Seasonal variation of microbial populations and biomass in Tatachia grassland soils of Taiwan

To investigate the seasonal variations of microbial ecology in grassland of Tatachia forest, soil properties, microbial populations, microbial biomass, and 16S rDNA clone library analysis were determined. The soil had temperatures 6.6–18.4°C, pH 3.6–5.1, total organic carbon 1.11–10.68%, total nitrogen 0.18–0.78%, and C/N ratios 3.46–20.55. Each gram of dry soil contained bacteria, actinomycetes, fungi, cellulolytic, phosphate-solubilizing microbes, and nitrogen-fixing microbes 4.54 × 10⁴ to 3.79 × 10⁷, 3.43 × 10² to 2.17 × 10⁵, 5.74 × 10³ to 3.76 × 10⁶, 1.97 × 10³ to 1.34 × 10⁶, 8.49 × 10² to 5.59 × 10⁵, and 3.86 × 10² to 3.75 × 10⁵ CFU, respectively. Each gram of soil contained 117–2,482 μg of microbial biomass carbon, 23–216 μg of microbial biomass nitrogen and 9–29 μg of DNA. The microbial populations, microbial biomass, and DNA decreased stepwise with the depth of soil, and they had low values in winter seasons. The microbial populations, microbial biomass carbon, microbial biomass nitrogen, and DNA at the BW2 horizon were 8.42–17.84, 19.26–64.40, 16.84–61.11, and 31.03–46.26% of those at the O horizon, respectively. When analyzing 16S rDNA library, members of Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, candidate division TM1, candidate division TM7, Gammatimonadetes, and Verrucomicrobia were identified. Members of Proteobacteria (44.4%) and Acidobacteria (33.3%) dominated the clone libraries. Within the phylum Proteobacteria, α-, β-, and γ-Proteobacteria were most numerous, followed by δ-Proteobacteria.     

DEVELOPMENT OF A GIS‐BASED FLOOD INFORMATION SYSTEM FOR FLOODPLAIN MODELING AND DAMAGE CALCULATION1

ABSTRACT: This work presents a flexible system called GIS‐based Flood Information System (GFIS) for floodplain modeling, flood damages calculation, and flood information support. It includes two major components, namely floodplain modeling and custom designed modules. Model parameters and input data are gathered, reviewed, and compiled using custom designed modules. Through these modules, it is possible for GFIS to control the process of flood‐plain modeling, presentation of simulation results, and calculation of flood damages. Empirical stage‐damage curves are used to calculate the flood damages. These curves were generated from stage‐damage surveys of anthropogenic structures, crops, etc., in the coastal region of a frequently flooded area in Chia‐I County, Taiwan. The average annual flood damages are calculated with exceedance probability and flood damages for the designed rainfalls of 2, 5, 10, 25, 50, 100, and 200 year recurrence intervals with a duration of 24 hours. The average annual flood depth in this study area can also be calculated using the same method. The primary advantages of GFIS are its ability to accurately predict the locations of flood area, depth, and duration; calculate flood damages in the floodplain; and compare the reduction of flood damages for flood mitigation plans.     

SPECTRAL ANALYSIS OF TIDAL FLUCTUATIONS IN GROUND WATER LEVEL1

ABSTRACT: Water level data at 16 ground water wells and two sea water gauging stations, coupled with barometric measurements in an alluvial plain in the central‐west region of Taiwan, are analyzed using spectral analysis in the time and frequency domains. The semi‐diurnal component from water level station is observed to be the most noticeable signal while the diurnal component is the less distinct signal recorded at the water level stations. Both semidiurnal and diurnal components are coupled with atmospheric pressure measurements. From the atmospheric pressure data, spectral analysis indicates that both the raw and the pressure adjusted water levels are almost in phase and retain the same amplitude in this area. It implies that the effect of pressure variations is not significant for the sea water and ground water level nearby; the astronomical tidal components, as expected, are the main factor causing fluctuation of ocean water and ground water levels in the Choshuihsi alluvial plain.     

