Skip to main content

Digital home working and its sustainability potential: human immobility and the mobilities of stuff

Despite the huge human and economic costs of the COVID pandemic, many commentators have observed that this disruption – or shock – to our resource-intensive daily lives could offer a catalyst for the great societal transformations necessary to meet the climate emergency.  

Radical growth of home working is an oft-cited example. According to Office for National Statistics (ONS) figures 50% of those in employment did some work from home in April 2020. This mainstreaming of home working has been facilitated by the rapid appropriation of digital devices and services into our everyday lives. It has been accompanied by equally rapid development of cultural skills and competencies required to (collectively) use those devices and services in a satisfactory way. And has led to major adjustments in how we work but also how we shop, interact, use our homes, engage with our local communities, learn, care for others and so on.  

Home working during the pandemic, March 2020 (image: Simon Evans on Flickr)

The question is whether these shifts could lead to systemic environmental gains. Is it an environmental ‘good’ or ‘bad’? As ever with academics, our answer is ‘it’s not straightforward...’, but when viewed from a systemic perspective it does offer an opportunity to re-imagine sustainable ways of life. 

When considering the environmental impacts of any technology or practice, understanding will be shaped by the scope of the analysis: what is considered inside the system being studied and what is ignored. A narrow scope, focused only on the technological parts of the system, makes it more straightforward to quantify the results (such as a ‘carbon footprint’ of something) but means missing out the broader implications – such as how any technology interacts with diverse social practices. One approach to this problem is to consider different scopes for analysis that address the direct, indirect and systemic impacts of a technology. We apply this framing to home working to consider some possibilities. 

Direct impacts are the environmental costs of constructing, using and disposing of a technology. Engineering methods, such as life cycle assessment (LCA) (or more colloquially, ‘carbon footprinting’) can be used to model the technology’s life cycle, systematically collect the relevant data and then apportion the ‘environmental burden’ to the different applications of that technology. In the case of digital home working, this will include the impacts of manufacturing the equipment used and providing the electricity to keep it operational: both the home laptops and Wi-Fi, but also a share of the networking equipment used to connect workers with their offices and each other, and the data centres used to power the applications they use. Accounting for this ‘hidden materiality’, and the large consumption of energy used by data centres, has led to some fearing that the impacts of digital home working are substantial. Applying University of Bristol models developed for digital services to video conferencing suggests that the truth is somewhere between the two. A ballpark estimate for the climate impact of a one-hour video conference, for example, would be about 50-100g CO2e depending on the setup used – roughly equivalent to driving 400-800m in a typical family car. This suggests that we should not let concerns about the direct environmental impact of digital services put us off a move to home working. 

Indirect impacts are the environmental costs of changing social practices related to the digital service. What do people stop doing? What do they start doing? Again, LCA can be used to quantify these – but only if one understands the nature of these changes. Social science insights are essential here, both to identify what changes to practice might occur, and to collect the data to quantify the extent to which they change across diverse populations.  

In the case of home working, the most obvious changes to practice are reduction in travel to work and decreases in energy use within workplaces. These two factors will potentially be substantially larger than the direct impacts of technology use – but will be more variable and harder to predict across the population. Reductions in heating and lighting in the workplace were, it would appear, largely offset by rises of domestic energy use (Hook et al., 2020). The most dramatic potential environmental savings are from the sharp reduction in commuting, with the Department for Transport reporting a 60% reduction in private car usage during 2020 and a 90% decline in the use of public transport. But even here we must consider a range of related indirect effects of the apparent immobility of people. During the same period, we witnessed a huge increase in online shopping as people ordered their goods for home delivery. The ONS shows that online retail sales increased from just under 19% of total retail sales in November 2019 to almost 40% within a year. Groceries, clothing, household products and takeaway foods saw the largest growth.  

The digital devices and services that allowed us to adapt so quickly to conditions of apparent human immobility also offered the technological affordances and cultural skills necessary for a commensurate growth in the circulation of goods, ordered online and delivered (often as individual items) to the homes of the immobile. Measuring these effects – especially if trying to capture the relative weighting of a trip to the shopping mall to purchase multiple items versus delivery of multiple individual items purchased online – would be necessary to estimate indirect impacts. 

Systemic impacts consist of a huge range of elements that shape, and are shaped by, technologies and social practices. In the case of home working, we pick out three core elements: infrastructures, cultures, and modes of provision. To consider the impact and potential of home working we need to recognise the changing home to include the re-purposing of space for home offices and the technologies required, from the high tech (digital devices and networks) to the low tech (desks and storage). Local communities are also changing, and development of local service infrastructures to support mass home working (for example, the re-invention of the local high street) together with a corresponding decline of city-based office infrastructures will be required if home working is to be viable over the longer term. Each of these changes come with their own direct and indirect environmental impacts.  

