Investigations of an intense aerosol loading during 2007 cyclone SIDR – A study using satellite data and ground measurements over Indian region

Tropical cyclones are prominent weather systems characterized by high atmospheric pressure gradients and wind speeds. Intense tropical cyclones occur in India during the pre-monsoon (spring), early monsoon (early summer), or post-monsoon (fall) periods. Originating in both the Bay of Bengal (BoB) and the Arabian Sea (AS), these tropical cyclones often attain velocities of more than 100 km h^?1 and are notorious for causing intense rain and storm surge as they cross the Indian coast. In this study, we examine the changes in the aerosol properties associated with an intense tropical cyclone “SIDR”, that occurred during 11–16 November 2007 over BoB. This cyclone, accompanied with very strong surface winds reaching 223 km h^?1, caused extensive damage over Bangladesh. Ground-based measurements of Aerosol Optical Depth (AOD) in the neighboring urban environment of Hyderabad, India, showed significant variations due to changes in wind velocity and direction associated with the cyclone passage. The Terra-MODIS and AVHRR satellite images showed prevalence of dust particles mixed with emissions from anthropogenic sources and biomass-burning AS, while the aerosol loading over BoB was significantly lower. The positive values of Aerosol index (AI) obtained from the Ozone Monitoring Instrument (OMI) suggested the presence of an elevated aerosol layer over the West coast of India, AS and Thar Desert during and after the cyclone episode. Meteorological parameters from the MM5 mesoscale model were used to study the variations in winds associated with the cyclonic activity. Particulate matter loading over the region during the cyclone period increased by ～45% with an accompanying decrease in columnar aerosol optical depth. The variations in Angstrom parameters suggested coarse-mode particle loading due to dust aerosols as observed in satellite data.     

Assessment of chemical process hazards in early design stages

A new method called SREST-layer-assessment method with automated software tool is presented that in a hierarchical approach reveals the degree of non-ideality of chemical processes with regard to SHE (safety, health and environment) aspects at different layers: the properties of the chemical substances involved (substance assessment layer (SAL)), possible interactions between the substances (reactivity assessment layer (RAL)), possible hazard scenarios resulting from the combination of substances and operating conditions in the various equipments involved (equipment assessment layer (EAL)), and the safety technologies that are required to run a process safely and in accordance with legal regulations (safety-technology assessment layer (STAL)). In RAL, EAL and STAL the main focus is put on process safety. A case study is used to show the principles of the method. It is demonstrated how the method can be used as a systematic tool to support chemical engineers and chemists in evaluating chemical process safety in early process development stages.     

The brighter side of e-waste—a rich secondary source of metal

Environmental Science and Pollution Research - This article details the electronic waste (e-waste) generation, their composition, health, and environment hazards, and legal rules for disposal as...     

Atmospheric deposition studies of heavy metals in Arctic by comparative analysis of lichens and cryoconite

Lichens and cryoconite (rounded or granular, brownish-black debris occurring in holes on the glacier surface) from Ny-Ålesund were used for understanding the elemental deposition pattern in the area. Lichen samples collected from low-lying coastal region and cryoconite samples from high altitudinal glacier area were processed and analysed for elements such as aluminium (Al), arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), cesium (Cs), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), vanadium (V) and zinc (Zn) through inductively coupled plasma mass spectrometry. Results showed that heavy metals, Al and Fe, are present in high concentration in the cryoconite samples. Al was also present in high amounts in seven of the eight lichen samples studied. The general scheme of elements in the decreasing order of their concentrations for most of the cryoconite samples was Al?>?Fe?>?Mn?>?Zn?>?V?>?Pb?>?Cr?>?Ni?>?Cu?>?Co?>?As?>?Cs?>?Cd while that for the lichen samples was Al?>?Fe?>?Zn?>?Mn?>?Pb?>?Cu?>?Cs?>?Cr?>?Ni?>?V?>?Co?>?As?>?Cd. Similarity in trends in the two sample types confirms that the environment indeed contains these elements in that order of concentration which overtime got accumulated in the samples. Overall comparison showed most elements to be present in high concentrations in the cryoconite samples as compared to the lichen samples. Within the lichens, elemental accumulation data suggests that the low-lying site (L-2) from where Cladonia mediterranea sample was collected was the most polluted accumulating a number of elements at high concentrations. The probable reasons for such deposition patterns in the region could be natural (crustal contribution and sea salt spray) and anthropogenic (local and long-distance transmission of dust particles). In the future, this data can form a baseline for monitoring quantum of atmospheric heavy metal deposition in lichens and cryoconite of Svalbard, Arctic.     

