Carbon Equivalent Emissions Research Articles

Sustainability Assessment and Techno-Economic Analysis of Thermally Enhanced Polymer Tube for Multi-Effect Distillation (MED) Technology.

Metal-alloys tubes are used in the falling-film evaporator of the multi-effect distillation (MED) that is the dominant and efficient thermal seawater desalination process. However, the harsh seawater environment (high salinity and high temperature) causes scale precipitation and corrosion of MED evaporators’ metal tubes, presenting a serious technical challenge to the process. Therefore, the metal/metal alloys used as the material of the MED evaporators’ tubes are expensive and require high energy and costly tube fabrication process. On the other hand, polymers are low-cost, easy to fabricate into tubes, and highly corrosion-resistant, but have low thermal conductivity. Nevertheless, thermally conductive fillers can enhance the thermal conductivity of polymers. In this article, we carried out a feasibility-study-based techno-economic and socioeconomic analysis, as well as a life-cycle assessment (LCA), of a conventional MED desalination plant that uses titanium tubes and a plant that used thermally enhanced polymer composites (i.e., polyethylene (PE)-expanded graphite (EG) composite) as the tubes’ material. Two different polymer composites containing 30% and 40% filler (expanded graphite/graphene) are considered. Our results indicate that the MED plant based on polymer composite tubes has favored economic and carbon emission metrics with the potential to reduce the cost of the MED evaporator (shell and tubes) by 40% below the cost of the titanium evaporator. Moreover, the equivalent carbon emissions associated with the composite polymer tubes’ evaporator is 35% lower than titanium tubes. On the other hand, the ozone depletion, acidification, and fossil fuel depletion for the polymer composite tubes are comparable with that of the titanium tubes. The recycling of thermally enhanced polymers is not considered in this LCA analysis; however, after the end of life, reusing the polymer material into other products would lower the overall environmental impacts. Moreover, the polymer composite tubes can be produced locally, which will not only reduce the environmental impacts due to transportation but also create jobs for local manufacturing.

Application of nature inspired algorithms for multi-objective inventory control scenarios

An inventory control system having multiple items in stock is developed in this paper to optimize total cost of inventory and space requirement. Inventory modeling for both the raw material storage and work in process (WIP) is designed considering independent demand rate of items and no volume discount. To make the model environmentally aware, the equivalent carbon emission cost is also incorporated as a cost function in the formulation. The purpose of this study is to minimize the cost of inventories and minimize the storage space needed. The inventory models are shown here as a multi-objective programming problem with a few nonlinear constraints which has been solved by proposing a meta-heuristic algorithm called multi-objective particle swarm optimization (MOPSO). A further meta-heuristic algorithm called multi-objective bat algorithm (MOBA) is used to determine the efficacy of the result obtained from MOPSO. Taguchi method is followed to tune necessary response variables and compare both algorithm's output. At the end, several test problems are generated to evaluate the performances of both algorithms in terms of six performance metrics and analyze them statistically and graphically.

Perennial Staple Crops: Yields, Distribution, and Nutrition in the Global Food System

Staple crops, which have large amounts of carbohydrates, proteins, and/or fats, provide the bulk of calories in people's diets. Perennial plants, which can be productive for many years without the need for replanting, can produce staple foods and environmental benefits, but their agronomic and nutritional properties haven't been considered synthetically in comparison to annual staples. Here we offer a framework to classify perennial staple crops according to their nutritional categories and cultivation status. We assemble literature to report on the yield potential of 51 perennial staple crops, only 15 of which are well-characterized in existing global datasets. We show the extent and distribution of perennial staple crop production in relation to annual crop types, calculate the carbon stocks they hold, and analyze their nutritional content for three macronutrients and nine micronutrients. We found that most perennial staple crops are regional crops (not globally traded) that grow in the subtropics to tropics. At least one perennial staple crop in each of the five nutritional categories has yields over 2.5 t/ha, in some cases considerably higher, competitive with and in many cases exceeding those of nutritionally comparable annual staples. Perennial staple crops only comprise ~4.5% of total cropland. They hold a modest ~11.4 GtC above and below ground, less than one third of the anthropogenic carbon-equivalent emissions for the year 2018, but more than the ~9 GtC held by the same amount of annual cropland. If linear growth in land under perennial staple production continues to 2040, and replaces only annual cropland, an additional ~0.95 GtC could be sequestered. Many perennial crops also had competitive macronutrient density and yield (per unit area) compared to annual staples; moreover, specific perennial staples are abundant in specific micronutrients, indicating that they can be a nutrient-dense part of diets, unlike the most ubiquitous annual staple crops (corn, wheat, rice) that do not appear in the top 85th percentile for any of the nine micronutrients analyzed. Transition of land and diets to perennial staple crops, if judiciously managed, can provide win-win solutions for both food production and ecosystems.

