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Publication Embargo Spatial distribution and hydrological influences of microplastic contamination in the upstream reach of the ambathale water treatment plant intake, Sri Lanka(Springer Science and Business Media, 2026-08-07) Rathnayake, D; Miguntanna, N; Rathnayake, UMicroplastic contamination has emerged as a global environmental concern, with rivers serving as important pathways for the accumulation and transport of these particles. This study investigated the spatial distribution of microplastic contamination and the influence of hydrological and physicochemical factors on microplastic occurrence in the upstream reach of the Ambathale Water Treatment Plant intake along the Kelani River, Sri Lanka. Water samples were collected from four locations within the study area, including three upstream sites and one downstream site. Microplastics were detected at all sampling locations, with Kelaniya recorded the highest microplastic concentration (20.08 ± 10.19 mg/L), while Ambathale had the lowest (9.12 ± 3.89 mg/L). Three main microplastic types were identified: fibers, fragments, and films. Fibers and fragments were the most abundant microplastic types across all sampling locations, while films occurred at comparatively lower concentrations. Statistical analyses revealed a significant positive correlation between river water level and microplastic concentration (r = 0.883, p = 0.001), indicating the importance of hydrological conditions in microplastic transport. Fiber and film concentrations exhibited particularly strong positive relationships with water-level fluctuations (r = 0.940 and r = 0.904, respectively; p < 0.01). Furthermore, positive associations between microplastic abundance and suspended solids suggest that particulate matter plays an important role in the transport and distribution of microplastics within the river system. The findings demonstrate significant spatial variability in microplastic contamination and highlight the influence of hydrological processes on microplastic occurrence and transport in the Kelani River. This study provides baseline information for future monitoring and contributes to a better understanding of microplastic dynamics in tropical freshwater environments.Publication Open Access CALCOM: An integrated techno-economic and life-cycle environmental framework for electric vehicle assessment in Sri Lanka(Elsevier B.V., 2026-08-01) Abeygunawardena, N; Wijayapala, A; Jathunga, TElectric vehicle (EV) adoption is accelerating worldwide, creating a need for comprehensive frameworks that assess economic feasibility and environmental performance. This study presents a context-adaptive levelized cost of mileage (CALCOM) framework to evaluate the economic and environmental performance of battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), and internal combustion engine vehicles (ICEVs) under Sri Lankan conditions. The framework integrates discounted life-cycle cost (LCC), net present value (NPV), and greenhouse gas (GHG) emissions into a unified assessment model. Real-world operational ad cost data were collected from owners representing Nissan Leaf (BEV), Toyota Aqua (HEV), and Toyota Vitz (ICEV). The analysis included purchase cost, energy consumption, maintenance, battery replacement, salvage value, and environmental costs over a 10-year ownership period. The BEV achieved the lowest levelized cost of mileage of 0.080 USD/km which further decreased to 0.050 USD/km under renewable charging. Life-cycle GHG emissions were 59% lower than those of ICEV. Sensitivity analysis identified electricity price, annual distance travelled, and charging efficiency as the primary determinants of BEV competitiveness. Threshold analysis indicated that BEVs remain economically attractive when domestic electricity tariffs are maintained below 0.32 USD/kWh. The findings demonstrate that BEVs offer the greatest economic and environmental benefits and offer evidence-based guidance for policies supporting electric mobility in developing countries.Publication Embargo Fusion of Lean Six Sigma-DMAIC Tools and Techniques into Construction Variation Management: Barriers and Strategies(American Society of Civil Engineers (ASCE), 2026-11-01) Shashini, T.W.K.N; Jayanetti, J.K.D.D.T; Disaratna, V; Ranadewa, T; Perera, B.A.K.SVariations in construction projects pose a significant challenge to achieving successful project outcomes. Lean Six Sigma has the potential to manage variations in the construction industry. This study aims to explore the fusion of lean Six Sigma (LSS)-Define, Measure, Analyze, Improve, and Control (DMAIC) tools and techniques into construction practice to manage variations. Adopting a pragmatic stance and a qualitative approach, empirical data were collected through a three-round Delphi expert survey using semistructured interviews, with the data analyzed through content analysis. The findings reveal that 25 LSS-DMAIC techniques and tools can be effectively applied to manage variations in the construction sector. In addition, 17 barriers and 21 strategies were identified, and a mapping was undertaken to align each barrier with suitable strategies. This research addresses a gap in existing literature by extending investigations of LSS-DMAIC in construction to the specific context of managing variations, identifying barriers