.g. 8.9% (95%CI: 0.6%, 17.2%) increase in FMD and 43.1% (95%CI: -79.8%, -6.3%) decrease in endothelin-1 at 5dMA], and changed HRV parameters [e.g. -7.2% (95%CI: -13.6%, -0.8%) in HFn and 13.4% (95%CI: 0.2%, 28.3%) in LF/HF ratio at lag3]. In the low omega-3 group, an IQR increase in ambient NO 2 was associated with elevations in coagulation markers (von Willebrand Factor, D-dimer) and a decrease in HRV (very-low frequency); however, null associations were observed between short-term NO 2 exposure and changes in lung function, blood lipids, and vascular function. Conclusions: The results in this study imply that dietary omega-3 PUFA consumption may offer respiratory and vascular benefits in response to short-term exposure of healthy adults to NO 2 levels below the NAAQS.

54 ENVIRONMENTAL SCIENCES↗

2021 Annual Site Environmental Report

This report provides the U.S. Department of Energy (DOE) and the public with information on the level of radioactive and non-radioactive pollutants (if any) that are added to the environment as a result of Princeton Plasma Physics Laboratory’s (PPPL) operations. The results of PPPL’s 2021 environmental surveillance and monitoring program are presented and discussed. The report also summarizes environmental initiatives, assessments, and community involvement programs that were undertaken in 2021. PPPL’s on-site operations were significantly curtailed in 2021 due to the global coronavirus pandemic. PPPL has engaged in fusion energy research since 1951. The Laboratory’s mission is to develop the scientific knowledge and advanced engineering to enable fusion to power the U.S. and the world, and to developing the understanding of plasmas from the nano- to the astrophysical scale. PPPL’s primary experiment, the National Spherical Torus Experiment-Upgrade (NSTX-U) is a collaboration among national laboratories, universities, and national and international research institutions and is a major element in the US Fusion Energy Sciences Program. Its design tests the physics principles of spherical torus (ST) plasmas, playing an important role in the development of smaller, more economical fusion reactors. Due to previous operational issues, NSTX-U did not operate in 2021. PPPL is engaged in a project to replace key NSTX-U components and systems to enable operation of this international fusion user facility. In 2021, PPPL’s radiological environmental monitoring program measured tritium in the air at the NSTX-U Stack and at onsite sampling stations. Using highly sensitive air monitors, PPPL is capable of detecting small changes in the ambient levels of tritium. The operation of an in-stack monitor located on D-site is used to demonstrate compliance with the National Emission Standard for Hazardous Air Pollutants (NESHAPs) regulations. Also included in PPPL’s radiological environmental monitoring program, are water monitoring – ground, surface, and waste waters. PPPL’s radiological monitoring program characterized the background levels of tritium in the environment and those data are presented in this report. Ground water monitoring continued under New Jersey Department of Environmental Protection’s (NJDEP) Site Remediation Program regulations. PPPL monitored for non-radiological contaminants, mainly volatile organic compounds (components of common degreasing solvents). In 2021, PPPL complied with permit limits for surface and sanitary discharges. PPPL was honored with awards for EPEAT-certified electronics purchasing and use of peracetic acid as an alternative water treatment chemical in its non-potable process water systems an NJDEP recycling award.

54 ENVIRONMENTAL SCIENCES↗

Cloud Condensation Nuclei Particle Counter from Kennaook Cape Grim

When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.

54 ENVIRONMENTAL SCIENCES↗

Aerosol Chemical Speciation Monitor (ACSM) Time-of-Flight (ToF) from Kennaook Cape Grim

When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.

54 ENVIRONMENTAL SCIENCES↗

Baseline status of BOM instruments at Kennaook Cape Grim

When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (stuart.baly@bom.gov.au, melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.

54 ENVIRONMENTAL SCIENCES↗

Ultrafine Condensation Particle Counter from Kennaook Cape Grim (a1-level)

When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed at the East River, Colorado, Water: Dataset

This data package contains simulation results of daily evapotranspiration for 17 locations of meteorological stations with different precipitation, air temperature and vegetation within the East River Watershed, Colorado (CLMResult.csv). Daily precipitation data is included for reference. These are the main results of the paper Tran, 2019. Meteorological stations names, latitude and longitude coordinates of meteorological stations, types of lands from the National Land Cover Database, and a comparison with the community land model (CLM) data are also included (Met_LC.csv). The purpose of this data is to analyze the spatio-temporal variations of evapotranspiration at the East River Watershed and understand the factors that control these variations. More information regarding the study, methods, and findings can be found in the Related Reference paper.

