https://orcid.org/0009-0009-6967-5181
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Abstract
Teleworking is increasingly popular, but its contribution to sustainability is still a matter of debate. A body of work highlights the need for an integrative view including commuting, housing space and ICT use. This paper develops such an integrative approach to analyze how the intensity of teleworking affects the carbon dioxide (CO2) emissions of these three domains. A quantitative survey was carried out for Swiss teleworkers (n = 1033). The CO2 equivalent emissions (CO2eq) were calculated for each domain and in total. The average annual CO2eq emissions per teleworker amount to a total of 1322 kg. Teleworkers’ commuting accounts for 532 kg, work-related housing space for 486 kg and ICT use for 286 kg. Our results show that more frequently teleworking reduces commuting and thereby lowers CO2eq emissions compared to low-frequency teleworkers. However, these savings are offset by additional CO2eq emissions from housing space and ICT use. The factors of teleworkers influencing total CO2eq emissions include the number of days working at a regular workplace and whether teleworkers have a home office room. The choice of residential location and of the mode of transport for commutes have significant effects in both the commuting and total models. Female gender, higher education and higher monthly household incomes show significant effects in the housing space and ICT models. The results are interpreted in light of the study’s methodological limitations, foremost the teleworker-only sample and the simplifying assumptions underlying the CO2eq emission calculations. However, the results suggest that the environmental benefits of teleworking depend on how it is implemented and practiced, as well as the layout and equipment of the workspaces at different workplaces. Thus, the paper provides an initial indication of teleworking arrangements and related CO2eq emissions in three domains and can serve as a starting point for future research on how teleworking arrangements should be organized in a more sustainable way.
Citation: Z’Rotz J, Ohnmacht T, Rérat P (2026) Do teleworking arrangements reduce CO2eq emissions? Effects on commuting, housing space and ICT use. PLOS Clim 5(7): e0000979. https://doi.org/10.1371/journal.pclm.0000979
Editor: Francesco Lamperti, Institute of Economics (Scuola Superiore Sant’Anna / RFF-CMCC European Institute on Economics and the Environment, ITALY
Received: November 3, 2025; Accepted: June 10, 2026; Published: July 15, 2026
Copyright: © 2026 Z’Rotz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Please see the dataset published on Zenodo. The dataset can be found here: https://zenodo.org/records/19101298. Dataset was cited in the paper.
Funding: This work was supported by the Swiss Federal Office of Energy SFOE as part of the ‘Swiss Energy research for the Energy Transition’ SWEET consortium SWICE (Sustainable Well-being for the Individual and the Collectivity in the Energy transition) (SFOE_SWEET-SWICE to TO). The authors bear sole responsibility for the conclusions and results. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Teleworking can be defined as paid work carried out outside the regular workplace provided by employers [1–3]. Following Asmussen et al. [4], telework arrangements can be understood as the combination of telework intensity and different workplaces. In Switzerland, on which this paper is based, 36.9% of employees worked at least occasionally from home in 2024 [5]. In general, teleworking may take place at home, in coworking spaces, or at third places (e.g., cafés, libraries, trains). Yet, teleworking has mainly been discussed as a way to reduce the environmental impact of commuting [6]. Research shows that teleworking reduces commuting frequency (e.g., [1,2,7]). However, teleworking may also generate rebound effects, such as longer commuting distances resulting from increased residential flexibility or additional leisure mobility (e.g., for Switzerland [8]). In addition, spillover effects may occur, including the duplication of information and communication technology (ICT) devices or increased housing space consumption due to the need for separate home office space [9,10].
The contribution of teleworking to sustainability is still a matter of debate. Overall, the potential of teleworking to reduce CO2eq emissions may vary across different teleworking arrangements, but several studies highlight rebound and spillover effects that may partially offset these benefits (e.g., [1,11–13]). This raises the question under which conditions telework arrangements can contribute to lower CO2eq emissions.
Against this background, this paper contributes to current research in two ways. The study advances the discussion by framing teleworking as a practice that affects simultaneously mobility, housing space, and ICT [8,14]. Empirically, this paper provides an integrated approach to the CO2eq implications of teleworking among teleworkers by considering commuting, housing space and ICT. Rather than analyzing domains in isolation, as in previous studies [1,15,16], this paper examines the environmental impacts of teleworking among teleworkers by jointly considering these domains, with a specific focus on teleworking intensity and using low-frequency teleworkers as the reference category. In addition, teleworkers are not a homogeneous group [4,17]: for example, teleworkers differ in their reasons for teleworking [18], and it is expected that different teleworking arrangements and workspace configurations are associated with distinct CO2eq emission patterns. By bringing these dimensions together, the study contributes to a more differentiated understanding of the conditions under which teleworking can be organized in a more sustainable way. Such an integrated analysis has rarely been carried out, mainly due to the limited availability of data [9].
