Consideration Of Carbon Emissions Research Articles

Green Order Sorting Problem in Cold Storage Solved by Genetic Algorithm

This study investigates the efficiency of cold storage warehouses and contributes to sustainable supply chain management by integrating eco-friendly practices into storage operations. In facilities for milk and its derivatives, unregulated order handling significantly increases energy consumption due to frequent door openings in the cooler. To address this challenge, we developed a novel mathematical model aimed at optimizing order sequences and minimizing energy costs, addressing a previously unexplored gap in the literature. A genetic algorithm (GA) was employed to solve this model, with careful consideration of carbon emissions generated during the algorithm’s execution. We utilized the Yates notation, an experimental design technique, to systematically optimize the GA’s parameters, ensuring robust and statistically valid results. This methodology enabled a thorough analysis of the factors influencing energy consumption. The findings enhance energy efficiency in cold storage warehouses, leading to reduced carbon dioxide emissions and fostering sustainable practices within supply chain management. Ultimately, this study successfully integrates green practices into cold storage operations, supporting broader sustainability objectives.

Cold Chain Distribution Route Optimization for Mixed Vehicle Types of Fresh Agricultural Products Considering Carbon Emissions: A Study Based on a Survey in China

With the improvement of people’s living standards and the widening of circulation channels, the demand for fresh agricultural products continues to increase. The increase in demand will lead to an increase in delivery vehicles, costs, and carbon emissions, among which the increase in carbon emissions will aggravate pollution and is not conducive to sustainable development. Therefore, it is very important to balance economic and environmental benefits in the distribution of fresh agricultural products. Based on the analysis of the distribution characteristics of fresh agricultural products, this paper studies the optimization of the cold chain distribution route of fresh agricultural products considering carbon emission. Firstly, the cold chain distribution route planning of fresh agricultural products was investigated and analyzed by the interview method, and the basis for establishing the model objective and constraint conditions was obtained. Then, taking the minimum total cost including carbon emission cost as the optimization goal, the cold chain distribution route optimization model for mixed vehicle types is established considering electric refrigerated vehicles, gasoline refrigerated vehicles, and so on. Genetic algorithm was used to solve the model, and MATLAB2018b was used to substitute specific case data for simulation analysis. The analysis results show that increasing the consideration of carbon emission and mixed vehicle types in the distribution route of fresh agricultural products can not only reduce the distribution cost but also reduce the carbon emission. To some extent, the research content of this paper can provide a reference for enterprises in planning cold chain distribution routes of fresh agricultural products.

Prediction of hydrogen consumption scale and hydrogen price based on LEAP model and two-factor learning curve

Under the dual-carbon target, hydrogen energy, as a zero-carbon secondary energy source, has great scope for replacing fossil feedstocks in the fields of energy, transportation and industry. However, the current research on the competitiveness of hydrogen energy in various fields is not sufficiently addressed. In this paper, we use the LEAP model to predict the future scale of hydrogen use and the two-factor learning curve to predict the trend of hydrogen price change from 2025 to 2050, using Qinghai Province as the research background. At the same time, considering the carbon emission reduction benefits and raw material costs, the competitiveness of hydrogen energy in energy, transportation, industry and other fields in the future is compared. The results show that: 1) The hydrogen load scale in Qinghai Province will grow fast from 2025 to 2030. From 2030 to 2040, it slows under the steady and basic scenarios but remains high under the accelerated one. By 2040, the consumption scales are 1.057 million, 649,000 and 442,000 tons respectively. 2) The price of hydrogen energy will drop rapidly from the current 28 CNY/kg to about 20 CNY/kg in the next 5 years. By 2040, the price of hydrogen energy will be reduced to about 17 CNY/kg. 3) In terms of hydrogen energy competitiveness, when carbon emissions are not taken into account, hydrogen energy is currently competitive in the transportation field. During 2032–2038, it will be competitive in the field of methanol synthesis. By 2040, hydrogen energy will not be competitive in the fields of ammonia synthesis and power/heating. When considering carbon emissions, the competitiveness of hydrogen energy in the transportation field will become greater. The competitive year in the field of methanol synthesis will be 1–2 years ahead. By 2040, it will not be competitive in the field of synthetic ammonia and power/heating, but the gap will be significantly reduced due to the consideration of carbon emissions.