Performance-based decision-making of buildings under seismic hazard considering long-term loss, sustainability, and resilience

It is of vital importance to incorporate sustainability and resilience in the performance-based decision-making of civil infrastructure under seismic hazard. However, a performance-based engineering framework utilizing component-level approach, integrating seismic loss, sustainability, and resilience in a multi-criteria decision-making (MCDM) is not yet extensively developed particularly for retrofit selection in a long-term perspective. This paper introduces a framework utilizing performance-based approach to couple seismic loss, sustainability, and resilience in decision-making framework for selection of different retrofit alternatives. A component-based probabilistic approach is developed for the seismic loss, sustainability, and resilience assessment in a long-term perspective. The resulting social, economic, and environmental consequences are converted to expected annual consequences (EACs) by considering the full range of seismic hazards, and are utilized as a multi-criterion in the technique for order preference by similarity to ideal solution (TOPSIS). The proposed long-term performance-based multi-criteria decision-making (PB-MCDM) framework considers five consequences, which include cost, casualties, equivalent carbon emissions, embodied energy, and repair time. Based on the illustrative example, it may be concluded that incorporating seismic sustainability and resilience in PB-MCDM approach in a long-term perspective can provide ideal solutions and better decision-making against retrofit alternatives.

Assessing the need for flexibility technologies in decarbonized power systems: A new model applied to Central Europe

The increasing use of renewable energy leads to a higher share of intermittent and volatile electricity generation. In this paper, we develop FLEXIES, a new open-source power system optimization model to determine the cost-efficient deployment of renewable electricity generation technologies and flexibility technologies. We apply FLEXIES in a case study of power systems in Central Europe (Switzerland, Austria, France, Germany, and Italy) in 2030, 2040, and 2050.The case study indicates that low-carbon electricity generation, batteries, and power-to-gas, consisting of multiple gas storages, are cost-efficient in 2050 – rather than burning natural gas in gas turbines. Such decarbonized power systems could be cost-efficient earlier assuming sufficiently high carbon prices. Furthermore, we find that onshore wind is prioritized over highly volatile solar generation due to a lower need for electricity storage. Interconnections enable higher shares of uniform generation technologies (on– and offshore wind, nuclear, biomass-waste) and reduce the need for solar and storage. Hence, compared to a case in which countries are isolated, interconnections reduce total electricity generation by up to 8.2%, system costs by up to 16.3%, and carbon equivalent emissions by up to 9.0%.Finally, we observe that decarbonized power systems entail a cost shift from the operational to the investment phase and total normalized costs could be higher than power market prices. Thus, new mechanisms may be needed to incentivize decarbonized power systems.

Modelling and evaluation of a biomethane truck for transport performance and cost

This article compares a conventional diesel-fuelled heavy goods vehicle with one that runs on compressed gas (CG): either Compressed Natural Gas (CNG) or biomethane. It includes an evaluation of the transport performance, carbon emissions, and total costs. 41 CG trucks were trialled by a supermarket, delivering goods from their distribution centre. One of the vehicles was instrumented with a gas flow meter, which measured the gas consumption, and a smartphone based data logger, which collected data from the truck’s Fleet Management System (FMS) interface. Similarly, a baseline diesel truck was instrumented. Based on the measurements that were collected in-service, fuel consumption models were developed and validated. Using the validated models, the CG and diesel trucks were compared for their transport performance, costs and carbon emissions. In addition, the vehicles were evaluated using telematics data and refuelling data from a year of transport operations for all 41 CG trucks and 9 diesel trucks. The results show that for a tonne.km of in-service (mostly long haul) transport work, compared to the diesel trucks, the CG trucks spend on average 22% more energy and their fuel cost is 30% lower for biomethane. When running on CNG, their equivalent carbon emissions is 10% lower than the baseline diesel, and when running on biomethane, their equivalent carbon emissions is 78% lower. Compared to long haul, the benefits are lower for regional operations, and are the lowest for city centre operations where using CNG, the CG truck’s equivalent carbon emissions is higher than the diesel truck.

