Life-cycle Emissions Research Articles

Cover Crops Can Reduce Greenhouse Gas Emissions from No-Till Maize in Southern Brazil: Insights from a Long-Term Field Experiment

Brazil is one of the countries that has the most agricultural area under no-till (NT) management. This research study aims to evaluate life-cycle greenhouse gas (GHG) emissions from maize (M) grain production in agroecosystems that used different cover crops under NT management in southern Brazil. The data for this study were from a long-term 41-year field experiment in southern Brazil. The long-term experiment evaluated the effects of fallow (F) and cover crops (oat (O), vetch (V), cowpea (B), pigeon pea (P), and lablab (L)) on nitrous oxide and methane emissions and soil carbon (C) sequestration in maize agroecosystems. Five cropping systems, FM, OV/M, OV/MB, PM, and LM, were evaluated. Our results show that cover crops can reduce life-cycle GHG emissions by ~40 to >100% through increased soil C sequestration. The agroecosystems with winter cover crops (OV/M and OV/MB) had higher life-cycle GHG emissions (0.5 kg CO2e kg−1 of M or 2.6 Mg CO2e ha−1) than the agroecosystem with winter F (0.06 kg CO2e kg−1 of M or 0.2 Mg CO2e ha−1). Summer cover crops (P and L) resulted in negative life-cycle GHG emissions (an average of −0.2 kg CO2e kg M−1 or −1.2 Mg CO2e ha−1) and increased the M grain yield. This study shows that cover crops can reduce greenhouse gas emissions from NT M in southern Brazil.

Load-Shifting Strategies for Cost-Effective Emission Reductions at Wastewater Facilities.

Significant hourly variation in the carbon intensity of electricity supplied to wastewater facilities introduces an opportunity to lower emissions by shifting the timing of their energy demand. This shift could be accomplished by storing wastewater, biogas from sludge digestion, or electricity from on-site biogas generation. However, the life cycle emissions and cost implications of these options are not clear. We present a multiobjective optimization framework for comparing cost- and emission-minimizing load-shifting strategies at a California case study facility with a relatively low carbon intensity grid and high spread in peak and off-peak electricity prices. We evaluate cost and emission trade-offs from the optimal flexible operation of both existing infrastructure and optimally sized energy flexibility upgrades. We estimate energy-related emission reductions of up to 9.0% with flexible operation of existing infrastructure and up to 16.8% with optimally sized storage upgrades. Only a fraction of these potential savings are realized under actual industrial energy tariffs and the EPA's recommended social cost of carbon. Energy flexibility may hold promise as a short-term emission-saving solution for the wastewater sector, but the extent of savings is heavily dependent on the cost of carbon, electricity tariffs, and emission intensity of the regional electricity grid.

Impact of electric vehicle battery recycling on reducing raw material demand and battery life-cycle carbon emissions in China

The rapid growth of electric vehicles (EVs) in China challenges raw material demand. This study evaluates the impact of recycling and reusing EV batteries on reducing material demand and carbon emissions. Integrating a national-level vehicle stock turnover model with life-cycle carbon emission assessment, we found that replacing nickel-cobalt-manganese batteries with lithium iron phosphate batteries with battery recycling can reduce lithium, cobalt, and nickel demand between 2021 and 2060 by up to 7.8 million tons (Mt) (67%), 12.4 Mt (96%), and 37.2 Mt (93%), respectively, significantly decreasing reliance on import. Moreover, battery recycling coupled with reuse can reduce carbon emissions by up to 6,532-6,864 Mt (36.0-37.9%), depending on four recycling methods employed. However, this reuse strategy delays battery recycling and risks lithium supply shortage, necessitating trade-offs between carbon reduction and material supply. Future technologies, such as lithium-sulfur and all-solid-state batteries, despite their energy efficiency, might exacerbate lithium shortage, underscoring the crucial need for increased lithium supply.

Evaluating the effectiveness of cost-minimal planning of decarbonized electricity systems in reducing life cycle greenhouse gas emissions

Abstract The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of decarbonization apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6-2.0% reduction in annual life cycle GHG emissions at a cost penalty of 3.2–9.6% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

Carbon removal efficiency and energy requirement of engineered carbon removal technologies

To ensure carbon negativity, processes that achieve carbon dioxide removal (CDR) from the atmosphere must consider lifecycle emissions and energy requirements across the entire system. We conduct a harmonized lifecycle...

