The Role of the Discount Policy of Prepayment on Environmentally Friendly Inventory Management

Nowadays, more and more consumers consider environmentally friendly products in their purchasing decisions. Companies need to adapt to these changes while paying attention to standard business systems such as payment terms. The purpose of this study is to optimize the entire profit function of a retailer and to find the optimal selling price and replenishment cycle when the demand rate depends on the price and carbon emission reduction level. This study investigates an economic order quantity model that has a demand function with a positive impact of carbon emission reduction besides the selling price. In this model, the supplier requests payment in advance on the purchased cost while offering a discount according to the payment in the advanced decision. Three different types of payment-in-advance cases are applied: (1) payment in advance with equal numbers of instalments, (2) payment in advance with a single instalment, and (3) the absence of payment in advance. Numerical examples and sensitivity analysis illustrate the proposed model. Here, the total profit increases for all three cases with higher values of carbon emission reduction level. Further, the study finds that the profit becomes maximum for case 2, whereas the selling price and cycle length become minimum. This study considers the sustainable inventory model with payment-in-advance settings when the demand rate depends on the price and carbon emission reduction level. From the literature review, no researcher has undergone this kind of study in the authors’ knowledge.

Research on the cost effectiveness of carbon emission reduction in the full life cycle of electric vehicles based on grey prediction

In order to research the carbon emission reduction potential of electric vehicles, a cost effectiveness model is used to calculate and compare the economic costs and carbon emissions of fuel vehicles and electric vehicles throughout the life cycle, and an improved grey prediction model is utilized to analyze the future trends of electric vehicle emission reduction benefits. The results show that electric vehicles play a positive role in carbon emission reduction, and the unit cost of carbon emission reduction is decreasing by years. Therefore, China should vigorously develop the electric vehicle industry and technology, and achieve the strategic goal of carbon emission reduction by promoting the electrification of vehicles.

LCA-Based Regional Distribution and Transference of Carbon Emissions from Wind Farms in China

As a clean form of energy utilization, wind power is important for alleviating climate change. Although no direct carbon emissions occur in wind power generation, there exist upstream carbon emissions from manufacturing and installation, which have indirect effects on both the locations of wind farms and areas involved in upstream production and manufacturing. In this paper, based on Input–Output based Life Cycle Analysis (IO-LCA), we explored the lifetime carbon emissions of 378 wind farms in China that were still in operation in 2015. The regional distributions of carbon emissions from wind farms during the whole lifetime were depicted. The embodied carbon emission transfers from the location of the wind farm operation to upstream turbine manufacturing regions were traced. The net emission reduction benefits among regions were also calculated. Results show that carbon emissions mainly distribute in Liaoning, Inner Mongolia, and Tianjin in the turbine manufacturing stage, with a total amount of 3.36 MT. Inner Mongolia contributes the largest carbon emissions (5.94 MT) in the farm construction stage. Inner Mongolia has transferred about 0.99 MT carbon emissions to itself and has the largest net emission reduction. Recognizing the carbon emission transfer of wind farms and dividing the carbon emission reduction responsibilities among regions may shed light on supply chain carbon emission reduction and provincial carbon quota allocation.

Carbon Emission Reduction Strategies Through Cleaner Production at Coconut Milk Processing Plant

The manufacturing industry is one of the most influential sectors contributing to greenhouse gas emissions. As the manufacturing industry strives to achieve its profit goal, most of them face various circumstances to control the rising carbon emissions from the energy, raw material consumption, and waste generations due to production activities. Therefore, it is difficult to quantify the amount of carbon emission reduction if the adjustment is not established according to the manufacturing output. This research concentrates on evaluating energy consumption and waste generation using a statistical approach by a coconut milk processing plant. This research aims to estimate the reduction of greenhouse gas emissions, mainly carbon dioxide (CO2). The baseline models of energy consumptions and waste generations were constructed using single and multiple linear regression methods. Besides, it investigates the performance of ultimate models of electrical consumption, water consumption, fuel consumption, solid waste generation, and wastewater generations using statistical analysis that involves coefficient of correlation, coefficient of determination, analysis of variance (ANOVA), etc. It indicates that with the implementation of the cleaner production (CP) strategy, the plant had reduced 10,474.94 tons of CO2 and 2,579.67 tons of CO2 in 2018 and 2019, respectively. This study is an aid to the management and engineers of the industry to investigate their accomplishment in reducing environmental impacts caused by production activities from any implementation made such as CP and green industry practices.

