ArticlePublisher preview available

Understanding future emissions from low-carbon power systems by integration of life-cycle assessment and integrated energy modelling

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract and Figures

Both fossil-fuel and non-fossil-fuel power technologies induce life-cycle greenhouse gas emissions, mainly due to their embodied energy requirements for construction and operation, and upstream CH4 emissions. Here, we integrate prospective life-cycle assessment with global integrated energy-economy-land-use-climate modelling to explore life-cycle emissions of future low-carbon power supply systems and implications for technology choice. Future per-unit life-cycle emissions differ substantially across technologies. For a climate protection scenario, we project life-cycle emissions from fossil fuel carbon capture and sequestration plants of 78-110 gCO2eq kWh⁻¹, compared with 3.5-12 gCO2eq kWh⁻¹ for nuclear, wind and solar power for 2050. Life-cycle emissions from hydropower and bioenergy are substantial (~100 gCO2eq kWh⁻¹), but highly uncertain. We find that cumulative emissions attributable to upscaling low-carbon power other than hydropower are small compared with direct sectoral fossil fuel emissions and the total carbon budget. Fully considering life-cycle greenhouse gas emissions has only modest effects on the scale and structure of power production in cost-optimal mitigation scenarios.
This content is subject to copyright. Terms and conditions apply.
Articles
https://doi.org/10.1038/s41560-017-0032-9
© 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
1Potsdam Institute of Climate Impact Research, PO Box 60 12 03 Potsdam, Germany, . 2Industrial Ecology Programme and Department of Energy and
Process Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. 3Center for Industrial Ecology, Yale School for Forestry
and Environmental Studies, New Haven, CT, USA. *e-mail: michaja.pehl@pik-potsdam.de; gunnar.luderer@pik-potsdam.de
The Paris Agreement of COP21 confirmed the goal of limiting
global temperature increase well below 2 °C and acknowledged
the need to achieve net greenhouse gas neutrality during the
second half of the century1. Previous research based on integrated
energy–economy–climate models has shown that achieving these
targets cost-effectively requires a rapid, almost full-scale decarbon-
ization of the electricity system by mid-century2,3. In electricity pro-
duction, ample low-carbon alternatives are available4 and electricity
is a potential substitute for fossil-based fuels in all economic sectors,
which leads to final energy electricity shares of 25–45% in stringent
mitigation scenarios2.
The life-cycle assessment (LCA) literature illustrates that all
energy transformation technologies are associated with upstream
energy demands and corresponding indirect (that is, not caused by
fuel-burning on site) greenhouse gas (GHG) emissions47. Concerns
have been voiced that these can impair the emission reduction
potential of low-carbon technologies6,8,9. However, LCA studies of
electricity mostly focus on impacts on a per-kilowatt-hour basis
in static settings, typically neglecting technology improvements in
electricity generation technologies, as well as the effects of concur-
rent decarbonization measures in other sectors of the energy system
and the economy6,10,11.
Integrated energy–economy–climate modelling approaches
estimate cost-optimal long-term strategies to meet the emissions
constraints implied by climate targets3. Whereas direct combustion
emissions as well as CH4 from fossil fuel extraction and indirect
land-use change emissions are accounted for by many state-of-the-
art modelling systems, other indirect emissions, in particular those
related to energy required for the construction of power plants
and the production and transportation of fuels and other inputs
(defined here as embodied energy use, EEU), are not considered in
the optimization. We investigate to what extent this omission leads
to incomplete internalization of externalities.
A previous study by Hertwich et al.5 used prospective LCA to
compare similar scenarios in terms of environmental impacts,
but relied on exogenous scenarios for technology deployment,
and focused on non-climate environmental impacts to assess co-
benefits and trade-offs of climate change mitigation. Daly et al.9 and
Scott et al.12 investigated the influence of national climate policy on
domestic and non-domestic indirect GHG emissions and found
them to have a large potential for carbon leakage, as the ratio of
emissions caused domestically and overseas shifts to the latter due
to imports of goods and services. However, their analysis consid-
ered only the United Kingdom, based carbon intensities on aggre-
gate input–output relationships rather than process detail, and did
not account for policy-induced non-domestic emission reductions
in the context of coordinated international climate change mitiga-
tion efforts. Portugal-Pereira et al.13 included LCA emission coef-
ficients in an integrated assessment model (IAM) and studied the
effect of taxing indirect emissions on the electricity mix. However,
they considered only the Brazilian electricity system and used static
LCA coefficients.
