Less than 2°C? An Economic-Environmental Evaluation of the Paris Agreement

1 Less than 2oC? An economic-environmental evaluation of the Paris Agreement Jaime Nietoab*, Óscar Carpinteroab, Luis J. Miguelb a Department of Applied Economics, Av. Valle Esgueva 6, University of Valladolid, Spain. b Research Group on Energy, Economy and System Dynamics, Paseo del Cauce, s/n, University of Valladolid. Abstract The literature dedicated to the analysis of the different climate agreements has usually focused on the effectiveness of the aims for emissions in the light of the advance in climate change. This article quantifies the variation in emissions that the Intended Nationally Determined Contributions (INDCs) will entail and their financial allocation and policies country-by-country and regionally. The objective is evaluating the Paris Agreement feasibility regarding the INDCs and, economic and environmental constraints. The criteria through which the 161 INDCs are analysed are as follows: i/ socio-economic impact of the transition; ii/ focus on energy management; iii/ substitution of non-renewable sources; iv/ the role of technology; v/ equality of the transition; vi/ compliance with emission reductions. The results obtained show that the Paris Agreement excessively relies on external financial support (41.4%). Moreover, its unilateralist approach, the socio-economic and biophysical constraints could be the underlying cause of the ineffectiveness of the 2ºC objective. This way, each country would emit an average of 37.8% more than in the years 2005-2015. When this is weighted, the figure would be a 19.3% increase, due mainly to the increases in China and India. These figures would lead the temperatures up to 3º-4ºC. Keywords: Climate change, INDCs, Climate policy, Climate finance. *Corresponding author. E-mail address: jaime.[email protected] (Jaime Nieto). 2 1. Introduction. The consequences of climate change induced by human activity are a growing concern for the international community (IPCC, 2014; UNEP, 2011; Melillo et al., 2014). Evident effects such as extreme meteorological phenomena, rising temperatures and rising sea levels show the rapid climatic adaptation of natural ecosystems. The rapid increase in these impacts and the fact that abrupt changes could arise leads to the conclusion that the cost of transferring the responsibility for putting it right to the coming generations becomes ever higher. In this sense, the IPCC (2014) has warned that if, by 2050, we have not managed to reduce the level of emissions with respect to 2010 by between 25% and 72%, then maintaining the rise in world temperatures to below 2oC with respect to preindustrial levels will be “more improbable than probable”. Besides the most visible consequences today, if the temperatures rose by more than 3oC-4oC, humanity would face a scenario of massive extinction of species, entailing risks for human health and severe restrictions on access to food and water, so vital for survival (IPCC, 2014). Achieving this goal involves phasing out fossil fuels whereby around 82% of the current reserves of coal, 49% of natural gas reserves and 33% of the oil reserves should remain underground in order to avoid an increase in temperatures of more than 2oC (McGlade & Ekins, 2015). Regarding these concerns, in December 2015, the 21st Conference of Parties (COP21) was celebrated, made up of 188 countries, and whose most important result was the Paris Agreement (UN, 2015) and the collection of Intended Nationally Determined Contributions (INDCs) submitted by each of the participating countries. After de burial of the Kyoto Protocol, the current agreement is an unilateral vision in which the players establish their own voluntary objectives (Spash, 2015) through the INDCs. Although the agreement indicates that the main priority is to “hold the increase in the global average temperature to well below 2oC above preindustrial levels”, during the COP21, the participants were sufficiently optimistic as to speak openly of 1.5oC. Not only this, but in spite of the fact that they incorporated such equality criteria as the obligation of the Developed Countries (DC) to a greater reduction in emissions and the channelling of financial resources to the Least Developed Countries (LDC), the COP21 succeeded in involving some countries with medium incomes in these differentiated efforts (Viola, 2016). 3 In response to global concerns of these issues, a widening literature on sustainability transitions has emerged in recent years (Markaard, Raven, and Truffer 2012). Literature on climate summits mostly evaluates whether they comply with emissions limits or not (den Elzen et al., 2011; UNEP, 2010; Kartha & Eriksson, 2011; Höhne et al., 2012). Considering COP21 and the Paris Agreement (2015), main contributions are related to its impacts in energy technologies evolution (Peters 2017; Lacal Arantegui and Jäger-Waldau 2017) or evaluate possible transition pathways under its contexts in different regions (Liobikienė and Butkus 2017; Van de Graaf 2017; Gao 2016). Some works, conversely, points out difficulties to accomplish the COP21 objectives according to geopolitical and governance limits from a general perspective of the Paris Agreement (Spash, 2015; Viola, 2016). Moreover, an increasing number of governments, municipalities and NGOs are creating its own low carbon transitions plans plans according to their own criteria, or those established in the aforementioned climate summits. Thus, on the basis of Wiseman et al. (2013), Nieto & Carpintero (2016) deal with a more in-depth analysis of 19 low-carbon transition plans from government sources and other dependent agencies, NGOs and research centres. In this article, Paris Agreement is evaluated on the light of biophysical, technological and economic limits, throughout a systematic analysis of each of the 161 INDCs submitted by the 188 countries in COP21. Thus, the aim of this article is to put these INDCs under the same microscope that analyzed some previous plans (Nieto & Carpintero, 2016), situating the focus on the socioeconomic impacts, international equality, technology, energy and emissions. This analysis will allow us to evaluate the feasability of the Paris Agreement policies in complying with its own objectives through the national commitments (INDCs). In the same way, we will evaluate the main limitations of the imposed governance and finance framework. In order to achieve these aims, a systematic analysis of the policies, the emission reduction commitments and the funding needs for implanting INDCs has been carried out. The article is structured as follows: Section two describes the methodological process used to give homogeneity to the data offered by the INDCs. Section three sets out the main results of the exhaustive analysis of these INDCs. Section four confronts the results extracted from INDCs with the biophysical restrictions and the literature. Finally, Section five summarizes the article’s main conclusions. 2. Methodology. 4 The flexibility of the Paris Agreement has led to a lack of systematic presentation of the INDCs. Therefore, this paper proposes a methology to homogenize data and categorize the information. For more detailed information, consult Annex A, as well as the repository of INDCs1. We have examined a total of 161 INDCs representing 188 countries that account for 97.8% of the world’s emissions. In order to achieve the aims of this article, we have paid special attention to the policies of mitigation as opposed to those of adaptation because of their economic (Buchner et al., 2015) and environmental importance. We have noted (as far as possible) the data concerning the objectives for reducing sectoral and global emissions, the policies for achieving the said objectives and their funding, with the greatest possible breakdown. We have also studied the proposed financial mechanisms and the nature of the agents who would lead the transition. We have grouped the different countries with respect to their level of income in accordance with the World Bank’s (WB) classification, establishing a distinct group for the 12 most contaminating countries on the planet (Top 12) in 2014 (72.2% of the total emissions) because of their relevance for climate policies. With reference to emissions, the INDCs have both unconditional and conditional objectives. The former would be carried out exclusively with domestic resources, while the latter would be conditional on receiving outside assistance. In general, the INDCs presented some problems that made the analysis more difficult; such as the discrepancies between the year of reference and that of the horizon. To resolve this issue, we have discarded those INDCs that do not have the year 2030 as their time horizon or the reference year outside the range 20052015. This reference year has been chosen because of two reasons. Firstly, EU used 2005 as one of the reference years (along with 1990 and 2030) in its Communication titled "A roadmap for moving to a competitive low carbon economy in 2050". Secondly, most of the INDCs are within this time range, so it was reasonable to use it. Besides, a differential analysis has been carried out of the 12 most contaminating countries (Top12), for which we were able to establish a common reference year of 2005. On the other hand, the reduction objectives are presented in different ways: i/ As a partial and/or sectoral objective: for instance, a proportion of renewable sources in the energy mix or objectives that are merely relative to one sector of the economy. These have not been considered in the calculation of emissions reductions. 1 http://www4.unfccc.int/submissions/INDC/Submission%20Pages/submissions.aspx 5 ii/ In GHG emissions intensity (CO2eq/GDP). To calculate the net variation in emissions, we proceed as set out in the methodological annex. iii/ As emissions reductions with respect to a base year. The only countries obliged to do so are those in Annex I2 and, with some exceptions, the only ones who do so in this way. No additional calculation is needed beyond establishing the base range and/or horizon year. iv/ As emissions reductions with respect to a trend scenario (business as usual). This is the most common, used by all the countries not in Annex 1, except Brazil3. To calculate the variation in absolute terms with respect to the base range, we proceed as detailed in the methodological annex. Taking a conservative stance, we have considered that the trend and the real variation in emissions is the same for the Annex I countries, assuming that they will carry out all the promised policies and that they will, indeed, reach the appointed goals. In addition, we have calculated the weighted emissions with respect to each country’s contribution to global emissions in 2013, the last year for which reliable, homogeneous data exist through the Emission Database for Global Atmospheric Research (EDGAR) of the European Commission. On the other hand, the necessary funding for each plan has been broken down into mitigation, adaptation and other expenses. The INDCs provide figures in dollars (without specifying any basis) to be expended from 2020 to 2030. Financial effort is measured as the share of financial funding allocated by the INDC over GDP (2010 constant dollars at market prices). External funding and its proportion over total funding has been evaluated as well. Similarly, we have obtained the amount of funding required per unit percent of emissions reduction. This information has been obtained directly from the data facilitated by the INDCs. When not provided, it has been made the assumption that the share of external funding equals the proportion of conditional emissions reduction over total emissions reduction. Finally, it has been summarized the main policies with respect to the different sectors of each country, as well as a summary table of the main policies to which each country is committed. The policies are broken down according to the Directives of the IPCC for the national inventories of greenhouse gases (1996). However, the breakdown of the energy sector has been used due to its strategic nature for some INDCs. 