Industrial Belt Research Articles

Assessment of heavy metal contamination and accumulation in soil and leafy vegetables collected from industrial belt in Bharuch district, Gujarat

Assessment of heavy metal contamination and accumulation in soil and leafy vegetables collected from industrial belt in Bharuch district, Gujarat

Acoustic Feature Extraction Based on Wavelet Transform for Industrial Induction Motor-Driven Belt Conveyor Condition Monitoring

The industrial induction motor-driven belt conveyor is an essential component in manufacturing facilities. Any unexpected shutdown can lead to significant disruptions, resulting in financial losses amounting to thousands of dollars per hour. Unfortunately, efficient mechanisms for monitoring the conveyor's condition are often lacking. Therefore, it is crucial to ensure early, precise, and effective detection of malfunctions in belt conveyors. This necessitates the identification of distinctive anomalies stemming from initial damage to the rotating machinery and motor components. This paper presents a non-invasive acoustic monitoring technique designed specifically for industrial belt conveyors. The method employed relies on wavelet transform-based feature extraction, offering notable advantages in terms of classification accuracy, time efficiency, and the quantity of feature vectors required for classifier training.

Elemental Profiling with Reference to Metal Index to Study Pollutant Load in Northern River of India

Present light was to determine elemental load in Sirsa river ecosystem to know the concentration of toxicants in this Sutlej river’s tributary that act as a gutter for industrial effluents of Baddi region. The inductively coupled plasma mass spectroscopy was used to detect concentration of elements in the department of biochemical engineering and biotechnology at IIT Delhi and the collected data was further analyzed statistically using one way ANOVA at (p≤0.05) followed by post hoc Duncan’s test to predict degree of variations and comparative profile in Table 1. The application of metal index was also performed to estimate water quality and co-related it with health hazards. Variations in concentration of elements was reported near common effluent treatment plant on pollutant Nallah (S2) in deceasing order read as Mg>Na>Ca>B>Zn>Cu>Mn>Fe>Mo>Al>Tl>Se in ppb. The concentration of elements reported at S1, S2, S3 were within permissible limit of WHO and Bureau of Indian Standards, except the value of Boron, Magnesium and Thallium were exceeded these guidelines constantly at site S2 of study area.The metal index values at S1, S2 and S3 were 1.55, 5.80 and 2.57 respectively. The site S2 was affected strongly due to presence of elemental dust and un-treated waste water discharged by chemical industrial units of Baddi region. This site (S2) was nearer to common effluent treatment plant on the bank of Sirsa river and found to be unsuitable at all with more value of metal index. It was also viewed to adopt such scale indices to estimate drinking water quality with respect to concentration of elements after equal interval of time; as there may be seasonal change in the load of debris due to rate of pollutants dumping in the riverine ecosystem which is directly proportional to the content of elements. The load of pollutants in water system was underlined to know the impact of inorganic waste discharges on water quality of river in this region of Himachal Pradesh along industrial belt.

Air Quality Analysis through IoT Device and Risk Prediction of Asthma Attack using ML Techniques