Cultural shifts must also be considered. Workplace cultures of presenteeism, long working hours, the status of private offices, and daily meetings are all challenged by home-working regimes. In addition, the rising use of digital platforms shows signs of fostering modes of provision through informal networks (such as familial and community based) that have, in recent history, been marginalised by the dominance of market modes of provision. Community sharing initiatives (such as food box schemes, local delivery hubs, community stores) coupled with the accumulating practical challenges of privately owned goods (as symbolised by the increasing percentage of domestic space devoted to storing seldomly used consumer goods and the decreasing use of expensive private cars) have been argued to indicate a shift towards collaborative consumption: the rejection of privately owned goods in favour of sharing (Southerton and Warde, forthcoming). While the direct and indirect environmental impacts of such systemic shifts are unknown, the potential to reduce the material flows of goods and reduce the impacts of human mobility are clear.  

Thinking in terms of the systemic implications of home working – symbolised by the immobility of people and rising mobility of goods during COVID – is more important than only measuring direct and indirect impacts. As things stand, we are moving in the direction of ‘hybrid’ working, presumably on the grounds of a ‘best of both worlds’ assumption. From a systems level perspective there is a huge risk that we end up with two systems: workplaces and home working. Whether this ends up being the worst of both worlds, layering new resource-efficient systems over old resource-intensive systems, will largely depend on whether debates regarding the post-COVID world takes the opportunity to re-imagine and re-configure the systemic impacts of technology and human practice on the environment (Geels et al., 2015). 

--------------------------

This blog is written by Chris Preist, Professor of Sustainability and Computer Systems at the University of Bristol. His research focuses on the environmental impact of digital technology and consumer electronic goods; and Dale Southerton, Professor in Sociology of Consumption and Organisation at the University of Bristol. He studies consumption, its role in organising everyday lives and its significance in processes of societal change.  

Popular posts from this blog

Converting probabilities between time-intervals

This is the first in an irregular sequence of snippets about some of the slightly more technical aspects of uncertainty and risk assessment.  If you have a slightly more technical question, then please email me and I will try to answer it with a snippet. Suppose that an event has a probability of 0.015 (or 1.5%) of happening at least once in the next five years. Then the probability of the event happening at least once in the next year is 0.015 / 5 = 0.003 (or 0.3%), and the probability of it happening at least once in the next 20 years is 0.015 * 4 = 0.06 (or 6%). Here is the rule for scaling probabilities to different time intervals: if both probabilities (the original one and the new one) are no larger than 0.1 (or 10%), then simply multiply the original probability by the ratio of the new time-interval to the original time-interval, to find the new probability. This rule is an approximation which breaks down if either of the probabilities is greater than 0.1. For exa...

1-in-200 year events

You often read or hear references to the ‘1-in-200 year event’, or ‘200-year event’, or ‘event with a return period of 200 years’. Other popular horizons are 1-in-30 years and 1-in-10,000 years. This term applies to hazards which can occur over a range of magnitudes, like volcanic eruptions, earthquakes, tsunamis, space weather, and various hydro-meteorological hazards like floods, storms, hot or cold spells, and droughts. ‘1-in-200 years’ refers to a particular magnitude. In floods this might be represented as a contour on a map, showing an area that is inundated. If this contour is labelled as ‘1-in-200 years’ this means that the current rate of floods at least as large as this is 1/200 /yr, or 0.005 /yr. So if your house is inside the contour, there is currently a 0.005 (0.5%) chance of being flooded in the next year, and a 0.025 (2.5%) chance of being flooded in the next five years. The general definition is this: ‘1-in-200 year magnitude is x’ = ‘the current rate for eve...

Coconuts and climate change

Before pursuing an MSc in Climate Change Science and Policy at the University of Bristol, I completed my undergraduate studies in Environmental Science at the University of Colombo, Sri Lanka. During my final year I carried out a research project that explored the impact of extreme weather events on coconut productivity across the three climatic zones of Sri Lanka. A few months ago, I managed to get a paper published and I thought it would be a good idea to share my findings on this platform. Climate change and crop productivity  There has been a growing concern about the impact of extreme weather events on crop production across the globe, Sri Lanka being no exception. Coconut is becoming a rare commodity in the country, due to several reasons including the changing climate. The price hike in coconuts over the last few years is a good indication of how climate change is affecting coconut productivity across the country. Most coconut trees are no longer bearing fruits and ...