Mahenthiran Sathiyamoorthy

Purpose: Existing BIM-enabled digital twins visualize indoor environmental quality but don't rank spaces by environmental risk across occupancy states. This study creates an occupancy-aware fuzzy analytical hierarchy process (FAHP) decision layer, integrated with a low-cost BIM-enabled DT, to generate ranked classroom priorities for intervention in educational buildings. Design/methodology/approach: A four-layer DT architecture (data acquisition, transmission/storage, modeling/integration, analysis/visualization) was implemented using Arduino UNO R4 Wi-Fi microcontrollers and low-cost sensors (temperature, humidity, CO, NO2, PM2.5, CO2) across five classrooms in an educational building in Vellore, India, under both occupied and unoccupied conditions. Data were transmitted via ThingSpeak and visualized in a Revit/Dynamo BIM model. Three experts pairwise compared six IEQ parameters using Buckley's geometric-mean FAHP to derive crisp weights (consistency ratio = 0.087). Final classroom scores combined weighted, normalized occupied and unoccupied values (a = 0.5), with sensitivity analysis across a = 0.3–0.9, and a two-tier decision rule reconciled relative FAHP rankings with absolute exceedance of WHO/ASHRAE guidelines. Findings: PM2.5 (0.428) and CO2 (0.231) received the highest weights. Classrooms 2 (0.2895) and 3 (0.284) ranked highest (worst relative IEQ) and were consistently top priorities across most a values; all five classrooms exceeded WHO CO guidelines at some point. Practical implications: Linking real-time IoT data to the DT supports demand-controlled ventilation and timely interventions, reducing unnecessary energy use and pollutant exposure, supporting SDG 7 and SDG 13. Originality/value: The study introduces a novel occupancy-differentiated FAHP weighting scheme that links BIM-DT sensor data directly to actionable classroom prioritization, thereby addressing the gap between IEQ visualization and facility management decision-making.

Industrial regions face a significant problem in groundwater management due to increased water demand and potential contamination risks. To establish an effective groundwater management plan in the industrial region, comprehensive understanding of both groundwater availability and quality is needed. Therefore, the main goal of this study was to determine the groundwater potential zone (GWPZ) of an industrial region while also taking water quality into account. For this purpose, the combination of remote sensing (RS), geographical information systems (GIS), and the fuzzy analytical hierarchy process (FAHP) was used. Geology, drainage density, rainfall, soil, slope, elevation, normalised difference vegetation index (NDVI), land use/land cover (LULC), and topographic wetness index (TWI) layers were integrated for the assessment. The GWPZ map is divided into five classes: very poor (10.01%), poor (21.79%), medium (31.36%), high (27.13%), and very high (9.71%) zones. The water quality parameters that exceeded the desirable limit in the study region was selected for groundwater quality zone (GWQZ) mapping. The GWQZ map was classified into three categories: within desirable limit (26.40%), within permissible limit (49.28%), and above permissible limit (24.32%). The integration of these two maps revealed that certain locations with medium to high GWPZ have low groundwater quality. Some areas of the very poor GWPZ had quite excellent groundwater quality. This study provided valuable insights into the spatial distribution of groundwater resources, highlighting areas where potential conflicts between quantity and quality may arise. This research showed that for sustainable management, both the quality and quantity of groundwater resources should be considered.

Microplastics (<5 mm) have become a pervasive environmental pollutant, contaminating marine and terrestrial ecosystems globally. Their persistence, low recycling rates, inadequate waste management, and extensive use in maritime activities facilitate widespread distribution. Microplastics are found in various media, including biota, water, soil, air, and human consumables. India’s growing plastic production and inadequate recycling infrastructure have intensified microplastic research over the past two decades. This study undertakes a systematic review of the extant literature on microplastics (MPs) in India’s freshwater ecosystems, with a focus on lacustrine and riverine environments. A comprehensive bibliographic search was performed utilizing multiple databases, including ScienceDirect, Google Scholar, and ResearchGate. Our finding reveals that marine ecosystems have received significant attention, other compartments (freshwater, terrestrial environments, and human consumables) remain understudied. Running streams facilitate microplastic transport across ecosystems, exacerbating their ubiquity. Moreover, this review synthesizes existing literatures on microplastic distribution, characteristics, fragmentation, and pathways of microplastics in Indian aquatic environments. Therefore, to better understand the microplastic issue, we propose broadening research to encompass uninvestigated Indian aquatic environments, particularly pristine areas, and exploring all aspects of microplastic pollution, along with this, this review highlights critical research gaps and recommends sustainable management strategies for mitigating microplastic pollution.

