Accredited official statistics

17 Global Impacts of UK Consumption

Updated 7 May 2024

Applies to England

© Crown copyright 2024

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This publication is available at https://www.gov.uk/government/statistics/england-biodiversity-indicators/17-global-impacts-of-uk-consumption

Data last updated: November 2023

Latest data available: 2021

Introduction

As this is an official statistic in development, the England biodiversity indicators project team welcomes feedback on the novel methods used in the development of this indicator. For example, feedback on whether this new indicator measures something users feel should be measured, and on how well it measures global impacts.

Official statistics in development are official statistics that are undergoing a development; they may be new or existing statistics, and will be tested with users, in line with the standards of trustworthiness, quality, and value in the Code of Practice for Statistics.

To give feedback, email the England biodiversity indicators project team at enviro.statistics@defra.gov.uk.

This official statistic in development estimates the global environmental impacts of UK consumption of agricultural crop commodities (and for some metrics additionally cattle-related and timber commodities), between 2005 and 2021. Impacts considered include:

  • tropical deforestation (headline result)
  • biodiversity loss
  • carbon dioxide (CO2) emissions related to tropical deforestation
  • water consumption and scarcity-weighted water footprint
  • cropland area harvested
  • material consumption (tonnes of biomass production)

Results are shown for total UK consumption of agricultural crop commodities. However, the underlying data set also breaks this down by the commodity responsible for the impact, and the production countries/territories in which the impacts take place. The production countries/territories included align with those reported by the Food and Agriculture Organisation of the United Nations (FAO). The breakdown of results for each impact can also be visualised through an external dashboard. The UK is included as one of the production countries within this breakdown (i.e. the indicator does not only focus on consumption of overseas production, but on total consumption wherever this is sourced from).

For the 2023 release of this indicator under development, there have been updates to the underlying data sources and methodology. These have been applied across the full time series, so the data presented here are consistent across all years presented, but differ from the data released within previous updates. See the technical documentation for further information about what has changed compared to previous releases.

Type of indicator

State indicator

Assessment of change

As this indicator is an official statistic in development it has not been assessed.

17. Global biodiversity impacts of UK consumption

Trend description for Figure 17.1

Annual UK consumption of crop, cattle-related and timber commodities in 2021 (the latest year for which data are available) was associated with an estimated 30,656 hectares of agriculture-driven deforestation worldwide (Figure 17.1); this is 49.6% lower than the annual estimate for the year 2005 (when the time-series began). The annual estimated area of deforestation associated with UK consumption in 2021 was 13.2% lower than in the year 2016, and 1.0% lower than in the year 2020.

Figure 17.1: Area of deforestation associated with UK consumption annually.

Download the data for Figure 17.1 in ods format

Source: Calculated via the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; the Food and Agriculture Organisation of the United Nations; and Singh & Persson (2023).

Notes about Figure 17.1:

  • estimates refer to crop, cattle-related, and timber commodities only
  • although in the 2021 and 2022 releases of this indicator only tropical and subtropical deforestation were reported, these estimates now refer to deforestation taking place globally, including in temperate and boreal regions
  • deforestation refers to conversion of natural forest to any commodity production related land use (including plantation forestry). Felling and replanting of tree areas that are already plantation forests is not considered deforestation
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Results for other impact metrics are presented within the Background section below.

Additional measures

Biodiversity Loss

Trend description for Figure 17.2

Annual UK consumption of crop commodities in 2021 was responsible for a predicted regional species loss of approximately 71 species (Figure 17.2); this is 24.0% lower than the annual estimate for the year 2005. The annual predicted regional species loss associated with UK consumption in 2021 was 13.9% higher than in the year 2016, and 6.5% higher than in the year 2020.

Figure 17.2. Predicted regional species loss associated with UK consumption annually.

Download the data for Figure 17.2 in ods format

Source: Calculated via the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; the Food and Agriculture Organisation of the United Nations; and Chaudhary and Kastner (2016).

