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Our goal in this contribution is to study and formulate different scenarios that will aid in identifying opportunities to increase environmental and energy sustainability of the urban environment of a tropical coastal city. These cities are among the most vulnerable to climate change and impacts on the energy infrastructures are particularly concerning. For this effort, the Weather Research and Forecast (WRF) model, with the Building Effect Parameterization and Building Energy Model (BEP-BEM) schemes are applied to the tropical coastal San Juan Metropolitan Area (SJMA) in Puerto Rico. SJMA has a total population of 2.0 million inhabitants in a total area of 750 km(2). Building use and heights required for BEP-BEM are estimated from the World Urban Database Access Portal Tool (WUDAPT), Local Climate Zones (LCZs) classification, which partitions the urban landscape into ten different urban classes. WUDAPT output was compared with observations from the NASA ATLAS Mission and NASA Landsat 8 imagery, and was found to be in good resemblance for their urban built up class. To test energy use and mitigation strategies for SJMA, we consider the heat wave event from 09-29-2014 to 10-02-2014. The new modeling methodology (BEP-BEM-WUDAPT) was found to improve results from non-urbanized versions when compared with observations from a network of weather stations. Air conditioning (AC) demand from urban WRF was found to be in good agreement with EnergyPlus (TM) simulations and available records from the local power utility company. The work explored building energy sustainability and mitigating options to include energy efficient building materials, white roofs, increase of indoor AC temperature set points, and use of high efficiency AC equipment. Among mitigating alternatives explored, results show that white roofs, target indoor temperatures and high efficient AC systems reduce the total energy demand by 6.9%, 9.9% and 16.15%, respectively. Furthermore, when considering all alternatives simultaneously, the peak demand decreased by 40% during a tropical heat wave event. (C) 2018 The Authors. Published by Elsevier B.V.