Search NASA⌕ Search

SEARCH · Search NASA

Results for “relative humidity”

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.

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

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Decontamination of SARS-CoV-2 and Other RNA Viruses from N95 Level Meltblown Polypropylene Fabric Using Heat under Different Humidities

In March of 2020, the World Health Organization declared a pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The pandemic led to a shortage of N95-grade filtering facepiece respirators (FFRs), especially surgical-grade N95 FFRs for protection of healthcare professionals against airborne transmission of SARS-CoV-2. We and others have previously reported promising decontamination methods that may be applied to the recycling and reuse of FFRs. In this study we tested disinfection of three viruses, including SARS-CoV-2, dried on a piece of meltblown fabric, the principal component responsible for filtering of fine particles in N95-level FFRs, under a range of temperatures (60–95 °C) at ambient or 100% relative humidity (RH) in conjunction with filtration efficiency testing. We found that heat treatments of 75 °C for 30 min or 85 °C for 20 min at 100% RH resulted in efficient decontamination from the fabric of SARS-CoV-2, human coronavirus NL63 (HCoV-NL63), and another enveloped RNA virus, chikungunya virus vaccine strain 181/25 (CHIKV-181/25), without lowering the meltblown fabric’s filtration efficiency.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Predicting fatal heat and humidity using the heat index model

A unique wet-bulb temperature of 35°C is often used as the threshold for human survivability, but recent experiments have shown that a person’s core temperature starts to rise at a wide range of critical wet-bulb temperatures. Here, it is shown that the model underlying the heat index correctly predicts those critical wet-bulb temperatures, explaining 95% of the variance in the values observed in laboratory heat-stress experiments. This is the first time the heat-index model has been validated against physiological data from laboratory experiments. For light and moderate exertion in an indoor setting, the heat index model predicts that the critical wet-bulb temperature ranges from 20 to 32°C, depending on the relative humidity, consistent with experimental results. Furthermore, for the same setting and exertion, the heat index model predicts fatal wet-bulb temperatures ranging from 24 to 37°C. Recent experiments have identified the critical combinations of heat and humidity, in an indoor setting, above which an individual is unable to maintain a standard core temperature, indicating severe heat stress. It is shown here why this state of severe heat stress cannot be predicted using the wet-bulb temperature. Instead, it is shown that the recently extended heat index model can explain nearly all of the variance in the observed critical combinations of temperature and humidity, and can be used to calculate fatal combinations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vertical Resolution Impacts Explicit Simulation of Deep Convection

Abstract The aggregation of tropical convection greatly influences the mean‐state of the atmosphere, altering humidity distributions, total atmospheric radiative cooling, and cloud amounts. Although studies have demonstrated the sensitivity of convective aggregation to horizontal resolution and domain size, few studies have explored the impact of vertical resolution on convective aggregation. Here, we investigate the impact of vertical resolution on simulations of deep convection and convective aggregation using the System for Atmospheric Modeling convection resolving model. We analyze simulations of tropical radiative‐convective equilibrium with varying vertical levels (32, 64, 128, and 256) across small (100 km), medium (700 km) and large (1,500 km) domains. We demonstrate that relative humidity and cloud fraction decrease with increasing vertical resolution as a result of reduced turbulent mixing. Vertical resolution also influences the occurrence of, onset time, and equilibrium intensity of aggregated convection, and also appears to affect the sensitivity of convective aggregation to domain size. Understanding how simulated convection aggregates, as well as its simulated sensitivity to model formulation, is critical for making and interpreting future predictions of global climate change.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗
DOE OSTI2021

Humidified single-scattering albedometer (H-CAPS-PM SSA ): Design, data analysis, and validation

In this work, we report the development and validation of a new humidified aerosol single-scattering albedometer to quantify the effects of water uptake on submicrometer particle optical properties. The instrument simultaneously measures in situ aerosol light extinction ( σ ep ) and scattering ( σ sp ) using a cavity-attenuated phase shift-single scattering albedo particulate matter (PM) monitor (CAPS-PM SSA , Aerodyne Research, Inc., Billerica, MA, USA). It retrieves by difference aerosol light absorption ( σ ap ) and directly quantifies aerosol single-scattering albedo (SSA), the aerosol “brightness.” We custom built a relative humidity (RH) control system using a water vapor-permeable membrane humidifier and coupled it to the CAPS-PM SSA to enable humidified aerosol observations. Our humidified instrument (H-CAPS-PM SSA ) overcomes problems with noise caused by mirror purge-flow humidification, heating, and characterizing cell RH. Careful angular truncation corrections in scattering, particularly for larger particles, were combined with empirical observations. Results show that the optimal operational size to be D p < 400 nm. The H-CAPS-PM SSA was evaluated with several pure single-component aerosols including ammonium sulfate ((NH 4 ) 2 SO 4 ), absorbing nigrosin, and levoglucosan, an organic biomass smoke tracer. The measured σ ep , σ sp , and the derived optical hygroscopicity parameter ( κ ) for size-selected ammonium sulfate are in good agreement with literature values. For dry size-selected nigrosin in the 100 < D p < 400 nm range, SSA values increased from ~0.3 to 0.65 with increasing D p . The enhancement in nigrosin σ ap at RH = 80% was a factor of 1.05–1.20 relative to dry conditions, with the larger particles showing greater enhancement. SSA increased with RH with the largest fractional enhancement measured for the smallest particles. For polydisperse levoglucosan, we measured an optical κ of 0.26 for both light extinction and scattering and negligible absorption. Our new instrument enables reliable observations of the effects of ambient humidity on mixed aerosol optical properties, particularly for light-absorbing aerosols whose climate forcing is uncertain due to measurement gaps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Empirical validation of building energy simulation model input parameter for multizone commercial building during the cooling season

