Authors: Vincent Carragher, PJ McLoughlin and Paul Kenny, Tipperary Energy Agency A precise understanding on wider benefits arising from renewable and sustainable energy is important for decision makers whether European, national, regional or local. One of these benefits is most certainly job creation. Prior to this review, it has been concluded that the literature carries a mix of methods, conversions and metrics in relation to job creation by such technologies. Poor definition of direct and indirect jobs is also prevalent in the literature (Dalton & Lewis, 2011 & Kammen et al, 2004) and this prevents clear comparison and analysis. The literature looks at both net or gross jobs created and those authors preferring the former discount job losses in the fossil-fuel industry. Such analysis is uncertain as it proves difficult to include the following effects: 1. Impacts of the current economic downturn; 2. The employment rate in fossil fuel-related industries has been declining (Kammen et al, 2004). Mechanisation normally reduces jobs in the fossil fuel industry, as in Figure 1, where since 1958 coal production increases despite reductions in jobs; 3. Fossil fuel extraction rates vary greatly. In Australia, coal is extracted at an average of 13,800 tonnes per person per year while in China, rates are 700 tonnes per employee per year (Greenpeace, 2009); 4. Since the 1900s, fossil-fuel installations were subsidised and supported publically, making jobs created per unit of currency invested problematic to assess; 5. Since 1882, energy research and development budgets for the fossil-fuel industry have been eight times larger than for renewable energy technologies and 35 times larger than for energy efficiency end-use options (Pasicko, 2011); 6. Mergers of national and multinational utility companies within the conventional energy industry have produced significant lay-offs (Kammen et al, 2004). Given the resources available and our wish to produce robust analysis and limit uncertainty, it was decided to assess gross employment figures. METHOD STRANDS This secondary research takes a four-strand approach to calculating the employment effects of these technologies. Strand 1 includes ‘Definitions’, ‘Job Categorisation’ and ‘Harmonisation’. Strand 1: Definitions [caption id="attachment_11442" align="alignright" width="1024"] Figure 1: Coal production and related job numbers in the USA (UNEP, 2008, p92) (click to enlarge)[/caption] A majority of authors include direct and indirect jobs and their average proportions taken from the data of Pollin & Garrett-Peltier (2009) are 53% direct jobs to 47% indirect jobs. A number of terms exist in the literature such as a job year, a person year or a full-time equivalent job (FTE) and these mean full-time employment for one person for one year. A direct job is related to the installation, construction, operation and maintenance of plant and relevant works on site. An indirect job is related to the manufacture of the components of the installation (off site). Induced jobs are not usually factored into the studies reviewed and they are those created or supported by the spending of the workers with direct and indirect jobs. In line with analysis in WDC (2008) and in IRBEA (2012), induced jobs were estimated to be 50% larger than the direct jobs created. Strand 1: Job Categorisation Reports in the literature have categorised jobs according to manufacturing and construction (M&C), operations and maintenance (O&M) and fuel processing. Some authors reviewed ignore operations and maintenance (O&M) and fuel processing. The principal reports identified and used here refer to these three categories. In general and excepting biomass, the majority of jobs created in these industries are in M&C while those in the fossil fuel industry are in fuel processing and O&M. On first analysis, this appears to disadvantage the former, but deployment of such technologies is likely to be staged. Given technology lifetimes of 25 to 40 years, cyclic development of such installations would prevent front loading of job opportunities. Strand 1: Harmonisation Studies reviewed report a variance of units and terminology with inter alia, job years, jobs/MWp (peak MW), nameplate MW, installed MW, MWa (average MW) and MWh generated. This variation makes comparison difficult, so it is essential to report in harmonised employment figures. To equate the electricity and heat production from various technologies, we favour the approach of Wei et al (2010) which calculates lifetime average employment per unit of energy in job years per GWh generated (see Appendix I). Employment factors such as construction and installation (job-years/MWp) are thus averaged over plant lifetime to obtain an average employment number (jobs/MWp), which is added to other employment impacts such as operations and maintenance. Next, to allow for comparison between technologies with different capacity factors, we calculate employment per unit of energy generated (job-years/GWh) or per unit of MWa of power output (job years/MWa) as in Wei et al (2010). Strand 2: Scoping This review was initially scoped to include 15 technologies (Appendix 2) appropriate to NWE countries. This was achieved by selecting a range of technologies for which appropriate data was available. These technologies were then reviewed by our ACE European NWE partners and revised to reflect the comments received. The table below reflects those revised technologies to which coal, nuclear, natural gas and carbon capture alternatives were added in order to provide fossil-fuel benchmarks and comparison.

