An integrated local climatic evaluation system for green sustainable eco-city construction: A case study in Shenzhen, China
Abstract Rapid urbanization has caused a series of environmental problems and increased demand for urban resources. The concept of green, sustainable eco-city constructions is becoming a world-wide common view. Considering the energy configuration and environmental suitability assessment, the outdoor local climate and thermal comfort conditions in a regional area should be effectively evaluated and analyzed to satisfy the resource-saving and environment-friendly demands. This paper proposes a new local climatic evaluation system (LCES) to predict and express local climatic patterns under different urban forms. The system has three modules: a pre-processing module, a dynamic calculation module, and a post-processing module. The pre-processing module uses GIS for parameter design and statistics. The calculation module adopts a regional climatic prediction model to calculate hourly climatic parameters from five dynamically linked sub-modules. The post-processing module expresses the climatic spatial visualizations through the temporal-spatial distributions of climatic parameters. We applied the LCES to conduct the climatic spatial analysis of a planning region in Shenzhen, China. Results from this case study show that local climate varies according to local urban form. During the research period, the average hourly urban heat island intensity (UHII) varied between −0.5 °C and 3 °Cand the average hourly new standard effective temperature (SET*) varied from 24 °C to 40 °C across the research area. We then used threshold values of UHII and SET* to identify problem areas for further analysis and re-planning. This user-friendly, integrated climatic evaluation system helps design climatic friendly urban environments. Highlights A newly integrated local climatic evaluation system (LCES) is developed. The proposed LCES consists of three modules and five databases. A case study in a typical ecological design region is conducted by using LCES. Local climatic distribution maps provide spatial visualization analysis. Problem areas are identified by defining threshold values.
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