Contamination of polychlorinated biphenyls and organochlorine pesticides in breast milk in Korea: Time-course variation,influencing factors,and exposure assessment

Breast milk is a noninvasive specimen to assess maternal and infant exposure to polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs). In this study, 206 breast milk samples were collected from 87 participants during lactation, at <7, 15, 30, or 90 days postpartum in four cities in Korea. The total concentrations of PCBs (ΣPCB) and OCPs (ΣOCP) ranged from <LOQ to 84.0 (median: 12.1) ng g⁻¹ lipid weight and from <LOQ to 559 (median: 144) ng g⁻¹ lipid weight, respectively. The residue levels of these contaminants measured in our study were relatively lower than those reported for European, African and Asian populations. Within a month postpartum typically after day seven the levels of ΣPCB and ΣOCP significantly increased. Some OCP compounds were correlated with maternal age, BMI, parity, and delivery mode. Certain types of dietary habits such as seafood and noodle consumption were significantly associated with ΣPCB and ΣOCP. The estimated daily intakes (EDIs) of ΣPCB and ΣOCP were 45.2–127 ng kg⁻¹ bw day⁻¹ and 625–1259 ng kg⁻¹ bw day⁻¹ during lactation, respectively, which are lower than the threshold values proposed by the US EPA and Health Canada. The exposure of Korean infants to chlordanes via breast milk had a potential health risk which deserves further investigation.     

Transgenic poplar trees expressing yeast cadmium factor 1 exhibit the characteristics necessary for the phytoremediation of mine tailing soil

Genetic engineering of plants for phytoremediation is thought to be possible based on results using model plants expressing genes involved in heavy metal resistance, which improve the plant’s tolerance of heavy metals and accumulation capacity. The next step of progress in this technology requires the genetic engineering of plants that produce large amounts of biomass and the testing of these transgenic plants in contaminated soils. Thus, we transformed a sterile line of poplar Populus alba X P. tremula var. glandulosa with a heavy metal resistance gene, ScYCF1 (yeast cadmium factor 1), which encodes a transporter that sequesters toxic metal(loid)s into the vacuoles of budding yeast, and tested these transgenic plants in soil taken from a closed mine site contaminated with multiple toxic metal(loid)s under greenhouse and field conditions. The YCF1-expressing transgenic poplar plants exhibited enhanced growth, reduced toxicity symptoms, and increased Cd content in the aerial tissue compared to the non-transgenic plants. Furthermore, the plants accumulated increased amounts of Cd, Zn, and Pb in the root, because they could establish an extensive root system in mine tailing soil. These results suggest that the generation of YCF1-expressing transgenic poplar represents the first step towards producing plants for phytoremediation. The YCF1-expressing poplar may be useful for phytostabilization and phytoattenuation, especially in highly contaminated regions, where wild-type plants cannot survive.     

Stream discharge characteristics through urbanization gradient in Danshui River, Taiwan: perspectives from observation and simulation

Urbanization and the subsequent changes in land use/cover inevitably influence the quality and even the quantity of stream water. This issue is widely studied through evaluations on land-use change scenarios or comparisons among historical patterns at the same watershed. However, observational stream discharge changes through urbanization gradient have rarely been discussed. In this study, we analyzed 5-year discharge data from 13 gauges in the Danshui River network with a wide range of urbanization gradient to explore the impacts on observational hydrological characteristics in individual catchments. The results reveal that stream discharge in pristine watersheds is characterized by a larger proportion of baseflow and is less fluctuating. When the forest coverage is <90%, the discharge fluctuation almost doubles. Meanwhile, the baseflow fraction decreases gradually with the increase of paddy area, which may concomitantly result from the increasing irrigation. Such a drop in baseflow may threaten the maintenance of the minimum flow required for the stream aquatic ecosystem. Furthermore, we simulated the stream discharges by TOPMODEL with blind land-use-independent parameters. The results show that the simulated discharges are satisfactory, particularly for the pristine catchments, but not as fitting for the paddy-intensive watersheds perhaps due to the unexpected irrigation. On the whole, the calibrated parameters are dependent with the landscape characteristics. The landscape-based parameter estimations can be applied to simulate discharge well, meaning the potential to assess the ungauged watersheds.     