54 ENVIRONMENTAL SCIENCES↗

Photonuclear Production of Radioxenon for Air Samples

Radioxenon plays an important role in ensuring compliance with the Comprehensive Nuclear-Test-Ban Treaty due to its ability to be transported through the atmosphere, as well as the fact that the half-lives of its isotopes provide a window long enough to be detected but not long enough that it could become background radiation. This allows it to be correlated with specific events that indicate the testing of nuclear weapons. Idaho National Laboratory supports this mission by providing spiked air samples for monitoring stations to enable instrument calibration and ensure measurement accuracy. We tested a photonuclear method of producing one of the main isotopes of radioxenon, Xe-135. We also tested the separation of Xe-135 from the parent isotope Xe-136 using the method of kinematic recoil. Aluminum coils were placed in quartz ampoules filled with enriched Xe-136 and were irradiated by a bremsstrahlung beam with an endpoint energy of 21 MeV. The results showed that we were not only successful in producing Xe-135 but also that the Xe-135 was deposited into the coil allowing it to be removed from the Xe-136 gas. The coil and the Xe-135 can then be chemically separated. At the time of counting the coil, it was calculated that there was about 18 Bq of activity from Xe-135 remaining in the coil. Future work includes determining the optimal material and geometry of the catcher to maximize the amount of Xe-135 captured.

07 ISOTOPE AND RADIATION SOURCES↗

Multiple Indicators of Extreme Changes in Snow-Dominated Streamflow Regimes, Yakima River Basin Region, USA

Snow plays a major role in the hydrological cycle. Variations in snow duration and timing can have a negative impact on water resources. Excluding predicted changes in snowmelt rates and amounts could result in deleterious infrastructure, military mission, and asset impacts at military bases across the US. A change in snowpack can also lead to water shortages, which in turn can affect the availability of irrigation water. We performed trend analyses of air temperature, snow water equivalent (SWE) at 22 SNOTEL stations, and streamflow extremes for selected rivers in the snow-dependent and heavily irrigated Yakima River Basin (YRB) located in the Pacific Northwest US. There was a clear trend of increasing air temperature in this study area over a 30 year period (water years 1991–2020). All stations indicated an increase in average air temperatures for December (0.97 °C/decade) and January (1.12 °C/decade). There was also an upward trend at most stations in February (0.28 °C/decade). In December–February, the average air temperatures were 0.82 °C/decade. From these trends, we estimate that, by 2060, the average air temperatures for December–February at most (82%) stations will be above freezing. Furthermore, analysis of SWE from selected SNOTEL stations indicated a decreasing trend in historical SWE, and a shift to an earlier peak SWE was also assumed to be occurring due of the shorter snow duration. Decreasing trends in snow duration, rain-on-snow, and snowmelt runoff also resulted from snow modeling simulations of the YRB and the nearby area. We also observed a shift in the timing of snowmelt-driven peak streamflow, as well as a statistically significant increase in winter maximum streamflow and decrease in summer maximum and minimum streamflow trends by 2099. From the streamflow trends and complementary GEV analysis, we show that the YRB basin is a system in transition with earlier peak flows, lower snow-driven maximum streamflow, and higher rainfall-driven summer streamflow. This study highlights the importance of looking at changes in snow across multiple indicators to develop future infrastructure and planning tools to better adapt and mitigate changes in extreme events.

