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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

GHG policy impacts for Seattle’s buildings: targets, timing, and scope

Many US cities are addressing climate change by setting goals to reduce their greenhouse gas (GHG) emissions by a specified amount within a specified time period. In order to achieve these goals, reducing emissions from existing buildings is crucial. Many cities are passing legislation to target existing buildings through benchmarking, auditing, retuning, or energy or emissions performance standards. As cities design legislation, they must consider the timing of the policies, how to prioritize building types and sizes, and how these design decisions will impact the city’s emissions. This paper addresses these questions for one particular US city: Seattle, Washington. A model of Seattle’s building stock was created with benchmarking and tax assessor data. It was then used to predict GHG emissions reductions due to different policy implementations for existing commercial and multifamily buildings. Key findings are: (1) the proposed emissions policy is expected to reduce cumulative emissions from buildings by 19% between 2020 and 2050; (2) delaying the implementation of the policy by five years could limit savings to 12%; and (3) including smaller buildings in the policy could increase savings to 34%. The lessons learned and how this can be used by other cities are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Projecting future climate change impacts on heat-related mortality in large urban areas in China

Highlights: • The study projects future heat-related mortality risk in 51 major cities in China. • The projections are based on high resolution climate and population projections. • Future heat mortality risk is likely to be considerable under all emission scenarios. • Climate mitigation and heat risk management are needed to reduce such risk. Global climate change is anticipated to raise overall temperatures and has the potential to increase future mortality attributable to heat. Urban areas are particularly vulnerable to heat because of high concentrations of susceptible people. As the world's largest developing country, China has experienced noticeable changes in climate, partially evidenced by frequent occurrence of extreme heat in urban areas, which could expose millions of residents to summer heat stress that may result in increased health risk, including mortality. While there is a growing literature on future impacts of extreme temperatures on public health, projecting changes in future health outcomes associated with climate warming remains challenging and underexplored, particularly in developing countries. This is an exploratory study aimed at projecting future heat-related mortality risk in major urban areas in China. We focus on the 51 largest Chinese cities that include about one third of the total population in China, and project the potential changes in heat-related mortality based on 19 different global-scale climate models and three Representative Concentration Pathways (RCPs). City-specific risk estimates for high temperature and all-cause mortality were used to estimate annual heat-related mortality over two future twenty-year time periods. We estimated that for the 20-year period in Mid-21st century (2041–2060) relative to 1970–2000, incidence of excess heat-related mortality in the 51 cities to be approximately 37,800 (95% CI: 31,300–43,500), 31,700 (95% CI: 26,200–36,600) and 25,800 (95% CI: 21,300–29,800) deaths per year under RCP8.5, RCP4.5 and RCP2.6, respectively. Slowing climate change through the most stringent emission control scenario RCP2.6, relative to RCP8.5, was estimated to avoid 12,900 (95% CI: 10,800–14,800) deaths per year in the 51 cities in the 2050s, and 35,100 (95% CI: 29,200–40,100) deaths per year in the 2070s. The highest mortality risk is primarily in cities located in the North, East and Central regions of China. Population adaptation to heat is likely to reduce excess heat mortality, but the extent of adaptation is still unclear. Future heat mortality risk attributable to exposure to elevated warm season temperature is likely to be considerable in China's urban centers, with substantial geographic variations. Climate mitigation and heat risk management are needed to reduce such risk and produce substantial public health benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding the Influence of Urban Form on the Spatial Pattern of Precipitation

Urban areas are known to modify the spatial pattern of precipitation climatology. Existing observational evidence suggests that precipitation can be enhanced downwind of a city. Among the proposed mechanisms, the thermodynamic and aerodynamic processes in the urban lower atmosphere interact with the meteorological conditions and can play a key role in determining the resulting precipitation patterns. In addition, these processes are influenced by urban form, such as the impervious surface extent. This study aims to unravel how different urban forms impact the spatial patterns of precipitation climatology under different meteorological conditions. We use the Multi-Radar Multi-Sensor quantitative precipitation estimation data products and analyze the hourly precipitation maps for 27 selected cities across the continental United States from the years 2015–2021 summer months. Results show that about 80% of the studied cities exhibit a statistically significant downwind enhancement of precipitation. Additionally, we find that the precipitation pattern tends to be more spatially clustered in intensity under higher wind speed; the location of radial precipitation maxima is located closer to the city center under low background winds but shifts downwind under high wind conditions. The magnitude of downwind precipitation enhancement is highly dependent on wind directions and is positively correlated with the city size for the south, southwest, and west directions. This study presents observational evidence through a cross-city analysis that the urban precipitation pattern can be influenced by the urban modification of atmospheric processes, providing insight into the mechanistic link between future urban land-use change and hydroclimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impacts of climate change, population growth, and power sector decarbonization on urban building energy use

Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Stationary Spatial Charging Demand Distribution for Commercial Electric Vehicles in Urban Area

The electric vehicle (EV) is an increasingly popu- lar mobility solution today. It is especially appealing for urban commercial usage including serving commuters and delivering goods. Commercial EVs, defined as electric taxi fleets in this paper, contribute a lot to the energy consumption and emission. One critical component to facilitate the adoption of EVs is to provide sufficient charging infrastructures for road users to alleviate the range anxiety. In this study, we develop an analytical model to profile the stationary spatial distribution of charging demand for any given fleet of commercial EVs, which serves as the necessary input for planning the location of charging infrastructures. Our model considers the movement of EVs as a random walk, with the underlying Markov process driven by the spatial demand that the commercial EV fleet needs to serve. We then define the electricity consumption and charging models and develop the probability distribution that an EV may need to recharge its battery at any given location in the city, based on the stationary distribution of the random walk process. We calibrate the performance parameters of EVs from the trip record and present numerical experiments based on New York City taxi trip data and compare the solution from simulation with our analytical solution. The result shows that analytical solution is quite close to the simulation result. This paper provides insights to the city agencies and private companies to make charging infrastructure location planning.

Qian, Xinwu↗
DOE OSTI2022

CityBES v2021

City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.

Hong, Tianzhen↗
DOE OSTI2013

Final Technical Report - Modernization of the Boulder Canyon Hydroelectric Project

The Boulder Canyon Hydroelectric Project (BCH) was purchased by the City of Boulder, CO (the city) in 2001. Project facilities were originally constructed in 1910 and upgraded in the 1930s and 1940s. By 2009, the two 10 MW turbine/generators had reached or were nearing the end of their useful lives. One generator had grounded out and was beyond repair, reducing plant capacity to 10 MW. The remaining 10 MW unit was expected to fail at any time. When the BCH power plant was originally constructed, a sizeable water supply was available for the sole purpose of hydroelectric power generation. Between 1950 and 2001, that water supply had gradually been converted to municipal water supply by the city. By 2001, the water available for hydroelectric power generation at BCH could not support even one 10 MW unit. Boulder lacked the financial resources to modernize the facilities, and Boulder anticipated that when the single, operational historical unit failed, the project would cease operation. In 2009, the City of Boulder applied for and received a U.S. Department of Energy (DOE) grant for $1.18 million toward a total estimated project cost of $5.155 million to modernize BCH. The federal funding allowed Boulder to move forward with plant modifications that would ensure BCH would continue operation. Federal funding was made available through the American Recovery and Reinvestment Act (ARRA) of 2009. Boulder determined that a single 5 MW turbine/generator would be the most appropriate capacity, given the reduced water supply to the plant. Average annual BCH generation with the old 10 MW unit had been about 8,500 MW-hr, whereas annual generation with a new, efficient turbine could average 11,000 to 12,000 MW-hr. The incremental change in annual generation represents a 30% increase in generation over pre-project conditions. The old turbine/generator was a single nozzle Pelton turbine with a 5-to-1 flow turndown and a maximum turbine/generator efficiency of 82%. The new unit is a double nozzle Pelton turbine with a 10-to-1 flow turndown and a maximum turbine/generator efficiency of 88%. This alone represents a 6% increase in overall efficiency. The old turbine operated at low efficiencies due to age and non-optimal sizing of the turbine for the water flow available to the unit. It was shut down whenever water flow dropped to less than 4-5 cfs, and at that flow, efficiency was 55 to 60%. The new turbine will operate in the range of 70 to 88% efficiency through a large portion of the existing flow range and would only have to be shut down at flow rates less than 3.7 cfs. Efficiency is expected to increase by 15-30%, depending on flow. In addition to the installation of new equipment, other goals for the project included: Increasing safety at Boulder Canyon Hydro Increasing protection of the Boulder Creek environment Modernizing and integrating control equipment into Boulder's municipal water supply system, and Preserving significant historical engineering information prior to power plant modernization. From January 1, 2010 through December 31, 2012, combined consultant and contractor personnel hours paid for by both the city and the federal government have totaled approximately 40,000. This equates roughly to seven people working full time on the project from January 2010 through December 2012. This project also involved considerable material expense (steel pipe, a variety of valves, electrical equipment, and the various components of the turbine and generator), which were not accounted for in terms of hours spent on the project. However, the material expense related to this project did help to create or preserve manufacturing/industrial jobs throughout the United States. As required by ARRA, the various components of the hydroelectric project were manufactured or substantially transformed in the U.S. BCH is eligible for nomination to the National Register of Historic Places due in part to its unique engineering features and innovative construction techniques. Special efforts were directed toward documenting the (largely original) interior of the plant and installing new equipment without modifying the power plant exterior in order to preserve the historical significance of the facility. In addition, a significant portion of the historical equipment within the power plant was preserved in place. The modernization project began with DOE grant award on January 1, 2010, and the project was completed on December 31, 2012. In addition to city engineering and hydroelectric staff, major project participants included AECOM (design/engineering) Canyon Industries (turbine/generator manufacture), Gracon Corporation (general construction contractor), Exponential Engineering Company (electrical engineering) and URS Corporation (historical documentation), as well as numerous other subcontractors and consultants.

