Nature-inspired polymer photocatalysts for green NADH regeneration and nitroarene transformation.

Photocatalysis has emerged as a promising approach for generating solar chemical and organic transformations under the solar light spectrum, employing polymer photocatalysts. In this study, our aim is to achieve the regeneration of NADH and fixation of nitroarene compounds, which hold significant importance in various fields such as pharmaceuticals, biology, and chemistry. The development of an in-situ nature-inspired artificial photosynthetic pathway represents a challenging task, as it involves harnessing solar energy for efficient solar chemical production and organic transformation. In this work, we have successfully synthesized a novel artificial photosynthetic polymer, named TFc photocatalyst, through the Friedel-Crafts alkylation reaction between triptycene (T) and a ferrocene motif (Fc). The TFC photocatalyst is a promising material with excellent optical properties, an appropriate band gap, and the ability to facilitate the regeneration of NADH and the fixation of nitroarene compounds through photocatalysis. These characteristics are necessary for several applications, including organic synthesis and environmental remediation. Our research provides a significant step forward in establishing a reliable pathway for the regeneration and fixation of solar chemicals and organic compounds under the solar light spectrum.

Comparison of different rainfall products with gauge-based measurements over Narmada River Basin, India.

The present study evaluates and compares the performance of different rainfall products, namely, Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), India Meteorological Department (IMD) gridded, Prediction of Worldwide Energy Resource (POWER), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record (PERSIANN-CDR) with gauge-based measurements over Narmada River basin, India. The ground-based daily rainfall data (1981-2020) of 11 gauging stations have been collected from the Water Resources Department, Madhya Pradesh and the evaluation of rainfall product has been accomplished on a point-to-grid basis (nearest neighbor method) at annual and seasonal scales with the help of continuous and categorical statistical metrics. The results reveal a strong positive correlation (> 0.75) between rainfall estimates of different products and gauge-based measurements at annual scale demonstrating higher similarity in rainfall estimates and observed data, whereas seasonal estimates have exhibited comparatively weaker relationship. Likewise, percent bias (PBIAS) demonstrates least bias in annual and monsoon rainfall estimates and high in other seasons. These findings reveal that rainfall estimates tend to improve with increasing time scale (season to annual). However, majority of the rainfall products have overestimated the low rainfall (western region) and underestimated the high rainfall (eastern and southeastern regions). Further, the values of critical success index (CSI) indicate IMD gridded product outperforms in detecting rainfall events accurately followed by POWER, PERSIANN-CDR, and CHIRPS. These results suggest that IMD gridded estimates provide the best alternate to ground-based rain measurements. However, rainfall estimates from POWER, PERSIANN-CDR and CHIRPS can also be used in various hydrometeorological investigations over Narmada River basin.

Comparative analysis of discharge and sediment flux from two contiguous glacierized basins of Central Himalaya, India.

In the present study, suspended sediment load (SSL), sediment yield and erosion rates in Pindari Glacier basin (PGB) and Kafni Glacier basin (KGB) have been estimated using daily discharge and suspended sediment concentration (SSC) data for three ablation seasons (2017-2019). For this, one meteorological observatory and two gauging sites have been established at Dwali (confluence point), and water samples have been collected twice in a day for high flow period (July to September) and daily for lean period (May, June and October). An area-velocity method and stage-discharge relationship has been established to convert water level into discharge (m3 s-1). For estimating SSC (mg/l), collected water samples have been filtered, dried, analysed and confirmed with an automatic suspended solid indicator. Further, SSL, sediment yield and erosion rates have been computed using SSC data. The results reveal that mean annual discharge in PGB (35.06 m3 s-1) has been found approximately 1.7 times higher than KGB (20.47 m3 s-1). The average SSC and SSL in PGB have been observed about 396.07 mg/l and 1928.34 tonnes, and in KGB, it is about 359.67 mg/l and 1040.26 tonnes, respectively. The SSC and SSL have followed the pattern of discharge. A significant correlation of SSC and SSL has been found with discharge in both the glacierized basins (p < 0.01). Interestingly, average annual sediment yield in PGB (3196.53 t/km2/yr) and KGB (3087.23 t/km2/yr) have been found almost identical. Likewise, the erosion rates in PGB and KGB have been witnessed about 1.18 and 1.14 mm/yr, respectively. Sediment yield and erosion rates in PGB and KGB have been found in correspondence with other basins of Central Himalaya. These findings will be beneficial for engineers and water resource managers in the management of water resources and hydropower projects in high-altitude areas and in the planning and designing of water structures (dams, reservoirs etc.) in downstream areas.

Changes in agricultural land use and its consequences on crop productivity, diversity, and food availability in an agriculturally developed state of India.

The present study, covering a period of 52 years (1966-2017), explores changes in agricultural land use and its consequences on crop productivity, diversity, and food availability in Haryana, an agriculturally developed state of India. The time series data on different parameters (area, production, yield, etc.) were collected from the secondary sources and analyzed with the help of compound annual growth rate, trend tests (simple linear regression and Mann-Kendall), and change point detection tests such as Pettitt, standard normal homogeneity, Buishand range, and Neumann ratio. Apart from above, the relative share of area and yield to total change in output was determined using decomposition analysis. The results revealed that agricultural land use became intensive and underwent significant alteration with multifold shifting in area from coarse cereals (maize, jowar, and bajra) to fine food grains (wheat and rice). The yield of all crops, especially wheat and rice witnessed a significant increase which subsequently led to an upsurge in their production. However, the production of maize, jowar, and pulses recorded negative growth despite of an increase in their yield. The results also revealed manifold increase in use of modern key inputs during the first two periods (1966-1985), but afterwards input use rate slowed down. Additionally, the decomposition analysis revealed that yield effect remained positive in changing the production of all crops, but area contributed positively only in wheat, rice, cotton, and oilseeds. The major findings of this study imply that the production of crops can be enhanced only through improvement in yield because there is no further scope left for horizontal expansion in cultivable area of the state.

Exploring spatial and temporal drought over the semi-arid Sahibi river basin in Rajasthan, India.

Rajasthan state of India is prone to recurrent droughts; hence, exploring drought severities over the semi-arid Sahibi river basin is crucial for drought management. To investigate drought severity, the Rainfall Anomaly Index (RAI) was applied at two time spans, such as annual (January to December) and the monsoon season (June to September), using long-term daily rainfall data (1961-2017) for nine rain gauge stations. Similarly, for the examination of various drought characteristics like magnitude, duration and intensity, run theory analysis was used. Trends in rainfall, drought severity, magnitude, duration and intensity were computed by employing both parametric (simple linear regression) and non-parametric (Mann-Kendall and Sen's slope) tests, while spatial pattern maps of rainfall and drought characteristics were prepared using geographical information system. The analysis of rainfall records revealed a declining trend in eastern and central parts, whereas remaining areas of the basin witnessed an increasing trend during two time spans. During the study period, drought occurrence varied both geographically and temporally. The extreme, severe and moderate drought events were more common during monsoon season. Amongst the stations, Tapukara, Bairath and Mundawar rain gauge stations experienced the largest number of drought events compared to other stations. At both time scales, the most extreme droughts in the Sahibi basin occurred in 1979, 1986, 1987, 1989 and 2002. At the annual time span, the basin had the longest drought duration of 300 days, with a drought magnitude of - 758.3 mm. Likewise, the Tapukara rain gauge station had the longest dry spell of 310 days, followed by Behrod and Kotkasim (306 days each), Kotputli and Tijara (305 days each) and Mundawar (303 days). Finally, the findings of this study are expected to be useful to agricultural scientists, policymakers and water resource managers.

Association between climatic variables and COVID-19 pandemic in National Capital Territory of Delhi, India.

Globally, since the end of December 2019, coronavirus disease (COVID-19) has been recognized as a severe infectious disease. Therefore, this study has been attempted to examine the linkage between climatic variables and COVID-19 particularly in National Capital Territory of Delhi (NCT of Delhi), India. For this, daily data of COVID-19 has been used for the period March 14 to June 11, 2020, (90 days). Eight climatic variables such as maximum, minimum and mean temperature (°C), relative humidity (%), bright sunshine hours, wind speed (km/h), evaporation (mm), and rainfall (mm) have been analyzed in relation to COVID-19. To study the relationship among different climatic variables and COVID-19 spread, Karl Pearson's correlation analysis has been performed. The Mann-Kendall method and Sen's slope estimator have been used to detect the direction and magnitude of COVID-19 trends, respectively. The results have shown that out of eight selected climatic variables, six variables, viz. maximum temperature, minimum temperature, mean temperature, relative humidity, evaporation, and wind speed are positively associated with coronavirus disease cases (statistically significant at 95 and 99% confidence levels). No association of coronavirus disease has been found with bright sunshine hours and rainfall. Besides, COVID-19 cases and deaths have shown increasing trends, significant at 99% confidence level. The results of this study suggest that climatic conditions in NCT of Delhi are favorable for COVID-19 and the disease may spread further with the increasing temperature, relative humidity, evaporation and wind speed. This is the only study which has presented the analysis of COVID-19 spread in relation to several climatic variables for the most densely populated and rapidly growing city of India. Thus, considering the results obtained, effective policies and actions are necessary especially by identifying the areas where the spread rate is increasing rapidly in this megacity. The prevention and protection measures should be adopted aiming at to reduce the further transmission of disease in the city.

Renewable Aromatics from Tree-Borne Oils over Zeolite Catalysts Promoted by Transition Metals.

Despite the ever-growing demand for benzene-toluene-xylene (BTX), the alternative route of production from tree-borne oils is rarely investigated and poorly understood. Here, we have synthesized a Zn-loaded Y-zeolite catalyst for the continuous production of bio-BTX from tree-borne oils (nonedible seed oil), e.g., neem oil. Our approach involves low-temperature selective cracking-dehydrogenation-aromatization of neem oil over metal-supported catalysts to xylene-rich aromatics. The physicochemical properties of the prepared catalyst were characterized using powder XRD, N2 physisorption, TEM, NH3-TPD, XPS, Py-FTIR, solid-NMR, and TG analyses. Mesoporous Y-zeolites with a pore diameter of 7.4 Šshowed better selectivity toward aromatics and were found to be the most effective catalyst for the aromatization process, especially for BTX. The aromatic yield was found to increase with the addition of Zn, and the highest conversion of 90-94% with an ∼75% BTX yield was achieved with the ZnY catalyst. During aromatization, a sizable number of short alkanes and olefins were also obtained on acidic Y-zeolites. The off-gas composition shows the presence of ∼45% C2-C4 olefins with 8.9% H2. The incorporation of Zn species can promote the dehydrogenation activity, and the subsequent aromatization required a suitable pore network. The optimized ZnY catalyst inspires the formation of toluene and xylenes, inhibiting the formation of benzene and gaseous alkanes.