Performance evaluation of ozone and particulate matter sensors

As public awareness and concern about air quality grows, companies and researchers have begun to develop small, low-cost sensors to measure local air quality. These sensors have been used in citizen science projects, in distributed networks within cities, and in combination with public health studies on asthma and other air-quality-associated diseases. However, sensor long-term performance under different environmental conditions and pollutant levels is not fully understood. In addition, further evaluation is needed for other long-term performance trends such as performance among sensors of the same model, comparison between sensors from different companies and comparison of sensor data to federal equivalence or reference method (FEM/FRM) measurements. A 10-month evaluation of two popular particulate matter (PM) sensors, Dylos DC1100 and AirBeam, and a popular ozone (O₃) sensor, Aeroqual 500, was performed as part of this study. Data from these sensors were compared to each other and to FEM/FRM data and local meteorology. The study took place at the Houston Regional Monitoring (HRM) site 3, located between the Houston Ship Channel and Houston's urban center. PM sensor performance was found to vary in time, with multivariate analysis, binning of data by meteorological parameter, and machine learning techniques able to account for some but not all performance variations. PM type (i.e., size distribution, fiber-flake-spheroid shape and black-brown-white color) likely played a role in the changing sensor performance. Triplicate individual Aeroqual O₃ sensors tracked reasonably well with the FEM data for most of the measurement period but had irregular periods of O₃ measurement offset. While the FEM data indicated 4 days where ozone levels were above the NAAQS, the Aeroqual ozone sensors indicated a substantially higher number of days, ranging from 9 to 16 for the three sensors.Implications: This paper evaluated the long-term performance of several commercial low-cost sensors (PM_2.5 and ozone) as compared to federal equivalence method (FEM) monitors under a range of meteorological and air quality conditions. PM_2.5 sensors performed well on low humidity days with winds indicative of sea salt or dust PM sources but had poor correlation with FEM data under other conditions. Two types of PM sensors were studied (Dylos 1100 and AirBeam) and data only correlated well between sensors of the same type. Sensor networks with multiple PM sensor types would not be as useful for comparative purposes as sensor networks of the same type. Relative humidity corrections alone did not increase sensor agreement with FEM to acceptable levels, specific information about PM sources and sensor response in the area measured is needed. Low-cost ozone sensors tested (Aeroqual) performed well but were biased high and overestimated days above ozone NAAQS.

Examining the functional range of commercially available low-cost airborne particle sensors and consequences for monitoring of indoor air quality in residences

Low-cost airborne particle sensors are gaining attention for monitoring human exposure to indoor particulate matter. This study aimed to establish the concentrations at which these commercially available sensors can be expected to report accurate concentrations. We exposed five types of commercial integrated devices and three types of "bare" low-cost particle sensors to a range of concentrations generated by three different sources. We propose definitions of upper and lower bounds of functional range based on the relationship between a given sensor's output and that of a reference instrument during a laboratory experiment. Experiments show that the lower bound can range from approximately 3 to 15 μg/m³ . At greater concentrations, sensor output deviates from linearity at approximately 300-3000 μg/m³ . We also conducted a simulation campaign to analyze the effect of this limitation on functional range on the accuracy of exposure readings given by these devices. We estimate that the upper bound results in minimal inaccuracy in exposure quantification, and the lower bound can result in as much as a 50% error in approximately 10% of US homes.

Feasibility of the Bag-Mediated Filtration System for Environmental Surveillance of Poliovirus in Kenya

