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Office buildings are now responsible for a large portion of the durable building stock's total energy consumption and play a key role in determining urban sustainability. Based on remote sensing and GIS data as well as statistical analysis methods, we found that building construction characteristics, socio-economic conditions, climate conditions, and microclimate contributed 32.27%, 18.37%, 13.84%, and 10.66%, respectively, to office building energy carbon emissions in China. Floor area, number of energy consumers, regional scientific investment, and heating degree days had positive relationships with office energy usages. Among these, the number of energy consumers had the greatest effect on OEC and heating degree day had the least effect. Technological progress may reduce energy demand, but the energy waste of office workers in buildings that adopt more energy-saving appliance, or admire for more comfortable temperature environment could offset these savings. Most of the taller buildings surveyed were constructed recently and equipped with energy-saving appliances, but these savings may have been offset by greater use of energy associated with higher income level, and greater support for energy spending from the government. These results provide baseline information for designing emission reductions programs and further studies.

There is in general good awareness of the potential role of green roofs to regulate urban thermal environments, but a lack of effective spatial modeling of this cooling effect for a given roof greening scheme at the city scale. This study proposes a simplified and feasible approach to simulate the cooling effect provided by green roofs as a mitigation option to combat urban heat island effects in high-density urban areas. In this study, we established a spatial model of the cooling effect of green roofs, which integrated remote sensing methods and a statistical model based on the law of diminishing marginal utility of the cooling efficiency of green roofs (DMUCE) deduced from previous studies. A case study in Xiamen City, China demonstrates the applicability and implications of the model. Our modeling clearly simulated the size and strength of the urban cool island and its variation under different green roof scenarios. We found that green roofs play an important part in moderating the thermal environment in areas where larger green spaces and waterbodies are largely absent. When the proportion of green roofs is implemented at scale, roofs that are only partly green can also create some extra cool islands (not merely normal islands) in high-density urban areas, equivalent to small green spaces and waterbodies. The sensitivity analysis of the cooling effect indicated that the maximum potential benefit of heat island reduction ranged from 4.04 km2 to 9.75 km2 when the coverage of green roofs was extended to the entire Xiamen Island. Besides, our results suggested that all proposed strategies would not remarkably moderate the thermal environment in the north of Xiamen Island, where urban planners should pay more attention in the future.

Limited success in 3R (reduce, reuse, recycle) implementation and conflicts in waste treatment plant construction call for active and sustained public participation in Chinese waste management. It is especially important to identify factors which affect citizen participation in waste reduction and recycling where waste policies are poorly implemented. In this paper we report the results of a research-constructed survey conducted in Xiamen, one of eight cities in China which have been operating waste source separation pilot programs since 2000. The results showed that while more than half of respondents were satisfied with local waste management, waste recycling was still inefficient and largely carried out by the informal sector. Satisfaction rates and basic residential house prices were positively correlated, and the satisfaction rate was higher in newly urbanizing areas than in old downtown and urban village areas. A structural equation model was used to identify key factors influencing citizen environmental willingness to participate in waste management, and this indicated that the most important influencing factor was citizen knowledge, followed by social motivation, while institutional factors had the smallest positive effect. Citizens who were better informed and lived in a community/family with more environmentally friendly behaviors have a greater propensity to participate in sustainable waste management. The model is useful for identifying causal relationships and ranking influencing factors in terms of their importance. The results indicate a waste policy hierarchy in Chinese cities, and future waste management should change from the current legislative-centered strategy. The results can be used to inform decision makers find locally effective strategies to improve public participation in waste management in accordance with socioeconomic and cultural conditions in China.

Construction industry is one of the most energy-intensive industries, and its output value plays a vital role in economic growth of China. It's expected to be valuable to investigate its sustainability and improvement paths under the background of environment-friendly and conservation-minded development. At first, we adopted a non-radial data envelopment analysis incorporating both natural and managerial disposability to study regional differences regards comprehensive performance of construction industry in China. And then, a multi-regional cross-industrial linkage analysis was carried out embodiment in the sustainable assessment and sensitivity analysis based on the Ghosh model. Accordingly, we intended to provide a systematic relational network focusing on the key provinces and industries which play important roles in improving the comprehensive performance of construction industry. In detail, Hebei, Shanghai, Hubei, Yunnan and Gansu were found to be the most inefficient on account of the results from sustainable assessment in 2007. In accordance with the results from the sensitivity analysis based on the regional input-output model, the adjustment of rationing in mining & processing of ores, manufacture of non-metallic mineral products and smelting & pressing of metals will effectively increase the comprehensive performance of construction industry in the above-mentioned provinces. Emphatically, the method integration used in this study, which could also be applied in other sectors and countries, is a new try to study an industry from the multi-regional and cross-industrial perspective.

