Laboratory Evaluation of Low-Cost Optical Particle Counters for Environmental and Occupational Exposures.
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ABSTRACT:
SUBMITTER: Sousan S
PROVIDER: S-EPMC8233711 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The aerosol scattering coefficient and Ångström exponent (AE) are important parameters in the understanding of aerosol optical properties and aerosol direct effect. These parameters are usually measured by a nephelometer network which is under-represented geographically; however, a rapid growth of air-pollution monitoring, using low-cost particle sensors, may extend observation networks. This paper presents the results of co-located measurements of aerosol optical properties, such as the aerosol scattering coefficient and the scattering AE, using low-cost sensors and using a scientific-grade polar Aurora 4000 nephelometer. A high Pearson correlation coefficient (0.94-0.96) between the low-cost particulate matter (PM) mass concentration and the aerosol scattering coefficient was found. For the PM10 mass concentration, the aerosol scattering coefficient relation is linear for the Dfrobot SEN0177 sensor and non-linear for the Alphasense OPC-N2 device. After regression analyses, both low-cost instruments provided the aerosol scattering coefficient with a similar mean square error difference (RMSE) of about 20 Mm-1, which corresponds to about 27% of the mean aerosol scattering coefficient. The relative uncertainty is independent of the pollution level. In addition, the ratio of aerosol number concentration between different bins showed a significant statistical (95% of confidence level) correlation with the scattering AE. For the SEN0177, the ratio of the particle number in bin 1 (radius of 0.15-0.25 µm) to bin 4 (radius of 1.25-2.5 µm) was a linear function of the scattering AE, with a Pearson correlation coefficient of 0.74. In the case of OPC-N2, the best correlation (r = 0.66) was found for the ratio between bin 1 (radius of 0.19-0.27 µm) and bin 2 (radius of 0.27-0.39 µm). Comparisons of an estimated scattering AE from a low-cost sensor with Aurora 4000 are given with the RMSE of 0.23-0.24, which corresponds to 16-19%. In addition, a three-year (2016-2019) observation by SEN0177 indicates that this sensor can be used to determine an annual cycle as well as a short-term variability.
| S-EPMC7249179 | biostudies-literature
Project description:In the last decade, more than half of U.S. children were born to working mothers and 65% of working men and women were of reproductive age. In 2004 more than 28 million women age 18-44 were employed full time. This implies the need for clinicians to possess an awareness about the impact of work on the health of their patients and their future offspring. Most chemicals in the workplace have not been evaluated for reproductive toxicity, and where exposure limits do exist, they were generally not designed to mitigate reproductive risk. Therefore, many toxicants with unambiguous reproductive and developmental effects are still in regular commercial or therapeutic use and thus present exposure potential to workers. Examples of these include heavy metals, (lead, cadmium), organic solvents (glycol ethers, percholoroethylene), pesticides and herbicides (ethylene dibromide) and sterilants, anesthetic gases and anti-cancer drugs used in healthcare. Surprisingly, many of these reproductive toxicants are well represented in traditional employment sectors of women, such as healthcare and cosmetology. Environmental exposures also figure prominently in evaluating a woman's health risk and that to a pregnancy. Food and water quality and pesticide and solvent usage are increasingly topics raised by women and men contemplating pregnancy. The microenvironment of a woman, such as her choices of hobbies and leisure time activities also come into play. Caregivers must be aware of their patients' potential environmental and workplace exposures and weigh any risk of exposure in the context of the time-dependent window of reproductive susceptibility. This will allow informed decision-making about the need for changes in behavior, diet, hobbies or the need for added protections on the job or alternative duty assignment. Examples of such environmental and occupational history elements will be presented together with counseling strategies for the clinician.
| S-EPMC2335294 | biostudies-other
Project description:ObjectiveThere is a lack of consensus on methods for cotton dust measurement in the textile industry, and techniques vary between countries-relying mostly on cumbersome, traditional approaches. We undertook comparisons of standard, gravimetric methods with low-cost optical particle counters for personal and area dust measurements in textile mills in Pakistan.MethodsWe included male textile workers from the weaving sections of seven cotton mills in Karachi. We used the Institute of Occupational Medicine (IOM) sampler with a Casella Apex 2 standard pump and the Purple Air (PA-II-SD) for measuring personal exposures to inhalable airborne particles (n = 31). We used the Dylos DC1700 particle counter, in addition to the two above, for area-level measurements (n = 29).ResultsThere were no significant correlations between the IOM and PA for personal dust measurements using the original (r = -0.15, P = 0.4) or log-transformed data (r = -0.32, P = 0.07). Similarly, there were no significant correlations when comparing the IOM with either of the particle counters (PA and Dylos) for area dust measurements, using the original (r = -0.07, P = 0.7; r = 0.10, P = 0.6) or log-transformed data (r = -0.09, P = 0.6; r = 0.07, P = 0.7).ConclusionOur findings show a lack of correlation between the gravimetric method and the use of particle counters in both personal and area measurements of cotton dust, precluding their use for measuring occupational exposures to airborne dust in textile mills. There continues to be a need to develop low-cost instruments to help textile industries in low- and middle-income countries to perform cotton dust exposure assessment.
