Agricultural Life Cycle Assessment Research Articles

Agricultural life cycle assessment: a system-wide bibliometric research

Agricultural life cycle assessment: a system-wide bibliometric research

Swiss Agricultural Life Cycle Assessment: A method to assess the emissions and environmental impacts of agricultural systems and products

PurposeAgricultural production, which dominates the environmental impacts of the food sector, has specific characteristics that need to be considered in life cycle assessment (LCA) studies. Agricultural systems are open, difficult to manage and control, strongly depend on natural resources and their impacts are highly variable and influenced by soil, climate and farm management. A specific framework, efficient methods and tools are thus needed to adequately assess the environmental impacts of agricultural systems.MethodsWe present the Swiss Agricultural Life Cycle Assessment (SALCA) concept and method, developed for a detailed and specific analysis of agricultural systems. It comprises rules for the definition of system boundaries, functional unit and allocation, emission models, a life cycle inventory (LCI) database, calculation tools, impact assessment methods and concepts for analysis, interpretation and communication. This paper focuses on emission models for gaseous N, nitrate leaching, P emissions to water, soil erosion, pesticides, heavy metals, emissions from animal production and impact assessment methods for soil quality and biodiversity. The models are calculated at the crop, field, animal group and farm levels and are integrated in a consistent and harmonised framework, which is ensured by exchanging intermediate results between models.Results and discussionThe SALCA concept has been applied in numerous LCA studies for crops and crop products, cropping systems, animal husbandry systems and animal products, food and feed products, farms and product groups, the agrifood sector and food systems. The SALCA methodology has also been a backbone of the LCI databases ecoinvent, AGRIBALYSE and the World Food LCA database. The strengths of SALCA lie in its comprehensiveness, specificity to agriculture, harmonisation, broad applicability, consistency, comparability, flexibility and modularity. The extensive data demand and the high complexity, however, limit the application of SALCA to experts. The geographical scope is limited to Central and Western Europe, with a special focus on Switzerland. However, due to the modular and flexible design, an adaptation to other contexts is feasible with reasonable effort.ConclusionsSALCA enables answering a wide range of research questions related to environmental assessment and is applicable to various goals and scopes. A further development would be the inclusion of the social and economic dimensions to perform a full sustainability analysis in the SALCAsustain framework.

Regionalized environmental damages and life cycle cost of chickpea production using LC-IMPACT assessment

Modern intensive agriculture worldwide is generating increasing environmental and economic pressures that hinder its sustainable development. This study proposes the joint use life cycle assessment (LCA) and life cycle costing (LCC) to evaluate irrigated chickpea production (ICP) and the eco-environmental situation of dry farming (DFCP). Data are collected from 625 chickpea farmers in in the Kermanshah province of Iran. The most updated approach, LC-IMPACT, is applied for the first time globally in agricultural activity LCA. Results indicate that most impact categories of ICP have higher rates than DFCP. On-Field emissions and pesticides in DFCP, and nitrogen and phosphate in ICP, are identified as the main hotspots. The LCC analysis reveals that the total emissions cost (EC) for DFCP and ICP is 130 and 53 $ per one tone of chickpea (1TCP−1), respectively. Additionally, the LCC for DFCP and ICP is computed as 837 and 666 $ 1TCP−1. The eco-efficiency rate of damage categories in DFCP shows a better situation compared to the ICP scenario. The findings indicate that the DFCP scenario exhibits a higher level of environmental friendliness compared to the ICP scenario. Finally, it can be concluded that the joint use of LC-IMPACT assessment method and LCC can contribute to achieving better eco-environmental conditions in chickpea production.

Validating Farmland Biodiversity Life Cycle Assessment at the Landscape Scale.

