The domestic and international experiences with market-based air pollution control and climate change programs demonstrate that comprehensive and accurate information on emissions is critical to a program’s success. Since 1995, the United States has operated a cap-and- trade program to limit sulfur dioxide emissions, an air pollutant that contributes to acid rain, from electric utilities. Under Title IV of the Clean Air Act Amendments of 1990, this program has reduced sulfur dioxide emissions by capping total emissions, distributing allowances to emit sulfur dioxide through a combination of free allocation and auctions, and allowing electric utilities to buy and sell allowances as needed to cover their emissions. Prior GAO reports and independent studies have shown that strong data collection, monitoring, reporting, and verification requirements have been central to this program’s success. First, with respect to setting a baseline level of emissions from regulated entities, the program relied on data spanning several years rather than any one year in particular. Specifically, it used historical average emissions from 1985 to 1987 as the baseline against which to measure reductions required to begin in 1995 and 2000. The use of historical data reduced the covered entities’ incentive to increase emissions prior to the program’s establishment to obtain a greater allowance allocation—the baseline years occurred too far before the announcement of the program. Averaging these data across several years also helped to ensure that the baseline reflected changes in emissions that can result in a given year due to economic and other conditions. As a result, the program achieved greater assurances that it reduced emissions from historical levels. In addition, electricity generating units regulated under Title IV of the Clean Air Act Amendments of 1990 are required to monitor and report their sulfur dioxide, nitrogen oxide, and carbon dioxide emissions, among other data. The monitoring and reporting requirement has ensured a high degree of compliance and overall program integrity. It is important to note that regulating a single pollutant, such as sulfur dioxide, from a largely homogenous population of electric utilities is less complicated than monitoring, reporting, and verifying emissions of up to six different greenhouse gases from diverse types of facilities. The European Union also has experience implementing a cap-and-trade program that illustrates the importance of quality data in a market-based system. As discussed in our November 2008 report, the European Union’s Emissions Trading Scheme (ETS) relies on a cap-and-trade model similar to that used in the U.S. acid rain program. The ETS began with a learning period—phase I—to gain experience with emissions trading from 2005 to 2007. Phase I included approximately 11,000 electric power and industrial installations in 25 member states, which accounted for about half of the EU’s carbon dioxide emissions. While the first phase provided key lessons about emissions trading, its cumulative effect on emissions is uncertain because of a lack of baseline emissions data. In the first phase, each EU member state had to identify which entities to regulate under the ETS (such as power plants, oil refineries, and other manufacturing facilities), obtain baseline emissions data for the covered entities, establish an emissions cap, and determine how many allowances to distribute to each covered entity. At the time, most member states had high-level, aggregated estimates on carbon dioxide emissions that accounted for sources within and outside the scope of the ETS, but did not have baseline data on a facility-specific basis. This facility-specific data was necessary to determine both the total emissions released by all entities covered under the ETS—a downstream program—as well as how many allowances each particular entity would need to cover its annual emissions. In addition, some member states had limited authority to collect data because they did not yet have in place a national law or regulation mandating submission of emissions data. Accordingly, member states based their emissions caps and allocation decisions on business-as-usual emissions projections and baseline data voluntarily submitted by covered entities. The inherent uncertainty about business-as-usual projections—i.e., how actual emissions compare to the emissions that would have occurred in the absence of the ETS—was compounded by the assumptions underlying the models used by member states to forecast emissions. The models incorporated assumptions about factors that influence business-as-usual emissions projections, such as economic growth and relative fuel prices. Some member states made relatively optimistic assumptions about economic growth, which resulted in higher projections of emissions. As such, while the first phase provided key lessons about emissions trading, the lack of facility-specific baseline data means its cumulative effect on emissions is uncertain. The lack of facility-specific baseline data also affected the price of ETS allowances. Under the ETS, covered entities are required to report emissions data that have been verified by third parties to their member states. In 2006, the release of emissions data revealed that the supply of allowances—the cap—exceeded the demand, and the allowance price collapsed. This illustrated the problems that can arise when a program relies on poor baseline emissions data and highlighted the need for accurate baseline data in setting an effective emissions cap and achieving the intended environmental objectives. See figure 2 for a graph displaying the allowance price trends in phase I. As we reported in our prior work on lessons learned