2 Industrialized countries that were members of the OECD (Organisation for Economic Cooperation and Development) in 1992, plus countries with economies in transition (the EIT Parties), including the Russian Federation, the Baltic States, and several Central and Eastern European States. 3 Unless explicitly mentioned alternatively, when a particular country is mentioned, the reference is its INDC, which can be consulted in the UNFCC repository, as explained in footnote 1. 6 3. Towards a new landscape: the INDCs in detail. An exhaustive analysis of all the INDCs has been carried out with respect to four criteria: i/ the quality of the information provided; ii/ the proposed policies; iii/ the funding needed to carry them out and, finally; iv/ the estimated reduction in emissions. 3.1. Quality of information The greatest difficulties involved in carrying out this research concerned the lack of homogeneity in the data. The INDCs come from different sources, the quantity and quality of the information is highly variable and even contains errors. The INDCs have been divided with respect to the quality of the general and funding information offered, according to the criteria of Table 1. Table 1. Information criteria General information Financial information Medium Quality Low or none emissions information and/or low or none policies Sufficient emissions information and/or sectoral disaggregated policies information. No financial information. Financial information in total amounts. Low Quality Good emissions information and highly deep disaggregated policies information. Financial information disaggregated by area (mitigation/adaptation) and/or by policies/sectors. High Quality Source: Own compilation on the basis of the INDCs submitted to COP21. According to what can be seen in Table 7, the quality of the information follows a trajectory which is inversely proportional to the level of income of the country collecting the said information. Only 18.5% of the plans can be considered as offering general information of high quality, and only 12.7% as far as finance is concerned. In addition, only the plans from countries with medium-low and low incomes offer a higher than average quality in both categories. These correspond mostly to small island states and African countries. For the former, climate change supposes the greatest possible threat (being submerged under the sea), while the latter see in the Paris Agreement an opportunity for sustainable development aided externally. The low quality of financial information provided by the OECD countries does not provide any data at all about the funding of their policies (two thirds of the plans have been classified as of “low quality”). The lack of any common standards or adequate auditing of the information 7 received means that the objectives are difficult to compare or measure, which in turn makes any effective control over compliance almost impossible. 3.2. Mitigation policies: energy, industry, agriculture, waste and LULUCF. The different policies under review in the INDCs respond to the following sectoral structure: i/ energy - electricity generation, transport and housing -; ii/ industrial processes; iii/ use of solvents and other products, iv/ agriculture, v/ change in land use and forestry (LULUCF) and, vi/ waste. Table 2 summarizes the principal policies by sectors and each one is assigned a code to facilitate understanding and clarity in the other summary tables. Table 2. Overview of main policies in the INDCs 8 G1 G2 G3 G4 G5 G6 G7 G8 R1 R2 R3 R4 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 I1 I2 I3 I4 I5 I6 I7 I8 I9 W1 W2 W3 W4 W5 A1 A2 A3 A4 A5 L1 SECTOR SUBSECTOR POLICY ACTION CODE Rural electrification. Substitute charcoal by electricity/Electrification Process efficiency. Best thermoelectric generation (coal and gas). Combined cycle power stations. Switch to natural gas. Decentralization of energy Off and on-grid roof solar panels, solar thermal and Transition to renwable and cleaner technologies. Renewable deployment: solar, wind, hydro. RESIDENTIAL Consumption efficiency. Enhanced technologies for heating and cooking Reconstruction, construction or improvement of Efficient technologies. ELECTRICITY GENERATION Best lighting technologies. Enhance buildings efficiency/solar thermal installation. Social awarness. Reduction Absolute reduction in energy consumption Spatial and urban planning. Improvement of road system. Promotion of electric and hybrid vehicle. Structural change. Mass public transport. Intermodality and switch to an efficient transport Fuels substitution. Carbon tax (emissions). Promotion and research on biofuels. Measures oriented to industrial ecology. Sectoral. Reduce emissions in cement industry. Non motorized transport. SECTOR POLICY ACTION INDUSTRY Process efficiency. Improve the overall efficiency of industry. Energy cogeneration. TRANSPORT Transport efficiency Encouraging acquisition of hybrid and efficient vehicles. Discourage acquisition of inefficient vehicles. ENERGY WASTE Circular economy and reduction. Reduce, Reuse, Recycle. Transform waste to energy. Structural change. Modernization and switch to an enhanced value added Tertiarisation (China). Emissions reduction. Carbon capture and storage and Carbon capture and use. Sectoral. Social awarness (minor support). Management. Improve landfill management,consctruct new ones and promotion of compost. Extractive industry. Reduce flaring and venting. Improvements in processes, efficiency and distribution. CODE L2 LULUCF Extend vegetation cover. Avoid defforestation. Afforestation and refforestation. Reduce emissions of rice fields. Others. Control of fertilizers and pesticides. Methan capture. Sanitation. Sanitation improvement in residential sector. AGRICULTURE Structural change. Modernization and intensification of agriculture. Climate Smart Agriculture. Source: Own compilation based on the INDCs reported to COP21. 