Life cycle assessment (LCA) aims at providing standardized evaluations of processes involving resource use, human health, and environmental consequences. Currently, spatial dependencies are most often neglected, though they are essential for impact categories like biodiversity. The "Swiss Agricultural Life Cycle Assessment for Biodiversity (SALCA-BD)" evaluates the impact of agricultural field management on 11 indicator species groups. We tested if its performance can be improved by accounting for the spatial context of the individual fields. We used high-resolution bird/butterfly point observations in two agricultural regions in Switzerland and built linear mixed models to compare SALCA-BD scores to the observed species richness at the field/landscape scale. We calculated a set of landscape metrics, tested their relationship with the landscape-model prediction errors, and then added all significant metrics as additional predictors to the landscape models. Our results show that field-scale SALCA-BD scores were significantly related to the observed field-scale richness for both indicator groups. However, the performance decreased when aggregated to the landscape scale, with high variability between regions. Adding specific landscape metrics improved the landscape model for birds but not for butterflies. Integrating the spatial context to LCA biodiversity assessments could provide moderate benefits, while its usefulness depends on the conditions of the respective assessment.

Coupling of crop and livestock production can reduce the agricultural GHG emission from smallholder farms

Ensuring global food security and environmental sustainability is dependent upon the contribution of the world's hundred million smallholder farms, but the contributions of smallholder farms to global agricultural greenhouse gas (GHG) emissions have been understudied. We developed a localized agricultural life cycle assessment (LCA) database to calculate GHG emissions and made the first extensive assessment of the smallholder farms' GHG emission reduction potentials by coupling crop and livestock production (CCLP), a redesign of current practices toward sustainable agriculture in China. CCLP can reduce the GHG emission intensity by 17.67%, with its own feed and manure returning to the field as an essential path. Scenario analysis verified that greater GHG emission reduction (28.09%-41.32%) will be achieved by restructuring CCLP. Therefore, this mixed farming is a mode with broader benefits to provide sustainable agricultural practices for reducing GHG emissions fairly.

Optimal environmental design of nitrogen application rate for facultative wheat using life cycle assessment

Nitrogen (N) supply is a relevant factor in wheat production, affecting yield and yield components. However, this input plays a dominant role in the environmental impact level arising within all the on-farm growing processes. To assess the effects of N fertilization on environmental impact levels, the agricultural life cycle assessment (LCA) was performed for facultative wheat as affected by sowing date (autumn versus spring) and N fertilization (0, 50, 100, 150, and 200 kg ha−1) on a chernozem soil under Pannonian conditions in Eastern Austria for two years (2019/2020 and 2020/2021). In this study, an LCA was performed to find the optimal cropping design to achieve a low environmental impact with an adequate yield level. Processes from cradle to farm gate were involved within the system boundary. As the functional units, grain N yield and land demand for generating the same grain N yield were used. SimaPro software and the ReCiPe 2016 method with Midpoint and Endpoint characterization model were involved. Data were interpreted for 18 impact categories. From an environmental point of view, wheat crops with high doses of N (˃ 150 kg ha−1) were associated with the highest environmental impact. The appropriate grain N yield should be reached to balance the environmental impact resulting from the fertilizer application and all the other inputs. A sufficient increase in yield must be achieved with increased fertilization to justify additional emissions that are related to N fertilization. Variants of winter wheat with medium inputs of N (between 100 and 150 kg ha−1) were associated with the lowest impact on the environment. Consequently, according to environmental impact assessment, it is disadvantageous not to fertilize wheat with N or, on the contrary, to over-fertilize it with N.

Farm diversity impacts on food production, income generation and environmental preservation: The Swiss case

