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• The outdoor environment indexes are integrated by simulation and empirical method. • Quantitatively study the interaction between green space and water bodies. • The proper layout of landscape planning can reduce the building carbon emissions. The rapid urban construction has made urban residential buildings become the main source of greenhouse gas emissions. So far, the existing studies on the impact of urban micro-climate on building energy carbon emissions have shown that green space (GS) and water bodies (WB) play positive roles in regulating outdoor thermal environment and reducing building energy consumption. Accordingly, this paper quantitatively explores the influence of the interaction between GS and WB on reducing building carbon emissions. First, the building's micro-climate is simulated by Computational Fluid Dynamics (CFD) to obtain outdoor thermal environment indexes, which are used as inputting data to calculate carbon emissions by software HDY-SMAD. Then, we utilize Geographic Information System (GIS) and Remote Sensing (RS) techniques to explore the natural surroundings of buildings, such as GS and WB distribution within the administrative scope of Dujiangyan. Next, the linear regression method is applied to analyze the relationship between GS, WB, and residential building carbon emissions, in which the residential carbon emissions data is obtained by social survey. Finally, the simulation results are verified by empirical research method. The findings demonstrate that the GS and WB have area, accessibility and seasonal differences in regulating local thermal environment and reducing building carbon emissions, and the overall regulation ability of WB for micro-climate is more significant than that of GS. In addition, the ratio area between GS and WB has the most significant influence on reducing building carbon emissions when it is 3:1 in winter, but this optimal ratio is 1:2 in summer. These conclusions can provide benchmark information for landscape planning and building energy conservation in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • Archetype development, model components and potential applications for UBEM are discussed. • Stochastic and dynamic occupancy models are among the most desired improvements for UBEM. • UBEM could be suitable for high accuracy predictions of future climate change scenarios. • Integration of socio-economic data in UBEM is promising but not currently applied. • Assigning value year from renovation records is tempting but could entail several pitfalls. Due to rapid urbanisation and the significant contribution of cities to worldwide energy use and greenhouse gas emissions, urban energy system planning is growing more important. Urban building energy modelling (UBEM) draws increasing attention in the energy modelling field due to its inherent capacities for modelling entire cities or building stocks, and the potential of varying data inputs, approaches and applications. This review aims to identify best practices and improvements for UBEM applications by examining previous research, with a focus on the currently least established approaches. Different archetype development procedures are analysed for common problems, six main under-developed input approaches or parameters are identified, and applications for future scenario development are surveyed. By analysing previous studies in related fields, this paper provides an overview of gaps in the published research and possible additions to future UBEM projects that can help expanding the existing modelling procedures. Comprehensive human behaviour models with additional aspects beyond occupant presence are identified as a major point of interest. Further research on socio-economic parameters, such as household income and demographics, are also suggested to further improve modelling. This study also underlines the potential for utilising UBEM as a tool for evaluating future climate change scenarios. [ABSTRACT FROM AUTHOR]

China is currently experiencing rapid urbanization. The building sector plays an important role in China's energy conservation and emission reduction. An increasing amount of energy will be steadily consumed in the building sector as the urbanization process accelerates. China's government attaches great importance to building energy efficiency (BEE). How does the urbanization process affect building energy consumption (BEC)? How much energy can be saved in the building sector through implementation of energy polices? These questions are critical for government development strategies and planning. Thus, in this paper, an econometric model (co-integration technique) is developed to analyze how China's BEC is affected by macroeconomic variables in the context of urbanization, and also forecast the BEC and BEE potential until 2020 under different scenarios. The research result shows that occupants’ lifestyles, residents’ living standards, and energy price have significant influences on BEC. The building sector is likely to contribute approximately 20% to China's energy conservation through electricity pricing reform. [ABSTRACT FROM AUTHOR]