Building energy use in China: Ceiling and scenario

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

Buildings are at the locus of three trends driving China's increased energy use and emissions: urbanization, growing personal consumption, and surging heavy industrial production. Migration to cities and urban growth create demand for new building construction. Higher levels of per-capita income and consumption drive building operational energy use with demand for higher intensity lighting, thermal comfort, and plug-load power. Demand for new buildings, infrastructure, and electricity requires heavy industrial production. In order to quantify the implications of China's ongoing urbanization, rising personal consumption, and booming heavy industrial sector, this study presents a lifecycle assessment (LCA) of the energy use and carbon emissions related to residential and commercial buildings. The purpose of the LCA model is to quantify the impact of a given building and identify policy linkages to mitigate energy demand and emissions growth related to China's new building construction. As efficiency has become a higher priority with growing energy demand, policy and academic attention to buildings has focused primarily on operational energy use. Existing studies estimate that building operational energy consumption accounts for approximately 25% of total primary energy use in China. However, buildings also require energy for mining, extracting, processing, manufacturing, and transporting materials, as well as energy for construction, maintenance, and decommissioning. Building and supporting infrastructure construction is a major driver of industry consumption--in 2008 industry accounted for 72% of total Chinese energy use. The magnitude of new building construction is large in China--in 2007, for example, total built floor area reached 58 billion square meters. During the construction boom in 2007 and 2008, more than two billion m{sup 2} of building space were added annually; China's recent construction is estimated to account for half of global construction. Lawrence Berkeley National Laboratory (LBNL) developed an integrated LCA model to capture the energy and emissions implications of all aspects of new buildings from material mining through construction, operations, and decommissioning. Over the following four sections, this report describes related existing research, the LBNL building LCA model structure and results, policy linkages of this lifecycle assessment, and conclusions and recommendations for follow-on work. The LBNL model is a first-order approach to gathering local data and applying lifecycle assessment to buildings in the Beijing area--it represents one effort among a range of established, predominantly American and European, LCA models. This report identifies the benefits, limitations, and policy applications of lifecycle assessment modeling for quantifying the energy and emissions impacts of specific residential and commercial buildings.

Analysis of Electrical Energy Savings From Daylighting Through Skylights

Enhancing energy efficiency while preserving sufficient daylight represents a significant challenge for residential buildings situated in hot, arid, and semi-arid climates, where cooling requirements constitute the primary component of annual energy consumption. This research introduces a parametric, multi-objective genetic algorithm (GA) workflow designed to investigate the combined impacts of window-to-wall ratio (WWR) and horizontal shading devices (HSDs) on annual energy use intensity (EUI) and useful daylight illuminance (UDI, 100–2000 lx) within a multi-story residential villa located in Al-Baha, Saudi Arabia. A baseline model was constructed in Rhino/Grasshopper and simulated utilizing Climate Studio, while Octopus was employed to produce Pareto-optimal solutions through SPEA-II and HypE across multiple generations. The optimisation targeted locations lacking daylight, with performance evaluations carried out at the home level to include extensive building trade-offs. The Pareto analysis demonstrates that the integration of controlled apertures with external shade can substantially enhance daylight access in previously poorly lit sections, with minimal alterations to the total building Energy Use Intensity (EUI). For the chosen compromise solution, the annual EUI decreases by approximately 1% compared to the baseline; however, the whole-building UDI declines, indicating that enhancing daylight in specific zones may diminish daylight availability in other areas if minimum daylight constraints are not enforced. The study illustrates a reproducible early-stage workflow and emphasizes the importance of establishing objectives and constraints that preserve daylight in habitable spaces while balancing energy efficiency and daylight performance in dwellings located in desiccated climates.

Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm

Herschel Finds Less Dark Matter but More Stars

China’s energy consumption in construction and building sectors: An outlook to 2100

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Improved energy performance evaluating and ranking approach for office buildings using Simple-normalization, Entropy-based TOPSIS and K-means method

Propagating downscaled future weather file uncertainties into building energy use

Urban microclimate and its impact on building performance: A case study of San Francisco

Sustainable High-rises

Structural, geographic, and social factors in urban building energy use: Analysis of aggregated account-level consumption data in a megacity

The effect of neighbourhood-level urban form on residential building energy use: A GIS-based model using building energy benchmarking data in Seattle

Energy use is an indicator of economic growth. However, high energy intensity has two main disadvantages. First, low energy efficiency increases a country’s dependence on other countries, especially when the country lacks energy sources. Second, if the country’s energy needs are met using traditional fossil fuels, this increases its CO2 emissions and reduces its air quality. Improving energy efficiency and reducing energy intensity are essential to reach the sustainability targets. This paper investigates the determinants of energy use in Turkiye for the period 1991–2019 by taking a dual approach. First, utilizing the Tapio decoupling factor, the decoupling factor analysis is not only being done for total energy use and real GDP, but also for industrial energy use and industrial income. Second, the factors determining the country’s total energy use are also examined, followed by an investigation of the indicators of energy use in the industry sector, which is highly energy intensive. For the industrial sector, two different decomposition analyses are performed and results are compared. The refined Laspeyres index method is adopted, and for each analysis, three main factors are considered. The empirical findings demonstrate that the income effect and population effect increased Turkiye’s total energy use, whereas the energy intensity effect decreased it. The first decomposition analysis for the industrial energy use reveals partly contrasting results with the previously published articles. For the industry sector, the second analysis show that productivity and employment increased Turkiye’s sectoral energy use; however, the sector’s energy intensity reduced it. Turkiye achieved some success in terms of reducing energy intensity at the sectoral and aggregate levels; however, as the findings of the present study demonstrate, further efforts are needed to lessen the country’s energy dependence and also to achieve future environmental sustainability targets. Trends relating to the determining factors in total and sectoral energy use are also compared in this paper, and some policy implications are presented.