Satellite Remote Sensing of Atmospheric SO_2: Volcanic Eruptions and Anthropogenic Emissions

In this article, we present satellite data analysis of atmospheric Sulfur Dioxide (SO_2) from volcanic eruptions and anthropogenic activities. Data from Global Ozone Monitoring Experiment (GOME) on board ERS-2 for the years 1996 to 2002 is analyzed using a DOAS based algorithm with the aim of retrieving SO_2 Slant Column Densities (SCDs). Difficulties in the retrieval of SO_2 SCDs due to instrumental effects are investigated in detail and significantly improved. The retrieved SCDs can be used to identify and monitor several volcanic eruptions. A brief introduction of different volcanic eruptions around the globe is presented Also informations about the anthropogenic SO_2 emissions can be easily achieved from the retrieved data set. A time series of anthropogenic SO_2 emissions over Eastern Europe is presented in this study. The time series showed high SO_2 SCDs over Eastern Europe during the winter months. The results demonstrate a high sensitivity of GOME instrument towards SO_2 emissions

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Inventory and GLOF Susceptibility of Glacial Lakes in Hunza River Basin, Western Karakorum

Northern latitudes of Pakistan are warming at faster rate as compared to the rest of the country. It has induced irregular and sudden glacier fluctuations leading to the progression of glacial lakes, and thus enhancing the risk of Glacier Lake Outbursts Floods (GLOF) in the mountain systems of Pakistan. Lack of up-to-date inventory, classification, and susceptibility profiles of glacier lakes and newly formed GLOFs, are few factors which pose huge hindrance towards disaster preparedness and risk reduction strategies in Pakistan. This study aims to bridge the existing gap in data and knowledge by exploiting satellite observations, and efforts are made to compile and update glacier lake inventories. GLOF susceptibility assessment is evaluated by using Analytical Hierarchy Process (AHP), a multicriteria structured technique based on three susceptibility contributing factors: Geographic, topographic, and climatic. A total of 294 glacial lakes are delineated with a total area of 7.85 ± 0.31 km2 for the year 2018. Analysis has identified six glacier lakes as potential GLOF and met the pre-established criteria of damaging GLOFs. The historical background of earlier GLOF events is utilized to validate the anticipated approach and found this method appropriate for first order detection and prioritization of potential GLOFs in Northern Pakistan

Monitoring of Ambient Air Quality Patterns and Assessment of Air Pollutants’ Correlation and Effects on Ambient Air Quality of Lahore, Pakistan

Industrialization, explosive population growth, anthropogenic activities, and vehicular exhaust deteriorate ambient air quality across the world. The current study aims at assessing the impacts on ambient air quality patterns and their co-relations in one of the world’s most polluted cities, i.e., Lahore, Pakistan, during a strict, moderate, and post-COVID-19 period of 28 months (March 2020–June 2022). The purpose of this study is to monitor and analyze the relationship between criteria air pollutants (SO2, particulate matter (PM 10 and 2.5), CO, O3, and NO2) through a Haz-Scanner 6000 and mobile van (ambient air quality monitoring station) over nine towns in Lahore. The results showed significantly lower concentrations of pollutants during strict lockdown which increased during the moderate and post-COVID-19 lockdown periods. The post-COVID-19 period illustrates a significant increase in the concentrations of SO2, PM10, PM2.5, CO, O3, and NO2, in a range of 100%, 270%, 500%, 300%, 70%, and 115%, respectively. Major peaks (pollution concentration) for PM10, PM2.5, NO2, and SO2 were found during the winter season. Multi-linear regression models show a significant correlation between PM with NO2 and SO2. The ratio of increase in the PM concentration with the increasing NO2 concentration is nearly 2.5 times higher than SO2. A significant positive correlation between a mobile van and Haz-Scanner was observed for CO and NO2 data as well as ground-based observation and satellite data of SO2, NO2, and CO. During the strict COVID-19 lockdowns, the reduction in the vehicular and industrial exhaust significantly improved the air quality of nine towns in Lahore. This research sets the ground for further research on the quantification of total emissions and the impacts of vehicular/industrial emissions on human health

Table_1_Solving the mysteries of Lahore smog: the fifth season in the country.docx

South Asian smog is an annually recurring air pollution event that is characterized by high concentrations of air pollutants, low visibility, and severe socio-economic disruptions. It is most frequently observed across the north-western parts of the Indo-Gangetic Plains (IGP). Since 2016, it has become so frequent and pervasive that they are colloquially referred to as “the fifth season” in the region. During this season populations residing in this area including cities such as Lahore, Amritsar, Faisalabad, Multan, Delhi etc. are exposed to hazardous levels of air pollution. This study attempts to understand the reasons for the recent increase in the intensity and frequency of intense air pollution episodes by utilizing ground-based and satellite observations. Time-series analysis, seasonal and annual variations in PM2.5 and AOD were carried out. Satellite data of UVAAI, CO, and fire count were used to determine the fire incidences and aerosol characterization. The results indicate that during the last decade, there has been an increase in air pollution sources while crop residue burning, and motor vehicles have greatly contributed to the increased frequency and intensity of such events. The meteorological and topographical data analysis revealed that the IGP provides ample cloud-condensation nuclei and optimum conditions for the accumulations of pollutants, especially in the post-monsoon and winter periods. The Mann-Kendall test was performed to confirm the annual and seasonal trends of PM2.5. The major cities of South Asia such as Lahore, Delhi, Kathmandu, and Dhaka have recently shown a decreasing trend with respect to annual AOD. However, an increase has been observed for the period of post-monsoon especially for cities of Lahore and Delhi. To distinguish potential sources of air pollutants during extreme smog episodes in the region, Analytical Hierarchy Process (AHP) was conducted to estimate the most contributing factors to the annual smog episodes. According to the data, the transboundary pollution resulting from open-field agriculture fires has been assigned moderate importance over vehicular emissions. A HYSPLIT trajectory model coupled with ground observations and satellite data shows that the agricultural fires do have a profound impact on the air quality of the region. It highlights the importance of transboundary pollution and cooperation among cities, regions, and countries across the shared airshed of the Indo-Gangetic Plains.</p

A computationally efficient symmetric diagonally dominant matrix projection-based Gaussian process approach

Although kernel approximation methods have been widely applied to mitigate the O(n3) cost of the n×n kernel matrix inverse in Gaussian process methods, they still face computational challenges. The ‘residual’ matrix between the covariance matrix and the approximating component is often discarded as it prevents the computational cost reduction. In this paper, we propose a computationally efficient Gaussian process approach that achieves better computational efficiency, O(mn2), compared with standard Gaussian process methods, when using m≪n data. The proposed approach incorporates the ‘residual’ matrix in its symmetric diagonally dominant form which can be further approximated by the Neumann series. We have validated and compared the approach with full Gaussian process approaches and kernel approximation based Gaussian process variants, both on synthetic and real air quality data