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5 November 2021

Environmental Impact Assessment of Agricultural Production Using LCA: A Review

,
and
1
School of the Environment, Florida Agricultural and Mechanical University, Tallahassee, FL 32307, USA
2
College of Agriculture and Food Sciences, Florida Agricultural and Mechanical University, Tallahassee, FL 32307, USA
3
Biological Systems Engineering, Florida Agricultural and Mechanical University, Tallahassee, FL 32307, USA
*
Author to whom correspondence should be addressed.
Climate2021, 9(11), 164;https://doi.org/10.3390/cli9110164
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Abstract

Life cycle impact assessment (LCA) provides a better understanding of the energy, water, and material input and evaluates any production system’s output impacts. LCA has been carried out on various crops and products across the world. Some countries, however, have none or only a few studies. Here, we present the results of a literature review, following the PRISMA protocol, of what has been done in LCA to help stakeholders in these regions to understand the environmental impact at different stages of a product. The published literature was examined using the Google Scholar database to synthesize LCA research on agricultural activities, and 74 studies were analyzed. The evaluated papers are extensively studied in order to comprehend the various impact categories involved in LCA. The study reveals that tomatoes and wheat were the major crops considered in LCA. The major environmental impacts, namely, human toxicity potential and terrestrial ecotoxicity potential, were the major focus. Furthermore, the most used impact methods were CML, ISO, and IPCC. It was also found that studies were most often conducted in the European sector since most models and databases are suited for European agri-food products. The literature review did not focus on a specific region or a crop. Consequently, many studies appeared while searching using the keywords. Notwithstanding such limitations, this review provides a valuable reference point for those practicing LCA.

1. Introduction

Food supply chains (FSCs) are very complex. There are many components involved in FSCs that process, produce, package, store, transfer, distribute, and market food products to final consumers [1]. Each element in the FSC process is essential, as in any other supply chain; a change in one component affects the others. The relationship between the food system and the economy, environment, and society is mentioned by some organizations and agencies, such as the Food and Agricultural Organization (FAO), Institute of Medicine (IOM), and National Research Council (NRC), when they define the FSC [2]. Therefore, the most crucial question is as follows: Which food production system is more sustainable for the environment and communities?
There are many concerns about food resources and massive population growth, such as meeting the food demand for the world’s population, production, and food consumption [1]. The total crop production must double or increase by at least 70% to meet the increasing world population’s demand by 2050 [3]. Models have estimated that a 2.4% annual increase in crop yield is necessary to reach the 2050 demand [4]. The rise in food demand results in substantial energy and resource use by the food supply chain, leading to different environmental impacts. Many organizations have mentioned environmental impacts associated with food production, including the use of land, water, and climate change. Significant environmental challenges that humans face are primarily due to climate change and the predicted future shortage of fossil fuels [5]. Farming methods, fertilizers, pesticides, water pumping, tractors to prepare the land, and transport of the crops or final food products via railroads, trucks, airplanes, or ships can all impact the environment. Lastly, food processing and food preservation methods such as refrigeration and packaging also contribute to environmental damages. There are many production sectors involved in environmental impacts, and one of them is the agricultural sector.
According to the Environmental Protection Agency (EPA), agricultural chemicals and pesticide manufacturing are two of the 68 area source groups that account for 90% of the overall emissions of the 30 urban air toxins. For example, in 2018, greenhouse gas (GHG) emissions from the agriculture economic sector accounted for 9.9% of total US greenhouse gas emissions. Furthermore, GHG from agriculture has increased by 10.1% since 1990 [6]. One of the direct greenhouse gases is nitrous oxide. Agricultural soil management operations such as synthetic and organic fertilizers and other cropping techniques, the management of manure, and the burning of agricultural wastes produce nitrous oxide. Agricultural soil management is the major source of N2O emissions in the US, accounting for around 75% of total emissions [7]. Agricultural soils, for example, are a major source of NOx pollution in California, with soil NOx emissions in the state’s Central Valley region being particularly high. Therefore, it is necessary to quantify the impacts of agricultural products along the food supply chain for sustainable production and consumption systems.
Since the number of operations in the food system is large and complex, many studies have used the life cycle assessment (LCA) methodology as a tool to study the overall resources used and the environmental impact of food products over its entire life cycle [8]. It is best known for its qualitative and quantitative analysis of a product’s environmental aspects over its whole life cycle [9]. Products in this context include both goods and services [10]. Environmental impacts in the LCA context refer to the adverse effects on the areas of concern such as the ecosystem, human health, and natural resources. Due to the limitation of raw materials and energy resources, LCA has been used since the 1960s to find solutions for sustainable productions [11].
Such research on the crop supply chain provides helpful information from the economic, social, and environmental perspectives. Using the LCA offers a better understanding of the energy, water, and material input and evaluates the outputs’ impacts. Thus, decision-makers in various fields can regulate new policies and use modern practices to improve the production supply chains. As observed in previous studies [9,12], many authors have used LCA to address environmental impacts over the entire life cycle of crops. However, the world’s largest industrial sector, the food supply chain, involves various crops and products that still need to be addressed by the LCA.
Therefore, this study’s broad objective is to synthesize the LCA studies relating to different environmental impacts from agricultural production to support stakeholders with decision-making. Besides, an in-depth analysis of the various steps involved in LCA is provided.

2. Materials and Methods

A literature review of published articles in international journals was undertaken using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to address the research aims.

2.1. Eligibility Criteria

The studies that applied the following selection criteria were chosen to reduce the number of articles: (i) using the LCA method, (ii) including GHG in their impact category and/or ecotoxicity, and (iii) researching agriculture products. A total of 36 research articles were eliminated because they were about FSCs and not GHG/ecotoxicity as an effect category, did not apply the LCA methodology, or utilized the LCA method for nonagricultural products. The LCA studies were analyzed extensively considering four phases of the LCA:
  • Goal and scope definition,
  • Life cycle inventory,
  • Life cycle impact assessment,
  • Life cycle interpretation/recommendation options.

2.2. Search Strategy

The literature review was done through the Google Scholar database. The keyword “LCA crop production” was used in the initial step, which yielded 59,100 studies as of July 2021. Later, more specific keywords were used, such as “agri-food supply chain and LCA” and “agri-food supply chain and GHG” combined with different fruit and vegetable products such as corn, peanuts, wheat, tomato, and apple. Nevertheless, the number of studies available remained enormous, the largest number of articles we got when we used the above key word with different crops was 7330, while the smallest number was 1820. A total of 110 articles were downloaded and analyzed. Twenty-nine studies were excluded because they were about FSCs and not about GHG/ecotoxicity as an effect category, or because they utilized the LCA method.
Furthermore, seven more were excluded because they used the LCA method for non-agricultural products. Accordingly, we ended up with 74 articles after applying the selection criteria. Figure 1 shows the steps used throughout the review and the inclusion criteria for the literature.
Figure 1. Steps followed for review and the inclusion/exclusion criteria.

2.3. Categorization

The data obtained from the reviewed articles included the year of study, the aim of the study, and the different steps involved in LCA assessment, which are discussed in the results section. The timeline, different components, the approach of the LCA, application of the LCA concept in the impact analysis, and suggestions for a sustainable food system are all covered.

2.4. Data Analysis

The analysis was carried out by obtaining the necessary information from the literature, as given in Table A1 and Table A2 (Appendix A). Then, the information was visualized by means of collapsible trees, bar charts, doughnut figures, and word clouds after the information was classified into different result sections. Word clouds have evolved as a straightforward and visually appealing technique of text representation. They are used in a variety of contexts to offer an overview by reducing text down to the most frequently occurring terms. This is usually done statistically as a pure text summary [13,14]. Word clouds can be the initial step to refine the important concepts of results, which could save a great deal of time for other researchers since they already know where to start and the most common terms and ideas [15]. Pie and doughnut charts represent the relationship of parts with the whole [16,17]. Collapsible trees, bar charts, and doughnut figures are designed to provide greater numerical detail. Combining word clouds and bar charts allowed presenting both qualitative and quantitative information on LCA results.
The collapsible tree diagram was created with R software Version 3.6.1, and the bar and doughnut figures were created with Microsoft Excel. When making word cloud figures using the word cloud online website (https://www.jasondavies.com/wordcloud/ accessed on November 2021), each word must be typed correctly since the size and the color of the words in the figure are affected by the number of words entered. Therefore, it is essential to make sure that the number of entered words is accurate.
Lastly, the study was organized in IMRAD format, which is the most common format for scientific papers. The term represents the first letters of the words introduction, materials and methods, results, and discussion. IMRAD format facilitates knowledge acquisition and enables easy evaluation of an article [18]. Currently, IMRAD is used by the majority of academic publications. Before the IMRAD structure, all academic writing followed the IBC (introduction, body, and conclusion) pattern. The IMRAD format is only a more specified variant of the IBC format. [19]. It is important to keep in mind that no one journal follows a standard or consistent format. Each journal has its structure, yet they all have a guideline for authors [20].

3. Results

3.1. Snapshot of Selected Studies

The characteristics of publications during 1998–2021 are displayed in Figure 2 to obtain an overview of LCA research. The number of publications per year has increased steadily since 2008, following development of the ISO standard.
Figure 2. Frequency of studies related to LCA of agricultural production from 1998 to 2021 (n = 74).
Critiques of the ISO 14040 series pre-2006 were that LCA is too nascent [21], and ISO 14040 does not address uncertainty, weighting, valuation, and allocation [22].
The release of the latest version of the ISO 14040 standard in 2006 explains why LCA research is attracting more attention. Moreover, some have recently gone so far as to state that the ISO 14040: 2006 series “has proven a suitable tool for sustainability assessment” [13,14]. Fava et al. (2009) claimed that ISO 14040 should be the basis for future LCA studies [23].
Studies found that the most common tool to study the impact on the environment associated with a product over its life cycle in the agri-food sector was the LCA ISO 14040 standard [14,15]. LCA ISO 14040 has four main phases: (1) goal and scope, which is the essential component of the LCA, (2) qualitative and/or quantitative inventory analysis of the used resources and the emissions released from the life cycle of a product, (3) life cycle impact assessment, which can be divided into classification, characterization, and evaluation, and (4) the interpretation, involving the identification of key issues, evaluation (including checking completeness, sensitivity, and consistency), and development of conclusions together with recommendations, as defined by ISO 14043 (Figure 3). The details of each phase are discussed below.
Figure 3. Overview of life cycle assessment (LCA) phases.

3.2. Phase 1: Goal and Scope Definition

3.2.1. Goal

According to Lee and Inaba (2004), the following questions should be addressed to set up the goal: Why perform LCA, who is the target audience, and what is the product under the LCA study [10]? These were recognized from the reviewed articles while examining the first phase of the LCA, as given in Figure 4. Some of the studies stated the answers to these questions directly, whereas others addressed them indirectly. Figure 5, Figure 6 and Figure 7 show the most common responses to each question.
Figure 4. Phase 1 (goal and scope definition) of life cycle assessment (LCA).
Figure 5. Quantitative and qualitative representation of the common aims of LCA from the literature.
Figure 6. Target audiences in the literature represented as bars (quantitative) and a word cloud (qualitative).
Figure 7. Common agricultural products used in LCA studies.

