A meta-analysis on carbon capture & storage technologies

The environmental concerns associated with the burning of fossil fuels led scientists to explore carbon capture and storage technologies (CCS) as one option for mitigating co₂emissions. One variant of CCS technology that can be applied to fossil sources is bio-energy carbon capture and sequestration (BECCS), a technology that provides an opportunity to create permanent negative carbon emissions (i.e., the removal of co₂from the atmosphere).

Over the past decade, many modeling scenarios have emerged that have incorporated the use of CCS technology as one of many strategies meant to mitigate climate change. As population continues to rise, global warming will be compounded by the increased demand for power and food; straining our ecosystem system. If the world continues to see unhindered emissions of greenhouse gasses, the amount emitted every year would rise from a current level of 30.6 gigatonnes (Gt) in 2010 to an estimated 55 Gt in 2020 (Rogelj, 2011). By the year 2100, this number will jump to 92 Gt representing a rise from 380 ppm to 550 ppm (Gough, 2010). The inclusion of CCS technology, however, can limit this rise dramatically. For example, the introduction of BECCS in long-term climate models shows that reductions, particularly in the power sector, can amount to 1600 Gt of CO2 over the period 2000-2100 (Vuuren, 2013). Depending on the saturation of BECCS technologies within the market, there could be a greater reduction of greenhouse gasses per year. However, does the literature agree on the impact of CCS technologies?

This paper conducts a meta-analysis on the estimated impact of the various CCS technologies on co₂, while evaluating economic costs. This paper evaluates findings from several strands of the literature by conducting meta-analysis on the impact of the technologies on co₂. Although the analysis surveys a vast body of literature, the statistical analysis focuses on impact on co₂ because of its importance and the large volume of research available (90 papers). The statistical analysis investigates the main reasons for the differences found in the literature that reflect research heterogeneity in terms of the period covered, methods, elasticities, and regional coverage, among other factors. The statistical analysis is supplemented with production data, trade data, and conversion coefficients. The data are used to validate the conclusions of the meta-analyses, and simple calculations are used to understand the economic and environmental implications of the conclusions.