A successful transformation of conventional SBR to MBR at Indian casino and facility: a case study of Chumash Casino and Resort Water Reclamation Facility (WRF), water reuse perspectives

A conventional sequencing batch reactor (SBR) was successfully transformed to a membrane bioreactor (MBR) at an Indian casino resort and hotel, Santa Ynez, California. The technical difficulties from the existing process at the site including a 3-mm screening unit, SBR biological tanks, and sand filtration were relieved of by new biological membrane technology. As the hotel and its vicinity expanded, the existing SBR was not able to treat an increased flow, which was major driving force for such membrane-upgraded project. In addition, as the area was in a high drought zone, without meeting the purpose of water reuse, new hotel expansion was not permitted. New membrane process was designed and built with new 2-mm screening unit, pre-anoxic, oxic (or aerobic), post-anoxic, and MBR tanks along with UV disinfection. The retrofitting work was conducted, minimizing a major revision on the existing SBR structure and its civil work. Therefore, the new packaged system has brought a number of benefits to the customer, thereby utilizing reclaimed water highly meeting the California Code of Regulations (CCR) Title 22 requirements. The reclaimed water goes to toilet water, cooling tower, and irrigation. This study details how such process transformation was technically finished and would help other similar cases in terms of retrofitting exiting biological process to a membrane application without a major civil construction. The cost analysis including capital, operation and maintenance (O&M) costs was included so that it will be practical to ones who will conduct future similar projects.     

Interrelationship between geochemical elements of sediment and groundwater at Samrak Park Delta of Nakdong River Basin in Korea: multivariate statistical analyses and artificial neural network approaches

This research was conducted at Samrak Park Delta of Nakdong River Basin in Busan Metropolitan City, Korea. The main objective of this study was to evaluate the interrelationship of geochemical elements in sediments and groundwater through multivariate statistical analyses and a multilayer perceptron artificial neural network model. The mean concentrations of chemical elements were Si (46%), Fe (16.9%), Al (15.7%), K (7.5%) and Ca (4.5%) in sediments, and Na (8650 mg/L), Mg (999 mg/L), Ca (432 mg/L), K (293 mg/L) and Cl (17,640 mg/L) in groundwater, respectively. The principal component analysis produced 3 kinds of factors with the variances of 63.37, 27.02 and 9.62%, respectively. It is suggested that the chemical components of sediments and groundwater were mainly originated from source rocks and seawater intrusion, with the minor impacts of irrigation and industry. Cluster analysis also showed that chemical elements were mainly controlled by the natural geogenic sources and seawater intrusion. Multilayer perceptron of artificial neural network (ANN) presented the good interrelationship between sediment and groundwater. The determination coefficients (R ²) between ANN predicted values and observed values in groundwater showed the high values of 0.61–0.97 except Mg, Mn and Sr. It is revealed that the chemical components of sediment and groundwater were derived from local geological origin and from the minor impact of anthropogenic sources. Multivariate analyses and ANN contributed to the identification of the mutual relationship between the geochemical elements of sediment and those of groundwater.     

Solar-activity cycle from observations of magnetic characteristics of prominences

According to measurements of the magnetic fields in quiescent prominences carried out by different teams in 1964–1989, the maximum values of the field correspond to the minimum values of the Wolf numbers averaged through the corresponding periods of observations. It has been shown that the synoptic noneclipse 2D linear polarimetry of quiescent Hα-prominences can be actually implemented; this method is based on the use of a coronagraph with a primary-optics diameter equal to or larger than 100 mm, a narrow-band filter with FWHM ≤ 0.4 nm, a standard linear polariod, and a high-precision linear polarimetric technique.     

Numerical Modeling of Ice Fog in Interior Alaska Using the Weather Research and Forecasting Model

An ice microphysics parameterization scheme has been modified to better describe and understand ice fog formation. The modeling effort is based on observations in the Sub-Arctic Region of Interior Alaska, where ice fog occurs frequently during the cold season due to abundant water vapor sources and strong inversions existing near the surface at extremely low air temperatures. The microphysical characteristics of ice fog are different from those of other ice clouds, implying that the microphysical processes of ice should be changed in order to generate ice fog particles. Ice fog microphysical characteristics were derived with the NCAR Video Ice Particle Sampler during strong ice fog cases in the vicinity of Fairbanks, Alaska, in January and February 2012. To improve the prediction of ice fog in the Weather Research and Forecasting model, observational data were used to change particle size distribution properties and gravitational settling rates, as well as to implement a homogeneous freezing process. The newly implemented homogeneous freezing process compliments the existing heterogeneous freezing scheme and generates a higher number concentration of ice crystals than the original Thompson scheme. The size distribution of ice crystals is changed into a Gamma distribution with the shape factor of 2.0, using the observed size distribution. Furthermore, gravitational settling rates are reduced for the ice crystals since the crystals in ice fog do not precipitate in a similar manner when compared to the ice crystals of cirrus clouds. The slow terminal velocity plays a role in increasing the time scale for the ice crystals to settle to the surface. Sensitivity tests contribute to understanding the effects of water vapor emissions as an anthropogenic source on the formation of ice fog.     

