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COMPARATIVE ANALYSES OF ECO TOXICITY OF PV TECHNOLOGIES, AND ITS MITIGATION

2026-06-01T00:00:00Z

Title: COMPARATIVE ANALYSES OF ECO TOXICITY OF PV TECHNOLOGIES, AND ITS MITIGATION Authors: GHOSH, SWATILEKHA; Singh, Santosh Kumar (SUPERVISOR); Yadav, Vinod Kumar (CO-SUPERVISOR) Abstract: The global solar photovoltaic (PV) installed capacity has been increasing exponentially since the beginning of the current millennium and has now surpassed 1,866 GW. It is further projected to exceed 4,500–5,000 GW by 2050 if it continues to grow at the same pace. Though capacity addition at this exponential rate will help meet the ever-growing energy demand, it may bring along several environmental concerns that have not received adequate attention from researchers and policymakers so far. The output of solar PV systems is sensitive to environmental conditions, and past research shows that it fluctuates widely with wind speed, wind direction, the chemical composition of available dust, dust particle size, relative humidity, and irradiance intensity. To maintain the output of PV installations at the intended or design levels, they require frequent cleaning with fresh water, a scarce resource in many parts of the world. Apart from power output, environmental factors also affect PV reliability, and partial shading conditions (PSC) are among the most significant. PSC may be created by non-uniform dust deposition on the module, inconsistent cleaning of the module glass, bird droppings, leaves, and shading from nearby trees, electric towers, and modules in adjacent rows at low sun altitude. Under PSC, the shaded cells become non-productive or under-productive, depending on the intensity of the shade. In such situations, the affected cells become a load on the productive or generating PV cells. This implies that the cell under PSC starts consuming or dissipating energy rather than generating it, and the temperature of the affected cells begins to rise. The literature indicates that cell temperatures can reach up to 400 °C under PSC. Apart from reducing the PV system's efficiency and power output at elevated temperatures, this also affects its reliability. The high temperature gradient within the module can cause the top glass to crack in extreme cases. Under such scenarios, atmospheric oxygen enters the module through cracks. It causes the Ethylene/Vinyl Acetate (EVA), which is used as a sealant in the modules, to catch fire. The phenomenon discussed in the paragraph above is one of the dominant early failure modes of PV modules and, together with the end-of-life (EoL) waste volume, contributes to the cumulative volume of PV waste. EoL PV waste management has not received sufficient attention from researchers yet, as EoL PV waste generation has a vii temporal offset of 25-30 years (i.e., the expected life of PV modules). Although the history of PV application for power generation dates back about seven decades, the installed capacity began to grow exponentially only at the beginning of the 21st century. And hence, presently, EoL PV waste generation and its management remain a crisis in the making; however, the world has reached a stage where it is imperative to recognize the issue it is heading to face in the near future. The PV waste volume was 1000 times less than the global electronic waste generated in 2014; however, the total PV waste may reach 8 million tons by 2030 and 78 million tons by 2050 under an early-failure scenario. The infrastructure required to handle even the existing E-waste volume is insufficient in developing countries, and 90% of this volume is disposed of in unscientific ways, as PV recycling technology is yet to reach commercial viability. The additional volume of PV waste will overburden the infrastructure, which is even inadequate to handle the existing e-waste volume, if the rate of PV waste generation is not restricted. Hence, it is imperative to investigate the effects of various environmental factors on PV reliability and to devise methods to mitigate early failures. The silver lining is that, according to an estimate from the International Renewable Energy Agency, these figures could drop by 78% in 2030 and by 30% in 2050 if early failures are averted or mitigated. To address the above problem, the present research work critically analyzes the renewable energy growth trend over the last two decades and identifies various technical and environmental challenges arising from policy biases in related policies. Further, the ecological footprints of the two most widely used technologies, i.e., crystalline silicon (c-Si) and cadmium telluride (CdTe), are analyzed holistically over the entire life cycle, and the environmental impact of c-Si is found to be greater than that of CdTe, contrary to common perception. Hence, a policy change is recommended to incentivize the production and use of CdTe PV modules. Lastly, the c-Si PV modules are further evaluated for the effectiveness of the hotspot prevention mechanism under partial-shading conditions, and the lacunae in the existing commercial PV module design are identified. Based on the findings of the above research, suitable policy changes are solicited to make PV energy environmentally sustainable and thereby keep the shade of this energy technology truly green.

