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At least 19 records

Does More Storage Give California More Water?

Abstract Increasing reservoir storage is commonly proposed to mitigate increasing water demand and provide drought reserves, especially in semiarid regions such as California. This paper examines the value of expanding surface reservoir capacity in California using hydroeconomic modeling for historical conditions, a future warm‐dry climate, and California's recently adopted policy to end groundwater overdraft. Results show expanding surface storage capacity rarely provides sizable economic value in most of California. On average, expanding facilities north of California's Delta provides some benefit in 92% of 82 years modeled under historical conditions and in 61% of years modeled in a warm‐dry climate. South of California's Delta, expanding storage capacity provides no benefits in 14% of years modeled under historical conditions and 99% of years modeled with a warm‐dry climate. Results vary across facilities between and within regions. The limited benefit of surface storage capacity expansion to statewide water supply should be considered in planning California's water infrastructure.

Nover, D. M.↗

More Than 40 yr of Potentially Induced Seismicity Close to the San Andreas Fault in San Ardo, Central California

Evidence for fluid–injection–induced seismicity is rare in California hydrocarbon basins, despite widespread injection close to seismically active faults. We investigate a potential case of injection–induced earthquakes associated with San Ardo oilfield operations that began in the early 1950s. The largest potentially induced events occurred in 1955 (M L 5.2) and 1985 (M w 4.5) within ~6 km from the oilfield. We analyze Synthetic Aperture Radar interferometric images acquired by Sentinel–1A/B satellites between 2016 and 2020 and find surface deformation of up to 1.5 cm/yr, indicating pressure–imbalance in parts of the oilfield. Fluid injection in San Ardo is concentrated within highly permeable rocks directly above the granitic basement at a depth of ~800 m. Seismicity predominantly occurs along basement faults at 6–13 km depths. Seismicity and wastewater disposal wells are spatially correlated to the north of the oilfield. Temporal correlations are observed over more than 40 yr with correlation coefficients of up to 0.71 for seismicity within a 24 km distance from the oilfield. Such large distances have not previously been observed in California but are similar to the large spatial footprint of injection in Oklahoma. Furthermore, the San Ardo seismicity shows anomalous clustering with earthquakes consistently occurring at close spatial proximity but long interevent times. Similar clustering has previously been reported in California geothermal fields and may be indicative of seismicity driven by long–term, spatially persistent external forcing.

58 GEOSCIENCES↗

Water-Energy Considerations in California’s Agricultural Sector and Opportunities to Provide Flexibility to California’s Grid

Water and energy use on farms are deeply linked, and trends changing the way water is used on farms have implications for the electrical grid, and vice versa. In 2014, California’s agricultural sector accounted for approximately 80% of the state’s water consumption and 5% of its electricity use. The majority of the electricity was for surface conveyance and groundwater pumping. Diminishing surface water availability and increasing reliance on groundwater pumping are likely to increase future energy demand. These trends are coincident with farms embracing new precision irrigation technologies that increase water productivity and crop yield, but may have the potential of other collateral effects, such as increasing energy intensity of irrigation and total electricity use, and thus demand on the grid. The impacts of these technologies and their loads on the electrical grid have been explored only to a limited degree, and the potential grid benefits afforded by these technologies have been studied even less. For example, studies show that California’s increasing adoption of renewable electricity may result in excess generation during certain periods of the day, and that responsive load management (i.e. demand response) may be a cost-effective method to shift loads to utilize this excess generation. The degree to which farms in California do or can provide responsive loads has not been explored. In this paper, we explore whether farms that are adopting technologies and automation for irrigation management can provide co-benefits to the grower and the electrical grid. To do so, we define the characteristics of future grid needs specifically related to responsive load management, explore existing market mechanisms and policies for proving those resources, estimate the temporal distribution of energy use for irrigation in California, and develop scenarios of how irrigation loads might meet these needs. We conclude by exploring potential ancillary service benefits and associated revenues that California’s agricultural industry may provide. Ancillary services include using loads to dynamically adjust demand on the system to alleviate short-run ramps and disturbances at timescales ranging from seconds up to an hour. With higher penetrations of renewable resources, larger quantities of ancillary services will be necessary and may become more valuable to the grid than traditional demand response. Ancillary services from agricultural loads is a nascent topic, and no such analysis has been conducted to quantify its benefits to our knowledge.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Assessing the PACE of California residential solar deployment: Impacts of Property Assessed Clean Energy programs on residential solar photovoltaic deployment in California, 2010-2015