Background: The air quality of any area depends upon the various PMs (particulate matter) and hazardous gases present in the air. Low-cost PM sensors and gas sensors are present in different target places to monitor the air quality, read the environmental data, and transmit it to local servers through the IoT device. The low-cost sensor is not reliable due to its low sensing capacity; therefore, the read data is calibrated with the meteorological data presented by the nearby meteorological Centre of that particular area. The calibrated reading data sent to the server could be analyzed through some Machine Learning [ML] models. The ML models help to predict the risk of asthma in a particular area. The risk of asthma is directly related to the air quality of the surroundings. It is observed that the air quality of the industrial area is much worse than the non-industrial belt. Air quality monitoring of industrial areas is always a challenging task due to the ununiformed pollution in some segregated places around the industry, emitting pollutants mostly from chimneys. The air quality of any area depends upon the PM (PM), i.e., PM2.5 and PM10.0, as well as the gasses like NO2(Nitrogen Dioxide), NH3 (Ammonia), SO2(Sulfur dioxide), CO(Carbon monoxide), O3(Ozone) and Benzene. These are the most hazardous gases generally emitted by common heavy industries like iron and steel. In this article, the researchers considered the industrial belt of the Asansol- Durgapur region of West Bengal, India, and predicted the risk of asthma attacks for the test dataset. The experiment was carried out on 10 different supervised machine learning [SML] models as well as semi-supervised machine learning (SSML) models. The SML models have been further refined through hyper-parameter tuning, and better results have been obtained in the case of some ML models. The result has been compared with the existing literature considering the same external environment from where the meteorological data was collected, and similar ML models have been used. The research outperformed the existing literature, which is depicted in the result and analysis section of the article. Methods: The study evaluated ML models, both supervised and semi-supervised, to assess pollution levels. Relevant features were selected while less relevant ones were discarded. Accuracy levels of different ML algorithms werecompared in the results. The most effective model for an IoT system was chosen to maximize accuracy. In semi-supervised learning, feature selection followed supervised learning, but testing was akin to unsupervised learning. Results were compared with supervised learning data, enhancing reliability. Results: The result employing various classifiers werepresented across tables after the independent parameter Ozone was removed. Following the output of several classifiers, the results were verified using the k-fold validation method, with k being set to 5 or 10, accordingly. Tables display the best outcome, which is indicated in bold characters. method: In this research work the researcher considered 9 different ML models and used them as supervised as well as semi supervised model to determine the pollution level of the certain area. In this research work the researcher also selected the most relevant features and discarded the less relevant features. In case of SML algorithm, the accuracy level of the different ML algorithm has been determined and depicted in the result analysis section. The most effective ML model has been chosen for the proposed embedded system so that accuracy could be achieved at most. In case of semi supervised algorithm the feature selection is done as per the supervised algorithm. In this case the training is done same as the SML algorithm, but the testing phase is done like unsupervised machine learning algorithm where the decision parameter is predicted and ultimately matched with the previously achieved data of SML algorithm. The reliability of this approach is much more effective than simple SML algorithm. Conclusion: This study focused on predicting asthma risk in the Asansol-Durgapur industrial belt, India, using low-cost PM and gas sensors. Data calibration with meteorological inputs enhanced accuracy. ML models predicted risk and were refined through hyper-parameter tuning. Comparative analysis showed superior performance, emphasizing the importance of precise air quality monitoring. While offering a robust framework for future research, the study’s limitation lies in its area-specific dataset.

Regeneration of Distressed Communities in Settlements Around Brownfields: Insights from Khulna, Bangladesh

As is known, Khulna, the third largest metropolis in Bangladesh has played a pivotal role in trade and industry during the 1950s and 60s. From the late 60s, the political shifts have caused a rapid decline of the industries, worsening the socio-economic condition of the workers' community and the physical condition of the surrounding urban areas of the industrial belt. Partial closures, leasing out, laying off of the mills and finally turning into urban brownfields, have made thousands of workers jobless. Khulna Newsprint mill is such a brownfield, closed in 2002 leaving a total of 6000 workers and employees unemployed with a hope of reopening. Despite 16 years passing, they continue to hold onto this hope of relaunching the mill while living next to the mill area with multiple deprivations in socio-economic aspects. In this context, the government has introduced a new industrial policy in 2010, emphasizing investment in State Owned Enterprises only for reopening. However, without recognizing distressed vernacular communities and a concurrent regeneration plan, this strategy has proven ineffective in a developing country like Bangladesh. This research examines how distressed vernacular communities of urban brownfields can be regenerated. The objectives are to identify the socioeconomic needs of the distressed community and investigate the spatial and physical resources of the Brownfield, which can be useful for the regeneration of the distressed community. It employs qualitative case study method. Data is collected through a questionnaire survey, focus group discussion, participant observation, Key person interview, planning document study, drawing and photography analyzed through content analysis using NVivo and Spatial Mapping analysis. In conclusion, the paper formulates a framework for the regeneration of distressed vernacular communities around the urban brownfields. It also provides recommendations for specialized policy guidelines on the sustainable regeneration of such distressed communities.

