Dataset Information

A Low-Cost Optoacoustic Sensor for Environmental Monitoring.

ABSTRACT: Attention to Black Carbon (BC) has been rising due to its effects on human health as well its contribution to climate change. Measurements of BC are challenging, as currently used devices are either expensive or impractical for continuous monitoring. Here, we propose an optoacoustic sensor to address this problem. The sensor utilizes a novel ellipsoidal design for refocusing the optoacoustic signal with minimal acoustic energy losses. To reduce the cost of the system, without sacrificing accuracy, an overdriven laser diode and a Quartz Tuning Fork are used as the light source and the sound detector, respectively. The prototype was able to detect BC particles and to accurately monitor changes in concentration in real time and with very good agreement with a reference instrument. The response of the sensor was linearly dependent on the BC particles concentration with a normalized noise equivalent absorption coefficient (NNEA) for soot equal to 7.39 × 10^-9 W cm^-1 Hz^-1/2. Finally, the prototype was able to perform NO₂ measurements, demonstrating its ability to accurately monitor both particulate and gaseous pollutants. The proposed sensor has the potential to offer a significant economic impact for BC environmental measurements and source appointment technologies.

SUBMITTER: Stylogiannis A

PROVIDER: S-EPMC7920291 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Low-Cost Optoacoustic Sensor for Environmental Monitoring.

Stylogiannis Antonios A Kousias Nikolaos N Kontses Anastasios A Ntziachristos Leonidas L Ntziachristos Vasilis V

Sensors (Basel, Switzerland) 20210216 4

Attention to Black Carbon (BC) has been rising due to its effects on human health as well its contribution to climate change. Measurements of BC are challenging, as currently used devices are either expensive or impractical for continuous monitoring. Here, we propose an optoacoustic sensor to address this problem. The sensor utilizes a novel ellipsoidal design for refocusing the optoacoustic signal with minimal acoustic energy losses. To reduce the cost of the system, without sacrificing accurac ...[more]

PMID: 33669390

Similar Datasets

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.

Project description:Environmental DNA (eDNA) metabarcoding is a relatively new monitoring tool featuring in an increasing number of applications such as the facilitation of the accurate and cost effective detection of species in environmental samples. eDNA monitoring is likely to have a major impact on the ability of salmonid aquaculture industry producers and their regulators to detect the presence and abundance of pathogens and other biological threats in the surrounding environment. However, for eDNA metabarcoding to develop into a useful bio-monitoring tool it is necessary to (a) validate that sequence datasets derived from amplification of metabarcoding markers reflect the true species' identity, (b) test the sensitivity under different abundance levels and environmental noise and (c) establish a low-cost sequencing method to enable the bulk processing of field samples. In this study, we employed an elaborate experimental design whereby different combinations of five biological agents were crossed at three abundance levels and exposed to sterile pre-filtered and unfiltered seawater, prior to coarse filtering and then eDNA ultrafiltration of the resultant material. We then benchmarked the low-cost, scalable, Ion Torrent sequencing method against the current gold-standard Illumina platform for eDNA surveys in aquaculture. Based on amplicon-seq of the 18S SSU rDNA v9 region, we were able to identify two parasites (Lepeophtheirus salmonis and Paramoeba perurans) to species level, whereas the microalgae species Prymnesium parvum, Pseudo-nitzschia seriata, and P. delicatissima could be assigned correctly only to the genus level. Illumina and Ion Torrent provided near identical results in terms of community composition in our samples, whereas Ion Torrent was more sensitive in detecting species richness when the medium was unfiltered seawater. Both methods were able to reflect the difference in relative abundance between treatments in 4 out of 5 species when samples were exposed to the unfiltered seawater, despite the significant amount of background noise from both bacteria and eukaryotes. Our findings indicate that eDNA metabarcoding offers significant potential in the monitoring of species harmful to aquaculture and for this purpose, the low-cost Ion Torrent sequencing is as accurate as Illumina in determining differences in their relative abundance between samples.

Project description:Analyses of the relationships between climate, air substances and health usually concentrate on urban environments because of increased urban temperatures, high levels of air pollution and the exposure of a large number of people compared to rural environments. Ongoing urbanization, demographic ageing and climate change lead to an increased vulnerability with respect to climate-related extremes and air pollution. However, systematic analyses of the specific local-scale characteristics of health-relevant atmospheric conditions and compositions in urban environments are still scarce because of the lack of high-resolution monitoring networks. In recent years, low-cost sensors (LCS) became available, which potentially provide the opportunity to monitor atmospheric conditions with a high spatial resolution and which allow monitoring directly at vulnerable people. In this study, we present the atmospheric exposure low-cost monitoring (AELCM) system for several air substances like ozone, nitrogen dioxide, carbon monoxide and particulate matter, as well as meteorological variables developed by our research group. The measurement equipment is calibrated using multiple linear regression and extensively tested based on a field evaluation approach at an urban background site using the high-quality measurement unit, the atmospheric exposure monitoring station (AEMS) for meteorology and air substances, of our research group. The field evaluation took place over a time span of 4 to 8 months. The electrochemical ozone sensors (SPEC DGS-O3: R2: 0.71-0.95, RMSE: 3.31-7.79 ppb) and particulate matter sensors (SPS30 PM1/PM2.5: R2: 0.96-0.97/0.90-0.94, RMSE: 0.77-1.07 µg/m3/1.27-1.96 µg/m3) showed the best performances at the urban background site, while the other sensors underperformed tremendously (SPEC DGS-NO2, SPEC DGS-CO, MQ131, MiCS-2714 and MiCS-4514). The results of our study show that meaningful local-scale measurements are possible with the former sensors deployed in an AELCM unit.

Dataset Information

A Low-Cost Optoacoustic Sensor for Environmental Monitoring.

Publications

A Low-Cost Optoacoustic Sensor for Environmental Monitoring.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets