Rice straw is one of the organic materials and natural residue of rice crop or paddy material and is the third-largest residue from agriculture after sugarcane bagasse and maize straw. Southeast Asian countries produce approximately 80% of rice production in the world. It leads to a large quantity of rice straw as a by-product every year. Surplus rice straw is a focal issue associated with storage of rice straw, removal of entire straw from the field, and very little time between the cultivation of the crop. Stubble burning is a quick, cheap, and efficient way to prepare the soil bed for wheat, the next crop. Rice straw has both nutrient and calorific values. Straw is the only organic material available in significant quantities to most rice farmers. About 40 percent of the nitrogen (N), 30 to 35 percent of the phosphorus (P), 80 to 85 percent of the potassium (K), and 40 to 50 percent of the sulfur (S) taken up by rice remains in vegetative plant parts at crop maturity. Straw is either removed from the field, burned in situ, piled or spread in the field, or incorporated in the soil. Open burning of the crop residue kills useful microflora of soil, leads to soil degradation, and contributes to harmful greenhouse gases such as SO2, NO2, CH4, N2O, carbon monoxide in the atmosphere including the hydrocarbon and particulate matter. Therefore, rice straw burning is a serious creator of environmental pollution. The study investigated environment-friendly options of rice straw such as bedding material for cattle, mushroom cultivation, nutrition in the soil, power generation, combustion material, pellet making, bio-gas, bio-ethanol, bio-char, acoustic material, 3D objects, cardboard and composite board, packaging materials, production of bio-composite, cement bricks, and handmade paper. The key purpose of this paper is to provide environmentally friendly alternatives to rice straw instead of open field burning.

Municipal solid waste deposition in metropolitan areas has become a major concern that, if not addressed, can lead to environmental degradation and possibly endanger human health. It is important to adopt a smart waste management system in place to cope with a range of waste materials. This research aims to develop a smart modelling method that could accurately predict and forecast the production of municipal solid waste. An integrated convolution neural network and air-jet system-based framework developed for pre-processing and data integration were developed. The results showed that machine learning algorithms could be used to detect different types of waste with high accuracy. The best performers were obtained from neural network models, which captured 72% of the information variation. The method proposed in this study demonstrates the feasibility of developing tools to assist urban waste through the supply, pre-processing, integration, and modelling of data accessible to the public from a variety of sources.

The objective of the present study was to prepare a record of the Residential, IUCN and WPA status of the birds recorded in four sites of Indore city. The study was of one-year duration (2018). The results showed that there were five species as winter migrants, one as summer migrant, six as local migrants, and 46 as resident species. Only one species, i.e. Psittacula eupatria was found to be in the near threatened category. According to WPA status, 5 species were Schedule I species, 1 schedule V, and 52 species as schedule IV species. These sites have a potential of augmentation of avian fauna shortly and these spaces abide by many species with a larger diversity than estimated. The present study is the first-ever record of avian species in the three sites of Indore city. The results of this study support the scope of conservation of these spaces for increasing the number of species shortly.

The textile industry occupies a significant hold on the global economy. This substantial industry often generates a large volume of effluents exceeding the permissible limit of discharge in the different regions of the world. Therefore, textile effluents act as pollutants altering the natural composition of various components of the environment. This paper discusses the impact of textile-based pollutants on agriculture including plants, soil, water and fisheries. The observed result is significant because textile effluents exert a widespread negative impact on the respective respondents, though plants show few positive effects. Prior treatment of textile wastewater is necessary before applying it to the soil, as there is a possibility of affecting the plant ecosystem via soil media. Plants are benefitted in terms of germination and growth, due to irrigation by textile effluents with proper dilution. The physical and biochemical properties of water streams along with aquatic organisms are impacted by these specific discharges, leading to even severe deterioration of particular living creatures. Pollutants released from various steps of textile processing have adverse effects on the environment, disturbing the food chain, ecosystem, and overall ecological balance.

All forms of life on earth including man have evolved in the presence of radiation and have always been exposed to them from the natural environment. The health effect from exposure to alpha particles depends greatly on how a person is exposed. If alpha-emitters are inhaled, swallowed, or get into the body through a cut, the alpha particles can damage sensitive living tissue. In this paper, investigations have been made to determine the presence of alpha activity in the air. Hence, the alpha activity was measured by collecting Airborne Particulate Matter (APM) non-simultaneously on Whatman filters from ten sampling sites in Kanyakumari District during the summer and winter seasons using a high volume sampling method. The sampling sites are characterized by different contributions from ore refining factories like Indian Rare Earths (IRE) Limited, mountain areas, some industrial, non-nuclear activities like tiles and brick factories in and around the Kanyakumari district. The alpha activity in airborne particulate matter collected was determined by Alpha Counter and their results were tabulated.

In this paper, the open-pit coal mine in semi-arid grassland was taken as the research object. The water samples of the open-pit coal mine and its surrounding areas were collected and the hydrochemical parameters were detected. The temporal and spatial distribution characteristics of the parameters such as pH, electrical conductivity, and dissolved oxygen in the groundwater were studied. The results showed that the groundwater in the study area was alkaline and brackish water. Climate factors might have a certain impact on the pH, conductivity, and dissolved oxygen of groundwater. The pH value of groundwater in the mining area was higher than that in the surrounding pastoral area, while the conductivity value of the mining area was between the pastoral area in the west and the Xilin river area in the east. The parameters of pH, conductivity and total dissolved solids of the four monitoring wells around the mining area showed a slow change or stable phenomenon in the vertical direction with the increase of groundwater depth. This study is of great significance to understand the characteristics of groundwater chemistry in mining areas and the rational development and utilization of groundwater resources.

Terrain characteristics and their evaluation usually come under geomorphological study and more particularly the applied geomorphological study (Prasad & Sarkar 2011). Foothills are a geographically defined zone having a gradual increase in elevation at the base of a mountain or hill range. Detailed assessment of the present terrain parameters of the study area using GIS is significant as it shows the influence on the landscape of the area. It is a prerequisite in effective management of the impact of transition upon the landscape and its natural resources for sustainable management. In the study, an attempt has been made to delineate the foothill belt of the Assam-Meghalaya border in Kamrup District, Assam using Geographical Information system (GIS), and remote sensing techniques. Datasets available from USGS Earth Explorer, i.e. Shuttle Radar Topographic Mission (SRTM) and Digital Elevation Model (DEM) are used for analyzing the elevation, contour, slope, and terrain characteristics. The present study aims at getting an information archive of the geomorphological and terrain characteristics of the Assam-Meghalaya foothills in Kamrup District, Assam, and its spatio-temporal variation.

The Shuaishui River originates from the southern mountainous area of Anhui Province and is an important water source for local residents. The ecological environment of this basin has been seriously damaged because of the effects of human disturbance. In August 2016, a field study of five units of the Shuaishui River Basin was conducted to understand the fish community structure and assess the ecological health status. A total of 43 fish species were collected from the entire river basin, and they belonged to 4 Orders, 10 Families, and 31 Genera. The maximum number of species belonged to the family Cyprinidae, and the main trophic guild was omnivorous fish. Among the five units, species number was the highest in unit 2 (27 species) and the lowest in unit 3 (12 species). The dominant species in the five units were mainly typical mountain-stream fish, such as Zacco platypus, Acrossocheilus fasciatus, and Vanmanenia stenosoma. In some areas, Varicorhinus barbatulus or Rhinogobius cliffordpopei also showed great dominance because of the impacts of the local habitat conditions. Redundancy analysis showed that altitude, water velocity, stream order, and water surface width were the main factors that influenced the distribution and species composition of the fish. Eigenvalues of the first two axes were 0.183 and 0.082 and explained 40.9% and 18.3% of the species-environment relationship variables, respectively. The ecological health of the five units and the entire basin was assessed based on the arithmetic mean of three indicators, namely, number of classification units, Shannon-Wiener index, and Berger-Parker dominance index. The results indicated that the ecological health status was relatively poor in unit 3, general in units 1 and 5, and good in units of 2 and 4. The status of the entire basin was general. To the best of our knowledge, this is the first comprehensive assessment of the ecological health of the Shuaishui River Basin, and it has great significance for the ecological management and protection of this basin.

The present study aimed to develop the activated carbon from fruit waste like sapota peel and to optimize the condition of developed activated carbon for complete removal of lead ions from the desired concentration of a lead solution. The activated carbon was prepared from sapota peel by using sulphuric acid. The physicochemical characterization of the obtained activated carbon was done for various parameters along with analysis of crystal nature (XRD) and structural morphology (SEM). The optimum conditions for adsorption were studied by altering pH (2-10), agitation speed (50-250 revolution per minute), temperature (10-60°C), adsorbent dose (0.02-0.14 g) and contact time (30-240 minutes). The optimized conditions necessary for complete removal of lead ions by the prepared adsorbent were pH - 5.5, agitation speed - 200 revolutions per minute, temperature - 60°C, time - 3 hours and adsorbent dose - 0.12 g. This study can be further helpful in designing the process of wastewater treatment for the removal of toxic metals from water particularly lead by adsorption.

In recent years, the field of Sustainable Smart Cities is rapidly burgeoning, and the related research carried out is unexplored, heterogeneous, and involves a plethora of issues. In this research, the framework for the Smart City Environmental Sustainability Index (SCESI) is defined and evaluated to guide the investments and monitor the progressive environmental development of Indian cities. The index is based on 24 environmental indicators, and their corresponding significance is assessed by the expert panel. SCESI is an integrated tool on a scale of 0 to 100, which depends upon the value of indicators and their relative weights. However, sometimes data for all the 24 environmental indicators may not be available. The present work determines the sensitivity analysis by applying certain interventions. Eight scenarios have been generated by taking various combinations of high and low weight indicators. The analysis of the study indicates that the occurrence of error is marginal in both cases of non-availability of high and low weight indicators. Thus, the sensitivity analyses critically assess the variations in the SCESI when there are uncertainties involved in the input data.