9 This analysis is dealt with from the sectoral point of view by policies and, secondly, from the regional point of view by country and income group. In order to evaluate most common policies at world level, it has been calculated the number of countries choosing each policy over total countries. Then to address the regional analysis, the same process has been made in each income group region. Further information on the method is in the methological annex. 3.2.1. Analysis by sector and policy As can be seen in Table 3, the policies that stand out most of all are those aiming for an electric mix based on renewable energies (95.2% of the INDCs). This policy is followed by transversal efficiency measures for all sectors and the increase in green cover through LULUCF. Some of these measures, such as the electrification of the economy and decentralized electricity generation (23% and 31% respectively), take on even greater importance on a regional scale. With respect to the decentralization of energy, oil rich countries stand out; countries such as Nigeria, which aims to install off-grid photovoltaic panels, or Equatorial Guinea , with its “home energy” programme. In addition to those already mentioned, an important role will be played in the future of energy by natural gas and the combined cycle power stations, according to what can be seen from the INDCs. Table 3. Top 15 policies. Source: Own compilation on the basis of INDCs submitted to the COP21. Information provided by total parties with policies. As for the transport subsector, there is a great bid to foster public transport and efficiency policies for private vehicles (29.4% and 27.0% of countries, respectively). The latter goal the countries hope to achieve through incentive-disincentive tax policies, in particular 16 Table 4 (continuation). Overview of policies by country (145-161). Country 145 Trinidad and Tobago 146 Tunez G1 R I4 W2 W5 L2 147 Turkmenistan 148 Turkey G1 G3 G6 R3 T6 T7 T8 I1 W1 W2 W4 A1 A4 L2 149 Tuvalu G1 G3 G7 150 UAE G1 G2 R3 T1 T6 T7 I1 W4 151 Ukraine 152 EU28 153 Uganda G1 G3 G4 R1 T1 A2 A5 L1 L2 154 Uruguay G1 T1 T4 T5 T6 T7 I4 W4 A3 A4 A5 L2 155 USA G1 R3 T1 I8 W4 156 Vanuatu G1 G3 G4 G7 L1 157 Venezuela G1 G3 G7 R2 R3 R4 T6 I4 I7 I8 W4 158 Vietnam G1 G2 G7 R T1 W1 W2 A5 L1 L2 159 Yemen G1 G2 G3 G4 G7 R3 R4 T1 I2 W2 A5 160 Zambia G1 G3 G4 R1 T4 A2 A5 L1 161 Zimbabue G1 G3 G4 G5 G7 R3 T4 W4 LULUCF Energy Resid. Transport Industry Waste Agric. Source: Own compilation on the basis of INDCs submitted to the COP21. 3.3. Finance, equity and leadership of the transition Means of implementation are needed to set these policies in motion. Article 9.1 of the Paris Agreement establishes that the DCs (Annex I countries, i.e. OECD) should provide the LDCs with financial resources. In addition, there should be reports every two years on the resources mobilized. In this sense, the great majority of the INDCs of the LDCs incorporate a series of unconditional objectives, assumed by the country itself, and other objectives conditioned by the reception of external support. Besides financial resources, other external support contemplated in the Agreement includes capacity-building and technology transfer. All the figures set out in this section must be considered with caution, due to the lack of homogeneity and clarity of the INDCs. Thus, the proportions destined to mitigation policies (83.2%), as opposed to those of adaptation, are often biased due to the high figures given by India (2500MM$), Iran (927.5MM$) and South Africa (898.79MM$) that account for 79.8% of the total funding. The group of countries that make the greatest effort in terms of finance with respect to their GDP are the low income countries, due both to their reduced level of GDP and the great quantity of external finance they have to account for. Specifically, 87.1%of all the financing required by the INDCs over the low income countries which has been evaluated corresponds to external resources. The choice, in Table 5, of the last indicator instead of the first is due to the fact that it is excessively biased because of the lack of data. It can be observed that the majority of countries requiring external financing do so in a relatively high proportion. This is such that a conservative estimate (only including the external financing explicitly mentioned) shows that almost half (41.4%) of the funding needed to completely implement the INDCs depends on international cooperation. Of course, this is a challenge in the design of climate funding which we shall deal with below. 17 Table 5. Financial allocation by income group (billions $). Total and effort related to GDP Mitigation (bs $) % over Total Adaptation (bs $) % over Total Other (bs $) Total (bs $)* % GDP % external support** Low 387.0 61.8% 156.4 25.0% 82.5 625.8 204.6% 87.1% Lower Middle 1016.3 35.9% 323.3 11.4% 1492.3 2831.8 99.1% 73.2% Upper Middle 1793.3 91.5% 167.4 8.5% 0.0 1960.7 69.4% 92.7% High 6.2 78.6% 1.5 19.4% 0.2 7.9 22.7% 77.8% High OECD ND ND ND ND ND ND ND ND Top 12 polluters 846.5 33.6% 222.8 8.8% 1452.3 2521.6 89.2% - TOTAL 3202.7 83.2% 648.5 16.8% 1574.9 5426.2 7.3% 41.4% Source: own compilation on the basis of INDCs submitted to COP21. GDP in 2005 constant dollars at market prices.* The totals in bs $ are not always the sum of Mitigation+Adaptation+Other because some INDCs offer totals with differences whose origin is not explained.