Evaluating the ENVI-met microscale model for suitability in analysis of targeted urban heat mitigation strategies

Microscale atmospheric models are increasingly being used to project the thermal benefits of urban heat mitigation strategies (e.g., tree planting programs or use of high-albedo materials). However, prior to investment in specific mitigation efforts by local governments, it is desirable to test and validate the computational models used to evaluate strategies. While some prior studies have conducted limited evaluations of the ENVI-met microscale climate model for specific case studies, there has been relatively little systematic testing of the model's sensitivity to variations in model input and control parameters. This study builds on the limited foundation of past validation efforts by addressing two questions: (1) is ENVI-met grid independent; and (2) can the model adequately represent the air temperature perturbations associated with heat mitigation strategies? To test grid independence, a “flat” domain is tested with six vertical grid resolutions ranging from 0.75 to 2.0 m. To examine the second question, a control and two mitigation strategy simulations of idealized city blocks are tested. Results show a failure of grid independence in the “flat” domain simulations. Given that the mitigation strategies result in temperature changes that are an order of magnitude larger than the errors introduced by grid dependence for the flat domain, a lack of grid independence itself does not necessarily invalidate the use of ENVI-met for heat mitigation research. However, due to limitations in grid structure of the ENVI-met model, it was not possible to test grid dependence for more complicated simulations involving domains with buildings. Furthermore, it remains unclear whether existing efforts at model validation provide any assurance that the model adequately captures vertical mixing and exchange of heat from the ground to rooftop level. Thus, there remain concerns regarding the usefulness of the model for evaluating heat mitigation strategies, particularly when applied at roof level (e.g. high albedo or vegetated roofs)

Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data

Combined sewer overflows (CSOs) represent a common feature in combined urban drainage systems and are used to discharge excess water to the environment during heavy storms. To better understand the performance of CSOs, the UK water industry has installed a large number of monitoring systems that provide data for these assets. This paper presents research into the prediction of the hydraulic performance of CSOs using artificial neural networks (ANN) as an alternative to hydraulic models. Previous work has explored using an ANN model for the prediction of chamber depth using time series for depth and rain gauge data. Rainfall intensity data that can be provided by rainfall radar devices can be used to improve on this approach. Results are presented using real data from a CSO for a catchment in the North of England, UK. An ANN model trained with the pseudo-inverse rule was shown to be capable of providing prediction of CSO depth with less than 5% error for predictions more than one hour ahead for unseen data. Such predictive approaches are important to the future management of combined sewer systems

The impact of heat mitigation strategies on the energy balance of a neighborhood in Los Angeles

Heat mitigation strategies can reduce excess heat in urban environments. These strategies, including solar reflective cool roofs and pavements, green vegetative roofs, and street vegetation, alter the surface energy balance to reduce absorption of sunlight at the surface and subsequent transfer to the urban atmosphere. The impacts of heat mitigation strategies on meteorology have been investigated in past work at the mesoscale and global scale. For the first time, we focus on the effect of heat mitigation strategies on the surface energy balance at the neighborhood scale. The neighborhood under investigation is El Monte, located in the eastern Los Angeles basin in Southern California. Using a computational fluid dynamics model to simulate micrometeorology at high spatial resolution, we compare the surface energy balance of the neighborhood assuming current land cover to that with neighborhood‐wide deployment of green roof, cool roof, additional trees, and cool pavement as the four heat mitigation strategies. Of the four strategies, adoption of cool pavements led to the largest reductions in net radiation (downward positive) due to the direct impact of increasing pavement albedo on ground level solar absorption. Comparing the effect of each heat mitigation strategy shows that adoption of additional trees and cool pavements led to the largest spatial‐maximum air temperature reductions at 14:00h (1.0 and 2.0 °C, respectively). We also investigate how varying the spatial coverage area of heat mitigation strategies affects the neighborhood‐scale impacts on meteorology. Air temperature reductions appear linearly related to the spatial extent of heat mitigation strategy adoption at the spatial scales and baseline meteorology investigated here

Cost-benefit considerations in regulatory analysis

Justification for safety enhancements at nuclear facilities, e.g., a compulsory backfit to nuclear power plants, requires a value-impact analysis of the increase in overall public protection versus the cost of implementation. It has been customary to assess the benefits in terms of radiation dose to the public averted by the introduction of the safety enhancement. Comparison of such benefits with the costs of the enhancement then requires an estimate of the monetary value of averted dose (dollars/person rem). This report reviews available information on a variety of factors that affect this valuation and assesses the continuing validity of the figure of $1000/person-rem averted, which has been widely used as a guideline in performing value-impact analyses. Factors that bear on this valuation include the health risks of radiation doses, especially the higher risk estimates of the BEIR V committee, recent calculations of doses and offsite costs by consequence codes for hypothesized severe accidents at U.S. nuclear power plants under the NUREG-1150 program, and recent information on the economic consequences of the Chernobyl accident in the Soviet Union and estimates of risk avoidance based on the willingness-to-pay criterion. The report analyzes these factors and presents results on the dollars/person-rem ratio arising from different assumptions on the values of these factors

Robot localization in water pipes using acoustic signals and pose graph optimization