Environmental sustainability EOQ model for closed-loop supply chain under market uncertainty: A case study of printer remanufacturing

The traditional economic order quantity (EOQ) model determines the optimal ordering strategy based on the premise that the market demand is constant, which leads to obvious deviations under uncertain circumstances. This work relaxes the limitations of the classical EOQ model and extends the application to closed-loop supply chain (CLSC) systems. First, through stochastic analysis, this revised model quantifies the impacts of market uncertainty on remanufacturing and operations processes. Then, by converting all the production indexes into carbon equivalent emissions, it conducts a comparative analysis of environmental efficiency under different acquisition scenarios. More importantly, based on the quantitative relationship between market uncertainty and production indexes, we devise an optimal ordering strategy for the maximization of environmental benefits under an arbitrary distribution of demand from the perspective of the entire CLSC. Finally, validated by numerical experiments and grounded with the data of printer remanufacturing, we demonstrate that the extended EOQ method can greatly reduce carbon equivalent emissions and improve environmental efficiency. This work provides a theoretical foundation for remanufacturers to formulate optimal ordering strategies under market uncertainty conditions while being more environmentally efficient without significantly increasing production input.

Effect of Renewable Fuels and Intake O2 Concentration on Diesel Engine Emission Characteristics and Reactive Oxygen Species (ROS) Formation

Renewable diesel fuels have the potential to reduce net CO2 emissions, and simultaneously decrease particulate matter (PM) emissions. This study characterized engine-out PM emissions and PM-induced reactive oxygen species (ROS) formation potential. Emissions from a modern heavy-duty diesel engine without external aftertreatment devices, and fueled with petroleum diesel, hydrotreated vegetable oil (HVO) or rapeseed methyl ester (RME) biodiesel were studied. Exhaust gas recirculation (EGR) allowed us to probe the effect of air intake O2 concentration, and thereby combustion temperature, on emissions and ROS formation potential. An increasing level of EGR (decreasing O2 concentration) resulted in a general increase of equivalent black carbon (eBC) emissions and decrease of NOx emissions. At a medium level of EGR (13% intake O2), eBC emissions were reduced for HVO and RME by 30 and 54% respectively compared to petroleum diesel. In general, substantially lower emissions of polycyclic aromatic hydrocarbons (PAHs), including nitro and oxy-PAHs, were observed for RME compared to both HVO and diesel. At low-temperature combustion (LTC, O2 < 10%), CO and hydrocarbon gas emissions increased and an increased fraction of refractory organic carbon and PAHs were found in the particle phase. These altered soot properties have implications for the design of aftertreatment systems and diesel PM measurements with optical techniques. The ROS formation potential per mass of particles increased with increasing engine O2 concentration intake. We hypothesize that this is because soot surface properties evolve with the combustion temperature and become more active as the soot matures into refractory BC, and secondly as the soot surface becomes altered by surface oxidation. At 13% intake O2, the ROS-producing ability was high and of similar magnitude per mass for all fuels. When normalizing by energy output, the lowered emissions for the renewable fuels led to a reduced ROS formation potential.

An integrated design method for functional cementitious composites (FCC)

The disease of the operating tunnel lining has seriously threatened traffic safety and needs to be cured urgently. Engineered Cementitious Composite (ECC), due to its excellent deformation ability and high damage tolerance, has the potential to retrofit the linings, but the quite high cost of raw material, mainly involving PVA fiber, has limited the broader application of ECC in the civil infrastructure. This paper proposed a practical design method of integrating four parts: engineering requirements, economical cost, matrix design and environmental assessment. A novel type of cementitious composites with low water absorption, moderate flexibility and light-weigh, named functional cementitious composite (FCC), was exploited to handle the common diseases of tunnel lining economically and environmentally. The results indicated that the cost-effective fiber is available to prepare the FCC, which shows great performance of cost-saving and functional properties. Besides, the functional characteristics, including low water sorptivity, light density and moderate flexibility, were optimized by response surface methodology (RSM) and subsequently the optimized results were proven by the test results. Finally, the environmental assessment emphasized an excellent material greenness of FCC with reduction of 26.9% embodied energy consumption and 26.2% carbon equivalent emission compared to the ECC (M45).