A sample of 239 farm year observations of Swiss farms was assessed at the product group level for analyzing the relationship between environmental and economic performance and correlations between product groups (Milk, Cattle, Cereal, Beets, and Potatoes). The farms cover the production regions valley, hill and mountains and practice organic production or proof of ecological performance (PEP), the Swiss standard production.The environmental dimension was covered by nine impact categories calculated by the Swiss Agricultural Life Cycle Assessment method (SALCA). The impacts were aggregated using a data envelopment analysis (DEA). The economic dimension is assessed by the family workforce income per product group calculated from a full cost data set from the Swiss farm accountancy data network (FADN). Hereby, all indirect costs, which cannot be directly attributed to the product groups, were allocated using standard costs.We also included productivity as a third dimension in our analysis, quantified as output per area for crop products and output per animal livestock unit for the animal product groups.No trade-offs between the environmental efficiency and the economic performance were identified. On the contrary, for Cattle and Milk we found significant synergies (1.5 times more observations show synergies than no effect or trade-offs).Furthermore we found that productivity correlated positively with environmental efficiency for Milk (coefficient = 0.27), Cattle (coefficient = 0.38) and Cereals (coefficient = 0.30), but only for Cattle (coefficient = 0.17) and Potatoes (coefficient = 0.47) it correlated with economic performance.For all product groups except Cereals, the organic farming system had 5% to 10 higher environmental efficiency and 5%–26% higher economic performance than the PEP farms. Although the differences were not significant, a consistent decrease up to −20% in environmental performance and productivity was observed between the valley/hill and the mountain region.Our results show no indication that farmers maximize their productivity or economic performance at the cost of environmental efficiency. However, the large variability suggests that there is a) room for improvement in several dimension simultaneously, and b) that maximizing productivity does not seem to be a necessity for these improvements.

Relevance of sludge management practices and substance modeling in LCA for decision-making: A case study in Chile

Reducing the costs and environmental impacts of sludge management is currently one of the main challenges faced by the wastewater treatment sector. Anaerobic digestion followed by land application has been widely endorsed as a low-impact approach to sludge management, mainly due to the recovery of biogas and the valorization of digestate. However, the influence that the operational conditions of digestion and the management practices of land application can have over the environmental performance of this strategy has been scarcely studied. Furthermore, most of the previous studies dealing with the environmental assessment of this strategy use simplified methods for estimating emissions after land application of sludge, and the lack of systematic accounting of these environmental flows might significantly affect the validity and comparability of the results. Therefore, this work performed an assessment of the influence that 4 relevant practices can have over the environmental impacts of this approach in the context of south-central Chile, providing a mass-balanced inventory for nitrogen, phosphorus and heavy metals in soil based on the ad hoc implementation of models developed for agricultural Life Cycle Assessment (LCA). A total of 16 scenarios were defined and 10 impact categories were evaluated, with the results showing that the environmental impacts were greatly influenced by the variables under study. Overall, solids retention time and the inclusion of pre-treatment mainly influenced climate change, fossil resource depletion and terrestrial ecotoxicity potential, while sludge application rate influenced the eutrophication, water ecotoxicity and human toxicity categories. The type of crop in the receiving soil was a significant driver behind the differences observed in the human toxicity category, which showed the highest variation and relevance in the final weighted result. The results clearly highlight the relevance of using context specific data as well as of quantifying the fate of nutrients, metals and heavy metals during LCA of sludge management. Based on the results, some policy and decision-making recommendations are formulated to optimize the environmental performance of sludge digestion and land application.

An approach to regionalise the life cycle inventories of Spanish agriculture: Monitoring the environmental impacts of orange and tomato crops

Agricultural life cycle assessment (LCA) at the sub-national regional level may be a valuable input for the decision-makers. Obtaining representative and sufficient data to develop life cycle inventories (LCIs) at that level is a relevant challenge. This study aims to contribute to the development of LCIs representative Spanish crops based on economic and operational information available in official sources to assess the average environmental impacts of these crops in the main producing regions. A comprehensive approach is proposed considering both the temporal variability and uncertainty of input data by using different methods (e.g. linear programming, weighted averages, Monte Carlo simulation, forecasted irrigation, etc.) to estimate the inventory data of reference holdings. From these inventories, the environmental assessment of those reference holdings is carried out. Two case studies are developed, on orange and tomato crops in the main producing regions, where climate change (CC), freshwater scarcity (WS), human toxicity non-cancer (HTnc), and freshwater ecotoxicity (ET) are evaluated. The environmental scores obtained differ significantly from region to region. The highest environmental scores of orange reference holdings correspond to Comunidad Valenciana for CC (1.94·10−1 kg CO2 eq.) HTnc (4.16·10−11 CTUh) and ET (7.45·10−3 CTUe), and to Andalucia in WS (17.4 m3 world eq.). As to greenhouse tomatoes, the highest scores correspond to Comunidad Valenciana in the four categories analysed (CC = 3.18 kg CO2 eq., HTnc = 3.6·10−9 CTUh, ET = 1.5 CTUe and WS = 13.3 m3 world eq.). The environmental scores estimated in this study are consistent with the literature, showing that the approach is useful to obtain a representative description of the environmental profile of crops from official statistical data and other information sources. Widening the data gathered in ECREA-FADN, and also that from other data sources used, would increase the quality of the environmental impact estimation.

