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This study examines the asymmetric effect of economic policy uncertainty (EPU) on life and non-life insurance consumption in India using monthly data from April 2004–October 2020. The paper has employed a nonlinear autoregressive distributed lag (NARDL) model with a structural break. The results reveal that there exists an asymmetric effect of EPU on life insurance as well as non-life life insurance consumption. A negative relationship is found between EPU and insurance consumption in both life and non-life insurance. Based on the findings, the study suggests the policymakers to consider the asymmetric effects of EPU while formulating insurance-related policies in India. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance is raging, but large size of India limits comprehensive exploration. This demands a sample like sewage, which could represent a large population and is often reported to harbor resistant microbes. Here, we did pan-India sewage sampling and studied the antibiotic resistance pattern in the microbial community. We used culture-based antibiotic susceptibility assays and estimated the level of antibiotics present at each site. We found high antibiotic resistance across all cities of India with more diversity of resistance profiles in bigger cities as compared to smaller ones. Bacillus and Pseudomonas were the most common, predominant resistant genera across Indian cities and many sites harbored multi-drug resistant phenotypes. Antibiotic concentrations were below recommended limits at all sites and thus high resistance is not likely caused solely due to antibiotics. Sewage proved to be a good representative for rapidly studying antibiotic resistance in a big country and for similar epidemiological strides. [ABSTRACT FROM AUTHOR]

Purpose: The paper investigates the effects of climate change along with ecological and carbon footprint on rice crop production in India during 1982–2016. Design/methodology/approach: The autoregressive distributed lag (ARDL), canonical cointegration regression (CCR) and fully modified ordinary least square (FMOLS) models are used in the paper. Findings: A long-run relationship is found between climate change and rice production in India. Results report that ecological footprint and carbon footprint spur long-term rice production. While rainfall boosts rice crop productivity in the short term, it has a negative long-term impact. Further, the findings of ARDL models are validated by other cointegration models, i.e., the FMOLS and CCR models. Research limitations/implications: This study provides insights into the role of ecological footprint and carbon footprint along with climate variables in relation to rice production. Originality/value: In the literature, the effects of ecological and carbon footprint on rice production are missing. Therefore, this is the first study to empirically examine the impact of climate change along with ecological footprint and carbon footprint on rice production in India. [ABSTRACT FROM AUTHOR]

The present study aims to examine the impact of climate change on wheat and rice yield in Punjab, India, during 1981–2017. The study employs fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and pooled mean group (PMG) approaches. The Pedroni cointegration has established a long-run relationship of climate variables with rice and wheat crops. FMOLS and DOLS models show that minimum temperature has a positive effect on both wheat and rice. In contrast, the maximum temperature is found to be negatively contributing to both crops. Rainfall has a significant adverse impact on the production of wheat. In the study period, seasonal rainfall has been found detrimental for the production of wheat and rice crops, indicating that excess rainfall proved counterproductive. Moreover, the Dumitrescu-Hurlin causality test has revealed a unidirectional causality running from minimum temperature, rainfall, and maximum temperature for rice and wheat production. The findings of the study suggest that the government should invest in developing stress-tolerant varieties of wheat and rice, managing crop residuals to curb other environmental effects, and sustaining natural resources for ensuring food security. [ABSTRACT FROM AUTHOR]

During August 2018 and 2019 the southern state of India, Kerala, received unprecedented heavy rainfall, which led to widespread flooding. We aim to characterize the convective nature of these events and the large-scale atmospheric forcing, while exploring their predictability by three state-of-the-art global prediction systems: the National Centers for Environmental Prediction (NCEP)-based India Meteorological Department (IMD) operational Global Forecast System (GFS), the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), and the Unified Model–based NCUM being run at the National Centre for Medium Range Weather Forecasting (NCMRWF). Satellite, radar, and lightning observations suggest that these rain events were dominated by cumulus congestus and shallow convection with strong zonal flow leading to orographically enhanced rainfall over the Ghats mountain range; sporadic deep convection was also present during the 2019 event. A moisture budget analyses using the fifth major global reanalysis produced by ECMWF (ERA5) and forecast output revealed significantly increased moisture convergence below 800 hPa during the main rain events compared to August climatology. The total column-integrated precipitable water tendency, however, is found to be small throughout the month of August, indicating a balance between moisture convergence and drying by precipitation. By applying a Rossby wave filter to the rainfall anomalies it is shown that the large-scale moisture convergence is associated with westward-propagating barotropic Rossby waves over Kerala, leading to increased predictability of these events, especially for 2019. Evaluation of the deterministic and ensemble rainfall predictions revealed systematic rainfall differences over the Ghats mountains and the coastline. The ensemble predictions were more skillful than the deterministic forecasts, as they were able to predict rainfall anomalies (greater than three standard deviations from climatology) beyond day 5 for August 2019 and up to day 3 for 2018. Significance Statement: The purpose of this study is to understand and unravel the large-scale mechanism behind the unprecedented heavy rainfall over Kerala, India, during August 2018 and 2019. The study brings out the importance of probabilistic rainfall predictions for extreme heavy rainfall events. The study reveals that large-scale moisture convergence plays a significant role in the extreme rain of August 2018 and 2019. The extreme rainfall of August is associated with a westward-propagating barotropic Rossby wave. The study also demonstrates that ensemble forecasts of extreme rain by the state-of-the-art prediction systems of GFS, IFS, and NCUM are skillful for longer lead times compared to deterministic models and, therefore, can provide better early warnings to the society. [ABSTRACT FROM AUTHOR]

Indian summer monsoon circulation can be characterized by mean tropospheric temperature (TT) gradient between ocean and land. Two major heat sources, one near the Myanmar Coast and the other near the Western Ghats play seminal role in defining this TT gradient. While both regions are characterized by very similar orographic features, there are significant differences in frequency of occurrence of precipitating clouds and their characteristics even when the amount of rain in June-July months is almost same in the two regions. Deeper (shallower) clouds appear more frequently over the Myanmar Coast (the Western Ghats). There is a sharp decrease in amount of rainfall from June-July to August-September in both the areas. Rather counter intuitively, during the June-July-August-September season, low and moderate rains contribute more to the total rain in the Myanmar Coast while heavy rains contribute more to the total rain in the Western Ghats. Western Ghats also gets more intense rains but less frequently. With significant differences in moisture availability, updraft, amount and characteristics of cloud condensate in the two regions, this study proposes that the nontrivial differences in features between them could be explained by linkages between cloud microphysics and large scale dynamics. Presence of more cloud liquid water and the role of giant cloud condensation nuclei reveals dominance of warm rain process in the Western Ghats whereas more cloud ice, snow and graupel formation in the Myanmar Coast indicates stronger possibility of cold rain coming from mixed phase processes. Stronger heating caused by mixed phase process in the mid and upper troposphere in the Myanmar Coast and its feedback on buoyancy of air parcel explains the appearance of deeper clouds. Thus, our study highlights importance of mixed phase processes, a major cause of uncertainty in GCMs. [ABSTRACT FROM AUTHOR]

Sewage wastewater pollutes water and poses a public health issue but it could also prove useful in certain research domains. Sewage is a complex niche relevant for research concerning 'one-health', human health, pollution and antibiotic resistance. Indian gut microbiome is also understudied due to sampling constraints and sewage could be used to explore it. Ostensibly, Indian sewage needs to be studied and here, we performed a cross-sectional pan-India sewage sampling to generate the first comprehensive Indian sewage microbiome. Indian sewage showed predominance of Burkholderiaceae, Rhodocyclaceae, Veillonellaceae, Prevotellaceae, etc. and has high representation of gut microbes. The identified gut microbes have overrepresentation of Veillonellaceae, Rikenellaceae, Streptococcaceae, and Bacillaceae. Imputed metagenomics of sewage microbiome indicated dominance of transport, motility, peptidases, amino acid metabolism, and antibiotic resistance genes. Microbiome-disease associations drawn using simple decision tree and random forest analysis identified specific microbes as potential predictors of diabetes and obesity in a city. Altogether, we generated the first Indian sewage microbiome and our non-invasive, high-throughput workflow could be emulated for future research, wastewater-based epidemiology and designing policies concerning public health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)