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Support Vector Machine: A Case Study in the Kert Aquifer for Predicting the Water Quality Index in Mediterranean Zone, Drouich Province, Oriental Region, Morocco

The expansion of urbanization and the amplification of anthropic activities in the Rif region require the establishment of wells. However, the irrational exploitation of water and natural conditions have generated the rise of the water table and the increase in pollution. Thus, the assessment of water quality has emerged as a significant concern. This study’s goal is to assess the adequacy of groundwater quality in two aquifers in the vicinity of the Mediterranean Zone - Drouich Province and Oriental Region, Morocco, for drinking water needs by taking 62 water samples of the Kert aquifer for 2019. The Water Quality Index (WQI) classifies water quality: as excellent, good, poor, very poor, etc. That is essential for conveying information about water quality to people and decision-makers in the affected area. The WQI in the Kert aquifer varies from 62.3 to 392.3. The calculation of the water quality index (WQI) of the Kert aquifer view is based that 45.16% of groundwater samples are of poor quality, making them acceptable for drinking. The study’s analysis is established with a geographic information system (GIS) setting. The index map provides decision-makers with a complete and interpretable picture for better water resource planning and management. SVM models are shown to account for 87.71% of the varying water quality score. Different statistical and intelligence models may make the index more predictable. These forecasts assist us in better managing the aquifer’s water quality.

Hicham Gueddari, Mustapha Akodad, Mourad Baghour, Abdelmajid Moumen, Ali Skalli, Yassine El Yousfi, Hanane Ait Hmeid, Mohamed Chahban, Ghizlane Azizi, Mohamed Chaibi et al.

Evaluation of Coliform and Faecal Coliform Bacteria in the Lakes of Broknes and Grovnes Peninsula, East Antarctica

More than 150 lakes on different peninsulas and islands are situated in the Larsemann Hills. The Larsemann Hills is an ice-free area and are located halfway between the Vestfold Hills and the Amery Ice Shelf on the southeastern coast of Prydz Bay, Princess Elizabeth Land, and East Antarctica. During 34th Indian Scientific Expedition to Antarctica (ISEA) from 2014 to 2015, twenty lake water samples in triplicates were collected from the Broknes & Grovnes peninsula. Coliform and fecal coliform bacteria were analyzed in these samples. Out of twenty, eleven lake water samples were found to be contaminated with coliform bacteria. However, fecal coliform bacteria were absent in all the lake water samples. Coliforms are found in the lakes of Broknes peninsula (P2 Lake & P3 Lake) and Grovnes peninsula (L1C NG, L1D NG, L1E NG, L7 NG, L7A NG, L7B NG, L2 SG, L4 SG & L5 SG). Antarctic lakes water is being polluted due to anthropogenic activities caused by various research activities and tourism. The present study confirms the presence of coliform bacteria in the lakes of East Antarctica which indicates an alarming situation and needs to be investigated further.

L. K. Bhardwaj and T. Jindal

Role of Channel Migration and Influencing Hydro-Geomorphic Attributes in Dibru River Basin Using Remote Sensing and GIS

"The action of the river is dynamic and exhibits morphological changes over time. River channel migration may take place because of sedimentation, geology, soil properties, geomorphic setup, precipitation, land use pattern, natural bank geometry (e.g., channel width, meander length, meander wavelength, amplitude, the radius of curvature, arc angle, and sinuosity), discharges of various frequencies (Brice 1982, MacDonald et al. 1991, Garcia et al. 1994), distribution of riparian vegetation, and vertical and horizontal heterogeneity of floodplain soils (Motta et al. 2012), etc. are some factors for channel migration. The present study is undertaken in the Dibru River Basin, the left-bank tributary of the Brahmaputra River. To identify the Spatio-temporal changes, satellite imagery is used in the GIS environment. The extraction of the river is done from the GIS software (Arc GIS 10.4) by digitizing process and tries to overlay the different time periods of shifting of the river and find out the rate of magnitude and nature of the river course changes. An interval of 10 years is taken to find the rate of magnitude and nature of changes in the river courses from satellite imagery. The time period is taken from 1977-2020 at 10 years intervals. Along with the rate of river course changes, channel avulsion is also shown with the help of satellite imagery. The Dibru Saikhowa National Park falls within the Dibru river basin, where numerous streams are found, within the national park. The Saikhoa river and Ajuka river flow within the national park. The Sursa river is a small channel linked with the Dangori river. With phases of time, the river made a headward erosion and confluence with the Ajuka river and formed a channel. The Saikhoa river flowed till 1987; due to deposition, the river abandoned its original course. In 1988, the Ajuka river and Sursa river merged and flowed northwest direction. The high discharges of the Lohit river diverted towards the Ajuka and Sursa Rivers and took a new channel named the Lower course of Lohit river within the study area. It can be called an avulsion channel because it changed its direction from its original to a new course in 1990. Since 1990, the course of the channel has been tremendously expanding its length and breadth, causing a flood, bank erosion, and deposition nearby human habitats and Dibru Saikhowa National Park. From the multi-temporal satellite imagery, the river courses were studied, and found the year of avulsion took place in the channel. Multi-temporal satellite imagery is used to identify the channel’s avulsion. An avulsion is the rapid separation of a river channel to form a new course, which is only possible due to flood, high discharge, soil properties or tectonic activity, etc. that creates instability and causes the channel avulsion.."