Life Cycle Assessment on Agricultural Production: A Mini Review on Methodology, Application, and Challenges

Agricultural Life Cycle Assessment (LCA) is an effective tool for the quantitative evaluation and analysis of agricultural materials production and operation activities in various stages of the agricultural system. Based on the concept of life cycle, it comprehensively summarizes the impact of agriculture on the environment, which is an effective tool to promote the sustainability and green development of agriculture. In recent years, agricultural LCA has been widely used in the agroecosystem for resource and environmental impacts analysis. However, some challenges still exist in agricultural LCA, i.e., the environmental impact assessment index system needs to be improved; its application in different production mode is limited; and combination research with other models needs more attention. This paper discusses the above-mentioned challenges and recommends research priorities for both scientific development and improvements in practical implementation. In summary, further research is needed to construct a regional heterogeneity database and develop innovated methodologies to develop more meaningful functional units for agricultural products to complement LCA by other models. These efforts will make agricultural LCA more robust and effective in environmental impacts assessment to support decision making from individual farm to regional or (inter)national for the sustainable future of agriculture.

Integrating life cycle assessment into landscape studies: a postcard from Hulunbuir

ContextConventional life cycle assessment (LCA) has been increasingly criticized for lacking spatial information, especially for agricultural systems where high spatial variation and sensitivity is present.ObjectivesThe objective of this research is twofold: first, to assess the potential environmental impacts and the production efficiency of pastoralism farming, and, second, to identify the influence of the spatial distribution of farms on the environmental impacts, if any.MethodsA cradle-to-gate spatialized agricultural LCA was conducted for 45 farms surveyed from the Hulunbuir Grassland by splitting direct onsite processes from upstream processes, adopting the spatialized characterization factors (SCFs) of IMPACT World+.ResultsContrasting results were observed for different impact categories regarding whether upstream or onsite processes served as the environmental hotspot. While direct onsite animal emissions did not show spatial dependency at the inventory stage, its resulting impact scores demonstrated the most contrasting spatial patterns among various impact categories, depending on whether and how spatial resolution and location were introduced during the life cycle impact assessment (LCIA) stage. Statistical evidence supported a high emission cluster for farms located close to Hailar city compared to a low cluster for those located further south/west of the city.ConclusionsA cradle-to-gate spatialized agricultural LCA was proposed and applied to assess the environmental impacts of pastoralism farming in Hulunbuir Grassland. The overall spatial dependency of the LCA results was weak at the individual farm level, if present; it depended on the interactions between the spatial variation within the life cycle inventory and the spatial resolution and location of the SCFs. Environmental burden shifting occurred between different impact categories, and the policy challenge of how to increase production efficiency in the pastoralism system remains.

Sustainability Estimation of Oat:Pea Intercrops from the Agricultural Life Cycle Assessment Perspective

