Improvement of Agricultural Life Cycle Assessment Studies through

Jul 17, 2014 - Improvement of Agricultural Life Cycle Assessment Studies through Spatial Differentiation and New Impact Categories: Case Study on Gree...
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Improvement of Agricultural Life Cycle Assessment Studies through Spatial Differentiation and New Impact Categories: Case Study on Greenhouse Tomato Production Assumpció Antón,*,†,‡ Marta Torrellas,† Montserrat Núñez,† Eva Sevigné,† Maria José Amores,‡ Pere Muñoz,† and Juan I. Montero† †

Institute for Food and Agricultural Research and Technology (IRTA), Carretera de Cabrils, km 2, Cabrils, Barcelona, 08348, Spain Departament d’Enginyeria Química, Universitat Rovira i Virgili, 26 Avda Països Catalans, Tarragona, 43007, Spain



S Supporting Information *

ABSTRACT: This paper presents the inclusion of new, relevant impact categories for agriculture life cycle assessments. We performed a specific case study with a focus on the applicability of spatially explicit characterization factors. The main goals were to provide a detailed evaluation of these new impact category methods, compare the results with commonly used methods (ReCiPe and USEtox) and demonstrate how these new methods can help improve environmental assessment in agriculture. As an overall conclusion, the newly developed impact categories helped fill the most important gaps related to land use, water consumption, pesticide toxicity, and nontoxic emissions linked to fertilizer use. We also found that including biodiversity damage due to land use and the effect of water consumption on wetlands represented a scientific advance toward more realistic environmental assessment of agricultural practices. Likewise, the dynamic crop model for assessing human toxicity from pesticide residue in food can lead to better practice in pesticide application. In further life cycle assessment (LCA) method developments, common end point units and normalization units should be agreed upon to make it possible to compare different impacts and methods. In addition, the application of site-specific characterization factors allowed us to be more accurate regarding inventory data and to identify precisely where background flows acquire high relevance.



INTRODUCTION Because life cycle assessment (LCA) was created for industrial systems, it has focused predominately on energy-related impacts. However, agricultural processes whose main energy source is the sun are more closely related to environmental matters such as natural resources (i.e., water and land), biodiversity, and toxicity caused by pesticides. The initiative European Food Sustainable Consumption and Production Round Table recently launched the draft of the Environmental Assessment of Food and Drink Protocol.1 The main aim of the ENVIFOOD Protocol is to establish a scientifically reliable, practical, and harmonized environmental assessment methodology for food and drink products across Europe. However, in accordance with the recommendations for life cycle impact assessment (LCIA) of the International Life Cycle Data System (ILCD) Handbook,2 LCIA methods proposed for land and water use were not scientifically mature enough to be recommended. Therefore, although land and water use from agricultural practice could have major environmental consequences, most agricultural studies consider these impact categories to be mere flow inventories expressed in m2 or m3 and do not assess the consequences of environmental damage © 2014 American Chemical Society

arising from these uses. Furthermore, the ILCD Handbook and the ENVIFOOD Protocol do not recommend any methods for assessing toxicity due to pesticide residues in food. Impacts in agriculture are clearly site dependent,3 whereas LCIA methods have traditionally relied mostly on generic, nonspatial, and steady-state multimedia environmental models. Unlike the so-called global impact categories, such as global warming and ozone depletion, regional impact categories (e.g., acidification, eutrophication, toxicity) need to have spatially differentiated models because evidence shows that differences in fate and effect factors such as exposure mechanisms and sensitivity can vary significantly in different geographical contexts.4,5 This article focuses on the impact categories that are significant for agricultural case studies, linked to water consumption, land use, and pesticide and fertilizer use, and that are also related to the importance of site-specific detailed Received: Revised: Accepted: Published: 9454

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Cut-off criteria were applied in accordance with the ILCD Handbook to include the most relevant processes and flows in the production system. Following previous studies performed in the area,19 we omitted any manufacturing and energy processes whose environmental consequences accounted for less than 5% of the total impact, except for the processes relevant to agricultural production systems (e.g., pesticide production). Primary data were the site-specific data for agricultural operations, such as water consumption and fertilizer and pesticide doses applied, and were representative of the area studied on the coast of Almeria (Southeastern Spain). These data were from tomato crop plants with a density of 1.23 plants·m−2 and two stems per plant. Best available technology criteria were assessed. The greenhouse structure was modeled as a generic data set representing the typical structure of a parral greenhouse.27 Secondary data for the following processes were obtained from the Ecoinvent database v2.2:28 manufacture of greenhouse components, substrate, fertilizers and pesticides; the electricity production mix; and transport and disposal of materials. The processes in Ecoinvent database most similar to the ones in the production system were selected and adapted in accordance with local information to model tomato production in a parral greenhouse production system. A detailed list of the characteristics and flows in the different stages for this case study can be found in the Supporting Information material. Impact assessment was conducted with the newest characterization methods, which provided CFs at different spatial resolutions for land use, water use, and toxicity categories, as well as improved nontoxic impact categories. To demonstrate how the new methods can help to improve environmental assessment in agriculture, results were compared with earlier, commonly used methods (ReCiPe and USEtox). Of the new impact methods developed, our study focused on the ones that are most relevant in agriculture. When different spatial resolutions were available, we chose the most sitespecific CFs. The new methods evaluated in our study were classified as follows. (a) Resource-use impacts, which cover impacts related to land use and water use. Land-use was assessed in terms of biodiversity,29,30 biotic production potential (BPP)7 and soil erosion,31 whereas water consumption was assessed in terms of midpoint water stress index, WSI,8,32 as well as damage caused to inland wetlands33,34 and coastal wetlands.35 The ILCD Handbook2 and ENVIFOOD Protocol1 recommend cautiously applying (level III) the method that considers soil organic matter36 because it is the most appropriate soilquality indicator among the existing approaches to assess landuse impacts at the midpoint level. No method was recommended for use at the end point level, except for the ReCiPe method, which can be used as an interim method. We applied an updated approach7 of the midpoint indicator when the change in soil organic carbon can be used as an indicator for impacts on BPP, and used the warm temperate dry climate region as the geographical reference unit. De Baan et al.30 developed CFs for land-use occupation and transformation using the species-area relationship model to assess the number of species that might be driven to extinction due to land use. These authors calculated the total number of regional and nonendemic species lost per five different taxonomic groups (mammals, birds, plants, reptiles, and amphibians) choosing biome ecoregion units to derive CFs. This total regional damage was then allocated to the different

