introtolca-lecture notes-lecture notes week 4

8/12/2019 Introtolca-Lecture Notes-Lecture Notes Week 4

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Lecture 10: Scope definition: requirements for data and data quality

Transcript

Lets quickly review where we stand in the goal and scope definition step of the LCA process. Weve

learned that the first task is to define the intended applications, purpose, and target audience of theanalysis. Once we define these goals, we must then determine the function and functional unit of

the product or service we are analyzing. Based on the functional unit, we can define the reference

flows. And, based on the reference flows, we can construct the initial system boundaries based on

our chosen life-cycle inventory methods and life-cycle impact assessment methods.

Weve completed these tasks in our current plastic bag and bottled soda LCA models. Weve also

learned that we may need to revisit all of these decisions based on what we learn in the inventory

analysis, impact analysis, and interpretation steps of an LCA.

Today well talk about the next steps in the scope definition process: determining the data

requirements and the data quality requirements necessary to meet the goals of our study. The term

data requirements refers to the types of flow data we need in our unit process inventories, while

the term data quality requirements refers to the characteristics those data must have in order for us

to have confidence in our results. Our discussion today will be based on guidance from the ISO

14040 series of standards for data and data quality requirements.

Lets begin with determining data requirements. All data used in an LCA must directly support the

stated goals of the LCA, so lets return to the goals I defined for my plastic bag as an example. The

intended application of my plastic bag LCA is to identify environmental hot spots in the plastic

bag life cycle. This broad goal suggests I should strive to include all relevant environmental impacts

in my study, which requires that I include the relevant elementary flows for quantifying all suchimpacts. In general, an LCA should strive to include the broadest range of flows possible, but, as

weve discussed, this can sometimes be difficult in practice due to time, resource, or data

constraints.

Lets take a look at my LCA model, where Ive listed the elementary data flows Ive determined I

need to capture in order to include all relevant environmental impacts, and thereby meet the goals

of my study. Given the length of my list, Ive included my data requirements on separate tab in my

spreadsheet model. We can see that Ive documented the elementary flows of resources, emissions

to air, emissions to water, and emissions to land required in my unit process inventories. Ive also

listed the specific name of each flow, using generally-accepted names for each type of mass. Youlldo the same in our spreadsheet model for the bottled soda life cycle.

You may now be asking yourself, how do I arrive at such a detailed list of flow data before actually

compiling the inventory data for my LCA? For my plastic bag LCA, Ive included the flow data that I

know are required for my chosen life-cycle impact assessment categories, as discussed in the last

lecture. Well discuss the impact assessment step more in future lectures, but for now lets take a

quick peek ahead so you can better visualize what Im talking about here.

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This is the tab Ill use to convert emissions of greenhouse gases in my plastic bag life cycle inventory

into units of carbon dioxide equivalents, which allows me to calculate an impact metric called

global warming potential. As we can see, to calculate global warming potential I need inventory

data for any flows of carbon dioxide, methane, nitrous oxide, and other air pollutants from my unit

processes. Thus, my data requirements should include these types of air pollutant flows if I want to

calculate global warming potential. And, when we review my data requirements list, we can see

that I have indeed included flows of these key air pollutants.

If I find in my inventory step that data on these air pollutants is not available, I can remove them

from my data requirements. However, if I do so, I may also need to adjust the goals and scope

defined for my LCA, since Id no longer be able to calculate global warming potential. Moreover, Id

also have to state explicitly that a limitation to my study is that it does not consider global warming

potential.

Alternatively, if one knows which data sources one will use for the life-cycle inventory step, one can

also look ahead to those data to determine which data flows can and cant be included in the list of

data requirements. The truth is, in many LCAs, the list of required flow data evolves with the

inventory and impact steps based on what data are available and the resources and time available

to the analyst. This is yet another example of the iterative nature of LCA.

Lastly, in the data requirements field of my scope definition, I want to indicate that all data used in

my study will come from secondary data sources.

This is because I dont have direct access to any actual processes in the plastic bag life cycle and also

because Im conducting an exploratory study with limited resources. In practice, youll find that

LCAs can be made up of data that are measured, estimated, or obtained from secondary sources,

and that LCAs often include mixtures of these data types.

