Air pollution has significant environmental and human health impacts and is the single greatest environmental health threat (WHO (World Health Organization), 2024). Exposure to air pollution has been linked to a range of adverse health effects, including respiratory diseases and cardiovascular conditions (Manisalidis et al., 2020). Monitoring air quality is crucial for managing and mitigating these risks, yet air quality monitoring networks are often limited in terms of spatial coverage (Seto et al., 2019), and in some contexts, particularly informal settlements or low- and middle-income countries (LMICs), may be non-existent (Smith et al., 2025). Further, traditional air quality monitors at fixed-site networks, though highly accurate, are costly to install and maintain, limiting their deployment to mostly urban, developed areas, but even then, coverage is limited (Xie et al., 2017). This spatial sparseness in monitoring networks hinders our ability to capture the full extent of air pollution, especially in rural or underserved areas (Karambelas et al., 2018).

In response to these challenges, there has been growing interest in using lower-cost, Internet of Things (IoT)-enabled sensors to complement traditional monitoring networks. These more affordable sensors can provide data on air quality at high spatial and temporal resolutions (Lu et al., 2021). Their versatility makes them valuable tools in high-income countries (HICs), where they can “plug the gap” by filling in air quality data in locations not typically covered by traditional networks, such as in urban parks, school playgrounds (e.g., Kumar et al., 2020; Pradhan et al., 2024), rural areas (e.g., McCarron et al. in review), or other outdoor locations where people spend time. Similarly, in LMICs or informal settlements, where air quality is frequently poor yet (Rentschler and Leonova, 2023) monitoring is often not performed routinely due to, for example, high costs associated with monitoring infrastructure, a lack of local capacity to set-up and maintain the monitoring stations and technological incompatibility (e.g., limited power or connectivity) (Bainomugisha et al., 2023; Bainomugisha et al., 2023), lower-cost sensors offer a promising and emerging solution for establishing baseline monitoring networks (Awokola et al., 2020).

One of the main benefits of lower-cost air quality sensors is their potential for off-grid use, allowing them to be deployed in areas with limited access to infrastructure. Relying on mains-powered systems presents several limitations, including the requirement for stable power restricting deployment locations (especially where electricity infrastructure is lacking or unreliable) and power outages or blackouts (which are common in some regions) (Awokola et al., 2020). To maximise the sustainability and deployment flexibility of lower-cost air quality sensors, solar power therefore presents a promising solution. Solar-powered sensors can operate independently of the grid, reducing long-term electricity costs and minimising environmental impact. In addition, solar-powered systems provide the potential for more remote air quality monitoring, enabling the deployment of sensors in previously unviable areas. While lower-cost sensors with built-in solar are becoming available, their limited variety restricts choice, and their typically higher cost makes them inaccessible to some users. Consequently, the ability to set up a custom solar-powered system is very useful.

The aim of this paper is to describe and translate practical learnings from the design and deployment of a solar-powered, lower-cost air quality sensor system into design-relevant lessons for off-grid monitoring. Adopting a systems-orientated perspective grounded in real-world deployment, the paper consolidates technical, environmental and institutional factors shaping system feasibility, resilience and scalability, and provides an applied reference for the development of sustainable, autonomous air quality monitoring in off-grid and under-monitored settings.

The following section draws on practical experience from designing and deploying solar-powered lower-cost air quality sensors to identify key considerations for off-grid monitoring in a range of settings. These insights are summarised in Figure 2, which brings together the technical and contextual factors influencing design and deployment decisions.

Deploying the solar-powered PurpleAir sensors in the Scottish setting provided valuable insights into the practicalities of designing and implementing a hyperlocal, off-grid air quality monitoring sensor network. Under typical conditions in Central Scotland, the solar setup - consisting of a 30 W panel and a 12 V 33 Ah battery - successfully met the energy demands of the PurpleAir sensor, demonstrating the practical feasibility of using such setups to support decentralised air quality monitoring in locations without access to mains electricity.

