SEARCH · Engineering Papers

Results for “MODELING”

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

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2019

Generalized Spatio-Temporal Model of Backsheet Degradation From Field Surveys of Photovoltaic Modules

Photovoltaic (PV) module backsheets degrade at different rates because of the specific polymeric materials and the local exposure environments of the installations. Studies of real-world backsheet degradation provide valuable information to understand backsheet degradation and failure. Field surveys of PV module backsheets were conducted on 1310 modules in four commercial PV power plant sites with different exposure times. The backsheet's local exposure environment is determined by its location along the rack length and depth, the modules' elevation above the ground, and the ground cover albedo. Backsheets that are installed at the ends of the module rack length exhibit larger degradation rates (with yellowness index difference of 1.14 $\pm$ 0.45 and 7.80 $\pm$ 1.3 for backsheets of poly (ethylene terephthalate) and poly (ethylene naphthalate) as the air-side layer, respectively) than backsheets in the center section of the rack. A generalized spatio-temporal model was developed to predict the large-scale backsheet degradation of different backsheet polymers across time/age and location in the PV power plant rack. The model utilizes a cubic-spline relationship between backsheet degradation and rack length, and a quadratic relationship between backsheet discoloration and rack depth. This generalized spatio-temporal model predicts the outdoor backsheet degradation with an adjusted- $R^2$ range between 0.31 to 0.89. The similarity between this model and the spatial variation of the rear-side irradiance, indicates that the irradiance plays a significant role in outdoor backsheet degradation. The generalized spatio-temporal model can be used to evaluate large scale PV backsheet performance, as well as a guidance for PV site designers and operations and maintenance crews.

14 SOLAR ENERGY↗

DOE OSTI2023

Enhancing Lithium-Ion Battery Aging Simulations: Coupling a High-Resolution, 3D, Grain-Scale Electromechanical Model to a Single-Particle Model

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. Unfortunately, this requires simulation of thousands of charge/discharge cycles, which can be rather time consuming depending on the fidelity of the simulation. The purpose of this talk is to discuss a new modeling framework that couples a high-resolution, continuous damage model (CDM) to a single particle model (SPM) resulting in a good combination of speed and fidelity. In previous work, a 3D, continuum-level chemo-mechanical model was developed to investigate cracking within a single cathode particle comprised of hundreds to thousands of randomly oriented grains. The CDM predicted that particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains were misaligned, they expanded different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. The model predicted that small particles with large grains develop significantly less damage than larger particles with small grains. Finally, the model predicted most of the chemo-mechanical damage accumulates in the first charge after formation. This chemo-mechanical "damage saturation" effect indicated that initial particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced. This led to a need for simulating fatigue-like mechanism that degrade the battery over longer time scales. In order to reach the time scales, need to resolve fatigue-like degradation, the CDM needs to be complemented by a faster model. Therefore, recent efforts have been focused on using results from the CDM to inform parameters within the SPM. These parameters are homogenization factors that are associated with diffusion, particle radius, and/or exchange current density. By coupling the CDM to the SPM, the aging simulation is broken up into two domains: short-term and long-term degradation. The short-term degradation occurs over a single cycle and is handled by the CDM due of its high fidelity, but relatively expensive computational cost. Such mechanism include break-in crack caused by mismatches in grain orientation. The long-term degradation occurs over tens of cycles and is handled by the SPM due it's computational efficiency. Most of the fatigue-like mechanism fall into this category. The eventual goal of this modeling framework is to upscale to a psudo-2D model allowing for full electrode simulation, which are informed by high-fidelity grain-scale simulations.

electrochemistry↗

DOE OSTI2020

Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)

The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.

Djalalova, Irina V.↗

DOE OSTI2014

Disease Prediction Models and Operational Readiness

INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the results are presented in this analysis.

biosecurity↗

DOE OSTI2021

A Bayesian Calibration Framework with Embedded Model Error for Model Diagnostics

We study the utility and performance of a Bayesian model error embedding construction in the context of molecular dynamics modeling of metallic alloys, where we embed model error terms in existing interatomic potential model parameters. To alleviate the computational burden of this approach, we propose a framework combining likelihood approximation and Gaussian process surrogates. Here we leverage sparse Gaussian process techniques to construct a hierarchy of increasingly accurate but more expensive surrogate models. This hierarchy is then exploited by multilevel Markov chain Monte Carlo methods to efficiently sample from the target posterior distribution. We illustrate the utility of this approach by calibrating an interatomic potential model for a family of gold-copper alloys. In particular, this case study highlights effective means for dealing with computational challenges with Bayesian model error embedding in large-scale physical models, and the utility of embedded model error for model diagnostics.

