Virtual Only | Track 2 | Session 2. Kaleidoscope of issues affecting sustainable city regions

The de-carbonisation of cities has become a new theme across the world. The government of Shanghai, a city currently in the process of achieving de-carbonisation, has announced that it will achieve carbon neutrality by 2060. This is not an easy target for a city with a population of about 25 million. The term “Fifth Façade” refers to the roof or top of the building. In recent years, the de-carbonisation potential of urban fifth façades has been gradually recognized. The installation of rooftop photovoltaic systems boosts the production of renewable energy and reduces the dependence on traditional fossil fuels, thereby lowering carbon emissions. This study will explore the potential of urban fifth façades in urban de-carbonisation by taking a digital approach in Shanghai. Urban planners used to use the product of the land area and building density to estimate the total area of urban fifth façades. Then, the de-carbonisation potential could be estimated according to the energy generated per unit area of roof photovoltaic technologies. However, this old method is quite inaccurate because of the ignorance of the influence of roof slope and aspect on the total area as well as the selection of photovoltaic technologies. For example, in the northern hemisphere, the fifth façade with a south-facing aspect can generate more energy while the north-facing fifth façade at a steep slope may not be suitable for installing photovoltaic systems. This study introduced a method to measure the potential of urban fifth façades by using UAV (Unmanned Aerial Vehicle) oblique photography in Shanghai. First, a four-axis UAV equipped with an image sensor was used to collect the oblique photographic information, and then a three-dimensional model of the city was constructed in an aerotriangulation algorithm. Afterward, threshold and identification algorithms were performed by using GIS technology to extract the fifth façades from the city model. Next, spatial analyses, such as slope analysis and aspect analysis, were performed on the extracted fifth façades. Finally, the potential could be pinpointed combined with the solar hours per year in Shanghai and the power density of suitable photovoltaic technologies. The method of this study takes a digital approach and gives consideration to the influence of slopes and aspects, thus greatly improving the accuracy and efficiency of the investigation of urban fifth façades. A distribution map of urban fifth façades in Shanghai was created in this method. Based on the technologies of rooftop photovoltaic systems as well as the slope and aspect analyses, the de-carbonisation potential of urban fifth façades in Shanghai was calculated. The result shows that the fifth façades in Shanghai can generate a considerable amount of renewable energy, which is of great significance for the de-carbonisation and carbon neutrality of the city. The distribution map shows that the de-carbonisation potential of fifth façades on the residential land in Shanghai is 2.3 times those of its commercial and industrial land, and the differences in such potentials between districts are huge. Therefore, a rational utilization plan might be needed to fully utilize the potential of fifth façades in Shanghai’s de-carbonisation process.

