Carbon emission coefficient of power consumption in India: baseline determination from the demand side

Substantial investments are expected in the Indian power sector under the flexibility mechanisms (CDM/JI) laid down in Article 12 of the Kyoto Protocol. In this context it is important to evolve a detailed framework for baseline construction in the power sector so as to incorporate the major factors that would affect the baseline values directly or indirectly. It is also important to establish carbon coefficients from electricity generation to help consider accurate project boundaries for numerous electricity conservation and DSM schemes. The objective of this paper is to provide (i) time series estimates of indirect carbon emissions per unit of power consumption (which can also be thought of as emission coefficient of power consumption) and (ii) baseline emissions for the power sector till 2015. Annual time series data on Indian electricity generating industry, for 1974–1998, has been used to develop emission projections till 2015. The impacts of generation mix, fuel efficiency, transmission and distribution losses and auxiliary consumption are studied in a Divisia decomposition framework and their possible future impacts on baseline emissions are studied through three scenarios of growth in power consumption. The study also estimates and projects the carbon emission coefficient per unit of final consumption of electricity that can be used for conducting cost benefit of emission reduction potential for several electricity conserving technologies and benchmarking policy models.     

Carbon intensity of electricity generation and CDM baseline: case studies of three Chinese provinces

A difficult and persistent issue in the discussion of Clean Development Mechanism is estimating a carbon emissions baseline, against which tradable permits may be certified. This paper examines the proposition of adopting sectoral, as opposed to project level, baselines by conducting case studies of the electricity industry in three Chinese provinces. We find that complicated central planning, financial and institutional factors have been behind the declining trend of carbon intensity in electricity generation and its provincial variations. Government planned electricity development which incorporates many of these factors and the associated industry carbon intensity may serve as a second best baseline. However, the limitation of the baseline we examine in this study plus difficulties numerous studies have revealed in baseline setting suggests that using baselines based on counterfactuals of what would happen will in the end either miss good emission reduction opportunities, or compromise the integrity of the regime.     

Impacts of China's emissions trading schemes on deployment of power generation with carbon capture and storage

The establishment of an emissions trading scheme (ETS) in China creates the potential for a “least cost” solution for achieving the greenhouse gas (GHG) emissions reductions required for China to meet its Paris Agreement pledges. China has pledged to reduce CO₂ intensity by 60–65% in 2030 relative to 2005 and to stop the increase in absolute CO₂ emissions around 2030. In this series of studies, we enhance the MIT Economic Projection and Policy Analysis (EPPA) model to include the latest assessments of the costs of power generation technologies in China to evaluate the impacts of different potential ETS pathways on deployment of carbon capture and storage (CCS) technology. This paper reports the results from baseline scenarios where power generation prices are assumed to be homogeneous across the country for a given mode of generation. We find that there are different pathways where CCS might play an important role in reducing the emission intensity in China's electricity sector, especially for low carbon intensity targets consistent with the ultimate goals of the Paris Agreement. Uncertainty about the exact technology mix suggests that decision makers should be wary of picking winning technologies, and should instead seek to provide incentives for emission reductions. While it will be challenging to meet the CO₂ intensity target of 550 g/kWh for the electric power sector by 2020, multiple pathways exist for achieving lower targets over a longer timeframe. Our initial analysis shows that carbon prices of 35–40$/tCO₂ make CCS technologies on coal-based generation cost-competitive against other modes of generation and that carbon prices higher than 100$/tCO₂ favor a major expansion of CCS. The next step is to confirm these initial results with more detailed modeling that takes into account granularity across China's energy sector at the provincial level.     

Decomposition for emission baseline setting in China's electricity sector

Decomposition analysis is used to generate carbon dioxide emission baselines in China's electricity sector to the year 2020. This is undertaken from the vantage point of the final consumer of electricity, and therefore considers factors influencing electricity demand, efficiency of generation, sources of energy used for generation purposes, and the effectiveness of transmission and distribution. It is found that since 1980, gains in efficiency of generation have been the most important factor affecting change in the emission intensity of electricity generated. Based upon known energy and economic policy, efficiency gains will continue to contribute to reductions in the emission intensity of electricity generated, however, fuel shifts to natural gas and increases in nuclear generation will further these trends into the future. The analysis confirms other sources in the literature that decomposition is an appropriate technique available for baseline construction, thereby suitable for the emerging carbon market and its related mechanisms.     