Fuel shifts reduce most of the greenhouse gas emissions from transportation in the United States

Decarbonizing the United States transportation sector has emerged as a critical objective to combat climate change due to its high greenhouse gas emissions, largely from light-duty vehicles. This study assesses the breakdown of life cycle emissions of various transportation options under average and maximum ridership scenarios and quantifies emissions reductions through mode shifts and technology advancements. Electrified transportation achieves half the greenhouse gas emissions of petroleum-fueled options in 2023, with projections indicating a reduction to one-fifth by 2050. Battery systems contribute up to one-fifth of lifetime emissions of electric vehicles and buses as of 2023, and this share is estimated to increase to half by 2050 as electricity emissions are greatly reduced with the decarbonization of electricity. The study concludes that shifting away from light-duty vehicles can achieve near-term greenhouse gas reductions, but these reductions are minimal in the long term when combined with transportation electrification powered by decarbonized electricity.

A Comprehensive Life Cycle Carbon Footprint Assessment Model for Electric Power Material Warehouses

Electric power material warehouses are critical to optimizing power grid supply chains and reducing carbon emissions, aiding the power sector’s decarbonization and climate goals. Nevertheless, to our knowledge, there are no comprehensive assessments of the life cycle carbon emissions associated with storage warehouses, so the emission reduction potential of the ever-increasing number of automated technologies is still unknown. This study presents an extensive life cycle carbon footprint assessment model tailored for electric power material warehouses, and it encompasses both traditional and automated frameworks. Utilizing a process-based life cycle assessment (LCA) methodology, carbon emissions across five distinct stages are examined: storage buildings and facilities, loading and unloading, transportation, packaging, and information management systems. For this purpose, warehouses in Jiangsu Province, China, are employed as a case study. The results show that automating warehouses can achieve a reduction in total carbon emissions of 42.85% compared with traditional warehouses, with total life cycle emissions of 39,531.26 tCO2, and the transportation stage is identified as the predominant contributor. This research not only offers actionable recommendations for strategies, including renewable energy integration, intelligent control systems, and standardized packaging protocols, but also establishes a framework for future investigations of refining carbon accounting methodologies—particularly in underexplored domains such as packaging.

Assessing the life cycle impacts of the remediation of shooting ranges in peatland environments

This paper aims to expand knowledge of the potential environmental impacts associated with the remediation of shooting ranges in peatland environments. While the remediation of these sites currently requires the excavation and disposal of contaminated soil to meet local environmental quality guideline values, there is a growing recognition that this remediation process causes substantial environmental impacts. A life cycle assessment (LCA) was undertaken to identify the life cycle impacts and potential mitigation measures to reduce them. The results showed that for the majority of impact categories, downstream landfilling processes dominated impacts; in particular, substantial greenhouse gas emissions were associated with the decomposition of carbon-rich peat soil caused by excavation and removal (119 t CO2 equivalents, representing 67.8 % of the life cycle emissions). In addition, gravel materials used for road building was important to several impact categories. The greenhouse gas mitigation potential was 17 % and included the use of renewable fuels, electric excavators, local site equipment, material selection and the reuse of materials. While the impacts from site infrastructure and excavation may be reduced through appropriate planning and management, the greenhouse gas emissions impact from excavating carbon-rich soil is proportional to the excavated soil volume. Therefore, the acceptability of these impacts should be carefully evaluated against the benefits of reduced contaminant leaching into the receiving environment.

Optimizing an integrated hybrid energy system with hydrogen-based storage to develop an off-grid green community for sustainable development in Bangladesh

An integrated renewable system that utilizes solid waste-based biogas is important steps towards the sustainable energy solutions to rural off-grid communities in Bangladesh. In this study, a hybrid energy system consisting of photovoltaic modules, wind turbines, biogas generators, fuel cells, and electrolyzer-hydrogen tank-based energy storage is optimized using non-dominated sorting genetic algorithm (NSGA-II). The hybrid system is optimized based on the cost of energy and human health damage as objective functions, and a fuzzy decision-making technique is employed to determine the optimal solution to the multi-objective approach. Additionally, several economic, ecological, and social indicators are also investigated while meeting a certain load reliability. An energy management strategy has been developed in the MATALB environment to satisfy the community load and the battery-driven electric vehicle load. Results from this comprehensive analysis suggest that the optimal configuration of PV/WT/FC/BG has an energy cost of 0.1634 $/kWh, and an ecosystem damage of 0.00098 species.year. The human health damage and the human development index of the optimized system are 0.1732 DALYs and 0.696 DALYs, respectively. Additionally, the proposed system has a lifecycle emission of 123,730 kg CO2-eq/year, carbon emission penalties of $1856/year, a job creation potential of 30 jobs/MW over the 25 years of project lifetime. The hybrid system oversees solid waste management solutions and provides the community with sustainable energy and vehicle recharge.