Notes about Figure 17.2:

  • estimates refer to crop commodities only
  • predicted regional species loss is defined as the number of species predicted to become extinct if current conditions continue, per ecoregion
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Trend description for Figure 17.3 (Biodiversity Loss)

Annual UK consumption of crop commodities in 2021 was responsible for an estimated 4.97 billion species richness-weighted hectares of land use worldwide (Figure 17.3); this is 28.3% lower than the annual estimate for the year 2005. The annual estimated species richness-weighted hectares of land use associated with UK consumption in 2021 was 10.3% higher than in the year 2016, and 3.8% higher than in the year 2020. Species richness-weighted hectares represent the hectares of crop production scaled by the number of species present in that hectare, therefore showing where there is overlap between production and areas of biodiversity importance.

Figure 17.3: Species richness-weighted crop area associated with UK consumption annually.

Download the data for Figure 17.3 in ods format

Source: Calculated via the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; the Food and Agriculture Organisation of the United Nations; MapSPAM; BirdLife International; and the International Union for the Conservation of Nature.

Notes about Figure 17.3:

  • estimates refer to crop commodities only
  • as species-hectares represent the hectares of crop production scaled by the number of species present, the total species- hectares can be significantly more than the total physical hectares, as each hectare will have more than one species present
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Trend description for Figure 17.4

Annual UK consumption of crop, cattle-related and timber commodities in 2021 was responsible for an estimated 6.0 million tonnes of CO2 emissions linked to deforestation worldwide, excluding peat drainage (Figure 17.4); this is 60.0% lower than the annual estimate for the year 2005. The annual estimated CO2 emissions linked to deforestation (excluding peat drainage) associated with UK consumption in 2021 was 20.3% higher than in the year 2016, and 1.6% higher than in the year 2020.

Figure 17.4: Deforestation emissions (excluding peat drainage) associated with UK consumption annually.

Download the data for Figure 17.4 in ods format

Source: Calculated within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; the Food and Agriculture Organisation of the United Nations; and Singh & Persson (2023).

Notes about Figure 17.4:

  • estimates refer to CO2 emissions from deforestation as a result of crop, cattle-related and timber commodities only
  • currently, deforestation linked emission calculations follow the methods developed by Pendrill et al. (2019) and the assumptions inherent in this approach are applied for tropical and non-tropical forest loss
  • although in the 2021 and 2022 releases of this indicator deforestation emissions including peat drainage were reported, these estimates now exclude peat drainage, due to changes in the underlying data
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Water consumption and scarcity-weighted water footprint

Trend description for Figure 17.5

Annual UK consumption of crop commodities in 2021 was responsible for an estimated 797.32 billion cubic metres of scarcity-weighted blue water use worldwide (Figure 17.5); this is 4.8% lower than the annual estimate for the year 2005. The annual estimated scarcity-weighted blue water use associated with UK consumption in 2021 was 28.3% higher than in the year 2016, and 5.0% higher than in the year 2020. Scarcity-weighted blue water use scales the blue water footprint (surface and groundwater consumed as a result of production) according to water availability in a region after human and aquatic ecosystem demands have been met.

Figure 17.5: Scarcity-weighted blue water use associated with UK consumption annually.

Download the data for Figure 17.5 in ods format

Source: Calculated via the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; the Food and Agriculture Organisation of the United Nations; the Water Footprint Network; and Boulay et al. (2018).

Notes about Figure 17.5:

  • estimates refer to crop commodities only
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Cropland area harvested

Trend description for Figure 17.6

Annual UK consumption of crop commodities in 2021 was associated with an estimated total land use footprint of 17.3 million hectares (Figure 17.6); this is 16.5% lower than the annual estimate for the year 2005. The annual estimated total land use footprint associated with UK consumption in 2021 was 17.4% higher than in the year 2016, and 6.3% higher than in the year 2020.

