The Impact of Low Carbon Policy on Migration

7/28/2019 The Impact of Low Carbon Policy on Migration

1/42

1

This review has been commissioned as part of the UK Governments Foresight

Project, Migration and Global Environmental Change. The views expressed do

not represent the policy of any Government or organisation.

DR15: The impact of low-carbon policy on migration

Michael Reilly and Yasmin Hossain

Government Office for Science, London, UK

October 2011

Migration and Global Environmental

Change


2/42

DR15 2

Contents

Abstract ...........................................................................................................................3Introduct ion ....................................................................................................................5

5

6

8

8

10

11

12

13

19

20

21

25

27

33

34

35

The sc ience of climate change ..................................................................................... Relevant theories of mobili ty and displacement ......................................................... Current and pro jected greenhouse gas emiss ions..................................................... Current emissions........................................................................................................... Future emissions ..........................................................................................................

Opportunities to abate future greenhouse gas emissions....................................... Energy efficiency.......................................................................................................... Low-carbon energy supply............................................................................................ Forestry and agriculture................................................................................................ Low-carbon cities..........................................................................................................

The macroeconomic impacts of mit igation ............................................................... Low-carbon jobs .......................................................................................................... Low-carbon policy and migration............................................................................... Renewable energy and rural development ................................................................ Conclusion: plausible scenarios for the impact of low-carbon po licy on migration

....................................................................................................................................... References ....................................................................................................................


3/42

DR15 3

Abstract

The paucity of evidence on the impact of current mitigation policy on migrationand the uncertainty surrounding future policy is highly problematic for projecting

outcomes, both temporally and geographically. Nevertheless, low carbonpolicies could have effects on population mobility and displacement by changingthe net expected income differentials between areas of origin and destination,disrupting the livelihoods of households reliant on natural resources, modifyingdirect transport costs and altering returns to human capital.

The global economic costs of greenhouse gas abatement are highly uncertain,but they will not be uniform across either countries or sectors. For all but themost pessimistic cost estimates, aggregate mitigation costs should be absorbedby future global economic growth, but there still exists some potential forregulatory arbitrage within sectors. Emissions-intensive firms open tointernational trade could cross borders in the absence of regional agreements.Renewable energy production is more labour intensive than fossil fuel productionin manufacturing and operational terms, although this is likely to lessen in thelong term as efficiency gains bring down costs. Direct employment in the energysector is relatively small compared with other sectors, and it is male dominated.Most new recruitment would be sourced from the existing workforce. If the USAis typical of developed countries, then relatively few low-carbon jobs may be lowskilled. The largest source of low-carbon jobs for the low skilled in thedeveloping world is likely to be in labour-intensive biofuel harvesting. Ineffectiveinternational governance of climate change would exacerbate the unequal

distribution of costs across countries and sectors, and as these costsaccumulate with inaction and climate damages rise, belated policy could result involatile changes in net expected income differentials between countries,livelihood losses from socioecological systems and direct transport costs.

Ambitious targets for large-scale hydropower and biomass production couldresult in internal displacement. New biomass markets also offer directopportunities for smallholders and households to diversify income; however, theycould present indirect threats if production has a disruptive effect on livelihoodsby diminishing the quantity and quality of local ecosystem services or if higherfood prices increase food insecurity. The growth expected in biomass production

would be expected to have an impact on households who are dependent onforests for their livelihoods, especially if a lack of rights renders them vulnerableto access restrictions. The Clean Development Mechanism (CDM), ReducingEmissions from Deforestation and Degradation (REDD+) and the green climatefund should improve the criteria for sustainable development objectives ofapproved projects so that vulnerable people are protected from both physicaland livelihood displacement.

Energy efficiency gains, the multilateral removal of fossil fuel-energy subsidiesand investment in clean energy technologies have the potential to changeexpected net income differentials in migration corridors. The precise impact of

direct transport costs on mobility will vary among migrants, but given thataverage costs to 2030 are expected to be high, it would probably have a


4/42

DR15 4

dampening effect on movement. Low-carbon urbanisation in developingcountries is a significant cross-sectoral opportunity, but achieving low-emissionbuilding, public transport and waste management is capital intensive. While high-density, compact cities may have lower costs of living and a higher quality of lifefor residents, low-income ruralurban migrants may be excluded from these

benefits.

Low-carbon policies have the opportunity to improve the access of rural areas inthe developing world to energy, which could have a highly significant impact onmobility. Stand-alone renewable technologies and micro-grids can becompetitive in rural areas and their effective deployment (including through theCDM) is likely to boost rural incomes and be a pull factor at areas of origin.Beyond the short term, with increased income the economic costs of mobilitymay be less prohibitive, and these movements would be part of a pathway todevelopment and not environmentally induced mobility with operational orgeopolitical difficulties.

The precise impacts of existing mitigation policy on migration are often difficult todistinguish, and more empirical research is urgently required in this area.Nevertheless, the impact on mobility in the short to medium term is likely to bemodest with some new direct employment opportunities for a range of skills andthe potential for low-income smallholders and households to diversify income. Inthe longer term, if the transition to a low-carbon society induces a new wave ofinnovation, the impact on labour markets could be transformative The sheer sizeof the developing-world population dependent on agriculture and forestry raisesconcerns that poorly designed and implemented policies to increase low-carbonenergy supply and improve carbon sequestration could, paradoxically, harm thelivelihoods that mitigation policy is intended to protect. If low-carbon policies arecrafted systemically at appropriate levels of governance and in accordance withother strategic objectives such as sustainable development, energy access,poverty reduction, adaptation to climate change, and maintaining ecosystemservices and biodiversity, the outcomes of greenhouse gas abatement are morelikely to be beneficial in the short, medium and long term.


5/42

DR15 5

Introduction

The transition to low-carbon societies will require socioeconomic changes thatare unlikely to be successful without support from a portfolio of national and

international policies. Although the implications for migration from climatechange have been explored in recent research, there is much less analysis onhow mitigation may influence human mobility and displacement. This paperreviews the main low-carbon technologies and policies that have been proposedto mitigate greenhouse gas emissions and considers their implications forhuman migration particularly, although not exclusively, in the context ofenvironmental change. In the section The science of climate change, a briefoverview of climate-change science is provided to illustrate the scale of thechallenge. Theory and evidence on rural to urban migration, displacement andenvironmentally induced migration is highlighted in the Relevant theories ofmobility and displacement section to identify key variables of interest. In theCurrent and projected greenhouse gas emissions section, current greenhousegas emissions for sectors and regions are summarised and future projectionsdiscussed. The technical and economic potential of opportunities to abategreenhouse gas emissions are examined in the Opportunities to abate futuregreenhouse gas emissions section with particular reference to their geography.

The macroeconomic implications of mitigation are explored in the sixth section,The macroeconomic impacts of mitigation, and the prospects for employment inthe seventh, Low-carbon jobs. Finally, the possible impacts of mitigation policyon migration are drawn out in the section Low-carbon policy and migration, andthis analysis is augmented in the final section, Renewable energy and rural

development, with some reflections on the role of renewable energy in ruraldevelopment. The considerable uncertainty surrounding future low-carbon policyin the medium to long term limits the bulk of this analysis to a horizon of 2030.

The science of climate change

There is strong evidence that global warming over the last half century has beencaused largely by human activity (Royal Society, 2010). In order to balance theenergy that the Earth absorbs directly from the sun, its surface and atmosphereemit infrared energy into space. In addition to the energy that the Earth absorbs

directly from the sun, it also receives infrared energy that is at first emitted fromits surface but then reflected back from its atmosphere. The warming caused bythis additional infrared energy is called the greenhouse effect. An increase in theglobal atmospheric concentrations of gases such as carbon dioxide (CO2),methane (CH4) and nitrous oxide (NO2) intensifies the greenhouse effect andcauses a positive radiative or climate forcing. It is extremely likely that themarked increase in the global atmospheric concentration of greenhouse gasessince the industrial revolution has been as a result of human activities such asthe burning of fossil fuels for energy, agriculture and deforestation (Solomon etal., 2007). Such activities have been strongly associated with historical pathwaysof human development.


6/42

DR15 6

The Intergovernmental Panel on Climate Change (IPCC) has estimated that ifgreenhouse gas emissions continue unabated, the globally averaged surfacetemperature would be 2.54.7C higher by 2100 compared with pre-industriallevels (Solomon et al., 2007). The potential for adverse, geographically unevenimpacts from this change in climate have been well documented and consensus

has emerged among a coalition of nation states that policies should bedeveloped to limit this increase to 2C (Stern, 2006; Parry et al., 2007; UNFCCC,2010). Although there are uncertainties surrounding the sensitivity of the climateto increases in greenhouse gas concentrations, the stabilisation target toachieve this goal with a 50% probability is around 450 parts per million (ppm) ofCO2 equivalent (CO2e). The scale of the challenge, then, is stark given that thecurrent concentration is already above 400 ppm and CO2 emissions weregrowing at an accelerating rate at the beginning of the century (Raupach et al.,2007; EEA, 2010).