Aims of LCA

As indicated in the literature, LCA studies can be partitioned into two major categories: descriptive and comparative. Descriptions aim to recognize the natural load of a chosen framework, while comparisons aim to differentiate between two frameworks. Among the discussed papers, 48 were descriptive, while 30 were comparative. As noted, the most common aim was to assess agricultural production, cultivation, processing, packaging, transport, and emission at all production stages to recognize the vast issues and to propose reasonable alternatives that decrease the environmental effects (Figure 5). The purpose of this review was to better understand how to use LCA to evaluate the environmental impact of agricultural production. The least common goal was to compare LCA to other methods, which may be due to the difficulty of making a fair comparison in terms of method performance.

Target Audience

The target audience defines who undertakes or commissions an LCA and for whom. It is critical to understand who will use the LCA results to provide them with helpful information. The majority of articles have multiple target audiences (TAs). Politicians working on climate change, decision-makers, and policymakers on global warming potential (GWP) footprints related to food and common agricultural policy (CAP) were the most common TAs, with 10 studies. Additionally, several studies targeted government sectors such as food sector policymakers, the country’s agriculture sector, and the fruit and vegetable sector. Following that, the producers, namely, the farmers and the producing industry, were targeted in eight studies, six of which provided information to the consumer on a local and international scale (see Figure 6). People working on social and economic development, such as government policymakers for sustainable consumption and production, future ecolabeling programs, and those working to improve the environmental and financial sustainability of existing agricultural systems, were also targeted. Another target audience was represented by the Florida food, agri-food, and citrus industries. As shown in Figure 6, only 35 of the 74 research articles analyzed clearly stated their target audience. The frequency of target audiences is also displayed as a word cloud for a rapid overview.

Agricultural

We divided the products into 11 categories: tomato, fruits, citrus, vegetable, fresh salad, grains, seeds, oil, sugar, flower, and trees, as shown in Figure 7. The most common product was tomato; 13 studies analyzed tomato production, including fresh tomato, canned tomato (whole peeled, paste, and diced), and ketchup. The second most common product was wheat with nine studies. Because some studies involved more than one crop, that explains why the same reference was used for multiple crop groups and why the number of studies on the chart exceeds the number of studies covered. Tomato production was separated into three categories since three types of tomato products (fresh tomato, canned tomato, and tomato ketchup) were considered, as indicated in the diagram.

3.2.2. Scope

The scope defines the product system boundaries that determine which unit processes should be included in the LCA analysis and which should be excluded. Table A2 (Appendix A) includes more information on all 74 studies, including their inputs and outputs inside and outside of the scope. Most studies (14) contained three to four phases in their boundaries, as shown in Figure 8A. There are two explanations for not including the eliminated phases in the majority of articles. The first is a lack of data and knowledge about individual inputs, making it difficult to get a decent overall view. Secondly, some authors excluded the minor influence stages because it was impossible to include all phases.
Figure 8. (A) Number of stages included in the systems obtained from the literature; (B) quantitative and qualitative illustration of the starting and ending points of the included stages as boundaries.
Since we are looking at the agri-food supply chain, most of the articles noticeably had similar steps when designing their boundaries. Depending on the selected crop and the target audience, there were slight differences in the scope’s starting point and finishing point (Figure 8B). According to the review, 47 studies started their scope from the nursery stage (cradle), which involves preparing the raw materials, buildings, and field or land. Furthermore, 25 studies began their scope from the farming stage (farm gate). Considering our focus on agricultural production, only one study started their scope after the farming stage.
Similarly, the final stage differed from one study to another, ranging from the farming stage to the grave, including the product’s processing, packaging, storing, and transferring stages. Thirty-one studies in the literature review included steps until the crop harvesting stage, whereas 16 authors included some or all of the processing, packaging, and storing stages in the study’s scope. A number of reviewed studies reached the point of distribution and consumption in their analysis. Disposal and waste management were the final stages in some studies, with 10 articles including the end-of-life phase in their analysis (Figure 8B). One study did not specific boundaries; thus, the number in Figure 8B is less than the number of studies reviewed [24].

3.2.3. Functional Unit

Another step of the goal and scope phase is to choose a functional unit of the scope. A functional unit is the reference unit in which elementary flows from the inventory until the impact assessment stage are represented. Selecting the ideal functional unit is necessary during the boundary designation step. The functional unit is dependent on the type of input materials (raw material) and the final products. Accordingly, the input unit might be separate from the outputs. For example, the output such as GHG emissions could be in kg·ha−1 while the final product could in tons or the input material could be in kWh for energy consumption and kg for fertilizers. Figure 9 shows the most common functional units used in previous studies.
Figure 9. Functional units identified from the studies.

3.2.4. Data Quality Requirement

The reliability of the results from LCA studies strongly depends on how data quality requirements are met. The following parameters should be considered: time-related coverage (selected year), geographical coverage (study area), and technology coverage (technology used in the processes stages). This paper examined the temporal and spatial data in detail and the used machinery in general.
It is understood from the literature review that most studies collected their data for a single year of cultivation (Figure 10B). The spatial scale of the analysis (global or regional) depends on the impact category. For example, global warming is a worldwide issue, whereas acidification is a regional issue. Furthermore, two countries were commonly represented in the evaluated research, Italy and the United States, with 17 and 14 studies, respectively (Figure 10A). When it comes to the technology used in each activity, the majority of the tools mentioned were agricultural equipment, which is to be expected given that we are investigating crop production.
Figure 10. (A) Quantitative (bars) and qualitative (word cloud) representation of the geographic coverage considered in the reviewed studies; (B) donut chart depicting the temporal scales used in the literature.

3.3. Phase 2: Life Cycle Inventory

The second step of the LCA is the life cycle inventory analysis (LCI). The product’s life cycle inventory results in an LCA study are obtained by summing up all fractional contributions of the input and output from each unit process in the product’s production system. Thus, LCI generates quantitative environmental information of a product throughout its entire life cycle.
Most studies at this stage specified the input material (water, fertilizer, pesticide, diesel, etc.) in each process of the production included in the scope, as well as the output (harvested crop, waste, emission to the air, soil, and water, etc.). Furthermore, they mentioned the sources of the inventory data (Figure 11), typically being from primary and/or secondary data sources. Primary data are obtained from specific processes throughout the life cycle of the researched product. Process activity data (physical measures of a process that results in GHG emissions or removal), direct emissions data (determined through direct monitoring, stoichiometry, mass balance, or similar methods) from a specific site, or data averaged across all sites containing the specific process are all examples of primary data [25]. Secondary data are collected from government departments, organizational records, and studies that previously gathered information from primary sources and made it available to other researchers.
Figure 11. Phase 2 (inventory) of life cycle assessment (LCA).
About 48% of the studies used secondary data, 13% used primary data, and 35% used both. One study collected data from a real farm experience. Three authors conducted interviews with owners to collect the data. Two studies used surveys with specific questions to collect the required information. One study mentioned that the source was primary, but the article did not specify their method. Seven studies utilized primary data, while the other nine used secondary data. The authors of the examined research utilized two types of secondary data methods: databases and previous studies. Eleven of the studies used databases, while five of them used previous studies. Five writers, on the other hand, gathered inventory data from databases and prior studies. Twenty-six studies utilized both primary and secondary approaches to reduce the uncertainty of their findings (Figure 12A,B).
Figure 12. (A) Data sources of the inventory stage rendered as a pie chart; (B) breakdown of primary and secondary data into various sources as obtained from the studies.

3.4. Phase 3: Life Cycle Impact Assessment

In life cycle impact assessment (LCIA), the significance of a product system’s potential environmental impacts, based on life cycle inventory results, is evaluated using LCIA. The LCIA consists of several elements: classification, characterization, normalization, and weighting. Of these four elements, normalization and weighting are considered optional, while the first two are mandatory elements in LCIA [10] (Figure 13). As shown in Figure 14, all 74 reviewed studies completed the classification and characterization phases, whereas 14 studies completed normalization and 10 completed weighting. Few studies included the waiting stage since it is optional and challenging.
Figure 13. Phase 3 (impact assessment) of life cycle assessment (LCA).
Figure 14. Quantitative and qualitative representation of the frequency of components of the LCIA phase in the reviewed studies.
The first step is classification, which involves identifying the impact assessment method. The most common standard method was the CML with various versions, such as CML 2 baseline 2000 V2/world, developed by the Center for Environmental Studies, and CML 2000 produced by the Center of Environmental Science of Leiden University. The second most common methods were ISO 14044 (2006), ISO (2000), and ISO 14040, followed by many other methods, such as IPCC 2001 GWP 100, proposed by the Intergovernmental Panel on Climate Change. For more information about the methods used in the studies, see Figure 15. The model used to calculate the impact is determined by the impact category the author intends to examine. As a result, LCA, ISO, and IPCC were the most commonly used impact methods since they provide categorization factors for ecotoxicity and climate change, which were among the criteria used to select articles for this review.
Figure 15. LCIA methods obtained from the literature review denoted by means of bar plots and a world cloud (classification).
Choosing the correct method for the LCA’s impact assessment stage depends on the impact category under investigation. Each method has categories; for example, CML 2000 has 10 environmental impact categories: abiotic depletion, global warming, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, photochemical oxidation, acidification, and eutrophication.
In the process to quantify the impact of a procedure or material used, impact categories are first chosen, followed by quantifying environmental impact in each impact category using the equivalency approach. This process is termed “characterization” [10]. Characterization includes the emissions to air, soil, and water, as represented in Figure 16. The most prevalent impact categories in the 74 papers were human toxicity and ecotoxicity, with 48 and 41 studies, respectively. Moreover, 34 studies included global warming potential as an effect category, whereas marine pollution (26 articles), freshwater aquatic ecotoxicity (23 articles), and acidification potential (22 articles) were topics of the remaining studies (Figure 16).
Figure 16. Illustration of LCIA impact categories from the literature (characterization).

