Sufficient or insufficient: Assessment of the intended nationally determined contributions (INDCs) of the world’s major greenhouse gas emitters

Abstract

The recent Conference of the Parties of the United Nations Framework Convention on Climate Change has resulted in the submission of the Intended Nationally Determined Contributions (INDCs) of 190 countries. This study aims to provide an analysis of the ambitiousness and fairness of the mitigation components of the INDCs submitted by various parties. We use a unified framework to assess 23 INDCs that cover 50 countries, including European Union (EU)-28 countries as parties to the Convention, which represent 87.45% of the global greenhouse gas emissions in 2012. First, we transform initial INDC files into reported reduction targets. Second, we create four schemes and six scenarios to determine the required reduction effort, which considers each nation’s reduction responsibility, capacity, and potential, thereby reflecting their historical and current development status. Finally, we combine the reported reduction target and the required reduction effort to assess INDCs. Evaluation results of the 23 emitters indicate that 2 emitters (i.e., EU and Brazil) are rated as “sufficient,” 7 emitters (e.g., China, the United States, and Canada) are rated as “moderate,” and 14 emitters (e.g., India, Russia, and Japan) are rated as “insufficient.” Most pledges exhibit a considerable distance from representing a fair contribution.

Keywords

Intended Nationally Determined Contributions / mitigation / responsibility / capacity / potential

Introduction

The release of CO₂ and other greenhouse gases (GHGs) as a result of human activities is causing climate change, which controls human development. To avoid the dangers of climate change, the global community of nations reached an agreement in 2015 to keep global average temperature rise considerably below 2°C above the pre-industry level and to pursue efforts that can further reduce it to 1.5°C. To accomplish these objectives, 190 countries, including one regional economic integration organization, i.e., the European Union (EU) and its 28 member states, had submitted their voluntary GHG reduction commitments, called Intended Nationally Determined Contributions (INDCs), by November 5, 2016. These INDCs, which account for 98.09% of global GHG emissions, outline the intended post-2020 climate action plans of these countries (^{UNFCCC, 2016}). INDCs undoubtedly represent a breakthrough in the international effort to curb future GHG emissions.

This study compares the reported reduction targets and required reduction efforts of several countries. The assessment conclusion presents the ambitious endeavors of the countries toward decarbonization and whether the submitted INDCs can achieve the global emission reduction objective. The assessment results may help countries formulate better policies. The remainder of this paper is organized as follows. Section 2 provides an overview of the relevant literature on the assessment of INDCs. Section 3 proposes a rating method for the reported reduction targets and required reduction efforts. The data resource is also provided in Section 3. Section 4 presents the results. Finally, Section 5 concludes the study and discusses its uncertainties.

Overview of the assessments of INDCs

Several studies have assessed the aggregated efforts of INDCs to reduce global emissions. In particular, the United Nations Framework Convention on Climate Change (UNFCCC), the United Nations Environment Programme (UNEP), and the Climate Action Tracker (CAT) present three essential reports.

UNFCCC released its synthesis report, which includes all INDCs submitted by October 1, 2015 (147 parties, including EU’s 28 member states), on October 30, 2015. This report, which covers over 80% of global emissions in 2010 (^{UNFCCC, 2015}), aims to assess the aggregate emission impact of domestic efforts before the 2015 United Nations Climate Change Conference (COP 21). The report provides qualitative and quantitative evaluations of INDCs. It states that all the information provided by INDCs about mitigation actions and the emission growth that will result from these actions is expected to slow down by a third in the period of 2010–2030 compared with that in the period of 1990–2010. Through these mitigation efforts, the world can stride toward its emission reduction target. Despite the extensive and unprecedented involvement of countries in such a global effort, the mitigation actions will not hold the world’s temperature below the 2°C trajectory. The temperature at the end of the century will strongly rely on many factors, including technological development, long-term actions, and the energy structure.