Carbon-neutral medical conferences should be the norm

Carbon-neutral medical conferences should be the norm

Multi-objective decision framework for comprehensive assessment of organic Rankine cycle system

A multiobjective decision framework, which is developed to determine the optimal operational parameters and choose the best working fluids for the organic Rankine cycle taking thermodynamics, economy, and environment into consideration, is proposed. Net output work, electricity production cost (EPC), and equivalent carbon emission (ECE) are adopted as the thermodynamic, economic, or environmental indicators in the decision framework. Then, a sensitivity analysis is conducted to investigate the effect of criteria weights on working fluid selection and their priority variations. Finally, the decision results obtained from the Technique for Order by Similarity to Ideal Solution are compared with those obtained by another two kinds of decision making methods, namely, Multi-Factor Evaluation and Vector-Based Ranking method. Butane, R245fa, R1233zd(E), R245ca, and R123 are chosen as the working fluids. The result shows that R1233zd(E) is recognized as the most appropriate working fluid under the above three decision methods in this work. The corresponding net output work, EPC, and ECE are 7.76 kW, 6.690 × 10−2 $/kWh, and 2.075 × 10−2 kg CO2eq/kWh, respectively.

Performance-based probabilistic framework for seismic risk, resilience, and sustainability assessment of reinforced concrete structures

Recent earthquakes have highlighted additional losses due to the lack of resilience of damaged structures. Environmental impact, as performance indicator, has also received increased attention within performance-based earthquake engineering. In this article, a combined probabilistic framework is proposed to assess seismic risk, sustainability, and resilience of a non-ductile reinforced concrete frame structure. The framework utilizes three-dimensional inelastic fiber-based numerical modeling approach to develop limit states associated with performance levels. The decision variables (i.e. repair cost, downtime, and equivalent carbon emissions) are quantified at both component level and system level and are compared considering seismic risk, sustainability, and resilience. In addition, the proposed approach considers uncertainties in the building performance and consequence functions of structural and non-structural components. Fast-track and slow-track schemes are utilized as a repair strategy and probabilistic resilience is quantified given the investigated time period. The proposed approach can aid the development of the next generation of performance-based engineering incorporating both resilience and sustainability.

Estimación de emisiones de GEI y sus trayectorias en grandes incendios forestales en Cataluña, España

A escala global, los incendios forestales son una fuente de emisiones significativas de gases y partículas a la atmosfera, emisiones que llegan a afectar grandes extensiones y pueden transportarse a distancias de escala continental. En este trabajo se han estimado las emisiones de los gases de efecto invernadero (GEI) procedentes de grandes incendios forestales ocurridos en los últimos 10 años en Cataluña, España, una región mediterránea muy afectada por la incidencia de fuegos de origen antrópico. Estas estimaciones se basan en la caracterización y cuantificación de la biomasa total de los combustibles forestales preexistentes en las áreas que se queman, la cuantificación de las pérdidas debidas a la combustión según la severidad del incendio y la aplicación de factores de emisión a la biomasa consumida. Los resultados obtenidos indican que los grandes incendios de la última década consumieron porcentajes variables entre 44,4% y 70,3% de la biomasa total disponible en las zonas incendiadas, con emisiones totales de carbono equivalente de entre 15 013 t y 387 335 t por incendio. Para determinar las trayectorias de los penachos de humo y concentraciones alcanzadas se utilizó el modelo Hybrid Single Particle Lagrangian Integrated Trajectory. Los penachos de humo de los incendios estudiados se desplazaron a grandes distancias, generalmente bajo situación anticiclónica, afectando al Mediterráneo y Norte de África.