| S-EPMC9030129 | biostudies-literature
Project description:Direct measurements of time- and size-resolved particulate matter (PM) concentrations are of major importance in air quality studies and pollution monitoring. Low-cost, compact optical particle counters (OPCs), which provide accurate PM measurements independent of the particle complex index of refraction (CRI), can be useful in personal exposure monitoring and distributed sensor network studies applications. A methodology is presented for the optimization of the sensor design and operation parameter space aimed at reducing the effect of the CRI on particle sizing errors. The Monte Carlo numerical simulation, which utilizes Mie scattering calculations, is used to determine the optimal detector angle for the specific set of constraints described by the weighting coefficients. The optimized detector position (θ = 48°) has the lowest dependency on CRI over the entire particle size range of 0.5-10 microns. The near-forward, optimized, and perpendicular detector angles are compared experimentally using monodisperse 2 μm and 4 μm particles of silica, PSL, and alumina; the light collection cone angle is set at α = 20° in all experiments. The data agree well with the numerical results for all tested scenarios. Overall, the perpendicular detector location has the best precision and worst accuracy related to the CRI variations. The optimized detector position has the best accuracy for both silica and alumina particles. The use of low-cost components, such as laser diodes, photodiodes, miniaturized integrated electronics, and simple component layouts allows for the development of compact OPCs capable of accurately sizing PM. The number of sizing bins, sizing accuracy and precision, and other parameters of interest can be used as an input to an optimization algorithm.
| S-EPMC6159267 | biostudies-literature
Project description:Low-cost sensors enable finer-scale spatiotemporal measurements within the existing methane (CH4) monitoring infrastructure and could help cities mitigate CH4 emissions to meet their climate goals. While initial studies of low-cost CH4 sensors have shown potential for effective CH4 measurement at ambient concentrations, sensor deployment remains limited due to questions about interferences and calibration across environments and seasons. This study evaluates sensor performance across seasons with specific attention paid to the sensor's understudied carbon monoxide (CO) interferences and environmental dependencies through long-term ambient co-location in an urban environment. The sensor was first evaluated in a laboratory using chamber calibration and co-location experiments, and then in the field through two 8 week co-locations with a reference CH4 instrument. In the laboratory, the sensor was sensitive to CH4 concentrations below ambient background concentrations. Different sensor units responded similarly to changing CH4, CO, temperature, and humidity conditions but required individual calibrations to account for differences in sensor response factors. When deployed in-field, co-located with a reference instrument near Baltimore, MD, the sensor captured diurnal trends in hourly CH4 concentration after corrections for temperature, absolute humidity, CO concentration, and hour of day. Variable performance was observed across seasons with the sensor performing well (R 2 = 0.65; percent bias 3.12%; RMSE 0.10 ppm) in the winter validation period and less accurately (R 2 = 0.12; percent bias 3.01%; RMSE 0.08 ppm) in the summer validation period where there was less dynamic range in CH4 concentrations. The results highlight the utility of sensor deployment in more variable ambient CH4 conditions and demonstrate the importance of accounting for temperature and humidity dependencies as well as co-located CO concentrations with low-cost CH4 measurements. We show this can be addressed via Multiple Linear Regression (MLR) models accounting for key covariates to enable urban measurements in areas with CH4 enhancement. Together with individualized calibration prior to deployment, the sensor shows promise for use in low-cost sensor networks and represents a valuable supplement to existing monitoring strategies to identify CH4 hotspots.
| S-EPMC10100561 | biostudies-literature
Project description:Soil volumetric water content ( V W C ) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available V W C sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors-SMEC300 and SM100-manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors-the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru-were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate ( M A E , R M S E , and R A E of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy ( M A E , R M S E , and R A E of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate ( M A E , R M S E , and R A E of 3.51%, 5.21% and 0.37 respectively) than YL69 ( M A E , R M S E , and R A E of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.
