Separating Measurement Error and Signal in Environmental Data: Use of Replicates to Address Uncertainty.

Measurement uncertainty has long been a concern in the characterizing and interpreting environmental and toxicological measurements. We compared statistical analysis approaches when there are replicates: a Naïve approach that omits replicates, a Hybrid approach that inappropriately treats replicates as independent samples, and a Measurement Error Model (MEM) approach in a random effects analysis of variance (ANOVA) model that appropriately incorporates replicates. A simulation study assessed the effects of sample size and levels of replication, signal variance, and measurement error on estimates from the three statistical approaches. MEM results were superior overall with confidence intervals for the observed mean narrower on average than those from the Naïve approach, giving improved characterization. The MEM approach also featured an unparalleled advantage in estimating signal and measurement error variance separately, directly addressing measurement uncertainty. These MEM estimates were approximately unbiased on average with more replication and larger sample sizes. Case studies illustrated analyzing normally distributed arsenic and log-normally distributed chromium concentrations in tap water and calculating MEM confidence intervals for the true, latent signal mean and latent signal geometric mean (i.e., with measurement error removed). MEM estimates are valuable for study planning; we used simulation to compare various sample sizes and levels of replication.

Low-Cost Water Quality Sensors for IoT: A Systematic Review.

In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.

Vibrational Spectroscopy as a Tool for Bioanalytical and Biomonitoring Studies.

The review briefly describes various types of infrared (IR) and Raman spectroscopy methods. At the beginning of the review, the basic concepts of biological methods of environmental monitoring, namely bioanalytical and biomonitoring methods, are briefly considered. The main part of the review describes the basic principles and concepts of vibration spectroscopy and microspectrophotometry, in particular IR spectroscopy, mid- and near-IR spectroscopy, IR microspectroscopy, Raman spectroscopy, resonance Raman spectroscopy, Surface-enhanced Raman spectroscopy, and Raman microscopy. Examples of the use of various methods of vibration spectroscopy for the study of biological samples, especially in the context of environmental monitoring, are given. Based on the described results, the authors conclude that the near-IR spectroscopy-based methods are the most convenient for environmental studies, and the relevance of the use of IR and Raman spectroscopy in environmental monitoring will increase with time.

Design, construction and characterisation of a portable gamma-ray spectrometer for low-level natural occurring radioactive material ex-situ measurement.

The activity concentrations in naturally occurring radioactive material (NORM) samples are conventionally measured using a gamma-ray spectrometer with a single detector (mostly HPGe or NaI:Tl) enclosed in a lead shield. In this work, a passive water shield to reduce background radiation reaching the detectors was designed using GEANT4-toolkit Monte Carlo simulations and then constructed. This measurement system is portable and cost-effective for ex-situ measurements. IAEA-375 soil and beach sand each placed in Marinelli beakers were measured using two LaBr3:Ce detectors in singles and coin-cidence modes. A novel method of background reduction by using photon time-of-flight was employed together with the measurement of the two photons energies. These samples were also measured in singles mode using a NaI:Tl detector inside the constructed water shield and HPGe detector shielded with lead to compare and validate the results of LaBr3:Ce detectors measurement. Both the simulated and measured results show that the water shield (500 mm thick) attenuates 2614.5 keV gamma rays by 90 %. The minimum detectable activity (MDA) measured for 24 h using the NaI:Tl detector without shield and inside the water shield are; 546 Bq kg-1 and 146 Bq kg-1 at 1460.8 keV (40K), 194 Bq kg-1 and 15 Bq kg-1 at 1764.5 keV (238U series), and 131 Bq kg-1 and 15 Bq kg-1 at 911.2 keV (232Th series), respectively. The measured activity concentrations of 238U and 232Th series and 40K radionuclides inside IAEA-375 soil agree with certified values to within measurement uncertainties. The measured activity of 138La in the LaBr3:Ce detector crystal is 263.8 ± 26.8 Bq kg-1. The internal activity of the LaBr3:Ce detector increases the MDA at 1460.8 keV and 2614.5 keV, which limits the measurement of primordial radionuclides with low activity concentration in singles mode. The activity concentrations of 238U and 232Th series radionuclides in beach sand were measured using NaI:Tl and LaBr3:Ce detectors. The results are consistent with those from HPGe measurement to within uncertainties.

Using national and local extant data to characterize environmental exposures in the national children's study: Queens County, New York.

OBJECTIVE: The National Children's Study is a long-term epidemiologic study of 100,000 children from 105 locations across the United States. It will require information on a large number of environmental variables to address its core hypotheses. The resources available to collect actual home and personal exposure samples are limited, with most of the home sampling completed on periodic visits and the personal sampling generally limited to biomonitoring. To fill major data gaps, extant data will be required for each study location. The Queens Vanguard Center has examined the extent of those needs and the types of data that are generally and possibly locally available. DATA: In this review we identify three levels of data--national, state and county--and local data and information sets (levels 1-3, respectively), each with different degrees of availability and completeness, that can be used as a starting point for the extant data collection in each study location over time. We present an example on the use of this tiered approach, to tailor the data needs for Queens County and to provide general guidance for application to other NCS locations. CONCLUSIONS: Preexisting and continually evolving databases are available for use in the NCS to characterize exposure. The three levels of data we identified will be used to test a method for developing exposure indices for segments and homes during the pilot phase of NCS, as outlined in this article.