13 HYDRO ENERGY↗
DOE OSTI2017

Resilient Solar and Storage Roadmap

Resilience to natural disasters is imperative for safe, economically productive cities. In the immediate aftermath of an earthquake, flood, or other disaster, one key element of resilience is continued operation of shelters and critical emergency management facilities. Operation of these facilities depends on reliable emergency power. Traditional emergency power systems use diesel generators with storage tanks, which provide power for only a few days in the absence of the electric or gas grid. However, a recent study has shown that gas and electric networks can require days or weeks to recover from a disaster, leaving facilities with generators at risk of running out of fuel. This has already been experienced in New York City after Hurricane Sandy where a combination of lengthy outages and high flood waters compromised the traditional diesel storage and generator backup infrastructure at hospitals and shelters. With the risk of natural disasters increasing due to climate change, we must turn to more resilient solutions for providing backup power to shelters, medical centers, and emergency operations centers. From 2015 to 2017, the City and County of San Francisco Solar and Storage for Resilience Project examined the use of microgrids and stand-alone solar electric generation with battery storage to provide resilient post-disaster power to critical facilities. The project evaluated 1,263 potential congregation and shelter sites across the city, 67 of which were identified as shelter sites with power requirements and opportunities to develop resilient infrastructure through solar and storage. Site visits were conducted for 18 of these buildings, spanning all 11 supervisor districts in San Francisco and a range of normal and emergency use types. The project team used observations from these site visits to create representative emergency power profiles for all 67 shelters in San Francisco. Using these profiles, the team found that 8.2 megawatts (MW) of photovoltaic panels and 12.9 MW of battery storage would be required to provide resilient backup power for San Francisco’s shelters following a disaster. Given the high capital cost of deploying this large resource, the project team investigated various financing options — a public-private partnership was found to be a viable pathway for financing resilient solar and storage. Given the added benefit of energy cost savings in normal operation, a public-private partnership financing model would save the City and County of San Francisco 6% over a traditional design-bid-build approach over a 20-year portfolio lifetime. This roadmap documents the project’s steps of identifying critical facilities, surveying power requirements, assessing renewable potential, evaluating financing options to develop the solar and storage systems for resiliency, and modeling individual sites for solar and storage installation. This roadmap also examines the challenges critical facilities face in providing resilient power, such as key technical, political, and financing barriers, as well as the opportunities and policy recommendations to further advance resilient solar and storage development in San Francisco. While this report focuses on a detailed study of San Francisco, the methods and outcomes are applicable to any city or town.

14 SOLAR ENERGY↗
DOE OSTI2019

Resilience Roadmap: A Collaborative Approach to Multi-Jurisdictional Resilience Planning

Extreme weather and aging infrastructure are creating unprecedented challenges in the United States and around the globe. Many communities have suffered damages from a variety of weather-related events, such as severe weather such as hurricanes, droughts, increasing temperatures, wildfires, and storm surges. Numerous efforts exist to improve resilience to protect national security, energy and water security, economic well-being, and quality of life. As severe weather events increase in frequency and severity, many cities, states, tribes, and federal agencies are addressing the impacts through resilience planning and measures. In an effort to support communities with resilience planning, the White House Council on Environmental Quality (CEQ) initiated preparedness pilot projects designed to showcase community resilience planning in the City of Houston and the State of Colorado. This publication is the full, technical document, for the Colorado pilot project. The process is also summarized in a user-friendly web-version on NREL's website (visit www.nrel.gov/resilience-planning-roadmap) for easier access and replicability. NASA's pilot project with the City of Houston is summarized separately (visit https://toolkit.climate.gov/case-studies/climate-resilience to learn more). water security, economic well-being, and quality of life. As severe weather events increase in frequency and severity, many cities, states, tribes, and federal agencies are addressing the impacts through resilience planning and measures. In an effort to support communities with resilience planning, the White House Council on Environmental Quality (CEQ) initiated preparedness pilot projects designed to showcase community resilience planning in the City of Houston and the State of Colorado. This publication is the full, technical document, for the Colorado pilot project. The process is also summarized in a user-friendly web-version on NREL's website (visit www.nrel.gov/resilience-planning-roadmap) for easier access and replicability. NASA's pilot project with the City of Houston is summarized separately (visit https://toolkit.climate.gov/case-studies/climate-resilience to learn more).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2006