Bayesian inference↗

DOE OSTI2016

Proposal of a Novel Approach to Developing Material Models for Micro-scale Composites Based on Testing and Modeling of Macro-scale Composites

The Los Alamos National Laboratory's Weapon Systems Engineering division's Advanced Engineering Analysis group employs material constitutive models of composites for use in simulations of components and assemblies of interest. Experimental characterization, modeling and prediction of the macro-scale (i.e. continuum) behaviors of these composite materials is generally difficult because they exhibit nonlinear behaviors on the meso- (e.g. micro-) and macro-scales. Furthermore, it can be difficult to measure and model the mechanical responses of the individual constituents and constituent interactions in the composites of interest. Current efforts to model such composite materials rely on semi-empirical models in which meso-scale properties are inferred from continuum level testing and modeling. The proposed approach involves removing the difficulties of interrogating and characterizing micro-scale behaviors by scaling-up the problem to work with macro-scale composites, with the intention of developing testing and modeling capabilities that will be applicable to the mesoscale. This approach assumes that the physical mechanisms governing the responses of the composites on the meso-scale are reproducible on the macro-scale. Working on the macro-scale simplifies the quantification of composite constituents and constituent interactions so that efforts can be focused on developing material models and the testing techniques needed for calibration and validation. Other benefits to working with macro-scale composites include the ability to engineer and manufacture—potentially using additive manufacturing techniques—composites that will support the application of advanced measurement techniques such as digital volume correlation and three-dimensional computed tomography imaging, which would aid in observing and quantifying complex behaviors that are exhibited in the macro-scale composites of interest. Ultimately, the goal of this new approach is to develop a meso-scale composite modeling framework, applicable to many composite materials, and the corresponding macroscale testing and test data interrogation techniques to support model calibration.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multiscale Modeling of Silicon Carbide Cladding for Nuclear Applications: Thermal Performance Modeling

The complex multiscale and anisotropic nature of silicon carbide (SiC) ceramic matrix composite (CMC) makes it difficult to accurately model its performance in nuclear applications. The existing models for nuclear grade composite SiC do not account for the microstructural features and how these features can affect the thermal and structural behavior of the cladding and its anisotropic properties. In addition to the microstructural features, the properties of individual constituents of the composites and fiber tow architecture determine the bulk properties. Models for determining the relationship between the individual constituents’ properties and the bulk properties of SiC composites for nuclear applications are absent, although empirical relationships exist in the literature. Here, a hierarchical multiscale modeling approach was presented to address this challenge. This modular approach addressed this difficulty by dividing the various aspects of the composite material into separate models at different length scales, with the evaluated property from the lower-length-scale model serving as an input to the higher-length-scale model. The multiscale model considered the properties of various individual constituents of the composite material (fiber, matrix, and interphase), the porosity in the matrix, the fiber volume fraction, the composite architecture, the tow thickness, etc. By considering inhomogeneous and anisotropic contributions intrinsically, our bottom-up multiscale modeling strategy is naturally physics-informed, bridging constitutive law from micromechanics to meso-mechanics and structural mechanics. The effects that these various physical attributes and thermo-physical properties have on the composite’s bulk thermal properties were easily evaluated and demonstrated through the various analyses presented herein. Since silicon carbide fiber-reinforced SiC CMCs are also promising thermal–structural materials with a broad range of high-end technology applications beyond nuclear applications, we envision that the multiscale modeling method we present here may prove helpful in future efforts to develop and construct reinforced CMCs and other advanced composite nuclear materials, such as MAX phase materials, that can service under harsh environments of ultrahigh temperatures, oxidation, corrosion, and/or irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2013

Natural Air-Sea Flux of CO2 in Simulations of the NASA-GISS Climate Model: Sensitivity to the Physical Ocean Model Formulation

