Health Benefits of Strategies for Carbon Mitigation in US Transportation, 2017‒2050.

Objectives. To quantify health benefits and carbon emissions of 2 transportation scenarios that contrast optimum levels of physical activity from active travel and minimal air pollution from electric cars. Methods. We used data on burden of disease, travel, and vehicle emissions in the US population and a health impact model to assess health benefits and harms of physical activity from transportation-related walking and cycling, fine particulate pollution from car emissions, and road traffic injuries. We compared baseline travel with walking and cycling a median of 150 weekly minutes for physical activity, and with electric cars that minimized carbon pollution and fine particulates. Results. In 2050, the target year for carbon neutrality, the active travel scenario avoided 167 000 deaths and gained 2.5 million disability-adjusted life years, monetized at $1.6 trillion using the value of a statistical life. Carbon emissions were reduced by 24% from baseline. Electric cars avoided 1400 deaths and gained 16 400 disability-adjusted life years, monetized at $13 billion. Conclusions. To achieve carbon neutrality in transportation and maximize health benefits, active travel should have a prominent role along with electric vehicles in national blueprints. (Am J Public Health. 2022; 112(3):426-433. https://doi.org/10.2105/AJPH.2021.306600).

Integrating ecosystem markets to co-ordinate landscape-scale public benefits from nature.

Ecosystem markets are proliferating around the world in response to increasing demand for climate change mitigation and provision of other public goods. However, this may lead to perverse outcomes, for example where public funding crowds out private investment or different schemes create trade-offs between the ecosystem services they each target. The integration of ecosystem markets could address some of these issues but to date there have been few attempts to do this, and there is limited understanding of either the opportunities or barriers to such integration. This paper reports on a comparative analysis of eleven ecosystem markets in operation or close to market in Europe, based on qualitative analysis of 25 interviews, scheme documentation and two focus groups. Our results indicate three distinct types of markets operating from the regional to national scale, with different modes of operation, funding and outcomes: regional ecosystem markets, national carbon markets and green finance. The typology provides new insights into the operation of ecosystem markets in practice, which may challenge traditionally held notions of Payment for Ecosystem Services. Regional ecosystem markets, in particular, represent a departure from traditional models, by using a risk-based funding model and aggregating both supply and demand to overcome issues of free-riding, ecosystem service trade-offs and land manager engagement. Central to all types of market were trusted intermediaries, brokers and platforms to aggregate supply and demand, build trust and lower transaction costs. The paper outlines six options for blending public and private funding for the provision of ecosystem services and proposes a framework for integrating national carbon markets and green finance with regional ecosystem markets. Such integration may significantly increase funding for regenerative agriculture and conservation across multiple habitats and services, whilst addressing issues of additionality and ecosystem service trade-offs between multiple schemes.

Carbon emissions reductions from Indonesia's moratorium on forest concessions are cost-effective yet contribute little to Paris pledges.

International initiatives for reducing carbon emissions from deforestation and forest degradation (REDD+) could make critical, cost-effective contributions to tropical countries' nationally determined contributions (NDCs). Norway, a key donor of such initiatives, had a REDD+ partnership with Indonesia, offering results-based payments in exchange for emissions reductions calculated against a historical baseline. Central to this partnership was an area-based moratorium on new oil palm, timber, and logging concessions in primary and peatland forests. We evaluate the effectiveness of the moratorium between 2011 and 2018 by applying a matched triple difference strategy to a unique panel dataset. Treated dryland forest inside moratorium areas retained, at most, an average of 0.65% higher forest cover compared to untreated dryland forest outside the moratorium. By contrast, carbon-rich peatland forest was unaffected by the moratorium. Cumulative avoided dryland deforestation from 2011 until 2018 translates into 67.8 million to 86.9 million tons of emissions reductions, implying an effective carbon price below Norway's US$5 per ton price. Based on Norway's price, our estimated cumulative emissions reductions are equivalent to a payment of US$339 million to US$434.5 million. Annually, our estimates suggest a 3 to 4% contribution to Indonesia's NDC commitment of a 29% emissions reduction by 2030. Despite the Indonesia-Norway partnership ending in 2021, reducing emissions from deforestation remains critical for meeting this commitment. Future area-based REDD+ initiatives could build on the moratorium's outcomes by reforming its incentives and institutional arrangements, particularly in peatland forest areas.

