Construction of a Virtual Washing Machine

Lasic, Emir; Stamminger, Rainer; Nitsch, Christian; Kessler, Arnd

doi:10.3139/113.110365

Cited by 12 publications

(5 citation statements)

References 14 publications

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“…However, we compared the average used in this study with the one reported by Lasic et al (2015) and found them consistent (both 1.7 g CO 2− eq/g detergent). Other sources of uncertainty and variability related to the detergent dataset were not considered in this study, such as the manufacturing processes, sourcing of raw materials, and sources of energy used for manufacturing.…”

Section: Variability and Uncertaintymentioning

confidence: 96%

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Shahmohammadi

Steinmann

Clavreul

et al. 2017

Int J Life Cycle Assess

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Purpose Variability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe. Methods Data from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability. Results and discussion Both inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5 × 10 2 g CO 2 − eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.Conclusions The combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

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Section: Variability and Uncertaintymentioning

confidence: 96%

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Shahmohammadi

Steinmann

Clavreul

et al. 2017

Int J Life Cycle Assess

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show abstract

“…Lasic and Stamminger [12] have also shown the way in which consumers must change their laundry washing behaviour when using washing machines with a high-rated capacity. They simulated the effect of deferring the wash unless a sufficient volume of load to fill (almost) the rated capacity of a large washing machine at a certain washing condition can be utilised.…”

Section: Resultsmentioning

confidence: 99%

Large Washing Machines Are Not Used Efficiently in Europe

Schmitz¹,

Alborzi²,

Stamminger³

2016

Tenside Surfactants Detergents

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Washing machines sold for private households are increasing in capacity. The aim of this study was to assess how these higher capacities are utilised by consumers. A consumer survey was conducted in eleven European countries with more than 5,000 participants who are substantially involved in washing laundry. Questions were asked about their washing machines and washing behaviour. The main outcome is that these new machines are welcomed, but it seems that the consumers are not utilising the larger capacities. This may result in higher energy and water consumption as the new machines are optimised to work most efficiently at maximum load conditions.

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“…Firstly, the average temperature of the washes is different to the temperature, which is the basis for the declaration (which is five times a cotton wash at a 60°C programme and two times a cotton wash at a 40°C programme, which gives a simple average of a nominal 54.3°C). This difference to the real‐life average nominal washing temperature is considered to have a linear effect of 0.020 kWh/K on the energy needed (Lasic et al ., – formula (6)). Real‐life average nominal temperatures are known from the same consumer survey in 11 European countries plus Turkey .…”

Section: Methodsmentioning

confidence: 99%

Load profiles and flexibility in operation of washing machines and dishwashers in Europe

Stamminger

Schmitz

2016

Int J Consumer Studies

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While the energy generation system is changing towards the use of more renewable energies, the problem of how to deal with fluctuating energy supply is increasing. Smart appliances in households are often referenced as one possible solution, as their operation may be shifted in time and, thus, used to balance an unstable energy supply. The potential of such appliances has been studied to date mainly in pilot installations with a very limited number of participants or by making assumptions on what might be possible. With this work, a semi-representative approach for 12 European countries was used to assess actual consumer habits for the use of washing machines and dishwashers which then could be used to calculate average load profiles for those appliances depending on the time of the day. Using these profiles, it is strait forward to calculate how much load may be shifted by those appliances in a demand response application. This allows aggregators or energy utilities to assign clear financial benefits to the shifting potential of those appliances. Consumers use the shifting of appliance operation already today for various reasons. Investigating these reasons allows to learn already a lot about the flexibility of consumers.

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Construction of a Virtual Washing Machine

Cited by 12 publications

References 14 publications

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Large Washing Machines Are Not Used Efficiently in Europe

Load profiles and flexibility in operation of washing machines and dishwashers in Europe

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