3.5. Phase 4: Life Cycle Interpretation/Recommendation Options

The primary purpose of interpretation, which is the last phase of the LCA, is to use the inventory results and impact assessment analysis to evaluate the starting point for product improvement. The starting point is to understand the process tree and then identify the key issues, i.e., the key processes, materials, activities, components, or even life cycle stages in developing a product. The primary purpose is followed up with improvement recommendations to find more environmentally friendly designs and/or process modification. Studies applied dominance analysis and marginal analysis to identify the key issues. The dominant aspects of the inventory table may be revealed by studying the environmental elements of a process matrix. An arbitrarily chosen criterion, such as “contribution greater than 1% of the total impact”, can be applied in identifying key issues from the matrix. Marginal analysis illustrates the changes in the process to which the intervention, effect, or index is most sensitive. In theory, marginal analysis is a powerful tool in determining product improvement options [8,26].
Many studies stated that, for a complete understanding of the significant driver of the impacts, it is necessary to include all stages and material used through a product’s life cycle, which is very challenging due to a lack of information and databases. However, depending on the aim of the LCA research, the literature review revealed a number of critical concerns, such as emissions from chemical and energy usage, the cultivation method used, land-use problems, and consumption waste.
Furthermore, studies in the literature proposed several recommendations for improving the agri-food system and reducing environmental consequences. One of them was adhering to the EPA and USDA pesticide and fertilizer guidelines. A frequent proposal was to use agricultural waste as animal feed. The most common request, however, was to enhance production without increasing inputs (Figure 17).
Figure 17. Phase 4 (interpretation/recommendation) of life cycle assessment (LCA).

4. Discussion

The present study reviewed articles related to the environmental impacts of agricultural production in LCA assessment. The main steps in conducting an LCA are defining the purpose of the study and boundary stages involved in the analysis, collecting the data of the inventory phase, estimating the impact of the involved process and used material, and then identifying the key issues, followed up with improvement recommendations. Most studies followed these steps, and some of them had common impact categories. However, implementing LCA is challenging and necessitates meticulous data collection.

4.1. Choice of Time, Spatial Domain, and Elementary Flows in LCA

Nearly 17% of studies did not mention the temporal scale of their analyses, depicting the inherent limitation of ISO 14040/ISO 14044 in considering the time period of evolution and process variations pertaining to diverse impact categories. The highest temporal resolution obtained from the literature was seasonal (4% of studies). The choice of time in LCA depends on the spatial and temporal scale of the impact categories considered. For example, the temporal scale of ecotoxicity varies from hours to years. On the other hand, ecotoxicity impacts have multiple transport pathways such as air, water, and soil emissions with diverse temporal scales. Establishing a time frame for the evaluation in LCA is challenging, as both very lengthy and very short periods of assessment are not practicable depending on the topic of the LCA. Extremely short timescales violate the concept of intergenerational equality, whereas extremely long ones marginalize short-term actions, lowering the incentive to act [27]. Consequently, care should be taken when defining the temporal scale of inventory flows.
About half of the studies (49%) used secondary data collection for the LCA, acquiring data from websites and previous studies. The studies that constituted primary datasets were fewer due to the trouble of obtaining data at the desired spatial/temporal resolution for the inventory flows. The selection of impact categories and spatial domains (Figure 16) clearly reflects a preference for secondary datasets. The major categories studied were human toxicity potential and terrestrial ecotoxicity (the primary contributor being agricultural pesticide emissions). Studies used the approximated characterization factor from models for a particular spatial and temporal horizon to assess the potential impacts. Multimedia chemical exposure models such as CalTOX [28], USES-LCA [28,29], IMPACT 2002 [30], and USEtox [31] can provide the time-dependent concentrations of a chemical in the environmental compartments of air, soil, water, plants, and sediments. The potential impacts are characterized on the basis of the chemical’s fate in an environmental partition and its effect.

4.2. Impact Assessment

The quantity of the input material at each stage of the crop production chain can reduce GHG, as well as emissions, including energy use (diesel, fuel, electricity) both on farm (crop production, machinery use) and off farm (transportation, refrigeration). Additional emissions include fertilizer production and use (N, P2O5, K2O), pesticide use (fungicide, herbicide, insecticide), raw material production and transportation, packaging production, and disposal (Table A2). These sources of emissions contribute to environmental impacts in various ways, including human toxicity, terrestrial toxicity, freshwater toxicity, aquatic toxicity, global warming, and acidification (Figure 16). It has been demonstrated that low-input crops have minimal impacts, but high-input crops have high impacts [32]. Furthermore, the type of input can affect the rate of the impacts. For example, replacing Thomas slag with triple superphosphate reduced the toxicity associated with the presence of heavy metals [33]. Simultaneously, replacing urea with ammonium nitrate reduced the influence of fertilization on eutrophication and acidity induced by ammonia volatilization [34].

4.3. LCA as a Tool in Environmental Policy Decisions

In order to achieve the population demand in the future, increasing food production is not the only pathway to increase food availability. Increased food production necessitates either more land or increased fertilizer and pesticide use on current arable land, with negative environmental consequences such as elevated GHG emissions, biodiversity loss, water contamination, and soil erosion [35]. That explains why, among the LCA papers, the most common target audiences were policymakers and producers, whereby policymakers regulate new policies for upcoming issues and producers follow these rules. The LCA methodology can be used to identify parameters and their variability in order to assist producers, wholesale and retail consumers, and policymakers in aligning their practices and purchasing decisions with low-carbon goals. LCA can also be used to analyze different production systems in order to quantify differences in input consumption and environmental consequences. The key parameters and their variability are then addressed to offer stakeholder metrics for evaluating and aligning their agricultural processes, purchasing decisions, and policies to optimize production supply chains.

4.4. Challenges in Collecting the Information and Limitations

Obtaining each LCA component from the reviewed studies is not simple for the reader due to the authors’ descriptive and nonexhaustive approach. Section 3 shows that diverse communities can benefit from this study on a local, international, and global scale. Hence, the author could have used a table or a flow chart to present the flow of components and stages to summarize the four phases and their components to enable the reader to focus on helpful information.
Another challenge is to identify what information needs to be included in the phases of the LCA. One of the essential characteristics of phase one of the LCA is using a functional unit; some authors mentioned it in the goal section while others mentioned it in the scope section. Noticeably, studies with an economic purpose often did not clearly report the functional unit.
The necessity of incorporating all production processes and their input materials, analyzing all phases to understand the environmental effect, and obtaining an optimal outcome from the LCA analysis of food production systems was emphasized by researchers. However, that is neither possible nor practical because of data limitations and cost restrictions [10]. Accordingly, the minor influential stages were excluded. Hence, most studies focused on a single phase of the food production chain. For example, some studies focused on the cultivation phase because they considered that the food production system’s environmental impact mainly comes from farming activities.
The literature review did not focus on a specific region or a crop. Consequently, many studies appeared while searching using the keywords. Therefore, we included 74 articles related to LCA in agricultural production in general, as well as GHG emissions and ecotoxicity as an LCA impact category.

4.5. Assumptions Used, Benefits, and Recommendations

The LCA of crops along a food supply chain can provide helpful information from an economic, social, and environmental perspective. Using the LCA, stakeholders can better understand the energy, water, and material input and evaluate the outputs’ environmental impacts. Thus, they can regulate new policies and use modern practices to improve the production supply chains.
A substantial understanding of each phase of the LCA is required to present an accurate food product’s environmental impact. This paper clearly explains the LCA’s major components that can serve as a primer for the scientific community. Specifically, because LCA is a systematic tool that allows for analyzing a product throughout its life cycle, LCA is used to study the economic value and importance from the local and global perspectives.
If the final product’s functional unit is introduced at either the goal or the scope stage, the study results would be unaffected from our perspective. However, we recommend illustrating the input’s measurement unit and the outputs while illustrating the production scope, followed by a table of units to be more readable for the audience to understand at which stage the inputs are being used and to represent the elementary flows. Defining the system boundary determines the impact pathway for an impact category that links the elementary flows from inventory to the endpoint of analysis. It is clear that the system boundary processes need to be defined according to the study’s goal and the impact category. Furthermore, the functional unit must be clearly defined to explain the elementary flows from inventory to the endpoint. It is essential to know the impact category that the LCA aims to estimate, which processes are related to it, and their cause–effect relationships. The impact assessment studies were mostly conducted in the European sector since most models and databases are suited for European agri-food products.

4.6. Research Gaps

The information obtained from the literature sheds light on some of the future research needs: (a) the impact of land use on GHG emissions [36], (b) LCA applications based on irrigation techniques using solar energy dealing with waste streams [37], (c) LCA of processed and homegrown vegetables [38], (d) packaging of foods with eco-design solutions [8], and (e) applications of LCA in organic agricultural practices, fertilization practices, mulching and milling techniques, and achievable production yields [39]. Some studies have called for more LCA applications in non-European and non-OECD countries to make their agri-food sector more environmentally friendly [40]. Therefore, it is understood that LCA can be used to make the agri-food supply chain more sustainable.
The inventory flows obtained from the present review point to the inter-dependency of three sectors in LCA: energy, food, and water. Consequently, policymakers can use LCA as a tool to spot the crucial areas that need improvisation within the framework of the food–energy–water nexus. Moreover, it is imperative to understand the drivers of environmental policy for selecting an environmentally friendly agri-food supply system. The regional variation of this nexus calls for more regional LCA assessments based on the allocation of resources. More research is needed to explore future scenarios [41] that drive resource consumption and policy design for long-term sustainability utilizing the LCA framework.