The Relationship Between Perceived Fairness of Performance Appraisal and Job Satisfaction

The aim ofthe study is to assess the relationship between perceived fairness of performance appraisal and the level ofxjob satisfaction in corporate employees. A sample of 100 has been selected. The sample constitutes of corporate employees from the Gurgaon-Delhi-Meerut industrial belt in the age range of 20-60 years have been included. The scales used were Scale for Perceived Fairness of Job Appraisal and the JSS. Statistical tools used were SPSS has been used for statistical analysis on the data that was collected. T-tests (two-tailed, independent) were run to study gender differences and age differences. A Pearson correlation test was run to study the correlation between the two variables and regression analysis used to determine significance. Results showed a correlation of 0.795 significant to <0.001 and A regression analysis gave R square = 0.632 and sig. F change <0.001 for PFPA and Job Satisfaction. Employees who were older than 36 showed a correlation coefficient off0.828 while employees who were younger than age 36 showed a correlation coefficient of 0.757. A T-test analysis gave a t-score ofl0.897 for PFPA and 1.128 for Job Satisfaction and a significance of 0.475 for PFPA and 0.262 for job satisfaction was found. Male employees showed a correlation coefficient of 0.775 and female employees showed a correlation of 0.819. A T-test analysis gave a t-score of 0.633 for PFPA and 0.640 for Job Satisfaction and a significance of 0.528 for PFPA and 0.523 for job satisfaction was found.

Spatio-temporal evolution of sports tourism industry integration: A empirical analysis of Xinjiang in China.

Since the issuance of the "Guiding Opinions on Vigorously Developing Sports Tourism" in 2016, the integration of sports and tourism has become a strategy in regional economic development. It creates new economic growth points, enhances local images, and promotes cultural communication. In the context of the "Tourism Makes Xinjiang Thrive" strategy, quantitatively investigating the integration of the sports and tourism industries helps people to better understand their interaction which can serve as the valuable input in policy-making for the comprehensive development of a region. This paper uses entropy weight method, stochastic frontier analysis and coupling coordination model to quantitatively analyze the effect of sports tourism industry integration in Xinjiang from the perspective of integration path. Meanwhile, the Dagum Gini coefficient and nuclear density estimation were used to analyze the regional differences and dynamic evolution of industrial integration quality. The result shows that (1) The sports and tourism integration quality in Xinjiang has not reached the optimal goal of complete integration. In the process of mutual industrial promotion, tourism promotes a higher degree of integration with the sports industry. (2) The industrial integration quality shows a phenomenon of "imbalance and inadequacy" among the regions. The regions with high quality of industrial integration were Urumqi, Ili, Kashgar, Altay and Changji, which have rich sports tourism resources. (3) The overall spatial difference in the quality of industrial integration presented a fluctuation downtrend. The difference between the tourism industrial belts was very significant.

Leadership Preference and Managerial Creativity in Corporate Sector Employees in the GDM Industrial Belt

The study aims to examine the relationship between leadership style preference and managerial creativity among corporate employees in the GDM Industrial Belt. The research uses mixed sampling methods, including simple random sampling and area or cluster sampling, to collect data. The sample consists of 115 corporate employees aged 20-60 years from the Gurgaon-Delhi-Meerut industrial belt. The scales used were Managerial Creativity Scale (MCS) by Sangeeta Jain, Rajnish Jain, and Upinder Dhar and Leadership Preference Scale (LPS) by L. I. Bhushan, 1995. The results showed a prevalence of preference for democratic leadership style among employees, with a higher correlation between managerial creativity and leadership preference. The Pearson's correlation between managerial creativity and leadership preference was 0.726. An independent-samples t-test showed a moderately significant difference in managerial creativity levels between male and female employees. The study highlights the importance of considering both leadership preferences and managerial creativity in the corporate sector

Labour segmentation in NCR Delhi’s automobile sector: a political response of capital to labour struggles

This paper aims to understand the changing dynamics of internal labour market segmentation intertwined with the history of working-class struggle in an industrial belt in India’s National Capital Region (NCR). Nuances of workers’ class struggle in the automobile sector in Delhi-NCR over the last 15 years have shown that unity between permanent and contract workers was key to several successful struggles against worsening work conditions and management control within the global value chains of automobile production. Our fieldwork findings, along with direct and indirect political engagement in the region, reveal that increasing salaries and allotment of supervisory roles to small sections of permanent workers, coupled with the simultaneous fragmentation a lower strata of workers into multiple categories with very low salaries, benefits and heavy workloads, have been significant attempts by capital to break class solidarity among different sections of workers. Relatively pro-labour legislation and trade unions tend to concentrate in high-wage zones, while low-wage and precarious employment remains unprotected by such institutional mechanisms. Labour segmentation is inherent to capitalist exploitation, guarded by institutional mechanisms. Advanced mechanisation reduces distinction of skill requirements between highly paid permanent and lowly paid contract workers. In this context, labour segmentation is a political response to trade unionism from the side of capitalist management.

