4.1 General discussion of the results and procedure
The results of the two life phases have shown that consumer behavior changes significantly per life phase concerning the number of different products (increase in the consumer basket) and quantity consumed. It is suggested that in future studies, each life stage is subdivided into life phases to consider these changing consumption behaviors under socio-psychological models of human development or consumer studies. In addition, using data from different study objects (in this case study: a newborn baby and 2 ½-year-old infant) with the same attributes (e.g., same family, social class, country) for calculating one life phase could further decrease uncertainties.
Collecting primary data, especially during the “childhood and youth stage,” was essential to make a valid statement about consumer behavior in this life stage per product category and enhance data quality by further expanding the database. In some cases, primary data collection was not feasible. For instance, medical masks, gloves, or disinfectants were not considered during childbirth because data collection at that moment but also retroactive was not possible. Furthermore, for the prenatal phase, any pre-birth examinations with devices (e.g., ultrasound) were omitted as data on machine types, and their energy consumption was unavailable. Also, primary data collection revealed that more diapers were used than on average (Diaperplanner 2021
), highlighting its importance compared to general assumptions.
Furthermore, the chosen study objects were deliberately not representative of Germany, as the Life-LCA method determined the impacts on individuals. The initial parameters would have to be similar for a generalization to obtain comparable results for the considered product categories. For instance, whether the infant is growing up in an urban or rural area would lead to different transport emissions (e.g., more accessible public transport in cities). A strong influence is also the income class of the parents, which affects the size of the living space and overall consumption patterns (German Environment Agency 2016
). Carrying out a Life-LCA for individuals living in a different country or culture also influences the results. For instance, electronic products such as a “baby phone” or “baby radiant warmer” would be redundant or considered luxury products in warmer or poorer countries than Germany. Further influencing factors are the electricity mix used and the housing situation (e.g., old vs. new building (good insulation) or house vs. apartment).
Even though the consumption of “food” by the study objects of this case study is similar to an average infant, a change in the diet itself, e.g., a more vegetarian and seasonal one, could influence the results. These examples show that general data cannot reflect each study object’s unique consumption behavior. In addition, using alternative products (e.g., reusable diapers) could also affect the results significantly. Some of the above alternatives are examined in a sensitivity analysis (see Sect. 4.2
Future studies with different social or cultural backgrounds and consumer behaviors and lifestyles are suggested to develop the Life-LCA method further and gain new insights.
The methodology (see Sect. 2.2.1
) to account for the mother’s food intake during pregnancy and breastfeeding contains some uncertainties as secondary data sources were used. It should be analyzed if secondary data (also for other product categories) in other life stages and phases in future studies could be an option if the individual aspects are not the study's focus (individual Life-LCA vs. Lifestyle-LCA (Goermer et al. 2020
)) or primary data collection is not feasible. Furthermore, the time for primary data collection could be reduced a lot as data collection on food is the most time-consuming effort for the study objects considering all product categories. However, a methodology to determine data quality would be necessary to classify specific sources of secondary data. In addition, the quality of the collected data and associated results depend on the accuracy and motivation of the study objects. Thus, in terms of the system boundaries of the study, the study object(s) should be selected based on available time.
Furthermore, this Life-LCA case study applied a prospective approach from conception onwards based on primary data, which is essential to classify the results with reduced uncertainty. It has to be mentioned that the time between the mother's conception and her realization that she was pregnant was considered in the calculations.
The criteria to determine cut-offs for product categories (based on certain hotspots) or life phases should be developed depending on the system boundaries of future Life-LCA studies. For instance, this study has shown that prenatal burdens are essential when setting the system boundaries to the first two life phases or the “childhood and youth stage.”
Although the study objects were examined for 15 months (nine months of pregnancy and six months after birth), there are uncertainties in the extrapolations and downward calculations for some product categories (e.g., “food”). In addition, the gender of the study objects was not considered in this study but might play an increasing role as the infant develops (e.g., food intake, clothes) and should be considered for other life phases (e.g., adolescence) and stages (e.g., early adulthood stage).
Furthermore, the results showed that AP and EP are more sensitive to the product category “food” (especially agricultural products). Influencing factors on the sensitivity are the type of consumed “product,” its particular impacts, as well as its consumed quantity. POCP is sensitive to the product category “transport” and its associated products (e.g., car) (see Fig. 4
). In the supplementary material, which factors influence the different impact categories and to which extent is presented in detail.
The life phase with the highest sensitivity regarding its environmental impacts cannot be identified because results highly depend on individual consumer choices.
This study used a relatively conservative approach in which all environmental impacts were allocated entirely to the infant. However, the question remains on how to allocate the impacts adequately between the infant and parents in a full Life-LCA from “conception to grave.” Additionally, in the context of a family, considering siblings and other generations, the question of allocation is relevant. Chapter 2.2.1 presents several assumptions and allocation options applied in this study. However, for Life-LCA, a methodology for an adequate allocation of burdens between family members considering all life stages (from childhood to old adulthood stage) and the degree of free decision (e.g., how to allocate burdens in case of sickness) is missing. Establishing such Life-LCA allocation rules per life stage/phase and product categories as well as external parameters (e.g., how is the car ride allocated if parents take an infant to the kindergarten on their way to the office) should be part of future methodological development.
