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Achieving carbon neutrality is an urgent, complex and arduous task in China. How to effectively exert carbon sequestration and improve carbon sequestration capacity of urban ecosystems should be solved. Compared with other terrestrial ecosystem types, frequent anthropogenic activities lead to more abundant carbon sink elements of urban ecosystems and more complex factors affecting their carbon sequestration capacity. Based on researches at multiple spatial and temporal scales, we analyzed key factors affecting the carbon sequestration capacity of urban ecosystems from different perspectives. We illuminated the composition and characteristics of carbon sinks of urban ecosystems, summarized the methods and characteristics of carbon sequestration capacity of urban ecosystems, and revealed the impact factors of carbon sequestration capacity of different carbon sink elements and the comprehensive impact factors of carbon sinks of urban ecosystems under the influence of human activities. With the continuous improved understanding of carbon sinks of urban ecosystems, it is necessary to further improve the accounting method of carbon sequestration capacity of artificial carbon sink systems, explore the key impact factors of comprehensive carbon sequestration capacity, change the research method from global to spatially weighted, discover the spatial coupling relationship between artificial and natural carbon sink systems, find out the optimal artificial-natural spatial configuration to achieve carbon sequestration capacity enhancement, break the limitations of increasing carbon sink of urban ecosystems, and finally contribute to the achievement of the urban carbon neutrality goal.

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Respiratory infection is the main route for the transmission of coronavirus pneumonia, and the results have shown that the urban spatial environment significantly influences the risk of infection. Based on the Wells-Riley model of respiratory infection probability, the study determined the human respiratory-related parameters and the effective influence range; extracted urban morphological parameters, assessed the ventilation effects of different spatial environments, and, combined with population flow monitoring data, constructed a method for assessing the risk of Covid-19 respiratory infection in urban-scale grid cells. In the empirical study in Shenyang city, a severe cold region, urban morphological parameters, population size, background wind speed, and individual behavior patterns were used to calculate the distribution characteristics of temporal and spatial concomitant risks in urban areas grids under different scenarios. The results showed that the correlation between the risk of respiratory infection in urban public spaces and the above variables was significant. The exposure time had the greatest degree of influence on the probability of respiratory infection risk among the variables. At the same time, the change in human body spacing beyond 1 m had a minor influence on the risk of infection. Among the urban morphological parameters, building height had the highest correlation with the risk of infection, while building density had the lowest correlation. The actual point distribution of the epidemic in Shenyang from March to April 2022 was used to verify the evaluation results. The overlap rate between medium or higher risk areas and actual cases was 78.55%. The planning strategies for epidemic prevention and control were proposed for the spatial differentiation characteristics of different risk elements. The research results can accurately classify the risk level of urban space and provide a scientific basis for the planning response of epidemic prevention and control and the safety of public activities.

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The patterns of green corridors in urban riverfront districts provide different synergistic cooling effects of blue-green space in urban areas. The purpose of this study is to quantify the spatial morphological impact of green corridors in riverfront block-scale area on the cooling effect. Three representative patterns (radiate, grid and dendritic) were selected in the study. The comprehensive influences analysis between multi-dimensional factors of spatial structure and morphology of green corridors and Ta (air temperature) distribution are processed by Envi-met4.4.5 simulation data and statistical analysis methods, such as regression tree model (BRT), were combined. The results showed that the D (distance from riverbank) has the greatest impact on the cooling effect of each belt green space. The D in the range of 600-750 m was affected by the cooling effect of blue-green space; The orientation with parallel to (southeast-northwest) or roughly the same as the prevailing wind direction (north-south) green corridors had relatively better cooling effect. When the width of green corridor was 20-25 m, the ME (marginal effect) of cooling was the largest; at 30-35 m (corridor width), the overall ME of cooling was the best; When the dPC (decreased probability connectivity, here the index was adapted to describe the connectivity degree) of green corridors was in the range of 0.5-1.5, the cooling effect of green corridor could be significantly improved. When dPC is 1.5, its marginal effect on temperature reached the maximum. The study provided a quantitative correlation technology for the morphological influence of blue-green space on the distribution of UCI (urban cooling island), which can guide the spatial layout control of green corridors in the planning and design of urban riverfront district.

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The spatial morphology of waterfront green spaces helps generate cooling effects to mitigate the urban heat island effect (UHI) in metropolis cities. To explore the contribution and influence of multi-dimensional spatial indices on the mitigation of UHIs, the green space of the riparian buffer along 18 river channels in Shanghai was considered as a case study. The spatial distribution data of the land surface temperature (LST) in the study area were obtained by using remote sensing images. By selecting the related spatial structure morphological factors of the waterfront green space as the quantitative description index, the growth regression tree model (BRT) was adapted to analyze the contribution of various indexes of the waterfront green space on the distribution of the LST and the marginal effect of blue-green synergistic cooling. In addition, mathematical statistical analysis and spatial analysis methods were used to study the influence of the morphological group (MG) types of riparian green spaces with different morphological characteristics on the LST. The results showed that in terms of the spatial structure variables between blue and green spaces, the contribution of river widths larger than 30 m was more notable in decreasing the LST. In the case of a larger river width, the marginal effect of synergistic cooling could be observed in farther regions. The green space that had the highest connectivity degree and was located in the leeward direction of the river exhibited the lowest LST. In terms of the spatial morphology, the fractional cover values of the vegetation (Fv) and area (A) of the green space were the main factors affecting the cooling effect of the green space. For all MG types, a large green patch that had a high green coverage and connectivity degree, as well as was distributed in the leeward direction of the river, corresponded to the lowest LST. The research presented herein can provide methods and development suggestions for optimizing spatial thermal comfort in climate adaptive cities.

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Different structural patterns of waterfront green space networks in built-up areas have different synergistic cooling characteristics in cities. This study's aim is to determine what kinds of spatial structures and morphologies of waterfront green spaces offer a good cooling effect, combined with three different typical patterns in Shanghai. A multidimensional spatial influence variable system based on the cooling effect was constructed to describe the spatial structural and morphological factors of the green space network. The ENVI-met 4.3 software, developed by Michael Bruse at Bochum, German, was used to simulate the microclimate distribution data, combined with the boosted regression tree (BRT) model and the correlation analysis method. The results showed that at the network level, the distance from the water body and the connectivity of green space had a stronger cooling correlation. The orientation of green corridors consistent with a summer monsoon had larger cooling effect ranges. In terms of spatial morphology, the vegetation sky view factor (SVF) and Vegetation Surface Albedo (VSAlbedo) had an important correlation with air temperature (T), and the green corridor with a 20-25 m width had the largest marginal effect on cooling. These results will provide useful guidance for urban climate adaptive planning and design.

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Different historical backgrounds and planning ideas have created different urban streetscape fabrics. The patterns of the streetscape fabric have affected urban microclimate factors and formed a unique local microclimate. This paper simulated the microclimatic effects in four study areas with different streetscape fabrics in Shanghai to compare the microclimatic conditions with a system of multi-dimensional street morphological indices using ENVI-met 4.3 software. At the street network fabric level, the results showed that streets with a south⁻north orientation, a small junction spacing, and a street network with better connectivity were conducive to mitigation of the air temperature heating intensity in the street space and improving the ventilation effect; at the street-site level: The indices of Build-to-line ratio (BL), Height-width ratio (H/W), and Sky view factors (SVF) played different roles that affected the distribution characteristics of the microclimate factors. The BL value of the streets between 0.5 and 0.8 generally had a positive relationship with the air temperature. The SVF value of the streets was positively correlated with the microclimate index, while the H/W values were negatively correlated with them. The morphological indicators of different levels also had a synergistic effect on the microclimatic impact of the street space fabric. This comparative analysis of microclimatic characteristics at the medium spatial scale will provide useful suggestions for urban climate adaptability in urban spatial morphology optimization in future urbanization development.

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Based on the theory of landscape ecological security pattern and the RS and GIS techniques, this paper analyzed the distribution of ecological security grades in Nanchong City, taking six elements including terrain condition, flood hazard, soil erosion, vegetation cover, geological disaster, and biological protection as the ecological constraints (or determinants) of urban expansion. According to the minimum cumulative resistance model, the ecological corridors and ecological nodes were built to strengthen the space contact of ecological network, and, on the basis of the protection of ecological safety, the reasonable trend of urban expansion and the optimization of space layout were investigated. The results showed that the ecological security of Nanchong City was quite good, with the regions of low ecological security mainly distributed in the west suburban mountains and the downstream region of Jialing River in the south of the City. Ecological elements were the most important constraints for the future expansion of urban space. There were more spaces for the urban expansion in the southern and northern parts of Nanchong City. To develop satellite towns would be the best selection to guarantee the ecological security of the city.

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Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

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Based on the five temporal Landsat TM remote sensing data of 1988, 1992, 1997, 2000, and 2004, and by using GIS spatial analysis and landscape pattern analysis, this paper analyzed the spatiotemporal pattern of urban growth and its driving forces in the urban agglomeration of central Liaoning Province (UACLP). From 1988 to 2004, the urban area in the UACLP had being increased from 812.55 km2 to 1345.86 km2, with an average growth rate of 32.96 km2 per year. The urban growth rate increased rapidly after 1997, and the urban growth intensity was up to the peak in 1997-2000. The urban growth was mainly concentrated in the central dense belt of the UACLP. From 1988 to 1997, the urban growth was relatively slow, its spatial pattern was compact, and edge growth and filling were the main urban growth types. From 1997 to 2004, the urban growth became faster with diffused spatial pattern and complex patch shape, and "frog leap" and diffusion were the main urban growth types. Non-agricultural population growth, economic growth, urban spatial mutual attraction, industrial development, and development zones construction policies were the main driving forces of urban growth in the UACLP.

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