On November 6, 2015, ^{UNEP (2015)} released the Emission Gap Report 2015, which provided an update on the assessment of the mitigation effects of INDCs submitted by October 1, 2015. The expert team prepared a preliminary assessment of 38 INDCs among the 59 submissions, accounting for 60% of current global GHG emissions and excluding emissions from land use, land use change and forestry (LULUCF). Assessments of the literature on INDCs are obtained from global and national studies, including estimates from many country-specific studies (e.g., World Resource Institute (WRI), Energy Research Institute, National Center for Climate Change Strategy and International Cooperation), official estimates (documents submitted by countries to UNFCCC), and eight global studies (e.g., CAT, PBL Netherlands Environmental Assessment Agency, International Energy Agency’s World Energy Outlook). The results show that the estimated emission level of the most likely scenario cannot limit global average temperature increase to below 3.5°C (range: 3°C –4°C) by 2100 with a probability of over 66%. However, if all INDCs are fully implemented, then the 2030 emission gap will still be 12 Gt CO₂e, thereby placing the world on track to a temperature rise of approximately 3°C by 2100, with significant climate impacts.

CAT, an independent science-based assessment, has been tracking government emission commitments and actions for years. In preparation for the adoption of the Paris Agreement in December 2015, CAT analyzed the INDCs of 32 parties (CAT, 2016), in which 59 countries (including EU-28 countries as parties to the Convention) covering 81.3% of global emissions in 2010 were analyzed. The CAT methodology for assessing and rating INDCs focuses on CO₂ and other GHG emissions from fossil fuel combustion, industries, agriculture, and waste sources, which account for 93% of global GHG emission in 2012. CO₂ and other GHG emissions from LULUCF, which comprise approximately 7% of global GHG emission, are not included in the effort sharing ranking system. In the assessment of this system, a wide range of literature on what researchers will consider a “fair” contribution to GHG reduction, including over 40 studies used by the Intergovernmental Panel on Climate Change (IPCC) and additional analyses performed by CAT, is compiled to complete the database. The final assessment result depends on a nation’s proposal on which part of the emission range is calculated. For example, if a government’s proposal is higher than any calculated emissions, then CAT rates it as “inadequate.”

Overall, the three aforementioned reports agree that despite the positive contribution of INDCs, a considerable gap remains between the political 2°C ambition and current intended contributions. The mitigation commitment of all countries should be upgraded to narrow the gap with the temperature target.

Other independent entities have also concluded that despite the reductions, the global GHG emission level is still projected to be higher in 2030 than in 2010 (^{Höhne et al., 2014}; ^{Davide and Vesco, 2016}; ^{den Elzen et al., 2016}). However, most studies have focused only on the aggregated effect of INDCs and the implication for achieving the temperature goal, which cannot offer comprehensive comparisons on the same basis among countries (^{Rogelj et al., 2016}). To our knowledge, only the report of CAT has ranked countries in terms of the ambitiousness of their individual INDCs. In the current study, we aim to analyze the INDCs submitted by parties and assess the proposed national pledges. First, we calculate each party’s reported reduction target, which is represented by the CO₂ emission reduction commitment in 2030 from the initial INDCs files. Second, we calculate each party’s required reduction effort according to the reduction factor. Finally, we compare the parties’ reported reduction target and required reduction effort and provide an assessment of their INDCs.

Method and data

We analyzed and rated all the INDCs of parties with high global CO₂ emission share in 2012 and specific quantifiable goals. Six parties, namely, North Korea, Libya, Syria, Nicaragua, Panama, and Timor-Leste, which account for 0.52% of the global emissions in 2012, have not submitted INDCs (Fig. 1). Meanwhile, the emission share of each of the 147 countries that have submitted INDCs was less than 0.45% in 2012. Their total emission share was 8.78%. Moreover, the emission share of 54 countries (27 parties, EU member states are counted as one party) was each higher than 0.45% in 2012. The INDCs of these 27 parties accounted for 90.56% of the global CO₂ emissions (the sum of the emission shares of the first two lines in Fig. 1). Among the 54 countries, Egypt, Saudi Arabia, Pakistan, and the United Arab Emirates, accounted for 3.11% of the global emissions in 2012. These countries submitted INDCs without specific GHG mitigation target and action, thereby implying that our evaluation objects are 50 countries (23 INDCs), which represent 87.45% of global emissions. Figure 1 shows the major countries that have submitted INDCs and their global emission shares.