Winter cereal:legume intercropping is considered a sustainable arable farming system not only in temperate regions but also in Mediterranean environments. Previous studies have shown that with suitable crop stand composition, high grain yield can be achieved. In this study, a life cycle assessment (LCA) of the influence of sowing ratio and nitrogen (N) fertilization on grain nitrogen yield of oat (Avena sativa L.) and pea (Pisum sativum L.) in intercrops was performed to find the optimal design to achieve low environmental impact. This study compared the environmental impact of oat:pea intercrops using agricultural LCA. Monocrops of oat and pea and substitutive intercrops, which were fertilized with different levels of N, were compared. The system boundaries included all the processes from cradle to farm gate. Mass-based (grain N yield) and area-based (land demand for generating the same grain N yield) functional units were used. The results covered the impact categories related to the agricultural LCAs. The ReCiPe 2016 Midpoint and Endpoint characterization model was used for the data expression. According to the results, an unfertilized combination of oat and pea (50%:50%) had the lowest environmental impact in comparison with the other 14 assessed variants and selected impact categories. In the assessed framework, pea monocrops or intensively fertilized oat monocrops can also be considered as alternatives with relatively low impact on the environment. However, an appropriate grain N yield must be reached to balance the environmental impact resulting from the fertilizer inputs. The production and use of fertilizers had the greatest impact on the environment within the impact categories climate change, eutrophication, and ecotoxicity. The results indicated that high fertilizer inputs did not necessarily cause the highest environmental impact. In this respect, the achieved grain N yield level, the choice of allocation approach, the functional unit, and the data expression approach played dominant roles.

Agricultural LCA for Food Oil of Winter Rapeseed, Sunflower, and Hemp, Based on Czech Standard Cultivation Practices

The demand for food vegetable oil is rising and this trend is reflected in the agricultural sector of the Czech Republic. The traditional oil crops of the Czech Republic are winter rapeseed and sunflower. These oil crops have high demands on energy inputs, for example, in the form of land preparation and chemical protection. At the same time, they are characterized by high food oil production and oiliness. Moreover, marginal oils crops, such as hemp, are also gaining prominence. This work aimed to evaluate the environmental impacts associated with the cultivation of winter rapeseed and sunflowers based on standard cultivation practices typical of the conditions of the Czech Republic. For comparison, an intensive cultivation strategy for hemp was modelled, also corresponding to the conditions of the Czech Republic. This study assessed the environmental impact of traditional oil crops from the agricultural Life Cycle Assessment (LCA) perspective. The system boundaries included all the processes from the cradle to the farm gate. Mass-based (volume of food oil) and area-based (land demand for generating the same volume of food oil) functional units were employed. The results cover nine impact categories related to the agricultural LCA. ReCiPe Midpoint (H) characterization and normalization models were used for the data expression. Hemp is a plant with generally low demands on the inputs of the growing cycle but generally has a low oil production, which affects the character of the results relating to the goal and scope definition of the study. Hemp food oil thus generated a higher environmental impact per unit of production and area compared to sunflower and rapeseed food oil.

A scalable and spatiotemporally resolved agricultural life cycle assessment of California almonds

PurposeCalifornia’s Central Valley produces more than 75% of global commercial almond supply, making the life cycle performance of almond production in California of global interest. This article describes the life cycle assessment of California almond production using a Scalable, Process-based, Agronomically Responsive Cropping System Life Cycle Assessment (SPARCS-LCA) model that includes crop responses to orchard management and modeling of California’s water supply and biomass energy infrastructure.MethodsA spatially and temporally resolved LCA model was developed to reflect the regional climate, resource, and agronomic conditions across California’s Central Valley by hydrologic subregion (San Joaquin Valley, Sacramento Valley, and Tulare Lake regions). The model couples a LCA framework with region-specific data, including water supply infrastructure and economics, crop productivity response models, and dynamic co-product markets, to characterize the environmental performance of California almonds. Previous LCAs of California almond found that irrigation and management of co-products were most influential in determining life cycle CO2eq emissions and energy intensity of California almond production, and both have experienced extensive changes since previous studies due to drought and changing regulatory conditions, making them a focus of sensitivity and scenario analysis.Results and discussionResults using economic allocation show that 1 kg of hulled, brown-skin almond kernel at post-harvest facility gate causes 1.92 kg CO2eq (GWP100), 50.9 MJ energy use, and 4820 L freshwater use, with regional ranges of 2.0–2.69 kg CO2eq, 42.7–59.4 MJ, and 4540–5150 L, respectively. With a substitution approach for co-product allocation, 1 kg almond kernel results in 1.23 kg CO2eq, 18.05 MJ energy use, and 4804 L freshwater use, with regional ranges of 0.51–1.95 kg CO2eq, 3.68–36.5 MJ, and 4521–5140 L, respectively. Almond freshwater use is comparable with other nut crops in California and globally. Results showed significant variability across subregions. While the San Joaquin Valley performed best in most impact categories, the Tulare Lake region produced the lowest eutrophication impacts.ConclusionWhile CO2eq and energy intensity of almond production increased over previous estimates, so too did credits to the system for displacement of dairy feed. These changes result from a more comprehensive model scope and improved assumptions, as well as drought-related increases in groundwater depth and associated energy demand, and decreased utilization of biomass residues for energy recovery due to closure of bioenergy plants in California. The variation among different impact categories between subregions and over time highlight the need for spatially and temporally resolved agricultural LCA.

