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"Environmental Monitoring methods."
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Association between exposure to ambient particulate matter and chronic obstructive pulmonary disease: results from a cross-sectional study in China
ObjectiveThe association between exposure to ambient particles with a median aerodynamic diameter less than 10/2.5 µm (particulate matter, PM10/2.5) and COPD remains unclear. Our study objective was to examine the association between ambient PM10/2.5 concentrations and lung functions in adults.MethodsA cross-sectional study was conducted in southern China. Seven clusters were randomly selected from four cities across Guangdong province. Residents aged ≥20 years in the participating clusters were randomly recruited; all eligible participants were examined with a standardised questionnaire and spirometry. COPD was defined as a post-bronchodilator FEV1/FVC less than 70%. Atmosphere PM sampling was conducted across the clusters along with our survey.ResultsOf the subjects initially recruited, 84.4% (n=5993) were included for analysis. COPD prevalence and atmosphere PM concentration varied significantly among the seven clusters. COPD prevalence was significantly associated with elevated PM concentration levels: adjusted OR 2.416 (95% CI 1.417 to 4.118) for >35 and ≤75 µg/m3 and 2.530 (1.280 to 5.001) for >75 µg/m3 compared with the level of ≤35 µg/m3 for PM2.5; adjusted OR 2.442 (95% CI 1.449 to 4.117) for >50 and ≤150 µg/m3 compared with the level of ≤50 µg/m3 for PM1. A 10 µg/m3 increase in PM2.5 concentrations was associated with a 26 mL (95% CI −43 to −9) decrease in FEV1, a 28 mL (−49 to −8) decrease in FVC and a 0.09% decrease (−0.170 to −0.010) in FEV1/FVC ratio. The associations of COPD with PM10 were consistent with PM2.5 but slightly weaker.ConclusionsExposure to higher PM concentrations was strongly associated with increased COPD prevalence and declined respiratory function.Trial registration number ChiCTR-OO-14004264; Post-results.
Journal Article
Blood Lead Levels in Children 5 to 7 Years of Age from the Republic of Georgia: A Feasibility Study on Lead Surveillance Using Volumetric Absorptive Microsampling
For years, children in the Republic of Georgia, have experienced elevated blood lead levels (BLLs). From September 2023 to April 2024, the National Center for Disease Control and Public Health in Georgia piloted a national surveillance program for lead in children in two western regions of the country, using volumetric absorptive microsampling (VAMS) to measure BLLs.
We monitored BLLs and assessed predictors of elevated BLLs in children 5-7 years of age from two regions in the Republic of Georgia. We also aimed to demonstrate the feasibility of VAMS for BLL surveillance.
Children 5-7 years of age were randomly selected from the regions of Adjara and Imereti, Georgia, and 1,635 children participated. A trained phlebotomist collected two capillary blood samples from the children's fingertips using
VAMS devices. The samples were analyzed using inductively coupled plasma tandem mass spectrometry. Guardians completed a questionnaire detailing demographics, household, and lifestyle characteristics. We employed multivariable logistic regression models to identify predictors of BLLs
or
in Georgia.
Approximately 39.8%, 20%, and 4% of the participants had BLLs
,
, and
, respectively. In both regions, male sex and unpainted housing predicted BLLs
but not BLLs
. In Imereti, urban living additionally predicted BLLs
, while small household size and metal toys [metal vs. plastic toys:
; 95% confidence interval (CI): 1.66, 7.72] were associated with BLLs
. In Adjara, age, housing type, use of certain spices (yes vs. no:
; 95% CI: 1.11, 1.94), and household lead bullet production (yes vs. no:
; 95% CI: 1.41, 31.6) predicted BLLs
but not BLLs
.
Our findings confirm that lead exposure remains a significant public health issue in two regions of the Republic of Georgia, despite a national decrease in BLLs over the past 5 years. To our knowledge, this research marks the first large-scale application of VAMS technology for national BLL surveillance, offering significant advantages as a less invasive lead testing method that is accurate and suitable for settings with limited resources to handle, store, and transport venous blood samples. https://doi.org/10.1289/EHP15788.
Journal Article
Natural and Conventional Cosmetics—Mercury Exposure Assessment
Mercury (Hg) can enter the human body through the respiratory tract and digestive system, but also through the skin. Sources of Hg in the environment can be natural processes, but also human activities, including agriculture, chemical, and pharmaceutical industries. Hg can also enter the body through food, but also with cosmetics that are used for a long time. Therefore, the aim of this study was to evaluate the Hg content in 268 randomly selected cosmetics: Natural and conventional, for face and body. Hg content was determined using an atomic absorption spectrometer (AMA 254, Leco, Prague, Czech Republic). It was shown that the face preparations were characterized by a significantly higher Hg content than the body preparations. No differences in the content of the tested element were found between natural and conventional preparations. Hg could be detected in all samples with concentrations measured from 0.348 to 37.768 µg/kg.
