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Building energy efficiency standards (BEES) are believed to be one of the most effective policies to reduce building energy consumption, especially in the case of the rapid urbanization content in China. However, there is little evidence backed up by measured data to validate the actual effectiveness of BEES in China. Using survey data collected from 1128 households in Chongqing China, this study applied the propensity scores matching method to estimate the effect of two BEES levels: the 50%-BEES (low level) and the 65%-BEES (high level). Results show that buildings built with 65%-BEES, on average, can reduce cooling and heating electricity use intensity (kWh/m2/a) by 41%, compared to buildings in the absence of the BEES. Meanwhile, the adoption of 50%-BEES can reduce cooling and heating electricity use intensity (kWh/m2/a) by 38%. However, energy savings are not significant if comparing buildings with 65%-BEES and 50%-BEES. The results indicate that there exists a performance gap between calculated design performance savings and actual operation energy savings. These empirical findings provide policymakers with valuable feedback on buildings’ actual performance. The findings suggest that it is necessary to incorporate outcome-based compliance pathways into the current BEES system. Lastly, a data-driven building policy evaluation mechanism should be developed in China. Energy consumption databases should be developed to support policies such as building energy codes and standards’ development and performance evaluation.

Reliable and objective data regarding building stock is essential for predicting and analyzing energy demand and carbon emission. However, China's building stock data is lacking. This study proposes a set of China building floor space estimation method (CBFSM) based on the improved building stock turnover model. Then it measures China's building stocks by vintage and type from 2000 to 2015, as well as building energy intensity (national level and provincial level) and energy-efficient buildings. Results showed that total building stocks increased significantly, rising from 35.2 billion m2 in 2000 to 63.6 billion m2 in 2015, with the average growth rate 4.0%. The deviations were well below 10% by comparing with China Population Census, which validated the reliability of CBFSM and the results. As for energy intensity, urban dwellings and rural dwellings showed relatively stable and increasing trend respectively. The commercial building energy intensity saw a downward trend during “12th Five Year Plan” period. This indicated the effectiveness of building energy efficiency work for commercial buildings since 2005.38.6 billion m2 residential dwellings and 5.7 billion m2 commercial buildings still need to be retrofitted in future. CBFSM can overcome shortages in previous studies. It can also provide Chinese government with technical support and data evidence to promote the building energy efficiency work.

This study uses the total-factor energy productivity change index (TFEPCH) to investigate the changes in energy productivity of construction industry for 30 provincial regions in China from 2006 to 2015, adopting the improved Luenberger productivity index combined with the directional distance function. In addition to traditional economic output indicator, this study introduces building floor space under construction as a physical output indicator for energy productivity evaluation. The TFEPCH was decomposed into energy technical efficiency change and energy technical progress shift. Results indicate that, first, energy productivity of China’s construction industry decreased by 7.1% annually during 2006–2015. Energy technical regress, rather than energy technical efficiency, contributed most to the overall decline in energy productivity of China’s construction industry. Second, energy productivity in the central region of China decreased dramatically, by a cumulative sum of approximately 77.1%, since 2006, while energy productivity in the eastern and western regions decreased by over 54.3 and 65.3%, respectively. Only two of the 30 provinces considered—Hebei and Shandong—improved their energy productivity during 2006–2015. The findings presented here provide a basis for decision-making and references for administrative departments to set differentiated energy efficiency goals and develop relevant measures. Additionally, the findings are highly significant for energy and resource allocation of Chinese construction industry in different regions.

China's energy consumption in the building sector (BEC) is not counted as a separate type of energy consumption, but divided and mixed in other sectors in China's statistical system. This led to the lack of historical data on China's BEC. Moreover, previous researches' shortages such as unsystematic research on BEC, various estimation methods with complex calculation process, and difficulties in data acquisition resulted in “heterogeneous” of current BEC in China. Aiming to these deficiencies, this study proposes a set of China building energy consumption calculation method (CBECM) by splitting out the building related energy consumption mixed in other sectors in the composition of China Statistical Yearbook-Energy Balance Sheet. Then, China's BEC from 2000 to 2014 are estimated using CBECM and compared with other studies. Results show that, from 2000 to 2014, China's BEC increased 1.7 times, rising from 301 to 814 million tons of standard coal consumed, with the BEC percentage of total energy consumption stayed relatively stable between 17.7% and 20.3%. By comparison, we find that our results are reliable and the CBECM has the following advantages over other methods: data source is authoritative, calculation process is concise, and it is easy to obtain time series data on BEC etc. The CBECM is particularly suitable for the provincial government to calculate the local BEC, even in the circumstance with statistical yearbook available only.

