Air quality in urban areas is deteriorating over time with the increased pollutant distribution levels mainly caused due to anthropogenic activities. In addition, these pollutant distribution levels may relate to changing meteorological conditions. However, the relationships were not researched in-depth in the context of Sri Lanka, a country with a significant impact on climate change. The main objective of this study was to provide a broader perspective on the seasonal variation of tiny particles in air (PM2.5 and PM10), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and sulfur dioxide (SO₂) in two urban cities (Colombo and Kandy) in Sri Lanka over 3 years period (20182021) and the possible relationships between air pollution and meteorological variables. Results show that all the aforementioned pollutants except O₃ consistently depict two peaks during the day, one in the morning (07:0009:00 local time) and the other in the evening (18:0020:00 local time). These peaks coincided with the traffic jams observed in both cities. The results further revealed that the concentration of all pollutants has significant seasonal variations. Compared to two monsoon seasons, the highest daily average PM2.5 (31.2μg/m³), PM10 (49.5μg/m³), NO₂ (18.9ppb), CO (717.5ppb), O₃ (18.5ppb), and SO₂ (9.4ppb) concentrations in Colombo are recorded during northeast monsoon (NEM) seasons while contrast pattern is observed in Kandy. In addition, it was found that wind speed with its direction is the most influencing factor for the pollutant concentration except for SO₂ and O₃ in two cities, and this is irrespective of the season. This studys findings contribute to understanding the seasonality of ambient air quality and the relationship between meteorological factors and air pollutants. These findings ultimately lead to designing and implementing season-specific control strategies to achieve air pollution reduction at a regional scale.

In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyses the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health.

COVID-19 is transmitted, at least in part, by airborne particles emitted by infected individuals. Wearing masks is one of the key actions that are required to prevent spreading COVID-19. To understand the variability in the performance, we evaluated the material performance of the whole mask, as manufactured, in terms of the penetration of particles, comfort and the quality factor of multiple copies of 29 different types. All masks were mounted to prevent leakage around the edges so the mask material and manufacture was tested, but the effects of the fit were not considered. The results of this study thus represent the upper bound of the performance of facemasks since leakage around the edges due to poor fit often overwhelms filtration through the mask material. The tests were performed at a steady flow rate of 30 L/min; mean values of the performance parameters were calculated for two different sizes; 0.12 µm and 0.3 µm. Of the masks tested, for 0.12 µm particles, N95 face filtering respirators consistently had the lowest peak penetration 1.7 ± 0.5%, while KN95 masks allowed 3.7 ± 2.6% penetration. In contrast, penetration through pleated procedure masks was 14.7 ± 16.9% due to one outlier - with that outlier removed, penetration decreased to 7.1 ± 4.3%; cloth masks allowed 26.4 ± 9.3% penetration. Tests on multiple copies of different masks demonstrated consistent performance of N95s, but considerably greater variability within the other classes of masks tested, leading to uncertainty in the degree of protection that they would provide.

The Aral Sea is an indispensable component of the socio-economic progress of Central Asia but has undergone substantial ecological transformations over the last few decades, primarily due to global warming and human activities. Among these changes, the basin area has decreased, and water levels have dropped. This paper focuses on a comprehensive analysis of the spatial variation of key climate parameters, such as temperature, precipitation, and potential evapotranspiration over the Aral Sea. Moreover, we examined the transformation of seasonal water areas in the Aral Sea during the growing and non-growing seasons between 2002 and 2017 and the influence of climate and human factors on these changes using Landsat satellite data. Our results indicate that the western section of the Aral Sea has experienced a reduction in water area by 2.41 km² and 1.83 km² during the warm (R² = 0.789) and cold (R² = 0.744) seasons, respectively, over the investigated period. The decrease in lake water volume during the warm season can be attributed to local climate variations, as a strong negative correlation exists between seasonal water storage change and temperature (potential evapotranspiration). The correlation analysis shows that the water change in the northern part of the Aral Sea during the growing season has a significant positive correlation with temperature (R = 0.52) and an insignificant negative correlation with precipitation (R = −0.22). On the contrary, in the west and east parts of the Aral Sea, there is a significant negative correlation with temperature (R = −0.71 and −0.62) and a high positive correlation with precipitation (R = 0.71 and 0.55) during the growing season.

Mask-wearing emerged as the key safety measure to prevent the spreading of COVID-19. In this study, we hypothesized a model to quantify the leakage flow rate through the face mask based on a parallel resistance model. The tests were performed in two ways: (I) mask material test, in which all masks were sealed to a flange to measure transmission through a full mask and prevent leakage around the edges, and (II) mannequin mask test, in which masks were fitted to a mannequin head tightly. For all masks, the pressure drop was measured at eight different flow rates between 5 and 85 LPM, and it was increased linearly with the flow rate (r2 > 0.98). The results of the study showed that the leakage flow rate was 10% of the total flow rate, even for the best-fitted N95 filtering facepiece respirators (FFRs) and KN95 masks. They showed higher resistance to the leaks. The procedure masks and cloth masks showed a leakage flow rate of 25% of the value of the total flow rate, quite a large proportion of the flow. They had lower resistance to leaks.

In recent years, rainfall extremes have increased significantly and have threatened the socio-economic development in Sri Lanka. This study investigates the rainfall extremes in the Mahaweli River Basin (MRB) of Sri Lanka with daily station datasets from 1985 to 2015. The extreme rainfall indices recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI) have been used in this study. Results showed a strong seasonal variation of rainfall extreme events over the MRB and a significant interdecadal change of extreme rainfall indices between 1985–1999 and 2000–2015 in the wet region of MRB, which is coherent with the decadal shift of southwest monsoon (SWM) rainfall from wet to dry situations since the year 2000. Based on the General Extreme Value distributions, the long-term mean of SWM rainfall in the wet region (814 mm) moved leftward for the 2000–2015 period (704 mm) and rightward for the 1985–2000 period, suggesting that SWM rainfall is decreased in the late period. The observed above-average (below-average) rainfall and associated rainfall extremes during the SWM can be ascribed to strengthening (weakening) moisture flux from the Arabian Sea direction and strong (weak) convergence over the study domain. The results further identified the negative correlation between Dipole Mode Index and SWM rainfall and associated rainfall extremes in the wet region, signifying that the negative Indian Ocean Dipole phase can enhance the SWM rainfall over the MRB. The negative correlation between Nino3.4 and SWM rain and extreme indices suggested that high probability of wet rainfall extremes in the La Nina phase. The findings of this study can be used to understand precipitation extremes in the context of climate change at the river basin scale and benefit policymakers in building local adaptation strategies in response to long-term climate change.