Periodic Reporting for period 3 - FINEPRINT (Spatially explicit material footprints: fine-scale assessment of Europe’s global environmental and social impacts)
Période du rapport: 2020-07-01 au 2021-12-31
In the era of globalisation, supply chains are increasingly organised on the international level, thus disconnecting the location of production from final consumption. Consumption has developed into a major, geographically distant driver of various local environmental and social impacts in countries extracting raw materials, such as copper, petroleum, soya or timber. It is hence a major societal challenge to reduce these global environmental and social impacts related to consumption.
Today, the world economy already uses more than 90 billion tonnes of renewable and non-renewable raw materials and levels are constantly increasing. This remarkable growth strongly increased environmental pressures and impacts related to raw material extraction, for example in mining or agriculture. Raw materials embodied in international trade augment even faster than material consumption. This demands considering the “teleconnections” between production and consumption, when designing policy instruments to realise more sustainable product supply chains and to reduce global environmental and social impacts of consumption in European countries.
Methods to assess the worldwide interlinkages between raw material extraction, international trade, manufacturing and final consumption have improved significantly over the past few years. The approach most widely applied for consumption-based (i.e. footprint-type) assessments at the country level is multi-regional input-output (MRIO) analysis. Global MRIO databases have been developed and continuously advanced, e.g. regarding the geographical and temporal coverage as well as the number of industries and products covered. Despite these improvements, the major limitation of all available MRIO databases is that their spatial resolution is limited to the national level. Available models thus assume an average environmental pressure or impact per unit of product originating from a certain country. Thus, they fail to link specific supply chains to the actual geographical location of production, leading to severely distorted footprint results, as the heterogeneity of environmental and social conditions within producing countries is not taken into account. The FINEPRINT project aims at overcoming some of these shortcomings of current supply chain and footprint models.
The overall objective of FINEPRINT is to develop and apply new methods for fine-scale assessments of global material flows, in order to perform spatially explicit analyses of material footprints and related environmental impacts of European consumption. This objective is achieved by
(1) investigating the spatial distribution of raw material extraction since the year 2000 on a high level of geographical detail for a wide range of raw materials, covering crops, fossil energy and metal ores;
(2) analysing the relation between trends and patterns of raw material extraction and related environmental impacts, including issues such as deforestation and water scarcity;
(3) creating physical MRIO models on the national level for a range of raw materials and related products, which are downscaled to the fine-scale level using earth observation data from remote sensing as well as regional statistics and transport data; and
(4) performing fine-scale assessments of the global material footprint of European countries and the related environmental impacts.
Through these activities, FINEPRINT aims at realising a major step forward in footprint science and contribute to establishing robust assessment frameworks for analysing the (un)sustainability of global supply chains and consumption patterns. More solid knowledge on the spatially explicit links between consumption and production will be a pivotal input for the design of European and international policy instruments to realise the transition towards more sustainable production and consumption patterns.
Today, the world economy already uses more than 90 billion tonnes of renewable and non-renewable raw materials and levels are constantly increasing. This remarkable growth strongly increased environmental pressures and impacts related to raw material extraction, for example in mining or agriculture. Raw materials embodied in international trade augment even faster than material consumption. This demands considering the “teleconnections” between production and consumption, when designing policy instruments to realise more sustainable product supply chains and to reduce global environmental and social impacts of consumption in European countries.
Methods to assess the worldwide interlinkages between raw material extraction, international trade, manufacturing and final consumption have improved significantly over the past few years. The approach most widely applied for consumption-based (i.e. footprint-type) assessments at the country level is multi-regional input-output (MRIO) analysis. Global MRIO databases have been developed and continuously advanced, e.g. regarding the geographical and temporal coverage as well as the number of industries and products covered. Despite these improvements, the major limitation of all available MRIO databases is that their spatial resolution is limited to the national level. Available models thus assume an average environmental pressure or impact per unit of product originating from a certain country. Thus, they fail to link specific supply chains to the actual geographical location of production, leading to severely distorted footprint results, as the heterogeneity of environmental and social conditions within producing countries is not taken into account. The FINEPRINT project aims at overcoming some of these shortcomings of current supply chain and footprint models.
