Remote sensing of atmospheric optical depth using a smartphone sun photometer

Rapid and Online Microvolume Flow-Through Dialysis Probe for Sample Preparation in Veterinary Drug Residue Analysis

A rapid and online microvolume flow-through dialysis probe designed for sample preparation in the analysis of veterinary drug residues is introduced. This study addresses the need for efficient and green sample preparation methods that reduce chemical waste and reagent use. The dialysis probe integrates with liquid chromatography and mass spectrometry (LC-MS) systems, facilitating automated, high-throughput analysis. The dialysis method utilizes minimal reagent volumes per sample, significantly reducing the generation of solvent waste compared to traditional sample preparation techniques. Several veterinary drugs were spiked into tissue homogenates and analyzed to validate the probe's efficacy. A diagnostic sensitivity of >97% and specificity of >95% were obtained for this performance evaluation. The results demonstrated the effective removal of cellular debris and particulates, ensuring sample integrity and preventing instrument clogging. The automated dialysis probe yielded recovery rates between 27 and 77% for multiple analytes, confirming its potential to streamline veterinary drug residue analysis, while adhering to green chemistry principles. The approach highlights substantial improvements in both environmental impact and operational efficiency, presenting a viable alternative to conventional sample preparation methods in regulatory and research applications.

Low-Cost Microplate Reader with 3D Printed Parts for under 500 USD

A 96-well microplate reader for absorption spectroscopy was designed, constructed, and tested at a total cost of ca. 500 USD. The reduced cost of the device represents the major technical contribution of this manuscript, as costs were reduced 7 fold from previous reports. The device was able to achieve 3σ limits of detection of ca. 0.01 absorbance units (AU) over a 60 second measurement for the mid-visible wavelength range. Component parts are either commercially available, or 3D printed from plans. Analysis wavelength can be altered throughout the visible region through use of various photographic or theatrical filters. This feature allows the well plate reader to be used for typical laboratory assays such as cell population estimation by optical density (OD) at 600 nm, or enzyme-linked immunosorbent assays (ELISA) at 450 nm. This manuscript reports on the motivation and process of constructing the device, lists required parts, presents data demonstrating device function, and provides the community of scholars with plans to reproduce the work. The device can be reproduced in laboratories lacking sufficient resources to purchase commercially available options and this outcome contributes towards empowerment of individuals and equity of scientific enquiry.

The future of Earth system prediction: Advances in model-data fusion

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

A review on the ability of smartphones to detect ultraviolet (UV) radiation and their potential to be used in UV research and for public education purposes

The effects of ultraviolet (UV) radiation on life on Earth have continuously been the subject of research. Over-exposure to UV radiation is harmful, but small amounts of exposure are required for good health. It is, therefore, crucial for humans to optimise their own UV exposure and not exceed UV levels that are sufficient for essential biological functions. Exceeding those levels may increase risk of developing health problems including skin cancer and cataracts. Smartphones have been previously investigated for their ability to detect UV radiation with or without additional devices that monitor personal UV exposure, in order to maintain safe exposure times by individuals. This review presents a comprehensive overview of the current state of smartphones' use in UV radiation monitoring and prediction. There are four main methods for UV radiation detection or prediction involving the use smartphones, depending on the requirements of the user: devoted software applications developed for smartphones to predict UV Index (UVI), wearable and non-wearable devices that can be used with smartphones to provide real-time UVI, and the use of smartphone image sensors to detect UV radiation. The latter method has been a growing area of research over the last decade. Built-in smartphone image sensors have been investigated for UV radiation detection and the quantification of related atmospheric factors (including aerosols, ozone, clouds and volcanic plumes). The overall practicalities, limitations and challenges are reviewed, specifically in regard to public education. The ubiquitous nature of smartphones can provide an interactive tool when considering public education on the effects and individual monitoring of UV radiation exposure, although social and geographic areas with low socio-economic factors could challenge the usefulness of smartphones. Overall, the review shows that smartphones provide multiple opportunities in different forms to educate users on personal health with respect to UV radiation.

Airborne Particulate Matter: Human Exposure and Health Effects

OBJECTIVE

Exposure to airborne particulate matter (PM) is estimated to cause millions of premature deaths annually. This work conveys known routes of exposure to PM and resultant health effects.

METHODS

A review of available literature.

RESULTS

Estimates for daily PM exposure are provided. Known mechanisms by which insoluble particles are transported and removed from the body are discussed. Biological effects of PM, including immune response, cytotoxicity, and mutagenicity, are reported. Epidemiological studies that outline the systemic health effects of PM are presented.

CONCLUSION

While the integrated, per capita, exposure of PM for a large fraction of the first-world may be less than 1 mg per day, links between several syndromes, including attention deficit hyperactivity disorder (ADHD), autism, loss of cognitive function, anxiety, asthma, chronic obstructive pulmonary disease (COPD), hypertension, stroke, and PM exposure have been suggested. This article reviews and summarizes such links reported in the literature.

Miniature Spatial Heterodyne Raman Spectrometer with a Cell Phone Camera Detector

A spatial heterodyne Raman spectrometer (SHRS) with millimeter-sized optics has been coupled with a standard cell phone camera as a detector for Raman measurements. The SHRS is a dispersive-based interferometer with no moving parts and the design is amenable to miniaturization while maintaining high resolution and large spectral range. In this paper, a SHRS with 2.5 mm diffraction gratings has been developed with 17.5 cm^-1 theoretical spectral resolution. The footprint of the SHRS is orders of magnitude smaller than the footprint of charge-coupled device (CCD) detectors typically employed in Raman spectrometers, thus smaller detectors are being explored to shrink the entire spectrometer package. This paper describes the performance of a SHRS with 2.5 mm wide diffraction gratings and a cell phone camera detector, using only the cell phone's built-in optics to couple the output of the SHRS to the sensor. Raman spectra of a variety of samples measured with the cell phone are compared to measurements made using the same miniature SHRS with high-quality imaging optics and a high-quality, scientific-grade, thermoelectrically cooled CCD.

A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones

This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding ‘scheme blocks’ framework was used to build the application (‘app’), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing–a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for ‘UAV toolkit’ (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping).