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Amidst the bleak picture of increasing joblessness and indebtedness presented by the National Sample Survey's employment surveys and debt surveys, a minimum standard of living for the nation's poor seems to be under threat. In response to this, recent schemes inspired by the Universal Basic Income debates appeared to have been designed more for political considerations, and have glaring identification issues and have been exclusionary. Rather than adopting a quasi-UBI as suggested in the Economic Survey of 2017 and doing away with many existing developmental programmes, this paper makes a case for, and presents the design of, a much better method targeting of transfers as a supplement, keeping fiscal as well as labour-market outcomes in mind. The sudden exogenous shock of COVID-19 to the incomes of the poor has made the case of a minimum income guarantee (MIG) for the poor more urgent. Had a MIG already been in place by early 2020, it would only have required a ramping up of the transfers to protect the incomes of the poor.

Landfilling is a cost‐effective method, which makes it a widely used practice around the world, especially in developing countries. However, because of the improper management of landfills, high leachate leakage can have adverse impacts on soils, plants, groundwater, aquatic organisms, and, subsequently, human health. A comprehensive survey of the literature finds that the probabilistic quantification of uncertainty based on estimations of the human health risks due to landfill leachate contamination has rarely been reported. Hence, in the present study, the uncertainty about the human health risks from municipal solid waste landfill leachate contamination to children and adults was quantified to investigate its long‐term risks by using a Monte Carlo simulation framework for selected heavy metals. The Turbhe sanitary landfill of Navi Mumbai, India, which was commissioned in the recent past, was selected to understand the fate and transport of heavy metals in leachate. A large residential area is located near the site, which makes the risk assessment problem both crucial and challenging. In this article, an integral approach in the form of a framework has been proposed to quantify the uncertainty that is intrinsic to human health risk estimation. A set of nonparametric cubic splines was fitted to identify the nonlinear seasonal trend in leachate quality parameters. LandSim 2.5, a landfill simulator, was used to simulate the landfill activities for various time slices, and further uncertainty in noncarcinogenic human health risk was estimated using a Monte Carlo simulation followed by univariate and multivariate sensitivity analyses.

This book will shed light on a cutting-edge technological platform that gives digital experts, creatives, and business executives enormous economic possibilities.It provides insight into the green Metaverse, and an innovative technology that can be used in achieving of the SDGs 2030.

With the launch of the Swachh Bharat Mission (SBM), India accelerated access to improved sanitation in a 'mass movement' emphasising people's participation and political leadership. However, SBM continues to be implemented at the administrative unit of districts, disassociated from the political and electoral units of Parliamentary Constituencies (PC). We provide estimates of India's 543 PCs by their performance on three important Water Sanitation and Hygiene (WASH) indicators: unsafe disposal of child stool, unimproved drinking water supply, and unimproved sanitary facilities. We used multilevel modelling to generate precision-weighted estimates of each indicator at PC-level, based on recently developed methodologies linking cluster GPS data from the National Family Health Survey (NFHS), 2016 to potential PCs. We found very high heterogeneity across PCs ranging from 0.95 per cent–95.85 per cent for unsafe stool disposal, 0.35 per cent–64.17 per cent for unimproved drinking water source, and 0.19 per cent–90.69 per cent for unimproved sanitation facility. Unsafe child stool disposal and unimproved sanitary facility were strongly correlated ( r = 0.85, Pearson and r = 0.83, Spearman). Monitoring of SBM data at the PC level will allow parliamentarians to effectively improve WASH conditions in their constituencies, while accounting for critical between-PC variability that may be obfuscated in an approach focussed on state or district means.