Assessment process

We assess and rate INDCs according to a specific assessment roadmap (Fig. 2), which is divided into two steps. In the first step, we extract the reported reduction target, which is represented by the CO₂ emission reduction commitment in 2030 from initial INDC files. In the second step, we calculate each party’s required reduction effort. We set up four schemes and six scenarios. The four schemes are responsibility-oriented, capacity-oriented, potential-oriented, and average weighting schemes. The scenarios limit the amount of emission space that nations can use. We set up six scenarios based on business as usual (BAU) and emission control scenarios. One combination of scheme and scenario results in one required reduction effort. Therefore, we obtain 24 required reductions. Finally, we compare the reported reduction targets of parties with their required reduction efforts and then provide an assessment of their INDCs.

Rating method

On the basis of CAT’s method, the rating method used in this study is described as follows (Fig. 3). If a country’s reported reduction target transformed from its INDC file is below the required reduction effort range, which is composed of 24 combinations of schemes and scenarios, then it is rated as “insufficient” (dark blue in the bar). This country’s INDC is considered not in line with the 2°C pathway limit. If a country’s commitment emission reduction from its INDC is higher than any of the required reduction effort, then it is rated as “sufficient” (white in the bar). Such proposal is determined to meet the Paris Agreement goal of limiting temperature change to below 2°C above the pre-industry level. Furthermore, countries with reported reduction targets that fall in the middle of the required ranges are rated as “moderate” (light blue in the bar). Their efforts are between “inadequate” and “sufficient.”

Reported reduction target

The first step is extracting the reported reduction target from the INDCs’ mitigation part (Supplementary Table 1). However, the INDCs of parties are heterogametic among submissions, both in terms of GHG coverage and mitigation effort. First, the emission reduction targets of Annex I Parties include six types of Kyoto Protocol gases (excluding NF₃) or all seven types of GHGs (including NF₃). Meanwhile, the GHG coverage of Non-Annex I Parties is different. Most parties listed only two to three types of GHGs. For comparability, we consider only CO₂ in our study because it is the leading GHG. Second, most countries express their contributions in the form of a quantifiable mitigation effort compared with a specific emission level in a reference year or a BAU scenario, from which targets can be transformed. The reference year emissions and BAU scenario emissions are collected from the CAIT Climate Data Explorer database of WRI. By contrast some developing countries (e.g., China and India) formulate their pledges in terms of emission intensity or emission peak year. Further assumptions on the development of the economy and the society are required to obtain the reported target of the two countries, which lead to uncertainties in their emission control efforts. The required emission target is obtained from the CAT report. In addition, four countries (United Arab Emirates, Egypt, Saudi Arabia, and Pakistan) have not specified a quantitative emission reduction commitment but have focused on mitigation action. We have not quantified their reported reduction target. All the reported reduction targets of the parties are projected to 2030 because most parties defined their INDC target year as 2030, except for the United States and Brazil, which adopted 2025 as their target year. We assume that the emission reductions of these two countries are linear in 2025–2030 and transform the target year into 2030.

In addition, heterogeneity appears in the reported promised conditions of parties. Several parties distinguish between unconditional and conditional targets. Among the 23 INDCs assessed, 9 parties have indicated their need for international financial support. They are requesting for market-based cooperation mechanisms and domestic and international financial assistance, such as emission allowance purchases and capacity-building support, toward their commitment. For assessment uniformity, only unconditional commitment is included in this study. Table 1 presents the CO₂ emission reduction commitment for 2030 under quantifiable unconditional commitment.

