End-user perspective of low-cost sensors for outdoor air pollution monitoring.

Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network.

Real-time sensors for indoor air monitoring and challenges ahead in deploying them to urban buildings.

Household air pollution is ranked the 9(th) largest Global Burden of Disease risk (Forouzanfar et al., The Lancet 2015). People, particularly urban dwellers, typically spend over 90% of their daily time indoors, where levels of air pollution often surpass those of outdoor environments. Indoor air quality (IAQ) standards and approaches for assessment and control of indoor air require measurements of pollutant concentrations and thermal comfort using conventional instruments. However, the outcomes of such measurements are usually averages over long integrated time periods, which become available after the exposure has already occurred. Moreover, conventional monitoring is generally incapable of addressing temporal and spatial heterogeneity of indoor air pollution, or providing information on peak exposures that occur when specific indoor sources are in operation. This article provides a review of new air pollution sensing methods to determine IAQ and discusses how real-time sensing could bring a paradigm shift in controlling the concentration of key air pollutants in billions of urban houses worldwide. We also show that besides the opportunities, challenges still remain in terms of maturing technologies, or data mining and their interpretation. Moreover, we discuss further research and essential development needed to close gaps between what is available today and needed tomorrow. In particular, we demonstrate that awareness of IAQ risks and availability of appropriate regulation are lagging behind the technologies.

Combining environment and health information systems for the assessment of atmospheric pollution on human health.

The use of emerging technologies for environmental monitoring with satellite and in-situ sensors have become essential instruments for assessing the impact of environmental pollution on human health, especially in areas that require high spatial and temporal resolution. This was until recently a rather difficult problem. Regrettably, with classical approaches the spatial resolution is frequently inadequate in reporting environmental causes and health effects in the same time scale. This work examines with new tools different levels of air-quality with sensor monitoring with the aim to associate those with severe health effects. The process established here facilitates the precise representation of human exposure with the population attributed in a fine spatial grid and taking into account environmental stressors of human exposure. These stressors can be monitored with innovative sensor units with a temporal resolution that accurately describes chronic and acute environmental burdens. The current understanding of the situation in densely populated areas can be properly analyzed, before commitments are made for reductions in total emissions as well as for assessing the effects of reduced trans-boundary fluxes. In addition, the data processed here with in-situ sensors can assist in establishing more effective regulatory policies for the protection of vulnerable population groups and the satellite monitoring instruments permit abatement strategies that are close to real-time over large geographical areas.

Rapid tests for diagnosis of leptospirosis: current tools and emerging technologies.

Leptospirosis is an emerging zoonosis with a worldwide distribution but is more commonly found in impoverished populations in developing countries and tropical regions with frequent flooding. The rapid detection of leptospirosis is a critical step to effectively manage the disease and to control outbreaks in both human and animal populations. Therefore, there is a need for accurate and rapid diagnostic tests and appropriate surveillance and alert systems to identify outbreaks. This review describes current in-house methods and commercialized tests for the rapid diagnosis of acute leptospirosis. It focuses on diagnostic tests that can be performed with minimal training and limited equipment in less-developed and newly industrialized countries, particularly in resource-limited settings and with results in minutes to less than 4 hours. We also describe recent technological advances in the field of diagnostic tests that could allow for the development of innovative rapid tests in the near future.