Accordingly, we ask the following research questions: How do the various teleworking arrangements influence CO2eq emissions, both in total and across the domains of commuting, housing space, and ICT? Which factors relating to paid work and living situations, commuting behavior and socio-demographics influence the CO2eq emissions of teleworkers?
To answer these research questions, a survey was conducted among Swiss teleworkers only who worked outside their regular workplace at least once during the past four weeks. CO2eq emissions are calculated on the basis of information about the respective workplaces and workspace, working days, commuting distance and means of transport, and ICT use. We calculated four regression models with CO2eq emissions as the dependent variables, one for total CO2eq emissions and then one for each of the three domains separately. The independent variables include information about telework arrangements, work and living situations and commuting behavior, with socio-demographic characteristics being used as control variables.
The remainder of the paper is structured as follows. The next section provides an overview of the literature. The third section outlines the study’s background and methods, while the fourth section presents the main results. The fifth section discusses the overall findings in relation to the research questions and concludes by addressing the study’s limitations and implications for future research.
2. Literature review
This section introduces the analytical distinction and underlying mechanisms of direct, rebound and spillover effects of telework and presents an overview of the relevant literature (Section 2.1). The results are then presented along the three domains of commuting (Section 3.3), housing space (Section 3.4) and ICT (Section 3.5). The final section concludes the literature review by outlining the assumptions derived from the preceding discussion.
2.1. Overview
O’Brien and Yazdani Aliabadi [9] and Hook et al. [19] provide systematic insights into the impact of teleworking on energy and therefore form the basis for the subsequent synthesis of literature. O’Brien and Yazdani Aliabadi [9] propose a conceptual framework that highlights the complexity of teleworking’s impacts. Telework changes the allocation of time and the organization of everyday practices, and these shifts may trigger rebound and spillover effects [8,9], for example, through altered mobility patterns, increased housing space use, or intensified use of ICT.
The direct effects of teleworking on energy consumption are those that occur immediately, such as the reduction in the number of trips to paid work. Rebound effects refer to changes in consumption or behavior that occur following efficiency gains or reductions and may offset or even increase overall consumption [20]. Examples of rebound effects are longer commuting distances due to more flexibility in housing and workplaces or increased leisure mobility (e.g., for Switzerland [8,21]). Spillover effects, often conceptualized as indirect rebound effects, capture broader behavioral changes across different domains [22], such as increased housing space due to the integration of paid work into the home by an additional home office space. In this sense, spillover effects can be understood as a specific type of rebound effects in which environmental gains in one domain (e.g., mobility) are partly offset by increased resource use in another domain (e.g., housing space). To capture these dynamics, we distinguish between direct, rebound, and spillover effects in our analysis in line with the presented literature.
Hook et al. [19] provide an empirical synthesis of 39 studies examining energy and climate outcomes. Their analysis revealed that teleworking can save energy and emissions, but these effects are inconsistent and depend on context because rebound and spillover effects (e.g., more travel, higher home energy, changes in where people live) can partly or fully counteract the initial savings.
Since 2020, teleworking has become an integral part of the organization of work [23] and has altered working habits [24]. However, the studies by O’Brien and Yazdani Aliabadi [9] and Hook et al. [19] predate its widespread adoption. The different scopes, methodological approaches and underlying assumptions of existing studies make it difficult to compare them and assess the overall impact of teleworking on energy-related CO2eq emissions [9,19]. The following literature review focuses on subsequent research, distinguishing between scope and methodology, and highlighting the key findings.
These studies reveal that most existing work primarily addresses the mobility sector. Since 2020 studies have more frequently addressed housing space and ICT areas, yet mobility, housing space, and ICT use are seldom analyzed together in an integrated manner (Table 1).
2.2. Mobility
Teleworking influences mobility in three main areas: as a direct effect on the number of commuting trips, as rebound effects on additional non-work travel, and as spillover effects on residential relocation.
Commuting-related CO2eq emissions depend strongly on distance [32] and mode of transport [33,34], which depend in turn on socio-demographic factors as gender, income and household composition [35,36]. In addition, Balthasar et al. [1] show that the proportion of teleworking within a working week, the regular place of work, attitudes toward individual mobility and previous relocation behavior all have an impact on CO2eq emissions.
Various studies indicate that teleworking can reduce overall commuting distances and the related CO2eq emissions (for Switzerland, e.g., [1,6,21,37]). However, several studies also identify rebound effects. For example, teleworkers tend to accept longer commuting [38–40] for Switzerland [2]. Z’Rotz et al. [18] report gender differences, with female teleworkers commuting for shorter periods than their male counterparts. Similarly, Hostettler Macias L et al. [21] show that teleworking increases the tolerance for commuting and that longer teleworking experience is associated with longer commuting distances.