Relevant theories of mobility anddisplacement

There are many theories of migration, but in view of the scope of this paper, thissection will focus on rural to urban migration, displacement by developmentprojects and the relationship between migration and environmental change

Harris and Todaro (1970) developed a model to describe rural to urban internalmigration in developing countries that introduced the concept of 'push' and 'pull'

forces and has been corroborated by some empirical evidence. They found thatthe migration decision was based principally on an individual's maximisation ofexpected financial benefits, and this suggested a framework for behaviour whereexpected economic benefits (including remittances) are compared with costs.According to this model, rural to urban migration proceeded mostly in responseto differences in expected rural and urban real incomes. It also explained theparadox of why increasing rates of rural to urban migration are possible evenwith ever-higher levels of urban unemployment.

The New Economics of Labour Migration Theory went further and suggestedthat the migration decision is made at the household level (Stark and Bloom,

1985). The rural household provides costs in exchange for insurance againstadverse environmental conditions. In this way, an informal agreement existsbetween the individual and the household reinforced by kin altruism andinheritance motives. This theory is particularly relevant to rural areas in least-developed countries where risk is more widely distributed. Remittances, forexample, may improve productivity in the area of origin through increasedliquidity despite loss of labour.

The Human Capital Theory posits that migration is highly selective and thatmigrants will tend to be those individuals for whom the expected financialbenefits are highest and migration costs are lowest (Taylor and Martin, 2001).

The pull of agglomeration in prosperous places where people with skills cluster


7/42

DR15 7

and human capital earns higher returns where it is plentiful is also strong (WorldBank, 2009).

Historical, social and cultural connections between areas of origin and areas ofdestination also have an influence on mobility. For example, more than half of all

international migrations occur between countries that share a common language(World Bank, 2009). In an analysis of movements between Mexico and the USA,Massey et al. (1994) found that an accumulation of social capital eventuallymakes mobility more attractive and accessible to communities by lowering thecosts of migration.

Human displacement is associated with many large-scale development projects.In its narrowest sense, displacement refers simply to physical displacement orthe geographic relocation of people from their homes to another locale. Newmodels for displacement and resettlement give further consideration to theeconomic dislocation and social exclusion that communities experience when

they are deprived of the land and resources that are integral to their means ofproduction (Cernea, 2000).

In 1990, the IPCC suggested that the greatest single impact of climate changecould be on human migration, but evidence suggests that environmental changeis rarely the sole cause of migration (Perch-Nielsen et al., 2008; Tacoli, 2009).Categorisations of environmentally induced migration reflect the complexity ofthe relationship, and Bates (2002) has described a continuum stretching frommobility to displacement. In some research there is evidence of an effect,although correlating migration with environmental change requires care, and

findings at first glance can seem contradictory. Mass migration in the Horn ofAfrica had been attributed to environmental degradation, but it was disruption tolong-standing traditional resource management systems for coping with spatialand temporal variability by conflict and scorched-earth government policies thatforced displacement from increasingly insecure areas (Kibreab, 1997). Migrationis already an established coping response to seasonal variation in rainfall, butdrought conditions can intensify existing migration patterns and if methods tomanage risk fail, outcomes can be less predictable. A study of the droughtconditions experienced by mostly sedentary farmers in northern Nigeria from1972 to 1974 found that such migrations tended to cover greater distances,lasted for longer periods and that there was an increase in the prevalence of

urban migrations (Morrissey, 2009). On the other hand, evidence from the 19835 drought in Mali found that migration was over shorter distances, shorter termand predominantly cyclical in nature (Findlay, 1994). Household capitalendowments both human and financial were found to be important indetermining the migratory response. For the dust-bowl migration in the USA fromOklahoma to California, distances were longer and migration was morepermanent because established coping responses failed (McLeman and Smit,2006). Again, household capital endowments were important in determining themigratory response: poor land tenure, social networks extending to Californiaand an ability to finance the costs and to work with cotton crops made migrationmore likely. Costly migration may be a less likely response to environmental

change because of the impoverishing effect it can have on poorer households. InBurkina Faso, it was found that although land degradation was more strongly


8/42

DR15 8

correlated with migration than episodic unfavourable climatic conditions, peopleliving in highly degraded areas migrated less than people living in less degradedareas (Henry et al., 2004).Thus, an inability to invest in migration may havelimited migration.

The paucity of evidence on the impact of current mitigation policy on migrationand the uncertainty surrounding future policy are highly problematic to projectingoutcomes both temporally and geographically. Any effects, moreover, will not actin isolation but will be part of a wider and more complex mix of determinants.Nevertheless, existing theory and the limited evidence on environmentallyinduced migration do point to key variables of interest. This review will thereforeconcentrate on ways in which mitigation policy could affect net expected incomedifferentials between areas of origin and destination, the returns to humancapital, direct transport costs and the livelihoods of households reliant on naturalresources.

Current and projected greenhouse

gas emissions

Current emissions

Global greenhouse gas emissions were approximately 49 GtCO2e in 20071, with

fossil fuel energy supply accounting for around two-thirds of emissions (seeFigure 1). The power generation sector is the major source of CO2 emissions

and provides electricity and heat for buildings and industry. Road transportationand industry-based manufacturing processes are also significant sources of CO2emissions, with the remainder generated by land-use change, mostly fromdeforestation. The other main greenhouse gases (CH4 and NO2) are by-productsof agricultural processes such as livestock production and fertiliser application.

1 Figure calculated using World Resources Institute CAIT tool. Greenhouse gas emissions fromland-use change are difficult to estimate and are not included in many country totals.


9/42

DR15 9

Figure 1: Global greenhouse gas emissions by sector (%).

Source: Baumert et al. (2004).

The geographical distribution of emissions varies by amount and sector. Mostgreenhouse gas emissions come from just a few countries China, the USA, theEuropean Union (EU), Brazil, Indonesia, the Former Soviet Union and India aremost prominent. The developed world currently emits slightly more than thedeveloping world but the sources of the emissions vary and reflect structuraldifferences in their economies (Figure 2). In high-income countries, the powerand transport sectors are the most significant emitters, whereas in middle-income countries the contribution from transportation is much smaller and that ofland-use change and agriculture is much higher. Low-income countries areresponsible for a very small proportion of global emissions, which are

predominantly from land-use change, forestry and agriculture.


10/42

DR15 10

Figure 2: Global greenhouse gas emissions by sector and income groups(%).

Source: World Bank (2010).Note: The size of each pie represents relative greenhouse gas contributions

from high-, middle- and low-income countries.

Future emissions

The drivers of CO2 emissions growth can be partly understood by expressingemissions in the form of the so-called Kaya identity (Kaya, 1990):

GDP

Energy

Energy

COPopulation

Population

GDPCO ***

2

2 =

The main determinants of CO2 emissions growth are income and populationgrowth, energy mix and energy intensity. The energy mix and energy intensity ofa national economy will vary depending on a number of factors including itseconomic structure, technology, climate, the spatial distribution of its populationand its endowment of natural resources. The increasing growth rate in CO2emissions observed in the previous decade has been attributed to increasingincomes and populations, and a slowing of progress in altering the energy mixand improving the energy intensity of economies (Raupach et al., 2007).

In the absence of mitigation policies, global greenhouse gas emissions areprojected to increase 4070% in 2030 (van Vuuren et al., 2009). Energy-related

emissions rise to 7080% of total emissions while the proportion of emissionsfrom land-use change declines as limits are reached in deforestation (Figure 3).

The strongest relative growth in emissions comes from industry and buildings,including indirect emissions from energy supply, followed by transportation andagriculture. Cities consume most of the worlds energy and urbanisation indeveloping countries is expected to drive future national emissions growth(World Bank, 2009). However, as loci of income, knowledge capital andinnovation, cities can be particularly energy- and emission-efficient spaces forhuman agglomeration (Glaeser and Kahn, 2010).


11/42

DR15 11

Figure 3: Baseline emissions to 2030 from an ensemble of models(GtCO2e).

Source: van Vuuren et al. (2009).

The share of emissions from developing countries is projected to rise, with Chinaovertaking the USA as the largest emitter in absolute terms if not on a per-capitabasis. Strong growth in emissions is also projected from India, Mexico, Africaand Brazil, but national projections are marked by uncertainty (Baumert et al.,2004).

Opportunities to abate future

greenhouse gas emissions

The main opportunities to abate greenhouse gas emissions and thereby stabiliseconcentration focus on altering the energy mix and carbon intensity ofeconomies, and improving the management of forestry and agriculture systems.Pacala and Socolow (2004) conceptualise abatement through stabilisation

wedges using existing technologies that modify the business-as-usual trajectoryof yearly emissions. The economic potential of most opportunities is dependenton the future price of carbon, but there is consensus on the main categories ofabatement opportunities (Stern, 2006; Barker et al., 2007; Nauclar and Enkvist,2009). For example, recent analysis from Nauclar and Enkvist (2009) suggeststhat based on a carbon price of 60/tCO2e, technical measures to improveenergy efficiency, the switch to a low-carbon energy supply and bettermanagement of natural carbon sinks could abate 38 GtCO2e per year by 2030(see Figure 4). Further technical measures and behavioural change couldreduce emissions by as much as 70% in 2030.


12/42

DR15 12

Figure 4: Major categories of abatement opportun ities depending for acarbon price of less than 60/tCO2e and 60100/tCO2e (GtCO2e per year).

Source: Nauclar and Enkvist (2009).

Energy efficiency

Improving energy efficiency means lowering the proportion of energy that is usedto produce a given output. Many potential opportunities have been identified forcapital stock used in energy supply, building, industry and transportation, butfully realising gains will require the removal of fossil fuel subsidies, regulationand investment in skills and technology. Improving energy efficiency is likely torepresent the most cost-effective policy option to mitigate CO2 emissions.Moreover, some opportunities are no regrets options, which are economicallyviable without the pricing of carbon. Developed countries have significantlyimproved their energy efficiency since the oil crisis in the early 1970s and theopportunity in developing countries not yet locked in to carbon-intensive capital

stock is likely to be greater (World Bank, 2009). China has been remarkablysuccessful since the 1980s in lowering the energy intensity of its growingeconomy through energy efficiency policies (Sinton et al., 1998).

There will be wider macroeconomic impacts of energy efficiency if savings areredirected into investment. Economic models suggest that consumers andbusinesses redirect their savings from energy costs into more productive andlabour-intensive parts of the economy, resulting in additional economic growthand employment (Geller and Attali, 2005). On the other hand, there is the riskthat an increase in energy efficiency could have a much lesser impact onameliorating energy intensity because of a rebound effect in consumption by

households and businesses. The risk is considered very low to moderate, and is


13/42

DR15 13

likely to vary between sectors, technologies and income groups (Greening et al.,2000; Sorrell, 2007).

Low-carbon energy supply

Stabilising greenhouse gas concentrations at a level to limit global warming to2C will not be possible without a radical change in the energy mix of the globaleconomy. Moving to a low-carbon energy supply will require fuel switching fromcoal to natural gas, renewable energy technologies for electricity production,carbon capture and storage (CCS), and a reduction in the proportion of fossilfuel used for transportation.

There is no single solution for a low-carbon supply of energy, althoughconcentrated solar power has enormous global potential (see Table 1). Ofcurrent renewable energy technologies, only hydropower, nuclear and biomassare both technically and economically viable compared with coal-basedelectricity generation, but higher carbon prices and technological innovation willincrease the options for regional and domestic energy systems. Technologieshave been deployed in developing countries since the 1970s at a variety ofscales and there are many examples of projects that have successfully attaineddevelopment objectives (Martinot et al., 2002). A scenario to achievestabilisation of greenhouse gas concentrations at 450 ppm projects dramaticincreases in renewable energy demand in many regions (see Figure 5), whichwill transform the geography of the energy system and its labour market.


14/42

Table 1: Estimated cost ($/kilowatt-hour) and potential (annually averaged terawatts) of ren

Source Estimated cost Estimated potential

Hydropower $0.030.10 per kilowatt-hour ~1.8 terawatts (currently 0.8)

Nuclear fission $0.0250.07 per kilowatt-hour ~11.2 terawatts by 2050 (currently0.37)

Biomass $0.020.09 per kilowatt-hour ~35 terawatts by 2050 using allavailable non-agricultural land (currentl0.04)

Wind $0.050.09 per kilowatt-hour ~1 terawatt (currently 0.094)


15/42


Geothermal $0.05 per kilowatt-hour


16/42


~0.5 terawatts forwave systems

Unevenly distributedgeographically; immaturetechnology; marginal potential onglobal scale

Source: Schiermeier et al. (2008); Additional author comments. Note: Cost for coal-based electricity generation is ~$0.030.05 perelectricity generation supplied in 2005, ~2 terawatts.


17/42

DR15 17

Figure 5: Demand for renewable energy by country/region under a 450 ppm scenario.

Source: IEA (2010).

In the developing world, traditional biomass (fuel wood, animal dung, crop residues) forcooking, heating and lighting provides a large proportion of the energy mix, but its use isinefficient. Modern biomass technology based on agriculture, forest residues and energy cropshas the potential to reduce the widely acknowledged economic, social, environmental andhealth costs of traditional biomass. Much of the projected growth in biomass production willmeet non-commercial demand for growing populations in developing countries, but as second-generation biofuel technology becomes technically viable, the production of transport biofuels

is likely to increase markedly. International trade in modern biomass feedstocks overall isgrowing and is perceived by some experts to be in its initial stages of development (Heinimand J unginger, 2009). There are regional imbalances between potential supply and expecteddemand, and developed countries such as the USA, EU and J apan may import in the futurefrom large-scale biomass energy plantations in Latin America, sub-Saharan Africa and easternEurope (Faaij and Domac, 2006).

The wind-energy sector has also been growing rapidly, but it faces economic and geographicconstraints. The most technically viable areas for onshore wind energy are in coastal areas(see Table 2). Archer and Jacobson (2005) found areas with particularly strong wind-powerpotential in northern Europe along the North Sea, the southern tip of the South America,

Tasmania, the Great Lakes region and the north-eastern and western coasts of Canada andthe USA. Household-scale wind power has been successfully deployed in the developing worldto generate electricity particularly in China. Offshore wind energy is less economic thanonshore, but wind speed can be much greater.


18/42

DR15 18

Table 2: Summary of the most attractive technical locations for onshore wind energy.

Region Location

EuropeNorth and west coasts of Scandinavia and the UK, some Mediterraneanregions

Asia East coast, some inland areas, Pacific Islands

Africa North, south-west coast

Australasia Most coastal regions

North America Most coastal regions, some central zones, especially where mountainous

SouthAmerica

Best towards the south, coastal zones in east and north

Source: World Energy Council (2010).

Solar technology generates energy using photovoltaics and concentrated solar power (CSP).Although solar technology appears expensive compared with coal-based electricity generation,in many rural areas it is competitive. In Kenya, for example, there is a large market for solarhome systems among rural households (J acobson, 2007). CSP is a proven if currentlyuneconomic technology with installations in the USA and Spain. Its main technically limitingfactor is direct normal irradiance (DNI), and as a consequence the most favourablegeographical areas are north Africa, southern Africa, the Middle East, north-western India,south-western USA, Mexico, Peru, Chile, the western part of China and Australia (IEA, 2010).Other factors hampering the huge potential of CSP include storage, cooling and the logisticalchallenge of transmission from locations that are remote from centres of energy demand. It is

economically feasible for the electricity generated to be supplied over long distances usinghigh-voltage direct current technology with relatively modest levels of subsidy, and ambitiousprojects such as Desertec and the Mediterranean Solar Plan aim to supply electricity from theMiddle East and north Africa to Europe (Ummel and Wheeler, 2008).

Hydropower has a major technical advantage over other renewable energies because, incontrast to intermittent sources, it is able to supply base load and peaking requirements. Themost installed capacity for hydropower is in Asia, Europe, North America and Latin America.

The extent of future technical and economical potential is debated, but most growth is expectedin Asia, Latin America and Africa (Bartle, 2002).

Fossil fuels will continue to be part of the energy mix of the global economy, and carboncapture and storage (CCS) technology will be required to stabilise greenhouse gas emissionsat 450 ppm. CCS systems are technically feasible, but industrial-scale demonstration projectsare necessary to improve the experience of combining capture, transport and storage. The


19/42

DR15 19

technology could become economical at carbon prices of around 3050/tCO2 (Campbell,2008). Evidence suggests that the technical potential for geological storage in deep onshoreand offshore geological formations is at least 2,000 GtCO2, but there may be gaps in regionalcapacity (Rubin et al., 2005). Research that compares the present and future location of pointsources of CO2 with suitable storage locations is limited, but transportation using pipelines or

shipping is feasible. There are, however, risks associated with the leakage of CO2 frompipelines and geological storage, and abrupt leakage could harm humans and ecosystems.

