Low-carbon Scenarios Modeling And Optimization:a Case Study Of Suzhou Eco-city

Global climate change, particularly global warming brought about by greenhouse-gas emissions, has garnered attention and presented major challenges on a global scale. Scholars across the globe now are focusing on the effect of anthropogenic activities, especially economic development and urban expansion, on climate change; and advocating for the reduction of the emission of carbon monoxide and other greenhouse gases. At the center stage of global economic development, China and its rapid industrialization as well as urbanization has received large amount of attention from the scientific community. How to sustain economic growth in China while meeting the goals of environmental protection, including greenhouse gas emission reduction is a study hotspot of domestic scholars. Effectively determining the direction of urban carbon emissions along with proper low-carbon policies will accomplish the goal of promoting cities actively adapt to the global change and ecological environment protection. This marks the importance of research and implementation of low-carbon cities in China. Currently, low-carbon research is transitioning from the theoretical paradigm to a quantitative one. The use of space-time carbon emissions data will provide an effective way of low-carbon city spacing optimization. However, the lack of research on meticulous spacing expression of carbon flux in regional scale, reasonable urban low-carbon targets, and spacing optimization decision-making of carbon emission limits the application of research on the urban carbon cycle in low-carbon urban planning and decision-making.This paper used Suzhou Eco-city in the Lake Tai region as its geographical study area, and used the urban carbon cycle theory and urban carbon metabolic theory as basis for the quantification of its carbon budget flux. The quantification is then used to explore possible carbon mitigation strategies and carbon mitigation potential in the region. On this basis, the low carbon scenario and the carbon flux spatial distribution under different mitigation strategies were simulated. Then low-carbon target decisions were carried out in accordance with the social cost theory and integrated assessment models on carbon emission, and the optimum point of low-carbon target of Suzhou Eco-City was determined. Lastly, this study utilized spatial optimization methods to achieve the goals of carbon mitigation flux spatial optimization of Suzhou Eco-City at the best target scenario. This study also provided future recommendations to mitigation and space optimization strategies for the study area based on the research findings. Results showed that:(1) Based upon the urban carbon cycle theory and urban carbon metabolic theory, meticulously estimating the spatial-temporal distribution of the urban carbon pool and flux could provide spatial data for low-carbon urban planning and management. Under the predicted planning objective, Suzhou Eco-city total carbon storage was 341775.07t; anthropogenic carbon storage was 113348.3t; natural carbon storage was 2228426.77t; Overall carbon flux of carbon emissions was 218146.8t/a, which increased 76.88% than that at present scenario; per capita carbon flux of carbon emission was 1.45t/a, which decreased 41.30% compared with that of 2.47t/a at present scenario. Analysis of carbon flux balance at the planning scenario showed that anthropogenic carbon emission flux was 224598.70 t/a while natural carbon sequestration flux was 6451.50t/a. Natural importing carbon flux offset only 2.8% of total anthropogenic exporting carbon flux. Thus, controlling anthropogenic carbon emissions was a key to developing low-carbon cities.(2) This study estimated the carbon mitigation potential of Suzhou Eco-City, simulated the spatial characteristics of carbon emissions at different low-carbon scenarios, and offered reference tactics to spatial decision-making of low-carbon urban. The carbon mitigation potential of four measures such as urban green space carbon sequestration, building energy use, traffic optimization mitigation and re-utilization of wastes was estimated, which was 16573.53t/a, 71514.61 t/a,2352.34t/a and 1160t/a respectively. Using the carbon emission reduction strategy implementation difficulty level,3 sets of scenarios were modeled. The carbon emissions were reduced to 196561t/a,161145.13t/a, and 126546t/a respectively and the per capita carbon emissions were reduced to 1.3 It/a,1.07t/a, and 0.84t/a respectively, showing significant reduction compared to the original planning scenario. The lowest per capita carbon emissions at the lowest carbon scenario reduced by 42%.(3) This paper used the carbon emission social cost theory as Suzhou Eco-city Low-carbon objective decision making theory. Analysis the total low-carbon social cost and abatement cost of different scenarios in Suzhou Eco-city.Result shows that:the incremental cost for different scenarios is￥0.81billions,￥2.80billions and￥6.36billions.To 2045, the total social value for different scenarios is￥1.84billions,￥3.01billions and￥4.83billions. when carbon emissions of Suzhou Eco-City is 151840.16t/a, per capita carbon emissions of 1.0lt/a, the cost-effectiveness of low-carbon agenda is optimal.On this basis, according to the principle of high carbon emission areas choosing high low-carbon strategies, a low-carbon spatial optimization algorithm was built to optimize the space of low-carbon strategies of the study area at the optimal low-carbon target scenario spatial, this study showed that a combination of carbon emissions social cost and spatial decision-making methods could be used as an effective tool for low-carbon target decision-making.