ENVIRONMENTAL SUSTAINABILITY OF BIOFUELS IN INDIA: AN LCA APPROACH

2026-10-01T00:00:00Z

Title: ENVIRONMENTAL SUSTAINABILITY OF BIOFUELS IN INDIA: AN LCA APPROACH Authors: PATEL, KULVENDRA; SINGH, S.K. (SUPERVISION) Abstract: The increasing global demand for energy, coupled with the environmental consequences of prolonged reliance on fossil fuels, has intensified the search for sustainable, renewable energy alternatives. Among these, biofuels have emerged as a promising solution due to their potential to reduce greenhouse gas emissions, enhance energy security, and support rural economies. In the Indian context, rapid industrialization, urbanization, and population growth have further increased energy demand, making the transition to cleaner fuels both an environmental necessity and a strategic priority. Bioethanol and biodiesel, as liquid biofuels compatible with existing infrastructure, have gained significant attention; however, their environmental sustainability varies considerably depending on feedstock selection, production processes, and regional conditions. Therefore, a comprehensive evaluation from a life cycle perspective is essential to ensure that hidden burdens across the different stages of production and use do not offset their perceived environmental benefits. This research systematically evaluates the environmental sustainability of bioethanol and biodiesel production in India using a Life Cycle Assessment (LCA) framework. For bioethanol production, diverse feedstocks, including molasses, broken grains, agricultural residues (rice straw, corn stover, cassava straw), and municipal solid waste, are assessed. At the same time, biodiesel pathways include edible oil-based (rapeseed, palm oil, palm stearin), non-edible oil-based (jatropha), waste-derived (used cooking oil), and third-generation (microalgae) feedstocks. A cradle-to-gate approach is adopted to quantify impacts across multiple categories, such as global warming potential, resource depletion, water consumption, toxicity, and ecosystem damage, using ReCiPe 2016, IMPACT 2002+, and IMPACT World+ methods, complemented by cumulative energy demand analysis and Monte Carlo simulation to ensure statistical robustness and uncertainty characterization. The results demonstrate that environmental performance is strongly feedstock-dependent across both biofuel systems. In bioethanol production, global warming impacts range from 3.3 to 3.8 kg CO₂ eq, with significant contributions from ecotoxicity categories (up to 7.21 kg 1,4 DCB eq), largely driven by energy-intensive stages such as pre-treatment, enzymatic vii Environmental Sustainability of Biofuels in India: An LCA Approach hydrolysis, and distillation. First-generation pathways, such as molasses and grain, exhibit moderate impacts but are heavily influenced by electricity and steam consumption, whereas second-generation feedstocks, such as agricultural residues, demonstrate comparatively lower impacts and improved resource efficiency due to waste valorization. However, MSW-based bioethanol exhibits poor energy performance (NER = 0.48, NEV = −47.39 MJ, NRnEV = −23.63 MJ) despite its circular-economy advantages. In biodiesel systems, substantial variation is observed across feedstocks, with palm oil and microalgae exhibiting the highest environmental burdens (5.92 and 5.89 kg CO₂ eq, respectively), primarily due to intensive agricultural inputs and energy consumption during cultivation and processing. In contrast, waste derived biodiesel from used cooking oil demonstrates the lowest impacts and minimal fossil resource use (0.15 kg oil eq), indicating strong environmental and circularity benefits. Non-edible feedstocks such as jatropha have moderate impacts, whereas rapeseed biodiesel has relatively higher burdens due to fertilizer-intensive cultivation practices. These findings highlight that feedstock selection is a critical determinant of sustainability outcomes in biodiesel production. Energy analysis further reveals that most agricultural residue-based bioethanol systems are energy-positive, with NER values up to 4.19 and NEV values around 32–33 MJ, indicating favorable net energy gains and reduced dependence on fossil fuels. Similarly, biodiesel from UCO demonstrates superior energy efficiency (NER = 5.49) and a lower cumulative energy demand than conventional feedstocks. Across both biofuel systems, key environmental hotspots include electricity consumption, steam generation, fertilizer use, and chemical inputs, emphasizing the need for process optimization and integration of renewable energy sources. Uncertainty analysis indicates low to moderate variability across most impact categories, with coefficients of variation generally between 4% and 10%, confirming the robustness and reliability of the model outputs. The probabilistic distributions follow near-lognormal behavior with well-defined confidence intervals, although higher variability is observed in toxicity-related categories, reflecting sensitivity to input parameters and underlying assumptions. The comparative assessment highlights that second-generation and waste-derived biofuels consistently outperform first-generation systems in environmental and energy performance, whereas third-generation pathways, such as microalgae, require further viii Environmental Sustainability of Biofuels in India: An LCA Approach technological advancements to reduce their energy and nutrient intensity. From a policy perspective, the findings support the promotion of non-edible and waste-based feedstocks, improved process efficiency, and the integration of renewable energy within biofuel production systems. In conclusion, this study provides a comprehensive, quantitative evaluation of the sustainability of bioethanol and biodiesel in India, demonstrating that their environmental performance is shaped by a complex interplay of feedstock characteristics, production technologies, and energy inputs. The integration of LCA, energy analysis, and uncertainty assessment provides a robust decision-support framework for identifying critical hotspots and guiding the development of sustainable biofuel systems aligned with climate mitigation, resource efficiency, and circular-economy objectives.

