Trace ambient levels of particulate mercury and its sources at a rural site near Delhi

Atmospheric particle-bound mercury levels were measured in PM₁₀ aerosols (HgP) at a rural site (Mahasar, Haryana) during winter 2014–15 and summer 2015. The PM₁₀ HgP was determined by using Differential Pulse Anodic Stripping Voltammetry through standard addition methods while the trace metals were determined by using an Atomic Absorption Spectroscopy. The mass concentrations of HgP varied from 591 to 1533 pg/m³ with an average of 1009?±?306 pg/m³ during the winter, while the mass concentrations of HgP varied from 43 to 826 pg/m³ with an average of 320?±?228 pg/m³ during the summer. However, it is difficult to assess whether these levels are harmful or not because there is no standard value available as National Ambient Air Quality Standard. The higher concentrations of HgP during winters were possibly due to favourable local meteorological conditions for the stagnation of particulate matter in the lower atmosphere and the increased emissions from existing natural or anthropogenic sources, regional sources and long-range transportation. Relatively low concentrations of HgP during summer might be due to increased mixing heights as well as scavenging effect because some light to heavy rain events were observed during summer time sampling. However, among other metals determined, the concentration of HgP was the lowest during both the seasons. The study may be useful in assessing the health impacts of PM₁₀ HgP and other metals.     

Formate and acetate levels compared in monsoon and winter rainwater at Dayalbagh, Agra (India)

A total of 59 rainwater samples were collected during the winter and monsoon (1991–92) at Dayalbagh, Agra. This site is relatively free from the influence of anthropogenic emissions and the volume-weighted average concentrations (VWA) of formate in the winter and monsoon were 22.5±6, 16.1±3 while acetate VWAs were 17.1±5 and 13.8±3 mol l^-1, respectively. Although the VWAs varied between seasons, it was not statistically different. Total deposition (in mmol m^-2) varied between season (winter formate, 1.4; acetate, 1.1; monsoon formate, 7.4; acetate, 6.4). A difference in VWA values may have occurred as a result of the dilution factor; the total rain depth from collected samples in the monsoon was 46 cm while that in winter was 6.3 cm. Sources at this site may be anthropogenic and natural; scavenging from the vapour phase, washout of soil particles and emissions from vegetative sources are probably important sources for formate and acetate.     

Radioactivity monitoring in the vicinity of Jawalamukhi thrust NW Himalaya,India for tectonic study

Natural Hazards - This work reports radon-thoron monitoring at two depths (60 and 90 cm) and at 82 sites around Jawalamukhi thrust of NW Himalaya, India using Solid State Nuclear Track...     

Bringing communities at the Centre of Impact Assessment of Road Projects: integrating AHP with qualitative research

GeoJournal - This paper proposes a framework for measuring impacts associated with road projects on rural communities situated on either side of the road alignment. The extant approaches for...     

Characterization and evaluation of processes governing the groundwater quality in parts of the Sabarmati basin,Gujarat using hydrochemistry integrated with GIS

Intense agricultural and industrial activities in any area are likely to make groundwater vulnerable with respect to its quality. In one such area which is a part of Sabarmati river basin of Gujarat, factors influencing the groundwater hydrochemistry in pre‐ and post‐monsoon season were evaluated. Groundwater samples were collected from 5 km × 5 km grids on the basis of spectral signature of vegetation and soil, observed on satellite image. Integration of Conventional graphical plots, Piper plot, saturation index values (estimated using PHREEQC) and GIS was helpful not only to create the database for analysis of spatial variation in respective water quality parameters but also to decipher the hydrogeochemical process occurring in such a large area. USSL diagram and % sodium were used to characterise the suitability of groundwater for irrigation. It was observed that leaching of wastes disposed from anthropogenic activities and agrichemicals is the major factor influencing the groundwater quality, in addition to the natural processes such as weathering, dissolution and ion exchange. Sea water relics are also impacting the groundwater quality. Control of indiscriminate and unplanned exploitation of groundwater, application of fertilizers and disposal of industrial wastes in the affected areas can possibly ensure groundwater protection from further pollution and depletion. Copyright © 2011 John Wiley & Sons, Ltd.     

Propagation of shear waves in viscoelastic medium at irregular boundaries

The aim of the paper is to study the shear wave propagation in a viscoelastic layer over a semi-infinite viscoelastic half space due to irregularity in the viscoelastic layer. It is of great interest to study the propaga-tion of shear waves in the assumed medium having a non planar boundary due to its similarity to most of the real situations. The perturbation method is applied to find the displacement field. The effect of complex wave number on dissipation factor is analysed. Finally, as an application, the result obtained has been used to get the reflected field in viscoelastic layer when the shear wave is incident on an irregular boundary in the shape of parabolic irregularity as well as triangular notch. It is observed that the amplitude of this reflected wave decreases with increasing length of the notch, and increases with increasing depth of the irregularity.     

Space–time forecasting of groundwater level using a hybrid soft computing model

Forecasting of space–time groundwater level is important for sparsely monitored regions. Time series analysis using soft computing tools is powerful in temporal data analysis. Classical geostatistical methods provide the best estimates of spatial data. In the present work a hybrid framework for space–time groundwater level forecasting is proposed by combining a soft computing tool and a geostatistical model. Three time series forecasting models: artificial neural network, least square support vector machine and genetic programming (GP), are individually combined with the geostatistical ordinary kriging model. The experimental variogram thus obtained fits a linear combination of a nugget effect model and a power model. The efficacy of the space–time models was decided on both visual interpretation (spatial maps) and calculated error statistics. It was found that the GP–kriging space–time model gave the most satisfactory results in terms of average absolute relative error, root mean square error, normalized mean bias error and normalized root mean square error.