Forestry and agriculture

Significant opportunities for low-cost abatement arise in both forestry and agriculture, but thefragmentation and the diversity of the social systems in these sectors means that fully realisingthese opportunities will be highly challenging. Furthermore, the costs calculated rarely if at allincorporate any livelihood losses that may be experienced by households dependent on theecosystem services in these sectors. Realising these opportunities in order to avert futureclimate damages would be self-defeating if actions severely disrupt livelihoods.

Forest ecosystems make a major contribution to the carbon cycle both as a sink foranthropogenic CO2 emissions and as a store for large reservoirs of CO2; they hold arounddouble the amount of CO2 that is in the atmosphere. Forests cover 30% of the total land areaat 4 billion hectares but are very unevenly distributed around the world (FAO, 2005). The 10countries with the largest forested areas are Russia, Brazil, Canada, the USA, China, Australia,the Democratic Republic of Congo, Indonesia, Peru and India. Deforestation, mostly throughland-use change for agriculture, occurs at a rate of around 13 million hectares per year,although there is also forest expansion to temper losses. In recent times, South America andAfrica have had the largest net losses, with Brazil and Indonesia alone accounting for two-

thirds of emissions in 2005. Expansion has recently been reported in Europe and Asia, mostlyin China.

Forestry can abate future CO2 emissions directly by increasing forested land area throughafforestation and reforestation, increasing the carbon density of existing forests and, mostimportantly, reducing emissions from deforestation and degradation. Indirectly, forestryactivities can also increase the sustainable use of biomass to replace fossil fuel CO2emissions.Most of the abatement opportunity for direct mitigation in forestry can be achieved at loweconomic costs, although there is some regional variability (Barker et al., 2007; Nauclar and

Enkvist, 2009). Forests are multi-functional and provide a rich variety of ecosystem servicesincluding flood protection, maintenance of soil fertility, carbon sequestration, hosting ofterrestrial biodiversity and water-catchment protection. They support livelihoods by providingincome (around 10 million people are formally employed in forest management andconservation and numbers for informal employment are believed to be much higher) and bysupplying biomass such as fuel wood, traditional medicines and food (FAO, 2005). The WorldBank (2008) estimates that forests contribute to the livelihoods of as many as 1.6 billionpeople; around 1.2 billion people are dependent on agro-forestry.

Agricultural land, for growing food and feed crops for livestock and for pasture, occupiesaround 38% of the total global land area (FAOSTAT, 2010). The relative area devoted to these

three uses differs markedly across regions of the world, reflecting the availability of localnatural resources, land availability, soil characteristics, climatic differences, and technology andmanagement practices. The global share of employment in the agriculture sector is around35%; nationally this share is very high at low levels of economic development but declines as


20/42

DR15 20

countries develop. The International Labour Organization estimates that 1 billion people areemployed in the sector but a much larger number are dependent on agriculture for livelihoods(World Bank, 2008; International Labour Organization, 2011). Most of the greenhouse gasemitted directly by agricultural production is CH4 and NO2, but the main abatementopportunities are actually based on carbon sink enhancement restoration of degraded land

and improved management of the land used for crops and pasture (Barker et al., 2007;Garnett, 2011). In economic terms, these measures are relatively low cost and require nosignificant capital investments (Nauclar and Enkvist, 2009). However, carbon sequestrationeventually gives rise to diminishing returns as soils reach their maximum potential, and isimpermanent if land-management practices revert back. Additional opportunities include betterrice and livestock management, reducing post-harvest waste, sustainable intensification andreducing the consumption of livestock products.

Low-carbon cities

There are other cross-sectoral abatement opportunities including waste management andbehavioural change, but the most significant opportunity is arguably low-carbon urbanisation,particularly in developing countries. Low-carbon urbanisation could realise abatementopportunities in transport and buildings especially, but also in low-carbon energy supply, wastemanagement, behavioural change and carbon sequestration. Estimates indicate that thepopulation living in urban areas will rise from 3.5 billion in 2010 to 4.9 billion in 2030, and thevast proportion of growth will be in the developing world (UN-HABITAT, 2011). Urbanpopulation growth in developing countries is driven in part by migrants responding to the netexpected income differentials between rural and urban areas (Todaro, 1980). Lower costs andlarger markets are creating new employment and investment opportunities in the developingworld (J ust and Thater, 2008; Wilson and Dragusanu, 2008).

Urban areas are heterogeneous and there is a large variation in both total and per-capitaemissions. The determinants are similar to those of CO2 emissions more generally and includeeconomic structure, urban form, stage of economic development, energy mix and state ofpublic transport (Dhakal, 2010). Many studies have found that in the developed world, highpopulation density is negatively correlated with CO2 emissions (Ingram, 1997; Scholz, 2006;Vance and Hedle, 2006; Wilson and Dragusana, 2008). Larger, denser cities create economiesof scale that facilitate efficiencies in energy use, recycling and public transport, therebyreducing per-capita emissions (Satterthwaite, 2008; Dodman, 2009; OECD, 2009). Thevariation in density and design between newer cities in the USA defined by the interstatehighway system, and older, more compact cities in Europe which rely more heavily on public

transportation, is a vital lesson to developing countries which still have the chance to influencethe shape of their cities (World Bank, 2010). Moving closer to the compact city model mayallow high-growth developing world cities to continue along their development path whileintegrating social and ecological systems more sustainably.

Including direct and indirect emissions, the buildings sector has the greatest technical andeconomic potential for delivering long-term reductions in greenhouse gas emissions (Barker etal., 2007). In developed countries, where the foundations of most existing buildings are set fordecades to come, retrofitting current infrastructure is the most feasible policy measure foroptimising emissions reductions in buildings (UNEP Sustainable Buildings and ConstructionInitiative, 2009). For low- and middle-income developing countries, however, the opportunity

exists to develop low-carbon building policies in order to lock in to a more sustainabledevelopment path.


21/42

DR15 21

Box 1 Case study of Masdar City, Abu Dhabi.

Masdar City is a carbon-neutral, zero-waste urban development project that was initiated in2006 to address the long-term aim of establishing Abu Dhabi and the United Arab Emirates(UAE) as world leaders in industries based on low-carbon technologies.

The initiative adopts a scaling-up approach to harness the planning and accounting benefitsof large economies of scale, while systematically integrating advanced renewable energytechnologies in order to deliver greater quantities of usable power (Nader, 2009). Forexample, the city will be a car-free zone with mobility provided in the form of an electricallypowered rapid transport system integrated into external networks. In addition to developingrenewable energy technologies that will reduce energy consumption, smart urban design isbeing incorporated into city plans, and all buildings will integrate intelligent infrastructure to

facilitate efficient resource use (Nader, 2009).

Masdar City will have the capacity to house 40,000 residents and the potential to create50,000 jobs in a range of businesses and institutions. It is likely, however, that a significantproportion of these jobs will be in areas requiring a high level of skills, in line with MasdarCitys broader aim to cultivate an innovative academic and business community that willgenerate significant intellectual property. The city hopes to encourage over 1,500 companiesin the field of low-carbon energy technologies to locate their offices and research facilitieswithin the city. To aid these flows of investment, Masdar City will be a free zone, in whichcompanies will have zero taxes and zero import tariffs, among other benefits (Reiche, 2010).Cooperation with the Massachusetts Institute of Technology will help develop the Masdar

Institute of Science and Technology a postgraduate educational and research institute thataims to mark Abu Dhabi as a global centre of excellence in sustainable energy-technologyresearch.

The Masdar City initiative is a key component of the UAEs long-term economicdiversification strategy. As the economy is mainly dependent on exporting fossil fuels, thegovernment hopes that the initiative will increase energy security and help prepare citizensfor a post-oil age (Reiche, 2010). The first phase of Masdars development is due to becompleted in 2016. The project thus far has experienced a number of challenges includinglagging foreign investment and a lack of regional demand; whether Masdar City will act as ablueprint for future eco-cities and energy policy remains to be seen. Questions also remain

over whether the concerted drive to attract highly skilled researchers and business peoplewill lead to the evolution of Masdar City as an exclusive and inequitable premium ecologicalenclave (Hodgson and Marvin, 2010).

The macroeconomic impacts of mitigation

The macroeconomics of mitigation illustrate some of the ways in which policy could affect net

expected income differentials. Abatement opportunities can be assessed based on their costfunctions, which calculate the marginal cost per unit of CO2e abated (see Figure 6). The costcurves of these functions will usually be convex because the marginal costs of abatement willrise as lower cost gains are exhausted and returns to scale diminish. Cost functions for


22/42

DR15 22

opportunities will vary in different economies because of underlying economic conditions andbecause the technical potential for opportunities will differ; they can also change over timebecause innovation has the potential to lower average costs.