So, now that Ive identified what flow data I need in my unit process inventories, I need to think

about the quality of those data. In other words, what characteristics do the data need to have for

me to have confidence that my LCA results have met the goals of my study? After all, LCA is a

modeling technique, and the outputs of any model are only as good as its inputs.

So how do we define the fuzzy concept of data quality? Fortunately, the ISO 14040 standards have

defined the different dimensions of data quality that we should be careful to address in any LCA.

Here is the list, which Ill go through one by one:

Time-related coverage, which refers to the desired age of the data; for example, the resultsof my plastic bag LCA will be far less relevant if Im using data from 20 years ago than if Im

using data from last year. When collecting primary data, time-related coverage can also

refer to the minimum length of time over which the data should be collected;

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Geographical coverage, which refers to the geographical area from which data for unitprocesses should be collected to satisfy the goals of the study. For example, one can gather

data on plastic bag manufacturing in a given state, for a given nation, or at the global

average level. In my study, Ill be analyzing the plastic bag life cycle in the United States, so

it wouldnt be ideal for me to use data obtained for plastic bag systems in Asia;

Technology coverage, which refers to the technology mix for a given unit processes. Thetechnology used in any unit process can vary greatly based on the type of technology, the

vintage of the technology, or the efficiency of the technology. For example, there may be

short haul single unit trucks or long haul tractor-trailer trucks that distribute my plastic bag

to the grocery store. Furthermore, within the single unit truck category, there may be

trucks with high efficiency engines and standard efficiency engines. Thus, in my unit process

for trucking, I need to know what mix of truck types and performance was used to generate

the inventory so I can be sure the technology mix reflects the real-world mix for distributing

my plastic bag.

In practice, time-related coverage, geographical coverage, and technology coverage can often be

ascertained from well-documented data sources, including many commercial LCA databases. As

such, you should get in the habit of always understanding and documenting these data quality

indicators in your LCA studies. In fact, youll do this is by assessing the:

Representativeness of the data,which is a qualitative assessment of the degree to whichthe data set reflects the true population of interest with respect to geographical coverage,

time period, technology coverage. The more representative your data are, the closer they

are to describing your actual system of study.

Two other critical indicators of data quality are consistency and reproducibility. In fact, these are so

important that many LCA experts recommend consistency and reproducibility be used as

fundamental guiding principles throughout an LCA, rather than a retrospective measure of quality. I

share this view, so well stress these as follows:

Consistencyis a qualitative assessment of how uniformly the study methodology is appliedto across the entirety of study steps and components. For example, for consistency we

want to use the same list of flows across unit processes, the same cut-off criteria for

excluded unit processes, data sources of similar quality, and data with the same level of

temporal, geographical, and technological coverage in all unit process inventories. Well

strive for consistency in all of these respects in our plastic bag and soda bottle LCA models.

Reproducibilityis a qualitative assessment of the extent to which the documentation ofmethods and data values allows independent reproduction of the results in the study. The

hallmark of good science is that it can be reproduced by independent experts. In our LCAs,

this means that well be documenting all data sources, calculations, estimation methods,

and modeling approaches so that they are crystal clear to your audience. In that way,

independent experts can understand your methods and validate or critique your results.

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Unfortunately, Ive seen many LCA studies that fail with respect to reproducibility of results. When

results are presented that I cant replicate, input variables are not documented explicitly, or

calculations arent clearly explained, I simply dont trust a studys results. And when the audience or

scientific community doesnt trusta studys results, there is no point in conducting the study in the

first place. Thats why youll develop the habit of thorough documentation in this course.

Two final measures of data quality recommended in the ISO 14040 guidelines are;

Precision, which is the measure of variability of the data values for each data category(variance)

Completeness, which refers to the percentage of locations reporting primary data out of thepotential number in existence for each data category in a unit process;

Id like to close with a few key points. First, when a study contains a comparative assertion made to

the public, the ISO 14040 guidelines require that all of the aforementioned data quality elements be

documented explicitly. This is done to ensure full transparency for any public claims. Second, dueto time restrictions I had to review these data quality elements quickly, but you need to understand

them very well. Thus, Ive provided some readings recommendations in the lecture notes. But dont

worry, youll gain familiarity with these data elements as we move forward into the inventory step.