from the international climate change programs, many experts participating on a panel we assembled in cooperation with the National Academy of Sciences would not expect the United States to encounter the data challenges experienced in the EU’s first trading phase because some baseline emissions data are already available. Several experts also stated that existing data on fossil fuel consumption are sufficient to establish an emissions trading program. These data can be used to estimate economy-wide carbon dioxide emissions as well as facility-specific data on carbon dioxide emissions from certain industrial sectors, such as power plants that have participated in the US sulfur dioxide emissions trading program. Collecting and reporting emissions data can also provide benefits beyond ensuring the integrity and results achieved through a greenhouse gas reduction program. Such data can be used by researchers to analyze environmental conditions and trends, create atmospheric and economic models, and provide early warning of potential environmental problems. It can also help inform and direct environmental management efforts. The availability of emissions data may aid strategic planning in the private sector, enabling individual firms to make better-informed decisions pertaining to capital investments and energy use. Because many states, municipalities, and private firms have established voluntary climate goals, emissions data will enable these organizations to assess progress and better account for performance. Finally, the availability of emissions data can provide a consistent and transparent basis for comparison between countries, industries, and individual firms and enhance public understanding of emissions sources. Monitoring, reporting, and verification needs for reliable data on greenhouse gas emissions depend first on the purpose and intended use of the data; for example, the data required for a mandatory program to limit emissions may vary substantially from that required for a business or governmental entity that voluntarily tracks its emissions for public relations or other purposes. First, as we have previously reported, the scope of a data collection effort—i.e. monitoring, reporting, and verification activities—is determined by the program’s point of regulation. An upstream mitigation program would affect a relatively small population of regulated entities, such as fuel importers and producers, whose products could be less difficult to measure and report. The quantity of emissions associated with those products could be calculated using available emissions factors. Under a cap-and-trade program, each importer or producer would have to hold an allowance for each ton of carbon dioxide emissions associated with its products. Alternatively, under an emissions tax, each regulated entity would have to pay the government a pre-determined amount of money for each ton of emissions associated with the combustion of its products. Under either system, accurate reporting and verification of emissions would help ensure the integrity of the program, and accurate and reliable baseline data would be necessary to track progress. On the other hand, data collection, monitoring, and verification requirements become more substantial under a downstream program because it could affect a larger population of regulated entities, potentially including industrial facilities, agricultural operations, mobile and other fuel combustion sources, and users of refrigerants. Again, each regulated entity would need to have accurate and reliable data on historical and current emissions, and in some cases, gathering such information would be relatively straightforward. For example, electricity generating units regulated under Title IV of the Clean Air Act Amendments of 1990 are required to monitor and report their carbon dioxide emissions. However, other regulated entities may face greater challenges in determining their emissions due to limited monitoring data or a lack of reliable emissions factors. Furthermore, the data requirements for a mitigation program become more complex and challenging as the number and types of covered activities increases. This challenge may be of particular concern in a downstream program that covers emissions from diffuse sources. Of the six primary greenhouse gases, emissions of some are better characterized than others. For example, carbon dioxide emissions from energy-related activities and cement processing are relatively easy to estimate with a high degree of accuracy, whereas measuring the emissions of other greenhouse gases stemming from other types of activities is more challenging. Specifically, there may be insufficient scientific understanding to develop a data collection methodology, data may be incomplete or missing, or emissions factors may not be sufficiently developed. For instance, nitrous oxide emissions occur from the production of caprolactam—a chemical used to produce a polymer—but there are currently not enough data on the production of caprolactam to estimate these emissions in the United States. In some cases, existing emissions inventories and registries that have been developed for a variety of purposes could help regulated entities in meeting potential requirements to establish baseline emissions levels and monitor, verify, and report their ongoing emissions. For example, the United States Environmental Protection Agency prepares an official U.S. greenhouse gas inventory each year to comply with its commitments under the United Nations Framework Convention on Climate Change (UNFCCC). This inventory provides national information on the activities that cause emissions and removals, as well as background on the methods used to make the calculations.