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS2016

New York, USA

New York City, one of the most populous and ethnically diverse cities in the world, has responded to a variety of enviornmental challenges in its history. The most recent is climate change, which is projected to have wide impacts on the city's critical infrastructure and population through higher temperatures, more intense flooding events and sea level rise. The city recognized the risks early and has become a national and international leader in responding to this new challenge, illustrating how this is possible for a large city. As part of a mature urban region, it is an excellent bellwether for the impacts that may be experienced by other cities, especially those in emerging metropolitan conurbations.

Solecki, William↗
NASA NTRSDate not supplied

Evaluating the Effects of Urban Expansion on Social and Environmental Vulnerability in Guatemala and Panama

Central America is one of the fastest urbanizing regions in the world, with the urban population expected to double by 2050. This growth is driving multiple societal issues, including infrastructure inequities, lack of accessible housing, and environmental degradation. This project partnered with NASA SERVIR, Sistema de la Integración Centroamericana (SICA), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), and Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPRENEDAC) to examine changes in urban extent and vulnerability in Guatemala City, Guatemala and Panama City, Panama. The team identified urban extent using Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 OLI-2 within Google Earth Engine’s LandTrendr algorithm. Next, they assessed urban vulnerability between formal and informal settlements by classifying different types of roof material using high-resolution Maxar Worldview 2 and 3 imagery and comparing it to socioeconomic and environmental risks. While both cities have expanded outward and become denser since 2000, Guatemala City has grown at a faster rate. The most vulnerable communities of both cities were located in the northwestern regions. These case studies can be used to inform similar methodologies in other Central American cities and help leaders identify the most vulnerable communities within their areas.

Aaron Whittemore↗
DOE OSTI2024

Integrated Urban Services: Program Impact and Business Plan Summary

The Integrated Urban Services (IUS) program, launched in 2021 and funded by the U.S. State Department under the United States-Association of Southeast Asian Nations (US-ASEAN) Smart Cities Partnership, aimed to bolster resilience in ASEAN cities by addressing challenges across food, energy, and water systems. Led by the National Renewable Energy Lab (NREL) with support from Regenerative Impact Ventures, the program focused on demonstrating the socio-economic benefits of integrated urban planning, educating stakeholders on circular economy principles, providing technical assistance to two ASEAN cities, and attracting private sector involvement. The program facilitated peer learning events, engaging public and private sector participants and leveraging knowledge from a group of global experts to inform approaches and best practices. Technical assistance was provided to two pilot cities, Iskandar Malaysia and Cagayan de Oro, Philippines, resulting in the development of market-driven business plans for resilient, circular, and regenerative energy-water-food system projects. The Iskandar Malaysia pilot focused on development of a state-of-the-art AgriTech Innovation Hub and Modern Farming Complex to enhance agricultural productivity and produce enough renewable energy to power the facilities. The Cagayan de Oro project aimed to enhance urban agricultural productivity and waste management through development of an Urban Precision Agricultural Complex featuring aeroponics, hydroponics, aquaponics, agrivoltaics, and a Black Solider Fly Facility for converting municipal solid waste into commodities. The success of the IUS program sets a precedent for replicating integrated urban service models globally, offering valuable insights for cities aiming to enhance their resilience and sustainability.

