An Exploration of Household Response to Personal Travel Carbon-Reduction Targets

In light of carbon peak and carbon neutrality goals, China has attached great importance to energy savings and carbon reduction. Carbon reduction in the transport sector is critical to achieving the two-carbon target, as it accounts for 9.41% of total carbon emissions. As the sharing economy grows, car sharing is considered to present excellent carbon reduction potential in the transportation sector. However, the current research is focused on car sharing usage, with a lack of research on the carbon reduction capability of car sharing in China. Hence, this study aims to investigate the carbon reduction capacity of car sharing, including usage rates of car-share services and changes in travel behavior, through an online questionnaire combined with carbon emission data from the transportation sector. The study aims to analyze the contribution of car-share services to carbon reduction in the transportation sector under the current model. The well-to-wheel (WTW) approach is employed, including the energy consumption of vehicles and carbon emissions in the production process. The research results indicate that the introduction of car-sharing services increases driving energy consumption; however, this increase is offset by the decrease in carbon emissions as a result of the production process. Therefore, the overall effect is a reduction in carbon emissions of 1.058971 million tons in 2021, accounting for 1.95 percent of total transport carbon emissions. In addition, the impact on different modes on carbon emission reduction is also explored in this study. The results demonstrate that the private car disposal rate shows the most significant influence on traffic carbon emissions; a 10% reduction in the number of private cars can lead to a 2.48% carbon reduction. The relevant conclusions of this study can provide support for the future development of car sharing in China and the reduction of carbon emissions in the transportation sector.

Background: Transportation has become the second-largest source of global carbon emissions. Promoting low-carbon development by means of public transport and green travel and analyzing the mechanism and path of the carbon emissions reduction effect of public transport have become key to reducing carbon emissions in the transportation field and achieving “carbon peak and carbon neutrality”. Methods: The data from 30 provinces (2010–2019) were extracted from China Emission Accounts and Datasets (CEADs), China Energy Statistical Yearbook, China Statistical Yearbook, and China Automobile Statistical Yearbook. The two-way fixed-effect model was used to explore the carbon emissions reduction effect of public transport development level. The mediating-effect model was used to verify the transmission role of energy consumption in the carbon emissions reduction effect of public transport development level. Results: The study suggests that the public transport development level and CO2 emissions are negatively correlated, showing an “Inverted U-shaped” curve relationship. Energy consumption is the transmission path of the carbon emissions reduction effect of public transport development level. The public transport development level adjusts the energy consumption structure through the traffic substitution effect, energy input optimization effect, and industrial structure optimization effect and then acts on carbon emissions. Moreover, the contribution rate of energy consumption is about 4.22%. In addition, regional heterogeneity is present in the transmission path of the carbon emissions reduction effect of public transport development level based on energy consumption. The carbon emissions reduction effect of public transport development level is more significant in the central and western regions than the eastern and northeast regions of China. Conclusion: The transmission mechanism of energy consumption in the carbon emissions reduction effect of public transport is worthy of attention. To promote low-carbon and circular development in the transportation sector, it is urgent to accelerate the green upgrading of transportation infrastructure, promote the low-carbon transformation of energy production and consumption, promote carbon emissions reduction in public transport, and strengthen the linkage regulation between effective government and an effective market.

Energy savings and emission reduction benefits of China's aluminum use paths in transport sector.

Background: In China, the transportation sector is the main energy consumer and the main source of carbon emissions. Reducing carbon emissions in the transportation sector is an important goal for China, especially during the current period of economic development. Due to the impact of pandemic shocks, the rapid development of green finance is conducive to supporting the transportation sector in achieving a carbon peak. Thus, we examined whether the development of green finance is still effective under the impact of a pandemic and the actual effect of green finance on the reduction of carbon emissions.Methods: In this study, we searched the internet for consumption structure data of vehicles and green finance indices of 30 Chinese provinces and cities from 2016 to 2021. A regression discontinuity model was constructed to test the effect of pandemic shock and green finance development on the reduction of transportation energy carbon emissions.Results: The results show that the impact of the COVID-19 pandemic has helped people change their preference toward more energy-efficient vehicles and reduce carbon emissions in the transportation sector. Green finance can effectively contribute to the reduction of transportation energy carbon emissions; however, the overall mitigation effect is limited.Conclusion: The empirical evidence is not only helpful in assessing the long-term impact of the COVID-19 pandemic but also conducive to the appropriate establishment of policy tools for supporting green finance development, which is further conducive to reducing carbon emissions in the transportation sector.