In this study, we present consistent and detailed modelling of
EEU and indirect GHG emissions for global scenarios of future
electricity systems. By linking an IAM with EEU coefficients from a
prospective LCA model, we can provide a holistic and detailed per-
spective on future life-cycle greenhouse gas emissions of low-carbon
technologies and power systems in the context of a universal climate
change mitigation regime, thus closing an important research gap1416
by quantifying these emissions and their effect on the choice of low-
carbon technologies in mitigation scenarios. This study combines
results from the REMIND model17,18, which details energy use and
Understanding future emissions from low-carbon
power systems by integration of life-cycle
assessment and integrated energy modelling
Michaja Pehl 1*, Anders Arvesen 2, Florian Humpenöder1, Alexander Popp1, Edgar G. Hertwich 3
and Gunnar Luderer1*
Both fossil-fuel and non-fossil-fuel power technologies induce life-cycle greenhouse gas emissions, mainly due to their embod-
ied energy requirements for construction and operation, and upstream CH4 emissions. Here, we integrate prospective life-
cycle assessment with global integrated energy–economy–land-use–climate modelling to explore life-cycle emissions of future
low-carbon power supply systems and implications for technology choice. Future per-unit life-cycle emissions differ substan-
tially across technologies. For a climate protection scenario, we project life-cycle emissions from fossil fuel carbon capture and
sequestration plants of 78–110gCO2eq kWh1, compared with 3.5–12gCO2eq kWh1 for nuclear, wind and solar power for 2050.
Life-cycle emissions from hydropower and bioenergy are substantial ( 100gCO2eq kWh1), but highly uncertain. We find
that cumulative emissions attributable to upscaling low-carbon power other than hydropower are small compared with direct
sectoral fossil fuel emissions and the total carbon budget. Fully considering life-cycle greenhouse gas emissions has only
modest effects on the scale and structure of power production in cost-optimal mitigation scenarios.
NATURE ENERGY | VOL 2 | DECEMBER 2017 | 939–945 | www.nature.com/natureenergy 939
The Nature trademark is a registered trademark of Springer Nature Limited.
... Of interest to the modeling community, which works on designing and improving such systems, are multiple scales, from micro to macro, and the associated applications ( Fig. 1 ). For example, on the macro scale, we study energy use within the whole economy ( McCollum et al., 2018 ;Pehl et al., 2017 ), as well as continent-wide or multi-region power systems ( Galán- Martín et al., 2018 ;Tröndle et al., 2020 ). On the meso scale, we assess regional multi-sector energy systems ( Baumgärtner et al., 2021 ) or optimize regional fuel supply chains ( De-León Almaraz et al., 2014 ;Ehrenstein et al., 2020 ). ...
... Particularly the provision of low-carbon technologies, e.g. solar photovoltaic, is currently carbon-intensive -due to the electricity mix used in the production -and carbon intensities for energy generation are thus pro-jected to change significantly ( Pehl et al., 2017 ). There are thus issues around the timeliness and trustworthiness of the data. ...
Article
Energy systems analysis supports in designing and operating reliable and cost-effective energy solutions to a range of sectors, including power, heating, mobility, and industry. Notwithstanding the wellbeing and prosperity implications for current generations, it becomes increasingly clear that our current global energy system has profound impacts on our planet, potentially breaching the safe operating space for humanity. Life cycle assessments are broadly used to account for environmental aspects, however, this traditional approach may fall short of designing truly sustainable alternatives. Here, we review the concept of absolute sustainability and how it can be incorporated into energy systems modeling and optimization. Besides providing background, guidance, and perspective, we also discuss remaining challenges related to environmental and computational aspects. Although much work is still required, the absolute environmental sustainability concept can already be used in energy systems modeling and would contribute to achieving a green energy transition within planetary boundaries, ensuring wellbeing and prosperity for future generations.
... The UN SDG 7 target 2 recommends increasing the use of renewable energy as part of the strategies for reducing the carbon intensity of economic output. According to Pehl et al. (2017), solar, wind, and other renewable energy sources create an insignificant carbon footprint compared to traditional fossil fuels (oil, coal, and gas). Also, natural resource utilization in African economies has been accompanied by high energy and material intensities, as well as waste generation (UN, 2016). ...