| S-EPMC7014303 | biostudies-literature
Project description: Not available
| S-EPMC7301737 | biostudies-literature
Project description:Exposure to occupational aerosols are a known hazard in many industry sectors and can be a risk factor for several respiratory diseases. In this study, a laboratory evaluation of low-cost aerosol sensors, the Dylos DC1700 and a modified Dylos known as the Utah Modified Dylos Sensor (UMDS), was performed to assess the sensors' efficiency in sampling respirable and inhalable dust at high concentrations, which are most common in occupational settings. Dust concentrations were measured in a low-speed wind tunnel with 3 UMDSs, collocated with an aerosol spectrometer (Grimm 1.109) and gravimetric respirable and inhalable samplers. A total of 10 tests consisting of 5 different concentrations and 2 test aerosols, Arizona road dust and aluminum oxide, were conducted. For the Arizona road dust, total particle count was strongly related between the spectrometer and the UMDS with a coefficient of determination (R2) between 0.86-0.92. Particle count concentrations measured with the UMDS were converted to mass and also were related with gravimetrically collected inhalable and respirable dust. The UMDS small bin (i.e., all particles) compared to the inhalable sampler yielded an R2 of 0.86-0.92, and the large bin subtracted from the small bin (i.e., only the smallest particles) compared to the respirable sampler yielded an R2 of 0.93-0.997. Tests with the aluminum oxide demonstrated a substantially lower relationship across all comparisons. Furthermore, assessment of intra-instrument variability was consistent for all instruments, but inter-instrument variability indicated that each instrument requires its own calibration equation to yield accurate exposure estimates. Overall, it appears that the UMDS can be used as a low-cost tool to estimate respirable and inhalable concentrations found in many workplaces. Future studies will focus on deployment of a UMDS network in an occupational setting.
| S-EPMC6309410 | biostudies-literature
Project description:ObjectiveFinely resolved PM2.5 exposure measurements at the level of individual participants or over a targeted geographic area can be challenging due to the cost, size and weight of the monitoring equipment. We propose re-purposing the low-cost, portable and lightweight Shinyei PPD42NS particle counter as a particle counting device. Previous field deployment of this sensor suggests that it captures trends in ambient PM2.5 concentrations, but important characteristics of the sensor response have yet to be determined. Laboratory testing was undertaken in order to characterize performance.MethodsThe Shinyei sensors, in-line with a TSI Aerosol Particle Sizer (APS) model 3321, tracked particle decay within an aerosol exposure chamber. Test atmospheres were composed of monodisperse polystyrene spheres with diameters of 0.75, 1, 2 3 and 6 um as well as a polydisperse atmosphere of ASHRAE test dust #1.ResultsTwo-minute block averages of the sensor response provide a measurement with low random error, within sensor, for particles in the 0.75-6μm range with a limit of detection of 1 μg/m3. The response slope of the sensors is idiomatic, and each sensor requires a unique response curve. A linear model captures the sensor response for concentrations below 50 μg/m3 and for concentrations above 50 μg/m3 a non-linear function captures the response and saturates at 800 μg/m3. The Limit of Detection (LOD) is 1 μg/m3. The response time is on the order of minutes, making it appropriate for tracking short-term changes in concentration.ConclusionsWhen paired with prior evaluation, these sensors are appropriate for use as ambient particle counters for low and medium concentrations of respirable particles (< 100 ug/m3). Multiple sensors deployed over a spatial grid would provide valuable spatio-temporal variability in PM2.5 and could be used to validate exposure models. When paired with GPS tracking, these devices have the potential to provide time and space resolved exposure measurements for a large number of participants, thus increasing the power of a study.
| S-EPMC4569398 | biostudies-literature
Project description:Low-cost sensors for measuring particulate matter (PM) offer the ability to understand human exposure to air pollution at spatiotemporal scales that have previously been impractical. However, such low-cost PM sensors tend to be poorly characterized, and their measurements of mass concentration can be subject to considerable error. Recent studies have investigated how individual factors can contribute to this error, but these studies are largely based on empirical comparisons and generally do not examine the role of multiple factors simultaneously. Here, we present a new physics-based framework and open-source software package (opcsim) for evaluating the ability of low-cost optical particle sensors (optical particle counters and nephelometers) to accurately characterize the size distribution and/or mass loading of aerosol particles. This framework, which uses Mie theory to calculate the response of a given sensor to a given particle population, is used to estimate the fractional error in mass loading for different sensor types given variations in relative humidity, aerosol optical properties, and the underlying particle size distribution. Results indicate that such error, which can be substantial, is dependent on the sensor technology (nephelometer vs. optical particle counter), the specific parameters of the individual sensor, and differences between the aerosol used to calibrate the sensor and the aerosol being measured. We conclude with a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer general recommendations for the choice of calibrant under different measurement scenarios.
| S-EPMC7995643 | biostudies-literature