For almost 100 years, the Asarco Company op-erated a copper smelter in Tacoma, Washington State. Air pollution from the smelter settled on the surface soil over more than 2,600 square kilometers of the Puget Sound basin. As part of the Tacoma Smelter Plume project, there have been a number of studies looking at soil ar-senic contamination, leading to the collection of more than 5,000 surface soil samples over the years. The present study aimed to pool all of the sampling results to create a model that can be used to further prioritize areas for ad-ditional sampling and remediation since not enough money is available to clean all residential parcels. This paper de-scribes a geostatistical simulation-based approach to com-pute for each block-group the expected number of residen-tial parcels where a given arsenic concentration threshold is exceeded with a minimum probability. This informa-tion is being currently used to select widely contaminated block-groups where all residential parcels are systemati-cally sampled and the ones exceeding a target threshold of 100 ppm are remediated.
It has been recommended to carry out ther-mal response tests (TRT) for a period of minimum 48 hours when the measured data are used together with a linear approximation of Kelvin’s infinite fine source func-tion for heat transport in porous materials to estimate ap-parent thermal conductivity of the ground. Recently an asymptotic solution of the line source function has been proposed to reduce the estimation error. This study exam-ined the potential of the new solution to also reduce the TRT period, as the new solution in principle can be ap-plied to early (short-time) data. For this analysis, a one-dimensional convective-conductive heat transport equation was applied for the circulating fluid, and three-dimensional conductive heat transport equations were applied for the ground, the grout, and the heat exchangers, to simulate heat transport and exchange between circulating fluid and the ground during TRT. Fluid temperatures simulated un-der different conditions were then used to estimate appar-ent thermal conductivity using both the linear approxima-tion and the asymptotic solution of the line source function. Results showed that the TRT period can be reduced to less than 20 hours with an average error less than 5 % even in case of extreme thermal conductivity of grout, which can markedly affect early (short-time) TRT data. The con-clusion was confirmed when also using actual TRT data collected at ground source heat pump (GSHP) test sites at Tokyo University of Agriculture and Technology and Saitama University.
Rice paddy fields are a major anthropogenic source for methane (CH4),one of the dominant green-house gases (GHGs). Recently, micrometeorological tech-niques for measuring GHG flux in a fileld scale have been developed. We evaluated a relaxed eddy accumulation (REA) method, a micrometeorological technique, to mea-sure methane (CH4) flux in a rice paddy field during a flow-ering stage in Thailand. CH4 flux at the paddy water sur-face was also measured using the closed chambers installed where no rice plant was grown. The CH4 fluxes with the REA and closed chamber methods ranged between 1.9 mg m-2 h-1 and 43.6 mg m-2 h-1,agreed well with those pre-viously reported in Southeast Asia. The exchange rates of CH4 between the atmosphere and the rice canopy tended to get higher during the daytime, and seemed to be reg-ulated by the diurnal variations of horizontal wind speed and soil temperature. In addition, temporal changes in CH4 fluxes at the water surface might be affected by soil tem-perature. The CH4 fluxes measured with the REA method were higher than those with the closed chamber method.
It appears that the REA method measured CH4 fluxes over rice plant canopy and the water surface whereas the closed chamber method did only over the water surface.
This study proposed a simple CO2 gas analyz-ing system for soil gas samples. The system consisted of a portable infrared-sensing CO2 probe with an RS232C-type interface and a personal computer. A free-software was used to collect signal outputs from the probe and store the output data in the computer. The calibration of the system gave a definite linear relationship between the outputs from the system and the actual CO2 concentrations of gas sam-ples. The calibration did not depend on temperature. Ef-fects of the sampling time on the CO2 concentrations were also quantified. Although the measured values linearly de-creased 1 to 2 % due to time-lag between gas sampling and gas analysis, it is possible to correct the measured values if the linear reduction was evaluated in advance.