60 research outputs found

    ESTIMATING METEOROLOGICAL INPUTS FOR URBAN DISPERSION MODELS

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    Meteorological variables such as surface friction velocity and heat flux are critical inputs to the current generation of dispersion models such as AERMOD. This paper examines methods to estimate these variables by applying Monin-Obukhov (M-O) similarity to measurements made on towers located in urban areas. The inputs to these methods are restricted to the wind speed and the standard deviation of temperature fluctuations data measured at a single level on a tower. The performance of these methods are evaluated with data collected at one urban and two suburban towers in Riverside, California during two months in 2007, The data consisted of mean winds and temperatures as well as heat and momentum fluxes using a sonic anemometer at one level on each tower. The major conclusions of this study are that during unstable conditions: 1) M-O theory provides adequate estimates of micrometeorological variables using urban measurements of mean winds and temperatures at one level when the standard deviation of temperature fluctuations is used to estimate heat flux, 2) the simple free convection estimate provides estimates of the heat flux that compare well with those from methods that account for stability effects through the M-O length, 3) all the methods overestimate heat flux close to neutral conditions, 4) the overestimation of heat flux does not appear to affect estimates of surface friction velocity, but results in overestimation of the vertical turbulent velocity. During stable conditions, 1) vertical and horizontal velocity fluctuations are related to friction velocity through similarity relationships derived in flat terrain, 2) estimates of the surface friction velocity based on temperature fluctuations do not improve upon those based on a constant value o

    Integrated Simulation Platform for Quantifying the Traffic-Induced Environmental and Health Impacts

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    Air quality and human exposure to mobile source pollutants have become major concerns in urban transportation. Existing studies mainly focus on mitigating traffic congestion and reducing carbon footprints, with limited understanding of traffic-related health impacts from the environmental justice perspective. To address this gap, we present an innovative integrated simulation platform that models traffic-related air quality and human exposure at the microscopic level. The platform consists of five modules: SUMO for traffic modeling, MOVES for emissions modeling, a 3D grid-based dispersion model, a Matlab-based concentration visualizer, and a human exposure model. Our case study on multi-modal mobility on-demand services demonstrates that a distributed pickup strategy can reduce human cancer risk associated with PM2.5 by 33.4% compared to centralized pickup. Our platform offers quantitative results of traffic-related air quality and health impacts, useful for evaluating environmental issues and improving transportation systems management and operations strategies.Comment: 35 pages, 11 figure

    Spatial particulate fields during highwinds in the imperial valley, California

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    We examined windblown dust within the Imperial Valley (CA) during strong springtime west-southwesterly (WSW) wind events. Analysis of routine agency meteorological and ambient particulate matter (PM) measurements identified 165 high WSW wind events between March and June 2013 to 2019. The PM concentrations over these days are higher at northern valley monitoring sites, with daily PM mass concentration of particles less than 10 micrometers aerodynamic diameter (PM10) at these sites commonly greater than 100 μg/m3 and reaching around 400 μg/m3, and daily PM mass concentration of particles less than 2.5 micrometers aerodynamic diameter (PM2.5) commonly greater than 20 μg/m3 and reaching around 60 μg/m3. A detailed analysis utilizing 1 km resolution multi-angle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD), Identifying Violations Affecting Neighborhoods (IVAN) low-cost PM2.5 measurements and 500 m resolution sediment supply fields alongside routine ground PM observations identified an area of high AOD/PM during WSW events spanning the northwestern valley encompassing the Brawley/Westmorland through the Niland area. This area shows up most clearly once the average PM10 at northern valley routine sites during WSW events exceeds 100 μg/m3. The area is consistent with high soil sediment supply in the northwestern valley and upwind desert, suggesting local sources are primarily responsible. On the basis of this study, MAIAC AOD appears able to identify localized high PM areas during windblown dust events provided the PM levels are high enough. The use of the IVAN data in this study illustrates how a citizen science effort to collect more spatially refined air quality concentration data can help pinpoint episodic pollution patterns and possible sources important for PM exposure and adverse health effects

    Evaluating AERMOD With Measurements From a Major U.S. Airport Located on a Shoreline

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    13-C-AJFE-UNC-007, 014This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Gavendra Pandey, Akula Venkatram, and Saravanan Arunachalam. 2023. Evaluating AERMOD with measurements from a major U.S. airport located on a shoreline. Atmospheric Environment, 294, 119506. https://doi.org/10.1016/j.atmosenv.2022.119506The impact of airport operations on air quality is a key public health concern for the population surrounding an airport. Air pollution regulations require the assessment of this impact using dispersion models. Modeling dispersion of aircraft-related sources poses challenges because of the large number and variety of airport sources, which include aircraft, ground operation vehicles, and traffic in and out of the airport, most of which are mobile. Emissions from aircraft sources are transient, buoyant, and occur at different heights from the ground. Quantifying these emissions as well as modeling the governing processes is challenging. An added complexity occurs when the airport is situated near a shoreline where meteorological conditions are far from being spatially uniform
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