Lesson 1Assessing data quality: temporal, geographic, technological representativeness and uncertaintyThis section presents data quality assessment for LCI, covering temporal, geographic, and technological representativeness, completeness, precision, and uncertainty, and how to score and document quality for bottle system datasets.
Temporal representativeness and data ageGeographic coverage and regional relevanceTechnological representativeness of processesCompleteness and precision of inventory flowsQualitative scoring and uncertainty flagsLesson 2Transport modeling: modal choices, typical distances for North America and Europe, fuel and load factorsThis section explains how to model freight transport for bottle systems, including choosing transport modes, estimating typical regional distances, and setting realistic fuel use, load factors, and backhaul assumptions for North America and Europe.
Selecting relevant freight transport modesTypical road, rail, sea distances by regionEstimating fuel consumption and emission factorsModeling load factors and empty backhaulsAllocating transport to functional unitLesson 3Identifying required inventory flows: materials, energy, transport, water, wasteThis section introduces how to identify all required inventory flows for bottle LCIs, including materials, energy, transport, water, emissions, and waste, and how to ensure completeness and consistency with the functional unit.
Linking flows to the functional unitListing material inputs and auxiliary materialsIdentifying energy carriers and utilitiesCapturing transport, water, and emissionsChecking completeness and avoiding double countingLesson 4Using secondary datasets: ecoinvent, US LCI, ELCD, GaBi proxies — how to search and select matching processesThis section focuses on selecting and using secondary LCI datasets from sources such as ecoinvent, US LCI, ELCD, and GaBi, including search strategies, proxy selection, metadata checks, and adapting datasets to bottle system needs.
Searching databases for matching processesInterpreting metadata and system boundariesChoosing and justifying proxy processesAdapting datasets to regional conditionsHandling cutoffs and allocation in datasetsLesson 5Documenting sources and citing datasets, papers, calculators, and government statisticsThis section explains how to transparently document all LCI sources, including databases, peer‑reviewed papers, industry reports, calculators, and government statistics, and how to cite them consistently for reproducible bottle studies.
Creating a structured LCI data logReferencing LCI databases and versionsCiting peer‑reviewed and industry studiesUsing and documenting online calculatorsReferencing government and statistical dataLesson 6Modeling manufacturing processes: steel production, injection/stretch blow molding for PET, forming and finishingThis section covers modeling manufacturing processes for PET and stainless steel bottles, including steelmaking routes, PET resin production, injection and stretch blow molding, forming, trimming, finishing, and integrating scrap and yield losses.
Steelmaking routes and alloy specificationsPET resin production and drying stepsInjection and stretch blow molding parametersForming, trimming, and surface finishingModeling scrap rates and material yield lossesLesson 7End-of-life pathways: recycling rates, mechanical recycling processes for PET and stainless steel, landfill, incineration with energy recoveryThis section explains how to model end‑of‑life for PET and stainless steel bottles, including regional recycling rates, mechanical recycling processes, landfill and incineration with energy recovery, and allocation of recycling benefits and burdens.
Collecting regional recycling and disposal ratesModeling PET mechanical recycling processesModeling stainless steel recycling routesLandfill and incineration with energy recoveryAllocation approaches for recycling creditsLesson 8Estimating material composition and mass flows for stainless steel and PET bottlesThis section describes how to estimate material composition and mass flows for PET and stainless steel bottles, including wall thickness, closures, labels, secondary components, and how to translate drawings or bills of materials into LCI inputs.
Interpreting drawings and specificationsEstimating PET and steel wall thicknessesAccounting for caps, labels, and coatingsConverting volumes to masses and densitiesBuilding mass balance tables for the LCILesson 9Use-phase modeling for reusable bottles: washing scenarios (hand vs. dishwasher), frequency of reuse, cleaning agents and hot water energyThis section details how to model the use phase of reusable bottles, including washing frequency, hand versus dishwasher cleaning, hot water energy demand, detergent use, and user behavior scenarios that strongly influence overall LCI results.
Defining realistic reuse frequency scenariosHand washing water, energy, and detergent useDishwasher cycles, loading, and energy profilesModeling hot water generation and fuel mixesSensitivity analysis on user behavior patterns