Modelling-based analyses of solar-powered air quality monitoring systems similarly demonstrate that optimal panel and battery configurations vary substantially across climatic contexts, with distinct failure risks emerging in cold, high-latitude regions compared to warmer, higher-irradiance environments (Shlipak et al., 2025). Given Scotland’s high latitude, short winter daylight hours, and relatively cold climate, these findings are likely to be transferable to regions with more favourable solar conditions, including many LMICs. In climates with more sustained solar irradiance and higher ambient temperatures, comparable systems could likely operate with smaller panels and reduced battery capacity, potentially removing the need for bulky lead-acid storage altogether. This highlights the importance of tailoring solar power configurations to local climatic conditions rather than adopting a one-size-fits-all approach (see considerations in Figure 2). In such contexts, where solar irradiance is generally higher and grid infrastructure more limited, solar-powered sensors are not just a viable option but a critical enabler of monitoring in contexts where grid access is limited or unreliable and for extending data collection into locations where it is most urgently needed (Pinder et al., 2019).

While our deployment focused on rural and suburban contexts, the underlying design principles (e.g., portability, off-grid autonomy) are equally applicable to urban environments, particularly areas underserved by regulatory monitoring infrastructure. In such hyperlocal contexts, where spatiotemporal heterogeneity in pollution concentrations is significant but poorly characterised (Che et al., 2023), solar-powered sensor networks offer the potential to generate fine-grained data capable of informing community-level interventions and urban policy decisions.

Seasonal variability emerged as a key constraint in the design and performance of the off-grid power system. During the northern hemisphere winter months, reduced solar irradiance and lower ambient temperatures significantly impacted both the efficiency and charging capacity of the battery, as well as the performance of the PWM charge controller owing to its inability to operate the solar panel at its higher cold-weather voltage and therefore converting less of the available solar power into usable charge. This resulted in reduced storage performance and increased risk of power interruptions, especially during extended periods of low sunlight. These challenges are likely to be compounded in built-up urban areas, where factors such as tall buildings and narrow street canyons introduce persistent shading effects that reduce the consistency and predictability of solar input. Comparable sensitivities to solar power system configuration and siting have also been reported in other real-world air quality monitoring deployments, where shading, mounting constraints, and charge-storage interactions limited data continuity despite substantially larger solar capacity and more favourable climatic conditions (Wei et al., 2019). This highlights the need to consider enhanced energy storage or auxiliary power solutions, particularly in built-up, high-latitude or seasonally variable environments, as well as system designs that can automatically recover from power interruptions and resume data logging without manual intervention.

Future designs would benefit from the integration of lithium-ion battery systems, which offer higher energy density and reduced volume, although their operational performance in low temperatures (typically below 0 °C) requires careful consideration, particularly in the months when sunlight hours decrease and temperatures are cooler. Additionally, using a maximum power point tracking (MPPT) charge controller would allow the system to harvest a greater proportion of the available solar energy by tracking the panel’s higher winter voltage and converting it efficiently to the battery’s charging voltage, thereby improving cold-season performance and overall system resilience.

Despite the technical viability of solar-powered systems for lower-cost air quality monitoring, deployment challenges remain that significantly affect their real-world applicability, particularly in urban and publicly accessible environments. The sealed lead-acid battery selected for this study, while cost-effective and relatively robust, was bulky and heavy. Its size and weight limited where it could be installed, bounded by practical and regulatory constraints (e.g., permissions from local authorities in our UK context). Mounting regulations prevented the placement of battery units above head height, which then required ground-level installations. This introduced a series of new risks including increased exposure to moisture, greater susceptibility to tampering or vandalism and potential obstructions to pedestrian access (Bulot et al., 2019). In densely built urban areas, where vertical surfaces are highly utilised and ground space limited, such limitations are likely to intensify (Guo et al., 2022). There is a growing recognition that air quality monitoring networks must be designed not only for accuracy and data reliability but also for public acceptability (e.g., Morton et al., 2021). Future work in this area should prioritise compact and integrated setups and co-design processes that account for the aesthetic, infrastructural and regulatory conditions of specific urban environments.