A new study by Berkeley Lab found that residential Property Assessed Clean Energy (R-PACE) programs increased deployment of residential solar photovoltaic (PV) systems in California, raising it by about 7-12% in cities that adopt these programs. R-PACE is a financing mechanism that uses a voluntary property tax assessment, paid off over time, to facilitate energy improvements and, in some jurisdictions, water and resilience measures. While previous studies demonstrated that early, regional R-PACE programs increased solar PV deployment, this new analysis is the first to demonstrate these impacts from the large, statewide R-PACE programs dominating the California market today, which use private capital to fund the upfront costs of the improvements. Berkeley Lab estimated the impacts using econometric techniques on two samples: -Large cities only, allowing annual demographic and economic data as control variables -All California cities, without these annual data Analysis of both samples controls for several factors other than R-PACE that would be expected to drive solar PV deployment. We infer that on average, cities with R-PACE programs were associated with greater solar PV deployment in our study period (2010-2015). In the large cities sample, solar PV deployment in jurisdictions with R-PACE programs was higher by 1.1 watts per owner-occupied household per month, or 12%. Across all cities, solar PV deployment in jurisdictions with R-PACE programs was higher by 0.6 watts per owner-occupied household per month, or 7%. The large cities results are statistically significant at conventional levels; the all-cities results are not. The estimates imply that the majority of solar PV deployment financed by R-PACE programs would likely not have occurred in their absence. Results suggest that R-PACE programs have increased PV deployment in California even in relatively recent years, as R-PACE programs have grown in market share and as alternate approaches for financing solar PV have developed. The U.S. Department of Energy’s Building Technologies Office supported this research.

14 SOLAR ENERGY↗

Understanding End‐of‐Century Snowpack Changes Over California's Sierra Nevada

Abstract This study uses dynamical and statistical methods to understand end‐of‐century mean changes to Sierra Nevada snowpack. Dynamical results reveal that middle‐elevation watersheds experience considerably more rain than snow during winter, leading to substantial snowpack declines by spring. Despite some high‐elevation watersheds receiving slightly more snow in January and February, the warming signal still dominates across the wet season and leads to notable declines by springtime. A statistical model is created to mimic dynamical results for 1 April snowpack, allowing for an efficient downscaling of all available general circulation models from the Coupled Model Intercomparison Project phase 5. For all general circulation models and emission scenarios, dramatic 1 April snowpack loss occurs at elevations below 2,500 m, despite increased precipitation in many general circulation models. Only 36% (±12%) of historical 1 April total snow water equivalent volume remains at the century's end under a “business‐as‐usual” emission scenario, with 70% (±12%) remaining under a realistic “mitigation” scenario.

Sun, Fengpeng↗

Detection of random noise and anatomy of continuous seismic waveforms in dense array data near Anza California

We develop a methodology to separate continuous seismic waveforms into random noise (RN), not random noise (NRN) produced by earthquakes, wind, traffic and other sources of ground motions, and an undetermined mixture of signals. The analysis is applied to continuous records from a dense seismic array on the San Jacinto fault zone. To detect RN signals, we cut hourly waveforms into non-overlapping 1 s time windows and apply cross-correlations to separate RN candidates from outliers. The cross-correlation coefficients between different RN candidates fall into a tight range (i.e. 0.09–0.35), while cross-correlation coefficients of RN candidates with NRN signals (e.g. seismic or air-traffic events) are lower. The amplitude spectra of RN candidates have a well-defined level, while the amplitude spectra of other signals deviate from that level. Using these properties, we examine the amplitude spectra of moving time windows and cross-correlation coefficients with RN templates in each hour. The hourly RN is quasi-stationary and the results cluster tightly in the parameter space of cross-correlation coefficients and L2 norm deviations from the mean spectra of RN candidates. Time windows with parameters in this tight cluster are identified as RN, windows that deviate significantly from the RN cluster are identified as NRN and windows with values in between are identified as mixed signals. Several iterations on each hourly data are used to update and stabilize the selection of RN templates and mean noise spectra. For the days examined, the relative fractions of RN, NRN and mixed signals in local day (night) times are about 26 (42 percent), 40 (33 percent) and 34 percent (25 percent), respectively.