Shanghai is currently in the process of de-carbonisation and carbon neutrality. The government announced that Shanghai will achieve carbon neutrality by 2060. This is not an easy target for a city with a population of about 25 million. Urban green spaces can play an important role in urban de-carbonisation and carbon neutrality, thanks to the carbon sinks delivered by vegetation. Especially, in high-density urban areas, green spaces are more precious resources. This study will investigate the green spaces and carbon sinks in Lujiazui CBD of Shanghai by taking a 3-D approach. The current statistical methods for urban green spaces are usually two-dimensional. Some relevant indicators, such as the green space rate, the vegetation greening rate, and the vertical projected area of vegetation, only demonstrate the proportion of green spaces to urban land areas. However, in the high-density urban areas with lots of skyscrapers, the area indicators cannot truly reflect the value of green spaces, especially in terms of urban de-carbonisation. Taking vegetation carbon sinks as an example, the carbon sink produced by one square kilometer of trees is dozens of times that of one square kilometer of grassland. Therefore, it would lead to very inaccurate outcomes to measure the value of green spaces in high-density urban areas only in two-dimensional manners. Given that various vegetation patterns in urban green spaces occupy a part of the three-dimensional spaces in cities, the index of space occupancy rate can better reveal the size and significance of green space vegetation in high-density urban areas. By investigating the size of various kinds of vegetation in urban green spaces and their distribution in 3-D urban spaces, while considering the photosynthesis intensity or chlorophyll content of various kinds of vegetation, it is possible to calculate the amount of the carbon sink generated in urban green spaces. This study introduced a three-dimensional method for investigating urban green spaces and carbon sinks based on UAV (Unmanned Aerial Vehicle) oblique photography. First, the oblique photographic information of Lujiazui CBD was collected with a four-axis UAV equipped with an image sensor, and a three-dimensional model of the CBD was constructed in an aerotriangulation algorithm. Then, the green spaces and vegetation were extracted from the city model by using certain AI-based image recognition algorithms, while the vegetation types were identified. Finally, the 3-D space occupancy rate of urban green spaces and the carbon sinks of vegetation were calculated based on the vegetation volume and chlorophyll content per unit volume of various types of vegetation. Using this method, the green spaces in Lujiazui CBD of Shanghai were investigated. The 3-D space occupancy rate of urban green spaces and the vegetation carbon sinks were calculated. Then, a heat map of urban vegetation carbon sinks in Lujiazui CBD was produced. The results of this study show that the 3-D space occupancy rate of green spaces in Lujiazui CBD reaches only 13.4%, with the total amount of vegetation carbon sinks far lower than that of carbon emissions in this area. This situation is very unfavorable for the de-carbonisation and carbon neutrality of Shanghai. In addition, the heat map demonstrates a very uneven distribution of vegetation carbon sinks in Lujiazui CBD: the carbon sinks are more concentrated along the Huangpu River in the eastern section than in the west section of Lujiazui CBD. Therefore, the planning of green space systems in Lujiazui CBD may need to be adjusted accordingly to meet the needs of urban de-carbonisation and carbon neutrality of Shanghai.

The use of biodiversity design methods to promote the construction of healthy cities is increasingly popular, and has become one of the hot spots in the field of "responding to public health threats by nature-based solutions". At present, researches on the effects of biodiversity on mental health are mostly based on the dimension of "measured biodiversity", while the exploration from the perspective of "perceived biodiversity", which can directly affect the psychology of landscape experiencers, is still scarce. In view of the restoration needs of urban residents' excessive consumption of directed attention, and on the premise of interpreting the connotation of perceived biodiversity and explaining the mechanism of attention restoration, this paper takes Chongqing, a typical city with high density and high heterogeneity, as the case area, and with the "urban parks" where can most interact with biodiversity, as the research object, and constructs a structural equation analysis model of the effect of perceived biodiversity on attention restoration based on the scale design and questionnaire survey. This study explores the causal relationship between perceived biodiversity and attention restoration. The results show that: 1) there is a significant positive correlation between perceived biodiversity and attention restoration; 2) for the four selected categories of perceptual biodiversity, birds and flowers have a great effect on perceived biodiversity promoting attention restoration, while insects and trees have a big one; 3) rare species diversity, species diversity, tactile diversity and olfactory diversity have the greatest influence on the perceived biodiversity of birds, insects, trees and flowers, respectively; 4) The effect of measured biodiversity or park area on attention restoration does not show the correlation trend that "the higher the actual biodiversity or the larger the park area, the more significant the restoration effect": the attention restoration efficiency of parks with high measured biodiversity or large area might be weaker than parks with low measured biodiversity or small area.