Figure 6: Abatement cost curve for a specific technology.

Source: Stern (2006).

The economic potential of abatement opportunities to 2030 has been assessed using a varietyof models, which are categorised as top-down and bottom-up, assuming an optimal responseto exogenous carbon prices (Barker et al., 2007; van Vurren 2009)2. Top-down modelssimulate substitution of inputs across the whole economy whereas bottom-up models focusmore on substitution of technologies within the energy system. Most models, whether top-down or bottom-up, agree that the greatest economic potential lies in developing countries,but realising them is likely to require international transfers from developed countries. Resultsfor sectors differ across models but tend to show that the largest potential for direct emissionreductions is in the energy supply sector both in absolute and relative terms (see Figure 7).Without new technological breakthroughs, the economic potential of decarbonising thetransport sector is limited and it is expected to remain largely fossil fuel based in 2030.

2 The methods of optimisation can differ across the models.


23/42

DR15 23

Figure 7: Economic potential for direct CO2-emission reduction in the energy supply,transport, building and industry sectors based on a comparison of top-down andbottom-up models.

Source: van Vuuren et al. (2009).

The macroeconomic costs of mitigation are highly uncertain and projections are predicted onthe underlying assumptions of models. van Vuuren et al. (2009) found that the direct costs of

abatement to meet a stabilisation target of 450 ppm CO2e are similar in range for top-downand bottom-up approaches and, assuming favourable policy design for the former andimplementation for the latter, they come in at $100-1,000 billion per annum to 2030. Theactual macroeconomic costs could be quite different, particularly, as is likely, if policy designand implementation is not economically optimal. The macroeconomic costs borne byemissions-intensive economies, for instance, could be higher than the direct costs (see Figure8). Mattoo et al. (2009) for instance find that even a modest global agreement on mitigationdepresses manufacturing output and exports in economies such as China and India. The SternReview estimates the average costs to stabilise at 550 ppm CO2e using top-down andbottom-up at around $1,000 billion per annum or the equivalent of 1% of gross domesticproduct (GDP) in 2050 within a range of 3% of GDP. Weyant (2009) argues controversially

that the range is actually 110% of GDP if less optimistic policy outcomes are considered.


24/42

DR15 24

Figure 8:Greenhouse gas emissions per un it of GDP for countr ies/regions, 2005.

Source: OECD (2009).

In the transition to a low-carbon economy, labour markets and wages will not exhibit theflexibility assumed by many top-down models. When labour-market rigidities are incorporatedinto simulations of the economic costs of mitigation, the losses to GDP are significantly higher(Babiker and Eckhaus, 2007; Guivarch et al., 2011). The magnitude of the effect variesdepending on economic structure, but this finding also suggests that policy makers craftingmitigation policy need to be mindful of its consequences for unemployment, which is unlikely inthe short term to be in political terms a price worth paying for mitigation. Transitional effectsfrom labour markets could be ameliorated by labour subsidies and training funded by revenuesfrom carbon taxes (Babiker and Eckhaus, 2007; Guivarch et al., 2011). There could also be anincongruity between the flexible global labour markets that will be required to mitigate climate

change cost effectively, and rigid national labour markets could be stiffened by restrictivemigration policies.

Certain abatement opportunities will also require more upfront capital expenditure as part oftheir costs (Figure 9). For the buildings and transport sectors the investments required areparticularly high, but these are no regrets options where the overall costs are justifiedeconomically by the benefits even without emissions pricing. The potential gains from low-carbon urbanisation, which depends on realising cross-sectoral opportunities, are substantial,but achieving these gains in a capital-constrained environment would be challenging. Withoutupfront low carbon investments, there is the aforementioned danger that economies willbecome locked-in to emissions-intensive infrastructure. Thus, the economic costs of mitigation

will rise with inaction.


25/42

DR15 25

Figure 9:Capital intensity and abatement potential for sector (/tCO2e).

Source: Campbell (2008).

The global economic costs of greenhouse gas abatement may be uncertain but they will not beuniform across either countries or sectors. For all but the most pessimistic cost estimates,aggregate mitigation costs should be absorbed by future global economic growth. But there stillexists some potential for regulatory arbitrage within sectors. Emissions-intensive firms open tointernational trade could be vulnerable to free-riding competitors, although the potential ofrelocation is limited because there are stronger determinants of location than greenhouse gasmitigation policies (Brunnermeier and Levinson, 2004; Copeland and Taylor, 2004). The impacton location and trade could be higher, however, if access to inputs such as capital stock,labour, technology and infrastructure is equivalent or better in the destination country, and ifdomestic markets are large. Thus, firms and labour could cross borders in the absence ofregional agreements.

Low-carbon jobs

Achieving stabilisation of greenhouse gas concentrations at 450 ppm CO2e will alter thegeography of the energy system and its labour market. There were around 2.3 million jobs inthe renewable energy sector in 2006, with most jobs growing and collecting feedstock forbiofuel production in Brazil, USA and China; a large number of jobs are also in Chinas solarthermal industry (UNEP, 2008). Renewable energy production is more labour intensive thanfossil fuel production in manufacturing and operational terms, although this is likely to lessen inthe long term as efficiency gains bring down costs (Kammen, 2006; Fankhauser et al., 2008;see Table 3). Roughly 9 million people are directly employed in the energy sector, mostly incoal, gas and hydropower (Rutovitz and Atherton, 2009). Direct employment in the energysector is relatively small compared with other sectors and it is male dominated. It is expected

that most new recruitment would be sourced from the existing workforce.


26/42

DR15 26

Table 3: Average projected employment over life of facility, jobs per megawatt of energy.Note figures are corrected for di fferences in capacity between fossil fuel plants andrenewable installations.

FacilityConstruction,manufacturing,installation

Operation andmaintenance, fuelprocessing

Total employment

Solar PV 5.766.21 1.24.80 7.4110.56

Wind 0.432.51 0.27 0.712.79

Biomass 0.40 0.382.44 0.782.84

Coal 0.27 0.74 1.01

Gas 0.25 0.70 0.95

Source: Kammen et al. (2006).

UNEP (2008) projects a significant increase in employment in the renewable energy sector by

2030 including up to 12 million new jobs in biofuel-related agriculture and industry butaccurate predictions are not possible because numbers and types of jobs will be stronglyinfluenced by future policies. Some care is required in distinguishing net job creation fromgross job creation. Low-carbon policies are also likely to induce structural change in economiesthat lead to the reallocation of labour across sectors and multiplier effects that affect indirectemployment opportunities (Fankhauser et al., 2008).

There is limited analysis available on the skills that will be required for low-carbon jobs. Dierdoffet al. (2009) found that less than a tenth of the occupations in renewable energy in the USA arelow-skill jobs but that there may be more opportunities in green construction andmanufacturing. If the USA is typical of developed countries and relatively few low carbon jobs

are low-skill jobs, then polices will be required to improve access to these occupations (Bivenset al., 2009; Martinson et al., 2010). On the other hand, Pollin et al. (2009) argue that cleanenergy investments will create more opportunities across all skillsets and provide better jobadvancements prospects than a fossil fuel-dominated energy sector. The largest source of low-carbon jobs for the low skilled in the developing world is likely to be in labour-intensive biofuelharvesting (UNEP, 2008). Estimates of the new opportunities that may be created in forestryare difficult to calculate and although new policies could have positive long-term impacts onemployment, the industry standard for afforestation and reforestation projects is based oneither mechanisation or seasonal, low-skill contract work (UNEP, 2008). Most of those formallyemployed in forestry are men, but there are an increasing number of opportunities for womenin subsectors such as agroforestry.


27/42

DR15 27

Low-carbon policy and migration

Nations will require a portfolio of low-carbon policies that is sensitive to their ownsocioeconomic conditions. A variety of policy instruments have been proposed for this portfolio

targets, market mechanisms such as taxes, subsidy reform and emissions trading schemes,regulatory standards, technology support policies, voluntary agreements and informationinstruments. There is a consensus among economists that pricing greenhouse gas emissionsthrough market mechanisms should be the kernel of policy portfolios because by offeringflexibility in the timing and the sources of abatement they will, in theory, incentivise cost-effective mitigation (Stern, 2006; OECD, 2009). Other instruments are likely to be necessary tocomplement pricing if there are barriers that could impede the responses of firms andconsumers to price signals. Barriers to technological innovation and deployment, for example,mean that public investment into research and development of emissions-reducingtechnologies and increased cooperation between the public and private sector are likely to berequired (Barker et al., 2007). The lack of empirical evidence on the effect of current mitigationpolicies on mobility makes this section highly speculative and the focus of the analysis ismainly on how mitigation could affect key variables of interest.