characterization factors (CFs). These impact categories have frequently been ignored because of their complexity or tend to be overly simplified. Most of the new models have been developed within the context of the LC-Impact European project,6 but we have also considered other relevant published methods.7,8 We conducted a greenhouse tomato crop case study in Almeria, Spain, to test the applicability of the new methodological improvements. Tomato (Lycopersicon esculentum) is the most important vegetable crop worldwide after potato. Current world production of tomato is about 130 million metric tons of fresh fruit produced on 4.6 million hectares. The Mediterranean basin is one of the regions with the highest tomato production in the world and accounts for 16.6% of total world production.9 An increasing amount of tomato production is done under local greenhouse structures. The parral greenhouse, a local plastic greenhouse with a simple frame structure, is the most common greenhouse structure in Southern Spain, the region with the most extensive production of protected crops in Europe.10 Several studies have applied LCA to greenhouse tomato production.11−15 A common conclusion of most of them is the lack of site-specific CFs for impact categories such as land and water use and the drawbacks regarding toxicity assessment.16−19



MATERIALS AND METHODS Goal and Scope. The case study was located in Almeria, Southern Spain. Tomato is a major crop in Almeria, with 8639 ha cultivated in the 2010−2011 growing period.20 In this region, 60% of tomato crops are produced in parral greenhouses and 20% of them are grown as protected soilless crops, using perlite as a substrate in 55.2% of the total soilless crop.21 Protected greenhouses on the coast of Almeria cover the geographic area at a latitude of between 36° 42' and 37° 24' N and a longitude of 1° 40' and 3° 00' W. This area belongs to the Southeastern Iberian forests and shrublands ecoregion.22 LCA is the methodology used for assessment following the ISO standards for LCA23,24 and in accordance with ILCD guidelines.25 We used an attributional LCA in this study. According to the ILCD, this study can be considered a C2 situation: an accounting description of the production system as it is, without interactions with other systems and without decision support.25 A system may have a number of possible functions; the one selected for the study will depend on the goal and scope of the LCA being done. In most agricultural LCAs, the functional unit (FU) is yield produced (e.g., kg·m−2). Commercial yields depend on different factors such as crop variety, meteorological conditions, and the presence or absence of pests. Results can therefore show high variability for similar inputs. Because we were more interested in the applicability of the methods than in the absolute value of the environmental impact of tomato production, the FU used in this study was the hectare (1 ha). The defined system boundary was from raw material extraction to the farm gate, including material waste disposal, but not recycling processes, as per the cutoff allocation procedure of Ekvall and Tillman.26 Packaging and commercialization processes were not within the scope of the study, as the aim was to focus on the means of tomato production. Fresh tomato production was analyzed to differentiate between the foreground and background systems with the aim of identifying the processes that can be managed by direct control (Supporting Information, Figure S1). 9455

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land-use types according to the area share they occupied and their habitat quality. We applied the agricultural land use CFs for the Iberian forests and shrublands biome (biome 1219) for our case study. Indicators for soil erosion impacts were defined at the end point level for natural resources and ecosystem quality through local available soil reserves at a spatial resolution of 5 arcmin.31 Damage to resources was expressed as surplus energy needed to make the resource available at some point in the future. The effect of soil erosion on ecosystem quality is expressed using a growth-based value potential: net primary production depletion (NPPD).31 Considerable work is currently being done to characterize water use. Among the different proposals, WSI at the midpoint level8 is the most mature of the methods proposed. We therefore applied the revised value of the WSI for the Spanish subwatershed.32 We also applied the new method developed by Verones et al.33,34 for assessing the effect of water consumption on inland wetland ecosystems. Site-specific CFs were derived for impacts of water consumption of the groundwater source for Ramsar convention wetlands, taking into account the threat level and rarity of the different taxa, and the wetland-type habitat. Coastal wetlands in arid and semiarid zones experience periods of increasing salinity as a consequence of high evaporative conditions, variability of inflows, impacts of human pressure, and their proximity to the sea. A specific CF for the coastal wetland in the area of the case study was generated. The CF was calculated as the product of a fate factor based on a salt balance and a water balance for wet and dry months. The effect factor calculation was based on species sensitivity distributions (SSD) from data collected describing the effect of salinity on 17 species (plants, fish, algae) native to the Albufera de Adra wetland35 at several end points (e.g., survival, growth inhibition). (b) Regarding toxicity, three new improvements were tested in our case study. First, an updated approach was used for coldblooded species that took into account the influence of the spatial variability of chemicals causing ecotoxicity.37 The CFs used in USEtox were calculated for different continental and subcontinental regions and different emission compartments. In our case study, we applied CFs for the region of continental Europe in the rural air, freshwater and agriculture soil emission compartments for human and ecosystem toxicity. Second, an assessment was done of the impact of chemical emissions on warm-blooded predators in freshwater food chains for the chemicals included in the USEtox method. To this end, fate and exposure factors for the water and air compartments and subsequently bioaccumulation factors and effect factors based on LD50 values for mammals and birds were calculated at global scale.38 Finally, the third improvement was to assess impacts on human health due to exposure to pesticide residue via food ingestion, in which we applied the dynamic multicrop model.39 This method provides global CFs by multiplying the human effect factor for the pesticide by the total population intake fraction of the pesticide via ingestion of the crop. The intake fraction is calculated as a result of detailed exchange processes between environmental media and vegetation.40 (c) Among the different nontoxic pollutant impact categories, we focused on the most significant impacts for agricultural case studies. that is, emissions due to the use of fertilizers that cause acidification6 and eutrophication.41