Other studies identify rebound effects associated with additional non-work travel, such as trip-chaining and leisure travel [41]. Vovsha et al. [42] demonstrate that travel patterns and household activity choices depend on time availability. As teleworking increases available time, individuals may engage in more out-of-home activities. On teleworking days, trips are therefore more likely to involve escorting children to school or additional purposes such as shopping and leisure [1,2].
2.3. Work and housing space
A spillover effect of teleworking is the increased demand for housing space as paid work shifts into the home environment. This often prompts relocation decisions and broadens the range of feasible residential locations, as proximity to the workplace becomes less important [43]. Teleworkers use more housing space per person due to the need for a dedicated workspace and socio-economic characteristics associated with teleworking [10]. The need for a dedicated office space at home can lead to moving to a larger dwelling [44,45]. Having a separate home office room reduces distractions and preserves the boundaries between professional and family life [46]. Regardless of causality, the fact that working from home requires more space is one of the factors influencing the tendency to continue living in larger homes [47]. Consequently, Moos et al. [48] find that increased energy and housing consumption at home can offset the environmental benefits gained from reduced commuting. Likewise, Shi et al. [28] emphasize the importance of building energy systems and heating practices, noting that the CO2eq emissions impact of teleworking varies depending on whether the whole dwelling is heated or only specific rooms.
Furthermore, teleworking can also reduce energy consumption in office buildings [11]. Such benefits increase with the amount of office space saved through flexible workstation models, where employees use shared desks rather than fixed individual ones. However, there is little evidence that employers actually adopt shared workspace concepts [9]. If these workspaces continue to be heated and lit without being used, the potential savings are significantly reduced [19]. Offices often remain fully operational, with no reduction in total workspace as long as a sufficient number of employees continue to work on site on the same time [49]. In addition, even if a substantial share of employees telework, organizations may not adjust heating or cooling settings in office buildings, meaning that unoccupied workplaces can continue to consume significant amounts of energy [9,23,50]. Consequently, energy consumption in office buildings tends to remain stable, as heating, cooling, and lighting systems typically operate regardless of occupancy levels. This indicates that the amount of workspace used per employee is a crucial factor in determining the CO2eq emission impacts of teleworking.
2.4. ICT
Teleworking is carried out using ICT [51], which have increased flexibility and autonomy regarding where, when, and how paid work is performed [46]. Yet, these technologies themselves consume energy during their whole life-cycle (production, use, maintenance, and disposal) [52]. At the same time, ICT can enhance efficiency by enabling digital substitutes for physical activities [52], such as video conferences substituting business travel. However, such e-substitutes may also generate rebound effects if efficiency gains stimulate higher overall usage, for example, through more frequent online meetings or increased email traffic. It can also be assumed that teleworking can change the way ICT is used.
On the one hand, teleworking can induce rebound effects through the increased use and acquisition of ICT devices. Additional workplaces may require duplicate devices such as external monitors or printers [9], leading to higher overall energy consumption. As Nakanishi [49] emphasizes, the net energy impact of teleworking largely depends on the efficiency and redundancy of ICT, with potential savings only achievable if home devices are more energy-efficient than those used in offices or if teleworking does not result in the use of additional equipment. Moreover, the intensified use of digital communication tools such as e-mail or videoconferencing to maintain contact with colleagues and clients can further increase ICT-related CO2eq emissions.
2.5. Conclusions
Overall, the potential of teleworking to reduce CO2eq emissions may vary across different teleworking arrangements. However, the extent to which this potential is realized depends on factors such as workspace use, residential energy efficiency, and changes in mobility patterns among teleworkers. Several studies also highlight rebound and spillover effects that may partially offset these benefits (e.g., [1,11–13]).
To gain a more comprehensive understanding of teleworking’s environmental effects, commuting, housing space and ICT should be examined as an integrated framework. Accordingly, this study distinguishes between direct effects (e.g., fewer commutes), rebound and spillover effects (e.g., increased workspace demand, duplicate ICT), as teleworking changes the everyday lives of teleworkers. Assessing the environmental impact of teleworking is inherently limited by system boundary definitions. These boundaries can seldom be fully captured, and rebound effects, e.g., like non-work travel, remain often unaccounted for.
Regarding commuting, research shows that teleworking affects commuting in different ways. Teleworking reduces the frequency of commuting, as employees do not have to commute to their regular workplace on teleworking days. At the same time, teleworking can be associated with longer commuting distances, for example, when employees live further away from their workplace due to less frequent commuting. It is hypothesized that commuting-related CO2eq emissions vary across teleworking intensities.
In the context of housing space, it is argued that telework often leads to a multiplication of workplaces and workspaces. Since energy consumption in housing space is dependent on the space used, an expansion of work-related housing space can lead to higher CO2eq emission-related effects. Based on these considerations, it is hypothesized that the use of multiple workplaces is associated with an increased need for work-related housing space, leading in turn to higher CO2eq emissions in the domain of housing space.