Ambitious targets in developing countries for large-scale hydropower production could directlyresult in internal displacement. Growth in hydropower production is projected in Asia, LatinAmerica and Africa, and exploitation of potential is explicitly targeted in the national climatechange plans of Brazil, India and China (Bartle, 2002; World Resources Institute, 2010). Thedevelopment of large-scale hydropower infrastructure is closely associated with controversiessurrounding the forced displacement and resettlement of vulnerable populations livingupstream in, or downstream of, impoundment zones and the subsequent loss of livelihoods.

Moreover, indirect environmental impacts from the development of hydropower can also lead todisplacement. It has been estimated that around 4 million people are displaced every year as aresult of dam-based development, although this number is likely to be larger (World BankEnvironment Department, 1996). Indigenous and tribal peoples have suffereddisproportionately from the negative impacts of large hydropower projects, which over time canperpetuate problems for people living at increasing distances from the site of the project,leading to multiple displacements (World Commission on Dams, 2000; Gellert and Lynch,2003).

Ambitious targets in both developed and developing countries for biomass consumption andproduction have the potential to influence internal mobility and displacement. Targets have

already been set for biofuel use in several developed and developing countries to 2020 andbeyond. Fischer (2009) found, using an integrated assessment modelling framework, that thedemands of future biofuel production on land use could be substantial and real cereal pricesconsiderably higher if targets are ambitious and the development of capital-intensive second-generation conversion technology is inhibited. Most of the expansion in land use whether forfirst-generation or second-generation biofuel production would be in Africa and LatinAmerica. Major changes in supply chain infrastructure will also be needed to link production toglobal markets (Richard, 2010). Mobility is likely to be directly affected by some newemployment opportunities in biofuel harvesting, but it could also be indirectly affected ifbiomass production has a disruptive effect on livelihoods by diminishing the quantity andquality of local ecosystem services, or if higher food prices increase food insecurity. The growth

expected in biomass production would be expected to have an effect on households who aredependent on forests for their livelihoods, especially if a lack of rights renders them vulnerableto access restrictions. Managing the trade-offs or synergies in complex socioecological forestrysystems is challenging, but a greater role for forest users in governance is likely to improveoutcomes (Agrawal et al., 2008; Persha et al., 2011). Processes for land transfers to large-


28/42

DR15 28

scale biofuel plantations vary considerably but customary land rights are often poorlycompensated (German et al., 2010). In Indonesia, for example, the customary rights ofindigenous people have been ignored by some oil palm plantations (Phalan, 2009). Alternatively, with effective governance at multiple scales, these new markets do offeropportunities for smallholders and households to diversify income (Rist et al., 2010).

The most technically viable areas for onshore wind energy are in coastal areas, which havebeen historically associated with population density. However, the elevation necessary forlarge-scale wind farms makes it less likely that they will compete for land with densepopulations. More detailed spatial, economic and geographical analysis is needed to accuratelyassess the potential of population displacement. Similarly, large-scale CSP projects would bemore likely to be located in areas where population is sparse. Small-scale hydropower,biomass, wind and solar technologies, on the other hand, have more potential in the medium tolong term to affect income differentials if they improve energy access in poor rural areas.


29/42

DR15 29

Box 2: Biofuels and migration.

The biofuels industry has had mixed socioeconomic impacts at country and regional levels.In Brazil, biofuels are an established industry, with around 1 million direct jobs in 2001 and afurther 300,000 jobs created indirectly in manufacturing and other sectors (Moreira, 2006).

African countries, most notably Tanzania, Kenya, Cameroon and Nigeria, have large swathesof land suitable for biofuel production and an abundance of low-skilled labour that makesthem well positioned to capture the benefits from increasing global demand for biofuels(Mitchell, 2011). Many of the worlds poorest countries are well placed to become majorproducers of biomass for first-generation biofuels, and most of the jobs created are likely tobe in impoverished rural areas (FAO, 2008). For large-scale production, increased jobopportunities for unskilled workers, higher and more regular income flows, road expansionand wider social networks can have positive livelihood effects. If expected benefits outweigh

the cost of migration, this could potentially stem or even reverse the flow of migration tourban areas (J ohnson and Rosillo-Calle, 2007). Recent international collaborations involvingboth governments and the private sector could result in the emergence of new migrationcorridors. For example, Chinese farms are investing in oil palm plantations in the DemocraticRepublic of Congo, and biofuels initiatives in Mozambique have been funded by companiesin Mauritius (Dauvergne and Neville, 2010).

There has been some debate, however, over the number of jobs likely to be created. Germanet al. (2010) affirm that employment levels can be far less than those related to displacedland uses; the FAO (2008) states that new job creation will only be higher if biofuel-feedstockproduction does not displace other agricultural activities, or if labour requirements in the

biofuels industry are greater. Labour intensity can vary substantially within a country and notall rural areas could expect to benefit from increased job creation (Kojima and J ohnson,2005). Smallholders working in emerging biofuels industries such as jatropha cultivation maynot realise gains as quickly (German et al., 2010).

While biofuels development if managed effectively could contribute to economic growth andalleviate poverty, controversies have emerged over the real beneficiaries of biofuelsexpansion, and displacement both physical and livelihood is plausible. Deforestation forland-use conversion has been particularly widespread in industrial-scale plantations,resulting in the displacement of those who depend on forests for their livelihoods. Marketincentives which favour biofuels production over more established agricultural industries can

raise the price of land, driving poorer people away from their means of production andfragmenting communities. Poorer households also face barriers which prevent them fromestablishing secure land rights which protect their rights to the land. There is additionalevidence to suggest that women are more vulnerable to displacement, as genderdiscrimination may limit their ability to own or inherit land (Department for InternationalDevelopment, 2007; FAO, 2008). In Kenya, for example, women provide 70% of agriculturallabour in the country yet own only 1% of the land that they farm with their families(Department for International Development, 2007). Smallholder farmers and pastoralists withcustomary land rights are also likely to be more vulnerable to eviction from the large-scaletransfer of land to investors.

The development of biofuels clearly has both technological and economic potential in thelong term, and southsouth partnerships will encourage economic growth in developingcountries. However, effective governance and policy will be required to minimisedisplacement and negative socioeconomic impacts.


30/42

DR15 30

Fossil fuel energy production and consumption subsidies distort the price of greenhouse gasemissions, and their elimination is widely acknowledged as a necessary step towards thepricing of emissions. IEA (2008) estimated the price gaps because of energy subsidies in anumber of non-Organisation for Economic Co-operation and Development (OECD) countriesand found that in many cases the deviation from world prices was significant. Simulation of the

multilateral removal of these subsidies results in real household income losses in emissions-intensive non-EU eastern European countries, Russia and oil-exporting countries, and at thesame time gains in energy-importing countries such as the EU and J apan, mostly because ofchanges to the terms of trade (OECD, 2009). Thus, if winners and losers are connected byestablished migration corridors, a significant change in expected net income differentials mayinfluence the volume and direction of migratory flows (see Figure 10).

Figure 10: Top migration corridors, 2005 (millions of migrants).

Source: World Bank (2009).

Although low-carbon urbanisation is a technically and economically viable abatement

opportunity, it will require significant upfront capital investment. It is not a straightforward policychallenge because it is based on a systemic approach to policy in a locale that has traditionallybeen governed at different scales by a variety of actors. Effective city-level governance is likelyto be necessary, and strong political leadership of mayors has proved useful in the developingworld (Dhakal, 2010). Low-carbon cities could be more attractive to migrants if net expectedincome differentials are widened by reductions in the cost of living, or if energy-efficiencysavings and additional agglomeration effects spur economic growth. The quality of life in urbanareas that have been planned sustainably would also be a pull factor. This notwithstanding,the impact of low-carbon urbanisation on ruralurban migrants is unlikely to be entirelybeneficent. Land values in high-density compact cities are usually expensive, and publictransport will not be affordable to all. In Delhi, despite a master plan to encourage mixed-use

planning, large numbers of low-income ruralurban migrants settling on its periphery havebeen excluded from its benefits (Tiwari, 2003).


31/42

DR15 31

Current levels of investment in low-carbon technology are dominated by China and the USA(see Figures 11 and 12). Chinese state-owned or partially state-owned organisations areinvesting heavily in large-scale low-carbon energy supply and the country itself is alsoattracting the most investment from public financial markets. The clear direction on low-carbonpolicy from Chinas 12th 5-year plan makes it attractive to public investors. Private investment

in research and development has traditionally been strong in the USA and it is well positionedto discover low-carbon innovations. Recent stimulus packages in the wake of the financialcrisis have also allocated significant resources to low carbon energy supply especially in theUSA ($65bn), China ($46bn), South Korea ($32bn), Germany ($15bn) and J apan ($10bn).Investments, particularly in large-scale low-carbon energy supply, will position nationaleconomies favourably for a future where greenhouse gas emissions are priced. Investmentwould be expected to be a pull factor for the medium- and high-skilled labour required by therenewable energy sector. For low-skilled labour in nearby countries, investment could indirectlyaffect future net expected income differentials. This could happen if the macroeconomic costsof mitigation are lowered, if investment stimulates endogenous technological change or ifenergy-efficiency savings are recycled into productive investments that result in additional

growth.