Accounting for correlational structures in stochastic comparative life cycle assessments through copula modeling

The presence of correlations between input parameters in a life cycle assessment (LCA) is a well-known issue. On top of that, the univariate distribution of environmental indicators, in most cases, does not follow the Gaussian nor the lognormal distribution. In this article, we introduce the copula modeling to build joint multivariate sampling spaces, irrespective of the marginal distributions of the environmental indicators, for LCA uncertainty analyses. To exemplify the proposed method, we integrate the copula modeling to the stochastic multiattribute analysis (SMAA) method to perform the normalization and weighting steps in a comparative agricultural LCA. An attributional LCA was performed to compare the environmental impact of two tomato production systems (GH, greenhouse; OF, open field) with different intensification levels. To choose the best environmental performance system, we implemented the outranking procedure of the SMAA method but based on the true multivariate distribution of the environmental indicators. As required by the SMAA method, initially, we fitted skewed multivariate distributions among the environmental indicators but accounting for their correlation structure through the copula method. Afterwards, the standard SMAA procedure was followed, leading to the calculation of overall scores indicating the environmental performance of the systems under comparison. After individual LCAs were performed for each grower, the variability observed in the primary data was propagated to the environmental indicators. The marginal distributions of the environmental indicators showed a right skewed trend which were fitted to gamma, log-normal, or Weibull distributions as applicable. The application of the copula method for the environmental indicators of the GH and OF systems resulted in D-vine models consisting of 46 and 45 bivariate copulas requiring 47 parameters each, respectively. Sampling the multivariate space configured by the D-vine models and integrating it with the SMAA method indicated that the OF system is more likely to have a better environmental performance with a rank acceptability index (RAI) of 57.6% while the GH system yielded a lower RAI (42.4%). We applied a stochastic unbiased approach to compare the environmental performance of agricultural systems but recognizing the correlation structure of the indicators. The copula method introduced here can be applied to uncertainty or multicriteria decision analysis where correlation needs to be accounted for. Joining the copula and the SMAA methods to produce an unbiased preference indicator allows to evaluate scenarios in a realistic way, producing results that can easily be communicated.