Required reduction effort

The second step is to calculate the required reduction effort for each country. Emission scenarios limit the amount of space that nations can release to the atmosphere. First, we determine six emission scenarios by comparing two scenarios: BAU and emission control. The BAU scenario provides information on how emissions are likely to develop in the absence of mitigation policies. The emission control scenario is represented by the Representative Concentration Pathway (RCP) 2.6 scenario, which can limit global mean temperature to approximately or below a 2°C increase since pre-industrial times (van Vuuren et al., 2007). The difference between the BAU emission scenario without INDC commitment and the emission control scenario results in an “emission gap” in the world, thereby indicating that global reduction effort is required.

Six emission scenarios

Here, we present six scenarios based on diverse gaps.

(1) BAU scenarios

We provide six different scenarios based on the Roadmaps toward Sustainable Energy Futures (RoSE) scheme using the Global Climate Assessment Model (GCAM). GCAM is an RCP-class model (^{Joint Global Change Research Institute, 2015}) that can be used to simulate scenarios, policies, and emission targets from various sources. It is calibrated between 1990 and 2005 and operates in 15-year time steps until 2095. The output includes projections of future energy supply, demand, resulting GHG emissions, radiative force, and the climate effects of 16 GHGs. This model has been widely used in national and international assessment activities, such as the Energy Modeling Forum, the United States Climate Change Technology Program, and IPCC assessment reports.

Six different scenarios (RoSE 111, RoSE 121, RoSE 131, RoSE 141, RoSE 161, and RoSE 171) and their corresponding emissions across the model are attributed to three dimensions: (1) underlying assumptions on future socioeconomic development determined by population and economic growth; (2) reference assumptions on long-term fossil fuel availability with a focus on variations in coal, oil, and gas; and (3) stringency and timing of climate protection targets and framework of an international climate policy. In this study, we set the climate policy regime as the baseline.

The RoSE scenario matrix is presented in Table 2. Each column corresponds to a combination of socioeconomic and fossil resource drivers. The growth speed of each parameter is divided into three levels: Fast (or High), Med, and Slow (or Low). Using the Rose 111 scenario as an example, “Med Growth” indicates that the growth speed of the economy is medium, “Fast Conv” represents fast convergence of economies, and “Med Pop” and “Med Fossils” denote moderate growth rates for population and fossil consumption.

(2) Emission control scenarios

The emission control scenario is determined by RCPs (van Vuuren et al., 2011; ^{Meinshausen et al., 2011}; ^{Moss et al., 2010}), which are scenarios for the possible future evolution of concentrations of various gases that affect climate. Different RCPs are related to varying radiative force levels. RCP2.6 represents strong abatement relative to a no-climate policy reference scenario, with CO₂ concentrations not exceeding approximately 450 ppm. Figure 4 shows the emission pathways of the world under RCP2.6 compared with those under RCP4.5 and RCP8.5. In RCP2.6, the peak year of CO₂ emissions is approximately 2020, and then emissions will decrease with a high speed compared with the pre-2020 level. In this case, the global CO₂ emission in 2030 will reach 26.24 GtCO₂, which is nearly the same level as that in 2003. Eventually, the difference between each BAU emission scenario and emission control scenario will require a global reduction effort. We obtain six global required efforts because we have six BAU scenarios.

RCPs are meant to serve as input for climate and atmospheric chemistry modeling as part of the preparatory phase for the development of new scenarios for the IPCC’s Fifth Assessment Report and beyond. Here, we select RCP2.6, which was developed by the IMAGE modeling team of the Netherlands Environmental Assessment Agency. The emission pathway is representative of scenarios in the literature with very low GHG concentration levels. RCP2.6 is a so-called “peak” scenario: the radiative force level first reaches a value of approximately 3.1 W/m² by mid-century and then returns to 2.6 W/m² by 2100 (Beltran et al., 2011; ^{Davide and Vesco, 2016}). To reach such radiative force levels, GHG emissions (and indirectly, air pollutant emissions) are reduced substantially over time. Emission data are obtained from the Potsdam Institute for Climate Impact Research.

