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Abstract In this study, we investigate the driving forces behind the changes in residential energy consumption (REC) in China’s urban and rural areas over the 2001–2012 period. Based on the logarithmic mean Divisia index method, the REC changes are decomposed into seven driving forces, which are climate change, energy price, energy expenditure mix, energy cost share (in total expenditure), expenditure share (in income), per capita income and population effects. According to the results, climate effect due to increasing days with abnormal temperature, energy cost share effect characterized by more expenditure to be paid for energy use, income effect describing constant income growth in the residential sector definitely increase REC in both urban and rural areas. In contrast, energy prices and energy expenditure mix effects negatively contribute to the REC increase, respectively because of the increase in energy prices and the transition from the low-priced energy to high-priced energy. Expenditure share and population effects play opposite roles in urban and rural areas, and the reasons and implications are analysed in depth.

China has achieved impressive rapid economic growth over the past 30 years but accompanied by significant extreme weather events and environmental changes caused by global change and overfast urbanization. Using the absolute hazards index (AHI), we assessed the spatial distribution patterns and related health effects of 4 major extreme natural disasters, including drought, floods (landslides, mudslides), hails, and typhoons from 2000 to 2011 at the provincial level in China. The results showed that (1) central and south China were the most affected by the 4 natural disasters, and north China suffered less; (2) the provinces with higher AHI suffered most from total death, missing people, collapse, and emergently relocated population; (3) the present health emergency response system to disasters in China mainly lacks a multidisciplinary approach. In the concluding section of this article, suggestions on preparedness and rapid response to extreme health events from environmental changes are proposed.

The acceptability, energy consumption, and environmental benefits of electric vehicles are highly dependent on travel patterns. With increasing ride-hailing popularity in mega-cities, urban mobility patterns are greatly changing; therefore, an investigation of the extent to which electric vehicles would satisfy the needs of ride-hailing drivers becomes important to support sustainable urban growth. A first step in this direction is reported here. GPS-trajectories of 144,867 drivers over 104 million km in Beijing were used to quantify the potential acceptability, energy consumption, and costs of ride-hailing electric vehicle fleets. Average daily travel distance and travel time for ride-hailing drivers was determined to be 129.4 km and 5.7 h; these values are substantially larger than those for household drivers (40.0 km and 1.5 h). Assuming slow level-1 (1.8 KW) or moderate level-2 (7.2 KW) charging is available at all home parking locations, battery electric vehicles with 200 km all electric range (BEV200) could be used by up to 47% or 78% of ride-hailing drivers and electrify up to 20% or 55% of total distance driven by the ride-hailing fleet. With level-2 charging available at home, work, and public parking, the acceptance ceiling increases to up to 91% of drivers and 80% of distance. Our study suggests that long range BEVs and widespread level-2 charging infrastructure are needed for large-scale electrification of ride-hailing mobility in Beijing. The marginal benefits of increased all electric range, effects on charging infrastructure distribution, and payback times are also presented and discussed. Given the observed heterogeneity of ride-hailing vehicle travel, our study outlines the importance of individual-level analysis to understand the electrification potential and future benefits of electric vehicles in the era of shared smart transportation.

Better prediction of turbulent airflow around urban trees is necessary because it impacts urban pollutant dispersion, outdoor thermal comfort, energy efficiency, pedestrian-level comfort and urban heat island mitigation. A major challenge is how to obtain an accurate numerical model of the turbulent flow field around trees and an improved parameterization of the turbulent momentum deficit using the drag coefficient (Cd). To address this challenge, we use wind tunnel tests and real trees to measure Cd for four common subtropical tree species: Ficus microcarpa, Mangifera indica, Michelia alba and Bauhinia blakeana. The results show that the Cd of the four trees ranges from 0.523 to 0.932, and that the negative relationship between Cd and wind speed (U) can be expressed by the exponential formula Cd=a*U−b. A three-dimensional model of wind modification by trees is proposed, and its accuracy is verified with wind tunnel measurements. With precise Cd and model, the predictability of the influence of trees on urban wind in subtropical areas is enhanced (root mean square error RMSE ranging from 2.89 m/s to 0.45 m/s). Future development and applications of the numerical model will help provide useful guidelines for urban landscape management and sustainable urban planning in terms of urban ventilation.

Various theories and approaches have been introduced in the debate on how to address sustainable consumption. In this study, we first discuss different theoretical perspectives on sustainable consumption, particularly developed in the fields of economics, social psychology and environmental sociology. We argue that neither an ‘individualist’ nor a system- or structural perspective alone is sufficient for understanding and analysing the transition towards sustainable consumption. Therefore, we propose to apply the Social Practices Approach (SPA) that combines both human agency and social structures to understand sustainable consumption issues. Following the SPA framework, we review and summarize research on sustainable consumption in China in particular on three consumption fields: food, housing energy and mobility. It is found that introducing more efficient production technology is commonly taken as the focal point in these sectors when sustainable consumption was introduced to China. Despite a rising interest in consumers' perceptions of products' sustainability in recent years, research has rarely paid any attention to consumers' behavioural change or to the transition dynamics towards sustainable consumption. In general, ‘individualist’ perspectives have largely dominated Chinese sustainable consumption research. This paper proposes to move attention to a better understanding of Chinese consumption issues by emphasizing the link between the provision of sustainable products and the diverse sustainable consumption practices. Also, images of food, energy, mobility and other consumption products that are undergoing transitions need to be considered in future research as these have consequences for socio-technical changes, material infrastructures and for ‘lifestyle’ innovations.

Livestock production in peri-urban areas constitutes an important sub-sector of the agricultural production system in China, and contributes to environmental degradation and local air borne pollution contributing to smog. As a result, local policies are being implemented to safeguard the environment. However, there has been little attempt to quantify the impact of environmental policies on livestock production structure, spatial distribution and their related greenhouse gases (GHGs) and ammonia (NH3) emissions. Here, we calculated the inventories of GHGs and NH3 emissions for 2010 and 2014 for peri-urban livestock production in Beijing, using reliable spatially explicit data, which was collected from 1748 industrial farms in 2010 and 2351 industrial farms in 2014, including pig, dairy, beef cattle, poultry and sheep farms. Our estimates indicated that total industrial livestock production increased by 17% between 2010 and 2014, even under the more strict environmental protection polices, with farm size decreasing by between 7% and 47%. Up to 50% of the industrial livestock farms have remained in operation, with the rest closing down or being moved to other regions. Following this trend, total GHGs emission decreased from 5.0 to 4.5 Tg CO2-eq between 2010 and 2014. Most of the GHGs emission reduction was due to the lowering of energy related carbon dioxide (CO2) emission in 2014. Total NH3 emission decreased from 102 to 96 Gg between 2010 and 2014, mainly due to more stringent environmental regulations for new and extended farms (increased in farm size), e.g. Discharge standard for pollutants for livestock and poultry breeding. Our study identified that GHGs and NH3 emission hotspots were concentrated in suburban areas (around the city centre and with less agricultural resource and population density) in 2010. However, between 2010 and 2014 these hotspots moved to the exurban plain and mountain area following the closure or sub-division of intensive farms in suburban regions and construction of new and small farms in exurban areas (around the suburban and with more agricultural resource and lower population density). Scenario analysis suggests that total GHGs emission can be reduced by up to 1.0 Tg CO2-eq (23% of total livestock sector emissions) in Beijing, using a combination of modifications of farm type, livestock diet and manure management. The integrated scenario can reduce CH4, N2O and NH3 emissions by 27%, 9% and 35%, compared to the reference scenario. Within this short period of time (5 years), policies have had direct impacts on peri-urban livestock production in Beijing, resulting in marked changes in the structure of different livestock sectors, as well as the GHGs and NH3 emission inventories and their spatial distribution. Our analysis clearly shows that the success of these (and future) polices relies on optimizing spatial management of new livestock production systems. Policy and farmer guidance should focus on optimizing livestock diet and on-farm manure management, industrial production systems and the pig and poultry sectors in peri-urban regions.

Solar accessibility, defined as the solar irradiation received in a spatial and temporal domain, is increasingly becoming a practical demand in a variety of applications, especially in dense and high-rise urban areas where people prefer natural daylighting accommodations and offices and enterprises desire rooftops with high exposure to sun for photovoltaic cells. However, new buildings may substantial alter spatio-temporal solar distribution and obstruct exposure to solar power significantly. Thus, providing an accurate quantification of how solar accessibility is impacted by a developing urban environment is a key step in the development of sustainable cities. Motivated by this observation, a solar irradiation estimation model has been designed, which allows solar radiation from a particular elevation and azimuth to pass through urban surfaces modelled as 3D polygons, resulting in the creation of 3D shadow surfaces. As such, the urban surfaces can also be represented as 3D point clouds of irradiations determined by both solar radiation and shadow. By applying the model to existing and planned urban environment, it is possible to estimate the transformation of solar accessibility at the district scale. As a case study, a master plan for the Kowloon East district proposed by the Hong Kong government has been considered, and an application of the propose methodology found that new buildings to be built in the district can obtain considerable solar energy, while having a marginal impact on existing buildings. This case study suggests that the model can be used in many other cities for a variety proposes.

Abstract With the increasing access of renewable energy resources and fast ubiquitous connection of everything, the traditional one-way power flow from centralized generation to end consumers will give way to bidirectional-way power flow with multidirectional energy network among central grids and distributed prosumers. To empower the prosumer-centric Energy Internet (EI) and enhance the integration of energy-aware services, digitalization and decentralization are the key enablers to achieve transactive EI. This article presents a systematic overview on how Internet of Things (IoT) drives the digitalization of transactive EI and how blockchain empowers the decentralization of transactive EI. A comprehensive discussion on the key infrastructures is provided for presenting how to implement digitalization and decentralization of transactive EI, including the last mile “Advanced metering infrastructure” (AMI), renewables integrator “smart inverter”, energy flow adjuster “energy router”, and coordinator “Microgrid”. Challenges and future trends are discussed from an extensive point of view, including energy physical space, data cyber space and human social space.