Environmental footprint family to address local to planetary sustainability and deliver on the SDGs

Vanham, Davy; Leip, Adrian; Galli, Alessandro; Kastner, Thomas; Brückner, Martin; Uwizeye, Aimable; Dijk, Kimo van; Ercin, Ertug; Dalin, Carole; Brandão, Miguel; Bastianoni, Simone; Fang, Kai; Leach, Allison M.; Chapagain, Ashok; Velde, M. van der; Sala, Serenella; Pant, Rana; Mancini, Lucia; Monforti-Ferrario, Fabio; Carmona-Garcia, Gema; Marques, Alexandra; Weiß, Franz; Hoekstra, Arjen Ysbert

doi:10.1016/j.scitotenv.2019.133642

Cited by 303 publications

(199 citation statements)

References 89 publications

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“…While our primary intention was to quantify WF caps at the basin level, the estimated monthly BWA figures for the world's river basins—when summed up over the year and all basins—can feed the discourse on PBs (Vanham et al, ). Steffen et al () have proposed 4,000 km 3 year −1 (with an uncertainty range of 4,000–6,000 km 3 year −1 ) as a PB for global blue freshwater consumption, while acknowledging the need for basin boundaries as well.…”

Section: A Basis For a Pb On Watermentioning

confidence: 99%

Capping Human Water Footprints in the World's River Basins

et al. 2020

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Increased water demand and overexploitation of limited freshwater resources lead to water scarcity, economic downturn, and conflicts over water in many places around the world. A sensible policy measure to bridle humanity's water footprint, then, is to set local and time‐specific water footprint caps, to ensure that water appropriation for human uses remains within ecological boundaries. This study estimates—for all river basins in the world—monthly blue water flows that can be allocated to human uses, while explicitly earmarking water for nature. Addressing some implications of temporal variability, we quantify trade‐offs between potentially violating environmental flow requirements versus underutilizing available flow—a trade‐off that is particularly pronounced in basins with a high seasonal and interannual variability. We discuss several limitations and challenges that need to be overcome if setting water footprint caps is to become a practically applicable policy instrument, including the need (for policy makers) to reach agreement on which specific capping procedure to follow. We conclude by relating local and time‐specific water footprint caps to the planetary boundary for freshwater use.

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Section: A Basis For a Pb On Watermentioning

confidence: 99%

Capping Human Water Footprints in the World's River Basins

et al. 2020

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“…The EU energy sector is responsible for many environmental pressures, the latter being resource use and pollution [4,5]. The most obvious one is the emission of GHGs, mostly CO 2 .…”

Section: Introductionmentioning

confidence: 99%

The consumptive water footprint of the European Union energy sector

Vanham

Medarac

Schyns

et al. 2019

Environ. Res. Lett.

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Energy security for the EU is a priority of the European Commission. Although both blue and green water resources are increasingly scarce, the EU currently does not explicitly account for water resource use in its energy related policies. Here we quantify the freshwater resources required to produce the different energy sources in the EU, by means of the water footprint (WF) concept. We conduct the most geographically detailed consumptive WF assessment for the EU to date, based on the newest spatial databases of energy sources. We calculate that fossil fuels and nuclear energy are moderate water users (136-627 m 3 /terajoules (m 3 TJ -1 )). Of the renewable energy sources, wood, reservoir hydropower and first generation biofuels require large water amounts (9114-137 624 m 3 TJ -1 ). The most water efficient are solar, wind, geothermal and run-of-river hydropower (1-117 m 3 TJ -1 ). For the EU territory for the year 2015, our geographically detailed assessment results in a WF of energy production from domestic water resources of 198 km 3 , or 1068 litres per person per day. The WF of energy consumption is larger as the EU is to a high level dependent on imports for its energy supply, amounting to 242 km 3 per year, or 1301 litres per person per day. The WF of energy production within the 281 EU statistical NUTS-2 (Nomenclature of Territorial Units for Statistics) regions shows spatially heterogeneous values. Different energy sources produced and consumed in the EU contribute to and are produced under average annual and monthly blue water stress and green water scarcity. The amount of production under WS is especially high during summer months. Imported energy sources are also partly produced under WS, revealing risks to EU energy security due to externalisation. For the EU, to decarbonise and increase the share of renewables of its energy supply, it needs to formulate policies that take the water use of energy sources into account. In doing so, the spatial and temporal characteristics of water use and water stress should particularly be considered.

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“…Therefore, efforts to sustainably manage reactive N use and to mitigate N release to the environment have implications for meeting sustainability objectives ranging from the local scale (e.g. municipal or institutional net-zero emissions targets) to achieving the United Nations' sustainable development goals (SDGs) (Vanham et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Geographic versus institutional drivers of nitrogen footprints: a comparison of two urban universities

MacDonald

Talbot

Moore

et al. 2020

Environ. Res. Lett.

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Excess reactive nitrogen (N) is linked to a myriad of environmental problems that carry large social costs. Nitrogen footprint tools can help institutions understand how their direct and indirect activities are associated with N release to the environment through energy use, food, and transportation. However, little is known about how geographic context shapes the environmental footprints of institutions. Defining the system boundaries over which institutions are responsible and able to control individual drivers of N footprints is also a challenge. Here, we compare and contrast the circa 2017 N footprints for two research intensive universities located in Montréal, Canada, with a combined full-time equivalent campus population of ∼83 000. Our estimate of McGill University's N footprint (121.2 t N yr −1 ) is 48% greater than Université de Montréal's (74.1 t N yr −1 ), which is also reflected on a per capita basis (3.3 and 1.6 kg N capita −1 yr −1 , respectively). Key institutional factors that explain the differences include McGill's larger residential and international student populations, research farm, and characteristics of its on-campus fuel use. We use a series of counterfactual scenarios to test how shared urban geographic context factors lead to an effective reduction of the N footprints at both universities: the relatively small direct role of both institutions in food intake on campus (29%-68% reduction compared to a counterfactual scenario), energy from hydroelectricity (17%-21% reduction), and minimal car commuting by students (2%-3% reduction). In contrast, the nearzero N removal from the municipal wastewater system effectively increases the N footprints (11%-13% increase compared to a modest N removal and offset scenario). Our findings suggest that a shared geographic context of a dense city with plentiful off-campus housing, food options, and access to hydroelectricity shapes the absolute N footprints of Montréal's two main universities more than the divergent institutional characteristics that influence their relative N footprints.

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Environmental footprint family to address local to planetary sustainability and deliver on the SDGs

Cited by 303 publications

References 89 publications

Capping Human Water Footprints in the World's River Basins

Capping Human Water Footprints in the World's River Basins

The consumptive water footprint of the European Union energy sector

Geographic versus institutional drivers of nitrogen footprints: a comparison of two urban universities

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