Although battery electric vehicles (BEVs) are climate-friendly alternatives to internal combustion engine vehicles (ICEVs), an important but often ignored fact is that the climate mitigation benefits of BEVs are usually delayed. The manufacture of BEVs is more carbon-intensive than that of ICEVs, leaving a greenhouse gas (GHG) debt to be paid back in the future use phase. Here we analyze millions of vehicle data from the Chinese market and show that the GHG break-even time (GBET) of China’s BEVs ranges from zero (i.e., the production year) to over 11 years, with an average of 4.5 years. 8% of China’s BEVs produced and sold between 2016 and 2018 cannot pay back their GHG debt within the eight-year battery warranty. We suggest enhancing the share of BEVs reaching the GBET by promoting the effective substitution of BEVs for ICEVs instead of the single-minded pursuit of speeding up the BEV deployment race.
China has set stringent fuel consumption rate (FCR) targets to address the serious environmental and energy security problems caused by vehicles. Estimating the technological progress and tradeoffs between FCR and vehicle attributes is important for assessing the viability of meeting future targets. In this paper, we explored the relationship between vehicle FCR and other attributes using a regression model with data from 2009–2016. We also quantified the difference in the tradeoff between local and joint venture brands. The result showed that from 2009 to 2016, if power and curb mass were held constant, 2.3% and 2.9% annual technological progress should have been achieved for local and joint venture brands, respectively. The effectiveness of fuel-efficient technologies for joint venture brands is generally better than that of local brands. Impacts of other attributes on FCR were also assessed. The joint venture brands made more technological progress with FCR improvement than that of local brands. Even if 100% of technological progress (assume the technological progress in the future were the same as that of 2009–2016) investment were used to improve actual FCR after 2016, it would be difficult to meet 2020 target. Accelerating the adoption of fuel-efficient technologies, and controlling weight and performance, are both needed to achieve the 2020 and 2025 targets.
With the development of the Internet age, the gradual deepening of reforms, and the continuous improvement of marketization, the financial ecological environment is directly related to the risk of financial institutions’ loans and the enthusiasm to support local economic development. Capital is accompanied by the physical development and evolution of the production and circulation of goods. After thousands of years of historical development and evolution, it has formulated its own development law and internal logic. In view of the unclear environmental and social evaluation indicators in supply chain research and the model’s failure to accurately describe the real supply chain network, an adaptive dynamic relaxation approximation algorithm model is proposed. This model introduces upstream and downstream transit stations as distributors and as a hub between customers, the transportation mode is improved to horizontal and vertical coordinated transportation, and multiple transportation methods are used for transportation. In this paper, the experimental group adopts a new model based on the approximate algorithm of dynamic relaxation factors, and the control group adopts the original old model. The two groups conduct comprehensive data analysis on social indicators, self-indicators, initial indicators, economic indicators, and environmental indicators in each year. Starting from the dimension, comprehensively consider the selection of indicators to measure the level of enterprise performance. The experiment proves that the transportation loss in the green supply chain is between the new model and the old model. When the number of partners is small, the degree of the optimal solution between the new and old models is not obvious, and the degree of optimization of the new model relative to the old model is increasing. It has a significant statistical difference (
P
<
0.05
). This shows that efforts to build a good financial ecological environment and an honest and reliable and healthy economic ecological environment are of great importance for promoting the continuous and rapid growth of the social economy.
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