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The Alliance for Residential Building Innovation (ARBI) team conducted a deep retrofit project within Stockton’s Large-Scale Retrofit Program that expanded on the standard package by adding HVAC, water heater and window upgrades to the ducting, attic and floor insulation, domestic hot water insulation, envelope sealing, lighting and ventilation upgrades. Post-retrofit site energy savings were 23% compared to the pre-retrofit case.
In this project,the Alliance for Residential Building Innovation (ARBI) team worked with builders in California to implement wall assemblies meeting a U-value lower than 0.050 Btu/h-ft2-°F. ARBI and its project team members helped builders identify preferred wall designs that met the requirements of their architects, structural engineers, and purchasing agents and that were acceptable to their subcontractors. Construction methods were observed and documented and construction costs obtained from builders were used to inform cost estimates for a range of advanced wall system types and insulation types. Wall framing types of 2 × 6 (16- and 24-in. on center [o.c.]) and double stud were modeled in Building Energy Optimization (BEopt™) software with cavity insulation levels ranging from R-19 to R-33 (double stud) and exterior rigid insulation of R-4, R-6, and R-8.
California has been seeing more wildfires in recent years, resulting in huge economic losses and threatening human health. Clarifying the meteorological environments of wildfires is foundational to improving the understanding and prediction of wildfires and their impacts. Here, 1535 California wildfires during 1984-2017 are systematically investigated. Based on two key meteorological factors - temperature and moisture anomalies - all wildfires are classified into four groups: hot-dry, hot-wet, cold-dry, cold-wet. Most (~60%) wildfires occurred on hot-dry days. Compositing the large-scale environments of the four groups shows that persistent high pressure and strong northeasterly wind descending from inland favor hot-dry conditions for wildfires. This analysis also reveals an important role of anomalies in southerly onshore flow that supports stronger convection, accompanied by more lightning flashes that provide a triggering mechanism for wildfires under hot-wet conditions. Self-organizing map analysis lends confidence in the large-scale meteorological pattern for dominating hot-dry wildfires in California. Besides wildfire occurrence, wildfire size is also influenced by meteorological anomalies through their magnitudes. Among them, moisture anomaly explains the largest fraction (~69%) of variability in wildfire sizes. Large-scale meteorological anomalies are found to play an important role in the devastating 2018 wildfire season in California. During 1984-2017, wildfire burned area has significantly increased by ~3.6% per year, indicating a doubling of burned area in 2017 relative to 1984, with the trend dominated by hot-dry wildfires in summer. Drying and warming in conjunction with strengthening of the high pressure in summer support more frequent and larger wildfires in California.
High river temperatures, or “thermal extremes”, can cause fish mortality and thermoelectric powerplant derating. Under climate change, projected higher air temperature and stronger surface energy fluxes will lead to increased water temperatures, exacerbating thermal extremes. However, cold hypolimnetic releases from thermally stratified reservoirs can depress tailwater temperatures and therefore alleviate thermal extremes. Thermal extremes are more harmful when they coincide with low flows, which we refer to as “hydrologic hot-dry events”. To assess multisectoral impacts of climate change over large regions, we evaluate thermal events according to three impact attributes: duration (D), intensity (I), and severity (S). We apply an established model framework to simulate streamflow and stream temperature over the southeastern US regulated river system. We quantify climate change impacts (by the 2080s under RCP8.5) by comparing historical and future periods and quantify regulation impacts by comparing unregulated and regulated scenarios. We find that climate change will exacerbate thermal extremes (all three metrics) in both unregulated and regulated scenarios, albeit less in the regulated scenario. Thermal mitigation from reservoir regulation will be stronger under climate change, decreasing the three metrics compared to the unregulated case. Even so, thermal extremes in the regulated scenario will still be more severe under climate change, and only 12.2%, 19.7%, and 26.0% of D, I, and S can be mitigated by reservoirs. Despite stronger reservoir stratification, the number of regulated river segments that experience simultaneous high temperature and low flow events (hydrologic hot-dry events) will increase by 21.4% by the 2080s under RCP8.5. These events will have a median annual duration of 10.3 days/year, over 10 times the historical value.
