Passive air sampling of organochlorine pesticides in a northeastern state of India, Manipur

Thirty-six polyurethane foam disk passive air samplers (PUF-PAS) were deployed over a year during January to December, 2009 at three locations, i.e., Imphal (urban site), Thoubal (rural site) and Waithou (alpine site) of Manipur, to assess the seasonal local atmospheric emission of selected organochlorine pesticides (OCPs). The average concentration of HCHs monitored at mountain site during hot season (Mar, Apr, and May) and rainy seasons (Jun, Jul, Aug, and Sep) were 403 and 349 pg/m3, respectively. DDTs had a high concentration with 384 pg/m3 at rural site and 379 pg/m3 at urban site during hot seasons. Endosulfans and chlordane were found high in concentration during hot seasons (260 pg/m3) and low during retreating monsoon seasons (44 pg/m3) at rural site. Most of the OCPs concentrations were high during cultivation period. The OCP concentrations of rainy season were highly correlated (p < 0.01) with OCPs of hot seasons. Further, positive correlation (p < 0.05) was also obtained between cold seasons and retreating monsoon. Principal component analysis showed a significant correlation among the four seasons and distribution pattern of OCPs in air. Back trajectory analysis by using HYPSLIT model showed a long range air transport of OCPs to the present study area. Present OCP levels at Manipur is an outcome of both local emission and also movement of air mass by long range atmospheric transport.     

Modeling spawning dates of Hucho taimen in Mongolia to establish fishery management zones.

The ecological impacts of recreational fisheries are of growing concern and pose a number of unique management challenges. Here we report on our efforts to provide guidance for managing a recreational fishery for taimen, the giant Eurasian trout (Hucho taimen) in Mongolia. This species has declined dramatically across its range of Siberia and Central Asia, and is currently listed as endangered in Mongolia. Strong populations persist in remote regions of Mongolia because of limited anthropogenic impacts and harvest, though interest in the fishery is expanding rapidly. Current fishing regulations list the spring "opening date" for taimen fishing as 15 June, although regulations have not been consistently enforced, partially because taimen spawn much earlier than 15 June in much of the country. Through a combination of statistical models, climate data, knowledge of taimen biology, and geographic information systems (GIS), we model taimen spawning dates for potential habitat in Mongolia. A parametric bootstrap procedure was used to simulate variability in spawning date derived from inter-annual climate variability and model error, from which we estimated the date in which taimen spawning is predicted to occur with 90% confidence. We recommend the designation of three fisheries management zones, with corresponding opening dates of 20 May, 1 June, and 15 June. Our fishery opening date recommendations are less restrictive than existing regulations. Provided there is little or no catch-and-release fishing mortality, this approach serves both environmental and human needs by protecting taimen during the reproductive period, while still allowing a post-spawning catch-and-release fishery that benefits local economies and generates revenue (through fishing concession fees) for local conservation efforts.     

Yar tsa Gumba (Cordyceps sinensis): A call for its sustainable exploitation

Yar tsa Gumba, the local name for Cordyceps sinensis, is an entomophilus fungus in the order Hypocreales and family Scolecosporaceae, found primarily in alpine and subalpine regions, from 3200 to 4000 m asl. The fungus is parasitic on caterpillars, primarily those in the genus Hepialus. Studies on Cordyceps sinensis indicate that the fungus may improve liver function, reduce cholesterol, adjust protein metabolism, inhibit lung carcinoma and treat aging disorders. In the last five years, since it was found in parts of Garhwal and Kumaun Himalaya, massive exploitation has occurred, leading to a drastic decrease in wild populations. This paper presents results of an exploration carried out on the fungus at several important sites, the mode of trafficking and suggested policy initiative for its sustainable exploitation.     

Sorption of cadmium and zinc from aqueous solutions by zeolite 4A, zeolite 13X and bentonite

The sorption and desorption of cadmium and zinc on zeolite 4A, zeolite 13X and bentonite has been studied using batch sorption studies. Parameters such as equilibrium time, effect of pH and sorbent dose were studied. The sorbents exhibited good sorption potential for cadmium and zinc with a peak value at pH 6.0 and 6.5, respectively. The sorption followed the Freundlich sorption model. More than 70% sorption occurred within 20 min and equilibrium was attained at around 90 min for the three sorbents. The metals sorption by zeolite 4A was higher than that by zeolite 13X and bentonite. The desorption studies were carried out using NaCl solution and the effect of NaCl concentration on desorption was also studied. Maximum desorption of 76% for cadmium and 80% for zinc occurred with 10% NaCl.     

Leachate Characterization and Assessment of Groundwater Pollution Near Municipal Solid Waste Landfill Site

Leachate and groundwater samples were collected from Gazipur landfill-site and its adjacent area to study the possible impact of leachate percolation on groundwater quality. Concentration of various physico-chemical parameters including heavy metal (Cd, Cr, Cu, Fe, Ni, Pb and Zn) and microbiological parameters (total coliform (TC) and faecal coliform (FC)) were determined in groundwater and leachate samples. The moderately high concentrations of Cl⁻, NO⁻ ₃, SO²⁻ ₄, NH⁺ ₄, Phenol, Fe, Zn and COD in groundwater, likely indicate that groundwater quality is being significantly affected by leachate percolation. Further they proved to be as tracers for groundwater contamination. The effect of depth and distance of the well from the pollution source was also investigated. The presence of TC and FC in groundwater warns for the groundwater quality and thus renders the associated aquifer unreliable for domestic water supply and other uses. Although some remedial measures are suggested to reduce further groundwater contamination via leachate percolation, the present study demand for the proper management of waste in Delhi.     

