The Exposure To Particulate Matter (PM) And Human Health
Prolonged exposure to particulate matter (PM) is associated with adverse impacts on human health leading to pulmonary and cardiovascular diseases. Rapid economic growth accompanied with a spur in industrialization, urbanization and energy consumption has led to increased emissions of PM which has put the health of citizens at stake. In 2012 alone, 0.6 million pre-mature deaths and loss of 25 million disability-adjusted life years could be attributed to ambient air pollution in India.
Traditionally, ambient PM monitoring is carried out at scarcely located research facilities or government environmental monitoring agencies. For instance, in India, under the purview of National Air Quality Monitoring Program (NAMP), the Central Pollution Control Board (CPCB) monitors the levels of PM10 and PM2.5 at 683 stations8 twice a week (8 hourly sampling per day) resulting in mere 104 annual observations per station. Only 76 government air quality monitoring stations in India broadcast real-time PM measurements which are accessible over the internet9. This is clearly too inadequate to locate pollution point sources, gauge spatio-temporal variations in PM, accurately estimate exposure for a population of 1.25 billion, and devise efficient strategies to combat this menace.
High investment costs incurred during installation and maintenance of PM analyzers have hindered extensive coverage and wide spread availability of measurements. Recently, due to frequent media attention and growing public awareness, there is a surge in the demand for real-time air quality data by concerned people who wish to monitor and regulate their exposure to ambient pollutants. In the last few years immense progress has been made in the development of portable low-cost sensors by small- and medium-sized enterprises for providing real-time information on PM levels.10, 11 Most of these aforementioned sensors detect particles via a light scattering method.12 These sensors have garnered widespread attention because of their affordability and their ability to characterize PM concentrations at a high spatial and temporal resolution. The data from such sensors is readily available to the user. Without a doubt, low-cost PM sensors have many promising applications. However, before large volume of unverified data is widely put forth in public domain, the instruments must be properly validated against certified methods and the results should be made aware to the consumer of the data.
Several studies in the last two years have evaluated the performance of few commercially available particle sensors in laboratory. Wang, et al. 13 assessed the performance of three low-cost PM sensors, Shinyei PPD42NS, Samyoung DSM501A and Sharp against US EPA certified methods under laboratory conditions and reported high dependence of the performance on particle composition, particle size and relative humidity (RH). Manikonda, et al. 14also evaluated the performance of four low-cost PM sensors (Speck, Dylos, TSI AirAssure and UB AirSense) using cigarette smoke and Arizona test dust under standard RH and temperature conditions and found adequate precision for monitoring PM exposure in indoor environments. Austin, et al. 15 evaluated the performance of Shinyei PPD42NS under laboratory conditions using monodisperse polystyrene spheres and found the sensor appropriate for low to medium concentrations of respirable particles (< 100 µg m-3).
Several studies have also evaluated the performance of few lost-cost PM sensors under ambient conditions. Mukherjee, et al. 16 compared the performance of low-cost AlphaSense Optical Particle Counter (OPC) with two reference analyzers namely GRIMM 11-R OPC and a β-Attenuation Monitor (BAM-1020, Met One Instruments) over a 12-week period at a site affected by wind-blown dust in California. Although the sensors demonstrated good correlation (r2 = 0.6 to 0.76, hourly average PM10 between 20 to 700 µg m-3) they only reported a small fraction (~20%) of reference (BAM-1020) measured PM10.
Holstius, et al. 17evaluated the performance of a custom-built platform that used a Shinyei PPD42NS using BAM-1020 as a reference at a regulatory monitoring site in California with low ambient PM2.5 mass concentration between 2 to 21 µg m-3. They were able to explain 72% of the variance observed in 24 hour PM2.5 data based on linear corrections. Jiao and co-workers12 tested five different types of low-cost PM sensors using BAM-1020 as a reference, at a site in south-eastern US with low ambient PM2.5 levels of ~10 µg m-3 and ordinary least squares (OLS) regression between the data sets revealed that only three sensors namely Dylos, Shinyei PPD60PV and Shinyei PPDD42NS had an r (Pearson correlation coefficient) value more than 0.5.
Nakayama, et al. 18 developed and tested the efficacy of Panasonic PM2.5 optical sensors by comparing year-round observations at four urban and suburban sites in Japan with federal equivalent methods (FEM) deployed at observatories ~1.7 to 4 km away and found good correlation with slopes of 0.97 to 1.23 and an r value of 0.89-0.95, when the daily averaged PM2.5 concentration varied between 5 to 55 µg m-3. They also reported that the low-cost sensors had a tendency to overestimate PM2.5 at RH > 70% when compared to the reference probably due to hygroscopic growth of particles. Crilley, et al. 19 also demonstrated significant positive artefact in PM2.5 mass concentrations measured by low-cost AlphaSense OPC PM sensor when compared with the reference (GRIMM) at RH > 85%.
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