Risk for estrogen-dependent diseases in relation to phthalate exposure and polymorphisms of CYP17A1 and estrogen receptor genes

Evidence has shown that polymorphisms of various genes known to be involved in estrogen biosynthesis and function are associated with estrogen-dependent diseases (EDDs). These genes include CYP17A1, estrogen receptor 1 (ESR1), and 2 (ESR2). Phthalates are considered estrogenic endocrine disruptors, and recent research has suggested that they may act as a risk factor for EDDs. However, extremely few studies have assessed the effects of gene–environment interaction on these diseases. We recruited 44 patients with endometriosis or adenomyosis, 36 patients with leiomyoma, and 69 healthy controls from a medical center in Taiwan between 2005 and 2007. Urine samples were collected and analyzed for seven phthalate metabolites using liquid chromatography tandem mass spectrometry. Peripheral lymphocytes were used for DNA extraction to determine the genotype of CYP17A1, ESR1, and ESR2. Compared to controls, patients with leiomyoma had significantly higher levels of total urinary mono-ethylhexyl phthalate (ΣMEHP) (52.1 vs. 29.6 μg/g creatinine, p?=?0.040), mono-n-butyl phthalate (MnBP) (75.4 vs. 51.3 μg/g creatinine, p?=?0.019), and monoethyl phthalate (MEP) (103.7 vs. 59.3 μg/g creatinine, p?=?0.031). In contrast, patients with endometriosis or adenomyosis showed a marginally increased level of urinary MEHP only. Subjects who were homozygous for both the ESR1 C allele (rs2234693) and CYP17A1 C allele (rs743572) showed a significantly increased risk for leiomyoma (OR?=?19.8; 95 % CI, 1.70; 231.5; p?=?0.017) relative to subjects with other genotypes of ESR1 and CYP17A1. These results were obtained after adjusting for age, cigarette smoking, MEHP level, GSTM1 genotype and other covariates. Our results suggested that both CYP17A1 and ESR1 polymorphisms may modulate the effects of phthalate exposure on the development of leiomyoma.     

Product Guide/1982

Abstract

An efficient venturi scrubber system making use of heterogeneous nucleation and condensational growth of particles was designed and tested to remove fine particles from the exhaust of a local scrubber where residual SiH₄ gas was abated and lots of fine SiO₂ particles were generated. In front of the venturi scrubber, normal-temperature fine-water mist mixes with high-temperature exhaust gas to cool it to the saturation temperature, allowing submicron particles to grow into micron sizes. The grown particles are then scrubbed efficiently in the venturi scrubber. Test results show that the present venturi scrubber system is effective for removing submicron particles. For SiO₂ particles greater than 0.1 μm, the removal efficiency is greater than 80–90%, depending on particle concentration. The corresponding pressure drop is relatively low. For example, the pressure drop of the venturi scrubber is ～15.4 ± 2.4 cm H₂O when the liquid-to-gas ratio is 1.50 L/m³. A theoretical calculation has been conducted to simulate particle growth process and the removal efficiency of the venturi scrubber. The theoretical results agree with the experimental data reasonably well when SiO₂ particle diameter is greater than 0.1 μm.     

The Reuse of Biosludge as an Adsorbent from a Petrochemical Wastewater Treatment Plant

Abstract

Biosludge was obtained from a petrochemical industry’s biological wastewater treatment plant. Zinc chloride (ZnCl₂) was used as a sludge activation agent during the pyrolytic process. Scanning electron microscope (SEM) image photographs, element composition, surface functional group, and pore structure were analyzed for the sludge adsorbent characteristics. Results indicated the proper ZnCl₂-immersed concentration, pyrolytic temperature, and time could produce adsorbent from the bio-sludge. The optimal conditions for a larger surface area adsorbent were 3 M ZnCl₂-immersed sludge pyrolyzed at 600 °C for 30 min and washed with 3 N hydrochloric acid (HCl) solution and distilled water. The predominant pore size of the sludge adsorbent was the mesopore.     

Decomposition of SF6 in an RF Plasma Environment

Abstract

Sulfur hexafluoride (SF₆)-contained gas is a common pollutant emitted during the etching process used in the semiconductor industry. This study demonstrated the application of radio-frequency (RF) plasma in the decomposition of SF₆. The decomposition fraction of SF₆ [η_SF6 (C_in–C_out)/C_in x 100%] and the mole fraction profile of the products were investigated as functions of input power and feed O₂/SF₆ ratio in an SiO₂ reactor. The species detected in both SF₆/Ar and SF₆/O₂/Ar RF plasmas were SiF₄, SO₂, F₂, SO₂F₂, SOF₂, SOF₄, S₂F₁₀, S₂OF₁₀, S₂O₂F₁₀, and SF₄. The results revealed that at 40 W, η_SF6 exceeded 99%, and the reaction products were almost all converted into stable compounds such as SiF₄, SO₂, and F₂ with or without the addition of oxygen. Sulfur oxyfluorides such as SO₂F₂, SOF₂, SOF₄, S₂OF₁₀, and S₂O₂F₁₀ were produced only below 40 W. The results of this work can be used to design a plasma/chemical system for online use in a series of a manufacturing process to treat SF₆-containing exhaust gases.     