Urban Complexity and the Dynamic Evolution of Urban Land Functions in Yiwu City: A Micro-Analysis with Multi-Source Big Data

The diversification of business forms leads to functional and spatial complexity in cities. The efficient determination of the complexity of an urban system is the basis for the scientific monitoring of the multi-functional aggregation within cities. Previous studies on the urban spatial structure were limited by the difficulty of collecting micro-data and the high time cost, and they focused on the macro-spatial structure, lacking fine-grained investigations of the micro-spatial structure. Additionally, high-resolution remote sensing images, which mainly rely on the textural characteristics of the spectrum of ground objects, cannot detect the social and economic functions of ground objects. Thus, it is difficult to meet the actual needs of urban planning and management. The purpose of this paper is to automatically identify the spatial heterogeneity and temporal variation of urban land use functions in the context of complex urban systems. The TF-IDF (term frequency–inverse document frequency) algorithm, a machine learning classification algorithm, and other methods are applied to identify the urban functions and distribution characteristics of the main urban area based on the POI (point of interest) data and urban form data. The results show the following: (1) From 2012 to 2022, all types of land use in Yiwu city grew at different rates, with logistics and warehousing space growing the fastest, which is in line with Yiwu’s goal of building a national logistics center for trade and services. (2) The residential area has a spatial structure with a dense central circle and a scattered periphery extending from northeast to southwest and from east to west. (3) The commercial service sector shows clear spatial differentiation between the core and the periphery. The commercial functional areas of Niansanli, Houzhai, and Chengxi, where the number of commercial POIs is relatively small, are located at the intersection of the administrative subdistricts near the city center, indicating that the commercial economic activities of the downtown subdistrict have a certain spillover effect on adjacent subdistricts. (4) The public facilities of each subdistrict are generally located in the core of each subdistrict, which ensures better convenience and accessibility. (5) Industrial land with a large total area that is scattered and mixed with urban residential land gradually tends to be centralized, forming an industrial belt around the city. This study comprehensively considers the aggregation relationship between urban buildings and land use and improves the accuracy of land identification and functional zoning.

Актуальные направления меридиональной трансформации транспортно-транзитной системы Азиатской России

The study focusses at describing and determining the prospects for the implementation and operational routes of the meridional transformation of the transport and transit system (TTS) of Asian Russia (AR) in the context of external sanctions pressure and the development of trade and economic cooperation with friendly and neutral states. Goal. Development and implementation of a promising model for connecting the TTS of Russia and the countries of the Global South, primarily in the direction of North Asia – Central Asia – South/West Asia. Tasks. To analyze and determine the prospects for the implementation and current routes of the meridional transformation of the TTS of the Republic of Armenia in the context of external sanctions pressure and the development of trade and economic cooperation with friendly and neutral states. Methodology. The research uses the methods of evolutionary and institutional theory, the theory of industrial and technological balance of the economy and technical and economic structures, expert and analytical assessments, content analysis of materials from periodicals. Results. Based on the theory of transit economy developed by the author's team, modeling the creation and functioning of trade routes and their innovation and industrial belts (IIB), a promising model of the interaction of the TTS of Russia and the countries of the Global South, primarily in the direction of North Asia – Central Asia – South/West Asia, has been developed. Theoretical, methodological, scientific and practical support for the change in the configuration of global, macroregional and regional trade routes of the AR is given, the necessity is justified and proposals for the directions of meridional transformation of the transport and communication infrastructure of the AR are developed. The necessity of intensification of the meridional transformation of the TTS AR is substantiated. The analysis of current infrastructure projects of meridional transformation is given, the groundwork, significance and complexity of the implementation of global projects of latitudinal and meridional transformation of the TTS AR are considered. Conclusions. The most effective direction of the meridional transformation of the TTS AR is the construction of a new Arctic Ocean – Indian Ocean (AO – IO) transport corridor based on the Sixth Technological Order.

FLORISTIC DIVERSITY OF AQUATIC PLANTS FROM THE INDUSTRIAL BELTS OF THE JAJPUR DISTRICT OF ODISHA, INDIA

A comprehensive study was undertaken to assess the aquatic flora in the Jajpur district of Odisha. The survey was conducted within different water habitats within the industrial belts of Jajpur district from 2021 to 2023, aimed at documenting the diverse aquatic habitats in this region. Extensive and intensive studies were carried out to identify and catalog the aquatic plants, with voucher specimens collected and herbaria prepared using established protocols. The research revealed a total of 84 species of aquatic and wetland plants belonging to 55 genera and 31 families. These included 44 marsh species, 18 amphibious species, 3 submerged species, as well as 10 free-floating and 9 fixed-floating species. These plants not only meet the essential needs of the local community but also play a crucial role in maintaining the ecological balance of the area. Further research will be vital in preserving these valuable bio-resources for future generations.