Collaborative multicenter logistics delivery network optimization with resource sharing.

Collaboration among logistics facilities in a multicenter logistics delivery network can significantly improve the utilization of logistics resources through resource sharing including logistics facilities, vehicles, and customer services. This study proposes and tests different resource sharing schemes to solve the optimization problem of a collaborative multicenter logistics delivery network based on resource sharing (CMCLDN-RS). The CMCLDN-RS problem aims to establish a collaborative mechanism of allocating logistics resources in a manner that improves the operational efficiency of a logistics network. A bi-objective optimization model is proposed with consideration of various resource sharing schemes in multiple service periods to minimize the total cost and number of vehicles. An adaptive grid particle swarm optimization (AGPSO) algorithm based on customer clustering is devised to solve the CMCLDN-RS problem and find Pareto optimal solutions. An effective elite iteration and selective endowment mechanism is designed for the algorithm to combine global and local search to improve search capabilities. The solution of CMCLDN-RS guarantees that cost savings are fairly allocated to the collaborative participants through a suitable profit allocation model. Compared with the computation performance of the existing nondominated sorting genetic algorithm-II and multi-objective evolutionary algorithm, AGPSO is more computationally efficient. An empirical case study in Chengdu, China suggests that the proposed collaborative mechanism with resource sharing can effectively reduce total operational costs and number of vehicles, thereby enhancing the operational efficiency of the logistics network.

Green Supply Chain Decisions Under Different Power Structures: Wholesale Price vs. Revenue Sharing Contract.

In the market, once consumers have a low-carbon preference, they will choose green low-carbon products. The market demand for green products is not only related to product price, but also consumers' low-carbon preference. In this way, enterprise has to consider the cost of carbon emissions in the process of production and operation. In this paper, we consider a two-level supply chain system composed of a manufacturer and a retailer. The supply chain system can determine the price of products and the level of carbon emission reduction through different supply chain contracts: wholesale price contract and revenue sharing contract. However, the power control structure of a manufacturer and a retailer is different, which will further affect the decision-making strategy of the supply chain system. We set up four models (Wholesale Price-NM and NR, and Revenue-Sharing-SR and SM) of the supply chain with carbon emission reduction, and calculated and analyzed. The results show that firstly, regardless of whether the manufacturer's power control structure or the retailer power structure is dominant, the manufacturer wholesale price with a contract on revenue-sharing is always higher than on wholesale price, and it is inversely proportional to the revenue-sharing proportion. Secondly, under the two power control structures, the carbon emission level of the manufacturer with a contract on revenue-sharing is always lower than on wholesale price, and it gradually decreases with the increase of the revenue-sharing proportion of the manufacturers. Thirdly, when the retailer dominates the supply chain, the retailer selling price with a contract on revenue-sharing is always higher than on wholesale price. Under the manufacturer's power control structure, when the revenue-sharing ratio is small, the retailer selling price with a contract on revenue-sharing is higher than on wholesale price; when the revenue-sharing ratio is large, the retailer selling price with a contract on revenue-sharing is lower than on wholesale price. Finally, the validity of the model is verified by an example, and the sensitivity of the parameters is analyzed.

The tail dependence of the carbon markets: The implication of portfolio management.

Emission trading scheme (ETS), the most popular market-based instrument, is widely used to solve carbon emission problems in the world. With the development of carbon market, carbon asset has been a popular financial product to invest and the risk management becomes important for government, regulated enterprises and other investors. As carbon prices have tail characteristics, this paper explores the extremal risks between carbon markets in US, Europe and China using tail dependence correlation coefficients. The empirical analysis demonstrates the tail dependence structure between carbon markets in US. and Europe is the same sign, which indicates that it is unwise to hold these two carbon assets as a portfolio. Moreover, the co-movements between European Union Emission Trade Scheme (EU ETS) and China's carbon markets are partly significant, and the operation mechanisms in China should be improved. In addition, the tail dependence test among the carbon pilots in China shows diversity. Hubei carbon trading pilot, located in central China, has extremal dependence with all other selected pilots for its regulatory program operation. The findings give insight to the carbon market regulars to improve the operation mechanism and are also useful for the investors to manage their portfolios, policymakers to make practically applicable regulations, and relevant organizations to develop procedures.

A novel bi-objective model of cold chain logistics considering location-routing decision and environmental effects.

Economic, environmental, and social effects are the most dominating issues in cold chain logistics. The goal of this paper is to propose a cost-saving, energy-saving, and emission-reducing bi-objective model for the cold chain-based low-carbon location-routing problem. In the proposed model, the first objective (economic and environmental effects) is to minimize the total logistics costs consisting of costs of depots to open, renting vehicles, fuel consumption, and carbon emission, and the second one (social effect) is to reduce the damage of cargos, which could improve the client satisfaction. In the proposed model, a strategy is developed to meet the requirements of clients as to the demands on the types of cargos, that is, general cargos, refrigerated cargos, and frozen cargos. Since the proposed problem is NP-hard, we proposed a simple and efficient framework combining seven well-known multiobjective evolutionary algorithms (MOEAs). Furthermore, in the experiments, we first examined the effectiveness of the proposed framework by assessing the performance of seven MOEAs, and also verified the efficiency of the proposed model. Extensive experiments were carried out to investigate the effects of the proposed strategy and variants on depot capacity, hard time windows, and fleet composition on the performance indicators of Pareto fronts and cold chain logistics networks, such as fuel consumption, carbon emission, travel distance, travel time, and the total waiting time of vehicles.

VOLATILE FATTY ACIDS FROM ORGANIC WASTES AS NOVEL LOW-COST CARBON SOURCE FOR Yarrowia lipolytica.

Microbial oil biosynthesis is envisaged as a promising technology for sustainable production of chemicals and fuels. Sugar-based substrates are the most typical carbon sources used for this purpose where metabolic pathways and stoichiometry are well known. However, the use of low-cost substrates is crucial for the economic viability of the process. Volatile fatty acids (VFAs) are considered to be a novel low-cost carbon source for microbial lipid production. They can be utilized by oleaginous yeasts to produce and store fatty acids in form of intracellular lipid bodies. In this work, Yarrowia lipolytica growth and substrate consumption were evaluated using the major VFAs present in anaerobic effluents. Individual VFAs as well as synthetic mixtures were tested at different concentrations to determine uptake rates and potential toxicity. Increasing VFA chain length resulted in greater biomass yield although, when added individually, 4 g Carbon/L VFA (e.g. 6.45 g/L of caproic and 10 g/L of acetic acid) caused inhibitory effects. Remarkably, biomass growth increased by 2.5-fold on real anaerobic fermentation effluent compared with synthetic mixtures. When real digestate was supplemented with synthetic VFAs up to 26.5 g/L, the inhibitory effect of the acids was counterbalanced. The results provided evidence of robustness of Y. lipolytica towards low-cost fermentation effluents and present this yeast as a promising candidate for the sustainable production of microbial oil using real digestates.

A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions.