The bag-mediated filtration system (BMFS) was developed to facilitate poliovirus (PV) environmental surveillance, a supplement to acute flaccid paralysis surveillance in PV eradication efforts. From April to September 2015, environmental samples were collected from four sites in Nairobi, Kenya, and processed using two collection/concentration methodologies: BMFS (> 3 L filtered) and grab sample (1 L collected; 0.5 L concentrated) with two-phase separation. BMFS and two-phase samples were analyzed for PV by the standard World Health Organization poliovirus isolation algorithm followed by intratypic differentiation. BMFS samples were also analyzed by a cell culture independent real-time reverse transcription polymerase chain reaction (rRT-PCR) and an alternative cell culture method (integrated cell culture-rRT-PCR with PLC/PRF/5, L20B, and BGM cell lines). Sabin polioviruses were detected in a majority of samples using BMFS (37/42) and two-phase separation (32/42). There was statistically more frequent detection of Sabin-like PV type 3 in samples concentrated with BMFS (22/42) than by two-phase separation (14/42, p = 0.035), possibly due to greater effective volume assayed (870 mL vs. 150 mL). Despite this effective volume assayed, there was no statistical difference in Sabin-like PV type 1 and Sabin-like PV type 2 detection between these methods (9/42 vs. 8/42, p = 0.80 and 27/42 vs. 32/42, p = 0.18, respectively). This study demonstrated that BMFS can be used for PV environmental surveillance and established a feasible study design for future research.

Use of passive SPME sampling devices to determine exposure of oil painters to organic compounds

A solid-phase microextraction (SPME) sampling device, called a needle trap samplers (NTS) that were packed with 60-80 mesh divinylbenzene (DVB) particles, was used to extract indoor volatile organic compounds (VOCs) that were emitted in an oil painting studio. This work compared the sampling performances of a passive NTS and an active charcoal desorption tube that was connected to a personal sampling pump (Method 1501), developed by the National Institute of Occupational Safety and Health, USA. The experimental results reveal that the NTS is a dependable alternative device to Method 1501 for monitoring indoor air quality. 2,2,4,6,6-Pentamethylheptane (isododecane) is the main emitted pollutant when oil painters use odorless thinner as a substitute solvent for turpentine oil, and the mean exposed concentrations of isododecane determined by NTS ranged from 0.83 to 3.10 ppm, which were dependent on whether the indoor ventilation was performed by the natural or mechanic mode. To maintain adequate air exchange rates in an oil painting studio, doors should be opened to increase air circulation, lowering the concentrations of isododecane to which painters are exposed.Implications: A needle trap sampler (NTS) was used to sample VOCs from oil painting in an indoor studio. Isododecane is the main emitted pollutant when painters use the odorless thinner. The NTS was evaluated to be a dependable alternative to Method 1501 for monitoring indoor air quality. To maintain adequate air exchange rates in a painting studio, doors should be opened to lower concentrations of VOCs.

Calibration and validation of a microporous polyethylene passive sampler for quantitative estimation of illicit drug and pharmaceutical and personal care product (PPCP) concentrations in wastewater influent

Wastewater-based epidemiology (WBE), the per capita normalised measurement of drugs, chemicals or metabolites in wastewater influent, relies on sampling and quantitative analysis to evaluate temporal and spatial trends of chemical consumption. Continuous, high-resolution, flow proportional composite sampling is optimal for accurate representations of chemical mass loads, but is rarely implemented, with conventional autosamplers providing relatively low frequency time or volume proportional samples. However, due to equipment or resource constraints at many wastewater treatment plants (WWTPs), even this may not be feasible. Passive sampling may provide an alternative sampling strategy. To investigate this, samplers comprising hollow, cylindrical Microporous Polyethylene Tubes (MPTs) containing polymeric sorbent phases of Strata-X and Strata-X in agarose were simultaneously deployed in a municipal WWTP influent stream. Samplers were extracted, analysed and evaluated for a range of illicit drugs and pharmaceuticals and personal care products (PPCPs) after 4, 7, 15, 21, and 29 day deployments. The MPT samplers were calibrated against 24-hour time proportional composite grab samples that were collected in parallel. Diffusion through the MPT governed uptake, reducing or eliminating the influence of external flow rates that may fluctuate unpredictably in a WWTP environment. Calibration data for six illicit drugs and fourteen PPCPs, including methamphetamine, benzoylecgonine, MDMA, codeine and carbamazepine, demonstrated linear accumulation in the samplers (R² ≥ 0.84). Derived sampling rates for these analytes ranged from 0.25 to 17 mL d^-1 for ibuprofen and verapamil, respectively. A validation study using this sampling rate data showed the MPT could effectively quantify concentrations (≥0.1 ng mL^-1) of a range of amphetamine-type stimulants, opioids and metabolites as well as nicotine, accounting for 95% of the variance in parallel composite grab sample concentrations of these compounds. The MPT sampler shows promise for providing essential monitoring data for WBE, informing future intervention and research strategies.