Quantitative Analysis of Carbon Emissions in Precision Turning Processes and Industrial Case Study

With growing concerns regarding the global environment, the industrial sector has played a significant role; that is, it is responsible for consuming large amount of energy and resources, while simultaneously producing wastes and carbon dioxide. A quantitative calculation of carbon emission in the turning process is presented in this paper. A generic carbon emission system boundary based on exergy balance is proposed first to avoid blurred system boundaries or the omission of elements. Then, a carbon emission model (iERWC) is formed by converting energy consumption (E), resource depletion (R) and waste generation (W) to equivalent carbon emissions (C) based on information flow (i), which effectively solves the problem of quantifying the impact of the machining process on the environment. Finally, the model is verified by experiments, and a simulation analysis is carried out. Additionally, the influence rule of processing parameters on carbon emissions is analyzed, and the cutting parameter that produces the lowest carbon emission is given.

Design optimization and control approach for a solar-augmented industrial heating

Process level integration of solar energy could give an economically feasible solution if the industrial process allows its practical integration. The solar-augmented industrial process behaves as a complex system influenced by uncertainty of solar radiation, variability of demand temperature and process time schedule as well as possibility of thermal stratification in the storage. Addressing these issues to reach the most economical solution has two dimensions to it. First, the solar thermal system needs to be optimally designed. This requires the development of a performance criterion that will deliver maximum solar energy to the industrial process, avoid large variations of energy in the storage, and meet investment constraints. Second, the identified optimal system should be dynamically controlled to enable uniform heat distribution and efficient auxiliary heat utilization. This paper presents a holistic design optimization and control approach for a solar-augmented industrial process to facilitate decision support. The proposed solution is designed and optimized for a dyeing industrial process case study that resulted in a 5.7 year payback period, 56.3% solar fraction, and 252.2 tons equivalent carbon emission reduction. Furthermore by implementing dynamic control, about 12.4% increase in solar gain that led to a 5.6% reduction in payback period is identified.

Estimation of methane and nitrous oxide emission from wetland rice paddies with reference to global warming potential.

Methane (CH4) and nitrous oxide (N2O) are two important greenhouse gases (GHG) and contribute largely to global warming and climate change. The impact of physiological characteristics of rice genotypes on global warming potential (GWP) and greenhouse gas intensity (GHGI) is not well documented. A 2-year field experiment was conducted with eight summer rice varieties: Dinanath, Joymoti, Kanaklata, Swarnabh, IR 64, Tapaswami (modern varieties), Number 9, and Jagilee Boro (indigenous varieties) for two successive seasons (December-June, 2015-2016 and December-June, 2016-2017) to estimate their GWP and GHGI. The GWP of the rice varieties ranged from 841.52 to 1288.67kg CO2-equiv. ha-1 and GHGI from 0.184 to 0.854kg CO2-equiv. kg-1 grain yield. Significant differences (p< 0.05) in seasonal GHG emission, GWP, GHGI, CEE (carbon equivalent emission), photosynthetic efficiency, stomatal conductance, transpiration rate, and grain productivity among the rice varieties were observed during the investigation. A good correlation of GWP (p< 0.01) was recorded with rate of stomatal conductance and transpiration rate of the varieties. The present study reveals a strong relationship between plant biomass (p< 0.01) with GWP and CEE of the rice varieties. The variety IR 64 and Number 9 are identified as the most suitable variety with lowest GWP (909.85 and 876.68kg CO2-equiv. ha-1 respectively) and GHGI (0.192 and 0.227kg CO2-equiv. kg-1 grain yield respectively) accompanied by higher grain productivity (4839 and 3867kgha-1 respectively). Observations from the study suggest that agricultural productivity and GHG mitigation can be simultaneously achieved by proper selection of rice genotypes.

Comparison of centralized and decentralized air-conditioning systems for a multi-storey/multi users building integrated with electric and diesel vehicles and considering the evolution of the national energy system

In this paper four different air conditioning systems designed for a building located in Naples, are investigated. The first plant is based on distributed energy conversion systems: twelve boilers and twelve chillers. In the second solution the space heating demand is satisfied by a centralised boiler while the cooling load is met by a centralised chiller. The third option consists of a trigeneration plant. The fourth configuration is composed by an electric heat pump satisfying space heating and cooling and a centralised boiler used for domestic needs. Dynamic simulations have been carried out to compare the energy and environmental performance of the centralised systems with those achieved by the distributed one. Besides, as further loads, for the third option, two electric vehicles charged by the cogenerated electricity surplus are compared to diesel cars. The results show that the best energy and environmental performance are achieved by the cogenerator-based system, with a primary energy demand of 120.6 MWh/y and equivalent dioxide carbon emissions of 25.2 t/y in the configuration without vehicles. This result is also confirmed with electric and diesel vehicles. The energy competitiveness of the plant with the electric heat pump is achieved only in a scenario with a high penetration of renewable energy sources.