ASEAN↗
DOE OSTI2022

Integrated Urban Services: Regional Launch Event, 10-11 and 12-13 August 2021 [Slides]

The Integrated Urban Services (IUS) Program virtual launch event was conducted on August 10th and 12th, 2021 and provided education to the 26 cities in the ASEAN Smart Cities Network focused on integrated urban planning and the energy-food-water nexus. Experts representing academia, government, NGOs, and the private sector were invited to share knowledge and key lessons from their experience working on urban development projects in the ASEAN region and around the world. The IUS program, which is funded by the U.S. State Department and implemented by the National Renewable Energy Laboratory, aims to promote systems integration and circular economy principles for resource recovery and reuse at the city scale. This new initiative will help ASEAN cities build resilience in their energy, water, and food provision systems. The objectives of this three-year project are to: Educate stakeholders on the benefits of circular economy approaches such as resource recovery and reuse, and on opportunities to build cost-efficient and resilient models of basic urban service and food provision; Provide technical assistance to two select cities within ASEAN to aid them in implementing regenerative EWF system pilot projects; and Engage the private sector to promote market-based planning and investment to support pilot project implementation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Multi-Modal Energy Analysis for Freight

This project addresses the impact of emerging technologies on inter-city freight energy demand, shipping time, and cost. Technologies addressed include electrified long-haul trucks, connectivity and efficient operations, and platooning. The research questions are addressed using national level analysis, a multi-modal inter-city freight energy model, and development of a Freight Mobility Energy Productivity (F-MEP) metric. This project improves on prior analysis and modeling by increasing the geographic and temporal resolution of freight flows. The inter-city freight energy model uses a bi-level optimization approach to minimize total network cost (lower level) and energy (upper level). Two new F-MEP frameworks are presented, one for intra-city freight mobility and one for inter-city freight mobility.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, United States

Abstract Midwestern cities require forecasts of surface nitrate loads to bring additional treatment processes online or activate alternative water supplies. Concurrently, networks of nitrate monitoring stations are being deployed in river basins, co‐locating water quality observations with established stream gauges. However, tools to evaluate the future value of expanded networks to improve water quality forecasts remains challenging. Here, we construct a synthetic data set of stream discharge and nitrate for the Wabash River Basin—one of the United States’ most nutrient polluted basins—using the established Agro‐IBIS and THMB models. Synthetic data enables rapid, unbiased and low‐cost assessment of potential sensor placements to support management objectives, such as near‐term forecasting. Using the synthetic data, we established baseline 1‐day forecasts for surface water nitrate at 12 cities in the basin using support vector machine regression (SVMR; RMSE 0.48–3.3 ppm). Next, we used the SVMRs to evaluate the improvement in forecast performance associated with deployment of additional nitrate sensors. We identified the optimal sensor placement to improve forecasts at each city, and the relative value of sensors at each candidate location. Finally, we assessed the co‐benefit realized by other cities when a sensor is deployed to optimize a forecast at one city, finding significant positive externalities in all cases. Ultimately, our study explores the potential for machine learning to make near‐term predictions and critically evaluate the improvement realized by expanding a monitoring network. While we use nitrate pollution in the Wabash River Basin as a case study, this approach could be readily applied to any problem where the future value of sensors and network design are being evaluated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Intensity and daily pattern of passenger vehicle use by region and class in China: estimation and implications for energy use and electrification

Given the explosive growth of the passenger vehicle market and energy demands in China, research on vehicle-use intensity and driver-travel patterns is critical for better assessing travel demand and its implications for alternative fuel vehicles, energy security, and environmental policies. This study attempts to estimate annual vehicle kilometers traveled (AVKT) per privately-owned passenger vehicle and their daily distance patterns by vehicle class and geographic region. The data sample from a survey consists of 169,292 privately owned passenger vehicles, made by 177 car manufacturers during 2003–2018, running in 82 cities from 27 provincial regions. The log-transformed average AVKT is estimated to be 12,377 km with 95% probability ranging from 5490 to 28,579 km. The investigation reveals that vehicles from South China have the highest AVKT at 13,320 km. Generally, vehicles in small cities have higher AVKT than in big cities, except AVKT of tier 1 cities being higher. Another trend is that more expensive or larger vehicles tend to be driven more. A model is fitted for estimating AVKT based on region, city type, automaker, price range, and certain vehicle features including class and age. Data of daily commuting distances in recent years are also analyzed. The average daily commuting distances typically range from 21 to 28 km. Using the validated Gamma distribution method, daily distance distributions are specified for different regions. It is found that 99% of the daily driving distance is no more than 88.0–112.0 km, depending on region. Utility factors of plug-in electric vehicles are also estimated to be much higher than those based on driving data in the USA. Finally, these findings suggest global mitigations strategies on vehicle fuel use, electrification, and greenhouse gases should consider vehicle-use intensity at the regional level.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Street context of various demographic groups in their daily mobility

Abstract We present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

Salgado, Ariel (ORCID:0000000177015372)↗