SEARCH · Search NASA

Results for “value factor”

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 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Statistical Association between the Candidate Repeating FRB 20200320A and a Galaxy Group

Abstract We present results from angular cross correlations between select samples of CHIME/FRB repeaters and galaxies in three photometric galaxy surveys, which have shown correlations with the first CHIME/FRB catalog containing repeating and nonrepeating sources: Wide-field Infrared Survey Explorer (WISE) × SCOS, DESI-BGS, and DESI-LRG. We find a statistically significant correlation (p-value <0.001, after accounting for look-elsewhere factors) between a sample of repeaters with an extragalactic dispersion measure (DM) > 395 pc cm −3 and WISE × SCOS galaxies with redshiftz> 0.275. We demonstrate that the correlation arises surprisingly because of a statistical association between FRB 20200320A (extragalactic DM ≈ 550 pc cm −3 ) and a galaxy group in the same dark matter halo at redshiftz≈ 0.32. We estimate that the host halo, along with an intervening halo at redshiftz≈ 0.12, accounts for at least ∼30% of the extragalactic DM. Our results strongly motivate incorporating galaxy group and cluster catalogs into direct host association pipelines for FRBs with ≲ 1 ′ localization precision, effectively utilizing the two-point information to constrain FRB properties such as their redshift and DM distributions. In addition, we find marginal evidence for a negative correlation at 99.4% confidence limit between a sample of repeating FRBs with baseband data (median extragalactic DM = 354 pc cm −3 ) and DESI-LRG galaxies with redshift 0.3 ≤z< 0.45, suggesting that the repeaters might be more prone than apparent nonrepeaters to propagation effects in FRB–galaxy correlations due to intervening free electrons over angular scales ∼0.°5.

Astronomy & Astrophysics↗

DOE OSTI2020

Validation of a Generalized Formulation for Load-Sharing Behavior in Epicyclic Gears for Wind Turbines: Preprint

In an ideal epicyclic gear set every parallel gear path transmits the same amount of torque. However, it is well known that certain manufacturing variations result in unequal load sharing between the parallel gear paths. Previous works have developed and validated a general closed-form analytical model of this phenomenon that describes the load sharing characteristics of epicyclic gear sets from three to six planets at any torque level. More recently, this analytical model has been reformulated to include the effects of gravity, carrier bearing clearance, and external applied moments, all of which are relevant to most gearboxes and their mounting configuration in horizontal-axis wind turbines. In this paper, the reformulated model is compared to load measurements collected from two similar wind turbine gearboxes with three-planet epicyclic gear sets. The resulting load sharing values are also compared to the mesh load factor requirements in the AGMA 6006 and IEC 61400-4 wind turbine gearbox design standards. Load sharing factors as high as 1.16 at extreme rotor moments and 1.08 with no moment were measured for the gearbox with cylindrical roller bearings, but the load sharing factor remained below 1.10 for the gearbox with tapered roller bearings The results show that in the wind turbine application, load sharing is not equal - even for three-planet systems with a floating central member because of the effects of gravity, rotor moments, and the resulting relative motions among the epicyclic gear components within the carrier bearing clearance.

closed-form analytical model↗

DOE OSTI2020

Validation of a Generalized Formulation for Load Sharing Behavior in Epicyclic Gears for Wind Turbines

closed-form analytical model↗

DOE OSTI2020

Method and system to separate optically measured coupled parameters

A system includes a first optical sensor sensitive to both a parameter of interest, Parameter1, and at least one confounding parameter, Parameter2 and a second optical sensor sensitive only to the confounding parameter. Measurement circuitry measures M1 in response to light scattered by the first optical sensor, where M1=value of Parameter1+K*value of Parameter2. The measurement circuitry also measures M2 in response to light scattered by the second optical sensor, where M2=value of Parameter2. Compensation circuitry determines a compensation factor, K, for the confounding parameter based on measurements of M1 and M2 taken over multiple load/unload cycles or over one or more thermal cycles. The compensation factor is used to determine the parameter of interest.