** The percentage represents the proportion of external resources required by those INDCs that do offer data. However, the total percentage is the total amount of external resources required by all the plans over the total financing of the all the INDCs, including those that have no breakdowns. In order to channel the public and private resources that finance the mitigation and adaptation policies of the DCs to the LDCs, the UNFCCC has developed a complex system of climate funding (Buchner et al., 2015; Román, 2013). The ones most cited by the INDCs are the Green Climate Fund (GCF), the Green Environment Facility (GEF) and the Clean Development Mechanism (CDM) for compensation. The CDM should be a zero sum game (Erickson et al., 2014) in which investment in mitigation projects in the LDCs generates ‘Certified Emission Reductions’ (CER) that can be used to increase emissions by the same amount that the investment reduced them, or alternatively can be sold on the carbon markets. In total, 42 countries want to gain access or have already gained access and want to continue with the CDM, not counting those who have expressed a desire to use unspecified market mechanisms. The funding sources proposed by countries say a lot about the agents who will guide the practical set up of the INDCs. Depending on whether the conditional part of the external support for the LDCs is larger or smaller, the transition will be influenced by the criteria established by the international institutions or by the particular interests of the countries with which they reach bilateral agreements. In addition, naturally, the degree of importance given to the public or private sector will have consequences in the transition’s directive criteria, its effectiveness, and the coordination between policies and how fast the changes are implemented. Based on the finance sections of INDCs, it can be seen that in low income countries, more importance is given to external support (in particular the GCF), donations, carbon markets and the CDM. The weakness of these States means that, in addition, the private sector plays an important role. Those outstanding for their confidence in the private sector are Burkina Faso , 18 Liberia and Sierra Leone . For its heterogeneity of agents, Uganda is also worthy of note, with a transition led by the public sector, but with the participation of the local communities, publicprivate partnerships (PPP) and the international community. In the medium-low income countries, public participation and multilateral finance institutions have greater weight. The external support continues to be the principal driving force of the transition, although bilateral agreements are gaining weight, while the participation in such control mechanisms as CDMs are falling slightly (this is a constant as income rises). While Indonesia mainly has confidence in the private sector, Bolivia does so in the public sector and demands that the external support should be totally non-returnable. As the countries’ level of income rises, the financial autonomy to put the transition into practice also rises. In the medium-high income countries, Colombia mainly has confidence in the private sector and tries to involve the university system in the transition; while Cuba, on the other hand, continues to have confidence in a transition through the public sector, with such measures as the distribution of clean technologies for the residential sector (lighting and cooking). China , however, deploys some very diverse means led by the state, such as the PPP, favourable taxation, public contracts, green credit and financial guidance through the public bank, disaster insurance, etc. As we analyze the INDCs of the countries with higher incomes, the information becomes scarcer, but it continues with the dynamic of increasing the internal autonomy and government leadership. 3.4. Reducing emissions? Since one of the objectives of this article is the evaluation of the efficacy of the INDCs to comply with the Paris Agreement, the calculation of the variation in absolute emissions for each one is fundamental. The said calculations have had to be done because of the disparity in the forms of presentation of the contributions and have been carried out according to what is set out in the section and annex on methodology. Table 7 shows these results. As explained in section 2, there has been needed to estimate emissions reductions from the INDC’s data for those not giving the information as a reduction from a base year. Taking the simple arithmetic means, and if the mitigation policies (BAU) are not carried out, then each country would double (an increase of 95.7%) their emissions of GHGs in 2030 as compared to their defined level between 2005-2015. In order to get a better adjusted calculation, if we take the weighted mean as each country’s contribution to world emissions (in 2014), the result would be an increase in 19 world emissions of 31.5%. This result can basically be explained by the top 12 polluters, which will be analysed separately below. . The setting in which mitigation policies are carried out is not much rosier. In the best of cases (conditional on the reception of external support from countries not included in Annex I), each country would emit an average of 37.8% more than in the years 2005-2015. When this is weighted, the figure would be a 19.3% increase, due to the contribution of some Top 12 polluters, as we discussed in the next subsection. . In the least optimistic case, in which none of the conditional policies are put into practice, each country would modify their emissions on average with respect to the base interval by 75.0%. If this is weighted, emissions would increase on a global level around 25.8%. Although the INDCs always talk about reductions, they are seen in GHG emissions intensity (CO2eq/GDP) or over a BAU setting. Predicting the countries where the GDP will grow much more than their emissions and the BAU settings being on the increase, the final result is that of a net increase in GHG emissions, which cancels out the reductions in the Annex I countries and Brazil. India, for instance, aims to more than quadruple their emissions, China aims to increase by 39.8%, while other countries such as Burundi , Papua New Guinea , Liberia , Bangladesh or Congo oscillate around a growth factor of between 3 and 4. The trend scenarios of Congo and Burundi stand out especially, as they plan to multiply their emissions by more than 6 and 5 times, respectively. . Figure 3. Emissions variations by income level and different scenarios from baseline 2005-2015 to 2030 Own elaboration on the basis of the INDCs submitted to COP21. 