Landslide probability mapping by considering fuzzy numerical risk factor (FNRF) and landscape change for road corridor of Uttarakhand,India

Landslide poses severe threats to the natural landscape of the Lesser Himalayas and the lives and economy of the communities residing in that mountainous topography. This study aims to investigate whether the landscape change has any impact on landslide occurrences in the Kalsi-Chakrata road corridor by detailed investigation through correlation of the landslide susceptibility zones and the landscape change, and finally to demarcate the hotspot villages where influence of landscape on landslide occurrence may be more in future. The rational of this work is to delineate the areas with higher landslide susceptibility using the ensemble model of GIS-based multi-criteria decision making through fuzzy landslide numerical risk factor model along the Kalsi-Chakrata road corridor of Uttarakhand where no previous detailed investigation was carried out applying any contemporary statistical techniques. The approach includes the correlation of the landslide conditioning factors in the study area with the changes in land use and land cover (LULC) over the past decade to understand whether frequent landslides have any link with the physical and hydro-meteorological or, infrastructure, and socioeconomic activities. It was performed through LULC change detection and landslide susceptibility mapping (LSM), and spatial overlay analysis to establish statistical correlation between the said parameters. The LULC change detection was performed using the object-oriented classification of satellite images acquired in 2010 and 2019. The inventory of the past landslides was formed by visual interpretation of high-resolution satellite images supported by an intensive field survey of each landslide area. To assess the landslide susceptibility zones for 2010 and 2019 scenarios, the geo-environmental or conditioning factors such as slope, rainfall, lithology, normalized differential vegetation index (NDVI), proximity to road and land use and land cover (LULC) were considered, and the fuzzy LNRF technique was applied. The results indicated that the LULC in the study area was primarily transformed from forest cover and sparse vegetation to open areas and arable land, which is increased by 6.7% in a decade. The increase in built-up areas and agricultural land by 2.3% indicates increasing human interference that is continuously transforming the natural landscape. The landslide susceptibility map of 2019 shows that about 25% of the total area falls under high and very high susceptibility classes. The result shows that 80% of the high landslide susceptible class is contained by LULC classes of open areas, scrubland, and sparse vegetation, which point out the profound impact of landscape change that aggravate landslide occurrence in that area. The result acclaims that specific LULC classes, such as open areas, barren-rocky lands, are more prone to landslides in this Lesser Himalayan road corridor, and the LULC-LSM correlation can be instrumental for landslide probability assessment concerning the changing landscape. The fuzzy LNRF model applied has 89.6% prediction accuracy at 95% confidence level which is highly satisfactory. The present study of the connection of LULC change with the landslide probability and identification of the most fragile landscape at the village level has been instrumental in delineation of landslide susceptible areas, and such studies may help the decision-makers adopt appropriate mitigation measures in those villages where the landscape changes have mainly resulted in increased landslide occurrences and formulate strategic plans to promote ecologically sustainable development of the mountainous communities in India's Lesser Himalayas.

     

Multivariate assessment of outflow water quality in highly urbanized creek system: implication of natural and anthropogenic processes

Environmental Science and Pollution Research - Nutrient source and transport study in tropical creeks adjacent to megacities are sparse on a regional and global scale. High-frequency chemical data...     

Catalytic degradation of toxic organic dye using an aluminum-doped Cu0.4Zn0.6-xAlxFe2O4 (x = 0.0, 0.2, 0.4, 0.6) spinel ferrite in a photo-Fenton system

Catalytic activity of spinel ferrite in breaking down toxic dye materials are promising due to their uniqueness. In this study, aluminum-doped copper zinc ferrite, Cu_0.4Zn_0.6-xAl_xFe₂O₄ (x = 0.0, 0.2, 0.4, 0.6), a catalyst for toxic dye degradation is synthesized through chemical co-precipitation route. The formation of the spinel ferrite catalyst is initially confirmed by Fourier transform infrared spectra, which shows the frequency of metal-oxygen bond vibration at 539 and 427 cm⁻¹ attributed to the tetrahedral and octahedral sites respectively. Higher intensity sharp peak of X-ray diffraction for (311) plane is the evidence for the phase purity and the formation of spinel ferrite. The crystallite size is found to decrease with the increase of Al³⁺ ion. The surface structure of the obtained particles is investigated using a scanning electron microscope. Analyses of the material's magnetic characteristics using a vibrating sample magnetometer (VSM) revealed that it is, in fact, a soft magnet, as evidenced by the loop of its hysteresis, which is narrow. The catalytic degradation of methylene blue dye under the mechanism of the photo-Fenton process is studied with the obtained spinel ferrites and the result is found to be as high as 96.5%. The process follows pseudo-second order kinetics and the Langmuir isotherm.     

Seasonal dynamics of phytoplankton in response to environmental variables in contrasting coastal ecosystems

Environmental Science and Pollution Research - Seasonal distribution of phytoplankton community and size structure was assessed in three different tropical ecosystems of the western Bay of Bengal...     

Promoting e-mobility in India: challenges,framework, and future roadmap

The purpose of the research is to identify the critical challenges that are impeding the adoption of e-mobility in India. It also aims to give a roadmap how to address these challenges while taking into considerations concerns of all the relevant stakeholders. Based on an in-depth literature review, an exploratory research design is employed to delve deep into various aspects of e-mobility. This is followed by a three-phase Delphi technique to identify and rate the e-mobility challenges in the Indian context. The study successfully identifies four different categories of challenges and proposes integrative framework for e-mobility. Further, the research goes on to lay out the future roadmap for mass adoption of electric vehicles (EVs) in India. The research is novel in terms of presenting a holistic viewpoint on e-mobility in India. Its originality lies in identifying the major inhibitors obstructing EVs adoption in India and then suggesting the roadmap how to overcome these impediments for mass adoption of e-mobility.     

Distribution of suspended particulate matter with trace element composition and apportionment of possible sources in the Raniganj coalfield,India

Ambient air monitoring for suspended particulate matter was carried over a period of one year in some coal mining areas of the Raniganj coalfield. Concentrations of seven elements in suspended particulate matter were determined. The set of data obtained was analysed to determine the sources of trace elements by factor analysis. The data could be interpreted on the basis of five factors. These factors are attributed to various sources of particulate matter by noting the dependence of factors on the elements.     

An integrated assessment model for cross-country pipelines

The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India.     

Evaluation of the Industrial Source Complex short-term model in a large-scale multiple source region for different stability classes

The original Industrial Source Complex Model (ISCST, 90346) and its latest version, the ISCST2 (92090), are evaluated for the 1- and 24-hour averaging periods, using six statistical parameters. The confidence limits on two parameters were obtained using the bootstrap, jacknife, seductive, and robust resampling techniques. Evaluation is conducted in a multiple point source environment and in all the different stability categories, using a year of meteorological data, emission inventory of the Lucas County, in Toledo, Ohio, and monitoring data from two nearby stations for the year 1987. This was representative of a real time situation in which the ISCST is generally applied for regulatory work. The sensitivity analysis shows that the ISC is a poor performing model in the 1-h and 24-h averaging period, neutral and stable categories, and modifications to it are necessary in order to improve its performance. Its performance changes depending on the chosen paired values. A better relative performance is observed in the unstable category relative to the neutral and stable categories. Improved model performance may be achieved by applying modifications to the physics on which the model is based.