Arsenic levels in human hair,Kandal Province,Cambodia: The influences of groundwater arsenic,consumption period,age and gender

This study focused on the analysis of As levels in human hair samples collected from six villages in the Kandal Province of Cambodia. Of interest were the influence of, and interactions among, certain factors affecting As intake into the human body: As concentrations in groundwater, period of groundwater consumption, age and gender. The results revealed As levels in human hair ranging from 0.06 to 30 μg g⁻¹ with median and arithmetic mean values of 0.61 and 3.20 μg g⁻¹ (n = 68), respectively. Furthermore, a linear relationship was found between As concentrations in human hair and in the local groundwater. Arsenic (III) is the dominant species in Kandal groundwater, constituting in most cases at least 60% of the total As. Arsenic concentration ranged from 5 to 1543 μg L⁻¹, with the median value 348 μg L⁻¹ and arithmetic mean 454 μg L⁻¹. In large rural, poor areas holding most of Kandal’s 1.1 million people, up to 2 in 1000 people are believed to be at risk of cancer through the As-enriched water they drink. A toxicity risk assessment provides a hazard quotient (HQ) equaling 5.12, also a clear indication of non-carcinogenic exposure risk. On the authors’ visit to Kampong Kong commune, Kandal Province, cases of arsenicosis were diagnosed in patients as a result of drinking As-enriched groundwater.     

RCP 8.5��A scenario of comparatively high greenhouse gas emissions

This paper summarizes the main characteristics of the RCP8.5 scenario. The RCP8.5 combines assumptions about high population and relatively slow income growth with modest rates of technological change and energy intensity improvements, leading in the long term to high energy demand and GHG emissions in absence of climate change policies. Compared to the total set of Representative Concentration Pathways (RCPs), RCP8.5 thus corresponds to the pathway with the highest greenhouse gas emissions. Using the IIASA Integrated Assessment Framework and the MESSAGE model for the development of the RCP8.5, we focus in this paper on two important extensions compared to earlier scenarios: 1) the development of spatially explicit air pollution projections, and 2) enhancements in the land-use and land-cover change projections. In addition, we explore scenario variants that use RCP8.5 as a baseline, and assume different degrees of greenhouse gas mitigation policies to reduce radiative forcing. Based on our modeling framework, we find it technically possible to limit forcing from RCP8.5 to lower levels comparable to the other RCPs (2.6 to 6 W/m²). Our scenario analysis further indicates that climate policy-induced changes of global energy supply and demand may lead to significant co-benefits for other policy priorities, such as local air pollution.     

Comparison of Frequency-Selection Strategies for 2D Frequency-Domain Acoustic Waveform Inversion

Several frequency-selection strategies have been used to obtain global minimum solutions in waveform inversion. One strategy, called the discretization method, is to discretize frequencies with a large sampling interval to minimize redundancy in wavenumber information. Another method, the grouping method, groups frequencies with redundancy in wavenumber information. The grouping method can be carried out in two ways. With the first method, the minimum frequency is fixed and the maximum frequency is gradually extended upward (i.e., the overlap-grouping method). Under the second method, frequencies are not overlapped across the groups and waveform inversion proceeds from lower to higher frequency groups (i.e., the individual-grouping method). In this study, we compare these three frequency-selection strategies using both synthetic and real data examples based on logarithmic waveform inversion. Numerical examples for synthetic and real field data demonstrate that the three frequency-selection methods provide solutions closer to the global minimum compared to solutions resulting from simultaneously performed waveform inversion, and that the individual-grouping method yields slightly better resolution for the velocity models than the other methods, particularly for the deeper part. These results may imply that using either too small or too large data sets at every stage slightly deteriorates inversion results, and that grouping data in appropriately sized aggregations improves inversion results.     

Electrokinetic Restoration of Sulfate‐Accumulated Saline Greenhouse Soil

Electrokinetic (EK) process was performed to restore sulfate‐originated saline soil and to evaluate the effect of treatment duration. Sulfate and potassium were the major ionic salts in the saline soil used in this study. A constant voltage gradient of 1 V/cm was applied for 8, 12, and 16 days. After EK treatment, anions and cations were transported toward anode and cathode, respectively, by electromigration. Chloride was completely removed, and 85.6% of nitrate was removed after 8 days of treatment. The increase of treatment period from 8 to 12 days had a negligible effect on the enhancement in the rate of sulfate removal; however, over 70% was removed after16 days. At the end of experiment, the electrical conductivity (EC) of the soil, an indicator of soil salinity, decreased to 1.93 dS/m from an initial value of 5.3 dS/m, and the distribution of sulfate was similar to that of EC. The operation time of 16 days was sufficient to restore the sulfate‐originated saline soil using the EK process.     