The acidification of terrestrial systems is mainly caused by compounds derived from nitrogen (NOx, NH3) and sulfur (SO2 and SO4),42 both of which are quite common ingredients in fertilizer compounds. Characterization models have been developed to evaluate the atmospheric fate, soil sensitivity through changes in the hydrogen ion (H+) concentration in the soil solution, and effects in the form of the potentially not occurring fraction (PNOF) of vascular plant species. New CFs have been provided for terrestrial acidification at midpoint for different countries and continents.6 End point CFs for changes in PNOF (%) following a change in soil pH due to pollutant emissions have been obtained.6 Fertilizer emissions can come from manufacture and application. Because we considered manufacture in Spain, we applied country CFs in both the foreground and background processes. Until now, European-generic CFs for freshwater eutrophication were available without addressing potential differences across regions. A new model developed spatially explicit quantitative global CFs for freshwater eutrophication impacts related to phosphorus emissions. Differences in hydrological, climatic and ecological processes across regions at a spatial resolution of 0.5° × 0.5° were taken into account when developing these CFs, which were based on the fate of P transported to downstream freshwaters.43 Effect factors were separately derived for four regions [(sub) tropical, xeric, temperate, and cold], two species groups (autotrophs and heterotrophs), and two freshwater types (lakes and streams).41,44 None of these methods included nitrogen as a relevant pollutant in freshwater, but only phosphorus emissions. For our case study, the perlite substrate retained all the phosphorus from the fertilizer application. Therefore, no foreground phosphorus emissions needed to be taken into account. We have applied the new CF to phosphorus emissions from background processes mainly from the manufacture of fertilizers. Nutrient enrichment of coastal ecosystems originating from freshwater runoff after the large-scale introduction of inorganic fertilizers, mainly nitrogen, has been identified as a major cause of marine eutrophication. The estimation of potential impacts of marine eutrophication was obtained from calculations based on the use of the three factors: the fate factor, which estimates the nitrogen fraction exported to marine waters depending on the nitrogen fate in soil, atmospheric fate, the fate in freshwater systems, and on nitrogen losses once in the marine compartment (denitrification, advection, and sedimentation); the exposure factor, which expresses the conversion from nitrogen to organic matter (phytoplankton biomass) in the photic zone and to dissolved oxygen consumption in bottom waters; and the effect factor, which represents the change in the potentially affected fraction of species in the receiving marine ecosystem due to the change in dissolved oxygen.6 To have a detailed explanation of the new methods, we invite readers to consult the corresponding references already published and the deliverables on the LC-IMPACT Web site.6



RESULTS Table 1 provides results for the new impact categories expressed in the respective units. It also shows the respective geographical unit of the CF used and the origin (foreground, background, or both) of the main contributors in the inventory. For land and water consumption, we focused on the foreground processes, that is, agricultural land use and water consumption for crop production. BPP transformation impacts were 1 order 9456

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Table 1. Results for Newly Developed Methodsa LC-IMPACT

unitb

impact score ha−1

geographical reference unit for CF

origin of flow contributors

ref CF

Resources agricultural land occupation, BPP agricultural land transformation, BPP agricultural land occupation, biodiversity

kg C·yr kg C·yr PLNE

7.90 × 10+3 2.88 × 10+4 6.38 × 10−05

agricultural land transformation, biodiversity

PLNE

4.22 × 10−03

erosion land natural resources erosion land ecosystem quality water stress index, WSI water consumption inland wetlands target water consumption inland wetlands target water consumption and salinity coastal wetlands water consumption and salinity coastal wetlands Toxicity higher predators human toxicity (USEtox updated) ecotoxicity (USEtox updated) human toxicity (food intake)

MJse NPPD m3 PDF m3·yr species·yr PAF·m3·yr

1.85 7.98 4.08 4.40 2.85 1.29

species·yr

1.02 × 10−06

yr DALYc PAF m3·d DALY

2.03 2.09 1.56 9.57

Nontoxic Pollutants freshwater eutrophication marine eutrophication

PAF m3·d PAF m3·d

4.41 × 10+02 2.67 × 10+05

acidification acidification

mol H+·L−1 m−2 m2

4.41 × 10−01 2.47 × 10+03

× × × × × ×

× × × ×

10+06 10+02 10+3 10−03 10−03 10+03

10−09 10−05 10+04 10−04

warm temperate dry warm temperate dry Biome 1219, Iberian forests and shrublands Biome 1219, Iberian forests and shrublands local, Almeria local, Almeria subwatershed ID-6103 local, Adra local, Adra local, Adra

foreground (1 ha) foreground (1 ha) foreground (1 ha)

7 7 6,30

foreground (1 ha)

6,30

foreground foreground foreground foreground foreground foreground

6,31 6,31 8,32 33,34 33,34 35

local, Adra

foreground (4081 m3)

35

global Europe Europe global

life cycle life cycle life cycle foreground (pesticides)

6,38 6 6 6,39

Grid 36.75N; 3.25E Spain to LME#26. Mediterranean Spain Spain Spain

background foreground background life cycle life cycle

6,44 6

(1 ha) (1 ha) (4081 m3) (4081 m3) (4081 m3) (4081 m3)

6 6

Results are expressed in the respective units per ha and show the geographical reference unit of each CF as well as the origin of the main flow contributors. bAbbreviations: PLNE, potentially lost nonendemic species; MJse, megajoules solar equivalents; NPPD, net primary production depletion; PDF, potentially disappeared fraction; PAF, potentially affected fraction; DALY, disability-adjusted life years. cEstimation in end point damage units53. a

(Table 1), which mean 1 order of magnitude higher compared to previous ReCiPe ecosystem assessments (Table S10). In our case study, the score at the end point for ecosystem damage due to increased salinity in coastal wetlands was 1.02 × 10−06 species·yr per ha, which was calculated after applying the newly developed midpoint local CFs in potentially affected fraction units per m3 (IS = 1.29 × 10+03 PAF m3·yr per ha) by considering recommended freshwater species density (7.89 × 10−10 species·m−3) and using the conversion dPDF/dPAF = 1.35 This value is similar to the order of magnitude of terrestrial acidification (1.06 × 10−06 species·yr per ha) and terrestrial ecotoxicity (8.37 × 10−07 species·yr per ha) estimated using the ReCiPe method (Supporting Information, Table S10) and clearly lower than the score for damage caused to inland wetlands. Regarding toxicity impacts, the application of the new spatial USEtox CFs for human toxicity updated to the continental scale (i.e., Europe) showed that, although impacts were reduced by almost 50% (Table 1) compared to the previous assessment (Supporting Information, Table S9), they were still on the same order of magnitude as the classical USEtox assessment (Table S9). However, the addition of a new impact category devoted to human toxicity due to pesticide residue via tomato ingestion calculated with the dynamic crop model39 result was 1 order of magnitude higher than the classical USEtox assessment and showed a score for damage of 9.57 × 10−04 disability-adjusted life years (DALY) per ha of tomato crop (Table 1), with almost 25% coming from the use of insecticides and the rest from the

of magnitude higher than occupation impacts. The biodiversity occupation impacts were 2 orders of magnitude lower than the biodiversity transformation impacts. Birds and plants, the groups with the highest number of species, showed the highest potential absolute species loss in both the occupation and transformation impacts (Supporting Information, Table S7). The results of effects due to erosion show that the equivalent of 1.85 × 10+6 MJse per ha would be needed to guarantee the resource in the future and that ecosystem damage can be calculated as the depletion of 7.98·10+2 NPP per ha. The results of the water consumption assessment are provided for midpoint impact categories in WSI, which shows the highest score (WSI = 1) in this subbasin. In addition, data on damage to wetland biodiversity due to groundwater consumption for irrigation are provided. According to Verones et al.,34 damage to biodiversity in inland wetlands can be expressed in two different end point units, the potentially disappeared fraction (PDF)·m3·yr, and species·yr. Table 1 shows the aggregate results for the different taxa considered (i.e., waterbirds, nonresidential birds, reptiles, mammals, and amphibians). The Supporting Information provides detailed figures on each taxon (Table S8). Impacts due to water consumption showed that waterbirds were the most affected species in absolute terms at the end point level, whereas waterbirds and nonresidential birds showed similar impact scores (IS) when the relative index, PDF, was used. Assuming that all taxa have the same weight and relevance, the aggregate damage to ecosystems resulted in 2.85 × 10−03 species·yr per ha 9457

