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At least 37 records · Page 2

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗

The history and nature of the Baltimore applications project

The Baltimore Applications Project (BAP), an experiment jointly conducted by the City of Baltimore and the National Aeronautics and Space Administration (NASA), was begun in May 1974 in response to a request by the City. The main purpose of the BAP is the identification of technology for beneficial application to the City operations. An independent evaluation, performed after three years of operation, indicates very good project results and confirms the choices of the experiment's basic features. The BAP demonstrates one way to achieve successful intergovernmental transfer of Federal technology.

Peake, H. J.↗

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Estes, Maurice G., Jr.↗

Estimation of Daily PM(sub 10) Concentrations in Italy (2006-2012) Using Finely Resolved Satellite Data, Land Use Variables and Meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particulate Matter/analysis↗

Seattle's System for Evaluating Energy Options

In 1975, the City Council developed a blueprint called "Energy 1990" for meeting Seattle's future electric energy needs. Priorities for addressing or offsetting expected growth in demand are in order: (1) conservation; (2) hydroelectricity; (3) other renewable sources such as wind, biomass, solar, and geothermal energy; (4) abundant nonrenewable resources such as coal, and (5) other renewables. An energy resources planning group was formed and a data base was established. Resource options were investigated and the recommendations were published.

Logie, P.↗

Identification of surface urban heat versus cool islands for arid cities depends on the choice of urban and rural definitions

The urban heat island (UHI) effect in arid cities can be small or even negative, the latter known as the urban cool island (UCI) effect. Differences in defining urban and rural areas can introduce uncertainties in detecting UHI or UCI, especially when the UHI signal is small. Here, we compared the surface UHI intensity (SUHII) estimated by a dozen different methods (with multiple urban and/or rural definitions) across 104 arid cities globally, providing a comprehensive evaluation of the uncertainty in SUHII estimates. Results show that the absolute difference in annual average SUHII (ΔSUHII) among methods exceeded 1°C in about half of the arid cities during both daytime and nighttime. Further, the overall annual mean ΔSUHII for all arid cities was 1.35°C during daytime and 1.03 °C at night. The uncertainty arising from simultaneous variations in urban and rural definitions was generally higher than that resulting from their individual changes. It was observed that, with varying definitions of urban and rural areas, nearly 50% of arid cities experienced a sign reversal in daytime SUHII estimates, while approximately 15% exhibited a sign reversal in nighttime SUHII. Variations in urban-rural differences in surface properties, such as vegetation index and albedo, due to differing urban and rural definitions, contributed strongly to the observed SUHII uncertainties. Overall, our results offer new insights into the ongoing debate on heat and cold islands in arid cities, emphasizing a critical need to standardize SUHII estimation frameworks.

54 ENVIRONMENTAL SCIENCES↗

Aircraft Based Remotely Sensed Albedo and Surface Temperatures for Three US Cities

High spatial resolution thermal infrared and visible data obtained from aircraft were used to measure, map, and model the surface energy budget characteristics of surfaces typical of the urban landscape for three US cities. Aircraft data collected from the Advanced Thermal and Land Applications Sensor (ATLAS) scanner allowed a detail analysis of the city, determining its surface thermal and visible reflectance properties. These data are critical in providing data that can be used to evaluate the overall "fabric" of the cities in relation to the urban heat island and air quality modeling.

Luvall, Jeffrey C.↗

Citywide indoor air sampling mirrors wastewater and clinical for environmental surveillance of respiratory viruses

Wastewater surveillance of respiratory pathogens can provide timely estimates of viral activity and disease trends in a population. Indoor air surveillance could be used similarly with some advantages but remains largely unvalidated at the community -scale. Here, an indoor air surveillance program was employed as part of public health environmental surveillance in Chicago, Illinois, USA. Ten air samplers were placed in healthcare and congregate living settings across the city. Weekly air samples were evaluated for influenza A, influenza B, respiratory syncytial virus, and SARS -CoV-2 over two respiratory virus seasons (2023 -2025). Citywide, aggregated air sample positivity and viral load were closely correlated with local clinical case and wastewater surveillance data across all respiratory viruses. Virus trends in air data often preceded clinical and wastewater, although this varied across pathogens and respiratory virus seasons. Further, whole -genome sequencing of SARS -CoV-2 showed close correlation of variant proportions across all datasets. At the building -scale, air samples obtained from a single sampling device provided efficient respiratory virus surveillance, with respiratory pathogen levels mirroring citywide clinical surveillance data. These data demonstrate that air surveillance can provide respiratory virus case and variant trend data at a building or community -scale, serving as an alternative or complementary tool for public health environmental surveillance.

Wilton, Rosemarie↗

Frankfort 100 Solar Feasibility Study

In 2021, The city of Frankfort, Kentucky ("Frankfort," or "the City") committed to ambitious climate targets: 1. City Clean Electricity: 100% clean electricity for city government operations by the end of 2023, 2. City Clean Energy: 100% clean energy for city government operations by the end of 2030, and 3. Community Clean Energy: 100% clean energy community-wide by the end of 2040. In 2022, Frankfort partnered with the National Renewable Energy Laboratory for a Phase I study to identify pathways to achieve the City's first two goals of City Clean Electricity by 2023 and City Clean Energy by 2030 (Phase I). As recommended in the final Phase I report described (described below), NREL was asked to perform an initial feasibility study for a PV project to offset the electricity used by city government operations. This report evaluates the feasibility of utility-scale solar and identifies potential barriers.