Statistical multisite simulations of summertime precipitation over South Korea and its future change based on observational data

In this study, a weather generator for summer (May 19 – September 15) precipitation over South Korea is developed. Precipitation data for 33 years (1979–2011) observed at 57 stations of Korea Meteorological Administration (KMA) are used to develop a new weather generator. Using the cyclostationary empirical orthogonal function (CSEOF) technique, the observed precipitation data is described as a linear combination of deterministic evolution patterns and corresponding stochastic amplitude (principal component) time series. An autoregressive-moving average (ARMA) model is used to generate one hundred sets of synthetic amplitude time series for the period of 1979–2061 (83 years) with similar statistical properties of the original amplitude time series. Based on these synthetic time series and the annually repeating evolution patterns, one hundred sets of synthetic summer precipitation were generated. Statistical characteristics of the synthetic datasets are examined in comparison with those of the KMA observational record for the period of the observational record. Characteristic changes of synthetic precipitations for a future period are also examined. The seasonal cycle in the synthetic precipitation is reproduced faithfully with typical bimodal peaks of summer precipitation. The spatial correlation patterns of the synthetic precipitation are fairly similar to that of the observational data. The frequency-intensity relationship of the synthetic precipitation also looks similar to that of the observational data. In the future period, precipitation amount increases except in the precipitation range of (0,10) mm day^?1 with nearly no change in the frequency of no-rain days; frequency increase is particularly conspicuous in the range of (100,500) mm day^?1.     

A study on the measurement and analysis of radioactivity concentration and the ambient dose rate in soil on the playgrounds of elementary schools in the Gwangju area

The aim of this study was to obtain nationwide basic data on the distribution of environmental radiation in normal times and to compare the characteristics and distribution in many areas. The data obtained can contribute to improve the radioactivity analysis technology, public health, and the environment in the future. Ten elementary schools in the Gwangju area were selected and soil samples were taken from the playgrounds of the selected schools for analysis. A high-purity Ge (HPGe) semiconductor detector, a multi-channel analyzer (MCA), and a FH40G dose rate detector were used to measure the radioactivity concentration of K-40 and Cs-137, and the ambient gamma dose rate. According to the measured radioactivity concentrations of ⁴⁰K and ¹³⁷Cs, the K-40 concentration (Bq/kg dry) was measured at 723.61 ± 162.72, which was higher than the minimum detection limit (MDL). The Cs-137 concentration (Bq/kg dry) measured was 0.203 ± 0.023, which was lower than the MDL. FH40G was used to measure the ambient gamma dose rate (nSv/h) in different areas. According to the measurement results, the ambient gamma dose rate was 176.73 ± 4.91. With regard to the correlation between the ambient gamma dose rate and radioactivity concentrations of ⁴⁰K and ¹³⁷Cs, ⁴⁰K showed a correlation coefficient with Cs-137 and the ambient gamma dose rate of ?0.36 and 0.124, respectively. ¹³⁷Cs revealed a correlation coefficient of 0.293 with an ambient gamma dose rate of ?0.210. In conclusion, the low correlation coefficient (<0.5) indicates no significant correlation between the ambient dose rate measurements of K-40 and ¹³⁷Cs.     

Spatial modeling of the highest daily maximum temperature in Korea via max-stable processes

This paper examines the annual highest daily maximum temperature （DMT） in Korea by using data from 56 weather stations and employing spatial extreme modeling. Our approach is based on max-stable processes （MSP） with Schlather＇s characterization. We divide the country into four regions for a better model fit and identify the best model for each region. We show that regional MSP modeling is more suitable than MSP modeling for the entire region and the pointwise generalized extreme value distribution approach. The advantage of spatial extreme modeling is that more precise and robust return levels and some indices of the highest temperatures can be obtained for observation stations and for locations with no observed data, and so help to determine the effects and assessment of vulnerability as well as to downscale extreme events.