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.     

Environmental quality of Korean coasts as determined by modified Shannon–Wiener evenness proportion

The coast of the Korean peninsula experiences a range of human impacts, including pollution, shipping, reclamation, and aquaculture, that have motivated numerous local studies of macrobenthic organisms. In this paper, 1,492 subtidal stations were compiled from 23 studies (areas) to evaluate environmental quality on a broader scale. A common index in biomonitoring, Shannon–Wiener evenness proportion (SEP), could not incorporate azoic or single-species samples. This shortcoming was overcome by developing an inverse function of SEP (ISEP), which was positively correlated with independent measures of water quality available for nine sites and was not biased by the size of the sampling unit. Additionally, at Shihwa Dike, where samples were collected before and after reinstating a tidal connection with the ocean, ISEP values improved over time, as expected. Thus, it is now possible to assign Korean subtidal sites to seven ISEP “grades” and to use their values and trends to guide coastal management.     

Assessment of anthropogenic influences on surface water quality in urban estuary, northern New Jersey: multivariate approach

Concentrations of selected heavy metals (Cd, Cr, Cu, Pb, Ni, Fe, and Zn), nutrients (NO ₃ ^? and NH₃), fecal coliform colonies, and other multiple physical–chemical parameters were measured seasonally from 12 locations in an urban New Jersey estuary between 1994 and 2008. Stepwise regression, principal component analysis, and cluster analysis were used to group water quality results and sampling locations, as well as to assess these data’s relationship to sewage treatment effluents and the distance to the mouth of the river. The BOD₅, NH₃, NO ₃ ^? and fecal coliform counts clustered as one group and positively correlated to the distances from treated effluent and the measures of magnitude at the discharge points. Dissolved solids and most metal species scored high along a single principal component axes and were significantly correlated with the proximity to the industrialized area. From these data, one can conclude that the effluent discharge has been a main source of anthropogenic input to the Hackensack River over the past 15 years. Therefore, the greatest improvement to water quality would come from eliminating the few remaining combined sewer overflows and improving the removal of nutrients from treated effluents before they are discharged into the creeks and river.     

Artificial neural network analysis for reliability prediction of regional runoff utilization

Many factors in the reliability analysis of planning the regional rainwater utilization tank capacity need to be considered. Based on the historical daily rainfall data, the following four analyzing procedures will be conducted: the regional daily rainfall frequency, the amount of runoff, the water continuity, and the reliability. Thereafter, the suggested designed storage capacity can be obtained according to the conditions with the demand and supply reliability. By using the output data, two different types of artificial neural network models are used to build up small area rainfall–runoff supply systems for the simulation of reliability and the prediction model. They are also used for the testing of stability and learning speed assessment. Based on the result of this research, the radial basis function neural network (RBFNN) model, using the Gaussian function that has a similar trend as the nature as basic function, has better stability than using the back-propagation neural network (BPNN) model. Despite the fact that RBFNN was more reliable than BPNN, it still made a conservative estimate for the actual monitoring data. The error rate of RBFNN was still higher than the correction of BPNN 4-3-1-1. This should have significant benefit in the future application of the instantaneous prediction or the development of related intelligent instantaneous control equipment.     