Geochemistry & Geophysics↗

Sources of Propane Consumed in California

Project Scope: The objective of this study is to specify the sources of propane consumed in California. It answers the questions, where does the propane used in California come from and how was it produced? The results of this study provide comprehensive, transparent, and verifiable estimates, based on the 2018 market. The information provided in this report is suitable for use to assess the life cycle carbon intensity of propane used as a transportation fuel in California. As the 2009 Low Carbon Fuel Standard (LCFS) aims to reduce California’s greenhouse gas (GHG) emissions and other smog-forming and toxic air pollutants, the appropriate designation of carbon intensity for propane as a transportation fuel is important for evaluating propane’s potential to contribute to GHG goals and understandings in the context of various actions. This study focuses on estimating the shares of total propane consumed in the state of California produced from petroleum refineries, natural gas plants, and bituminous sands sources inside California and elsewhere. Results: An estimated 590 million gallons of propane were consumed in California in 2018, of which, 59.5% originated from refinery production and 40.5% originated from natural gas plants. The majority of this was sourced from refinery production in California, 334 million gallons. Most of the propane imported to California for consumption was sourced from natural gas plants, 113 million gallons, with over half of the imported volume sourced from Canada. The volume sourced from bituminous sand upgrader and fractionator operations was negligible. Details from this analysis are presented in the table below which provides an overview of the propane flows estimated in this study by region and production method. The shares and volumes presented here represent a snapshot for 2018. A significant increase in propane demand, such as could be caused by increased use of propane as a transportation fuel in the state, would affect California’s propane production, imports, and exports. The method and data sources used for the estimates provided in this report also provide the framework which could be used for future updates. Key Method Considerations: The values presented here are based on a two-step approach where the first step was to determine the flows of propane into and out of California from different regions and the second step was to estimate the propane production methods in each region. A volume balance approach is used as the primary method for tracking the volume of propane in and out of California as propane production and import volumes are available by Petroleum Administration of Defense District (PADD) from EIA and neither inter-PADD propane transfers nor state-specific non-prime supplier consumption are available from a public data source. The volume balance performed for this study covered PADD 5 (the West Coast), which includes Arizona, California, Nevada, Oregon, and Washington. The volume balance used all available public datasets to determine propane production, imports, exports, and consumption. Volumes unaccounted for by these datasets were estimated using the resulting volume balance by assuming market equilibrium. Consumption within each state in PADD 5 was estimated based on known import, export, and production volumes and this amount was used to develop the volume balance. EIA only tracks consumption at the state level by prime supplier sales. The volume balance approach provides the basis to correct for additional propane consumed in-states where propane is transferred to California. To determine the California propane sources and trade in 2018. volume of propane consumed in California, the volume balance approach is again used where it was estimated all imported volumes not specifically flagged for re-export were consumed, and the remaining consumption was produced in-state. The California Energy Commission (CEC) provided the total volume of propane imported and exported from California in 2018; this volume data set along with commodity tracking from the Canada Energy Regulator (CER) and the International Trade Commission (ITC) which tracks port of entry and final destination was used to determine where propane originated from and where it was ultimately consumed. For example, the CER tracks propane leaving Canada and entering each state within the U.S. Imported propane from Canada to California – marked for California – is assumed to be consumed in California. When no further data were available, import volumes were assumed to be consumed in California without pass-through (i.e., no propane imported to California was directly sold and exported). In most cases, the production method for each propane source region was applied to the volume of propane transferred to California. In other words, the shares of propane sourced from natural gas and refineries for each production region was assigned to California imports based on their contribution to the total volume flows into California to determine the production method for propane consumed in-state. For volumes imported into California from PADD 4, Washington State, Canada, and the rest of the world (Argentina, Chile, Norway, Peru, South Korea, and Trinidad and Tobago), the volumes sourced from petroleum refineries and natural gas plants reflect the either production ratio for the region or, in cases where the sources specific to the amounts exported to California could be determined, the sources specific to the volumes transferred to California.

