Ranking Negative Emissions Technology Options under Uncertainty

Raymond R Tan,11* Elvin Michael R Almario,[1] Kathleen В Aviso,[1] Jose В Cruz, Jr[3] [4] and Michael Angelo В Promentilla[1]

Introduction

Climate change has been recognized for some tune now as a critical global environmental issue that is approaching crisis levels (Rockstrom et ah, 2009). Atmospheric carbon dioxide (CO,) concentration now exceeds 400 ppm, and continues to rise due to additional emissions driven by economic development and population growth. The problem is further compounded by contributions of other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N,0). Potential adverse impacts of climate change include sea level rise, weather disruptions, ocean acidification, and changes in precipitation patterns, among others. As a result of a strong scientific consensus of the gravity of the problem, public awareness of the climate issue has grown; the international community has also made significant progress towards concerted effort to mobilize solutions, especially via the Paris Agreement and the Sustainable Development Goals (SDGs) of the United Nations (UN). Nevertheless, the problem has progressed to the extent that research is now needed both for mitigation of climate change, and for adaptation to impacts that are already occurring (IPCC, 2018). For example, Tan and Foo (2018) discuss the need for integrated water management strategies as a means to reduce the vulnerabilrty of industrial systems to reduced water availability due to climatic disruptions.

Pacala and Socolow (2004) suggested that deep cuts in GHG emissions can be achieved through massive deployment of existing low-carbon technologies, including energy efficiency enhancement, renewables, nuclear energy, and CO, capture and storage (CCS). They proposed different technologies to be viewed as “stabilization wedges” contributing incremental reductions whose cumulative effect would result in the required reduction of CO, emissions on a global scale. The concept remains applicable today, and is much more plausible than assuming that a single technology can solve the problem. Recent data suggests that even more drastic cuts in GHG emissions are needed in order to avoid catastrophic climate change with a tempera true rise of about 2 °C by the year 2100. A more preferable trajectory should lead to a temperature rise of just 1.5 °C, which will result in serious but manageable impacts; however, achieving this target will require global net GHG emissions to reach zero by mid-century (IPCC, 2018). According to Haszeldine et al. (2018), such a trajectory will require large-scale commercial deployment of CCS and CO, removal (CDR) or negative emissions technologies (NETs).

CDR or NETs are different techniques that can achieve net removal of CO, from the atmosphere. They rely on different mechanisms for carbon fixation. For example, four decades ago, Dyson (1977) speculated on the potential of intensive cultivation of biomass (e.g., via reforestation) at a massive global scale to avert climate crisis; he computed rough estimates of the potential of such a solution, and discussed temporal, laud and nutrient constraints. Today, such natural climate solutions are considered to be important stabilization wedges (Griscom et al., 2017). Other NETs include direct air capture (DAC), bioenergy with CCS (BECCS), biocliar application (BA), soil carbon management (SCM), and enhanced weathering (EW). In the coming decades, these technologies will har e to be deployed throughout the world to help curb GHG emissions down to net zero level by 2050. They will also har e to be systematically evaluated based on various environmental and techno-economic criteria so that the best technology can be used in any given geographic region or country. Quantitative tools for multiple attribute decision making (MADM) are, therefore, essential for ensuring that the best decisions are made towards achieving sustainability (Sikdar. 2009). Such decisions also need to be made even when there are gaps in data due to corporate secrecy or due to the novelty of the technologies involved (Sikdar, 2019).

In this chapter, the classical MADM technique, known as simple additive weighting (SAW) (MacCrimmon, 1968), is used to compare selected NETs under data uncertainty. Interval numbers are used to represent the epistemic uncertainty due to the fundamental lack of knowledge about how NETs perform at commercial scales. The rest of this chapter is organized as follows: Section 2 gives a brief overview of the literature on CDR and NETs. Section 3 describes the generic interval SAW methodology. In section 4, the procedure is then applied to NETs based on data from the literature. The implications of these results are discussed and sensitivity analysis is performed. Finally, section 5 gives the conclusions and suggests prospects for future research. An appendix listing definitions of relevant acronyms is given, along with two other appendices showing the computer code used in the analysis. The latter will allow the reader to replicate or modify the results shown here.

