2017
DOI: 10.1002/ieam.1889
|View full text |Cite
|
Sign up to set email alerts
|

A step toward regionalized scale‐consistent agricultural life cycle assessment inventories

Abstract: Life cycle inventory (LCI) regionalization (i.e., the determination of input and output flows from production processes at a subcountry scale) is a priority in life cycle assessment (LCA) studies, particularly in the agri-food sector. Many regionalized LCAs fail to ensure that microlevel inventories are consistent with country-level aggregated data-or "scale consistent." They also fail to construct LCIs using international reference guidelines and trustworthy standardized data sources. This failure generates i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
11
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
8

Relationship

3
5

Authors

Journals

citations
Cited by 15 publications
(11 citation statements)
references
References 25 publications
0
11
0
Order By: Relevance
“…Activity data used to build the life cycle inventory (LCI) were mainly obtained from the farm survey. The inventory for on-farm emissions from forage cultivation, pastures, manure management and enteric fermentation by cattle was adapted as recommended in the method set up for regionalized inventories by Morais et al [41]. Considering the best available estimates applicable for the region of Azores, we used national-level data corresponding to the Intergovernmental Panel on Climate Change (IPCC) Tier 2 approach [42] applied in the Portuguese GHG National Inventory Report (NIR) [43] instead of using Tier 1 defaults.…”
Section: Life Cycle Inventorymentioning
confidence: 99%
“…Activity data used to build the life cycle inventory (LCI) were mainly obtained from the farm survey. The inventory for on-farm emissions from forage cultivation, pastures, manure management and enteric fermentation by cattle was adapted as recommended in the method set up for regionalized inventories by Morais et al [41]. Considering the best available estimates applicable for the region of Azores, we used national-level data corresponding to the Intergovernmental Panel on Climate Change (IPCC) Tier 2 approach [42] applied in the Portuguese GHG National Inventory Report (NIR) [43] instead of using Tier 1 defaults.…”
Section: Life Cycle Inventorymentioning
confidence: 99%
“…There is evidence that SBP reduce nitrogen leaching when compared with SNP [60], but not in a life cycle assessment approach. Besides placing more emphasis on the regionalization of the inventories and activity data, these additional impact categories should also be assessed using regionalized life cycle impact assessment methods [31]. There are now multiple highly regionalized methods available, mainly focusing on land use [61,62] and biodiversity impacts [63,64].…”
Section: Discussionmentioning
confidence: 99%
“…In recent years, LCA regionalization has been one of the main trends within the LCA community [30], as it is of crucial importance for accuracy in results. There are now regionalized agricultural inventories in Portugal, and Alentejo in particular, that enable LCA analyses based on scale-consistent local data [31]. While in the past, the absence of data and models limited the analyses, there are now resources for using a specific inventory for SBP and SNP in Alentejo [31].…”
Section: Inventory Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…Inventory flows for feed ingredients were also obtained from ecoinvent [54]. In this study, the inventories for the main ingredients of the feed (maize silage and grain, wheat and barley) were regionalized for Portugal using the approach of Morais et al [56], which is based on a regionalized adaptation of inventory guidelines produced by the Agribalyse [57] and the World Food LCA Database [58]. The inventory flows adapted for Portugal were the yield, land use, land transformation, fertilizer and pesticide use.…”
Section: Inventory Analysismentioning
confidence: 99%