Speaker
Description
In the context of global efforts to address climate change, cities, as the core spatial carriers of human activities, bear significant responsibility for emission reductions. Urban carbon emissions account for more than 70% of global emissions, and with the acceleration of urbanization, population density and urban expansion have further driven the growth of carbon emissions (Shi et al., 2016). How to optimize urban spatial elements (such as building density, land use, etc.) to reduce carbon emissions has become a critical issue that needs to be addressed. Existing research has primarily focused on carbon emission analysis at the city and urban agglomeration scale (Zhang et al., 2017), while studies on carbon emission mechanisms at the internal urban scale, especially at the plot level, are relatively scarce. Given that national planning is often based on land plots as the basic unit, it is of practical significance to develop low-carbon planning strategies at this scale. Moreover, most studies rely on model results to provide low-carbon recommendations (Hurlimann et al., 2021; Woodruff et al., 2022), lacking quantitative assessments based on actual plots and failing to verify the actual emission reduction effects of low-carbon strategies. Therefore, this study focuses on the micro-scale of urban plots, exploring the mechanisms between urban elements and carbon emissions, and provides guidance for low-carbon urban construction through practical low-carbon micro-renovation and effect assessment.
This study focuses on the central urban area of Nanjing, China. Using global 1 km carbon emission grid data form the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) and multi-source big data, the spatial-temporal evolution of urban land carbon emissions from 2000 to 2022 is analyzed. Combining literature review and planning perspectives, the study divides the influencing factors of urban land carbon emissions into three categories: functional attributes, spatial form, and carrying capacity. Using the Multiscale Geographically Weighted Regression (MGWR) model and Geo Detector model, the study reveals the mechanisms and interaction effects between urban elements and carbon emission intensity. The results show that the carbon emissions in Nanjing's central urban area have experienced three stages: expansion (2000-2010), stability (2011-2017), and contraction (2018-2022). The impact of functional attributes, spatial form, and carrying capacity on carbon emission intensity has significant spatial heterogeneity, with carrying capacity factors contributing the most to the spatial differentiation of carbon emissions. In addition, about 60% of the influencing factors show synergistic effects, indicating that carbon reduction planning should consider the interactions between elements to accurately identify carbon emission driving mechanisms and propose low-carbon planning strategies suitable for the micro-scale of urban plots.
To verify the practical effects of the theoretical model, the study implements a low-carbon micro-renovation plan for an actual plot in the Liuhe District of Nanjing and conducts a quantitative carbon emission assessment. The results show that the annual carbon emission intensity has decreased from 6.96 kg/m² to 6.38 kg/m² (an 8.38% reduction), and the total annual carbon emissions have dropped from 1827.33 tons to 1674.20 tons (a reduction of 153 tons). This result validates the significant effect of the low-carbon micro-renovation strategy in reducing both carbon emission intensity and total emissions, further demonstrating the important role of plot-level low-carbon planning in urban emission reduction.
This study further emphasizes the core role of urban planning in low-carbon city construction by demonstrating that comprehensive carbon reduction strategies at the micro-plot scale can effectively lower urban land carbon emission intensity, thereby providing strong support for achieving low-carbon city goals. The effort proposes an actionable low-carbon construction spatial paradigm and stresses that future urban planning must promote sustainable urban development through multi-dimensional, multi-scale collaborative optimization.
References
HURLIMANN, A., MOOSAVI, S. & BROWNE, G. R. (2021). Urban planning policy must do more to integrate climate change adaptation and mitigation actions. LAND USE POLICY, 101.
SHI, L., CHU, E., ANGUELOVSKI, I., AYLETT, A., DEBATS, J., GOH, K., SCHENK, T., SETO, K. C., DODMAN, D., ROBERTS, D., ROBERTS, J. T. & VANDEVEER, S. D. (2016). Roadmap towards justice in urban climate adaptation research. NATURE CLIMATE CHANGE, 6, 131-137.
WOODRUFF, S. C., MEEROW, S., STULTS, M. & WILKINS, C. (2022). Adaptation to Resilience Planning: Alternative Pathways to Prepare for Climate Change. JOURNAL OF PLANNING EDUCATION AND RESEARCH, 42, 64-75.
ZHANG, Y.-J., PENG, Y.-L., MA, C.-Q. & SHEN, B. (2017). Can environmental innovation facilitate carbon emissions reduction? Evidence from China. ENERGY POLICY, 100, 18-28.
Keywords | Carbon emissions; Micro perspective;Multiscale Geographic Weighted Regression; Low-carbon micro-renovation |
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Best Congress Paper Award | No |