Moisture Transport Associated with Southwest Monsoon Rainfall Over Sri Lanka in Relatively Wet and Dry Rainfall Years

Atmospheric moisture transportation associated with the occurrence of relatively wet and dry southwest monsoon (SWM) years over Sri Lanka is still not fully understood. This study focused on investigating the role of moisture transport in contrast SWM years. We selected seven wet (SWMWet) and nine dry (SWMDry) years for 1985-2015 and found that the whole country experiences above-average (below average) rainfall in SWMWet (SWMDry) years. In SWMWet years, strengthening moisture-laden low-level jets (LLJ) from the Arabian Sea bring a large amount of moisture towards Sri Lanka. In contrast, the weakening of the LLJ from the Arabian Sea direction is observed in SWMDry years. As a consequence, the climatological mean of net moisture flux (4.35 ×105 kg s-1) over the study domain is increased (5.33×105 kg s-1) and decreased (3.98 ×105 kg s-1) in SWMWet and SWMDry years, respectively. With respect to long-term Vertically Integrate Moisture Flux Divergence (VIMFD, –3.28×10-5 kg m-2 s-1), negative anomalous VIMFD (–1.78×10-5 kg m-2 s-1 ) in SWMWet years and positive anomalous VIMFD (1.44×10-5 kg m-2 s-1 ) in SWMDry years are recorded, which ascribed above-average and below-average rainfall over the country. Furthermore, strong moisture convergence (divergence) center in the western/ southwestern part of Sri Lanka during the SWMWet (SWMDry) years explain why strong positive and negative SWM rainfall anomalies are concentrated in these two regions. Furthermore, results highlighted a strong relationship between net moisture flux availability and SWM rainfall (r= 0.63) that may explain the observed SWM rainfall variability over the country

Changes of Air Pollutants in Urban Cities during the COVID-19 Lockdown-Sri Lanka

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 analyzes 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

Machine Learning Techniques to Predict the Air Quality Using Meteorological Data in Two Urban Areas in Sri Lanka

The effect of bad air quality on human health is a well-known risk. Annual health costs have significantly been increased in many countries due to adverse air quality. Therefore, forecasting air quality-measuring parameters in highly impacted areas is essential to enhance the quality of life. Though this forecasting is usual in many countries, Sri Lanka is far behind the state-of-the-art. The country has increasingly reported adverse air quality levels with ongoing industrialization in urban areas. Therefore, this research study, for the first time, mainly focuses on forecasting the PM10 values of the air quality for the two urbanized areas of Sri Lanka, Battaramulla (an urban area in Colombo), and Kandy. Twelve air quality parameters were used with five models, including extreme gradient boosting (XGBoost), CatBoost, light gradient-boosting machine (LightBGM), long short-term memory (LSTM), and gated recurrent unit (GRU) to forecast the PM10 levels. Several performance indices, including the coefficient of determination (R2), root mean squared error (RMSE), mean absolute error (MAE), mean squared error (MSE), mean absolute relative error (MARE), and the Nash–Sutcliffe efficiency (NSE), were used to test the forecasting models. It was identified that the LightBGM algorithm performed better in forecasting PM10 in Kandy (R2 = 0.99, MSE = 0.02, MAE = 0.002, RMSE = 0.1225, MARE = 1.0, and NSE = 0.99) . In contrast, the LightBGM achieved a higher performance (R2 = 0.99, MSE = 0.002, MAE = 0.012, RMSE = 1.051, MARE = 0.00, and NSE = 0.99) for the forecasting PM10 for the Battaramulla region. As per the results, it can be concluded that there is a necessity to develop forecasting models for different land areas. Moreover, it was concluded that the PM10 in Kandy and Battaramulla increased slightly with existing seasonal changes

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Streamflow Variability in Mahaweli River Basin of Sri Lanka during 1990–2014 and Its Possible Mechanisms

This study investigates the variation of seasonal streamflow and streamflow extremes in five catchments of the Mahaweli River Basin (MRB) Sri Lanka from 1990 to 2014, and the relationship between streamflow and seasonal rainfall in each catchment is then examined. Furthermore, the influence of Indian Ocean Dipole (IOD) and El Nino and Southern Oscillation (ENSO) on the seasonal rainfall and streamflow in the upper (UMRB) and lower reaches (LMRB) of MRB are explored. It’s found that the rainfall amount in southwest monsoon (SWM) season contributes 29.7% out of annual total rainfall in the UMRB, while the LMRB records 41% of the total rainfall during the northeast monsoon (NEM) season. The maximum streamflow of upper (lower) Mahaweli catchments is observed in the SWM (NEM) season. Catchments in the UMRB (LMRB) recorded strong interannual variability of seasonal overall flow (Q50), Maximum 10-day, and 30-day flows during the SWM (NEM) season. It’s further revealed that the catchment streamflow in the UMRB is closely correlated with the SWM rainfall in the interannual time scale, while streamflow of catchments in the LMRB is closely associated with the NEM rainfall. The effects of ENSO and IOD on streamflow are consistent with their impacts on rainfall for all catchments in MRB, with strong seasonal dependent. These suggested that the sea surface temperature anomalies in the both Indian Ocean and tropical Pacific Ocean are important factors affecting the streamflow variability in the MRB, especially during the SWM season

