A Green Vehicle Routing Optimization Model with Adaptive Vehicle Speed Under Soft Time Window

This study investigates a green multimodal routing problem with soft time window. The objective of routing is to minimize the total costs of accomplishing the multimodal transportation of a batch of goods. To improve the feasibility of optimization, this study formulates the routing problem in an uncertain environment where the capacities and carbon emission factors of the travel process and the transfer process in the multimodal network are considered fuzzy. Taking triangular fuzzy numbers to describe the uncertainty, this study proposes a fuzzy nonlinear programming model to deal with the specific routing problem. To make the problem solvable, this study adopts the fuzzy chance-constrained programming approach based on the possibility measure to remove the fuzziness of the proposed model. Furthermore, we use linear inequality constraints to reformulate the nonlinear equality constraints represented by the continuous piecewise linear functions and realize the linearization of the nonlinear programming model to improve the computational efficiency of problem solving. After model processing, we can utilize mathematical programming software to run exact solution algorithms to solve the specific routing problem. A numerical experiment is given to show the feasibility of the proposed model. The sensitivity analysis of the numerical experiment further clarifies how improving the confidence level of the chance constraints to enhance the possibility that the multimodal route planned in advance satisfies the real-time capacity constraint in the actual transportation, i.e., the reliability of the routing, increases both the total costs and carbon emissions of the route. The numerical experiment also finds that charging carbon emissions is not absolutely effective in emission reduction. In this condition, bi-objective analysis indicates the conflicting relationship between lowering transportation activity costs and reducing carbon emissions in routing optimization. The sensitivity of the Pareto solutions concerning the confidence level reveals that reliability, economy, and environmental sustainability are in conflict with each other. Based on the findings of this study, the customer and the multimodal transport operator can organize efficient multimodal transportation, balancing the above objectives using the proposed model.

Effectively exploring the impacts of urban spatial structures on carbon dioxide emissions is important for achieving low-carbon goals. However, most previous studies have examined the impact of urban spatial structure on total carbon emissions based only on polycentricity. Fine-grained studies on subsectoral carbon emissions and other dimensions of urban spatial structure are lacking. Therefore, our study comprehensively explores the impact of urban dispersion and polycentricity on total carbon emissions and carbon emissions of four subsectors (industry, power, civilian, and transportation) from 2012 to 2017 while considering the effects of city size. Results reveal that the nighttime light data is useful for measuring urban spatial structure, and a polycentric, decentralized urban spatial structure correlates with the reduced total carbon emissions and transportation carbon emissions. Meanwhile, a decentralized urban spatial structure gives rise to lower industrial carbon emissions and civilian carbon emissions, whereas a multicenter urban spatial structure contributes to minimizing carbon emissions from power systems. However, in small and medium-sized cities, urban spatial structure differently affects the total carbon and transportation carbon emissions.

Carbon inequality in residential buildings: Evidence from 321 Chinese cities

Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.

IntroductionPopulation expansion and economic development increased global greenhouse gas emissions, leading to serious environmental degradation. China, the world's largest developing country and promoter of the “Belt and Road Initiative” (BRI), accounts for 28.8% of the world"s total energy carbon emissions. How to reduce energy consumption to achieve the “double carbon” target (i.e., carbon peaking and carbon neutrality) and promote the implementation of Green BRI is still a serious challenge that China needs to face. MethodsWe evaluated China's carbon emissions using three indicators (i.e., total carbon emission, carbon intensity, and carbon emissions effect), and used spatial analysis to reveal the spatial and temporal trends of China's carbon emissions. In addition, the LMDI model was adopted to explore the driving mechanism of carbon emissions, so as to seek a path that can achieve harmonious economic and environmental development, as well as the “double carbon” target.ResultsChina's total carbon emission increased at a rate of 226.12% from 2000 to 2019, while the carbon intensity decreased at a rate of 48.84%. Carbon emission showed a trend of increasing and then decreasing from southwest to northeast. From 2000 to 2019, the total carbon emission, Gross Domestic Product (GDP), population size and total energy consumption are growing in synergy. Economic and population effects are positively related to carbon emissions, while technology effects are negatively related to it, indicating technological innovations contribute to the reduction of carbon emissions.DiscussionSome suggestions were proposed to control carbon emissions with a view to helping policy makers to formulate relevant policies. The findings provide a scientific basis and reference for the country to achieve the “double carbon” target and the low-carbon sustainable development of BRI.