Funding

This material was based on work partially supported by the USDA-National Institute of Food and Agriculture’s Evans-Allen Project, grant 11979180/2016-01711 and 1890 Institution Capacity Building grants 2017-38821-26405, the National Science Foundation under grant No. 1735235, awarded as part of the National Science Foundation Research Traineeship as well as the Saudi Arabian Cultural Mission (SACM) under grant No. KSA10009393.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data sharing does not apply to this article as no new data were created or analyzed in this study.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Common aims in the selected studies.
Table A1. Common aims in the selected studies.
AimType of AimStudies
Evaluate the impact of all or most stages of FSCDescriptive[12,38,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69]
Determine environmental differences of different cultivation optionsComparative[24,36,39,70,71,72,73,74,75,76,77]
Estimate the impact of energy consumptionDescriptive[42,43,48,50,78,79,80]
Investigate the impact of different fertilization rates and typeComparative[34,70,81,82,83,84]
Quantify impacts associated during cultivation cycle of a crop using life cycle analysisDescriptive[32,85,86,87,88]
Investigate the impact of different pesticide rates and typeComparative[28,89,90,91,92]
Evaluate the suitability of LCADescriptive[34,93,94]
Compare the energy and GHG of regional and national scale Comparative[40,95,96]
Compare the impact of the cultivation of different cropsComparative[97,98,99]
Provide datasets on several agricultural productsDescriptive[47,100]
Compare two different methodsComparative[101,102,103]
Table
Table A2. Inventory data of the selected studies.
Table A2. Inventory data of the selected studies.
#Reference Data SourcePracticeInputUnitOutput Unit
1[42]Primary data
Not mentioned how 		Field preparation
Seeding
Post seeding
weed control
Creation of
irrigation ditches
Irrigation
Irrigation
Supporting with
reeds
Fertilization
Plant protection
Harvest
Life cycle inventory data (per 1 t of beans produced) and (per 1 ha cultivated)		Diesel
Seeds
Manure
Water (electricity)
Herbicides, insecticides, fungicides
N fertilizer, P2O5, K2O
Manure cattle, sheep
Seaweeds
Land occupation 		60 kw tractor
60 kw tractor
kg
kg
ton
ton
m2/year		Emissions to air, water, and soil)
harvested beans		kg
2[43]Primary data
(real farm)
Secondary data (previous studies)		Cultivation and crop
Orange transport
Selection and washing
Primary extraction		Fertilizers: N, P2O5, K2O
Water
Diesel
HDPE bins
Electric energy
Water
Recycled water		kg
MJ
kg
MJ
kg
MJ
kg		CO2, CO, NOx, SO2, N2O, NH3
Oranges
Wastes (leaves, rejected, citrus)
Wastewater
purification plant
Scraps		kg
kg
kg
kg
kg
kg
kg
3[44]Primary data
(Interview)
secondary data
(Databases) 		Crop management practices
Maintenance of watering canals
Bank management
Plowing
Fertilizing
Harrowing
Sowing
Application of
plant protection
products
Harvesting
Fertilizers
Cuoio torrefatto
(12% N);
ORVET 8 (8% N);
Urea (46% N);
Calce Fosfopotassica
(8% P2O5–22% K2O–20% CaO);
Complesso
(18% N–36% K2O);
ORVET
(10% N–5% P2O5–15% K2O);
Complesso
(11% N–12% P2O5–36% K2O)
Pesticides
Gulliver
Londax 60 DF–Square 60 WDG
Pull 52 DF
Sunrice
Karmex
Buggy–Clinic 360
Stratos ultra
Aura
K-Othrine
Dipterex
Heteran
Nominee
Rifit
Cannicid–Poladan		Excavation hydraulic digger
Ploughing
Tillage, plowing
Fertilizing, by broadcaster
Tillage, harrowing, by rotary harrow
Sowing
Application of plant protection
products, by field sprayer
Combine harvesting
12% N, 46% N, 21% P2O5, 50% K2O 		m3
ha
ha
ha
ha
ha
kg/ha		Direct field emissions
(CH4, NH3, etc.)
Indirect emissions from combustion
delivered refined rice
Rice byproducts:
husk, flour, broken
grains, green grains		kg
4[104]Secondary data (previous studies) Fertilizer production (process gas and fuel)
Arable farming
P fertilizer application
Fertilizer production (effluents)
Arable farming (volatilization)
Fertilizer production (nitric acid production)
Arable farming (denitrification/nitrification)
Arable farming (leaching)
P fertilizer production (effluents) 		NANAFossil fuels (oil, natural gas, hard coal, lignite)
Minerals (phosphate rock, potash)
Land
Cd
CH4, CO2, CO, NOx,
particles, SO2, NMVOC
Ntot
NH3
N2O
NO3-N
Ptot 		NA
5[95]Secondary data
(databases)		Field production
Diced tomato processing
Tomato paste processing
Diced tomato packaging
Tomato paste consumer packaging
Transport: long-haul truck, rail		Fertilizers (synthetic/organic)
Crop protection (chemical/organic)
Energy (diesel, gas, electricity)
Seeds/plants
Water
Energy
Chemicals
Packaging materials
Fuel use efficiency		L/mt kmField emissions of N2O during tomato production
Field emissions of CO2
GHG emissions associated with the production of seeds and transplants
Emissions intensity		kg CO2/mt km
6 [78]Primary
(survey and interview)
Secondary data
(databases and previous studies) 		Pesticides
Fertilizers
Machinery
Energy
water		NANAEmission from direct energy consumption and field emission
Harvested apple 		1 ton
7[8]Primary data
(real farm)
Secondary data
(databases)		 NASteel, aluminum, concrete, glass fiber resin, plastic
Water
Fertilizer, manure
Pesticide
Packaging
Diesel		kg
m3
kg
kg
kg
kg		Organic waste
Construction waste
Packaging
Plastics
oils
Hazardous waste		kg
kg
kg
kg
kg
kg
8[45]Primary data
(interview)
Secondary data
(databases)		Motion of tractors
Conveying and unloading
Optical selection
Washing
Peeling
Crushing and pulping for the juice
Sorting
Can filling and pasteurization
Water purification
Palletizing
Irrigation
Tomato fertilization
Plant protection
Tomato fruit transport
Packaging		Diesel
Electricity Natural gas
Water
N, P2O5, K2O
Insecticide, fungicide
Tin can, label, carton tray, plastic film, pallet, box for transport, plastic boxe		kg
kWh/can
kWh/can
m3/Can
kg
L
g/can 		The resulting impact was provided as output.NA
9[46]Primary data
(Surveys		Resources
Raw materials and fossil fuels
Electric and thermal energy		Occupation, permanent crop, fruit, extensive
Transformation, to permanent crop, fruit, extensive
Transformation, from pasture and meadow
Water, process, unspecified natural origin
Fertilizer N, P2O5, K2O
Pesticides
Planting
Irrigating
Pesticide treatments
Transport
Power saw
Petrol unleaded at a refinery
Diesel at refinery
Lubricating oil
Sawmill
Transport, lorry 16–32 ton,
EURO
Orchard end of life 		ha·year
ha
ha
m3
ton
ton
ha
m3
ha
kton·km
p
kg
kg
kg
p
ton·km
p		Emission in water
Nitrogen, total
Phosphorus, total
Potassium
Waste treatments
Disposal, hazardous waste,
25% water, to hazardous
waste incineration		ton
ton
ton
kg
10[47]Primary data
(interview)
Secondary data
(databases)		Fuels, fertilizers, pesticides, water use, agricultural
machinery models and use, yield, harvest schedule, distance and
means of transport to the packing facility.		NANAAir emission
Water and soil waste 		NA
11[48]Primary data
(Survey)
Secondary data
(databases)		Life cycle inventory data for greenhouse tomato and cucumber (per 1 ton of produced
crop).
Energy coefficients of different inputs and output used		Machinery
Labor
Diesel fuel
Electricity
Natural gas
Nitrogen
Phosphate
Potassium
Sul
Farmyard manure
Pesticides
Water for irrigation
Plastic
1. Machinery
Tractor, self-propelled
Stationary
Equipment implemented, machinery
2. Human labor
3. Natural gas
4. Diesel fuel
5. Biocide
Herbicide, fungicide, insecticide
6. Fertilizers: N, P2O5, K2O
7. Micro (M)
8. Farmyard: manure
9. Water for Irrigation
10. Electricity
11. Seeds		kg
h
L
kWh
m3
kg
kg
kg
kg
kg
kg
m3
kg
kg·year
kg·year
h
m3
L
kg
kg
kg
kg
m3
kWh
kg		Tomato/cucumberkg
12[70]Primary data
(real farm)
Secondary data
(databases)
1-
Preliminary considerations
Doses of fertilizing products applied
2-
Stage of compost production (CP)
Collection and transport of the organic waste
Industrial composting process
Biofilter characteristics and gaseous emissions
3-
Stage of mineral fertilizer production (FP)
4-
Stage of compost transport
5-
Stage of mineral fertilizers transport (FT)
6-
Stage of cultivation (Cu)
Fertigation infrastructure substage (CuF)
Phytosanitary substances substage (CuP)
Machinery and tools substage (CuM)
Irrigation substage (CuI)
Post-application emissions sub-stage (CuE)
Nursery plants substage (CuN)
Management of waste generated in the cultivation stage
7-
Greenhouse (G)
Greenhouse structure substage (GS)
Greenhouse management substage (GM
Avoided burdens of dumping OFMSW and BA in landfill		Fertilizer application
Compost
HNO3, KNO3, KPO4H2, K2SO4
Nitrogen application organic, mineral
Irrigation water
Per area
Per ton tomato
Open field (OF)
Commercial yield, Total yield
Tomato average diameter
Tomato average weight
Greenhouse (GH)
Commercial yield
Total yield diameter
Tomato average weight
Trucks		g·m−2
g·m−2
L·m−2
m3·FU−1
t·ha−1
mm
g
t·ha−1
t·ha−1
mm
g
T MAL		Outputs of the composting process in the industrial composting
plant of Castelldefels
Greenhouse gases
13[71]Secondary data
(both)		Wheat life cycle inputs
Transport		N, P: conv
Pesticide: conv
Phosphate rock: org
Manure: org
Diesel (org and conv)
Gasoline (org and conv)
Truck, rail transport 		kg, kg P
kg
kg of
manure P
L
L
t km		Baking,
packaging,
and sales
Wheat
Flour		kg
14[39]Secondary data
(Both)		NAAverage yield per cultural cycle
Specific area
Water
Organic fertilizers
Crop residues (durum wheat)
Manure
Foliar nitrogenous fertilizer
Differentiated and prolonged release nitrogenous fertilizer
Mineral fertilizers
Controlled release NPK fertilizer (14–7–14)
NPK complex fertilizer
Total nutrient supply
N (organic fertilizers)
N (mineral fertilizers)
N (total)
P (total, as P2O5)
K (total, as K2O)
Pesticides (active substances)
Benfluralin (herbicide)
Propyzamide (herbicide)
Boscalid (fungicide)
Pyraclostrobin (fungicide)
Cyprodinil (fungicide)
Fludioxonil (fungicide)
Deltamethrin (insecticide)
Spinosad (insecticide)
Black LDPE mulching film (35 mm; 28 g/m2) 		t
m2
m3
t
t
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg		To air: NH3, NOx
Groundwater:   N O 3 −
Surface waters: (PO4)
Soil
Heavy metals (Cd, Cr, Cu, Ni, Pb, Zn)
Pesticides (active substances)
15[96]Secondary data
(databases)		Fertilizer production
Pesticide production
Production of greenhouse infrastructure		Mineral fertilizer N
Mineral fertilizer P
Mineral fertilizer K
Manure compost
Organic fertilizer
Steel
Aluminum
Glass
Plexiglas
Plastic
Iron
Concrete
Rockwool 		N kg·ha−1·year−1
P kg·ha−1·year−1
K kg·ha−1·year−1
N kg·ha−1·year−1
N kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1		Machine use
Energy demand heating
changes in soil organic carbon		h ha−1
GJ year−1
N2O emissions direct N2O emissions indirect Humus sequestration
16[81]Primary data
(real farm)		NAN min in the soil in spring
Mineral N fertilizer rate
Atmospheric N deposition
Net N mineralization during vegetation
Mineralization of N from sugar beet leaves (easily degradable part)
Mineralization of N from sugar beet leaves (slowly degradable part)		NANH3 volatilization
N2O emission
N removal with beets
N content of leaves
N uptake of winter wheat in autumn		One ton of grain
17[49]Primary data
(interview)
Secondary data
(databases)		Greenhouse
Training system
Irrigation system		Low-density