Scenario Prediction of China’s Natural Gas Consumption and Carbon Emissions in the Next Ten Years

Based on Johansen Cointegration Test, this paper sheds light on the long-run equilibrium relationship between natural gas consumption, gas production, and GDP in China. Three different natural gas demand scenarios of low, medium and high rates in the next ten years are considered, and a Neural Network Autoregression Model is used to predict the future carbon dioxide emission. We conclude: (1) In all three scenarios, the growth rates of natural gas consumption are all higher than those of natural gas production, while the gap between demand and domestic supply will gradually turn broader and China will largely rely on imports ; (2) In the scenario of low-rate economic growth, natural gas consumption will grow slowly, and it will be difficult to realize the carbon emission reduction targets by 2030 due to low-rate substitution of natural gas for coal; (3) If medium-rate to high-rate economic growth sustains, coupled with rapid increase in natural gas consumption and production, China’s Carbon Emission Reduction Targets for 2030 can be achieved with high-rate substitution of natural gas for coal.

COMPARISON OF EFFICIENCY AND CARBON EMISSIONS OF FILAMENT ELECTRIC STOVES AND INDUCTION ELECTRIC STOVES

Issues related to energy sustainability and carbon emission reduction are continuously being concerned by the Government of the Republic of Indonesia. Various efforts and programs have been launched to achieve targets of the related issues. As known that energy use for cooking by the household is continuously increasing in relation to population growth that will of course increase in energy need which relates to the sustainability of presence energy and carbon emission. Accordingly, the LPG stove conversion program to an electric stove was introduced in order to achieve the target to solve such issues. This paper compared of efficiency and carbon emissions of both electric filament stoves and induction stoves. The result indicated that the induction stove has better efficiency compared with the electric stove. The study also was proved that the carbon emissions for both types of stoves were relatively low in comparison with LPG stoves. However, the enormous operational power of the induction stove is still a challenge that must be resolved to achieve the target of energy sustainability in Indonesia.

Does the Agglomeration of Producer Services and the Market Entry of Enterprises Promote Carbon Reduction? An Empirical Analysis of the Yangtze River Economic Belt

As the world’s largest carbon emitter, China has been committed to carbon emission reduction and green development. Under the goal of “double carbon”, adjusting the industrial structure and promoting the development of producer services are regarded as effective emission reduction paths. In this paper, from the perspective of market entry of enterprises, we firstly investigate the transmission mechanism between market entry of enterprises and industrial agglomeration and summarize the carbon emission reduction mechanism of producer services. Based on the panel data of 110 prefecture-level cities in China’s Yangtze River Economic Belt (YREB) from 2003 to 2017, we analyze the impact of producer services on carbon emission reduction by using the dynamic spatial panel model. The empirical results show that China’s urban carbon dioxide emissions have noticeable spatial spillover effects and high emission club clustering characteristics and exhibit a noticeable snowball effect and leakage effect in time and space dimensions. The development of the producer services can effectively reduce carbon emission levels, effectively solving the dilemma of “stabilizing growth and promoting emission reduction”. Furthermore, there is an apparent synergistic effect between enterprises’ market entry and industrial agglomeration. The agglomeration of producer services can effectively promote the entry of innovative new enterprises, thus increasing the carbon emission reduction effect. However, due to resource mismatch and isomorphic development, this carbon emission reduction effect has apparent industrial heterogeneity and regional heterogeneity. Finally, this paper makes suggestions for optimizing regional industrial structure, strengthening inter-regional linkage cooperation, and promoting the advanced development of the producer services.