Results from twin control simulations of the preindustrial CO2 gas exchange (natural flux of CO2) between the ocean and the atmosphere are presented here using the NASA-GISS climate model, in which the same atmospheric component (modelE2) is coupled to two different ocean models, the Russell ocean model and HYCOM. Both incarnations of the GISS climate model are also coupled to the same ocean biogeochemistry module (NOBM) which estimates prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2. Model intercomparison is carried out at equilibrium conditions and model differences are contrasted with biases from present day climatologies. Although the models agree on the spatial patterns of the air-sea flux of CO2, they disagree on the strength of the North Atlantic and Southern Ocean sinks mainly because of kinematic (winds) and chemistry (pCO2) differences rather than thermodynamic (SST) ones. Biology/chemistry dissimilarities in the models stem from the different parameterizations of advective and diffusive processes, such as overturning, mixing and horizontal tracer advection and to a lesser degree from parameterizations of biogeochemical processes such as gravitational settling and sinking. The global meridional overturning circulation illustrates much of the different behavior of the biological pump in the two models, together with differences in mixed layer depth which are responsible for different SST, DIC and nutrient distributions in the two models and consequently different atmospheric feedbacks (in the wind, net heat and freshwater fluxes into the ocean).

Gas exchange↗

NASA NTRS2015

Digital Astronaut Project Biomechanical Models: Biomechanical Modeling of Squat, Single-Leg Squat and Heel Raise Exercises on the Hybrid Ultimate Lifting Kit (HULK)

The NASA Digital Astronaut Project (DAP) implements well-vetted computational models to predict and assess spaceflight health and performance risks, and to enhance countermeasure development. The DAP Musculoskeletal Modeling effort is developing computational models to inform exercise countermeasure development and to predict physical performance capabilities after a length of time in space. For example, integrated exercise device-biomechanical models can determine localized loading, which will be used as input to muscle and bone adaptation models to estimate the effectiveness of the exercise countermeasure. In addition, simulations of mission tasks can be used to estimate the astronaut's ability to perform the task after exposure to microgravity and after using various exercise countermeasures. The software package OpenSim (Stanford University, Palo Alto, CA) (Ref. 1) is being used to create the DAP biomechanical models and its built-in muscle model is the starting point for the DAP muscle model. During Exploration missions, such as those to asteroids and Mars, astronauts will be exposed to reduced gravity for extended periods. Therefore, the crew must have access to exercise countermeasures that can maintain their musculoskeletal and aerobic health. Exploration vehicles may have very limited volume and power available to accommodate such capabilities, even more so than the International Space Station (ISS). The exercise devices flown on Exploration missions must be designed to provide sufficient load during the performance of various resistance and aerobic/anaerobic exercises while meeting potential additional requirements of limited mass, volume and power. Given that it is not practical to manufacture and test (ground, analog and/or flight) all candidate devices, nor is it always possible to obtain data such as localized muscle and bone loading empirically, computational modeling can estimate the localized loading during various exercise modalities performed on a given device to help formulate exercise prescriptions and other operational considerations. With this in mind, NASA's Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) laboratory and NSBRI-funded researchers by developing and implementing well-validated computational models of exercises with advanced exercise device concepts. This report focuses specifically on lower-body resistance exercises performed with the Hybrid Ultimate Lifting Kit (HULK) device as a deliverable to the AEC Project.

health↗

NASA NTRS2022

Importance of Different Parameterization Changes for the Updated Dust Cycle Modeling in the Community Atmosphere Model (Version 6.1)

The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.

mineral dust parameterizations↗

NASA NTRS2023

An Investigation into the Effect of Liquid Accumulation on Thermo-Physiologic State using an Advanced Moisture Model Coupled with a High Resolution Human Thermal Model

A physics-based mathematical model for simulating heat and moisture transport on the skin and within clothing was developed to improve the accuracy of human thermal modeling predictions. In a previous study, a set of sweating hotplate experiments was specifically created to obtain test data for model validation. The clothing moisture model was subsequently coupled with a human thermal model and tested by simulating human experiments described in the open literature, which served to verify the model’s ability to predict whole body thermo-physiologic state in work-rest cycles during which sweating was known to occur. In this study, a human subject test was specifically designed to validate the model’s ability to predict local and whole body sweat evaporation and accumulation on the surface of the body. The human subject test incorporated twelve clothed male subjects of moderate physical fitness, ages 18-30, which were prescribed a work-rest cycle in a climate-controlled chamber (25 °C, 50% RH). Two activity levels were considered during the active stage (4 MET vs. 6.5 MET), and two sets of ending ambient conditions were considered for the final rest stage (25 °C vs. 15 °C, 50% RH). Model predictions were compared to the measured local skin temperatures, core temperatures, and whole body sweat losses. In general, the model was able to reproduce the trends observed in the human subject trial, but more importantly, provided insight into how dynamic changes in liquid content can impact the evolution of local and whole body thermo-physiologic state. This study demonstrates the ability of an advanced moisture model to capture distinct physics attributable to moisture accumulation, allowing for increased accuracy in predicting human thermal state and for interpreting the results of measurements derived from human subject tests.

