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“…Pesticides The EU inventory of pesticides in Sala et al (2015) was replaced by its most up-to-date version from Leclerc et al (2019). The inventory of Leclerc et al (2019) was complemented with emissions from three additional EU countries (Bulgaria, Croatia, and Romania, previously neglected) and upscaled based on the ratio between European and global agricultural land (3.84%, Faragò et al 2019).…”
Purpose Characterizing environmental impacts at the global scale is crucial to define references against which compare the environmental profile of products and systems. Within this study, global emissions and resource uses have been collected and characterized for the following impact categories: climate change, ozone depletion, human toxicity (cancer and non-cancer), ecotoxicity, particulate matter, ionizing radiation, photochemical ozone formation, acidification, eutrophication (terrestrial, marine, and freshwater), land use, water use, and resource use. The results can be used as normalization factors (NFs) in the context of the life cycle assessment (LCA). Material and methods The global NFs are built on an extensive collection of data on emissions and resources extracted at a global scale in 2010, gathering different sources and comparing them. A hierarchical approach was applied to the selection of data sources. Extrapolations, mainly temporal data-gap filling, were applied for complementing the inventories for missing data. In order to calculate NFs, the inventory was characterized by using the International Reference Life Cycle Data System (ILCD) midpoint indicators and the EU Environmental Footprint (EF) set, which includes recently released models.
Results and discussionThe resulting global NFs (ILCD and EF) were reported and discussed for each impact category. Coverage completeness and robustness of both the underpinning inventories and impact assessment models were used to define the level of uncertainty in the calculations. Based on the contribution analysis of the main elementary flows, it resulted that only few elementary flows drive the overall impact for most of the impact categories. Moreover, the ratio between the NFs at EU27 in 2010 and global level showed that Europe generally covers less than 10% of the global impact.
Conclusion and outlookThe quantification of the current levels of environmental pressures entails critical aspects, as it consists of accounting of emissions and resources, relying on data often incomplete or based on modeling. Despite the attempts made for increasing NFs coverage and robustness, the calculation in the present study highlights the need of further efforts aiming at overcoming the uncertainties and the limitations identified both at the inventory (i.e., difficulty in retrieving complete and recent data) and characterization levels (e.g., consistency between inventory and impact assessment regarding spatialization, system boundaries). Most importantly, any assessment based on the use of NFs should be carefully discussed and interpreted in light of the limitations discussed in this paper.
“…Pesticides The EU inventory of pesticides in Sala et al (2015) was replaced by its most up-to-date version from Leclerc et al (2019). The inventory of Leclerc et al (2019) was complemented with emissions from three additional EU countries (Bulgaria, Croatia, and Romania, previously neglected) and upscaled based on the ratio between European and global agricultural land (3.84%, Faragò et al 2019).…”
Purpose Characterizing environmental impacts at the global scale is crucial to define references against which compare the environmental profile of products and systems. Within this study, global emissions and resource uses have been collected and characterized for the following impact categories: climate change, ozone depletion, human toxicity (cancer and non-cancer), ecotoxicity, particulate matter, ionizing radiation, photochemical ozone formation, acidification, eutrophication (terrestrial, marine, and freshwater), land use, water use, and resource use. The results can be used as normalization factors (NFs) in the context of the life cycle assessment (LCA). Material and methods The global NFs are built on an extensive collection of data on emissions and resources extracted at a global scale in 2010, gathering different sources and comparing them. A hierarchical approach was applied to the selection of data sources. Extrapolations, mainly temporal data-gap filling, were applied for complementing the inventories for missing data. In order to calculate NFs, the inventory was characterized by using the International Reference Life Cycle Data System (ILCD) midpoint indicators and the EU Environmental Footprint (EF) set, which includes recently released models.
Results and discussionThe resulting global NFs (ILCD and EF) were reported and discussed for each impact category. Coverage completeness and robustness of both the underpinning inventories and impact assessment models were used to define the level of uncertainty in the calculations. Based on the contribution analysis of the main elementary flows, it resulted that only few elementary flows drive the overall impact for most of the impact categories. Moreover, the ratio between the NFs at EU27 in 2010 and global level showed that Europe generally covers less than 10% of the global impact.
Conclusion and outlookThe quantification of the current levels of environmental pressures entails critical aspects, as it consists of accounting of emissions and resources, relying on data often incomplete or based on modeling. Despite the attempts made for increasing NFs coverage and robustness, the calculation in the present study highlights the need of further efforts aiming at overcoming the uncertainties and the limitations identified both at the inventory (i.e., difficulty in retrieving complete and recent data) and characterization levels (e.g., consistency between inventory and impact assessment regarding spatialization, system boundaries). Most importantly, any assessment based on the use of NFs should be carefully discussed and interpreted in light of the limitations discussed in this paper.
“…This is reasonable as country-specific conditions determine the CFs calculated with the NSQI aggregation approach. Therefore, in the case of Sweden, where more than half of the surface is currently covered by forests (Faragó et al., 2019), the area-adjusted normalisation reference for mechanical filtration is lower (making the normalised indicator higher) compared to Greece, which is currently covered by a lower share of forests (25%) and a higher share of arable land (17%) (Fig. 4).…”
Section: Resultsmentioning
confidence: 99%
“…When instead one country is selected (in this case Sweden), the ranking of land use types is similar across the two approaches; however, due to differences in the re-scaling and aggregation approaches adopted, the relative contribution of the four indicators to the aggregated index changes from one approach to another.Fig. 4Land cover in Greece and Sweden according to Faragó et al. (2019).…”
Section: Resultsmentioning
confidence: 99%
“…For what concerns the NSQI approach, uncertainties related to the national inventories need to be considered, as these are quite country-specific as addressed in Faragó et al. (2018).…”
Section: Resultsmentioning
confidence: 99%
“…According to this, the resulting unit of the characterisation is a weighted result expressed in points per unit of inventory flow (Pt/m 2 a). The normalisation references used in this work correspond to the occupation impacts calculated using the re-scaled CFs (according to technique B) and the globally-applicable national land use inventories developed in Faragò et al. (2018).…”
Impacts associated with land use are increasingly recognized as important aspects to consider when conducting Life Cycle Assessment (LCA). Across the existing models accounting for land use activities in life cycle impact assessment, a balance is yet to be found between complexity and comprehensiveness on one hand, and applicability on the other hand. This work builds on the LANd use indicator value CAlculation (LANCA
®
) model, assessing the impacts of land use activities on five soil properties, and aims at developing an aggregated index to improve its applicability. First a statistical analysis is conducted, leading to the shortlisting of the four most significant soil quality indicators. Then two options for aggregating the selected indicators are presented: the soil quality index (SQI), based on linear aggregation, and the normalisation–based soil quality index (NSQI), where the aggregation process involves normalisation integrated into the characterisation step. Country-specific and global average characterisation factors (CFs) are calculated for 57 land use types considering both land occupation and land transformation interventions with the two suggested approaches. The two indices present similar ranking of land use types but the relative contribution of the separate indicators to the aggregated index varies according to the approach adopted. The differences between the aggregation approaches suggested are discussed, together with the limitations related to both the LANCA
®
model and the aggregation approaches. This work represents a first step towards the widespread application of a comprehensive and robust land use model at midpoint level in LCA. Finally, a number of recommendations for the future development of the LANCA
®
model and of the related soil quality models are provided.
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