Impact of aviation non-CO₂ combustion effects on the environmental feasibility of alternative jet fuels

Alternative fuels represent a potential option for reducing the climate impacts of the aviation sector. The climate impacts of alternatives fuel are traditionally considered as a ratio of life cycle greenhouse gas (GHG) emissions to those of the displaced petroleum product; however, this ignores the climate impacts of the non-CO(2) combustion effects from aircraft in the upper atmosphere. The results of this study show that including non-CO(2) combustion emissions and effects in the life cycle of a Synthetic Paraffinic Kerosene (SPK) fuel can lead to a decrease in the relative merit of the SPK fuel relative to conventional jet fuel. For example, an SPK fuel option with zero life cycle GHG emissions would offer a 100% reduction in GHG emissions but only a 48% reduction in actual climate impact using a 100-year time window and the nominal climate modeling assumption set outlined herein. Therefore, climate change mitigation policies for aviation that rely exclusively on relative well-to-wake life cycle GHG emissions as a proxy for aviation climate impact may overestimate the benefit of alternative fuel use on the global climate system.     

Brassica carinata as an alternative oil crop for the production of biodiesel in Italy: engine performance and regulated and unregulated exhaust emissions

A comparison of the performance of Brassica carinata oil-derived biodiesel with a commercial rapeseed oil-derived biodiesel and petroleum diesel fuel is discussed as regards engine performance and regulated and unregulated exhaust emissions. B. carinata is an oil crop that can be cultivated in coastal areas of central-southern Italy, where it is more difficult to achieve the productivity potentials of Brassica napus (by far the most common rapeseed cultivated in continental Europe). Experimental tests were carried out on a turbocharged direct injection passenger car diesel engine fueled with 100% biodiesel. The unregulated exhaust emissions were characterized by determining the SOOT and soluble organic fraction content in the particulate matter, together with analysis of the content and speciation of polycyclic aromatic hydrocarbons, some of which are potentially carcinogenic, and of carbonyl compounds (aldehydes, ketones) that act as ozone precursors. B. carinata and commercial biodiesel behaved similarly as far as engine performance and regulated and unregulated emissions were concerned. When compared with petroleum diesel fuel, the engine test bench analysis did not show any appreciable variation of output engine torque values, while there was a significant difference in specific fuel consumption data at the lowest loads for the biofuels and petroleum diesel fuel. The biofuels were observed to produce higher levels of NOx concentrations and lower levels of PM with respect to the diesel fuel. The engine heat release analysis conducted shows that there is a potential for increased thermal NOx generation when firing biodiesel with no prior modification to the injection timing. It seems that, for both the biofuels, this behavior is caused by an advanced combustion evolution, which is particularly apparent at the higher loads. When compared with petroleum diesel fuel, biodiesel emissions contain less SOOT, and a greater fraction of the particulate was soluble. The analysis and speciation of the soluble organic fraction of biodiesel particulate suggest that the carcinogenic potential of the biodiesel emissions is probably lower than that of petroleum diesel. Its better adaptivity and productivity in clay and sandy-type soils and in semiarid temperate climate and the fact that the performance of its derived biodiesel is quite similar to commercial biodiesel make B. carinata a promising oil crop that could offer the possibility of exploiting the Mediterranean marginal areas for energetic purposes.     

LCA法在木本生物柴油清洁生产评估方面的应用研究

生命周期评价(LCA)作为一种能全程评估产业链和产品环境影响、资源消耗、净能效率的重要方法,近年来得到了越来越多的关注,也开始被用于生物柴油清洁生产领域,能为产业可持续提供决策依据。对木本生物柴油的LCA体系、评估模型与方法、国内外木本生物柴油LCA研究现状进行了综述。结果显示:木本生物柴油在燃烧阶段相比石化柴油具有清洁排放的优点,但整个生命周期的排放未必清洁,主要与我国燃煤发电、化肥和辅料生产排放有关;木本生物柴油产业作为低碳产业,温室效应和能源消耗均低于石化柴油,整个生命周期中以种植和生产阶段的排放和消耗最大并针对性提出改进措施;未来我国木本生物柴油生命周期评价应通过建设产业标准数据库、更多注重不同原料不同工艺的对比评估、兼顾经济性和生态服务功能的评估进一步拓展木本生物柴油研究的深度和广度。     