Four schemes

We use the emission reduction factor to divide the required global emission reduction effort into parties’ reduction efforts. The emission reduction factor is a comprehensive index composed of seven indicators that are grouped into three dimensions: Carbon emission reduction responsibility, carbon emission reduction capacity, and carbon emission reduction potential. Countries with higher responsibility, capacity, and potential in CO₂ emission reduction should assume more obligations and implement more reduction efforts. We set two to three indicators in each dimension. Table 3 provides an overview of the seven indicators and three dimensions, along with their explanations.

Carbon emission reduction responsibility

The required emission reduction effort is determined by the level of historical emissions of a country. This principle was first proposed by Brazil in the Kyoto Protocol negotiation and is perceived as the most significant influence factor, which means that an abatement of burden corresponds with emissions. The indicators include cumulative CO₂ emissions, per capita CO₂ emissions, and CO₂ emissions in 2012, which represent a country’s historical emission level and current emission status.

The cumulative CO₂ emission indicator describes the long-term emission level. We select 1990 as the starting year for cumulative emissions because each country should have been aware of the climate problem caused by GHG emissions since 1990 (^{UNFCCC, 1997}). The per capita CO₂ emission indicator reflects a country’s per capita carbon emission level at a certain time point; it shows the social fair principle and regional fair principle of reduction, i.e., everyone has equal rights to obtain resources (^{Baer et al., 2009}; ^{Phylipsen et al., 1998}). Future emission trend can be reflected from the current emission level. Countries with higher current emissions should assume more responsibility in reducing emissions.

Carbon emission reduction capacity

Several studies have used responsibility and capacity as bases for explicitly distributing emission reduction (^{Baer et al., 2009}; ^{Winkler et al., 2013}). The associated principle, “vertical,” indicates that rich countries should implement more reduction efforts. Given their diverse abilities, the respective responsibility of countries to protect the climate system varies from one another. Developed countries have higher capabilities compared with developing countries. Here, we select two indicators: gross domestic product (GDP) per capita and the Human Development Index (HDI). GDP per capita represents a nation’s economic development level; it characterizes the economic feasibility of emission reduction (^{Yi et al., 2011}; ^{Ott et al., 2004}). HDI compensates for the deficiency in measuring society-related state of development, which is a composite statistic that comprises life expectancy, education, and per capita income indicators. A country with longer life expectancy at birth, longer education period, and higher GDP per capita should assume more responsibility toward achieving emission reduction.

Carbon emission reduction potential

Carbon emission reduction potential represents a country’s emission reduction space, which determines the amount of reduction that can be implemented domestically and corresponds to the “development level principle.” A country with higher potential is obligated to utilize this advantage and reduce more domestic emissions (^{Winkler et al., 2007}). Carbon emission intensity (carbon emission per unit of GDP) describes a country’s carbon emission efficiency and reflects its energy development stage. A nation with higher national carbon emission intensity has lower carbon emission efficiency, and thus, has more space and potential to contribute to emission reduction (^{Wang et al., 2013}; Wang et al., 2016). The proportion of coal consumption to total energy consumption represents a country’s energy consumption structure. At present, carbon emissions primarily result from the combustion of fossil fuel emissions in most areas of the world. A nation with a higher proportion of coal consumption has greater potential to adjust its energy structure and bear more responsibility (^{Ringius et al., 1998}).

