Consensus-based method development to assess water use in LCA
The WULCA working group’s overall goal focuses on providing practitioners, from both industry and academia, with a consensual and consistent framework to assess, compare and disclose the environmental performance of products and operations regarding freshwater use. In addition to create a discussion platform that boosted the scientific research around water use in LCA, WULCA significantly influenced the creation of the draft standard ISO DIS 14046 on water footprinting: five members of WULCA, including the convener, were directly involved as national representatives within the ISO process. The main scientific deliverables so far have been a framework for water use impact assessment in LCA (Bayart et al., 2010), a review of existing methods for water use in LCA (Kounina et al., 2013),and under review are two papers from a quantitative method comparison and application (Boulay, Bayart, et al., 2013; Boulay, Motoshita, et al., 2013) and a numerous of disseminating activities, including scientific seminars and trainings. These outcomes serve as building blocks for the development of a consensual method.
In May 2013, WULCA received the mandate from the UNEP SETAC Life Cycle Initiative (Project on Global Guidance on Environmental life cycle impact assessment indicators) to lead the harmonization and consensus building for the water use impact category.
The objective of this specific project conducted within WULCA working group was therefore to coordinate the consensuses building process and lead the scientific work into achieving a harmonized method for assessing water use in LCA, involving key method developers and stakeholders through an international collaborative effort.
Preliminary discussions within this working group identified the relevant question from an LCA perspective regarding potential impacts of water consumption at the midpoint level to be: “What is the potential to deprive another freshwater user (human or ecosystem) by consuming freshwater in this region?” (Boulay et al, Int.JLCA, 2015).
Outcomes from expert discussions within WULCA first identified the need to transition from WTA and CTA towards a demand-to-availability ratio (DTA), in order to better answer the overarching question since both ecosystem water demand and human consumption are considered in “demand”. The proposal was accepted by a panel of 48 LCA experts from academia, industry and governmental institutions during three international expert workshops held in Zurich, San Francisco and Tzukuba in 2014. One main limitation identified, in addition to the challenge associated with quantifying ecosystem water demand was that the DTA ratio (similarly to CTA and WTA) fails to represent the absolute water availability (per unit of surface). It only focuses on a metric relative to the use, resulting in loss of information. For example, a DTA ratio of 0.5 describes that half of the water is required by current users, but whether this amount of water is 10 or 1 000 000 m3 for the same area, is unknown. This sometimes leads to arid areas showing less scarcity than known water-abundant regions and the relevance of this for LCA application can be questionable. Three proposals emerged during the workshops that could overcome this limitation: DTAA, DTAx, and 1/AMD.
The process first used a pre-selection criterion to evaluate the relevance of each indicator with respect to the question to be answered. Non relevant indicators were filtered out from the second step (DTAA). Second, a set of criteria were used to guide the decision leading to the selection of 1/AMD through consensus, which is the basis for the recommended AWARE method.
AWARE is to be used as a water use midpoint indicator representing the relative Available WAter REmaining per area in a watershed, after the demand of humans and aquatic ecosystems has been met. It assesses the potential of water deprivation, to either humans or ecosystems, building on the assumption that the less water remaining available per area, the more likely another user will be deprived (Boulay et al., 2016, submitted).
It is first calculated as the water Availability Minus the Demand (AMD) of humans and aquatic ecosystems and is relative to the area (m3 m-2 month-1). In a second step, the value is normalized with the world average result (AMD = 0.0136m3m-2 month-1) and inverted, and hence represents the relative value in comparison with the average m3 consumed in the world (the world average is calculated as a consumption-weighted average). Once inverted, 1/AMD can be interpreted as a surface-time equivalent to generate unused water in this region. The indicator is limited to a range from 0.1 to 100, with a value of 1 corresponding to the world average, and a value of 10, for example, representing a region where there is 10 times less available water remaining per area than the world average. The map below shows the factors at annual level per watersheds (normal average over 12 months).