A Consideration of Whole-Life Carbon Emissions by Indiana Manufacturers in Efforts to Gauge Lifecycle Sustainability Records in the Multinational Automobile Industry

Purpose: The Ricardo Report (2020) recommends a holistic analysis of the effects of the global auto industry on sustainability by assessing the impacts of automobiles on the environment throughout their lifecycle. Much of the literature on sustainability in the transportation sector focuses on vehicle exhaust emissions and their contribution to urban smog, and there has been little consideration of emissions produced during the automobile manufacturing process itself. 
 Materials and Methods: This study builds on the lifecycle emissions approach recommended by the Ricardo Report. Specifically, data on the pounds of pollution emitted was collected from the Toxic Release Inventory report of major multinational automobile producers and analyzed via piecewise linear regression analyses to provide insight about the pollution emitted during a vehicle’s production. 
 Findings: The findings in this study will fill a gap in Ricardo’s “birth to grave” proposal to quantify whole-life carbon emissions in the automobile sector.
 Unique Contribution to Theory, Practice and Policy: As sustainability efforts within the automotive market continues to evolve, it is important to analyze automobile whole-life carbon emissions rather than just what is emitted from the tailpipe, and this study fills a gap in the Ricardo Report by providing data related to the rates of pollution emitted during the manufacture of vehicles at multinational automobile factories in America.

Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles

In order to achieve the goal of low-carbon, efficient delivery using unmanned vehicles, a multi-objective optimization model considering carbon emissions in the problem of optimizing multi-route delivery for unmanned vehicles is proposed. An improved genetic algorithm (IGA) is designed for solving this problem. This study takes into account constraints such as the maximum service duration for delivery, the number of vehicles, and the approved loading capacity of the vehicles, with the objective of minimizing the startup cost, transportation cost, fuel cost, and environmental cost in terms of the carbon dioxide emissions of unmanned vehicles. A combination encoding method based on the integer of the number of trips, the number of vehicles, and the number of customers is used. The inclusion of a simulated annealing algorithm and an elite selection strategy in the design of the IGA enhances the quality and efficiency of the algorithm. The international dataset Solomon RC 208 is used to verify the effectiveness of the model and the algorithm in small-, medium-, and large-scale cases by comparing them with the genetic algorithm (GA) and simulated annealing algorithm (SA). The research results show that the proposed model is applicable to the problem of optimizing the multi-route delivery of unmanned vehicles while considering carbon emissions. Compared with the GA and SA, the IGA demonstrates faster convergence speed and higher optimization efficiency. Additionally, as the problem’s scale increases, the average total cost deviation rate changes significantly, and better delivery solutions for unmanned vehicles are obtained with the IGA. Furthermore, the selection of delivery routes for unmanned vehicles primarily depends on their startup costs and transportation distance, and the choice of different vehicle types has an impact on delivery duration, total distance, and the average number of trips. The delivery strategy that considers carbon emissions shows a 22.6% difference in its total cost compared to the strategy that does not consider carbon emissions. The model and algorithms proposed in this study provide optimization solutions for achieving low-carbon and efficient delivery using unmanned vehicles, aiming to reduce their environmental impact and costs. They also contribute to the development and application of unmanned vehicle technology in the delivery field.

Towards Sustainable Two Warehouse Inventory Management: Flexible Payments and Demand-Driven Optimisation with Preservation Technology and Carbon Emission Considerations

Towards Sustainable Two Warehouse Inventory Management: Flexible Payments and Demand-Driven Optimisation with Preservation Technology and Carbon Emission Considerations

Location-pricing decisions with carbon emission considerations: A behavioral game-theoretic approach

