Discovering meaningful information from large amounts of environment and health data to reduce uncertainties in formulating environmental policies

This study uses knowledge discovery concepts to analyze large amounts of data step by step for the purpose of assisting in the formulation of environmental policy. We performed data cleansing and extracting from existing nation-wide databases, and used regression and classification techniques to analyze the data. The current water hardness in Kaohsiung, Taiwan contributes to the prevention of cardiovascular disease (CVD) but exacerbates the development of renal stones (RS). However, to focus on water hardness alone to control RS would not be cost effective at all, because the existing database parameters do not adequately allow for a clear understanding of RS. Analysis of huge amounts of data can most often turn up the most reliable and convincing results and the use of existing databases can be cost-effective.     

Tillage and field scale controls on greenhouse gas emissions

There is a lack of understanding of how associations among soil properties and management-induced changes control the variability of greenhouse gas (GHG) emissions from soil. We performed a laboratory investigation to quantify relationships between GHG emissions and soil indicators in an irrigated agricultural field under standard tillage (ST) and a field recently converted (2 yr) to no-tillage (NT). Soil cores (15-cm depth) were incubated at 25 degrees C at field moisture content and 75% water holding capacity. Principal component analysis (PCA) identified that most of the variation of the measured soil properties was related to differences in soil C and N and soil water conditions under ST, but soil texture and bulk density under NT. This trend became more apparent after irrigation. However, principal component regression (PCR) suggested that soil physical properties or total C and N were less important in controlling GHG emissions across tillage systems. The CO2 flux was more strongly determined by microbial biomass under ST and inorganic N content under NT than soil physical properties. Similarly, N2O and CH4 fluxes were predominantly controlled by NO3- content and labile C and N availability in both ST and NT soils at field moisture content, and NH4+ content after irrigation. Our study indicates that the field-scale variability of GHG emissions is controlled primarily by biochemical parameters rather than physical parameters. Differences in the availability and type of C and N sources for microbial activity as affected by tillage and irrigation develop different levels and combinations of field-scale controls on GHG emissions.     

Comparison of preservation values between Internet and interview survey modes: the case of Dokdo,South Korea

With the increase in employment of Internet surveys, there is a need to address how this survey mode affects inferences. Internet and interview modes are compared in estimating the preservation value of Dokdo, South Korea. Estimates of willingness to pay in the Internet survey are smaller than those in the interview survey. This may be attributable to the interview respondents being conscious of the presence of the interviewers, given the social importance of Dokdo to Koreans. Internet surveys may be effective in reducing overestimation of the willingness to pay in situations where potential social desirability is present.     

Income and distance-decay effects on willingness to pay estimated by the contingent valuation method

This study suggests a methodology for enhancing accuracy in evaluating amenity by the contingent valuation method when household's willingness to pay (WTP) is dependent to its income and the distance between a respondent's residence and the location of a target facility. Using a linear city model, this study demonstrates the influences of income and distance-decay effects on WTP. Simulations are performed to check the validity of the model, as well as to predict consequences when income and distance-decay effects are not properly treated. Finally, the suggested methodology is applied to two real cases. The estimation results from a structural model show that the calculated total benefit varies largely when income and distance-decay effects exist and are ignored. Also, an ad hoc model generates significantly different estimates from the utility difference model this study adopted. The difference in estimates suggests that the total benefit has to be estimated by a structural model.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

An isolated AC module for photovoltaic energy conversion

In this paper, an isolated ac module with pseudo dc-link and galvanic isolation is proposed for photovoltaic energy conversion. The studied grid-tie ac module can individually extract the maximum solar power from each photovoltaic panel and transfer to ac utility system. It consists of an interleaved active-clamping single-ended primary-inductive circuit (SEPIC) with a secondary voltage doubler, a full-bridge polarity selector operating under line frequency to achieve high efficiency. For the studied topology, key features such as reduced input current ripple, zero-voltage switching (ZVS) of primary switches, low reverse-recovery current of the output diodes, and lower switch voltage stress are obtained. Also, to reduce input current ripple, an interleaved control strategy is adopted. A simple control strategy is proposed to generate a rectified sinusoidal waveform voltage at the pseudo dc-link capacitors and achieve the high maximum power point tracking (MPPT) accuracy. The operation principles and design considerations of the studied ac module are analyzed and discussed. A prototype with 25–60 V dc input, 110 V/60 Hz ac output and 150 W power rating has been constructed for verifying the feasibility of the proposed ac module.     

Experimental investigation of a 250-kW turbine organic Rankine cycle system for low-grade waste heat recovery

An organic Rankine cycle (ORC) is generally used for converting low-grade heat into electricity. In this study, an extensive literature survey was conducted to identify current research gaps on experimental ORC systems. Specifically, there is limited experimental data and limited details on thermal and expander efficiencies of ORC systems. In order to address these gaps, the objective of this study included developing a turbine ORC with a power output exceeding 50 kW and thermal efficiency exceeding 8% for a heat source temperature < 120°C. The experimental results indicated that the system achieved a net power output of 242.5 kW and a thermal efficiency of 8.3% (the highest value for a turbine ORC system for the heat source temperature below 120°C). Thus, the study addressed the gaps identified in the research area of ORCs.     

Inhibition of residual <Emphasis Type="Italic">n</Emphasis>-hexane in anaerobic digestion of lipid-extracted microalgal wastes and microbial community shift

Converting lipid-extracted microalgal wastes to methane (CH₄) via anaerobic digestion (AD) has the potential to make microalgae-based biodiesel platform more sustainable. However, it is apparent that remaining n-hexane (C₆H₁₄) from lipid extraction could inhibit metabolic pathway of methanogens. To test an inhibitory influence of residual n-hexane, this study conducted a series of batch AD by mixing lipid-extracted Chlorella vulgaris with a wide range of n-hexane concentration (～10 g chemical oxygen demand (COD)/L). Experimental results show that the inhibition of n-hexane on CH₄ yield was negligible up to 2 g COD/L and inhibition to methanogenesis became significant when it was higher than 4 g COD/L based on quantitative mass balance. Inhibition threshold was about 4 g COD/L of n-hexane. Analytical result of microbial community profile revealed that dominance of alkane-degrading sulfate-reducing bacteria (SRB) and syntrophic bacteria increased, while that of methanogens sharply dropped as n-hexane concentration increased. These findings offer a useful guideline of threshold n-hexane concentration and microbial community shift for the AD of lipid-extracted microalgal wastes.