Polyethylene
Sawn timber
Steel
Wire
Polyethylene
Sawn timber
Wire
Polyethylene
Polyvinylchloride		k
m3
kg
kg
kg
m3
kg
kg
kg		Fresh tomato
Air emissions
NH3
N2O-N
NOx-N
Water emissions
N-NO3		t
kg·ha−1
kg·ha−1
18[50]Primary data
(real farm)
Secondary data
(previous studies and databases)		Cultivation
and crop
Primary process
(citrus selection and washing, extraction)
Secondary process
(refining; centrifugation)
Secondary process
(refining; pasteurization and cooling)
Concentration and cooling
Packaging and storage
Transport of final products		Fertilizers
Water
Diesel
Electric energy
Water
Recycled water
Water-oil emulsion
Electric energy
Cooling water
Raw juice
Methane
Electric energy
Steam
Electric energy
Methane
Steam
Cooling water
electric energy
Essential oil
Electric energy
Natural juice
Concentrated juice
HFO, Diesel		NAAir emissions
Amount of citrus fruit
Wastes (scraps, leaves, rejected citrus)
Wastewater to a purification plant
Scraps to pressing
process
Essential oil to packaging and storage
Wet wastes
Wastewater to purification
plant
Natural and concentrated juice
Concentrated juice		NA
19[40]Secondary data
(previous studies)		(larvae/fingerlings, fertilizers, and feeds). NANAnitrogen and phosphorus emissions NA
20[51]Primary data
(reports)
Secondary data
(databases)		Land use
Pesticides
Fertilizer use
Fuel use
Seed use
Sun use
Agr. operations
Lime hydrated
Cane
Cane transport
River water
Air
Softened water
Ammonium sulfate
Sulfuric acid
Yeast
Transport of filter cake
Transport of ashes 		Diuron, Glyphosate, Gesapox 80, MSMA 72, Amine Salt, Isoctilic ester 48, Asulox 40, Goxone, Amigan 65, Merlin 75, Sulfatante 90, Unspecified
Urea, P2O5, K2O
Diesel
Cane seed
Solar energy
Harvesting
Fertilizing
Planting
Irrigating
NaOH 50% in H2O
HCl 30% in H2O 		ha/year
kg/ha·year
kg/ha·year
kg/ha·year
kg/ha·year
kg/ha·year
kg/ha·year
kg/day
kg/ha·year
GJ/day
ha/year
ha/year
ha/year
ha/year
t/day
t/day
t/day
t/day
km
t/day
t/day
t/day
t/day
t/day
t/day
km		Cane products
Cane
Agr. Wastes
Emissions
N2O
N total to water
Pesticides to water Pesticides to soil
Sugar
Molassesa
Electr. to networka
Alcohol
Biogas
Ash (P2O5 equiv.)
Ash (K2O equiv.)
Sludge/wastewater/cake (urea equiv.)
Sludge/wastewater/cake (P2O5 equiv.)
Sludge/wastewater/cake (K2O equiv.)
Emissions to air
PM10
Nitrogen oxides
Emissions to water
Wastewater
Inorganic solids
Total nitrogen
Chemical oxygen demand
Total phosphorus
Emissions to soil
Ashes
Filter cake 		t/day
t/day
kg/day
kg/day
kg/day
kg/day
t/day
t/day
GJ/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
t/day
21[52]Primary data
(interview)
Secondary data
(databases)		Seed production and transport
Fertilizer protection and transport
Pesticide production and transport
Machinery protection and maintenance
Energy carriers and protection		 NANAEmission to air and water
Solid emission 		NA
22[53]Secondary data
(databases)
Cultivation:
Plastic cover
Greenhouse
Transportation:
small truck, truck, sea, pre-cooling, and storage		fuel consumption, refrigeration, drivingL/t km
kWh/m3/year		Waste management (CO2 emission, t/t)
Paper, board, plastics
CO2 emission from packaging, transportation, and storage
Transportation
Farm to packing house
Packinghouse to wholesale 		kg/t
kg/t
kg/t·km
kg/t
23[54]Secondary data (databases)Cattle manure
Fuel use for various types of driving machinery and for different loads
Low power
Medium power
High power
Combine
Willow harvester		N, P2O5, K2O fertilizer
Slurry
Power		mg/kg
mg/kg
kw		Willow
Straw
Wheat		mg/kg
mg/kg
mg/kg
24[82]Secondary data
(both)		Yields for main products
Straw yields and crop residues
Moisture content
Quantity of seed
Use of machinery (number of passes)
Sowing and harvest date
Quantity of fertilizers
Types of fertilizers in integrated systems
Types of fertilizers in organic systems
Pesticide applications
Chemical seed dressing
Machinery classes
Tractor harvester Trailer machinery,
tillage
Slurry tank		Steel, unalloyed
Steel, alloyed
Other metals
Rubber
Plastics
Others (glass, paints, etc.)		NAAmmonia emissions
Nitrate leaching
P-emissions
N2O emissions
Heavy-metal emissions
Pesticide applications
Tractor combustion emissions		NA
25[97]Secondary data
(both)		Inventory of agricultural inputs
Agrochemical types and application rates
Seeding rate
Irrigation water intake
Fuel consumption in agricultural operations
Operating rate in machinery
Agricultural machinery type
Seed yield		Fertilizers and lime
Nitrogen fertilizer (urea and diammonium phosphate)
Phosphate fertilizer (diammonium phosphate)
Potassium fertilizer (potassium chloride)
Agricultural lime (calcic carbonate)
Pesticides: Clopyralid, Haloxyfop, Picloram, Glyphosate, Linuron, Thiophanate-methyl, Prochloraz
Seed
Seed for sowing
Irrigation requirement
Irrigation water intake
Diesel consumption: plowing, harrowing, crushing
sowing, spraying, weeding, hilling/fertilizing harvest
Tractor for field operations
Tools and harvester
Seed yield 		kg N
kg P2O5
kg K2O
kg CaCO3
kg
kg
m3
kg
kg
kg
t/ha		Ammonia (NH3)
Nitrates (NO3)
Nitrous oxide (N2O)
Nitrogen oxides (NOx)
Phosphates (PO4)
Carbon dioxide (CO2)
Glyphosate (main pesticide in rapeseed)
Linuron (main pesticide in sunflower)		kg/xkg
kg/xkg
kg/xkg
kg/xkg
kg/xkg
kg/xkg
kg/xkg
kg/xkg
kg/xkg
26[55]Secondary data
(databases)		Inventory data on wheat production (1995–2011, year−1).
Wheat grown in paddy fields and Wheat grown in upland fields		Production costs
Seed
Chemical fertilizers
Purchased manure
Pesticides 49858
Fossil fuels 14760
Electricity
Land improvement and irrigation
Agricultural services
Buildings
Agricultural machinery
Fossil fuels
Heavy oil
Diesel oil
Kerosene
Gasoline
Motor oil
Premixed fuel
Calcium carbonate
fertilizer
Nitrogen balance
Chemical fertilizers
Purchased manure
Atmospheric deposition
Wheat straw (incorporated)
Wheat
Wheat straw (total)
Denitrification
Ammonia volatilization
Surplus 		yen·ha−1
L·ha−1
kg·ha−1
kg N·ha−1		Wheat straw
Wheat
Air-emission sources included fossil fuel combustion, fertilizer application, and crop residue incorporation
Emissions in fossil fuel combustion were calculated using the CO2, CH4, and N2O emission factors
and the NOx and SOx emission factors
The CO2 emission factor of calcium carbonate fertilizer on a weight
the basis was 12%
27[105]Primary data
(real farm)
Secondary data
(previous studies and databases) 		Farming
Irrigation
Soil management
Pest treatment
Fertilization
Pruning
Harvesting
Olive oil mill
Washing
Milling
Pressing
Decantation
Oil pomace mill
Pitting
Drying
Solvent extraction
Dysventilation and condensation 		Water
Pesticides
Fertilizers
Diesel
Lubrification oil
water
Electric energy
Water
Electric energy
Hexane 		m3
kg
kg
kg
L
m3
kWh
L
kWh
kg		Olive mill
Wastewater
Water from washing
Virgin olive
Exhausted pomace
Pomace oil 		L
L
L
L
kg
kg
28[56]Primary data
(interview)		Fertilization
Pesticides
Packaging
Transportation 		N, P, K
Lubricating oils
Seeds
Tomatoes
Sugar beets
Tomato paste
Raw sugar
Sugar solution
Vinegar
Spice emulsion
Salt
Tomato ketchup
Packaging system for tomato paste
Packaging system for ketchup
Transportation
Shopping
Household phase
Electricity production
Waste management		 CH4, N2O, CO NMHC
Biological oxygen demand (BOD)
NOx
Other organic compounds
Water emissions
Soil emissions		kg per FU
kg per FU
g per FU
m3 per FU
kg soil per FU
29[72]Secondary data
(databases)		Primary input and output flow from the case study farms during broccoli cropping
Flow
Inventory of retail-to-grave processes
RDC
Retailer
Household		Occupation, arable land
Plants (plugs)
CO2 from air fixed in crop
Tractor use
Diesel (for field operations)
Steel (spare parts replacement)
Labor (labor-intensive operations)
Diesel (for workers’ transport)
Plastic (fleece, mulch…)
Pesticides (unspecified)
Fertilizers: N, P, K
Manure/organic fertilizers
Irrigation
Bluewater, surface water
Bluewater, groundwater
Infrastructure (pipes, sprinklers…)
Electricity (pumps)
Input packed broccoli to RDC
Diesel for transport to RDC
From Spain
From the UK
Electricity RDC storage
Input packed broccoli to retailer
Diesel for transport to retailer
Electricity retailer storage and display
Solid waste from retailer to landfill
Broccoli
LDPE packaging
Diesel for solid waste transport
Input broccoli to household
Petrol for transport to household
Diesel for transport to household
Electricity home storage
Electricity cooking
Natural gas cooking
Tap water
Solid waste from household to landfill
Broccoli
LDPE packaging
Diesel for solid waste transport
Cooking wastewater to WWTP
Cooked broccoli (input to human excretion)		m2·year
number
kg CO2
hours
L
kg
kg N, kg P2O5, kg K2O
kg
m3
m3
kg
kWh
kg
kg
kg
MJ
kg
MJ
kg
kg
kg
MJ
MJ
MJ
L
kg
kg
kg
L
kg		Crop
Soil emissions (literature)
CO2 from soil
CH4 from soil
NH3 from soil
NOx from soil
N2O from soil
NO3 from soil
PO4 from soil
Change in soil organic carbon (SOC) 		kg
kg CO2
kg CH4
kg NH3
kg NOx
kg N2O
kg NO3
kg PO4
kg C
30[38]Secondary data
(databases)
Data inventory for the agricultural phase
Data inventory for the processing phase (data refer to FU)		Seeds
Compost from cow and horse manure
Fosetyl-Al
[Thio]carbamate-compounds
[Sulfonyl]urea-compounds
Diesel fuel
Water
Electricity for irrigation
LDPE film (greenhouse)
Land
Salad (Valerianella locusta)
Salad
Electricity
Water
Sodium hypochlorite
PP film 		Mg
g
mg
mg
mg
g
dm3
kWh
mg
m2
g
g
kWh
dm3
mg
g 		Emissions to air
Carbon dioxide
Carbon monoxide
Nitrogen oxides
Particulate hydrocarbons
Dinitrogen monoxide
Ammonia
Benfluralin
Fosetyl-Al
Propamocarb
Emissions to water
Benfluralin
Fosetyl-Al
Propamocarb
Emissions to soil
Benfluralin
Fosetyl-Al
Propamocarb
Salad bag (130 g)
Salad scraps
PP film waste
Wastewater		g
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
p
g
31[98]Secondary data
(previous studies)		NANANANANA
32[73]Primary data
(interview)
Secondary data
(databases)		Main characteristics of the life cycle inventory of the studied conventional (Con) and organic (Org) groups of fruit tree orchards crops in Spain. Data refer to 1 ha and year unless otherwise statedDrip irrigation
Surface irrigation
Water use
Electricity
Presence of cover crops
Machinery use
Fuel consumption
Mulching plastic
Mineral nitrogen
Mineral phosphorus
Mineral potassium
Manure
Slurry
Cover crop seeds
Other organic fertilizers
Total carbon inputs
Total nitrogen inputs Synthetic pesticides
Sulfur
Copper
Paraffin
Natural pesticides
Production
Yield 		% of cases
% of cases
m3
kWh
%
h
L
kg
kg N
kg P2O5
kg K2O
mg
mg
kg
kg
kg
kg
kg active matter
kg
kg
kg		Soil emissions
Direct nitrous oxide
Indirect nitrous oxide
Methane
Carbon 		kg N2O
kg N2O
kg CH4
kg C
33[57]Secondary data
(previous studies)
LCI to produce a single oil palm seedlingElectricity
Diesel
Polybag
Water
Fertilizer: N, P2O5, K2O
Thiocarbamate
Pyrethroid
Organophosphate
Dithiocarbamate
Unspecified pesticide
Urea/sulfonylurea
Glyphosate
Transportation Van 		kWh
L
kg
L
kg
kg
kg
kg
kg
kg
kg
kg
tkm		 Emissions to air
NH3
N2O
NO
N2
Glyphosate
Metsulfuron-methyl
Glufosinate ammonium
Paraquat
Emissions to water
N O 3 −
P O 4 − 3
Glyphosate
Metsulfuron-methyl
Carbofuran
Glufosinate ammonium
Paraquat
Emissions to soil
Glyphosate
Metsulfuron-methyl
Carbofuran
Glufosinate ammonium
Methamidophos
Paraquat		kg/t FFB
kg/t FFB

