Faculty of Applied Science

A Review of Climate Change Impacts, Adaptation, and Mitigation in South Asia.

2026-08-13T03:57:15Z

A Review of Climate Change Impacts, Adaptation, and Mitigation in South Asia. Vijitharan, S. Climate change is a critical global issue, challenging and threatening various sectors in different ways. South Asia is one of the front-line regions to the impacts of climate change. According to the World Bank estimates, in 2021, around 1.9 billion people were in South Asia, including Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. Therefore, this review aims to assess the impacts of climate change and the existing mitigation and adaptation measures with effectiveness across the South Asian region. We reviewed published reports, journal articles, policy documents, and other grey literature for this study. The findings of this study revealed that total greenhouse gas emissions in South Asia increased from 2.11 TgCO2 in 2000 to 4.16 TgCO2 equivalent in 2019, with an annual rate of change of 5.11%. In total greenhouse gas emissions in 2019, approximately 70% was captured by carbon emissions from 51% in 2000. Among these eight nations, India was the leading greenhouse gas emitter, followed by Pakistan and Bangladesh. South Asia is highly vulnerable to cyclones, floods, erosion, sea level rise, and other natural disasters. Agricultural production is a crucial source of income. Food insecurity was growing due to decreased agricultural yield due to global warming. Not only the agriculture sector, it severely affects other sectors such as health, coastal and marine, energy, water resources, forests, and other ecosystems. The economic cost associated with climate change on a long-term basis is showing an increase by the end of this century. A higher percentage of financial losses can be expected in India. The impacts of climate change can further aggravate water insecurity, the spread of diseases, and biodiversity loss. India, Bangladesh, and the Maldives’ average annual Gross Domestic Product (GDP) growth (%) was nearly equal. However, the CO2 emissions of Bangladesh, Pakistan, and Maldives were 30, 12, and 1,516 times less than India’s, respectively. Noticeably, we found that climate finance and CO2 emissions were strongly and positively correlated, r(6) = .92, p < .05. Similarly, a positive correlation was observed between the average loss due to climate hazards and climate finance, r(6) = .96, p < .01. Therefore, South Asia is witnessing severe effects of climate change, hurting several economic sectors and creating serious obstacles to the area's sustainable development. To lessen these effects and increase resilience to adapt to the changing climate, prompt action is needed in the form of low-carbon development plans, climate-smart agriculture, climate-resilient strategies, Nature-based solutions, sustainable forest and ecosystem management, and strict policies and governance.

Blue Carbon Potential of Mirissanduwa and Kadolgasnelella Conservation Mangrove Forest, Negombo Estuary, Sri Lanka

2026-08-10T03:32:12Z

Blue Carbon Potential of Mirissanduwa and Kadolgasnelella Conservation Mangrove Forest, Negombo Estuary, Sri Lanka Fernando, W.T.S.; Vijitharan, S.; Chathurani, S.H.U.; Jayasundara, J.M.N.M. Mangroves are unique ecosystems thriving in harsh tropical and warm temperate conditions. These ecosystems are crucial for fighting climate change due to their ability to capture and store "blue carbon". The significant carbon stored in mangroves underscores their immense worth as a natural solution for climate change mitigation. Despite mangroves being a recognized source of climate change mitigation, there are limited studies on their role in the Negombo Estuary. The research intends to provide data supporting the protection, restoration, and sustainable management of these vital habitats to directly reduce atmospheric CO2 and enhance climate resilience. Sri Lanka's coastlines host 21 true mangrove species, with significant patches in the Negombo Estuary. The study investigated blue carbon reserves and environmental conditions. Ten 5 m x 5 m plots were randomly sampled to analyse blue carbon. Aboveground biomass (AGB), Belowground biomass (BGB) and Carbon stocks of mangrove biomass were estimated using Diameter at Breast Height (DBH) measurements and allometric equations. A total number of 10 soil samples were randomly collected from each plot to a depth of 30 cm, each using a soil corer. Soil samples were collected to determine pH, salinity, and Total Organic Carbon (TOC). TOC was measured using Loss on Ignition (LOI) method. The total blue carbon was calculated by adding aboveground carbon, belowground carbon and TOC. The study revealed that Rhizophora mucronata was the dominant species. Calculated total aboveground, belowground, TOC and blue carbon stocks were 776.23, 318.71, 438.40 and 1533.34 Mg C ha-1 respectively. Average soil pH was 7.62 ± 0.19 and salinity was 2.90 ± 0.66%. This research enhances our understanding of blue carbon storage in mangroves, underscoring their role in climate change mitigation. Further studies on blue carbon storage and promoting mangrove-based eco tourism are recommended for sustained conservation and economic developmentment.