54 ENVIRONMENTAL SCIENCES↗

NNSS Soils Monitoring: Plutonium Valley (CAU 366) FY2019

Desert Research Institute (DRI) conducted a field assessment of the potential for radionuclide-contaminated soil to be transported from the Plutonium Valley Dispersion Sites Contamination Area (CA) because of both wind and storm water runoff. This activity supported U.S. Department of Energy (DOE) Environmental Management Nevada Program (EM NV) efforts to establish post-closure monitoring plans for the Plutonium Valley Dispersion Sites Corrective Action Unit (CAU) 366. The DRI task was intended to identify the likely mechanism(s) of transport and determine the meteorological conditions that might cause the movement of radionuclide-contaminated soils. The emphasis of the work was on collecting sediment transported by channelized storm runoff and measuring airborne dust concentrations and associated wind conditions. These data will facilitate an appropriate post-closure monitoring program. In 2011, DRI installed meteorological monitoring stations north and south of the Plutonium Valley CA—known as Pu Valley North and Pu Valley South, respectively—as well as a fluvial sediment sampling station within the CA. Since installation, temperature, wind speed, wind direction, relative humidity, precipitation, solar radiation, barometric pressure, soil temperature, volumetric soil moisture content, and airborne particulate concentrations have been collected at both meteorological stations. The maximum, minimum, and average or total (as appropriate) for each of these parameters were recorded for each 10-minute interval. The sediment sampling station included an automatically activated sampling pump with collection bottles for suspended sediment, which was activated when sufficient flow was present in the channel, and passive traps for bedload material that was transported down the channel during runoff events. This report presents data collected from these stations during fiscal year (FY) 2019. During the FY2019 (October 1, 2018, through September 30, 2019) reporting period, the warmest month was July and the coldest month was February. Monthly total solar radiation was highest in June or July (depending on the station) and lowest in December. Monthly mean wind speeds were highest during February. At the Pu Valley North station, winds were commonly northerly, northwesterly, and southerly. At the Pu Valley South station, the wind direction was more variable and winds frequently came from most directions, excluding westerly and northwesterly winds. Winds above 15.0 miles per hour (mph) (24.1 kilometers per hour [km/hr]) were frequently southerly at both stations, and less-frequent strong winds were northerly (at the Pu Valley South station) or northwesterly (at the Pu Valley North station). Monthly average relative humidity ranged from 18 percent in August to 62 percent in January and February. Monthly total precipitation ranged from zero at both stations in September to 2.23 inches (in) (56.6 millimeters [mm]) during February at the Pu Valley South station and 2.09 in (53.1 mm) during March at the Pu Valley North station. From October 1, 2018, through September 30, 2019, the total precipitation was 8.23 in (209 mm) and 8.15 in (207 mm) at the Pu Valley South and Pu Valley North stations, respectively. The largest daily precipitation totals of 1.46 in (37.1 mm) and 1.14 in (29.0 mm) occurred at the Pu Valley South and Pu Valley North stations, respectively, on March 6, 2019. However, the ISCO autosampler was not activated during any storm event in FY2019 because the channel water depth measurements were insufficient for suspended sediment sample collection. Additionally, because no significant flow through the channel was indicated, no bedload samples were collected. Light breezes of 0.0 mph to 5.0 mph (0.0 km/hr to 8.0 km/hr) occurred most frequently (approximately 55 percent to 57 percent of the time). The frequency of occurrence diminished exponentially as the wind speed increased such that winds in excess of 25.0 mph (40.2 km/hr) occurred less than 0.01 percent of the time. Winds in excess of 15.0 mph (24.1 km/hr) were most commonly southerly, which is likely controlled by the topography of the valley because topographic highs define the east and west sides of the valley and converge toward the north.The concentrations of PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 micrometers [μm]) and PM10 (particulate matter with an aerodynamic diameter ≤10 μm) in the air generally increase as wind speed increases. However, the particle profiler at the Pu Valley South station regularly malfunctioned, which resulted in poor data quality and a limited period of record within FY2019. Therefore, discussion of the annual dust observations is mostly limited to the Pu Valley North station. At the Pu Valley North station, significant increases in windblown dust concentrations were observed when wind speeds exceeded 15.0 mph (24.1 km/hr), especially during southerly winds. When all wind speeds were considered, high dust concentrations at the Pu Valley North station were frequently associated with northerly, northwesterly, or southerly winds. The majority of PM10 transport at the Pu Valley North station occurred when winds were blowing northerly and northwesterly because of the high frequency of winds up to 15.0 mph (24.1 km/hr). The ratio of PM10 to PM2.5 is a qualitative indicator of the proximity of dust sources to the observation point and the values of the PM10 to PM2.5 ratio tend to be higher nearer to the source. The PM10 to PM2.5 ratio increased from 1.2 to 2.8 with higher wind speeds at the Pu Valley North station. This increase suggests that some locally sourced PM10 was present in the air when local winds exceeded 15.0 mph (24.1 km/hr). Local dust suspension is interpreted during major dust events when peaks in the PM10 to PM2.5 ratio occur simultaneously with the maximum wind speed and the peak PM10 concentration. Analysis of the five major dust events in FY2019 revealed that northerly winds were dominant in three events and southerly winds were dominant in two events. Local suspension of dust within Plutonium Valley is suspected to have occurred during two of the five major events (April 9, 2019, and September 28 to 29, 2019), and a nonlocal source of dust is presumed for the three other major dust events (October 14, 2018; May 16, 2019; and September 2, 2019). The three suspected regional dust transport events exhibited winds that typically did not exceed the 15.0 mph (24.1 km/hr) wind speed threshold for local dust transport and featured PM10 to PM2.5 ratios that indicate large-scale regional dust transport. Similar event characteristics (e.g., wind speed and PM10 concentration) were observed at air monitoring stations approximately 70 mi (113 km) to the northwest within the Tonopah Test Range (TTR). Therefore, these three regional events may not reflect transport from the Plutonium Valley CA. Routine monitoring of meteorological and hydrologic parameters at Plutonium Valley has been discontinued at the request of EM NV, effective at the conclusion of FY2019. Environmental data acquisition has been completed, and both Pu Valley North and Pu Valley South meteorological stations within Plutonium Valley as well as the ISCO autosampler station within the CA were removed on October 14, 2019.

