Biological nitrate removal from water resources

During the recent decades, the increasing trends in nitrate ion concentration in ground water sources have meant more research to find effective procedures for the prevention of even more water contamination by nitrogen sources. In this study a pilot was designed to examine the application of biological method for eliminating nitrate from the water of well No.903 of Mehrabad Airport, Tehran, Iran. Design, installation and running processes were done from April to November 2003. A fixed biological bed containing five-centimeter trunk pipes 16 mm in diameter were installed in the reactor and the system was operated with upflow current. Instead of Methanol, Acetic acid was used as the carbon source because of its easier acceptance by the public, lower price and availability as well as easier storage. The pilot was run in different hydraulic retention times from 48 h up to one hour. Considering economical, operational and maintenance factors, retention time of 2 h was determined to be optimum, in which 77% nitrate removal was achieved. Considering a ratio of 2 for COD/N, inlet COD of about 140 mg/L and the optimum retention time, COD removal of about 80% is also accomplished in this process. The amount of nitrite concentration, pH values, COD and turbidity is also evaluated versus different hydraulic retention times.     

Accounting for spatial patterns of multiple geological data sets in geological thematic mapping using GIS-based spatial analysis

This paper presents a Geographic Information System (GIS)-based spatial analysis scheme to account for spatial patterns and association in geological thematic mapping with multiple geological data sets. The multi-buffer zone analysis, the main part of the present study, was addressed to reveal the spatial pattern around geological source primitives and statistical analysis based on a contingency table was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multiple geological data sets from Ogdong in Korea was carried out to illustrate application of this methodology. The results obtained from the case study indicated that some geochemical elements and residual magnetic anomaly dominantly affected spatial patterns of the mineral potential map in the study area and the dominant classes of input data layers were also extracted. This information on spatial patterns of multiple geological data sets around mines could be used as effective evidences for the interpretation of the integrated layer within GIS.     

Kernel Eigenspace Separation Transform for Subspace Anomaly Detection in Hyperspectral Imagery

This letter proposes a nonlinear version of the eigenspace separation transform (EST) for subspace anomaly detection in hyperspectral imaging. The EST is defined in terms of the eigenvectors of the difference correlation matrix (DCOR) obtained using the data from the two classes. Using ideas found in the machine learning literature (i.e., the kernel trick), a nonlinear version-kernel EST (KEST)-is achieved by expressing the DCOR in terms of dot products in feature space and replacing all dot products with a Mercer kernel function that is defined in terms of input data space. Experimental results indicate that KEST outperforms many other commonly used subspace anomaly detection algorithms.     

Climate change and its role in forecasting energy demand in buildings: A case study of Douala City,Cameroon

Journal of Earth System Science - The foremost role of a building is to assure the comfort of its occupants. The thermal comfort of a building depends on the outdoor climate and requires a demand...     

Development of the Operational Oceanographic System of Korea

Ocean Science Journal - The Korea Operational Oceanographic System (KOOS) was developed at the Korea Institute of Ocean Science and Technology (KIOST) to produce real-time forecasting and...     

Groundwater Impacts from the M5.8 Earthquake in Korea as Determined by Integrated Monitoring Systems

This paper describes the impacts of the M5.8(5.1) Gyeongju earthquakes on groundwater levels using data obtained from a unique coastal monitoring well. The monitoring strategy integrates conventional water level monitoring with periodic, continuous measurements of temperature and electrical conductivity (EC) within the water column of the well. Another important component of the monitoring system is a new instrument, the InterfacEGG, which is capable of dynamically tracking the freshwater-saltwater interface. Although the system was set up to monitor seawater intrusion related to over-pumping, as well as rainfall and tidal effects, it recorded impacts associated with a large earthquake and aftershocks approximately 241 km away. Seismic energies associated with the M5.8(5.1) Gyeongju earthquakes induced groundwater flows to the monitoring well through fractures and joints in the crystalline basement rocks. Temperature and EC logging data showed that the EC vertical profile declined from an average of approximately 5300 to 4800 μS/cm following the earthquakes. The temperature profile showed a trend toward lower temperatures as the depth increased, a feature not commonly observed in previous studies. Data from the InterfacEGG suggested that the rise in EC was not due to the saltwater intrusion, but from the tendency for brackish water entering the borehole to induce convective mixing at deeper depths as the seismic waves travel through the well-aquifer system. The increase in groundwater levels was caused by pulse of colder, less brackish water flowing into the well because of the earthquake. This behavior reflects an enhancement in rock permeability by removing precipitates and colloidal particles from clogged fractures, which improve the hydraulic connection with a nearby unit with a higher hydraulic head. This study suggests there is value added with a more aggressive monitoring strategy.     

Improved Chlorophyll-a Algorithm for the Satellite Ocean Color Data in the Northern Bering Sea and Southern Chukchi Sea