Buildings accounts for 36% of global final energy use and greenhouse gas (GHG) emissions according to the International Energy Agency. Among the final energy uses of global buildings, space heating accounts for the largest proportion (approximately 34%). For example, space heating energy consumption in Northern Chinese cities accounted for 24.1% of the total energy consumption of buildings, while in Europe, the proportion of heating-related energy utilized in residential buildings was approximately 70% of the total energy use of buildings. For cold-winter cities, where people experience a long heating period during winter to overcome the frigid weather, the figure is even more pronounced. Therefore, it is natural to believe that more challenges regarding building energy-saving are faced by cold-winter cities. Studies have suggested that urban greening plays an important role in reducing building energy consumption. For example, Wong et al. (2011) simulated the variables, including green plot ratio (GPR) and greenery density, in Singapore (Tropical Marine climate) and found that they can cause 0.9-1.2˚C air temperature changes, which can reduce cooling loads by 5-10%. Erell and Zhou (2022) also found that the night-time temperature could decrease due to the increasing surface cover vegetation in Tel Aviv (Subtropical Mediterranean climate), which further reduces the need for building heating and cooling. Therefore, building energy consumption can be attenuated if these urban greening factors are properly modified. However, relevant research in cold climate remains to be explored. Meanwhile, buildings in high-density cities are usually taller and denser than those in low-density cities, and the microclimate of high-density cities is also different from that of low-density cities. Therefore, it is necessary to consider whether the effect of windproof and heat preservation of greening on building energy saving is as significant as that of low-density cities in winter. Therefore, the aim of this study is to explore the impact of high-density urban block greening on building Heating Energy Consumption (HEC) in cold-winter cities. This study analyses the impact of greening on HEC with 3 variables: Green Space Ratio (GSR), Green Plot Ratio (GPR), Tree View factor (TVF) and Green Layout (GL). Firstly, 121 experimental block models with different GSR, GPR, TVF and GL are built according to 5 plant types: deciduous trees, deciduous shrubs, evergreen trees, evergreen shrubs and grassland. Secondly, the coupling simulation method of microclimate and building energy consumption (ENVI-met+EnergyPlus) is applied to simulate the HEC of each block. Finally, the influence of 4 greening variables on building energy consumption is identified by regression analysis. The results show that, in contrast to low-density block greening, which is conducive to reducing HEC, high-density block greening has the opposite effect. Specifically, with the increase of GSR and GPR, the HEC elevates gradually for all plant type blocks apart from evergreen tree type block; TVF had no significant effect on HEC; and GL of evergreen trees has an impact on HEC-- planting evergreen trees in the upwind direction of the block can reduce HEC to a certain extent. These results confirm the particularity of the impact of block greening on HEC in high-density and cold-winter cities, and provide a reference for determining how dense trees should be planted and what kind of plant species should be chosen as block greenery in urban planning and design processes.

Indian cities have distinct street characteristics with complex geometric features and various human activities. People encroach the street space and modify it as per their requirements. At the same time, Indian cities are susceptible to heat waves and related health hazards, hence, it is paramount to ensure a thermally comfortable outdoor space for the occupants. The three-dimensional (3D) Computational Fluid Dynamics (CFD) model ENVI-met has been widely used as a tool for heat mitigation research all over the world. However, applications have mostly catered to the less dense European context. We seek to understand whether ENVI-met can model the high density, complex geometry accurately for urban settings of Indian megacities such as Mumbai and Kolkata (Aw Köppen Classification) for heat mitigation research. We chose three similar neighbourhoods in both cities, 1) neighbourhoods with organic encroachments housing pottery and clay modelling activities (Kumbhadwada in Mumbai and Kumartuli in Kolkata), 2) neighbourhoods with linear encroachments (Fashion Street in Mumbai and Boipara in Kolkata), and 3) neighbourhoods with discrete encroachments (Dadar Flower Market in Mumbai and Mallickghat Flower Market in Kolkata). 12 simulations were performed for all six neighbourhoods for summer and winter using the Energy Plus Weather (EPW) Airport data of Mumbai and Kolkata as meteorological forcing for the simulation, whereas field campaign data was used for validation. All simulations were performed for a 12-hour duration from 5 AM to 5 PM with the first four simulated hours discarded from the final analysis as they were used as spin up time. To model the partial encroachments, we used the single wall z wall feature of ENVI-met. For validation, we used four number of statistical measurements, i.e., the coefficient of determination (R2), Mean Bias Error (MBE), Willmott’s Index of Agreement (d) and Root Mean Square Error (RMSE). We validated model output for two seasons (summer and winter) and urban forms (shallow canyon, deep canyon) using receptor output at the field measurement sites. Our validation shows that for all the neighbourhoods in Mumbai for both seasons, ENVI-met underestimates Ta. ENVI-met performs better in the summer compared to winter due to slightly overcast conditions in the winter. However, despite the moderately high deviation between simulated and measured data, ENVI-met is predicting the trends well (d value >0.9). For the Dadar flower market and Kumbhadwada, RMSE is low due to nearby anthropogenic heat sources. In both seasons, ENVI-met underestimates Ta for Boipara, Mallickghat and Kumartuli in Kolkata. For all three neighbourhoods, ENVI-met overestimates Tmrt. However, in general, the correlation between measured and simulated data is acceptable. The undertaken research is a very first step towards analysing the efficiency of ENVI-met for modelling high-density complex urban neighbourhoods with heterogeneous morphologies in Indian cities. Future studies are recommended considering hourly forcing of wind speed to evaluate model performance.