This study examines the nexus between business strategy and carbon emissions by utilising a dataset of U.S. firms from 2007 to 2020. It focuses on two broad types of firms, that is, prospectors and defenders. Regarding carbon emissions, we consider total emissions (Scope 1 & 2), direct emissions (Scope 1) and indirect emissions (Scope 2). The results reveal a significant association between business strategy and total carbon emissions as well as direct carbon emissions. Notably, the results suggest that prospectors, compared to defenders, display higher levels of total and direct carbon emissions. Our findings contribute to the debate on whether prospectors in developed countries mismanage sustainability issues. The study offers valuable insights into the interplay between business strategy and carbon emissions and provides empirical evidence that business strategy is an important determinant of total and direct carbon emissions.

This study takes Kunming City, Yunnan Province, China as the research area, to provide reference basis for revealing the change law of land use structure and energy consumption and carbon emissions in Kunming, optimizing land use structure and realizing the development of low-carbon city. Based on the data of land use structure and energy consumption in Kunming from 1997 to 2017, based on the estimation of total energy consumption carbon emissions, carbon intensity and per capita carbon emissions, the correlation between land use structure and energy consumption carbon emissions in Kunming has been calculated and analyzed in the past 20 years. Results: 1) The total amount of carbon emissions in Kunming has increased significantly in the past 20 years. It increased from 34.46 × 105 t to 95.09 × 105 t, an increase of about 2.8 times. 2) The types of land use with the highest correlation between land use structure and total carbon emissions of energy consumption, carbon emission intensity and per capita carbon emissions are urban and village and industrial and mining land (0.8258), cultivated land (0.8733) and garden land (0.7971) respectively. 3) The correlation between construction land and total carbon emissions is greater than that of agricultural land. Conclusion: There is a close correlation between land use structure and carbon emissions from energy consumption in Kunming.

With the gradual development of a capital city subcenter, numerous residents gradually move to the subcenter, increasing the demand for fresh food. Thus, an adequate supply of fresh food to the subcenter should be guaranteed, while reducing the logistics costs, maintaining the quality and quantity, complying with sustainable development, and cooperating with the city to complete the food basket logistics and distribution. Accordingly, we propose the optimization of logistics distribution paths for fresh products. After field research, we found that the main fresh product distribution point in the Beijing subcenter is the Baliqiao wholesale market, one of Beijing’s vegetable basket projects, and the main distribution targets are large- and medium-sized markets in the subcenter. We optimize a fresh food distribution path model using minimum total cost and carbon emissions as the objective function according to the layout of the subcenter, and the best path is determined using improved ant colony optimization. The optimization results provide a basis for fresh food distribution in the capital city subcenter. We use scientific methods to analyze the travel routes of vehicles transporting fresh products in the subcenter to obtain the best distribution path for logistics companies, aiming to reduce the waste of resources and pollution to the environment by reducing the overall distribution costs and carbon emissions. Therefore, this type of study can benefit logistics companies and the subcenter population while contributing to sustainable development.

Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms

The 3D sand printing (3DSP) technology provides a richer realization path for the sustainable development of the manufacturing industry. It has the advantages of one-time molding, reducing design constraints and machining amount, and easy control of casting dimensional accuracy. Therefore, studying the impact of process parameters of the printing process on printing efficiency, resource consumption, and carbon emissions is the basis for the sustainable development of 3DSP technology. In this paper, starting from the main influencing parameters such as printing layer thickness, recoater speed, printing angle, and single printing quantity, a relationship model between printing parameters and carbon emission sources is constructed. A total factor carbon emission prediction model of 3DSP process including the impact of capital and labor is established. Build an influence relationship with printing parameters as independent variables and carbon emissions as dependent variables. Taking the sand casting industry as an example to verify the above model, the experimental results show that the thickness of the printing layer has the greatest impact on carbon emissions. When the layer thickness is 0.36 mm, the speed of the recoater is 0.22 m/s, the printing angle is (0°, 0°, 90°), and the single print quantity is 84, the total carbon emission is the lowest and 28.77% less compared to the parameter with the highest carbon emission. The average relative error of the predictive model is 1.929%. The results of this study can provide some new ideas for sustainable development of additive manufacturing technology.

