The effects of climate change on biodiversity should depend in part on climate displacement rate (climate-change velocity) and its interaction with species' capacity to migrate. We estimated Late ...Quaternary glacial-interglacial climate-change velocity by integrating macroclimatic shifts since the Last Glacial Maximum with topoclimatic gradients. Globally, areas with high velocities were associated with marked absences of small-ranged amphibians, mammals, and birds. The association between endemism and velocity was weakest in the highly vagile birds and strongest in the weakly dispersing amphibians, linking dispersal ability to extinction risk due to climate change. High velocity was also associated with low endemism at regional scales, especially in wet and aseasonal regions. Overall, we show that low-velocity areas are essential refuges for Earth's many small-ranged species.
•Global plastic waste trade networks (GPWTNs) from 1988 to 2017 are established.•The spatiotemporal evolution of the GPWTNs is analyzed.•The direct and indirect impacts of China’s import ban on the ...GPWTNs are evaluated.•Practical implications are given according to analysis of the GPWTNs.
Millions of tonnes (teragrams) of plastic waste are traded around the world every year, which plays an important role in partially substituting virgin plastics as a source of raw materials in plastic product manufacturing. In this paper, global plastic waste trade networks (GPWTNs) from 1988 to 2017 are established using the UN-Comtrade database. The spatiotemporal evolution of the GPWTNs is analyzed. Attention is given to the country ranks, inter- and intra-continental trade flows, and geo-visual communities in the GPWTNs. We also evaluate the direct and indirect impacts of China’s plastic waste import ban on the GPWTNs. The results show that the GPWTNs have small-world and scale-free properties and a core-periphery structure. The geography of the plastic waste trade is structured by Asia as the dominant importer and North America and Europe as the largest sources of plastic waste. China is the unrivaled colossus in the global plastic waste trade. After China’s import ban, the plastic waste trade flows have been largely redirected to Southeast Asian countries. Compared with import countries, export countries are more important for the robustness of GPWTNs. Clearly, developed countries will not announce bans on plastic waste exports; these countries have strong motivation to continue to shift plastic waste to poorer countries. However, the import bans from developing countries will compel developed countries to build new disposal facilities and deal with their plastic waste domestically.
We consider the cap-and-trade mechanism and the consumers’ preference for low-carbon products and develop an evolutionary game model to understand the evolutionary behavior of the retailers and the ...manufacturers in a retailer-led supply chain. As shown in this figure, in such a retailer-led supply chain, the retailers have two strategies: a low-carbon promotion strategy (LCPS) and a non-promotion strategy (NPS) and the manufacturers can choose between a carbon emissions-reduction strategy (CERS) and a no-reduction strategy (NRS).
(1) A Stackelberg game structure is used to determine the optimal solutions for each retailer and each manufacturer. As these strategies can be chosen by retailers and manufacturers, and modelled using probabilities of different choices, (2) the EG model is developed for the retailer group and the manufacturer group to investigate the stability of the equilibrium strategies. As SD is a technique tool to simulate and analyze dynamic and transient behavior, (3) the system dynamics model for evolutionary game is applied to a case study of the refrigerator industry to simulate the dynamic game process and investigate how the emission cap, market price of carbon credits, and consumers’ preferences for low-carbon products influence the evolution of behaviors of retailers and manufacturers.
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•Under cap-and-trade, the evolutionary game model is developed to understand the evolutionary behavior of the retailers and the manufacturers in a retailer-led supply chain.•A Stackelberg game structure is used to determine the optimal solutions for each retailer and each manufacturer.•The system dynamics model for evolutionary game is applied to a case study of the refrigerator industry to do the sensitivity analysis.
Governments and consumers are paying more attention to environmental protection. China, Korea, and several European countries have implemented market-based cap-and-trade systems to reduce carbon emissions. At the same time, consumers are willing to pay more for low-carbon products. The decisions of manufacturers and retailers may be impacted by these factors. This paper considers a scenario with a model economy under the effects of a cap-and-trade policy, with consumers who prefer low-carbon products, and develops an evolutionary game (EG) model to examine the evolution of behaviors for powerful retailers (such as Amazon, Gome, Walmart, etc.) and manufacturers in a retailer-led supply chain. In such a supply chain, the retailers can choose whether or not to promote low-carbon products and manufacturers can choose whether or not to reduce carbon emissions. A Stackelberg game structure is used to identify the optimal decisions for manufacturers and retailers. A model is developed to investigate the stability of the equilibrium solutions of the evolutionary game. System dynamics is used to simulate and analyze dynamic and transient behaviors, and is used to simulate the evolutionary game in a Chinese appliance industry. The simulation results show that the emissions cap, the market price of carbon credits, and the consumers’ preferences for low-carbon products are key factors influencing the retailers’ and manufacturers’ behavior. To increase long-term profits for both retailers and manufacturers, the retailers and the manufacturers should make sustainable decisions in tandem.