This paper presents a critical advancement in Building Energy Modeling (BEM) through an empirical validation approach using a high-quality dataset from a multizone commercial office building in Oak Ridge, TN, USA. BEM is widely utilized in diverse construction applications, but its effectiveness relies on the accuracy of its predictions. The study focuses on empirical validation of input parameters in BEM, including building envelope data, infiltration modeling, and rooftop unit system performance curves. The validation of simulation input parameters leads to substantial improvements in the accuracy of simulation results. Notable both NMBE and cv (RMSE) values are reduced by 0.5 % for indoor air temperature and 17 % for indoor air relative humidity compared to the previous model. At the system level, both NMBE and cv (RMSE) values are reduced by 2 % for fan energy consumption and 4 % for cooling energy consumption, compared to the previous model. A literature review highlights a significant gap in empirical validation studies, which predominantly concentrate on either component-level or whole building validation. Furthermore, many studies employ simplified setups that may not faithfully represent the complexities of multizone commercial buildings. This paper distinguishes itself by emphasizing the critical importance of component-level input parameter validation. It underlines the need to validate data related to building envelope components and HVAC system performance curves, resulting in more accurate simulation outcomes. In conclusion, the utilization of actual multizone commercial building data enhances the study's practical relevance. In summary, this research underscores the pivotal role of input parameter validation in enhancing the accuracy and reliability of BEM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Humidity’s impact on greenhouse gas emissions from air conditioning

We report that the increasing need to cool the air in our built environment is both a cause and an effect of climate change. Air conditioning accounts for a large portion of global greenhouse gas emissions today, which we estimate at 3.9%; however, the role that humidity plays in these emissions is often overlooked. Here, we show that the emissions associated with reducing air humidity (i.e., removing water vapor from air) are larger than emissions associated with reducing air temperature (i.e., cooling air). We calculate these emissions for today and 2050 and show how dramatically humidity-related emissions will increase with rising cooling demand around the world. We also calculate the minimum separation energy for removing water vapor from air and find that this is at least an order of magnitude less than the processes used today.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Particle-Phase Diffusion Modulates Partitioning of Semivolatile Organic Compounds to Aged Secondary Organic Aerosol

The diffusivity of semivolatile organic compounds (SVOCs) in the bulk particle phase of a viscous atmospheric secondary organic aerosol (SOA) can have a profound impact on aerosol growth and size distribution dynamics. Here, we investigate the bulk diffusivity of SVOCs formed from photo-oxidation of isoprene as they partition to a bimodal aerosol consisting of an Aitken (potassium sulfate) and accumulation mode (aged α-pinene SOA) particles as a function of relative humidity (RH). The model analysis of the observed size distribution evolution shows that liquid-like diffusion coefficient values of D b > 10 –10 cm 2 s –1 fail to explain the growth of the Aitken mode. Instead, much lower values of Db between 2.5 × 10 –15 cm 2 s –1 at 32% RH and 8 × 10 –15 cm 2 s –1 at 82% RH were needed to successfully reproduce the growth of both modes. The diffusivity within the aged α-pinene SOA remains appreciably slow even at 80% RH, resulting in hindered partitioning of SVOCs to large viscous particles and allowing smaller and relatively less viscous particles to effectively absorb the available SVOCs and grow much faster than would be possible otherwise. Our results have important implications for modeling SOA formation and growth in the ambient atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Challenges to detection: Humidity as a spur to chemical agent change

Detecting chemical agents in outdoor environments such as a battlefield is made challenging by not only the spurious signatures from background chemicals and surfaces (e.g. asphalt, dirt, concrete), but also by the chemical transformation of the actual agents. The change of CW agents to other species can be catalyzed by other chemicals present in the scene, by different substrates, as well as by local weather conditions. Some of the final environmental transformation products are known (e.g. for the G agents methylphosphonic acid), but many of the intermediate chemical states are not, nor are the rates of transformation to the other intermediates or the end products. In this study we have made preliminary optical investigations into the degradation products of a G-agent intermediate, namely methylphosphonic anhydride and its rate of conversion to the more stable methylphosphonic acid. Using infrared and Raman spectroscopies, we have found that the relative humidity (RH) greatly affects the rate of change and we report first results from these studies.