The location-pricing problem aims to solve pricing and facility location problems at the same time. While the demand of customers is known in the classical facility location problem, it is a function of price in the location-pricing problem. Moreover, some other factors, such as production, transportation and inventory costs, and competition, can affect the final price of products, making the location-pricing problem more complicated. Considering the necessity of incorporating environmental aspects into supply chain design and the importance of considering the behavioral characteristics of decision-makers, this study addresses the location-pricing problem based on these two significant perspectives. In this paper, there is a lead company responsible for locating and planning a set of manufacturers in the first echelon. On the other hand, the focal manager controls the total emissions and sets the wholesale price. In the second echelon, there are two retailers that base their pricing strategies on social preferences in order to gain a larger market share. The competition between the retailers determines the demands of the customers. The modeling approach is based on the Stackelberg-behavioral Nash game and is formulated as a bi-level mixed-integer nonlinear programming model. The problem is solved using a combination of an analytical solution method and the utilization of a commercial optimization solver. The proposed model is assessed using a real case study in the energy sector. The results indicate that deviating from purely selfish behavior in the pursuit of profit can lead to beneficial outcomes. Generally speaking, price competition between status-seeking retailers results in lower prices for the leader and followers compared to the standard game theory approach. This leads to an increase in average demand in the market, which results in increased profit for members and consequently improves the performance of the whole system. Also, it is worth mentioning that the status-seeking behavior of retailers results in a decrease in retail prices, which improves social welfare.

Optimization of multimodal transportation path selection under low-carbon and time-schedule situation

Multimodal transportation has improved the effectiveness and efficiency of the transport and logistics industry. Unifying a transport unit and selecting a reasonable transport plan dramatically save both time and cost of delivery. Considering that time schedules exist in marine and airline logistics, more and more focus on the sustainability of the transport industry and the special need time-sensitivities cargos, this paper will establish an optimization model with the goal of minimizing the total cost of transportation, which is the combination of transport cost, time efficiency and consideration of carbon emission. The genetic algorithm will be used to solve the problem in this article. The effectiveness of this model is proved to be effective through the application of the case study, and the study results can provide support in decisioning a multimodal transport plan.

Optimum Design of an Electric Vehicle Charging Station Using a Renewable Power Generation System in South Korea

In the context of global warming and fossil fuel depletion, electric vehicles (EVs) have become increasingly popular for reducing both carbon emissions and fossil fuel consumption. However, as the demand for EV charging power rises along with the expansion of EVs, conventional power plants require more fuel, and carbon emissions increase. This suggests that the goal of promoting EV adoption to mitigate climate change and reduce reliance on fossil fuels may face significant challenges. Therefore, there is a need to adopt renewable energy generation for EV charging stations to maximize the effectiveness of EV distribution in an eco-friendly way. This paper aims to propose an optimal renewable energy generation system for an EV charging station, with a specific focus on the use of an actual load profile for the station, the consideration of carbon emissions and economic evaluation, and the study of a specific case location in Korea. As a case study, an EV charging station in Korea was selected, and its renewable energy fractions (REF) of 0%, 25%, 50%, 75%, and 100% were considered for comparison of carbon emissions and economic evaluation with the help of HOMER software. In addition, the system with 25% REF was analyzed to find the best operating strategy considering the climate characteristics of the case site. The results show that the system configuration of PV/ESS is the most economical among all the REF cases, including PV, WT, and ESS, due to the meteorological characteristics of the site, and that the system with REF below 25% is the most optimal in economic terms and carbon emissions.

Study on the Optimization of the Material Distribution Path in an Electronic Assembly Manufacturing Company Workshop Based on a Genetic Algorithm Considering Carbon Emissions

In order to solve the problems of high carbon emissions, low distribution efficiency and high costs related to the process of material distribution in manufacturing workshops, a multi-objective workshop material distribution path optimization problem model is established, and the model is solved using an improved genetic algorithm. The problem is processed using Gray code and crossover and variation operations with a genetic algorithm. To improve the search accuracy and convergence speed of the algorithm, an adaptive mutation method is proposed to enhance the diversity of the population and to achieve global optimal path objective finding. The improved algorithm is applied to workshop path multi-station logistics path planning, which effectively solves the transport path optimization and station solving problems in workshop logistics distribution, and the convergence speed and convergence accuracy of the algorithm are significantly improved. Finally, a simulation analysis is carried out on the optimization of the production material distribution of a smart gas meter workshop owned by K Company, which is an electronic assembly manufacturing company. We used MATLAB software for the case company logistics distribution route model for data analysis and solving. Due to the consideration of carbon emissions, we did not consider two kinds of experiments, which were two different cases of the optimal path. The experimental results verify that the distribution optimization scheduling model can meet the demands for immediate material distribution in the production workshop, which is conducive to improving material distribution efficiency, reducing logistics costs and achieving the goal of lowering carbon emissions. This optimization model has a certain utility in that in the current context of aiming for carbon neutral and carbon peaking, early low carbon distribution layout can reduce the environmental cost of the enterprise, making material distribution a more environmental economic path.

