Estimating the Recreation Demand and Economic Value of Mountain Biking in Moab,Utah: An Application of Count Data Models

This paper reports the results of both standard and truncated count data travel cost demand models for estimating demand for and the economic value to participants in mountain biking in the Moab, Utah, area. The empirical estimates for average trip demand per person per season were 2.25 and 2.53 trips under truncated Poisson and truncated negative binomial models, respectively. Consumer surplus per person per trip for both models was approximately US $585. The total annual use value for mountain biking in the Moab area was US $1.33 million. This value suggests that this recreation has a higher value than most other activities in the area and that public land managers should be aware of the relative value of mountain biking as they make allocation decisions.     

Rapid estimation of compost enzymatic activity by spectral analysis method combined with machine learning

The aim of this study was to investigate the feasibility of using visible near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) as an easy, inexpensive, and rapid method to predict compost enzymatic activity, which traditionally measured by fluorescein diacetate hydrolysis (FDA-HR) assay. Compost samples representative of five different compost facilities were scanned by DRS, and the raw reflectance spectra were preprocessed using seven spectral transformations for predicting compost FDA-HR with six multivariate algorithms. Although principal component analysis for all spectral pretreatments satisfactorily identified the clusters by compost types, it could not separate different FDA contents. Furthermore, the artificial neural network multilayer perceptron (residual prediction deviation = 3.2, validation r² = 0.91 and RMSE = 13.38 μg g^?1 h^?1) outperformed other multivariate models to capture the highly non-linear relationships between compost enzymatic activity and VisNIR reflectance spectra after Savitzky–Golay first derivative pretreatment. This work demonstrates the efficiency of VisNIR DRS for predicting compost enzymatic as well as microbial activity.     

Kinetics of phenol biodegradation at high concentration by a metabolically versatile isolated yeast Candida tropicalis PHB5

A highly tolerant phenol-degrading yeast strain PHB5 was isolated from wastewater effluent of a coke oven plant and identified as Candida tropicalis based on phylogenetic analysis. Biodegradation experiments with C. tropicalis PHB5 showed that the strain was able to utilize 99.4 % of 2,400 mg l^?1 phenol as sole source of carbon and energy within 48 h. Strain PHB5 was also observed to grow on 18 various aromatic hydrocarbons. Haldane model was used to fit the exponential growth data and the following kinetic parameters were obtained: μ _max?=?0.3407 h^?1, K _S?=?15.81 mg l^?1, K _i?=?169.0 mg l^?1 (R ²?=?0.9886). The true specific growth rate, calculated from μ _max, was 0.2113. A volumetric phenol degradation rate (V _max) was calculated by fitting the phenol consumption data with Gompertz model and specific degradation rate (q) was calculated from V _max. The q values were fitted with Haldane model, yielding following parameters: q _max?=?0.2766 g g^?1 h^?1, K _S ′?=?2.819 mg l^?1, K _i ′?=?2,093 (R ²?=?0.8176). The yield factor (Y _X/S ) varied between 0.185 to 0.96 g g^?1 for different initial phenol concentrations. Phenol degradation by the strain proceeded through a pathway involving production of intermediates such as catechol and cis,cis-muconic acid which were identified by enzymatic assays and HPLC analysis.     

A process-based model on methane emission with its oxidation process from rice fields and corresponding control indices

In this paper, a mathematical model is developed for net methane emission from rice fields by coupling methane production model with methane oxidation model. Several dynamical regimes were formed through qualitative analysis of the model, and corresponding dynamic features were interpreted through emission indices. Sensitivity of the model is discussed under the effects of temperature and oxygen concentration in methanogenic and methane oxidation phases, respectively, and interpreted by defining an index; in addition, control parameters are identified and their threshold limits defined. The out-busting emission tendency of methane is considered separately and a forcing strategy was defined to force emission level towards zero in the long term. Lastly, a complete control strategy is proposed for reducing methane emission.     

Environmental injustice and flood risk: a conceptual model and case comparison of metropolitan Miami and Houston,USA

Regional Environmental Change - This article outlines a conceptual model and comparatively applies it to results from environmental justice (EJ) studies of flood risk in the Miami, Florida, and...     

Use of portable X-ray fluorescence spectrometry for environmental quality assessment of peri-urban agriculture

Urban expansion into traditional agricultural lands has augmented the potential for heavy metal contamination of soils. This study examined the utility of field portable X-ray fluorescence (PXRF) spectrometry for evaluating the environmental quality of sugarcane fields near two industrial complexes in Louisiana, USA. Results indicated that PXRF provided quality results of heavy metal levels comparable to traditional laboratory analysis. When coupled with global positioning system technology, the use of PXRF allows for on-site interpolation of heavy metal levels in a matter of minutes. Field portable XRF was shown to be an effective tool for rapid assessment of heavy metals in soils of peri-urban agricultural areas.     