The life cycle assessment and scenario simulation prediction of intelligent electric vehicles

Currently, advancements in intelligence, connectivity, and electrification serve as crucial pillars for enhancing traffic efficiency and reducing energy consumption and emissions, with intelligent electric vehicles holding inherent advantages. This study employs life cycle assessment theory to develop models for evaluating the life cycle of intelligent electric and fuel vehicles, covering four stages: raw material acquisition, manufacturing and assembly, operation and use, and end-of-life recycling. This study further investigates the impact of single-vehicle intelligence and vehicle-road coordination technology on the life cycle energy-saving and emission-reduction performance of electric and fuel vehicles in urban and highway scenarios and examines the potential of clean power structures to reduce the energy consumption and emissions of intelligent electric vehicles. The findings indicate that in urban road scenarios, L2-L3 level intelligent electric vehicles with vehicle-road coordination technology reduce life cycle carbon emissions by 20.22 %-22.35 % compared to the L1 level, while fuel vehicles show a reduction of 15.77 %-19.58 %. In highway scenarios, intelligent electric vehicles achieve a reduction of 12.29 %-14.50 %, whereas fuel vehicles show a decrease of 3.47 %-5.91 %. Finally, a life cycle prediction evaluation model was developed to quantitatively forecast and compare the life cycle energy consumption and emissions of intelligent electric and fuel vehicles by 2035. Research indicates that by 2035, the life cycle carbon emissions of intelligent electric vehicles will decrease by 67.81 % compared to 2023 levels, whereas intelligent fuel vehicles will see a reduction of 60.78 %. The life cycle carbon emissions and overall environmental impact potential of intelligent electric vehicles are expected to be reduced by approximately 30 % and 29 %, respectively, compared to intelligent fuel vehicles. These findings provide theoretical and practical guidance for promoting and developing intelligent electric vehicles.

China's carbon peak analysis and life-cycle greenhouse gas emission estimation under the plastics limit order

China's carbon peak analysis and life-cycle greenhouse gas emission estimation under the plastics limit order

Moving Beyond Diesel Generators: Exploring Renewable Backup Alternatives for Data Centers

Abstract This study investigates sustainable alternatives to diesel generators for data centre backup power, focusing on renewable diesel (HVO), Hydrogen energy storage (HES), batteries (Lithium-ion and Sodium Sulfur) and Compressed Air Energy Storage (CAES). As environmental scrutiny of data centres grows, the need for cleaner energy sources intensifies. Our research assesses various storage technologies’ energy performance metrics, environmental impacts, and economic feasibility. HVO is a seamless substitute for conventional diesel, compatible with existing infrastructure and less carbon-intensive. CAES offers lower life cycle emissions and operational costs but is geographically dependent. While currently more costly, batteries could achieve better economics with increased operational hours. However, extending the backup duration increases their capital and operating costs significantly, which is less advantageous than other technologies, where only fuel costs increase with longer backup times. For existing data centres transitioning to sustainable energy, HVO is optimal; for new facilities, CAES is ideal if geography allows, with HES as a robust alternative. This analysis offers a pathway for data centres to adopt sustainable, cost-effective energy storage solutions and reduce carbon footprints through on-site renewables or green energy procurement.

Double-Layer Optimization and Benefit Analysis of Shared Energy Storage Investment Considering Life-Cycle Carbon Emission

As a crucial path to promote the sustainable development of power systems, shared energy storage (SES) is receiving more and more attention. The SES generates carbon emissions during its manufacturing, usage, and recycling process, the neglect of which will introduce a certain extent of errors to the investment of SES, especially in the context of the large-scale integration of renewable energy and dramatic increase in demand for SES capacity. To enhance the accuracy of SES investment, we propose a double-layer optimization model to compute the optimal configuration of a shared energy storage station (SESS) considering its life-cycle carbon emission. First, the service mode, settlement method, profit mechanism, and application scenarios of SESS are introduced. Second, the life-cycle assessment approach is used to calculate the life-cycle carbon emission of SESS, and the uncertainty of supply and demand is considered. Then, a double-layer optimization model that considers the economic operation of multi-microgrid systems and the optimal allocation of SESS is established. The lower-layer model’s Karush–Kuhn–Tucher (KKT) condition is derived to convert the double-layer model into a single-layer one. Finally, a combined heat and power (CHP) three-microgrid system is used to demonstrate the validity of our proposed model, and the economy of SESS investment is analyzed from multiple perspectives. The results show that considering the life-cycle carbon emission of SESS can provide more accurate guidance for investing in and measuring the carbon emission and reduction for SESS.