The Bering and Chukchi seas are an important conduit to the Arctic Ocean and are reported to be one of the most productive regions in the world’s oceans in terms of high primary productivity that sustains large numbers of fishes, marine mammals, and sea birds as well as benthic animals. Climate-induced changes in primary production and production at higher trophic levels also have been observed in the northern Bering and Chukchi seas. Satellite ocean color observations could enable the monitoring of relatively long term patterns in chlorophyll-a (Chl-a) concentrations that would serve as an indicator of phytoplankton biomass. The performance of existing global and regional Chl-a algorithms for satellite ocean color data was investigated in the northeastern Bering Sea and southern Chukchi Sea using in situ optical measurements from the Healy 2007 cruise. The model-derived Chl-a data using the previous Chl-a algorithms present striking uncertainties regarding Chl-a concentrations – for example, overestimation in lower Chl-a concentrations or systematic overestimation in the northeastern Bering Sea and southern Chukchi Sea. Accordingly, a simple two band ratio (R_rs(443)/R_rs(555)) algorithm of Chl-a for the satellite ocean color data was devised for the northeastern Bering Sea and southern Chukchi Sea. The MODIS-derived Chl-a data from July 2002 to December 2014 were produced using the new Chl-a algorithm to investigate the seasonal and interannual variations of Chl-a in the northern Bering Sea and the southern Chukchi Sea. The seasonal distribution of Chl-a shows that the highest (spring bloom) Chl-a concentrations are in May and the lowest are in July in the overall area. Chl-a concentrations relatively decreased in June, particularly in the open ocean waters of the Bering Sea. The Chl-a concentrations start to increase again in August and become quite high in September. In October, Chl-a concentrations decreased in the western area of the Study area and the Alaskan coastal waters. Strong interannual variations are shown in Chl-a concentrations in all areas. There is a slightly increasing trend in Chl-a concentrations in the northern Bering Strait (SECS). This increasing trend may be related to recent increases in the extent and duration of open waters due to the early break up of sea ice and the late formation of sea ice in the Chukchi Sea.     

Present climate simulation over Korea with a regional climate model using a one-way double-nested system

Summary This study investigates the capability of the regional climate model RegCM3 to simulate surface air temperature and precipitation over the Korean Peninsula. The model is run in one-way double nested mode, with a 60 km grid point spacing “mother” domain encompassing the eastern regions of Asia and a 20 km grid point spacing nested domain covering the Korean Peninsula. The simulation spans the three-year period of 1 October 2000 through 30 September 2003 and the boundary conditions needed to run the mother domain experiment are provided from the NCEP reanalysis of observations. The model results are compared with a high density station observation dataset to examine the fine scale structure of the surface climate signal. The model shows a good performance in capturing both the sign and magnitude of the seasonal and inter-annual variations of the surface variables both over East Asia as a whole and over the Korean Peninsula in the nested system. Some persistent biases are however present. Surface temperature is systematically underestimated, especially over mountainous regions in the warm season. This feature may be due to the relatively coarse representation of the Korean topography. The simulated precipitation over the mother domain successfully reproduces the broad spatial pattern of observed precipitation over East Asia along with its seasonal evolution. On the other hand, fine scale details from the nested results show a varying level of quality for the different individual years. Because of the better resolved topographic forcing, the increased resolution of the nested model improves the spatial agreement with the fine scale observation fields for temperature and cold season precipitation. For summer monsoon precipitation the simulation of individual monsoon convective events and tropical storms is however more important than the topographic forcing, and therefore the performance of the nested system is more case-dependent.     

Impact of Turbulent Mixing in the Stratocumulus-Topped Boundary Layer on Numerical Weather Prediction

The impact of enhanced turbulent mixing induced by radiative cooling at the top of the stratocumulus-topped boundary layer (STBL) on numerical weather prediction is examined. An additional term involving top-down turbulent mixing via in-cloud radiative cooling is applied to the Yonsei University (YSU) planetary boundary layer (PBL) parameterization scheme using a top-down diffusivity profile and cloud-top entrainment. The modified scheme is evaluated in an advection fog case over the Yellow Sea of Korea using the Weather Research and Forecasting (WRF) model and in global medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). In the fog case simulation, consideration of the additional top-down mixing parameterization in the YSU PBL simulates less formation and more rapid dispersion of the fog. As a result, the modified scheme simulates a drier and warmer boundary layer and a moister and cooler layer above the PBL. The modified algorithm also improves surface temperature prediction over the Yellow Sea accompanying early dissipation of the fog. In the global medium-range forecast experiment, the modified scheme simulates overall enhanced PBL mixing over the STBL in the tropics and subtropical ocean, showing drier and warmer regions near the surface and moister and cooler regions above the PBL, resulting in prediction of reduced low level cloud amount and increased downward shortwave radiation at the surface. The modified scheme appears to improve systematic bias in temperature and humidity in the lower troposphere compared to the control simulation.     

Development of an Observation Processing Package for Data Assimilation in KIAPS

A new observation processing system, the Korea Institute of Atmospheric Prediction Systems (KIAPS) Package for Observation Processing (KPOP), has been developed to provide optimal observation datasets to the data assimilation (DA) system for the Korean Integrated Model, KIM. This paper presents the KPOP’s conceptual design, how the principal modules have been developed, and some of their preliminary results. Currently, the KPOP is capable of processing almost all observation types used by the Korea Meteorological Administration (KMA) and some new observation types that have a positive impact in other operational centers. We have developed an adaptive bias correction (BC) method that only uses the background of the analysis time and selects the best observations through the consecutive iteration of BC and quality control (QC); it has been verified that this method will be the best suited for the KIAPS DA system until the development of variational BC (VarBC) has been completed. The requirement of considering the radiosonde balloon drift in the DA according to the increase of spatial resolution of the NWP model was accounted for using a balloon drift estimation method that considers the pressure difference and wind speed; thus the distance error was less than 1% in the sample test. Some kind of widely used methods were tested for height adjustment of the SURFACE observation, and a new method for temperature adjustment was outlined that used the correlation between temperature and relative humidity. In addition, three types of map projection were compared: the cubed-sphere (CS), equidistance (ED), and equirectangular (ER) projection for thinning. Data denial experiments were conducted to investigate how the KPOP affected the quality of the analysis fields in the three-dimensional variational data assimilation system (3D-Var). Qualified observations produced by the KPOP had a positive impact by reducing the analysis error.