For the time being, there will be no change to the data on the site, which remains unchanged from the CARMA 2.0 release in August, 2008. Our hope is to make the upgraded database public within six months.

Check back with the CARMA blog for updates as the new database comes together.

I want to make clear that the numbers discussed here and in the articles referenced above are not from a CGD “report” on India’s carbon emissions. The data in question come from the Carbon Monitoring for Action (CARMA) global database (online at www.carma.org), which provides estimated carbon emissions for power plants and companies in every country – not just India.

Much of CARMA’s data for Indian power plants comes directly from the Ministry of Power’s own emissions database. As part of an effort to secure funding through the U.N.’s Clean Development Mechanism, the Ministry has disclosed information obtained from companies and plants since late 2006, and we have commended them for doing so. The latest version of that data provides power generation and carbon emissions at the plant level for fiscal year 2006-2007 and is used in CARMA 2.0. So far, we have only matched a portion of the plants in the Indian database to the global one used in CARMA; we hope to complete that matching process for CARMA 3.0. Our policy is to report the most recently disclosed data whenever they are available. In this case, that means we must rely upon data for FY 2006-2007.

CARMA directly incorporates publically disclosed data for 16 of NTPC’s 21 plants operating in FY 2006-2007. For the remaining five plants, CARMA’s statistical model provides estimates. Since, upon closer inspection, the Power Ministry actually reports information for these plants, we are provided with an unexpected opportunity to compare the CARMA estimates to the disclosed numbers. For the five plants in question, the CARMA model overestimated power production by 3.8% and overestimated total emissions by 9.7%. Since these plants make up only 30% of NTPC’s total generating capacity, the overall discrepancy between CARMA’s numbers and NTPC’s disclosed totals for FY 2006-2007 are very low (see table below).

NTPC reports that the company’s power production for FY 2007-2008 was about 200 million MWh. For the purposes of CARMA, however, we can only report figures for 2006-2007; the Power Ministry has not yet released the carbon emissions data for FY 2007-2008. It’s possible to generate an estimate, though, since NTPC has reported a coal requirement of 125 million metric tons. Burning that much coal would release about 196 million U.S. tons of CO2, and NTPC also has a number of gas plants that would add to the total. Since NTPC knows precisely how much fuel their plants are consuming and the specific calorific value of that fuel, they should be able to ascertain the accuracy of that estimate. In any event, we’ll know for sure when the Power Ministry releases new data, probably in December.

I also want to examine NTPC’s claims regarding “efficiency” – in this case, the amount of CO2 emitted per unit of power produced. The assertion made in a number of articles is derived from the company’s own internal analysis, utilizing (old) CARMA 1.0 data that (for Indian plants) relied upon reported emissions and power output for FY 2005-2006. The annual totals for that period, as reported to the Power Ministry by NTPC, were about 165 million MWh and 166 million U.S. tons CO2. The company proceeded to substitute power production for 2007-2008 while retaining the emissions figure from 2005-2006. The resulting carbon intensity (CO2 per unit of power) was then compared to other power companies generating more than 125 million MWh per year after 1) removing from consideration companies relying on fossil fuel for less than 50% of power generation and 2) stripping the remaining companies of any carbon-free power plants. NTPC calls the resulting measure “normalized CO2 intensity.”

NTPC’s pairing of power production from 2007-2008 with emissions data from 2005-2006 resulted in an artificially low carbon intensity. I’ve re-created NTPC’s analysis, correcting for this error and using more recent data from CARMA 2.0. The table below shows the results. I’ve included a column showing “unadjusted” CO2 intensity that doesn’t employ NTPC’s step of stripping companies of their carbon-free facilities (nuclear, hydro, wind, solar, etc.).

NTPC is middle-of-the-pack on either measure. This shouldn’t be surprising given the company’s heavy reliance on coal. The companies ranked higher generally utilize more natural gas (which is significantly cleaner than coal) and/or supercritical combustion technology (which is marginally cleaner than the technology employed in NTPC’s plants to date). NTPC does fare quite well when compared to Chinese power companies.

Finally, we shouldn’t let carbon intensity distract us from the big picture. If we are truly serious about avoiding dangerous and rapid climate change, probabilistic modeling suggests an aggressive 2020 target would aim for a global total of 25 gigatons of CO2. For the sake of argument, let’s imagine a world where developed countries and their enormous emissions disappear overnight. This leaves the developing world with the entire 25 Gton CO2 allowance to “play with.” Recent modeling by the Energy Information Administration suggests that total energy production (all uses, not just electricity) in the developing world will be about 100 billion MWh in 2020. Even if we assume profligate, Northern societies eliminate all emissions in a dozen years, meeting the global emissions target would entail an average carbon intensity across the developing world of about 550 pounds of CO2 per MWh – lower than even the most efficient gas plant can reach today. No efficiency improvement will ever reduce the emissions from coal power to anywhere near this level.