Brief Overview of NETs

NETs achieve removal of CO, from the atmosphere through different mechanisms. This section provides a brief qualitative description of selected NETs for terrestrial deployment. McLaren (2012) and McGlashau et al. (2012) both gave early techno-economic assessments of various NETs, taking into account sequestration potential, cost and technology maturity. In McLaren (2012), maturity was quantified using the Technology Readiness Level (TRL). Tire TRL is a 9-point scale that was originally developed by the United States National Aeronautics and Space Administration (NASA), but which has since been adopted more widely throughout the world (Mankins, 2009). Table 1 defines the different levels in the scale. The physical and economic limits to the deployment of NETs at the global scale were estimated by Smith et al. (2016a); similar studies har e scaled down the estimates to the level of single countries (Smith et al., 2016b; Alcalde et al., 2018). A more recent series of papers give comprehensive reviews of the status of NETs. Tire first of these papers reviews the scientific state-of-the-art of the NETs literature (Minx et al., 2018). Tire second paper by Fuss et al. (2018) surveyed the potential, cost, and risks associated with various NETs. The thud paper discusses the role of technology innovation in the potential scale-up ofNETs to commercially and environmentally significant levels (Nemet et al., 2018).

This chapter considers the terrestrial NETs considered by Smith et al. (2016b) for the United Kingdom and Alcalde et al. (2018) for Scotland. Brief descriptions of the alternatives are given here.

BECCS achieves negative emissions by combining bioenergy with CCS. Conventional bioenergy systems are nearly carbon-neutral because photosynthesis during plant growth offsets downstream CO, emissions from the combustion of biomass. In a system at steady state, the carbon flows to and from the atmosphere balance each other out. Application of CCS to the emissions fr om biomass combustion plants can dramatically reduce the CO, flow into the atmosphere. The carbon flows in the resulting BECCS system are imbalanced, with photosynthetic fixation becoming larger than combustion emissions. The

Table 1. TRL definitions (Mankms, 2009).

Level

TRL definition

1

Basic principles observed and reported.

2

Technology concept and/or application fonnulated.

3

Analytical and experimental cntical function and or characteristic proof-of-concept.

4

Component and or breadboard validation in laboratory environment.

5

Component and/or breadboard validation in relevant environment.

6

System/subsystem model or prototype demonstration in a relevant environment.

7

System prototype demonstration in the planned operational environment.

8

Actual system completed and qualified through test and demonstration in the operational environment.

9

Actual system proven through successful system and or mission operations.

imbalance results in a net removal of atmospheric carbon. As with conventional CCS, BECCS systems require secure geological storage of the captured CO,. In addition. BECCS can be implemented in either dedicated biomass-fired plants, or plants that co-fire biomass with fossil fuels, such as coal. In the latter case, negative emissions only accrue from the CO, emissions from the biomass fraction of the fuel mix.

Afforestation and reforestation (AR) is arguably the most mature and potentially reliable NET option, and is simply the reversal of positive CO, emissions resulting from land use change (LUC). It is also classified as a natural climate solution (Griscom et al.. 2017). Tree growth absorbs CO, from the atmosphere and locks up the carbon in solid form within the plant biomass. Additional carbon is also stored naturally in forest soil as a result. As pointed out by Dyson (1977), large-scale AR can result in significant climatic benefits duiing the period of growth. The negative emissions rate eventually declines as the carbon stock becomes saturated when forests mature over the course of several decades. Despite its simplicity, there are potential drawbacks or barriers, including competition for resources (e.g., land, fertilizer) that are also needed for agriculture to feed the world. A recent study by Bastin et al. (2019) estimated the potential for AR at 205 Gt of carbon, based on an additional 0.9 x Ю9 ha of forest area.