: chemical warfare agent detection, Methylphosphon↗
DOE OSTI2022

Aqueous spray-drying synthesis of alluaudite Na 2+2x Fe 2–x (SO 4 ) 3 sodium insertion material: studies of electrochemical activity, thermodynamic stability, and humidity-induced phase transition

In pursuit of high-energy density sodium insertion materials, polyanionic frameworks can be designed with tuneable high-voltage operation stemming from inductive effect. Alluaudite Na 2 Fe 2 (SO 4 ) 3 polysulfate forms one such earth-abundant compound registering the highest Fe 3+ /Fe 2+ redox potential (ca. 3.8 V vs. Na/Na + ). While this SO 4 -based system exhibits high voltage operation, it is prone to thermal decomposition and moisture attack leading to hydrated derivatives, making its synthesis cumbersome. Also, the Na–Fe–S–O quaternary system is rich with (anhydrous to hydrated) phase transitions. Herein, we demonstrate scalable aqueous-based spray drying synthesis of alluaudite Na 2+2x Fe 2–x (SO 4 ) 3 sodium insertion material involving the formation of bloedite Na 2 Fe(SO 4 ) 2 ·4H 2 O as an intermediate phase. Moreover, a reversible phase transition from alluaudite to bloedite under controlled conditions of temperature and relative humidity is reported for the first time. Thermochemistry measurements revealed the enthalpies of formation (ΔH° f ) of alluaudite and bloedite are exothermic. Hydrated bloedite (ΔH° f = –117.16 ± 1.10 kJ/mol) was found to be significantly more energetically stable than anhydrous alluaudite (ΔH° f = –11.76 ± 1.25 kJ/mol). The calorimetric data support the observed synthesis and transformation (hydration-dehydration) pathways. Spray drying route led to spherical morphology delivering capacity ~80 mAh/g. Spray drying can be extended for rapid economic synthesis of sulfate class of battery materials.

25 ENERGY STORAGE↗
DOE OSTI2021

The De-Icing Comparison Experiment (D-ICE): a study of broadband radiometric measurements under icing conditions in the Arctic

Abstract. Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in Utqiaġvik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the US Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator–heater performance overall was skillful with the average of the systems mitigating ice formation 77 % (many >90 %) of the time during which icing conditions were present. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ∼0.6 ∘C of warming, enough to subsaturate the air up to a relative humidity (with respect to ice) of ∼105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes was assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources in both the shortwave and longwave.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Validation of Hygrothermal Simulations with Wall Performance Experiments in an Environmental Chamber

Oak Ridge National Laboratory is developing a web tool, built on a rule-based expert system, that aids stakeholders in designing energy-efficient moisture-durable walls. Currently, the tool’s expert system database is mostly populated with expert opinion, but work is being done to incorporate durability assessment based on stochastic hygrothermal modeling. Chamber experiments have been conducted to validate the hygrothermal models. The measured temperature and humidity have been compared with those predicted by the hygrothermal model. Experiments and comparison to one-dimensional hygrothermal modeling results were completed with two walls, a Structural Insulated Panel (SIP) based wall and a Concrete Masonry Unit (CMU) based wall. The two walls were succumbed to typical Chicago weather in ORNL’s Heat, Air and Moisture chamber. The walls were sequentially exposed to different scenarios, including diffusion, wetting, air leakage and solar radiation. For the most part, the hygrothermal simulations can be successfully used to predict the performance of these wall systems for the moisture transport phenomenon. Errors between measured and simulated values decreased as measurements got closer to the interior side of the wall. The root mean square error was larger for relative humidity (up to 17.5%-RH for CMU) than for temperature (up to 4.5°C for CMU wall). The errors were larger for the CMU wall than the wood frame wall. The phenomenon, including liquid water, caused large discrepancies between measurement and simulation results, and simulated results showed slower drying of materials than measured results. The one-dimensional nature of the simulation model made simulating air leaks difficult but not impossible.