It is quite reasonable to decry the inequity of this reality, and there is no shortage of good arguments to that effect. After all, on a per capita basis, India’s power sector emissions are just 6% of those in the United States and 25% of those in China. These considerations must be central to any global agreement to finance clean technology and combat climate change. But let’s not avoid the truth: No matter how efficiently we burn coal, it can only lead to disaster. And India, perhaps more than any other country, will bear the brunt of climate change.

We have also created a Version Tracker page that lists the release dates and changes made to CARMA as we go along. We hope you explore and enjoy the new information and, as always, I encourage you to stay informed of our work by signing up for our newsletter on the right side of the page.

A quick preview: The new data show continuing rapid growth in power-related emissions, especially in China — but also in Europe and the United States. Marginal improvements in plant efficiency are being swamped by the sheer scale of expansion; CARMA 2.0 includes information on nearly 6,500 plants that are planned for construction in the future. And on a slightly lighter (but still serious) note, Antarctica, the last carbon-free continent in CARMA 1.0, now joins the ranks of the emitters.

To be notified when CARMA 2.0 is officially released, join our newsletter on the right side of the homepage.

Although the creators — led by Kevin Gurney of Purdue — generated the data primarily as a tool for expanding scientific exploration of human influence on the carbon cycle, there are sure to be other uses in the social sciences and public policy. The maps, for example, give us the best look yet at the spatial distribution of emissions in the U.S., allowing us to think about areas where the introduction of clean technologies or energy conservation would have the biggest CO2 bang for the buck. That’s not an insignificant issue, because using limited clean technology funds most efficiently must be a priority.

If the methodology can be extended to countries other than the U.S. — as envisioned in Vulcan’s sister project named Hestia — then finding least-cost, highest-mitigation solutions will become easier. It may be that the most effective and efficient use of scarce mitigation funds is not in the U.S. or Europe but, instead, in more rapidly developing societies where the technological status quo is much dirtier and rate of growth in emissions far higher. Detailed spatial data is required to provide a complete answer.

In the vein of CARMA, Vulcan is also a tool for public education and awareness. For example, California — a relatively clean locale in terms of power plant emissions — shows a much dirtier profile once Vulcan’s data on transporation emissions is included. Indeed, one can see emissions clustering around the state’s major transporation and commute routes. And given that some of the Vulcan data is available in hourly time-steps, you can see your region “inhale and exhale” CO2 as people head to work and factories fire up.

All in all, Vulcan is an excellent complement to the CO2 disclosure process and one we hope CARMA users take a look at.

For example, the Sierra Club provides a running list of proposed

These efforts have had an effect. In the case of

The Carbon Monitoring for Action (

The third plant in the list, Mundra, is projected to produce more carbon dioxide per year than the biggest emitters in the

To make

We hope that the widget will make it even easier for our friends in environmental organizations and for climate activists around the world to tap

It is obvious that societies will have difficulty adapting to coming climate change without better information on the magnitude and location of expected climatic impacts at the local level. Identifying the problem spots is only the first step. Detailed projections on a range of natural phenomena are critical to choosing the appropriate intervention.

For example, if the glacier that feeds your local river basin is disappearing, it’s easy enough to see you have a problem. But how you respond will likely depend on what is expected to happen to precipitation, runoff, groundwater recharge, and evapotranspiration as well as seasonal trends in temperature and snowpack accumulation that will impact the rate of deglaciation. The decision to build a dam, expand groundwater extraction, or switch to an entirely different water source is affected by that information.

At present, the deployment of modeled climate projections at the regional or local scale is quite limited. In general, the spatial resolution provided by existing global circulation models (GCMs) is inadequate for local-scale adaptation and planning. Increased temporal resolution is also critical for particular applications. Adequately understanding changes in crop yields, for example, requires projections of overnight temperatures, not just daily means.

For the research community, there are three approaches to addressing this handicap. 1) Statistical “downscaling” of existing GCMs to increase the spatial and temporal resolution of the output. A good example of this technique is a study led by Stanford’s Ros Naylor on the effects of climate variability on Indonesian rice cultivation. 2) The development of country or regional climate models that are “nested” within GCMs. A new 5-year research program at the UK’s Hadley Centre will focus on improving this kind of work. 3) The creation of next-generation, high-resolution GCMs. The U.S.’s National Center for Atmospheric Research (NCAR) has plans to run a high-resolution version of its own GCM at Japan’s Earth Simulator Center, which houses one of the world’s fastest supercomputers.

Each approach has its own strengths — usually reflecting an inherent tradeoff between accuracy and required computing power. I’m particularly excited about the prospects for high-resolution GCMs. I’ve been told we might expect output from the NCAR/Earth Simulator exercises in a couple of years.

That gives the social science/development community an idea of how much time it has to get ready. Once the local-scale climate projections are available, we’ll need research tools able to turn the raw data into actionable information. Issues like agricultural production, health impacts, and water availability are in need of some serious cross-disciplinary research if climate adaptation is going to be effectively addressed.

Natural scientists have been fighting the good fight on the climate front for years. Helping shape the adaptation agenda — with an eye toward maximizing its impact on sustainable development — is one way social scientists can provide valuable assistance as we enter a dangerous period for the world’s most vulnerable societies.