A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems

A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.

The Potential of Ultraviolet Radiation Meters in Secondary Schools as a Sun Protection Intervention Mechanism for Adolescents

The aim of this pilot study was to assess whether the installation of ultraviolet radiation (UVR) meters in secondary schools has the potential to improve adolescents’ sun protection-related knowledge, attitudes, and behaviours and reduce their exposure to UVR during school hours. Data were collected from students at two schools via online pre- and post-intervention surveys, measurement of sunscreen usage, polysulfone UVR exposure badges, and photographs of the schoolyards to assess hat and shade use. Several operational issues limited the quantity and quality of data that could be collected, and findings were mixed. While there were no significant changes in either self-reported or observed sun protection behaviours, there were significant improvements in UVR knowledge among students at the intervention school, and reactions to the meter were highly favourable. Students reported consulting the meter regularly and using it to make decisions about their sun protection behaviours. Overall, the study results offer some support for the use of UVR meters in areas frequented by adolescents and provide insights into the process issues that are likely to need to be addressed when attempting to trial sun protection interventions in schools.

Genome-scale transcriptional dynamics and environmental biosensing

Genome-scale technologies have enabled mapping of the complex molecular networks that govern cellular behavior. An emerging theme in the analyses of these networks is that cells use many layers of regulatory feedback to constantly assess and precisely react to their environment. The importance of complex feedback in controlling the real-time response to external stimuli has led to a need for the next generation of cell-based technologies that enable both the collection and analysis of high-throughput temporal data. Toward this end, we have developed a microfluidic platform capable of monitoring temporal gene expression from over 2,000 promoters. By coupling the "Dynomics" platform with deep neural network (DNN) and associated explainable artificial intelligence (XAI) algorithms, we show how machine learning can be harnessed to assess patterns in transcriptional data on a genome scale and identify which genes contribute to these patterns. Furthermore, we demonstrate the utility of the Dynomics platform as a field-deployable real-time biosensor through prediction of the presence of heavy metals in urban water and mine spill samples, based on the the dynamic transcription profiles of 1,807 unique Escherichia coli promoters.

Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile

Integration of low-cost air quality sensors with the internet of things (IoT) has become a feasible approach towards the development of smart cities. Several studies have assessed the performance of low-cost air quality sensors by comparing their measurements with reference instruments. We examined the performance of a low-cost IoT particulate matter (PM10 and PM2.5) sensor in the urban environment of Santiago, Chile. The prototype was assembled from a PM10-PM2.5 sensor (SDS011), a temperature and relative humidity sensor (BME280) and an IoT board (ESP8266/Node MCU). Field tests were conducted at three regulatory monitoring stations during the 2018 austral winter and spring seasons. The sensors at each site were operated in parallel with continuous reference air quality monitors (BAM 1020 and TEOM 1400) and a filter-based sampler (Partisol 2000i). Variability between sensor units (n = 7) and the correlation between the sensor and reference instruments were examined. Moderate inter-unit variability was observed between sensors for PM2.5 (normalized root-mean-square error 9-24%) and PM10 (10-37%). The correlations between the 1-h average concentrations reported by the sensors and continuous monitors were higher for PM2.5 (R2 0.47-0.86) than PM10 (0.24-0.56). The correlations (R2) between the 24-h PM2.5 averages from the sensors and reference instruments were 0.63-0.87 for continuous monitoring and 0.69-0.93 for filter-based samplers. Correlation analysis revealed that sensors tended to overestimate PM concentrations in high relative humidity (RH > 75%) and underestimate when RH was below 50%. Overall, the prototype evaluated exhibited adequate performance and may be potentially suitable for monitoring daily PM2.5 averages after correcting for RH.