STATUS OF GROUNDWATER QUALITY IN LUDHIANA DISTRICT OF PUNJAB, INDIA

2026-05-01T00:00:00Z

Title: STATUS OF GROUNDWATER QUALITY IN LUDHIANA DISTRICT OF PUNJAB, INDIA Authors: GOYAL, DEEPALI; Singh, S.K. (SUPERVISION); Haritash, A.K. (CO-SUPERVISOR) Abstract: The present study provides an integrated assessment of groundwater quality in Ludhiana district, Punjab, based on 152 groundwater samples characterized by 18 physicochemical parameters. These were synthesized into a Drinking Water Quality Index (WQI) to evaluate potable suitability. The WQI classification shows that 2.6% of samples are “excellent” and 57.9% “good,” whereas 32.9%, 4.0%, and 2.6% fall into “poor,” “very poor,” and “unsuitable” categories, respectively, indicating spatially heterogeneous degradation in groundwater quality. Hydrogeochemical characterization, supported by facies diagrams, ionic diagnostics, saturation indices, and multivariate statistics, indicates that groundwater chemistry is primarily governed by carbonate and silicate weathering, with active cation exchange. Saturation indices show that groundwater is generally supersaturated with respect to calcite, dolomite, and aragonite, and undersaturated with respect to halite, fluorite, and sylvite. Spatial variability in nitrate and other key parameters reflects localized agricultural and urban influences, while IDW interpolation in QGIS has been used to generate spatial distribution maps of major ions. In the present study, irrigation suitability has been evaluated using salinity, sodicity, and carbonate–bicarbonate hazard indices, including EC, %Na, SAR, and PI. In addition, an Irrigation Water Quality Index (IWQI) is computed using EC, SAR, Na⁺, Cl⁻, and HCO₃⁻ concentrations. Salinity classification indicates that 62.5% of samples fall within the “medium” EC range (250–750 µS/cm), while 37.5% fall within the “high” category. Hazard assessment indicates that 75% of samples fall within the excellent-to-permissible range based on %Na, 97.4% belong to the S1 class (low sodicity) based on SAR, and all samples fall within PI Classes I–II. However, IWQI based classification indicates irrigation constraints, with 21.7% of samples under “severe restriction” (IWQI < 40), 37.5% under “high restriction” (40–55), 33.6% under “moderate restriction” (55–70), and only 7.2% under “low restriction” (70–85). IDW based GIS mapping delineates zones of elevated irrigation risk, particularly in eastern Samrala and Khanna, parts of Ludhiana II and Machhiwara, and southern to western xvi Pakhowal and Sidhwan Bet, whereas low-restriction pockets are confined to limited villages such as Sherpur Kalan, Bardeke, Hathur, and Dholanwal. An ANN-based predictive model for IWQI is developed using the multilayer perceptron architecture in IBM SPSS with standardized inputs. The optimal network includes five input neurons (EC, SAR, Na⁺, Cl⁻, HCO₃⁻), two hidden layers, and one sigmoid-activated output neuron, trained using batch learning and gradient-descent backpropagation. The model achieved RMSE values of 0.09 for training and 0.07 for testing, indicating strong predictive performance and close agreement between observed and simulated IWQI values. Sensitivity analysis shows that Cl⁻ has the highest normalized importance (100%), followed by SAR (59.7%), Na⁺ (58.5%), HCO₃⁻ (53.1%), and EC (27.2%), confirming the dominant influence of salinity and sodicity on irrigation water quality. Additionally, nitrate distribution has been examined to distinguish regional hydrogeological controls from localized anthropogenic influences. The weak statistical association between nitrate concentration and hydraulic parameters indicates that regional groundwater flow is not the principal control on nitrate occurrence. The lack of a coherent downgradient nitrate plume suggests that nitrate distribution is governed mainly by localized recharge and anthropogenic inputs. A conservative nitrate-transport scenario simulated by coupling the calibrated transient MODFLOW flow model with MT3D-USGS shows a decline in mean nitrate concentration from 8.86 mg/l in Year 1 to 6.51 mg/l in Year 10 (~27% reduction), contraction of the >45 mg/l footprint from ~1.70% to ~0.88%, and a reduction in peak concentrations to a maximum simulated value of ~69.95 mg/l after 10 years.