Simultaneous Sampling of Gas- and Aerosol-Phase TDI with a Triple Filter System

Abstract

A new triple filter system sampler/model is proposed for the precise and accurate simultaneous sampling and determination of gas- and aerosol-phase 2,4-toluene diisocyanate (TDI). The system consists of two front Teflon filters for sampling aerosol-phase TDI and a final coated glass fiber filter to collect gas-phase TDI. The aerosol-phase TDI is collected on the first Teflon filter, while the second Teflon filter is used to estimate gaseous TDI adsorbed by the first. According to the gas adsorption test of two Teflon filters in series, the TDI gas adsorption fraction of the two filters is almost the same. Results of the evaporation test using pure TDI aerosols collected on the Teflon filter show that significant evaporation of the compound does not occur during sampling. These two findings allow the use of a model to estimate accurate gasand aerosol-phase TDI concentrations. The comparison test with an annular denuder shows that the triple filter system can minimize the TDI sampling bias between the dual filter and the annular denuder systems.     

Inorganic Acid Emission Factors of Semiconductor Manufacturing Processes

Abstract

A huge amount of inorganic acids can be produced and emitted with waste gases from integrated circuit manufacturing processes such as cleaning and etching. Emission of inorganic acids from selected semiconductor factories was measured in this study. The sampling of the inorganic acids was based on the porous metal denuders, and samples were then analyzed by ion chromatography. The amount of chemical usage was adopted from the data that were reported to the Environmental Protection Bureau in Hsin-chu County according to the Taiwan Environmental Protection Agency regulation. The emission factor is defined as the emission rate (kg/month) divided by the amount of chemical usage (L/month). Emission factors of three inorganic acids (i.e., hydrofluoric acid [HF], hydrochloric acid [HQ], and sulfuric acid [H₂SO₄]) were estimated by the same method. The emission factors of HF and HCl were determined to be 0.0075 kg/L (coefficient of variation [CV] = 60.7%, n = 80) and 0.0096 kg/L (CV = 68.2%, n = 91), respectively. Linear regression equations are proposed to fit the data with correlation coefficient square (R²) = 0.82 and 0.9, respectively. The emission factor of H₂SO₄, which is in the droplet form, was determined to be 0.0016 kg/L (CV = 99.2%, n = 107), and its R² was 0.84. The emission profiles of gaseous inorganic acids show that HF is the dominant chemical in most of the fabricators.     

Integrated model of simulated occupant injury risk and real medical costs

Introduction

The purpose of this study was to develop an integrated methodology that links occupant injury risk functions, estimated in the laboratory, with real world medical treatment costs by using the abbreviated injury score (AIS). Using our model, the expected medical treatment costs for crash injuries to various body regions and of different severities can be investigated.

Methods

First, the simulation results are compared with NHTSA crash data. We used a modified kinematics simulation model that incorporates an F = E^b function as a supplement to the previous Steffan's model to obtain a more accurate acceleration history a(t). Second, head injury criteria HIC₃₆ can be calculated from a(t), and we use the injury probability P as a function of HIC_36, as proposed by Kuppa, to obtain the injury risk function for various AIS values. Third, medical treatment cost models for various AIS values can be calculated by using a regression cost model with real world data. Finally, the injury risk function and medical treatment cost models are linked through AIS values. We establish an integrated methodology and predict medical costs and car safety data using real world police reports, medical treatment costs, and laboratory simulation results.

Results

Using head injuries in frontal crashes as an example, we focus on simulation parameters for different vehicle models, with and without airbags. We specifically examine impact closing speed, Delta-V, and impact directions.

Conclusion

Simulation results can be used to supplement insufficient real crash data, in particular ΔV, and injury risk results from police crash reports.

Impact on industry

The proposed integrated methodology may provide the vehicle industry with a new safety assessment method. Real crash data coupling provides consumers with more realistic and applicable information.