Identifying improvement potentials in cement production with life cycle assessment

Cement production is an environmentally relevant process responsible for 5% of total anthropogenic carbon dioxide emissions and 7% of industrial fuel use. In this study, life cycle assessment is used to evaluate improvement potentials in the cement production process in Europe and the USA. With a current fuel substitution rate of 18% in Europe and 11% in the USA, both regions have a substantial potential to reduce greenhouse gas emissions and save virgin resources by further increasing the coprocessing of waste fuels. Upgrading production technology would be particularly effective in the USA where many kiln systems with very low energy efficiency are still in operation. Using best available technology and a thermal substitution rate of 50% for fuels, greenhouse gas emissions could be reduced by 9% for Europe and 18% for the USA per tonne of cement. Since clinker production is the dominant pollution producing step in cement production, the substitution of clinker with mineral components such as ground granulated blast furnace slag or fly ash is an efficient measure to reduce the environmental impact. Blended cements exhibit substantially lower environmental footprints than Portland cement, even if the substitutes feature lower grindability and require additional drying and large transport distances. The highest savings in CO(2) emissions and resource consumption are achieved with a combination of measures in clinker production and cement blending.     

Factors affecting life cycle assessment of milk produced on 6 Mediterranean buffalo farms

This study quantifies the environmental impact of milk production of Italian Mediterranean buffaloes and points out the farm characteristics that mainly affect their environmental performance. Life cycle assessment was applied in a sample of 6 farms. The functional unit was 1 kg of normalized buffalo milk (LBN), with a reference milk fat and protein content of 8.3 and 4.73%, respectively. The system boundaries included the agricultural phase of the buffalo milk chain from cradle to farm gate. An economic criterion was adopted to allocate the impacts on milk production. Impact categories investigated were global warming (GW), abiotic depletion (AD), photochemical ozone formation (PO), acidification (AC), and eutrophication (EU). The contribution to the total results of the following farm activities were investigated: (1) on-farm energy consumption, (2) manure management, (3) manure application, (4) on-farm feed production (comprising production and application of chemical fertilizers and pesticides), (5) purchased feed production, (6) enteric fermentation, and (7) transport of purchased feeds, chemical fertilizers, and pesticides from producers to farms. Global warming associated with 1 kg of LBN resulted in 5.07 kg of CO₂ Eq [coefficient of variation (CV) = 21.9%], AD was 3.5 × 10⁻³ kg of Sb Eq (CV = 51.7%), PO was 6.8 × 10⁻⁴ kg of C₂H₄ Eq (CV = 28.8%), AC was 6.5 × 10⁻² kg of SO₂ Eq (CV = 30.3%), and EU was 3.3 × 10⁻² kg of PO₄³⁻ Eq (CV = 36.5%). The contribution of enteric fermentation and manure application to GW is 37 and 20%, respectively; on-farm consumption, on-farm feed production, and purchased feed production are the main contributors to AD; about 70% of PO is due to enteric fermentation; manure management and manure application are responsible for 55 and 25% of AC and 25 and 55% of EU, respectively. Methane and N₂O are responsible for 44 and 43% of GW, respectively. Crude oil consumption is responsible for about 72% of AD; contribution of CH₄ to PO is 77%; NH₃ is the main contributor to AC (92%); NO₃⁻ and NH₃ are responsible for 55 and 41% of EU, respectively; contribution of P to EU is only 3.2%. The main characteristics explaining the significant variability of life cycle assessment are milk productivity and amount of purchased feed per kilogram of LBN. Improvement of LBN production per buffalo cow is the main strategy for reducing GW and PO; improvement of the efficiency of feed use is the strategy proposed for mitigating AD, PO, AC, and EU.     

Greenhouse gas emissions from milk production and consumption in the United States: A cradle-to-grave life cycle assessment circa 2008

This article presents a cradle-to-grave analysis of the United States fluid milk supply chain greenhouse gas (GHG) emissions that are accounted from fertilizer production through consumption and disposal of milk packaging. Crop production and on-farm GHG emissions were evaluated using public data and 536 farm operation surveys. Milk processing data were collected from 50 dairy plants nationwide. Retail and consumer GHG emissions were estimated from primary data, design estimates, and publicly available data. Total GHG emissions, based primarily on 2007 to 2008 data, were 2.05 (90% confidence limits: 1.77–2.4) kg CO₂e per kg milk consumed, which accounted for loss of 12% at retail and an additional 20% loss at consumption. A complementary analysis showed the entire dairy sector contributes approximately 1.9% of US GHG emissions. While the largest GHG contributors are feed production, enteric methane, and manure management; there are opportunities to reduce impacts throughout the supply chain.     

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.     

Biodiesel production in a semiarid environment: a life cycle assessment approach

While the use of biodiesel appears to be a promising alternative to petroleum fuel, the replacement of fossil fuel by biofuel may not bring about the intended climate cooling because of the increased soil N2O emissions due to N-fertilizer applications. Using a life cycle assessment approach, we assessed the influence of soil nitrous oxide (N2O) emissions on the life cycle global warming potential of the production and combustion of biodiesel from canola oil produced in a semiarid climate. Utilizing locally measured soil N2O emissions, rather than the Intergovernmental Panel on Climate Change (IPCC) default values, decreased greenhouse gas (GHG) emissions from the production and combustion of 1 GJ biodiesel from 63 to 37 carbon dioxide equivalents (CO2-e)/GJ. GHG were 1.1 to 2.1 times lower than those from petroleum or petroleum-based diesel depending on which soil N2O emission factors were included in the analysis. The advantages of utilizing biodiesel rapidly declined when blended with petroleum diesel. Mitigation strategies that decrease emissions from the production and application of N fertilizers may further decrease the life cycle GHG emissions in the production and combustion of biodiesel.     

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.     

Prospective environmental life cycle assessment of nanosilver T-shirts

A cradle-to-grave life cycle assessment (LCA) is performed to compare nanosilver T-shirts with conventional T-shirts with and without biocidal treatment. For nanosilver production and textile incorporation, we investigate two processes: flame spray pyrolysis (FSP) and plasma polymerization with silver co-sputtering (PlaSpu). Prospective environmental impacts due to increased nanosilver T-shirt commercialization are estimated with six scenarios. Results show significant differences in environmental burdens between nanoparticle production technologies: The "cradle-to-gate" climate footprint of the production of a nanosilver T-shirt is 2.70 kg of CO(2)-equiv (FSP) and 7.67-166 kg of CO(2)-equiv (PlaSpu, varying maturity stages). Production of conventional T-shirts with and without the biocide triclosan has emissions of 2.55 kg of CO(2)-equiv (contribution from triclosan insignificant). Consumer behavior considerably affects the environmental impacts during the use phase. Lower washing frequencies can compensate for the increased climate footprint of FSP nanosilver T-shirt production. The toxic releases from washing and disposal in the life cycle of T-shirts appear to be of minor relevance. By contrast, the production phase may be rather significant due to toxic silver emissions at the mining site if high silver quantities are required.     

食品生命周期碳排放评价研究

基于生命周期评价（LCA）理论,探讨界定食品生命周期碳排放的核算范围,对食品生命周期从原料生产、加工、消费到废物处理各阶段的碳排放进行清单分析,并提出了食品生命周期碳排量的评价框架和方法。     

产品生命周期评价体系研究

为更好地用量化的数据来判断产品的绿色程度，以利于产品生命周期评价，建立了由产品层次维、生命周期维、指标维构成的生命周期评价的三维集成体系结构以及由环境属性指标、资源属性指标、能源属性指标和经济性指标构成的生命周期评价指标体系，并针对评价过程中生命周期权重的确定，产品环境属性数据库的建立以及环境影响因子的确定，给出了有效的解决方法。     

Comparative life cycle assessment of standard and green roofs

Life cycle assessment (LCA) is used to evaluate the benefits, primarily from reduced energy consumption, resulting from the addition of a green roof to an eight story residential building in Madrid. Building energy use is simulated and a bottom-up LCA is conducted assuming a 50 year building life. The key property of a green roof is its low solar absorptance, which causes lower surface temperature, thereby reducing the heat flux through the roof. Savings in annual energy use are just over 1%, but summer cooling load is reduced by over 6% and reductions in peak hour cooling load in the upper floors reach 25%. By replacing the common flat roof with a green roof, environmental impacts are reduced by between 1.0 and 5.3%. Similar reductions might be achieved by using a white roof with additional insulation for winter, but more substantial reductions are achieved if common use of green roofs leads to reductions in the urban heat island.     

Genetic value of herd life adjusted for milk production.

Cow herd life adjusted for lactational milk production was investigated as a genetic trait in the breeding objective. Under a simple model, the relative economic weight of milk to adjusted herd life on a per genetic standard deviation basis was equal to CVY/dCVL where CVY and CVL are the genetic coefficients of variation of milk production and adjusted herd life, respectively, and d is the depreciation per year per cow divided by the total fixed costs per year per cow. The relative economic value of milk to adjusted herd life at the prices and parameters for North America was about 3.2. An increase of 100-kg milk was equivalent to 2.2 mo of adjusted herd life. Three to 7% lower economic gain is expected when only improved milk production is sought compared with a breeding objective that included both production and adjusted herd life for relative value changed +/- 20%. A favorable economic gain to cost ratio probably exists for herd life used as a genetic trait to supplement milk in the breeding objective. Cow survival records are inexpensive, and herd life evaluations from such records may not extend the generation interval when such an evaluation is used in bull sire selection.     