We use the objective information entropy method and the subjective dimension weight set method to determine the emission reduction factor. The information entropy method can determine the information weights of the uncertainty degree of the information source. In the dimension weight set method, we establish four types of scheme: A: average weighting scheme, B: responsibility-oriented scheme, C: capacity-oriented scheme, and D: potential-oriented scheme. Each scheme has its reduction tendency and is distinguished by its weight of dimension. For example, the responsibility-oriented scheme gives more attention to emission reduction responsibility; thus, the indicators for the emission reduction responsibility dimension have higher dimension weights (DWs) compared with those for the other two dimensions. We then set four schemes and obtain four reduction factors to further determine the required reduction effort for each country.

Weights of the four schemes

Dimension weights (DW)

Given the current level of economic development, industrial structure layout and historical emissions are diverse among countries worldwide, and the emission reduction process of countries will emphasize different indicators. For comprehensiveness, we establish four schemes: responsibility-oriented, capacity-oriented, potential-oriented, and average weighting schemes. Different schemes respond to diverse DWs and reflect the emphasis of the carbon emission reduction effort. The specific setting and characteristic of each DW are presented in Table 4.

Indicator weights (IWs)

IW reflects the importance of each country’s responsibility, capacity, and potential in the assessment. In this study, we use the information entropy method to determine the information character of the uncertainty degree of a country’s indicator information source. First, we set up the original evaluation matrix as follows:

(1)X=\left(\begin{array}{lll}{x}_{\mathrm{1},\mathrm{1}}& \dots & x_{\mathrm{1},n}\\ ⋮& \ddots & ⋮\\ x_{m,\mathrm{1}}& \cdots & x_{m,n}\end{array}\right),

where x_{ij} denotes the raw data of the indicator, with i representing the serial number of the country, and j representing the selected indicator; m= 28; and n = 7. To avoid the influence of the scale of each indicator, we normalize every indicator of the countries as follows:

(2)y_{i,j}={\displaystyle \frac{x_{i,j}-\underset{i}{\min }{x}_{i,j}}{\underset{i}{\max }{x}_{i,j}-\underset{i}{\min }{x}_{i,j}}},

where y_{ij} is the normalized data. The resulting normalize matrix is as follows:

(3)Y=\left(\begin{array}{lll}{y}_{\mathrm{1},\mathrm{1}}& \dots & y_{\mathrm{1},n}\\ ⋮& \ddots & ⋮\\ y_{m,\mathrm{1}}& \cdots & y_{m,n}\end{array}\right)\mathrm{.}

Third, in accordance with the basic principle of the entropy weight method, the entropy weight e_j of indicator j can be calculated as follows:

(4)e_j=-k{\displaystyle {\sum }_{i=\mathrm{1}}^m{p}_{i,j}\times \ln p_{i,j}},

where k = 1/lnm, p_{i,j}=y_{i,j}/{\displaystyle {\sum }_{i=\mathrm{1}}^m{y}_{i,j}}, and m is the total number of evaluated countries. In particular, p_{ij}=\mathrm{0} and p_{i,j}\times \ln p_{i,j}=\mathrm{0}. Each indicator weight under different dimensions can be expressed as follows:

(5)I{W}_j={\displaystyle \frac{\mathrm{1}-e_j}{{\displaystyle {\sum }_{j=\mathrm{1}}^n\mathrm{1}-e_j}}},

where I{W}_j is the entropy weight of indicator j. The final weight of each indicator is calculated as follows:

(6)W_j=I{W}_j\times D{W}_j,

where \mathrm{0}\le W_j\le \mathrm{1}, {\displaystyle {\sum }_{j=\mathrm{1}}^{\mathrm{7}}{W}_j}=\mathrm{1}, and D{W}_j is the subjective dimension weight, D{W}_j\in \left({\displaystyle \frac{\mathrm{1}}{\mathrm{3}}},{\displaystyle \frac{\mathrm{1}}{\mathrm{5}}},{\displaystyle \frac{\mathrm{3}}{\mathrm{5}}}\right).