PDF HTML阅读 XML下载 导出引用 引用提醒 我国城市发展与能源碳排放关系的面板数据分析 DOI: 10.5846/stxb201911292591 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学重点基金项目（71533005）；国家重点研发项目（2017YFF0207303） The impact of urbanization on carbon emissions: Analysis of panel data from 158 cities in China Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:城市化与城市能耗及其碳排放密切相关，城市发展过程中的人口城市化进程和产业总量与结构调整都是能源碳排放变化的主要驱动因素。以2006-2015年全国158个地级城市的面板数据为基础，从总量变化趋势和空间变化趋势两个角度分析了研究期内的我国城市发展特征及能源碳排放特征；并利用面板计量分析方法研究了城市发展因素对城市总能耗、总能耗碳排放、单位能耗碳排放量的驱动特征。结果表明：城市化每提升0.095%，总能耗上升1%。虽然城市总能耗及能耗碳排放在降低，但是单位能耗碳排放在增加；第二产业和第三产业发展对总能耗及能耗碳排放的驱动作用大；城市第三产业的发展有利于能源结构优化调整等；并基于研究发现给出一些政策建议。 Abstract:Urbanization is closely related to urban energy consumption and associated carbon emissions. The process of population urbanization and industrial structure adjustment in urban development are the main drivers of changes in carbon emissions. Based on the panel data of 158 prefecture-level cities in China from 2006 to 2015, this study analyzes the urban development characteristics and energy carbon emission characteristics of China from total volume and spatial variation. The study uses panel measurement to analyze the driving characteristics of urban development factors on total urban energy consumption, total carbon emissions, and carbon emissions per unit energy consumption. The results show that for every 0.095% increase in urbanization, the total energy consumption increases by 1%. Although the total urban energy consumption and carbon emissions are decreasing, the carbon emissions per unit energy consumption are increasing. The total energy consumption of secondary and tertiary industries is also increasing. The development of tertiary industries in the city is beneficial for the optimization and adjustment of the energy structure. Based on the findings, some policy suggestions are proposed. 参考文献 相似文献 引证文献

Hydropower is the largest renewable source of electricity generation, the carbon emissions of which have attracted a lot attention. However, the system boundaries of existing studies are either incomplete or inaccurate. Therefore, this study provides a systems accounting framework for evaluating both the direct and indirect carbon emissions from a hydropower plant. It is based on the hybrid method as a combination of the process analysis and the input-output analysis. To demonstrate the framework, a case study for a typical pumped storage hydropower plant (NPSHP) is carried out. The total carbon emissions are estimated as 5828.39 kt in the life-cycle of the case system. The end-of-use stage causes the largest carbon emissions (38.4%), followed by the construction stage (34.5%), the operation stage (25.6%), and the preparation stage (1.5%). The direct carbon emissions are mainly released from sediments in the end-of-use stage and the surface of reservoirs in the operation stage (94.8%). The indirect carbon emissions are 2.8 times higher than the direct carbon emissions. The material, machinery, energy, and service inputs respectively account for 7.1%, 14.7%, 15.9%, and 62.3% of the total indirect carbon emissions by the case system. The indicator of EGOC (electricity generation on carbon emission) for the NPSHP is calculated as 26.06 g CO2-eq./kWh, which is lower than that of most other power plants.

As global climate change continues to accelerate,the frequency and intensity of forest fires continue to grow.Forest fires,which play an important ecological role in forest ecosystems,have a very significant effect on carbon emissions and carbon sinks,and also play an important role in the carbon cycle. Although the impact of forest fires on carbon emissions has been analyzed in detail,studies that scientifically and accurately measure carbon and carbonaceous gas emissions from forest fires are lacking. Carbon dioxide( CO2) emissions from temperate forest fires are usually calculated based on Intergovernmental Panel on Climate Change guidelines( IPCC 1997) and only include direct effects of burning.Forest fires have been shown to release significant amounts of carbon into the atmosphere and play a significant role in theglobal carbon cycle and carbon balance. In this study,we estimated the level of emissions from forest fires for carbon and carbonaceous gases including CO2,carbon monoxide( CO),methane( CH4),and non-methane hydrocarbons( NMHC)from 1953 to 2012 in Heilongjiang Province,China. We used a geographic information system based modeling approach to simulate emissions using a two-step procedure. First,we calculated total carbon released from forest fires in Heilongjiang for selected years between 1953 and 2012 by merging and analyzing measurements of several parameters. Second,we calculated the amounts of four carbonaceous gases released during the burn,CO2,CO,CH4,and NMHC,using several different experimentally derived emission factors. The origin of each of the inputs used in our models was based on a combination of analysis of forest fire inventory,forest resources inventory,field research,and laboratory experiments.Direct total carbon emissions from forest fires in Heilongjiang during 1953—2012 were about 5. 88×107t,and mean annual carbon emissions were about 9. 80 ×105t per year,accounting for 8. 66% of the direct total carbon emissions from forest fires in China. Carbon emissions of four trace gases,CO2,CO,CH4and NMHC,from forest fires were 1. 89×108,1.06×107,6.33×105and 4. 43×105t,respectively; mean annual emissions of CO2,CO,CH4and NMHC were 3. 15×106,1.77×105,1.05×104and 7. 38×103t,respectively,accounting for 7. 74%,6. 52%,9. 42% and 6. 53% of the amounts of CO2,CO,CH4and NMHC released from forest fires in China,respectively,during that period. Our results indicate that combustion efficiency of coniferous broad-leaved mixed forest is lower than other forest types. The mean annual burned area for this type of forest accounts for 57. 54% of China's total burn area,while this area's fires account for only 38. 57% of carbon total emissions from forest fires. We propose the following forest fire management strategy. First,our studies show that the area's mean annual forest fire carbon emissions have an important impact on the regional carbon balance. So,we suggest strengthening the management of forest fuels( fine fuels,heavy fuels,etc.) as part of the regional forest fire management strategy. Fuels on the ground do not decompose easily in Heilongjiang's cold and dry temperate forests. Land managers should implement a reasonable prescribed burning plan designed to reduce the accumulation of combustible fuels.A policy for conducting periodic prescribed burning will reduce the incidence of forest fires. Prescribed burning should help land managers to control and limit the incidence and intensity of wildfires while allowing them to improve the condition of the ecosystem. Finally,we should give full consideration to the role of forest fires in maintaining the ecological balance of forest ecosystems.

