Greenhouse Gas Emission Analysis of Integrated Production-Inventory-Transportation Supply Chain Enabled by Additive Manufacturing

2021 ◽  
Author(s):  
Lei Di ◽  
Gaurav Manish Shah ◽  
Yiran Yang ◽  
Cuicui Wei
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Greenhouse Gas ◽  
Emission Intensity ◽  
Manufacturing Industry ◽  
Ghg Emissions ◽  
Ghg Emission ◽  
Integrated Production ◽  
Production Inventory ◽  
Traditional Manufacturing

Abstract The manufacturing industry is a major source of greenhouse gas emissions (GHG). Additive manufacturing, owing to its multiple advantages, plays a critical role in innovating the current manufacturing industry, especially from a supply chain perspective. Currently, the majority of research on GHG emissions in the manufacturing industry is focused on traditional manufacturing, either single processes in the supply chain or specific case studies, indicating the lack of models on GHG emissions in additive manufacturing-enabled supply chain structures. In this work, a mathematical model is established to estimate the GHG emissions in both traditional manufacturing and additive manufacturing-enabled supply chains. To explore the advantages of additive manufacturing in terms of fast production and reduced or even eliminated the need for assembly and labor involvement, a unique integrated production-inventory-transportation structure is investigated in additive manufacturing case studies. The results indicate that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the additive manufacturing technique in the supply chain. Also, the impacts of rush order rate, emission intensity, and vehicle GHG emission constant rate on the overall GHG emissions are investigated in the sensitivity analysis. Results indicate that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in additive manufacturing.

Greenhouse Gas Emission Analysis of Integrated Production-Inventory-Transportation Supply Chain Enabled by Additive Manufacturing

2021 ◽  
pp. 1-14
Author(s):  
Lei Di ◽  
Yiran Yang
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Supply Chains ◽  
Greenhouse Gas ◽  
Manufacturing Industry ◽  
Ghg Emissions ◽  
Chain Structure ◽  
Integrated Production ◽  
Production Inventory ◽  
Supply Chain Structure

Abstract Additive manufacturing (AM), owing to its unique layer-wise production method, can offer evident advantages comparing to traditional manufacturing (TM) technologies such as faster production, lower cost, and less waste. The uses of AM in rapid tooling, prototyping, and manufacturing have been innovating the current manufacturing industry from the process level to the entire supply chain. Most existing research on AM is focused on process improvement and new materials, largely neglecting the potential economic and environmental benefits enabled by AM supply chains. This research investigates an innovative supply chain structure, i.e., the integrated production-inventory-transportation (PIT) structure that is uniquely enabled by AM because of its capability of fabricating the entire product with less or even no need for assembly and labor involvement. This paper quantifies and compares the greenhouse gas (GHG) emissions of TM and AM-enabled PIT supply chains. The manufacturing industry is a major source of GHG emissions in the U.S., which therefore needs to be studied in order to explore opportunities for reducing GHG emissions for environmental protection. Case study results suggest that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the AM-enabled PIT supply chain structure. Sensitivity analysis results show that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in the AM-enabled PIT supply chain.

scholarly journals Economic and Environmental Optimization of the Forest Supply Chain for Timber and Bioenergy Production from Beetle-Killed Forests in Northern Colorado

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 689 ◽  
Author(s):  
She ◽  
Chung ◽  
Han
Keyword(s):  
Supply Chain ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Ghg Emissions ◽  
Optimization Approach ◽  
Ghg Emission ◽  
Bioenergy Production ◽  
Trade Offs ◽  
Environmental Objectives ◽  
Northern Colorado

Harvesting mountain pine beetle-infested forest stands in the northern Colorado Rocky Mountains provides an opportunity to utilize otherwise wasted resources, generate net revenues, and minimize greenhouse gas (GHG) emissions. Timber and bioenergy production are commonly managed separately, and their integration is seldom considered. Yet, degraded wood and logging residues can provide a feedstock for bioenergy, while the sound wood from beetle-killed stands can still be used for traditional timber products. In addition, beneficial greenhouse gas emission (GHG) savings are often realized only by compromising net revenues during salvage harvest where beetle-killed wood has a relatively low market value and high harvesting cost. In this study we compared Sequential and Integrated decision-making scenarios for managing the supply chain from beetle-killed forest salvage operations. In the Sequential scenario, timber and bioenergy production was managed sequentially in two separate processes, where salvage harvest was conducted without considering influences on or from bioenergy production. Biomass availability was assessed next as an outcome from timber production managed to produce bioenergy products. In the Integrated scenario, timber and bioenergy production were managed jointly, where collective decisions were made regarding tree salvage harvest, residue treatment, and bioenergy product selection and production. We applied a multi-objective optimization approach to integrate the economic and environmental objectives of producing timber and bioenergy, and measured results by total net revenues and total net GHG emission savings, respectively. The optimization model results show that distinctively different decisions are made in selecting the harvesting system and residue treatment under the two scenarios. When the optimization is fully economic-oriented, 49.6% more forest areas are harvested under the Integrated scenario than the Sequential scenario, generating 12.3% more net revenues and 50.5% more net GHG emission savings. Comparison of modelled Pareto fronts also indicate the Integrated decision scenario provides more efficient trade-offs between the two objectives and performs better than the Sequential scenario in both objectives.

