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This study presents the first attempt in Sri Lanka to generate a forest fire risk map covering the entire country using a GIS-based forest fire index (FFI) model. The model utilized seven parameters: land use, temperature, slope, proximity to roads and settlements, elevation, and aspect. All these parameters were derived using GIS techniques with ArcGIS10.4 and QGIS3.16. Data from Remote Sensing sources, particularly the MODIS hotspot real-world dataset, were employed to gather fire count information for the year 2020. Validation was conducted through the merging hotspot technique and kernel density estimation (KDE). The research findings highlight the districts in the Central and Uva provinces, such as NuwaraEliya (10.3 km2), Kandy (2.74 km2), and Badulla (10.41 km2), as having a “very low risk'' of forest fire potential. Conversely, districts like Hambanthota (0.1 km2), Kaluthara (0.04 km2), and Kurunegala (0.2 km2) exhibit a “very high risk'' of forest fire potential, although it is negligible compared country's total area. Overall, the study suggests that Sri Lanka is not currently facing a significant threat of forest fires and is a “medium risk'' of forest fires as 49.49% of land falls under this category. These results are of immense value to relevant authorities, including the Ministry of Wildlife and Forest Resources Conservation, in formulating effective strategies to manage and mitigate forest fire risks in the country.

The wearing of respirators has significantly increased over the last years mainly due to the COVID-19 pandemic. The prolonged wearing of respirators may have impacted the Heart Rate Variability (HRV) of the consumer. The scientific community has been attempting to understand the possible influential factors behind it. Unfavorable environmental factors may play a significant role in influencing the HRV for prolonged wearing of the respirators, mainly due to air pollution, and high concentrations of toxic metals and organochlorine compounds in the blood. Hence, this study aims to investigate the influence of unfavorable environmental conditions on the HRV parameters for prolonged wearing of N95 respirators. The study cohort was selected from the young volunteers living in the Aral Sea region, which is infamous for unfavorable environmental conditions due to dust storms with toxic particles, soil salinity, and high usage of pesticides. The study cohort consisted of 1110 male volunteers aged 19–22 and divided into two groups, inhabitants from unfavorable environment (North group) and inhabitants from unaffected environmental conditions (South group). HRV parameters of RMSSD, SDNN, pNN50, HF, LF/HF, SI, SBP, DBP, and SpO2 were measured and statistically compared in two stages, without wearing N95 respirators and while wearing an N95 mask for a 30–40 min period. Our analysis showed a significant increase in RMSSD, SDNN, pNN50 %, and HF parameters while wearing an N95 mask for a 30–40 min period in both groups. SI and LF/HF ratio shows a significant increase while wearing N95 in the «North » group and SI and LF/HF ratio decreased in the «South » group. The prevalence of distribution of subjects having SI more than 150 conv. units while wearing N95 marks in the «North » group were significantly higher compared to the «South » group. Autonomic tone reactivity to the N95 respirators was found in the «North » group in the form of an increase in sympathetic activity. We can conclude that the features of autonomic tone reactivity to wearing N95 respirators were found in the subjects from the environmentally unfavorable regions in the form of measuring the autonomic nervous system imbalance in favor of the increase in SNS activity. This observation is possibly related to the effects of organochlorine pesticides and heavy metals on the human nervous system in the participants living in unfavorable regions of the Aral ecological disaster.

Access to clean water is one of the most basic human needs for health and well-being and it is accepted as the 6th goal of the United Nations’ sustainable development goals. Emerging Contaminants from pharmaceutical compounds are one of the main pollutants of water bodies all over the world. Efficient and sustainable treatment of pharmaceutical contaminants is a challenging issue across the globe as these contaminants have complex chemical compositions that are poisonous to living beings. In addition, most of the treatment practices are ineffective or cost prohibitive. Hence, the effective removal of pharmaceutical contaminants from water bodies is important in enhancing access to safe water for people across the world. This review discusses the recent development of innovative applications of nanotechnology-based adsorption techniques currently practiced in the water treatment process, with the objective of reviewing different variants of nanoadsorbents utilized for removing pharmaceutical contaminants from water bodies. Nonadsorbents such as Carbon nanotubes (CNTs), with their unique features, were found to have comparably higher potential to efficiently remove pharmaceutical wastes from water bodies. This review audit can be implemented in associated policy decisions and practices in the water treatment industry to shift contemporary emphasis from inefficient traditional methods to focus on developing cost-effective CNT treatments for pharmaceutical pollution. Implementing such treatment interventions as policies will help to reach the SDGs for the betterment of the world.