Ganguli, Anurag↗

DOE OSTI2020

Panel Session 116: Waste Management from Remediation of Legacy Sites or Unplanned Releases

Past experiences have shown that there is often a disconnect between Indigenous societies and Western society. This disconnect can be attributed to different value systems between these two group and is not limited to the USA and Canada but also extends into Australia, New Zealand, and the Central Asia Republics (the 'five Stans'). The intent of this Panel Session to give voice to representatives from Indigenous communities, the challenges presented in remediation processes, and potential solutions. Standard risk assessment assumptions developed for Western societies often do not adequately address the cultural and spiritual values that may be unique to indigenous societies. This panel focused on the perspectives of Indigenous societies (e.g., Indian Tribes (US), First Nations (Canada)) related to risk assessment of environmental remediation challenges, including deep geological disposal of HLW and ILW, near-surface disposal of LLW and in-situ entombment of nuclear reactor components, and environmental remediation of abandoned uranium mines and historic wastes. Standard risk assessment assumptions often do not adequately address the cultural and spiritual values that may be unique to indigenous societies. Factoring those into a risk assessment that still meets regulatory requirements and policies such as reasonably anticipated land use at US EPA CERCLA sites can be challenging but has the potential to lead to a site or facility approach that is more accepted. Panelists with presentations: The U.S. Nuclear Regulatory Commission Regulatory Process - A Path for Indigenous Knowledge? (Francis Cameron); Local Community Perceptions and Remediation Projects (Michelle Roberts); Indigenous Perspectives on Risk Assessment (Bob Watts); Navajo Superfund Program: Fundamental Law and Traditional Ecological Knowledge (Dariel Yazzie); Risk Assessment: Two Indigenous Approaches (Whitney Fraser)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Measurement of the Neutron Magnetic Form Factor at Large Momentum Transfer Using the Super-Bigbite Apparatus in Jefferson Lab Hall-A

The nucleon elastic electromagnetic form factors help us study the electromagnetic structure of the nucleon, benchmark theoretical models, and improve our understanding of non-perturbative quantum chromodynamics and confinement. The Nobel Prize-winning electron-nucleon scattering experiments by Robert Hofstadter and collaborators in the 1950s at Stanford High Energy Physics Lab were the first nucleon form factor measurements performed using leptonic probes. The Super Bigbite Spectrometer (SBS) program at Hall-A of Jefferson Lab represents the latest efforts to measure nucleon form factors. This ambitious program aims to significantly extend the current data set in terms of square momentum transfer (Q2) with high precision. The advent of novel detector technologies, like Gas Electron Multipliers (GEM), which provide excellent position resolution (< 100 ?m) while withstanding high background particle rates (several hundred MHz/cm2) over a large active area, has paved the way for open-geometry, moderate solid angle spectrometers, which are central to all form factor experiments in the SBS program. The first experimental run group in SBS ran successfully between September 2021 and February 2022, collecting data for the measurement of the magnetic form factor of the neutron Gn M at five squared momentum-transfer values: 3.0, 4.5, 7.5, 9.8, and 13.5 (GeV /c)2. This extends the existing high-precision data for Gn M by about a factor of four. The ratio technique was used, which involved the simultaneous measurement of exclusive quasielastic scattering of D(e,e?n)p and D(e,e?p)n from a deuterium target. Pre-preliminary results for D(e,e?n)p and D(e,e?p)n quasi-elastic ratio, and the neutron magnetic form factor Gn M , for Q2 points 3.0, 9.8, and 13.5 (GeV /c)2 are presented.

