Damage vector for life-cycle analysis

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Question

What are the damages per unit purchased commodity using a life-cycle assessment?

Answer

There are two parts to this: damage vector and damage factor. For details, see {{#opasnet_base_link:Op_en5902}} .

For an example of an actual LCA, see LCA of a coffee cup.

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library(OpasnetUtils)

# [[Damage vector for life-cycle analysis]]. We need impactsPerDollar, damagesPerImpact, and damages.
objects.latest("Op_en5902", code_name = "initiate") 

impactsPerDollar <- EvalOutput(impactsPerDollar)
damagesPerImpact <- EvalOutput(damagesPerImpact)

cat("Impacts per dollar\n")
oprint(head(impactsPerDollar@output))

cat("Damages per impact\n")
oprint(head(damagesPerImpact@output))

Rationale

Damages are calculated using this formula:

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle damages_{s,c,d} = \frac{ activity_s * impactsPD_{s,c} * damagesPI_{c,d} * 365}{normalisation_d},}

where

damages are the damages caused by the activity in meaningful units such as DALYs,
activity are the direct inputs of an activity (in Euro), such as in LCA of a coffee cup, table Direct inputs of a coffee cup,
impactsPD or impactsPerDollar are data from the damage vector (size 430*17) in Opasnet Base of this page,
damagesPI or damagesPerImpact are data from the Damage factors table below,
normalisation are impacts turned into meaningful units such as in Normalisation data for life cycle assessments#Data
the outcome is scaled by 365 to reflect yearly impacts ⇤--#: . I'm not sure why, if the activity is in functional units and it is not clear that the activity happens once per day. --Jouni (talk) 17:30, 29 January 2014 (EET) (type: truth; paradigms: science: attack)
s is purchasing sector,
c is unique category (this is often summed up so that it does not show in the damage variable),
d is damage index.

Data

Damage vector

The damage vector contains 430 purchasing sectors and 17 unique categories of impact. See {{#opasnet_base_link:Op_en5902}} .

Damage factors

Damage factors are described in the table below.

⇤--#: . The units should be explained! --Jouni (talk) 07:34, 28 December 2013 (EET) (type: truth; paradigms: science: attack)

Damage factors(-)
Obs	Unique_categories	Human health	Ecosystem quality	Climate change	Resources	Water consumption
1	Carcinogens	0.0000028	0	0	0	0
2	Non-carcinogens	0.0000028	0	0	0	0
3	Respiratory inorganics	0.0007	0	0	0	0
4	Ionizing radiation	0.00000000021	0	0	0	0
5	Ozone layer depletion	0.00105	0	0	0	0
6	Respiratory organics	0.00000213	0	0	0	0
7	Aquatic ecotoxicity	0	0.0000502	0	0	0
8	Terrestrial ecotoxicity	0	0.00791	0	0	0
9	Terrestrial acidification/nutrification	0	1.04	0	0	0
10	Land occupation	0	1.09	0	0	0
11	Aquatic acidification	0	0	0	0	0
12	Aquatic eutrophication	0	0	0	0	0
13	Global warming	0	0	1	0	0
14	Non-renewable energy	0	0	0	1	0
15	Mineral extraction	0	0	0	1	0
16	Water withdrawal	0	0	0	0	0
17	Water consumption	0	0	0	0	1

Calculations

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library(OpasnetUtils)

# Create the damage factor table based on data from [[Damage vector for life-cycle analysis]]

damagesPerImpact <- opbase.data("Op_en5902.damage_factors")
damagesPerImpact$Obs <- NULL
damagesPerImpact <- Ovariable("damagesPerImpact", damagesPerImpact)

# Take the impact factor table from the database. Do the same procedures as with damagesPerImpact.

impactsPerDollar <- Ovariable("impactsPerDollar", data = opbase.data("Op_en5902"))

damages <- Ovariable("damages", 
	dependencies = data.frame(Name = c(
		"damagesPerImpact", 
		"impactsPerDollar",
		"activity",
		"normalisation"
	)),
	formula = function(...) {
		
		out <- activity * impactsPerDollar * damagesPerImpact # Actual equation.

#		out <- CollapseMarginal(
#			out, 
#			cols = "Unique_categories", 
#			fun = "sum"
#		)

#		out <- out / normalisation * 365 # Normalise and scale to daily values.

		return(out)
	}
)

objects.store(damagesPerImpact, impactsPerDollar, damages)
cat("Ovariables damagesPerImpact, impactsPerDollar, damages saved.\n")

Keywords

References

Related files