In order to solve the optimization problem of wet waste collection and transportation in Chinese cities, this paper constructs a chance-constrained low-carbon vehicle routing problem (CCLCVRP) model in waste management system and applies certain algorithms to solve the model. Considering the environmental protection point of view, the CCLCVRP model combines carbon emission costs with traditional waste management costs under the scenario of application of smart bins. Taking into the uncertainty of the waste generation rate, chance-constrained programming is applied to transform the uncertain model to a certain one. The initial optimal solution of this model is obtained by a proposed hybrid algorithm, that is, particle swarm optimization (PSO); and then the further optimized solution is obtained by simulated annealing (SA) algorithm, due to its global optimization capability. The effectiveness of PSOSA algorithm is verified by the classic database in a capacitated vehicle routing problem (CVRP). What's more, a case of waste collection and transportation is applied in the model for acquiring reliable conclusions, and the application of the model is tested by setting different waste fill levels (WFLs) and credibility levels. The results show that total costs rise with the increase of credibility level reflecting dispatcher's risk preference; the WFL value range between 0.65 and 0.75 can obtain the optimal solution under different credibility levels. Finally, according to these results, some constructive proposals are propounded for the government and the logistics organization dealing with waste collection and transportation.

Multi-Agents-Based Modeling and Simulation for Carbon Permits Trading in China: A Regional Development Perspective.

China has been actively taking actions to control carbon emissions and promoting development of a carbon market. However, there are many disadvantages in a carbon market, owing to various designs and policies still under trial and implementation. Adopting the multi-agents technique, we constructed a framework about national carbon market to estimate the effect of a different design of policy made on the GDP (Gross Domestic Product) and environment. In particular, national and regional abatement policies were analyzed in our study. The results showed the carbon-trading mechanism can effectively reduce carbon emissions and make a negative impact on GDP. National abatement can neither be too high nor too low for reducing carbon emissions and maintaining economic stability. For different regions, the central region was impacted the most by a carbon trading mechanism, and the east region was the opposite. Moreover, the "sweeping approach" policy should be replaced by a regional "discriminating policy" because the abatement requirement to the western region was low and to the eastern region was relatively high, which is more beneficial to China's regional development.

Addressing climate change through a market mechanism: a comparative study of the pilot emission trading schemes in China.

The questions of how to mitigate climate change and its impact on human health are currently high on the Chinese agenda for future development. The emission trading scheme (ETS) has become one of China's most important instruments to address climate change through a market mechanism. In the wake of the evolution from regional pilots to a nationwide scheme, it is inevitable to be confronted with tremendous political-economic-institutional challenges. To facilitate a smooth start-up of the upcoming nationwide ETS, this study provides a systematic overview of seven ETS pilots, involving the detailed comparison of ETS design and the in-depth evaluation of market performance, both internal and external performance, based on trading data. Then, the achievements and deficiencies of seven ETS pilots are summarized, several challenges for the current time are discussed, and policy proposals for China's national-level ETS are navigated further coupled with international experience. This study finds that China's ETS pilots, from the short-term perspective, are successful, especially in the reinforcement of China's capacity to develop a market-based scheme in an economy that still cherishes many non-market endowments. However, deficiencies lie in both the internal and external market performance, such as the carbon price lacking a signal function, insufficient incentives for compliance, too low market liquidity, and much too high market fragmentation. Moreover, the retrospective examination of China's ETS pilots suggests that a nationwide ETS should at least be based on an extension of the cap duration from single year to several years, uniform rules on monitoring/reporting/verification and allowance allocation, and the improvement of institutional foundation.

A comparative analysis of Chinese regional climate regulation policy: ETS as an example.

An effective and powerful regulation is indispensable for the development and smooth operation of a cap-and-trade emission trading scheme (ETS). Seven regional pilot ETSs have been established and gradually improved in China, from which the experiences and lessons learned may provide useful references to facilitate China's national ETS regulation. This article systematically reviews and compares the practices and policies of carbon trading regulation in China's seven pilot schemes from three major aspects of regulatory institutions and subjects, regulatory objects and content, and regulatory means and techniques, and covering both internal and external regulatory architectures. The comparative analysis has demonstrated that the regional pilot schemes have made notable achievements in developing ETS regulatory systems with Chinese characteristics, but they still have considerable deficiencies. Referencing both international and domestic pilot experiences, this study recommends that China's national ETS improve regulatory institutional basis, foster an extensive participation of pluralistic regulatory subjects with a clear division of powers and responsibilities, establish effective regulatory systems on carbon finance, and continuously enrich regulatory techniques and platforms.