Deriving consistent ocean biological and biogeochemical products from multiple satellite ocean color sensors

A methodology is developed for deriving consistent ocean biological and biogeochemical products from multiple satellite ocean color sensors that have slightly different sensor spectral characteristics. Specifically, the required coefficients for algorithm modifications are obtained using the hyperspectral in situ optical measurements from the Marine Optical Buoy (MOBY) in the water off Hawaii. It is demonstrated that using the proposed approach for modifying ocean biological and biogeochemical algorithms, satellite-derived ocean property data over the global open ocean are consistent from multiple satellite sensors, although their corresponding sensor-measured normalized water-leaving radiance spectra nLw(λ) are different. Therefore, the proposed approach allows satellite-derived ocean biological and biogeochemical products to be consistent and can therefore be routinely merged from various satellite ocean color sensors. The proposed approach can be applied to any satellite algorithms that use the input of sensor-measured nLw(λ) spectra.

Comparative evaluation of four suspended particulate matter (SPM) sampling devices and their use for monitoring SPM quality

Representative sampling of suspended particulate matter is fundamental for assessing river sediment quality, including the distribution and physicochemical characterisation of particles at different hydrological events. This study compares time-integrated samplers and discrete sampling methods, focusing on (a) the representativeness of the different methods and (b) the comparability between the various sampling techniques. The study investigates whether different sampling devices used under the same conditions can reproduce the annual mean. Two time-integrated sampling techniques (Binnensammler floating collector (BS); self-constructed Phillips sampler (PS)) and two discrete sampling systems (continuous-flow centrifuge (CFC); hydrocyclone (HC)) were compared. The monitoring program (August 2013 to August 2014) was conducted using a 4-week sampling frequency at two different monitoring stations in the Rhine river basin. The analysis of physicochemical parameters included total organic carbon (TOC), particulate phosphorus (PP), grain size distribution (GSD), metals, and organic pollutants (PCBs, HCB, PAH). A nested analysis of variance (ANOVA) was used to evaluate the dependence of suspended matter quality parameters on the sampling method, the sampling device, and the sampling station. According to ANOVA, physical and chemical parameters as well as persistent organic pollutants are homogenous for the time-integrated samplers PS and BS. Comparing PS and the reference technique CFC, only the mean annual concentration of TOC is significantly higher for CFC (5.91%; PS, 4.53%) due to degradation processes. With the exception of TOC, Ni, and GSD, data of BS was comparable with that of CFC. Comparing CFC and HC, there are significant differences for GSD, Zn, and Ni. An analysis of the time series of GSD < 63 μm and sum of PAHs confirms the findings of the nested ANOVA, showing that HC time series display significant differences compared with the other samplers.

Laboratory and field evaluation of real-time and near real-time PM2.5 smoke monitors

Increases in large wildfire frequency and intensity and a longer fire season in the western United States are resulting in a significant increase in air pollution, including concentrations of PM_2.5 (particulate matter <2.5 µm in aerodynamic diameter) that pose significant health risks to nearby communities. During wildfires, government agencies monitor PM_2.5 mass concentrations providing information and actions needed to protect affected communities; this requires continuously measuring instruments. This study assessed the performance of seven candidate instruments: (1) Met One Environmental beta attenuation monitor (EBAM), (2) Met One ES model 642 (ES642), (3) Grimm Environmental Dust Monitor 164 (EDM), (4) Thermo ADR 1500 (ADR), (5) TSI DRX model 8543 (DRX), (6) Dylos 1700 (Dylos), and (7) Purple Air II (PA-II) in comparison with a BAM 1020 (BAM) reference instrument. With the exception of the EBAM, all candidates use light scattering to determine PM_2.5 mass concentrations. Our comparison study included environmental chamber and field components, with two of each candidate instrument operating next to the reference instrument. The chamber component involved 6 days of comparisons for biomass combustion emissions. The field component involved operating all instruments in an air monitoring station for 39.5 days with hourly average relative humidity (RH) ranging from 19% to 98%. Goals were to assess instrument precision and accuracy and effects of RH, elemental carbon (EC), and organic carbon (OC) concentrations. All replicate candidate instruments showed high hourly correlations (R² ≥ 0.80) and higher daily average correlations (R² ≥ 0.90), where all instruments correlated well (R² ≥ 0.80) with the reference. The DRX and Purple Air overestimated PM_2.5 mass concentrations by a factor of ~two. Differences between candidates and reference were more pronounced at higher PM_2.5 concentrations. All optical instruments were affected by high RH and by the EC/OC ratio. Equations to convert candidate instruments data to FEM BAM type data are provided to enhance the usability of data from candidate instruments.Implications: This study tested the performance of seven candidate PM_2.5 mass concentration measuring instruments in two settings - environmental chamber and field. The instruments were tested to determine their suitability for use during biomass combustion events and the effects of RH, PM mass concentrations, and concentrations of EC and OC on their performance. The accuracy and precision of each monitor and effect of RH, PM concentration, EC and OC concentrations are varied. The data show that most of these candidate instruments are suitable for measuring PM_2.5 concentration during biomass combustions with a proper correction factor for each instrument type.