面向产品全生命周期评价环境决策模型研究

在ISO14000系列国际标准的基础上,提出了在数据清单分析和影响评价的过程中,利用模糊层次分析法建立产品全生命周期评价环境决策模型的方法。模型在获得产品全生命周期环境影响数据清单之后,通过对环境影响因子的权重 的确定,可以对产品的环境影响进行量化分析,并根据分析结果评价产品的环境影响值,从而实现产品环境友好度评价由定性向定量的转化。     

Variability and uncertainty in life cycle assessment models for greenhouse gas emissions from Canadian oil sands production

Because of interest in greenhouse gas (GHG) emissions from transportation fuels production, a number of recent life cycle assessment (LCA) studies have calculated GHG emissions from oil sands extraction, upgrading, and refining pathways. The results from these studies vary considerably. This paper reviews factors affecting energy consumption and GHG emissions from oil sands extraction. It then uses publicly available data to analyze the assumptions made in the LCA models to better understand the causes of variability in emissions estimates. It is found that the variation in oil sands GHG estimates is due to a variety of causes. In approximate order of importance, these are scope of modeling and choice of projects analyzed (e.g., specific projects vs industry averages); differences in assumed energy intensities of extraction and upgrading; differences in the fuel mix assumptions; treatment of secondary noncombustion emissions sources, such as venting, flaring, and fugitive emissions; and treatment of ecological emissions sources, such as land-use change-associated emissions. The GHGenius model is recommended as the LCA model that is most congruent with reported industry average data. GHGenius also has the most comprehensive system boundaries. Last, remaining uncertainties and future research needs are discussed.     

Toward meaningful end points of biodiversity in life cycle assessment

Halting current rates of biodiversity loss will be a defining challenge of the 21st century. To assess the effectiveness of strategies to achieve this goal, indicators and tools are required that monitor the driving forces of biodiversity loss, the changing state of biodiversity, and evaluate the effectiveness of policy responses. Here, we review the use of indicators and approaches to model biodiversity loss in Life Cycle Assessment (LCA), a methodology used to evaluate the cradle-to-grave environmental impacts of products. We find serious conceptual shortcomings in the way models are constructed, with scale considerations largely absent. Further, there is a disproportionate focus on indicators that reflect changes in compositional aspects of biodiversity, mainly changes in species richness. Functional and structural attributes of biodiversity are largely neglected. Taxonomic and geographic coverage remains problematic, with the majority of models restricted to one or a few taxonomic groups and geographic regions. On a more general level, three of the five drivers of biodiversity loss as identified by the Millennium Ecosystem Assessment are represented in current impact categories (habitat change, climate change and pollution), while two are missing (invasive species and overexploitation). However, methods across all drivers can be greatly improved. We discuss these issues and make recommendations for future research to better reflect biodiversity loss in LCA.     

A comparative life cycle assessment of petroleum and soybean-based lubricants

A comparative life cycle assessment examining soybean and petroleum-based lubricants is compiled using Monte Carlo analysis to assess system variability. Experimental data obtained from an aluminum manufacturing facility indicate significantly less soybean lubricant is required to achieve similar or superior performance. With improved performance and a lower use rate, a transition to soybean oil results in lower aggregate impacts of acidification, smog formation, and human health from criteria pollutants. Regardless of quantity consumed, soybean-based lubricants exhibit significant climate change and fossil fuel use benefits; however, eutrophication impacts are much greater due to non-point nutrient emissions. Fundamental tradeoffs in the carbon and nitrogen cycles are addressed in the analysis, demonstrating that a transition to soybean oil may result in climate change benefits at the expense of regional water quality.     

Beef production in balance: considerations for life cycle analyses

Life Cycle Assessments (LCA) are useful tools to analyze a product's "carbon footprint" (e.g., the net greenhouse gas (GHG) emissions expressed as standardized carbon dioxide equivalents per unit of product) considering all phases of the production chain. For beef, an LCA would include the GHG emissions from feed production, from the enteric fermentation of the cattle, from the cattle's waste, and from processing and transportation. Identifying the scope and scale of the LCA is critical and key to preventing inappropriate applications of the analysis (e.g., applying a global LCA for beef to the regional or national scale). Ideally, a LCA can integrate the complex biogeochemical processes responsible for GHG emissions and the disparate animal and agricultural management techniques used be different phases of the beef production chain (e.g., feedlot vs. cow-calf) and different production systems (e.g., conventional vs. organic).     

Assessing environmental impact of textile supply chain using life cycle assessment methodology

The environmental impact of textile supply chain of selected cotton, wool and polyester apparels consumed in Australia was accessed in this study using life cycle assessment methodology. The environmental impact category, climate change was used for this assessment. Climate change is related to the emissions of greenhouse gases to the atmosphere and the reference unit of climate change impact category is kg CO₂ equivalent. The environmental impact of these apparels was then scaled up based on their total consumption in Australia in 2015. The results highlight the differences in environmental impact between the three apparels. This study demonstrates that the main contributor to climate change is the consumer use stage for cotton and polyester apparel whereas wool apparel production process contributes more impact than consumer use stage. Energy use is the main factor of environmental impact. Sensitivity analysis was carried out based on the different parameters used to develop baseline model, such as change of transport from airfreight to sea freight; change of transport distance, change of consumer laundering behaviour. Around 10% CO₂ equivalent emission can be reduced from base case by reducing washing machine energy up to 40%. A high efficient washing machine and full load machine wash can save energy and reduce carbon emission.