Cascading loss and loss risk multipliers amid a changing climate in the Pacific Islands

Human society has experienced, and will continue to experience, extensive loss and damage from worsening anthropogenic climate change. Despite our natural tendencies to categorise and organise, it can be unhelpful to delineate clean boundaries and linear understandings for complex and messy concepts such as loss and damage. Drawing on the perspectives of 42 local and regional Pacific Islander stakeholders, an underexplored resource for understanding loss and damage, we explore the complexity and interconnectedness of non-economic loss and damage (NELD). According to participants, Pacific Islander worldviews, knowledge systems and cosmologies often make it difficult to separate and evaluate NELD independently, challenging the nomenclature of NELD categories developed through international mechanisms. Instead, NELD understandings are often centred on the interdependencies between losses, including the cascading flow-on effects that can occur and the nature of some losses as risk multipliers (i.e. one loss creating the risk for further losses). Most notably, losses to biodiversity, ecosystem services and land are critically linked to, and have cascading effects on, livelihoods, knowledge, ways of life, wellbeing, and culture and heritage. We argue that loss and damage is not always absolute, and that there are NELD that are arguably reparable. Concerning, however, is that biodiversity loss, as a risk multiplier, was considered the least reparable by participants. We put forward that NELD understandings must consider interconnectivity, and that biodiversity and ecosystem conservation and restoration must be the focus for interventions to prevent irreparable and cascading losses from climate change in the Pacific Islands.     

Environmental impact of leaching of trace elements from fly ash dumps on aquatic ecosystems

Ten sampling points were selected in Kanhan River, situated near the ash dump sites of Koradi Thermal Power Plant, Nagpur. The leaching of trace elements from fly ash dumps was experimentally determined by acid digestion, batch leaching and toxicity characteristic leaching procedure tests. Elemental concentrations in river water, sediment, plankton and five commonly prevailing fish species (Catla catla, Labeo bata, Cyprinus carpio, Cirrhinus reba, Puntius ticto) were determined using a Flame Atomic Absorption Spectrophotometer during the pre-monsoon and post-monsoon seasons. Metal concentrations (Cr, Mn, Zn, Cu, Fe, Ni, Cu and Pb) in river water were higher during the pre-monsoon season compared to the post-monsoon season. Zn (30.65?mg/kg) was observed to be the most predominant metal in plankton during the pre-monsoon season while, during the post-monsoon season, Fe (21.19?mg/kg) showed the maximum concentration. Muscles of C. catla had metal concentrations (Cr, Mn, Zn, Fe, Cu and Pb) above the permissible limits of Food and Agricultural Organization (FAO 1983) during the pre-monsoon season. Bioaccumulation factor (BAF) was found highest for Cr (37.5) in muscles of C. catla during the pre-monsoon season, while BAF was observed to be maximum in L. bata for Cu (28.09), which may be detrimental for human consumption.     

GIS-based statistical model for the prediction of flood hazard susceptibility

At present, flood is the most significant environmental problem in the entire world. In this work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of Bengal basin, India. Fourteen flood causative factors extracted from different datasets like DEM, satellite images, geology, soil and rainfall data have been considered to predict FS. Three heuristic models and one statistical model fuzzy Logic (FL), frequency ratio (FR), multi-criteria decision analysis (MCDA) and logistic regression (LR) have been used. The validating datasets are used to validate these models. The result shows that 68.71%, 68.7%, 60.56% and 48.51% area of the basin is under the moderate to very high FS by the MCDA, FR, FL and LR, respectively. The ROC curve with AUC analysis has shown that the accuracy level of the LR model (AUC?=?0.916) is very much successful to predict the flood. The rest of the models like FL, MCDA and FR (AUC?=?0.893, 0.857 and 0.835, respectively) have lesser accuracy than the LR model. The elevation was the most dominating factor with coefficient value of 19.078 in preparation of the FS according to the LR model. The outcome of this study can be implemented by local and state authority to minimize the flood hazard.

     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

Identification of sources affecting fog formation using receptor modeling approaches and inventory estimates of sectoral emissions

Positive matrix factorization (PMF) was used to identify factors affecting fog formation in Kanpur during the ISRO-GBP land campaign-II (LC-II) in December 2004. PMF predicted factors were validated by contrasting the emission strength of sources in the foggy and clear periods, using a combination of potential source contribution function (PSCF) analysis and quantitative emission inventory information. A time series aerosol chemical data set of 29 days and 12 species was decomposed to identify 4-factors: Secondary species, Biomass burning, Dust and Sea salt. PMF predicted particle mass with a satisfactory goodness-of-fit (slope of 0.83 ± 0.17 and R² of 0.8), and strong species within 11–12% relative standard deviation. Mean contributions of anthropogenic factors were significantly higher during the foggy period for secondary species (2.9 ± 0.3) and biomass burning (1.2 ± 0.09) compared to the clear period. Local sources contributing to aerosols that mediated fog events at Kanpur, based on emissions in a 200 km × 200 km area around Kanpur city were thermal power plants and transportation (SO₂) and biofuel combustion (BC and OM). Regional scale sources influencing emissions during the foggy period, in probable source regions identified by PSCF included thermal power plants, transportation, brick kilns and biofuel combustion. While biofuel combustion and transportation are distributed area sources, individual point sources include coal-fired thermal power plants located in Aligarh, Delhi, Ghaziabad, Jhansi, Kanpur, Rae Bareli and Rupnagar and brick kilns located in Allahabad, Agra, Farrukhabad, Ghaziabad, Kanpur, Ludhiana, Lucknow and Rae Bareli. Additionally, in the foggy period, large areas of probable source regions lay outside India, implying the significance of aerosol incursion from outside India.