Microwave assisted solvent-free synthesis and biological activities of novel imines (Schiff bases)

Twelve new ortho-Hydroxyketimines were synthesized by conventional as well as microwave method and evaluated for their antinemic activity against Meloidogyne incognita [(Kofoid and White) Chitwood]. Conventional methods for synthesis of Schiff bases require refluxing at 140°C of the reactants in different solvents for at least 24 h or more, where as the microwave-assisted synthesis has brought down the reaction time from 24 h to 1 minute. The procedure reported is simple as it does not require any organic solvents and the time has been reduced to only 1 minute. Comparative yields of all compounds by different methods revealed that the yield was low in conventional method (79–87%) as compared to microwave assisted synthesis (94–97%). The bioassay revealed that all the test compounds exhibited promising nematicidal activity; N-propyl-2-hydroxypropiophenonimine being the most effective with LC₅₀ value of 74.46 mgL^?1 followed by N-hexyl-2-hydroxyacetophenonimine with LC₅₀ value of 99.60 mgL^?1 after 72 h of exposure. The results obtained from bioassay indicated that this class of compounds has not only given a lead with regard to potential of Schiff bases in pest control, but has suggested that a carbon chain length of 6 atoms in the side chain is optimum on the basis of structure activity relationship (SAR).     

Biocatalytic amidation of carboxylic acids and their antinemic activity

A series of novel N-alkyl substituted amides, synthesized by enzyme catalysis, were evaluated against root-knot nematode, Meloidogyne incognita and found to have potential antinemic activity. The corresponding amides were prepared by the condensation of equimolar amounts of carboxylic acids with different alkyl amines in the presence of Candida antarctica lipase at 60–90°C in 16–20 h. The reactions were carried out in a non - solvent system without the use of any activating agents. All the products were obtained in appreciable amounts and the yields for different compounds varied between 77.4–82.3%. The synthesized compounds were characterized using spectroscopy techniques namely Infra Red (IR) and Nuclear Magnetic Resonance (NMR) (¹H and ¹³C). Nematicidal activity of synthesized amides was evaluated against J₂s of Meloidogyne incognita at 500, 250, 125 and 62.5 ppm concentrations after 24 h, 48 h and 72 h of exposure. Among all the tested compounds, N-propyl-butyramide, N-propyl-pentanamide and N-propyl-hexanamide were found to possess significant activity with LC₅₀ values of 67.46, 83.49 and 96.53 respectively. N-propyl-butyramide with LC₅₀ value of 67.46 ppm was found to be most active amide against J₂s of Meloidogyne incognita. The bioactivity study showed that an increase in alkyl chain significantly decreased the activity of amides against root-knot nematode.     

Effect of compression ratio,nozzle opening pressure,engine load,and butanol addition on nanoparticle emissions from a non-road diesel engine

Currently, diesel engines are more preferred over gasoline engines due to their higher torque output and fuel economy. However, diesel engines confront major challenge of meeting the future stringent emission norms (especially soot particle emissions) while maintaining the same fuel economy. In this study, nanosize range soot particle emission characteristics of a stationary (non-road) diesel engine have been experimentally investigated. Experiments are conducted at a constant speed of 1500 rpm for three compression ratios and nozzle opening pressures at different engine loads. In-cylinder pressure history for 2000 consecutive engine cycles is recorded and averaged data is used for analysis of combustion characteristics. An electrical mobility-based fast particle sizer is used for analyzing particle size and mass distributions of engine exhaust particles at different test conditions. Soot particle distribution from 5 to 1000 nm was recorded. Results show that total particle concentration decreases with an increase in engine operating loads. Moreover, the addition of butanol in the diesel fuel leads to the reduction in soot particle concentration. Regression analysis was also conducted to derive a correlation between combustion parameters and particle number emissions for different compression ratios. Regression analysis shows a strong correlation between cylinder pressure-based combustion parameters and particle number emission.

     

Assessing Public Preferences for Forest Biomass Based Energy in the Southern United States

This article investigated public preferences for forest biomass based liquid biofuels, particularly ethanol blends of 10% (E10) and 85% (E85). We conducted a choice experiment study in three southern states in the United States: Arkansas, Florida, and Virginia. Reducing atmospheric CO₂, decreasing risk of wildfires and pest outbreaks, and enhancing biodiversity were presented to respondents as attributes of using biofuels. Results indicated that individuals had a positive extra willingness to pay (WTP) for both ethanol blends. The extra WTP was greater for higher blends that offered larger environment benefits. The WTPs for E10 were $0.56 gallon^?1, $0.58 gallon^?1, and $0.48 gallon^?1, and for E85 they were $0.82 gallon^?1, $1.17 gallon^?1, and $1.06 gallon^?1 in Arkansas, Florida, and Virginia, respectively. Although differences in WTP for E10 were statistically insignificant among the three states, significant differences were found in the WTP for E85 between AR and FL and between AR and VA. Preferences for the environmental attributes appeared to be heterogeneous, as respondents’ were willing to pay a premium for E10 in all three states to facilitate the reduction of CO₂ and the improvement of biodiversity but were not willing to pay more for E85 in order to enhance biodiversity.     