03 NATURAL GAS↗

The Cost of Floating Offshore Wind Energy in California Between 2019 and 2032

California’s energy planning is centered around meeting the emissions reduction and renewable energy requirements of Senate Bill 350 by 2030. However, state power system planning is expected to eventually address California’s requirement to achieve 100% of total retail electricity sales from renewable energy and zero-carbon resources by 2045, as mandated by Senate Bill 100. To comply with these directives, California needs to investigate the further development of energy efficiency, storage, and a diverse range of renewable energy, zero-carbon emission, and transmission resources, including offshore wind. Wind resources off the coast of California have the potential to generate a significant portion of the state’s electric energy as it moves toward a zero-carbon economy and can help diversify its energy mix. Floating offshore wind technology, which is suitable for the deep waters along the California coast, is currently in a precommercial phase, with approximately 84 megawatts (MW) installed worldwide at the end of 2019. Globally there are over 7,000 MW in planning and permitting phases of development, with the first commercial-scale projects expected to be operational in 2024. This study provides site-specific cost and performance data for floating offshore wind to inform California’s long-term energy planning. The identification of new resources to meet California’s policy goals at least cost is part of the Integrated Resource Planning (IRP) process, which is coordinated by the California Public Utilities Commission (CPUC). In 2019–2020 IRP modeling, offshore wind was included for the first time as a candidate resource in some sensitivity cases (CPUC 2019). The data and information presented in this report can be used to update offshore wind inputs in future IRP cycles. The authors conducted a geospatial cost analysis over portions of the offshore wind resource area of California. The analyzed spatial domain includes sites with a mean wind speed of at least 7 meters per second and water depths between 40 meters (m) and 1,300 m. Costs and energy production vary across this analysis domain. We calculated these parameters on a grid layout with over 750 sites, with each site representing a 1,000-MW commercial offshore wind power plant. Levelized cost of energy (LCOE) was calculated at each site over the analysis domain. The resulting variation in LCOE across the analysis domain is illustrated through heat maps in this report. Five study areas were selected within the analysis domain where more detailed cost analysis was conducted and cost parameters, such as annual energy production, capital cost expenditures (CapEx), operational cost expenditures (OpEx), and net capacity factors are reported. These five study areas include Morro Bay, Diablo Canyon, Humboldt, Cape Mendocino and Del Norte.

17 WIND ENERGY↗

Unprecedented Shifts in Hydrology Are Emerging Across California's Critical Basins: An Evaluation From 0.5 to 3.5°C

With advances in climate models and downscaling techniques, stakeholders anticipate high-resolution analysis to inform regional to local changes in water management. Here, we produce hydrologic projections from an ensemble of Earth System Models (ESMs) that were selected and downscaled to support California's 5th Climate Assessment. An ensemble of 19 ESMs was downscaled to a 3-km resolution across California using a statistical-dynamical downscaling approach and subsequently run through two calibrated hydrology models. Although California has been extensively studied in the context of climate change, we provide the first evaluation of the warming thresholds at which hydroclimate metrics demonstrate statistically significant shifts. We show that present-day to near-term warming levels in Klamath and Northern Sierra Nevada basins, which serve as a critical source of water for California, show statistically significant decreases in snowfall and peak snowpack and associated decreases in summer snowmelt and runoff. More generally, shifts in these hydroclimate metrics occur for intermediate elevation basins ranging from 1,315 to 1,455 m (4,314.3–4,773.6 ft), while the warming level of emergence is delayed for lower and higher elevation basins. We also find that several basins already demonstrate significant increases in 5- to 100-year runoff intensities, primarily due to the increasing influence of precipitation falling as rain. Hydroclimate metrics with trends that demonstrate near-term warming levels of emergence are reflected in reanalysis-based observations, suggesting California is entering a fundamentally different hydroclimate regime. While this will likely stress California's water management, the research provided can support when to implement adaptation efforts.

Bass, B. [Univ. of California, Los Angeles, CA (Un↗

California CO 2 Storage Assurance Facility Enterprise (C2SAFE): Final Technical Report