Relevance of emissions timing in biofuel greenhouse gases and climate impacts

Employing life cycle greenhouse gas (GHG) emissions as a key performance metric in energy and environmental policy may underestimate actual climate change impacts. Emissions released early in the life cycle cause greater cumulative radiative forcing (CRF) over the next decades than later emissions. Some indicate that ignoring emissions timing in traditional biofuel GHG accounting overestimates the effectiveness of policies supporting corn ethanol by 10-90% due to early land use change (LUC) induced GHGs. We use an IPCC climate model to (1) estimate absolute CRF from U.S. corn ethanol and (2) quantify an emissions timing factor (ETF), which is masked in the traditional GHG accounting. In contrast to earlier analyses, ETF is only 2% (5%) over 100 (50) years of impacts. Emissions uncertainty itself (LUC, fuel production period) is 1-2 orders of magnitude higher, which dwarfs the timing effect. From a GHG accounting perspective, emissions timing adds little to our understanding of the climate impacts of biofuels. However, policy makers should recognize that ETF could significantly decrease corn ethanol's probability of meeting the 20% GHG reduction target in the 2007 Energy Independence and Security Act. The added uncertainty of potentially employing more complex emissions metrics is yet to be quantified.     

Operation of marine diesel engines on biogenic fuels: modification of emissions and resulting climate effects

The modification of emissions of climate-sensitive exhaust compounds such as CO(2), NO(x), hydrocarbons, and particulate matter from medium-speed marine diesel engines was studied for a set of fossil and biogenic fuels. Applied fossil fuels were the reference heavy fuel oil (HFO) and the low-sulfur marine gas oil (MGO); biogenic fuels were palm oil, soybean oil, sunflower oil, and animal fat. Greenhouse gas (GHG) emissions related to the production of biogenic fuels were treated by means of a fuel life cycle analysis which included land use changes associated with the growth of energy plants. Emissions of CO(2) and NO(x) per kWh were found to be similar for fossil fuels and biogenic fuels. PM mass emission was reduced to 10-15% of HFO emissions for all low-sulfur fuels including MGO as a fossil fuel. Black carbon emissions were reduced significantly to 13-30% of HFO. Changes in emissions were predominantly related to particulate sulfate, while differences between low-sulfur fossil fuels and low-sulfur biogenic fuels were of minor significance. GHG emissions from the biogenic fuel life cycle (FLC) depend crucially on energy plant production conditions and have the potential of shifting the overall GHG budget from positive to negative compared to fossil fuels.     

Identification of 'carbon hot-spots' and quantification of GHG intensities in the biodiesel supply chain using hybrid LCA and structural path analysis

It is expected that biodiesel production in the EU will remain the dominant contributor as part of a 10% minimum binding target for biofuel in transportation fuel by 2020 within the 20% renewable energy target in the overall EU energy mix. Life cycle assessments (LCA) of biodiesel to evaluate its environmental impacts have, however, remained questionable, mainly because of the adoption of a traditional process analysis approach resulting in system boundary truncation and because of issues regarding the impacts of land use change and N(2)O emissions from fertilizer application. In this study, a hybrid LCA methodology is used to evaluate the life cycle CO(2) equivalent emissions of rape methyl ester (RME) biodiesel. The methodology uses input-output analysis to estimate upstream indirect emissions in order to complement traditional process LCA in a hybrid framework. It was estimated that traditional LCA accounted for 2.7 kg CO(2)-eq per kg of RME or 36.6% of total life cycle emissions of the RME supply chin. Further to the inclusion of upstream indirect impacts in the LCA system (which accounted for 23% of the total life cycle emissions), emissions due to direct land use change (6%) and indirect land use change (16.5%) and N(2)O emissions from fertilizer applications (17.9%) were also calculated. Structural path analysis is used to decompose upstream indirect emissions paths of the biodiesel supply chain in order to identify, quantify, and rank high carbon emissions paths or 'hot-spots' in the biodiesel supply chain. It was shown, for instance, that inputs from the 'Other Chemical Products' sector (identified as phosphoric acid, H(3)PO(4)) into the biodiesel production process represented the highest carbon emission path (or hot-spot) with 5.35% of total upstream indirect emissions of the RME biodiesel supply chain.     