Gulap Sonowal, Gitika Thakuriah and Satyendra Hazarika

An Overview of the Role of Smallholders in Oil Palm Production Systems in Changing Climate

Oil palm production contributes tremendously to the economies of tropical countries, a location where cultivation takes place. The cultivation of oil palm is usually dominated by smallholders and produces about 40% of global palm oil demand. Therefore, in this study, we aim to investigate the role of smallholder oil palm growers in ensuring palm oil production in a changing climate. This study was based on a conventional literature review. Relevant articles were retrieved using search terms such as “climate change” or “oil palm” or “climate change and oil palm” OR “oil palm smallholders” OR “oil palm growers”. The documents were selected by (i) examining the title of the document, (ii) the abstract (iii) and the content of the document sequentially. Only documents that meet the inclusion criteria were selected for the review. The results of this study demonstrated that global climatic changes have a greater negative effect on oil palm production in the tropics. Rising temperatures result in water stress to the palms, as does variability in rainfall, which reduces productivity, declining floral abortion, increase in pests and diseases infestation, and yield loss. Oil palm smallholder growers contribute immensely to global food security. Smallholders are estimated to manage approximately 40% of the global oil palm planted area, producing 40% of the global palm oil demand. In Africa, smallholders produced more than 60% of palm oil demand, 33% in Papua New Guinea, and 40% in Malaysia. In Latin America, where 87% of oil palm growers are smallholders, they produce over 60% of the demand for palm oil. Oil palm production creates jobs and poverty alleviation, provides the most efficient oil, provides vitamins for body-building, and provides nutritious and healthy food. This study recommends long-term and short-term policies on climate change and oil palm, improved regional academic leadership, with a focus on collaboration with scientists in consumer countries, improved institutional research, and collaboration in research between producer and major consumer countries.

Ahmed Abubakar and Mohd Yusoff Ishak

Seasonal Characterization and Possible Solutions for Municipal Solid Waste Management in the City of Patna, Bihar, India

The present study aims to characterize the municipal solid waste (MSW) generated in the municipality of Patna, the second-largest city in Eastern India. MSW is heterogeneous and the composition varies with seasons and within the different parts of the city. MSW samples were characterized for the three different seasons Winter (November), Summer (May), and Monsoon (August) to select feasible waste treatment methods. The physical characterization indicates that the major fractions of the MSW were biodegradable (48.83%) and inert (18.26%), which shows variations in different seasons of about ~5%. On a seasonal basis, the chemical characterization of MSW revealed that the moisture content varies between 43.21% to 51.78%, and volatile matter between 20.18% to 29.45%. ash content between 20.20% to 26.23% and fixed carbon between 4.11% to 5.91%. The C/N was found to be between 15.81 to 28.84 and the calorific value lies between 1212 to 2627 kcal.kg-1 during different seasons. The characterization of MSW highlights the virtue of waste segregation at the source and developing an efficient MSW system, including the potential for recycling, composting, anaerobic digestion, and production of refuse-derived fuels (RDFs). The outcomes of the present study will be helpful for Patna Municipal Corporation (PMC) in the planning for implementing suitable waste treatment technologies for integrated solid waste management systems (ISWM).

F. A. Siddiqui, R. Singh and Prashant

Responses of Grass Species to Elevated CO2 – A Review of Three Decades of Research and Future Direction

Rising atmospheric carbon dioxide accelerates growth and modifies physiological responses in plants. Over the last 40 years, the global scientific community had taken up initiatives to make out the role of plants in capturing and storing atmospheric carbon dioxide. This review consolidates the research of the past three decades on the responses of grass species to elevated levels of CO2. An enhancement in intercellular CO2 concentration, water use efficiency, photosynthesis, total non-structural carbohydrates, and total biomass was noticed in grass species under controlled growth systems supplied with varying levels of CO2. Each of these responses reflects the potency of grasses to survive and store ample carbon in CO2-enriched environments. Reduction in stomatal conductance, transpiration rate, and total nitrogen concentration was in effect positive responses, in connection with the acclimatization of plants at CO2-enriched environments. This review ascertains that in experimental microclimatic environments with varying CO2 regimes or varying treatment duration, grasses show positive growth responses. Thus it illustrates the efficient atmospheric carbon sequestration of grasses irrespective of their photosynthetic pathway (whether C3/C4).