Article
Full-text available
Financial intermediation drives resource allocation in the economy, which can influence the carbon emission intensity of economic output (CO2gdp). This study examines the impact of bank credit allocation on CO2gdp in African economies during the period 1995–2018. Two policy scenarios are empirically evaluated, taking into account the behaviour of financial intermediaries with limited financial resources for credit supply to the productive sectors. Policy Scenario I, a credit allocation system that places a greater emphasis on financing demands of government and state-owned enterprises (GSEs), has a positive (increasing) effect on CO2gdp. The alternative policy scenario, Policy Scenario II, which places a greater emphasis on financing demands of private sector entities (PSUs), has a negative (decreasing) effect on CO2gdp with stronger impact in the more carbon-intensive economies. In addition, renewable energy consumption makes greater contribution to reducing CO2gdp under Policy Scenario II. By implication, more credit supply to the PSUs strengthens the link between resource allocation and economic efficiency, resulting in the creation of greener economic output. Thus, the development of financial intermediation could play a role in helping African economies avoid carbon-intensive path to economic growth.
... Wind power plants contribute in reducing the greenhouse gas (GHG) emissions into the atmosphere (Pehl et al., 2017). Wind power plant emits approximately 6.3 g CO 2eq /kWh on average (Wang and Sun, 2012). ...
Article
Full-text available
The objective of this paper is to assess the wind energy resource in the central region of Thailand for wind power generation, along with analyzing the economic feasibility and appropriate feed-in-tariff (FIT) of a proposed 15 MW wind power plant. A microscale wind resource map was created using measured wind data, a computational fluid dynamics wind flow modeling and high-resolution topography databases. Five utility-scale wind turbine generators (WTG), with hub heights ranging from 80 to 120 m above ground level (agl), were used to estimate the annual energy production (AEP). Considering the available wind resource, the most appropriate WTG was identified, and a wind power plant layout was achieved to maximize the AEP as well as minimizing the wake losses. The maximum net AEP, capacity factor (CF), %AEP improvement, %wake loss reduction, and CO2eq emission avoidance were also analyzed. Several financial indices and the levelized cost of energy (LCOE) were analyzed on the basis of a cost–benefit analysis. The economic sensitivity of the costs was used to determine the most appropriate FIT for the project. Results reveal that the mean annual wind speed at 120 m agl in the central region of Thailand reaches 5.8 m/s. The net AEP, CF, %AEP improvement, %wake loss, and CO2eq emission avoidance for a 15 MW wind power plant are estimated at 41 GWh/year, 30%, 6%, 10% and 231 ktonnes CO2eq/year, respectively. The LCOE for a base case scenario is estimated at 0.093 US$/kWh, with a FIT of 0.195 US$/kWh. Finally, the results of this work can be used as guidelines for wind power project development in the central region of Thailand and in other regions of the world where the wind resource is low to moderate under current existing WTG technology.
... Generally, these scenarios are based on population levels and rely on technical solutions such as renewable energy and negative emission technologies for carbon storage (Langsdorf, 2011;Commission, 2012;Benndorf et al., 2014;IEA, 2019). This has sparked a wide range of empirical studies globally on required materials and life cycle assessments of renewable electricity (Kleijn and Voet, 2010;Zuser and Rechberger, 2011;Bustamante and Gaustad, 2014;Hayes and McCullough, 2018;Giurco et al., 2019;Hertwich et al., 2019), the embodied energy and emissions of renewable power technologies (Daly et al., 2015;Gibon et al., 2015;Hertwich et al., 2015;Scott et al., 2016;Pehl et al., 2017) and the demand for critical materials (Benndorf et al., 2014;Viebahnn et al., 2015). ...
Article
Full-text available
Conceptual and empirical work on socio-technical transitions, such as energy transition strategies, often disregard the limited planetary capacity of available land. This paper explores the trade-offs between energy transition pathways and land use in different geographical contexts. We draw on empirical data from three contrasting case-study countries: Vietnam, New Zealand and Finland. An enhanced calculation model based on the Ecological Footprint method is used to assess land consumption for different transition pathways towards a low-carbon society. More specifically, the spatial impacts of the energy sector and its carbon dioxide emissions are assessed for different timeframes, namely the past, the present and future scenarios (by 2030 and the 2040s) based on the national energy strategies of these countries. The results show a lack of consideration in these strategies of the land area required to ensure an adequate implementation for each national territory. Hence, we argue for an acknowledgement of spatial factors, namely land availability and the geographical context, in theories and policy strategies on socio-technical transitions.