Salonvaara, Mikael↗
DOE OSTI2020

Degradation in photovoltaic encapsulation strength of attachment: Results of the first PVQAT TG5 artificial weathering study

Delamination of the encapsulant in photovoltaic (PV) module technology results in immediate optical loss and may enable subsequent corrosion or mechanical damage. The effects of artificial weathering were not previously known; therefore, an empirical study was performed to survey the factors most affecting adhesion, including the ultraviolet (UV) source (ie, Xe or fluorescent lamp[s]), the optical filters for the lamp, the chamber temperature, and the relative humidity. Natural weathering was also performed at locations, including the following: Golden, Colorado; Miami, Florida; Phoenix, Arizona; QiongHai, China; Riyadh, Saudi Arabia; and Turpan, China. Specimens were constructed using a laminated glass/poly (ethylene-co-vinyl acetate)/glass geometry. The compressive shear test (CST) was used to quantify the mechanical strength of attachment, taken as a proxy for adhesion. The fractography of select specimens (including cross-sectional optical microscopy) was used to verify the failure mode (delamination or decohesion). Additional analysis of the local solar spectrum as well as the specimen temperature was performed to interpret the results of natural weathering. The goals of this study include to identify the most significant stressors, clarify where strong coupling may occur between stressors, and validate accelerated test results relative to natural weathering. The importance of specimen conditioning (for moisture) and hygrometric degradation as well as the effects of UV degradation are identified in this paper.

14 SOLAR ENERGY↗
DOE OSTI2023

The Role of Interactive Soil Moisture in Land Drying Under Anthropogenic Warming

Abstract Relative humidity (RH) is projected to increase over ocean but decrease over land under anthropogenic warming. The land RH decrease was previously attributed to ocean influences on land changes. Here, we show that interactive soil moisture (SM) is necessary and may be sufficient for anthropogenic warming to reduce the land RH. The land RH decrease is absent in simulations with realistic land‐ocean geometry but fixed SM, and present in simulations with interactive SM but no oceans or changes in precipitation minus evaporation. The land RH decrease is coupled to the SM decline and the latter could be understood as a natural response of interactive SM to anthropogenic warming. Specifically, prior to adjustments in SM and RH, evaporation would increase by ∼6% K −1 following the Clausius–Clapeyron relation, outpacing the radiatively constrained ∼2% K −1 precipitation increase. This prior imbalance depletes SM and consequently reduces RH through the coupling between SM and RH.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Correlation of Mesoscale Humidity Anomalies With Mesoscale Organization of Marine Stratocumulus From Observations Over the ARM Eastern North Atlantic Site

The structure of mesoscale cellular organization in marine cloud-topped boundary layers is found to be well characterized by using a novel compositing approach based on mesoscale variations in the column water vapor path (WVP). The approach is applied to ground-based observations from the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic site. Based on a set of satellite and ground-based observational criteria, 381 hr of closed-cell and 227 hr of open-cell cases were selected from late 2015 to early 2018. Strong correlations are found between mesoscale-filtered cloud properties and WVP for both closed-cell and open-cell regimes. In the moist atmospheric columns, the clouds are thicker with higher tops and lower bases, and stronger precipitation compared to that in the dry columns. Overall, cloud properties of open and closed cells covary similarly with mesoscale moisture perturbations, except that the correlation of liquid water path with WVP is much weaker for open cells. The relations of subcloud properties with WVP are also examined. In the moist columns, surface equivalent potential temperature and relative humidity are higher than in the dry columns. A marginally negative correlation between mesoscale-filtered subcloud turbulence eddy dissipation rate and WVP is found for closed cells. These results are consistent with the conceptual model of closed cellular mesoscale circulations of Zhou and Bretherton (2019).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying Optical Loss of High-Voltage Degradation Modes in PV Modules Using Spectral Analysis [Slides]

The direct current bias for photovoltaic (PV) modules interconnected in series-strings may include both high voltage negative ("HV-") and positive ("HV+") polarity with respect to the electrical ground. Multiple degradation modes, resulting in quantifiable optical loss, were found to occur during HV-/HV+ sequential stress, including: corrosion of the external glass surface, encapsulant delamination (at its interfaces with the glass and the PV cell), internal haze formation (resulting from a chemical interaction between the glass and the encapsulant), corrosion and migration of the gridlines, and corrosion of the silicon nitride (SixNy) antireflective coating on the cell. The effects of these separate modes were examined using monolithic (e.g., glass or PV cell) and laminated-coupon (glass/encapsulant/glass or glass/encapsulant/cell/encapsulant/backsheet) specimens. Characterizations during and after unbiased accelerated testing at 85 degrees C/85% relative humidity included: spectrophotometry, optical microscopy, electron microscopy, and ellipsometry. For some module components (i.e., the glass and the SixNy coating), the optical performance was determined through iterative analysis of empirical measurements. Concentrating on just their spectral effect, a novel model was then developed to estimate the transfer of light to the PV cell and the return of light from the PV module with simultaneous degradation mechanisms, which was compared to a mini-module previously subjected to HV-/HV+ stress. The model suggests one-third of the current loss observed for the mini-module can be attributed to the optical degradation of the packaging materials. The dominant degradation modes include encapsulant delamination and corrosion of the SixNy coating. Recommendations are given so that the optical model may be improved relative to accelerated testing and validated relative to field aging.

14 SOLAR ENERGY↗