Uncertainty in life cycle greenhouse gas emissions from United States natural gas end-uses and its effects on policy

Increasing concerns about greenhouse gas (GHG) emissions in the United States have spurred interest in alternate low carbon fuel sources, such as natural gas. Life cycle assessment (LCA) methods can be used to estimate potential emissions reductions through the use of such fuels. Some recent policies have used the results of LCAs to encourage the use of low carbon fuels to meet future energy demands in the U.S., without, however, acknowledging and addressing the uncertainty and variability prevalent in LCA. Natural gas is a particularly interesting fuel since it can be used to meet various energy demands, for example, as a transportation fuel or in power generation. Estimating the magnitudes and likelihoods of achieving emissions reductions from competing end-uses of natural gas using LCA offers one way to examine optimal strategies of natural gas resource allocation, given that its availability is likely to be limited in the future. In this study, the uncertainty in life cycle GHG emissions of natural gas (domestic and imported) consumed in the U.S. was estimated using probabilistic modeling methods. Monte Carlo simulations are performed to obtain sample distributions representing life cycle GHG emissions from the use of 1 MJ of domestic natural gas and imported LNG. Life cycle GHG emissions per energy unit of average natural gas consumed in the U.S were found to range between -8 and 9% of the mean value of 66 g CO(2)e/MJ. The probabilities of achieving emissions reductions by using natural gas for transportation and power generation, as a substitute for incumbent fuels such as gasoline, diesel, and coal were estimated. The use of natural gas for power generation instead of coal was found to have the highest and most likely emissions reductions (almost a 100% probability of achieving reductions of 60 g CO(2)e/MJ of natural gas used), while there is a 10-35% probability of the emissions from natural gas being higher than the incumbent if it were used as a transportation fuel. This likelihood of an increase in GHG emissions is indicative of the potential failure of a climate policy targeting reductions in GHG emissions.     

餐厨废弃油脂生物柴油对船舶柴油机性能、排放特性以及燃烧特性的影响北大核心CSCD

为探讨生物柴油应用于船舶柴油机的可行性,将餐厨废弃油脂生物柴油与柴油混合,在船舶柴油机上进行试验,测试其对船舶柴油机性能、排放特性和燃烧特性的影响。结果表明:生物柴油混合物的高黏度以及低热值会降低有效热效率,并导致燃油消耗率略有升高;由于生物柴油的高含氧量促进完全燃烧,相比于柴油,燃烧生物柴油混合物后,一氧化碳排放量最高下降17%,二氧化碳排放量最高下降5.1%,二氧化硫排放量最高下降41%,碳烟排放量最高下降36%;生物柴油过快的燃烧速率提高了气缸内的燃烧温度,以及高含氧量促进了氮氧化物的排放;生物柴油混合物燃烧时的缸内压力与柴油非常接近。餐厨废弃油脂生物柴油对船舶柴油机的性能、燃烧特性和排放特性均具有较好的表现,可以作为柴油的替代燃料用于船舶柴油机。     

Characterizing model uncertainties in the life cycle of lignocellulose-based ethanol fuels

