The effect of sustainable mobility transition policies on cumulative urban transport emissions and energy demand

Deep decarbonization potential and implementation path under provincial differences in China's fleet electrification

Fleet electrification is considered to be an important measure for reducing carbon emissions in the road transport industry. Considering the heterogeneity of the NEV market penetration and the vehicle types in different provinces, how to design targeted and time-sequenced road transport decarbonisation reduction strategies has become a key issue that needs to be discussed urgently. In this study, the NEVs ownership in China's 31 provinces is used as an intermediate variable. Considering the process of energy transition and changes in vehicle structure, a two-layer scenario framework that combines Shared Socioeconomic Pathways scenarios and model structure was developed to predict carbon emissions. This study firstly analyzes the electrification process and carbon emission reduction potential of provincial road transport industry by region, vehicle type and stage. The potential for reducing carbon emissions was determined under benchmark, transition, and electrification scenarios. The results indicate that the Pearson Correlation Coefficient-Discrete Wavelet Transform-Bidirectional Long Short-term Memory prediction model has an mean absolute percentage error of 8.583 and an R-squared of 0.975. China's road transportation industry total carbon emissions will reach its peak as early as 2027, due to the rapid implementation of renewable energy and fleet electrification. Shanghai, Jiangsu, Shandong, Henan, and Guangdong have set carbon peak targets that can be achieved faster with the transition plan for new energy vehicles to replace fossil fuel vehicles. This paper proposes a timing-responsive deep decarbonization path and policy recommendations for China's road transport industry in sub provincial and time-series settings.

Co-drivers of Air Pollutant and CO2 Emissions from On-Road Transportation in China 2010-2020

Co-controlling the emissions of air pollutants and CO2 from automobiles is crucial for addressing the intertwined challenges of air pollution and climate change in China. Here, we analyze the synergetic characteristics of air pollutant and CO2 emissions from China's on-road transportation and identify the co-drivers influencing these trends. Using detailed emission inventories and employing index decomposition analysis, we found that despite notable progress in pollution control, minimizing on-road CO2 emissions remains a formidable task. Over 2010-2020, the estimated sectoral emissions of VOCs, NOx, PM2.5, and CO declined by 49.9%, 25.9%, 75.2%, and 63.5%, respectively, while CO2 emissions increased by 46.1%. Light-duty passenger vehicles and heavy-duty trucks have been identified as the primary contributors to carbon-pollution co-emissions, highlighting the need for tailored policies. The driver analysis indicates that socioeconomic changes are primary drivers of emission growth, while policy controls, particularly advances in emission efficiency, can facilitate co-reductions. Regional disparities emphasize the need for policy refinement, including reducing dependency on fuel vehicles in the passenger subsector and prioritizing co-reduction strategies in high-emission provinces in the freight subsector. Overall, our study confirms the effectiveness of China's on-road control policies and provides valuable insights for future policy makers in China and other similarly positioned developing countries.

Sustainable development pathways for energies in Yangtze River Delta urban agglomeration

The sustainable development of urban agglomerations plays a pivotal role in national and global efforts to reduce emissions. By focusing on the efficient exchange and optimization of energy consumption across various sectors, the sustainable development of energy systems within urban agglomerations can be achieved. However, the overall impact of the cross-sector energy optimization and complementarity has not been quantitatively analyzed. Here, we focused on the Yangtze River Delta (YRD) urban agglomeration in China and proposed an optimization framework for energy, environment, and economy. The framework considered four sectors: transportation sector, power sector, industry sector, and building sector, in order to determine the most sustainable development pathway for the urban agglomeration. The optimization model considers total costs and greenhouse gas emissions reduction as the objectives and utilizes technologies as constraints to optimize the pathway. We found that this optimization strategy resulted in a 53.1 billion tons increase in CO2 emissions reduction in the region. The results of emission reduction varied across sectors, ranging from 4.5 to 22.2 billion tons CO2 equivalent, and across cities, ranging from 7.1 to 4688.1 Mt. The results suggest that the core cities in the urban agglomeration can take on a leadership role. By promoting cross-sector collaboration and implementing energy recycling, the energy efficiency of surrounding cities can be greatly improved, leading to the sustainable development of the urban agglomeration.