ICT is a key prerequisite for implementing telework. Shifting paid work to multiple workplaces may require an expansion of the necessary ICT infrastructure, such as additional monitors, desktop computers or printers at different workplaces. This multiplication of ICT infrastructure can increase energy consumption, especially through production. Although individual studies indicate that the direct energy consumption of ICT is relatively low compared to commuting or housing space, the multiplication of devices across multiple workplaces can still lead to additional CO2eq emissions. Against this background, it is hypothesized that a higher number of workplaces is associated with increased ICT-related CO2eq emissions.
The data-gathering process and statistical analysis used to investigate these assumptions will be presented in the following section.
3. Methods
3.1. Study background and survey design
This study is embedded in the broader framework of the SWICE (Sustainable Well-being for the Individual and the Collectivity in the Energy transition) project, which aims to generate empirically based knowledge to inform sustainable planning strategies in Switzerland. The research team designed an online survey on workplace choices, commuting behavior, housing space and ICT use. The survey combined closed-ended questions, Likert-scaled attitudes and open-ended responses and was available in German, French and English. Before the survey was sent out, a pre-test was conducted by the research team and external experts.
Participant recruitment for the survey took place between 28 November and 9 December 2024. Participants were recruited from the panel of the market research institute to ensure a representative sample of the Swiss working population in the French- and German-speaking parts (the Italian part was left out due to its small demographic weight). Respondents had teleworked at least once in the past month, defined as working from home, in a coworking space, at a third place (e.g., cafés, library), or on the move. The panel generated 1230 answers after data-cleansing. The analysis is based on the telework dataset, which is published online (see [53]).
3.2. Ethics statement
Participation in the survey was entirely voluntary. All participants provided written informed consent for their anonymized data to be used for research purposes. All collected data were fully anonymized and used only in aggregated form, ensuring that no individual respondents can be identified. The study was conducted in accordance with institutional ethical guidelines and approved by the Ethics Committee of the Lucerne University of Applied Sciences and Arts. The study complies with applicable legal and ethical standards.
3.3. Descriptives
The proportion of women in the sample is 41.2% (Table 2). The average age is 47.2 years. In terms of educational attainment, 40.6% of respondents have a university degree, 40.3% hold upper secondary or higher vocational qualification (middle level), and 19.1% have completed compulsory schooling or vocational education (lower level).
The monthly household income of respondents is spread across several income categories. 28.2% of respondents have a household income less than CHF 9000 per month, 24.6% have CHF 9001–12000, and 31.3% have more than CHF 12000. 16.0% of respondents did not provide any information about their income.
The average household size is 2.7 persons. Household types include couples with children (39.0%), couples without children (33.0%), single-person households (19.8%), and single-parent households (8.2%). Compared to the Swiss working population, men, older workers and those in larger households (with couples or families) are slightly over-represented.
The respondents use two different workplaces on average, with ‘working on the move’ not included in this calculation. A large majority of participants work at a regular workplace (97.5%), with almost as many working from home (98.0%). In addition, coworking spaces are used by 6.1% of respondents, ‘on the move’ by 41.0% and other workplaces by 9.1%. On average respondents work three days at a regular workplace and two days from home. The average employment rate is 88.9%, with full-time employment in Switzerland defined as an average workweek of 42 hours.
3.4. Data preparation and enrichment of the dataset with CO2 equivalent figures
Data preparation included the enrichment of the dataset with CO2 equivalent figures for commutes, housing space and ICT. A measure of carbon dioxide equivalents (CO2eq) was applied. The CO2eq standard is a metric used to quantify the climate impact of various greenhouse gases, including carbon dioxide, methane and nitrous oxide. These values are expressed as emissions in kilograms of CO2eq (kg CO2eq/anno or passenger kilometer). The respective CO2eq factors are shown in Table 3. The assumptions for each domain are explained below.
3.4.1. Commuting.
Calculating the CO2eq emissions for commuting follows the method of Balthasar et al. [1]. We use routing driving distance with short-distance algorithm. The study participants report their number of working days per week, working location within a working week and the postcode of the regular workplace location, as well as the main mode of transport for the commute. The CO2eq factors incorporate both embodied energy from the production of transport modes and infrastructure, and the operational energy required for their use [55], which are the commonly used CO2eq factors in Switzerland. CO2eq emissions are calculated by multiplying the respective CO2eq factor by the commuting distance between the workplaces and the place of residence (derived using short-distance algorithms), the mode of transport, and information on daily workplace locations (see Table 3). These data reflect a regular working week. CO2eq emissions are calculated over a period of seven days and then extrapolated to provide an estimate of the emissions for the entire year for paid work (on average 46.9 weeks).
