Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

Zhou, Yuyu; Clarke, Leon; Eom, Jiyong; Kyle, Page; Patel, Pralit; Kim, Son H.; Dirks, James A.; Jensen, Erik Steen; Liu, Ying; Rice, Jennie S.; Schmidt, Laurel; Seiple, Timothy E.

doi:10.1016/j.apenergy.2013.08.034

Cited by 156 publications

(98 citation statements)

References 23 publications

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“…Previous studies are limited in addressing the effect of a changing climate on building energy demands while simultaneously considering other energy sectors in the underlying human systems. In recent years, the impacts of climate change on building energy use have been evaluated using IA models by constructing estimates of heating and cooling degree days from air temperature outputted from climate models (Isaac and van Vuuren, 2009;van Ruijven et al, 2011;Zhou et al, , 2014Yu et al, 2014). The feedback from the climate on the energy system was calculated from climate model output in advance using a one-way coupling scheme, and the impact of these changes in the energy system on climate was rarely considered in these studies.…”

Section: Building Energy Usementioning

confidence: 99%

The integrated Earth system model version 1: formulation and functionality

et al. 2015

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Abstract.The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human-Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. The iESM project integrates the economic and humandimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human-Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.

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Section: Building Energy Usementioning

confidence: 99%

The integrated Earth system model version 1: formulation and functionality

et al. 2015

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“…These studies can be divided into three categories (Ciscar and Dowling, 2014): (1) assessments of the statistical relationship between climatic conditions and energy variables (De Cian et al, 2013); (2) incorporation of empirical results into broader modelling systems (Isaac and van Vuuren, 2009;Mima and Criqui, 2009;Roson and van der Mensbrugghe, 2012); and (3) integration of technological choices into broader modelling systems (Eom et al, 2012;Zhou et al, 2014). Most studies agree that the effect of climate change on global energy use is miniscule, as decreases in heating are counteracted by increases in cooling.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the economic impact of changes in energy demand for space heating and cooling systems under varying climatic scenarios

et al. 2016

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The building sector is highly sensitive to climate change, where energy is used for numerous purposes such as heating, cooling, cooking and lighting. Space heating and cooling account for a large proportion of overall energy use, and the associated energy demand is also affected by climate change. Here, we project the economic impact of changes in energy demand for space heating and cooling under multiple climatic conditions. We use an economic model coupled with an end-use technology model to explicitly represent the investment costs for air-conditioning technologies, which influence the macroeconomy. We conclude that the negative effects on the economy from increases in the use of space cooling are sufficiently large to neutralize the positive impacts from reductions in space heating usage under climate change, which results in significant economic loss. The economic loss under the highest emissions scenario (RCP8.5) would correspond to a −0.34% (−0.39% to −0.18%) change in global gross domestic product (GDP) in 2100 compared with GDP without any climate change, while the impact under the lowest emissions scenario (RCP2.6) would result in a −0.03% (−0.07% to −0.01%) change in global GDP in 2100. The economic losses are mainly generated by incremental technological costs and not by changes in energy demand itself. The amount of economic loss can vary substantially based on assumptions of technological costs, population and income. To reduce the negative impacts of climate change measures for reducing the costs of air conditioning will be an important consideration for the building sector in the future.

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“…Some authors even claim that the generation of typical year weather data is not very sensitive to the weighting of different weather variables [39]. Studies have shown that climate change has significant impacts on building energy use [40], [41], and thus, it needs to be incorporated in urban infrastructure planning [42]; because of the climate change taking place globally and its vital role in energy use, the record period for TMY selection should accordingly contain recent meteorological data and be reasonably long enough to reflect the climatic trend well [43]. Two sets of weather data files were formed based on different periods to assess their impact on the accuracy of building energy analyses [44].…”

Section: Introductionmentioning

confidence: 99%

Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China

et al. 2017

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Abstract:Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

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Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

Cited by 156 publications

References 23 publications

The integrated Earth system model version 1: formulation and functionality

The integrated Earth system model version 1: formulation and functionality

Quantifying the economic impact of changes in energy demand for space heating and cooling systems under varying climatic scenarios

Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China

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