Leached out and runoff
g/t FFB
34[58]Primary data
(real farm)
Secondary data
(databases)		Fertilizer doses, application emissions, and irrigation water (per ha) for lettuce and escarole crops in the open field (OF), plastic mulch (PM), plastic mulch combined with fleece system (PM F), and greenhouse (GH) systems.
Characteristics of materials and electricity and diesel consumption (per ha) included
in the inventory. PY polyethylene, PP polypropylene.		Fertilizer doses
N optimum
P2O5
K2O
Mulch
Fleece
Main pipe 1
Main pipe 2
Main pipe 3
Secondary pipes
Drip irrigation pipes
(laterals)
Pumps
Electricity (pumps)
Electricity (climate system)
Diesel (crop management) 		kg
m2
m2
m
m
m
m
kg
MJ
MJ		Air emissions
NH3-N
NO2-N
Water emissions
NO3-N
Irrigation water		kg
kg
m3
35[59]Primary data
(interview)		Principal inputs involved in the analysis of the “Delizie di Bosco del Piemonte” production
chain for raspberries and giant American blueberries
Nursery
Rooting
Mulching
Covering
Covering
Fertigation system Fertigation system Fertigation
Fertigation
Nozzles
Cold storage
Field
Soil preparation
Soil preparation
Mulching
Total processes
Mulching
Irrigation system
Irrigation system
Irrigation
Irrigation
Base fertilization
Total fertilization
Covering
Covering
Plant protection
treatments
Post-harvesting
Refrigeration
Flow packaging
Flow packaging
Flow packaging 		Substratum
Black PE
White PE
Metal supports
PVC piping
PVC tubing
Compost mix
Water
PVC
Electrical energy
Plow or cultivator
Harrow
Bed-former
Diesel consumption
PE sheeting
PVC piping
PVC tubing
Water
Electrical energy for the well
Manure
Compost
White PE
Metal supports
p.a.
Electrical energy
Electrical energy
PE tray
PE wrapping
L·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
m3·ha−1
kg·ha−1
kWh·m−3
h·ha−1
h·ha−1
h·ha−1
L·h−1
kg·ha−1
kg·ha−1
kg·ha−1
m3·ha−1
kWh·ha−1
t·ha−1
t·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kWh·kg−1
kWh·kg−1
g·kg−1
g·kg−1
GWP (global warming potential) IPCC 100a
Nonrenewable energy 		kg CO2 eq
MJ primary
36[60]Secondary data
(databases)		Rice production
tillage, growing, harvest 		Machines, materials Rice field
Pollution (emissions)
Product, byproduct
Rice field product, byproduct, pollution
37[36]Primary data
(survey)
Secondary data
(previous studies and databases)		 Seed
Power tiller diesel fuel use
GHG intensity diesel fuel
Power tiller life expectancy
Power tiller weight
Tractor L diesel fuel/h
Tractor weight
Embodied GHG of steel
Bullocks
Allocation to straw
Tractors embodied emission
Fertilizers
Pesticides
Manure
Nitrogen use efficiency 		kg CO2 eq·ha−1
L/h
kg CO2 eq·L−1
Years
kg
L/h
kg
kg CO2 eq·kg steel−1
kg CO2 eq·h−1
kg CO2 eq·h−1
kg CO2 eq·kg−1
CO2-eq kg/kg CO2-eq·t−1 		Methane emissions
Nitrous oxide emissions
SRI CH4 and N2O emissions
Electricity-based emissions from irrigation.
Embodied GHG emissions associated with electricity
Harvest
Soil organic carbon
kg CO2-eq·ha−1
kg CO2 eq·ha−1
kg CO2 eq·ha−1 kg CO2 eq·kWh−1
GHG emissions·h−1
kg CO2 eq·ha−1
38[61]Primary data
(interview)		Primary production
Grading and packing
Regional distribution center
Supermarkets 		Piscicide production
N fertilizer production
Tools
Machinery
Water
Compost
Field diesel
Packaging
Electricity
Electricity
Pallets and packaging
Electricity
Pallets and packaging 		NALand-use change
Direct emission
Nitrate
Nitrous oxide
Ammonia
Waste
Waste
waste		NA
39[62]Primary data
(reports)
Secondary data
(previous studies)		Orchard establishment inputs
Agricultural stage inputs
Retail stages inputs
Consumption stages inputs		Water
Electricity
Diesel
Machinery
Materials
Transport
L
kW
kg
kg
kg
tkm		Apple
Peach
(NPK) NOx
N2O
Machinery production emissions and diesel
consumed for machinery operations		kg
kg
40[74]Secondary data
(both)		Annual chemical inputs for managing a mature orange grove in Florida
Chemical mowing
Herbicide spray
Pesticide spray
Fertilization
Use of energy products for undertaking various cultural activities at a mature orange grove in Florida
Site preparation
Management of a mature
orange grove		Roundup weather max
Solicam 80 DF
Karmex WP
Roundup weather max
Prowl H20
Simazine 4L
Roundup weather max
Mandate
Direx 4L
Roundup weather max
Spray oil
Copper (Kocide 3000)
Agrimek (if no mite resistance)
Zn, Mn, B
Lorsban 4EC
Copper (Kocide 3000)
Spray Oil
MgO
Dolomite
Mowing (mechanical)
Mowing (chemical)
Discing
Soil shaping
Planting
Mowing (mechanical) Mowing (chemical)
Fertilization (16–0–16–4 MgO)
Fertilization (lime)
Herbicide
Pesticide
Conditioning
Topping
Hedging
Brush removing
Chopping brush
Dead tree removal
Irrigation
Fruit picking
Transporting pickers Roadsiding fruit		mL/ha
kg/ha
kg/ha
mL/ha
mL/ha
mL/ha
mL/ha
mL/ha
mL/ha
mL/ha
L/ha
kg/ha
mL/ha
kg/ha
mL/ha
kg/ha
L/ha
kg/ha
kg/ha
Emission from energy use
Emission from material use		g CO2 eq./FU
g CO2 eq./FU
41[75]Primary data
(survey)
Secondary data
(databases)		Principal inputs involved in the production and distribution chain (scenarios 1 and 2) for strawberries
Nursery
Rooting
Mulching
Covering
Covering
Fertigation system Fertigation system Fertigation
Fertigation
Cold storage
Field
Soil preparation
Soil preparation
Mulching
Total processes
Mulching
Irrigation system
Irrigation system
Irrigation
Irrigation
Base fertilization
Total fertilization
Covering
Covering
Plant protection
treatments
Post-harvesting
Refrigeration
Flow packaging
Flow packaging 		Substratum
Black PE
White PE
Metal supports
PVC piping
PVC tubing
Compost mix
Water
Electrical energy
Plow or cultivator
Harrow
Bed-former
Diesel consumption
PE sheeting
PVC piping
PVC tubing
Water
Electrical energy for the well
Manure
Compost
White PE
Metal supports
p.a.
Electrical energy
PE tray
PE wrapping 		L·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
m3·ha−1
kWh·m−3
h·ha−1
h·ha−1
h·ha−1
L·h−1
kg·ha−1
kg·ha−1
kg·ha−1
m3·ha−1
kWh·ha−1
t·ha−1
t·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kWh·kg−1
g·kg−1
g/kg		GWP (global warming potential) IPCC 100a
Non-renewable energy 		kg CO2 eq·UF−1
kg CO2 eq·UF−1
42[93]Secondary data
(databases)		Life cycle inventory data for watermelon cultivation (per ha).
Characterization factors of inputs used in watermelon production.
Parameters and coefficients of objective functions.		1. Human labor (man/woman)
2. Diesel fuel
Plowing
Discing
Ditcher
3. Machinery
Tractor and self-propelled
Implement and machinery
4. Fertilizers
Nitrogen (N)
Phosphate (P2O5)
Potassium (K2O)
Microelements
5. Farmyard manure
6. Electricity
7. Chemicals
Fungicide
Insecticide
8. Seeds
9. Plastics
Machinery
Diesel fuel
Chemical fertilizers
(a) Urea
(b) Phosphate (P2O5)
(c) Potassium (K2O)
Manure
Pesticides
Electricity
Plastics
Constanta
N
K2O
P2O5
Manure
Diesel
Electricity
Seed
Chemicals
Machinery
Plastic
Water
h
L
kg
kg
kg
kWh
kg
kg
kg
kg
L
kg
kg
kg
kWh
kg
kg
kg
kg
kg
L
kWh
kg
kg
kg
kg
MJ		Watermelon
On-farm emissions
N fertilizer
Diesel fuel		kg
kg
MJ
43[76]Secondary data
(databases)		NAMulching film for pot production (PP)
Wind-stopper (galvanized iron)
Hydraulic pipe/micro pipe (PEHD/PELD/PVC)