N. C. Sashna, Aparna Sreekumar and C. C. Harilal

Mountainous City Landscape Water Supply System Potential Carbon Footprint: Case of the Philippines’ Catbalogan Sky City Mega Project

Catbalogan Sky City Mega Project (CSCMP) is a climate-change (CC) adaptation strategy proposed after Typhoon Haiyan devastated the Philippines in November 2013. It is currently being built on top of a hill about 120m from sea level to avoid the impact of storm surges, sea-level rise, and flooding. With the city’s continued expansion, water demand further worsens the supply gap. This study focused on determining the carbon footprint of the proposed water supply scarcity solution. This solution includes the construction of a reservoir to receive runoff water from the watershed where the CSCMP is located. Results of the study show that the reservoir can supply the water requirement for the entire city. However, the carbon footprint of the recommended solution is between 123% and 557% due to water treatment of heavily contaminated runoff water and the power consumption in distributing water to higher elevations. There is a need for the city to design a harvesting system that will reduce the need for more intense water treatment (i.e., reducing exposure of runoff water to contaminants) and the use of renewable energy in powering pumps and other treatment activities.

Ronald L. Orale and Doris Montecastro

Assessment of Corrosion Potential Based on Water Quality Index in the Distribution Network of Urban Patna, Bihar, India

Corrosion in the distribution network pipe can lead to pipe failure and water quality problems. This study assesses the corrosion or scaling potential based on the Water Quality Index (WQI) of drinking water in the distribution networks of Patna, Bihar, India. The water samples were collected from 18 points of the distribution network. In situ parameters like temperature, pH, electrical conductivity, and TDS were measured. Other parameters such as Alkalinity, Total hardness, Calcium, Magnesium, Chloride, Residual chlorine, Sulfate, Nitrate, and Dissolved oxygen were examined in the laboratory. Corrosiveness indicators, such as the Langelier saturation index (LSI), Ryznar stability index (RSI), Puckorius scaling index (PSI), Larson-Skold index (Ls), and Aggressive index (AI) are being used for water sample corrosion prediction. Experimental Corrosion rate (CR) is analyzed to show the actual prediction of corrosion. WQI was calculated to observe the effect of water quality on Corrosiveness indices and CR. A general conclusion was reached that LSI concludes 66.67% corrosive, 22.22% scaling, and 11.11% neutral, RSI concludes 88.88% corrosive, 5.56% scaling, and 5.56% neutral, PSI indicates 38.88% corrosive, 5.56% scaling, and 55.56% neutral, Ls indicates 94.44% scaling, and 5.56% corrosive, AI indicates 77.78% corrosive, and only 22.22% scaling. The average Experimental Corrosion rate is found at 1.91 mils per year. In this study, a weak correlation (r = 0.35) between Corrosion rate and WQI has been observed. A weak correlation is also observed between corrosion rate and corrosiveness indices (r < 0.5). It is concluded that the Corrosiveness Indices fail to represent the actual behavior of water.

Saurabh Kumar, Reena Singh and N. S. Maurya

Scenedesmus obliquus and Chlorella vulgaris – A Prospective Algal Fuel Source

In recent years, the prospective use of algae as an alternate fuel source for petroleum-based fuels has increased drastically. It has been researched extensively and proven that it can be used as a sustainable feedstock for producing green energy considering environmental safety. This article focused on the economically viable algal feedstock for the production of lipid content for its use as a feedstock for biodiesel production. For this purpose, the algal species Scenedesmus obliquus and Chlorella vulgaris were selected, and it was grown under lab and open ambient conditions with two Blue green Medium (BG-11) and Bold Basal medium (BBM). Upon the yield, it was noticed that the BG-11 medium gave optimum lipid yield for both species. Hence, it was determined that through this medium higher lipid yield can be expected, and based on the GC-MS result it was notified that it can be a viable source of alternate fuel.

V. Hariram, J. Godwin John, E. Sangeethkumar, B. Gajalakshmi, V. Ramanathan, M. Vinothkumar, R. Selvakumar and M. Balachandar

Assessing the Suitability of Oil Palm (Elaeis guineensis) Production in Peninsular Malaysia based on Soil, Climate and Land Use

