The climate test: a tool to evaluate alignment of energy infrastructure decisions with climate goals

Figures & data

Figure 1. Conceptual framework, data source types, and component inputs metrics for the climate test decision metric to evaluate emissions significance of individual fossil fuel projects.

Table 1. Summary of data inputs (baseline and Monte Carlo analysis ranges) used for the climate test case study of a natural gas pipeline.

Cat.	ID	Fig 2 ID	Climate significance metric parameters:	Type	Input influencing value	Distribution Type	Simulation value ranges
			Key inputs, intermediate result values				Units	Baseline	Exploratory range (n = 10,000)			Reasonable range (n = 10,000)
									Min	Median	Max	Min	Median	Max
Climate Scenario Characteristics (CS)	CS-1	(vi)	Climate scenario ID	Input	Source: IPCC 1.5°C Report Database (IAMC/IIASA) (Huppmann et al., 2018)	Discrete – uniform	–	N/A – Median across scenarios	Compatible model scenarios Labelled: 1–18			Compatible model scenarios labelled: 1–18
	CS-1A	(5)	Budgeted carbon emissions*	Intermed. result	CS-1, P-1Aiia-d	Indirect	GtCO2	66.90	20.61	62.14	103.71	30.63	64.36	98.20
	CS-1B	(8)	Fossil energy demand				EJ	1393.92	354.31	1347.42	3464.43	734.44	1363.61	2853.11
Project Characteristics (P)	P-1	(A)	Project lifecycle emissions	Intermed. result	P-1A, EES-1	Indirect	GtCO2	0.668	0.000156	0.423	1.297	0.107	0.502	1.076
	P-1A	=(2) + (3)	Project direct emissions	Intermed. result	Source: Project documentation (FERC, 2019); P-1Aiia-d, P-1Aiii	Indirect	GtCO2	0.00797	0.000087	0.0051	0.0152	0.0013	0.0060	0.0126
	P-1Aiia	(i)	Project construction start year	Input	Source: Project documentation (FERC, 2019) or default	None	–	2020	2020			2020
	P-1Aiib	(ii)	Project construction duration	Input		None	Years	5	5			5
	P-1Aiid	(iii)	Project operating lifespan	Input		Triangle	Years	26	0.3	25.5	49.7	10.2	25.5	39.9
	P-1Aiii	(iv)	Project capacity utilization factor	Input		Triangle	%	95.8%	1%	69%	100%	26%	77%	100%
	P-1B	(1)	Project indirect emissions: upstream	Intermed. result	P-1Ai, P-1Aiia-d, EES-1A	Indirect	GtCO2	0.085	0	0.053	0.223	0.010	0.063	0.181
	P-1C	(4)	Project indirect emissions: downstream	Intermed. result	P-1Ai, P-1Aiia-d, EES-1B	Indirect	GtCO2	0.576	0	0.365	1.117	0.09243	0.432	0.927
	P-2	(C)	Project lifetime energy supplied	Intermed. result	P-1Ai, P-1Aiia-d	Indirect	EJ	11.90	0.1295	7.561	22.67	2.003	8.962	18.90
Existing Energy System Characteristics (EES)	EES-1	(v)	Indirect emissions factor ID	Input	Source: NETL LCA (Littlefield et al., 2019)	Discrete – non-uniform	–	2 (mean)	1 (2.5%ile)	2 (mean)	3 (97.5%ile)	1 (2.5%ile)	2 (mean)	3 (97.5%ile)
	EES-2	(6)	Committed emissions	Intermed. result	Source: Tong et al. (2019), P-1Aii, EES-2A,EES-2B,EES-2C	Indirect	GtCO2	50.35	10.93	41.94	55.87	36.06	49.67	56.21
	EES-2A	(x)	Additive factor for upstream activities	Input	Source: NETL LCA (Littlefield et al., 2019)	Triangle	%	10%	5.54%	13%	20.40%	5.63%	13%	20.4%
	EES-2B	(vii)	Share of committed emissions realized by target date	Input	N/A	Triangle	%	100%	0.40%	70.70%	100%	80.1%	94.1%	100%
	EES-2C	(viii)	Years to target date for linear decline to share of committed emissions realized	Input	N/A	Triangle	years	0	0.04	17.68	25.00	10.07	20.61	25.00
	EES-3	(9)	Committed energy: via emission intensity	Intermed. result	EES-2, EES-3A	Indirect	EJ	725.15	151.93	589.58	788.85	507.61	698.42	752.58
	EES-3A	(ix)	Linear percentage change in committed emissions intensity to 2050	Input	N/A	Triangle	%	0%	−20%	0%	20%	−5%	0%	5%

Figure 2. Graphical schematic of climate test components, labelled (A)–(G), and relationship to input parameters, labelled (i)–(x), that were varied during Monte Carlo and single factor sensitivity analyses. The graphs in the top row are all emissions-related, with units of GtCO₂, and combine to create the emissions impact component (E), or the numerator of the emissions significance metric (G). Similarly, the graphs in the second row are all energy-related, with units of EJ, and combine to create the energy contribution component (F), or the denominator of the emissions significance metric (G). Across rows, from left to right, the graphs in the leftmost column are all characteristics of the project being evaluated, which are then used to compare the project to the characteristics of the climate goal, given existing energy system characteristics, found in the middle column. Together, simulated variations in the input parameter values drive variation in the emissions impact and energy contribution component results, and produce a distribution of emissions significance metric results, as shown in the far right graph. Each simulation result is judged against the same decision criteria of ≤1 for projects consistent with the climate goal and >1 for projects with a significant climate impact.

Figure 3. Frequency histogram for climate test emissions significance results from the Monte Carlo simulation using the wide exploratory range (left) and the narrower ‘reasonable’ range of the input variables (right).

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Data availability statement

All data used to support this analysis, as well as a beta version of the climate test tool itself, are available on FigShare at: 10.6084/m9.figshare.19606225.