Mudiyanselage, Anuruddha Rathnayake↗

DOE OSTI2021

A review of imputation strategies for isobaric labeling-based shotgun proteomics

The throughput efficiency and increased depth of coverage provided by isobaric-labeled proteomics measurements have led to increased usage of these techniques. However, the structure of missing data is uniquely different than unlabeled studies. In this review, we compare the efficacy of nine imputation methods on a CPTAC proteomics iTRAQ dataset. Imputation methods were evaluated with regard to accuracy, variability, statistical hypothesis test inference and run time over datasets consisting of varying number of iTRAQ plexes and percentages of missing data. In general, expectation maximization and random forest imputation methods yielded the best performances, and constant-based methods performed poorly consistently across all dataset sizes and percentages of missing values. For datasets with small sample sizes and higher percentages of missing data, results indicate that statistical inference with no imputation may be preferable. Based on the findings in this review, there are core imputation methods that perform higher for isobaric-labeled proteomics data, but great care and consideration as to whether imputation should be used should be given for datasets comprised of a small number of samples, as well as to factors such as computational time and reproducibility of imputation values.

Bramer, Lisa M.↗

DOE OSTI2023

Monte Carlo Analyses of the FOEHN Experiment

The FOEHN critical experiment, which has been carried out at Cadarache (France) in the reactor EOLE in the early 70s, was designed to verify RHF design analyses. This study focuses on the impact of the FOEHN experiment uncertainties on the calculation of the energy deposition. The latter has been obtained by the Monte Carlo codes Serpent and MCNP. In the calculation of the energy deposition, the first code relies on KERMA factors whereas the latter code relies on Q-values. The two Monte Carlo codes share the same geometry and material specifications. In addition to the design and experiment parameters uncertainties, nuclear data also impacts the calculation of the energy deposition. In this study, the MCNP simulations use three different nuclear data library sets: ENDF/B versions VII.0, VII.1, and VIII.0. Finally, the ksens card of MCNP, using perturbation theory, has been used to identify the cross sections and isotopes with largest impact on the effective multiplication factor. By showing that the use of different software and computational methodologies and design parameters uncertainties do not significantly impact the core power distribution, this work demonstrate the appropriateness of the tools and methods employed for the conversion of involute-plate reactors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Simulation of enhanced light extraction from periodic, disordered, and quasi-periodic OLED structures

Here we have developed a rigorous scattering matrix theory of light emission from periodically structured media using a Green’s function approach. We computationally simulate the spectral power inside the structure, incorporating Purcell factor enhancements, and find internal waveguiding modes and plasmonic losses. We simulate the light-outcoupling factor η out and describe how corrugations and structured media can enhance η out . We have extended our framework to describe non-periodic disordered arrays as well as aperiodic quasi-crystalline arrays. Flat organic light-emitting diodes (OLEDs) have low outcoupling with η out ~20% since most of the light is trapped in waveguided modes in higher index layers or lost to plasmonic excitations at the metal cathode. Periodically corrugated OLEDs can achieve highly enhanced η out ~65%-70% for pitch values between 1000 and 2000 nm, representing an enhancement factor >3 over planar structures. Periodic corrugations strongly diffract trapped waveguided and plasmonic modes to the emissive air cone. Disordered templates also can cause significant enhanced outcoupling with η out ~50%-55% for smaller nearest-neighbor separations of 300–400 nm. Quasi-crystalline tilings can also lead to enhancements of η out ~50%-55%. This framework can be utilized to design novel structured media that can generate high light extraction.

42 ENGINEERING↗

DOE OSTI2022

Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6

Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Scaling Properties of φ -Meson and Light Charged Hadron Production in Small and Large Systems at PHENIX

Recent results on the identified charged-hadron (π ± , K ± , p, p¯) production vat midrapidity region (|η| < 0.35) have been measured by the PHENIX experiment in p + Al, 3 He + Au, Cu + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and U + U collisions at $\sqrt{s_{NN}}$ = 193 GeV. These measurements are presented through the invariant transverse-momentum (p T ) and transverse-mass (m T ) spectra for different collision centralities. The averaged freeze-out temperature value for different systems was found to be 166.1 ± 2.2 MeV, and do not exhibit any dependence on the collision centrality and $\langle$N parti $\rangle$ values. The particle ratios of K/π and p/π have been measured in different centrality ranges of large and small collision systems. The values of K/π ratios measured in all considered collision systems were found to be consistent with those measured in p+p collisions. Furthermore, the identified charged-hadron nuclear-modification factors (R AB ) are also presented. Enhancement of proton R AB values over meson R AB values was observed in central 3 He+Au, Cu+Au, and U+U collisions. The proton R AB values measured in p+Al collision system were found to be consistent with R AB values of Φ, π ± , K ± , and π 0 mesons, suggesting that the size of the system produced in p+Al collisions is too small for recombination to cause a noticeable increase in proton production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.