Has China achieved synergistic reduction of carbon emissions and air pollution? Evidence from 283 Chinese cities

The emission of greenhouse gases poses enormous pressure on current carbon emissions and carbon reduction. Accurate quantification of carbon emissions from coal-fired power plants is of great significance for achieving the dual carbon goal. To enable enterprises to better understand their carbon emissions, this study constructs a carbon emission model and carbon emission data accounting model for coal-fired power plants. Case data calculations and a carbon emission reduction analysis were conducted. The experiment showcases that the carbon sensitivity of the inner side of the boiler under control conditions is higher than that of the operating parameters controlled on the inner side of the steam turbine, with a maximum total value of 16.67 g/MJ; the annual average low calorific value of coal remains between 16,000 kJ/kg; the activity level of coal remains between 30,000 TJ; and the oxidation probability of coal char during combustion fluctuates, with a maximum of 99.8%. In the calculation of coal-fired carbon emissions, the fitting difference between the emissions of generator unit 1 and generator unit 2 is maintained within 2%. Overall, the CO2 emissions of power plants involved in the study are generally high. The model built through this study has well analyzed the carbon emissions of power plants. It is of great significance for the actual carbon emission reduction of coal-fired power plants.

The Hu-Bao-O-Yu urban agglomeration is an important energy exporting and high-end chemical base in China, and is an important source of carbon emissions in China. The early achievement of peak carbon emissions in this region is particularly crucial to achieving the national carbon emission reduction targets. However, there is a lack of multi-factor system dynamics analysis of resource-dependent urban agglomerations in Northwest China, as most studies have focused on single or static aspects of developed urban agglomerations. This paper analyses the relationship between carbon emissions and their influencing factors, constructs a carbon emission system dynamics model for the Hu-Bao-O-Yu urban agglomeration, and sets up different single regulation and comprehensive regulation scenarios to simulate and predict the carbon peak time, peak value, and emission reduction potential of each city and urban agglomeration under different scenarios. The results show that: (1) Hohhot and Baotou are expected to reach peak carbon by 2033 and 2031 respectively, under the baseline scenario, while other regions and the urban agglomeration will not be able to reach peak carbon by 2035. (2) Under single regulation scenarios, the effect of factors other than the energy consumption varies across cities, but the energy consumption and environmental protection input are the main factors affecting carbon emissions in the urban agglomeration. (3) A combination of the economic growth, industrial structure, energy policy, environmental protection, and technology investment is the best measure to achieve carbon peaking and enhance the carbon emission reduction in each region as soon as possible. In the future, we need to coordinate the economic development, energy structure optimisation and transformation, low-carbon transformation of industry, strengthen research on carbon sequestration technology, and further increase the investment in environmental protection to make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration with an optimal emission reduction.

The impact of human carbon emissions on climate has generated widespread global concern. We selected 24 countries as research objects and analysed the changes in carbon emissions in different countries between the establishment of emission reduction actions in 1990 and 2014. Then, we selected 19 factors representing four categories (economy, population, technology and energy) to explore the key factors that led to changes in carbon dioxide (CO2) emissions in different countries. Emission reduction actions since 1990 did not lead to marked improvements, and only five countries (Russia, Germany, the United Kingdom, Italy and France) achieved reductions in carbon emissions. The factors that influenced CO2 emissions varied among countries. In most developing countries, reductions in CO2 emissions were caused by reductions in poverty and inherent natural conditions. Moreover, the extent of influence of a given factor on CO2 emissions differed among countries. The global economic crisis may cause similar fluctuations in CO2 emissions in many countries. Adjustments to energy and industrial structures are the main reason for the reduction in carbon emissions, whereas economic growth and urbanization are the two major contributors to the growth of carbon emissions. According to historical carbon emissions data, a green energy revolution must be implemented to address global climate change and ensure the sustainable development of human societies.

Faced with increasingly strict carbon emission control, high-emission enterprises need scientific and rational management systems and methods to strengthen carbon emission reduction management. Among the many management systems and methods, the carbon budget has become an effective emission reduction management tool, allowing the planning of carbon emissions and emission reduction activities and rational arrangement of economic inputs. However, judging from the research status and business practices in China and abroad, there is no general carbon budget system to guide the development of carbon emission and emission reduction activities. Based on this background, this paper first attempts to construct an enterprise carbon budget system comprising four sub-budgets: carbon emission, carbon emission reduction and cost, carbon emission rights trading, and carbon emission reduction net profit/loss. It draws on the idea of interactive control to consider the impact of changes in carbon prices, energy prices, and policy guidelines on carbon emission reductions and losses. A carbon budget management system based on interactive control is then constructed and applied to China National Aviation Holding Air China Group (AC Aviation). The research results show that the carbon budget system based on interactive control can dynamically adjust carbon emission reduction behavior based on changes in carbon and energy prices to make carbon budgeting a more viable carbon reduction tool and institutional arrangement.