Article
Shares of renewable energy are rapidly increasing in many countries due to emissions policies and declining prices. Investment planning for future renewable deployment often relies on optimization models. Memory usage and solving time restrict these models, leading to tradeoffs in the treatment of temporal complexity, spatial complexity, and physical representation. A common approach is to reduce the temporal complexity of models. Reducing temporal complexity is often achieved by using time-series aggregating and modelling representative periods instead of a complete time series. But the impacts of such approaches are still poorly understood, especially for very low emissions systems with high shares of variable renewable energies. In this paper, the impacts of using time-series aggregation methods on optimal system design are investigated. It is found that the negative impact of time-series aggregation increases for lower emissions. It is also identified that modelling wind time-series data with representative days introduces this negative impact primarily and that representing wind time-series data with representative days decreases the reliability of supply defined as unserved load (0.05%–18.0%), introduces a bias in installed capacity (−31.15% to +12.2%), and underestimates total system cost (2.5%–44.9%). These effects are largest in cases with the strongest emission constraints. When designing low emissions systems with a high share of variable renewable energies, it is recommended not to use time-series aggregation to create representative days for wind power output. This paper contributes an Open Source analysis framework containing time-series aggregation and capacity expansion that should be applied when testing future time-series aggregation methods to reduce the identified negative impacts.
Conference Paper
In the last few decades, the topic of sustainability has become more and more widespread, which is logically explained by its relevance, given the environmental conditions and challenges posed by climate change. However, there are many contradictions and controversies regarding sustainable development. Therefore, the purpose of this study is to try to understand the true essence of sustainability as a concept. As a subject of research, no less relevant, one might say, even a “fashionable” industry today, the renewable energy was chosen. It is on the example of the latter that we try to explore the “reality” and the “possibility” of sustainable development.
Article
Full-text available
Utility wood pellets (wood pellets) are a densified biomass fuel that can generate electricity or heating when burned. Production, consumption, and trade of wood pellets have grown substantially since the late 2000s in a small number of countries. The locus of consumption growth is industrial power plants where wood pellets are frequently used for co-firing with, or replacement of, coal. The catalytic factors for the robust wood pellet expansion have been European Union (EU) climate change policies and incentives, particularly designating the product as a 'renewable energy,' assessing their carbon emissions as zero, and providing financial support. The United States, with its sizeable forests and timber plantations, reacted by intensifying wood pellet production for export, primarily to the United Kingdom and several EU member states. In 2021, U.S. wood pellet exports reached $1 billion for the first time. Wood pellet consumption is also rising in Asia with South Korea and Japan, driven by their own climate change policies, incentivizing rapid recent growth in imports. This paper examines the rise of wood pellets as an alternative energy source and traded commodity in the era of climate change.
Book
Full-text available
Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy. Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.
Article
Ultra-thin two-dimensional (2D) silicon nanosheets (SiNSs) have potential applications in electronic, energy storage, and energy conversion devices owing to their unique properties. However, high-yield and large-scale manufacturing of high-quality ultra-thin 2D SiNSs remains a great challenge. This report describes a simple, high-yield (>98%), and large-scale method for preparing ultra-thin 2D SiNSs. The developed approach improves the yield of SiNSs (thickness < 5 nm) by controlling the interaction force between the Si ingot and the abrasive grains during the diamond wire grinding process. The ultra-thin SiNSs deliver enhanced tap density and a limited variable solid electrolyte interphase growth interface. A dynamic chemical vapor deposition technique is carried out to increase the uniformity of the carbon coating on the ultra-thin SiNSs. Lithium-ion batteries employing SiNS-carbon composite anodes exhibit ultra-high initial Coulombic efficiency (88.1%) at a high Si content (79%). The full battery constructed with the fabricated SiNS-carbon composite anode and a commercial LiFePO4 cathode exhibits strong stability (1 C over 600 cycles with a capacity retention rate >80%). The results presented herein confirm the significant potential applicability of the developed method for synthesizing ultra-thin SiNSs with carbon coatings.
