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At least 991 records · Page 55

Statistical sensitivity on right-handed currents in presence of eV scale sterile neutrinos with KATRIN

The KATRIN experiment aims to determine the absolute neutrino mass by measuring the endpoint region of the tritium β-spectrum. As a large-scale experiment with a sharp energy resolution, high source luminosity and low background it may also be capable of testing certain theories of neutrino interactions beyond the standard model (SM). An example of a non-SM interaction are right-handed currents mediated by right-handed W bosons in the left-right symmetric model (LRSM). In this extension of the SM, an additional SU(2){sub R} symmetry in the high-energy limit is introduced, which naturally includes sterile neutrinos and predicts the seesaw mechanism. In tritium β decay, this leads to an additional term from interference between left- and right-handed interactions, which enhances or suppresses certain regions near the endpoint of the beta spectrum. In this work, the sensitivity of KATRIN to right-handed currents is estimated for the scenario of a light sterile neutrino with a mass of some eV. This analysis has been performed with a Bayesian analysis using Markov Chain Monte Carlo (MCMC). The simulations show that, in principle, KATRIN will be able to set sterile neutrino mass-dependent limits on the interference strength. The sensitivity is significantly increased if the Q value of the β decay can be sufficiently constrained. However, the sensitivity is not high enough to improve current upper limits from right-handed W boson searches at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Soil incubation methods lead to large differences in inferred methane production temperature sensitivity

Abstract Quantifying the temperature sensitivity of methane (CH 4 ) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q 10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q 10 values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model ( ecosys ) to interpret incubation observations and investigate controls on inferred CH 4 production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH 4 production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH 4 production. CH 4 production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q 10 values (1.2–3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q 10 values of CH 4 production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q 10 values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q 10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

54 ENVIRONMENTAL SCIENCES↗

Three-dimensional Fréchet sensitivity kernels for electromagnetic wave propagation

Electromagnetic imaging methods are useful tools for monitoring subsurface changes in pore-fluid content and the associated changes in electrical permittivity and conductivity. The most common method for georadar tomography uses a high frequency ray-theoretic approximation that is valid when material variations are sufficiently small relative to the wavelength of the propagating wave. Georadar methods, however, often utilize electromagnetic waves that propagate within heterogeneous media at frequencies where ray theory may not be applicable. In this paper we describe the 3-D Fréchet sensitivity kernels for EM wave propagation. Various data functional types are formulated that consider all three components of the electric wavefield and incorporate near-, intermediate-, and far-field contributions. We show that EM waves exhibit substantial variations for different relative source-receiver component orientations. The 3-D sensitivities also illustrate out-of-plane effects that are not captured in 2-D sensitivity kernels and can influence results obtained using 2-D inversion methods to image structures that are in reality 3-D.

58 GEOSCIENCES↗

On the dual advantage of placing observations through forward sensitivity analysis

The four-dimensional variational data assimilation methodology for assimilating noisy observations into a deterministic model has been the workhorse in forecasting centres for over three decades. While this method provides a computationally efficient framework for dynamic data assimilation, it is largely silent on the important question concerning the minimum number and placement of observations. To answer this question, we demonstrate the dual advantage of placing the observations where the square of the sensitivity of the model solution with respect to the unknown control variables, called forward sensitivities, attains its maximum. By following this approach, we can force the observability Gramian to be of full rank, which in turn guarantees efficient recovery of the optimal values of the control variables, which is the first of the two advantages of this strategy. We further show that the proposed strategy of placing observations has another inherent optimality: the square of the sensitivity of the optimal estimates of the control with respect to the observations (used to obtain these estimates) attains its minimum value, a second advantage that is a direct consequence of the above strategy for placing observations. Our analytical framework and numerical experiments on linear and nonlinear systems confirm the effectiveness of our proposed strategy.

97 MATHEMATICS AND COMPUTING↗

Traffic-Sensitive Live Migration of Virtual Machines

In this paper we address the problem of network contention between the migration traffic and the VM application traffic for the live migration of co-located Virtual Machines (VMs). When VMs are migrated with pre-copy, they run at the source host during the migration. Therefore the VM applications with predominantly outbound traffic contend with the outgoing migration traffic at the source host. Similarly, during post-copy migration, the VMs run at the destination host. Therefore the VM applications with predominantly inbound traffic contend with the incoming migration traffic at the destination host. Such a contention increases the total migration time of the VMs and degrades the performance of VM application. Here, we propose traffic-sensitive live VM migration technique to reduce the contention of migration traffic with the VM application traffic. It uses a combination of pre-copy and post-copy techniques for the migration of the co-located VMs, instead of relying upon any single pre-determined technique for the migration of all the VMs. We base the selection of migration techniques on VMs' network traffic profiles so that the direction of migration traffic complements the direction of the most VM application traffic. We have implemented a prototype of traffic-sensitive migration on the KVM/QEMU platform. In the evaluation, we compare traffic-sensitive migration against the approaches that use only pre-copy or only post-copy for VM migration. We show that our approach minimizes the network contention for migration, thus reducing the total migration time and the application degradation.