Revan topological indices of supramolecular Fushine acid useful in medical applications

2026-07-31T07:24:47Z

Revan topological indices of supramolecular Fushine acid useful in medical applications Gunawardhana, D.C.; Sino, A. M. F. S.; Moulis, K.; Perera, K. K. K. R.; Lanel, G. J. Chemical graph theory plays a pivotal role in mathematical chemistry by representing chemical structures as graphs, with vertices denoting atoms and edges denoting chemical bonds. Topological indices, numerical invariants derived from such graphs, have been widely employed in quantitative structure property relationship (𝑄𝑆𝑃𝑅) and quantitative structure activity relationship (𝑄𝑆𝐴𝑅) studies. These indices correlate molecular structure with physicochemical and biological properties and have become crucial tools in drug design. Supramolecular chemistry, which studies entities formed bymolecular self-assembly through non-covalent interactions, offers an exciting avenue for designing complex molecular architectures. In this work, we investigate the supramolecular structure of Fuchsine (C₂₀H₁₉N₃HCl), a magenta dye of significant microbiological and histological importance. We construct a supramolecular sheet, denoted [𝑚, 𝑛], comprising 𝑚 × 𝑛 units of Fuchsine molecules. The corresponding chemical graph is simple, connected, and finite, consisting of 38𝑚𝑛 + 𝑚 + 𝑛 vertices and 42𝑚𝑛 edges, which are further classified by the Revan degrees of their end vertices. We derive closed-form expressions for several Revan degree-based topological indices of the supramolecular Fuchsine sheet, including the first and second Revan indices(𝑅1 and 𝑅2), Atomic Bond Connectivity Revan index(ABCR), Geometric-Arithmetic Revan index(𝐺𝐴𝑅), the first and second hyper Revan indices(𝐻𝑅1 and 𝐻𝑅2), the first and second modified Revan indices(𝑚𝑅1 and 𝑚𝑅2) , forgotten Revan index(𝐹𝑅). A detailed numerical and graphical analysis demonstrates that all these indices increase monotonically with the parameters m and n, reflecting the scaling behaviour of the supramolecular structure. Among the indices studied, the first hyper Reven index exhibits the highest values, whereas the first modified Revan index yields the lowest. Our findings provide a comprehensive mathematical characterization of the supramolecular Fuchsine graph, offering valuable insights for modelling and predicting the properties of complex chemical systems using topological descriptors.

Rehan-lanel indices of anti-tuberculosis drugs

2026-07-31T07:12:00Z

Rehan-lanel indices of anti-tuberculosis drugs Gunawardhana, D. C.; Sino, A. M. F. S.; Moulis, K.; Perera, K. K. K. R.; Lanel, G. J. Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health threat and continues to demand new, effective therapeutic agents. Chemical graph theory offers a powerful approach to studying molecular structures and predicting their physicochemical properties without the need for extensive laboratory experiments. In chemical graph theory, molecules are represented as graphs where atoms are vertices and covalent bonds are edges, allowing computation of numerical descriptors called topological indices that capture the structural and connectivity features of molecules. The objective of this study is to identify the selected Rehan–Lanel(RL) indices that are highly correlated with the physicochemical properties of anti-tuberculosis drugs and to use these indices to build regression models capable of predicting properties such as boiling point, flash point, molar refractivity, molar volume, and polarizability for anti-tuberculosis drugs, namely, amikacin, bedaquiline, clofazimine, delamanid, ethambutol, ethionamide, imipenem-cilastatin, isoniazid, levofloxacin, linezolid, moxifloxacin, and 𝑝-aminosalicylic acid. Chemical graphs of these anti-tuberculosis drugs were constructed, representing each atom as a vertex and each bond as an edge. The first, second, third, and fourth RL indices and corresponding Revan versions of these RL indices were calculated for each drug. Six physicochemical properties were compiled for the same set of compounds. Statistical analyses were performed to investigate the relationships between each topological index and each physicochemical property. The results revealed that different indices exhibited strong and highly significant correlations with specific properties. Certain Rehan–Lanel indices showed the highest correlations with molar refraction, molar volume, and polarizability, while specific Rehan– Lanel Revan indices correlated best with boiling point and flash point. This study demonstrates that chemical graph theory and topological indices provide an efficient, low- cost approach to predict physicochemical properties of anti-tuberculosis drugs, supporting early-stage drug screening and design. Future research may focus on integrating these indices or developing hybrid descriptors to simultaneously predict multiple properties, further enhancing their application in quantitative structure–property relationship studies and drug discovery.