Assessment of Hydro-Geochemical Indices of Periyar River in Eloor Industrial Belt (Kerala), India to Identify Potential Environmental Impacts

The study investigated the role of hydrogeochemical parameters that act as indicators of environmental pollution in industrial areas of Periyar River, Kerala India. A total of 20 water/sediment samples collected along the industrial stretch of Eloor-Vypin area during the premonsoon season of the year 2020. Among the hydrochemical parameters, extent of pollution was imparted by the assessment of nutrients and heavy metals concentration. The micro nutrients such as silicate (640-3440μg/L), ammonia (4.42-894.2μg/L), phosphate (28.65-132.41μg/L), nitrite (3.12-30.14μg/L), and nitrate (50.13-851.97μg/L) were found to have higher enrichment at locations near the industrial areas of the study. The identified heavy metals, Zn, Mn, Pb, Cr, Cd, and Th having concentrations ranging from 1.0-152.4, 1.2-49.2, 1.2-31.7, 3.0-26.2, 1.1-13.3, 0.1-3.2μg/L, respectively. Various pollution indices suggest that the sediments having low to moderate level heavy metal contamination. The conditions may be worsen in the future if the industrial activities are continued in an unregulated manner. Keywords: Industrial Pollution; Heavy Metals; WQI; Hydrochemical Studies; Contamination Factor

Hydrochemical investigation of groundwater quality for drinking and irrigational purposes from industrial belt of Jharkhand, India

AbstractGroundwater (GW) is a key water resource for domestic and agricultural activities. Industrial activities often affect GW chemistry. Therefore, assessment of GW quality for drinking and irrigation purposes is required to be assessed to ensure its suitability in and around industrial setups. Present study was planned to investigate the GW suitability for domestic and irrigation purposes around Bokaro Industrial Area, Jharkhand, India. Sodium Absorption Ratio (SAR), Residual Sodium Carbonate (RSC), Permeability Index (PI), and percentage sodium (% Na) were evaluated for irrigation purposes, while pH, total hardness (TH), and electrical conductivity (EC), Total dissolve solid (TDS), F−, SO42−, HCO3−, Cl−, NO3−, Na+, K+, Ca2+, and Mg2+ for domestic usage. Results showed wide variation in the physicochemical characteristics as major cations were found in the order: Ca2+ > Mg2+ > Na+ > K+, while major anions were in the order of HCO3−> Cl−> SO42−> NO3−> F−. The range of pH 6.15–7.73 and EC was 230–1676 μS cm−1, while TH, Cl−, HCO3−, SO4−, NO3‐, F−, Ca2+, Mg2+, Na+, and K+ was varied from 66–743, 3.3–289.9, 61–392, 5.5–148.5, 1.2–61.4, 0.66–4.38, 14.5–170.3, 4.9–80.2, 12.3–102.7, and 0.37–5.7 mg/L, respectively. It was found that GW quality at most of the sites was suitable for irrigation and domestic purpose except at few locations. Further, results revealed that industrial activity has noticeable impact on the groundwater quality but, the overall suitability indicates a potential recharge system for the aquifers in the area which maintains the GW chemistry. Albeit alarming values of some of the GW parameters, namely, pH, total hardness, F−, HCO3−, Cl−, NO3−, Na+, Ca2+, and Mg2+ at some locations require attention to design and execute effective water management plans to avoid possible irrigation and human health risks in future.