Development of a Novel Equilibrium Passive Sampling Device for Methylmercury in Sediment and Soil Porewaters

We explored the concept of equilibrium passive sampling for methylmercury (MeHg) using the strategy developed for hydrophobic organic chemicals. Passive sampling should allow prediction of the concentration of the chemically labile fraction of MeHg in sediment porewaters based on equilibrium partitioning into the sampler, without modeling diffusion rates through the sampler material. Our goals were to identify sampler materials with the potential to mimic MeHg partitioning into animals and sediments and provide reversible sorption in a time frame appropriate for in situ samplers. Candidate materials tested included a range of polymers embedded with suitable sorbents for MeHg. The most promising were activated carbon (AC) embedded in agarose, thiol-self-assembled monolayers on mesoporous supports embedded in agarose, and cysteine-functionalized polyethylene terephthalate, which yielded log sampler-water partition coefficients of 2.8 to 5 for MeHgOH and MeHg complexed with dissolved organic matter (Suwannee River humic acid). Sampler equilibration time in sediments was approximately 1 to 2 wk. Investigation of the MeHg accumulation mechanism by AC embedded in agarose suggested that sampling was kinetically influenced by MeHg interactions with AC particles and not limited by diffusion through the gel for this material. Also, AC exhibited relatively rapid desorption of Hg and MeHg, indicating that this sorbent is capable of reversible, equilibrium measurements. In sediment:water microcosms, porewater concentrations made with isotherm-calibrated passive samplers agreed within a factor of 2 (unamended sediment) or 4 (AC-amended sediment) with directly measured concentrations. The present study demonstrates a potential new approach to passive sampling of MeHg. Environ Toxicol Chem 2020;39:323-334. © 2019 SETAC.

Dual-channel mobile fluorescence lidar system for detection of tryptophan

We present a dual-channel mobile lidar system based on laser-induced fluorescence (LIF) for real-time standoff detection and concentration distribution analysis of tryptophan. The system employs an ultraviolet laser excitation source and signal detectors for receiving fluorescence signals within two different wavelength bands. The performed experiments measured tryptophan aerosols at two different standoff distances. Moreover, distilled water and ethanol solutions were also detected for comparison. The results show that the system can detect LIF signals of tryptophan, give early warnings, locate the diffusion sources, and monitor the variation of the aerosol concentration distribution in real time.

Nanoparticle-based 'turn-on' scattering and post-sample fluorescence for ultrasensitive detection of water pollution in wider window

Ultrasensitive detection of heavy metal ions in available water around us is a great challenge for scientists since long time. We developed an optical technique that combines Rayleigh scattering of UV light (365 nm) and post-sample fluorescence detection from colloidal silver (Ag) nanoparticles (NPs) having a surface plasmon resonance (SPR) band at 420 nm. The efficacy of the technique is tested by the detection of several model toxic ions, including mercury, lead, and methylmercury in aqueous media. The light scattering from the Hg-included/inflated Ag NPs at 395 nm was observed to saturate the light sensor even with ppm-order concentrations of Hg ions in the water sample. However, the pollutant is not detected at lower concentrations at this wavelength. Instead, the fluorescence of a high-pass filter (cut-off at 400 nm) at 520 nm is applied to detect pollutant concentrations of up to several hundreds of ppm in the water sample. We also detected lead and methylmercury as model pollutants in aqueous media and validated the efficacy of our strategy. Finally, we report the development of a working prototype based on the strategy developed for efficient detection of pollutants in drinking/agricultural water.