Renewable and low carbon fuel standards being developed at federal and state levels require an estimation of the life cycle carbon intensity (LCCI) of candidate fuels that can substitute for gasoline, such as second generation bioethanol. Estimating the LCCI of such fuels with a high degree of confidence requires the use of probabilistic methods to account for known sources of uncertainty. We construct life cycle models for the bioconversion of agricultural residue (corn stover) and energy crops (switchgrass) and explicitly examine uncertainty using Monte Carlo simulation. Using statistical methods to identify significant model variables from public data sets and Aspen Plus chemical process models,we estimate stochastic life cycle greenhouse gas (GHG) emissions for the two feedstocks combined with two promising fuel conversion technologies. The approach can be generalized to other biofuel systems. Our results show potentially high and uncertain GHG emissions for switchgrass-ethanol due to uncertain CO? flux from land use change and N?O flux from N fertilizer. However, corn stover-ethanol,with its low-in-magnitude, tight-in-spread LCCI distribution, shows considerable promise for reducing life cycle GHG emissions relative to gasoline and corn-ethanol. Coproducts are important for reducing the LCCI of all ethanol fuels we examine.     

Full chain energy analysis of biodiesel from Jatropha curcas L. in Thailand

Biodiesel production from Jatropha curcas Linnaeus (JCL) has been considered for partial substitution of diesel fuel for transportation in Thailand. The aim of this study is to investigate the energy consumption for long-term investment (20 years) of Jatropha Methyl Ester (JME) production in Thailand using a life cycle approach. Apart from the average result, two scenarios--best and worst case--are set up to illustrate the range of results due to the variety of management practices. The main contributors to the energy use are JCL cultivation, transesterification, and transportation process. The net energy gain (NEG) and net energy ratio (NER) of biodiesel and coproducts from the life cycle of JCL are 4720 GJ/ha and 6.03, respectively. Even if only biodiesel is considered without coproducts, the NER is 1.42, still higher than 1. The study will support decision makers in the energy policy sector to make informed decisions vis-a-vis promotion of JCL plantations for biodiesel.     

Approach for energy saving and pollution reducing by fueling diesel engines with emulsified biosolution/ biodiesel/diesel blends

The developments of both biodiesel and emulsified diesel are being driven by the need for reducing emissions from diesel engines and saving energy. Artificial chemical additives are also being used in diesel engines for increasing their combustion efficiencies. But the effects associated with the use of emulsified additive/biodiesel/diesel blends in diesel engines have never been assessed. In this research, the premium diesel fuel (PDF) was used as the reference fuel. A soy-biodiesel was selected as the test biodiesel. A biosolution made of 96.5 wt % natural organic enzyme-7F (NOE-7F) and 3.5 wt % water (NOE-7F water) was used as the fuel additive. By adding additional 1 vol % of surfactant into the fuel blend, a nanotechnology was used to form emulsified biosolution/soy-biodiesel/PDF blends for fueling the diesel engine. We found that the emulsified biosolution/soy-biodiesel/PDF blends did not separate after being kept motionless for 30 days. The above stability suggests that the above combinations are suitable for diesel engines as alternative fuels. Particularly, we found that the emulsified biosolution/soy-biodiesel/PDF blends did have the advantage in saving energy and reducing the emissions of both particulate matters (PM) and polycyclic aromatic hydrocarbons (PAHs) from diesel engines as compared with PDF, soy-biodiesel/PDF blends, and emulsified soy-biodiesel/ PDF blends. The results obtained from this study will provide useful approaches for reducing the petroleum reliance, pollution, and global warming. However, it should be noted that NO(x) emissions were not measured in the present study which warrants the need for future investigation.     