human thermal model↗

NASA NTRSDate not supplied

Finite Element Modeling of Extravehicular Mobility Units for Use With Human Body Models – Motivation, Major Challenges, Use Cases and Preliminary Work

Finite element modeling of pressurized spacesuits and implementation with human body models offers many advantages over physical experimentation, but also presents significant challenges. A model of pressurized spacesuit softgoods was developed, integrated with an existing hardgoods model, and fitted to a human body model. Two representative loading scenarios were simulated: dynamic external suit loading and internal occupant-driven loading, to serve as proof-of-concept for the modeling techniques employed. The modeled interactions behaved as intended and illustrate that finite element models of pressurized spacesuits can be used in conjunction with human body models to assess the biomechanical behavior. Further model development and experimental validation are needed.

Finite Element↗

NASA NTRS2024

Finite Element Modeling of Extravehicular Mobility Units for Use With Human Body Models – Motivation, Major Challenges, Use Cases and Preliminary Work

Finite Element↗

DOE OSTI2018

South Asian monsoon precipitation in CMIP5: a link between inter-model spread and the representations of tropical convection

CMIP5 models exhibit a mean dry bias and a large inter-model spread in simulating Indian monsoon precipitation but the origins of the bias and spread have not been well understood. Using moisture and energy budget analysis that exploits the weak temperature gradients in the tropics, we show that they are linked to the convection simulated over the equatorial Indian Ocean. About half of the 21 models analyzed operate at the steep gradient of the non-linear relationship between the normalized precipitable water and normalized precipitation, where small differences in the former are amplified as large differences in precipitation. These models preferentially produce higher precipitation over the equatorial Indian Ocean, and contribute disproportionately to the inter-model spread and multi-model mean dry bias in monsoon precipitation. Conversely, models on the flat side of the relationship are in better agreement with each other and with observations. Under the RCP8.5 forcing scenario, models on the steep part of the relationship project stronger response to warming and dominate the inter-model spread in the projection. This study identified the normalized precipitable water as a key metric for understanding the behavior of model simulated equatorial and Indian monsoon precipitation.

Hagos, Samson (ORCID:0000000175919933)↗

DOE OSTI2015

Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

McFarland, James↗

DOE OSTI2019

Model of temperature, evaporation, and productivity in elevated experimental algae raceways and comparison with commercial raceways

Elevated Experimental Raceways (EERs) have been used at many research sites in the United States to evaluate algal biomass productivity. This paper develops temperature and evaporation models for EERs and then evaluates whether the temperature profile and resultant productivity in an EER is representative of large-scale commercial raceways. Open water surface evaporation and temperature models with shading algorithms were programmed in Python and calibrated with temperature and evaporation data from the EERs in the Regional Algal Feedstock Testbed (RAFT) experiments at the University of Arizona. The final calibrated model for EERs was named the EERTEM (Elevated Experimental Raceway Temperature and Evaporation Model). The energy balance algorithms in the Biomass Assessment Tool (BAT model) were also added to the Python code and used to develop temperature simulations of standard commercial paddlewheel raceways. A comparison of BAT and EERTEM simulations indicated that EER temperature fluctuations are not representative of in ground commercial paddlewheel raceways, primarily due to the buffering effect of soil heat flux in commercial raceways. With the different temperature profiles, biomass productivities of three algae species in the EERs were compared to productivities in commercial raceways. Differences in productivity between EERTEM and BAT model temperature profiles were observed when the maximum daytime temperature of one raceway was in the optimal growth range but the temperature of the other raceway exceeded or was below the optimal growth range.

Khawam, George↗

DOE OSTI2016

Modeling fuels and fire effects in 3D: Model description and applications

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose. In this work, we present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates modeling fuels across a wide range of detail. Large trees or shrubs with specific coordinates are modeled as individual “Plants”, while understory plants are modeled as collections of plants called “LayerSets”. Both Plants and LayerSets contain various fuel particles (leaves, needles, twigs) with various properties including shape, size and surface area to volume ratio. A wide range of vegetation and treatments can be modeled, analyzed quantitatively and visualized in a 3D viewer. We describe the modeling approach and demonstrate fuel modeling at different levels of detail, fuel treatment and fire effects capabilities. Lastly, detailed model equations are provided in the Appendices.

54 ENVIRONMENTAL SCIENCES↗