Calculating residential carbon dioxide emissions—a new approach

All Annex 1 Parties are required to submit an annual national greenhouse gas inventory to the United Nations Framework Convention on Climate Change using the common report format. The inventory is to include a sectoral report for energy, listing different sectors and their associated greenhouse gas emissions (principally carbon dioxide, methane, and nitrous oxide). The sectors and their associated emissions can be used as a benchmark to show changes in emissions over time. In certain cases, these changes can be misleading, since an apparent emission reduction in one sector can result in a significant increase in the emissions of another, typically electricity production. Applying the emissions to the sector responsible for the final energy demand (as opposed to the sector that generates the energy) allows researchers and policy makers to develop reduction strategies that are targeted to the demand.This paper demonstrates this by removing the equivalent residential emissions from category A.1.a (Public Electricity and Heat Production) and applying them to category A.4.b (Residential) in Nova Scotia, a Canadian province that relies heavily on fossil fuels for electrical generation. The shift in emissions changes an apparent 4.1 percent decrease in Nova Scotia's residential emissions between 1991 and 2001 to an 8.2 percent increase.     

Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options

In Copenhagen climate conference China government promised that China would cut down carbon intensity 40–45% from 2005 by 2020. CET (carbon emissions trading) is an effective tool to reduce emissions. But because CET is not fully implemented in China up to now, how to design it and its potential impact are unknown to us. This paper studies the potential impact of introduction of CET on China’s power sector and discusses the impact of different allocation options of allowances. Agent-based modeling is one appealing new methodology that has the potential to overcome some shortcomings of traditional methods. We establish an agent-based model, CETICEM (CET Introduced China Electricity Market), of introduction of CET to China. In CETICEM, six types of agents and two markets are modeled. We find that: (1) CET internalizes environment cost; increases the average electricity price by 12%; and transfers carbon price volatility to the electricity market, increasing electricity price volatility by 4%. (2) CET influences the relative cost of different power generation technologies through the carbon price, significantly increasing the proportion of environmentally friendly technologies; expensive solar power generation in particular develops significantly, with final proportion increasing by 14%. (3) Emission-based allocation brings about both higher electricity and carbon prices than by output-based allocation which encourages producers to be environmentally friendly. Therefore, output-based allocation would be more conducive to reducing emissions in the Chinese power sector.     

Tracking the genealogy of CO2 emissions in the electricity sector: An intersectoral approach applied to the Spanish case

This paper analyses the factors leading to CO₂ emissions in the Spanish electricity generation sector in order to propose effective mitigation policies aimed at tackling those emissions. Traditionally, two broad categories of those factors have been considered in the literature: those related to the supply of electricity (technological features of the sector) and those related to the level of economic activity (demand factors). This paper focuses on an additional element, which has usually been neglected, the structural factor, which refers to the set of intersectoral transactions (related to the technologies used in other productive sectors) which connect, in either a direct or an indirect way, the general economic activity with the supply of electricity and, thus, with the emissions of the electricity generation sector. This analysis allows us to identify the so-called “sectors structurally responsible for emissions” (SSER), whose production functions involve transactions which connect the demand for goods and services with the emissions of the electricity generation sector. The methodology is based on an input–output approach and a sensitivity analysis. The paper shows that there are structural rigidities, deeply ingrained within the economic system, which lead to emissions from the electricity generation sector for which this sector cannot be held responsible. These rigidities limit the effectiveness of policies aimed at emissions mitigation in this sector.     

Estimation of carbon baselines for power generation in India: the supply side approach

In this paper, attempt has been made to develop framework for estimating realistic baseline for carbon emissions from power generation in India till the end of the Eleventh Five Year Plan Period (2010–2011). This is done through development of a realistic generation plan till 2010–2011, taking into account new Greenfield projects, capacity augmentation/addition plans and commissioning schedule of new projects and incorporating the impacts of government imposed norms for energy conservation in baseline estimate. Such a supply side framework for estimation of baselines is useful for developing countries like India where the electricity markets are supply constrained. Also, the paper demonstrates the evaluation of additional emission reductions over and above the business as usual baseline by identification and quantification of future possibilities of changes in specific coal consumption and auxiliary consumption of around 70 existing thermal power plants using data envelopment analysis (DEA).     

