Large-Eddy Simulation of Flow and Pollutant Transport in Urban Street Canyons with Ground Heating

Our study employed large-eddy simulation (LES) based on a one-equation subgrid-scale model to investigate the flow field and pollutant dispersion characteristics inside urban street canyons. Unstable thermal stratification was produced by heating the ground of the street canyon. Using the Boussinesq approximation, thermal buoyancy forces were taken into account in both the Navier–Stokes equations and the transport equation for subgrid-scale turbulent kinetic energy (TKE). The LESs were validated against experimental data obtained in wind-tunnel studies before the model was applied to study the detailed turbulence, temperature, and pollutant dispersion characteristics in the street canyon of aspect ratio 1. The effects of different Richardson numbers (Ri) were investigated. The ground heating significantly enhanced mean flow, turbulence, and pollutant flux inside the street canyon, but weakened the shear at the roof level. The mean flow was observed to be no longer isolated from the free stream and fresh air could be entrained into the street canyon at the roof-level leeward corner. Weighed against higher temperature, the ground heating facilitated pollutant removal from the street canyon.Singapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Monitorin

On the estimation of wind speed in urban canyons for ventilation purposes-Part 2: Using of data driven techniques to calculate the more probable wind speed in urban canyons for low ambient wind speeds

For low ambient wind speeds, airflow in deep urban canyons is characterized by a high scatter and important fluctuation as no coupling is established between the undisturbed wind flow and the flow inside the canyon. Thus, thermal and mechanical forces determine the wind speed characteristics. Existing studies based on experimental comparison have shown that under the above boundary conditions, deterministic models may predict with sufficient accuracy the mean wind speed but not the fluctuation caused by the thermal phenomena. In the present paper, data have been collected through an extensive experimental campaign in seven canyons. Then, data driven techniques, to predict the more probable wind speed in deep urban canyons as a function of the prevailing thermal and inertia phenomena, have been developed. The proposed methodologies are strictly valid inside the limits of the experimental data, i.e. aspect ratios between 1.7 and 3.25, and can be used to estimate the more probable wind speed close to the facades of urban canyons. © 2007 Elsevier Ltd. All rights reserved

On the use of data driven wand fuzzy techniques to calculate the wind speed in urban canyons

The present per presents the results of an extensive study aiming to develop and validate alternative data driven techniques able to estimate the wind speed in urban canyons. The use of deterministic techniques to calculate the wind speed in canyons present a low accuracy because of the high uncertainty of the input data and the incomplete description of the physical phenomena. ill Extended experimental data collected from seven urban canyons have been used to create a data base of the main parameters that define the phenomenon. Using fuzzy clustering techniques, clusters of input-output data have been developed using as criteria the inertia and gravitational forces. For each cluster using statistical analysis, the more probable wind speed inside the canyon and the corresponding input values have been estimated Thus, a reduced data space has been created. This reduced data space has been used to develop four data driven prediction models The models are : A 31) graphical interpolation method, a tree based model as well as a linear regression model Using the results of the graphical interpolation model, a fuzzy estimation model has been developed as well. All methods have been compared against the experimental data

Recent progress on passive cooling techniques. Advanced technological developments to improve survivability levels in low-income households

Low-income households in developed and less developed countries suffer from serious indoor environmental problems such as heat stress, lack of comfort and poor indoor air quality. Passive cooling of buildings and in particular solar and heat protection techniques, heat dissipation and heat amortisation techniques have reached a very high degree of maturity. New technological developments have proven extremely efficient in decreasing the need for cooling and improving indoor environmental conditions. Developments on the field of solar and heat protection, such as highly reflective coatings for the urban environment and the building envelope and new knowledge and developments on the field of ground and convective cooling and ventilation, may help low-income citizens to considerably improve their quality of life during the overheating period. These new developments are characterised by low cost and are easy to apply. This paper investigates the potential of the more promising new developments on the field of passive cooling, like the cool reflective coatings to improve outdoor and indoor conditions of low-income households in warm areas of the planet, ground cooling using earth to air heat exchangers, and discusses the potential of new ventilation techniques and systems for improving indoor comfort and air quality. Results show a very high potential to improve indoor environmental conditions and contribute towards higher passive survivability levels. © 2007 Elsevier B.V. All rights reserved

Smart stormwater management in urban areas by roofs greening

By 2050 the world population will grow to about 9 billion contributing to deep changes in urban areas structure. This would increase the effect of water deficiency and along with projected climate changes the impact of urban flood-ings, urban heat islands or drought. Smart cities could be key part of the solution contributing to improve the quality life of citizen in urban areas with the adoption of smart, intelligent technologies and infrastructure for energy, water, mobility, buildings, and government. The concept of smart water refers to the ability to provide and manage this primary resource in quantitative and qualitative terms in order to satisfy the future needs of population. The green roof (GR) is a technique belonging to the sectors of smart energy and smart water. It could provide several benefits: sound and thermal insulation of the buildings, mitigation of the urban heat island effects, reduction of air pollution, additionally, GR induces important hydraulic advantages acting as an effective tool for reducing flood risk in urban area with runoff reduction, attenuation and delay of the peak flow. In this paper, the retention capacity of two green roof test beds located in the campus of University of Salerno has been investigated. The analysis has referred to measures of runoff and rainfall conducted in 2017 during the months of February and March. The two roofs substantially differ in the composition of the water storage layer made up of expanded clay in GR1 and of commercial drainage panels in GR2. The retention capacity of the two test beds has been compared. The results confirm that both green roofs, although to a different extent, are effective for the reduction of total runoff volume of rainwater falling on their area