The environmental burden caused by energy consumption during the use phase of machine tool systems is widely acknowledged and hence ways must be found to use energy more efficiently. There is ...potentially a significant amount of energy savings that could be realized by selecting alternative machine tools and reducing the idle energy consumption through better scheduling. This paper proposes an energy-saving optimization method that considers machine tool selection and operation sequence for flexible job shops. The former seeks to reduce the energy consumption for machining operations, and the latter aims to reduce the idle energy consumption of machine tools. A mathematical model is formulated using mixed integer programming and the energy consumption objective is combined with a classical objective, the makespan. A Nested Partitions algorithm, which has proved to be robust for NP-hard problems, is utilized to solve the model. The proposed method is evaluated in a test case by two scenarios with different energy optimization schemes as well as the classical makespan objective. The results show that the proposed method is effective at realizing energy-savings for a flexible machining job shop.
•This work offers an energy-responsive optimization method for flexible job shop.•The problem is modeled by integrating machine selection and operation sequence.•The results show the relationship among machining energy, idle energy and makespan.•The results can help making decision on energy efficient operational production.
A time-indexed integer programming formulation is developed and used to identify manufacturing schedules that minimize electricity cost and the carbon footprint under time-of-use tariffs without ...compromising production throughput. The approach is demonstrated using a flow shop with 8 process steps operating on a typical summer day. Results suggest that shifting electricity usage from on-peak hours to mid-peak hours or off-peak hours, while reducing electricity cost may increase CO2 emissions in regions where the grid base load is met with electricity from coal-fired power plants. The trade-off between minimizing electricity cost and reducing CO2 emissions is shown via a Pareto frontier.
A new ‘econological scheduling’ model combining the economic and ecological aspects of a multi-part multi-machine setup operating under a time-of-use tariff is presented. The operating speed of the ...machines and the frequency of operating speed change are allowed to vary, and the peak load and energy consumption during a shift is estimated using discrete event simulation. The electricity cost and environmental impact for a target production quota are simultaneously minimized using a multi-criterion meta-heuristic optimization. The proposed model is demonstrated via a case study on a manufacturing unit producing parts using machining and welding operations. A comparison among econological, economic, and ecological approaches and the underlying dynamics of scheduling under a time-varying electricity tariff are presented as one of several strategies for enabling a manufacturing system to be more eco-friendly without substantially increasing the electricity cost.
An urgent challenge in the manufacturing industry is increasing efficiency while decreasing energy consumption and environmental impact. Past studies addressing these issues have mainly focused on ...tool path optimization only considering machining efficiency. In this paper, we present a methodology to optimize the tool path for high efficiency, low energy consumption and carbon footprint in milling process. Firstly, the description and influencing factors of tool path are introduced. Then, a multi objective tool path optimization model with maximum machining efficiency, minimum energy consumption and carbon emission is proposed. Furthermore, the solution of the proposed model is introduced, which including two steps, one is the calculation of the number of cutter contact points (CCP), the other is using adaptive dynamic GA to optimize the connection sequence and ways of each CCP. Finally, the effectiveness and practicability of the method are verified by the machining experiments.
We consider the problem of scheduling jobs on a single machine to minimize the total electricity cost of processing these jobs under time-of-use electricity tariffs. For the uniform-speed case, in ...which all jobs have arbitrary power demands and must be processed at a single uniform speed, we prove that the non-preemptive version of this problem is inapproximable within a constant factor unless
P
=
NP
. On the other hand, when all the jobs have the same workload and the electricity prices follow a so-called pyramidal structure, we show that this problem can be solved in polynomial time. For the speed-scalable case, in which jobs can be processed at an arbitrary speed with a trade-off between speed and power demand, we show that the non-preemptive version of the problem is strongly NP-hard. We also present different approximation algorithms for this case, and test the computational performance of these approximation algorithms on randomly generated instances. In addition, for both the uniform-speed and speed-scaling cases, we show how to compute optimal schedules for the preemptive version of the problem in polynomial time.
The biofilm matrix is a dynamic environment in which the component microbial cells appear to reach homeostasis and are optimally organized to make use of all available nutrients. The major matrix ...components are microbial cells, polysaccharides and water, together with excreted cellular products. The matrix therefore shows great microheterogeneity, within which numerous microenvironments can exist. Although exopolysaccharides provide the matrix framework, a wide range of enzyme activities can be found within the biofilm, some of which will greatly affect structural integrity and stability.
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