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Global Environmental Footprints
Glen Peters, Robbie Andrew, Jonas Karstensen (CICERO)Nordic Council of Ministers, Environment and Economy Group (16/03/2017)
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• Why look at “environmental footprints”?• Methods and data• Policy relevance• Policy applications• Questions and discussion
Outline
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Consumption-based emissions are:production-based emissions – emissions to produce exports + emissions to produce imports
Source: Global Carbon Budget 2016 (update)
Consumption-based emissions
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Consumption-based emissions are:production-based emissions – emissions to produce exports + emissions to produce imports
Source: Global Carbon Budget 2016
Consumption-based emissions
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Can calculate an environmental footprint for all environmental problems, but policy implications can differ
Source: Hoekstra and Wiedmann (2014)
Global environmental footprints
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• Scale– Product, person, household, city, state, country– Bottom-up (LCA), top-down (MRIO)
• Flow– Physical (water in a melon, carbon in coal)– Virtual (emissions air/water to produce a product)
• Supply chain– Apparent consumption (direct trade flows only)– Final consumption (global supply chains)
Definitions
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• Air pollutants (most common, virtual, final consumption)– Long-lived: CO2, GHG (“carbon footprints”)
– Short-lived: SO2, black carbon, etc
• Material footprints – Metals ores, fossil fuels, construction, biomass, etc– Apparent (Domestic Material Consumption, DMC)– Final consumption (physical and virtual flows)
• Water– Green (used by plants, rainwater)– Blue (ground, surface: hydropower, irrigation, industry)– Grey (polluted)– Apparent or final consumption
Environmental footprints (1)
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• Land– Crops, pastures, forests– Physical areas– Apparent or final consumption– Related (ecological footprint, HANPP)
• Economic– Trade in Value Added (TiVA)– Economic flows– Final consumption
• …
Environmental footprints (2)
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Danish CO2 emissions differ when using environmental (UNFCCC) and economic (NAMEA) accountsInternational transport the main issue, and effects all Nordic countries (to different degrees)
Emissions data
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Different datasets, different total emissions, different sector distribution
Emissions data
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• Multi-regional input-output analysis– Economic method with data from System of National Accounts– Top-down allocation between sectors– Data driven approach
• Key assumptions– Linear, output is proportional to inputs – Monetary data (not physical)– Aggregation (e.g., 100 sectors)– Each industry produces one product
• Assumptions ok for historical attribution at national level
Linking production to consumption
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Hot colours represent largest transactions between sectors in the (New Zealand) economy
Source: Robbie Andrew
Input-Output Analysis
Consuming Sector
Prod
ucin
g Se
ctor
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Hot colours represent largest transactions between sectors in the (global) economy
Source: Robbie Andrew
Multi-regional Input-Output Analysis
Consuming Region and Sector
Prod
ucin
g Re
gion
and
Sec
tor
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• GTAP-MRIO: 120 countries, 57 sectors, 1997, 2001, 04, 07, 11– CICERO version in timeseries 1990-2014 (CO2 only)
• WIOD: 40 countries, 35 sectors, 1995-2011• Eora: 187 ‘countries’, average 85 sectors, 1970+, automated• EXIOBASE: 43 countries, 163 sectors, 2000, 2008, time-series (?)• OECD: 34+27 countries, 34 sectors, 1995-2011• …• Most have VA, CO2, some GHG, less land, water, materials, …• Problems with ‘off-the-shelf’ data and results
Economic Accounts
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Large structural uncertainties in production emissions, propogates to consumptionDespite difference in absolute values, trends are generally similar.
Structural uncertainties
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• Context (global)– Unharmonised global policy, carbon leakage, competitiveness– Not big changes in the Nordics (net importers, but relatively stable)
• Policies– Consumption-based target, border carbon adjustments• Slight improvement in efficiency, effectiveness, but at the cost of equity• Need financial transfers to offset inequities (could do along trade flows)
– Consumer policies• Labels, standards, nudges, information, reporting, etc• Uncertain impact at individual and macro level• Can help, but probably not sufficient levers to signficantly effect macro level?
Carbon Footprints
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• Context (local)– Water/land ‘scarcity’, more a question of degradation– Impacts very local (water basin, converted land)– Who decides context (local or global citizens)
• Policies– Difficult to generalize (Norway is water rich, but not “productive”)– Generally policy focused on (household, industry) consumers• Product specific (less meat good for land, water, health, climate)• Impact specific (restrictions on products from sensitive areas)
– Technology or yield improvements
Land & Water Footprints
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• Context (local)– Resource efficiency and security– Often not environmentally focussed (unless waste flows)
• Policies– Need to seperate materials (too much context lost in aggregation)– Consumer and industry policies (consume less of X, Y, and Z)– Role of construction activities important
Material Footprints
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• What is the policy objective?– Paris Agreement (clear)– Materials, land, water, etc (resource efficiency, security?)
• What is the role of the environmental footprint?– Most impacts are domestic (in most cases)– What is advantage in a consumption (or trade) policy?– Differentiate policy on domestic versus on imported?
• What is the confidence in the estimates?– The policy needs sufficiently accurate indicators
Three framing issues
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• Footprints useful, but perhaps not sufficient to implement• Quality– Independent data sets are broadly “consistent”, but differences large
• Conflicting data– Data sets are conflicting, and harmonization required
• Aggregation and targeting– Country and broad sector level, ok. Detailed results more uncertain.
• Interpretation– Footprints embody a variety of issues, making interpretation difficult
Uncertainty
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• Carbon, climate– Context and motivation clear– Unclear that consumption policies justify added complexity
• Materials, land, water, …– Unclear context and motivation– Broad conclusions can be made (e.g., reduce consumption)– But specifics matter (which water basin has a scarcity issue)
• Resource efficiency– May be best to modify indicators to suit policy application
Policy
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• Tracking– Value in tracking progress, improved understanding of global systems– Prepares for potential policy applications
• Methodologies– Considerable progress has been made in last 10 years– Knowledge gaps in reconciling data, method choices, updating, …
• Policy context– In past driven by researchers (“hey, look at my results”)– In future, need motivation from policy– What problems need to be solved? Are footprints the answer?
Future perspectives