STUDY OF AEROSOLS IN INDOOR - OUTDOOR MICROENVIRONMENTS FOR URBAN HOUSEHOLDS OF DELHI

2026-02-01T00:00:00Z

Title: STUDY OF AEROSOLS IN INDOOR - OUTDOOR MICROENVIRONMENTS FOR URBAN HOUSEHOLDS OF DELHI Authors: SHARMA, MONIKA; Mishra, Rajeev Kumar (SUPERVISOR); Khare, Mukesh (CO-SUPERVISOR) Abstract: Rapid urbanization increases the population density in urban regions, which compromises the standard of living. Indoor air quality in urban regions is a serious concern. To understand the indoor air quality in residential homes of one of the India’s most polluted cities, Delhi. This is a region where detailed studies remain scarce, especially in residential context. This study analyzed the concentration of indoor particulate matter and particle number concentration in urban clusters where significant socioeconomic differences exist within the same geographical domain. To understand the indoor air quality in residential homes of one of the India’s most polluted city, Delhi. This is a region where detailed studies remain scarce, especially in residential context. This study also estimated the seasonal variations of indoor and outdoor particle number concentrations in different socioeconomic household conditions in the urban city Delhi. This study investigated the impact of festival activities on household indoor air quality in megacity Delhi. The study included different phases and activities during the festival and normal conditions and analysed the impact of different emissions. The portable aerosol spectrometer was employed to measure quasi-ultrafine, sub-fine, fine, and coarse particle concentrations in the kitchen, bedroom, and outdoor conditions. Indoor air quality is crucial for the well-being of residents, as people spend 80% of their time indoors. Particulate matters (PM10, PM2.5, and PM1) were measured in two major indoor microenvironments (kitchen and bedroom) along with outdoors of the selected households during winter, summer, and monsoon seasons. Four major income groups were considered for the study. A poorly ventilated kitchen was found to have higher concentrations of PM10 (247 μg/m3), PM2.5 (200 μg/m3), and PM1 (153 μg/m3), respectively. Indoor, PM1 contributed ~40 to 85 % to PM10. During winter, the seasonal mean I/O ratio of PM10, PM2.5, and PM1 ranged between 1.1 and 1.8 in bedroom and between 0.8 and 2.2 in kitchen. The influence of outdoor particulate matter concentration on indoor air was observed to be high during winter, followed by summer and monsoon. The higher concentration in kitchen leads to an exposure of 0.10 μg, and in bedroom, it was 0.11 μg for adults with a higher breathing rate. The exposure depends on the xi concentration and exposure time. The PM2.5 depositions were found more in the lower lung regions. The findings of the study revealed that quasi-ultrafine (250 to 500 nm) particle concentration was high (2.1×106 #cm-3) in urban poor households during the winter season. Indoor quasi-ultrafine particle concentration ranged between ~105–106 #cm-3 in the kitchen and bedroom. In a properly ventilated kitchen, a significant reduction in indoor particle number concentration (1.2×106 #cm-3 to 7.1×105 #cm-3) was observed. The number concentration of coarse particles was found