In recent years, palm oil production has grown rapidly as a result of rising demand. Oil palm plantations have been established on thousands of acres to meet this demand. The objective of this study is to assess the suitability of oil palm production as driven by soil, climate, and land use. The land suitability assessment (LSA) method was adopted in this study. We use geospatial techniques of overlay mapping as a suitable land suitability assessment method, in which the evaluation criteria are recorded as superimposed layers. A land suitability map is produced by integrating these layers into a single layer. The method is also applied to delineate available areas for growing oil palm in Peninsular Malaysia. The findings revealed that suitable soil areas for oil palm production are extensively found in the selected regions of Peninsular Malaysia, in states like Selangor and some parts of Kedah, Kelantan, and Terengganu with clay loam and sandy loam soil properties, while in the southern region like Melaka, moderate suitability for oil palm production was found due to the domination of clay soil in the area. Highly suitable areas were estimated (mean annual water deficit <150>400mm) for oil palm production as a result of poor water availability was 31104.00ha (0.25%). The Land Use Land Cover Map of Peninsular Malaysia revealed the suitable areas to cover an average of 10885001.46 ha (82.45%), water bodies 1239505.58 ha (9.39%), built-up areas (unsuitable areas) 1051544.34 ha (7.96%), and bare surface areas are also not suitable areas for oil palm production at 26509.73 ha (0.20%). This study recommends that oil palm plantations be expanded into areas with highly suitable soils and climates.

A. Abubakar, M. Y. Ishak, A. B Aisyah, Md. K. Uddin and M. H. Ahmad

Multi Techniques for Agricultural Image Disease Classification and Detection: A Review

The agriculture sector has a significant impact on the market in every country. Identifying crop disease with conventional methods is a hard operation and it needs more time, effort, and experts with continuous farm monitoring. Blight and other crop diseases have severe consequences on crop yields and cause enormous economic losses worldwide. Plant health monitoring and disease detection are critical components of sustainable agriculture. Machine learning and deep learning techniques are used to identify plant diseases and associated with severity detection in plant leaves. The adoption of these techniques still faces several important challenges. In recent years, improvements in technology and researchers’ interest in this area have made it possible to obtain an optimal solution. In addition to providing a detailed explanation of the proposed technique, which is deep learning architecture that uses the deep convolutional extreme learning machine (DC-ELM) for faster training, this study focuses on how machine learning and deep learning techniques detect plant diseases and infections that affect different crops. The proposed model is capable of providing good computational performance and allowing the learning process to be completed with less processing time. Finally, several challenges and problems with the existing system, as well as future research objectives, are enumerated and discussed.

M. Amudha and K. Brindha

Sensitivity of WRF Model for Simulation of 2014 Massive Flood Over Kashmir Region: A Case of Very Heavy Precipitation

The present study simulates the devastating floods in Kashmir that caused widespread damage in the valley from September 2-6 2014. The study used NCEP-NCAR FNL data for the initialization and simulation of the WRF ARW model. Statistical analysis of temperature over four places namely Anantnag, Srinagar, Pulwama, and Baramulla taking RMSE and MBIAS at 24, 48, 72, and 96 hours was also done against observed ECMWF-ERA5 temperature data. Further analysis of RMSE and MBIAS showed a minimum value at 48, 72, and 96 h indicating the improvement of prediction after 6 hours. Rainfall amount was under-predicted by the model with a time lag of 4 h while temperature time series over four districts were significantly closer to observation. Furthermore, the Model was able to capture the strong vertical velocities along with sufficient moisture content up to 600 hPa at the time of observed rainfall.

Zahid Nabi and Dinesh Kumar

A Framework for Improving Urban Land Cover Using Object and Pixel-Based Techniques via Remotely Sensed Data

Recently, the advancement of remote sensing technology played a key role in urban land/cover mapping, planning, tourism, and environmental management. Images with a high spatial resolution for urban classification are widely used. Despite the high spectral resolution of the image, spectral confusion happens among different land covers. Furthermore, the shadow problem also causes poor results in the classification based on traditional per-pixel spectral approaches. This study looks at ways of improving the classification of urban land cover using QuickBird images. Maximum likelihood (ML) pixel-based supervised as well as Rule-based object-based approaches were examined on high-resolution QuickBird satellite images in Karbala City, Iraq. This study indicates that the use of textural attributes during the rule-based classification procedure can significantly improve land-use classification performance. Furthermore, the results show that rule-based results are highly effective in improving classification accuracy than pixel-based. The results of this study provide further clarity and insight into the implementation of using the object-based approach with various classifiers for the extended study. In addition, the finding demonstrated the integration of high-resolution QuickBird data and a set of attributes derived from the visible bands and geometric rule set resulted in superior class separability, thus higher classification accuracies in mapping complex urban environments.