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use of fungicides. Copper chloride oxide hydrate, one of the most popular fungicides, was not taken into account because metals are not within the scope of this new method. In the ecosystem toxicity impact category, the results after applying the updated CFs were on the same order of magnitude as the classical assessment, but showed a slight nonrepresentative reduction due to the uncertainty of the toxicity assessments. In both the old and new versions, chlorotalonil was the biggest contributor. However, there was a major reduction in the impact score for this substance in the new version. Of the new nontoxic impact categories, we focused on the ones related to the manufacture and use of fertilizers: marine eutrophication due to N emissions to air and water, freshwater eutrophication caused by P emissions, and acidification due to NH3, NOx and SO2 emissions. The comparison to other impact categories with similar units (i.e., PAF) showed that the results for freshwater eutrophication (4.41 × 10+02 PAF m3·d per ha) (Table 1) had less impact than marine eutrophication (2.67 × 10+05 PAF m3·d per ha) (Table 1) and also less impact than the updated ecotoxicity categories (1.56 × 10+04 PAF m3·d per ha) (Table 1). In the previous assessment using the ReCiPe method, impacts on marine eutrophication were calculated in units of kg N equiv; because of the different units used, comparing the results is not feasible. Similarly, new acidification impacts are not comparable with classical ones because different units are used, i.e., mol H+·L−1 m−2 for the new impacts and kg SO2 equiv for the classical ones. In the previous ReCiPe assessment at midpoint, contributions from SO2, NOx, and NH3 were calculated to be 52.3%, 19.6%, and 28.1%, respectively, while in the new method, the contributions for these three emissions were 49.9%, 15.1%, and 35.0%, respectively. This shows the increasing importance of ammonia emissions and the reduced contribution of NOx and SO2 emissions. The Supporting Information contains results from a previous classical midpoint assessment using the ReCiPe and USEtox methods (TS9) and an end point assessment using the ReCiPe method (TS10). These results were used to compare our results and identify any improvements.

It is clear that one spatial unit may be more or less appropriate than another depending on the impact or damage,45 but the selection of a spatial unit is usually defined by the available information. For instance, we were able to calculate WSIs for subbasins32 because information is found thanks to European directives to establish a framework for EU action in the field of water policy.46 It is also possible to assess damage to wetlands because the Ramsar Convention covers wetlands located in the area of study, which means again that more accessed and CFs can be calculated.33,34 In fact, the CF for the impact of salinity was developed specifically for the area of this case study35 (Albufera de Adra wetland). Other methods of interest were ruled out because they referred to specific geographic areas (e.g., The Netherlands).47 The information available is very often summarized by country, which is a convenient administrative and social unit, but not necessarily a uniform ecoregion or an area of environmental interest. Besides the more general features, the newly developed methods also have some special features. The new methods allowed us to assess land-use occupation and transformation damage expressed as BPP or biodiversity damage, which is an improvement over the ReCiPe results expressed as inventory flows of the total area at the time of occupation (m2·yr). In both cases, we gained a better perspective on end point damage. Using BPP gave us an initial calculation of the influence of land use using organic matter as an indicator of BPP and the climate region as the geographical reference unit. Using biodiversity units, we compared the influence of activity under study (agriculture) with other major activities (i.e., urban activities, forest management and pasture management) for the different bioma. Despite the complexity of land-use and biodiversity assessments, the next step that should be taken is to make more accurate assessments of different agricultural practices by developing more specific land-use types (e.g., greenhouse agriculture, organic agriculture) instead of generic ones (agriculture). This topic is also mentioned by Milà i Canals et al.48 Because updated CFs are available for the continental and subcontinental scale in the USEtox method, more precise information on spatial differentiation is also available. We found differences when comparing results using the old global scale and the new continental scale (Europe) of the USEtox method. More detailed information on environmental compartments and fate and exposure processes makes it possible to conclude that previous global CFs information can be overestimated impacts that were evaluated in Europe.37 Our results show that, although more pesticide emission flows were included in the new method, most of them made little contribution. The improvements made in the freshwater eutrophication category through the addition of site-specific, grid-level CFs and taxonomic groups make a significant contribution to environmental assessments. In our case study in particular, the methodological improvements were less relevant because the level of P emissions was not high and originated in background processes (e.g., fertilizer production), where detailed information is less available. Including atmospheric transport across more specific regions makes a major contribution when calculating the impact of acidification. The most relevant substances are included in the new method, which means that the most important acidifying chemicals are covered. Although developers have provided aggregate CFs at the country level,6 the use of the country as a geospatial unit can reduce the accuracy of some results,



DISCUSSION New approaches in LCIA methods can provide a more comprehensive assessment of agricultural activity. There has been a clear improvement in major environmental impact categories such as land and water use and in the specific assessment of impact categories that are strongly dependent on site-specific conditions. However, several points still remain a bit imprecise, especially from the point of view of applicability. The main points for discussion are related to spatial resolution, different units for the damage covered, and applicability with a special focus on linking inventory flows to the impact CFs. Spatial Resolution. From a scientific and environmental point of view, there is no doubt that more site-specific CFs offer a better approach to grasping the local particularities of crop production. The different methods provide CFs based on homogeneous areas such as climate region (land-use change), biome (land use on biodiversity damage), and watersheds (water consumption), as well as different geographical reference units that range from large continental areas (e.g., Europe for toxicity impact categories) to more large-scale grids (e.g., freshwater eutrophication and erosion). 9458