Climate change has brought serious impact on the planet and human daily life. According to the data of the International Energy Agency, China's total carbon dioxide emission ranks first in the world, while the per capita carbon dioxide emission of the United States is the highest (14.4 t CO2/person. The energy consumption of China in the field of residents is increasing year by year (see Fig.1). By 2019, the per capita energy consumption has reached 438 kg of standard coal. China promises that carbon emissions peak by 2030 and carbon neutralization by 2060. It is of great significance to take the people as the center, realize the "double carbon goal" and mobilize the public to participate in the practice of low-carbon behavior. To promote urban residents to participate in low-carbon behavior practice is an effective way to reduce energy consumption and achieve the dual-carbon goal. This study summarizes the policy development process of urban residents' energy-saving awareness and low-carbon behavior in China from four aspects: information policy, economic policy, technical policy and administrative policy. By using econometric and statistical methods such as Structural Equation Model, taking Hangzhou as an example and analyzing urban residents' low-carbon behavior intention and low-carbon policy perception level, this study explores the impact of low-carbon policy perception on low-carbon behavior intention. The results show that the degree of participation and satisfaction of low-carbon policy has a positive and significant impact on low-carbon behavior intention, but the impact of low-carbon policy understanding on low-carbon behavior intention is not significant. This shows that China has made some progress in the popularization of low-carbon policy. In the future, we should pay more attention to the formulation of urban residents' participatory low-carbon policy, and at the same time enhance residents' satisfaction with low-carbon policy, so as to promote residents' intention to low-carbon behavior. So as to build a lower carbon and healthier cities and the planet.

Habitat quality can reflect the ability and potential of an ecosystem to provide conditions for species reproduction. Habitat quality is an important indicator of regional biodiversity and ecosystem service levels, and is also the key to ensuring regional ecological security and improving human well-being. In the context of rapid urbanization, changes in land use patterns will be the main driver of urban habitat quality damage. This paper takes Kunming City as a research case, 2005 and 2020 phase 2 30m raster land use data as the data source, and uses the land use transfer matrix to reflect the dynamic process of mutual transformation between various land use types and areas. With the help of the FLUS model improved by cellular automata, we simulated the development of the study area under the natural development and planning protection scenarios of the city to 2035. With the aid of the habitat quality module of the INVEST model,we evaluate the spatial and temporal variation characteristics of land use and habitat quality in Kunming from 2005 to 2035. The research results show that: (1) From 2005 to 2020, the habitat quality of the study area was relatively good, the areas of low habitat quality and high habitat quality increased, the area of medium habitat quality decreased, and the overall habitat quality continued to decline. The spatial distribution shows the characteristics of decreasing from the hills and mountainous areas to the population gathering places around the Dianchi Lake in the central southwest, and the diffusion trend is obvious. (2) The habitat quality change intensity decreased in both scenarios. Compared with the results of habitat quality and degradation degree under the natural change scenario, the degradation intensity of the planned conservation scenario is weaker, the area of low habitat quality area gradually decreases, the area of medium habitat quality remains stable, the area of high habitat quality increases, and the habitat quality improves. improvement, indicating that the implementation of ecological protection measures is conducive to the protection of regional biodiversity. By simulating future land use scenarios in Kunming, this paper measures the relationship between land use change and habitat quality, and constructs a logical perspective connecting "past-present-future", which is of great significance for scientifically managing ecosystems and promoting optimal resource allocation.