Live Migration↗

Adaptive Power Flow Approximations With Second-Order Sensitivity Insights

The power flow equations are fundamental to power system planning, analysis, and control. However, the inherent non-linearity and non-convexity of these equations present formidable obstacles in problem-solving processes. To mitigate these challenges, recent research has proposed adaptive power flow linearizations that aim to achieve accuracy over wide operating ranges. The accuracy of these approximations inherently depends on the curvature of the power flow equations within these ranges, which necessitates considering second-order sensitivities. In this paper, we leverage second-order sensitivities to both analyze and improve power flow approximations. We evaluate the curvature across broad operational ranges and subsequently utilize this information to inform the computation of various sample-based power flow approximation techniques. Additionally, we leverage second-order sensitivities to guide the development of rational approximations that yield linear constraints in optimization problems. In conclusion, this approach is extended to enhance accuracy beyond the limitations of linear functions across varied operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A New LMP-Sensitivity-Based Heterogeneous Decomposition for Transmission and Distribution Coordinated Economic Dispatch

Transmission and distribution coordinated economic dispatch (TDCED) will be necessary to settle the problems caused by high penetrations of distributed generators in future grids. An efficient heterogeneous decomposition algorithm (HGD) was proposed to solve the TDCED, but it may diverge occasionally. To overcome this shortcoming, a new HGD (N-HGD) with enhanced convergency is proposed and studied in this paper. Compared with the previous HGD, the N-HGD similarly decomposes the TDCED into transmission ED and distribution ED subproblems, but it considers the sensitivity of the boundary locational marginal price to load injections to enhance convergency and avoid divergence. Two kinds of sensitivity computing methods, M-c and M-p, are studied. M-c is based on a centralized sensitivity equation, executed on the transmission side. M-p is based on a probing mechanism and can be executed distributedly on the distribution side. The reason for the N-HGD's improved convergency is theoretically analyzed, and the optimality is proven. Numerical tests show that N-HGD performs better than the original HGD, as well as a penalty-based modified HGD that needs a careful parametertuning process. Furthermore, compared with M-c, an M-p-based N-HGD is preferable because it has a much lower computational cost and no additional communicational cost.

distribution↗

Sensitivity Analysis of a Polyphase Wireless Power Transfer System under Off-Nominal Conditions

Misaligned and/or variable coil airgaps cause coupling coefficient variation in wireless power transfer (WPT) systems, resulting in a decrease in the system’s transmitted power and efficiency. This paper presents sensitivity analyses of a three-phase, Y-Y connected, series-tuned WPT system in the frequency domain in terms of several different electric vehicle wireless charging off-nominal conditions (misalignments in Δ x and Δ y directions, change of airgap Δ z , and the roll Δψ, pitch Δθ, and yaw ΔΦ angles) as specified in Society of Automotive Engineers (SAE) J2954 Standard. Coil inductance matrices were obtained by measuring the self- and mutual inductances of the primary and secondary coil phase windings at variable airgap classes (from 5 cm to 30 cm) for five different charging positions as identified in SAE J2954. These 6 × 6 inductance matrices were used in sensitivity and Plexim/PLECS simulation analyses. The sensitivity of the WPT system was analyzed analytically using the input impedance and phase angle, voltage gain, current gain, quality factor, and coupling coefficient parameters of the series-tuned WPT system. The results were confirmed experimentally on a 50 kW WPT system.