Figure 11: Asset finance for large-scale energy, 2010 ($ bill ion).

Source: World Economic Forum (2011).


32/42

DR15 32

Figure 12: Venture capital and PE finance for clean energy, 2010 ($ bill ion).

Source: World Economic Forum (2011).

International sector agreements based on a variety of policy instruments have been proposedas a cost-effective policy response to the uneven distribution of mitigation costs acrosscountries and sectors (de Coninck et al., 2008). Well-designed agreements could amelioratecompetitiveness impacts for individual countries and would be expected to diminish anywidening in income differentials.

Without new technological breakthroughs, the economic potential of decarbonising thetransport sector is limited and it is expected to remain largely fossil fuel based in 2030. IEA(2010) calculates that the low-carbon policies required to stabilise greenhouse gas emissionsat 450 ppm CO2e would reduce demand for crude oil and, as a result, real prices wouldincrease more slowly than in other scenarios (see Figure 13). Rising global demand and thenecessity to develop more expensive sources of supply means that prices are expected toremain volatile. The precise impact of direct transport costs on mobility will vary amongmigrants but given that average costs to 2030 are expected to be high, it would probably havea dampening effect on movement.

Figure 13: Average real crude oil price based on pol icy scenarios, 19802035 ($/barrel).


33/42

DR15 33

Source: IEA (2010).

International governance of climate change could have an impact on mobility anddisplacement. Incomplete participation of countries and industries substantially increases theeconomic costs of mitigation because it reduces flexibility in ways to meet stabilisation targets

(OECD, 2009; Weyant, 2009). These additional costs would exacerbate the unequaldistribution of costs across countries and sectors, and as these costs accumulate with inactionand climate damages rise, belated policy could result in volatile changes in net expectedincome differentials between countries, livelihood losses and direct transport costs. Substantialdifferences in costs between countries may have an effect on international mobility becausethere is usually a correlation between GDP losses and unemployment (Okun, 1970; Lee,2000). International governance of climate change is an unprecedented game of prisonersdilemma complicated not only by the uneven distribution of both costs and benefits but alsobecause the rewards for cooperation and defection change over time. In a pessimisticscenario, an effective group of national cooperators is not possible (Helm, 2008).

The major challenge that the United Nations Framework Convention on Climate Change(UNFCCC) has to grapple with is that realising opportunities for abatement in developingcountries will require new transfer mechanisms to address the responsibility of developedcountries for historic emissions. Two important policy instruments to provide internationaltransfers have been established: the CDM (valid until 2012) and REDD+. A green climate fundwill also provide financial support for mitigation and adaptation in the developing world basedon contributions from developed countries there is a commitment to provide $100 billion peryear by 2020. The CDM offers developed countries with more cost-effective greenhouse gasemissions abatement options by allowing reductions to be made more flexibly in fundedprojects located in developed countries. The projects in these host countries also have afurther aim of meeting sustainable development objectives. However, sustainable development

has no international standards and host countries can define their own objectives. Sutter andParreo (2007) find evidence of a trade-off between cost-effective emission reduction andsustainable development objectives in CDM projects, which are heavily weighted to the former.Of currently registered CDM projects, most are based on hydropower (30%), wind power(19%), biomass (11%) and biogas (11%); biofuel projects are rare because of rule restrictions(UNFCCC, 2011). This looseness in defining sustainable development objectives means thatthere is currently no systematic process to protect vulnerable people from displacement as aresult of a CDM project. Governance of future iteration of the CDM should improve the criteriafor sustainable development objectives. Similarly, the new rules for REDD+ and the greenclimate fund also face the challenge of managing this trade-off in an equitable way. Polices onconservation projects in multilateral development agencies have been broadened to re-definethe concept of restrictions on access to natural resources to include livelihood displacement aswell as physical displacement (Cernea, 2006); and this revised concept seems highly relevantto mitigation policy.

Renewable energy and rural development

Low-carbon policies have the opportunity to improve the access of rural areas in thedeveloping world to energy, which could have a highly significant impact on mobility. Therelationship between energy consumption and per-capita income is complex, but they are

strongly correlated. Reducing poverty in rural areas will require improved access to energy ingeneral and electricity in particular. Renewable energy technologies have an important part toplay because in many rural areas it is not economic to extend large centralised electricity gridsto meet their needs. Better energy services can improve incomes directly by improvingproductivity in agriculture and non-agriculture enterprises and indirectly by enhancing


34/42

DR15 34

education and health outcomes through better heating, lighting, cooking and communications(Cabraal et al., 2005). Martinot et al. (2002) captured lessons to be learned from projects thathave used renewable technologies such as modern biomass, photovoltaic solar and small-scale hydropower and wind to improve development outcomes. The most cost-effectivebalance between off-grid and on-grid energy will vary considerably by area and will depend on

the marginal cost of grid extension (Deichmann et al., 2010). Stand-alone renewabletechnologies and micro-grids can be competitive in rural areas and their effective deployment(including through the CDM) is likely to boost rural incomes and be a pull factor at areas oforigin. Beyond the short term with increased income, the economic costs of mobility may beless prohibitive, and these movements would be part of a pathway to development and notenvironmentally induced mobility with operational or geopolitical difficulties. Thus, mitigationpolicy if carefully crafted and implemented could be one way of many to address potentialvolatilities in movements that may be induced by environmental change.

Conclusion: plausible scenarios for the

impact of low-carbon policy on migration

The precise impacts of existing mitigation policy on migration are often difficult to distinguish,and more empirical research is urgently required in this area. To sum up, low-carbon policiescould have impacts on population mobility and displacement by affecting the net expectedincome differentials between areas of origin and destination, disrupting the livelihoods ofhouseholds reliant on natural resources, changing direct transport costs and altering returns tohuman capital. The uncertainties surrounding future mitigation policy are considerable, and thecomplexity of the migration decision make judgements on orders of magnitude challenging.

Nevertheless, the impact on mobility in the short-to-medium term is likely to be modest withsome new direct employment opportunities for a range of skills and the potential for low-incomesmallholders and households to diversify income. In the longer term, if the transition to a low-carbon society induces a new wave of innovation, the impact on labour markets could betransformative (Milunovic and Rasco, 2008; Fankhauser et al., 2009). This particular scenariowill depend on the success of national policies, flexibility of labour markets and effectiveinternational climate change governance. With delayed action, the policies then required tostabilise greenhouse gas concentrations could result in economic and social instability, whichmight induce new volatilities in migratory flows. In terms of orders of magnitude, the largestexpected effects on mobility and displacement illustrate that low-carbon policy is in some waysboth a threat and an opportunity to reducing poverty in the developing world. Mitigation

measures, imposed inequitably, will disrupt the livelihoods of households dependent on naturalresources. Successful adaptation to climate change should be sensitive to social structure andfor mitigation surely the same is true (Adger et al., 2005). The sheer size of the developing-world population dependent on agriculture and forestry raises concerns that poorly designedand implemented policies to increase low-carbon energy supply and improve carbonsequestration could, paradoxically, harm the livelihoods that mitigation policy is intended toprotect. On the other hand, effectively deployed small-scale renewable energy technologiescould provide an important boost to rural incomes, especially over the medium-to-long term,and lower the costs of mobility. In short, if low-carbon policies are crafted systemically atappropriate levels of governance and in accordance with other strategic objectives such assustainable development, energy access, poverty reduction, adaptation to climate change and

maintaining ecosystem services and biodiversity, the outcomes of greenhouse gas abatementare much more likely to be beneficial in the short, medium and long term.


35/42

DR15 35

References

Adger, W.N., Arnel, N.W. and Tompkins, E.L. (2005). Successful adaptation to climate changeacross scales. Global Environmental Change 15: 7786.

Agrawal, A., Chatre, A. and Hardin, R. (2008). Changing governance of the worlds forests.Science 320: 1460.

Archer, C.L. and J acobson, M.Z. (2005). Evaluation of global wind power. Journal ofGeophysical Research 110: D12110.

Babiker, M. and Eckhaus, R.S. (2007). Unemployment effects of climate policy. EnvironmentalScience and Policy 10: 600609.

Barker T., Bashmakov, I., Bernstein, L., et al. (2007). Technical summary. In: Climate Change2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change. Cambridge, United Kingdom: CambridgeUniversity Press.