to implementation, and proposing strategies, an area that has not been explicitly examined previously. By investigating the barriers to implementing LSS-DMAIC and by suggesting tailor-made strategies for overcoming each barrier, the study makes both theoretical and practical contributions. It provides a framework for on the applicability of LSS-DMAIC in developing countries while offering construction managers context-specific solutions to enhance project outcomes and improve stakeholder satisfaction.Publication Open Access Drivers of carbon emissions in G7 economies: Evidence on energy use, globalisation, urbanisation, industrialisation and innovation(Elsevier Ltd, 2026-08-26) Weerasinghe, L; Vithanage, N; Rupasinghe, D; Keesha, C; Jayathilaka, RRising CO2 emissions remain a major sustainability challenge, particularly in advanced economies that account for a considerable share of historical emissions. This study examines the key determinants of CO₂ emissions in G7 countries by jointly considering globalisation, energy consumption, urbanisation, industrialisation, and technological innovation. Using a balanced panel dataset for Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States over the period 1997–2023, the analysis applies panel regression techniques and country-specific multiple linear regressions to capture both common effects and heterogeneity across economies. The results indicate that energy consumption is a robust driver of CO₂ emissions across the G7. Technological innovation contributes to emission reduction at the panel level; however, its effect becomes statistically insignificant in country-specific estimations, reflecting cross-country differences in innovation structures and policy environments. Globalisation significantly increases emissions in Canada, while its influence is negligible elsewhere. Urbanisation shows a mitigating effect only in the United States, and industrialisation increases emissions in Canada and Italy but reduces emissions in Japan. Overall, the findings highlight that decarbonisation strategies in advanced economies should prioritise the transition to clean energy while strengthening innovation-oriented climate policies tailored to country-specific contexts.Publication Open Access Anthocyanin (ATH)-incorporating polyvinylpyrrolidone-ethyl cellulose-(2-hydroxypropyl)-β-cyclodextrin (PVP–EC–BCD) nanofiber-based pH sensor for ocular pH detection during accidental chemical spills(Royal Society of Chemistry, 2026-02-03) Sandaruwan, B; Liyanage, R; Costha, P; Dassanayake, R.S; Wijesinghe, R.E; Herath H.M.L.P.B.; Nalin de S.K.M; de Silva, R.M; Rajapaksha, S.M; Wijenayake, U; Manatunga, D.CThe existing ocular pH detection methods encounter numerous limitations, including low accuracy, poor sensitivity across a wide pH range, and patient discomfort, highlighting the need for innovative approaches. A novel biosensor for ocular pH detection has been developed to assess ocular health and chemical injuries in clinical settings. This study uses the pH-sensitive properties of anthocyanins (ATHs), natural pigments extracted from butterfly pea flowers, to develop a novel pH-responsive nanofiber mat. ATHs are integrated into a polymer blend containing polyvinylpyrrolidone (PVP), ethyl cellulose (EC), and (2-hydroxypropyl)-β-cyclodextrin (BCD) to fabricate electrospun nanofibers. The acquired characterization, employing scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and thermogravimetric analysis (TGA), confirmed the successful fabrication of the ATH-infused nanofibers with a mean diameter ranging from 121 to 396 nm. Four formulations were tested: PVP:EC:BCD:ATH (18 ppm), PVP:EC:BCD:ATH (25 ppm), PVP:EC:BCD:ATH (35 ppm), and PVP:EC:BCD:ATH (50 ppm). Among them, the 50 ppm ATH-incorporating nanofiber mat exhibited the best performance in terms of color clarity, response time, and pH sensitivity. The fabricated 50 ppm ATH incorporating nanofiber mat demonstrated a rapid pH response time of less than 5 seconds (s) while exhibiting a color variation from pink to blue to green across the pH range of 1 to 12, providing a rapid and accurate method for visual pH detection. Based on the color performance of the 50 ppm ATH-incorporating system, a standardized color reference chart was developed to serve as a practical and visual guide for estimating pH levels in clinical applications. Zebrafish toxicity assays were conducted further to validate the safety and biocompatibility of the developed sensor, revealing no significant toxic effects across the range of ATH concentrations.Publication Open Access Nature-Based Urban Drainage Solutions Using Industrial Waste-Incorporated Pervious Concrete Pavements(Multidisciplinary Digital Publishing Institute (MDPI), 2026-03-11) Ratnapala, N; Miguntanna, Nandika; Miguntanna, Nadeeka; Rathnayake, UPervious concrete pavements have gained increasing attention as a sustainable stormwater management solution due to their ability to reduce runoff volume and improve water quality through infiltration. This study investigates the stormwater runoff treatment potential and performance efficiency of pervious concrete pavements incorporating industrial waste materials, namely recycled concrete aggregate (RCA), ceramic waste (C), and waste tires (T), as partial replacements for natural coarse aggregates. Concrete mixes were prepared by replacing 10%, 20%, and 