Third, as with all other aspects of the LCA process, in practice one must iterate on data quality

requirements depending on study goals, scope, and inventory data and how all these steps change

over time. And fourth, note that as part of the LCA process well come back to all of these data

quality elements later and score how well we did as the study nears completion.

Additional notes

See the Data Requirementstab of the Plastic_Bag_LCA_Week_4.ods file, which contains the list of

flow data that are included in the plastic bag LCA model. Note that this tab has a slightly different

appearance than the screenshot shown in the lecture video due to recent changes to the

spreadsheet. These flow data were chosen on the basis of: (1) representing all major

environmental impact categories in the impact characterization model chosen for this analysis (the

U.S. EPA's TRACI, which well discuss in Week 8); and (2) their availability in the publicly-available

life-cycle inventory data sources selected for this study. The publicly-available data sources we used

for the inventories are listed in each unit process inventory tab. In practice, data requirements are

typically determined by the availability of data to model the system, the environmental impacts one

includes in the analysis, the flow data required by the impact characterization model to analyze the

included environmental impacts, and the data quality requirements specified for the study (e.g.,

geographical, temporal, and technology coverage). Take a look at the data requirements section of

theEnvironment Agencys LCA of carrier bagsfor one example of how data requirements are

documented in practice.

This tab will be made available in the Week 7/8 version of the HDPE grocery bag LCA spreadsheet,

which is when well be discussing the life-cycle impact assessment (LCIA) step of an LCA. For now,

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just understand that in order to quantify a given environmental impact in an LCA, we need to ensure

that the mass flows that are relevant to that impact are included in our life-cycle inventory data.

Take a look at the Data Quality Requirementstab of the Plastic_Bag_LCA_Week_4.ods file, which

contains descriptions of the desired geographical, temporal, and technology coverage of the LCA in

order to meet the stated goals of the study. Because we are interested in identifying environmentalhot spotsin our example HDPE grocery bag LCA, the statements of geographical, temporal, and

technology coverage are fairly broad. For example, the desired temporal coverage is data from

within the past 10 years, given that older data are likely to be sufficient for the identifying major

hot spotsin the plastic bag life cycle. Take a look at the data requirements section of the

Environment Agencys LCA of carrier bagsfor one example of how data quality requirements are

documented in practice.

In Week 6, well discuss assessments of representativeness and other data quality indicators in more

depth. Youll also perform a representativeness check on your bottled soft drink LCA toward the

end of this course. For now, just understand the basic concept of representativeness and think

about the representativeness of your analysis as you build out your bottled soft drink LCA model.

Well discuss a structured approach for checking the consistency of an LCA in Week 9, when youll

also perform a consistency check on your bottled soft drink LCA. For now, just understand the basic

concept of consistency as defined above and think about the consistency of your analysis as you

build out your bottled soft drink LCA model. Furthermore, youll ensure reproducibility of your

bottled soft drink LCA model by documenting all data sources and modeling assumptions and

capturing all calculations in your spreadsheet model.

For a detailed discussion on identifying and specifying data requirements and data quality

requirements in an LCA, see Sections 6.8 and 6.9 of the following report. The detailed guidanceprovided in these sections underscores the importance of, and the nuances associated with,

establishment of important data and data quality requirements. In this course, we are taking a very

basic approach to identifying data requirements and data quality requirements in the interest of

time. In practice, however, these steps require much thought and careful planning. Youll

appreciate just how complicated and important these steps are in practice when reading Sections

6.8 and 6.9!

European Commission - Joint Research Centre (JRC) - Institute for Environment andSustainability: International Reference Life Cycle Data System (ILCD) Handbook - General

guide for Life Cycle Assessment - Detailed guidance. First edition March 2010. EUR 24708EN. Luxembourg. Publications Office of the European Union; 2010.

http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-

handbook-general-guide-for-life-cycle-assessment-detailed-guidance-pbLBNA24708/

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Lecture 11: Scope definition: review and reporting

Transcript

Welcome back! Today well wrap up our discussions of goal and scope definition. By now, it should

be clear to you just how important proper definitions of goals and scope are for a credible andtransparent LCA. We have just two more topics before we move on to collecting and working with

data in the inventory analysis step.

