To combat climate change, China's building sector, responsible for almost 50 % of national emissions, must undergo a drastic decarbonization transformation. This paper charts the optimal path to achieve this goal, leveraging a combined framework of the Low Emissions Analysis Platform (LEAP) and System Dynamics (SD) for scenario-based forecasting of energy consumption and emissions in 2021-2060. A linear programming model is further developed to identify the lowest-cost combination of 26 building green technologies that align with China's carbon peaking and carbon neutrality targets. Results show that in a business-as-usual scenario, building carbon emissions will peak at 6393 million tons of CO2 in 2041, missing the 2030 carbon peaking target. Key drivers of this shortfall include the high energy intensity for "Transport, Storage and Post" and the large carbon emission factors for "Wholesale, Retail Trades, Hotels, and Catering Services" and "Residential" sectors. Under various technology application scenarios assuming uniform penetration rates, the 2030 carbon peak target appears attainable, though at a considerably high cost. Finally, under optimal technology combinations, building carbon emissions are forecasted to peak in 2030 at 5139 million tons of CO2, a mere 4.4 % increase from 2020. The cost of this optimized combination is projected to represent only 1.5 % of the total GDP in 2060. This scenario also leads to a significantly weaker correlation between energy consumption and carbon emissions in the building sector around 2036, nearly 17 years ahead of the business-as-usual trajectory.
Keywords: Building carbon emissions; Emission reduction path; Green technology; Low emissions analysis platform; Optimization model; System dynamics.
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