Taps (PEHD/PVC)
Tunnel cover
Tunnel structure (galvanized iron)
Poles (galvanized iron/wood)
Sprinklers (galvanized iron)
Hydraulic fittings (PE)
Solenoid (PVC)
Support canes (bamboo)
Black clip (PP)
Plates PP black wire (nylon)
Green thread (PVC)
Iron wire (galvanized iron)
Elastics/hooks/butterfly valve (PE)
Irrigation bar (aluminum)
Block (concrete)
Covering (gravel/volcanic stones)
Raincoat towel (PVC/PP/PEHD)
A chain-link fence (galvanized iron)
Centrifugal/submersible pump (Cast iron/stainless steel)
Electrical panel (PEHD/copper)
Burlap (jute)
String (sisal)
Wire basket (iron)
Plastic net (PP)
Plastic box (PP)		NATotal yearly GHG emissions are divided into different categories (kg CO2 eq/m2/year)
NFS ¼ nursery farm structure; AGS ¼ aboveground structures; IC ¼ inputs of cultivation; P ¼ packaging; EFS ¼ emissions from soil		NA
44[106]Secondary data
(databases)
NAStrawberry (nursery field)
PE punnet
PE plastic film
End-of-life
Transport
Electricity		NANonrenewable energy
IPCC GWP 100a		MJ·UF−1
kg CO2 eq·UF−1
45[79]Primary data
(surveys)		Gasoline at the refinery (US)
Diesel at the refinery (US)
Urea ammonium nitrate (UAN), (US)
Monoammonium phosphate (US)
Waxes/paraffin at the refinery (US)
Potassium sulfate, at regional storage (Europe)
Mined from natural sources, only transport is modeled
Fishmeal
Potassium carbonate, at the plant (Europe)
Sulfur (elemental) at the refinery (US)
Yeast (surrogate data, yeast produced as a co-product)
Serenade is a strain of Bacillus subtilis (Swiss)
Glyphosate, at regional storehouse (Europe)
Diphenyl-ether compounds at regional storehouse (Europe)
Phtalamide compounds at regional storehouse (Europe)
Pesticide unspecified, at regional storehouse RER
Developed based on Recycled Organics Unit (2006),
updated with regionally appropriate LCI datasets
Electricity grid mix (West US)
Modeled based on power rating and hours of operation
(California model) and Diesel (US)
Truck (combination)—diesel
rail (US diesel)		Gasoline
Diesel
Urea ammonium nitrate (UAN)
Monoammonium phosphate (MAP)
Adjuvant (stylet oil)
Potassium sulfate
Phytamin component: seabird guano
Phytamin component: fishmeal
Phytamin component: potassium carbonate
Sulfur dust
Serenade
Roundup Ultra Max
Goal 2XL
Chateau, Pristine (Boscalid and Pyraclostrobin)
Compost production
Electricity
Equipment operation
Truck, rail shipping
International shipping 		NAIPCC Tier 2 emissions were used to calculate the field-based
N2O emissions from fertilizer and compost application and
vineyard plant matter, including leaves, clippings, and cover
crop residue following mowing (Intergovernmental Panel on
Climate Change 2006; Point et al. 2012).		NA
46[63] Secondary data
(databases)
Fossil energy life cycle factors for agricultural inputsNitrogen
Phosphorous
Potassium
Lime
Sulfur
Micronutrients
Cover crop seed
Herbicide
Insecticide
Fungicide
Gasoline
Diesel
Plastic
Agriculture machinery Electricity 		MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/kg
MJ/L
MJ/L
MJ/kg
MJ/h
MJ/kWh
Direct N2O emissions from agricultural
Emissions (e.g., volatile organic compound
(VOC), carbon monoxide (CO), carbon dioxide (CO2), nitrogen monoxide (NO), nitrogen dioxide (NO2), nitrous oxide (N2O), particulate matter (PM10), particulate matter (PM2.5), sulfur dioxide (SO2), sulfur trioxide (SO3), methane (CH4))
Emissions and energy use in transportation 		NA
47[24]Secondary data (databases)
Electricity production
Oil production Plastic P1
production
Gutter A1 production
Gutter A1 use and demolition Incineration of P1/A1
Recycling process Material B production
Product system
Electricity production
Oil production Plastic P2
production
Gutter A2 production
Gutter A2 use and demolition Incineration of P2/A2
Recycling process Material B production
Product system		Electricity
Oil
Plastic P1
Produced A1
Installed A1
Incinerated P1/A
A1 in recycling
Avoided material B		MJ
kg
kg
100 m
100 m
kg
kg
kg		CO2
CH4
N2O
NOx
SO2		kg
kg
kg
kg
kg
48[64]Secondary data (databases)Planting and maintenance
Harvesting and baling
Receiving/storage
Drying and chopping
Pelletizing/cooling/screening
Packing and storage		Seed
Fertilizer
Pesticide/herbicide
Land use
Machinery
Fuel
Machinery
Fuel
Electricity
Air
Plastic bag		kg·ha−1
ha
kg·ha−1
ha
MJ
MJ
kWh		Strawbale
CO2
N2O
CH4
SO2
PO4
Pellet		kg
g CO2 eq
g CO2 eq
g CO2 eq
g CO2 eq
g SO2 eq
g PO4 eq
kg
49[65]Primary data
(real farm)
Secondary data
(database and previous studies)		Production characteristics
Greenhouse plastic
Water consumption
Growing media
Fertilizer
Pesticide
Electric power
Diesel and petrol
Post-harvest chemicals		Plastic consumption
Rejected steams
Power consumption
Diesel
Petrol
Cardboard box
Bunching paper
Rubber band
Strapping roll
Water
Substrate (red ash)
Pesticide
Pesticide empty containers
Calcium nitrate
Other fertilizers
Acids
Post-harvest chemicals
Post-harvest water use		g
#
kWh
g
g
g
g
g
g
L
g
g
g
g
g
g
g
L		Roses
CO2
CH4
N2O		Bunch
g
g
g
50[32]Secondary data
(database and previous studies)		Production of crop inputs, production and use of diesel, and field emissionsN (ammonium nitrate)
P2O5 (triple superphosphate
K2O (potassium chloride)
CaO
Seed for sowing
Pesticide (active ingredient)
Diesel
Natural gas (for grain drying)
Agricultural machinery
Grain dry matter yield
Stem/straw dry matter yield
Sugar/tuber dry matter yield
Followed bycatch crop (%)
Succeeding crop NO3-N emitted		kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha		Hemp
Sunflower
Rapeseed
Pea
Wheat
Maize
Potato
Sugar beet
NH3-N
NO3-N
N2O-N
PO4-P		ha
ha
ha
ha
ha
ha
ha
ha
emissions/kg
emissions/kg
emissions/kg
emissions/kg
51[100]Secondary data
(database and previous studies)
Infrastructure:
  • Buildings
  • Machinery
Fieldwork processes:
  • Soil cultivation
  • Fertilization
  • Sowing
  • Chemical plant protection
  • Mechanical treatment
  • Harvest
  • Transport
Mineral fertilizers
Organic fertilizers
Pesticides
Seed
Feed		kg
kg
kg
kg
kg		Potatoes organic, at the farm
Rapeseed extensive, at the farm
Wheat grains conventional, Barrois, at the farm
Carbon dioxide CO2
Sulfur dioxide SO2
Lead Pb
Methane CH4
Benzene C6H6
Particulate Matter PM
Cadmium Cd
Chromium Cr
Copper Cu
Monoxide N2O
Nickel Ni		kg
kg
kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
52[85]Primary data (survey)Tractors and equipment
Buildings required energy
Carriers
Mineral fertilizer
Tree nursing
Constructions for hail protection
Water for irrigation
Application of compost		Pesticides
Fungicide
Insecticide
Herbicide
Other plants
treatment products
Fertilizers
N-fertilizer
Ca- and Mg-fertilizer
(kg Ca, Mg)
K-fertilizer
P-fertilizer
Machinery
Diesel
Tractor
Equipment
Buildings		kg active matter
kg N
kg K2O
kg P2O5
kg
kg
kg
m2		Total receipts
Yield 		USD·ha−1
t·ha−1
53[89]Secondary data (databases)Pesticide
Seeds
PK fertilizer
N fertilizer
Machinery mulching
Machinery irrigation
Machinery pesticide
Machinery fertilization
Machinery weeding
Machinery soil tillage
Machinery harvest
Machinery sowing		Energy input MJ eqCH4