42 ENGINEERING↗

Global synthesis of the temperature sensitivity of leaf litter breakdown in streams and rivers

Streams and rivers are important conduits of terrestrially derived carbon (C) to atmospheric and marine reservoirs. Leaf litter breakdown rates are expected to increase as water temperatures rise in response to climate change. The magnitude of increase in breakdown rates is uncertain, given differences in litter quality and microbial and detritivore community responses to temperature, factors that can influence the apparent temperature sensitivity of breakdown and the relative proportion of C lost to the atmosphere vs. stored or transported downstream. We synthesized 1025 records of litter breakdown in streams and rivers to quantify its temperature sensitivity, as measured by the activation energy (Ea, in eV). Temperature sensitivity of litter breakdown varied among twelve plant genera for which Ea could be calculated. Higher values of Ea were correlated with lower-quality litter, but these correlations were influenced by a single, N-fixing genus (Alnus). Ea values converged when genera were classified into three breakdown rate categories, potentially due to continual water availability in streams and rivers modulating the influence of leaf chemistry on breakdown. Across all data representing 85 plant genera, the Ea was 0.34 ± 0.04 eV, or approximately half the value (0.65 eV) predicted by metabolic theory. Our results indicate that average breakdown rates may increase by 5–21% with a 1–4 °C rise in water temperature, rather than a 10–45% increase expected, according to metabolic theory. Differential warming of tropical and temperate biomes could result in a similar proportional increase in breakdown rates, despite variation in Ea values for these regions (0.75 ± 0.13 eV and 0.27 ± 0.05 eV, respectively). The relative proportions of gaseous C loss and organic matter transport downstream should not change with rising temperature given that Ea values for breakdown mediated by microbes alone and microbes plus detritivores were similar at the global scale.

54 ENVIRONMENTAL SCIENCES↗

Substrate availability and not thermal acclimation controls microbial temperature sensitivity response to long-term warming

Microbes are responsible for cycling carbon (C) through soils, and predicted changes in soil C stocks under climate change are highly sensitive to shifts in the mechanisms assumed to control the microbial physiological response to warming. Two mechanisms have been suggested to explain the long-term warming impact on microbial physiology: microbial thermal acclimation and changes in the quantity and quality of substrates available for microbial metabolism. Yet studies disentangling these two mechanisms are lacking. To resolve the drivers of changes in microbial physiology in response to long-term warming, we sampled soils from 13- and 28-year-old soil warming experiments in different seasons. We performed short-term laboratory incubations across a range of temperatures to measure the relationships between temperature sensitivity of physiology (growth, respiration, carbon use efficiency, and extracellular enzyme activity) and the chemical composition of soil organic matter. We observed apparent thermal acclimation of microbial respiration, but only in summer, when warming had exacerbated the seasonally-induced, already small dissolved organic matter pools. Irrespective of warming, greater quantity and quality of soil carbon increased the extracellular enzymatic pool and its temperature sensitivity. We propose that fresh litter input into the system seasonally cancels apparent thermal acclimation of C-cycling processes to decadal warming. Our findings reveal that long-term warming has indirectly affected microbial physiology via reduced C availability in this system, implying that earth system models including these negative feedbacks may be best suited to describe long-term warming effects on these soils.

59 BASIC BIOLOGICAL SCIENCES↗

WE-D-BRE-07: Variance-Based Sensitivity Analysis to Quantify the Impact of Biological Uncertainties in Particle Therapy

Purpose: In particle therapy, treatment planning and evaluation are frequently based on biological models to estimate the relative biological effectiveness (RBE) or the equivalent dose in 2 Gy fractions (EQD2). In the context of the linear-quadratic model, these quantities depend on biological parameters (α, β) for ions as well as for the reference radiation and on the dose per fraction. The needed biological parameters as well as their dependency on ion species and ion energy typically are subject to large (relative) uncertainties of up to 20–40% or even more. Therefore it is necessary to estimate the resulting uncertainties in e.g. RBE or EQD2 caused by the uncertainties of the relevant input parameters. Methods: We use a variance-based sensitivity analysis (SA) approach, in which uncertainties in input parameters are modeled by random number distributions. The evaluated function is executed 10{sup 4} to 10{sup 6} times, each run with a different set of input parameters, randomly varied according to their assigned distribution. The sensitivity S is a variance-based ranking (from S = 0, no impact, to S = 1, only influential part) of the impact of input uncertainties. The SA approach is implemented for carbon ion treatment plans on 3D patient data, providing information about variations (and their origin) in RBE and EQD2. Results: The quantification enables 3D sensitivity maps, showing dependencies of RBE and EQD2 on different input uncertainties. The high number of runs allows displaying the interplay between different input uncertainties. The SA identifies input parameter combinations which result in extreme deviations of the result and the input parameter for which an uncertainty reduction is the most rewarding. Conclusion: The presented variance-based SA provides advantageous properties in terms of visualization and quantification of (biological) uncertainties and their impact. The method is very flexible, model independent, and enables a broad assessment of uncertainties. Supported by DFG grant WI 3745/1-1 and DFG cluster of excellence: Munich-Centre for Advanced Photonics.