Interactions between electricity-saving measures and carbon emissions from power generation in England and Wales

The relationship between electricity demand reduction and the consequent change in carbon emissions is central to greenhouse gas emissions policy. This paper examines this relationship for the power system of England and Wales. Previous analysis showed that the commonly used conversion factor based on the system average emission factor significantly underestimates these savings (Hitchin and Pout, 2002. The carbon intensity of electricity: how many kgC per kWhe?. Building Serv. Eng. Res. Technol. 23(4)). Thus any policy analysis based on the system-average emission factor will under-estimate the potential for carbon savings from reductions in electricity demand. The present paper extends the previous analysis by using more detailed modelling to explore differences between demand reductions of differing load shape and magnitude; and the sensitivity of these figures to changes of the fuel mix of the generation system.     

Evaluating renewable portfolio standards and carbon cap scenarios in the U.S. electric sector

This report examines the impact of renewable portfolio standards (RPS) and cap-and-trade policy options on the U.S. electricity sector. The analysis uses the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) model that simulates the least-cost expansion of electricity generation capacity and transmission in the U.S. to examine the impact of a variety of emissions caps—and RPS scenarios both individually and combined. The generation mix, carbon emissions, and electricity price are examined for various policy combinations simulated in the modeling.     

CO2 emissions structure of Indian economy

This paper analyses carbon dioxide (CO₂) emissions of the Indian economy by producing sectors and due to household final consumption. The analysis is based on an Input–Output (IO) table and Social Accounting Matrix (SAM) for the year 2003–04 that distinguishes 25 sectors and 10 household classes. Total emissions of the Indian economy in 2003–04 are estimated to be 1217 million tons (MT) of CO₂, of which 57% is due to the use of coal and lignite. The per capita emissions turn out to be about 1.14 tons. The highest direct emissions are due to electricity sector followed by manufacturing, steel and road transportation. Final demands for construction and manufacturing sectors account for the highest emissions considering both direct and indirect emissions as the outputs from almost all the energy-intensive sectors go into the production process of these two sectors. In terms of life style differences across income classes, the urban top 10% accounts for emissions of 3416 kg per year while rural bottom 10% class accounts for only 141 kg per year. The CO₂ emission embodied in the consumption basket of top 10% of the population in urban India is one-sixth of the per capita emission generated in the US.     

Incentives of carbon dioxide regulation for investment in low-carbon electricity technologies in Texas

This paper compares the incentives a carbon dioxide emissions price creates for investment in low carbon dioxide-emitting technologies in the electricity sector. We consider the extent to which operational differences across generation technologies – particularly, nuclear, wind and solar photovoltaic – create differences in the incentives for new investment, which is measured by the operating profits of a potential entrant. First, astylized model of an electricity system demonstrates that the composition of the existing generation system may cause electricity prices to increase by different amounts over time when a carbon dioxide price is imposed. Differences in operation across technologies therefore translate to differences in the operating profits of a potential entrant. Then, a detailed simulation model is used to consider a hypothetical carbon dioxide price of $10–$50 per metric ton for the Electric Reliability Council of Texas (ERCOT) market. The simulations show that, for the range of prices considered, the increase in electricity prices is positively correlated with output from a typical wind unit, but the correlation is much weaker for nuclear and photovoltaic. Consequently, a carbon dioxide price creates much stronger investment incentives for wind than for nuclear or photovoltaic technologies in the Texas market.     