Moreover, one aim of this study is to promote environmental awareness among readers, especially young families. The decision to have children is associated with unavoidable future emissions, which continue over generations and can contribute to an individual’s carbon legacy depending on the allocation of the associated impacts (Murtaugh and Schlax 2009
). Given the additional emissions involved when giving birth to a child, the question of whether to have children quickly drifts into ethical discussions. One argument, of course, is that procreation is a fundamental meaning of life. Thus, this highlights the importance of this study as it helps young families reduce emissions after ovulation through sustainable consumer choices by identifying hotspots and showing alternatives, such as in the following sensitivity analysis.
4.2 Sensitivity analysis
In the following, a sensitivity analysis is carried out by modeling product alternatives in different product categories:
“Clothes,” “hobbies and leisure,”; and “living, household, and accessories”
Where possible, secondary materials are modeled instead of primary materials, e.g., “cotton fibers from recycled clothes” instead of “standard cotton fibers” or “recycled wood” instead of primary material for furniture. These changes lead to a reduction of approximately − 75% for GWP for “living, household, and accessories” and “clothes” and a lower reduction of − 10% for “hobbies and leisure.” Moreover, the use of recycled clothes leads to a -92% reduction in EP.
Cosmetics, hygiene, and cleaning
One alternative to common diapers are reusable diapers made from bamboo fibers (Shanmugasundaram and Gowda 2011
). Thus, a bamboo diaper without thermoplastic polyurethane adhesive (Mendoza et al. 2019
) is modeled as an alternative diaper for the product category “cosmetics, hygiene, and accessories.” This new product reduces the number of diapers to be worn to 12 (total weight reduction of 99.6%). Therefore, this product cluster is not prominent anymore for “cosmetics, hygiene, and cleaning.” However, “energy and water” impacts double in all impact categories, as the reusable diapers must be washed and dried daily. In this case study, this does not significantly affect the results as the family receives 100% renewable electricity. If, however, Germany’s electricity grid mix is modeled, the results amount to 3,560 kg CO2
-eq. (diapers share: 65% (2,320 kg CO2
-eq.)). Thus, the diapers show results equivalent to “transport” and “food.”
The family’s energy consumption was modeled as 100% hydropower. However, due to the challenges of double-counting renewable energy (Holzapfel et al. 2022
), other electricity mixes might be used for modeling. For example, if the “German electricity grid mix” is used, an increase in the environmental impacts of the category “energy and water” will be noticed, which would make this category the most significant contributor to GWP (currently seventh-largest: 1.2%) with a share of 27% in the infancy phase.
A vegan diet could reduce all impacts by up to 65–79%. For this alternative, the consumption quantity is not changed in the modeling, but, for example, the egg (dough) and pork filling of the “Maultasche” (= special German pasta with filling) is substituted with a vegan alternative. Furthermore, other non-vegan product clusters are substituted with vegan clusters (e.g., “meal vegetarian” is substituted with “meal vegan”). It is assumed that the reduced amount of meat and other dairy products (42 kg) leads to three times the consumption of other products in the product category “food” (mainly fruits and vegetables), as observed in the first Life-LCA case study. This increased amount is evenly distributed among the remaining 23 food clusters.
Furthermore, formula feeding instead of breastfeeding is modeled. Among other production steps, formula milk requires farming, storage, pasteurization, drying, cooling, packaging, and shipping (Linnecar et al. 2014
). An assumed average consumption of formula milk of + 500 kcal per day (see Sect. 2.2.1
) for the observed five-month breastfeeding period in this study would result in 75,000 kcal, equal to 13 kg of milk powder and 100 L of water for mixing. For GWP, this results in 366 kg CO2
-eq, comparable to the emissions of the complete product category “transport” for the prenatal phase based on 700 km (gasoline car).
Savings for GWP and POCP of -70% are possible if the study objects travel all distances by bus instead of a gasoline car (transport to and from the hospital is considered with a taxi in this scenario).
The results in Sect. 3.2
did not include a vacation trip in the third year of life, as this is determined solely by the parents. If this trip’s environmental burden were considered and shared equally between parents and the infant, emissions for “transport” would increase by 40%. The share of transport for GWP regarding all product categories is then 10% higher for the infancy phase.
4.3 Comparison of the infancy phase results with the approximation of the first Life-LCA case study
In the first Life-LCA case study, consumption in the “childhood and youth stage” was determined based on the assumption that every year of the infancy phase (from birth to 17 years) contributes 50% of the calculated baseline year (48th year) (estimated 4,500 kg CO2-eq. per year). Transport emissions of the study object were excluded in the first Life-LCA case study because the study object was driven instead of being the driver. However, this study has shown that transport emissions lead to impacts of approx. 30% of the overall GWP in the infancy phase and therefore should be considered in future studies. For consistent comparison, transport emissions of the infancy phase are not considered. On a 1-year basis, the infancy phase leads to average emissions of about 800 kg CO2-eq. The estimated 4,500 kg CO2-eq. per year from the first Life-LCA case study seems overestimated by roughly six times the impact (when including the transport emissions (1,150 kg CO2-eq.), impacts are still overestimated by roughly four times). However, there is a correlation when comparing the emissions based on the weight of the study object instead of time (on a yearly basis, including the weight of the infant at three years of age (15 kg) compared with an adult (75 kg)). Thus, the case study has shown that primary data collection and detailed consideration of individual life phases are essential to validate generic assumptions. However, the identified connection should be further investigated and validated in future case studies, especially for the pending life phases in the “childhood and youth stage.”