Socioeconomic factors and future challenges of the goal of limiting the increase in global average temperature to 1.5 °C

ABSTRACT The Paris Agreement has confirmed that the ultimate climate policy goal is to hold the increase in the global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the increase to 1.5 °C. Moving the goal from 2 °C to 1.5 °C calls for much more concerted effort, and presents greater challenges and costs. This study uses an Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) to evaluate the role of socioeconomic factors (e.g. technological cost and energy demand assumptions) in changing mitigation costs and achieving the 1.5 °C and 2 °C goals, and to identify the channels through which socioeconomic factors affect mitigation costs. Four families of socioeconomic factors were examined, namely low-carbon energy-supply technologies, end-use energy-efficiency improvements, lifestyle changes and biomass-technology promotion (technology cost reduction and social acceptance promotion). The results show that technological improvement in low-carbon energy-supply technologies is the most important factor in reducing mitigation costs. Moreover, under the constraints of the 1.5 °C goal, the relative effectiveness of other socioeconomic factors, such as energy efficiency improvement, lifestyle changes and biomass-related technology promotion, becomes more important in decreasing mitigation cost in the 1.5 °C scenarios than in the 2 °C scenarios.

[1]  Emanuele Borgonovo,et al.  Sensitivity of projected long-term CO2 emissions across the Shared Socioeconomic Pathways , 2017 .

[2]  K. Calvin,et al.  A multi-model assessment of the co-benefits of climate mitigation for global air quality , 2016 .

[3]  Karen C. Seto,et al.  Beyond Technology: Demand-Side Solutions for Climate Change Mitigation , 2016 .

[4]  Tomoko Hasegawa,et al.  Implication of Paris Agreement in the context of long-term climate mitigation goals , 2016, SpringerPlus.

[5]  T. Masui,et al.  Bridging greenhouse gas emissions and renewable energy deployment target: Comparative assessment of China and India , 2016 .

[6]  T. Yokohata,et al.  Economic implications of climate change impacts on human health through undernourishment , 2016, Climatic Change.

[7]  F. Creutzig,et al.  Energy and environment. Transport: A roadblock to climate change mitigation? , 2015, Science.

[8]  Kenichi Wada,et al.  A short note on integrated assessment modeling approaches: Rejoinder to the review of "Making or breaking climate targets - The AMPERE study on staged accession scenarios for climate policy" , 2015 .

[9]  Tomoko Hasegawa,et al.  Consequence of climate mitigation on the risk of hunger. , 2015, Environmental science & technology.

[10]  G. Luderer,et al.  Energy system transformations for limiting end-of-century warming to below 1.5 °C , 2015 .

[11]  Emanuele Borgonovo,et al.  Sensitivity to energy technology costs: a multi-model comparison analysis. , 2015 .

[12]  S. Mima,et al.  The Costs of Climate Change for the European Energy System, an Assessment with the POLES Model , 2015, Environmental Modeling & Assessment.

[13]  Tomoko Hasegawa,et al.  The effectiveness of energy service demand reduction: A scenario analysis of global climate change mitigation , 2014 .

[14]  Kiyoshi Takahashi,et al.  Land use representation in a global CGE model for long-term simulation: CET vs. logit functions , 2014, Food Security.

[15]  Shinichiro Fujimori,et al.  Development of a global computable general equilibrium model coupled with detailed energy end-use technology , 2014 .

[16]  Keywan Riahi,et al.  Transport electrification: A key element for energy system transformation and climate stabilization , 2014, Climatic Change.

[17]  Jessica Strefler,et al.  The value of bioenergy in low stabilization scenarios: an assessment using REMIND-MAgPIE , 2014, Climatic Change.

[18]  Elmar Kriegler,et al.  Land-use transition for bioenergy and climate stabilization: model comparison of drivers, impacts and interactions with other land use based mitigation options , 2014, Climatic Change.

[19]  John P. Weyant,et al.  Energy efficiency potentials for global climate change mitigation , 2014, Climatic Change.

[20]  Toshihiko Masui,et al.  Halving global GHG emissions by 2050 without depending on nuclear and CCS , 2014, Climatic Change.

[21]  K. Calvin,et al.  Bioenergy in energy transformation and climate management , 2014, Climatic Change.

[22]  P. Shukla,et al.  Role of energy efficiency in climate change mitigation policy for India: assessment of co-benefits and opportunities within an integrated assessment modeling framework , 2014, Climatic Change.