SCM entails modifying agr icultural practices to minimize the loss of naturally-occurring soil carbon (Griscom et al., 2017). As crop residues also contribute to the carbon stock in soil, conditions can be optimized to encourage carbon deposition and, at the same time, minimize the decay that releases CH4. More precise dosing of nitrogen fertilizers can also reduce N,0 emissions. Another NET option, BA, may be regarded as a special case of SCM. Carbonizing biomass via pyrolysis into biochar gives three distinct benefits. First, biochar is more chemically stable than untreated biomass, and can thus result in more permanent sequestration of carbon in soil. Secondly, under proper application conditions, biomass can enrich soil and reduce the need for agricultural inputs (e.g., irrigation water, fertilizers), thus reducing agricultural carbon footprint further. Thirdly, the gaseous and liquid co-products of biocliar production can be used as carbon-neutral fuels that can displace conventional fossil fuel products, thus resulting in additional carbon credits. One major uncertainty in both SCM and BA systems is the extent and permanency of carbon storage in agricultural lands. It has been suggested that large-scale systems may require integrated techniques involving remote sensing to keep track of non-point emissions of GHGs from soil, so that the level of negative emissions can be monitored and verified (Tan, 2019).

DAC involves capture of CO, from air using different solvents or mass separating agents using contactors with different configurations. The underlying physical principle is similar to that of post- combustion CO, capture in CCS and BECCS, except that the CO, needs to be removed from a source with an extremely low concentration (approximately 400 ppm in air) as compared to CO,-rich flue gas from combustion plants. The low source concentration results in thermodynamic penalties which are partially offset because there is no need to achieve high removal rates (Sanz-Perez et al., 2016). Calciumlooping systems using wet scrubbers and calcination to release a pure CO, stream is considered as the most mature DAC technology; other options include supported amine-based capture (McLaren, 2012).

Like CCS and BECCS, DAC requires CO, handling infrastructure and secure geological storage sites for its implementation.

The final NET option considered here is EW. This process takes advantage of the fact that rocks such as basalt naturally react with atmospheric CO, in the presence of moisture (from precipitation); the resulting reaction products dissolve in runoff, and ultimately flow into the sea which acts as the final carbon sink. Under normal conditions, this weathering process occurs at a geologically slow pace on exposed rock surfaces. EW entails artificially accelerating this process by mining the CO,-absorbing rocks and minerals, crushing them into a powder, and applying them to agricultural or marginal lauds (Smith et ah, 2016b). This process creates a larger surface area for contact, and results in accelerated carbon fixation that is potentially significant for climate change mitigation purposes. The potential scale of EW is constrained more by land area and weather conditions than by mineral supply (Smith et ah, 2016a). In the case of agricultural lands, application rate also needs to be calibrated in order to avoid adverse impacts on soil fertility (Smith et ah, 2016b; Alcalde et ah, 2018).

Each of these terrestrial NET alternatives har e their own respective advantages and disadvantages. In addition to the obvious criterion of sequestration potential, the water, energy and nutrient footprints need to be considered due to the stress that they put on limited resources (Smith et ah, 2016). Finally, for commercial scale-up, cost and TRL are also critical factors (McLaren, 2012). Comparison of the alternatives is also hampered by the limited historical data and knowledge, which results in uncertainties in performance or cost estimates. Tlius. there is a need to develop a simple, robust methodology that allows comparison of NETs to be done based on multiple criteria, even under conditions of uncertainty.

  • [1] ! Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines.
  • [2] ! Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines.
  • [3] National Academy of Science and Technology, Science Heritage Building, DOST Complex, General Santos Ave, Taguig,4044 Metro Mamla, Philippines.
  • [4] Cruz & Associates, 19 Piko Street, Silang, Cavite 4118, Philippines. * Corresponding author: This email address is being protected from spam bots, you need Javascript enabled to view it
  • [5] ! Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines.
 
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