Assessment of phenol infiltration resilience in soil media by HYDRUS-1D transport model for a waste discharge site

The movement of contaminants through soil imparts a variety of geo-environmental problem inclusive of lithospheric pollution. Near-surface aquifers are often vulnerable to contamination from surface source if overlying soil possesses poor resilience or contaminant attenuation capacity. The prediction of contaminant transport through soil is urged to protect groundwater from sources of pollutants. Using field simulation through column experiments and mathematical modeling like HYDRUS-1D, assessment of soil resilience and movement of contaminants through the subsurface to reach aquifers can be predicted. An outfall site of effluents of a coke oven plant comprising of alarming concentration of phenol (4–12.2 mg/L) have been considered for studying groundwater condition and quality, in situ soil characterization, and effluent characterization. Hydrogeological feature suggests the presence of near-surface aquifers at the effluent discharge site. Analysis of groundwater of nearby locality reveals the phenol concentration (0.11–0.75 mg/L) exceeded the prescribed limit of WHO specification (0.002 mg/L). The in situ soil, used in column experiment, possess higher saturated hydraulic conductivity (K _S ?=?5.25?×?10^?4 cm/s). The soil containing 47 % silt, 11 % clay, and 1.54 % organic carbon content was found to be a poor absorber of phenol (24 mg/kg). The linear phenol adsorption isotherm model showed the best fit (R ²?=?0.977, RMSE?=?1.057) to the test results. Column experiments revealed that the phenol removal percent and the length of the mass transfer zone increased with increasing bed heights. The overall phenol adsorption efficiency was found to be 42–49 %. Breakthrough curves (BTCs) predicted by HYDRUS-1D model appears to be close fitting with the BTCs derived from the column experiments. The phenol BTC predicted by the HYDRUS-1D model for 1.2 m depth subsurface soil, i.e., up to the depth of groundwater in the study area, showed that the exhaustion point was reached within 12 days of elapsed time. This clearly demonstrated poor attenuation capacity of the soil to retard migration of phenol to the groundwater from the surface outfall site. Suitable liner, based on these data, may be designed to inhibit subsurface transport of phenol and thereby to protect precious groundwater from contamination.     

Geo-spatial analysis of the temporal trends of kharif crop phenology metrics over India and its relationships with rainfall parameters

The Global Inventory Modeling and Mapping Studies bimonthly Normalized Difference Vegetation Index (NDVI) data of 8?×?8 km spatial resolution for the period of 1982–2006 were analyzed to detect the trends of crop phenology metrics (start of the growing season (SGS), seasonal NDVI amplitude (AMP), seasonally integrated NDVI (SiNDVI)) during kharif season (June to October) and their relationships with the amount of rainfall and the number of rainy days over Indian subcontinent. Direction and magnitude of trends were analyzed at pixel level using the Mann–Kendall test and further assessed at meteorological subdivision level using field significance test (α?=?0.1). Significant pre-occurrence of the SGS was observed over northern (Punjab, Haryana) and central (Marathwada, Vidarbha and Madhya Maharashtra) parts, whereas delay was found over southern (Rayalaseema, Coastal Andhra Pradesh) and eastern (Bihar, Gangetic West Bengal and Sub-Himalayan West Bengal) parts of India. North, west, and central India showed significant increasing trends of SiNDVI, corroborating the kharif food grain production performance during the time frame. Significant temporal correlation (α?=?0.1) between the rainfall/number of rainy days and crop phenology metrics was observed over the rainfed region of India. About 35–40 % of the study area showed significant correlation between the SGS and the rainfall/number of rainy days during June to August. June month rainfall/number of rainy days was found to be the most sensitive to the SGS. The amount of rainfall and the number of rainy days during monsoon were found to have significant influence over the SiNDVI in 24–30 % of the study area. The crop phenology metrics had significant correlation with the number of rainy days over the larger areas than that of the rainfall amount.     

Fractionation and bioavailability of metals and their impacts on microbial properties in sewage irrigated soil

A study was conducted to evaluate the effect of long-term irrigation of sewage contaminated with heavy metals like Cd, Cr, Cu and Pb on microbial and biochemical parameters of soils of West Bengal, India. The microbial parameters included microbial biomass carbon (MBC), microbial metabolic quotient; the biochemical parameters included fluorescein diacetate hydrolyzing activity, beta-glucosidase, urease, phosphatase, and aryl sulphatase activities. A sequential extraction technique was used to quantify water soluble, exchangeable, carbonate bound, Fe/Mn-oxide bound, organically bound, and residual metal fractions. Metal concentrations in the two most labile fractions (i.e., water soluble and exchangeable fractions) were generally low. Total metal concentrations at each site seemed to be associated with soil amorphous Fe and Al minerals. The MBC and the enzymes studied were significantly and negatively correlated with water soluble and exchangeable metals but not significantly correlated with other forms, indicating that water soluble and exchangeable forms exerted a strong inhibitory effect on the soil microbial and biochemical parameters. It was concluded that irrigating soils with metal contaminated sewage seemed to damage soil quality in the long term.