Cup plant, an alternative to conventional silage from a LCA perspective

The growing awareness of the importance of biodiversity in agroecosystems in increasing and ensuring the supply of biomass has led to heightened interest from governments and farmers in alternative crops. This article assesses one such alternative crop, cup plant (Silphium perfoliatum L.), in terms of the environmental aspects of cultivation for forage production. Many studies have previously focused on cup plant, but so far, this plant has not been assessed using the life cycle assessment (LCA) method. This study compares the environmental load of cup plant with the most commonly grown silage crops in Central European conditions—maize—and with another common forage crop—lucerne using LCA. The system boundaries include all the processes from cradle to farm gate and both mass-based (1 ton of dry matter) and area-based (1 ha of monoculture) functional units were chosen for the purposes of this study. The results cover the impact categories related to the agricultural LCAs, and the ReCiPe Midpoint (H) characterization model was used for the data expression, by using SimaPro 9.0.0.40 software. This study compares the cultivation of cup plant with the most commonly grown silage crop in Central European conditions—maize—and with another common forage crop—lucerne. The paper shows the potential of cup plant to replace conventional silage (maize and lucerne silage mix) with certain environmental savings in selected impact categories, and importantly, while still maintaining the same performance levels in dairy farming as with conventional silage, as already reported in previous publications. For the Czech Republic alone, this would, in practice, mean replacing up to 50,000 ha of silage maize and reducing the environmental load by about tens of percent or more within the various impact categories and years of cultivation. Cup plant can replace the yield and quality of silage maize, represents a lower environmental load per unit of production and unit of area and generally carries many other benefits. Thus, cup plant is a recommendable option for dairy farming. Given the recent experience and knowledge of the issue, the cup plant can be considered an effective alternative to conventional silage.

农业生命周期评价研究进展

PDF HTML阅读 XML下载 导出引用 引用提醒 农业生命周期评价研究进展 DOI: 10.5846/stxb201906201307 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41901255）；中国科学院战略性先导科技专项（A类）（XDA20010303） Research Progress of life cycle assessment on agriculture Author: Affiliation: Fund Project: The National Natural Science Foundation of China（41901255）；Strategic Priority Research Program of the Chinese Academy of Science (XDA20010303), 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:作为评价产品系统全链条环境影响的有效工具，生命周期评价（LCA）方法已广泛用于工业领域。农业领域也面临着高强度的资源和环境压力，LCA在农业领域的应用应运而生。旨在综述已有农业LCA研究的基础上，鉴别农业LCA应用存在的问题，并为农业LCA未来的发展提出建议。目前农业LCA存在系统边界和功能单位界定不明晰、缺少区域清单数据库、生命周期环境影响评价模型（LCIA）不能准确反映农业系统环境影响、结果解释存在误区等方面的问题。为了科学准确地衡量农业系统的环境影响，促进农业系统的可持续发展，文章认为农业LCA应该从以下几个方面加强研究，即科学界定评价的参照系、系统边界的扩大及功能单位的合理选取、区域异质性数据库构建与LCIA模型开发、基于组织农业LCA的开发以及对于利益相关者行为的研究。 Abstract:As an effective tool for evaluating the environmental impact of production system from cradle to grave, the Life Cycle Assessment (LCA) method has been widely used in relevant studies on the industrial sector. The agricultural sector is also accompanied by high-intensity resource and environmental pressures, and the application of LCA in agriculture has emerged. This paper aims to review the existing research in agricultural LCA, identify the problems of the application of LCA in agriculture, and make recommendations for the future development of agricultural LCA. At present, several challenges exist in agricultural LCAs: unclear definitions of system boundary and functional unit, lack of regional inventory databases, inaccurate life cycle impact assessment (LCIA) model in reflecting the environmental impact of the agricultural system, and misunderstanding in the interpretation of the results. In order to scientifically and accurately measure the environmental impacts of agricultural systems and promote their sustainable development, the article advocates that the agricultural LCA should strengthen research from the following aspects: the scientific setting of the reference system, expansion of system boundaries and rational selection of functional units, construction of the regionally heterogeneous database and development of LCIA model, development of LCA on organizational agriculture, and research on stakeholder behaviors. 参考文献 相似文献 引证文献

Leveraging Crop Budgets to Assess the Environmental Impact of Agricultural Operations

