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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.

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2022 Central California Travel Study

# 2022 Central California Travel Study The 2022 Central California Travel Study collected demographic and travel pattern information to better understand household travel behavior in the state’s San Joaquin Valley region. ## Data Collection Agency The Fresno Council of Governments conducted the household travel study in collaboration with metropolitan planning organizations in Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare counties in California. ## Survey Methodology The two-part study consisted of a survey and a travel diary. The survey gathered data on household demographic composition and typical travel behaviors. The travel diary gathered individual travel data during a specified travel period for all members of a given household. ## Travel Diary Methods Households with smartphones were encouraged to complete their travel diaries using the rMove smartphone app for up to seven consecutive days. Households without smartphones or those unwilling to participate via smartphone completed their travel diaries online (using the web-version of rMove) or by calling the survey call center. These households reported travel for one day (Tuesday, Wednesday, or Thursday). ## Recruitment Sampling Methods The majority of the recruitment was conducted via address-based sampling, a type of probability sampling, with a focus on reaching county-level targets in collaboration with metropolitan planning organizations in the region. Supplemental sampling methods, primarily non-probability, were employed during all waves of data collection to improve survey representation. The supplemental sample included targeted outreach to hard-to-survey populations via transit rider email lists; local housing authorities; Nichols Research, a California-based market research firm; and the Ipsos™ KnowledgePanel, an online random probability panel. See the documentation for more information about sampling and weighting. ## Survey Records, Data, and Documentation In total, 7,406 households completed 19,084 surveys representing 150,012 trips across 42,567 person-days.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Central California Travel Study

# 2022 Central California Travel Study The 2022 Central California Travel Study collected demographic and travel pattern information to better understand household travel behavior in the state’s San Joaquin Valley region. ## Data Collection Agency The Fresno Council of Governments conducted the household travel study in collaboration with metropolitan planning organizations in Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare counties in California. ## Survey Methodology The two-part study consisted of a survey and a travel diary. The survey gathered data on household demographic composition and typical travel behaviors. The travel diary gathered individual travel data during a specified travel period for all members of a given household. ## Travel Diary Methods Households with smartphones were encouraged to complete their travel diaries using the rMove smartphone app for up to seven consecutive days. Households without smartphones or those unwilling to participate via smartphone completed their travel diaries online (using the web-version of rMove) or by calling the survey call center. These households reported travel for one day (Tuesday, Wednesday, or Thursday). ## Recruitment Sampling Methods The majority of the recruitment was conducted via address-based sampling, a type of probability sampling, with a focus on reaching county-level targets in collaboration with metropolitan planning organizations in the region. Supplemental sampling methods, primarily non-probability, were employed during all waves of data collection to improve survey representation. The supplemental sample included targeted outreach to hard-to-survey populations via transit rider email lists; local housing authorities; Nichols Research, a California-based market research firm; and the Ipsos™ KnowledgePanel, an online random probability panel. See the documentation for more information about sampling and weighting. ## Survey Records, Data, and Documentation In total, 7,406 households completed 19,084 surveys representing 150,012 trips across 42,567 person-days.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Central California Travel Study

# 2022 Central California Travel Study The 2022 Central California Travel Study collected demographic and travel pattern information to better understand household travel behavior in the state’s San Joaquin Valley region. ## Data Collection Agency The Fresno Council of Governments conducted the household travel study in collaboration with metropolitan planning organizations in Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare counties in California. ## Survey Methodology The two-part study consisted of a survey and a travel diary. The survey gathered data on household demographic composition and typical travel behaviors. The travel diary gathered individual travel data during a specified travel period for all members of a given household. ## Travel Diary Methods Households with smartphones were encouraged to complete their travel diaries using the rMove smartphone app for up to seven consecutive days. Households without smartphones or those unwilling to participate via smartphone completed their travel diaries online (using the web-version of rMove) or by calling the survey call center. These households reported travel for one day (Tuesday, Wednesday, or Thursday). ## Recruitment Sampling Methods The majority of the recruitment was conducted via address-based sampling, a type of probability sampling, with a focus on reaching county-level targets in collaboration with metropolitan planning organizations in the region. Supplemental sampling methods, primarily non-probability, were employed during all waves of data collection to improve survey representation. The supplemental sample included targeted outreach to hard-to-survey populations via transit rider email lists; local housing authorities; Nichols Research, a California-based market research firm; and the Ipsos™ KnowledgePanel, an online random probability panel. See the documentation for more information about sampling and weighting. ## Survey Records, Data, and Documentation In total, 7,406 households completed 19,084 surveys representing 150,012 trips across 42,567 person-days.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Central California Travel Study