Degradation of photovoltaic (PV) module encapsulant characteristics that lead to mechanical embrittlement and delamination remains a cause of failure in solar installations. A multiscale reliability model connecting the encapsulant mechanical and fracture properties to the degraded molecular structure and interfacial bonding to adjacent solar cell and glass substrates was previously published. The model, developed primarily for poly(ethylene-co-vinyl acetate) acetate (EVA) encapsulants, remains to be experimentally validated. Determining the degradation and crosslinking kinetics of alternative encapsulants, such as polyolefin elastomer (POE) and EVA/POE/EVA composites (EPE), can generalize the model. In this work, we subject fully cured EVA, POE, and EPE encapsulants to accelerated thermal aging to determine how high temperatures impact reaction kinetics. An increase in gel content (crosslinking) and decrease in crystallinity of the encapsulants under hot-aerobic (90 degrees C, 22% RH) and hot-anaerobic (90 degrees C, sealed in N 2 air) aging were observed, even in the absence of UV and crosslinking initiators. Fourier transform infrared spectroscopy (FTIR)-attenuated total reflectance analysis showed insignificant encapsulant degradation, demonstrating the critical role of UV and moisture in accelerating degradation. Adhesion testing performed on coupon-level specimens (cell/encapsulant/glass laminates) showed decreases in adhesion energy, Gc , from 5000 h of hot-dry (90 degrees C, ~1% RH) and hot-humid (90 degrees C, 60% RH) aging. POE coupons demonstrated the best stability, followed by EPE then EVA. For EVA and POE, hot-humid aged coupons experienced a larger decrease in Gc due to enhanced hydrolytic degradation. Hot-dry aging condition demonstrated that thermal degradation of the interface could be significant even if the encapsulant experiences negligible degradation in the absence of UV and elevated humidity.
In this study, a novel sizing methodology was developed for centralized and interconnected operating strategies of transactive microgrids and several variables were investigated including starting month, initial charge of battery, load variability, unit cost of solar panels and energy storage, number of systems, climate, and required reliability to determine their effect on total cost. The centralized strategy improved cost by seven to ten percent compared to the isolated strategy in every case. The interconnected strategy saved an incremental amount of money consistently compared to the isolated standard. The number of connected systems was not a strong effect. It was thought that increasing the number of systems would increase the benefit of energy sharing. Climate zones studied (“Cold”; “Hot-Dry/Mixed Dry”; “Mixed Humid”; and “Cold but with lower solar irradiation”) showed a large variation on cost with the Hot-Dry/Mixed Dry being the least expensive and Cold, with lower solar irradiation being the most expensive. Cost sensitivity analysis was performed showing that the unit cost of solar has a greater effect on the total cost. Required reliability of power, measured in outage hours, exhibited an inverse relation with cost.
To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.
Climate and land use patterns are expected to change dramatically in the coming century, raising concern about their effects on wildfire patterns and subsequent impacts to human communities. The relative influence of climate versus land use on fires and their impacts, however, remains unclear, particularly given the substantial geographical variability in fire-prone places like California. Here, we developed a modeling framework to compare the importance of climatic and human variables for explaining fire patterns and structure loss for three diverse California landscapes, then projected future large fire and structure loss probability under two different climate (hot-dry or warm-wet) and two different land use (rural or urban residential growth) scenarios. The relative importance of climate and housing pattern varied across regions and according to fire size or whether the model was for large fires or structure loss. The differing strengths of these relationships, in addition to differences in the nature and magnitude of projected climate or land use change, dictated the extent to which large fires or structure loss were projected to change in the future. Despite this variability, housing and human infrastructure were consistently more responsible for explaining fire ignitions and structure loss probability, whereas climate, topography, and fuel variables were more important for explaining large fire patterns. For all study areas, most structure loss occurred in areas with low housing density (from 0.08 to 2.01 units/ha), and expansion of rural residential land use increased structure loss probability in the future. Regardless of future climate scenario, large fire probability was only projected to increase in the northern and interior parts of the state, whereas climate change had no projected impact on fire probability in southern California. Given the variation in fire-climate relationships and land use effects, policy and management decision-making should be customized for specific geographical regions.