Ammar Shaker Mahmoud, Mustafa Ridha Mezaal, Mustafa Raad Hameed and Ahmed Samir Naje

Future Predictions of Precipitation and Discharge Using CMIP5 Models in the Western Ghats Region, India

Climate change is expected to exacerbate the hydrological cycle globally and have a significant impact on water resources. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report states that observed and projected increases in both temperature and precipitation variability are the main reasons for projected climate change impacts on natural water resources. The examination of meteorological variables of the region, especially when agriculture is rainfall dependent, is very essential to formulate feasible adaptation strategies. As a result, using CORDEX-SA (Coordinated Regional Downscaling Experiment-South Asia) rainfall data (2021 to 2050), trend analysis was used to examine variations in rainfall data in the Kokkarne catchment of the Seetha river basin. Regression analysis was used to identify the season-wise rainfall trend. Annual, Summer, Monsoon, and Winter rainfall have depicted increasing trends with a rate of 2.46, 1.21, 2.77, and 0.009 mm per year respectively. The post-monsoon rainfall has projected a declining trend with a rate of -1.54 mm per year. Hence it is recommended that the designed strategies in the agricultural sector have to take the increasing, decreasing, and erratic nature of the trend of rainfall into consideration. Further considering the use of a Multi-Model Ensemble (MME) is reducing the SD and CV of rainfall data by 862 mm and 48.5% respectively. 87% of annual rainfall is contributed by monsoon season only with a Standard deviation of 424.4 mm and CV of 12%.

Shilpa A. Veerabhadrannavar and B. Venkatesh

Prediction of Marine Water Quality Index Using a Stacked Classifier Under Machine Learning Architecture

The health of humankind is intrinsically associated with the health of the marine and ocean ecosystems. The pollution of the coastal region due to urbanization, for example, principally harms the growth of the ecosystem with poor-quality of water, which aggravates the survival of marine organisms and animals. The toxicity of the contaminated seafood would affect the human-ocean ecosystem thereby bringing down the economic rank of the region as well. Therefore, it is mandatory to assess the quality of the marine and ocean water to initiate any statutory measures to protect the regional marine water against pollution and dumping of toxic matter. This paper, therefore, presented an architecture of machine learning techniques to assist in classifying marine water quality. The proposed framework evaluated various classification models and selected the best fit out of the top-performing algorithms through training and optimizing. The finalized model was a stacked classifier, which was then deployed to predict the marine water quality index from the physicochemical and biological properties of the water.

K. Komathy

Study of the Effectiveness of Making a Retention Pond for Urban Flood Management: A Case Study of the Barabai River, South Kalimantan

The upstream of the Barabai River is experiencing land conversion from forest to agricultural and mining areas. In 2021, f loods and river overflows will inundate nearly 75% of Barabasi City. The solution given is to build a Retention Pool so that the flow of the Barabai River before entering Barabai City is diverted to the Retention Pool. By conducting hydrological and hydraulic flow analysis with the application of HEC RAS with unsteady flow conditions, the water level profile along the Barabai River can be displayed including the flow behavior in the retention pond during flooding. As a result, the retention pond is only effective at accommodating 25% of the discharge during a flood. By optimizing using the HEC RAS program, alternatives to inundation or flooding in Barabai City are obtained, namely: widening the Barabai river 2x, expanding the regulation pool to 95 ha, building a second retention pond of 40 ha, and normalizing the Barabai River that enters Barabai City.

Nely Ana Mufarida and Nanang Saiful Rizal

Selective Detection of Zn2+ Ions by Ratiometric Receptor (E)-N?-(1-(2, 5-Dihydroxy phenyl) Ethylidene) Isonicotinohydrazide: A DFT Study

The metal ion sensing characteristics of a novel Schiff-based ratiometric UV-visible chemosensor (E)-N’-(1-(2,5-dihydroxy phenyl)ethylidene) isonicotinohydrazide) (R1) has been explored. In EtOH:H2O (7:3, v/v), it has high sensitivity and selectivity for Zn2+ among a series of metal ions. With the addition of Zn2+ ions solution, R1 displayed discriminating spectral activity. The other metal ions did not affect R1 in any way. Furthermore, the addition of Zn2+ ions to R1 and LMCT action caused the shifting of the peak to a longer wavelength of 406 nm. The interaction of Zn2+ ions with R1 was further investigated using Density Functional Theory (DFT) investigations. Zn2+-R1 combination has a lower energy (2.2667 kcal.mol-1 to 0.9339 kcal.mol-1) than R1, indicating a strong connection with excellent stability. The Zn2+-R1 complex’s association constant (Ka) was discovered to be 6795M-1 and 6836M-1 using Benesi-Hildebrand and Scatchard plots respectively. The detection limit was determined to be 276 nM.

