Smartphones are playing an increasing role in the sciences, owing to the ubiquitous proliferation of these devices, their relatively low cost, increasing processing power and their suitability for integrated data acquisition and processing in a ‘lab in a phone’ capacity. There is furthermore the potential to deploy these units as nodes within Internet of Things architectures, enabling massive networked data capture. Hitherto, considerable attention has been focused on imaging applications of these devices. However, within just the last few years, another possibility has emerged: to use smartphones as a means of capturing spectra, mostly by coupling various classes of fore-optics to these units with data capture achieved using the smartphone camera. These highly novel approaches have the potential to become widely adopted across a broad range of scientific e.g., biomedical, chemical and agricultural application areas. In this review, we detail the exciting recent development of smartphone spectrometer hardware, in addition to covering applications to which these units have been deployed, hitherto. The paper also points forward to the potentially highly influential impacts that such units could have on the sciences in the coming decades.

Here, we report, for what we believe to be the first time, on the modification of a low cost sensor, designed for the smartphone camera market, to develop an ultraviolet (UV) camera system. This was achieved via adaptation of Raspberry Pi cameras, which are based on back-illuminated complementary metal-oxide semiconductor (CMOS) sensors, and we demonstrated the utility of these devices for applications at wavelengths as low as 310 nm, by remotely sensing power station smokestack emissions in this spectral region. Given the very low cost of these units, ≈ USD 25, they are suitable for widespread proliferation in a variety of UV imaging applications, e.g., in atmospheric science, volcanology, forensics and surface smoothness measurements.

We report on the development of a low-cost spectrometer, based on off-the-shelf optical components, a 3D printed housing, and a modified Raspberry Pi camera module. With a bandwidth and spectral resolution of $\approx 60\mathrm{nm}$ and 1 nm, respectively, this device was designed for ultraviolet (UV) remote sensing of atmospheric sulphur dioxide (${\mathrm{SO}}_2$), $\approx 310\mathrm{nm}$. To the best of our knowledge, this is the first report of both a UV spectrometer and a nanometer resolution spectrometer based on smartphone sensor technology. The device performance was assessed and validated by measuring column amounts of ${\mathrm{SO}}_2$ within quartz cells with a differential optical absorption spectroscopy processing routine. This system could easily be reconfigured to cover other UV-visible-near-infrared spectral regions, as well as alternate spectral ranges and/or linewidths. Hence, our intention is also to highlight how this framework could be applied to build bespoke, low-cost, spectrometers for a range of scientific applications.

Volcanic gas emissions are intimately linked to the dynamics of magma ascent and outgassing and, on geological time scales, constitute an important source of volatiles to the Earth's atmosphere. Measurements of gas composition and flux are therefore critical to both volcano monitoring and to determining the contribution of volcanoes to global geochemical cycles. However, significant gaps remain in our global inventories of volcanic emissions, (particularly for CO₂, which requires proximal sampling of a concentrated plume) for those volcanoes where the near‐vent region is hazardous or inaccessible. Unmanned Aerial Systems (UAS) provide a robust and effective solution to proximal sampling of dense volcanic plumes in extreme volcanic environments. Here we present gas compositional data acquired using a gas sensor payload aboard a UAS flown at Volcán Villarrica, Chile. We compare UAS‐derived gas time series to simultaneous crater rim multi‐GAS data and UV camera imagery to investigate early plume evolution. SO₂ concentrations measured in the young proximal plume exhibit periodic variations that are well correlated with the concentrations of other species. By combining molar gas ratios (CO₂/SO₂ = 1.48–1.68, H₂O/SO₂ = 67–75, and H₂O/CO₂ = 45–51) with the SO₂ flux (142 ± 17 t/day) from UV camera images, we derive CO₂ and H₂O fluxes of ~150 t/day and ~2,850 t/day, respectively. We observe good agreement between time‐averaged molar gas ratios obtained from simultaneous UAS‐ and ground‐based multi‐GAS acquisitions. However, the UAS measurements made in the young, less diluted plume reveal additional short‐term periodic structure that reflects active degassing through discrete, audible gas exhalations.

Volcanoes represent one of the largest natural sources of metals to the Earth’s surface. Emissions of these metals can have important impacts on the biosphere as pollutants or nutrients. Here we use ground- and drone-based direct measurements to compare the gas and particulate chemistry of the magmatic and lava–seawater interaction (laze) plumes from the 2018 eruption of Kīlauea, Hawai’i. We find that the magmatic plume contains abundant volatile metals and metalloids whereas the laze plume is further enriched in copper and seawater components, like chlorine, with volatile metals also elevated above seawater concentrations. Speciation modelling of magmatic gas mixtures highlights the importance of the S²⁻ ligand in highly volatile metal/metalloid degassing at the magmatic vent. In contrast, volatile metal enrichments in the laze plume can be explained by affinity for chloride complexation during late-stage degassing of distal lavas, which is potentially facilitated by the HCl gas formed as seawater boils.

Recently, we reported on the development of low-cost ultraviolet (UV) cameras, based on the modification of sensors designed for the smartphone market. These units are built around modified Raspberry Pi cameras (PiCams; ≈USD 25), and usable system sensitivity was demonstrated in the UVA and UVB spectral regions, of relevance to a number of application areas. Here, we report on the first deployment of PiCam devices in one such field: UV remote sensing of sulphur dioxide emissions from volcanoes; such data provide important insights into magmatic processes and are applied in hazard assessments. In particular, we report on field trials on Mt. Etna, where the utility of these devices in quantifying volcanic sulphur dioxide (SO₂) emissions was validated. We furthermore performed side-by-side trials of these units against scientific grade cameras, which are currently used in this application, finding that the two systems gave virtually identical flux time series outputs, and that signal-to-noise characteristics of the PiCam units appeared to be more than adequate for volcanological applications. Given the low cost of these sensors, allowing two-filter SO₂ camera systems to be assembled for ≈USD 500, they could be suitable for widespread dissemination in volcanic SO₂ monitoring internationally.