Two roof pond configurations combined with a water-to-air heat exchanger (WAHE) are evaluated. Test cells of 1.35 m × 1.35 m x 1.35 m with the same thermal properties, except for the roofs, are built in a hot-dry climate with mild winters. They are connected with a WAHE placed inside the roof pond's water by a pipe through which the indoor air is re-circulated. The first roof consists of a 0.35 m deep water pond covered with a floating polystyrene insulation 0.03 m thick, and a spray system located 0.5 m above it that operates at night. The second roof is covered with an aluminum plate separated by a 0.10 m air gap above a 0.25 m deep water pond. We ran multiple series and compared the results to a control cell that had a California energy code compliant insulated roof. Predictive equations are developed to dimension the WAHE system. Results demonstrate that the cells with roof ponds have better cooling performance than the code compliant control cell. The best performance is obtained in the cell with the WAHE operating continuously. In this case, the indoor temperature stayed below 24 °C even with ambient temperatures above 35 °C.
Accelerated warming in the Arctic, as compared to the rest of the globe, might have profound impacts on mid-latitude weather. Most studies analyzing Arctic links to mid-latitude weather focused on winter, yet recent summers have seen strong reductions in sea-ice extent and snow cover, a weakened equator-to-pole thermal gradient and associated weakening of the mid-latitude circulation. We review the scientific evidence behind three leading hypotheses on the influence of Arctic changes on mid-latitude summer weather: Weakened storm tracks, shifted jet streams, and amplified quasi-stationary waves. We show that interactions between Arctic teleconnections and other remote and regional feedback processes could lead to more persistent hot-dry extremes in the mid-latitudes. The exact nature of these non-linear interactions is not well quantified but they provide potential high-impact risks for society.
Abstract Satellite observations show that the surface urban heat island intensity (SUHII) has been increasing over the last two decades. This is often accompanied by an increased urban-rural contrast of vegetation greenness. However, the contribution of uneven vegetation trends in urban and rural areas to the trend of SUHII is unclear, due to the confounding effects of climate change and changes in man-made infrastructures and anthropogenic heat sources. Here we use a data-model fusion approach to quantify such contributions during the peak growing season. We show that the LAI dif (the urban-rural difference of leaf area index) is increasing ( P < 0.05) in 189 of the selected 228 global megacities. The increasing trend of LAI dif from 2000 to 2019 accounts for about one quarter of the trend in satellite-derived SUHII, and the impact is particularly evident in places with rapid urbanization and rural cropland intensification. The marginal sensitivity of SUHII to LAI dif is the strongest in hot-humid megacities surrounded by croplands and in hot-dry megacities surrounded by mixed woody and herbaceous vegetation. Our study highlights the role of long-term vegetation trends in modulating the trends of urban-rural temperature differences.
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This paper presents a preliminary reliability analysis of field-aged glass/glass (G/G) PV modules. Several characterization tests were performed on more than 60 modules with two different encapsulant types (EVA and ionomer) exposed in hot-dry Arizona (AZ) climate over 10-35 years. The common degradation mode observed in both encapsulant types was the delamination of encapsulant along with encapsulant browning (EVA only), glass cracking (EVA only), and metallic corrosion over junction box area (ionomer only). The EVA encapsulated G/G modules showed the higher median power degradation rate at 0.91-1.99%/yr whereas modules with ionomer showed the lower at 0.21%/yr.
