International audienc

International audienceLife-cycle assessment and carbon footprint studies are widely used by decision makers to identify climate change mitigation options and priorities at corporate and public levels. These applications, including the vast majority of emission accounting schemes and policy frameworks, traditionally quantify climate impacts of human activities by aggregating greenhouse gas emissions into the so-called CO2-equivalents using the 100-year Global Warming Potential (GWP100) as the default emission metric. The practice was established in the early nineties and has not been coupled with progresses in climate science, other than simply updating numerical values for GWP100. We review the key insights from the literature surrounding climate science that are at odds with existing climate impact methods and we identify possible improvement options. Issues with the existing approach lie in the use of a single metric that cannot represent the climate system complexity for all possible research and policy contexts, and in the default exclusion of near-term climate forcers such as aerosols or ozone precursors and changes in the Earth’s energy balance associated with land cover changes. Failure to acknowledge the complexity of climate change drivers and the spatial and temporal heterogeneities of their climate system responses can lead to the deployment of suboptimal, and potentially even counterproductive, mitigation strategies. We argue for an active consideration of these aspects to bridge the gap between climate impact methods used in environmental impact analysis and climate science

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SummaryIn the ongoing debate about the climate benefits of fuel switching from coal to natural gas for power generation, the metrics used to model climate impacts may be important. In this article, we evaluate the life cycle greenhouse gas emissions of coal and natural gas used in new, advanced power plants using a broad set of available climate metrics in order to test for the robustness of results. Climate metrics included in the paper are global warming potential, global temperature change potential, technology warming potential, and cumulative radiative forcing. We also used the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) climate change model to validate the results. We find that all climate metrics suggest a natural gas combined cycle plant offers life cycle climate benefits over 100 years compared to a pulverized coal plant, even if the life cycle methane leakage rate for natural gas reaches 5%. Over shorter time frames (i.e. 20 years), plants using natural gas with 4% leakage rate have similar climate impacts as those using coal, but are no worse than coal. If carbon capture and sequestration becomes available for both types of power plants, natural gas still offers climate benefits over coal as long as the life cycle methane leakage rate remains below 2%. These results are consistent across climate metrics and the MAGICC model over a 100-year timeframe. Although it is not clear whether any of these metrics are better than the others, the choice of metric can inform decisions based on different societal values. For example, whereas annual temperature change reported may be a more relevant metric to evaluate the human health effects of increased heat, the cumulative temperature change may be more relevant to evaluate climate impacts, such as sea level rise, that will result from the cumulative warming.

Life Cycle Analysis of Natural Gas Extraction and Power Generation 3 Upstream Data Upstream data include the supply shares of natural gas and coal, as well as the energy requirements and material flows for the key activities for extraction, processing, and transport. These data are used to model the RMA and RMT stages in NETL's natural gas and coal models. 3.1 Natural Gas The primary unit processes of this model are based on data compiled by NETL. Secondary unit processes, such as production of construction materials besides steel, are based on third party data. Appendix A includes details on how these data are assembled in a model and references the detailed documentation in NETL's unit process library. Where data for the inventory are available, high and low values are collected, along with an expected value. When results are presented, three cases are shown: an expected case, a high case, and a low case. The high and low results (error bars on the results) are a deterministic representation of the variability on the data and not indicative of an underlying distribution or likelihood. 3.1.1 Sources of Natural Gas This inventory and analysis includes results for natural gas domestically extracted from seven sources in the lower 48 states: