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      Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring

      1 , 2 , 3 , 3
      Journal of Sensors
      Hindawi Limited

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          Abstract

          Low-cost sensors are an opportunity to improve the spatial and temporal resolution of particulate matter data. However, such sensors should be calibrated under conditions close to the final ones before any monitoring actions. The paper presents the results of a collocated comparison of four models of low-cost optical sensors with a TEOM 1400a analyser. SDS011 (Nova Fitness), ZH03A (Winsen), PMS7003 (Plantower), and OPC-N2 (Alphasense) sensors were used in this research. Three copies of each sensor model were placed in a common box to compare the sensor performance under the same measurement conditions. Monitoring of the PM 2.5 fraction was conducted for almost half a year from 21 August 2017 to 19 February 2018 in Wrocław (Poland). Reproducibility between sensor units was assessed on the basis of coefficient of variation (CV). CV values were lower than 7% in the case of SDS011 and PMS7003 sensors and equal to 20% for OPC-N2 units. CV was higher than 50% for ZH03A, mainly due to malfunctions. During the measurements, the trends of outputs from sensors were generally similar to TEOM data, but significant overestimation of PM 2.5 concentrations was observed for the sensor raw data. A high linear relationship between TEOM and sensors was noticed for 1 min, 15 min, and 1-hour averaged data for PMS7003 sensors ( R 2 0.83 –0.89), for SDS011 units ( R 2 0.79 –0.86), and for one unit of ZH03A ( R 2 0.74 –0.81). R 2 values for daily averages were at the level 0.91–0.93 for PMS7003, 0.87–0.90 for SDS011, and 0.89 for ZH03A. OPC-N2 had only a moderate linear relationship with TEOM ( R 2 0.53 –0.69 for daily data and 0.43–0.61 for shorter time averages). Quite large dispersion of data and high relative errors of PM 2.5 estimation were observed for concentration ranges below 20–30 μg/m 3. The impact of high relative humidity level was observed for SDS011 and OPC-N2 devices—clear overestimation of outputs was observed above 80% RH.

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          Most cited references23

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          Clearing the air: a review of the effects of particulate matter air pollution on human health.

          The World Health Organization estimates that particulate matter (PM) air pollution contributes to approximately 800,000 premature deaths each year, ranking it the 13th leading cause of mortality worldwide. However, many studies show that the relationship is deeper and far more complicated than originally thought. PM is a portion of air pollution that is made up of extremely small particles and liquid droplets containing acids, organic chemicals, metals, and soil or dust particles. PM is categorized by size and continues to be the fraction of air pollution that is most reliably associated with human disease. PM is thought to contribute to cardiovascular and cerebrovascular disease by the mechanisms of systemic inflammation, direct and indirect coagulation activation, and direct translocation into systemic circulation. The data demonstrating PM's effect on the cardiovascular system are strong. Populations subjected to long-term exposure to PM have a significantly higher cardiovascular incident and mortality rate. Short-term acute exposures subtly increase the rate of cardiovascular events within days of a pollution spike. The data are not as strong for PM's effects on cerebrovascular disease, though some data and similar mechanisms suggest a lesser result with smaller amplitude. Respiratory diseases are also exacerbated by exposure to PM. PM causes respiratory morbidity and mortality by creating oxidative stress and inflammation that leads to pulmonary anatomic and physiologic remodeling. The literature shows PM causes worsening respiratory symptoms, more frequent medication use, decreased lung function, recurrent health care utilization, and increased mortality. PM exposure has been shown to have a small but significant adverse effect on cardiovascular, respiratory, and to a lesser extent, cerebrovascular disease. These consistent results are shown by multiple studies with varying populations, protocols, and regions. The data demonstrate a dose-dependent relationship between PM and human disease, and that removal from a PM-rich environment decreases the prevalence of these diseases. While further study is needed to elucidate the effects of composition, chemistry, and the PM effect on susceptible populations, the preponderance of data shows that PM exposure causes a small but significant increase in human morbidity and mortality. Most sources agree on certain "common sense" recommendations, although there are lonely limited data to support them. Indoor PM exposure can be reduced by the usage of air conditioning and particulate filters, decreasing indoor combustion for heating and cooking, and smoking cessation. Susceptible populations, such as the elderly or asthmatics, may benefit from limiting their outdoor activity during peak traffic periods or poor air quality days. These simple changes may benefit individual patients in both short-term symptomatic control and long-term cardiovascular and respiratory complications.
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            Particulate matter beyond mass: recent health evidence on the role of fractions, chemical constituents and sources of emission

            Particulate matter (PM) is regulated in various parts of the world based on specific size cut offs, often expressed as 10 or 2.5 µm mass median aerodynamic diameter. This pollutant is deemed one of the most dangerous to health and moreover, problems persist with high ambient concentrations. Continuing pressure to re-evaluate ambient air quality standards stems from research that not only has identified effects at low levels of PM but which also has revealed that reductions in certain components, sources and size fractions may best protect public health. Considerable amount of published information have emerged from toxicological research in recent years. Accumulating evidence has identified additional air quality metrics (e.g. black carbon, secondary organic and inorganic aerosols) that may be valuable in evaluating the health risks of, for example, primary combustion particles from traffic emissions, which are not fully taken into account with PM2.5 mass. Most of the evidence accumulated so far is for an adverse effect on health of carbonaceous material from traffic. Traffic-generated dust, including road, brake and tire wear, also contribute to the adverse effects on health. Exposure durations from a few minutes up to a year have been linked with adverse effects. The new evidence collected supports the scientific conclusions of the World Health Organization Air Quality Guidelines and also provides scientific arguments for taking decisive actions to improve air quality and reduce the global burden of disease associated with air pollution.
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              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.
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                Author and article information

                Journal
                Journal of Sensors
                Journal of Sensors
                Hindawi Limited
                1687-725X
                1687-7268
                October 31 2018
                October 31 2018
                : 2018
                : 1-16
                Affiliations
                [1 ]Department of Air Conditioning, Heating, Gas Engineering and Air Protection, Faculty of Environmental Engineering, Wrocław University of Science and Technology, 50-373 Wrocław, Poland
                [2 ]INSYSPOM, 54-427 Wrocław, Poland
                [3 ]Department of Climatology and Atmosphere Protection, Institute of Geography and Regional Development, Faculty of Earth Science and Environmental Management, University of Wrocław, 51-621 Wrocław, Poland
                Article
                10.1155/2018/5096540
                e01c44b1-65ec-49c4-933b-288f0e583668
                © 2018

                http://creativecommons.org/licenses/by/4.0/

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