54 ENVIRONMENTAL SCIENCES↗

A Hierarchical Optimization Method for Electric Vertical Takeoff and Landing Aircraft Network Design

Electric vertical takeoff and landing aircraft (eVTOLs) are expected to serve urban air mobility in a station-to-station configuration, which makes the optimal network design of eVTOL stations a critical question to explore. Existing approaches often face limitations, such as the inability to interact station locations with demand or difficulty in finding the optimal solution for large study regions. Here, this paper first proposes a mathematical model to generate optimal eVTOL station locations while considering associated potential eVTOL demand, and then proposes a heuristic algorithm, Hierarchical Optimization MEthod (HOME), to efficiently solve the model. With a case study of Southern California, HOME was compared to 1) directly solving the original integer linear programming-based network design problem, and 2) employing the widely used genetic algorithm. Results suggest that HOME can find optimal solutions with limited computational resources. The proposed framework powered by HOME provides a computationally efficient way to support urban air mobility planning.

97 MATHEMATICS AND COMPUTING↗

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity evaluation of the Kudryavtsev permafrost model

Modeling is an important way to assess current and future permafrost spatial distribution and dynamics, especially in data poor areas like the Arctic region. Here, we evaluate a physics-based analytical model, Kudryavtsev's active layer model, which is widely used because it has relatively few data requirements. This model was recently incorporated into a component modeling toolbox, allowing for coupled modeling of permafrost and geomorphic processes over geological timescales. However, systematic quantitative assessment of the influence of its controlling parameters on permafrost temperature and active layer thickness predictions has not been undertaken before. In this work, we investigate the sensitivity of the Kudryavtsev's active layer model by Monte Carlo simulations to generate probability distributions for input parameters and compare predictions with a comprehensive benchmark dataset of in-situ permafrost observations over entire Alaska. Predicted permafrost surface temperature is highly dependent on mean annual air temperature (r = 0.78 on average), annual temperature amplitude (–0.41), and winter-averaged snow thickness (0.30). Uncertainty of predicted permafrost temperature is relatively small (RMSE = 1 °C), when air temperature and snow depth are well constrained. Similarly, RMSE between simulated and observed ALT at stations is ~0.08 m. However, under given air temperature and snow conditions, soil water content bias can significantly affect modeled active layer thickness (RMSE = 0.1 m or 40% of the observed active layer thickness). If soil water content has a large bias, improvements in other parameters may not significantly improve the active layer predictions of the Kudryavtsev's model.

54 ENVIRONMENTAL SCIENCES↗