Strategies for Carbon Reduction

The streetscape of any city reflects the natural built fabric of the street and adds to the experiential quality of that space. A sustainable streetscape ensures that the spaces are long-lasting and functional as a part of the greater sustainable eco-system. Over the past two centuries, mankind has increased the concentration of carbon dioxide (CO2) in the atmosphere from 280 to more than 380 parts per million by volume, and it is still increasing every day. If Earth continues to emit carbon without control, the surface temperature is expected to rise by 3.4 °C by the end of this century. Climate change of that magnitude would likely have serious, long-lasting, and, in many cases, devastating consequences for the planet Earth. Egypt has become one of the biggest emitters of atmospheric pollutants from the transportation sector. The level of carbon emissions and its effect on air quality are placed high on the research agenda. The transportation sector has a great impact on increasing CO2 emissions. The transportation and traffic sectors produce a quarter of the global CO2 emissions due to the heavy use of fossil fuels. This research aims to study the effects of street shape and design on CO2 production. This paper presents an analysis of road transportation in Egypt, taking Helmiet EL-Zaitoun as the main case study, with a focus on energy demand and carbon dioxide (CO2) emissions. Carbon emissions are measured using “Testo 315-3” as a measuring instrument to identify the relationship between street design and quality on the amount of carbon emissions produced. The results of this research suggest that street quality affects the amount of CO2 emissions produced. A car moving at a constant speed will produce fewer CO2 emissions than a car forced to start–stop every while because of external factors such as cracks in the roads occurring from bad streetscape elements. The presented research provides a set of guidelines to enhance the quality of the streetscape and design in order to reduce the amount of CO2 produced in the streets.

Bottom-up social innovations are being used in the transportation sector with unintended outcomes for carbon emission reducing potentials. Activists and policy makers have called for studies on the potentials of such innovations in reducing carbon emissions to aid policy recommendations. This study explores the potentials of such an innovation in the transport sector in Nigeria of reducing carbon emissions. Called Message by users, this social innovation is used like an informal courier service to deliver items of trade, documents and medicine among others using the public transportation system. This social innovation saves users costs of transporting the items themselves using public or private transportation or formal courier services. Data on number of Messages sent was collected by personal observation at a public transport terminal for Ikeja bound passengers from Ile-Ife (towns in southwestern Nigeria) for seven days. Ninety-four Messages consisting of 106 items were observed to be sent at the terminal using the Message system during the period. Two scenarios that may lead to savings in carbon emissions were highlighted in the study; the first, if the sender boards a public transportation vehicle to deliver the item and the second, if private transportation was used rather than the Message system. The round-trip distance for the two options was estimated to be 400 Km. A six-passenger 2-litre engine public transportation vehicle which consumes an estimated 9L/100 Km was assumed for the study. The results showed that for the first scenario, 1,297.2 Kg CO2 will be produced and 7783.2 Kg CO2 for the second scenario if senders had used these alternatives other than the message system for the 94 Messages. The study concludes that the Message can be regarded as a Low-carbon Bottom-up social innovation and recommends public and/or private efforts to scale-up this innovation in other climes.

The transportation sector is the second largest contributor to human-generated carbon dioxide (CO2) emissions. A key goal of the U.S. Department of Transportation is to implement environmentally sustainable policies that can reduce carbon emissions from transportation sources. Smart growth—characterized by compact, mixed use; greater network connectivity; and environments friendly to alternative modes—may encourage reductions in vehicle travel and emissions. A better understanding of travel behavior in conventional and smart growth communities is needed to inform policies. A behavioral data set is analyzed to determine whether smart growth developments are associated with lower CO2 emissions. Sample selection models are estimated from a 2009 travel behavior survey of 15,213 households to capture the conditionality of emissions on the decision to drive (or not) by household members on a given day. Results indicated that 12% of responding households used alternative modes or did not travel from home; the rest of the sample traveled in an automobile and therefore contributed to CO2 emissions. CO2 emissions were calculated from vehicle miles traveled and the fuel efficiency of the vehicle used for specific trips taken by household members. The developed framework models whether CO2 emissions are associated with land use, sociodemographics, and preferences for adopting information technology. Tailpipe CO2 emissions are lower for households that reside in mixed land use neighborhoods with good network connections (on the order of 9%). As a long-term strategy, CO2 emissions reductions from smart growth developments can be substantial.