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expressed as the surplus energy needed to make the resource available at some point in the future.31 Instead of using energy units (MJ-eq ), the new approach uses emergy units (MJ-solar equiv ).31 This is a suitable unit for evaluating soil depletion, which indicates the anticipated energy removal from nature to produce a unit of soil eroded during land occupation.51 ReCiPe uses monetary units expressed as the marginal increase in costs due to the extraction of a resource.52 Therefore, agreement on assessing the cost of soil depletion could be a further step for comparing this damage to other resource damage. The method for marine eutrophication characterizes impacts at the midpoint level. The fate model uses emission data and loss rate coefficients for N groundwater and surface freshwater, as well as a deposition model for atmospheric emissions.6 Results are expressed in PAF m3 d, which can be qualitatively compared to other impacts. Nevertheless, a further step toward ecosystem damage is also advisible. USEtox provides data on damage to human health and freshwater ecosystems, but does not provide a terrestrial ecosystem indicator. In the previous assessment with ReCiPe, the terrestrial ecotoxicity midpoint indicator was 1 order of magnitude lower than the freshwater ecotoxicity midpoint indicator. On the contrary, end point damage results showed higher impact for terrestrial than for freshwater ecotoxicity, which can be explained by the higher conversion factor from midpoint to end point for terrestrial ecotoxicity than for freshwater ecotoxicity. This conversion factor depends in turn on the lowest value for freshwater species density (terrestrial species density, 1.38 × 10−8 m−2, and freshwater species density, 7.89 × 10−10 m−3).52 Another important area for further research is to refine the reference values for species density in the different ecosystems. Including the human toxicity impact category due to food intake changed our results dramatically. Although USEtox provides midpoint impacts, we estimated human health damage in end point damage units following average DALY weighted by incidence cases for carcinogenic and noncarcinogenic effects (i.e., 11.5 yr lost and 2.7 yr lost, respectively).53 The previous assessment with USEtox gave an IS of 5.13 × 10−05 DALY per ha, whereas the new calculation gave a score of 9.57 × 10−04 DALY per ha due to food ingestion plus 2.09 × 10−05 DALY per ha due to emissions to other environmental compartments. Therefore, the total human toxicity impact value was 1 order of magnitude higher. Assuming an intake of 15 kg tomato per capita and year,54 this damage could translate into a loss (either due to early death or illness) of three seconds of healthy life per capita and year as a result of annual tomato consumption. Fantke et al.55 estimated the total burden for pesticide use per person for different crops to be a loss of 2.3 min per capita and year and compared it to the 21 min lost per capita and year due to nonsmoker exposure to secondhand smoke over a lifetime reported by Hänninen and Knol.56 However, the comparison of our results on human health toxicity damage and the previous assessment using ReCiPe, where the greatest human health damage was due to climate change (4.91 × 10−2 DALY per ha), shows that this category is clearly more important than human health toxicity. We can conclude that the use of common units for human health such as DALY,57 allow us to compare the effects of toxicity and climate change on humans. However, the factors created to express impact categories as final damages should be reviewed and assessed in greater detail. Applicability. The application of classical ReCiPe52 assessment results has shown that, despite clear exceptions, most of

especially for large, nonuniform countries. Because calculations of CFs have been performed to grid scale, other aggregate units could be provided, in this sense the combination of GIS and LCA tools could be useful. Indicator Units. Midpoint CFs are considered more robust and generate less uncertainty when modeling the full causeeffect chain compared to end point CFs. However, end point results simplify the comparison of damage in stressors with different modes of action and allow for weighting of impact categories. After end point calculations, the importance of the different impact categories can be determined.51 The complexity of environmental processes makes it difficult to quantify damage. However, because LCA is a comprehensive methodology for assessing potential damage, it is important to look for a safe balance of reliable and understandable results, and let other tools perform detailed specific damage or absolute risk assessment (e.g., Environmental Risk Assessment).49 To test the applicability of the methods, practitioners need to have a clear understanding of what they are quantifying. Interpreting damage results may be complicated for nonexperts. When focusing on the three Areas of Protection (AoP), it might be easier to reach an agreement on the units for human health and resources than for the natural environment. In the natural environment AOP, the different impact category models tested give results in different units, thus making it difficult to compare them. The way results are interpreted changes depending on the end point unit chosen. For example, water consumption damage in wetlands can be expressed as PDF·m3·yr or species· yr. The former considers the same area loss and species-area relationship, whereas the latter explicitly takes differences in ecosystem species richness and vulnerability into account and attributes higher impacts to regions with rare and threatened species,34 which appears to be a more realistic approach. In addition, the use of species·yr also as an end point damage unit in the ReCiPe methodology allowed us to make preliminary and interim comparisons regarding what the new impact means. The comparison with the classical assessment methodology showed that values of the total ecosystem damage were now greater due to the inclusion of impact of groundwater consumption on wetland species. Similarly, our results allowed us to conclude that salinity increase caused less biodiversity damage than that found when assessing impacts of groundwater consumption in inland wetlands. However, at present, it is assumed that all taxa are equally important. Other weighting systems (e.g., based on species richness per taxon and ecological function) may be developed in the future.35 Regarding land-use impact categories, the use of absolute units of potentially lost nonendemic or regional species represents an improvement over the old relative PDF. Selecting relative or absolute impacts is based on a value choice: choosing relative impacts gives equal weight to ecosystems, whereas absolute impacts stress the ecological function of those ecosystems.50 The effect of soil erosion on ecosystem quality is expressed using a growth-based unit: potential NPPD as a response to carbon soil loss. Similarly, C expressed in grams is selected as being representative of BPP. Both methods consider organic matter or C to be an indicator of impacts on ecosystem quality because organic matter provides a range of soil properties responsible for soil resilience and fertility.36 However, further steps should be taken to link NPP and BPP to biodiversity damage. Damage to resources due to erosion impact is 9459