This study investigates a green intermodal routing problem considering carbon tax regulation and a mixed (combined soft and hard) time window to improve cost- and time-effectiveness and promote carbon emission reduction in intermodal transportation. To enhance the feasibility of problem optimization, we model the uncertainty of both the carbon tax rate and the intermodal network capacity in the routing problem. By using interval fuzzy numbers to formulate the twofold uncertainty, an interval fuzzy linear optimization model is established to address the problem optimization, in which the optimization objective of the model is to minimize the total costs (consisting of transportation, time, and carbon emission costs). Furthermore, we conduct crisp processing of the proposed model to make the problem solvable, in which the optimization level, a parameter whose value is determined by the receiver before solving the problem, is introduced to represent the receiver’s attitude towards the reliability of transportation. We present a numerical experiment to verify the feasibility of the optimization model. The sensitivity analysis shows that the economics and environmental sustainability of the intermodal routing optimization conflict with its reliability. Improving the reliability of transportation increases both the total costs and the carbon emissions of the intermodal route. Furthermore, through comparison with deterministic modeling, the numerical experiment shows that modeling the twofold uncertainty can cover the different decision-making attitudes of the receiver, provide intermodal routes that are sensitive to the optimization level, enable flexible route decision-making, and avoid unreliable transportation. Through comparison with hard and soft time windows, the numerical experiment proves that the mixed time window is more applicable for problem optimization, since it can obtain the intermodal route that yields improved economics and environmental sustainability and simultaneously satisfies the receiver’s requirement for timeliness. Through comparison with the green intermodal route aiming at minimum carbon emissions, the numerical experiment indicates that carbon tax regulation under an interval fuzzy carbon tax rate is not feasible in all decision-making scenarios where the receivers have different attitudes regarding the reliability of transportation. When carbon tax regulation is infeasible, bi-objective optimization can provide Pareto solutions to balance the objectives of reduced costs and lowered carbon emissions. Finally, the numerical experiment reveals the influence of the release time of the transportation order at the origin and the stability of the interval fuzzy capacity on the routing optimization in the scenario in which the receiver prefers highly reliable transportation.

This article estimated the size of carbon sink, emission, net carbon farmland ecosystem in China costal regions (including ten provinces) with statistic data from 1990 to 2010(which include crop yield and agricultural consumptions). Conclusions are as following: (1) the total carbon sink, emission and net of farmland ecosystem in China costal regions all increased since 1990. Carbon is obviously more than carbon emission, for example, total carbon in 2010 is 3 times more than carbon emission, which showed that the costal region is generally a sink region. While, because the increasing rate of carbon emission (265%) exceeded that of carbon (44%), the carbon function of farmland ecosystem in China costal regions will be saturated within several decades. (2) There were significant temporal-spatial differences in carbon sink, emission and net among different costal regions. Further, there are also differences in per area carbon sink, emission and net among different costal regions. The total and per area carbon emission increased year by year from 1990, while that of carbon and net changed drastically. The total carbon and net in relative developed regions has a down trend from 1990 to 2010. a special example: carbon emission exceeded carbon and caused that net carbon and per area net carbon was negative in 2010 in Shanghai, which indicated that Shanghai has been a carbon source region in 2010 because the decrease of cropland and increase of agricultural consumptions. (3) The proportion of carbon sinks in the main crops of farmland ecosystem in China costal regions compared with that of the whole nation decreased since 1990, which indicate that with the decrease of cropland and increase of agricultural consumptions, the carbon function of costal farmland is weaken.