Rainfall Intensity Duration Frequency (IDF) curves can be identified as a major role in the planning of urban drainage infrastructure. Sri Lanka, which is an island surrounded by the Indian Ocean, is frequently exposed to various climatic alterations. Sri Lanka has specific region-wise IDF relationships for the entire country, however, these IDF curves were developed more than 30 years ago. Many in-situ rainfall observations in Sri Lanka have insufficient record lengths and the absence of finer time scale records (e.g. 15 min, hourly) leading to unreliable IDF curve developments. Given this importance, the present paper demonstrates the application of Satellite-based Precipitation Product (SbPP) daily rainfall in developing IDF curves for Sri Lanka. Rainfall satellite estimates derived from Integrated Multi-satellite Retrievals for GPM (IMERG), Tropical Rainfall Measuring Mission (TRMM-3B42), and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) have been used to evaluate the ability of application of remote sensing data to develop IDF curves for Sri Lanka against rain gauge (RG) data. Our study breaks new ground by generating 50 IDF curves tailored to specific locations covering the whole county Sri Lanka, using daily rainfall data from RGs and three SbPPs during the period between 1990 and 2019. This marks a significant departure from the conventional approach, offering a more granular understanding of rainfall patterns in the country. By providing IDF curves for individual locations, our research presents a novel contribution to Sri Lanka's IDF history. At first, to evaluate the accuracy of SbPPs, statistical analysis was conducted using continuous and categorical evaluation indices. Second, IDF curves were developed and compared with the presently available IDF curves. Results showcased that IMERG outperformed all SbPPs, while PERSIANN-CDR showed dire performances. The IMERG and TRMM-3B42 products tend to overestimate light precipitation regions in high elevations and overestimate heavy rainfall in low elevations compared to rain gauge data. Rainfall intensities derived by rain gauge data depicted relative changes within ±30% for shorter durations and ±20% for longer durations while SbPPs showed beyond ±30% difference concerning the previously developed IDFs. It was apparent that these products have significant inaccuracies which cannot be neglected when utilizing them in developing IDF curves. This study will be beneficial in solving design problems associated with urban runoff control and disposal where knowing the rainfall intensities of different return periods with different durations is vital.

This study investigated the potential use of sewage sludge-based activated carbon in the removal of copper (Cu) and cadmium (Cd) ions from aqueous solutions. The activated carbon (AC) was prepared by chemical activation using potassium hydroxide KOH and heating in a tube furnace at 600 °C for 2 h. The produced activated carbon was further subject to a sulfurization process to enhance its removal efficiency. The study used Box-Behnken Design (BBD) in response surface methodology (RSM) to optimize several parameters, including initial metal concentration, activated carbon dose, pH, and contact time. Results showed that the sulfurization process introduced sulfur functional groups (SO) to the surface of the activated carbon and decreased its specific area from 190 to 173 m2/g. The quadratic model was suggested as the best model to describe the effect of the adsorption parameters on the removal percentage with high R2 values (≥0.9) and p-value less than 0.05. Second-order polynomial equations, analysis of variance (ANOVA), and three-dimensional surface plots were developed to assess the interaction between the parameters and the optimal conditions to remove copper and cadmium ions. The optimum removal parameters for copper ions were 300 min, 100 ppm initial concentration, 20 g/L activated carbon dose, and pH 6, with a removal efficiency of 83.9%. Cadmium removal of 87.5% was achieved at 11 ppm, 300 minutes contact time, pH 6, and 2.5 g/L adsorbent dose. The activated carbon capacity in removing copper and cadmium was 16 mg/g and 17.6 mg/g respectively. The sulfurization process increased the removal percentage for copper and cadmium ions by 14.5 and 18.7% respectively. Advanced analytical techniques such as FITR, SEM-EDX, BET surface area, and elemental analysis were used to characterize the materials.