Figure 17.6: Cropland area harvested associated with UK consumption annually.

Download the data for Figure 17.6 in ods format

Source: Calculated via the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; and the Food and Agriculture Organisation of the United Nations.

Notes about Figure 17.6:

  • estimates refer to crop commodities only
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Material consumption (tonnes of biomass production)

Trend description for Figure 17.7

Annual UK consumption of crop, cattle-related, and timber commodities in 2021 was responsible for an estimated 142.6 million tonnes of material production worldwide (Figure 17.7); this is 12.8% lower than the annual estimate for the year 2005. The annual estimated material production associated with UK consumption in 2021 was 13.8% higher than in the year 2016, and 8.4% higher than in the year 2020.

Figure 17.7: Crop production (biomass) associated with UK consumption annually.

Download the data for Figure 17.7 in ods format

Source: Calculated via the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from EXIOBASE; and the Food and Agriculture Organisation of the United Nations.

Notes about Figure 17.7:

  • estimates refer to crop, cattle-related and timber commodities only
  • note that the entire time series has been recalculated compared to the previous data release, to ensure consistency across the time series following updates to underlying data sources and updates to the methodology used to calculate the indicator (see the technical documentation for further information)

Further information

Relevance of Figure 17.1

The UK government’s 25 Year Environment Plan has set out a series of indicators (the Outcome Indicator Framework) to track progress. One of these indicators (K1) relates to the ‘overseas environmental impacts of UK consumption of key commodities’ and is designed to measure the impacts associated with UK consumption of key commodities. Last year’s release fed into this indicator in the 2022 reporting for the Outcome Indicator Framework. The full list of indicators in development can be found in the 25 Year Environment Plan Outcome Indicator Framework.

The UK and England Biodiversity Indicators are currently being assessed alongside the Environment Improvement Plan Targets, and the new Kunming-Montreal Global Biodiversity Framework Targets, when this work has been completed the references to Biodiversity 2020 and the Aichi Global Biodiversity Framework Targets will be updated.

Methodology

The full methodology for this indicator can be found in the technical documentation. This indicator is being published as an official statistic in development to facilitate user involvement in its development. Information on how the underlying data have been obtained and how the indicator has been prepared is available in the technical documentation. We would welcome any feedback, particularly on the usefulness and value of these statistics. You can email us at: enviro.statistics@defra.gov.uk.

The indicator is based on MRIO (multi-regional input-output) modelling. MRIOs model global trade flows representing the monetary inputs and outputs across different countries/territories and their commercial sectors (for example, oilseeds, cattle farming, and paddy rice). The MRIO data used for this indicator are from EXIOBASE.

The EXIOBASE data set has been selected due to its considerable temporal coverage, and to increase alignment and consistency with other UK footprint accounts (the UK Carbon and Material Footprints). Additionally, it allows for data to be broken down into a high number of different sectors compared to other MRIO data sets (however, note that EXIOBASE country/territory data are more aggregated than in some MRIO data; therefore a separate data set available via the associated dashboard which is not part of this data release has been published using data from the Global Trade Analysis Project (GTAP) to provide an alternative that may be more appropriate for certain countries/territories).

The MRIO data are hybridised with physical data (tonnes of each commodity) from the Food and Agriculture Organization FAOSTAT and, in the case of timber, UN Comtrade, using the Stockholm Environment Institute’s IOTA (Input Output Trade Analysis) model (Croft et al., 2018). This step allows for a higher resolution breakdown of commodities (for example, palm oil and soybeans, instead of just oilseeds) and of countries/territories of origin than MRIO data would provide alone. This step also allows trade – in physical units – at a commodity level to be included before these data are integrated within the sector-level MRIO framework. This gives results at a greater level of product-specificity, and accuracy, than a standalone MRIO-based account. The FAO Statistics were chosen for use because they are a comprehensive set of global production statistics, collected from official national statistics of each country/territory, which can be easily incorporated into the modelling framework. For timber, UN Comtrade data were used instead due to the discontinuation of FAO timber trade data. The modelling framework allows for an estimation of the country/territory of origin of a commodity, accounting for cases where commodities are embedded within other products as an ingredient or input, and cases where commodities are re-exported through multiple countries/territories before the point of consumption in the UK.