20 In effect, Figure 3 reflects a decreasing tendency in mean emissions as income rises. However, the weighted mean shows an initially upward trajectory which then decreases as the income level increases. This is so because the low income countries currently represent a very small fraction of the emissions, while India (lower middle) would explain the highest point. On the other hand, the upper middle countries see China’s increase compensated for by the absolute reduction in emissions proposed by Brazil. As can be seen, the OECD countries (all of those in Annex I) are the only ones that plan to make an absolute reduction in emissions. Finally, as can be seen in Table 7, the countries that use their resources less efficiently (measured in dollars by percent unit of absolute reduction or over the BAU scenario) are the LDCs4. This is due to two reasons. The first one is beacuse they are the countries that plan to depend on greater external funding. The second one is because their mitigation policies would be more than compensated for by economic growth. 3.5. The Top 12 polluters pathway Top 12 polluters encompasses 60% of world population and 72.2% of GHG emissions. Policies and objectives established by this groups will affect 6 out of 10 world inhabitants (and probably increasing as population in China, India and others do not stop rising). Regarding the information provided by Top 12 polluters can be seen (Table 6 ) that policies information varies amongst them, but financial information is of low quality in general. In the first place of policies these countries choose a transition towards a renewable electricity mix. In the second place in most used policies by, Top 12 polluters arethe improvement in the efficiency of private vehicles (77%). As a result of the Top 12 policies and emissions reduction objectives, the whole Paris Agreement expected outcomes vary. In fact, when the average emissions reduction objectives are weighted by the countries contribution to GHG world emissions, the result is lower. This is because the increases in China and India (39.8% and 232.78%) respectively) are offseted by the reduction compulsorily proposed by Annex I countries plus Brazil. Nevertheless, if just China and India are taken apart, Paris Agreement expected outcomes would be rather differents. For instance, without their contribution, the emissions would decrease by 4.0% in the Conditional 4The high index shown by the upper middle countries is due to the high inefficiency in reducing emissions of the funding used by Iran (77.3MM$ per percent unit of reduction over the BAU scenario). 21 scenario, while they would slighlt rise by 2.5% unconditionally. In other words, given the past behaviour of DCs economies, the incorporation of China and India to their consumption and production patterns would be the main reason why the Paris Agreement objectives are so difficult to achieve. Paradoxically, without the economic contribution of India (as China does not provide finance information) the allocation or resources destined to mitigation would be almost halved in terms of world GDP, droping to 3.9%. Table 6. Overview of Top12 polluters. Information, emissions and financial resources. General Information quality Financial Information quality Main policies* Share of total emissions BAU Unc Cond China High Low - 39.8% - G1, G2, G5, T1, T6, T8, T10, I3, I5, I6, I7, W1, W3, A4, A5, L1, L2 23.9% U.S.A. Low Low - -28.0% - G1, R3, T1, I8, W4 12.1% EU-28 Low Low - -34.8% - No information. 9.0% India Medium Medium - 232.8% - G1, G3, G5, G6, R2, R3, T1, T4, T5, T6, T7, W1, W2, W5, L2 5.7% Brazil Medium Low - -43.0% - G1, G7, T1, T6, I1, L1, L2 5.7% Russian Fed. Low Low - 10.3% - No information. 5.3% Japan High Low - -22.7% - G1, G4, R, T1, T5, T6, T7, I1, I2, W1, W4, A4, L1, L2 2.8% Canada Low Low 35.0% -30.0% No information. 2.0% Congo, DR Medium Medium 74.0% 74.0% 44.4% G1, G3, A1 1.5% Indonesia Medium Low 123.7% 65.6% 32.0% G1, G7, W1, W4, A1, L1, L2 1.5% Australia Low Low - -28.0% - G1, G7, T1 1.5% Korean Rep. Medium Low 51.9% -4.3% - No information. 1.3% Total 71.2% 26.3% 10.5% 72.2% Weighted 24.5% 20.5% 19.2% Absolute emissions variation respect 2005 (%) Own elaboration on the basis of the INDCs analyzed (INDCs,2016). *According to the code stated in Table 2. 4. Economic and environmental features of INDCs In order to globally evaluate the INDCs, we follow the definition of Fischer-Kowalski (2011) of a socio-metabolic transition towards sustainability as that in which society does not pass the limits imposed by the biophysical system upon which it depends. To do this, it is not enough to analyze the sufficiency or insufficiency of the reduction in GHG emissions to the atmosphere. It is also necessary to evaluate the energy and material sustainability of the suggested policies to promote a socio-economic structure. Section 4.1, 4.2, 4.3 and 4.4 contrasts policies collected in the INDCs (see section 3.2) with the literature. Supported in this literature, we discuss the feasibility of INDCs proposed policies and its capability to jointly achieve the 2ºC objective. Section 4.5 and 4.6 follow the same rationale but referring to finance (see section 3.3) and emissions reduction (see section 3.4) respectively rather than policies. The variables through which the INDCs are classified are as follows: i/ socio-economic impact of the 22 transition; ii/ focus on energy management; iii/ substitution of non-renewable sources; iv/ the role of technology; v/ equality of the transition; vi/ degree of compliance with emission reductions. 