Interconnections among energy consumption, carbon emissions, and economic impacts for sustainable buildings

Climate change caused by increased carbon emissions seriously jeopardizes the sustainable development of human beings. Accounting for 29% of global energy consumption and 28% of global carbon emissions, buildings are critical for the reduction of energy and emissions with great economic impacts. At present, carbon emission reduction of buildings is carried out by reducing energy consumption since carbon emissions are difficult to measure. In addition, reducing building energy consumption can also bring economic benefits by lowering the associated energy cost. However, reducing the same amount of energy consumption may result in different amounts of carbon emission reduction at different locations and different times based on the availability of clean energy generation. In addition, the potential participation of the carbon trading schemes may change the economic calculation of building retrofit. To promote the development of sustainable buildings, it is essential to reveal the connections among building energy consumption, carbon emissions, and related economic impacts. To reveal these connections, we identified three challenges concerning building energy rating, carbon emission reduction, and economic evaluation. The first challenge is that there are discrepancies in the current building energy rating systems. Energy rating is widely adopted in practice to reduce building energy consumption on a large scale. However, a building may not receive the same energy rating results from when it is designed to when it is operated. These inconsistent rating results weaken the credibility of building energy rating systems. The second challenge comes out of the uncertainty of the carbon emission reduction potential of buildings in the era of increasing clean energy. Building retrofits can lead to emission reduction for the next few decades while the composition of carbon emission in electricity generation is changing dynamically due to the increasing capacity and fluctuating availability of clean energy. Without an accurate long-term prediction of carbon emission reduction of various building retrofit measures, one may miss the most effective retrofit measures. Lastly, there is a lack of economic incentives for building owners to reduce carbon emissions. It is necessary to design a pricing scheme including both energy and carbon to incentivize building owners to reduce energy consumption and carbon emissions. To address certain aspects of the three major challenges identified, we propose the following three research tasks: First, this dissertation developed individualized empirical baselines for existing buildings in the operation stage that are consistent with their modeled baselines in the design stage. An engineer can obtain the individualized empirical baseline for a building by following three simple steps using the open-source tool we provided. Second, this dissertation developed a novel method to predict the carbon emission reduction potential of building retrofits by using dynamically changing electricity emission factors under different clean energy adoption scenarios. We found that using the constant emission factor causes estimation bias for locations where clean energy is dominated. What’s more, the most energy-efficient measure may not be the most efficient emission measure, especially in locations with high clean energy penetration. At last, this dissertation proposed a systematic economic evaluation method to investigate the economic impacts of carbon emission trading schemes on building retrofits. The reduction of the payback period and the increase of the return on investment are adopted as evaluation metrics. The economic evaluation method can be used by building owners to estimate their additional economic benefits when the U. S. building sector is incorporated into the carbon emission trading scheme. This can accelerate the reduction of carbon emissions from U. S. buildings. In the future, the open-source tool of obtaining individualized empirical baselines can be integrated into existing building energy r ting practices by developing an interactive website. The carbon emission reduction potential of the building sector in the U. S. can be predicted in the future by applying the workflow proposed in this dissertation to other building types and regions. An open-source tool of optimal building retrofit strategy including both energy and carbon benefits is worth to be developed.