# 2022 Central California Travel Study The 2022 Central California Travel Study collected demographic and travel pattern information to better understand household travel behavior in the state’s San Joaquin Valley region. ## Data Collection Agency The Fresno Council of Governments conducted the household travel study in collaboration with metropolitan planning organizations in Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare counties in California. ## Survey Methodology The two-part study consisted of a survey and a travel diary. The survey gathered data on household demographic composition and typical travel behaviors. The travel diary gathered individual travel data during a specified travel period for all members of a given household. ## Travel Diary Methods Households with smartphones were encouraged to complete their travel diaries using the rMove smartphone app for up to seven consecutive days. Households without smartphones or those unwilling to participate via smartphone completed their travel diaries online (using the web-version of rMove) or by calling the survey call center. These households reported travel for one day (Tuesday, Wednesday, or Thursday). ## Recruitment Sampling Methods The majority of the recruitment was conducted via address-based sampling, a type of probability sampling, with a focus on reaching county-level targets in collaboration with metropolitan planning organizations in the region. Supplemental sampling methods, primarily non-probability, were employed during all waves of data collection to improve survey representation. The supplemental sample included targeted outreach to hard-to-survey populations via transit rider email lists; local housing authorities; Nichols Research, a California-based market research firm; and the Ipsos™ KnowledgePanel, an online random probability panel. See the documentation for more information about sampling and weighting. ## Survey Records, Data, and Documentation In total, 7,406 households completed 19,084 surveys representing 150,012 trips across 42,567 person-days.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

County Electric Vehicle Home Charging Access Shares From the 2030 National Charging Network Study

This file contains modeled county-level home electric vehicle charging access shares from the study The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure by Wood et al. (2023). These are based on modeling in There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure by Ge et al. (2021).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

County Land-Use Regulations for Solar Energy Development in Colorado

We present a survey of county-level policies on ground-mounted solar development across Colorado, including both solar-specific ordinances as well as general land-use code that might be applicable in counties without solar-specific policies. This report provides an accessible reference for stakeholders interested in identifying counties with particular regulations or in analyzing the diversity of regulations across Colorado. We defined a set of search criteria to find information on solar definitions and classifications, permitting processes, and use-specific requirements in each of Colorado's 64 counties. With those criteria, we reviewed relevant ordinances, land-use code, and comprehensive and master plans. If any uncertainties were identified, we contacted county officials for clarification. The findings are categorized and mapped to illustrate the distribution of key policies adopted across Colorado's counties on the following topics: solar definitions, solar siting policy documentation, categorization of PV systems for permitting, 1041 permitting, solar on agricultural land, panel height restrictions, fencing requirements, vegetation management, visual impacts, decommissioning plans, and financial assurance for decommissioning. Additionally, we identify and discuss policies that might impact the deployment of agrivoltaics, a dual land use combining both agriculture and solar on the same land, which might not fit neatly in existing zoning definitions and solar-specific regulations.

14 SOLAR ENERGY↗

Consumer Benefits of Clean Energy: The resilience value of residential solar + storage systems in the continental U.S.

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. Clean energy resources that are located behind the meter have the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Solar plus storage systems (PVESS) are clean energy resources that can supply backup power without requiring fuel resupply or increasing local emissions. This report examines the regional value of PVESS for resilience by calculating a benefit-cost ratio (BCR) that considers the annual resiliency benefits of PVESS and the annualized cost of the investment. In addition, we estimate the expected technical mitigation potential of PVESS systems at the county-level to these expected events, and characterize the customer interruption costs by determining the value of lost load at the state level.

14 SOLAR ENERGY↗

EV Stock and Load Forecasting for HECO [Slides]

This presentation covers the work completed for the HECO Forecasting Department for the Electric Vehicle Stock and Load Forecast for Integrated Grid Planning project. This project uses a suite of detailed analytical tools developed by the National Laboratory of the Rockies, including TEMPO and EVI-Pro, to develop future scenarios to 2050 of county-level electric vehicle adoption and associated annual hourly charging load profiles for the state of Hawaii.

33 ADVANCED PROPULSION SYSTEMS↗

Residue Retention Requirement (Crop Residues)

County-level minimum residue (dry tons/acre/year) required to remain on fields to maintain soil carbon and limit erosion; defines the biophysical constraint on residue removal.

crop residue↗

Electric Grid Visualization: Hourly Generation, Load, Unserved Load, and Locational Marginal Prices during a 2018 Heatwave

Visualization of hourly generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided as well as a county-level choropleth map of temperature.