Identification of hot spots and well managed areas of Pichavaram mangrove using Landsat TM and Resourcesat—1 LISS IV: an example of coastal resource conservation along Tamil Nadu Coast, India

The present work is a multi-temporal satellite based study on the spatial dynamic of an important coastal habitat, the Pichavaram mangrove ecosystem, over a period of 15 years. The Pichavaram mangrove forest near Chidambaram, South India is the second largest mangrove forest in the world. Unsupervised classification, the Iterative Self Organising Data Analysis Technique (ISODATA), has been used to classify the mangrove cover into the open and dense classes. The status of the classes has been monitored using Landsat TM of 1991, 2001, and Resourcesat–1 LISS IV of 2006 satellite data. The study demonstrated that by classifying mangrove ecosystem into just the 3 classes using remote sensing data and by studying their temporal variations, it is possible to get a reasonably accurate picture of the extent and condition of the mangrove ecosystem. The total area of the Pichavaram mangrove showed a net increase of 2.51 km² within a span of 15 years (1991 to 2006). The hot spots that are at a risk of being degraded, and on the other hand, the mangrove areas that are well managed are identified using Geographical Information System (GIS) tools for the restoration and conservation measures.     

Sorption kinetics and isotherm modelling of imidacloprid on bentonite and organobentonites

Bentonite was modified by quaternary ammonium cations viz. cetytrimethylammonium (CTA), cetylpyridinium (CP), rioctylmethylammonium (TOM) and pcholine (PTC) at 100% cation exchange capacity of bentonite and was characterized by X-ray diffraction, CHNS elemental analyser and Fourier transform infrared spectroscopy. The sorption of imidacloprid on organobentonites/bentonite was studied by batch method. Normal bentonite could adsorb imidacloprid only upto 19.31–22.18% while all organobentonites except PTC bentonite (PTCB), enhanced its adsorption by three to four times. Highest adsorption was observed in case of TOM bentonite (TOMB) (76.94–83.16%). Adsorption kinetic data were fitted to pseudo-first-order, pseudo-second-order and intraparticle diffusion models. For normal bentonite data were best fitted to pseudo-first-order kinetic, while for organobentonites fitted to pseudo-second-order kinetics. Sorption data were analysed using Freundlich, Langmuir, Temkin and Dubinin–Radushkevich isotherm models. Data were well fitted to Freundlich adsorption isotherm. Product of Freundlich adsorption constant and heterogeneity parameter (K_f.1/n) was in following order: TOMB (301.87) > CTA bentonite (CTAB) (152.12) > CP bentonite (CPB) (92.58) > bentonite (27.25). Desorption study confirmed hysteresis and concentration dependence. The present study showed that the organobentonite could be a good sorbent for removal of imidacloprid from natural water sample also. Percentage adsorption and Distribution coefficient (mL g^?1) value of different adsorbent was in following order: TOMB (74.85% and 297.54) > CTAB (55.78% and 126.15) > CPB (45.81% and 84.55) > bentonite (10.65% and 11.92).     

The role of disinfectants and sanitizers during COVID-19 pandemic: advantages and deleterious effects on humans and the environment

Environmental Science and Pollution Research - Disinfectants and sanitizers are essential preventive agents against the coronavirus disease 2019 (COVID-19) pandemic; however, the pandemic crisis...     

Morphological and Biochemical Characteristics of Avian Faecal Droppings and Their Impact on Survival of Avian Influenza Virus

Environmental specimens such as faecal droppings are considered important for the detection of avian influenza viruses (AIV). In view of lower rates of AIV isolation from avian faecal droppings, characterization of droppings is imperative to elucidate contributing factors. However, there are no reports on morphological and biochemical characteristics of droppings. The objective of the present study was the characterization of droppings from different avian species and their impact on the AIV detection and isolation. A total of 373 droppings belonging to 61 avian species from 22 families of apparently healthy wild migratory, resident, domestic birds and poultry were studied during five winter migratory bird seasons between 2007 to 2012 and 2016–2017. The colour, morphology and size of the droppings varied from species-to-species. These data could be useful for the identification of avian species. Droppings from 67% of the avian species showed acidic pH (4.5–6.5); nine species showed neutral pH (7.0), and 11 species showed alkaline pH (7.5). The infectious titers of AIV in droppings with acidic pH were significantly lower (p < 0.05) than those of the droppings with neutral and alkaline pH. However, acidic pH did not hamper AIV detection by real-time RT-PCR. In order to avoid the impact of acidic pH, collecting fresh droppings into viral transport medium (pH 7.0–7.5) would help improve the rate of AIV isolation.