to be the lowest (< 1.1×103 #cm- 3) among other sizes. However, indoor sources resulted in a higher I/O ratio of 40. Lower- income group kitchens exhibited a higher number concentration of different-sized particles, which also influenced bedroom concentration. During the festival period, the indoor ultrafine particle concentration was found to be 6.7 × 104 #cm-3, which was the highest observed indoor concentration throughout the study. The particle number concentration of the nanoparticles in indoor environment ranged from 104 to 105 #cm-3. Ultrafine size range particles contributed up to 85% to the total particle numbers. Fireworks contributed to higher particle numbers in indoors, followed by cooking, dusting, and worshiping. The size distribution pattern of the particles emitted during cooking activities and fireworks were found to be different. Particle size range 10 to 30 nm contributed 31 % to total particle numbers on fireworks day, whereas on a normal day, it contributed only 13 %. During a normal day, 100 to 1000 nm size particles contributed ~50 % to the total particle numbers. The diurnal pattern of the indoor environment was different to the outdoor. The outdoor fireworks activities also influenced indoor pollutants with respect to trace metals, which makes the indoor air quality more toxic and affects the occupants' health. Indoor particle number concentration (PNC) varies significantly in different microenvironments. Cooking, dusting, and incense stick burning are major indoor activities that generate different-sized particle numbers. The number concentration of the quasiultrafine particles (qUFP) was found to be a maximum of (106 #cm-3), followed by subfine (105 #cm-3), fine (104 #cm-3), and coarse (103 #cm-3) particles. The winter season exhibits a higher decay period of particles in indoor. The number concentration of xii particles observed during nighttime was higher than the concentration during daytime. The particles generated during cooking took more time to decay, up to 320 minutes, followed by dusting (120 to 300 minutes) and incense stick usage (< 200 minutes). Roasting, stir frying, and gravy preparation emit a higher concentration of qUFP (4 to 5×106 #cm-3) and sub-fine (6 to 8×105 #cm-3) particles. More fine particles were generated during stir-frying (3×104 #cm-3) and coarse particles (2×103 #cm-3) were emitted at high levels during roasting. The boiling method of cooking generates a very less number of qUFP and subfine particles (< 105 #cm-3). The measured particle number concentration linearly correlated with particulate matter, and the influence of indoor sources was found to be more in the studied microenvironments. Indoor number concentrations were found to be higher than in the outdoor environment. Households with good infrastructure conditions were found to have less influence on one microenvironment than another. Improving indoor air quality relies not only on sources but also on ventilation status, built infrastructure, occupants’ behaviour, and the influence of outdoor air. Since people spend the majority of their time indoors, it will be more vulnerable to residents. Indoor pollution in households needs to be mitigated and regulated for a better standard of living.