Rapid Assessment of Opioid Exposure and Treatment in Cities Through Robotic Collection and Chemical Analysis of Wastewater

INTRODUCTION

Accurate data regarding opioid use, overdose, and treatment is important in guiding community efforts at combating the opioid epidemic. Wastewater-based epidemiology (WBE) is a potential method to quantify community-level trends of opioid exposure beyond overdose data, which is the basis of most existing response efforts. However, most WBE efforts collect parent opioid compounds (e.g., morphine) at wastewater treatment facilities, measuring opioid concentrations across large catchment zones which typically represent an entire municipality. We sought to deploy a robotic sampling device at targeted manholes within a city to semi-quantitatively detect opioid metabolites (e.g., morphine glucuronide) at a sub-city community resolution.

METHODS

We deployed a robotic wastewater sampling platform at ten residential manholes in an urban municipality in North Carolina, accounting for 44.5% of the total municipal population. Sampling devices comprised a robotic sampling arm with in situ solid phase extraction, and collected hourly samples over 24-hour periods. We used targeted mass spectrometry to detect the presence of a custom panel of opioids, naloxone, and buprenorphine.

RESULTS

Ten sampling sites were selected to be a representative survey of the entire municipality by integrating sewer network and demographic GIS data. All eleven metabolites targeted were detected during the program. The average morphine milligram equivalent (MME) across the nine illicit and prescription opioids, as excreted and detected in wastewater, was 49.1 (standard deviation of 31.9) MME/day/1000-people. Codeine was detected most frequently (detection rate of 100%), and buprenorphine was detected least frequently (12%). The presence of naloxone correlated with city data of known overdoses reversed by emergency medical services in the prehospital setting.

CONCLUSION

Wastewater-based epidemiology with smart sewer selection and robotic wastewater collection is feasible to detect the presence of specific opioids, naloxone, methadone, and buprenorphine within a city. These results suggest that wastewater epidemiology could be used to detect patterns of opioid exposure and may ultimately provide information for opioid use disorder (OUD) treatment and harm reduction programs.

Out of sight, out of mind: participatory sensing for monitoring indoor air quality

In southern Chile, epidemiological studies have linked high levels of air pollution produced by the use of wood-burning stoves with the incidence of numerous diseases. Using a quasi-experimental design, this study explores the potential of participatory sensing strategies to transform experiences, perceptions, attitudes, and daily routine activities in 15 households equipped with wood-burning stoves in the city of Temuco, Chile. The results suggest that the experience of using a low-cost sensor improves household members' awareness levels of air pollution. However, the information provided by the sensors does not seem to improve the participants' self-efficacy to control air quality and protect themselves from pollution. The high degree of involvement with the participatory sensing experience indicates that the distribution of low-cost sensors could be a key element in the risk communication policies.

Testing a novel biotechnological passive sampler for monitoring atmospheric PAH pollution

In this study we evaluated a new type of passive air sampler, the "mossphere" device, filled with a Sphagnum palustre clone. For this purpose, we compared the atmospheric levels of polyaromatic hydrocarbons (PAHs) collected using this device and those collected in conventional bulk deposition and particulate matter (PM10) samplers. All three types of samplers were exposed at 10 sites affected by different levels of pollution and located in two different climate zones. The bulk deposition/ mossphere comparison yielded a greater number of significant regressions with higher coefficients of determination than the PM10/ mossphere comparison. No significant regressions were observed for 3-ring PAHs in either comparison. The mosspheres explain ca. 50% of the variability of the concentrations of 4-, 5- and 6-ring PAHs and total PAHs detected in PM10 and ca. 70% of the corresponding concentrations detected in the bulk deposition. The use of the Sphagnum clone enables standardization of the set-up, thus making the mossphere device a good sampling tool for monitoring 4-, 5- and 6-ring and total PAHs, especially those associated with bulk deposition. The findings indicate the potential usefulness of this innovative technology for mapping PAH levels.