4.1. Socio-economic impact Although the Director of Strategies of the UNFCCC has admitted that the fight against climate change requires a “fundamental transformation in the way we use and produce energy” (Thorgeirsson, 2015), there is a generalized belief that this is consistent with maintaining the current socio-economic system (Spash, 2016). Although numerous INDCs, such as China, appeal to economic growth and the modernization of their productive structure as a mitigation strategy, there is abundant empirical evidence of the string correlation between growth and environmental impact (de Bruyn et al., 1998; Stern, 2004; Tapia-Granados & Carpintero, 2013; Tapia-Granados, et al., 2012; Wagner, 2008; Carpintero, 2005). Far from there being a process of dematerialization associated with economic growth (Shafik, 1994)5, what has been observed is a process of environmental load displacement (Peng et al., 2016; Muradian et al., 2002; Cole, 2004). The transfer of “dirty” production to the poor regions has been facilitated by productive specialization, commerce and international finance (Batra et al., 1998; Andersson & Lindroth, 2001; Steen-Olsen, et al., 2012). In addition, we know that both technological industry (Sun-Hee, 2002) and, in general, industrial modernization and the switch to a tertiary economy (Carpintero, 2003) are great consumers of both energy and materials. On the other hand, numerous INDCs, of note among them being Bangladesh, Cameroon, Turkey or Morocco, express their interest in modernizing their agricultural systems, although they do not explain how this might mitigate the emissions of GHG. However, history tells us that agricultural modernization turns into a process of subordination to industry, making the former dependent on the latter and closely linked to oil products6. Thus, agriculture modernization would only result in an increase in both direct and indirect emissions. The indirect emissions are not usually assigned to agriculture, which are normally reduced to 5As established by the Environmental Kuznets Curve. 6 - Related with its use in making pesticides and herbicides, fuel for machines and that associated with the transport needed to carry the food from where it is produced to where it is consumed (a distance that this process increases). 23 methane from livestock and the directly emitted waste. This way, the contribution of modern agriculture to climate change is often undervalued. For all the above reasons, the link between economic growth and wellbeingandalso between growth and environmental sustainability is weakening, as an abundant literature on ecological economics has long been stressing (Víctor, 2015; Jackson, 2011). Measures from industrial ecology approach, followed by Rwanda among others, would contribute in a more effective way to reduce environmental impacts (Ivner et al., 2015; Wen and Meng, 2015; Yu et al., 2015; Côte and Liu, 2016). Given the environmental costs of modern agriculture, it would be much more interesting to transit towards agroecology, with a similar performance for modern agriculture but with less dependence on petroleum and environmental impacts (Altieri, 1995; Gliessman, 2006; Badgley, 2007; Pretty et al., 2003; Seufert, 2012). This model would be based on a proximity system of agricultural foodstuffs that would reduce the need for transport as well as a less meat intensive diet. Bhutan, for instance, advocates encouraging organic farming. China, on the other hand, advocates measures aimed at encouraging an agricultural system that adequately closes the ecological cycles, as well as reaching “zero growth” in pesticides and herbicides (intensive in petroleum use). 4.2. Demand side management policies With the exception of a few countries, such as Algeria, Barbados, Bhutan or Costa Rica , the majority of the INDCs assume there will be a growing demand for energy, i.e, energy demand is considered as an exogenous variable. Instead of proposing ways to reduce energy demand, beyond the general compromise with efficiency gains, the INDCs focus on changing the energy mix. -However, this view would seem to ignore the energy resources we have counted on in the past and which can be counted on in the future. The development and growth of industrial society cannot be understood without the concurrence of fossil fuels and their enormous energy potential(Hall 2011; Fouquet 2016). There are, therefore, at least two factors that seriously compromise this basic assumption of the great majority of INDCs and government sources studied. First of all, the arrival of the conventional peak oil (Hubbert, 1956; ASPO, 2008, IEA, 2010) has opened the door for non-conventional oil with a much lower energy performance (EROEI7) (Hall & Klitgaard, 2012), which are also more expensive and contaminating to extract 7 - Energy returned on energy invested (EROEI) is the mean energy performance as the relation between the amount of energy obtained by each unit of energy invested in a process. 24 (Heinberg, 2013). This, together with the foreseeable arrival of extraction peaks in other vitally important energy sources (Heinberg, 2007), leads us to anticipate risks for the future energy supply. Moreover, the International Energy Agency (IEA) (2016) recognized that it is not assured that investments in new oil explorations will be enough to meet demand due to high decline in output from existing fields. Secondly, if the transitions towards low-carbon economies of the INDCs are to be taken seriously, leaving a high proportion of fossil fuels underground should be mandatory (McGlade & Perkins, 2015). The substitution of the energy they provide (to say nothing of whether such provision will get larger or not) by other sources free from GHGs would seem to be complicated, if not accompanied by a reduction in energy consumption, as we shall see below. The main hurdle to follow this path is that it implies changing consumption and production patterns by means of demand side management policies (Creutzig et al. 2016), especially in DCs and emergent countries. Nevertheless, these policies applied to agriculture, transport, buildings and other sectors show interesting results for climate change mitigation (Creutzig et al. 2016). For instance, households’ food consumption has high impacts on energy consumption and direct and indirect emissions (Di Donato, Lomas, and Carpintero 2015). Therefore, changes in diets would be able to reduce by 35% GHG emissions (Stehfest et al. 2009), but it would require a huge conversion in agro-alimentary sector. In addition, reduction of transport needs would require re-organizing the cities design once all of their infrastructures are yet installed. Finally, this reduction in transport needs could need shorter commercialization channels and reducing the volume of international trade. 