Mineralogical and geochemical characterization of precipitates on stream receiving acid mine water, Korea

Seasonal variations of water chemistry occurred in acid mine drainage receiving mine and leachate water. Sulfate and metal concentrations were low in winter but high in spring and summer. Mine waters were highly acidic (up to pH 3.4) in nature with high concentrations of manganese, copper and zinc but high electrical conductivity and sulfate in leachate. The blue and brownish yellow precipitates were formed under different chemical environments of acid mine drainage. Brownish yellow (Munsell color 7.5YR 8/12), blue (Munsell color 2.5B 9/7) and light blue (Munsell color 2.5B 9/3) precipitates deposited on the stream bottom receiving acid mine water. The brownish yellow precipitates formed in the acid mine water, whereas the blue and light blue precipitates formed in the leachate water. The brownish yellow precipitates consisted mainly of ferrihydrite, whereas the blue and light blue precipitates consisted of glaucocerinite and/or woodwardite.     

Sequential extraction and leaching characteristics of heavy metals in abandoned tungsten mine tailings sediments

The chemical speciation of potentially toxic elements (As, Cd, Cu, Pb, and Zn) in the contaminated soils and sulfides-rich tailings sediments of an abandoned tungsten mine in Korea was evaluated by conducting modified BCR sequential extraction tests. Kinetic and static batch leaching tests were also conducted to evaluate the potential release of As and other heavy metals by acidic rain water and the leaching behaviors of these heavy metals. The major sources of the elements were As-, Zn- and Pb-bearing sulfides, Pb carbonates (i.e., cerussite), and Pb sulfates (i.e., anglesite). The biggest pollutant fraction in these soil and tailing samples consists of metals bound to the oxidizable host phase, which can be released into the environment if conditions become oxidative, and/or to residual fractions. No significant difference in total element concentrations was observed between the tailings sediments and contaminated soils. For both sample types, almost no changes occurred in the mobility of As and the other heavy metals at 7 days, but the mobility increased afterwards until the end of the tests at 30 days, regardless of the initial pH. However, the mobility was approximately 5–10 times higher at initial pH 1.0 than at initial pHs of 3.0 and 5.0. The leached amounts of all the heavy metal contents were higher from tailings sediments than from contaminated soils at pH > 3.0, but were lower at pH < 3.0 except for As. Results of this study suggest that further dissolution of heavy metals from soil and tailing samples may occur during extended rainfall, resulting in a serious threat to surface and groundwater in the mine area.     

Cu(II) adsorption at the calcite-water interface in the presence of natural organic matter: Kinetic studies and molecular-scale characterization

We have characterized the adsorption of Suwannee River humic acid (SRHA) and Cu(II) on calcite from preequilibrated solutions at pH 8.25. Sorption isotherms of SRHA on calcite follow Langmuir-type behavior at SRHA concentrations less than 15 mg C L⁻¹, whereas non-Langmuirian uptake becomes evident at concentrations greater than 15 mg C L⁻¹. The adsorption of SRHA on calcite is rapid and mostly irreversible, with corresponding changes in electrostatic properties. At pH 8.25, Cu(II) uptake by calcite in the presence of dissolved SRHA decreases with increasing dissolved SRHA concentration, suggesting that formation of Cu-SRHA aqueous complexes is the primary factor controlling Cu(II) sorption at the calcite surface under the conditions of our experiments. We also observed that surface-bound SRHA has little influence on Cu(II) uptake by calcite, suggesting that Cu(II) coordinates to calcite surface sites rather than to surface-bound SRHA.Cu K-edge X-ray absorption near edge structure (XANES) and extended X-ray absorption fine-structure (EXAFS) spectroscopic results show that the local coordination of Cu adsorbed at the calcite surface is very similar in the presence and absence of SRHA. Ca backscatterers at ∼3.90 Å indicate that Cu(II) forms tetragonally distorted inner-sphere adsorption complexes in both binary and ternary systems. Subtle differences in the XANES and EXAFS between binary sorption samples and ternary sorption samples, however, prevent us from ruling out the formation of ternary Cu-SRHA surface complexes. Our findings demonstrate that SRHA plays an important role in controlling the fate and transport of Cu(II) in calcite-bearing systems.     

A Closure Study of Aerosol Hygroscopic Growth Factor during the 2006 Pearl River Delta Campaign

Measurements of aerosol physical, chemical and optical parameters were carried out in Guangzhou, China from 1 July to 31 July 2006 during the Pearl River Delta Campaign. The dry aerosol scattering coefficient was measured using an integrating nephelometer and the aerosol scattering coefficient for wet conditions was determined by subtracting the sum of the aerosol absorption coefficient, gas scattering coefficient and gas absorption coefficient from the atmospheric extinction coefficient. Following this, the aerosol hygroscopic growth factor, f(RH), was calculated as the ratio of wet and dry aerosol scattering coefficients. Measurements of size-resolved chemical composition, relative humidity (RH), and published functional relationships between particle chemical composition and water uptake were likewise used to find the aerosol scattering coefficients in wet and dry conditions using Mie theory for internally- or externally-mixed particle species [(NH₄)₂SO₄, NH₄NO₃, NaCl, POM, EC and residue]. Closure was obtained by comparing the measured f(RH) values from the nephelometer and other in situ optical instruments with those computed from chemical composition and thermodynamics. Results show that the model can represent the observed f(RH) and is appropriate for use as a component in other higher-order models.     

Statistical prediction of heavy rain in South Korea

1. Introduction In recent decades, extreme weather events seem to be growing in frequency and risk due to water-related disasters. According to the World Meteorological Or- ganization report (ISDR and WMO, 2004) on World Water Day, 22 March 2004, the economic losses caused by water-related disasters, including floods, droughts and tropical cyclones, are on an increasing trend as follows: the yearly mean in the 1970s was about 131 billion US dollars, 204 billion dollars in the 1980s, and …     

Impact of vegetation feedback on the temperature and its diurnal range over the Northern Hemisphere during summer in a 2 × CO2 climate

This study examines the potential impact of vegetation feedback on the changes in the diurnal temperature range (DTR) due to the doubling of atmospheric CO₂ concentrations during summer over the Northern Hemisphere using a global climate model equipped with a dynamic vegetation model. Results show that CO₂ doubling induces significant increases in the daily mean temperature and decreases in DTR regardless of the presence of the vegetation feedback effect. In the presence of vegetation feedback, increase in vegetation productivity related to warm and humid climate lead to (1) an increase in vegetation greenness in the mid-latitude and (2) a greening and the expansion of grasslands and boreal forests into the tundra region in the high latitudes. The greening via vegetation feedback induces contrasting effects on the temperature fields between the mid- and high-latitude regions. In the mid-latitudes, the greening further limits the increase in T _max more than T _min, resulting in further decreases in DTR because the greening amplifies evapotranspiration and thus cools daytime temperature. The greening in high-latitudes, however, it reinforces the warming by increasing T _max more than T _min to result in a further increase in DTR from the values obtained without vegetation feedback. This effect on T _max and DTR in the high latitude is mainly attributed to the reduction in surface albedo and the subsequent increase in the absorbed insolation. Present study indicates that vegetation feedback can alter the response of the temperature field to increases in CO₂ mainly by affecting the T _max and that its effect varies with the regional climate characteristics as a function of latitudes.     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 mass (21.5 μg m^− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM_2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.     

Temperature trends in the skin/surface, mid-troposphere and low stratosphere near Korea from satellite and ground measurements

Various types of satellite (AIRS/AMSU, MODIS) and ground measurements are used to analyze temperature trends in the four vertical layers (skin/surface, mid-troposphere, and low stratosphere) around the Korean Peninsula (123–132°E, 33–44°N) during the period from September 2002 to August 2010. The ground-based observations include 72 Surface Meteorological Stations (SMSs), 6 radiosonde stations (RAOBs), 457 Automatic Weather Stations (AWSs) over the land, and 5 buoy stations over the ocean. A strong warming (0.052 K yr^?1) at the surface, and a weak warming (0.004～0.010 K yr^?1) in the mid-troposphere and low stratosphere have been found from satellite data, leading to an unstable atmospheric layer. The AIRS/AMSU warming trend over the ocean surface around the Korean Peninsula is about 2.5 times greater than that over the land surface. The ground measurements from both SMS and AWS over the land surface of South Korea also show a warming of 0.043～0.082 K yr^?1, consistent with the satellite observations. The correlation average (r = 0.80) between MODIS skin temperature and ground measurement is significant. The correlations between AMSU and RAOB are very high (0.91～0.95) in the anomaly time series, calculated from the spatial averages of monthly mean temperature values. However, the warming found in the AMSU data is stronger than that from the RAOB at the surface. The opposite feature is present above the mid-troposphere, indicating that there is a systematic difference. Warming phenomena (0.012～0.078 K yr^?1) are observed from all three data sets (SMS, AWS, MODIS), which have been corroborated by the coincident measurements at five ground stations. However, it should also be noted that the observed trends are subject to large uncertainty as the corresponding 95% confidence intervals tend to be larger than the observed signals due to large thermal variability and the relatively short periods of the satellitebased temperature records. The EOF analysis of monthly mean temperature anomalies indicates that the tropospheric temperature variability near Korea is primarily linked to the Arctic Oscillation (AO), and secondarily to ENSO (El Niño and Southern Oscillation). However, the low stratospheric temperature variability is mainly associated with Southern Oscillation and then additionally with Quasi-Biennial Oscillation (QBO). Uncertainties from the different spatial resolutions between satellite data are discussed in the trends.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

Observations of boundary-layer convection cells measured by dual-Doppler radar and echosonde,and by microbarograph array

Three-dimensional air motion, observed with radar in a convective planetary boundary layer under light wind conditions, is organized in cellular structures scaled from 2 to 5 km; simultaneous acoustic echosonde measurements indicate that near the ground there are smaller cells than those observable by the radar. At heights of 400 m, cell scales become as large as those observable by the radar. Pressure fluctuations at the ground measured with spatial pressure transducers, at the same time as the radar and echosonde observations, traveled at the same speed and direction as the radar volume-averaged wind. The length scale determined at the ground with pressure fluctuation data was between 1.2 and 2.4 km, smaller than the largest radar-measured motion scales.