Article
Full-text available
Most prior studies have found that substituting biofuels for gasoline will reduce greenhouse gases because biofuels sequester carbon through the growth of the feedstock. These analyses have failed to count the carbon emissions that occur as farmers worldwide respond to higher prices and convert forest and grassland to new cropland to replace the grain (or cropland) diverted to biofuels. By using a worldwide agricultural model to estimate emissions from land-use change, we found that corn-based ethanol, instead of producing a 20% savings, nearly doubles greenhouse emissions over 30 years and increases greenhouse gases for 167 years. Biofuels from switchgrass, if grown on U.S. corn lands, increase emissions by 50%. This result raises concerns about large biofuel mandates and highlights the value of using waste products.
Article
Full-text available
The greenhouse gases (GHG) emissions from land-use change are of particular concern for land-based biofuels. Emissions avoided by substituting fossil fuels with biofuels may be offset by emissions from direct and indirect land-use changes (LUC). There is an urgent need to investigate what impact land-use change emissions may have on the expansion of bioenergy and biofuels, in the context of EU mitigation policies. This paper focuses on Ireland, which faces a number of challenges in delivering its renewable energy and GHG reduction targets. The Irish TIMES energy systems model was used to assess the impact of a range of land-use change emissions’ levels on the evolution of Ireland’s low-carbon energy system. A reference scenario was developed where LUC is ignored and Ireland achieves a least-cost low-carbon energy system by 2050. If high indirect land-use change (ILUC) emissions are included, this results in a decrease by 30 % in bioenergy and a 68 % increase in marginal abatement costs by 2050. Hydrogen is used instead of bioenergy in the freight sector in this scenario, while private cars are fuelled by renewable electricity. If GHG emissions from ILUC were considered less severe, indigenous grass biomethane becomes the key biofuel representing 31 % of total bioenergy consumption. This is in line with recent research in Ireland of the key role that grass biomethane can play. The full article is available from: http://rdcu.be/kuBg
Article
Full-text available
Rapid cuts in greenhouse gas emissions require an almost complete transformation of the energy system to low carbon energy sources. Little consideration has been given to the potential adverse carbon consequences associated with the technology transition. This paper considers the embodied emissions that will occur to replace the UK’s fossil fuel-reliant energy supply with low carbon sources. The analysis generates a number of representative scenarios where emissions embodied in energy systems are integrated within current national climate and energy policy objectives. The embodied emissions associated with a new low carbon energy system are lower than the emissions reduction associated with the low carbon energy sources, confirming that there is a carbon return on investment. However, even if the UK reaches its 2050 territorial climate target, it is estimated that by 2050 an additional 200 Mt CO2 emissions are generated overseas (compared to 128 Mt generated within the UK) in the production of imported fuels and infrastructure components. The cost-optimal model results suggest that more electrification would need to occur, supported by nuclear energy, mainly in replacement of natural gas to mitigate these emissions. However, due to a number of deployment barriers, other policy interventions along the energy supply chain are likely needed, which are discussed alongside the model results. There could be more emphasis on an absolute reduction in energy demand to reduce the scale of change needed in supplying energy; new business models oriented towards performance and not sales; and existing trade schemes and international effort-sharing frameworks could be extended.
Article
The fields of life cycle assessment (LCA) and integrated assessment (IA) modelling today have similar interests in assessing macro-level transformation pathways with a broad view of environmental concerns. Prevailing IA models lack a life cycle perspective, while LCA has traditionally been static- and micro-oriented. We develop a general method for deriving coefficients from detailed, bottom-up LCA suitable for application in IA models, thus allowing IA analysts to explore the life cycle impacts of technology and scenario alternatives. The method decomposes LCA coefficients into life cycle phases and energy carrier use by industries, thus facilitating attribution of life cycle effects to appropriate years, and consistent and comprehensive use of IA model-specific scenario data when the LCA coefficients are applied in IA scenario modelling. We demonstrate the application of the method for global electricity supply to 2050 and provide numerical results (as supplementary material) for future use by IA analysts.