On account of “double carbon” targeted regional public buildings in Beijing—Research on carbon emission measurement

Energy conservation and carbon reduction in the construction field is an important part of China’s dual-carbon strategy. And construction operation Carbon emissions during the period. It is also the stage where carbon emissions account for the largest proportion of the whole life cycle of buildings, among which. The carbon emissions per unit area of public buildings are twice that of civil buildings. This study takes the sub-center of Beijing City as an example, focusing on “double carbon”. Under the goal, the research on the measurement of carbon emissions of public buildings within a radius of about 812 square kilometers in the sub-center, from the perspective of urban construction development and the overall carbon emissions of regional-level buildings, on the basis of the research on the actual operation data of urban buildings, the bottom-up carbon emission measurement method of the sub-center has been established, combined with research data analysis, during the operation period, the carbon emissions per unit area of public buildings are twice that of civil buildings. This finding highlights the key role of public buildings in the stage with the largest carbon emissions in the entire life cycle of buildings. In addition, our study also puts forward the characteristics and suggestions of carbon emission reduction of public buildings in the sub-center area, which are instructive for formulating targeted work suggestions on the “dual carbon” goals of urban development. This study not only focuses on the carbon emission measurement of individual buildings, but also expands the perspective to urban construction development and regional levels, filling the gap in the overall research on regional building carbon emission measurement in existing research. It also combines the latest building energy-saving design standards and green building ratings to conduct detailed measurement and analysis of the carbon emission levels of buildings with different energy-saving design standards.

Life-cycle environmental burdens of cultivated seaweed as blue food: The case study of Wakame and Kelp in Dalian, China

Cultivated seaweed, known as typical blue food, benefits environmental sustainability like climate change mitigation when replacing land-based food with carbon-intensive fertilizer input. However, seaweed cultivation still generates environmental burdens that remain unclear, especially in China, where approximately 60 % of global seaweed is cultured. Here, we developed life cycle assessment (LCA) models to quantitatively compare the environmental performance of two seaweed species of wakame (Undaria pinnatifida) and kelp (Saccharina japonica) cultivated by floating rafts. We also developed scenarios to examine the environmental performance by controlling the seedling density and cultivation line inputs. Results show that the environmental loads of wakame are 10–40 % higher than those of kelp, with carbon footprints of 44–59 kgCO2e and 37–58 kgCO2e per ton wet weight, respectively. Seaweed cultivation at sea produces the most environmental burdens. The polyethylene cultivation lines are the crucial input influencing environmental performance. Extending the service time of cultivation lines by 10 % reduces the environmental load by ∼5 % on average. Lower seedling density with fewer cultivation line inputs slightly decreases the environmental burden but with less seaweed yield. Nitrogen and phosphorus removed by seaweed harvest are two orders of magnitude lower than fertilizers applied in land cropping systems of coastal provinces but are four orders higher than the life-cycle emissions of seaweed cultivation. We reviewed the carbon footprint of previous investigations on seaweed farming to compare with ours. Our study adds new knowledge to quantitatively understand the environmental burdens of cultured seaweed (especially for wakame Undaria pinnatifida) as a blue food alternative to land-based foods.

Quantifying the life cycle emissions of hybrid structures with advanced bio- and conventional materialization for low-embodied carbon urban densification of the Amsterdam Metropolitan Area

More than 20% of global carbon emissions are linked with the production of construction materials used in the built environment. The use of bio-materials along with urban densification strategies that avoid demolition and reduce material demand, have been recommended to achieve urban sustainability goals. Addressing these measures, this study compares the life cycle embodied carbon emissions of seven hybrid top-up structural systems composed of concrete, steel and advanced engineered timber products made out of softwood and hardwood species. The life cycle carbon emissions (expressed in kgCO2-eq) were estimated following a cradle-to-grave approach, with a functional unit equivalent to 1 m2 of top-up structural system and focusing on The Netherlands and the city of Amsterdam as main geographical scope. A statistical analysis was included to account for the potential variation of emissions across each life cycle stage, using Monte Carlo simulations for random sampling. The results indicate that predominantly bio-based structures present a staggering 60% lower embodied carbon emissions compared with predominantly concrete, steel and modestly hybrid systems. Preserving the long-term carbon storage capacity of timber elements through high-quality reuse can offset 30–60% of the total positive emissions of the predominantly bio-based systems. Up to 6MtCO2-eq of the national carbon budget in The Netherlands can be saved from a radical uptake of bio-based structures in Amsterdam by 2050. Diversification of material diets with bio-based alternatives is recommended, along with established policy that can guarantee sustainable sourcing and prolonged lifespans through high-end reuse practices.