Qualification testing of solar photovoltaic (PV) modules per IEC 61215 standard encompasses a set of well-defined accelerated stress tests (irradiation, environmental, mechanical and electrical) with strict pass/fail criteria based on functionality/performance, electrical and mechanical safety, and visual requirements. The qualification testing does not identify all the possible reliability failures or durability issues witnessed in the actual field. However, it does identify the major/catastrophic design quality issues (infant mortality), which could occur early in a module’s field life. Unfortunately, in the industry, there is no consensus-based standard or protocol available to validate manufacturers’ warranty period claims based on the end-of-life wear-out failure mechanisms. Being able to predict the field degradation rates and lifetime using mode-specific accelerated tests on moderately field-aged modules, for example 10 years, for certain commonly occurring degradation modes would be a powerful contribution to all the stakeholders of the PV industry. There is a need to formulate guidelines to find the correlation of accelerated testing with field degradation for individual degradation modes observed in the field. Potential approaches to fulfill this need were experimented in this project and are presented in this report. Two of the most commonly seen degradation modes – encapsulant browning and solder bond thermomechanical fatigue – are addressed in this report through presenting the accelerated testing methods and physical modelling approaches. Two accelerated test methods (UV and thermal cycling) were designed to induce the wear-out mechanisms in the modules and not infant mortality failures. To focus on the wear-out failure modes, the tests were performed on field-aged modules, instead of fresh modules, with known degradation rates and degradation modes. The degradation rates were measured based on the degradation rates of individual cell parameters (short-circuit current, I sc and series resistance, R s ) instead of the degradation rate of maximum power (P max ) which cannot be used to study any specific/limited degradation mode as the P max degradation could be caused by many different degradation modes. The key characteristic parameter considered for encapsulant discoloration and solder bond degradation is I sc and R s , respectively. The developed physical models/equations relating the testing degradation data and field weather data were utilized to determine the acceleration factor (AF) and to predict the degradation rate for a specific degradation mode of PV modules installed in two different climates, Arizona (hot) and New York (cold). The predicted degradation rates for encapsulant browning and solder bond degradation have also been validated against the actual measured field degradation rates. UV testing cost reduction: To determine acceleration factor, single UV chamber was used for accelerated UV testing at three different temperatures simultaneously, instead of three chambers for three temperatures (or one chamber sequentially which is an extremely time-consuming approach). A passive heating approach was successfully used to achieve and maintain multiple temperatures in the accelerated UV chamber. Foam insulation boards of varying thicknesses were utilized to obtain three different temperatures for UV testing. However, these foam materials tend to disintegrate in the presence of moisture. To alleviate this problem, silicone heating blankets with temperature controls and humidifier can be used if the UV testing is to be performed under hot-humid conditions instead of conventional hot-dry conditions. Thermal cycling testing cost reduction: Single thermal cycling chamber was used for accelerated thermal cycling testing at three different upper temperatures simultaneously, instead of three chambers for three upper temperatures (or one chamber sequentially which is an extremely time-consuming approach). An active heating approach based on silicone heating blankets was successfully used to achieve and maintain multiple upper temperatures in the accelerated thermal cycling chamber. Such blankets provide stable temperature control and thereby more reliable and repeatable for replicate experiments.
The operating temperatures of photovoltaic (PV) modules can be impacted by the selection of specific packaging materials, e.g., backsheets and encapsulants. This research focuses on the evaluation of operating temperature reduction of one-cell modules by comparing conventional Tedlar/polyester/Tedlar (TPT) backsheet with novel thermally conductive backsheets (TCBs) materials. A large number of one-cell modules with two TCB types (TCB_A and TCB_B) and baseline TPT type were fabricated and installed in three different climatic conditions of the hot-dry desert in Arizona (high and low wind speed locations) and North Carolina (temperate with low wind speed location). In this study, these two TCBs were compared with conventional TPT backsheet in terms of performance, lifetime and levelized cost of energy (LCOE). The field results were analyzed for thermal performance of TCBs compared to TPT at three sites for two and half years. This study concludes that the thermal and electrical performances of the PV modules can be improved by using TCB_A in hot and dry climate sites and TCB_B at temperate climate sites. Therefore, the lifetime of TCB-based modules is expected to be higher than TPT-based modules. Using backsheet-specific power degradation levels and assuming the same cost for both types of backsheets, the LCOE of modules using TCBs is estimated to be lower than that of TPT.
Histidyl-histidine is a remarkably effective catalyst of peptide bond formation in the reaction of glycine in a fluctuating (hot-dry, cold-wet) clay environment. It has shown turnover numbers (molecules of glycine incorporated in oligoglycines per molecule of catalyst) as high as 18 in a single cycle and as high as 52 overall. A number of other dipeptides were tested, as well as monomeric histidine, N-acetyl histidine, and imidazole, none of which showed turnover numbers greater than one. Histidyl-histidine is a model for a prebiotic protoenzyme, and implications for the development of a simple translation mechanism are discussed.
Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop−water productivity model) were evaluated for baseline (1980−2009) and mid-century climates (2040−2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to ~31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.