Article
In this paper we study the impact of alternative metrics on short- and long-term multi-gas emission reduction strategies and the associated global and regional economic costs and emissions budgets. We compare global warming potentials with three different time horizons (20, 100, 500 years), global temperature change potential and global cost potentials with and without temperature overshoot. We find that the choice of metric has a relatively small impact on the CO 2 budget compatible with the 2° target and therefore on global costs. However it substantially influences mid-term emission levels of CH 4 , which may either rise or decline in the next decades as compared to today’s levels. Though CO 2 budgets are not affected much, we find changes in CO 2 prices which substantially affect regional costs. Lower CO 2 prices lead to more fossil fuel use and therefore higher resource prices on the global market. This increases profits of fossil-fuel exporters. Due to the different weights of non-CO 2 emissions associated with different metrics, there are large differences in nominal CO 2 equivalent budgets, which do not necessarily imply large differences in the budgets of the single gases. This may induce large shifts in emission permit trade, especially in regions where agriculture with its high associated CH 4 emissions plays an important role. Furthermore it makes it important to determine CO 2 equivalence budgets with respect to the chosen metric. Our results suggest that for limiting warming to 2 °C in 2100, the currently used GWP100 performs well in terms of global mitigation costs despite its conceptual simplicity. Copyright Springer Science+Business Media Dordrecht 2014
Article
Understanding which energy future configurations provide publicly acceptable levels of energy security, affordability, and environmental protection is critical for institutional decision-making. However, little is known about how scenarios influence energy preferences. Here we present nationally representative UK data on public preferences for energy futures using the my2050 scenario-building tool that encourages engagement with the holistic complexities of system change. Engagement with the tool strengthened existing preferences for renewable energy and intentions to take personal action. Importantly, patterns of energy preferences were influenced by exemplar scenarios, which served as reference points that anchored choices. Carbon capture and storage, nuclear power, biofuels, and changes to heating and travel were particularly impacted by scenarios indicating uncertainty and ambivalence regarding these options. Scenarios (and scenario-building tools) are valuable for engaging citizens about future energy systems. However, care is required in their design and interpretation to reach robust conclusions about underlying preferences and acceptance.
Article
Technology-rich integrated assessment models (IAMs) address possible technology mixes and future costs of climate change mitigation by generating scenarios for the future industrial system. Industrial ecology (IE) focuses on the empirical analysis of this system. We conduct an in-depth review of five major IAMs from an IE perspective and reveal differences between the two fields regarding the modelling of linkages in the industrial system, focussing on AIM/CGE, GCAM, IMAGE, MESSAGE, and REMIND. IAMs ignore material cycles and recycling, incoherently describe the life-cycle impacts of technology, and miss linkages regarding buildings and infrastructure. Adding IE system linkages to IAMs adds new constraints and allows for studying new mitigation options, both of which may lead to more robust and policy-relevant mitigation scenarios. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
Article
This work evaluates implications of incorporating LCA-GHG (life cycle assessment of GHG emissions) into the optimisation of the power generation mix of Brazil through 2050, under baseline and low-carbon scenarios. Furthermore, this work assesses the impacts of enacting a tax on LCA-GHG emissions as a strategy to mitigate climate change. To this end, a model that integrates regional life cycle data with optimised energy scenarios was developed using the MESSAGE-Brazil integrated model. Following a baseline trend, the power sector in Brazil would increasingly rely on conventional coal technologies. GHG emissions from the power sector in 2050 are expected to increase 15-fold. When enacting a tax on direct-carbon emissions, advanced coal and onshore wind technologies become competitive. GHG emissions peak at 2025 and decrease afterwards, reaching an emission level 40% lower in 2050 than that of 2010. However, if impacts were evaluated through the entire life cycle of power supply systems, LCA-GHG emissions would be 50% higher in 2050 than in 2010. This is due to loads associated with the construction of plant infrastructures and extraction and processing of fossil fuel resources. Thus, taxes might not be as effective in tackling GHG emissions as shown by past studies, if they are only applied to direct emissions.
Article
Land-use change, mainly the conversion of tropical forests to agricultural land, is a massive source of carbon emissions and contributes substantially to global warming. Therefore, mechanisms that aim to reduce carbon emissions from deforestation are widely discussed. A central challenge is the avoidance of international carbon leakage if forest conservation is not implemented globally. Here, we show that forest conservation schemes, even if implemented globally, could lead to another type of carbon leakage by driving cropland expansion in non-forested areas that are not subject to forest conservation schemes (non-forest leakage). These areas have a smaller, but still considerable potential to store carbon. We show that a global forest policy could reduce carbon emissions by 77 Gt CO 2, but would still allow for decreases in carbon stocks of non-forest land by 96 Gt CO 2 until 2100 due to non-forest leakage effects. Furthermore, abandonment of agricultural land and associated carbon uptake through vegetation regrowth is hampered. Effective mitigation measures thus require financing structures and conservation investments that cover the full range of carbon-rich ecosystems. However, our analysis indicates that greater agricultural productivity increases would be needed to compensate for such restrictions on agricultural expansion.