Figure 1: Map of AWARE factors for non-agricultural activities (normal average over 12 months) Interpretation – Spatio-temporal scale
The indicator is calculated at the sub-watershed level and monthly time-step, and then aggregated, if needed, to country and/or annual resolution. This aggregation can be done in different ways to better represent an agricultural use or a domestic/industrial use, based on the time and region of water use. Characterization factors for agricultural and non-agricultural use are therefore provided, as well as default (“unknown”) ones if the activity is not known.
ATTENTION! An aggregated value at country/annual level based on consumption:
• Does not represent the “average picture” of the country/year. It may completely exclude large regions where no/very low consumption occur (i.e. deserts, most of Canada, etc.).
• Is strongly influenced by agricultural water use (in both “unknown” and “agri” values).
• Represents where/when water is most consumed: often in dryer months/regions.
If the value “doesn’t look right”, look closer! (See which one to prioritize based on the variability information provided in the Excel document)
Interpretation – Relative to the world average
It should be noted that a factor value of 1 is not equivalent to the factor for the average water consumption in the world, i.e. the world average factor to use when the location is not known. This value is calculated as the consumption-weighted average of the factors, which are based on 1/AMD and not AMD, hence the world consumption-based average has a value of 43 for unknown use and 20 and 46 respectively for non-agricultural and agricultural water consumption respectively.
Download (Sub) Watershed level values (annual and monthly)
Downlaod Country level values (annual and monthly) can be obtained here:
Use the table below for version tracking.
Version Tracking Table
|Version number||Date online||Details|
|1.0||June 23rd, 2015||First version, only generic averages available, monthly and annual, country and (sub) watersheds.|
|1.1||August 18th, 2015||Adjustment of EWR data in some regions, additional averages available at country level (agri, non-agri).|
|1.1c||September 17th, 2015||Aggregation error in country values have been corrected, watersheds values have not changed.|
|1.2||November 25th, 2015||Upper cutoff value changed from 1000 to 100.|
|1.2||February, 2016||“unknown” values added in addition to AGRI and NON-AGRI.|
|1.2||April, 2016||"Addition of the Spatial and Temporal standard deviations indicating which resolution to prioritize for each country."|
|1.2||May, 2017||Bug fixed for unspecified compartment input flow in csv file.|
|1.2c||Feb, 2019||Country and region aggregation has been refined, no changes to watershed values.|
Find other versions of the indicators for sensitivity testing country level (different cut-off choices or EWR modelling) as well as other indicators (DTA, DTAx)for comparing and interpreting results, or performing sensitivity studies in
Input data for the calculation of the AWARE factors was obtained from the WaterGAP model, as described in:
Reference to underlying global hydrology model:
Müller Schmied, H., Eisner, S., Franz, D., Wattenbach, M., Portmann, F. T., Flörke, M., and Döll, P.: Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration, Hydrol. Earth Syst. Sci., 18, 3511-3538, doi:10.5194/hess-18-3511-2014, 2014.
Reference to underlying global water use model:
Martina Flörke, Ellen Kynast, Ilona Bärlund, Stephanie Eisner, Florian Wimmer, Joseph Alcamo, Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: A global simulation study, Global Environmental Change, Volume 23, Issue 1, February 2013, Pages 144-156, ISSN 0959-3780, http://dx.doi.org/10.1016/j.gloenvcha.2012.10.018.
The data provided can be downloaded here:
The data are provided on river basin level, with the World's largest 34 river basins being divided into sub-basins. Water uses were summed for each (sub-)basin, river availability is provided for the most downstream cell of each (sub-)basin
Boulay A-M, Bare J, Benini L, et al (2018) The WULCA consensus characterization model for water scarcity footprints: assessing impacts of water consumption based on available water remaining (AWARE). Int J Life Cycle Assess 23:368–378. doi: 10.1007/s11367-017-1333-8
Boulay, A.-M., Bare, J., Benini, L., Berger, M., Klemmayer, I., Lathuilliere, M., … Ridoutt, B. (2014). Building consensus on a generic water scarcity indicator for LCA-based water footprint : preliminary results from WULCA. In LCA Food (Vol. 2050). San Francisco.