Ecological sustainability and high-quality development of the Yellow River Delta in China based on the improved ecological footprint model

Aiming at the traditional ecological footprint model, the improved ecological footprint of the carbon footprint effectively makes up for the singularity of the ecological footprint's consideration of carbon emissions, and plays an important role in promoting high-quality development and ecological sustainability. This paper selects 2015, 2018 and 2020 as important time points for the study, corrects the ecological footprint parameter factors based on net primary productivity (NPP), measures the ecological footprint after the improvement of the carbon footprint, studies the spatial and temporal variation in the ecological footprint at the 100-m grid scale with the support of IPCC greenhouse gas inventory analysis, and analyzes the current ecological conservation status of the Yellow River Delta. Additionally, in the context of a low carbon economy, the decoupling index of carbon emissions and GDP is extended to the evaluation and analysis of high-quality development. The study showed that (1) the ecological footprint of the Yellow River Delta has increased year by year, from 0.721 hm2·person− 1 to 0.758 hm2·person− 1, an average annual increase of 2.9%; the ecological carrying capacity has decreased from 0.40 hm2·person− 1 to 0.31 hm2·person− 1, an overall decrease of 28.59%. (2) The overall ecological deficit of the Yellow River Delta grid is lightly overloaded, with most of the ecological surplus occurring in the northern and eastern parts of the study area and a few moderate and heavy overloads in the center of the core area where there is a lot of built-up land and the area is small and easy to gather. (3) Based on the low-carbon economy analysis, 2015, 2017 and 2020 reach absolute decoupling and are in the ideal scenario. However, in the rest of the years, carbon emissions and economic development are still in a large contradiction, and decoupling has fluctuated and varied greatly in the last six years. The effective combination of ecological footprint and low carbon economy analysis provides an important theoretical basis for improving ecological conservation and achieving high-quality development.

Technical note on “Inventory management in supply chains with consideration of Logistics, green investment and different carbon emissions policies”

This study presents an extension of the model proposed by Huang et al. (2020), which investigated the effects of carbon policies and green technologies on the integrated inventory management of a two-echelon supply chain with consideration of carbon emissions during the processes of production, transportation, and storage. Specifically, since the inventory policy impacts on the economic and environmental performances of the supply chain, this study proposes a mathematical model for the integrated inventory management of the single-vendor single-buyer supply chain under a consignment stock policy. The aim is, thus, to highlight advantages and disadvantages of the consignment stock agreement with respect to the traditional policy based on the model proposed by Hill (1999). To compare the results, the same three carbon emissions policies are considered: i.e., limited total carbon emissions, carbon taxation, and cap-and-trade. The proposed model can assist firms in determining their optimal inventory policy (i.e., agreement, production quantity, delivery quantity, and green investment amount) with an aim of minimizing the supply chain costs under different carbon emissions policies.

Design of low-carbon and cost-efficient concrete frame buildings: a hybrid optimization approach based on harmony search

ABSTRACT The development of sustainable building structures has been a crucial measure for carbon reduction. With consideration of both carbon emissions and costs, the sustainable design of building structures is complicated and time consuming for designers. To simplify the process of sustainable design optimization, the present study proposes a multi-objective harmony search algorithm for the design of concrete frame buildings considering low-carbon and cost-efficient requirements. This hybrid method combines structural analysis with local component optimization. Process-based life cycle assessment was used to identify carbon-intensive and high-cost structural members, and these members were optimized using discrete design variables and complicated constraints. Furthermore, a case study was conducted on a four-story frame building, in which the embodied emissions and costs were estimated as 1270.91 tCO2e and 0.67 million USD in the initial design scheme. Beams were identified as the optimization target for this building, and a set of Pareto-optimal solutions was obtained, indicating potential emission and cost reductions of 17.9% and 12.3%, respectively, compared with the initial designs. This study provides an easy and practical approach for the sustainable design of concrete frame buildings and enables designers to better understand building structural optimization from an economic and low-carbon perspective.