Lian, Zhichuang↗

DOE OSTI2021

Resilience of terrestrial and aquatic fauna to historical and future wildfire regimes in western North America

Wildfires in many western North American forests are becoming more frequent, larger, and severe, with changed seasonal patterns. In response, coniferous forest ecosystems will transition toward dominance by fire-adapted hardwoods, shrubs, meadows, and grasslands, which may benefit some faunal communities, but not others. We describe factors that limit and promote faunal resilience to shifting wildfire regimes for terrestrial and aquatic ecosystems. We highlight the potential value of interspersed nonforest patches to terrestrial wildlife. Similarly, we review watershed thresholds and factors that control the resilience of aquatic ecosystems to wildfire, mediated by thermal changes and chemical, debris, and sediment loadings. We present a 2-dimensional life history framework to describe temporal and spatial life history traits that species use to resist wildfire effects or to recover after wildfire disturbance at a metapopulation scale. The role of fire refuge is explored for metapopulations of species. In aquatic systems, recovery of assemblages postfire may be faster for smaller fires where unburned tributary basins or instream structures provide refuge from debris and sediment flows. We envision that more-frequent, lower-severity fires will favor opportunistic species and that less-frequent high-severity fires will favor better competitors. Along the spatial dimension, we hypothesize that fire regimes that are predictable and generate burned patches in close proximity to refuge will favor species that move to refuges and later recolonize, whereas fire regimes that tend to generate less-severely burned patches may favor species that shelter in place. Looking beyond the trees to forest fauna, we consider mitigation options to enhance resilience and buy time for species facing a no-analog future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Black-Box Optimization for Design of Concentrating Solar Power and Photovoltaic Hybrid Systems with Optimal Dispatch Decisions

The hybridization of concentrating solar power (CSP) and photovoltaics (PV) can enable dispatchable renewable electricity generation at a lower price than current stand-alone CSP systems. However, designing a CSP-PV hybrid system can be challenging because of the many degrees of freedom in design that affect the internal and external system interactions and trade-offs. We develop a methodology to determine optimal designs for CSP-PV hybrids by implementing NLopt's derivative-free, or “black-box,” algorithms around pre-existing CSP-PV hybrid simulation software that utilizes the National Renewable Energy Laboratory’s System Advisor Model (SAM); we then employ a dispatch optimization model to determine operational decisions that maximize a plant’s profits. We present optimal designs for CSP-PV hybrid systems dispatching against four time-of-delivery (ToD) pricing structures. NLopt’s algorithms can improve the base case design’s power purchase agreement (PPA) price by 15% to 21%, depending on the ToD pricing structure. In addition, we present the resulting optimal CSP-PV hybrid design’s annual performance metrics, which tend to have capacity factors between 50% and 62%, but are able to generate electricity during the year’s highest-valued periods about 90% of the time. Lastly, we investigate the trade-offs between capacity factor and PPA price using Pareto fronts and demonstrate that, for some ToD pricing structures, the system capacity factor can increase by 20% but at the expense of a 2% increase in PPA price.

black-box↗

DOE OSTI2020

Low-energy 23 Al β-delayed proton decay and 22 Na destruction in novae

The radionuclide 22 Na is a target of γ-ray astronomy searches, predicted to be produced during thermonuclear runaways driving classical novae. The 22 Na (p, γ) 23 Mg reaction is the main destruction channel of 22 Na during a nova, hence, its rate is needed to accurately predict the 22 Na yield. However, experimental determinations of the resonance strengths have led to inconsistent results. In this Rapid Communication, we report a measurement of the branching ratios of the 23 Al β-delayed protons as a probe of the key 204-keV (center-of-mass) 22 Na (p, γ) 23 Mg resonance strength. We report a factor of 5 lower branching ratio compared to the most recent literature value. The variation in 22 Na yield due to nuclear data inconsistencies was assessed using a series of hydrodynamic nova outburst simulations and has increased to a factor of 3.8, corresponding to a factor of ≈ 2 uncertainty in the maximum detectability distance. Finally, this is the first reported scientific measurement using the Gaseous Detector with Germanium Tagging system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Absolute measurement of the Fano factor using a Skipper-CCD