To determine deforestation rates and carbon dioxide (CO2) emissions from deforestation, data from Chalmers University of Technology which link deforestation and commodity production (Singh & Persson, 2023) are used to proportionally attribute UK deforestation impacts based on the volumes of each commodity the UK consumes within each production country/territory. For example, if the Singh & Persson (2023) data set links x hectares of deforestation in a given country/territory with the production of a particular commodity, and the UK consumes y% of that commodity, then it is assumed that the UK is responsible for y% of those x hectares. This deforestation data set was selected as it provides data on deforestation and its associated agricultural commodity drivers, with comprehensive coverage. Positive change would likely be represented by a reduction in deforestation rates and CO2 emissions from deforestation but would need to be interpreted alongside additional information (such as remaining forest area, deforestation per tonne of production, and understanding of the drivers behind the change) for a robust assessment.

To estimate biodiversity loss, two separate methods are utilised. The first method uses crop- and country/territory-specific characterisation factors, provided by Chaudhary and Kastner (2016), which are used to estimate the impact per tonne of production for 152 crops/crop groups in 171 countries/territories. This gives an estimate of regional species loss (the number of species predicted to be committed to extinction if current conditions continue per ecoregion). Positive change would be represented by a decrease in predicted species loss. The other method to estimate biodiversity loss (providing separate results from the first method) uses MapSPAM data (a modelled global data set providing information on which crops are grown where) alongside species richness information from the International Union for the Conservation of Nature (IUCN) and BirdLife International to estimate ‘species richness-weighted extent of crop production’. This represents the hectares of crop production scaled by the number of species present in that hectare, and therefore where there is overlap between production and areas of biodiversity importance. Positive change would be represented by a decrease in ‘species richness-weighted extent of crop production’ embedded in consumption.

Water consumption was estimated from the Water Footprint Network. To account for water scarcity in regions of production, blue (irrigated) water consumption was scaled by water availability in a region after human and aquatic ecosystem demand has been met, using conversion factors sourced from Boulay et al. (2018). Positive change would be represented by a reduction in scarcity-weighted blue water use.

Caveats, limitations and uncertainties

For accurate interpretation of the results presented within this indicator, it is necessary to understand the following caveats:

  • data tracing all commodities exactly back to their countries/territories of origin are not publicly available. Whilst based on empirical statistics, the outputs produced by this indicator are derived from modelling so should be considered as estimates rather than exact values
  • only the country/territory of origin, and not the exact location of origin, can be obtained from the current version of the indicator as only national scale data were used. This means impacts are based on average production practices per country/territory, not the actual impacts at the exact location the product came from. This could be improved by using sub-national data (where available) in subsequent iterations of the indicator
  • data linking impacts to trade are compiled at the national level, meaning any action by the UK in specific regions will be ‘averaged’ across the full global supply chain. Therefore, it will be hard to differentiate UK action from the actions of other consumer nations. The indicator will be more responsive to multi-national/-lateral action than to UK action specifically
  • the objective of this data set is to identify impacts that are geographically specific, so linking consumption to production location is key to understanding these impacts. An MRIO is therefore linked to additional data through a modelling framework to estimate consumption via production location. We use EXIOBASE for this, so that the financial flows (the picture of the whole economy) align with the UK Material and Carbon Footprints. However, each of these is measuring something that does not vary with location and so does not require this additional step (for example, estimates of carbon from consumption are based on factors applied to the production process, not the location of the process). Hence there are limits to how much this set of indicators and the Material and Carbon indicators can be directly compared
  • lags in the underlying data sets mean that data are only available up to 2021 in the current release. Care should be taken in analysing trends over time which can reflect complex changes in production volume, trade distributions, estimated inter-sectoral demands and final consumption expenditure
  • estimates of the environmental impacts of consumption reported by other sources could differ from results reported here due to differences in the underlying data and methods. Use of different MRIOs as the data set underlying this indicator (for example, GTAP rather than EXIOBASE) could also lead to differences in results, due to factors including geographic and sectoral resolution, temporal coverage and lag. Note that a separate data set (not forming part of the UK data release) using GTAP has been published on the associated dashboard website, which will allow for a wider variety of countries/territories to have access to data on their consumption impacts.
  • the presence of oil palm and soy as key sources of UK deforestation risk is common to other assessments, but the data reveal UK linkages to other supply chains (such as beans, cassava, paddy rice) that are not often considered as ‘deforestation risk’ commodities in other publications. These supply chains warrant further investigation to understand which sectors of consumption link to these estimated impacts.