Optimal economic growing quantity for reproductive farmed animals under profitable by-products and carbon emission considerations

Some agricultural industries such as livestock and poultry farming produce “growing items” whose weight and value constantly increase over time. Growing items and their related industries are vital in supplying the needed food and fiber for the world population. More importantly, concerns for the preservation of natural resources have led to sustainable goals of reducing greenhouse gas emissions (GHGEs) released by growing items. Recently, an inventory system called “economic growing quantity (EGQ)” was designed for growing items. This paper designs, develops, and optimizes a sustainable model for EGQ system, entitled “sustainable EGQ (SEGQ)”, where the hidden costs and revenues associated with the sustainability of growing items are considered under a carbon tax policy. The cost function incorporates purchasing, transportation, feeding, shortage, setup, holding, and carcass disposal costs as well as the tax costs of greenhouse gas (GHG) emitted from manure, feed fermentation, carcasses, holding and transportation processes. The revenue function takes the earned income from the sale of grown items as well as their byproducts into account. Accordingly, a nonlinear program (NLP) is developed to maximize the total profit. The novelty of this paper resides in its consideration of the reproductive patterns and byproducts of growing items, gradual sales, shortage costs, major sources of GHGEs and their hidden costs, and finally a design of the main variables to mitigate the GHGs emitted by the growing items. Findings demonstrate that the SEGQ model with reproducible items and profitable byproducts increases the growth cycle and decreases the quantity of growing items needed at the start of the inventory cycle.

A three-dimensional ant colony optimization algorithm for multi-compartment vehicle routing problem considering carbon emissions

A three-dimensional ant colony optimization algorithm (TDACO) is proposed to solve the multi-compartment vehicle routing problem (MCVRP) arising in many industries, such as petrol station replenishment, cold chain logistics, and waste collection. The objective of this problem to be minimized is the total transportation cost including the consideration of carbon emissions (TC_CE). In TDACO, a new three-dimensional pheromone concentration matrix is first presented to learn and accumulate the valuable information from excellent individuals or ants. Then, to make the algorithm have high-quality search in the initial stage, five heuristic rules are designed to initialize the pheromone concentration matrix and construct the initial population or colony. In addition, the vehicle capacity rate and carbon emissions are brought into the state transition rule to reasonably guide the global search towards the promising solutions or regions. Moreover, an adaptive local search with the speed-up search strategy and the first move strategy is devised to perform effective exploitation from the promising regions. Finally, comparative experiments on benchmark problem instances with different scales are conducted, and the superior performance of the proposed TDACO is verified.

Life cycle assessment for carbon emission impact analysis for the renovation of old residential areas

Urban residential buildings are the prime contributors to carbon emissions, whose reduction is significantly affected by old residential areas as essential components of urban renewal. In current studies on the potential for carbon reduction in residential localities, the measurement standard mostly used is the amount of carbon reduced during operations because of the energy-saving renovation of building monomers. This study conducted a life cycle assessment for the carbon emission impact analysis of the renovation of old residential areas, with a comprehensive consideration of carbon emissions at the materialization, demolition, and use stages of the renovation process. Five systems in these areas were evaluated: landscape greening, building monomers, water resources, solid waste, and infrastructure. An actual residential renovation case was used as a reference in comparing the life cycle carbon reduction effects of different technical measures. The results showed that carbon reduction effects are overestimated by 5.54% (from 29.59% to 35.13%) when embodied carbon is disregarded. Among the renovation measures, adding green spaces, recycling garbage, and replacing energy-saving lamps in public areas offer short carbon payback, whereas the addition of rooftop solar photovoltaic panels is the most efficient carbon-reduction measure. This study completes and expands the scope of accounting for residential renovation from spatial and temporal scales. It can also guide the low-carbon renovation of old residential areas to help cities save energy and reduce emissions.

Modeling of a carbon emitted production inventory system with interval uncertainty via meta-heuristic algorithms

Modeling of a production inventory system under uncertain economic situation is a difficult task. Tackling this difficulty, the proposed work attempts to formulate a production inventory model with time dependent defective rate, greenness of the product dependent demand and production rates under interval uncertainty. Consideration of carbon emission during the production with interval valued time dependent emission rate is also an important feature of the proposed model. Furthermore, reduction technology is taken into the account for reducing the large scale of carbon emission. The proposed model is formulated mathematically with the help of interval differential equations and interval parametric approach. Thereafter, various interval valued cost components as well as average profit related to the model are obtained using interval mathematics. To handle the interval valued average profit, center-radius technique of interval optimization is applied. To verify the validity of the developed model, four numerical examples are considered and solved by meta-heuristic algorithms. Also, sensitivity analyses are carried out on the best found policy with respect to different system parameters of this model.

Synthesis of heat exchanger network with complex phase transition based on pinch technology and carbon tax

The aim of this paper is to integrate carbon emissions into the synthesis of heat exchanger network for an industrial process with a four-stage pyrolysis gas compression cycle and depropanizers. Problem table is used to determine the pinch point for the design of heat exchanger network. Due to the complex phase transition of the mixture in the system, the phase transition is considered as a pseudo-stream with constant heat capacity flow rate according to its thermal load and material characteristics within several individual temperature intervals. The contribution of carbon tax is also introduced to the total annual cost to determine the suitable minimum approach temperature(△Tmin). Compared with traditional pinch point method, △Tmin is determined as 8°C instead of 9°C due to the consideration of carbon emission. The pinch point is obtained at 80.15°C for hot streams and 72.15°C for cold streams, under which the minimum hot and cold utilities required by the heat exchanger network are 28046.89 kW and 69324.05kW respectively. The total annual cost is saved by 4,446,559 USD.a−1 and the carbon emission is reduced by 96689.31t/a. Results indicate that the consideration of carbon emissions based on carbon tax is helpful to obtain a better heat exchanger network in terms of total annual cost and energy efficiency on the way to carbon neutrality.

Design a sustainable supply chain for the textile and clothing industry with consideration of carbon emissions

The clothing industry accounts for nearly 60% of the global textile industry. It is largely responsible for the consumption of non-renewable resources. According to studies, it is responsible for nearly 10% of greenhouse gas emissions in the world (Cuc and Vidovic (2014)). The aim of this article is to propose a planning approach that integrates two decision levels (strategic and tactical), using a new mixed integer linear programming model (MILP) that integrates carbon emissions in SCMP (Supply Chain Management Planning). This approach must be used in a general way in all SCMP industries for the control of carbon flows and resources. It could be used as a decision support tool to evaluate and monitor the effects of carbon emissions. This tool offer to the industrials the best choices at different stages (selection of suppliers, plants, transportation modes, storage etc.), with lower cost and carbon emissions. For this purpose, the approach is tested on several scenarios, based on severals literature case studies in the textile and clothing sectors. The results show that carbon price uncertainty would significantly influence the economic and environmental management of the supply chain, and the repartition of the manufacturing activity (insource or outsource). Over a range of carbon price scenarios, the results show a reduction over to 36% in carbon emissions in the supply chain.

Quantification of Building Carbon Emissions in China a Using Hybrid LCA Model

During their life cycle, buildings not only consume a lot of resources and energy, but also produce a large amount of carbon emissions, which have a serious impact on the environment. In the context of global emissions reduction, the trend has been to low carbon buildings. As a major carbon emitting country, it is urgent to promote emission reduction in the construction industry and to establish a model for carbon emissions and calculation in buildings. To this end, this paper collates life cycle carbon emission calculation methods based on life cycle theory and establishes a mixed life cycle carbon emission calculation model for buildings to provide ideas for low carbon buildings in China. A case study of a hospital in Guangming City, Anhui Province is also conducted to verify the feasibility of the model. The results show that the total carbon emission of the hospital is 43283.66 tCO2eq, with the production phase, construction phase, use and maintenance phase and end-of-life phase accounting for 9.13%, 0.35%, 90.06% and 0.46% of the total carbon emission respectively. An analysis of the factors influencing carbon emissions at each stage is presented, and recommendations are given for corresponding emission reduction measures. The carbon emission calculation model based on the hybrid LCA proposed in this study enables a more comprehensive consideration of carbon emissions in the life cycle of a building, and has implications for the study of building carbon emission calculation.