Skipper-CCD can achieve deep sub-electron readout noise making possible the absolute determination of the exact number of ionized electrons in a large range, from 0 to above 1900 electrons. In this work we present a novel technique that exploits this unique capability to allow self-calibration and the ultimate determination of silicon properties. We performed an absolute measurement of the variance and the mean number of the charge distribution produced by $^{55}$Fe X-rays, getting a Fano factor absolute measurement in Si at 123K and 5.9 keV. A value of 0.119 $\pm$ 0.002 was found and the electron-hole pair creation energy was determined to be (3.749 $\pm$ 0.001) eV. This technology opens the opportunity for direct measurements of the Fano factor at low energies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Cesium Removal Performance Comparisons of Crystalline Silicotitanate Media Batches with Savannah River Site Waste Simulant

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with Crystalline Silicotitanate (CST) media to process radioactive waste solutions for the removal of Cs137. TCCR currently focuses on dissolving Savannah River Site (SRS) Tank 10H waste (primarily sodium salt cake solids) within the tank followed by at-tank ion exchange column treatment. Plans are underway to prepare and install a second TCCR unit at SRS. Capacity and particle size differences exist between archived (IE-911) and more recently-prepared CST media batches (9120- B and 9140-B). Side-by-side comparison testing was performed to evaluate the cesium removal performance of each batch to aid in selecting the preferred CST batch and media characteristics to load into the second TCCR unit. Batch contact equilibrium and flow-through column tests have been conducted with three CST batches using an SRS Average Simulant. Simulant batch contact equilibrium cesium loading results for the three CST batches (including two lots of one batch) are provided in Table ES-1. The 35 °C data indicates that the archived IE-911 batch has a higher cesium capacity than recently-prepared CST media and that the minor TCCR CST 9120-B media lot (2099000035) has similar cesium removal performance to the major TCCR lot (2099000034). Tests conducted at 25 ºC for the archived IE-911 CST batch indicated lower cesium removal performance with this simulant batch than was observed recently with a different SRS Average Simulant batch. A dilution factor (DF) is typically utilized when modeling engineered CST media cesium loading performance to account for mass contributions from the binder material. In cases where CST performance is lower than expected, this factor includes corrections for the binder and for low performance. The ZAM (Zheng, Anthony, and Miller) Isotherm Model DF values are provided in Table ES-1 for each simulant batch contact result. DF values near 0.5 were determined for the 9120-B and 9140-B CST batch contact tests while DF values near 0.6 (20% higher) were determined for the tests with IE-911. These dilution factors are lower than recently observed with a different SRS Average Simulant batch (9140-B DF = 0.68; IE-911 DF = 1.0). Based on these results, it appears that some component in the simulant solution used for equilibrium testing may have resulted in reduced cesium loading on the CST media.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Assessing the predictive impact of factor fixing with an adaptive uncertainty-based approach .

Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identify groups of sensitive parameters, then quantifies which groups can be safely fixed at nominal values without exceeding a maximum acceptable error, demonstrated using the 21-dimensional Sobol’ G-function. Furthermore, three error measures are considered for quantities of interest, namely Relative Mean Absolute Error, Pearson Product-Moment Correlation and Relative Variance. Results demonstrate that factor fixing may cause large errors in the model results unexpectedly, when preliminary analysis suggests otherwise, and that the default value selected affects the number of factors to fix. To improve the applicability and methodological development of factor fixing, a new research agenda encompassing five opportunities is discussed for further attention.

54 ENVIRONMENTAL SCIENCES↗