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The increased demand for improving indoor thermal environment in the hot summer and cold winter climate zone (HSCW) in the Yangtze River region in China poses enormous challenges in terms of energy policy and design solutions for this unique region. A comprehensive understanding of people's habits and behaviors involving winter heating is imperative for decision making for urban heating infrastructure investment strategies that significantly impact on the decarbonization of heating. However, there has been little knowledge gained from large-scale studies in this region. The aim of this study is to develop a rigorous survey method in order to obtain reliable data for analysis. Five municipal/capital cities across the upper, middle and downstream Yangtze River are surveyed based on 30 randomly generated locations in each city. A total of 8,471 valuable samples were obtained in the survey conducted in the winter from November 2017 to March 2018. It is revealed that air conditioning/air source heat pumps are the predominant systems, accounting for 63% and 58% for bedroom and living room heating respectively.The use patterns of heating are diverse featuring 'part-time-part-space' systems in accordance with the occupancy patterns. There is significant evidence of the habit of opening a window to provide a gap for fresh air irrespective of whether the heating is in use. Two-step cluster analysis is employed to subdivide occupants' heating-related behaviors into three clusters to characterize households. This study fills the knowledge gap of winter-heating-related behaviors. The research outcomes will benefit building energy simulations for energy prediction and help policy makers make decisions on providing strategic guidance in terms of winter heating solutions in this region.

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Deep resource exploitation is imperative, but it is facing with more complicated mining environment and more dangerous mining disturbances to induce the potential catastrophe process. Solid backfill technology, which can control the strata movement and prevent potential hazards, has been used as the primary method in deep mining for surface subsidence control and ecosystem protection. In this study, taking backfill mining area no. 930 in the Tangkou coal mine as background, the probability integral model was adopted to predict the surface subsidence at different mining depths and filling ratios. The filling ratio was designed for deep mining based on the regression analysis of the predicted surface subsidence results. The study shows that the backfilling ratio at the Tangkou deep coal mining area should be controlled at a level greater than 82.5%, and the mining damage to the surface under this condition was analyzed. Furthermore, control strategies for deep backfill mining are proposed in which the backfill density can be enhanced by optimizing the tamping machine, material composition, and tamping process. Finally, the measurement of the backfill mass and surface subsidence showed that the actual filling ratio was controlled at 82.57%, which ensures adequate protection of the surface buildings during the mining process.