scholarly journals Future greenhouse gas emissions from metal production: gaps and opportunities towards climate goals

2021 ◽  
Author(s):  
Ryosuke Yokoi ◽  
Takuma Watari ◽  
Masaharu Motoshita
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Emission Intensity ◽  
Ghg Emissions ◽  
Ghg Emission ◽  
Metal Production ◽  
Gas Emissions ◽  
Per Capita

The projected GHG emissions cannot reach the climate goal under any SSP. Further efforts on lowering per capita in-use metal stocks and GHG emission intensity of metal production and promoting recycling are the key to achieve the climate goal.

scholarly journals Greenhouse Gas Emission Intensity Assessment for Power Plants in Peninsular Malaysia

2021 ◽  
Vol 88 (2) ◽  
pp. 14-26
Author(s):  
Sazalina Zakaria ◽  
Radin Diana R. Ahmad ◽  
Ahmad Rosly Abbas ◽  
Mohd Faizal Mohideen Batcha
Keyword(s):  
Greenhouse Gas ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Power Plants ◽  
Greenhouse Gas Emission ◽  
Ghg Emissions ◽  
Peninsular Malaysia ◽  
Ghg Emission ◽  
Reduction Strategies ◽  
Emission Reduction Strategies

The power sector has been playing a vital role in the industrialization, societal and economic development of a nation. In Malaysia, the total power generation for 2014 is 147,480GWh and eventually accounts for 54% of total carbon emissions for that year alone. A study was conducted to quantify the greenhouse gas emission from stationary combustion from several power plants in Peninsular Malaysia, followed by proposal for the emission reduction strategies. For the GHG emissions assessment, the Greenhouse Gas Protocol: A Corporate Accounting and Reporting Standard and Intergovernmental Panel on Climate Change (IPCC) methodologies was adopted. Based on this study, the highest GHG emission intensity were from coal power plants which ranged from 0.67 – 0.85 tCO2/ MWh. The GHG emission intensity for natural gas power plants ranged from 0.38 – 0.78 tCO2/ MWh. The overall GHG emission intensity for all power plants studied was estimated to be 0.54 tCO2/ MWh. The large variations in CO2 emissions per MWh of electricity generated in fossil fuel power plants were due to differences in generation efficiency, fuel selection, technology, and plant age. In supporting Malaysia’s conditional commitment of 45% GHG emissions intensity reduction target against the country’s GDP, the emission reduction strategies up to 2025 were assessed using three key scenarios namely Business-As-Usual (BAU), Planning (PLAN) and Ambitious (AMB). Based on the analysis, the projection indicates that the emissions intensity for the power sector is about 0.79 tCO2/ MWh, 0.49 tCO2/ MWh, and 0.44 tCO2/ MWh under the BAU, PLN AMB scenarios respectively. Finally, GHG emission reduction potentials were also outlined in this paper.

scholarly journals Trade-offs between high yields and greenhouse gas emissions in irrigation wheat cropland in China

2014 ◽  
Vol 11 (8) ◽  
pp. 2287-2294 ◽  
Author(s):  
Z. L. Cui ◽  
L. Wu ◽  
Y. L. Ye ◽  
W. Q. Ma ◽  
X. P. Chen ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Greenhouse Gas ◽  
Ghg Emissions ◽  
Triticum Aestivum L ◽  
Ghg Emission ◽  
Trade Off ◽  
Trade Offs ◽  
High Yields ◽  
Scientific Attention