3.4.2. Housing space.
To calculate CO2eq emissions generated by paid work-related workspaces, the housing space at different workplaces is considered. The question was ‘How much space in square meters is available to you at the respective workplace?’, and respondents were asked to quantify the workspace they use primarily themselves. The calculation assumes that housing spaces are heated continuously at the same temperature, regardless of whether they are used or not. In practice, energy savings through teleworking in the office sector are likely to be low or non-existent [28]. Air-conditioning systems are not (yet) an issue in Switzerland, which is why they are not considered here.
Space-heating accounts for the majority of energy consumption in households, with floor area being the primary determinant of heating energy demand [28]. Other factors influencing energy requirements for heating include heat loss from the building envelope, indoor temperature and outdoor temperature. As we have no information on building standards, the calculations are based on average values for the operation of the floor area [56]. Annual CO2eq emissions are therefore calculated by multiplying the used workplace in square meters by an average CO2eq factor per square meter (see Table 3).
3.4.3. ICT.
To calculate the CO2eq emissions generated by the use of ICT, the ICT at each workplace is considered, including external monitor, desktop computer and printer. It is assumed that every teleworker has a laptop. CO2eq factors and device-specific life-cycle assumptions are based on Gröger [57]. The CO2eq emissions are calculated in order to cover production-related and use-phase emissions, with a distinction made between active use and standby power. A daily usage time of seven hours per day, five days per week, was assumed for a full-time position (printers: 0.1 hours per day). An average service life of five years was assumed for all devices. Annual CO2eq factor for the use phase was estimated using the following formula for a full-time position:
where usePower represents the use power demand (W), sbPower the standby power demand (W), and useHours the average daily active operating hours. The factor 0.365 converts daily watt-hours into annual kilowatt-hours (365 days/ 1000). To control for differences in workload, the resulting use-phase emissions were multiplied by the individual employment rate (workload fraction, e.g., 0.8 for 80% employment). This adjustment ensures that use-phase emissions are proportionally scaled for part-time employment.
To determine total ICT CO2eq emissions, the respective number of devices is added together and multiplied by the respective CO2eq factors for the devices (see Table 4). Due to the complexity of collecting data on additional ICT use, such as the exact duration, the number of e-mails or video conferences, or even the use of data storage and data centers, these aspects cannot be considered in this paper. However, they might compensate for the simplified nature of the calculation.
3.4. Variables for modelling
The CO2eq emissions are used as dependent variables. The annual emissions in kilograms of CO2 equivalent (kg CO2eq/a) per person is calculated for each of the domains commuting, housing space and ICT and then added up to determine the total. The independent variables are characteristics of the work and living situation and of commuting behavior, with the socio-demographic characteristics being used as control variables. The number of working days per week at regular workplaces and from home and whether the individuals work in a coworking space provide information about teleworking arrangements. Furthermore, the variable ‘having a home office room’ captures whether respondents have a separate room they use as an office at home. In addition, workload captures the respondents employment rate. Three categories were distinguished: high workload (reference category, more than 80%), middle workload (51–80%), and low workload (below 50%). The variable was included to account for differences in working hours that may influence work-related activities.
Variables related to location, such as residential location choice measured by proximity of the workplace to the place of residence and residential attractiveness, provide insights into individuals’ preferences for work and residential locations. The ‘attractiveness of the residential environment’ typically refers to the subjective perception of the quality and appeal of the residential area. Both variables are relevant because teleworking alters the relationship between place of residence and workplaces, influencing residential preferences and the perceived importance of workplace location. In addition, the variable relating to commuting behavior such as the use of public transport (recoded 1 if used at least once a week in the last six months) captures individual attitudes toward and preferences for environmental behavior.
Socio-demographic characteristics are included as control variables in the regression models. Factors such as household type, gender, age, education and monthly household income may influence teleworking patterns.
3.5. Modelling
To predict CO2eq emissions, four regression models were estimated, one for total CO2eq emissions, and one each for the domains of commuting, housing space and ICT use. The regression model was selected in an iterative process, testing potentially relevant predictors related to paid work (e.g., workplace), commuting, individual preferences and attitudes, and socio-demographic characteristics. To ensure robust statistical inference, heteroskedasticity-consistent standard errors were employed. In addition, bootstrap resampling with 5000 replications was applied to obtain standard error estimates that are robust to potential deviations from distributional assumptions [58]. Both approaches yield substantively consistent results. Multicollinearity among the explanatory variables was assessed using variance inflation factors (VIF). For the predictors, tolerance values ranged between.50 and.96 and corresponding VIF values between 1.04 and 2.00, indicating no problematic multicollinearity. Model fit and explanatory power were evaluated using standard indicators (e.g., F-test, R2). Statistical significance was assessed using conventional thresholds (p < 0.1, p < 0.05, p < 0.01, p < 0.001).
