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Increasing the share of weather-dependent renewables in the electricity grid is essential to deeply decarbonize the electricity system. Wind and solar "droughts" or low generation days can severely impact grid stability in a renewable-rich grid. This paper analyzes for the first time wind, solar, and hybrid energy-droughts in India using a stochastic weather generator. Available literature analyze the observational data that is of limited duration (30–40 years). Therefore, discussion of low-probability high-impact renewable energy-droughts that have long return periods (in the range of 30 years) is limited in the literature. The present study seeks to address this research gap by exploring the risk of wind, solar, and wind-solar powered energy-droughts based on simulated long time series (5000 years). It is found that the weather generator captures mean, seasonality, and correlation between wind speed and solar irradiance and is therefore used to estimate return periods of extreme wind and solar-droughts. Our analysis shows that wind-droughts are more intense than solar-droughts in India. We examine the role that wind-solar hybridization can play in offsetting low wind energy episodes. The benefits of hybridization are regionally dependent. In South India, hybrid plants have advantages over either wind or solar plants alone. In comparison, for Rajasthan, the benefits of hybridization are limited. When one of the regions (South India or Rajasthan) has a renewable drought, the other region has only a 10% probability of having a similar drought. Our findings highlight the need for having robust inter-regional grid connections to mitigate regional level renewable droughts. • Stochastic weather generator (long timeseries) is used for drought analysis. • Wind-droughts are more intense than solar-droughts over India. • Wind-solar hybridization reduces drought intensity more effectively in South India. • Incentives for hybrid plants should be region specific. • Hybrid energy droughts are complementary between regions (south and west India). [ABSTRACT FROM AUTHOR]

• Disruptions during the COVID-19 lockdown caused children to miss immunizations. • Government catch-up efforts substantially reversed these effects. • Yet, children that were due vaccinations during the lockdown remained 10–15% less likely to be immunized 4–5 months later. • Catch-up was more likely to be incomplete among children of low socioeconomic status. • Ensuring all children are fully immunized requires careful tracking and disaggregated data. Governments around the world suspended immunization outreach to control COVID-19 spread. Many have since resumed services with an emphasis on catch-up vaccinations. This paper evaluated immunization disruptions during India's March-May 2020 lockdown and the extent to which subsequent catch-up efforts reversed them in Rajasthan, India. In this retrospective observational study, we conducted phone surveys to collect immunization details for 2,144 children that turned one year old between January and October 2020. We used logistic regressions to compare differences in immunization timeliness and completed first-year immunization status among children that were due immunizations just before (unexposed), during (heavily exposed), and after (post-exposure) the lockdown. Relative to unexposed children, heavily exposed children were significantly less likely to be immunized at or before 9 months (OR 0.550; 95% CI 0.367–0.824; p = 0.004), but more likely to be immunized at 10–12 months (OR 1.761; 95% CI 1.196–2.591; p = 0.004). They were also less likely to have completed their key first-year immunizations (OR 0.624; 95% CI 0.478–0.816; p = 0.001) by the time of survey. In contrast, post-exposure children showed no difference in timeliness or completed first-year immunizations relative to unexposed children, despite their younger age. First-year immunization coverage among heavily exposed children decreased by 6.9 pp to 10.4 pp (9.7% to 14.0%). Declines in immunization coverage were larger among children in households that were poorer, less educated, lower caste, and residing in COVID red zones, although subgroup comparisons were not statistically significant. Disruptions to immunization services resulted in children missing immunization during the lockdown, but catch-up efforts after it was eased ensured many children were reached at later ages. Nevertheless, catch-up was incomplete and children due their immunizations during the lockdown remained less likely to be fully immunized 4–5 months after it lifted, even as younger cohorts due immunizations in June or later returned to pre-lockdown schedules. [ABSTRACT FROM AUTHOR]

• Comparative studies on the basis of presence and absence of minerals. • Discrimination of the mineral body from the settlements. • Pyrrhotite and limonite (iron ore) minerals have been traced. • Mixture Tuned Matched Filtering algorithm produces a better mineral map. Geology majorly deals with the structures, features, minerals, rocks, etc. of the planet Earth. Geologists are using the technology of remote sensing for structural interpretation and regional mapping. Ores and minerals identification are also done with the help of remote sensing. This paper is mainly focused on the identification of minerals and mapping with the help of various algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using airborne hyperspectral data. Minerals are identified on the basis of the visible and near-infrared spectral reflectance. Spectral reflectance is having absorption features at different positions and absorption peaks are used for the analysis of imagery. This technique provides surface mineralogical details. SAM algorithm mainly computes the angle between the unknown pixel spectrum and unique pixel spectrum. SFF algorithm matched the continuum removed the spectrum of the imagery pixel from the continuum removed reference spectra. MTMF algorithm detects the abundance of the minerals and removes the erroneous positive. Total 13 endmembers (minerals) were identified in the study area. These minerals are grouped into clay minerals, iron minerals, carbonate minerals, and other minerals. These endmembers are used for the mineral map creation from different algorithms. Algorithms produce the diverse kind of mineral map and these are compared with each other on the basis of the mineralogy and discrimination of mineralized region from settlements. Mineral map produced by MTMF algorithm provides convenient results with better accuracy than other algorithms. [ABSTRACT FROM AUTHOR]

• The adaptive coherence estimator and matched filtering methods are used to map rock phosphate in ASTER data. • The spectral maps of above spectral methods are integrated to delineate phosphate in dolomite. • The results are validated in the field using a qualitative colorimetric method. • Few important patches of phosphate in addition to the main mine are confirmed in the field. This paper applies reflectance spectroscopy and Advanced Space borne thermal emission reflection radiometer (ASTER) data processing to delineate dolomite-hosted rock phosphate around Udaipur City, Western India, using visible-near infrared (VNIR) and short wave infrared (SWIR) bands of the ASTER sensor. A number of ASTER image spectra and field spectra (resampled to ASTER bands) of pure dolomite and rock phosphate are compared and found to be consistent in terms of the presence of absorption minima at 2.3 µm for dolomite and the absence of the same feature in the spectra of the rock-phosphate. Before attempting spectral mapping, ASTER SWIR band data are clipped using the spatial extent of host rock; which has been prepared from the reference geological map and consequently updated using VNIR-SWIR derived image enhanced products at selected part of the study areas. Two sub-pixel spectral methods namely adaptive coherence estimator (ACE) and matched filtering (MF) methods are applied to ASTER SWIR bands to delineate rock-phosphate-rich zones within dolomite. The output images of the above algorithms are integrated in a principal component (PC) image to delineate phosphate pixels. A principal component; which has similar sign of Eigen vector loading for ACE and MF abundance image is used to delineate rock phosphate within dolomite. The results are validated in the field using a qualitative colorimetric method and also by comparing image spectra of spectrally anomalous zone with the ASTER resampled laboratory spectra of rock phosphate samples. A number of sporadic but important patches of phosphate rich zones in addition to the main surface exposures of the Jhamar Kotra Mine are confirmed in the field. The proposed method is a novel application of spectral mapping of phosphate deposits in dolomitic and carbonatic rocks and present approach of ASTER data processing can be used to delineate phosphate rich zones occurring within similar geological provinces in any parts of the world. [ABSTRACT FROM AUTHOR]

• Thermo-mechanical characteristics of two bentonites from India are presented. • Variation of swell pressures of bentonite with variation in thermal loading and densities is presented. • The development of time swelling curves for various thermal histories is presented. • The swell pressures of both the bentonite decreased with an increase in the thermal loading. The deep geological disposal system is an internationally adopted option for the disposal of high-level nuclear waste (HLW). It consists of a highly expansive bentonite, which is used as a buffer material and as a part of an engineered barrier system. Bentonite provides sufficient swelling pressure and low hydraulic conductivity to the barrier system giving long-term stability. The high-temperature waste canister in DGR and the variation in temperature due to thermal gradient impose a thermal loading on the compacted bentonite buffer and may alter the swelling pressures of the compacted bentonite. Hence it is necessary to investigate the influence of thermal loading on the swelling pressure of compacted bentonite. The paper discusses an assessments of swell pressures of two compacted bentonites (Barmer 1 (B 1) and Barmer 2 (B 2)) from Barmer district of Rajasthan, India with initial dry densities of 1.5 Mg/m3, 1.75 Mg/m3, and 2 Mg/m3 and subjected to 110 °C and 200 °C, hydrated with distilled water. The swelling load is recorded and compared with non-heated samples of same densities. Experimental and theoretical evidences indicated that the swelling pressure of heated compacted bentonite decreased with an increase in the temperature. Statistical analysis is also presented with the help of analysis of variance (ANOVA). [ABSTRACT FROM AUTHOR]

Summary Based on a study of how rural land brokers mediate the arrival of a Special Economic Zone in rural Rajasthan, this paper argues that theories of collective social capital cannot explain how networks, norms, and trust interact in a process of economic change. It then reconstructs Bourdieu’s distinct theory of individual social capital by showing how better-connected farmers are able to broker land and capture profits at the expense of fellow villagers, undermining trust, norms, and collective action. It argues that social capital is most plausibly seen as an aspect of social inequality that hinders inclusive development. [ABSTRACT FROM AUTHOR]

