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Chen, L., 2020. The green building design of subtropical ocean climate adaptability. In: Li, L. and Huang, X. (eds.), Sustainable Development in Coastal Regions: A Perspective of Environment, Economy, and Technology. Journal of Coastal Research, Special Issue No. 112, pp. 50-54. Coconut Creek (Florida), ISSN 0749-0208. With the increasing global warming, climate change has affected human survival and development, which has become an important problem facing the world. Therefore, green building has become the most important development trend, which is an important measure of the corresponding sustainable development strategy. Through green building, China can implement energy conservation and emission reduction strategy, which will better deal with global warming. Green building needs mult-disciplinary technology combination, which needs to set the design goal according to the local environment, form and function. By strengthening the natural regulation of climate, green buildings can better apply the environmental climate change, which will meet the requirements of energy conservation and health. This paper mainly studies the adaptability of the subtropical marine climate green building, which can better design the building in line with energy conservation, health and function. Taking Guangzhou as an example, this paper analyzes the adaptive design of green building through examples. [ABSTRACT FROM AUTHOR]

Load matching is an inevitable problem that restricts the development of photovoltaic (PV) system used in buildings. The objective of this paper is to solve this problem by conducting a load matching assessment and optimization of PV system in different climate zones of China. The influences of the tilt angle, orientation, PV plot ratio and building height on the achievement of zero energy buildings (ZEBs) were evaluated. The PV potentials of roofs and facades were analyzed and optimized based on self-sufficiency and self-consumption. Net load variance and the maximum electricity import were employed as indices to evaluate the performance of PV systems in different climate zones of China. The results of the load matching assessment show that electricity generations from roof PV systems in low-rise buildings can meet most of the energy demand (at least 70%) in all climate zones of China. East and west facades of mid-rise buildings have an advantage over south façades in Kunming and Guangzhou in terms of load matching. It is necessary to combine roofs, south, east and west facades to meet the ZEBs requirement of for high-rise building. When the heating/cooling demand is dominant, the tilt angle should be higher/lower than the latitude of the specific location. This research will be helpful in designing building PV systems in different climate zones of China. Load matching analysis is helpful in designing building PV system in different climate zones of China. The results show that east and west facades of mid-rise buildings have an advantage over south façade in Kunming and Guangzhou. It is necessary to combine roof, south, east and west facades to meet the requirement of ZEBs for high-rise building. Image 1 • Load matching with PV system were analyzed for zero energy buildings. • PV potential were investigated based on self-sufficiency and self-consumption. • The optimal combinations of PV system were obtained in different climate zones. • East and west facades have advantages over south façade in Kunming and Guangzhou. [ABSTRACT FROM AUTHOR]

With the acceleration of global urbanization and climate change, dengue fever is spreading worldwide. Different levels of dengue fever have also occurred in China, especially in southern China, causing enormous economic losses. Unfortunately, there is no effective treatment for dengue, and the most popular dengue vaccine does not exhibit good curative effects. Therefore, we developed a Generalized Additive Mixed Model (GAMM) that gathered climate factors (mean temperature, relative humidity and precipitation) and Baidu search data during 2011–2015 in Guangzhou city to improve the accuracy of dengue fever prediction. Firstly, the time series dengue fever data were decomposed into seasonal, trend and remainder components by the seasonal-trend decomposition procedure based on loess (STL). Secondly, the time lag of variables was determined in cross-correlation analysis and the order of autocorrelation was estimated using autocorrelation (ACF) and partial autocorrelation functions (PACF). Finally, the GAMM was built and evaluated by comparing it with Generalized Additive Mode (GAM). Experimental results indicated that the GAMM (R2: 0.95 and RMSE: 34.1) has a superior prediction capability than GAM (R2: 0.86 and RMSE: 121.9). The study could help the government agencies and hospitals respond early to dengue fever outbreak. [ABSTRACT FROM AUTHOR]