First-order estimates of the costs, input-output energy analysis, and energy returns on investment of conventional and emerging biofuels feedstocks

Here we report on a static, algebraic, spreadsheet-implemented modeling approach to estimate the costs, energy inputs and outputs, and global warming potential of biomass feedstocks. Inputs to the model included literature sourced data for: environmental factors, crop physiological-parameters such as radiation use efficiency and water use efficiency, and crop cost components. Using an energy-input-output life-cycle-assessment approach, we calculated the energy associated with each cost component, allowing an estimate of the total energy required to produce the crop and fuel alongside the energy return on investment. We did this for crop scenarios in the upper Midwest US and Far West US (for algae). Our results suggested that algae are capable of the highest areal biomass production rates of 120 MG/(ha·a), ten times greater than Maize. Algal fuel systems had the highest costs, ranging from 28 to 65 US $/GJ, compared to 17 US $/GJ for Maize ethanol. Algal fuel systems had the lowest energy returns on investment, nearly 0, compared to 25 for Switchgrass to ethanol. The carbon equivalent emissions associated with the production schemes predictions ranged from 40 (Maize) to 180 (algae PBR) CO2eq/GJnet. The promise of low cost fuel and carbon neutrality from algae is demonstrated here to be extremely challenging for fundamental reasons related to the capital-intensive nature of the cultivation system.

A non-probabilistic model of carbon footprints in remanufacture under multiple uncertainties

Uncertainties in remanufacturing systems add difficulties to the carbon footprint analysis of remanufacturing systems. Traditional probabilistic method requires a large amount of historical data to speculate the distribution types of uncertain variables. This study, based on interval analysis, applies a non-probabilistic method to the environmental assessment on remanufacturing systems in the form of carbon equivalent emissions. Considering four types of uncertainties, we establish the relationship among the quality loss of returned end of use products and environmental indexes. The results of sensitivity analysis indicate that the uncertain variables present different environmental benefits even at the same uncertainty level; however, it is interesting that when all the uncertainties are used as interval variables, the uncertainty level of their comprehensive impacts on environment does not enlarge accordingly, because the uncertain intervals of the variables are counteracted by each other. This model provides a novel method for practitioners in remanufacturing systems to quantify the impacts of uncertainties on the environment and subsequently make the optimal decision in production.

Economic and Environmental Impact Assessment of Tractor Guidance Technology

Core Ideas Tractor guidance (TG) technology allows for spatially precise input applications. A decision‐support tool was developed to quantify environmental and economic impacts of TG. Greatest C equivalent emission reductions and cost savings occurred with Cotton‐Only scenario. TG was profitable for operations evaluated and led to C equivalent emissions reductions. This tool may improve agricultural sustainability and enhance technology adoption. Tractor guidance technology allows for more spatially precise input applications, which leads to efficiency gains that are difficult to quantify at the systems level. A decision‐support tool, Tractor Guidance Analysis (TGA), was developed to quantify carbon equivalent (CE) emission reductions associated with this technology for three scenarios (500 ha each): (i) cotton (Gossypium hirsutum L.), (ii) soybean [Glycine max (L.) Merr.], and (iii) cotton and soybean mixed. Carbon equivalent emission reductions for cotton, soybean, and mixed enterprises were 27.5, 5.6, and 16.5 kg ha−1, with attendant increases in farm profitability ($68,700, $16,900, and, $42,900, respectively). Tractor guidance led to total farm CE emission reductions of 15.7, 3.5, and 9.6 Mg for cotton, soybean, and mixed operations, respectively. These results highlight that CE reductions are (i) crop specific, (ii) scale dependent, and (iii) equipment and input‐use specific. Consequently, TGA can improve agricultural sustainability by informing users of economic and environmental repercussions of tractor guidance and may thereby enhance technology adoption.