In many of the countries/territories where commodities are driving rapid impacts, the UK represents a small proportion of the total demand. However, the underlying data set allows the proportion of demand to be identified and the other consumers also contributing to the demand, hence providing better opportunities to work with producer countries/territories and to work multi-laterally with other consumer countries/territories to address sustainable production and reduce impacts.

To discuss the data and methodology, caveats, limitations and uncertainties associated with this indicator under development, the development team at the Stockholm Environment Institute, University of York, can be contacted at info@commodityfootprints.earth.

Additional notes

  • all crops with data recorded in FAOSTAT are included (see technical documentation for further detail and exceptions)
  • “Cattle-related commodities” refer to meat, offal, fats and hides from cattle and buffalo as reported within FAOSTAT, and aligning with data usages within Singh & Persson, 2023. Note that impacts attributed to cattle result from land used for pasture, whilst impacts from commodities used as feed are presented as impacts associated with the raw commodity (for example, soy).
  • underlying data sets currently restrict analysis to the years 2005 to 2021. See the technical documentation for further information about planned data updates for each underlying data set
  • characterisation factors are used as estimates of an environmental impact per unit of stressor (for example, the land use per kg of production or the biodiversity loss per unit of pollutant)

Background

This indicator was calculated by the Stockholm Environment Institute under a project managed by the Joint Nature Conservation Committee (JNCC) and contracted by the Department for Environment Food and Rural Affairs (Defra) to develop an indicator for the 25YEP’s Outcome Indicator Framework. It builds on data from a variety of sources, including the Norwegian University of Science and Technology’s (NTNU) EXIOBASE trade model, Chalmers University of Technology (Singh & Persson, 2023), the Food and Agriculture Organisation of the United Nations, UN Comtrade, the Water Footprint Network, the Water Use in Life Cycle Assessment (WULCA) (Boulay et al., 2018), ETH Zurich and the Institute of Social Ecology Vienna (Chaudhary and Kastner, 2016), BirdLife International and the IUCN. It also builds on previous work including a proof of concept study which recommended MRIO as the approach to use for this indicator (Route2 Sustainability & Carbon Smart, 2019) and a separate study investigating an alternative approach which was not recommended to be taken forward (Harris et al., 2019; both of these studies are available on the Defra Science and Research Projects website). JNCC has also produced entry-level guides introducing the area/topics of sustainable production and consumption in general and various ways to measure the sustainability of consumption, which may be of interest to anyone wishing to learn more (Hawker et al., 2020; Harris, 2023).

In addition to the headline metric presented in the key results section (deforestation), footprints were also calculated for biodiversity, deforestation-related CO2 emissions, scarcity-weighted water footprint, land use footprint (hectares per commodity) and material footprint (tonnes per commodity). Further graphs (for example, intensity of each footprint rather than the magnitude) can be found in Annex 1 of the technical documentation. Additional breakdowns of commodities and producing countries/territories can be visualised using the associated dashboard.