Boulay A-M, Bare J, De Camillis C, Döll P, Gassert F, Gerten D, Margni M, et al. 2015. Consensus building on the development of a stress-based indicator for lca-based impact assessment of water consumption: Outcome of the expert workshops. The International Journal of Life Cycle Assessment:1-7.
Frischknecht, R., Fantke, P., Tschümperlin, L., Niero, M., Antón, A., Bare, J., … Jolliet, O. (2016). Global guidance on environmental life cycle impact assessment indicators: progress and case study. The International Journal of Life Cycle Assessment, 21(3), 429–442. doi:10.1007/s11367-015-1025-1.
Boulay, A.-M., Bare, J., Benini, L., Berger, M., Lathuilliere, M., Manzardo, A., … Pfister, S. (2016). Consensus-based water scarcity footprint method from WULCA: the AWARE model. International Journal of Life Cycle Assessment, under revi.
Boulay, A.-M., Pfister, S., Motoshita, M., Schenker, U., Benini, L., Gheewala, S. H., … Harding, K. (2016). Global Guidance for Life Cycle Impact Assessment Indicators, Chapter 5a: Water scarcity. UNEP SETAC Life Cycle Initiative, http://www.lifecycleinitiative.org/applying-lca/lcia-cf/ .
Caldeira C, Quinteiro P, Castanheira E, et al (2018) Water footprint profile of crop-based vegetable oils and waste cooking oil: Comparing two water scarcity footprint methods. J Clean Prod 195:. doi: 10.1016/j.jclepro.2018.05.221
Absar SM, Boulay A-M, Campa MF, et al (2018) The tradeoff between water and carbon footprints of Barnett Shale gas. J Clean Prod. doi: 10.1016/j.jclepro.2018.06.140
What are the units and what do they mean?
A m3-world eq. (obtained from the multiplication of the factor in m3 world-eq./m3 consumed with the inventory in m3 consumed) represents a cubic meter consumed on average in the world. The average refers to a consumption-weighted average, and hence represents the locations where water is currently consumed. This is therefore a comparative unit, representing the “average cubic meter consumed in the world”.
Why are there different factors? What is the difference between “agri” and “non-agri”? Is irrigation water consumption included in both?
At the native scale, monthly and (sub)basin scale, there is only one AWARE factor, calculated with the equation described in the documentation. When this factor has to be provided at different scales, such as annual or country scale, the factors must be aggregated. The difference between “agri” and “non-agri” only lies in the way they are aggregated, reflecting better the temporal or geographical patterns of consumption for agricultural or non agricultural activities, if the exact month and/or watershed is not known. The calculation of the native CF is always the same, and always includes all human water consumption.
Is groundwater availability included?
In WaterGAP, only the renewable part of groundwater storage is considered, which is groundwater recharge. Groundwater recharge is calculated as a fraction of runoff from land but additional recharge from irrigated land is considered, too. More information can be found in Müller Schmied et al (2014) and Döll & Fiedler (2008). Fossil Ground water is not included.
How do I use the AWARE factors?
The local AWARE factor is meant to be multiplied with the local water consumption inventory. Water consumption is defined in Bayart et al. (2010) as a use of water where release into the original watershed does not occur because of evaporation, product integration, or discharge into different watersheds or the sea.
Can I use the AWARE factors to calculate the water footprint of a nation?
The AWARE factors are developed for LCA purposes, and hence for “marginal” water consumptions, i.e. water consumption that does not change the background level of water availability significantly. For large-scale assessment, a different version of AWARE factors can be used. Stay tuned for more development on this (SETAC Europe 2017).
Is reused/desalinated water included?
Water consumption is calculated in WaterGAP as the difference between water withdrawals and return flows. Water reuse lowers the amount of water abstracted in a region, and also reduces return flows. It is therefore indirectly considered in the calculation, but not included in the definition of water consumption which refers to direct freshwater consumption. The same applies for desalinated water.
Copyright 2014 WULCA | All Rights Reserved |Back to the top