4.3. Substitution of non-renewable energies On applying a management approach to the energy supply, the INDCs only consider a substitution of the current energy mix by another one with a greater renewable and/or nuclear proportion. Nevertheless, the ability to substitute one technology for another is far from being perfect. The support or maintenance of nuclear energy is subject to limitations as far as resources goes, and this should be taken into account. If the forecast of the IEA turns out to be true, the extraction peak of uranium may well be reached in the next few decades (Zittel & Schindler, 2006). On the other hand, the substitution by biomass (in particular biofuels) is also subject to strong limitations (de Castro et al., 2014; Pimentel et al., 2007; Patzek, 2004). Due to the strong dependence of modern agriculture on fossil fuels, agrofuels present a very poor Comentario [O1]: Añadir breve mención a gestión demanda yu refeeremncia Creutzig 2016. 25 EROEI (de Castro et al., 2014). Furthermore, their cultivation enters into competition with land dedicated to food production, upon which it would exercise such pressure as to possibly result in price rises. In addition, the electrification of the economy, even if it could be done totally through renewable sources, would not be simple at all. In this sense, there are sound arguments to sustain that renewable sources do not have sufficient capacity to replace the energy potential of fossil fuels (Moriarty and Honnery, 2016; Capellán-Pérez et al., 2014; 2015; de Castro et al., 2011; 2013; Hoogwijk et al., 2004). There are also rigidities in the substitution of sources due to the different uses they have. For instance, the fuel used in planes, transport and heavy industry cannot simply be substituted by electric energy. In spite of some meritorious efforts in this sense, it would seem clear that it is very difficult to consider a simple technological exchange in the energy mix if it is not accompanied by a reduction in energy consumption. Finally, it is worth to mention that in absence of a clear policy of leaving fossil fuels underground (McGlade & Ekins, 2015), the international community could face the green paradox. As the market penetration of non-fossil sources increases, their demand would fall, leading to decrease of prices. If there is no political decision to leave fossil fuels underground, their consumption will probably be rebooted via prices incentives. So, if these circumstances are to be avoided, changing the energy mix through is not enough to address decarbonisation. 4.4. The role of technology The transition towards a hypocarbon model is already possible today, but it would involve a great socio-economic transformation, as stated before. Therefore, technological solutions are proposed, prominently, those referred to efficiency. These policies are the ones that have captured the most funding in recent years8 (Buchner et al., 2015) and are the preferred policies of the INDCs. Although they are destined to reducing energy consumption, the rebound effect (Polimeni et al., 2008; Blake, 2005; Carpintero, 2003; Duarte et al., 2013) may paradoxically cause the opposite effect, since the most efficient technology reduces the price and increases consumption beyond the initial reduction. 8In its less conservative range (HSBC, 2014). 32 the following equation is solved: A.2. ((𝐼2030∗𝐺𝐺𝐺2030)−(𝐼𝐵𝐵∗𝐺𝐺𝐺𝐵𝐵)) (𝐼𝐵𝐵∗𝐺𝐺𝐺𝐵𝐵)−100 =∆𝐸. Where I2030/BY is the intensity of emissions in 2030 and the base year respectively; 𝐺𝐺𝐺2030/𝐵𝐵 is the GDP in 2030 and the base year respectively; and ∆𝐸 is the percentage variation of the emissions. Both China and India present their data in this way and require additional hypotheses. They have had to use the projections of the GDP for the year 2030 of the OECD. In the case of the INDCs that apply a reduction on a BAU scenario, the procedure was as follows: applying arbitrary emissions of 100, the problem was solved using the following equation: A.3 (�100∗(1+∆𝐵𝐵𝐵)∗(1−∆𝐺𝑃𝑃𝐺)�−100) 100 =∆𝐸. Where ∆𝐵𝐵𝐵 is the percentage variation of emissions in the BAU scenario; ∆𝐺𝑃𝑃𝐺 is the proposed percentage reduction in emissions on the BAU scenario (conditional and unconditional, depending on the case); and ∆𝐸 is the percentage variation in the emissions. BAU scenario refers to the emissions in the horizon year if policies were not applied, usually based on historical emissions trends. With a conservative assumption, we have considered that the INDCs which propose a reduction range will finally achieve the upper bound. Regarding the policies analysis, we have to differentiate three analyses: policies at world level, policies at regional level, and sectoral-regional analysis. Policies at world level are assessed throughout the number of countries using each policy over total countries, according to eq. A4: A4. 𝛼𝑊=∑𝐺𝑖 𝑁 Being subscript i each policy, regardless the sector and ∑𝐺𝑖 the number of countries using each policy (𝐺𝑖𝑖 ) considered and N the total number of countries. Top 15 policies are shown in Table 4. For the regional level, an analogous calculation is made: A5. 𝛼𝑟=∑𝐺𝑖,𝑟 𝑁𝑟 33 Where the numerator represents the same as in A4 but for region (income group) r. The denominator is the number of countries in region r. Figure 1 shows the deviation from each top 15 policy share by income group to the world average, namely: 𝛼𝑟− 𝛼𝑊. Finally, we take the arithmetical mean of 𝛼𝑟 and 𝛼𝑊 by sector: A6. 𝛼𝑖,𝑊= ∑𝛼𝑊 𝑁𝑗 ; 𝛼𝑖,𝑟= ∑𝛼𝑟 𝑁𝑗 With 𝑁𝑖 being the number of policies in each sector j. By proceeding this way, we obtain an approximation to the relative importance of each sector in the different regions and in the world. 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