Reducing the environmental impact of household consumption is widely recognised to be essential for achieving sustainable societies. Designing targeted policies requires detailed data on which households contribute how much to environmental footprints.
While many studies look into average environmental footprints of households, assessments across household income remain limited and focused on carbon, energy or material footprints. Furthermore, the existing literature is dominated by Input-Output Analysis despite increasing data availability making it possible to use process-based Life Cycle Assessment (pLCA) as well, with the latter offering potentially much higher levels of detail.
This study addresses this gap by estimating the environmental footprints from the consumption of household goods, appliances and food for 200,000 European households from 24 European countries and the European Union (EU) using a pLCA approach. To do so, pLCAs for the EU covering 16 impact categories are mapped to expenditure data from the EU Household Budget Survey (HBS).
The research question is: How are the environmental footprints from the consumption of household goods, appliances and food distributed across household income groups in the EU?
The study focused on carbon, water use, land use and resource use (minerals and metals) footprints, which are considered to be headline indicators. The results show that the carbon, water use and land use footprints at EU-level (without Austria, Italy and Germany), are dominated by the consumption of food and therefore largely independent from household income. The resource use footprint is dominated by appliances. The 10% households with the highest income have, on average, 2.8 times the carbon footprint, 6.4 times the water use footprint, 3.4 times the land use footprint and about 8.2 times the resource footprint of households belonging to the lowest income decile. Income inequality (with about 28.6 times the mean household income for top decile vs bottom decile households at EU-level) is much larger. At the same time, the range of household environmental footprints is large in all impact categories due to factors other than household income. The difference to existing literature, which generally finds a stronger connection between income and impacts, particularly for the carbon footprint, mainly stems from the exclusion of mobility and housing.
The study furthermore discusses the significant limitations of HBS data and outlines what
improvements are required to get more robust, comprehensive and detailed estimates of household environmental footprints. Ideally, future HBS would record physical quantities and/or prices along with the expenditures, which would make it possible to consider product quality differences. Using digital tools might make it possible to record consumption all year round or even for multiple years and thus mitigate the bias from infrequent purchases.
Future research should include services, housing and mobility and use regionalised impact data and find mitigation strategies for infrequent purchases and the product quality problem. The pLCA approach should be upheld due to the granularity it offers, for example for the assessment of the distribution of EFs under scenarios.

Current cravings for more are taking a great toll on the Earth and its most vulnerable communities. The rise in ’fast furniture’ has contributed to this issue, popularizing the idea that furniture can be cheap, to the point of being disposable. To understand the size of this issue and how much more damage to the environment might be in store if these trends continue, we need to measure the amount of the furniture stock now and project what might be needed in the future. Currently, there is a knowledge gap in understanding how much furniture is in our homes, especially on a national scale. This thesis aims to quantify the stock and flows of household furniture materials in the US, distinguished by income and area type (i.e., urban or rural). To inform strategies toward circularity in household furniture, a second object of the study is to investigate the effects of repair and reuse – lifetime extension strategies – on the behavior of the American household furniture stock. To quantify the stock of furniture units, the average number of furniture units per m2 of residential floor space was collected using a bottom-up approach. The results were scaled to the national level using residential floor space data from the Integrated Model to Assess the Global Environment (IMAGE), scenario SSP2. Dynamic stocks and flows were calculated based on projected changes in residential floor space to understand how the stocks and flows might behave over time. The lifetime extension scenarios were simulated by extending the lifetime and adding mass (for repair) of a percentage of the furniture in the stock. Overall, demand for household furniture is not expected to saturate until the end of the 21st century. The highest-earning quintile owns half of the furniture stock mass, and material inequality is expected to remain until the end of the century in the base case. Urban residents own a majority of the household furniture and are expected to own a larger share as urbanization continues. About three-quarters of the furniture stock is wood-based, presenting opportunities for carbon storage but challenges in the volume of hard-to-recycle and low-durability particleboard. Circularity efforts to decrease furniture demand should target higher-income groups and separate strategies for lower-income groups should aim to increase affordability and access to more durable furniture. Urbanization also presents opportunities for local furniture circularity projects and hubs to attract skilled furniture repairers and secondhand distributors.

This study sets out to assess the material based consequences of changes in future oil demand. In doing so, this study aims to quantify the physical, industrial petroleumscape. To achieve this, the evolution of the world’s petroleum infrastructures are modelled based on two SSP2 scenarios; a baseline scenario and a 1.5-degree scenario. This study estimates dynamic embedded materials from 1971 towards 2050, as well as the associated in- and outflow. Based on the end-of-life characteristics of the sector, the model assesses the potential for material circularity within the sector. This study finds that storage and pipelines are the driving stages of material use in the petroleum industry, and that steel and concrete are the most used materials. Furthermore, it shows that changes in  oil demand have an immediate effect on the material stock and inflow, but only effect the outflow of material after 2040. To reach material circularity within the petroleum sector a decrease demand is needed to lower the inflow, and end-of-life practices need to be improved, especially the recovery of pipelines after decommissioning and the recycling rate of concrete. 