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Most inventory databases (e.g., the Ecoinvent database) use a country or region code to indicate the location of supply chain processes, and not knowing the exact location can make it difficult to carry out a full life cycle assessment. Improvement of LCIA also means that flows in background processes could acquire increased importance not properly taken into account when average data from generic databases are used. Special attention should be paid to the high quantity of flows contributing to toxicity impact categories, because it is important to ensure that the results are consistent. Therefore, the application of these new characterization factors will generate greater knowledge and higher confidence in the quality and accuracy of the inventory data. In addition, the application of new models could require extra work to prepare the inventory (e.g., soil erosion), given that more information is needed to calculate it. Integration between LCA tools, databases, and GIS software could help LCA practitioners apply the new spatial methods. Correctly interpreting the results is also quite complex. For example, it may be difficult for practitioners to clearly understand why the fenbutatin oxide insecticide has a higher impact than chlorotalonil fungicide on human toxicity but not on ecosystems. Practitioners should be provided with clear guidelines on how to interpret the damages. As mentioned by the different authors who developed methods, the use of more local CFs reduces the uncertainty of the impact. The uncertainty of our results is directly proportional to the uncertainty of the different geographicalscale CFs. Data and guidelines on the definition of uncertainty in LCI and LCIA are needed to interpret results properly. As an overall conclusion, for agricultural production systems, the newly developed impact categories help fill some important gaps related to land use, water consumption, pesticide toxicity, and nontoxic emissions linked to fertilizer use. This is true not only because the new CFs were included, but also because this offered a significant advance in the information provided on site-specific impacts. Being able to include biodiversity damage due to land use and the effect of water consumption on wetlands represents a major scientific advance toward a more realistic environmental assessment of agricultural practices. Likewise, the new dynamic crop model for assessing human toxicity due to pesticide residue in food can lead to better practice in pesticide application, which will also benefit ecosystem biodiversity.

the major contributions are related to energy impacts. Moreover, the ReCiPe and USEtox methods do not include CFs for most emissions of pesticide active ingredients into the air or through ingestion during food consumption. The new impacts therefore provide a fresh perspective on environmental damage in this case study in particular and in agricultural assessments in general. In addition, we have used interim normalization factors6 to make a qualitative comparison between the models used in the classical ReCiPe method and the new ones. Table 2 provides a Table 2. Qualitative Assessment Based on Preliminary Normalization6 Reference Values Comparing Impact Scores from the New Categories with Normalization Values Using the ReCiPe Methodology impact category

score

land use wetland target specific site: Adra human toxicity cases ecosystems toxicity human toxicity pesticide intake marine eutrophication Mediterranean freshwater eutrophication acidification, end point Spain particulate matter formation metal resource fossil resource

low high low high high low low high similar low similar

qualitative estimate of the scores that were lower, similar, or higher than the ReCiPe normalized values (Supporting Information, Table S10). These results highlight the importance of water consumption, acidifying emissions, and pesticide use in our case study. The LCIA stage has clearly been improved because the existence of different spatial CFs makes it possible to specify impact damage in a more precise and accurate way. However, it is important to find an optimal spatial resolution in connection with life cycle inventories58 because advances in impact assessment can produce new gaps in the inventory, which means the final result is highly dependent on the availability of inventory information. This is true because the models used to estimate emissions are not always simple (e.g., pesticides, fertilizers) and information on background flows48 may be highly complex or insufficient. Generating emission models for phosphorus, nitrogen compounds, and metal emissions in the inventory is a complex task for which scientific consensus is lacking and this adds uncertainty to the results. Moreover, to obtain more accurate assessments of pesticides, better agreement should be reached on system boundary inventory emission calculations59,60 and some “natural” organic products should be included. It would be advisible to review the generic pesticide database to ensure that the most popular pesticides, especially copper compounds, are included and exclude any banned pesticides from generic data sets. Being able to apply site-specific CFs will depend on practitioners’ knowledge of the supply chain, for which information on foreground processes is usually plentiful, but it is not always available for background processes. The more information is available on the location of background processes, the more accurate the results will be.



ASSOCIATED CONTENT

S Supporting Information *

Detailed information is provided on the inventory flows included, intermediate calculations for the new impact categories land use, and water consumption impacts detailed per each taxon and ReCiPe and USEtox assessment. This material is available free of charge via the Internet at http:// pubs.acs.org.



AUTHOR INFORMATION

Corresponding Author

*Phone: +34937507511, ext 1203; fax: +34937533954; e-mail: [email protected]. Notes

The authors declare no competing financial interest. 9460

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(15) Boulard, T.; Raeppel, C.; Brun, R.; Lecompte, F.; Hayer, F.; Carmassi, G. Environmental impact of greenhouse tomato production in France. Agron. Sustain. Dev. 2011, 31 (4), 757−777. (16) Antón, A.; Castells, F.; Montero, J.; Huijbregts, M. Comparison of toxicological impacts of integrated and chemical pest management in Mediterranean greenhouses. Chemosphere 2004, 54 (8), 1225− 1235. (17) Antón, A.; Castells, F.; Montero, J. I. Review of land use indicators used in Life Cycle Assessment: Application in the study of environmental assessment of mediterranean greenhouses. J. Cleaner Prod. 2007, 15 (5), 432−438. (18) Martínez-Blanco, J.; Muñoz, P.; Antón, A.; Rieradevall, J. Assessment of tomato Mediterranean production in open-field and standard multi-tunnel greenhouse, with compost or mineral fertilizers, from an agricultural and environmental standpoint. J. Cleaner Prod. 2011, 19, 985−997. (19) Torrellas, M.; Antón, A.; Montero, J. I. An environmental impact calculator for greenhouse production systems. J. Environ. Manage. 2013, 118, 186−195. ́ (20) Junta-de-Andaluciá Valoración de la campaña horticola almeriense 2010/11; Consejeriá de Agricultura. Secretariá general del medio rural y la producción ecológica 2012. (21) Data-Collection of Existing Data on Protected Crop Systems (Greenhouses and Crops Grown under Cover) in Southern European EU Member States; EFSA Technical Report; Agricultural University of Athens: Athens, 2009; pp 1−216. (22) Olson, D.; Dinerstein, E.; Wikramanayake, E.; Burgess, N.; Powell, G.; Underwood, E.; D’Amico, J.; Itoua, I.; Strand, H.; Morrison, J.; Loucks, C.; Allnutt, T.; Ricketts, T.; Kura, Y.; Lamoreux, J.; Wettengel, W.; Hedao, P.; Kassem, K. Terrestrial Ecoregions of the World: A New Map of Life on Earth. BioScience 2011, 51 (11), 933− 938. (23) Environmental ManagementLife Cycle AssessmentPrinciples and Framework; ISO-14040; International Organisation for Standardisation ISO: Geneva, 2006. (24) Environmental ManagementLife cycle assessmentRequirements and guidelines; ISO-14044; International Organisation for Standardisation ISO: Geneva, 2006. (25) EU-JRC-IES. General guide for life cycle assessmentDetailed guidance. International Reference Life Cycle Data System (ILCD) Handbook; European Commission-Joint Research Centre, Institute for Environment and Sustainability: Luxemburg, 2010. (26) Ekvall, T.; Tillman, A. Open-loop recycling, criteria for allocation procedures. Int. J. Life Cycle Assess. 1997, 2 (3), 155−162. (27) Antón, A.; Torrellas, M.; Raya, V.; Montero, J. I. Modelling the amount of materials to improve inventory datasets of greenhouse infrastructures. Int. J. Life Cycle Assess. 2014, 19, 29−41. (28) Frischknecht, R.; Junblugth, N.; Althaus, H.-J.; Doka, G.; Dones, R.; Heck, T.; Hellweg, S.; Hischeir, R.; Nemecek, T.; Rebitzer, G.; Spielmann, M.; Wernet, G. Overview and Methodology; Ecoinvent Report no. 1; Swiss Centre for Life Cycle Inventories: Dübendorf, Switzerland, 2007. (29) de Baan, L.; Alkemade, R.; Koellner, T. Land use impacts on biodiversity in LCA: A global approach. Int. J. Life Cycle Assess 2013, 18, 1216−1230. (30) de Baan, L.; Mutel, C.; Curran, M.; Hellweg, S.; Koellner, T. Land use in LCA: Global characterization factors based on regional and global potential species Extinctions. Environ. Sci. Technol. 2013, 47, 9281−9290. (31) Núñez, M.; Antón, A.; Muñoz, P.; Rieradevall, J. Inclusion of soil erosion impacts in life cycle assessment on a global scale: Application to energy crops in Spain. Int. J. Life Cycle Assess. 2013, 18 (4), 755−767. (32) Núñez, M.; Pfister, S.; Vargas, M.; Anton, A. Spatial and temporal specific characterisation factors for water use impact assessment in Spain. Int. J. Life Cycle Assess. Submitted for publication. (33) Verones, F.; Pfister, S.; Hellweg, S. Quantifying area changes of internationally important wetlands due to water consumption in LCA. Environ. Sci. Technol. 2013, 47 (17), 9799−9807.

