Transcript Key Data Sources - Low Emission Capacity Building Programme

Introduction
• SEI has been asked by UNDP to create draft baseline data sets for 22 of the
countries participating in the LECB programme.
• These data sets have been developed within SEI’s LEAP software and are
available now for review.
• We hope they will serve as a useful foundation for analysis in the LECB
programme.
• The data sets are only intended as a starting point for analysis. They are
based only on readily available and regularly maintained international
sources of data. It is expected that local experts can greatly improve on
them using local data and local expertise.
• In this webinar we will introduce these draft baselines and describe how
to get access to LEAP and the data sets.
Charlie Heaps
[email protected]
Outline
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Introduction
Key data sources
Data structure
Key calculations: historical (1990-2009) and
baseline (2010-2040)
• A brief introduction to LEAP
• Getting access to LEAP and the draft baseline
data sets
• Templates for mitigation analysis
Charles Heaps
[email protected]
Key Data Sources
• Macroeconomic and Demographic Data
– Population for UN Population Prospects (UN, 2010)
– GDP (MER &PPP) & Sectoral Value Added from World
Development Indicators (World Bank, 2012)
• Energy Data
– Energy statistics from IEA World Energy Balances, 2011
• Includes data on consumption, conversion, primary production,
imports & exports, statistical differences and stock changes.
– For some countries, data on fossil fuel reserves from World
Energy Council (WEC)
• Emissions Data
– Energy sector emission factors from IPCC Tier 1 (1996)
– Non-energy sector emissions from EDGAR v4.1 (PBL, 2011)
Charles Heaps
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Data Structures – 1. Energy
• Energy Demand
– Households
– Services
– Agricultural & Fishing Energy
Use
– Industrial Energy Use
(Broken down into 13 subsectors where data
available: iron & steel, chemicals, etc.)
– Transport
(broken down by mode where data available:
road, rail, aviation, shipping, pipelines)
– Non-energy Fuel Use
(e.g. feedstocks for production of chemicals)
• Statistical Differences
• Energy Conversion
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Distribution Losses
Own Use
Heat Production
CHP
Electric Generation
Oil Refining
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(Only in relevant countries – omits some sectors
such as gas works, charcoal making)
• Primary Production
– Indigenous production
– Imports & Exports
(negative)
– Stock changes
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Data Structures: 2. Non-Energy
• Taken directly from nonenergy sector emissions
from PBL’s EDGAR Database
(v4.1)
• Disaggregated by sector and
subsector and by each
individual pollutant (CO2,
CH4, N2O, halocarbons, SF6,
etc.)
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Note error in LEAP data sets: double counting of
emissions from production of minerals (Need to
erase branch “Production of Minerals 2A”)
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Industrial Processes
– Cement and lime production (CO2 from
chemical reaction), Halocarbons and
SF6, etc.
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Solvents and Products
– Paint, degreasing & chemicals.
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Agriculture
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LUCF
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Includes CH4 from solid waste disposal and
wastewater handling and waste
incineration (potential for double counting
with energy sector).
Other Energy
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Forest fires, grassland fires, forest fire post-burn decay
Waste
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Mainly CH4 from enteric fermentation, manure
management, rice cultivation, ag. waste burning,
direct soil emissions, etc.
Fugitive emissions not accounted for in energy sector
calculations
Other Non Energy
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Fossil fuel fires, indirect N2O from
agriculture, etc.
Charles Heaps
[email protected]
Key Calculations
1. Historical Data (“Current Accounts”): 1990-2009
1.
Energy Demand
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Historical energy intensities (EI) calculated by sector using IEA energy data
(E) and activity level data (AL).
EI = E /AL
Activity levels set to population (household sector), value added (services,
industry and agriculture), total GDP (industry and non-energy fuel use)
Historical tends in fuel shares within each sector (subsectors for industry,
modes for transport), calculated directly from IEA energy statistics.
GHG Emissions (P) are the product of energy use (E) and IPCC Tier 1
emission factors (EF) for each pollutant.
P = E x EF
2.
Energy Supply (“Transformation” in LEAP)
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Simple model of how supply sector attempts to meet demand calculated
above.
Major sectors (transmission & distribution, electric generation, heat
production, CHP, oil refining modeled accounted for in terms of the historical
efficiencies and shares of each key technology/feedstock fuel).
Supply-side GHG emissions modeled with IPCC Tier 1 emission factors.
Non-Energy Sector GHGs
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No calculations – taken directly from EDGAR database.
Key Calculations
2. Baseline Projections (2010-2040)
Summary: changes in baseline emissions due to growth in populations and GDP,
structural shifts in economies, and trends in energy intensities and fuel switching.
1.
Energy Demand: Activity Levels
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2.
GDP projected using regional (not national) growth rates from U.S. EIA International Energy
Outlook 2011.
Population projected using UN Population prospects 2010.
Value added shares projected based on historical trends since 1995.
Energy Demand: Intensities and Fuel Shares
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3.
Sectoral energy intensities projected based on historical trends since 1995.
Fuel shares projected based on historical trends since 1995.
GHG emission factors remain constant.
Energy Supply (“Transformation” in LEAP)
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Electric generation mix projected based on historical trends since 1995.
Electric generation efficiency projected based on historical trends since 1995.