Bartle, A. (2002). Hydropower potential and development activities. Energy Policy 30: 12311239.

Bates, D.C. (2002). Environmental refugees? Classifying human migrations caused byenvironmental change. Population and Environment 23: 465477.

Baumert, K.A., Herzog, T. and Pershin, J . (2004). Navigating the Numbers. Washington, DC:World Resources Institute.

Bivens, J ., Irons, J . and Pollack, E. (2009). Green Investments and the Labor Market: HowMany Jobs could be Generated and what Type? Washington, DC: Economic Policy Institute.

Brunnermeier, S. and Levinson, A. (2004). Examining the evidence on environmentalregulations and industry location. Journal of the Environment and Development 13: 641.

Cabraal, A., Barnes, D.F. and Agarwal, S. (2005). Productive uses of energy for ruraldevelopment.Annual Review of Environment and Resources 30: 117144.

Campbell, W. (2008). Carbon Capture and Storage: Assessing the Economics. McKinsey &Company.

Cernea, M. (2000). Risks, Safeguards and reconstruction: a model for population displacementand resettlement. In: M. Cernea and C. McDowell (eds), Risks and Reconstruction:Experiences of Resettlers and Refugees. Washington, DC: The World Bank.

Cernea, M. (2006). Re-examining displacement: a redefinition of concepts in development andconservation policies. Social Change 36: 835.

de Coninck, H.C., Fischer, C., Newell, R. and Ueno, T. (2008). International technology-oriented agreements to address climate change. Energy Policy 36: 335356.


36/42

DR15 36

Copeland, B.R. and Taylor, S. (2004). Trade, growth and the environment. Journal ofEconomic Literature XLII: 771.

Dauvergne, P., and Neville, K. (2010). Forest, food and fuel in the tropics: the uneven socialand ecological consequences of the emerging political economy of biofuels. The Journal of

Peasant Studies 37: 631660.

Deichmann, U., Meisner, C., Murray, S. and Wheeler, D. (2010). The Economics of RenewableEnergy Expansion in Rural Sub-Saharan Africa. Policy Research Working Paper 5193.Washington, DC: World Bank.

Department for International Development. (2007). Land: Better Access and Secure Rights forPoor People. London: Department for International Development.

Dhakal, S. (2010). GHG emissions from urbanization and opportunities for urban carbonmitigation. Current Opinion in Environmental Sustainability 2: 277283.

Dierdoff, E.C., Norton, J .J ., Drews, D.W., Kroustalis, C.M., Rivkin, D. and Lewis, P. (2009).Greening of the World of Work: Implications for O*NET SOC and New and EmergingOccupations. Raleigh, NC: National Center for O*NET Development.

Dodman, D. (2009). Blaming cities for climate change? An analysis of urban greenhouse gasemissions inventories. Environment and Urbanization 21: 185201.

EEA. (2010). Atmospheric greenhouse gas concentrations (CSI 013). Available from:http://www.eea.europa.eu/data-and-maps/indicators/atmospheric-greenhouse-gas-

concentrations/atmospheric-greenhouse-gas-concentrations-assessment-3.

Faaij, A.P.C. and Domac, J . (2006). Emerging international bio-energy markets andopportunities for socioeconomic development. Energy for Sustainable Development X: 719.

Fankhaeser, S., Sehlleier, F. and Stern, N. (2008). Climate change, innovation and jobs.Climate Policy 8: 421429.

FAO (2005). Global Forest Resources Assessment. Rome: Food and Agricultural Organisation.

FAO (2008). The State of Food and Agriculture Biofuels: Prospects, Risks and Opportunities.

Rome: Food and Agricultural Organisation.

FAOSTAT (2010). Rome: Food and Agricultural Organisation. Available from:http://faostat.fao.org/.

Findley, S.E. (1994). Does drought increase migration? A study of migration from rural Maliduring the 19831985 drought. International Migration Review 28: 539553.

Fischer, G. (2009). World Food and Agriculture to 2030/50: How do Climate Change andBioenergy Alter the Long-term Outlook for Food, Agriculture and Resource Availability? ExpertMeeting on How to Feed the World in 2050, 24 J une, Rome, Italy.

Garnett, T. (2011). Where are the best opportunities for reducing greenhouse gas emissions inthe food system (including the food chain)? Food Policy 26: S23S32.


37/42

DR15 37

Geller, H., and Attali, S. (2005). The Experience with Energy Efficiency Policies andProgrammes in IEA Countries: Learning from the Critics. Paris, France: IEA.

Gellert, P., and Lynch, B. (2003) Megaprojects as displacements. International Social ScienceJournal 55: 1525.

German, L., Schoneveld, G., Skutch, M., Andriani, R., Obidzinski, K., and Pacheco, P. (2010).The Local Social and Environmental Impacts of Biofuel Feedstock Expansion: A Synthesis ofCase Studies from Asia, Africa and Latin America. CIFOR Info Brief No. 34. Bogor, Indonesia:CIFOR.

Glaeser, E.L., and Kahn, M.E. (2010). The greenness of cities: Carbon dioxide emissions andurban development. Journal of Urban Economics 67: 404418.

Greening L.A., Greene, D.L. and Difiglio, C. (2000). Energy efficiency and consumption therebound effect a survey. Energy Policy 28: 389401.

Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. (2011). The costs of climate policies ina second-best world with labour market imperfections. Climate Policy 11: 768788.

Harris, J .R. and Todaro, M. (1970). Migration, unemployment and development: a two-sectoranalysis.American Economic Review 60: 126142.

Heinim, J ., and J unginger, M. (2009). Production and trading of biomass for energy anoverview of the global status. Biomass and Bioenergy 33: 13101320.

Helm, D.R. (2008). Climate-change policy: Why has so little been achieved? Oxford Review ofEconomic Policy 24: 211238.

Henry, S., Pichao, V., Ouacodraogo, D. and Lambin, E.F. (2004). Descriptive analysis of theindividual migratory pathways according to environmental typologies. Population andEnvironment 25: 397422.

Hodgson, M., and Marvin, S. (2010) Urbanism in the anthropocene: Ecological urbanism orpremium ecological enclaves? City: Analysis of Urban Trends, Culture, Theory, Policy, Action14: 298313.

IEA (2008). World Energy Outlook. Paris: OECD/IEA.

IEA (2010). World Energy Outlook. Paris: OECD/IEA.

Ingram, G. (1997). Patterns of Metropolitan Development: What Have We Learned? PolicyResearch Working Paper 1841. Washington, DC: World Bank.

International Labour Organization (2011). Global Employment Trends 2011. Geneva: ILO.

J acobson, A. (2007). Connective power: Solar electrification and social change in Kenya.

World Development 35: 144162.

J ohnson, F., and Rosillo-Calle, F. (2007). Biomass, Livelihoods and International Trade-Challenges and Opportunities for the EU and Southern Africa Climate and Energy Report.Stockholm: Stockholm Environment Institute.


38/42

DR15 38

J ust, T. and Thater, C. (2008). Megacities: Boundless Growth? Frankfurt: Deutsche BankResearch.

Kammen, D.M., Kapadia, K. and Fripp, M. (2006). Putting Renewables to Work: How ManyJobs Can the Clean Energy Industry Generate? Report of the Renewable and Appropriate

Energy Laboratory. Berkeley: University of California.

Kaya, Y. (1990). Impact of Carbon Dioxide Emissions Control on GNP Growth: Interpretation ofproposed scenarios Paper presented to the IPCC Energy and Industry Subgroup, ResponseStrategies Working Group, Paris, France.

Kibreab, G. (1997). Environmental causes and impact of refugees movements: a critique of thecurrent debate. Disasters 21: 2038.

Kojima, M. and J ohnson, T. (2005). Potential for Biofuels for Transport in DevelopingCountries. Washington DC: The World Bank.

Lee, J . (2000). The robustness of Okuns Law: Evidence from OECD countries. Journal ofMacroeconomics 22: 331356.

McLeman, R. and Smit, B. (2006). Migration as an adaptation to climate change. ClimaticChange76: 3153.

Massey, D., Goldring, L., and Duran, J . (1994). Continuities in transnational migration: ananalysis of nineteen Mexican communities.American Journal of Sociology 99: 14921533.

Martinot, E., Chaurey, A., Lew, D., Moreira, J ., and Wamukonya, N. (2002). Renewable energymarkets in developing countries.Annual Review of Energy and the Environment 27: 309348.

Martinson, K., Stanczyk, A. and Eyster, L. (2010). Low-Skill Workers Access to Quality GreenJobs. Urban Institute Brief 13.

Documents

The Impact of Low Carbon Policy on Migration