Greenpeace engaged the Australian-based Institute for Sustainable Futures, which operates within the University of Technology of Sydney, to model the employment effects this sustainable energy scenario would have compared to business as usual.
The model calculates indicative numbers of jobs that would either be created or lost under the Greenpeace Energy [R]evolution, more specifically jobs in power generation and electrical efficiency excluding heating, cooling and transport. The [R]evolution scenario was developed to show how, technically and financially, the world could re-invent its energy mix to dramatically cut carbon emissions. The scenario developed means a nine-fold increase in renewable energy, replacing nuclear and a proportion of coal-fired power, plus widespread energy efficiency improvements. The Reference (‘business as usual’) scenario is the International Energy Agency 2007 projection.
This section provides a simplified overview of how the calculations were performed and the employment factors were determined. A full and detailed methodology used for each of these steps is available in the ISF report, “Energy sector jobs to 2030: a global analysis”6. The 2008 Energy [R]evolution provides all the data on how the scenarios were developed. Both documents are available at www.greenpeace.org.
the model The calculations were made using cautious, informed estimates. The main steps were:
The model used a range of inputs, including data from the International Energy Agency, USA Energy Information Association (EIA), European Renewable Energy Council (EREC), European Wind Energy Association (EWEA), USA National Renewable Energy Laboratory(NREL), Renewable Energy Policy Project (REP), census data from the USA, Australia, and Canada, Centre of Full Employment and Equity (CoFEE), and the International Labour Organisation (ILO)7.
direct and indirect jobs These calculations only take into account direct employment, for example, the construction team needed to build a new wind farm. They do not cover indirect employment, for example,the extra services in a town to accommodate construction teams.The effect on the results is to provide a lower estimate in some cases.
determining the ‘employment factors’ An employment factor is a number used to calculate how many jobs are required per unit of electrical capacity. It takes into account jobs in manufacturing,construction, operation and maintenance and fuel. The table below lists the employment factors used in the calculations. These factors are calculated for OECD countries. For other regions, a regional adjustment was used.
key points: Employment factors for coal were worked out in the most detail, because of its dominance in the current electricity supply.The calculations to arrive at the employment factors included figures from real national employment data where available, established models, projected volumes of international coal trade and regional production estimates (from IEA). The employment and production data was collected for as many major coal producing countries as possible, the full list is provided in the Appendix8.
When considering employment from coal, it is important to note that coal is mined using extremely different methods around the world. The employment per unit of electricity also varies according to the type of coal and the efficiency of generation. For example, in Australia, coal is extracted at an average of 13,800 tons per person per year using highly mechanised processes while in Europe, the average coal miner is responsible for only 1,843 tonnes per year. China is a special case:even though it currently has a very low average rate of extraction per person (700 tons per employee per year) this will change very soon,as thousands of small mines close and new super-mines open. For this reason, the model uses US employment factors for the future coal production in China that is above current levels.
The factors for gas generation are taken from a publicly available model called JEDI, developed by the National Renewable Energy Laboratory in Washington to help work out local benefits of different types of energy supply.
For nuclear energy, construction, manufacturing and installation factor is derived from a Nuclear Energy Institute (NEI) 2009factsheet, while the operations and maintenance is calculated using Energy Information Administration (EIA) census data. Fuel employment is calculated from Australian census data.
For the renewable energies, the employment factors were taken from industry data where available, as listed in Table 2.5, or derived,depending on the maturity of the technology9.
regional job multipliers
The employment factors used in this model for all processes apart from coal mining reflect the situation in the (typically wealthier) OECD regions. The regional multiplier is applied to make the jobs per MW more realistic for other parts of the world. In developing countries it typically means more jobs per unit of electricity because of more labour intensive practices. The multipliers change over the study period in line with the projections for Gross Domestic Product per worker. This reflects the fact that as prosperity increases, labour intensity tends to fall.
learning adjustments or ‘decline factors’
This accounts for the projected reduction in the cost of renewables over time, as technologies and companies become more efficient, and production processes are scaled up. Generally, jobs per MW would fall in parallel with this trend.
local manufacturing and fuel production
Some regions do not manufacture the equipment needed for wind power or PV, for example.The model takes into account the percentage of renewable technology which is made locally. The jobs in manufacturing components for export are counted in the region where they originate. The same applies to coal and gas, because they are traded internationally, so the model shows the region where the jobs are actually located.
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