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.     

Determination of pesticide residues in IPM and non-IPM samples of mango (Mangifera indica)

Studies were conducted to analyze the residue of commonly used pesticides viz. methyl parathion, chloropyrifos, endosulfan, cypermethrin, fenvalerate, carbendazim, imidacloprid and carbaryl in mango, Dashehari variety, integrated pest management (IPM) and non-IPM samples were collected from the IPM and non-IPM orchards, Lucknow, India. We also present a method for the simultaneous determination of these pesticides in mango samples. Residues of methyl parathion, chloropyriphos, endosulfan, cypermethrin, fenvalerate were extracted from the samples with acetone: cyclohexane: ethyl acetate in the ratio 2:1:1 followed by cleanup using neutral alumina. Analysis was performed by gas chromatography-electron capture detector (GC-ECD) with a megabore column (OV-1). Residues of carbendazim, imidacloprid and carbaryl were extracted with acetone and after cleanup, analysis was performed by high performance liquid chromatography (HPLC) using photo diode array (PDA) detector. Recoveries of all the pesticides ranged between 72.7-110.6%, at 0.1 and 1.0 microg g(-1) level of fortification. The residues detected in non-IPM samples of mango were found to be below the prescribed limits of maximum residue limit (MRL) while IPM samples were free from pesticide residues.     

Assessment of the impact of pesticide residues on microbiological and biochemical parameters of tea garden soils in India

The main aim of this study was to assess the impact of pesticidal residues on soil microbial and biochemical parameters of the tea garden soils. The microbial biomass carbon (MBC), basal (BSR) and substrate induced respirations (SIR), beta-glucosidase activity and fluorescein diacetate hydrolyzing activity (FDHA) of six tea garden soils, along with two adjacent forest soils (control) in West Bengal, India were measured. The biomass and its activities and biochemical parameters were generally lower in the tea garden soils than the control soils. The MBC of the soils ranged from 295.5 to 767.5 micro g g(- 1). The BSR and SIR ranged from 1.65 to 3.08 mu g CO2-C g(- 1) soil h(- 1) and 3.08 to 10.76 micro g CO2-C g(- 1)h(- 1) respectively. The beta-glucosidase and FDHA of the soils varied from 33.3 and 76.3 micro g para-nitrophenol g(- 1) soil h(- 1) and 60.5 to 173.5 micro g fluorescein g(- 1)h(- 1)respectively. The tea garden soils contained variable residues of organophosphorus and organochlorine pesticides, which negatively affected the MBC, BSR, SIR, FDHA and beta -glucosidase activity. Ethion and chlorpyriphos pesticide residues in all the tea garden soils varied from 5.00 to 527.8 ppb and 17.6 to 478.1 ppb respectively. The alpha endosulfan, beta endosulfan and endosulfan sulfate pesticide residues in the tea garden soils ranged from 7.40 to 81.40 ppb, 8.50 to 256.1 ppb and 55 to 95.9 ppb respectively. Canonical correlation analysis shows that 93% of the total variation was associated with the negative impact of chlorpyriphos, beta and alpha endosulfan and endosulfan sulfate on MBC, BSR and FDHA. At the same time ethion had negative impact on SIR and beta-glucosidase. Data demonstrated that the pesticide residues had a strong impact on the microbial and biochemical components of soil quality.     

Heredity and risk of disease

Mathematical modeling of competing risks often uses a single risk function for all individuals within a population. In this paper we use several specific examples to argue that such representations remain approximations until account is taken of the existence of genetic variability within and between populations, and the impact of this upon liability to disease. The extent of human genetic variability is also indicated.