30% of the coarse aggregate volume with each waste material, and the results were compared with normal pervious concrete. Stormwater runoff treatment performance was evaluated by analyzing key water quality parameters, including total suspended solids (TSSs), pH, turbidity, color, and electrical conductivity (EC), using collected urban runoff samples. In addition, mechanical properties (compressive, tensile, and flexural strength) and hydraulic properties (porosity and infiltration rate) were assessed to ensure structural and functional suitability. The results demonstrate that pervious concrete pavements incorporating industrial waste materials exhibit effective pollutant removal while maintaining acceptable mechanical performance in accordance with ASTM standards. Among the investigated pervious concrete types, pavements containing 10% recycled concrete aggregate and 10% ceramic waste showed superior reductions in TSS, turbidity, and color compared to other waste-based and normal pervious concrete mixes. This study demonstrated significant reductions in particulate pollutants (TSS, turbidity, and color), while increases in pH and electrical conductivity highlighted early-age ion leaching from the concrete matrix, underscoring both the treatment benefits and the need for long-term monitoring under realistic deployment conditions. Overall, the findings highlight the potential of industrial waste-based pervious concrete pavements as an environmentally sustainable and effective solution for urban stormwater management.Publication Embargo Infill Masonry Strut Models in Reinforced Concrete Frames: Multilevel Reliability Analyses for Predicting In-Plane Responses(John Wiley and Sons Inc, 2026-03-10) Raheem, S; Thamboo, J; Mallikarachi, C; Wijesundara, K; Dias, PThe moment-resisting reinforced concrete (RC) frame infilled with masonry walls is a common form of construction for low- to medium-rise buildings. The importance of considering the infill masonry walls (IMW) in seismic analysis is accentuated due to the interaction between infills and the surrounding frame. Several analytical IMW models have been proposed to model IMW as equivalent diagonal struts, and the appropriateness of those models has been justified through experimental and numerical calibrations. However, the reliability of those analytical models is not well substantiated. Therefore, the reliabilities of five different analytical models have been evaluated herein using the First-Order Reliability Method (FORM). The stochastic uncertainties involved in predicting the in-plane capacities of IMW-RC frames have been incorporated in the reliability analyses. Subsequently, reliabilities of IMW models have been ascertained using experimental data sets compiled at two different scales, namely (1) single story–single bay and (2) multistory IMW-RC frames. 120 experimental data sets of single story–single bay IMW-RC frames tested under in-plane loading and three multistory IMW-RC frames tested on shake-tables were used to assess the reliabilities of IMW models. The results showed that the IMW models considered have predicted the in-plane behavior of IMW-RC frames (single or multistory) to certain levels of accuracy. The predicted reliability indices (β values) of the models vary between 1.03 and 4.13. The reliabilities differ when different aspects of the predictions are being considered, such as peak or ultimate load and drift capacities of single story–single bay frames or base shear and story drift of multistory frames. Therefore, depending on the requirement (strength- or displacement-based design), the IMW models should be selected appropriately to carry out the seismic analyses of IMW-RC buildings.Publication Open Access Status Quo Bias and EV Adoption: A Prospect Theory Perspective from a Developing Country Context(Multidisciplinary Digital Publishing Institute (MDPI), 2026-04-01) Theekshana, D; Gamage, K. A.A; Herath, R; Kavirathna, C.A; Jayasinghe, S; Weerakkody W.A.SElectric vehicles (EVs) are promoted to decarbonise road transport, yet uptake remains slow in many emerging markets. This study examines consumer resistance to EV adoption in Sri Lanka by modelling status quo bias (SQB) using a Prospect Theory lens. An online survey of urban vehicle owners and near-term buyers yielded 157 responses; after screening and removing influential outliers, 151 cases were analysed using partial least squares structural equation modelling (PLS-SEM). The model tests five Prospect Theory-aligned antecedents, namely, loss aversion, reference dependence, risk perception, framing effects, and uncertainty aversion, and evaluates environmental concern as a moderator. Results indicate that loss aversion has a significant positive effect on SQB (β = 0.216, p = 0.005) and uncertainty aversion is the strongest predictor (β = 0.453, p < 0.001), while reference dependence, risk perception, and framing effects show positive but statistically non-significant direct effects. Moderation tests show that environmental concern significantly moderates the effects of reference dependence (β = 0.181, p = 0.039) and framing effects (β = 0.179, p = 0.037) on SQB, but does not significantly moderate the loss aversion, risk perception, or uncertainty aversion paths. Overall, perceived losses and—especially—ambiguity surrounding EV ownership appear to sustain reliance on internal