Observing the Global Ocean with Biogeochemical-Argo

Biogeochemical-Argo (BGC-Argo) is a network of profiling floats carrying sensors that enable observation of as many as six essential biogeochemical and bio-optical variables: oxygen, nitrate, pH, chlorophyll a, suspended particles, and downwelling irradiance. This sensor network represents today's most promising strategy for collecting temporally and vertically resolved observations of biogeochemical properties throughout the ocean. All data are freely available within 24 hours of transmission. These data fill large gaps in ocean-observing systems and support three ambitions: gaining a better understanding of biogeochemical processes (e.g., the biological carbon pump and air-sea CO₂ exchanges) and evaluating ongoing changes resulting from increasing anthropogenic pressure (e.g., acidification and deoxygenation); managing the ocean (e.g., improving the global carbon budget and developing sustainable fisheries); and carrying out exploration for potential discoveries. The BGC-Argo network has already delivered extensive high-quality global data sets that have resulted in unique scientific outcomes from regional to global scales. With the proposed expansion of BGC-Argo in the near future, this network has the potential to become a pivotal observation system that links satellite and ship-based observations in a transformative manner.

NanoSIMS: Microscale Quantification of Biogeochemical Activity with Large-Scale Impacts

One major objective of aquatic microbial ecology is to understand the distribution of microbial populations over space and time and in response to environmental factors. Perhaps more importantly, it is crucial to quantify how those microbial cells affect biogeochemical processes of interest, such as primary production, nitrogen cycling, or the breakdown of pollutants. One valuable approach to link microbial identity to activity is to carry out incubations with stable-isotope-labeled substrates and then quantify the isotope incorporation by individual microbial cells using nanoscale secondary ion mass spectrometry (NanoSIMS). This review summarizes recent efforts in this field, highlights novel methods, describes studies investigating rare metabolisms as well as widespread microbial activity, and hopes to provide a framework to increase the use and capabilities of NanoSIMS for microbial biogeochemical studies in the future.

Multiple hazardous elements in nanoparticulate matter from a Caribbean industrialized atmosphere

Modern microscopy studies are capable of revealing ultra-fine particles (UFPs) and nanoparticles (NPs) that are produced in the processes related to traffic vehicular, industrial, metropolitan, and marine aerosol dry deposition in the coastal zones. Especially, secondary aerosol passages complexes categories of NPs and UFPs, which can be accumulated on construction compounds and by dry deposition, encourages multiples monuments deterioration routes. The advanced electron microscopies method is one of the most utilized in environmental studies. Between the different industrial areas in the world, the Caribbean area is the most relevant symbols of air quality due to climatic conditions with strong winds, but this study shows that regionally the most industrialized region does not have an adequate air quality. In the present work, electron microscopy analyses are used to describe of the extent of ultra-fine particle and nanoparticles in walls in contact to weathering. Numerous phases were recognized by advanced mineralogy methods. Thanks to the new analytical procedure it was feasible to understand NPs and UFPs; the occurrence of potential hazardous elements (PHEs), most of them as minerals but also combined in multiple accumulations with Al-Cr-Fe-K-Mg-Pb-Si-Ti-Zn amorphous; and carbonaceous phases.