• A hybrid algorithm applying ST, HT and RBDT is designed for recognition of multiple PQ disturbances. • Designed HPQI and HPLI indices effectively detect and localize the CPQDs. • Proposed RBDT supported decision rules driven by features computed from HPQI and HPLI effectively classified the CPQDs. Classification accuracy higher than 98% is achieved. • Performance of algorithm is better compared to HT and RBDT based technique. • Algorithm is validated to recognize CPQDs incident on practical distribution network. Hence, it can be incorporated in online PQ monitoring devices. This paper proposes an algorithm based on the Stockwell transform (ST) and Hilbert transform (HT) to classify complex power quality disturbances (CPQDs). Two indices are used for detection and locating the CPQDs. The first index is the hybrid power quality index (HPQI), which is used to classify CPQDs. The Stockwell maximum values factor (SMVF), Stockwell summation values factor (SSVF), and Stockwell variance values factor (SVVF) are computed by utilizing the ST to process a voltage signal having a superimposed PQ disturbance. To compute the Hilbert index (HI), the voltage signal is also processed using the HT. The HPQI index is calculated by element-to-element multiplication of the SMVF, SSVF, SVVF, HI, and a weight factor (WF). The second index is the hybrid power quality disturbance time localization index (HPLI), which is used to locate the complex PQ events in a given time frame. For classification of investigated CPQDs, seven different features extracted from various indices defined using ST and HT are taken as input to the rule-based decision tree (RBDT). RBDT classifies the disturbances using simple decision rules, which has the merit of low computational time. The algorithm is able to correctly detect CPQDs with a 98% accuracy rate. The proposed algorithm outperforms the literature's algorithm, which is based on HT and RBDT. Furthermore, it is demonstrated that the algorithm effectively recognizes CPQDs that occur in real-time on a practical distribution network in Rajasthan State, India. [Display omitted] [ABSTRACT FROM AUTHOR]

In developing countries, urbanization and rapid population growth has resulted in a substantial increase in generation of Municipal Solid Waste (MSW). Safe collection, transportation and treatment of MSW are among the major issues for Indian cities. Poor MSW management practices have negative impact on public health, environment and climate change. India currently only treats 21% of MSW while the remainder disposed in unsanitary landfill sites with no recycling and treatment technologies. This paper reviews the existing MSW management practices, challenges and provides recommendations for improving MSW management for the city of Jaipur in Rajasthan, India. Despite being the state capital as well as the top tourist destination in northern part of India, there is no detailed study which reviews the waste management strategies of this city along with identifying the key challenges. The study reveals that the major challenges for MSW management in Jaipur include uncontrolled landfilling, inadequate public participation as well as failings of implementation of MSW legislation and waste conversion. Recommendations for improvement include public awareness campaigns, public-private partnership, investment in lined landfills, recycling and waste to energy techniques. Optimization models and life cycle assessment tools should be employed to minimize cost and the environmental impact of MSW management. This study will provide policy makers and private sector stakeholders to develop strategies for future planning, investment and execution of improved MSW management in Indian cities. [Display omitted] • In Jaipur city 50% MSW is treated while rest is subjected to unsanitary landfilling. • Indian cities have inadequate MSW management practices treating only 21% of MSW. • Lack of public participation, proper treatment techniques and sanitary landfill in the city. • Recycling facilities, waste to energy techniques and sanitary landfilling is required. • Role of optimization and LCA models in planning suitable MSW management practices. [ABSTRACT FROM AUTHOR]

Simplified remotely sensed hydrothermal alteration map of the Mundiyawas-Khera copper deposit and photomicrographs of the mineralized rocks comprising sericite (Ser) and scapolite (Scp), the major constituents of the phyllic alteration zone. • Volcanogenic copper mineralization in the Mundiyawas-Khera area is hosted by felsic volcanic rocks and dolomites. • Phyllic and propylitic alteration zones are good indicators of the copper mineralization. • Phyllic, argillic and propylitic alteration in the area was identified using the SWIR bands of ASTER. • This study identified potential copper mineralized zones in semi-concealed to concealed areas of the Alwar basin. This paper discusses the effectiveness of spectroscopic techniques for identifying hydrothermal alteration zones associated with the Mundiyawas-Khera copper deposit, Alwar Basin, western India, and assesses implications for mineral exploration targeting in the greater Alwar basin. Mineral specific SWIR bands of ASTER were spectrally enhanced to highlight areas of anomalous Al-OH and Mg-OH responses, representing key mappable expressions of the Mundiyawas-Khera copper deposit. The hydroxyl-bearing mineral zones were identified at 98% and 95% threshold pixels, respectively. Kaolinite ± scapolite, sericite (muscovite), tremolite and dolomite, contained in the felsic volcanic and dolomitic copper host rocks, were identified from spectroscopic data and corroborated with petrographic and XRD data. On this basis, distinct argillic, phyllic and propylitic hydrothermal alteration zones could be identified at Mundiyawas-Khera. The integrated approach presented here (i) identified a well defined phyllic alteration pattern in the felsic volcanic rocks, (ii) resulted in a comprehensive remotely sensed hydrothermal alteration map illustrating the spatial distribution of the copper-related hydrothermal alteration zones (i.e., an eastern argillic, a central phyllic, and a western propylitic zone), (iii) helped to delineate potential copper-rich zones coincident with a known lithostructural trend, and (iv) has implications for copper exploration in the greater Alwar basin. [ABSTRACT FROM AUTHOR]