Journal Article
Evaluating causative factors for landslide susceptibility along the Imphal-Jiribam railway corridor in the North-Eastern part of India using a GIS-based statistical approach
The Northeast part of India is experiencing an increase in infrastructure projects as well as landslides. This study aims to prepare the landslide susceptibility map of Tamenglong and Senapati districts, Manipur, India, and evaluates the state of landslide susceptibility along the Imphal-Jiribam railway corridor. Efficient statistical methods such as frequency ratio (FR), information value (IoV), weight of evidence (WoE), and weighted linear combination (WLC) were used in model preparation. A total of 322 landslide points were randomly divided into training (70%) and testing (30%) datasets. Nine causative factors were utilized for landslide susceptibility mapping (LSM). The importance of which was obtained using the information gain (IG) method. FR, IoV, WoE, and WLC were used to prepare the LSM using the training datasets and nine causative factors. Moreover, the accuracy and consistency were evaluated using AUC-ROC, precision, recall, overall accuracy (OA), balanced accuracy (BA), and
F
-score. The validation results showed that all methods performed well with the highest AUC and precision values of 0.913 and 0.95, respectively, for the IoV method, while the WLC method had the highest OA, BA, and
F
-score values of 0.808, 0.81, and 0.812, respectively. Finally, the results from LSM were used to evaluate the state of landslide susceptibility along the Imphal-Jiribam railway corridor. The results showed that 34% of the areas had high and very high susceptibility, while 40% were under less and significantly less susceptibility. The Tupul landslide area lay in medium susceptibility where the disastrous landslide occurred on 30 June 2022. Susceptibility values around the Noney and Khongsag railway station ranged from high to very high susceptibility. Thus, the study manifests the need for LSM preparation in rapidly constructing areas, which in turn will help the policymakers and planners for adopting strategies to minimize losses caused due to landslides.
Journal Article
Calibration Assessment of Low-Cost Carbon Dioxide Sensors Using the Extremely Randomized Trees Algorithm
As the monitoring of carbon dioxide is an important proxy to estimate the air quality of indoor and outdoor environments, it is essential to obtain trustful data from CO2 sensors. However, the use of widely available low-cost sensors may imply lower data quality, especially regarding accuracy. This paper proposes a new approach for enhancing the accuracy of low-cost CO2 sensors using an extremely randomized trees algorithm. It also reports the results obtained from experimental data collected from sensors that were exposed to both indoor and outdoor environments. The indoor experimental set was composed of two metal oxide semiconductors (MOS) and two non-dispersive infrared (NDIR) sensors next to a reference sensor for carbon dioxide and independent sensors for air temperature and relative humidity. The outdoor experimental exposure analysis was performed using a third-party dataset which fit into our goals: the work consisted of fourteen stations using low-cost NDIR sensors geographically spread around reference stations. One calibration model was trained for each sensor unit separately, and, in the indoor experiment, it managed to reduce the mean absolute error (MAE) of NDIR sensors by up to 90%, reach very good linearity with MOS sensors in the indoor experiment (r2 value of 0.994), and reduce the MAE by up to 98% in the outdoor dataset. We have found in the outdoor dataset analysis that the exposure time of the sensor itself may be considered by the algorithm to achieve better accuracy. We also observed that even a relatively small amount of data may provide enough information to perform a useful calibration if they contain enough data variety. We conclude that the proper use of machine learning algorithms on sensor readings can be very effective to obtain higher data quality from low-cost gas sensors either indoors or outdoors, regardless of the sensor technology.