The first topic is critical review. As I mentioned in the previous lecture, one hallmark of good science

is that it can be reproduced by others. Another hallmark of good science is that it has stood up to

critical review by ones peers. In a critical review, independent experts will evaluate an LCA to

ensure that its stated goals are supported by its scope and methods, its data sources are

appropriate and credible, its methods are of sufficient rigor and transparency while also being free

of major errors, and that its results are properly interpreted and communicated. In short, critical

review provides a valuable external quality check by knowledgeable experts.

There are several reasons one might want a critical review. First and foremost, if an LCA makes

comparative assertions to be disclosed to the public, the ISO 14040 standards require that the study

undergo critical review by a panel of independent experts before being made available to the public.

Second, external peer review can provide added credibility to a study, because the audience knows

that knowledgeable experts have performed an important quality check. Third, Ive always found

that external peer review only strengthens a study, because independent experts can often offer

helpful advice on better data sources, better methods, and better ways of communicating the

studys contents.

A critical review can either occur at the end of a study, or concurrently with it. Concurrent reviewmeans that reviewers provide feedback on the goal and scope definitions as they are formed, and

on preliminary results from the inventory analysis and impact assessment steps. One advantage to

concurrent review is that it provides the analyst with early feedback so that, when changes are

necessary, they can be made before getting too far ahead when changes become more difficult to

implement.

The extent and type of critical review should be specified in the scope of a study. Similarly, who the

reviewers are and their level of expertise should be stated as well. Now, its very important that the

reviewers are independent experts, meaning they have not been involved in the study and dont

have a vested interest in its outcomes. Moreover, there are guidelines for setting acceptablequalifications for reviewers, which Ive referred you to in the lecture notes. Lastly, a review

statement and authors responses to reviewer comments are typically included in the final LCA

report for full transparency.

Lets now move on to our second topic: the reporting format. In this course, you wont be writing a

formal report for your bottled soda LCA study. However, it is important that you understand the

elements of a proper report for when you do issue such reports in the future. Also, note that nearly

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all of the elements of a proper report will be included in our spreadsheet models in the interests of

documentation and transparency.

The ISO 14040 standards state that reports should ensure that:

Results and conclusions are reported completely and accurately, and without bias to theintended audience,

All results, data, methods, assumptions, and limitations are reported transparently, and Results and interpretation are used in a matter that is consistent with the goals of the study.

To accomplish these goals, many practitioners follow a reporting template for LCA studies, which

has also been laid out by the ISO 14040 standards. There are seven major sections to this template,

which Ill explain briefly one by one:

The first section contains general aspectsof the LCA study, including the study commissioner, the

date of the report, and, when required, a statement that the study has been conducted in

accordance with ISO 14040 guidelines.

The second section describes the goals defined for the study, including the purpose, intended

applications, the target audience, who conducted the study, and whether comparative assertions

will be disclosed to the public.

Recall that weve documented all of these goal definition elements on the first tab of our

spreadsheets.

The third section describes the scope defined for the study, including the function, functional unit,

system boundaries, data and data quality requirements, the impact assessment methodology,

allocation methods, cut-off criteria, and critical review requirements.

Recall that weve documented most of these elements on the first tab of our spreadsheet as well.

Moreover, before we complete our study, well go back and document allocation methods and cut -

off criteria, too.

The fourth section describes in detail the inventory analysis step, including the types of data, the

sources of data, descriptions of unit processes, and calculation methods. This section can also

include the results of any sensitivity analyses that were performed to refine the system boundaries,

which well learn how to do later in this course. As you build your bottled soda LCA model, youll

include most of these reporting elements as part of your modeling structure. For example, each unit

process inventory will be contained on a separate tab for ease of review.

The fifth section covers the life-cycle impact assessment step. Ideally, this section describes the

impact assessment method that was chosen, how the impact assessment method supports the goals

of the study, and other details that well discuss when we cover impact assessment later in this

course.


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With respect to your spreadsheet model, your impact assessment methods and calculations will be

contained on dedicated tabs, which will serve as your documentation.