Technologies

Biomass Solar PV Carbon Capture & Storage
Geothermal Solar Thermal Nuclear
Landfill Gas Wind Coal
Hydroelectricity Energy Efficiency Natural Gas
Blanco and Rodrigues (2009) surveyed the wind industry and found that 59% of the direct jobs created were based in manufacture (N=328). This fraction was discounted from the jobs created here, as per objective 5, and gives a more accurate metric for the domestic jobs created by wind farm installations in Ireland (see * Table 1). Strand 3 and 4: Methodology Review and Data Collation A comprehensive desk-top review of academic and energy industry sources ranging from non-government organisations to universities, across Europe, North America and Canada has been conducted. Unfortunately, few academic peer-reviewed sources were found. In order to provide a comprehensive assessment of the impact of these technologies on jobs it was decided to scope all potential jobs in this review incorporating direct, indirect and induced jobs. This review concluded with compilation of employment data relating to employment for renewable and sustainable energy and conventional energy installations. As mentioned the Wei et al study provided the main thrust of the approach adopted here. In addition, data from other studies was evaluated increasing the reliability of the data (job years/GWh generated). RESULTS AND DATA COLLECTION Where available, production metrics were compiled for most of the technologies, and include the following:
  • Installed capacity (MWp)
  • Average capacity (MWa)
  • Plant lifetime
  • Capacity factor
  • Energy generated (GWh)
  • Employment (person year/job-year/FTE)
A short version of the resultant conversions is presented in Table 1, while a complete version can be found here. The job estimate for offshore wind in Table 1 is 1.16 job years/GWh and is referenced in just one study. Another eight studies presented a mix of offshore and onshore job creation data. Table 1: Ranked job creation estimates (job-years/GWh) for technologies
Energy Technology Direct Indirect Induced jobs Total Average
Solar PV1 0.75 0.67 1.12 2.54 1.62
Solar PV2 0.50 0.45 0.75 1.70
Solar PV3 0.12 0.11 0.18 0.41
Solar PV 4 0.58 0.52 0.87 1.97
Solar PV 5 0.76 0.39 0.35 1.50
Hydroelectric 1 0.14 0.13 0.21 0.48 1.44
Hydroelectric 2 - - - 3.49
Hydroelectric 3 0.17 0.08 0.09 0.34
Landfill Gas 1 0.59 0.53 0.88 2.00 1.29
Landfill Gas 2 0.17 0.15 0.25 0.57
Offshore Wind 0.34 0.31 0.51 1.16 1.16
Offshore Wind * 0.14 0.31 0.51 0.96 *0.96
Biomass 1 0.12 0.10 0.17 0.39 0.61
Biomass 2 0.10 0.09 0.15 0.34
Biomass 3 0.26 0.23 0.39 0.88
Biomass 4 0.48 0.19 0.18 0.85
Wind 1 0.14 0.12 0.21 0.47 0.48
Wind 2 0.05 0.05 0.08 0.18 0.42
Wind 3 0.11 0.09 0.16 0.36
Wind 4 0.08 0.08 0.13 0.29
Wind 5 0.07 0.06 0.10 0.23
Wind 6 0.17 0.16 0.26 0.59
Wind 7 0.29 0.15 0.14 0.58
Wind 8 0.34 0.32 0.51 1.17
Geothermal 1 0.13 0.12 0.20 0.45 0.40
Geothermal 2 0.14 0.13 0.21 0.48
Geothermal 3 0.12 0.10 0.17 0.39
Geothermal 4 0.13 0.06 0.07 0.26
Solar Thermal 1 0.21 0.19 0.32 0.72 0.40
Solar Thermal 2 0.08 0.08 0.13 0.29
Solar Thermal 3 0.07 0.06 0.10 0.23
Solar Termal 4 0.10 0.09 0.16 0.36
Energy Efficiency 1 - - - 0.36 0.38
Energy Efficiency 2 - - - 0.17
Energy Efficiency 3 - - - 0.59
Energy Efficiency 4 - - - 0.48
Energy Efficiency 5 - - - 0.29
Carbon Capture & Storage 0.09 0.09 0.14 0.32 0.32
Nuclear 0.07 0.07 0.11 0.25 0.25
Coal 0.06 0.05 0.09 0.20 0.20
Natural Gas 0.06 0.05 0.09 0.20 0.20