Climate change signal analysis for Northeast Asian surface temperature

Climate change detection, attribution, and prediction were studied for the surface temperature in the Northeast Asian region using NCEP/NCAR reanalysis data and three coupled-model simulations from ECHAM4/OPYC3, HadCM3, and CCCma GCMs (Canadian Centre for Climate Modeling and Analysis general circulation model). The Bayesian fingerprint approach was used to perform the detection and attribution test for the anthropogenic climate change signal associated with changes in anthropogenic carbon dioxide (CO2) and sulfate aerosol (SO42-) concentrations for the Northeast Asian temperature. It was shown that there was a weak anthropogenic climate change signal in the Northeast Asian temperature change. The relative contribution of CO2 and SO42- effects to total temperature change in Northeast Asia was quantified from ECHAM4/OPYC3 and CCCma GCM simulations using analysis of variance. For the observed temperature change for the period of 1959-1998, the CO2 effect contributed 10%-21% of the total variance and the di     

What is responsible for increasing flood risks? The case of Gangwon Province,Korea

We examined the anthropogenic and natural causes of flood risks in six representative cities in the Gangwon Province of Korea. Flood damage per capita is mostly explained by cumulative upper 5% summer precipitation amount and the year. The increasing flood damage is also associated with deforestation in upstream areas and intensive land use in lowlands. Human encroachment on floodplains made these urban communities more vulnerable to floods. Without changes in the current flood management systems of these cities, their vulnerability to flood risks will remain and may even increase under changing climate conditions.     

Sensitivity of MM5 and WRF mesoscale model predictions of surface winds in a typhoon to planetary boundary layer parameterizations

Sea surface winds and coastal winds, which have a significant influence on the ocean environment, are very difficult to predict. Although most planetary boundary layer (PBL) parameterizations have demonstrated the capability to represent many meteorological phenomena, little attention has been paid to the precise prediction of winds at the lowest PBL level. In this study, the ability to simulate sea winds of two widely used mesoscale models, fifth-generation mesoscale model (MM5) and weather research and forecasting model (WRF), were compared. In addition, PBL sensitivity experiments were performed using Medium-Range Forecasts (MRF), Eta, Blackadar, Yonsei University (YSU), and Mellor–Yamada–Janjic (MYJ) during Typhoon Ewiniar in 2006 to investigate the optimal PBL parameterizations for predicting sea winds accurately. The horizontal distributions of winds were analyzed to discover the spatial features. The time-series analysis of wind speed from five sensitivity experimental cases was compared by correlation analysis with surface observations. For the verification of sea surface winds, QuikSCAT satellite 10-m daily mean wind data were used in root-mean-square error (RMSE) and bias error (BE) analysis. The MRF PBL using MM5 produced relatively smaller wind speeds, whereas YSU and MYJ using WRF produced relatively greater wind speeds. The hourly surface observations revealed increasingly strong winds after 0300 UTC, July 10, with most of the experiments reproducing observations reliably. YSU and MYJ using WRF showed the best agreements with observations. However, MRF using MM5 demonstrated underestimated winds. The conclusions from the correlation analysis and the RMSE and BE analysis were compatible with the above-mentioned results. However, some shortcomings were identified in the improvements of wind prediction. The data assimilation of topographical data and asynoptic observations along coast lines and satellite data in sparsely observed ocean areas should make it possible to improve the accuracy of sea surface wind predictions.     

Analysis of resistivity data obtained from cone penetrometer in contaminated soil layers

In horizontally layered soils of different electrical properties, electrical potential distribution becomes complex and the obtained resistivity data may be limited in reflecting the actual soil profile. Thus the objective of this study was to identify the factors that affect resistivity measurement on the cone penetrometer and further investigate the sensitivity of measured resistivity to different types and concentrations of contaminants at the subsurface level. First, a theoretical resistivity equation was derived to provide a means of computing the geometric factor. The effective volume of measurement on the cone penetrometer was investigated and laboratory soil box tests verified the dominance of partially high resistivity regions within the effective volume of measurement over the apparent resistivity. Such effect was found to lead to possible discrepancies between the recorded resistivity data and the actual depth of measurement. Measurements on contaminated soil layers indicated that resistivity cones are efffective in delineating inorganic contaminants in soils of high water contents, and detecting NAPLs floating above the groundwater table provided that soils adjacent to the plume are not dry of water. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.