combustion vehicles in this developing-country context, underscoring the need for interventions that reduce uncertainty (credible infrastructure signals, stable policy, serviPublication Embargo E-commerce success redefined: integrating information systems and customer empowerment for e-customer engagement(Emerald Publishing, 2026-03-17) Boyagoda, G; Thalagala, S.M; Pathirana, S.L; Jeewantha, S; Wisenthige, KPurpose – This study aims to explore the impact of system quality, information quality, service quality and customer empowerment on customer satisfaction and e-commerce success in Sri Lanka, focusing on Millennials and Generation Z. By integrating the DeLone and McLean Information Systems Success (D&M ISS) model with customer empowerment theory, the research seeks to provide insights into the key drivers of e-customer engagement in e-commerce. Design/methodology/approach – A structured questionnaire was used to collect data from 413 respondents employing the purposive sampling technique. The data collection instrument comprised 32 questions related to system quality, information quality, service quality, customer empowerment and customer satisfaction, as well as demographic questions. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Findings – The results revealed that the system quality, information quality and service quality significantly influence customer satisfaction and intention to use the system in the context of e-commerce, which leads to higher customer engagement. Furthermore, the findings substantiate the crucial role that customer empowerment plays in terms of increasing customer satisfaction. Research limitations/implications – This study focuses on Millennials and Generation Z e-customers in Sri Lanka. It provides insights into this demographic, but does not capture the diverse cultural and technological landscape of the entire country. The study examines Information System (IS) dimensions and customer empowerment, excluding other significant variables like overall customer engagement. Self-reported data may introduce biases, and future research with larger sample sizes and different methods could improve the validity. Focusing on four selected online shopping platforms may limit the applicability as the e-commerce landscape is continuously evolving. Practical implications – The findings offer guidance to e-commerce businesses and policymakers to enhance their digital services and customer satisfaction. Businesses can improve their system quality with intuitive designs, offering accurate information to boost engagement and deliver excellent service quality. Initiatives such as interactive tools, loyalty programs and tailored support can empower customers, fostering a stronger impact. Policymakers can support e-commerce growth by improving regulations and providing training programs. These measures contribute to a more efficient and satisfying online shopping experience, driving long-term customer loyalty and business growth. Social implications – The research emphasises the role of customer empowerment in fostering customer engagement, contributing to the growth of the digital economy and enhancing online shopping experiences. Originality/value – This research enhances the academic understanding of e-commerce success by strengthening the DeLone and McLean Information Systems Success model by adding the concept of customer empowerment. This unique improvement is applied in the context of Sri Lanka, an emerging market with its own socio-economic characteristics. This addition provides new insights into key factors affecting e-customer engagement in the e-commerce sector.Publication Embargo Focus on Middle East and Central Asia: rationale of IMF assistance seeking(Springer Science and Business Media Deutschland GmbH, 2026-03) Wisenthige, K; Pathiranage, H. S.K; Jayathilaka, RThis study delves into the rationale behind the tendency of nations in the Middle East and Central Asia (MECA) to seek aid from the IMF. The IMF supports global financial stability, aiming to foster economic growth and prosperity across its member countries by promoting policies that encourage monetary cooperation and financial resilience. The study employs a conditional fixed-effects logit model, the analysis spans 22 years of data from twenty-five MECA countries to identify the factors driving these nations to seek IMF assistance. It focuses on six determinants: Current Account Balance (CAB), Inflation (INF), Corruption (CORR), General Government Net Lending and Borrowing (GGNLB), General Government Gross Debt (GGGD), and Gross Domestic Product Growth (GDPG). The fixed-effects logit shows that slower GDP growth raises the odds of an IMF programme, while short-run changes in corruption control and public debt ratios are not significant once country and year effects are absorbed. Inflation is weakly positive; the current account balance is still insignificant. A post-GFC and an income-group robustness check confirm the pattern. Furthermore, the study identifies Lebanon, a lower-middle-income country, as a leading example of seeking IMF assistance during the study period. Overall, this research highlights the importance of policymakers understanding the dynamics and rankings within the MECA region to effectively address economic challenges, provide financial support, and foster a more sustainable economic structure.