N. S. Patil, R. B. Dhake, R. Phalak, U. A. Fegade, C. Ramalingan and V. Saravanan

Estimation of Soil Contamination with Heavy Metals in the Streets of Al-Diwaniyah City in Al-Qadisiyah Governorate, Iraq

This study aims to calculate the contamination levels of the elements (Pb, Cr, Ni and Cd) in soil samples taken from the Iraqi city of Al-Diwaniyah in the Al-Qadisiyah Governorate. Twenty samples of dust collected between the street and the sidewalk were collected for some areas of Al-Diwaniyah city, and then analyses were conducted to determine the concentrations of toxic and carcinogenic elements with the global determinants. The study’s findings revealed that there were very high concentrations of heavy metals compared to the internationally permissible limits, where the highest concentration of lead and chromium was in Main Street - Al-Asry District (112.6 ppm) and (115.1 ppm), respectively, and the lowest concentration of them was in Health Center Street - Al-Furat District (15.8 ppm) and (48.8 ppm), respectively, where the lowest lead value exceeded the internationally permitted limits and the lowest chromium value fell below the permissible limit. As for nickel and cadmium, the highest values of nickel and cadmium appeared in Main Street - Eastern Republican District which amounted to (135.2 ppm) and (2ppm), respectively, which is significantly greater than the internationally permissible limit, while the lowest values appeared in University Street - University District, which is (3.6 ppm) (0.05 ppm) respectively, which is less than the internationally permissible limit. It is noted from the results obtained that high rates of heavy metals concentrations in the soil samples of Al-Diwaniyah City indicate that the main factor in this rise is pollution caused by human activities, and the reason for this is due to the effect of vehicle launchers and some launchers of workshops and factories, as well as its presence in sand-laden dust of various sources. This rise might have an effect on the environment and human health at all of the selected sites.

Kawthar Hassan Obayes

Comparison of GIS-Based Intrinsic Groundwater Vulnerability Assessment Methods: DRASTIC and SINTACS

The possibility of contaminants percolating and diffusing into the groundwater system is referred to as groundwater vulnerability. When groundwater once gets polluted it is very difficult to process/clean it so, measures must be taken to assess the vulnerability of the groundwater for effective groundwater conservation and management planning. This study aims to evaluate and map the vulnerability of Raipur city using the SINTACS and DRASTIC models and to compare their effectiveness between them. To assess the hydrogeological setting and evaluate aquifer vulnerability, each model includes seven environmental parameters (aquifer hydrogeologic features, effective infiltration, topographic slope, soil media, water table depth, unsaturated conditions, and hydraulic conductivity). The parameter data sets are evaluated in a Geographical Information system (GIS) environment to get the vulnerability index (VI), the index is categorized into five classes that show low to high vulnerability. The area under the low class for DRASTIC and SINTACS is 26.14% and 20.34% respectively whereas for the highly vulnerable class it is 15.54% and 22.54% respectively of the total area. By comparing the 15-groundwater sample value of nitrate concentration on the two vulnerability maps it was found that the SINTACS method result was shown to be significantly associated with the nitrate concentration with an accuracy of 86.7 percent.

Indrajeet Sahu, A. D. Prasad and Ishtiyaq Ahmad

Anthropogenic Influence on Protected Areas: A Case Study of Achanakmar Tiger Reserve (ATR), Chhattisgarh, India

India’s broad network of protected areas, which encompasses 4.93% of the country’s geographical area, is exposed to immense anthropogenic pressures that can create an imbalance and also hinder the prime objective of wildlife conservation and protection. The present study assesses some of these problems in relation to the Achanakmar Tiger Reserve (ATR). The main anthropogenic influence in ATR is the presence of eighteen core villages, five buffer villages, and 49 fringe villages in the periphery of the reserve area. The population density of the core zone was higher (16.0 people/km2) as compared to the buffer zone (7.41 people/km2). Another important disturbance in the protected area is state highway 8 which bisects the entire core zone into two halves. This highway also connects the neighboring state of Madhya Pradesh and there is the continuous movement of traffic, which hampers the smooth movement of wild animals. ATR also has a wide network of tourist roads of 192 km passing through the core zone. The average population density of livestock in ATR is relatively high compared to the average population of wild ungulates. It creates competition between wild ungulates for food, and they are also under constant threat of infectious diseases. The livestock depredation by apex predators is one of the major reasons for man-wildlife conflict in ATR. The cattle kill incidences by both the apex predator (tiger and leopard) was 378 during the period of three years (2015 to 2018) and these incidences were recorded more in the core zone as compared to the buffer zone. In the present study, anthropogenic effects on ATR have been studied and evaluated. It concludes that for effective management and conservation of tigers in ATR, these aspects need to be considered. To restore the tiger population in ATR, there must be a proper balance between human (anthropogenic) approaches and conservation benefits for the effective sustainability of the protected areas.

Anupama Mahato and S. S. Singh

Evaluation of Heavy Metals in Vegetables from Two Origins Marketed in Northern Peru

The objective of the study was to evaluate the concentration of arsenic, chromium, cadmium, and lead in onion (Allium fistulosum and Allium cepa), tomato (Solanum lycopersicum), and celery (Apium graveolens) from two origins (local - Chachapoyas province and from the coast-province of Chiclayo) that are sold in the model market of the city of Chachapoyas. Six samples were taken on three different dates in November 2020, which were collected by non-probabilistic sampling (by convenience), which allowed choosing the most appropriate sample (according to its origin). For the determination of heavy metals, the Agilent 4100 MP-AES spectrometer was used. The concentration of As, Cr, and Cd in the vegetables remained below the Maximum Allowable Limits of the international standards with which they were compared; however, the concentration of Pb exceeded the Maximum Allowable Limits in all the samples analyzed, obtaining the lowest value in the celery samples from the local origin (0.15 mg.kg-1) and the highest value in the tomato samples from the coast (0.21 mg.kg-1). Therefore, it is concluded that only Pb is higher than the Maximum Allowable Limits with which it was compared.

J. Grández, M. Oliva, E. Morales, M. Goñas, S. Chavez A. Guivin, L. Quiñones and M. Milla

Association Between PM2.5 Induced Diseases and COVID-19: A Systematic Review

A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic that started in China (Wuhan, Hubei region) in December 2019, called Coronavirus disease. This systematic review intends to evaluate the correlation of pre-existing particulate matter (PM2.5) induced comorbidities along with COVID-19 spread and mortality. A search was operated to report the association between PM2.5 and COVID-19 outbreak and evaluating the PM2.5 related disease affected by COVID-19 infection. The research was conducted in consent with the criteria of PRISMA (Preferred Reporting Items for Systematic Reviews, and Meta-Analyses). We filtered the review and research articles published only in the English language and selected these keywords: air pollution, particulate matter, COVID-19, health impact. We obtained a total of 27 appropriate published articles in their final version. Additional articles were rectified by searching through Scopus, PubMed and Google Scholar. We concluded that the values of coagulation biomarkers in all SARS-CoV-2 patients were considerably higher as compared with healthy people. It was noted that Hypertension, Diabetes, COPD, CVD, Asthma and Cancer possess an evident relation with COVID-19 severity. Globally, air pollutants affect the body’s immunity, leading to people being more susceptible to pathogens. In addition, transmission from person-to-person dynamic of the new respiratory virus was considered the environmental factors’ role in accelerating coronavirus spread and its lethality. COVID-19 patients with pre-existing comorbidities induced by particulate matter show a high risk of mortality as compared to COVID-19 patients without these comorbidities.

Gulshan Sharma, Era Upadhyay and Pawan Tiwari

A Critical Review of the Impact of COVID-19 on Plastic and Food Waste

This research aims to show the positive and negative indirect effects of COVID-19 on municipal solid waste management systems, especially for plastic waste and food waste. The COVID-19 pandemic has affected the entire waste management sector. As the pandemic spread and lockdowns were enforced in many countries, government and municipal waste operators had to quickly adapt their waste management programs and procedures to the situation. In the pandemic condition, waste generation has switched from industry and commercial to domestic areas. Reduced recycling activities have made municipal waste collection and disposal more difficult. This paper focuses on all the challenges and it’s possible resolutions for managing food and plastic waste during the pandemic of COVID-19.

Prashant Shukla and Sachi Choudhary

Analysis and Characterization of Municipal Solid Wastes Generated in a Community in the Northern Philippines

The residential community of Potia in the Northern Philippines experiences various problems arising from mismanaged municipal solid waste. Hence, a waste analysis and characterization study on the generated municipal solid wastes was conducted to determine the municipal solid waste generation data which can be used for planning and formulation of potential solutions. For three consecutive days, the generated municipal solid wastes were gathered from the sample which included residential sources, commercial sources (food establishments, service centers, general stores, and markets), industrial sources, and institutional sources (institutions and health units). The total generated municipal solid waste in Potia is about 508.30 kg.day-1 of which most were contributed by the residential sources (70.59%), followed by commercial (25.09%), industrial (2.64%), and institutional (1.70%). The overall composition of the generated MSW is also dominated by biodegradable waste (76.90%), followed by residual waste (14.66%), recyclable waste (7.35%), and special waste (1.08%). The total volume of daily generated MSW is about 3.37 m3.day-1.