The overall objective of FINEPRINT is to develop and apply new methods for fine-scale assessments of global material flows, in order to perform spatially explicit analyses of material footprints and related environmental impacts of European consumption. This objective is achieved by
(1) investigating the spatial distribution of raw material extraction since the year 2000 on a high level of geographical detail for a wide range of raw materials, covering crops, fossil energy and metal ores;
(2) analysing the relation between trends and patterns of raw material extraction and related environmental impacts, including issues such as deforestation and water scarcity;
(3) creating physical MRIO models on the national level for a range of raw materials and related products, which are downscaled to the fine-scale level using earth observation data from remote sensing as well as regional statistics and transport data; and
(4) performing fine-scale assessments of the global material footprint of European countries and the related environmental impacts.
Through these activities, FINEPRINT aims at realising a major step forward in footprint science and contribute to establishing robust assessment frameworks for analysing the (un)sustainability of global supply chains and consumption patterns. More solid knowledge on the spatially explicit links between consumption and production will be a pivotal input for the design of European and international policy instruments to realise the transition towards more sustainable production and consumption patterns.
Global resource extraction and related environmental impacts:
• We established a first version of the spatially explicit global data set of non-renewable resource extraction based on data from a private consultancy database, covering more than 60 metals, minerals and fossil fuels. However, as the private database poses copyright restrictions, we additionally exploit official statistics as well as a mining company reports to publish global mining maps based on publicly available data.
• As existing global crop maps of agricultural production turned out to be of too low quality and time coverage, we decided to develop new methods to create crop maps based on automated classification of satellite images. To test the robustness of the approach, we applied this new method in a case study of the state of Mato Grosso in Brazil, one of the largest producing regions of soybeans and other major crops.
• We developed data sets on the environmental impacts of resource extraction. Most notably, we created a new data set on the direct land use of global mining activities based on visual interpretation of satellite images. This new data set covers more than 6,000 mines worldwide. The data set is visualised in an interactive online tool on the FINEPRINT webpage (www.fineprint.global/viewer).
• In order to understand better the drivers of impacts related to resource extraction, we also further developed spatial statistical models and tested the method for the case of the deforestation impacts of agriculture in the province of Mato Grosso, Brazil.
Spatially explicit global supply chain models:
• As the core of our global supply chain models, we are developing input-output models in physical units for a wide range of raw materials. The most prominent output so far is a global biomass input-output model for agriculture and food products (FABIO) based on UN FAO data. The first version of the model covers 190 countries, 130 products and a time series of 1986 to 2013.
• We applied this model on selected topics related to global biomass use, such as the global land footprint of the EU bioeconomy, where we also tested options to downscale the national data to the grid cell level using available global crop maps.
• In order to illustrate supply chains from resource extraction (agriculture) via processing stages to the country of final consumption, we also developed an interactive online tool for visualising global biomass flows in the form of Sankey diagrams, available on the FINEPRINT website (www.fineprint.global/fabio-viewer).
• Similar to the case of biomass flows, we also compiled the first global physical MRIO model for iron and steel products, in order to assess worldwide supply chains of this raw material of crucial importance for a wide range of economic activities.
Communication and dissemination activities:
• We set-up a comprehensive project website (www.fineprint.global) providing access to data and codes, data visualisation tools as well as to FINEPRINT-related publications. The website has more than 320 visitors per month.
• We initiated a series of short pieces of 3-6 pages featuring particularly interesting aspects of FINEPRINT research in the form of ‘FINEPRINT Briefs’, i.e. (nine Briefs were published in the reporting period).
• We use the online platform ‘ResearchGate’ to communicate our results (www.researchgate.net/project/FINEPRINT). Currently, the project has almost 60 followers and the 23 FINEPRINT-related updates posted in the reporting period were read almost 600 times.
• We established a Twitter Account for FINEPRINT (@fineprintglobal) and set 19 Tweeds in the reporting period. The FINEPRINT Tweeds were read around 12,000 times.
• FINEPRINT was also featured on the website of other organisations. Most outstanding, the website of the European Space Agency presented our ERC project in the section on “Observing the Earth”. The article “Tracing the environmental impacts of supply chains” was read more than 2,000 times.
• We gave 17 oral presentations on FINEPRINT, including two FINEPRINT special sessions, at various international conferences in the fields of Industrial Ecology, Ecological Economics, Economic Geography, and Earth Observation.
• In order to expand and deepen our network, we organised 12 exchange meetings (half day to three days) with a wide range of institutions in Europe and beyond, covering academia, policy institutions and NGOs.
• We hosted six guest researchers from Spain, Italy, Finland and Korea, for periods from three to nine months to perform research in cooperation with the FINEPRINT team.