<p indent=0mm>Cities account for more than 70% of global carbon emissions and play an important role in mitigating climate change and achieving carbon peak and carbon neutrality. As the Paris Agreement emphasizes the need to reach global peaking of greenhouse gas emissions as soon as possible, it is significant to predict carbon emissions at the city level. However, the current COVID-19 pandemic has dramatically impacted global socioeconomic development and carbon emissions, downplaying the reference value for most urban carbon emission prediction models. In fact, existing studies on urban carbon emission prediction have also suffered from some shortcomings, such as unclear analyses of the impact of the pandemic, single scenario prediction, unified setting of growth rates, and failure to provide decision support for the government’s carbon peak work. Therefore, a multi-scenario study on urban carbon emission prediction and carbon peak in the post-pandemic period would provide local governments with scientific data to make their carbon peak action plan. To that end, we set five-carbon emission scenarios: bussiness as usual (BAU), high emissions (HE), extremely high emissions (EHE), low emissions (LE) and extremely low emissions (ELE). Based on the Monte Carlo method, we adjust the probabilities of different periods and different carbon emission scenarios to simulate uncertain evolution of carbon emissions as well as carbon emission reduction. Combining with multi-scenario analyses with the Mann-Kendall trend test and Theil Sen’s trend slope estimation method, we predict carbon emissions of the Pearl River Delta Urban Agglomeration (PRD) from 2021 to 2035 and analyze the evolution path of PRD’s carbon emissions as well as its potential for carbon peak and carbon emission reduction from 2006 to 2035. Discussions are made on the possibility of achieving conditional areas’ carbon peak goal in 2025 in Guangdong and China’s carbon peak goal in 2030. We find that: (1) Carbon emissions of PRD increased rapidly from 2006 to 2016. Dynamic simulation shows that carbon emissions a significant peak in 2020 and decrease to 248.85 M~270.06 Mt in 2035. Carbon intensity decreases by 84.18%–85.21% from 2006 to 2035. Based on the emission reduction of the BAU scenario, the cumulative carbon emission reduction potential of the LE scenario and ELE scenario is as high as 304.86 M and 587.22 Mt from 2021 to 2035. Carbon emission reduction potential based on dynamic simulation of random combination scenario is between −81.68 and 128.25 Mt, with a probability of 67.65% to achieve further emission reduction. The probability of reducing 27.44 Mt carbon emissions is the largest. (2) Shenzhen, Zhuhai, Huizhou and Dongguan are four cities that show an inverted “U” shaped evolution path to achieve carbon peak. All of them reach the carbon peak no later than 2020. From 2006 to 2035, especially after the carbon peak, carbon emissions of these cities will decrease significantly. Their carbon emissions will reduce by 14.15 M–15.40 Mt, 9.17 M–9.94 Mt, 24.07 M–26.08 Mt and 22.36 M–24.24 Mt in 2035, respectively. The cumulative carbon emission reduction potential from 2021 to 2035 is −7.99 M–8.69 Mt, −3.48 M–4.87 Mt, −5.97 M–15.39 Mt and −8.77 M–12.62 Mt, respectively. However, being earlier to reach a carbon peak reduces their carbon emission reduction potential from 2021 to 2035. (3) Guangzhou, Foshan, Zhongshan, Jiangmen and Zhaoqing are five cities that could potentially reach carbon peaks but with divergent evolution paths. Some scenarios are at risk of not reaching a carbon peak. The possibility for Guangzhou, Foshan and Zhongshan to achieve the carbon peak target of conditional areas in Guangdong Province in 2025 is more than 96.01%, while that for Jiangmen and Zhaoqing is less than 20.08%. Moreover, there is a possibility of 2.04% for Jiangmen and Zhaoqing not to reach a carbon peak. In 2035, the emission reduction of the five cities will be 56.90 M–61.87 Mt, 44.35 M–48.16 Mt, 23.92 M–25.91 Mt, 33.78 M–36.58 Mt and 20.15 M–21.88 Mt, respectively. The cumulative carbon emission reduction potential of these cities from 2021 to 2035 is significant, which is −23.75M–26.60 Mt, −17.51 M–<sc>22.17 Mt,</sc> −6.64 M–12.19 Mt, −7.57 M–17.82 Mt and −3.86 M–11.79 Mt, respectively. (4) Being earlier to reach a carbon peak is conducive for cities to reduce carbon emissions. The curve of cumulative carbon emission reduction potential shows that the marginal potential of carbon emission reduction increases with time. So early adoption of emission reduction measures and early realization of carbon peak will promote carbon emission reduction. When making action plans for carbon peak, we should prevent cities from reaching false carbon peak during the platform period, pay attention to the demonstration and acceleration effect of carbon peak cities with relatively high carbon emissions, and explore the carbon emission reduction potential of cities that have difficulties in reaching carbon peak by optimizing their energy structure and utilization efficiency.

长三角城市群碳排放与城市用地增长及形态的关系