ACKNOWLEDGMENTS This work is financially supported by the project “Life Cycle Impact Assessment Methods for Improved Sustainability Characterisation of Technologies” (LC-IMPACT), Contract No. 243827, funded by the European Commission under the Seventh Framework Programme. Furthermore, we would like to thank Jerónimo Pérez Parra from IFAPA in Almeria, and Juan Carlos López from Las Palmerillas, CAJAMAR, for their support in the provision of data and information for preparation of the inventory. Three anonymous reviewers have provided significant comments to the manuscript, their input is gratefully acknowledged.



REFERENCES

(1) FoodSCP-RT ENVIFOOD Protocol, Environmental Assessment of Food and Drink Protocol; European Food Sustainable Consumption and Production Round Table (SCP RT), Working Group 1; Brussels, Belgium, 2013. (2) EU-JRC-IES Recommendations for Life Cycle Impact Assessment in the European context. International Reference Life Cycle Data System (ILCD) Handbook; European Commission-Joint Research Centre, Institute for Environment and Sustainability: Luxemburg, 2011. (3) Milà i Canals, L. Contributions to Life Cycle Analysis for Agricultural Systems. Site-dependency and soil degradation impact assessment. Ph.D. Thesis, Universitat Autònoma Barcelona, Bellaterra (Cerdanyola del Vallès), 2003. (4) Potting, J.; Hauschild, M. Spatial Differentiation in life cycle impact Assessment. A decade of method development to increase the environmental realism of LCIA. Int. J. Life Cycle Assess. 2006, 11 (Special issue 1), 11−13. (5) Sala, S.; Marinov, D.; Pennington, D. Spatial differentiation of chemical removal rates from air in life cycle impact assessment. Int. J. Life Cycle Assess. 2011, 16 (8), 748−760. (6) LC-IMPACT Life Cycle Impact assessment Methods for imProved sustAinability Characterisation of Technologies; ENV.2009.3.3.2.1; Stichting Katholieke Universiteit: The Netherlands, 2009−2013. http://www.lc-impact.eu/. (7) Brandão, M.; Milà i Canals, L. Global characterisation factors to assess land use impacts on biotic production. Int. J. Life Cycle Assess. 2013, 18 (6), 1243−1252. (8) Pfister, S.; Koehler, A.; Hellweg, S. Assessing the Environmental Impacts of Freshwater Consumption in LCA. Environ. Sci. Technol. 2009, 43 (11), 4098−4104. (9) FAOSTAT Food and Agricultural Organization of United Nations. http://faostat3.fao.org (accessed 28th June 2013). (10) Eurostat European Commission, Eurostat, Agriculture, Data, Database, Statistics http://epp.eurostat.ec.europa.eu/portal/page/ portal/agriculture/data/database (accessed 12 December 2012). (11) Antón, A.; Montero, J. I.; Muñoz, P.; Castells, F. LCA and tomato production in mediterranean greenhouses. Int. J. Agr. Resour. Gov. Ecol. 2005, 4 (2), 102−112. (12) Torrellas, M.; Antón, A.; Ruijs, M.; García Victoria, N.; Stanghellini, C.; Montero, J. Environmental and economic assessment of protected crops in four European scenarios. J. Cleaner Prod. 2012, 28, 45−55. (13) Williams, A. G.; Audsley, E.; Sandars, D. L. Determining the environmental burdens and resource use in the production of agricultural and horticultural commodities; Defra Research Project IS0205; Cranfield University and Defra: Bedford, England, August 2006; pp 1−97. (14) Stoessel, F.; Juraske, R.; Pfister, S.; Hellweg, S. Life cycle inventory and carbon and water foodprint of fruits and vegetables: application to a Swiss retailer. Environ. Sci. Technol. 2012, 46 (6), 3253−3262. 9461