Finally, we can obtain the emission reduction factor K_i of country i by linearly aggregating each indicator and the associated final weight as follows:

(7)K_i={\displaystyle {\sum }_{j=\mathrm{1}}^{\mathrm{7}}{W}_j}\times y_{i,j},

where emission factor K_i reflects a country’s contribution toward climate change mitigation and the GHG emission reduction process. A country with a higher emission factor K_i should commit to more emission reduction effort. The required emission reduction effort of each country E_i can be calculated as follows:

(8)E_i=E\times K_i/{\displaystyle {\sum }_{i=\mathrm{1}}^{\mathrm{28}}{K}_i},

where E is the global emission gap between global BAU and the RCP2.6 scenario.

The final required reduction effort is presented in Table 5.

Assessment data

The second source adopted to develop the analysis is the model data selected from several databases. Considering the availability of all data, we choose 2012 as the base year, thereby establishing a comprehensive index system that reflects national emission characteristics. In the aspect of GHG emission, we only consider CO₂ emitted from fossil fuels. Other non-energy-related emissions (e.g., from land use change and forestry) are not considered. All the emission data are obtained from the CAIT Climate Data Explorer database, namely, the “CO₂ Emission from Fuel Combustion” edition (^{WRI, 2016}). Emission data include domestic cumulative CO₂ emissions for the period of 1990–2012, per capita CO₂ emissions, and CO₂ emissions in 2012. The statistical data of coal and primary energy consumption are provided by British Petroleum (^{BP, 2016}). The global population data are obtained from the publication “World Population Prospects” (2015 edition) of the United Nations Department of Economic and Social Affairs (UN DESA, 2015). The GDP data, which were calculated in 2005 constant dollar, are from the ^{World Bank (2015)}. The HDI of the countries is from the United Nations Development Programme (^{UNDP, 2015}). Among which, the HDI of EU is obtained from the arithmetic mean of its 28 member states.

Results

The pairwise combination of the four schemes and six scenarios provides 24 required reduction efforts for each party in 2030. We calculate the average required reduction effort under each scheme for one party. Figure 6 shows the average effort with respect to the BAU scenario of main emitters. China, the United States, EU, India, Russia, and Japan will be required to reduce their CO₂ emissions by 9%–19%, 21%–42%, 19%–35%, 10%–22%, 32%–45%, and 73%–121%, respectively, by 2030, compared with their BAU emissions. The required reduction efforts vary because of different schemes. The result illustrates that countries with lower carbon intensity and proportion of coal consumption to total energy consumption have lower emission reduction potential. Thus, these countries do not need to exert considerable required reduction effort in the potential-oriented scheme. This case is applicable to most developed countries, such as the United States, EU, Japan, and Korea. Most developing countries, such as China, India, Russia, Iran, Indonesia, and South Africa, typically have lower emission reduction capacity because they have lower GDP per capita and HDI compared with developed countries. Developing countries will benefit the most from the capacity-oriented scheme. That is, wealthy countries generally mitigate more emissions. For several major emitters, including developing and developed countries, such as China, the United States, EU, India, Russia, and Japan, emission reduction responsibility is greater than those of other emitters. These countries have less emission space in the responsibility-oriented scheme.

Figure 7 shows the required reduction effort (histogram) compared with the reported reduction target (boxplot) of 23 parties. The results illustrate that the choice of schemes and scenarios will affect the required reduction effort. The required reduction effort response of different parties varies because of diverse choices. Australia, Kazakhstan, and Vietnam are spread widely in terms of required emission reduction effort. That is, they are considerably affected by emission scenarios and schemes. However, the required reduction effort of China, the United States, EU, India, Russia, Iran, Brazil, and Mexico are relatively stable and less affected by emission scenarios and schemes. These parties are found in the upper half of Fig. 7 (large emitters) and accounted for 70.35% of the global emissions in 2012. Despite the uncertainties in the required effort for small emitters, the global required effort level remains robust by calculating the required reduction effort for each country.