Highlights Agriculture Extension Resources should be used for regional life cycle assessments of agriculture. Fertilizer is the major contributing factor of environmental impact, when using a spatial functional unit. Ecoinvent may under-estimate the environmental impact of maize production. Abstract . Current attempts to quantify the sustainability of agricultural operations are hampered by the lack of information to adequately address variation of farming operations. Differences in weather, soil, local consumers, and transportation pathways affect the agricultural operation of a given parcel of land. These differences may significantly influence life cycle assessments involving agricultural systems. Agricultural extension publications and human expertise may fill gaps present in commonly utilized databases for environmental impact calculations. A methodology was developed integrating information from Nebraska Crop Budgets with Ecoinvent 3.6 in OpenLCA, to investigate pesticide production contribution and compare environmental impacts on a per acre and per bushel basis. Seven budgets were selected, outlining no-till corn production under no-rotation, soybean/corn rotation, and ecofallow schemes. Of thirteen tested pesticides, only five were greater than 5% of the total impact relative to 19-Corn in at least one impact category. Pesticide contribution was greatest for products containing multiple active ingredients and with higher yearly applied amounts. Exclusion of pesticide production in agricultural life cycle assessments may not significantly impact results. Relative impacts between budgets were greater than 83% on a per acre and per bushel basis compared to Ecoinvent, demonstrating life cycle assessments can be impacted by operational differences within similar production systems. Per acre impacts were 4% less to 227% greater than published maize grain production in Ecoinvent 3.6 for the United States. Per bushel impacts were similar at 6% to 280% greater. Result differences are dependent on the crop budget used and impact category considered. Fertilizer was the greatest contributor toward all tested categories. Per acre calculations were defined by applied nitrogen while per bushel calculations followed nitrogen productivity. With simple integration and specificity granted with crop budgets, extension resources should be used for region-specific life cycle assessments of agricultural and bio-based products to replace general assumptions. Keywords: Crop production, Extension, Food energy water nexus, Life cycle assessment, Sustainability.

Life cycle assessment of wheat production and wheat-based crop rotations.

In the northern Great Plains (NGP), wheat is the primary grain commodity. There is a need for the NGP to have a detailed analysis of environmental impacts for wheat-based agricultural production systems to better understand regional agroecosystems. This article provides a cradle-to-field gate life cycle assessment (LCA) for NGP dryland wheat (Triticum aestivum L.) production. The environmental impacts for winter wheat production using crop rotation and agricultural intensification are quantified. Fourteen no-till crop rotations ranging in duration from 2 to 6 yr were evaluated and compared using data from a historical 13-yr replicated rotation study (>300 observations). Midpoint LCA categories chosen for this comparison are energy, agricultural land use, climate change potential, freshwater eutrophication, and freshwater ecotoxicity due to their direct links with agricultural management practices. The NGP farmers commonly use a fallow period every other year due to moisture limitations. This specific agricultural practice and allocations within rotations are critical considerations within agricultural LCAs. Two aspects of fallow considerations and a sensitivity analysis were also performed. The allocated midpoint impacts between crops in rotational studies averaged 0.31, 0.79, 0.62, and 0.63kg CO2 eq. per unit of winter wheat when energy, economic, mass, and cereal unit allocations were used, respectively. Economic analysis of the studied experimental crop was performed; results demonstrated that crop insurance policies improved diversification economics by 20%. Agricultural diversification benefits and burdens were better represented by endpoint damage assessments than by midpoint impact analysis.

Assessing the climate and eutrophication impacts of grass cultivation at five sites in Sweden

ABSTRACT In this study, Life Cycle Assessment (LCA) methodology was combined with the agro-ecosystem model DNDC to assess the climate and eutrophication impacts of perennial grass cultivation at five different sites in Sweden. The system was evaluated for two fertilisation rates, 140 and 200 kg N ha−1. The climate impact showed large variation between the investigated sites. The largest contribution to the climate impact was through soil N2O emissions and emissions associated with mineral fertiliser manufacturing. The highest climate impact was predicted for the site with the highest clay and initial organic carbon content, while lower impacts were predicted for the sandy loam soils, due to low N2O emissions, and for the silty clay loam, due to high carbon sequestration rate. The highest eutrophication potential was estimated for the sandy loam soils, while the sites with finer soil texture had lower eutrophication potential. According to the results, soil properties and weather conditions were more important than fertilisation rate for the climate impact of the system assessed. It was concluded that agro-ecosystem models can add a spatial and temporal dimension to environmental impact assessment in agricultural LCA studies. The results could be used to assist policymakers in optimising use of agricultural land.