One of the most fundamental tasks for robots inspecting water distribution pipes is localization, which allows for autonomous navigation, for faults to be communicated, and for interventions to be instigated. Pose-graph optimization using spatially varying information is used to enable localization within a feature-sparse length of pipe. We present a novel method for improving estimation of a robot’s trajectory using the measured acoustic field, which is applicable to other measurements such as magnetic field sensing. Experimental results show that the use of acoustic information in pose-graph optimization reduces errors by 39% compared to the use of typical pose-graph optimization using landmark features only. High location accuracy is essential to efficiently and effectively target investment to maximise the use of our aging pipe infrastructure

Effects of urbanization on regional meteorology and air quality in Southern California

Urbanization has a profound influence on regional meteorology and air quality in megapolitan Southern California. The influence of urbanization on meteorology is driven by changes in land surface physical properties and land surface processes. These changes in meteorology in turn influence air quality by changing temperature-dependent chemical reactions and emissions, gas–particle phase partitioning, and ventilation of pollutants. In this study we characterize the influence of land surface changes via historical urbanization from before human settlement to the present day on meteorology and air quality in Southern California using the Weather Research and Forecasting Model coupled to chemistry and the single-layer urban canopy model (WRF–UCM–Chem). We assume identical anthropogenic emissions for the simulations carried out and thus focus on the effect of changes in land surface physical properties and land surface processes on air quality. Historical urbanization has led to daytime air temperature decreases of up to 1.4&thinsp;K and evening temperature increases of up to 1.7&thinsp;K. Ventilation of air in the LA basin has decreased up to 36.6&thinsp;% during daytime and increased up to 27.0&thinsp;% during nighttime. These changes in meteorology are mainly attributable to higher evaporative fluxes and thermal inertia of soil from irrigation and increased surface roughness and thermal inertia from buildings. Changes in ventilation drive changes in hourly NOx concentrations with increases of up to 2.7&thinsp;ppb during daytime and decreases of up to 4.7&thinsp;ppb at night. Hourly O3 concentrations decrease by up to 0.94&thinsp;ppb in the morning and increase by up to 5.6&thinsp;ppb at other times of day. Changes in O3 concentrations are driven by the competing effects of changes in ventilation and precursor NOx concentrations. PM2.5 concentrations show slight increases during the day and decreases of up to 2.5&thinsp;µg&thinsp;m−3 at night. Process drivers for changes in PM2.5 include modifications to atmospheric ventilation and temperature, which impact gas–particle phase partitioning for semi-volatile compounds and chemical reactions. Understanding process drivers related to how land surface changes effect regional meteorology and air quality is crucial for decision-making on urban planning in megapolitan Southern California to achieve regional climate adaptation and air quality improvements.</p

Beam Test Performance and Simulation of Prototypes for the ALICE Silicon Pixel Detector

The silicon pixel detector (SPD) of the ALICE experiment in preparation at the Large Hadron Collider (LHC) at CERN is designed to provide the precise vertex reconstruction needed for measuring heavy flavor production in heavy ion collisions at very high energies and high multiplicity. The SPD forms the innermost part of the Inner Tracking System (ITS) which also includes silicon drift and silicon strip detectors. Single assembly prototypes of the ALICE SPD have been tested at the CERN SPS using high energy proton/pion beams in 2002 and 2003. We report on the experimental determination of the spatial precision. We also report on the first combined beam test with prototypes of the other ITS silicon detector technologies at the CERN SPS in November 2004. The issue of SPD simulation is briefly discussed.Comment: 4 pages, 5 figures, prepared for proceedings of 7th International Position Sensitive Detectors Conference, Liverpool, Sept. 200

Reconstruction of the frequency-wavenumber spectrum of water waves with an airborne acoustic Doppler array for non-contact river monitoring

This work presents a novel method to reconstruct the frequency-wavenumber spectrum of water waves based on the complex acoustic Doppler spectra of scattered sound measured with an array of microphones. The reconstruction is based on a first-order small-roughness-amplitude expansion of the acoustic wave scattering equation, which is discretized and inverted by means of a singular value decomposition. An analogy of this approach to the first-order Bragg scattering problem is demonstrated by means of a stationary phase expansion. The approach enables the reconstruction of the dispersion relation of water waves when the ratio between roughness height and acoustic wavelength is less than 0.1, and when the surface wavelength is larger than 1/2 of the acoustic wavelength. The method is validated against synthetic data and data from laboratory and field experiments, to demonstrate its applicability to two-and three-dimensional complex patterns of water waves, and specifically to the surface deformations that arise naturally in a turbulent open-channel flow. Fitting the reconstructed data with the analytical dispersion relation enables the non-contact estimate of the underlying flow velocity for hydraulic conditions where the coexistence of different types of turbulence-forced and freely propagating water waves would limit the accuracy of standard non-contact Doppler velocimetry approaches, paving the way for robust and accurate non-contact river monitoring using acoustics

Hacia una tecnología de apoyo conductual "no aversivo"

En este artículo se hace una introducción del tratamiento conductual no aversivo. Se sugieren importantes definiciones y se presentan tres elementos fundamentales: a) un emergente conjunto de procedimientos para apoyar a personas con trastornos conductuales graves; b) criterios de validación social que insisten en la dignidad de las personas; y c) una recomendación de que se prohíban o limiten ciertas estrategias. Estos elementos se definen con la esperanza de que provoquen ulteriores debates y análisis empíricos del apoyo conductual positivo

The International Urban Energy Balance Models Comparison Project: First Results from Phase 1

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no com- parison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling ap- proaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux