The growing population and rapid urbanization are significant challenges for Indian cities. Pune City generates nearly 2,258 tonnes of waste per day. Pune’s informal waste sector has demonstrated remarkable efficiency, cost-effectiveness, and self-sustainability. Moreover, it contributes to favorable economic and social outcomes for the city. With the support of the self-help group SWaCH Seva Sahakari Sanstha Maryadit, Pune, the municipal solid waste management model has successfully achieved a remarkable 95 percent segregation rate. Implementing the Pune municipal solid waste management model showcases the active and efficient engagement of informal waste workers in the collection and resource utilization process. This underscores the possibility of favorable economic, social, and environmental results stemming from collaborations between municipalities and waste pickers. This paper looks at the role of SWaCH in line with Pune Municipal Corporation towards the present waste management system. Primarily reliant on labor, this model accomplishes recycling tasks at a notably lower cost compared to conventional mechanized and centralized waste management approaches. It can also accomplish high recycling levels and relatively considerable plastic waste segregation. Promoting the retrieval of valuable materials, especially plastics, for local and global recycling enterprises actively contributes to the advancement of a circular urban waste management approach. The objective of this research is to explore and provide a realistic understanding of Pune’s current status of waste generation, collection, transportation, and disposal. Apart from the SwaCH-PMC model, the paper also focuses on plastic waste recycling, the Red Dot Campaign towards sanitary waste, and household e-waste management in Pune.

Diseases caused by bacteria, fungi, and viruses are a problem for many crops. Farmers have challenges when trying to evaluate their crops daily by manual inspection across all forms of agriculture. Also, it is difficult to assess the crops since they are affected by various environmental factors and predators. These challenges can be addressed by employing crop disease detection approaches using artificial intelligence-based machine learning and deep learning techniques. This paper provides a comprehensive survey of various techniques utilized for crop disease prediction based on machine learning and deep learning approaches. This literature review summarises the contributions of a wide range of research works to the field of crop disease prediction, highlighting their commonalities and differences, parameters, and performance indicators. Further, to evaluate, a case study has been presented on how the paradigm shift will lead us to the design of an efficient learning model for crop disease prediction. It also identifies the gaps in knowledge that are supposed to be addressed to forge a path forward in research. From the survey conducted, it is apparent that the deep learning technique shows high efficiency over the machine learning approaches, thereby preventing crop loss.

This article discusses the major challenges related to greenhouse gas (GHG) emissions in the electricity sector and their impact on global climate change. The electricity sector is responsible for about a quarter of total global GHG emissions. To address these challenges, Life Cycle Assessment (LCA) is used to measure the environmental impact of different energy sources and electricity generation and distribution processes. The circular economy is presented as a promising approach to reducing the carbon footprint of the electricity sector. By optimizing the use and value of materials throughout their life cycle, this approach contributes to waste minimization and resource efficiency. Morocco is committed to reducing its GHG emissions and has adopted policies and regulatory frameworks to combat climate change. This study aims to calculate the climate change impacts of electricity distribution phases by applying a life-cycle approach to the case of an electricity distribution company in Morocco. This assessment makes it possible to identify significant contributors from each area. In the context of this company, it is a question of demonstrating how the application of the principles of the circular economy concepts contributes to the reduction of greenhouse gas emissions, in particular, that of scope 3. This study may be useful for other similar companies.

The Vamanapuram River Basin (VRB) is home to a diverse range of plant species, including 152 distinct species from 50 botanical families. Poaceae, Leguminosae, Araceae, and Aseraceae are the most abundant, with 13 species. Euphorbiaceae, Acanthaceae, Apocynaceae, and Rubiaceae also contribute to the biodiversity hotspots. The VRB’s vegetation profile is characterized by a dynamic interplay of plant forms and ecological niches, with 74 herbs, 30 shrubs, 12 grasses, 1 liana, and 35 towering trees. The Poaceae family thrives in this environment due to hydrological factors. The sampling sites P6 and P5 exhibit high relative frequency and density, with key species like Macaranga peltata, Ficus hispida, and Swietenia macrophylla. Diversity indices like the Shannon-Wiener diversity index reaffirm the VRB’s tropical forest character. Beta-diversity patterns reveal unique plant species distribution dynamics among different panchayaths, emphasizing their ecological complexities. The study emphasizes the demand for specialized management and conservation techniques in this environmentally active region.

Sawdust, a product of the forest industry is mostly left untreated as solid waste. This phenomenon is well observed along the Lagos Lagoon in Nigeria where hundreds of trees are cut daily by sawmills to deliver wood for mainly the furniture industry. Different types of trees are utilized in this manner and the massive amounts of sawdust produced as a result of these activities are polluting the environment causing health risks for humans and animals. Cellulose, a glucose bio-polymer is a major structural component of sawdust and could be developed as a renewable energy resource should the cellulose be degraded into glucose, a fermentable sugar. This saccharification was done with Aspergillus niger cellulase and to make the cellulose more susceptible for cellulase action the sawdust was delignified with hydrogen peroxide. Both delignified and non-delignified sawdust were treated with the cellulase enzyme at incubation temperatures of 30°C, 40°C, 50°C, and 60°C. Delignification proved to be effective as an increased amount of sugar was released from all delignified sawdust materials relative to the non-delignified materials when saccharified with A. niger cellulase. Most of the materials were degraded at an incubation temperature of 40°C and 50°C and the highest percentage saccharification of 58% was obtained during the degradation of delignifed cellulose from the tree, Ricindendron heudelotti

The study presented aims to find the most appropriate climate dataset for the data-scarce Jalaur River Basin (JRB), Iloilo, Philippines, by evaluating the statistical performance of five rainfall datasets (APHRODITE, CPC NOAA, ERA5, SA-OBS, and PGF-V3) with resolutions of 0.25° and 0.5° having a time domain of 1981 to 2005. Bilinear interpolation implemented through Climate Data Operator (CDO) was used to extract and process grid climate datasets with Linear scaling as bias correction to minimize product simulation uncertainties. The datasets were compared to the lone meteorological station nearest to JRB investigated at monthly and annual timescales using six statistical metrics, namely, Pearson’s correlation coefficient (r), coefficient of determination (R2), modified index of agreement (d1), Kling-Gupta efficiency, Nash-Sutcliffe efficiency (NSE), and RMSE-observations standard deviation ratio (RSR). The results indicate a strong positive correlation with the observed data for both rainfall and temperature (r > 0.8; R2, d1 > 0.80). Although graphical observation shows an underestimation of rainfall, goodness-of-fit values indicate very good model performance (NSE, KGE > 0.75; RSR < 0.50). In terms of temperature, variable responses are observed with significant overestimation for maximum temperature and underestimation for minimum temperature. SA-OBS proved to be the best-performing dataset, followed by ERA5 and PGF-V3. These key findings supply useful information in deciding the most appropriate gridded climate dataset for hydrometeorological investigation in the JRB and could enhance the regional representation of global datasets.

With the rapid advancement of Remote Sensing Technology, monitoring the agricultural land has become a facile task. To surveil the growth of paddy crops and provide detailed information regarding monitoring soil, drought, crop type, crop growth, crop health, crop yield, irrigation, and fertilizers, different types of remote sensing satellites are used like Landsat 8, Sentinel 2, and MODIS satellite. The main aim of Landsat 8, Sentinel 2 and MODIS satellites is to monitor the land and vegetation area and to provide data regarding agricultural activities. Each of these satellites possesses a different spectral band, resolution, and revisit period. By using the remote sensing spectral indices, different types of vegetation indices are calculated. This survey paper provides comprehensive about Remote Sensing and the major parameters that influence for growth of paddy crops, like soil and water, and the future scope of agriculture and its demand in research is discussed.

The in-lab incubation experiments were conducted to identify the passivation effect of corn vinasse biochar, which was prepared at different temperatures, on heavy metal Pb in paddy soil of the Pb-Zn mining area. The results showed that after 30 days of biochar amended to the soil, the soil pH and organic carbon content increased by 2.72%-8.47% and 27.79%-65.26%, respectively. The CO32- and OH- contained in corn vinasse biochar could react with Pb and generate carbonate and hydroxide of Pb. In comparison with the treatment control, the bioavailable fractions of Pb were reduced by 26.6%, 23.30%, 26.95%, and 35.33%, respectively, in biochar-amended treatments. Exchangeable fractions of Pb decreased by 21.50%, 21.33%, 22.58%, and 22.58% for the treatment 3% (300°C), 6% (300°C), 3% (600°C), and 6% (300°C) corn vinasse biochar, respectively, compared with the treatment control. As a whole, corn vinasse biochar could effectively promote the transformation of Pb in soil from the exchangeable fractions into the Fe-Mn oxide-bound fractions and residue fractions, with a significant passivation effect for Pb in soil and more effective passivation by high-temperature preparation and increased dosage of biochar.

Lignin, being highly resistant, needs to be eliminated in the process of extraction of soluble reducing sugar and bioethanol production from lignocellulosic biomass. In the present work, pretreatment of sugarcane bagasse (SCB) was performed using NaOH of various concentrations (1-5%) to facilitate delignification. The hydrolysis efficiency of pretreated SCB was evaluated at different reaction times by the production of reducing sugar using the Cellic CTec2 enzyme. The maximum cellulose content of 57.6% and lignin removal of 62.04% were observed with 2% sodium hydroxide at 121°C autoclaved for 60 min. The hemicellulose content decreased with increasing NaOH concentration with the maximum decrease of 13.6% from native bagasse having 26.5% xylan content. The microstructure, morphology, and chemical composition of SCB were analyzed using Field Emission Scanning Electron Microscopy (FESEM), Fourier Transform InfraRed (FTIR), and XRD. The hydrolysis with 10 FPU.g-1 of enzyme at 48 h of reaction time shows a maximum yield of 12.34 g.L-1 corresponding to 55.53 ± 0.45% at 2% NaOH pretreated SCB. This study claims that lignin components exhibited the highest susceptibility to NaOH pretreatment, which directly affects enzymatic hydrolysis.

Heavy metals like cadmium (Cd), mercury (Hg), bismuth (Bi), and arsenic (As) are potent and harmful poisonous sources that cause havoc on health conditions for the population of the world. However, the response of our crop species to these potent heavy metals-related toxicity is still left to be fully understood. It is a matter of great concern, as we are heavily dependent on crop species like rice, wheat, peas, etc. Our study here aims to learn about the defensive mechanism of Pisum sativum L. aided with putrescine and mycorrhiza against the stress created by Cd-related toxicity. We quantified physiological parameters such as the membrane-related injury and stability index. We further measured the total free proline content, lipid peroxidation content, and SOD activity. We executed our quantitative experiments on the stressed pea plants due to the exogenously applied Cd-toxicity in the presence and absence of mycorrhiza and putrescine. Insights of our significant results will improve the understanding of readers of the role of mycorrhiza and putrescine in improvising the tolerance level of a pea plant over Cd-related toxicity.