14 SOLAR ENERGY↗

Comparative Study of Variations in Quantum Approximate Optimization Algorithms for the Traveling Salesman Problem

The traveling salesman problem (TSP) is one of the most often-used NP-hard problems in computer science to study the effectiveness of computing models and hardware platforms. In this regard, it is also heavily used as a vehicle to study the feasibility of the quantum computing paradigm for this class of problems. In this paper, we tackle the TSP using the quantum approximate optimization algorithm (QAOA) approach by formulating it as an optimization problem. By adopting an improved qubit encoding strategy and a layer-wise learning optimization protocol, we present numerical results obtained from the gate-based digital quantum simulator, specifically targeting TSP instances with 3, 4, and 5 cities. We focus on the evaluations of three distinctive QAOA mixer designs, considering their performances in terms of numerical accuracy and optimization cost. Notably, we find that a well-balanced QAOA mixer design exhibits more promising potential for gate-based simulators and realistic quantum devices in the long run, an observation further supported by our noise model simulations. Furthermore, we investigate the sensitivity of the simulations to the TSP graph. Overall, our simulation results show that the digital quantum simulation of problem-inspired ansatz is a successful candidate for finding optimal TSP solutions.

97 MATHEMATICS AND COMPUTING↗

A Satellite Assessment of the Urban Heat Island in Morocco

Urban ecosystems interact with surroundings via land cover changes and their subsequent impact on surface temperature. In emerging countries, large urban agglomerations often form around cities, and only few studies have evaluated their impact. This study carries out the first ever large-scale assessment of urban heat island (UHI) and reflects on its mitigation in Morocco.The analysis reveals a well-defined UHI in urban-areas built within vegetated lands and an urban heat sink (UHS) in urban-areas built within arid regions. Both UHI and UHS amplitudes are higher during day than nighttime, emphasizing vegetation physiological activity. We show a monotonic increase in UHI amplitude with urban-area size. However, unlike previous studies, our analysis shows that as urban-areas built in desert-like environments grow in size, the UHS gradually decreases to ultimately turn into an UHI. On average, cities built within vegetation are warmer than rural fringe by 1.51°C during daytime. This suggests that daytime urban heating may exacerbate the potential climate warming. Our results also suggest that adapted trees constitute a natural cooling mechanism and should be part of urban heating mitigation in Morocco.

Urban Heat Sink↗

Improvement of aerosol optical depth data for localized solar resource assessment

Solar irradiance, especially for direct normal irradiance (DNI), is sensitive to the atmospheric aerosols, which can strongly extinguish DNI over areas with elevated aerosol loadings. The National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL), uses AOD from MERRA-2 reanalysis and is further downscaled from 0.5° to 2-km based on elevation. However, the elevation-based downscaling may not accurately represent AOD, especially over the areas with large AOD gradients. This study examined whether the 1-km MODIS MAIAC satellite-retrieved AOD product can better represent the AOD distribution and be used to improve solar irradiance assessment. We focused on areas with relatively high AOD over North America (California, and New York City, US, and Mexico City in Mexico, in particular). The evaluation of MAIAC AOD and MERRA-2 AOD against ground-truth AERONET AOD shows that MAIAC AOD exhibits smaller RMSE by about 0.05 and higher correlation coefficient by 0.1-0.6 than MERRA-2 AOD. In addition, MERRA-2 AOD shows larger negative bias. The simulated DNI using MAIAC AOD (DNIMAIAC) and using MERRA-2 AOD (DNINSRDB) were evaluated with DNI observations. The results show the performance of DNIMAIAC is better than that of DNINSRDB with smaller RMSE by 0.5-1.5%, smaller positive mean bias by 0.8-3.1% and comparable correlation for the 3 sites analyzed. Overall, 1-km MAIAC AOD shows higher accuracy than 2-km elevation-based MERRA-2 AOD, leading to better performance of the simulated DNI using MAIAC AOD. Therefore, 1-km MAIAC AOD can be used to improve the accuracy of solar resource assessment.

14 SOLAR ENERGY↗

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Ohio River main stem study - The role of geographic information systems and remote sensing in flood damage assessments

The Pittsburgh District, Corps of Engineers, has conducted feasibility analyses of various procedures for performing flood damage assessments along the main stem of the Ohio River. Procedures using traditional, although highly automated, techniques and those based on geographic information systems have been evaluated at a test site, the City of New Martinsville, Wetzel County, WV. The flood damage assessments of the test site developed from an automated, conventional structure-by-structure appraisal served as the ground truth data set. A geographic information system was developed for the test site which includes data on hydraulic reach, ground and reference flood elevations, and land use/cover. Damage assessments were made using land use mapping developed from an exhaustive field inspection of each tax parcel. This ground truth condition was considered to provide the best comparison of flood damages to the conventional approach. Also, four land use/cover data sets were developed from Thematic Mapper Simulator (TMS) and Landsat-4 Thematic Mapper (TM) data. One of these was also used to develop a damage assessment of the test site. This paper presents the comparative absolute and relative accuracies of land use/cover mapping and flood damage assessments, and the recommended role of geographic information systems aided by remote sensing for conducting flood damage assessments and updates along the main stem of the Ohio River.

Edwardo, H. A.↗

Remote sensing for evaluating post-disaster damage conditions: The Pierre, South Dakota tornado, 23 July 1973

Remote sensing data obtained from aerial reconnaissance of tornado damage to the city of Pierre, South Dakota on July 23, 1973 was evaluated to determine its value as a decision making and management tool in post-disaster restoration activities. The imaging techniques used are briefly discussed, and both aerial and closeup color photographs are provided which were used in the evaluation. The immediate advantages of the data are identified as a 'quick-look' assessment, and a list is given which outlines the additional advantages for which positive rescue and cleanup action may be initiated. Hail and flood damage evaluation, and remote sensing of crop damage due to insect of disease infestation is also briefly described.

Rusche, A. E.↗