Mongird, Kendall (ORCID:0000000328077088)↗

Heat Wave Impacts on Western US Electricity System

Visualization of hourly generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018 and 2058. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided as well as a county-level choropleth map of temperature.

Mongird, Kendall↗

County Electric Vehicle Home Charging Access Shares from the 2030 National Charging Network Study

This file contains modeled county-level home electric vehicle (EV) charging access shares from the study, "The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure" by Wood et al. (2023). These are based on modeling in "There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure" by Ge et al. (2021). Wood, Eric, et al. 2023. The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREP/TP-5400-85654. https://www.nlr.gov/docs/fy23osti/85654.pdf . Ge, Yanbo, et al. 2021. There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5400-81065. https://www.nlr.gov/docs/fy22osti/81065.pdf .

24 POWER TRANSMISSION AND DISTRIBUTION↗

Improved resource use decisions and actions through remote sensing

Operational uses of remote sensing for improving management decisions and actions concerning resource uses are considered in terms of first generation, or direct-action; and second generation or indirect, delayed-action applications. From among applications completed during 1974-75, seven case studies are offered in illustration of the many contrasts which can be drawn between first and second generation application studies. These include: (1) multi-agency river basin planning; (2) corridor assessment and route location for highway location together with improvement of county-level planning decisions; (3) improving timber management practices; (4) enforcement of new state statutes; (5) county-wide open space preservation; (6) land value reappraisal relative to property tax equalization; and (7) optimizing agri-business processing plant locations.

Hill-Rowley, R.↗

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Santanello, Joseph A.↗

Using NASA Environmental Data to Enhance Public Health Decision Making

The Universities Space Research Association at the NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this collaboration are to develop high-quality spatial data sets of environmental variables, and deliver the data sets and associated analyses to local, state and federal end-user groups. These data can be linked spatially and temporally to public health data, such as mortality and disease morbidity, for further analysis and decision making. Three daily environmental data sets have been developed for the conterminous U.S. on different spatial resolutions for the time period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be made available to public health professionals, researchers and the general public through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer reviewed publications. To date, two of the data sets have been released to the public in CDC WONDER, Daily Air Temperature and Heat Index for years 1979-2010, and Daily Fine Particulate Matter (PM2.5) air quality measures for years 2003-2008. These data in CDC WONDER can be aggregated to the county-level, state-level, or regional-level as per users need and downloaded in tabular, graphical, and map formats. The summary statistical output are available to web and app developers via the WONDER Application Programming Interface (API). The linkage of these data with the CDC WONDER system provides a significant addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER online system. It also substantially expands public access to NASA environmental data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

The overall goal of this study is to address issues of environmental health and enhance public health decision making by using NASA remotely sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) Office of Surveillance, Epidemiology and Laboratory Services. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the environmental data sets and associated public health analyses to local, state and federal end ]user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) on a 10-km grid using US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of MODIS Land Surface Temperature (LST); and (3) a 12-km grid of daily incoming solar radiation and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline, stroke and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county-level, state-level, or regional-level as per users f need and downloaded in tabular, graphical, and map formats. This provides a significant addition to the CDC WONDER online system, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER. It also substantially expands public access to NASA data, making their use by a wide range of decisionmakers feasible.

Al-Hamdan, Mohammad↗

Improving the Monitoring of Crop Productivity Using Spaceborne Solar-Induced Fluorescence

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change.

Guan, Kaiyu↗

SMAP L4 Assessment of the US Northern Plains 2017 Flash Drought

A rapidly developing "flash drought" occurred over the US Northern Plains in the summer of 2017, spurred by unusually high temperatures and strong evaporative demand. The impacts of the drought included widespread reductions in rangeland and agricultural productivity that cascaded into significant economic losses. Here, we used satellite information from the NASA Soil Moisture Active Passive (SMAP) mission to clarify the nature and impact of the drought on regional vegetation growth. The model enhanced SMAP Level 4 Soil Moisture (L4SM) and Carbon (L4C) products were used with other ancillary data to examine spatial and seasonal anomalies in surface to root zone soil moisture and vegetation productivity (GPP). We find that the flash drought was triggered by a mid-July heat wave, conditioned by exceptionally low spring rainfall. The drought resulted in anomalous low soil moisture levels and regional GPP collapse, coinciding with severe (D3) to exceptional (D4) drought conditions indicated from the US Drought Monitor. The SMAP L4C GPP anomalies closely tracked reported county-level crop production anomalies for the major regional crop types, indicating generally larger productivity decline in managed croplands than surrounding natural areas. The SMAP L4 global products provide an effective indicator of vegetation growth changes and moisture-related restrictions on ecosystem productivity that are complementary with more traditional drought assessment tools.

GPP↗