Three cities (Wuhan, Xiangyang, and Yidu) were selected as samples of three typical sizes of cities (large, medium, and small) in China to study the spatial layout of retail stores. The authors analyzed the spatial characteristics of different types of retail stores and the influential factors of their spatial distributions using tools of spatial statistics, based on big data of retail stores from the Baidu map. The results show that the spatial distribution of retail stores in the large city of Wuhan shows the characteristics of multi-center and multi-layer, while Xiangyang, the medium-sized city, shows a single center layout, and Yidu, the small city, shows dispersed layout. The agglomeration levels of different types of retail stores show a sequence: integrated retail store > professional retail store > supermarket > special retail store. Population size, transportation accessibility, types of retailing, and green-space accessibility are the main factors which affect the spatial distributions of retail stores. The results can provide the scientific basis for spatial planning and optimization of retail stores in multiple sizes of cities.

A framework called Object-Oriented Precise Decision-making (OOPD) was proposed which oriented to the lake itself. The framework was based on Numerical Source Apportionment powered by 3-dimensional water quality model, which then quantified the causality of water quality improvement and load reduction. The proposed framework was applied to support short-term decision making of Lake Yilong, a eutrophic lake. Results showed that Chenghe sub-watershed and Chengbeihe sub-watershed were important pollution source no matter considering which monitoring station and under which water diversion scenario. In addition, comprehensive pollution control should be considered to ensure that Huzhong monitoring station or Hudong monitoring station meet water quality standards. However, considerable load reduction cannot guarantee water quality if there was no water diversion. Water quality of three monitoring stations would be improved a lot under 20 and 30 million m³ annual water diversion scenario. Finally, based on the analyses above, suggestion of focused pollution control project was given for each sub-watershed and an evaluation of one bean product wastewater treatment extension project was given to illustrate how to combine micro and macro aspects in OOPD.

Using the international vehicle emission (IVE) model and on-road vehicle monitoring data, the carbon emission factors of three main types of vehicles in Shenzhen were calculated. Then, the authors estimated carbon emission intensities of several main roads and analyzed the spatial-temporal characteristics of transportation carbon emissions in Shenzhen. Finally, scenario analysis was used to quantitatively compare three kinds of low-carbon transport development strategies. The results showed that the transportation carbon emissions of the investigated roads were highly spatially heterogeneous, and the intensities of transportation carbon emissions in urban centers and the roads linking urban centers were higher than other roads. The transportation carbon emissions of the investigated roads had apparent daily cycle, and they had four main types: single-peak curve, double-peak curve, fluctuation curve, and stable curve. The transportation carbon emissions were high in morning and evening commuting hours during workdays. The comparative analyses of three low-carbon transportation development scenarios indicated that the mild-constraint carbon mitigation scenario could better meet the targets of socioeconomic development and transportation development of Shenzhen.

The DeST model is used to simulate the energy consumption of typical civil buildings in Shenzhen, and the temporal and spatial characteristics of energy consumption of various types of buildings are summarized. The results show that different civil buildings in Shenzhen have different energy consumption characteristics in space and time. Residential buildings with low energy consumption per unit area are most widely distributed, and commercial buildings with limited numbers have the largest volume and high energy intensity, so the total consumption can not be ignored. Meanwhile, office buildings, most sensitive to the parameters change, have great energy saving potential. Combined with the development plan of Shenzhen 13th Five-Year Plan, suggestions on the strategy of building carbon reduction in Shenzhen can be summarized as follows: 1) building a comprehensive smart city, creating an exhaustive monitoring network for measuring energy consumption of various types of buildings, managing energy consumption behavior more scientifically; 2) constructing green buildings in an allround way, implementing green building standards when constructing new buildings, and valuing the reconstruction of old buildings as well, taking appropriate measures (for instants, taking part of the transformation, demolishing and reconstructing, optimizing the room combination and improving energy efficiency) when reconstructing according to the different energy consumption characteristics of the different types of buildings.