Representative levels of blood lead, mercury, and urinary cadmium in youth: Korean Environmental Health Survey in Children and Adolescents (KorEHS-C), 2012–2014

AbstractBackgroundThis study examined levels of blood lead and mercury, and urinary cadmium, and associated sociodemographic factors in 3–18 year-old Korean children and adolescents.Materials and methodsWe used the nationally representative Korean Environmental Health Survey in Children and Adolescents data for 2012–2014 and identified 2388 children and adolescents aged 3–18 years. The median and 95th percentile exposure biomarker levels with 95% confidence intervals (CIs) were calculated. Multivariate regression analyses were performed on log transformed exposure biomarker levels adjusted for age, sex, area, household income, and father’s education level. The median exposure biomarker levels were compared with data from Germany, the US, and Canada, as well as the levels of Korean children measured at different times.ResultsThe median levels of blood lead and mercury, as well as urinary cadmium were 1.23μg/dL, 1.80μg/L, and 0.40μg/L (95% CIs, 1.21–1.25, 1.77–1.83, and 0.39–0.41, respectively). The blood lead levels were significantly higher in boys and younger children (p<0.0001) and children with less educated fathers (p=0.004) after adjusting for covariates. Urinary cadmium level increased with age (p<0.0001). The median levels of blood mercury and urinary cadmium were much higher in Korean children and adolescents than those in their peers in Germany, the US, and Canada. Blood lead levels tended to decrease with increasing age and divergence between the sexes, particularly in the early teen years. Median levels of blood lead and urinary cadmium decreased since 2010.ConclusionSociodemographic factors, including age, sex, and father’s education level were associated with environmental exposure to heavy metals in Korean children and adolescents. These biomonitoring data are valuable for ongoing surveillance of environmental exposure in this vulnerable population

Photovoltaic ac parameter characterization for dynamic partial shading and hot spot detection

This study investigates ac parameter characterization to detect partial shading within a series string of photovoltaic (PV) cells. Partial shading detection is needed to prevent hot spotting, a condition that reduces panel power performance and accelerates cell degradation. A PV cell is comprised of series and parallel resistances and parallel capacitance, which are affected by voltage bias, illumination, and temperature. When the string is under a maximum power point tracker or constant voltage controller, partial shading results in a clear increase in capacitance that is detectable by measuring the ac impedance magnitude in the 10-70 kHz frequency range. When the shaded cells become moderately negatively biased, there is a clear increase in parallel resistance. These trends in the PV cell physical characteristics can be used to develop partial shading detection methods that utilize the switching ripple of the power converter that controls the PV string

Photovoltaic Hot Spot Detection for Solar Panel Substrings Using AC Parameter Characterization

Hot spotting is a problem in photovoltaic (PV) systems that reduces panel power performance and accelerates cell degradation. In present day systems, bypass diodes are used to mitigate hot spotting, but it does not prevent hot spotting or the damage it causes. This paper presents an active hot spot detection method to detect hot spotting within a series of PV cells, using ac parameter characterization. A PV cell is comprised of series and parallel resistances and parallel capacitance, which are affected by voltage bias, illumination, and temperature. Experimental results have shown that when a PV string is under a maximum power point tracking control, hot spotting in a single cell results in a capacitance increase and dc impedance increase. The capacitance change is detectable by measuring the ac impedance magnitude in the 10-70 kHz frequency range. An impedance value change due to hot spotting can be detected by monitoring one high-frequency measurement in the capacitive region and one low-frequency measurement in the dc impedance region. Alternatively, the dc impedance can also be calculated using dc operating point measurements. The proposed hot spot detection method can be integrated into a dc-dc power converter that operates at the panel or subpanel level.close0

A New DC Arc Fault Detection Method Using DC System Component Modeling and Analysis in Low Frequency Range

In this paper, system component and arc modeling are presented, along with low frequency range analysis for dc arc fault detection. With an arc fault model consisting of a voltage source and variable resistor, the system during arcing can be described as an equivalent circuit model, which gives motivation for the proposed arc detection method. The presented model represents the low frequency characteristics of the main system components and arc in a dc system. Their influence on the line current can be well described and, as a result, it can be utilized for arc detection. The proposed method can distinguish normal operation from arcing and, as a result, dramatically reduces the possibility of false-positives. Experimental results verify the model validity and performance of the method