In accordance with the rating method described in Section 3.3, we assess nations as “inadequate” (dark blue), “sufficient” (white), or “medium” (light blue) based on the comparison of the required reduction effort and the reported reduction target. Table 5 provides the assessment result of the 23 parties.

The evaluation results of the 23 parties indicate that EU and Brazil are rated as “sufficient.” That is, they are exerting the most ambitious effort. Seven countries are rated as “medium,” namely, China, the United States, Canada, South Africa, Venezuela, Argentina, and Algeria. Finally, 14 countries are rated as “inadequate,” namely, Australia, Iran, India, Indonesia, Japan, South Korea, Mexico, Ukraine, Thailand, Russian Federation, Turkey, Kazakhstan, Vietnam, and Malaysia. Their targets provide considerable opportunity for emission growth until 2030.

Among the world’s top 10 emitters, five are rated as “inadequate” (India, Russian Federation, Japan, South Korea, and Iran), three parties (China, United States, and Canada) are rated as “medium,” and EU (28 members) is rated as “sufficient.” The remaining country in the list, i.e., Saudi Arabia, is not included in the evaluation because it lacks specific and quantifiable INDC goals. Most current pledges are “inadequate” because of the unconditional quantizable mitigation aspects of INDCs, which indicates a considerable distance from representing a fair contribution. Therefore, we assume that the global emission reduction objective will be difficult to achieve through the submitted INDCs. The motivation of short-term contributions must be strengthened in future negotiations.

Conclusions and discussion

Undoubtedly, INDCs represent a breakthrough in terms of international effort to curb future GHG emissions. The number of participating countries is 189, which is considerably more than those of previous international efforts, such as the Kyoto Protocol and the Cancun pledges. Since the establishment of INDCs, positive consequences that go beyond benefits to the climate have been achieved. INDCs should provide the first step toward the formation of an ambitious global climate action. At present, however, the number of parties whose pledges are rated as medium is 7, whereas 14 have pledges that are rated as “inadequate.” Most countries have presented mediocre endeavors toward decarbonization. First, INDCs do not only reflect a country’s strength and attitude, but also its responsibility. Each party should work to implement a new transparent mechanism and fulfill its promise. Second, the mitigation commitment of all countries should be upgraded to close the gap toward the temperature target. Further actions and initiatives for narrowing this gap are necessary, such as enhancing energy efficiency with emphasis on industries, buildings, and transport; expanding the use of renewable energy technologies; and strengthening international cooperation and coherence.

This research exhibits many limitations and uncertainties. First, we consider only fossil fuel-related CO₂ emissions exclude the effect of LULUCF because of considerable uncertainties in sector statistics. Moreover, specific LULUCF emission projections are frequently lacking. In general, considering emissions from LULUCF will weaken mitigation effort. Second, in terms of this study’s comparability, we consider only CO₂ and disregarded other GHGs. Although CO₂ is the most abundant GHG, six or seven kinds of GHGs identified in the Kyoto protocol are included in the INDCs of most Annex I parties. When all types of GHG emissions are considered simultaneously with LULUCF, the emission space will continuously narrow, thereby resulting in stressful situations. Third, we have not considered the impact from other countries when assessing the required reduction effort for each country. A frequent occurrence is observed in which one country obtains financial support from other countries or is restricted because of various factors. Thus, the required reduction effort of these countries will be affected. However, the quantification of these indicators is difficult; hence, we have not included it in our evaluation. Finally, emission reduction indicators for calculating the required reduction effort are selected based on a country’s emission reduction responsibility, potential, and capacity, which comprehensively consider various factors that influence reduction effort. The index system can still be improved. Indicators that can present extensive characteristics will render our index system faultless. Continued effort is required to boost the chances of success of the Paris Agreement, and an adequate assessment of parties’ pledges is indispensable to provide feature-for-feature and comprehensive comparisons.

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