Among various elements of urban infrastructure, there is significant opportunity to improve existing buildings’ sustainability, considering that approximately 40% of the total primary energy consumption and 72% of electricity consumption in United States is consumed by the building sector. Many different efforts focus on reducing the energy consumption of residential buildings. Data-validated building energy modeling methods serve the role of supporting this effort, by enabling the identification of the potential savings associated with different potential retrofit strategies. However there are many uncertainties that can impact the accuracy of energy model results, one of which is the weather input data. Measured weather data inputs located at each building can help address this concern, however, weather station data collection for each building is also costly and typically not feasible. Some weather station data is already collected, however, these are generally located at airports rather than near buildings, and thus do not capture local, spatially-varying weather conditions which are documented to occur, particularly in urban areas. In this study we address the impact of spatial temperature differences on residential building energy use. An energy model was developed in EnergyPlus for a residential building located in Mueller neighborhood of Austin, TX, and was validated using actual hourly measured electricity consumption. Using the validated model, the impact of measured spatial temperature differences on building energy consumption were investigated using multiple weather stations located throughout the urban area with different urban fractions. The results indicate that energy consumption of a residential building in a city with a 10% higher urban fraction would increase by approximately 10%. This variation in energy consumption is likely due to the impact of UHI effects occurring in urban areas with high densities.
more »
« less
Simulating urban energy use under climate change scenarios and retrofit plans in coastal Texas
Rapid urbanization, climate change, and aging infrastructure pose significant challenges to achieving sustainability and resilience goals in urban building energy use. Although retrofitting offers a viable solution to mitigate building energy use, there has been limited analysis of its effects under various weather conditions associated with climate change in urban building energy use simulations. Moreover, certain parameters in energy simulations necessitate extensive auditing or survey work, which is often impractical. This research proposes a framework that integrates various datasets, including building footprints, Lidar data, property appraisals, and street view images, to conduct neighborhood-scale building energy use analysis using the Urban Modeling Interface (UMI), an Urban Building Energy Model (UBEM), in a coastal neighborhood in Galveston, Texas. Seven retrofit plans and three weather conditions are considered in the scenarios of building energy use. The results show that decreasing the U-value of building envelopes helps reduce energy use, while increasing the U-value leads to higher energy consumption in the Galveston neighborhood. This finding provides direction for coastal Texas cities, like Galveston, to update building standards and implement retrofit measures.
more » « less- Award ID(s):
- 2122054
- PAR ID:
- 10518626
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Urban Informatics
- Volume:
- 3
- Issue:
- 1
- ISSN:
- 2731-6963
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)In the United States, approximately 40% of the primary energy use and 72% of the electricity use belong to the building sector. This shows the significance of studying the potential for reducing the building energy consumption and buildings’ sustainability for ensuring a sustainable development. Therefore, many different efforts focus on reducing the energy consumption of residential buildings. Data-validated building energy modeling methods are among the studies for such an effort, particularly, by enabling the identification of the potential savings associated with different potential retrofit strategies. However, there are many uncertainties that can impact the accuracy of such energy model results, one of which is the weather input data. In this study, to investigate the impact of spatial temperature variation on building energy consumption, six weather stations in an urban area with various urban density were selected. A validated energy model was developed using energy audit data and high-frequency electricity consumption of a residential building in Austin, TX. The energy consumption of the modeled building was compared using the selected six weather datasets. The results show that energy use of a building in an urban area can be impacted by up to 12% due to differences in urban density. This indicates the importance of weather data in predicting energy consumption of the building. The methodology and results of this study can be used by planners and decision makers to reduce uncertainties in estimating the building energy use in urban scale.more » « less
-
more » « less
Abstract In the US, more than 80% of fatal cases of heat exposure are reported in urban areas. Notably, indoor exposure is implicated in nearly half of such cases, and lack of functioning air conditioning (AC) is the predominant cause of overheating. For residents with limited capacity to purchase, maintain, and operate an AC system, or during summertime power outages, the ability of buildings to maintain safe thermal conditions without mechanical cooling is the primary protective factor against heat. In this paper, we use whole-building energy simulations to compare indoor air temperature inside archetypical single-family residential buildings without AC at the start and middle of the century in eight US cities. We ran the models using hourly output from 10 year regional climate simulations that explicitly include heating from mid-century projections of urban development and climate change under a ‘business-as-usual’ emissions scenario. Moreover, to identify the impacts from evolving construction practices, we compare different versions of building energy standards. Our analysis shows that summertime overheat time may increase by up to 25% by the middle of century. Moreover, we find that, while newer building energy codes reduce thermal comfort under moderate outdoor weather, they perform better under extreme heat.
-
more » « less
Abstract Intense rainfall from tropical cyclones has the potential to induce coastal acidification, which will become more common and severe as climate change continues. We collected carbonate chemistry samples from Galveston Bay, Texas before and after Hurricane Harvey in 2017 and 2018. Here, we show ecosystem level acidification and calcium carbonate undersaturation in Galveston Bay following the storm. This acidification event, driven by extreme rainfall from Harvey, persisted for over 3 weeks because of prolonged flood mitigation reservoir releases that continued for over a month after the storm. In addition, the large volume of stormwater led to high oyster mortality rates in Galveston Bay and acidification may have impeded recovery of these vital reefs. It is also likely that undersaturation has occurred outside of our study, unrecorded, following other high-rainfall storms. The projected increase in tropical cyclone rainfall under climate change may thus represent a significant threat to coastal calcifying ecosystems.
-
Chronis, A. (Ed.)Traditional building energy simulation tools often assess performance as a function of the unique climate, physical characteristics, and operational parameters that define specific buildings and communities, planned or existing. This paper presents the results of a sensitivity analysis on the input parameters(relating to both the building and climate) that affect the annual energy consumption loads of an existing residential neighborhood in the U.S. Midwest over the anticipated service life of its buildings using the Urban Modeling Interface (umi). Accordingly, first, the effect of multiple building construction characteristic packages and inclusion of outdoor vegetation, are investigated under typical meteorological climate conditions. Afterwards, since typical climate conditions may not adequately describe the potential extreme conditions that will be encountered over the entire service life of these buildings, alternative weather datasets were also utilized in the sensitivity analysis. The study’s findings suggest that cooling loads are expected to increase dramatically over the next five decades, both due to changes in the climate and the more wide-spread use of air-conditioning units. Since the results showed that trees can effectively reduce cooling loads by up to 7%, it is recommended that urban vegetation should be considered as an effective adaptation measure for facing the growing cooling demands.more » « less