The California CO 2 Storage Assurance Facility Enterprise (C2SAFE) project conducted a preliminary study into the feasibility of a commercial-scale carbon dioxide (CO 2 ) storage complex located in California’s Southern San Joaquin Valley (SSJV). The work represents the first phase of a multi-phased development approach outlined by the United States Department of Energy’s (DOE’s) Carbon Storage Assurance and Facility Enterprise (CarbonSAFE) program meant to develop carbon storage sites capable of permanently storing 50 million metric tonnes of CO 2 , or greater, injected over a typical facility life of 20 to 30 years. This report represents the culmination of work performed under C2SAFE and outlines a phased implementation plan for large-scale, industrial carbon capture and permanent storage in California’s SSJV. The report is meant to be a standalone document and as such provides high-level summaries of all tasks of the project, but is also meant to complement the other three topical reports issued by the project – reports referenced herein. The study considered multiple scenarios including an east-side storage facility, a west-side storage facility, and potential multi-site storage facilities. The east-side storage facility is to be located at Clean Energy Systems, Inc.’s Kimberlina Power Plant, or nearby, and the west-side facility will be located at the California Resources Corporation’s (CRC’s) Elk Hills oil field. The majority of carbon emissions are planned to be captured from existing sources and transported to the selected and verified storage site(s). Capture from the single closest source to the eastern storage facility and the sources within the Elk Hills field would meet the CarbonSAFE storage goal of 50 million tonnes. The study has shown there is sufficient storage capacity to meet this requirement and more; thus, capture from any of the numerous additional large nearby sources would substantially leverage the CarbonSAFE investment. A comparison of preliminary CO 2 capture, transportation, and storage costs to economic value and incentives in the state shows current market conditions make it economically feasible to develop large-scale industrial storage sites in California’s SSJV. The business case for Carbon Capture and Storage (CCS) in California’s SSJV appears economically viable today for large CO 2 point sources involved in the production of transportation fuels, such as oilfield cogeneration units and steam boilers. The overall levelized CCS cost is estimated at roughly 125 per tonne of CO 2 , which includes CO 2 amine-solvent post-combustion capture, transportation, and storage. The levelized CO 2 capture cost is based on today’s technology, with no future cost reduction factored in for technology improvement. The sum of the value of incentives and revenue from California Low Carbon Fuel Standard (LCFS) credits (discounted roughly 20% from their current transaction value), sale of California cap-and-trade emission allowances, and Section 45Q tax credits—either for saline storage or the Enhanced Oil Recovery (EOR) credit plus CO 2 sales revenue—is about 165/tonne-CO 2 . The economic viability of CCS for Natural Gas Combined Cycle (NGCC) power plants in the SSJV is more site-specific. A plant providing power solely to the electric grid, if it added CCS, should be eligible for Section 45Q tax credits and could sell its excess cap-and-trade emission allowances, but it would not generate LCFS credits. Using the cost and incentive values detailed in this report, it would not be economical for such a plant to add CCS today, barring other considerations. An NGCC plant within an oilfield (e.g., CRC Elk Hills and NRG Sunrise) that provides power to the oilfield as well as to the grid should receive “partial credit” in terms of generating LCFS credits if it added CCS (pro-rated for the fraction of power going to the oilfield). Such a plant should also be eligible for Section 45Q tax credits and garner revenue from selling its excess cap-and-trade emission allowances. Using the cost and incentive values described in this report, the economic viability of adding CCS today would depend on the relative fractions of electricity supplied to the oilfield and the grid. As the value of cap-and-trade emission allowances grows over time (either by market forces or the escalating floor price), the relative fraction of power needing to remain in the oilfield to achieve “breakeven” would diminish. At some point, even plants providing all their power to the grid would be candidates for economical CCS application. The C2SAFE team has proposed to expand upon the knowledge gained during this study by conducting a detailed feasibility assessment under a follow-on phase of the program, Phase II – Feasibility. This would include detailed data collection at the two sites, analysis, reporting, stakeholder outreach, and risk mitigation activities to support the development of a commercial carbon storage complex in the SSJV.

58 GEOSCIENCES↗

Causes of and Solutions to Wind Speed Bias in NREL's 2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf

