The quality of water served in the Orotta National Referral Hospital

Background: The principal risks to human health associated with the consumption of unsafe drinking water are microbiological. According to the WHO and UNICEF report 2.6 billion people do not have access to good quality of water. About 1.1 billion people globally do not have access. About 2 million people mostly of less than 5 years children also die as a result of diarrheal diseases related to consumption of water that is microbiologically contaminated. Objective: The objective of this study was to measure the quality of water served to the different sections of Orotta National Referral Hospital using WHO protocols. Methods: Water samples were collected from different sources in the National Referral Orotta Hospital compound according to the WHO guidelines and the multi-tube method or most probable number method was used for the microbiological count. Results: The findings from the study showed that some of the samples of water from National Referral Pediatric Hospital, and National Medical and Surgical Referral Hospital reservoirs did not meet some of the WHO guidelines for safe drinking water. Conclusion and recommendations: The water contamination emanated from the reservoirs of the Orotta Hospital, because the samples taken as a control from outside the Hospital compound were free of contamination. Water reservoirs should be washed on regular basis. Chlorination and other treatment modalities for the water in the reservoir should also be considered and applied. Water quality surveillance should be done several times in a year not only just once

Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China

Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China. Evaluation of long-term aerosol optical depth (AOD) data from models and reanalysis, can greatly promote understanding of spatiotemporal variations in air pollution in China. To do this, AOD (550 nm) values from 2000 to 2014 were obtained from the Coupled Model Inter-comparison Project (CIMP6), the second version of Modern-Era Retrospective analysis for Research, and Applications (MERRA-2), and the Moderate Resolution Imaging Spectroradiometer (MODIS; flying on the Terra satellite) combined Dark Target and Deep Blue (DTB) aerosol product. We used the Terra-MODIS DTB AOD (hereafter MODIS DTB AOD) as a standard to evaluate CMIP6 Ensemble AOD (hereafter CMIP6 AOD) and MERRA-2 reanalysis AOD (hereafter MERRA-2 AOD). Results show better correlations and smaller errors between MERRA-2 and MODIS DTB AOD, than between CMIP6 and MODIS DTB AOD, in most regions of China, at both annual and seasonal scales. However, significant under- and over-estimations in the MERRA-2 and CMIP6 AOD were also observed relative to MODIS DTB AOD. The long-term (2000–2014) MODIS DTB AOD distributions show the highest AOD over the North China Plain (0.71) followed by Central China (0.69), Yangtse River Delta (0.67), Sichuan Basin (0.64), and Pearl River Delta (0.54) regions. The lowest AOD values were recorded over the Tibetan Plateau (0.13 ± 0.01) followed by Qinghai (0.19 ± 0.03) and the Gobi Desert (0.21 ± 0.03). Large amounts of sand and dust particles emitted from natural sources (the Taklamakan and Gobi Deserts) may result in higher AOD in spring compared to summer, autumn, and winter. Trends were also calculated for 2000–2005, for 2006–2010 (when China introduced strict air pollution control policies during the 11th Five Year Plan or FYP), and for 2011–2014 (during the 12th FYP). An increasing trend in MODIS DTB AOD was observed throughout the country during 2000–2014. The uncontrolled industrialization, urbanization, and rapid economic development that mostly occurred from 2000 to 2005 probably contributed to the overall increase in AOD. Finally, China's air pollution control policies helped to reduce AOD in most regions of the country; this was more evident during the 12th FYP period (2011–2014) than during the 11th FYP period (2006–2010). Therefore this study strongly advises the authority to retain or extend these policies in the future for improving air quality

Spatiotemporal investigations of multi-sensor air pollution data over Bangladesh during COVID-19 lockdown

This study investigates spatio-temporal changes in air pollution (particulate as well as gases) during the COVID-19 lockdown period over major cities of Bangladesh. The study investigated the aerosol optical depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites, PM2.5 and PM10 from Copernicus Atmosphere Monitoring Service (CAMS), and NO2 and O3 from Tropomi-5P, from March to June 2019–2020. Additionally, aerosol sub-types from the Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) were used to explore the aerosol types. The strict lockdown (26 March–30 May 2020) led to a significant re-duction in AOD (up to 47%) in all major cities, while the partial-lockdown (June 2020) led to in-creased and decreased AOD over the study area. Significant reductions in PM2.5 (37–77%) and PM10 (33–70%) were also observed throughout the country during the strict lockdown- and par-tial-lockdown. The NO2 levels decreased by 3–25% in March 2020 in the cities of Rajshahi, Chat-togram, Sylhet, Khulna, Barisal, and Mymensingh, in April by 3–43% in Dhaka, Chattogram, Khulna, Barisal, Bhola and Mymensingh, and May by 12−42% in Rajshahi, Sylhet, Mymensingh, and Rangpur. During the partial-lockdown in June, NO2 decreased (9−35%) in Dhaka, Chatto-gram, Sylhet, Khulna, Barisal, and Rangpur compared to 2019. On the other hand, increases were observed in ozone (O3) levels, with an average increase of 3–12% throughout the country during the strict lockdown and only a slight reduction of 1–3% in O3 during the partial-lockdown. In terms of aerosol types, CALIPSO observed high levels of polluted dust followed by dust, smoke, polluted continental, and clean marine type aerosols over the country in 2019, but all types were decreased during the lockdown. The study concludes that the strict lockdown measures were able to significantly improve air quality conditions over Bangladesh due to the shutdown of industries, vehicles, and movement of people