Uncertainty analysis of life cycle greenhouse gas emissions from petroleum-based fuels and impacts on low carbon fuel policies

The climate change impacts of U.S. petroleum-based fuels consumption have contributed to the development of legislation supporting the introduction of low carbon alternatives, such as biofuels. However, the potential greenhouse gas (GHG) emissions reductions estimated for these policies using life cycle assessment methods are predominantly based on deterministic approaches that do not account for any uncertainty in outcomes. This may lead to unreliable and expensive decision making. In this study, the uncertainty in life cycle GHG emissions associated with petroleum-based fuels consumed in the U.S. is determined using a process-based framework and statistical modeling methods. Probability distributions fitted to available data were used to represent uncertain parameters in the life cycle model. Where data were not readily available, a partial least-squares (PLS) regression model based on existing data was developed. This was used in conjunction with probability mixture models to select appropriate distributions for specific life cycle stages. Finally, a Monte Carlo simulation was performed to generate sample output distributions. As an example of results from using these methods, the uncertainty range in life cycle GHG emissions from gasoline was shown to be 13%-higher than the typical 10% minimum emissions reductions targets specified by low carbon fuel policies.     

Life cycle assessment of greenhouse gas emissions from plug-in hybrid vehicles: implications for policy

Plug-in hybrid electric vehicles (PHEVs), which use electricity from the grid to power a portion of travel, could play a role in reducing greenhouse gas (GHG) emissions from the transport sector. However, meaningful GHG emissions reductions with PHEVs are conditional on low-carbon electricity sources. We assess life cycle GHG emissions from PHEVs and find that they reduce GHG emissions by 32% compared to conventional vehicles, but have small reductions compared to traditional hybrids. Batteries are an important component of PHEVs, and GHGs associated with lithium-ion battery materials and production account for 2-5% of life cycle emissions from PHEVs. We consider cellulosic ethanol use and various carbon intensities of electricity. The reduced liquid fuel requirements of PHEVs could leverage limited cellulosic ethanol resources. Electricity generation infrastructure is long-lived, and technology decisions within the next decade about electricity supplies in the power sector will affectthe potential for large GHG emissions reductions with PHEVs for several decades.     

Greenhouse Gas Emission Evaluation of the GTL Pathway

Gas to liquids (GTL) products have the potential to replace petroleum-derived products, but the efficacy with which any sustainability goals can be achieved is dependent on the lifecycle impacts of the GTL pathway. Life cycle assessment (LCA) is an internationally established tool (with GHG emissions as a subset) to estimate these impacts. Although the International Standard Organization's ISO 14040 standard advocates the system boundary expansion method (also known as the "displacement method" or the "substitution method") for life-cycle analyses, application of this method for the GTL pathway has been limited until now because of the difficulty in quantifying potential products to be displaced by GTL coproducts. In this paper, we use LCA methodology to establish the most comprehensive GHG emissions evaluation to date of the GTL pathway. The influence of coproduct credit methods on the GTL GHG emissions results using substitution methodology is estimated to afford the Well-to-Wheels (WTW) greenhouse gas (GHG) intensity of GTL Diesel. These results are compared to results using energy-based allocation methods of reference GTL diesel and petroleum-diesel pathways. When substitution methodology is used, the resulting WTW GHG emissions of the GTL pathway are lower than petroleum diesel references. In terms of net GHGs, an interesting way to further reduce GHG emissions is to blend GTL diesel in refineries with heavy crudes that require severe hydrotreating, such as Venezuelan heavy crude oil or bitumen derived from Canadian oil sands and in jurisdictions with tight aromatic specifications for diesel, such as California. These results highlight the limitation of using the energy allocation approach for situations where coproduct GHG emissions reductions are downstream from the production phase.     

Calculator tool for determining greenhouse gas emissions for biosolids processing and end use

A greenhouse gas (GHG) calculator tool (Biosolids Emissions Assessment Model, BEAM) was developed for the Canadian Council of Ministers of the Environment to allow municipalities to estimate GHG emissions from biosolids management. The tool was developed using data from peer reviewed literature and municipalities. GHG emissions from biosolids processing through final end use/disposal were modeled. Emissions from nine existing programs in Canada were estimated using the model. The program that involved dewatering followed by combustion resulted in the highest GHG emissions (Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). The programs that had digestion followed by land application resulted in the lowest emissions (-26 and -23 Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). Transportation had relatively minor effects on overall emissions. The greatest areas of uncertainty in the model include N(2)O emissions from land application and biosolids processing. The model suggests that targeted use of biosolids and optimizing processes to avoid CH(4) and N(2)O emissions can result in significant GHG savings.     