The growing world population gaining affluence is driving the extraction of raw materials. Resource availability is finite and concerns about future supply shortages rise. An approach to tackle this problem is circular economy which entails multiple strategies to reduce the demand of virgin materials. The implementation of those strategies require knowledge about material stocks and flows in a society. Material Flow Analysis can provide those insights. This fast developing field brought about MaTrace models which allow to trace the fate of materials in an open-loop recycling system. Recycling is only one of multiple circular strategies, thus the purpose of this research is to integrate an elaborate reuse model into a MaTrace model to build the foundation of a model which considers multiple circular strategies in sufficient ways.

Two existing models were combined to achieve this: Consumer goods present in the MaTrace model were redirected into a reuse model and the end of life products of the reuse model were fed back into the MaTrace model. The impacts of this model extension were investigated by comparing the total in-use stock when considering one, two, and three consumer products' use cycles. Furthermore, Monte Carlo simulations were conducted to gain an understanding of the model behaviour.

The results show that the total in-use stock increases in the peak by 8 % when reuse is considered. However, the gross stock dynamics do not change significantly in comparison to the original model. The evaluation of the Monte Carlo simulations revealed that the input which contributes the most uncertainty to the total in-use stock is the split of the initial material inflow. Furthermore, the results of the Monte Carlo simulations appear to be strongly connected to the initial input data. On the basis of this research it can be recommended to further extend MaTrace models to obtain a more comprehensive representation of a circular economy. Furthermore, MaTrace models using time series data for inflows and model parameter have to be created, this way MaTrace models can follow the evolution of MFA from static to dynamic models.

The growing demand for food production and the global developments regarding the intensification and mechanization of agriculture are likely to affect material use in the agricultural sector in some way in the future. This study addressed a research gap regarding the current and future material requirements of the global agricultural system, and it represents a first attempt to estimate the size and composition of the current global material stock embedded in agricultural field machinery. The study also explored the potential future developments of this material stock in five Shared Socioeconomic Pathways (SSPs) through a material scenario analysis, which utilized scenario data generated by an integrated assessment model IMAGE. Available country-level data on the number of machinery in use was linked to agricultural production data through the calculation of ‘mechanization factors’, which describe the relationship of the size of the in-use machinery stock and the annual production quantities of a country. Regionally aggregated mechanization factors were used in combination with regional production data for the estimation of the total numbers of different field machinery currently in use in 26 world regions. These numbers were combined with literature-based estimates of the average material compositions and masses of different types of agricultural field machinery to quantify their current in-use material stocks. Steel (121 Mt), ductile iron (86 Mt), and rubber (21 Mt) were identified as the largest global material stocks of agricultural field machinery, and the largest shares of the materials were found in tractors and combine harvesters. The results of the quantification of the current material stock were incorporated in a material scenario analysis in combination with IMAGE scenario data on agricultural production in the different SSPs. The scenario analysis involved two scenario models with distinct assumptions concerning the development of mechanization levels over time. Depending on the SSP scenario and the model assumptions, the results of the scenario analysis indicated a 50 to 200 percent growth in the global material stock of agricultural machinery by the year 2100. While the scenario analysis assumed the current agricultural practices and technologies to maintain their importance in the future, the study also explored some newer developments taking place in the global agricultural system and the ways they might influence the material stock of agricultural machinery in the future.

This study is a first attempt to address some of the more significant gaps in the available data on (European) furniture. Furthermore, this study takes a dynamic stock analysis approach to look into material stock- and flow dynamics of European household furniture and project them over time. A total of 11 material categories in 14 furniture product categories are assessed. Using principles of dynamic stock analysis and IMAGE data on population and residential floorspace per capita: a Python model has been developed to assess required furniture- and material stocks, the required primary material used in furniture production and the total amount of recycled- and landfilled material per year, and to project the results overtime. To further inform the model, a material database is developed, containing material- and lifetime information on 14 furniture product categories and a survey (n=108) on household furniture has been conducted to derive furniture intensities per unit residential surface. To project the development of material stocks- and flows in European household furniture over time, two scenarios are defined: the business-as-usual or the ‘baseline’ scenario and a second scenario called ‘the reduced waste scenario’ in which reuse and recycle fractions are gradually increased over time. Following business-as-usual patterns in the baseline scenario, the total material stock for furniture is projected to increase with roughly 97 Mt (or 20%) to 584 Mt, towards 2050. The total amount of landfilled- and recycled waste material from household furniture is estimated to be 36 Mt and 4 Mt respectively in 2050. The total amount of required primary material is estimated to increase to 38.5 Mt in total in 2050. In the reduced waste scenario, the total amount of landfilled material is estimated to decrease to 15 Mt in 2050, where the amount of recycled material is estimated to increase to 15 Mt. Also the amount of required primary material is estimated to decrease to less than 18 Mt in 2050. The results from the reduced waste scenario show that a gradual increase from the reuse fraction from 2021 onwards (from 6% to 35% with a 1% step per year) and a gradual increase from the recycle fraction from 2021 onwards (from 10% to 50% with a 2% step per year), would be enough to reduce the need for primary material by half towards 2050. Based on these results, it is the author’s conviction that furniture should be given a separate waste status, similar to that of cars as set out in the end-of-life vehicle directive (European Commission, 2000): materials inside furniture should be labelled and furniture manufacturers should develop dismantling guidelines for their products to ease repair, remanufacturing and recycling. Targets should be set on the country level for the recycling of waste furniture and for the use of recycled (furniture) material in primary production. … Let’s wake up to furniture waste.