[23]  M. Sugiyama,et al.  Role of end-use technologies in long-term GHG reduction scenarios developed with the BET model , 2014, Climatic Change.

[24]  John P. Weyant,et al.  Preface and introduction to EMF 27 , 2014, Climatic Change.

[25]  A. Grubler,et al.  Technology portfolios: Modelling technological uncertainty and innovation risks , 2014 .

[26]  K. Riahi,et al.  Energy security under de-carbonization scenarios: An assessment framework and evaluation under different technology and policy choices , 2014 .

[27]  Dieter Gerten,et al.  The economic potential of bioenergy for climate change mitigation with special attention given to implications for the land system , 2011 .

[28]  T. Wigley,et al.  Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration , 2011 .

[29]  H. Lotze-Campen,et al.  Food consumption, diet shifts and associated non-CO2 greenhouse gases from agricultural production , 2010 .

[30]  K. Lindgren,et al.  The feasibility of low CO2 concentration targets and the role of bio-energy with carbon capture and storage (BECCS) , 2010 .

[31]  Bas Eickhout,et al.  Climate benefits of changing diet , 2009 .

[32]  P. Heuberger,et al.  Conditional probabilistic estimates of 21st century greenhouse gas emissions based on the storylines of the IPCC-SRES scenarios , 2008 .

[33]  Priyadarshi R. Shukla,et al.  Low-carbon society scenarios for India , 2008 .

[34]  Bas Eickhout,et al.  Stabilizing greenhouse gas concentrations at low levels: an assessment of reduction strategies and costs , 2007 .

[35]  K. Riahi,et al.  Importance of Technological Change and Spillovers in Long-Term Climate Policy , 2006 .

[36]  Jean Charles Hourcade,et al.  Endogenous Structural Change and Climate Targets Modeling Experiments with Imaclim-R , 2006 .

[37]  QK Ahmad,et al.  Climate change 1995. Economic and social dimensions of climate change. Contribution of working group III to the second assessment report of the intergovernmental panel on climate change , 1997 .

[38]  Paul S. Armington.  A Theory of Demand for Products Distinguished by Place of Production (Une théorie de la demande de produits différenciés d'après leur origine) (Una teoría de la demanda de productos distinguiéndolos según el lugar de producción) , 1969 .

[39]  J. Eom,et al.  The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview , 2017 .

[40]  M. Kainuma,et al.  SSP3: AIM implementation of Shared Socioeconomic Pathways , 2017 .

[41]  P. Kyle,et al.  Land-use futures in the shared socio-economic pathways , 2017 .

[42]  M. Strubegger,et al.  Shared Socio-Economic Pathways of the Energy Sector – Quantifying the Narratives , 2017 .

[43]  K. Riahi,et al.  The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century , 2017 .

[44]  Shinichiro Fujimori,et al.  Key factors affecting long-term penetration of global onshore wind energy integrating top-down and bottom-up approaches , 2016 .

[45]  Detlef P. van Vuuren,et al.  Exploring the implications of lifestyle change in 2 °C mitigation scenarios using the IMAGE integrated assessment model , 2016 .

[46]  O. Edelenbosch,et al.  Deep decarbonisation towards 1.5°C-2°C stabilisation , 2016 .

[47]  Charlie Wilson,et al.  Diagnostic indicators for integrated assessment models of climate policy , 2015 .

[48]  H. Turton,et al.  Induced technological change in moderate and fragmented climate change mitigation regimes , 2015 .

[49]  Alban Kitous,et al.  Mitigation strategies and energy technology learning: an assessment with the POLES model , 2015 .

[50]  M. Hamdi-Chérif,et al.  Energy efficiency policies and the timing of action: An assessment of climate mitigation costs , 2015 .

[51]  N. Vohra,et al.  Role of energy efficiency in climate change mitigation policy for India: Assessment of co-benefits and opportunities within an integrated assessment modeling framework , 2014 .

[52]  Keywan Riahi,et al.  A new scenario framework for climate change research: the concept of shared socioeconomic pathways , 2013, Climatic Change.

[53]  P. Mahadevan,et al.  An overview , 2007, Journal of Biosciences.

[54]  S. Robinson,et al.  A standard computable general equilibrium (CGE) model in GAMS , 2002 .

[55]  J. Edmonds,et al.  A review of mitigation cost studies , 1996 .