The sixth section covers the interpretation step, including your results, your data quality

assessment, and any assumptions and limitations that would affect how your results should be

interpreted.

Each of these elements will also occupy separate tabs in your spreadsheet model.

The seventh and final section describes the critical review, including the type of review, the review

report, and responses to comments. Obviously, this section is only required for reports that

undergo critical review.

Ive found that having this reportingstructure in mind as I conduct an LCA study helps me better

document and organize my information along the way, which makes report writing much easier

when the study is complete.

Again, even though you wont write a final report, I hope its clearhow most of these required

sections will be captured automatically in your spreadsheet by the way youll build it out. My goal

is for you to document all aspects of your study within your spreadsheet so that, hopefully, report

writing will be a natural extension of what youve learned in this course.

That said, I want to stress that there are more details associated with each of these sections than

Ive discussed here, so Ive provided some recommended readings in the lecture notes that you can

consult you can learn more. You should definitely do so if youre planning to write an LCA report

anytime soon. Lastly, so you can see some real-world examples of how good LCA reports are

structured, Ive provided some links to recent publicly-available LCA reports in the lecture notes.

Ill see you next time!

Additional notes

For some examples of critical review -- including the involvement of independent experts, their

comments, and the authorsresponses to their commentssee the LCA reports that are listed

under note 11.3 below.

As youll recognize toward the end of this course, the design of our HDPE grocery bag LCA and

bottled soft drink LCA models closely follows these major reporting elements and sections. In

practice, when conducting an LCA, careful planning of the analysis, data sources and structure, andthe model format can make writing a formal report much easier.

Here are a few recent studies that generally follow the ISO 14040 guidelines for reporting. Take a

look at them and see if you can identify the major sections weve discussed above. Note how this

reporting format is valuable for several reasons:

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It forces one to document clearly all major study design, data, analysis, and interpretationdecisions.

It provides a step-by-step overview of the entire LCA process, which makes for intuitivereading.

It allows the audience to easily identify analysis assumptions and decisions of interest bylooking to the appropriate section; for example, one can easily find the definition of the

functional unit by jumping to that section (as opposed to hunting for it in a poorly formatted

report).

It facilitates critical review by explicitly documenting all major steps and assumptions in anLCA study.

There are many other examples of well-formatted LCA reports in the public domain. See if you can

find some yourself! Also, you may also encounter poorly-formatted LCA reports in practice. Having

an idea of how useful a well-formatted report can be is a good reminder to follow best practice

reporting protocols in your own LCAs!

Environment Agency (2011). Life Cycle Assessment of Supermarket Carrier Bags. Bristol, UK.Report: SC030148.Click here to access this report.

World Steel Association (2011). Methodology report: Life cycle inventory study for steelproducts. Brussels, Belgium. ISBN 978-2-930069-66-1.

https://www.worldsteel.org/dms/internetDocumentList/bookshop/LCA-Methodology-

Report/document/LCA%20Methodology%20Report.pdf

PE Americas (2010). Life Cycle Impact Assessment of Aluminum Beverage Cans. Boston, MA.http://www.aluminum.org/Content/ContentFolders/LCA/LCA_REPORT.pdf

Bio Intelligence Service (2010). Nordic Life Cycle Assessment: Wine Packaging Study.Paris,France.http://www.tetrapak.com/se/DocumentBank/LCA%20Nordic%20Wine%20comparative_Au

gust_10_with%20final%20statement.pdf
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Lecture 12: Life cycle inventories: the basics

Transcript

Were now ready to move on to the inventory analysis step in the LCA process.

I know youre probably eager start collecting and

analyzing data for your bottled soda LCA, so today were

going to jump right into it with an overview of our

inventory modeling approach. Well use my plastic bag

LCA spreadsheet as an example, but youll be laying out

your bottled soda spreadsheet model in exactly the same

way.

But first, I wanted to remind you that well be using only

secondary data in this course as a matter of practicality.