References

  • Boulay, A.M., Bare, J., Benini, L., Berger, M., Lathuillière, M.J., Manzardo, A., Margni, M., Motoshita, M., Núñez, M., Pastor, A.V. & Ridoutt, B. 2018. The WULCA consensus characterization model for water scarcity footprints: assessing impacts of water consumption based on available water remaining (AWARE). The International Journal of Life Cycle Assessment, 23(2), pp. 368-378. Available at: https://link.springer.com/article/10.1007/s11367-017-1333-8

  • Chaudhary, A. & Brooks, T. 2018. Land Use Intensity-Specific Global Characterization Factors to Assess Product Biodiversity Footprints. Environmental Science & Technology, 52(9), pp. 5094-5104. Available at: https://pubs.acs.org/doi/10.1021/acs.est.7b05570

  • Chaudhary, A. & Kastner, T. 2016. Land use biodiversity impacts embodied in international food trade. Global Environmental Change, 38, pp. 195-204. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0959378016300346

  • Croft S.A., West C.D. & Green J.M. 2018. Capturing the heterogeneity of sub-national production in global trade flows. Journal of Cleaner Production, 203, pp. 1106–1118. Available at: https://www.sciencedirect.com/science/article/pii/S0959652618326180

  • Croft, S., West, C., Harris, M., Otley, A. & Way, L. 2021. Towards indicators of the global environmental impacts of UK consumption: Embedded Deforestation. JNCC Report No. 681, JNCC, Peterborough, ISSN 0963-9091. Available at: https://hub.jncc.gov.uk/assets/709e0304-0460-4f83-9dcd-3fb490f5e676

  • Harris, M., Hawker, J., Croft, S., Smith, M., Way, L., Williams, J., Wilkinson, S., Hobbs, E., Green, J., West, C. & Mortimer, D. 2019. Is the Proportion of Imports Certified as Being from Sustainable Sources an Effective Indicator of UK Environmental Impact Overseas? Contracted Report to Defra. Available at: https://randd.defra.gov.uk/ProjectDetails?ProjectId=20329

  • Harris, M. 2023. An introduction to consumption-based metrics. JNCC Report 743: Annex 1. JNCC, Peterborough. Available at: https://hub.jncc.gov.uk/assets/dc81dd16-9b1c-4eeb-b350-dcadd5ade736#jncc-report-743-annex-1.pdf

  • Hawker, J., Smith, M., Way, L., Harris, M., Donovan, D., Wright, E. & Wilkinson, S. 2020. The LET (Linking Environment to Trade) Guide. JNCC, Peterborough. Available at: https://hub.jncc.gov.uk/assets/daa8e792-a36e-436b-98d7-e2f38e860650

  • International Union for the Conservation of Nature (IUCN). 2021. The IUCN Red List of Threatened Species. Version 2021-3. Available at: https://www.iucnredlist.org. Downloaded on 20th December 2021.

  • Mekonnen, M.M. and Hoekstra, A.Y. 2010. The green, blue and grey water footprint of crops and derived crops products. Available at: https://www.waterfootprint.org/media/downloads/Report47-WaterFootprintCrops-Vol1.pdf

  • Pendrill, F., Persson, U.M., Godar, J., Kastner, T., Moran, D., Schmidt, S. & Wood, R., 2019. Agricultural and forestry trade drives large share of tropical deforestation emissions. Global Environmental Change, 56, pp. 1-10. Available at: https://www.sciencedirect.com/science/article/pii/S0959378018314365

  • Route2 Sustainability & Carbon Smart. 2019. Piloting Indicators for The Global Environmental Impacts of UK Consumption. Defra Report. Available at: https://hub.jncc.gov.uk/assets/daa8e792-a36e-436b-98d7-e2f38e860650

  • Singh, C. & Persson, M. 2023. Agriculture commodity- and forestry-driven deforestation and associated carbon emissions (2001-2021). Chalmers University of Technology. Data supplied by authors.

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