Spatially-Explicit Environmental and Economic Assessment of Negative Emissions Technologies

Global-scale modeling of future energy pathways compatible with the Paris Climate Agreement indicates that deployment of negative emissions technologies (NETs) in the US will be essential to avoid end-of-century temperature rise greater than 1.5-2 °C. These platforms aid existing mitigation efforts by actively removing CO2 from the atmosphere. Top-down models have been very effective at delineating the requirements for NETs (how much) under climate constraints. This dissertation aims at providing a bottom-up framework for furthering decision-making by understanding what locations (where) and which technological options (how) should be pursued. Specifically, we have carried out life-cycle analysis (LCA) and techno-economic analysis (TEA) of the two most prominent NETs; i.e., bioenergy with CO2 capture and storage (BECCS) and direct air capture (DAC).

We used LCA and TEA to understand how regional biophysical and socio-technical features influence the environmental and economic performance of BECCS. We evaluated both terrestrial BECCS (T-BECCS), which makes use of terrestrial crops, and aquatic BECCS (A-BECCS), which makes of marine macroalgae (“seaweed”). Our first analysis revealed that spatiality strongly influences the environmental performance of the various stages making up the A-BECCS life cycle. Results indicate that only the Gulf of Mexico region could offer appealing A-BECCS because of a confluence of suitable storage options and marine biomass hotspots. Our second study revealed that spatiality strongly influences the transport and storage (T&S) portions of the BECCS life cycle. Still, our results indicate that 40-65% of land area could deliver system-integration costs compatible with 2030 carbon prices. Results are strongly influenced by the cost of geologic sequestration, as several reservoirs offering large theoretical storage potential are characterized by exorbitant costs due to high depths and low permeabilities. Locations such as the Southeast present appealing BECCS readiness owing to high biomass productivity interspersed with well-explored sinks.

Our BECCS analysis also reveals that some locations with good proximity to high-quality geological storage sites are not appealing for BECCS deployment (e.g., the Southwest and West). Based on mapping, we noted that many of these locations also produce large excess quantities of renewable electricity during the daytime. We hypothesized that this surplus electricity could be utilized to power DAC. We therefore conducted a contextually-explicit TEA to estimate system costs and potential. We estimated that 0.68-4.30 Mt-CO2/year could be profitably sequestered via DAC (as powered by excess electricity) within the next two years using this concept. This amount could increase up to an average of 15 Mt-CO2/year during 2035-2050 based on our simulations of the US Mid-Century Strategy for Deep Decarbonization, which constitutes 10% of the US’ negative emissions budgets in the same period.

Finally, our analysis of the LCA literature showed us the need for a metric for comparison across dissimilar NETs. We therefore conducted a critical review on literature pertaining to normalized carbon metrics to document this need. Using case studies drawn from recent literature, we illustrate the value of a new metric, carbon return on investment (CROI), and showcase its utility and versatility in prioritizing CO2 as the primary goal for NETs. We also make key recommendations for LCA practitioners pertaining to how to calculate and interpret the CROI metric.

Across these analyses, the ranked-order contributions of this work include: (1) designing and showcasing how spatially-explicit LCA and TEA reveal interesting outcomes that would not otherwise be apparent, (2) demonstrating the role of complementary NETs in the US and how they could be deployed to serve synergistic benefits, and (3) addressing the need for transparent assessment of NET processes via critical accounting of CO2 emissions and removals.