J. M. Ngohayon and J. Tulagan

Chromate Reduction by Allochromatium sp. Isolated from the Coastal Area of Visakhapatnam

A phototrophic purple bacterium Allochromatium sp. strain GSKRLMBKU–01 was used in this study for the reduction of hexavalent chromium. This phototrophic bacterium was isolated from samples collected from the coastal area of Visakhapatnam, India. Both the cells (free (FC) and alginate entrapped immobilized (IC)) are used for the reduction of chromate. Among them, chromate reduction was increased using immobilized cells. Immobilized cells entrapped in sodium alginate reduced the chromate up to 33 ± 3.0 ?M on the 8th day of incubation by Allochromatium sp., incubated in presence of light (2000 lx) under the strictly anaerobic conditions, while a chromate reduction up to 26 ± 0.20 ?M was recorded by FC of Allochromatium sp. Chromate reduction can be recorded even up to the 20th day by both FC and IC. An incubation period of 8 days was found to be optimum for its growth and chromate reduction. The maximum growth in terms of dry cell weight (DCW) of FC is recorded up to 1.7 ± 0.20 g.L-1 and IC is 2.0 ± 0.30 g.L-1. The growth was recorded even on complete chromate reduction. The final pH of the FC was recorded at pH 8.5 ± 0.10, while the final pH of 8.6 ± 0.20 was recorded for the IC of Allochromatium sp. in the growth medium. The obtained results were mentioned in terms of mean and standard deviation which are statistically significant at P ? 0.001 level. The detoxification of chromium in the large-scale systems by employing a purple phototrophic bacteria Allochromatium sp., is proposed.

Kadari Rajyalaxmi, S. Girisham, S. M. Reddy and E. Sujatha

Local Community-Based Management Model in Karimunjawa National Park

This research aims to study the management model of Karimunjawa National Park Based on Local Communities. Activities are carried out in all sections of Karimunjawa National Park Management. Data sources are informants involved in Karimunjawa National Park Management and secondary data was collected using rapid monitoring methods, namely in-depth interviews, field observations, FGDs, and various other data collection techniques (technique triangulation). Methods of Data Analysis were observation using interactive data analysis. Empowerment of local communities in the Karimunjawa National Park in the Karimunjawa National Park area is carried out in three ways: coral reef rehabilitation activities, mangrove forest planting, and lowland tropical forest tree-planting efforts to develop a conservation village model.

Rizal Akbar Aldyan, MTh. Sri Budiastuti, Warto and Wiwik Setyaningsih

Satellite-Based Statistical Analysis of Hilla River Water Quality Parameters, Iraq

Since industrial and human activities have been developed, water quality intensely degrades in Hilla River, Iraq. Using remote sensing technology provides data for assessing and monitoring water quality in surface water bodies. Thus, in this study, Landsat 8 satellite images (2016 to 2021) were statistically tested for developing linear models capable of estimating water quality parameters in the river based on field data, including turbidity (turb), electric conductivity (EC), hydrogen ions (pH), total suspended solids (TSS), chloride ions (Cl), sulfate ions (SO4), Alkalinity (ALK), total hardness (TH), calcium (Ca), potassium (K), sodium (Na), magnesium (Mg), and total dissolved solids (TDS). The results showed that seven parameters have a significant relationship with the spectral bands ratio (p-value less than 0.05). Some of them (TDS, SO4, and ALK) are positively correlated with bands ratio (Band10/Band3, Band10/Band3 and Band10/Band4, and Band3/Band7), respectively. Others (Mg, Ca, TH and pH) are inversely correlated with (Band4/Band7, Band1/Band4, Band1/Band4, and Band1/Band2), respectively. However, K, Na, TDS, Cl, EC and turb have an insignificant correlation with any band ratio.

Fatimah D. Al-Jassani, Hussein A. M. Al-Zubaidi and Nisren J. Al-Mansori

Preparation of Carboxymethyl Cellulose from Musa paradisiaca Pseudo Stem Using an Alkaline Treatment

Carboxymethyl cellulose (CMC) extraction from Musa paradisiaca (MP) pseudo stem by alkaline treatment and their properties were examined in the current research work. One of the most well-known types of lignin biomass waste that is readily available globally is MP. In many nations, including Taiwan, Sri Lanka, the Philippines, India, and the Philippines, these plants have been used for traditional reasons. Whole plant parts have been used as food, including the pseudo-stem, flower buds, trunk, fruits, and leaves. Sequestration of cellulose was attained by alkaline treatment and bleaching from raw fibers. Cellulose fiber is a biodegradable, naturally occurring, and renewable polymer that is used in a variety of industries, including the food, paper, cosmetic, and pharmaceutical sectors. The cellulose obtained from forest and agricultural residue has numerous advantages such as being environmentally safe, recyclable, and economically feasible respectively. The main process of cellulose extraction from MP pseudo stem are digesting process using a digester, bleaching, and neutralization which shows a zero-waste process. The alkali treatment takes less time to get a final product whereas enzyme treatment, and steam explosion treatment takes high energy and more cost. Hence, cellulose extract from alkaline treatment is economically feasible and environmentally friendly.

Vijayaraghavan Gopal, Dharani Dharan Dharmarajan and Sivamani Sivalingam

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