While the PurpleAir sensor itself has relatively modest energy requirements (~0.9 W continuous draw) (PurpleAir, 2026), the addition of a Wi-Fi dongle to enable remote data transmission significantly increased the system’s overall power demand. Combined, these components required an estimated 2 W continuous load, or approximately 45.6 Wh per 24-h period. This additional energy burden presented a major constraint for year-round, solar-powered operation in a temperate, high-latitude context. Simulations using the JRC Photovoltaic Geographical Information System (PVGIS v.5.3) (European Commission, 2025) suggested that a 30 W panel with a 30 Ah lithium-polymer battery would result in power outages on around 26% of winter days in Central Scotland. Even a more robust 60 W panel reduced this only to 6.8% of days, at significantly higher cost. The lack of low-power or sleep modes in both the sensor and the dongle restricted opportunities to optimise energy use. Moreover, the absence of integrated cellular capability within the PurpleAir meant that connectivity relied on proximity to an existing Wi-Fi network or the use of a MiFi device, further increasing the system’s continuous power draw and narrowing the range of viable deployment locations.

These constraints reflect a broader tension in sensor system design between energy efficiency, autonomy and reliable data transmission, particularly where solar irradiance is more limited. Recent developments in low-power wide-area networks (LPWANs) such as LoRaWAN or NB-IoT offer promising alternatives, however the continual bridging of this gap requires greater collaboration between sensor manufacturers, network providers and the research community to ensure off-grid systems remain both energy-efficient and data-reliable (Clements et al., 2017).

Beyond technical feasibility, the deployment of solar-powered air quality sensors encountered institutional and infrastructural barriers, particularly in relation to the governance of public space. Although the off-grid nature of solar-powered sensors theoretically supports flexible and decentralised deployment, the additional equipment, including solar panels and battery housing, raises practical concerns around safety and visibility. In this pilot, permission to mount sensors on lighting columns required extensive negotiation, including structural assessments in some cases, and was refused outright in others due to concerns about wind loading on ageing infrastructure. Similar constraints on where sensors can be safely and permissibly installed have been noted in urban sensor network research, where placement decisions are shaped by contested governance arrangements and infrastructural limitations rather than technical feasibility alone (Robinson et al., 2022). These experiences highlight a key tension between the decentralised potential of solar-powered sensors and centralised governance of infrastructure/land. This tension can constrain the ability of lower-cost, solar-powered monitoring systems to enhance spatial coverage and support wider public engagement (e.g., McCarron et al. in review). Overcoming this barrier will require not only technical adaptation (e.g., lighter, more compact solar components), but also greater institutional willingness (at both national and local levels) to support innovative monitoring approaches. Without more enabling governance arrangements, the potential of solar-powered, lower-cost sensor systems to fill critical gaps in monitoring coverage, particularly in hyperlocal urban or underserved setting, may remain unrealised.

Drawing on a real-world deployment, this paper highlights how technical design choices, environmental conditions, and institutional constraints collectively shape the feasibility, resilience, and scalability of solar-powered, off-grid air quality monitoring systems. These interdependencies are rarely considered together in existing work yet are central to the practical deployment of off-grid air quality monitoring systems.

Looking forward, improving the feasibility and scalability of solar-powered air quality sensor deployments will require attention not only to technical advancements (e.g., battery chemistry, panel efficiency) but also to the institutional and infrastructural arrangements that enable long-term sustainability. In urban contexts, particularly in areas where hyperlocal air quality concerns intersect with gaps in monitoring infrastructure, or in less-developed regions where air quality monitoring infrastructure is scarcer, solar power offers a practical solution for autonomous sensing at the street or neighbourhood scale.

While this pilot focused on a temperate, high-latitude environment which offers its own challenges, the insights gained are applicable to a wider range of settings and have broader relevance for infrastructurally constrained areas. The transferability of solar-powered air quality monitoring systems is shaped not just by hardware, but by the presence of local capacity to install, maintain and interpret data from these systems. As hyperlocal monitoring gains prominence as a tool for identifying and addressing hyperlocal air quality issues, there is a need for governance models and funding structures that support the deployment of autonomous, context-responsive sensing technologies at scale. Hyperlocal sensors powered by renewable energy (e.g., wind) could support baseline exposure assessments and enable more targeted air quality interventions, especially in rapidly urbanising or industrialising areas where pollution sources are poorly mapped.