Equilibrium and fixed-bed kinetics study on hazelnut skin polyphenols extraction using choline chloride –lactic acid-based NADES and water as solvents

This paper focuses on the potential of Hazelnut Skin, a waste product from the food industry, as a source of polyphenols in line with circular economy principles. Two environmentally friendly solvents, water and Natural Deep Eutectic Solvent (NADES), were utilized for the extraction process. First of all, the extraction potential of both solvents was evaluated and an amount of 172.2 mg/g and 470.2 mg/g of free polyphenols per unit mass of solid were obtained using Water and NADES respectively. The solid–liquid equilibrium was also deeply investigated observing that two main phenomena are involved during the process: solubilisation and adsorption. An innovative model based on the combination of Langmuir isotherm and the introduction of a partitioning coefficient to describe a progressive approach to the solubility limit was then proposed to characterize the thermodynamics of the system. While NADES showed promising results compared to water in terms of amount of polyphenols extracted, there are several challenges that need to be addressed before implementing NADES in large-scale extraction processes. Hence, in this study continuous tests were conducted to observe the behavior of both solvents in a fixed-bed column that emulates a section of an industrial belt extractor. The experimental data collected were fitted by means of the Broken Intact Cells (BIC) Model. It was found out that the internal mass transfer resistance is the controlling one and the correspondent mass transfer coefficient estimated was 1.3·10-3 min−1 for Water and 6.67·10-4 min−1 for NADES. The results obtained from this study can be considered valuable resources for improving the existing methods of extracting polyphenols from waste matrices using water and for developing innovative approaches that utilize NADES as a solvent.

Time series analysis of groundwater quality at selected sites of Purba and Paschim Burdwan, West Bengal, India.

The Water Quality Index (WQI) is used to monitor the health and usability of a water body. In this study, we aimed to construct time series prediction models using groundwater WQI (GW-WQI) at four sites: IISCO-Asansol, Durgapur Town, Burdwan University, and Burdwan Station. While statistical spatio-temporal analysis has been reported earlier, no time series analysis of the data or predictive modelling has been done. Pre-monsoon and post-monsoon physico-chemical data from 2010 to 2022 were obtained from the West Bengal Pollution Control Board website to calculate the GW-WQI. Prediction modelling was performed using R 4.1.3 software. Best fit forecast models were selected to predict future trends of GW-WQI with 80% of the data. Subsequently, the models were validated using R-squared, root mean square error (RMSE), mean absolute error (MAE), maximum absolute percentage error (MAPE), and Thiel's U for the model using 20% of the data. Our results show that GW-WQI was good in pre-monsoon but unfit for drinking in post-monsoon in IISCO-Asansol, Durgapur Town, Burdwan University, and Burdwan Station. Arsenic, fluoride, and mercury were the major contaminants resulting in poor GW-WQI. Seasonal ARIMA was the best model for Burdwan University and IISCO-Asansol, ETSfor Durgapur Station, and BaggedARIMA for Burdwan Station. The forecast model for Durgapur and Burdwan Station predicted a sharp increase until 2027 but was fluctuating for IISCO-Asansol and Burdwan University. Thus, GW-WQI is a major problem in the industrial belt of West Bengal that is likely to remain high or worsen in the future.

Factors Influencing Customer Preference towards Organised Food Retailing

In India the scope of organized food retailing has increased in the last few years, offering ample amount of opportunities to Indian business. Due to large consumer base, India provides an opportunity for their retailers all over the world to sell their products in India. In any business, change is the only permanent thing. Consumers prefer modern retail stores over the conventional and traditional stores. This has resulted in a major change in consumer behaviour. After considering the important changes in the consumer scenario in India, especially with regard to the present changing pattern in organized retail stores, the researcher has decided to study on consumer behaviour in organized retail industry with reference to organized food retail. This study has been focused on the Bangalore region which is a fast growing industrial belt in South India. It provides a guideline for further research in the area of organized retailing. This study gets importance because in this study, the consumer awareness, factors influencing consumer behaviour, marketing strategies, promotional mix, benefits and problems faced by the consumers and opportunities for the departmental stores in this area have been studied. This research is also getting importance because it aims to identify the consumer response and decision making behaviour in organized food retail. It also shows the future scenario of organized retailing keeping in view of current perspective.

Development of a field-deployable analytical workflow for determining current status and indicative human health risks at a historic dl-POPs hotspot

