Impacts of the morphology of new neighborhoods on microclimate and building energy

https://doi.org/10.1016/j.rser.2020.110030Get rights and content

Highlights

  • Process creates and tests new neighborhood morphologies for impact on meteorology in a mesoscale weather model.

  • Allocates individual meteorological profiles to buildings and runs parallel computation of each building’s energy use.

  • First step to assessing future microclimate and building energy consumption using global climate and population projections.

Abstract

In anticipation of emerging global urbanization and consequent increases in energy use and carbon dioxide emissions, better understanding and quantification of climate effects on energy use in cities are needed, requiring coordinated research into large-scale, regional, and microclimate impacts to and from the city structure. The methodology described here addresses this need by (1) demonstrating a process for creating and testing example morphologies for new neighborhoods for their impact on local and regional meteorology within a two-way-coupled four-domain nested mesoscale weather model (6 km horizontal resolution outer domain, 90 m horizontal innermost domain) and (2) allocating resulting building-level meteorological profiles to each building in a neighborhood for parallel computation of building-by-building energy use. Our Chicago Loop test case shows that the morphology of even a small new added development to a neighborhood affects not only its own microclimate, but also the microclimate of the original neighborhood to which the development was added, and that these changes in microclimate affect both neighborhoods’ building energy use. This method represents an important step toward quantifying and analyzing the relationships among climatic conditions, urban morphology, and energy use and using these relationships to inform energy-efficient urban development and planning.

Section snippets

Introduction and background

Global and climates are primary drivers of heating and cooling demand for buildings. The United States, comprising only 4.4% of the world's population, consumes 19% of the world's primary energy production. In 2010, buildings accounted for the largest fraction (41%) of primary energy consumption. This fraction of consumption amounts to 40% of total US carbon dioxide (CO2) emissions, contributing significantly to global warming and to regional climate change [1]. Climate change impacts, urban

Numerical weather prediction simulation with high-resolution urban topography

Five 1-year, four-domain, nested meteorological simulations for 2015 were run using the Weather Research and Forecasting (WRF) model on the ORNL Titan supercomputer for two locations: one for the ORNL research campus and four for the Chicago Loop area. Each simulation contained urban terrain inputs at 10 m resolution. The four simulations run for the Chicago Loop include one each for (1) the Loop alone, (2) the Loop with an added Clark-Roosevelt development (southwest of the Loop) proposed at

Results and discussion

An overall summary of the weather simulation results is given first; then a more specific analysis is given for temperature, wind speed, and relative humidity. Finally, the results of the building energy use simulation are discussed. Direct and diffuse radiation results are discussed in the Supplementary Information.

Conclusions

We have demonstrated a methodology for testing different morphologies for new developments in cities within a mesoscale model and have shown that the addition of even a small development to an existing neighborhood can change the microclimate of the existing neighborhood. As mesoscale models are often coupled with Earth system models to understand regional impacts of large-scale systems under future scenarios, this methodology may be used further to understand global impacts and feedbacks from

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle LLC for the U.S. Department of Energy (DOE); and by the DOE Office of Science as a part of the research in Multi-Sector Dynamics within the Earth and Environmental System Modeling Program; and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the DOE Office of Science and the National Nuclear Security Administration. It used

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    This manuscript has been authored by UT-Battelle LLC under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

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