LCA of a coffee cup

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Question

What are the life cycle impacts of a coffee cup?

Answer

+ Show code- Hide code library(OpasnetUtils) library(ggplot2) objects.latest("Op_en6007", code_name = "answer") # [[OpasnetUtils/Drafts]]. We need truncateIndex. objects.latest("Op_en5902", code_name = "initiate") # [[Damage vector for life-cycle analysis]]. We need damagesPerImpact, impactsPerDollar, damages. objects.latest("Op_en5904", code_name = "initiate") # [[Damage vector for life-cycle analysis]]. We need normalisation. # Take the direct requirements of an activity (in this case, producing a cup of coffee). activity <- opbase.data("Op_en5902.coffee_cup_inputs") activity$Obs <- NULL # Remove the redundant Obs column. cat("Primary prosesses related to a cup of coffee (in Euro)\n") oprint(activity) # This is not needed because zero rows are just redundant and ovariable product is more flexible than matrix product. # Combine the direct requirements of a coffee cup with a full vector of requirements and fill empty cells with 0. #activity <- merge( # unique(EvalOutput(impactsPerDollar)@output["Purchasing_sector"]), # activity, # all.x = TRUE #) # #activity$Result[is.na(activity$Result)] <- 0 activity <- Ovariable("activity", data = activity) damages <- EvalOutput(damages) damages <- truncateIndex(damages, c("Purchasing_sector", "Damage_categories")) # Truncates # of bins to 10. # Plot results on a bar graph. cat("Effects smaller than or equal to ", limit / sum(sums$Freq) * 100, " % of the total effect are not shown. Numbers are NOT normalised, because there seems to be something strage in normalisaton.\n") ggplot(damages@output, aes(x = Damage_categories, weight = damagesResult, fill = Purchasing_sector)) + geom_bar() + theme_grey(base_size = 18) + theme(axis.text.x = element_text(angle = 45)) + labs( title = "Life cycle impacts of a cup of coffee", x = "Damage", y = "Amount" ) ggplot(damages@output, aes(x = Damage_categories, weight = damagesResult, fill = Damage_categories)) + geom_bar() + theme_grey(base_size = 18) + theme(axis.text.x = element_text(angle = 45)) + labs( title = "Life cycle impacts of a cup of coffee", x = "Damage", y = "Amount" )

Rationale

Data

The data are based on discussions at CII, January 2013.

Direct inputs of a coffee cup(Euro)

Obs	Purchasing_sector	Result	Description
1	31131A - Sugar cane mills and refining	0.1
2	112120 - Dairy cattle and milk production	0.2
3	311820 - Cookie, cracker, and pasta manufacturing	0.5
4	311920 - Coffee and tea manufacturing	0.2
5	221100 - Electric power generation, transmission, and distribution	0.1
6	322299 - All other converted paper product manufacturing	0.04
7	335210 - Small electrical appliance manufacturing	0
8	335221 - Household cooking appliance manufacturing	0.01

See also

• Damage vector for life cycle analysis
• Normalisation data for life-cycle assessments