Household carbon emissions from energy use are rapidly increasing in conjunction with growing urbanization; their reduction is critical for local urban climate improvement and the sustainable development of cities. Low-carbon behavior is proved as a key element determining residents’ lifestyle. Understanding how that behavior affects household energy use will be useful in promoting low-carbon households. In this study, Xiamen, a coastal city was divided into areas at high and low risk of flooding. We used the path analysis method—integrated with behavior and socioeconomic factors—to explore the mechanisms of low carbon behavior effects on household direct energy use and related carbon emissions. We found that socioeconomic conditions combined with low-carbon behavior had direct and indirect impacts on household carbon emissions. Low-carbon behavior in the high-risk area contributed most to reducing carbon emissions. Education level was the important factors in the low-risk area. Government-led policies encouraging low-carbon behavior were effective in reducing household carbon emissions in the high-risk area. However, in low-risk areas, education about a low-carbon lifestyle is an effective means for reducing carbon emissions.

The increase of municipal solid waste (MSW) with urbanization is causing serious environmental problems as well as resource shortage. Thus, accounting virtual water content of MSW within a city could indicate resource-saving significance of waste management, and can further strengthen integrated policy-making on both resource use and waste management in urban metabolism contexts. However, virtual water saving efforts from recycling MSW are currently lacking in the literature. Therefore, to foster attention on this area, an evaluative framework for virtual water in MSW has been developed for systematic management of resource metabolism. Accumulated virtual water contained in MSW from Xiamen for 2004, 2008 and 2012 was evaluated by process analysis, based on statistical and survey data of MSW. Following the evaluation, we found that efficient management of MSW would improve its recyclability and promote virtual water saving, as observed from the virtual water saving potential of MSW during recycling, which range from 483.9 to 7633.3 m3 tonne−1. Likewise, the total virtual water amount in MSW in Xiamen rapidly increased from 2004 to 2012, total virtual water amount in MSW in Xiamen in 2004 is 2757.9～36750.4×105 m3, total virtual water amount in MSW is 7574.4～68957.2×105 m3 in Xiamen in 2012, as per capita MSW collection went up from 2002 to 2013 slowly. Therefore, encouraging source separation collection of MSW is necessary in relation to decisions regarding sustainable management of MSW and water resources, verified by evidence that per tonne of wastepapers, woods/bamboos, and food remnants contain much higher virtual water than that of other MSW components. Furthermore, integrated water management through production processes of MSW's components has proved important for saving water resources and improving environmental performance, due to the higher water consumption during planting, farming, or growing of raw materials than other processes of production. This is verified by the annual virtual water contained in food remnants, which account for more than 85% of total virtual water discharged with MSW in the selected years, with fish and shrimp taking the dominant part of virtual water content of food remnants. Certainly, MSW recycling would play great role in improving urban water metabolism efficiency as revealed by findings from this study. Hence, accounting for virtual water content of MSW could expand virtual water research field from product trade to MSW management.

Green roofs are thought to be an effective measure to solve the contradiction between land shortages and ecological construction, especially address urban heat island (UHI) effects in high-density urban areas. However, few empirical studies have focused on the cooling effect of green roof projects at urban scales. This study quantified the cooling effect of green roofs in Xiamen Island, China, where 540,000 m2 of green roofs were implemented between 2015 and 2017, in order to address the two research questions: (1) do green roofs in high-density urban areas have a significant cooling effect at the city scale and (2) what is the extent of the cooling? The relative difference between the average land surface temperature (LST) of Xiamen Island and the green roofs stemmed from Landsat 8 remote sensing image in the summers of 2014 and 2017 were calculated in geographic information systems (GIS) to represent the cooling effect of green roof project. Results showed that: (1) the average LST difference between green roofs and Xiamen Island decreased by 0.91 °C, indicating that green roofs could effectively alleviate UHI effects in high-density urban areas; (2) The cooling effect was significant up to 100 m from the green roof installation in Xiamen Island, we called it as characteristic cooling buffer zone; (3) Regression analysis revealed that for every 1000 m2 increase in green roof area, the average LST of the roof and its characteristic cooling buffer zone decreased by 0.4 °C. These findings provide the empirical proof for the cooling effect of green roofs on the surrounding environment in high-density urban areas and important insights for urban planners and government agencies for the effective mitigation of UHI impacts.

The aim of this paper is to explore the relationship between spatial-temporal patterns of vehicles types and numbers in different urban functional zones and traffic-related air pollutant emissions with real-time traffic data collected from traffic surveillance video and image recognition. The data were analyzed by using video-based detection technique, while the air pollution was quantified via pollutant emission coefficients. The results revealed that: (1) the order of traffic-related pollutant emissions was expressway > business zone > industrial zone > residential zone > port; (2) daily maximum emissions of each pollutant occurred in different functional zones on weekdays and weekends. With the exception of expressway, the business zones had the highest emissions of CO, HC and VOC on weekdays, while the highest emissions of all the pollutants (CO, HC, NOx, PM2.5, PM1.0, and VOC) were at the weekend. The industrial zone had the highest emissions of NOx, PM2.5 and PM1.0 on weekdays; (3) pollutant emissions (CO, HC, NOx, PM2.5, PM1.0 and VOC) in all functional zones peaked in the morning and evening peak except at port sites; (4) cars and motorcycles represented the major source of traffic-related pollutant emissions. Collecting data through video-based vehicle detection with finer spatio-temporal resolution represents a cost-effective way of mapping spatio-temporal patterns of traffic-related air pollution to contribute to urban planning and climate change studies.