Agriculture is predominantly practiced in the Cuddalore district, Tamil Nadu, India. The aim of this research work is to examine the groundwater suitability for drinking and irrigation activities and identify the factors influencing the groundwater quality. Physicochemical parameters such as pH, total dissolved solids, calcium, magnesium, sodium, potassium, chloride, sulphate, bicarbonate and nitrate are obtained for 62 groundwater samples (pre-monsoon and post-monsoon seasons). Based on the drinking water quality index (DWQI), most of the groundwater samples were good for drinking purposes in the region. The groundwater with elevated DWQI needs treatment before consumption. The parameters such as EC, Na%, SAR, MH and KR were integrated to produce a single irrigation water quality index (IWQI); it showed that most groundwater in the region is good for agricultural usage. Only a few samples were poor for agricultural usage. In these poor water quality areas, surface water and rainwater should be considered as alternative sources. There is a slight decrease in the concentration of groundwater ions during post-monsoon due to the dilution and dissolution processes. A multilinear regression model is also developed to predict the DWQI and the IWQI. The scatter diagram between various ions depicts that the geochemical process and anthropogenic sources influence the groundwater quality.

Lake ecosystems provide vital services, but face escalating threats from synthetic microplastic (MP) pollution driven by human activities, necessitating urgent action. This study investigates MP contamination in Dharapadavedu Lake, Tamil Nadu, India, characterizing its presence and distribution. MPs in water and sediment were assessed using NOAA's standardized protocol. The results indicate that mean concentration of MPs in lakeshore sediment and water was 2.46 ± 1.06 particles/kg and 1.26 ± 0.88 particles/L, respectively. Significantly, medium-sized MPs (500–1,000 μm) were most abundant, comprising predominantly white, red, and green colors with fragments and fiber morphotypes. Attenuated total reflection Fourier transform infrared spectroscopy revealed valuable insights into the polymer composition of MPs in the lake, identifying four primary types: nylon (polyamide), high-density polyethylene, low-density polyethylene, and polypropylene. Pollution load index data reveals that MP pollution levels of 2.26 in sediment and 1.46 in water indicate a moderate to high level of risk. These findings reveal that the repercussions of recreational activities, anthropogenic activities, and fishing practices around the lake contributed to the accumulation of MPs in the lake. This study fills a research gap by investigating MP pollution in Dharapadavedu Lake for the first time, establishing a baseline contamination estimate.

Ranipet district in Tamil Nadu is one of the major industrial zones in India. Groundwater has been extensively used in this region for drinking, agricultural, and industrial purposes. For finding the groundwater quality, representative samples have been collected in the premonsoon (PRM) and postmonsoon (POM) seasons of 2023 and analysed for major physicochemical parameters. The drinking suitability was analysed based on drinking water quality index, and it showed that 68.52 and 70.37% of samples from the PRM and POM seasons are classified as poor groundwater for drinking. The groundwater's suitability for irrigation was analysed based on various irrigation quality indices, and it highlighted that most of the groundwater was suitable for agriculture. Industrial suitability was determined by several industrial quality indices. Due to the simultaneous application of several indices, a sample is categorised into many water quality groups, introducing bias into handling and decision-making. The Mamdani fuzzy inference system creates a unique integrated industrial water quality index to address this issue. The index revealed that only 24.07 and 9.26% of samples from the PRM and POM seasons, respectively, were free of corrosion or scaling, while the remaining samples were inappropriate for industrial use.

Groundwater is an essential source for household, irrigation and industry needs. The amount of groundwater and its quality are rapidly declining because of urbanization and industrialization. Groundwater resources in hard rock regions should be handled properly to maximize their utilization. This work aims to demarcate the Groundwater Potential Zones (GWPZ) in a part of the Palar River Basin (Ponnai sub-basin) by combining Remote Sensing (RS), Geographic Information System (GIS) and Fuzzy-Analytical Hierarchy Process (FAHP). The factors which influence the groundwater like geology, land use/land cover (LULC), geomorphology, slope, soil, rainfall, lineament density (LD), drainage density (DD), normalized difference vegetation index (NDVI), topographic wetness index (TWI) and topographic position index (TPI) are considered for mapping of GWPZ. The weightage is allocated to these parameters on the basis of the FAHP technique and the obtained groundwater potential map was classified as, very poor (13.5%), poor (21.76%), moderate (31.5%), good (20.66%) and very good (8.54%). The GWPZ map was validated with the actual well yield of the Ponnai sub-basin. The research work will serve as a guideline for the effective use of groundwater and long-term sustainable management of the aquifer in the Ponnai sub-basin.