However, in the future you may need to compile primary

data directly from the systems you are studying, so lets

quickly discuss how one actually gets primary data for unit

process inventories. In practice, there are many different

ways of gathering primary data, but here are some of the most common:

Direct process measurements over a period of time Utility and fuel bills Process monitoring and control software Meters readings from equipment Equipment and process specifications, and Company data logs and records

If youre interested, recommended readings for furtherguidance on collecting primary data have

been provided in the lecture notes. Well spend the rest of this lecture observing how Ive laid out

my plastic bag LCA spreadsheet model in the inventory analysis step.

First, note that Ive used a single tab to contain the inventory for each unit process in my life cyclesystem. Ive labeled the tab with a brief name that describes the unit process, making sure to use

the same unit process name I used in my system diagram. Ive chosen to order my tabs roughly in

the order they appear in the life cycle of my plastic bag, but you can order them in any way that

makes sense to you, for example, alphabetically.

Second, for ease of navigation around my model, Ive made use of the hyperlink feature in my

spreadsheet software. At the top of each unit process inventory tab, I can jump back to the system

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diagram. And I can click on a unit process box in my system diagram to jump to the inventory tab

for that unit process.

Third, Ive laid out each unit process inventory tab in the exact same way. At the top, I list the unit

process name. In the following rows well be tracking the important data quality characteristics we

discussed earlier: time-related coverage, geographical coverage, and technology coverage. Welldothis for each unit process inventory to get in the habit of paying close attention to data quality; this

will also make our data quality assessment later in the study much easier. Moreover, tracking data

quality for each unit process will help us ensure consistency throughout our LCA model.

Fourth, Ive provided space for additional notes, including any allocation or scope details that help

me interpret my inventory as well as document key data assumptions. These notes are very

important for ensuring transparency and reproducibility of our modeling results.

Lastly, Ive organized the actual inventory data into the four major categories we discussed earlier:

flows from nature, flows from the technosphere, flows to the technosphere, and flows to nature.

Under each category, Ive listed the specific flow names that are captured across my unit process

inventories. Note-and this is very importantthat Ive made sure that all flows in each category

appear in the same row in every unit process inventory in my model.

For example, flows of carbon dioxide to nature always appear in this row, whether it be on my

ethylene to HDPE pellets unit process tab or my diesel truck unit process tab. Using the same layout

across my unit process inventory tabs is a matter of convenience; it allows me to easily sum up flow

data across all unit process models. I do this on a tab Ive labeled life-cycle inventory summary,

where you can see Ive simply summed up flows of carbon dioxide using a formula that refers to the

same row number in every unit process worksheet. Youll do the same in your bottled soda LCA

spreadsheet.

Note also that weve added a seventh column to our standard unit process inventory structure,

which well use for noting references for the data. Welluse standard citation format for all

references, which you can review in the lecture notes. Carefully recording the sources of all data in

our unit process inventories is critical for ensuring full transparency and reproducibility. Ive created

a master list of references on the last tab in my spreadsheet, which Ive organized in alphabetical

order.

For those of you wholl use commercial LCA software packages in practice, the good news is that you

dont need to worry about such careful organization of data, rows, and tabs because the software

will track all data relationships for you. In our case, organizing your model in this way will help you

better visualize system flows and data relationships, which should improve your understanding of

the course material.

To get you started, weve provided inventory data tabs for all background processes in your bottled

soda LCA model, which can be downloaded today. Specifically, weve provided cradle to gate unit

process inventories for transportation fuels like diesel fuel, industrial fuels like natural gas, and for

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U.S. average electricity generation and distribution. Weve also provided a life-cycle inventory

summary tab, which youll use to sum up flows across your life-cycle system.

In the next few lectures, well discuss how the inventory analysis step works so you can begin

compiling and analyzing unit process inventory data for foreground processes in your bottled soda

LCA model. Before too long, youll have a complete life-cycle inventory in place, which will give youa first glimpse of the environmental hot spots in the bottled soda life-cycle.

Additional notes

The following report contains very detailed guidance on the elements of LCI generation and

compilation, including some discussion of primary data collection considerations:

European Commission - Joint Research Centre - Institute for Environment and Sustainability:International Reference Life Cycle Data System (ILCD) Handbook - Specific guide for Life

Cycle Inventory data sets. First edition March 2010. EUR 24709 EN. Luxembourg.