How quota allocation affects the unified ETS of China: a simulation with dynamic CGE model.

The national unified carbon trading market has been officially launched at the end of 2017. The carbon emission quotas should be primary concern, which can be allocated in the form of free and paid ways. However, few literatures studied the economic and environmental impacts of quotas allocation. Thus, this paper constructs 7 scenarios and employs a dynamic, recursive computable general equilibrium (CGE) model to simulate carbon trading market, to probe the relationship between quota allocation and carbon price, and the economic and environmental impact of carbon trading scheme (ETS). Empirical results indicate (1) carbon price has an upward trend with time, which reflects a corresponding increase in emission reduction pressure. Specifically, carbon price increases from 12.44-90.57 CNY/t in 2017 to 65.20-523.44 CNY/t in 2030. In addition, whether under carbon intensity criterion (CIC) or carbon emission criterion (CEC), there is a positive relationship between carbon price and free allocation ratio due to the change of the relationship between supply and demand of quota. With a given free allocation ratio, the price formed with CIC grows faster than that with CEC. (2) Compared with the benchmark scenario, the GDP of China decreases in all scenarios. However, a high level of free allocation ratio combined with CIC may prevent GDP dropping too fast. (3) As for industrial output, covered industries in ETS undertake the largest output losses with an average decline by 4.03-13.60%. Similar to GDP variation, a high free allocation ratio combined with CIC is helpful for sustainable development of industry. (4) Carbon trading has a remarkable effect on emission reductions both in covered and uncovered industries of ETS. Free allocation will reduce market efficiency, which implies it should be cut down gradually at the later stages.

Carbon emission reduction and profit distribution mechanism of construction supply chain with fairness concern and cap-and-trade.

Fairness concern behavior is extremely common in social life, and many scholars are beginning to pay attention to this behavior. In this study, we investigate a two-echelon construction supply chain that consists of a general contractor and a subcontractor under cap-and-trade policy. We study the carbon emission reduction decisions and profit distribution mechanism in the construction supply chain with fairness concern and cap-and-trade. We use the Nash bargaining model to describe the fairness concerns of the construction supply chain members and use the co-opetition model to portray the profit distribution. We show that the fairness concern can impose an adverse influence on firms' profits and decrease the magnitude of their carbon emission reductions. The subcontractor's fairness concern causes greater losses to the construction supply chain's profit. We further demonstrate the impact of fairness concern on the optimal decisions of the general contractor and the subcontractor through numerical analysis.

Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions.

In order to solve the optimization problem of emergency logistics system, this paper provides an environmental protection point of view and combines with the overall optimization idea of emergency logistics system, where a fuzzy low-carbon open location-routing problem (FLCOLRP) model in emergency logistics is constructed with the multi-objective function, which includes the minimum delivery time, total costs and carbon emissions. Taking into account the uncertainty of the needs of the disaster area, this article illustrates a triangular fuzzy function to gain fuzzy requirements. This model is tackled by a hybrid two-stage algorithm: Particle swarm optimization is adopted to obtain the initial optimal solution, which is further optimized by tabu search, due to its global optimization capability. The effectiveness of the proposed algorithm is verified by the classic database in LRP. What's more, an example of a post-earthquake rescue is used in the model for acquiring reliable conclusions, and the application of the model is tested by setting different target weight values. According to these results, some constructive proposals are propounded for the government to manage emergency logistics and for the public to aware and measure environmental emergency after disasters.