dx.doi.org/10.1021/es501474y | Environ. Sci. Technol. 2014, 48, 9454−9462

Environmental Science & Technology

Article

developments in life cycle assessment. J. Environ. Manage. 2009, 91, 1−21. (52) Goedkoop, M.; Heijungs, R.; Huijbregts, M.; De Schryver, A.; Struijs, J.; van Zelm, R. ReCiPe 2008 A life Cycle Impact Assessment Method Which Comprises Harmonised Category Indicators at the Midpoint and the Endpoint Level; PRé Consultants: Amersfoort, Netherlands, 2009. (53) Huijbregts, M. A. J.; Rombouts, L. J. A.; Ragas, A. M. J.; Van de Meen, D. Human-toxicological effect and damage factors of carcinogenic and noncarcinogenic chemicals for life cycle impact assessment. Integr. Environ. Assess. Manage. 2005, 1 (3), 181−192. (54) MAGRAMA. Base de datos del consumo en Hogares. http:// www.magrama.gob.es/ca/alimentacion/temas/consumo-ycomercializacion-y-distribucion-alimentaria/panel-de-consumoalimentario/base-de-datos-de-consumo-en-hogares/ (last access on 11th of July 2014). (55) Fantke, P.; Friedrich, R.; Jolliet, O. Health impact and damage cost assessment of pesticides in Europe. Environ. Int. 2012, 49, 9−17. (56) Hänninen, O; A, K. European Perspectives on Environmental Burden of Disease: Estimates for Nine Stressors in Six Countries; National Institute for Health and Welfare: Helsinki, Finland, 2011. (57) Heijungs, R. On the use of units in LCA. Int. J. Life Cycle Assess. 2005, 10 (3), 173−176. (58) Huijbregts, M. A critical view on scientific consensus building in life cycle impact assessment. Int. J. Life Cycle Assess. 2014, 19, 477− 479. (59) Rosenbaum, R.; Anton, A.; Bengoa, X.; Bjørn, A.; Brain, R.; Bulle, C.; Cosme, N.; Dijkman, T. J.; Fantke, P.; Felix, M.; Geoghegan, T. S.; Gottesbüren, B.; Hammer, C.; Humbert, S.; Jolliet, O.; Juraske, R.; Lewis, F.; Maxime, D.; Nemecek, T.; Payet, J.; Räsänen, K.; Roux, P.; Schau, E. M.; Sourisseau, S.; van Zelm, R.; von Streit, B.; Wallman, M. The Glasgow consensus on the delineation between pesticide emission inventory and impact assessment for LCA. Int. J. Life Cycle Assess. (submitted for publication). (60) van Zelm, R.; Larrey-Lasselle, P.; Roux, P. Bridging the gap between life cycle inventory and impact assessment for toxicological assessments of pesticides used in crop production. Chemosphere 2014, 100, 175−181.

(34) Verones, F.; Saner, D.; Pfister, S.; Baisero, D.; Rondinini, C.; Hellweg, S. Effects of consumptive water use on biodiversity in wetlands of international importance. Environ. Sci. Technol. 2013, 47 (21), 12248−12257. (35) Amores, M.; Verones, F.; Raptis, C.; Juraske, R.; Pfister, S.; Stoessel, F.; Anton, A.; Castells, F.; Hellweg, S. Biodiversity impacts from salinity increase in a coastal wetland. Environ. Sci. Technol. 2013, 47 (12), 6384−6392. (36) Milà i Canals, L.; Romanya, J.; Cowell, S. Method for assessing impacts on life support functions (LSF) related to the use of ‘fertile land’ in life cycle assessment (LCA). J. Cleaner Prod. 2007, 15, 1426− 1440. (37) Sala, S.; Marinov, D.; Pennington, D. Spatial differentiation of chemical removal rates from air in life cycle impact assessment. Int. J. Life Cycle Assess. 2011, 16 (8), 748−760. (38) Golsteijn, L.; Van Zelm, R.; Veltman, K.; Musters, G.; Hendriks, A. J.; Huijbregts, M. A. J. Including ecotoxic effects on warm-blooded predators in life cycle impact assessment. Integr. Environ. Assess. Manage. 2011, 8 (2), 372−378. (39) Fantke, P.; Juraske, R.; Antón, A.; Friedrich, R.; Jolliet, O. Dynamic multicrop model to characterize impacts of pesticides in food. Environ. Sci. Technol. 2011, 45 (20), 8842−8849. (40) Fantke, P.; Wieland, P.; Juraske, R.; Shaddick, G.; Sevigné, E.; Friedrich, R.; Jolliet, O. Parameterization models for pesticide exposure via crop consumption. Environ. Sci. Technol. 2012, 46 (23), 12864−12872. (41) Azevedo, L. A.; Van Zelm, R.; Elshout, P. M. F.; Hendriks, A.; Leuven, R. S. E. W.; Struijs, J.; de Zwart, D.; Huijbregts, M. A. J. Species richnessphosphorus relationships for lakes and streams worldwide. Glob. Ecol. Biogeogr. 2013, 22 (12), 1304−1314. (42) Roy, P. O.; Deschenes, L.; Margni, M. Life cycle impact assessment of terrestrial acidification: Modeling spatially explicit soil sensitivity at the global scale. Environ. Sci. Technol. 2012, 46 (15), 8270−8278. (43) Helmes, R. J. K.; Huijbregts, M. A. J.; Henderson, A. D.; Jolliet, O. Spatially explicit fate factors of phosphorous emissions to freshwater at the global scale. Int. J. Life Cycle Assess. 2012, 17, 646− 654. (44) Azevedo, L. A.; Henderson, A. D.; Van Zelm, R.; Jolliet, O.; Huijbregts, M. A. J. Assessing the importance of spatial variability versus model choices in life cycle impact assessment: The case of freshwater eutrophication in europe. Environ. Sci. Technol. 2013, 47 (23), 13565−13570. (45) Mutel, C. L.; Pfister, S.; Hellweg, S. GIS-based regionalized life cycle assessment: How big is small enough? Methodology and case study of electricity generation. Environ. Sci. Technol. 2012, 46, 1096− 1103. (46) EC, Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. In 2000. (47) van Zelm, R.; Schipper, A. M.; Rombouts, M.; Snepvangers, J.; Huijbregts, M. Implementing groundwater extraction in life cycle 1 impact assessment: Characterization factors based on plant species richness for the Netherlands. Environ. Sci. .Technol. 2011, 45 (2), 629− 635. (48) Milà i Canals, L.; Rigarlsford, G.; Sim, S. Land use impact assessment of margarine. Int. J. Life Cycle Assess. 2013, 18, 1265−1277. (49) Olsen, S. I.; Christensen, F. M.; Hauschild, M.; Pedersen, F.; Larsen, H. F.; Tørsløv, J. Life cycle impact assessment and risk assessment of chemicalsA methodological comparison. Environ. Impact Assess. Rev. 2001, 21 (4), 385−404. (50) Köelner, T.; de Baan, L.; Beck, T.; Brandão, M.; Civit, B.; Margni, M.; Milà i Canals, L.; Saad, R.; Maia de Souza, D.; MüllerWenk, R. UNEP-SETAC guideline on global land use impact assessment on biodiversity and ecosystem services in LCA. Int. J. Life Cycle Assess. 2013, 18, 1188−1202. (51) Finnveden, G.; Hauschild, M.; Ekvall, T.; Guinée, J.; Heijungs, R.; Hellweg, S.; Koehler, A.; Pennington, D.; Suh, S. Recent 9462

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