4. Results
In a first step, the relevant influencing factors, such as the number of workplaces, housing space and the number of ICTs, as well as the average CO2eq emissions, will be evaluated descriptively. The regression models are then discussed in the following section. Net effects of CO2eq emissions (kg, per year) are then presented based on the analysis.
4.1. Descriptive statistics of CO2eq emissions by commuting, housing space and ICT use
The average annual CO2eq emissions per teleworker associated with paid work and teleworking amount to a total of 1321.6 kg (see Table 5).
The average CO2eq from teleworkers’ commuting is 531.6 kg per year. The average distance from teleworkers home to the regular workplace is 29.2 km (one way), which is significantly above the national average of 13.9 km [59]. The average distance to coworking spaces is 26.3 km, while the average distance to other workplaces is 59.1 km. The mode of transport varies depending on the workplace and differs significantly from the national average. 44.4% of respondents get to their regular workplace using public transport, 33.9% drive by car, 15.4% cycle, and 6.3% walk or use an e-scooter. Nationwide, 51.3% of the working population commute by car, 30.5% use public transport, 10.0% cycle, 9.2% walk and 0.5% register other modes.
The picture is slightly different for travel to coworking spaces: 49.6% of respondents use public transport and 31.5% drive by car, while 7.9% cycle and 11.0% walk. While most respondents (39.8%) take public transport or drive to other workplaces (42.0%), a minority cycle (8.0%) or walk (10.2%).
In terms of housing space, an average of 485.9 kg of CO2eq is emitted per teleworker per year. The average of total workspace is 20.5 m2, whereas regular workplace size is 10.8 m2 and 8.5 m2 in coworking spaces. At home, 66.8% of respondents have a separate office room to telework. At 13.8 m2, the average size of this is larger than that of external workplaces.
On average 286.3 kg of CO2eq is emitted per teleworker per year for ICT use. Respondents use an average of 1.5 external monitors, 0.9 desktop computers and 1.5 printers. However, the equipment varies significantly between different workplaces. Most workstations at regular workplaces have external monitors (82.7%), desktop computers (51.6%) and printers (95.7%). Workplaces at home have less equipment: 65.4% have external monitors, 41.9% desktop computers and 57.8% printers. Coworking spaces tend to be even less well equipped (external monitors 49.2%, local desktop computers 22.2%, printers 42.9%).
4.2. Results of the multivariate regression analysis
The objective of the regression analysis is to identify the factors associated with differences in CO2eq emissions among teleworkers. The results are presented in Table 6.
4.2.1. Workspaces at home, in coworking spaces, and at the employer.
A key factor in the models is the number of days teleworkers spend at their regular workplace (see Table 6). This variable has significant positive effects on the housing space and ICT models. Also the number of days working from home are positive associated with CO2eq emissions in the housing space and ICT models. In addition, working at a coworking space is associated with higher CO2eq emissions in the housing space model. The positive relationship between the number of days working at a regular workplace and CO2eq emissions in the housing space and ICT models suggest that more frequent workplace use is associated with higher CO2eq emissions. The ICT model shows that the more frequently teleworkers work from home, the higher their CO2eq emissions are.
Working from home often involves the explicit use of a separate home office room, which in turn has a significant positive effect on CO2eq emissions in all models. This means that working in a separate home office room has a comparable impact on CO2eq emissions and that these teleworkers tend to equip their home offices with more extensive ICT infrastructure. In addition, the positive association between having a separate home office and commuting-related CO2eq emissions may also point to a rebound effect.
4.2.2. Location and commuting aspects.
Residential location choices, such as proximity of the place of residence to paid work and the attractiveness of the residential environment, are significant for CO2eq emissions (see Table 6). The attractiveness of the residential environment has a significant positive effect on the total and commuting models.
Proximity to the workplace has significant negative effects in the total and commuting models. The use of public transport shows negative effects in the total, commuting and ICT models.
4.2.3. Socio-demographic aspects.
Among the socio-demographic control variables, only gender, education and higher income in the ICT model, as well as monthly household income in the housing space model, show significant effects (see Table 6). Monthly household income has a significant positive effect in the housing space model. Other variables such as household structure, or age have no significant effect. The lack of significant coefficients suggests that the socio-demographic aspects have only little impact on CO2eq emissions.
To sum up, both CO2eq emission-increasing and emission-reducing factors can be identified that are closely related to work organization, housing conditions and choice of transport. CO2eq emissions increase with the number of days working at the regular workplace per week in housing space and ICT models, while having a home office room also contributes to higher CO2eq emissions in all models. Working at a coworking space contributes to higher CO2eq emissions in the housing space model. The attractiveness of the place of residence is positively associated with CO2eq emission in the total and commuting models. The monthly household income has an increasing effect on housing space CO2eq emissions. Female gender, education and higher monthly household incomes are negatively associated with the ICT model. Other socio-demographic control variables show no significant effects.