Journal Article
Benthic foraminifera as bio-indicators of natural and anthropogenic conditions in Roscoff Aber Bay (Brittany, France)
Living benthic foraminifera, known as environmental bio-indicators of both natural and anthropogenic conditions in marine environments, were investigated in the coastal environment of Roscoff Aber Bay (Brittany, France). Eight sampling sites subject to natural variations (freshwater inputs, tides) and/or anthropogenic impacts (pollution, eutrophication) were studied over four seasons in 2021–2022 (November, February, May, August). We sought to understand the spatial distribution of foraminiferal populations within and between sampling sites over the different seasons and to identify sensitive species and those tolerant to anthropogenic impacts. To this end, sedimentary and biogeochemical characteristics of the sediments were examined by measuring grain size, temperature, oxygen, salinity, pH, environmental pigment concentration (chl a and phaeopigments), total organic carbon (TOC), isotopic ratios of carbon (δ 13 C), nitrogen (δ 15 N) and sulfide (δ 34 S), and chl a fluorescence. Considering these parameters as potential driving factors, four environments were distinguished among the sampling sites: open water, terrestrial, oligotrophic and eutrophic. These showed an increasing gradient of organic supply as well as very different microbial activities, highlighted by carbon and sulfide isotopic ratios. Foraminiferal population study revealed the dominant species characterising these main environments. The lowest abundance but highest diversity of foraminifera was found in the harbour site, associated with the dominance of Haynesina germanica , suggesting this species is tolerant to eutrophic environments and anthropogenic impacts. Open water was dominated by Ammonia beccarii and Elphidium crispum , while Quinqueloculina seminula was the most abundant species in the site with the greatest terrestrial influence. Interestingly, the observed organic enrichment of the harbour due to anthropogenic activities (fisheries, waste deposits, etc.) does not seem to significantly affect foraminiferal diversity. Overall, the benthic foraminiferal species in Roscoff Aber Bay appear to be an excellent proxy for marine environmental conditions under various natural and anthropogenic influences.
Journal Article
Evaluating the impact of climate change on yield and water use efficiency of different dry-season rice varieties cultivated under conventional and alternate wetting and drying conditions
This study is the first attempt to assess rice cultivation under alternate wetting and drying (AWD) and continuous flooding (CF) using the latest scenarios from the Intergovernmental Panel on Climate Change (IPCC), utilizing AquaCrop Model. Field experiments were conducted during the dry season 2023 to get the model calibration and validation input. We used two shared socioeconomic pathways scenarios (SSP3-7.0 and SSP5-8.5) developed within Coupled Model Intercomparison Project Phase 6 (CMIP6) and projected the rice growth during 2040–2070. The simulation results demonstrated the effectiveness of AquaCrop in capturing crop development across treatments and varieties. This model’s accuracy in simulating canopy cover (nRMSE = 14–32.5%), time series biomass (nRMSE = 22–42.5%), grain yield (Pd = 4.36–24.38%), and total biomass (nRMSE = 0.39–18.98%) was generally acceptable. The analysis of future climate shows an increasing trend in the monthly average temperature by 0.8 °C (Tmin) and 1.3 °C (Tmax) in both scenarios. While ETo values were not anticipated, rainfall was expected to increase with average values of 5.62 mm to 11.25 mm. In addition, the study found that varieties with growing periods longer than 93 days after transplanting (DAT), such as CAR15 and Sen Kra Ob, were most impacted by heat stress conditions, leading to reduced yield, harvest index (HI), and water use efficiency (WUE). In our case, CAR15 and Sen Kra Ob grain yields were reduced by 53% and 8%, respectively. AWD maintains superior WUE compared with CF regardless of the type of varieties, suggesting this technique is a drought-adaptive strategy.
Journal Article
Exploring alternatives for detecting microplastics in the human body: questionnaire survey
Microplastics (MPs) can enter the body via plastic products. Given modern plastic exposure, we seek to assess MP exposure in large populations through epidemiological tools. In this quasi-experimental study, every participant filled out a questionnaire, and those who satisfied any of the following requirements were not allowed to continue in the study: Diabetes, ulcerative colitis, Crohn’s disease, infectious diseases. Participants in the exposure and control groups were provided three hot meals in disposable plastic tableware (DPT) (n = 30) or non-DPT (n = 30), respectively. After a month of observation, individuals in the exposure group discontinued the three meals provided in DPT (n = 27) for 1 month as the post-exposure group. Each Participant in the three groups received a questionnaire survey and fecal sample collection. We compared the differences in MP levels between different groups and used the Bland–Altman analysis method to evaluate the consistency of the results obtained by different measurement methods. Statistically significant differences in the total quantity (
P
(0.80 matching degree) = 0.020;
P
(0.65 matching degree) < 0.001) and types (Polyethylene Terephthalate (EVA) (
P
= 0.039), Polyethylene Terephthalate (PET) (
P
= 0.022), Polyvinyl Butyral (PVB) (
P
= 0.013), Chlorinated Polyethylene (CPE) (
P
= 0.039), phenolic epoxy resin (
P
= 0.012)) of MPs were observed between the exposure and post-exposure groups. The Bland–Altman analysis results indicate that the two methods exhibit good consistency in the three groups (control group: mean difference = 0.54, agreement limits (95% CI) = − 0.44 ~ 1.54; exposure group: mean difference = 0.41, agreement limits (95% CI) = − 0.19 ~ 1.01; post-exposure group: mean difference = 0.19, agreement limits (95% CI) = − 0.63 ~ 1.02). The method based on questionnaire surveys can substitute the method of fecal sample detection to evaluate the exposure of MP particles.
Journal Article