Incorporating time-corrected life cycle greenhouse gas emissions in vehicle regulations

Beginning with model year 2012, light-duty vehicles sold in the U.S. are subject to new rules that regulate tailpipe greenhouse gas (GHG) emissions based on grams of CO(2)-equivalent per mile (gCO(2)e/mi). However, improvements in vehicle technology, lower-carbon fuels, and improvements in GHG accounting practices which account for distortions related to emissions timing all contribute to shifting a greater portion of life cycle emissions away from the vehicle use phase and toward the vehicle production phase. This article proposes methods for calculating time-corrected life cycle emissions intensity on a gCO(2)e/mi basis and explores whether regulating only tailpipe CO(2) could lead to an undesirable regulatory outcome, where technologies and vehicle architectures with higher life cycle GHGs are favored over technologies with lower life cycle emissions but with higher tailpipe GHG emissions. Two life cycle GHG assessments for future vehicles are presented in addition to time correction factors for production and end-of-life GHG emissions. Results demonstrate that, based on the vehicle designs considered here, there is a potential for favoring vehicles with higher life cycle emissions if only tailpipe emissions are regulated; moreover, the application of time correction factors amplifies the importance of production emissions and the potential for a perverse outcome.     

Combinatorial life cycle assessment to inform process design of industrial production of algal biodiesel

The use of algae as a feedstock for biodiesel production is a rapidly growing industry, in the United States and globally. A life cycle assessment (LCA) is presented that compares various methods, either proposed or under development, for algal biodiesel to inform the most promising pathways for sustainable full-scale production. For this analysis, the system is divided into five distinct process steps: (1) microalgae cultivation, (2) harvesting and/or dewatering, (3) lipid extraction, (4) conversion (transesterification) into biodiesel, and (5) byproduct management. A number of technology options are considered for each process step and various technology combinations are assessed for their life cycle environmental impacts. The optimal option for each process step is selected yielding a best case scenario, comprised of a flat panel enclosed photobioreactor and direct transesterification of algal cells with supercritical methanol. For a functional unit of 10 GJ biodiesel, the best case production system yields a cumulative energy demand savings of more than 65 GJ, reduces water consumption by 585 m(3) and decreases greenhouse gas emissions by 86% compared to a base case scenario typical of early industrial practices, highlighting the importance of technological innovation in algae processing and providing guidance on promising production pathways.     

Effect of feeding strategies and cropping systems on greenhouse gas emission from Wisconsin certified organic dairy farms

Organic agriculture continues to expand in the United States, both in total hectares and market share. However, management practices used by dairy organic producers, and their resulting environmental impacts, vary across farms. This study used a partial life cycle assessment approach to estimate the effect of different feeding strategies and associated crop production on greenhouse gas emissions (GHG) from Wisconsin certified organic dairy farms. Field and livestock-driven emissions were calculated using 2 data sets. One was a 20-yr data set from the Wisconsin Integrated Cropping System Trial documenting management inputs, crop and pasture yields, and soil characteristics, used to estimate field-level emissions from land associated with feed production (row crop and pasture), including N₂O and soil carbon sequestration. The other was a data set summarizing organic farm management in Wisconsin, which was used to estimate replacement heifer emission (CO₂ equivalents), enteric methane (CH₄), and manure management (N₂O and CH₄). Three combinations of corn grain (CG) and soybean (SB) as concentrate (all corn = 100% CG; baseline = 75% CG + 25% SB; half corn = 50% CG + 50% SB) were assigned to each of 4 representative management strategies as determined by survey data. Overall, GHG emissions associated with crop production was 1,297 ± 136 kg of CO₂ equivalents/t of ECM without accounting for soil carbon changes (ΔSC), and GHG emission with ΔSC was 1,457 ± 111 kg of CO₂ equivalents/t of ECM, with greater reliance on pasture resulting in less ΔSC. Higher levels of milk production were a major driver associated with reduction in GHG emission per metric tonne of ECM. Emissions per metric tonne of ECM increased with increasing proportion of SB in the ration; however, including SB in the crop rotation decreased N₂O emission per metric tonne of ECM from cropland due to lower applications of organically approved N fertility inputs. More SB at the expense of CG in the ration reduced enteric CH₄ emission per metric tonne of ECM (because of greater dietary fat content) but increased N₂O emission per metric tonne of ECM from manure (because of greater N content). An increased reliance on pasture for feed at the expense of grain resulted in decreased in milk production, subsequently leading to substantially higher emissions per metric tonne of ECM.     