Preparing for net zero greenhouse gas emissions in 2050: lifecycle emissions of dairy products in Brazil

Dairy products play an important role in human nutrition and the world economy. Livestock farming, including cows rearing to produce milk and dairy products, is one of the world's major sources of greenhouse gas emissions. Progress towards net zero goals requires monitoring emissions from companies and products, and greenhouse gas inventories are essential. This work quantifies greenhouse gas emissions from milk production, considering the milk delivered at the farm gate and the milk delivered at the cooperative gate. Emissions accounting was based on greenhouse gas inventories for two units and lifecycle emissions for major farm inputs. Results have shown that milk production on the farm emits 0.57 kg CO2e / liter, with enteric fermentation accounting for more than 90% of emissions at the farm gate, and more than 50% at the milk processing unit gate. Dairy production adds 0.533 kg CO2e / liter to the emissions coming from raw milk, most of which comes from wastewater treatment. Thus, the footprint of dairy products is 1.103 kg CO2e / liter of processed milk. The producers' cooperative's greenhouse gas emissions are essentially indirect and amount to 0.626 kg CO2e/liter of milk delivered to customers, in which emissions from purchased milk account for more than 85% and emissions from transportation account for around 15%.

Life Cycle Assessment and Process Optimization of Precipitated Nanosilica—A Case Study in China

To mitigate environmental emissions in the industrial nanosilica sector and promote its sustainable development, the life cycle assessment (LCA) method is employed to evaluate the environmental impacts throughout the life cycle of industrial precipitated nanosilica. This LCA spans from the acquisition and transportation of raw materials to the production of nanosilica. By identifying the critical contributing factors, effective optimization strategies have been proposed to enhance the environmental performance of the nanosilica life cycle. The effects of electricity, alkalis, acids, and steam on the life cycle emission factors of nanosilica were examined. The results indicate that substituting traditional coal power and steam with cleaner alternatives like wind energy, hydroelectric power, and solar power (both photovoltaic and thermal), as well as biogas steam, can lead to a significant reduction in the life cycle emission factors of nanosilica, ranging from 50% to 90%. Notably, the types of acids and alkalis used only significantly reduce certain environmental factors. These findings provide valuable theoretical insights and practical guidance for the industrial nanosilica sector, particularly in the areas of energy conservation, emission reduction, and the transition towards a lower-carbon economy.

Advancing equitable value chains for the global hydrogen economy

Hydrogen is a rapidly growing focus for countries seeking to develop green industries, but there are many questions about how the nascent global hydrogen economy will develop, and what this implies for equitable sharing of benefits and burdens between nations. In this perspective we summarize emerging trends in national hydrogen strategies and develop recommendations for researchers and policymakers to center equity in hydrogen development. This will require integrating innovation and development perspectives on international technology transfer, developing more detailed representation of hydrogen trade in systems models, building equity considerations into national and international planning processes, and establishing robust technology transfer efforts. Policymakers will also need to grapple with the difficulties of verifying life cycle emissions of hydrogen if hydrogen trade emerges as a significant trend, potentially requiring new methods of emissions accounting and trade reforms that prioritize international equity.

Observing the interaction between energy generation carbon emissions and economic conditions could consider generation, intensity, and times of the day.

Management of carbon emissions of regional electricity generation involves resolving much nuanced relationships. However, current studies pertaining to the relationship between energy and the economy utilize only quarterly and annual data and focus on the long-run relationship but are oblivious to temporal associations. This study takes the context of the State of Texas and utilizes per 15min of data between 2007 and 2020 to derive the monthly time series of life-cycle emissions, emissions factor, and energy generation. The study also divides each day into three portions (0:00-8:00, 8:00-16:00, and 16:00-24:00) in order to descend precision down to the hourly level. Impulse-response analysis indicates that (1) employment conditions impact emissions by affecting the amount of electric energy generated, while demographic (population as reflected by property price) tends to impact emissions by affecting the carbon intensity of electricity, and (2) the emissions produced during 0:00-8:00 display different reaction to fluctuation of regional economic conditions compared to emissions produced during other periods, the effect emanates from either energy generation fluctuation or emissions factor shocks. The broader implication of the findings lies in an emphasis on time-interval-specific analysis and concurrent consideration of both energy generation and emissions factors that can lead to optimized policy implementation results.