The conventional disposal practices of rice stalks (RS) such as burning in situ or incorporating in the soil, contribute to climate change and endanger the long-term soil fertility. This study investigated the production of activated carbon (AC) using rice stalks as a sustainable recycling solution. The rice stalks (RS) were carbonized in a tube furnace at 500 °C and heating rate of 10 °C/min for 2 h. The rice stalks-based activated carbon (RSA) properties were analyzed based on Brunauer-Emmett-Teller (BET) technique to measure the surface area and transform infrared spectroscopy (FTIR) measurements to identify the surface functional groups. RSA was also characterized using X-ray diffraction (XRD) and scanning electron microscopy with energy dispersive X-Ray spectroscopy (SEM-EDX). Batch experiments were conducted to examine the efficiency of RSA in removing phenol, with varying operation parameters comprising pH (2–9), initial phenol concentration (IPC) (50–200 mg/L), reaction time (5–300 min), and RSA dose (0.2–2 g/100 ml). The surface area (SBET) of RSA was 488.26 m2/g with a total micropore volume of 0.165 cm³/g, and a pore diameter of 6.99 nm. The highest phenol uptake of RSA was 80.37 mg/g. The kinetics of phenol adsorption was found to be accurately described by the pseudo-second-order reaction, while the Langmuir model provided a better match for the isotherm process than the Freundlich model. The thermodynamic study indicated that the adsorption process was exothermic and spontaneous. These results confirm that the adsorption process occurred due to physical forces, rather than involving chemical bonding, providing further insight into the underlying mechanisms.

Ill-planned irrigation systems and pesticide overuse during 1950-1960 severely impacted the soil system in the Aral Sea region. Organochlorine compounds including DDT (dichlorodiphenyltrichloromethylmethane), DEE (dichlorodiphenyldichloroethylene), DDD (dichlorodiphenyldichloromethane), HCCH (hexachlorane) and toxic metals are readily available in soil systems. Thus, long-term exposure to these toxic environmental conditions increases the health risk of the people. Hence, this study investigates environmental influence on the development of power motor qualities, physical endurance, and oxygen capacity in young people living in this region. The study cohort included 609 volunteers aged 18-25 in two different geographical regions, North and Nukus in Uzbekistan. All participants were assessed based on the one-mile walking test for strength motor qualities, dynamic and static power endurance, and maximum oxygen consumption (MOC) in addition to hematological indices. Data analysis revealed significantly lower values of all fitness test parameters and MOC in young men and only parameters of dynamic power endurance living in the North region. Both male and female participants of the North cohort had lower red blood cell (RBC) and hemoglobin (Hb) levels compared to the cohort from Nukus. A high prevalence (28% of males and 96% of females) and the nature of anemia (normocytic and normochromic) were found. This study has sufficiently characterized the change in muscular strength and physical endurance in youth in this region. The decrease of MOC and muscle strength and endurance in young men and women may have an influence from organochlorine pesticides on haemopoiesis and subsequent decreasing of oxygen capacity in the blood.

Oil-in-water emulsions are used in a variety of applications, but they are often unstable and can break down over time due to different mechanisms such as flocculation and coalescence, as well as gravitational separation, like creaming and sedimentation, which can occur either independently or concurrently. This study investigated the utilize of chitin nanocrystals (ChiNCs) as stabilizers for O/W emulsions which is derived from a green and renewable material. ChiNCs were produced by acid hydrolysis of chitin powder. The ChiNC's TEM results showed a needle-like morphology with a length of 200–800 nm and a width of 20–80 nm. The surface charge of ChiNCs is negative at pH > 7 and positive at pH