The building sector, which accounts for over 20% of China's total energy-related carbon emissions, has great potential to reduce emissions and is critical to achieving China's emissions peak and carbon neutrality targets. However, the lack of data on operational carbon emissions and end-use carbon emissions in the building sector at the city level has become a major barrier to the development of building energy conservation policies and carbon peaking action plans. This study uses a combination of "top-down" and "bottom-up" methods to account for the operational carbon emissions of buildings in 321 cities in China from 2015 to 2020. The energy consumption in buildings is further broken down into six end uses: central heating, distributed heating, cooking and water heating (C&W), lighting, cooling, appliances and others (A&O). The dataset can serve as a reference to support city-level policies on peak building emissions and is of great value for the improvement of the carbon emissions statistical accounting system. [ABSTRACT FROM AUTHOR]

While national policies play a crucial role in shaping local development, effective governance is essential for rural revitalization. However, the successful implementation and impact of these policies in rural areas can vary due to unique local circumstances, limited information, and a lack of sophisticated decision making tools. Closing the divide between overarching national policies and practical rural development is an immediate necessity. This study begins by creating a comprehensive five-dimensional evaluation system encompassing industrial economy, public utilities, transportation and logistics, policy and institutions, and resources and the environment. It then summarizes four typical development modes—the suburban fusion mode, the characteristic industry-oriented mode, the humanistic and ecological resource-based mode, and the balanced development mode with less distinct characteristics—through an analysis of the Chinese government's policy framework for rural construction. Subsequently, it introduces a decision support system for rural construction and development founded on multi-source heterogeneous big data and integrated algorithms. This system was tested using 782 townships as samples for classification, evaluation, and decision support. The results leverages insights into current rural development trends to efficiently align with national policies and provide customized implementation recommendations tailored to local resource characteristics. This contributes to the practical execution of rural revitalization strategies and the advancement of scientific rural decision making. [ABSTRACT FROM AUTHOR]

With in-depth efforts in the national strategy of innovation-driven development, the demand for talent in cities is burgeoning. Cities in China have released a large number of preferential policies to attract talent as these cities look to gain an edge in increasing talent competition. This study empirically studied the effect of talent competition on urban innovation using a panel data set of 298 prefectural-level cities in China from 2010 to 2019 based on the difference-in-difference model and an event study method. The results show that there are heterogeneous effects of talent competitions on urban innovation, which may widen the gap between urban innovation in different cities. The effect of talent competition in different cities showed a significant positive correlation with the level of urban development, and there is a "head effect" of talent competition on urban innovation. Moreover, the results of the mechanism analysis indicate that the effect of talent competition on urban innovation is mainly through talent flow. These findings can help policymakers formulate scientific and reasonable talent policies to promote the strategy of innovation-driven development. [ABSTRACT FROM AUTHOR]

Social progress and economic development has resulted in the need to focus on the impacts of building microenvironment on the energy consumption in office buildings. The concept of a building's microenvironment was introduced to understand the local microclimate around a building that is formed by the surrounding urban green spaces, the distribution of roads, and building proximity. For this research, we adopted a regression analysis to quantify the impacts of building microenvironment on energy consumption in office buildings. Taking the government office buildings of Guangdong Province as an example, we measured the building microenvironment through the urban green space density, road density, and number of points of interest (POI) around the buildings. The results showed that when the green space density increased by one unit, the energy consumption in government office buildings was reduced by 0.277%. Moreover, an increase of 1% in road density and in the number of POI increased the energy consumption in government office buildings by 0.288% and 0.048%, respectively. Furthermore, we discussed the heterogeneous impacts of building microenvironment on the energy consumption in government office buildings at varying scale levels. Green space and road density had less impact on the energy consumption in larger buildings, whereas the number of POI had no significant impact on small-scale buildings but did have a significant impact on large-scale buildings. There were also some limitations in the study. The data were limited to government office buildings, and did not include panel data, as well as it lacked building characteristics such as orientation, floor height, and building materials. In addition, it was impossible to evaluate the impacts of meteorological factors such as wind speed and thermal radiation on energy consumption in buildings. Nonetheless, our study demonstrates that energy-aware urban planning and design have the potential to unlock energy efficiency for cities worldwide. [ABSTRACT FROM AUTHOR]