4.3. Net effects of CO2eq emissions (kg, per year)
The next step is to calculate scenario-based net CO2eq emissions for different teleworking arrangements. This calculation is separate from the regression analysis and is based on estimated avoided commuting CO2eq emissions and additional CO2eq emissions from housing space and ICT production.
On average, respondents use two different workplaces: most of them alternate between their regular workplace provided by their employer and their home. To calculate the net effects of different teleworking arrangements, we define a counterfactual scenario in which all paid work would take place exclusively at their regular workplace. For all workplaces outside the regular workplace, namely the home office, coworking spaces, and third places, additional CO2eq emissions are estimated based on the work-related housing space and the ICT infrastructure at these workplaces. Thus, coworking spaces and third places are treated as workplaces in the classification of teleworking arrangements and are also included in the CO2eq calculation through their associated workspace and ICT-related CO2eq emission factors.
The number of full teleworking days serves as the basis for estimating commuting-related CO2eq emissions savings. In addition, information on home office space, coworking spaces and third places is used to estimate additional CO2eq emissions from housing space and ICT. In the calculation, only the CO2eq factors for producing devices were taken into account for ICT (see Table 4). Combining these figures yields the overall effect among teleworkers: commuting-related CO2eq emission savings minus the additional CO2eq emissions from housing space and ICT at home, coworking spaces and third places. The net annual effect of different teleworking arrangements on CO2eq emissions can be expressed as follows:
Negative values in Table 7 represent savings due to teleworking arrangements; positive values represent additional CO2eq emissions.
Based on the reported average of 1.3 full days working from home, on average the estimated avoided commuting emissions amount to 218.9 kg CO2eq per teleworker per year, assuming that these teleworking days fully replace commuting trips. In addition, the savings are offset by rebound and spillover effects due to additional CO2eq emissions in the home office or at coworking spaces, on average, from housing space (236.2 kg CO2eq for an average of additional 10.2 m2) and ICT use (49.6 kg CO2eq for an average of additional 1.7 devices). This results in a net difference of 66.9 kg CO2eq emissions per teleworker when comparing observed teleworking arrangements with a scenario in which paid work would take place entirely at the employer’s workplace.
Based on the scenario-based net calculation among teleworkers, the observed teleworking arrangements are associated with avoided commuting-related CO2eq emissions, while additional CO2eq emissions arise from work-related housing space and ICT production. This calculation should be interpreted as a comparison with a counterfactual scenario in which paid work would take place at the regular workplace. However, this analysis does not capture ‘real’ savings compared with non-teleworkers and does not account for rebound effects such as additional non-commuting travel or long-term effects (e.g., longer commuting distances, non-work-travel).
5. Discussions, limitations and future research
Understanding the environmental implications of teleworking arrangements has become increasingly important. Teleworkers do not represent a homogeneous group, as they differ in their teleworking arrangements [1,4,17,18], which may influence their behavior and associated CO2eq emissions. By analyzing variation within the group of teleworkers regarding teleworking arrangements, the study provides new insights into how different settings relate to differences in CO2eq emission patterns in Switzerland.
By doing this, this paper contributes to the scientific debate by addressing this research gap for teleworking arrangements in Switzerland. Unlike many previous studies considering only one domain (e.g., [1,39,48]), this paper adopts a broader perspective shedding light on the potential savings of teleworking among teleworkers, as well as rebound and spillover effects. A key contribution of the study is the quantification of these CO2eq emissions based on empirical data. In doing so, the paper opens the discussion on the conditions under which teleworking arrangements can be organized in a more sustainable way. Understanding how different teleworking arrangements reshape commuting, housing space, and ICT infrastructures helps explain the rebound and spillover effects across these domains in this study.
To sum up, in Switzerland the average annual CO2eq emissions per teleworker associated with paid work and teleworking is calculated at a total of 1321.6 kg, while teleworkers’ commuting accounts for 531.6 kg, housing space for 485.9 kg and ICT use for 286.3 kg. Although teleworking eliminates the need to commute and reduces commuting-related CO2eq emissions, potential rebound effects such as increased non-work travel are still not accounted for in this analysis. In addition, these savings from commuting are already largely offset by rebound and spillover effects due to additional CO2eq emissions in the housing space and ICT use. This analysis confirms the importance of adopting a more integrated approach, as increasingly emphasized in recent research [9], and it distinguishes itself from studies that focus solely on commuting aspects [1,16,25]. Furthermore, the analysis highlights the importance of workplace design and ICT use in reducing CO2eq emissions, as seen in previous studies [15,26,29,30].