This paper introduces an integrated workflow that effectively evaluates environmental and health risks of dioxin-like Persistent Organic Pollutants (dl-POPs) at industrial hotspot regions. The developments of validated, cost effective and user-friendly analytical strategies which can be field deployable are quintessential for routine monitoring of dl-POPs, particularly in developing countries. This study addresses the lacunae by enabling an exclusive gas chromatography triple quadrupole mass spectrometer based analytical workflow substituting conventional magnetic sector high resolution mass spectrometer technique and validated the methodology as per the European Union regulation 644/2017. The viable monitoring utility of the methodology for predicting enviro-food-health nexus was field-tested by analyzing fish and sediment samples from the Eloor-Edayar industrial belt, a solitary POPs hotspot in India. The profiles of congeners indicate that dl-POPs were formed through precursor pathways, suggesting the potential release of chlorinated precursor species from surrounding industrial area as the root cause. Fish samples from hotspots were observed to have 8 times higher levels of polychlorinated dibenzo-p-dioxin/furans (PCDD/Fs) and 30 times higher levels of polychlorinated biphenyls (PCBs) than the control sites. A strong statistically significant (p < 0.05) positive correlation was observed between dl-POPs levels in fish and sediment samples at the study site and the Biota sediment accumulation factors for PCDD/Fs and dl-PCBs ranged from 0.019 to 0.092 and 0.004 to 0.671 respectively. The estimated weekly intake from fish consumption in the study region was observed to be 3 to 24 times higher than the maximum levels set by the European food safety authority (2 pgTEQ kg−1bwweek−1). Hence, the periodic surveillance of dl-POPs employing user friendly/validated confirmatory tools stands highly imperative to safeguard human health and environment. Keywords: Dioxin and PCBs, GC-MS/MS, POPs Hotspot, Biota-sediment accumulation factor, Correlation analysis, Health risk assessment.

Lathyrism in Spain: Lessons from 68 publications following the 1936–39 Civil War

ABSTRACT After the end of the Spanish Civil War (1936–1939), an estimated 1,000 patients presented with lathyrism due to their excessive and prolonged consumption of grasspea (Lathyrus sativus L.) against the backdrop of poverty, drought, and famine. Based on 68 scientific communications between 1941 and 1962 by qualified medical professionals, the disease emerged in different geographical locations involving selective populations: (1) farmers from extensive areas of central Spain, traditionally producers and consumers of grasspea; (2) immigrants in the industrial belt of Catalonia and in the Basque Country, areas with little or no production of grasspea, which was imported from producing areas; (3) workers in Galicia, an area where the legume is neither produced nor consumed, who were seasonally displaced to high-production areas of grasspea in Castille; and (4) inmates of overcrowded postwar Spanish prisons. Original reports included failed attempts by Carlos Jiménez Díaz (1898–1967) to induce experimental lathyrism, the neuropathology of lathyrism in early stages of the disease in two patients, as reported by Carlos Oliveras de la Riva (1914–2007), and the special susceptibility of children to develop a severe form of lathyrism after relatively brief periods of consumption of the neurotoxic seed of L. sativus. In the Spanish Basque Country, L. cicera L. (aizkol) was cultivated exclusively as animal fodder. Patients who were forced to feed on this plant developed unusual manifestations of lathyrism, such as axial myoclonus and severe neuropsychiatric disorders, unknown in other regions of the country and previously unreported. The postwar epidemic of lathyrism in Spain represents the most extensively studied outbreak of this self-limiting but crippling upper motor neuron disease.

Stabilisation of Spent Wash by Polyhydroxybutyrate (PHB) Producing Microorganisms Isolated from Karad Region, Maharashtra

In recent years, there has been a significant increase in the needs of the overgrowing population. Naturally, industrial belts increased worldwide to satisfy the variety and quantity of needs. While producing the products, a huge quantity of waste is generated and added continuously to the environment, causing hazardous effects on the flora and fauna. Spent wash is one of the most important types of industrial waste since it is the liquid waste that is left over after making alcohol and it pollutes the environment. Despite effluent quality standards, untreated or partially treated sewage frequently enters water courses or soils. It is always overloaded with organic and inorganic substances. The stabilization of the effluent by microorganisms is reflected in the form of COD reduction. The present study attempted to isolate the PHB-producing organisms and use them to stabilize the spent wash. The locally isolated, characterized, and identified 11 PHB-producing microorganisms from the Karad region of Maharashtra were used to stabilize spent wash. They include Candida orthopsilosis, Bacillus subtilis, Bacillus cereus, Bacillus megaterium, Klebsiella grimontii, Citrobacter fruendii, and members of Staphylococcus and Rhodococcus. All potential organisms were reported to stabilize the spent wash. The degree of stabilization was measured in terms of the percent reduction of COD and BOD. The % reduction was reported at 95.31% and 81.39% of COD and BOD, respectively, by Klebsiella grimontii, followed by 92.18% and 80.46% reductions of COD and BOD, respectively, by Staphylococcus. These organisms are promising in the treatment of spent wash.