With increasing urbanisation, urban household electricity consumption (UHEC) has become the most dynamic aspect of China's energy growth. However, existing studies suffer from outdated data, a small scope, and a lack of research into new influencing factors. There are significant challenges to the promotion of urban household energy-efficiency strategies, which may arise from the intervention of several new inter-provincial differences and other influencing factors. To better understand the variability, volatility characteristics, and influencing factors of change in provincial UHEC, this study analyses and assesses the influencing factors based on an extended STIRPAT model of Chinese provincial panel data from 2005 to 2020. The findings revealed rapid increases in provincial urban household electricity consumption and significant provincial differences in UHEC in China stemming from variation in economic level and energy use. Urbanisation, income, the size of the older population, and area per capita contributed to household electricity consumption. Conversely, household size, heating days (HDD), and air conditioning dampened household electricity consumption. However, television and cooling days (CDD) did not accurately explain the variation in household electricity use in this study. Finally, this study suggests targeted policy recommendations that could promote the implementation of energy-efficiency strategies in Chinese urban households. [ABSTRACT FROM AUTHOR]

City size expansion in China creates substantial economic circulation, which impacts CO2 emissions. Since CO2 production primarily comes from human activities, CO2 emissions are mainly in cities. To achieve China's carbon neutrality and provide specific implementation guidance for future carbon-reduction policies, it is worth assessing China's pressure on carbon reduction in the urban aspect. Highly developed social productivity and a market economy lead to a dramatic increase in the interconnection between cities, and the spatial distribution of CO2 emissions emerges in a spatial association. Therefore, it is of great significance to investigate the interaction of CO2 emissions with spatial effects. Taking the Yangtze River Delta urban agglomeration (YRDUA) as the research target area, this paper utilizes city-size indices to construct spatial-association networks of CO2 emissions for the first time. It employs social network analysis to explore the structures of whole networks, clusters, and city nodes. The main results show that: (1) the spatial associations of CO2 emissions in the YRDUA's cities have become tighter over time. (2) The networks of CO2 emissions in the YRDUA's cities have noticeable spatial-spillover effects, and the interaction of CO2 emissions between cities is dominant. (3) Nanjing is the paramount "bridge" node in the networks. (4) Nanjing, Hangzhou, Wuxi, Shanghai, Changzhou, Suzhou, Nantong, and Hefei will be the decisive cities for efficient CO2 emission control in the future. Overall, this paper reveals the role of carbon reduction in the YRDUA's cities and proposes suggestions for establishing a transboundary energy-saving mechanism to improve the efficiency of energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

This paper attempts to accurately evaluate the contribution of construction dust to China's PM2.5 emissions in order to increase environmental authorities' efficiency at managing emissions in urban environments. The study was conducted in the main urban area of Chongqing. Three typical construction sites were designated as the study area, where PM2.5 emission concentration data were collected through field investigation and processed by an AERMOD model. PM2.5 emission intensity and annual average PM2.5 emissions from construction dust in the study area were also ascertained. The results showed that the PM2.5 emission intensity and annual average PM2.5 emissions from construction dust in the study area were 0.0059 kg/m² month and 6220.5 t, respectively. The PM2.5 emission concentration of construction dust showed a negative correlation with real-time wind speed. This paper's conclusions can serve as a reference for related departments that make decisions on PM2.5 emission management. [ABSTRACT FROM AUTHOR]

This paper puts the Twelfth Five-year (2011-2015) Plan as baseline scenario, and sets up optimism scenario and pessimistic scenario. Under the above scenarios, the paper explores the potential of energy conservation and emission reduction of new green buildings and non-green buildings in Chongqing. The results show great potential for energy conservation of new buildings in Chongqing. In optimism scenario, with reasonable policy and market intensify, CO2 reduced by energy saving will be equal to that produced by 47% new population in urbanization in Chongqing. New green residential building is the key to promote building energy conservation. As the improvement of energy efficiency standards, new non-green residential buildings should be an important issue in long term. [ABSTRACT FROM AUTHOR]

Based on current situation and relative plan of energy efficiency of existing buildings, the authors aim to explore the potential of energy conservation and emission reduction of existing buildings retrofit in Chongqing, in medium and long term (2016-2035). Scenario analysis is used to predict energy conservation of existing residential buildings and commercial buildings from 2016 to 2035. The authors create three potential future policy and market scenarios, which include baseline scenario as the Twelfth Five-year (2011-2015) plan, optimism scenario and pessimistic scenario. The results showed that there exists great potential for energy conservation of existing buildings in Chongqing. In the Sixth Five-year (2031-2035), reasonable policy and market intensify will cause energy conservation potential to rise up to 117,100 tons of SCE, and reduce 353,800 tons of CO2. Existing commercial buildings are the key to promote building energy conservation, while existing residential buildings with increasing energy intensity should be an important issue in long term. [ABSTRACT FROM AUTHOR]