How information and communication technology drives carbon emissions: A sector-level analysis for China

Understanding the carbon implications of information and communication technology (ICT) is critical for tackling climate change challenges in the digital era. This paper develops an embodied carbon analysis framework by integrating input-output approaches to explore the extent to which and how ICT drives carbon emissions at the sector level. With the proposed framework, we not only assess the carbon emissions embodied in various ICT subsectors but also reveal the formation and changing mechanism by identifying their source sectors, transfer paths, and economic drivers. Using China as a case study, we find that ICT sector is far from being environment-friendly while considering its embodied carbon impacts, which are dozens of times greater than the direct impacts. This is because ICT sector can induce significant amounts of emissions through its requirement for carbon-intensive intermediate inputs from non-ICT sectors. The electricity sector and basic material sectors (e.g. chemicals, metal, and non-metal) are the most important carbon sources, and are involved in major carbon transfer paths. The fast growth of embodied emissions in ICT sector is driven by the large-scale expansion of final demand for ICT products, although improvements in upstream production efficiency have largely slowed the growth. We suggest that integrated carbon management strategies incorporating mitigation measures for specific sectors, supply chains, and economic drivers are particularly required for addressing ICT-related carbon emission issues.     

Joint electricity and carbon market for Northeast Asia energy interconnection

Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades. The key challenges for achieving this goal are carbon emission trading and electricity sector regulation, which are also the major components of the carbon and electricity markets, respectively. In this paper, a joint electricity and carbon market model is proposed to investigate the relationships between electricity price, carbon price, and electricity generation capacity, thereby identifying pathways toward a renewable energy transition under the transactional energy interconnection framework. The proposed model is a dynamically iterative optimization model consisting of upper- level and lower-level models. The upper-level model optimizes power generation and obtains the electricity price, which drives the lower-level model to update the carbon price and electricity generation capacity. The proposed model is verified using the Northeast Asia power grid. The results show that increasing carbon price will result in increased electricity price, along with further increases in renewable energy generation capacity in the following period. This increase in renewable energy generation will reduce reliance on carbon-emitting energy sources, and hence the carbon price will decline. Moreover, the interconnection among zones in the Northeast Asia power grid will enable reasonable allocation of zonal power generation. Carbon capture and storage (CCS) will be an effective technology to reduce the carbon emissions and further realize the emission reduction targets in 2030-2050. It eases the stress of realizing the energy transition because of the less urgency to install additional renewable energy capacity.     

The effect of energy end-use efficiency improvement on China’s energy use and CO2 emissions: a CGE model-based analysis

With its rapid economic growth, China is now confronted with soaring pressure from both its energy supply and the environment. To deal with this conflict, energy end-use efficiency improvement is now promoted by the government as an emphasis for future energy saving. This study explores the general equilibrium effect of energy end-use efficiency improvement on China’s economy, energy use, and CO₂ emissions. This paper develops a static, multisector computable general equilibrium model (CGE) for China, with specific detail in energy use and with the embodiment of energy efficiency. In order to explore the ability of subsidizing non-fossil-generated electricity on moderating potential rebound effects, in this model, the electricity sector was deconstructed into five specific generation activities using bottom–up data from the Chinese electricity industry. The model is calibrated into a 16-sector Chinese Social Accounting Matrix for the year 2002. In the analysis, seven scenarios were established: business as usual, solely efficiency improvement, and five policy scenarios (taxing carbon, subsidized hydropower, subsidized nuclear power, combination of taxing carbon and subsidized hydropower, combination of taxing carbon and subsidized nuclear power). Results show that a sectoral-uniform improvement of energy end-use efficiency will increase rather than decrease the total energy consumption and CO₂ emissions. The sensitivity analysis of sectoral efficiency improvement shows that efficiency improvements happened in different sectors may have obvious different extents of rebound. The three sectors, whose efficient improvements do not drive-up total national energy use and CO₂ emissions, include Iron and Steel, Building Materials, and Construction. Thus, the improvement of energy end-use efficiency should be sectoral specific. When differentiating the sectoral energy-saving goal, not only the saving potential of each sector but also its potential to ease the total rebound should be taken into account. Moreover, since the potential efficiency improvement for a sector over a certain period will be limited, technology measures should work along with a specific policy to neutralize the rebound effect. Results of policy analysis show that one relatively enhanced way is to combine carbon taxing with subsidized hydropower.     

