Marion Bonhomme

Solar Panels reduce both global warming and Urban Heat Island

The production of solar energy in cities is clearly a way to diminish our dependency to fossil fuels, and is a good way to mitigate global warming by lowering the emission of greenhouse gases. However, what are the impacts of solar panels locally ? To evaluate their influence on urban weather, it is necessary to parameterize their effects within the surface schemes that are coupled to atmospheric models. The present paper presents a way to implement solar panels in the Town Energy Balance scheme, taking account of the energy production (for thermal and photovoltaic panels), the impact on the building below and feedback towards the urban micro-climate through radiative and convective fluxes. A scenario of large but realistic deployment of solar panels on the Paris metropolitan area is then simulated. It is shown that solar panels, by shading the roofs, slightly increases the need for domestic heating (3%). In summer however, the solar panels reduce the energy needed for air-conditioning (by 12%) and also the Urban Heat Island (UHI): 0.2K by day and up to 0.3K at night. These impacts are larger than those found in previous works, because of the use of thermal panels (that are more efficient than photovoltaic panels) and the geographical position of Paris, which is relatively far from the sea. This means that it is not influenced by sea breezes, and hence that its UHI is stronger than for a coastal city of the same size. But this also means that local adaptation strategies aiming to decrease the UHI will have more potent effects. In summary, the deployment of solar panels is good both globally, to produce renewable energy (and hence to limit the warming of the climate) and locally, to decrease the UHI, especially in summer, when it can constitute a health threat.

Análise do impacto da morfologia urbana na demanda estimada de energia das edificações: um estudo de caso na cidade de Maceió, AL

Este estudo apresenta um metodo simplificado de analise e mapeamento morfologico do tecido urbano para auxiliar no estudo da climatologia e do impacto da forma urbana na demanda de energia das edificacoes. Diferentes parâmetros foram empregados na analise da geometria urbana, a fim realizar uma cartografia de areas morfologicamente homogeneas, cada uma apresentando uma influencia diferente na demanda energetica das edificacoes. Numa primeira etapa, os parâmetros morfologicos urbanos foram automatizados e calculados em um sistema de informacao geografica, para diferentes resolucoes espaciais. Os resultados morfologicos obtidos para uma aplicacao na cidade de Maceio, AL, foram analisados por meio da Analise de Componentes Principais (ACP), a partir da qual foi possivel identificar a significância dos parâmetros para o contexto urbano considerado. A analise de agrupamento (Clustering Analysis) permitiu que as diferentes configuracoes tipologicas fossem agregadas, classificadas e, na sequencia, submetidas as simulacoes computacionais para estimativa da demanda de energia das edificacoes. Seis indicadores morfologicos foram conservados e cinco classes tipologicas representativas do tecido urbano de Maceio foram destacadas. Observou-se um impacto importante na demanda de energia de tres parâmetros morfologicos principais: a densidade total construida, a verticalidade, a compacidade e o prospecto medio.

Impact of spatial and spectral resolutions on the classification of urban areas

Classification of land cover in urban areas can play an important role in urban planning decisions and in characterizing urban materials properties such as reflectance. Taking into account the large offer of new and future remote sensing sensors with different spectral and spatial characteristics, it is important to compare their classification performances in urban area. To this aim, this work simulates from airborne data the at sensor images acquired by three space borne instruments (Pléiades, SENTINEL-2 and HYPXIM) in the Visible Near Infrared (0.4 μm - 1.0 μm) and Shortwave Infrared (1.0 μm-2.5μm) spectral ranges. Five classification maps with 8 land cover classes over the city of Toulouse (France) are generated with a Support Vector Machine rule. Correct values of accuracy are obtained in all cases (kappa coefficient higher than 0.65 and overall accuracy better than 70 %). Nevertheless, coarser spatial resolutions do not allow mapping urban details and SWIR data was necessary to discriminate between classes.

MUSE: An Open Urban Management Decision Support System

Abstract This paper describes a decision support tool for urban planners. Numerous research studies show that energy consumed and produced in cities can be related to its morphology. Yet, the urban energy paradox is defined as follows: on the one hand, the densification of cities reduces transportation and buildings consumptions. On the other hand, this densification has a negative impact on urban microclimate and renewable energies potential. The goal of this work is to develop a decision support system for urban planners faced with urban energy paradox. Our research is based on a previous work developed by Luc Adolphe et al. in the SAGACites project. This research led to the development of the geographic information system (GIS) platform called MORPHOLOGIC, which, among other things, evaluates the energy consumption of city blocks. Our goal is to add new features in MORPHOLOGIC: one of them calculates solar potential (photovoltaic and thermal), using a simplified model of shadows. The new version of MORPHOLOGIC called MUSE, based on the open source GIS called OrbisGis developed by the IRSTV institute, will allow urban planners to evaluate the best urban form to reduce GHG emissions.