Fiber from DDGS and Corn Grain as Alternative Fillers in Polymer Composites with High Density Polyethylene from Bio-based and Petroleum Sources

The steady increase in production of corn based ethanol fuel has dramatically increased the supply of its major co-product known as distiller’s dried grain with solubles (DDGS). Large amount of DDGS and corn flour are used as an animal feed. The elusieve process can separate DDGS or corn flour into two fractions: DDGS fraction with enhanced protein and oil content or corn flour fraction with high starch content, and hull fiber. This study investigated the feasibility of using fiber from DDGS and corn grain as alternative fillers to wood fiber in high density polyethylene (HDPE) composites made with two different sources of polymers. Two fiber loading rates of 30 and 50% were evaluated for fiber from DDGS, corn, and oak wood (control) to assess changes in various physical and mechanical properties of the composite materials. Two HDPE polymers, a bio-based HDPE made from sugarcane (Braskem), and a petroleum based HDPE (Marlex) were also compared as substrates. The biobased polymer composites with DDGS and corn fibers showed significantly lower water absorption than the Marlex composite samples. The Braskem composite with 30% DDGS fiber loading showed the highest impact resistance (80 J/m) among all the samples. The flexural properties showed no significant difference between the two HDPE composites.     

Urban soil quality of Raipur,Chhattisgarh, India

Soil quality in urban areas in India is degraded due to multiple anthropogenic activities. The objectives of this work are to determine the concentration variations, toxicity, and sources of carbons, metals, and ions in the surface soil of Raipur, the industrialized capital city of Chhattisgarh state, India. High concentrations of Al, K, Ca, Ti, Fe, and elemental carbon (EC) were registered. Relatively lower concentrations of V, Cr, Mn, Ni, Cu, Zn, Sr, Ba, Pb, organic carbon (OC), and carbonate carbon (CC), as well as ions (viz. F^–, Cl^–, NO₃^–, SO₄^2–, Na⁺, K⁺, Mg²⁺, and Ca²⁺), were also recorded. EC was found to be one of the major pollutants, although enrichment factors pointed to high contamination with SO₄^2–, K⁺, Mg²⁺_, Cr, Mn, and Pb; and extreme contamination with NO₃^– and Ca²⁺. The spatial and temporal variations, enrichment factors, toxicity, and sources of the chemical species detected in the soil are discussed.     

Estimation of land surface temperature using different retrieval methods for studying the spatiotemporal variations of surface urban heat and cold islands in Indian Punjab

Spatial patterns of land surface temperature (LST), surface urban heat island (SUHI), surface urban cold island (SUCI), and their seasonal variations during January (winter) and September (summer) were analyzed over the three cities of Indian Punjab (Balachaur, Ludhiana and Bathinda) using Landsat 5, 7 and 8 satellite data of the years 1991, 2001, 2011, and 2018. Urban hot spots and Urban Thermal Field Variance Index (UTFVI) were used to measure the ecological environment of these cities. Land surface temperature was retrieved from Landsat satellite data using Plank equation, mono-window algorithm (MWA), single-channel algorithm (SCA), and radiative transfer equation. The LST derived using these algorithms was validated with MODIS-LST product. The relationship between LST derived from Landsat 5, 7 and 8 using the four methods and MODIS-LST product was higher with the SCA algorithm (R²?>?0.75). Land surface temperature was significantly positively correlated with built-up but significantly negatively correlated with vegetation. The surface urban heat intensity was higher during September than January, and it was higher in Ludhiana followed by Bathinda and Balachaur, irrespective of the season. Besides built-up area and population density, soil moisture availability in surrounding rural areas has significant impact on increasing surface urban heat intensity during September than January. The SUCIs were formed in the center of Bathinda city during January 1991, but these were in Ludhiana and Balachaur cities during January 2011. The most critical areas for ecological environment based on UTFVI were identified and the critical UTFVI values (>?0.020) were highest in Bathinda city followed by Balachaur and Ludhiana cities. These results suggest that SUHIs and SUCIs are influenced by seasons and the mitigating plans to counteract the overheating of urban areas should be formulated taking into account soil moisture availability in surrounding rural areas, landscape pattern, seasonal variations, local climatic conditions, urban growth, and development plan etc.

     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.