Greenhouse gas emissions and land use change from Jatropha curcas-based jet fuel in Brazil

This analysis presents a comparison of life-cycle GHG emissions from synthetic paraffinic kerosene (SPK) produced as jet fuel substitute from jatropha curcas feedstock cultivated in Brazil against a reference scenario of conventional jet fuel. Life cycle inventory data are derived from surveys of actual Jatropha growers and processors. Results indicate that a baseline scenario, which assumes a medium yield of 4 tons of dry fruit per hectare under drip irrigation with existing logistical conditions using energy-based coproduct allocation methodology, and assumes a 20-year plantation lifetime with no direct land use change (dLUC), results in the emissions of 40 kg CO?e per GJ of fuel produced, a 55% reduction relative to conventional jet fuel. However, dLUC based on observations of land-use transitions leads to widely varying changes in carbon stocks ranging from losses in excess of 50 tons of carbon per hectare when Jatropha is planted in native cerrado woodlands to gains of 10-15 tons of carbon per hectare when Jatropha is planted in former agro-pastoral land. Thus, aggregate emissions vary from a low of 13 kg CO?e per GJ when Jatropha is planted in former agro-pastoral lands, an 85% decrease from the reference scenario, to 141 kg CO?e per GJ when Jatropha is planted in cerrado woodlands, a 60% increase over the reference scenario. Additional sensitivities are also explored, including changes in yield, exclusion of irrigation, shortened supply chains, and alternative allocation methodologies.     

The carbon footprint of dairy production systems through partial life cycle assessment

Greenhouse gas (GHG) emissions and their potential effect on the environment has become an important national and international issue. Dairy production, along with all other types of animal agriculture, is a recognized source of GHG emissions, but little information exists on the net emissions from dairy farms. Component models for predicting all important sources and sinks of CH₄, N₂O, and CO₂ from primary and secondary sources in dairy production were integrated in a software tool called the Dairy Greenhouse Gas model, or DairyGHG. This tool calculates the carbon footprint of a dairy production system as the net exchange of all GHG in CO₂ equivalent units per unit of energy-corrected milk produced. Primary emission sources include enteric fermentation, manure, cropland used in feed production, and the combustion of fuel in machinery used to produce feed and handle manure. Secondary emissions are those occurring during the production of resources used on the farm, which can include fuel, electricity, machinery, fertilizer, pesticides, plastic, and purchased replacement animals. A long-term C balance is assumed for the production system, which does not account for potential depletion or sequestration of soil carbon. An evaluation of dairy farms of various sizes and production strategies gave carbon footprints of 0.37 to 0.69 kg of CO₂ equivalent units/kg of energy-corrected milk, depending upon milk production level and the feeding and manure handling strategies used. In a comparison with previous studies, DairyGHG predicted C footprints similar to those reported when similar assumptions were made for feeding strategy, milk production, allocation method between milk and animal coproducts, and sources of CO₂ and secondary emissions. DairyGHG provides a relatively simple tool for evaluating management effects on net GHG emissions and the overall carbon footprint of dairy production systems.