This report provides the results of a detailed analysis into the causes of high wind speed bias in the 20-year wind resource data set for offshore California the National Renewable Energy Laboratory (NREL) released in 2020, herein called CA20. The data set was developed using the state-of-the-art Weather Research and Forecasting (WRF) model. Notably, no floating lidars were available at the time in offshore California to validate offshore hub-height wind speeds. In late 2020, the Pacific Northwest National Laboratory (PNNL) deployed two floating lidars in the California outer continental shelf (OCS), near the Bureau of Ocean Energy Management (BOEM) call areas of Humboldt and Morro Bay. Using these observations through 2021, NREL found considerable bias in modeled hub-height winds at both locations: up to +2 m/s at Humboldt over a 6-month period, and up to +1 m/s at Morro Bay over a one-year period. Upon the discovery of this bias, the Department of Energy (DOE) and BOEM funded NREL and PNNL to investigate the causes of, impacts of, and solutions to the bias in the CA20 data set. This report summarizes the findings of this research. We first investigated whether different WRF model setups could lead to reduced bias. We found that the choice of planetary boundary layer (PBL) scheme - which controls the vertical turbulent mixing of momentum, heat, and moisture in the lowermost part of the atmosphere - greatly affected hub-height wind speeds in the region. Specifically, switching from the Mellor-Yamada-Nakanishi-Niino (MYNN) scheme used in CA20 (and widely used across a range of operational and research weather models) to the less common Yonsei University (YSU) scheme nearly eliminated the bias at both the Humboldt and Morro Bay lidar locations. The large discrepancy between the MYNN- and YSU-modeled hub-height winds pointed towards the role of atmospheric stability. In general, PBL schemes agree well in conditions of high turbulence and mixing, normally referred to as "unstable" conditions. By contrast, PBL schemes start to diverge in "stable" conditions, where turbulence is low and thermal stratification (i.e., higher temperature air sitting on top of colder air) greatly suppresses vertical mixing. Under such conditions, winds aloft can decouple from surface effects and greatly accelerate, causing high wind speeds at hub-height and frequent low-level jets (LLJs). We determined that these stable conditions are in fact dominant in offshore California. The region is characterized by moderate-to-extreme stable stratification with a LLJ on average around 200 meters above sea-level. To our knowledge, no wind energy area globally has as strongly stable stratification as offshore California. Under these extreme conditions, we determined that the MYNN scheme models higher stability than YSU, resulting in less vertical turbulent mixing than YSU, allowing for the acceleration of hub-height winds, more intense LLJs, and higher-amplitude inertial oscillations. Using surface observations, we found that MYNN overestimates near-surface stability, whereas YSU tends to model stability better. We then considered several short-term case studies to assess additional meteorological drivers of the bias at Humboldt. We found that during synoptic scale northerly flows driven by the North Pacific High and inland thermal low, a coastal warm bias in the MYNN case studies contributes to the modeled wind speed bias by altering the boundary layer thermodynamics via a thermal wind mechanism. Given the strong performance of the YSU-based runs in offshore California, NREL has produced and published an updated version of the CA20 data set with YSU as the PBL scheme. This updated data set is now part of NREL's 2023 National Offshore Wind (NOW-23) data set, which covers all the U.S. offshore waters. The development and final validation of the NOW-23 data set in offshore California is documented in this report.

17 WIND ENERGY↗

Fallowed agricultural lands dominate anthropogenic dust sources in California

Air pollution remains a major problem in many parts of California, significantly impacting public health and regional climate. However, the contribution of anthropogenic dust from agricultural sources, among major pollutants in California’s semi-arid Central Valley, remains largely unclear. Here, we used the Cropland Data Layer from the U.S. Department of Agriculture to identify crop types and land use/cover and leveraged satellite-derived estimates of major dust events between 2008 and 2022 over California. We identified fallowed land—an unplanted agricultural land parcel—as a key anthropogenic dust source in California. Specifically, we find that the Central Valley accounts for about 77% of total fallowed land areas in California, where they are associated with about 88% of major anthropogenic dust events. We also find that the geographic coverage of these fallowed lands expanded between 2008 and 2022 with associated increasing anthropogenic dust activities. Additionally, these anthropogenic dust activities are sensitive to the drought severity over the fallowed lands, with potential cumulative effects on downstream dust burden during prolonged multi-year drought conditions. Overall, our results have important implications for public health, including increased risk for Valley fever and for regional climates, such as increases in extreme precipitation and snowmelt over the Sierra Nevada.

Climate sciences↗

Climate and air pollution impacts of generating biopower from forest management residues in California

California faces crisis conditions on its forested landscapes. A century of aggressive logging and fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency. Between commercial harvests on California’s working forestlands and the increasing number of acres the state treats each year for fire risk reduction and carbon sequestration, California forests generate millions of tons of woody residues annually—residues that are typically left or burned in the field. State policymakers have turned to biomass electricity generation as a key market for woody biomass in the hope that it can support sustainable forest management activities while also providing low-carbon renewable electricity. However, open questions surrounding the climate and air pollution performance of electricity generation from woody biomass have made it difficult to determine how best to manage the risks and opportunities posed by forest residues. The California Biomass Residue Emissions Characterization (C-BREC) model offers a spatially-explicit life cycle assessment framework to rigorously and transparently establish the climate and air pollution impacts of biopower from forest residues in California under current conditions. The C-BREC model characterizes the variable emissions from different biomass supply chains as well as the counterfactual emissions from prescribed burn, wildfire, and decay avoided by residue mobilization. We find that the life cycle ‘carbon footprint’ of biopower from woody residues generated by recent forest treatments in California ranges widely—from comparable with solar photovoltaic on the low end to comparable with natural gas on the high end. This variation stems largely from the heterogeneity in the fire and decay conditions these residues would encounter if left in the field, with utilization of residue that would otherwise have been burned in place offering the best climate and air quality performance. California’s energy and forest management policies should account for this variation to ensure desired climate benefits are achieved.

54 ENVIRONMENTAL SCIENCES↗

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