Temporal carbon intensity analysis: renewable versus fossil fuel dominated electricity systems

In order to overcome the negative effects of climate change and ensure a global low-carbon future, decarbonizing the electricity sector has been recognized as an important focus area. Internationally, policymakers use average carbon intensity (in gCO₂-e/kWh) in calculating greenhouse gas (GHG) emissions from the electricity system. However, average carbon intensity is a single rate and a fixed quantity; thus, it does not provide any information about the time-varying nature of carbon intensity. The focus of this paper is to show the usefulness of time-varying carbon intensity estimation, which can provide detailed insights into GHG emissions, and help in identifying potential emission cut opportunities from the electricity sector in order to lessen atmospheric pollution. Time-varying carbon intensity estimation (i) reveals temporal variability of carbon intensity, (ii) explores the interplay between generations and emissions, (iii) identifies peak carbon-intensive hours, and (iv) provides evidence for designing appropriate demand-side management strategies with respect to GHG emission reduction.     

The responsibility for carbon emissions and carbon efficiency at the sectoral level: Evidence from China

This work reviews benefit-based principles to measuring responsibility for carbon emissions at the sectoral level using environmental input–output analysis. Several new emissions multipliers are proposed to measure sectoral carbon efficiency. These principles are used in an empirical analysis of carbon emissions in China, and differences between the principles are compared. The results indicate that all principles considered can prevent double-counting of emissions but that different principles may lead to significantly different attributions of responsibility for carbon emissions and to different multiplier values for particular sectors. Electricity and heat supply is found to be the sector with the highest emissions responsibility under all but the consumer responsibility principle, as well as the highest carbon multiplier under all principles. However, this sector's responsibility under producer responsibility principles is greater than that under other principles. Basic metals and transportation and post and telecommunication are among the top five sectors with the greatest responsibilities under all but the consumer responsibility principle, whereas construction has the highest consumer responsibility among all sectors. The pros and cons and policy implications of each principle are also discussed.     

Carbon-sensitive meta-productivity growth and technological gap: An empirical analysis of Indian thermal power sector

This paper measures carbon-sensitive efficiency and productivity growth in technologically heterogeneous coal-fired thermal power plants in India for the period of 2000 to 2013. It uses a unique data set of 56 plants, obtained petitioning the Right to Information Act 2005. We apply ‘within-MLE’ fixed effects stochastic frontier model to get consistent estimates of meta-directional output distance function. The thermal power plants are grouped into two categories: central sector and state sector. We find that the state sector plants have higher potential to simultaneously increase electricity generation and reduce carbon emissions than the central sector plants. If all the state and central sectors plants were made to operate on the meta-frontier, reduction of 98 million tonnes of CO₂ could have been achieved. Carbon-sensitive productivity growth in the central sector plants is higher than the plants in state sector, though in both the sectors productivity growth is governed by carbon-sensitive innovation effect. Commercialisation or autonomy in electricity generation also induces carbon-sensitive productivity growth and reduces carbon-sensitive productivity growth gap.     

Sharing mitigation burden among sectors in China: Results from CEEPA

Based on the China Energy and Environmental Policy Analysis model which takes into account the current characters and potential reforms of energy markets in China, and from the perspective of economy-wide cost-effectiveness, this study aims to analyze how carbon mitigation burdens should be shared among key emission sectors in China, as well as how these sectors would behave to meet their burdens. This study finds that in general, allocating mitigation burdens based on historical emissions could realize the national target in a cost-effective way. However, some adjustments should be made to the coal, electricity, and transportation sectors. The mitigation targets for all sectors, especially for the coal sector, should not be set too high in the short-term. And the burden shared by the electricity sector should increase if electricity pricing is deregulated; meanwhile, energy efficiency and the energy input structure should be improved in the electricity sector.     

Adoption of energy efficient technologies and carbon abatement: the electricity generating sector in India

A behavioral micro-economic framework was developed to analyze the impact of alternative mixes of policy reforms that eliminate existing regulatory distortions and a carbon emissions-tax on incentives to adopt energy efficient technologies and their implications for carbon emissions and output. An empirical application of this framework to the electricity-generating sector in India demonstrates that elimination of existing domestic and trade policy distortions has the potential to reduce carbon emissions even in the absence of an emissions-tax, by inducing the adoption of energy efficient technologies. In the presence of these policy reforms, an emissions-tax achieves a given level of abatement with higher output levels than in the absence of these reforms. This analysis indicates the potential for achieving a complementarity between the goals of reducing carbon emissions and increasing electricity generation by identifying the regulatory distortions that are hindering adoption of energy efficient technologies and tailoring policy reforms to specific distortions.