Publications Office of the European Union; 2010

http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-

handbook-specific-guide-for-life-cycle-inventory-lci-data-sets-pbLBNA24709/

To better understand each of these tabs, refer to the Plastic_Bag_LCA_Week_4.ods file. Note that

these tabs have slightly different appearances than the screenshots shown in the lecture video due

to recent changes to the spreadsheet. Try to follow along as I discuss each tab, and take some time

to understand the content of each tab as well as the calculations that occur to generate the life-

cycle inventory (LCI) results. Here are some additional points to consider:

- Observe how each unit process inventory has its product output expressed as a multiplier

of one for ease of scaling.

- Note that the order of flows has changed compared to the lecture videos. Specifically,

inputs to nature and outputs to nature appear first in each inventory so that these standard

flows appear on the same rows in each unit process inventory across the spreadsheet. This

allows for easy summation of LCI data on the LCI Resultstab of the spreadsheet (which

lists flows in the same order and rows as the unit process inventories observe this for

yourself).

- Please read the important notes on the Read Metab of the spreadsheet, which contain

information on how to properly interpret the spreadsheet.

- This spreadsheet will be built outin week-by-week fashion over the duration of the

course, based on the topics covered each week. A similar process can be followed as you

develop your bottled soft drink LCA model.

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12.2
http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-handbook-specific-guide-for-life-cycle-inventory-lci-data-sets-pbLBNA24709/http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-handbook-specific-guide-for-life-cycle-inventory-lci-data-sets-pbLBNA24709/http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-handbook-specific-guide-for-life-cycle-inventory-lci-data-sets-pbLBNA24709/http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-handbook-specific-guide-for-life-cycle-inventory-lci-data-sets-pbLBNA24709/http://bookshop.europa.eu/en/international-reference-life-cycle-data-system-ilcd-handbook-specific-guide-for-life-cycle-inventory-lci-data-sets-pbLBNA24709/


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To keep the model intuitive and simple, all unit processes are represented byaggregated

inventoriesthat contain:

1. only the major inputs and outputs to and from the technosphere that are related to thephysical transformation that occurs in the unit process;

2. flows from nature that account for the original resource inputs into the energy systems thatfuel the unit process;

3. flows to nature that arise from the energy systems that fuel the unit process; and4. flows to nature due to direct emissions from the unit process itself.

For example, consider the aggregated unit process inventory for production of ethylene (see the

Ethylene Mfgtab), which is also depicted in the figure below:

1. Inputs from the technosphere include processed natural gas and refined petroleumproducts, which are converted into ethylene; the output to the technosphere is ethylene.

2. The production of ethylene includes the consumption of electricity, natural gas, and otherfuels, which are denoted by dashed ovals in the figure. The system boundary for the

aggregated unit process inventory includes the extraction, conversion, and transport

processes necessary to produce these fuels from natural resources. For example, electricity

is produced by extracting and processing coal, natural gas, etc. and using these fuels to

generate electricity in a power plant. Thus, the system boundary includes the extraction/

conversion, transport, and generation processes to convert resources from nature into the

fuels consumed by the ethylene production process. As such, the inputs from nature refer

to the primary energy sources extracted from nature related to all fuels consumed in

ethylene production.

3. The extraction, processing, conversion, and transport of fuels consumed in the productionof ethylene result in emissions to air, water, and land. These emissions are included in the

outputs to nature leaving the aggregated unit process. See the processes denoted by boxes

in the figure; these are the processes from which the emissions to air, land, and water

leaving the system boundary arise.

4. The combustion of fuels in the production of ethylene, and other process-related emissions(such as waste generation) from the ethylene production process are also included in the

outputs to nature. See the processes denoted by boxes in the figure; these are the

processes from which the emissions to air, land, and water leaving the system boundary

arise.

These aggregated inventories provide a more convenient form for the simple LCAs well conduct in

this course, and allow us to include the life-cycle systems for production of fuels consumed in our

unit processes in an efficient manner. Youll also work with aggregated unit process inventories in

Part 2 of Homework 4.


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The first version of the bottled soft drink LCA spreadsheet will be released soon. Watch for the

announcement!

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introtolca-lecture notes-lecture notes week 4

Documents