Long-Term Seasonal Drought Trends in the China-Pakistan Economic Corridor

In recent years, drought events have influenced agriculture, water-dependent industries, and energy supply in many parts of the world. The China–Pakistan Economic Corridor (CPEC) is particularly susceptible to drought events due to large-scale monsoon circulation anomalies. Using the 0.5 × 0.5 resolution rainfall and potential evapotranspiration data set from the Climatic Research Unit (CRU), we assessed the changes in seasonal drought variation and effects of climate variables on drought over the CPEC for the period of 1980 to 2018 using the Standardized Precipitation Evapotranspiration Index (SPEI). Our results show a statistically significant negative trend of SPEI over the hyper-arid region for two monsoons (December–February and June–September) and intra-monsoonal seasons (March–May and October–November), suggesting that the hyper-arid region (southern and southwestern part of the CPEC) is experiencing more frequent drought. A high probability for the occurrence of winter (30–35%) and summer (20–25%) droughts are observed in hyper-arid regions and gradually decreases from south to north of the CPEC. Decreasing seasonal rainfall and increasing potential evapotranspiration with increasing temperature in hyper-arid and arid regions resulted in frequent drought events during the winter monsoon season (from December to February). The findings from this study provide a theoretical basis for the drought management of the CPEC and a framework for understanding changes in drought in this region from climate projections

Cognitive and psychiatric symptom trajectories 2–3 years after hospital admission for COVID-19: a longitudinal, prospective cohort study in the UK

Background: COVID-19 is known to be associated with increased risks of cognitive and psychiatric outcomes after the acute phase of disease. We aimed to assess whether these symptoms can emerge or persist more than 1 year after hospitalisation for COVID-19, to identify which early aspects of COVID-19 illness predict longer-term symptoms, and to establish how these symptoms relate to occupational functioning. Methods: The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study of adults (aged ≥18 years) who were hospitalised with a clinical diagnosis of COVID-19 at participating National Health Service hospitals across the UK. In the C-Fog study, a subset of PHOSP-COVID participants who consented to be recontacted for other research were invited to complete a computerised cognitive assessment and clinical scales between 2 years and 3 years after hospital admission. Participants completed eight cognitive tasks, covering eight cognitive domains, from the Cognitron battery, in addition to the 9-item Patient Health Questionnaire for depression, the Generalised Anxiety Disorder 7-item scale, the Functional Assessment of Chronic Illness Therapy Fatigue Scale, and the 20-item Cognitive Change Index (CCI-20) questionnaire to assess subjective cognitive decline. We evaluated how the absolute risks of symptoms evolved between follow-ups at 6 months, 12 months, and 2–3 years, and whether symptoms at 2–3 years were predicted by earlier aspects of COVID-19 illness. Participants completed an occupation change questionnaire to establish whether their occupation or working status had changed and, if so, why. We assessed which symptoms at 2–3 years were associated with occupation change. People with lived experience were involved in the study. Findings: 2469 PHOSP-COVID participants were invited to participate in the C-Fog study, and 475 participants (191 [40·2%] females and 284 [59·8%] males; mean age 58·26 [SD 11·13] years) who were discharged from one of 83 hospitals provided data at the 2–3-year follow-up. Participants had worse cognitive scores than would be expected on the basis of their sociodemographic characteristics across all cognitive domains tested (average score 0·71 SD below the mean [IQR 0·16–1·04]; p<0·0001). Most participants reported at least mild depression (263 [74·5%] of 353), anxiety (189 [53·5%] of 353), fatigue (220 [62·3%] of 353), or subjective cognitive decline (184 [52·1%] of 353), and more than a fifth reported severe depression (79 [22·4%] of 353), fatigue (87 [24·6%] of 353), or subjective cognitive decline (88 [24·9%] of 353). Depression, anxiety, and fatigue were worse at 2–3 years than at 6 months or 12 months, with evidence of both worsening of existing symptoms and emergence of new symptoms. Symptoms at 2–3 years were not predicted by the severity of acute COVID-19 illness, but were strongly predicted by the degree of recovery at 6 months (explaining 35·0–48·8% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); by a biocognitive profile linking acutely raised D-dimer relative to C-reactive protein with subjective cognitive deficits at 6 months (explaining 7·0–17·2% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); and by anxiety, depression, fatigue, and subjective cognitive deficit at 6 months. Objective cognitive deficits at 2–3 years were not predicted by any of the factors tested, except for cognitive deficits at 6 months, explaining 10·6% of their variance. 95 of 353 participants (26·9% [95% CI 22·6–31·8]) reported occupational change, with poor health being the most common reason for this change. Occupation change was strongly and specifically associated with objective cognitive deficits (odds ratio [OR] 1·51 [95% CI 1·04–2·22] for every SD decrease in overall cognitive score) and subjective cognitive decline (OR 1·54 [1·21–1·98] for every point increase in CCI-20). Interpretation: Psychiatric and cognitive symptoms appear to increase over the first 2–3 years post-hospitalisation due to both worsening of symptoms already present at 6 months and emergence of new symptoms. New symptoms occur mostly in people with other symptoms already present at 6 months. Early identification and management of symptoms might therefore be an effective strategy to prevent later onset of a complex syndrome. Occupation change is common and associated mainly with objective and subjective cognitive deficits. Interventions to promote cognitive recovery or to prevent cognitive decline are therefore needed to limit the functional and economic impacts of COVID-19. Funding: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Wolfson Foundation, MQ Mental Health Research, MRC-UK Research and Innovation, and National Institute for Health and Care Research.</p