Abstract. Although the concept of producing higher yields with reduced greenhouse gas (GHG) emissions is a goal that attracts increasing public and scientific attention, the trade-off between high yields and GHG emissions in intensive agricultural production is not well understood. Here, we hypothesize that there exists a mechanistic relationship between wheat grain yield and GHG emission, and that could be transformed into better agronomic management. A total 33 sites of on-farm experiments were investigated to evaluate the relationship between grain yield and GHG emissions using two systems (conventional practice, CP; high-yielding systems, HY) of intensive winter wheat (Triticum aestivum L.) in China. Furthermore, we discussed the potential to produce higher yields with lower GHG emissions based on a survey of 2938 farmers. Compared to the CP system, grain yield was 39% (2352 kg ha−1) higher in the HY system, while GHG emissions increased by only 10%, and GHG emission intensity was reduced by 21%. The current intensive winter wheat system with farmers' practice had a median yield and maximum GHG emission rate of 6050 kg ha−1 and 4783 kg CO2 eq ha−1, respectively; however, this system can be transformed to maintain yields while reducing GHG emissions by 26% (6077 kg ha−1, and 3555 kg CO2 eq ha−1). Further, the HY system was found to increase grain yield by 39% with a simultaneous reduction in GHG emissions by 18% (8429 kg ha−1, and 3905 kg CO2 eq ha−1, respectively). In the future, we suggest moving the trade-off relationships and calculations from grain yield and GHG emissions to new measures of productivity and environmental protection using innovative management technologies.

scholarly journals A Rough Set Based Assessment of the Strategies to Reduce Greenhouse Gas Emissions: A Tanzanian Shipping Sector Perspective

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Erick P. Massami ◽  
Benitha M. Myamba
Keyword(s):  
Greenhouse Gas ◽  
Rough Set ◽  
Statistical Data ◽  
Ghg Emissions ◽  
Ghg Emission ◽  
Sea Transport ◽  
Abatement Strategies ◽  
Reduction Strategies ◽  
Emission Reduction Strategies ◽  
Synthetic Assessment

The Greenhouse Gas (GHG) emissions due to transport operations have drastically increased in recent years. The sea transport in particular contributes 2.7 to 3 percent of CO2, a major component of GHG emissions globally. Numerous measures have been undertaken locally and internationally to alleviate the sea transport share of Greenhouse Gases. However, most of these measures will be fruitful if ship investors (e.g., ship owners and operators) would fully employ the GHG emission reduction strategies. Due to the scarcity of the statistical data in this respect, this study therefore presents a rough set synthetic assessment (RSSA) model to GHG emission abatement strategies in the Tanzanian shipping sector. The results of the assessment reveal that the Tanzanian shipping companies engaged in Cabotage trade are aware of the abatement strategies and moderately apply them.

First field estimation of greenhouse gas emissions from European soil-dwelling Scarabaeidae larvae targeting the genus Melolontha

2020 ◽  
Author(s):  
Carolyn-Monika Görres ◽  
Claudia Kammann
Keyword(s):  
Greenhouse Gas ◽  
Carbon Emissions ◽  
Developmental Stages ◽  
Ghg Emissions ◽  
Field Measurements ◽  
Spatial And Temporal Variability ◽  
Activity Levels ◽  
Ghg Emission ◽  
Forest Sites ◽  
Wide Range

<p>Arthropods are a major soil fauna group, and have the potential to substantially influence the spatial and temporal variability of soil greenhouse gas (GHG) sinks and sources. The overall effect of soil-inhabiting arthropods on soil GHG fluxes still remains poorly quantified since the majority of the available data comes from laboratory experiments, is often controversial, and has been limited to a few species. The main objective of this study was to provide first insights into field-level carbon dioxide (CO<sub>2</sub>), methane (CH<sub>4</sub>) and nitrous oxide (N<sub>2</sub>O) emissions of soil-inhabiting larvae of the Scarabaeidae family. Larvae of the genus <em>Melolontha</em> were excavated at various grassland and forest sites in west-central and southern Germany, covering a wide range of different larval developmental stages, and larval activity levels. Excavated larvae were immediately incubated in the field to measure their GHG emissions. Gaseous carbon emissions of individual larvae showed a large inter- and intra-site variability which was strongly correlated to larval biomass. This correlation persisted when upscaling CO<sub>2</sub> and CH<sub>4 </sub>emissions to the plot scale. Field emission estimates for <em>Melolontha</em> spp. were subsequently upscaled to the European level to derive the first regional GHG emission estimates for members of the Scarabaeidae family. Estimates ranged between 10.42 and 409.53 kt CO<sub>2</sub> yr<sup>-1</sup>, and 0.01 and 1.36 kt CH<sub>4</sub> yr<sup>-1</sup>. Larval N<sub>2</sub>O emissions were only sporadically observed and not upscaled. For one site, a comparison of field- and laboratory-based GHG emission measurements was conducted to assess potential biases introduced by transferring Scarabaeidae larvae to artificial environments. Emission strength and variability of captive larvae decreased significantly within two weeks and the correlation between larval biomass and gaseous carbon emissions disappeared, highlighting the importance of field measurements. Overall, our data show that Scarabaeidae larvae can be significant soil GHG sources and should not be neglected in soil GHG flux research.</p>

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