• We established a first version of the spatially explicit global data set of non-renewable resource extraction based on data from a private consultancy database, covering more than 60 metals, minerals and fossil fuels. However, as the private database poses copyright restrictions, we additionally exploit official statistics as well as a mining company reports to publish global mining maps based on publicly available data.
• As existing global crop maps of agricultural production turned out to be of too low quality and time coverage, we decided to develop new methods to create crop maps based on automated classification of satellite images. To test the robustness of the approach, we applied this new method in a case study of the state of Mato Grosso in Brazil, one of the largest producing regions of soybeans and other major crops.
• We developed data sets on the environmental impacts of resource extraction. Most notably, we created a new data set on the direct land use of global mining activities based on visual interpretation of satellite images. This new data set covers more than 6,000 mines worldwide. The data set is visualised in an interactive online tool on the FINEPRINT webpage (www.fineprint.global/viewer).
• In order to understand better the drivers of impacts related to resource extraction, we also further developed spatial statistical models and tested the method for the case of the deforestation impacts of agriculture in the province of Mato Grosso, Brazil.
Spatially explicit global supply chain models:
• As the core of our global supply chain models, we are developing input-output models in physical units for a wide range of raw materials. The most prominent output so far is a global biomass input-output model for agriculture and food products (FABIO) based on UN FAO data. The first version of the model covers 190 countries, 130 products and a time series of 1986 to 2013.
• We applied this model on selected topics related to global biomass use, such as the global land footprint of the EU bioeconomy, where we also tested options to downscale the national data to the grid cell level using available global crop maps.
• In order to illustrate supply chains from resource extraction (agriculture) via processing stages to the country of final consumption, we also developed an interactive online tool for visualising global biomass flows in the form of Sankey diagrams, available on the FINEPRINT website (www.fineprint.global/fabio-viewer).
• Similar to the case of biomass flows, we also compiled the first global physical MRIO model for iron and steel products, in order to assess worldwide supply chains of this raw material of crucial importance for a wide range of economic activities.
Communication and dissemination activities:
• We set-up a comprehensive project website (www.fineprint.global) providing access to data and codes, data visualisation tools as well as to FINEPRINT-related publications. The website has more than 320 visitors per month.
• We initiated a series of short pieces of 3-6 pages featuring particularly interesting aspects of FINEPRINT research in the form of ‘FINEPRINT Briefs’, i.e. (nine Briefs were published in the reporting period).
• We use the online platform ‘ResearchGate’ to communicate our results (www.researchgate.net/project/FINEPRINT). Currently, the project has almost 60 followers and the 23 FINEPRINT-related updates posted in the reporting period were read almost 600 times.
• We established a Twitter Account for FINEPRINT (@fineprintglobal) and set 19 Tweeds in the reporting period. The FINEPRINT Tweeds were read around 12,000 times.
• FINEPRINT was also featured on the website of other organisations. Most outstanding, the website of the European Space Agency presented our ERC project in the section on “Observing the Earth”. The article “Tracing the environmental impacts of supply chains” was read more than 2,000 times.
• We gave 17 oral presentations on FINEPRINT, including two FINEPRINT special sessions, at various international conferences in the fields of Industrial Ecology, Ecological Economics, Economic Geography, and Earth Observation.
• In order to expand and deepen our network, we organised 12 exchange meetings (half day to three days) with a wide range of institutions in Europe and beyond, covering academia, policy institutions and NGOs.
• We hosted six guest researchers from Spain, Italy, Finland and Korea, for periods from three to nine months to perform research in cooperation with the FINEPRINT team.
FINEPRINT will make significant progress beyond the state of the art in all thematic areas covered by the project. Results delivered by the end of the project will include new methodologies, new global datasets and models, a wide range of empirical assessments as well as innovative online tools to communicate results. Following the principle of open science, we make available all data and codes underlying our research in a GitHub repository (github.com/fineprint-global) containing codes related to the handling and processing of geospatial data sets, the creation of global physical supply chain models and the programming of data visualisation tools.
Global resource extraction and related environmental impacts:
• Creation of various new global data sets with high spatial resolution that will open up a range of research opportunities far beyond FINEPRINT. Among others, these data sets will cover annual time series of global maps of mining of fossil fuels and metal ores since the year 2000, data sets on land use of global mining, data sets on deforestation related to global mining, and global pilot data sets on water input in mining. We will feature all new data sets in open data repositories such as PANGAEA for geospatial data.