The data from these eight reports is taken and averaged at 0.48 job years/GWh or 0.42*(domestic) job-years/GWh. The latter focuses on those jobs created in Ireland by investment in wind and attempts to exclude the manufacturing jobs created in other countries. The analysis in Table 1 focuses on job years created per GWh of energy produced or conserved and has not taken the relative costs of the technologies into account. CONCLUSIONS  This study has enabled an assessment to be made of the overall impacts of renewables and sustainable energy technologies on employment in Tipperary, in Ireland and in ACE partner countries. It is a synthesis of existing studies and can support scenario analysis and assist policy makers in answering the employment consequences of renewable and sustainable energy investment. Like other studies, Table 1 shows that such investment generates more jobs per unit energy than fossil fuel alternatives. It can be seen for example that investment in Solar PV yields 8 times more jobs per unit energy than investment in gas. This employment increase occurs because renewable energy production and sustainable energy technologies are more labour intensive, and they require less imported technology. Table 1 clearly points the way for countries with high solar exposure, while waste treatment at landfill would appear to be a favourable technology where capacity exists. Offshore wind farms and biomass offer strong job creation prospects dependent only on resources. In general, investing in biomass installations offers 50% more jobs than wind (0.42), solar thermal (0.40) and geothermal (0.40) installations. In preference to replacement of retired fossil fuel plants it would appear that investment in energy efficiency upgrades would have strong economic impacts as such investment creates 90% more jobs per unit of energy saved/produced. This analysis relies on references authored over 11 years and has thus captured impacts of technological innovation over this period. Variation of jobs generated for equivalent technologies differs within studies and presents an inconsistency and the range of job per energy unit difference is large. Earlier studies often estimated lower job generation figures and this appears inconsistent with the tenet that increased innovation and mechanisation reduces employment. RECOMMENDATIONS Investigation on the causes of variation, within the job generation figures of the technologies, would be of great value. Findings from such research would allow the appropriate calculation of the job creation consequences of these technologies in diverse locations as variations maybe due to differences which occur in the application of these technologies at the local level. More research on the types of jobs created by these technologies would be of great value, would add further depth to the data and would help determine training needs and policy development. Preliminary work (Pollin & Garrett-Peltier, 2009) has been completed in the case of Ontario. Standardised approaches such as that developed by Wei et al, Dalton & Lewis and herein should be updated frequently due to the impacts of increased technological impacts. This updating could support the investigation on the causes of variation mentioned above. References are available on request Tipperary Energy Agency, Craft Granary, Church Street, Cahir, Co Tipperary. See www.tea.ie or call 052 7443090. Appendix I A 228MW (35% capacity factor) wind installation creates 500 C&M jobs over 5 years (2,500 job-years) and 40 O&M jobs over 20 years (800 job-years) (Wei et al (2010, p923). Presuming the plant lifetime is 25 years:Appendix I
  • C&M: 2500/(228*25*0.35) = 1.25 jobs per MWa
  • O&M: 800/(228*25*0.35) = 0.40 jobs per MWa
Appendix II
  • 1. Large-scale wind power (+50kW)
  • 2. Small-scale wind power (up to 50kW)
  • 3. Tidal power
  • 4. Wave power
  • 5. Solar PV
  • 6. Solar thermal
  • 7. Hydroelectricity
  • 8. Geothermal heating
  • 9. Biomass
  • 10. Biogas
  • 11. Biofuel
  • 12. Domestic retrofit
  • 13. Deep retrofit (passive house standard perhaps)
  • 14. Electric vehicles