Fuel mix and efficiency in all other sectors assumed to remain constant.
GHG emission factors remain constant
Imports and exports assumed constant after 2009.
Non-Energy Sector GHGs
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Assumed to remain constant.
Charles Heaps
[email protected]
References and Links
•
European Commission, Joint Research Centre (JRC)/Netherlands Environmental
Assessment Agency (PBL). 2010. Emission Database for Global Atmospheric
Research (EDGAR), release version 4.1. http://edgar.jrc.ec.europa.eu
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International Energy Agency, 2011. World Energy Balances. OECD/IEA, Paris,
France.
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Intergovernmental Panel on Climate Change. 1996. Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories. Volume 3: Reference Manual.
http://www.ipcc-nggip.iges.or.jp/public/gl/invs1.html
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United States Energy Information Administration. 2011. International Energy
Outlook 2011. Washington, DC. http://www.eia.doe.gov/oiaf/ieo/
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United Nations. 2010. Word Population Prospects 2010 Revision. United Nations.
New York, USA. http://esa.un.org/unpd/wpp/index.htm
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World Energy Council. 2007. Survey of Energy Resources 2007. WEC. London.
http://www.worldenergy.org/documents/ser2007_final_online_version_1.pdf
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World Bank. World Development Indicators 2012. World Bank. , Washington DC,
USA. http://data.worldbank.org/data-catalog
Charles Heaps
[email protected]
Key
Characteristics
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Easy-to-use scenario-based modeling software for energy planning and GHG
mitigation assessment.
Broad scope: demand, transformation, resource extraction, GHG & local air
pollutants emissions, social cost-benefit analysis, non-energy sector sources and
sinks.
Not a model of a particular energy system: a tool for modeling different energy
systems.
Support for multiple methodologies such as transport stock-turnover modeling,
electric sector load forecasting and capacity expansion, econometric and
simulation models.
Low initial data requirements: most aspects optional.
Links to MS-Office (Excel, Word and PowerPoint).
Local (cities, states), national, regional and global applicability.
Medium to long-term time frame, annual time-step, unlimited number of years.
Download from: www.energycommunity.org/download
Charles Heaps
[email protected]
LEAP Structure & Calculation Flows
MacroEconomics
Demographics
Demand
Analysis
Environmental Loadings
(Pollutant Emissions)
Transformation
Analysis
Stock
Changes
Resource
Analysis
Integrated Cost-Benefit Analysis
Statistical
Differences
Non-Energy Sector
Emissions Analysis
Environmental
Externalities
Charles
10 Heaps
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Charles Heaps
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The Tree
• The main data structure used
for organizing data and
models, and reviewing results
• Icons indicate types of data
(e.g., categories,
technologies, fuels,
key assumptions and
pollution effects)
• User can edit data structure.
• Supports standard editing
functions (copying, pasting,
drag & drop of groups of
branches)
Charles Heaps
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Modeling at Two levels
1.
2.
Basic non controversial physical accounting calculations handled
internally within software (stock turnover, energy demand and supply,
electric dispatch and capacity expansion, resource requirements,
costing, pollutant emissions, etc.).
Additional modeling can be added by the user (e.g. user might specify
market penetration as a function of prices, income level and policy
variables).
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Users can specify spreadsheet-like expressions that define data and models,
describing how variables change over time in scenarios:
Expressions can range from simple numeric values to complex
mathematical formulae. Each can make use of
– math functions,
– values of other variables,
– functions for specifying how a variable changes over time, or
– links to external spreadsheets.
Charles
13 Heaps
[email protected]
Getting LEAP and
The Baseline Country Data Sets
• Download LEAP, here: www.energycommunity.org/download
• Install LEAP by running the downloaded file setup.exe
• We recommend that you fully enable LEAP by registering it, here:
www.energycommunity.org/register
• LEAP available at no charge to those participating in LECB Project . Make
sure you request a free license and note you are part of LECB project.
• Download country data sets and reports from:
ftp://forums.seib.org/LECB/LEAPAreas
• Data sets are single “.leap” data files. Double-click a “.leap” data file to
install it into LEAP.
• Explore results for a country by going to the Results view and choosing
among the saved “Favorite” charts. Favorite charts correspond to those in
each country report.
Charles Heaps
[email protected]
LEAP Demonstration
• At this point in the webinar we will switch to a
live demonstration of LEAP
– Showing its basic features
– Exploring some of the country data sets
– Showing some of their results using the “Favorite
Charts” menu option
– Showing how the results in LEAP are derive from a
combination of its built-in calculations and the
way its data and expressions are entered.
Charles Heaps
[email protected]
Templates for Mitigation
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Each country data set includes a suggested
branch structure template (but currently no
data) for carrying out mitigation
assessments.
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We hope this will serve as a useful default
for organizing analyses, but feel free to adapt
or change in your own mitigation
assessments.
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The template is implemented as a set of
branches in LEAP's Tree Structure. Look for
groups of branches labeled "Polices and
Measures" at the same level as the Baseline
branches within each sector.
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Under each set of P&M branches you will
find sets of branches dealing with types of
policies and measures relevant to each
sector.
Under each category, enter the
energy to be saved from each
P&M. Typically you will enter
energy savings as negative values
representing the energy avoided
by the measure.
Charles Heaps
[email protected]