Factors influencing the CO2eq emissions of teleworkers in Switzerland are workspace-specific, availability of a separate home office room or number of days working at a regular workspace, and location-specific, with the wish for proximity to workplace as a factor for residential location choice. The use of public transport also has implications for CO2eq emissions. Socio-demographic control variables play a limited role overall: female gender, education and higher monthly household income show effects.
Particularly noteworthy is that among teleworkers, a higher number of teleworking days and having a separate home office room are positively associated with CO2eq emissions related to housing space and ICT. This finding is consistent with previous studies highlighting the rebound and spillover effects of teleworking on housing space [10,48]. But beyond ecological considerations, the social aspects also need to be addressed. Research on boundary management highlights the separation of paid work and private life as an important factor for well-being. Having a separate home office room can help minimize disruptions and distractions [60]. Future research should therefore examine whether the availability of a separate home office room is associated with the greater well-being of teleworkers.
Overall, among individuals who telework at least once per month, the results suggest that different teleworking arrangements are linked to rebound and spillover effects due to increased housing space and higher ICT use. At the same time, the scenario-based calculation further indicates potential commuting-related CO2eq emissions savings. Thus, the environmental benefits of telework arrangements depend on how it is implemented in practice and on the layout of the workspace [15,26,29,30]. Based on our research for Switzerland, several levers can be discussed for reducing CO2eq emissions in the context of teleworking. Reducing the amount of workspace used per person can lead to significant savings, while higher occupancy rates and more compact or flexible workspaces can reduce CO2eq emissions. In terms of commuting, the aim is to reduce commuting distances and frequency, and to switch to public transport and active mobilities. Measures that reduce housing space, ICT and commuting requirements are, for example, location-based coworking spaces, with multimodal work infrastructure and conscious spatial planning in residential neighborhoods. Coworking also takes advantage of the positive aspects of spatial separation between paid work and home.
The empirical analysis is situated in Switzerland, a context characterized by comparatively high levels of teleworking, specific housing patterns, and distinct mobility infrastructures. The findings should therefore be interpreted in relation to this national context. Such limitations suggest that the results should be interpreted as indicative approximations rather than precise measurements of actual CO2eq emissions among teleworkers. Among the limitations of this research is the fact that calculations of the dependent variables are based on simplified calculations and assumptions. Furthermore, the analysis relies on several simplifying and strong assumptions regarding CO2eq emission factors. The selected CO2eq emission factors may therefore be subject to debate. There are uncertainties and missing information regarding the age and standard of ICT and buildings, the energy performance of workspaces and other relevant contextual factors that were not available in the dataset. Additional rebound effects such as non-work travel, changes in residential location, lifestyle, or consumption patterns often extend beyond the scope of conventional analyses, which were not controlled for in this study. Consequently, empirical results should be interpreted within the limits of the chosen framework, acknowledging that both underestimation and overestimation of CO2eq emissions are possible depending on the boundaries applied, which limits the accuracy of the ecological assessment.
The cross-sectional design does not allow causal statements as the observed associations are based on a self-selected sample of teleworkers and does not use causal identification strategy (e.g., experimental design). The identified effects describe associations, but do not allow clear conclusions to be drawn about the causal relationships of teleworking on commuting, home office room or ICT use. In addition, potential endogeneity issues cannot be fully ruled out. Certain characteristics such as housing conditions, mobility behavior, or individual preferences may simultaneously influence both teleworking arrangements and CO2eq emission outcomes, making it difficult to disentangle cause and effect.
Moreover, the study design does not include a control group of non-teleworkers. As a result, the findings describe differences within the group of teleworkers who telework at least once per month rather than differences between teleworkers and non-teleworkers. This limits the ability to assess how teleworking affects CO2eq emissions, as differences observed in the models may partly reflect underlying socio-economic or occupational characteristics rather than the presence or absence of teleworking itself. Also, the regression models may not capture all relevant determinants of mobility behavior, housing characteristics, and ICT use. As a result, some relevant factors could remain unobserved.
Furthermore, various aspects, such as workplace design, access to public transport or environmental policy, cannot be influenced at the individual level. In our case, employees’ freedom of choice in the workplace may be restricted; for example, they may not be able to design their workspace. However, such organizational arrangements can influence employees’ CO2eq emissions. Therefore, promoting sustainable practices in the workplace requires collective action, with employers playing a key role in enabling environmentally friendly behavior [61].
Despite all of the limitations, the estimates provide an initial indication of the potential relationships between teleworking arrangements and CO2eq emissions and can serve as a starting point for future research employing more refined data and methods. Building on these findings, further research is needed to account for the heterogeneity of teleworkers, including differences in socio-demographic characteristics, job types, and work location autonomy. Moreover, future studies should advance the integrated analysis of multiple impact domains. In particular, integrating environmental and well-being dimensions would enable a more comprehensive understanding of how telework arrangements shape everyday practices and energy use.
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