60 APPLIED LIFE SCIENCES↗

Sensitivity of the diagnostic radiological index of protection to procedural factors in fluoroscopy

Purpose: To evaluate the sensitivity of the diagnostic radiological index of protection (DRIP), used to quantify the protective value of radioprotective garments, to procedural factors in fluoroscopy in an effort to determine an appropriate set of scatter-mimicking primary beams to be used in measuring the DRIP. Methods: Monte Carlo simulations were performed to determine the shape of the scattered x-ray spectra incident on the operator in different clinical fluoroscopy scenarios, including interventional radiology and interventional cardiology (IC). Two clinical simulations studied the sensitivity of the scattered spectrum to gantry angle and patient size, while technical factors were varied according to measured automatic dose rate control (ADRC) data. Factorial simulations studied the sensitivity of the scattered spectrum to gantry angle, field of view, patient size, and beam quality for constant technical factors. Average energy (E{sub avg}) was the figure of merit used to condense fluence in each energy bin to a single numerical index. Results: Beam quality had the strongest influence on the scattered spectrum in fluoroscopy. Many procedural factors affect the scattered spectrum indirectly through their effect on primary beam quality through ADRC, e.g., gantry angle and patient size. Lateral C-arm rotation, common in IC, increased the energy of the scattered spectrum, regardless of the direction of rotation. The effect of patient size on scattered radiation depended on ADRC characteristics, patient size, and procedure type. Conclusions: The scattered spectrum striking the operator in fluoroscopy is most strongly influenced by primary beam quality, particularly kV. Use cases for protective garments should be classified by typical procedural primary beam qualities, which are governed by the ADRC according to the impacts of patient size, anatomical location, and gantry angle.

60 APPLIED LIFE SCIENCES↗

SU-F-J-40: Evaluation of Sensitivity of the Automatic Matching Between Cone-Beam CT Image and Simulation CT Image in TrueBeam 2.0 Imaging System 6DoF Considering Different Uncertainty Sources

Purpose: To estimate the sensitivity of TrueBeam 2.0 Imaging System 6DoF automatic matching tool through the acquisition of cone-beam CT images in different phantoms applying submillimeter translations and rotations of tenths of a degree and registered with image simulation CT. Methods: To evaluate overall system-wide image, we consider two uncertainties source; First, the uncertainty of the manual phantom displacement (ε-m). This uncertainty is calculated by a digital caliper (0.01 mm) for vertical (Vrt), lateral (Lat) and longitudinal (Lng). A digital inclinometer (0.01°) for the pitch and roll and the own phantom scale to evaluate the coordinate rotation (Rtn). The second uncertainty is the displacement detected by the algorithm system of matching (σ-d) that we obtain from the standard deviations of the different measurements. We use three different phantoms. The BrainLab Radiosurgery system for supporting masks with an anthropomorphic dummy adapted to allow displacements of 0.1 mm in Vrt, Lat and Lng dimensions and rotations of 0.1° in Pitch dimension. For the analysis of the Rtn and Roll dimensions we use two homemade phantoms (RinoRot and RinoRoll, La Fe Hospital, Valencia, Spain) that allow rotations of 0.3°. Results: In the case of manual displacement of 0.10 ± 0.03 mm in the translations, the system detect 0.10 ± 0.07 mm, 0.12 ± 0.07 mm and 0.13 ± 0.07 mm (mean ± SD) in Lat, Vrt and Lng respectively. In the case of rotational dimension, manual displacement of 0.3 ± 0.1° was detected with 0.19 ± 0.06°, 0.29 ± 0.03° and 0.27 ± 0.06° in Pitch, Roll and Rtn. Conclusion: We conclude that the sensitivity of the automatic matching system is within 0.10 mm in translations and 0.3° in rotations. These values are under the own sensitivity of the software.

60 APPLIED LIFE SCIENCES↗

WE-DE-201-11: Sensitivity and Specificity of Verification Methods Based On Total Reference Air Kerma (TRAK) Or On User Provided Dose Points for Graphically Planned Skin HDR Brachytherapy