• New methodologies to assess agricultural production and impacts using satellite data in combination with automated crop classification based on machine learning. We will apply this method in several case studies in important agricultural production countries in the global South (e.g. Brazil, India). This will serve as the basis to upscale the method to the global level in the future and to produce crop maps of high resolution and quality in the future.
• The new FINEPRINT data sets as well as various other global data sets that are of high importance for analyses related to raw material extraction and supply chains will be integrated into a global and open database with a consistent geospatial grid at 30 arc-second spatial resolution (approximately 1x1 km in the equator). The database will be available at the project webpage (www.fineprint.global) as well as on PANGAEA.
Spatially explicit global supply chain models:
• Already by half-time of the project, FINEPRINT significantly advanced the state of the art regarding the development of global, multi-regional physical input-output models. The global physical model of biomass flows (FABIO) will be further extended in terms of product detail (currently covering 130 agri-food products, it will be expanded by wood and paper products as well as biomaterials) and updated to the then latest year available.
• At the end of the project we will have implemented regional test cases how information on agricultural production by grid cell from remote sensing (see above) can be combined with regional trade statistics and the FABIO model. This will deliver a highly innovative method to calculate fine-scale biomass footprints of consumption and to assess the global drivers of local impacts, for example land and water use in agriculture. This will deliver knowledge about the environmental hotspots of biomass supply chains at an unprecedented level of precision and detail.
• Similar to FABIO, the project will deliver the first set of physical MRIO models for metal ores that overcome limitations of current models that use monetary data to allocate flows along supply chains. In addition to the model for global flows of iron and steel products developed in the first half of the project, we will also construct physical MRIO models for copper and aluminium, and possibly other mineral resources.
• While we use remote sensing data and regional statistics to link national biomass flows with the grid cell level, we will set up transport models (or similar optimisation models) for the case of metal ores. These models will allow tracing the flows of metal ores from the location of extraction via potential processing (in smelters and refineries) to a port, from which raw or processed materials are exported to other countries for further manufacturing.
Global resource extraction and related environmental impacts:
• Creation of various new global data sets with high spatial resolution that will open up a range of research opportunities far beyond FINEPRINT. Among others, these data sets will cover annual time series of global maps of mining of fossil fuels and metal ores since the year 2000, data sets on land use of global mining, data sets on deforestation related to global mining, and global pilot data sets on water input in mining. We will feature all new data sets in open data repositories such as PANGAEA for geospatial data.
• New methodologies to assess agricultural production and impacts using satellite data in combination with automated crop classification based on machine learning. We will apply this method in several case studies in important agricultural production countries in the global South (e.g. Brazil, India). This will serve as the basis to upscale the method to the global level in the future and to produce crop maps of high resolution and quality in the future.
• The new FINEPRINT data sets as well as various other global data sets that are of high importance for analyses related to raw material extraction and supply chains will be integrated into a global and open database with a consistent geospatial grid at 30 arc-second spatial resolution (approximately 1x1 km in the equator). The database will be available at the project webpage (www.fineprint.global) as well as on PANGAEA.
Spatially explicit global supply chain models:
• Already by half-time of the project, FINEPRINT significantly advanced the state of the art regarding the development of global, multi-regional physical input-output models. The global physical model of biomass flows (FABIO) will be further extended in terms of product detail (currently covering 130 agri-food products, it will be expanded by wood and paper products as well as biomaterials) and updated to the then latest year available.
• At the end of the project we will have implemented regional test cases how information on agricultural production by grid cell from remote sensing (see above) can be combined with regional trade statistics and the FABIO model. This will deliver a highly innovative method to calculate fine-scale biomass footprints of consumption and to assess the global drivers of local impacts, for example land and water use in agriculture. This will deliver knowledge about the environmental hotspots of biomass supply chains at an unprecedented level of precision and detail.
• Similar to FABIO, the project will deliver the first set of physical MRIO models for metal ores that overcome limitations of current models that use monetary data to allocate flows along supply chains. In addition to the model for global flows of iron and steel products developed in the first half of the project, we will also construct physical MRIO models for copper and aluminium, and possibly other mineral resources.
• While we use remote sensing data and regional statistics to link national biomass flows with the grid cell level, we will set up transport models (or similar optimisation models) for the case of metal ores. These models will allow tracing the flows of metal ores from the location of extraction via potential processing (in smelters and refineries) to a port, from which raw or processed materials are exported to other countries for further manufacturing.