Analysis of spatial and seasonal distributions of MODIS aerosol optical properties and ground-based measurements of mass concentrations in the Yellow Sea region in 2009

Satellite-retrieved data on aerosol optical depth (AOD) and Ångström exponent (AE) using a moderate resolution imaging spectrometer (MODIS) were used to analyze large-scale distributions of atmospheric aerosols in East Asia. AOD was relatively high in March (0.44?±?0.25) and low in September (0.24?±?0.21) in the East Asian region in 2009. Sandstorms originating from the deserts and dry areas in northern China and Mongolia were transported on a massive scale during the springtime, thus contributing to the high AOD in East Asia. However, whereas PM10 with diameters ≤10 μm was the highest in February at Anmyon, Cheongwon, and Ulleung, located leeward about halfway through the Korean Peninsula, AOD rose to its highest in May. The growth of hygroscopic aerosols attendant on increases in relative humidity prior to the Asian monsoon season contributed to a high AOD level in May. AE typically appears at high levels (1.30?±?0.37) in August due to anthropogenic aerosols originating from the industrial areas in eastern China, while AOD stays low in summer due to the removal process caused by rainfall. The linear correlation coefficients of the MODIS AOD and ground-based mass concentrations of PM10 at Anmyon, Cheongwon, and Ulleung were measured at 0.4~0.6. Four cases (6 days) of mineral dustfall from sandstorms and six cases (12 days) of anthropogenically polluted particles were observed in the central area of the Korean Peninsula in 2009. PM10 mass concentrations increased at both Anmyon and Cheongwon in the cases of mineral dustfall and anthropogenically polluted particles. Cases of dustfall from sandstorms and anthropogenic polluted particles, with increasing PM10 mass concentrations, showed higher AOD values in the Yellow Sea region.     

Changes of Soil Enzyme Activities By Simulated Acid and Nitrogen Deposition

Effects of acid and nitrogen depositions on soil microbial activities were studied in a laboratory-based experiment. Five treatments were added to forest soil for five weeks, and soil enzyme activities were determined along with chemical properties. There was little change in pH and nitrogen availability. Dehydrogenase, phosphatase and arylsulphatase activities were decreased by all the acidic treatments compared to the control, while urease activity was increased by the pH 4 treatment. at the same pH treatment, different nitric acid contents induced different urease activities. the results suggest that acid deposition would inhibit microbial activities and that more study is needed to elucidate the impact on nitrogen cycling in forests.     

Quaternary stratigraphy, sediment characteristics and geochemistry of arsenic-contaminated alluvial aquifers in the Ganges–Brahmaputra floodplain in central Bangladesh

This study focuses on the Quaternary stratigraphy, sediment composition, mineralogy, and geochemistry of arsenic (As)-contaminated alluvial aquifers in the Ganges–Brahmaputra floodplain in the central Bangladesh. Arsenic concentrations in 85 tubewells in Manikganj area, 70 km northwest of Dhaka City, range from 0.25 µg/L to 191 µg/L with a mean concentration of 33 µg/L. Groundwater is mainly Ca–HCO₃ type with high concentrations of dissolved As, Fe, and Mn, but low level of SO₄. The uppermost aquifer occurs between 10 m and 80 m below the surface that has a mean arsenic concentration of 35 µg/L. Deeper aquifer (> 100 m depth) has a mean arsenic concentration of 18 µg/L. Sediments in the upper aquifer are mostly gray to dark-gray, whereas sediments in the deep aquifer are mostly yellowing-gray to brown. Quartz, feldspar, mica, hornblende, garnet, kyanite, tourmaline, magnetite, ilmenite are the major minerals in sediments from both aquifers. Biotite and potassium feldspar are dominant in shallow aquifer, although plagioclase feldspar and garnet are abundant in deep aquifer sediments. Sediment composition suggests a mixed provenance with sediment supplies from both orogenic belts and cratons. High arsenic concentrations in sediments are found within the upper 50 m in drilled core samples. Statistical analysis shows that As, Fe, Mn, Ca, and P are strongly correlated in sediments. Concentrations of Cd, Cu, Ni, Zn, and Bi also show strong correlations with arsenic in the Manikganj sediment cores. Authigenic goethite concretions, possibly formed by bacteria, are found in the shallow sediments, which contain arsenic of a concentration as high as 8.8 mg/kg. High arsenic concentrations in aquifers are associated with fine-grained sediments that were derived mostly from the recycled orogens and relatively rapidly deposited mainly by meandering channels during the Early to Middle Holocene rising sea-level conditions.