Purpose: To investigate the sensitivity and specificity of a novel verification methodology for image-guided skin HDR brachytherapy plans using a TRAK-based reasonableness test, compared to a typical manual verification methodology. Methods: Two methodologies were used to flag treatment plans necessitating additional review due to a potential discrepancy of 3 mm between planned dose and clinical target in the skin. Manual verification was used to calculate the discrepancy between the average dose to points positioned at time of planning representative of the prescribed depth and the expected prescription dose. Automatic verification was used to calculate the discrepancy between TRAK of the clinical plan and its expected value, which was calculated using standard plans with varying curvatures, ranging from flat to cylindrically circumferential. A plan was flagged if a discrepancy >10% was observed. Sensitivity and specificity were calculated using as a criteria for true positive that >10% of plan dwells had a distance to prescription dose >1 mm different than prescription depth (3 mm + size of applicator). All HDR image-based skin brachytherapy plans treated at our institution in 2013 were analyzed. Results: 108 surface applicator plans to treat skin of the face, scalp, limbs, feet, hands or abdomen were analyzed. Median number of catheters was 19 (range, 4 to 71) and median number of dwells was 257 (range, 20 to 1100). Sensitivity/specificity were 57%/78% for manual and 70%/89% for automatic verification. Conclusion: A check based on expected TRAK value is feasible for irregularly shaped, image-guided skin HDR brachytherapy. This test yielded higher sensitivity and specificity than a test based on the identification of representative points, and can be implemented with a dedicated calculation code or with pre-calculated lookup tables of ideally shaped, uniform surface applicators.

60 APPLIED LIFE SCIENCES↗

Microbial Interactions Related to N 2 O Emissions and Temperature Sensitivity from Rice Paddy Fields

The soil microbiome is a driver of nitrous oxide (N 2 O) emissions in terrestrial ecosystems. Identifying the core microbiome of N 2 O emissions and its temperature sensitivity from trillions of soil microorganisms is a great challenge and is essential to improving the predictability of soil-climate feedback related to increasing temperature. Here, the integrated soil microbiome covering archaeal, bacterial, fungal, algal, and microfaunal communities was studied to disengage the potential linkage with its N 2 O emissions and its temperature sensitivity in paddy fields by hunting for core species pairs. The results showed that between-group interactions of core bacterial and archaeal members and the within-group interactions of core bacterial members jointly contributed to the N 2 O emissions and its temperature sensitivity. The contribution of between-group interactions (32 to 33%) was greater than that of within groups (10 to 18%). These results suggested that N 2 O emissions and their fluctuations related to climate warming are affected by the within- and between-group interactions of the soil microbiome. Our results help advance the knowledge on the importance of microbial keystone species and network associations in controlling N 2 O production and their responses to increasing temperature.

59 BASIC BIOLOGICAL SCIENCES↗

Long-wavelength sensitivity limit in MBE-grown PbSnTe:In films: Correlation with the film structure and composition

PbSnTe:In films with a long-wavelength sensitivity limit of over 20 μm and low “dark” conductivity are studied. The spectral dependences of the photoconductivity obtained at different temperatures using a Fourier spectrometer are compared with data on the film composition determined by X-ray microanalysis. The established nonmonotonic temperature dependence of the long-wavelength sensitivity limit is attributed to the combination of the temperature dependence of the PbSnTe band gap and the Burstein–Moss effect making the largest contribution to low-temperature measurements due to the long lifetime of excess charge carriers. It is shown that the difference between the band-gap values determined from the measured composition and temperature dependences of the long-wavelength sensitivity limit can be related to the inhomogeneity of the composition of the films grown by molecular beam epitaxy.

36 MATERIALS SCIENCE↗

Enabling Hyper-Differential Sensitivity Analysis for Ill-Posed Inverse Problems

Inverse problems constrained by partial differential equations (PDEs) play a critical role in model development and calibration. In many applications, there are multiple uncertain parameters in a model that must be estimated. However, high dimensionality of the parameters and computational complexity of the PDE solves make such problems challenging. A common approach is to reduce the dimension by fixing some parameters (which we will call auxiliary parameters) to a best estimate and use techniques from PDE-constrained optimization to estimate the other parameters. In this article, hyper-differential sensitivity analysis (HDSA) is used to assess the sensitivity of the solution of the PDE-constrained optimization problem to changes in the auxiliary parameters. Foundational assumptions for HDSA require satisfaction of the optimality conditions which are not always practically feasible as a result of ill-posedness in the inverse problem. Here we introduce novel theoretical and computational approaches to justify and enable HDSA for ill-posed inverse problems by projecting the sensitivities on likelihood informed subspaces and defining a posteriori updates. Our proposed framework is demonstrated on a nonlinear multiphysics inverse problem motivated by estimation of spatially heterogeneous material properties in the presence of spatially distributed parametric modeling uncertainties.

97 MATHEMATICS AND COMPUTING↗

Quantifying the Uncertainty of the Future Hydrological Impacts of Climate Change: Comparative Analysis of an Advanced Hierarchical Sensitivity in Humid and Semiarid Basins

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. Further, the results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions.

54 ENVIRONMENTAL SCIENCES↗