N2O

CO2

Ph

NH3

NO−3		t CO2 eq·ha−1·year−1
kg N eq·ha−1·year−1
t CO2 eq·ha−1·year−1
kg N eq·ha−1·year−1
kg N eq·ha−1·year−1
kg N eq·ha−1·year−1
54[77]Primary data (farmers)
Secondary data (databases and references)		Transportation
Fertilization
Pesticides
Irrigation		Inputs
1. Diesel fuel
2. Transportation
3. Human labor
4. Chemical fertilizers
(a) Nitrogen
(b) Phosphate
(c) Potassium
(d) Sulfur
5. Manure
6. Chemical pesticides
(a) Fungicide
(b) Insecticide
7. Irrigation water
The total energy input
L
kg
h
kg
kg
kg
m3
MJ		Grape
Ammonia (NH3)
Ammonia (NH3)
Benzene
Benzo (a) pyrene
Cadmium (Cd)
Carbon dioxide (CO2)
Carbon dioxide (CO2) from urea.
Carbon monoxide (CO)
Chromium (Cr)
Copper (Cu)
Diazinon
Dinitrogen monoxide (N2O)
Dinitrogen monoxide (N2O)
Dinitrogen monoxide (N2O) from atmospheric deposition
Hydrocarbons (HC, as NMVOC)
Methane (CH4)
Nickel (Ni)
Nitrate (NO3)
Nitrogen oxide (NOx)
Nitrogen oxides (NOx)
PAH (polycyclic hydrocarbons)
Particulates (b2.5 mm)
Phosphorus emissions from fertilizers application emitted into groundwater.
Selenium (Se)
Sulfur dioxide (SO2)
Tillet
Zinc (Zn) 		kg
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
55[83]Primary data
(field experiment)
Secondary data (database)
Fertilization
Cutting preparation
Spraying
Ploughing
Disking
Harrowing
Marking
Spraying
Mechanical weeding
Fertilizing
Lignin production
and application
Harvest
Transport
Liquidation 		Tractor/harvester
Machinery
Diesel fuel		kg·ha−1
CO2
PM
SO2
p		kg Mg−1 CO2 eq
kg MP 10 eq
kg SO2 eq
kg p eq
56[90]Secondary data (databases and previous studies)Pesticide application Active ingredients of the pesticide tActive ingredients emissionsUnitless
57[66]Primary
(survey)
Secondary data
(database and previous studies)		Nursery
Tomato cultivation
Packaging
Transportation
Reporting period
Country
(Production site)
Growing period
Greenhouse
structure
Substrate
Greenhouse
heating
CO2 enrichment
Yield
Fertilization
Irrigation
Energy
consumption		ton·ha−1
kg N·ha−1, kg P2O5·ha−1, kg K2O·ha−1
water m3·ha−1
kWh·ha−1		Nitrogen oxides, phosphates, and pesticides emissions
nitrous oxide, and ammonia		g N eq
g P eq
58[86]Secondary data
(databases)		Applying farmyard manure
Land preparation
Planting
Fertilizing
Harvesting 		N-based fertilizers
P-based fertilizers
K-based fertilizers
Pesticides
Farmyard manure
Microelements
Diesel fuel
Water		kg
kg
kg
kg
t
kg
L
m3		Carbon dioxide (CO2)
Sulfur dioxide (SO2)
Methane (CH4)
Benzene
Cadmium (Cd)
Chromium (Cr)
Copper (Cu)
Dinitrogen monoxide (N2O)
Nickel (Ni)
Zinc (Zn)
Benzo(a)pyrene
Ammonia (NH3)
Selenium (Se)
PAH (polycyclic hydrocarbons)
Hydrocarbons (HC, as NMVOC)
Nitrogen oxides (NOx)
Carbon monoxide (CO)
Particulates (<2.5 μm)		kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
59[67]Secondary data
(databases)		Fertilization,
split fertilization, chemical fallow, liming,
sowing and
spraying at the farm		NPK-fertilizer
N-fertilizer
Roundup (glyphosate)
Dolomite (CaO)
Celest Formula M (fludioxonil)
Starane XL (fluroxypyr/florasulam)
Fastac 50 (alpha-ceypermethrin)		kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
kg·ha−1
N2O
NH3
NOx		kg N2O-N/kg N input
kg NH3-N
NOx-N/kg
60[103]Primary data
(real farm)
Secondary data (databases)		production, transport to
the farm and use on the farm		Fertilizers, pesticides,
field materials, pesticide spray equipment, irrigation system and
packaging manufacturing		NAPesticide emissionNA
61[87]Secondary data
(databases and previous studies)
  • Production of nitrogenous mineral fertilizer
  • Transportation of organic fertilizer
  • Production of phosphorus mineral fertilizer
  • Production of potassium mineral fertilizer
  • Production of lime
  • Production of agricultural equipment
  • Production of seeds for sowing/default seeds harvested crop scenario
Production of diesel		Fertilizer N, P, K
Lime
Fuel
Seeds
Agricultural
equipment		NAAgricultural engine
emissions (CO, HC, NOx,
SO2, PM, CO2) (EPA
2004)
Direct field emission from
fertilization (NO3, NH4,
N2O, NOx, CO2, PO4)
Hemp straws and seeds		NA
62[91]Secondary data (databases)Pesticide application S-Metolachlor (H)
Simazine (H)
Glyphosate (H)
Glufosinate ammonium (H)
Dimethenamid-P (H)
Atrazine (H)
Alachlor (H)
Acetochlor (H)
2,4-d-dimethylammonium…
2,4-d-2-ethylhexyl ester (H)
Fipronil (I)
Chlorpyrifos (I)		kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn
kg/kg corn		Pesticide emission to air, surface water, and groundwater %
63[101]Primary data
(real farm)
Secondary data (databases)		Manufacture
of greenhouse components, substrate, fertilizers, and pesticides.
the electricity production mix; and transport and disposal of
materials		greenhouse components Water consumption and fertilizer and
pesticide doses applied		kg, m2, m3
M3
kg, L
kg		N2O
NOx
NH3
Azoxystrobin
Chlorothalonil
Clofentezine
Fenbutatin oxide
Mancozeb
Spinosad
Copper chloride oxide, hydrate
Concrete
Plastics
Substrate 		kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
64[94]Primary data (survey)
Secondary data (databases and previous studies)
  • Agricultural field operations (including plowing, harrowing, sowing, chemical weed control, harvesting, straw baling);
  • Seeds, fertilizers, and pesticides production.
  • Grain drying.
  • Nitrogen and phosphate (fertilizers)’ emissions; and
  • Pesticide’s emissions.
Yield
Grain
Straw
Agricultural field operations
Ploughing
Harrowing by rotary harrow
Sowing
Fertilizing by broadcaster
Slurry spreading
Pest control application by field
Sprayer
Harvesting
Bailing
Transport (tractor and trailer)
Grain drying
Seeds
Fertilizers
Calcium ammonium nitrate (CAN)
Ammonium nitrate
Pig slurry
Dairy cattle slurry
Pesticides
Tribenuron-methyl
Pyraclostrobin
Tebuconazole
Pirimicarb
Difensulfuron
2,3-d-Bromoxinil		t/ha
t/ha
number of repetitions (rep)
rep
rep
rep
rep
rep
rep
rep
rep
rep
rep
kg/ha
kg N/ha
kg N/ha
kg N/ha
kg N/ha
g/ha
g/ha
g/ha
g/ha
g/ha
g/ha
g/ha 		Fertilizers’ emissions
NH3
N2O
NO3
PO4
Pesticides’ emissions
Tribenuron-methyl
Pyraclostrobin
Tebuconazole
Pirimicarb
Thifensulfuron-methyl (difensulfuron)
2,4-d-Bromoxynil		kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
kg/ha
65[80]Secondary data (databases) Slurry tanker
and spreading device production
Tractor production
Diesel production		Raw materials
Energy		 Field emissions NH3, N2O, NO3, PO4
Other emissions
to air, soil, water		kg N
66[84]Secondary data
(databases)		Transportation of raw materials
Production of technical oxide
Transportation of technical oxide
Production of fertilizer
Transportation of fertilizer
Spreading		Zinc ashes9 kg·ha−1
every three years		Zn
ZnCl2
ZnO		kg
kg
kg
67[68]Primary data (interview)Desiccation
Liming
Soybean and sunflower seeds treatment
Sowing and fertilization
Topdressing fertilization
Pesticide and herbicide application
Soybean and sunflower harvesting 		Product
Resources
Occupation, arable,
non-irrigated
Materials/fuels
Seeds
Limestone
Urea, as N
Single superphosphate,
as P2O5
Triple superphosphate,
as P2O5
Potassium chloride,
as K2O
Herbicides
Insecticides
Fungicides
Mineral oil
Boric acid
Liming
Pesticide application
Sowing and fertilization
Pesticide application
Harvesting		kg
ha·year−1
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
ha
ha
ha
ha
ha		Emissions to air
Ammonia
Dinitrogen monoxide
Nitrogen oxides
CO2, fossil
CO2, land transformation
Emissions to water
Nitrate
Cadmium 2
Copper
Zinc
Lead
Nickel
Chromium
Emissions to soil
Cadmium
Copper
Zinc
Lead
Nickel
Chromium
Herbicides
Insecticides
Fungicides		kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
68[99]Primary data
(survey)
Secondary data (databases)		Direct agricultural inputs
Production of the different agricultural
inputs,		 Information about tractors and implements, labor hours, and input rates such as agrochemicals and water use)
nitrogen (urea and ammonium nitrate),
phosphorous or potassium-based fertilizers and herbicides (terbutilazine,
alachlor, lumax, and S-metolachlor		 NH3
N2O
NO3 		kg N2O-N·ha−1·kg−1
69[92]Secondary data (databases and previous studies)Pesticide application Abamectin
Azadirachtin
Chlorpyrifos
Clofentezine
Copper oxychloride
Fenazaquin
Fenbutatin-oxyde
Fluroxypyr
Fosetyl-Al
Glufosinate-ammonium
Glyphosate
Hexythiazox
Imazalil
Imidacloprid Insecticide
Lambda-cyhalothrin
Mancozeb
MCPA
Paraquat
Propargite
Pyridaben
Pyriproxyfen
Spinosad
Tebufenpyrad
Thiabendazole
White mineral oil (paraffin oil)		kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
kg·m−2
Pesticide emission NA
70[88]Primary data (survey and interview)
Secondary data (Databases and previous studies)		NACut flowers
Carnation support net
Plastic cover material
Putty for sun protection
Water for the putty used for sun protection
Transporting of cut flowers to Athens (2 times per week)
Electricity consumption for refrigeration of the cut flowers, water pumping
Fertilizers
Water for plant protection
Fungicides, Pesticides
Soil disinfection (once every three years)
Water for soil disinfection, plant watering (3 times per week)
Humidification 		Stems/year
kg/year
kg/year
kg/year
m3/year
km/year
kWh/year
kg N/year, kg P/year, kg K/year
m3/year
kg/year
kg/year
m3/year 		N2O, NOx, and ammoniaNA
71[28]Secondary data (databases and previous studies)Pesticide application Abamectine
Azoxystrobin
Benomyl
Bromopropylate
Captan
Cyromazine
Deltametrin
Fenarimol
Iprodione
Kresoxim-metil
Mancozeb
Pimetrozine		kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
kgai·FU−1
Pesticide emission to air, soil, and water NA
72[12]Secondary data
(databases)		Fertilizer application
Seeds use
Plant protection production application
Agriculture activity 		N, P, K fertilizerNANH3
NOx
N2O
NO3
PO4−3
P
HMa
Heavy metal
Active ingredients
CO2
NMVOC
PM		NA
73[102]Secondary data (databases)NAPesticide
N Fertilizer
P Fertilizer		NAN2O, air emission
P, water
Emission
NO−3, water
Emission
Pesticides,
water
emission		NA
74[69]Primary data (surveys)
Secondary data (databases)		Soil tillage
Seedbed preparation
Owing
Fertilization
Plant protection
Harvest
Stubble cultivation
Transport to the farm and grain drying		Fertilizer use
Number of passes for fertilizer spreading
Pesticide use (active ingredients)
Herbicides
Fungicides
Insecticides
Other pesticides
Total pesticides
Number of passes for pesticide spraying 		kg N·ha−1·year−1
kg P2O5·ha−1·year−1
kg K2O·ha−1·year−1
ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
kg·ha−1·year−1
ha−1·year−1		Yields
Gross energy yield
Raw protein yield
Gross margin
kg DM·ha−1·year−1
GJ·ha−1·year−1
kg·ha−1·year−1
D·ha−1·year−1

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