Petroleum hydrocarbons in semipermeable membrane devices deployed in the Northern Gulf of Mexico and Florida keys following the Deepwater Horizon incident

The Deepwater Horizon (DWH) oil spill from April to July of 2010 contaminated Gulf of Mexico waters through release of an estimated 4.1 × 10⁶ barrels of oil. Beginning in June of 2010, semipermeable membrane devices (SPMDs) were deployed near areas with sensitive marine habitats (Alabama Alps and Western Shelf) potentially exposed to that oil. Elevated TPAH50 concentrations, flux rates and similarity of histograms and diagnostic ratios for polycyclic aromatic hydrocarbons (PAH) from SPMDs to weathered floating oil collected during the DWH spill indicates the Alabama Alps habitats were affected. While not affected by oil from the DWH spill, the temporal pattern of PAH contamination of SPMDs deployed near the Western Shelf between July 2010 and March 2011 could indicate prevailing currents affected contaminant transport to the Western Shelf Area (East and West Flower Garden, Sonnier, and Stetson Banks) from non-DWH sources, including oil and gas exploration, shipping, and Mississippi River effluent.

Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study

Low-cost air monitoring sensors are an appealing tool for assessing pollutants in environmental studies. Portable low-cost sensors hold promise to expand temporal and spatial coverage of air quality information. However, researchers have reported challenges in these sensors' operational quality. We evaluated the performance characteristics of two widely used sensors, the Plantower PMS A003 and Shinyei PPD42NS, for measuring fine particulate matter compared to reference methods, and developed regional calibration models for the Los Angeles, Chicago, New York, Baltimore, Minneapolis-St. Paul, Winston-Salem and Seattle metropolitan areas. Duplicate Plantower PMS A003 sensors demonstrated a high level of precision (averaged Pearson's r = 0.99), and compared with regulatory instruments, showed good accuracy (cross-validated R² = 0.96, RMSE = 1.15 µg/m³ for daily averaged PM_2.5 estimates in the Seattle region). Shinyei PPD42NS sensor results had lower precision (Pearson's r = 0.84) and accuracy (cross-validated R² = 0.40, RMSE = 4.49 µg/m³). Region-specific Plantower PMS A003 models, calibrated with regulatory instruments and adjusted for temperature and relative humidity, demonstrated acceptable performance metrics for daily average measurements in the other six regions (R² = 0.74-0.95, RMSE = 2.46-0.84 µg/m³). Applying the Seattle model to the other regions resulted in decreased performance (R² = 0.67-0.84, RMSE = 3.41-1.67 µg/m³), likely due to differences in meteorological conditions and particle sources. We describean approach to metropolitan region-specific calibration models for low-cost sensors that can be used with cautionfor exposure measurement in epidemiological studies.

High Stability and Strong Fluorescence of Carbon Nanodots as Nanosensor for Hg2+ in Environmental Waters

Pollution of toxic heavy-metal ions such as mercury ions (Hg²⁺) is well known to severely threaten ecological environment and human health. Correspondingly, development of a fast and sensitive method for detecting heavy-metal ions is urgently needed and has been received widespread attention in recent years. In this study, carbon nanodots (CDs) with strong blue fluorescence were synthesized by a microwave-assisted hydrothermal method. The as-prepared blue fluorescent CDs not only have excellent stability (e.g. photostability, salt stability and pH stability), but also have extremely high selectivity and sensitivity for probing Hg²⁺ via fluorescence quenching. Specifically, fluorescence of CDs is gradually quenched along with the increase in Hg²⁺ concentration, and a low concentration of Hg²⁺ can be identified (with low detection limit, 15 nM). Therefore, the novel fluorescent CDs could be developed for detecting Hg²⁺ in aqueous conditions, and have great potential for fast probing Hg²⁺ in environmental samples.

Nanoparticle Bridges for Studying Electrical Properties of Organic Molecules and Gas Sensor Applications

Molecules have high potential for novel applications as building blocks for electronic devices such as sensors due to the versatility of their electronic properties. Their use in devices offers a great potential for further miniaturization of electronic devices. We describe a method where nanoparticles functionalized with short-chain organic molecules are used to build a molecular electronics device (nanoMoED) sensor for studying electrical properties of organic molecules. We also report the application of such a nanoMoED for detecting environmental gases. Here we provide a detailed description of the nanoMoED fabrication process, nanoparticle synthesis and functionalization, the basics of the electrical measurements, and nanoMoED applications. The platform described here is capable of detecting electrical current flowing through just a few molecules. The versatility of such nanoMoEDs makes this platform suitable for a wide range of molecular electronics and molecular sensing applications.