Pub Date : 2020-08-01DOI: 10.22034/GJESM.2019.06.SI.01
T. Tran, L. T. Pham, Q. Ngô
Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019; this disease has been rapidly spreading worldwide. Iran was the first Middle East country to report a coronavirus death, it has been severely affected. Therefore, it is crucial to forecast the pandemic spread in Iran. This study aims to develop a prediction model for the daily total confirmed cases, total confirmed new cases, total deaths, total new deaths, growth rate in confirmed cases, and growth rate in deaths. The model utilizes SARS-CoV-2 daily data, which are mainly collected from the official website of the European Centre for Disease Prevention and Control from February 20 to May 04, 2020 and other appropriated references. Autoregressive integrated moving average (ARIMA) is employed to forecast the trend of the pandemic spread. The ARIMA model predicts that Iran can easily exhibit an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future. This study predicts that Iran can control the SARS-CoV-2 disease in the near future. The ARIMA model can rapidly aid in forecasting patients and rendering a better preparedness plan in Iran.
{"title":"Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran)","authors":"T. Tran, L. T. Pham, Q. Ngô","doi":"10.22034/GJESM.2019.06.SI.01","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.01","url":null,"abstract":"Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019; this disease has been rapidly spreading worldwide. Iran was the first Middle East country to report a coronavirus death, it has been severely affected. Therefore, it is crucial to forecast the pandemic spread in Iran. This study aims to develop a prediction model for the daily total confirmed cases, total confirmed new cases, total deaths, total new deaths, growth rate in confirmed cases, and growth rate in deaths. The model utilizes SARS-CoV-2 daily data, which are mainly collected from the official website of the European Centre for Disease Prevention and Control from February 20 to May 04, 2020 and other appropriated references. Autoregressive integrated moving average (ARIMA) is employed to forecast the trend of the pandemic spread. The ARIMA model predicts that Iran can easily exhibit an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future. This study predicts that Iran can control the SARS-CoV-2 disease in the near future. The ARIMA model can rapidly aid in forecasting patients and rendering a better preparedness plan in Iran.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43871207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.22034/GJESM.2019.06.SI.06
S. Tamang, P. Singh, B. Datta
Artificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs artificial neural network-based curve fitting techniques in prediction and forecasting of the Covid-19 number of rising cases and death cases in India, USA, France, and UK, considering the progressive trends of China and South Korea. In this paper, three cases are considered to analyze the outbreak of Covid-19 pandemic viz., (i) forecasting as per the present trend of rising cases of different countries (ii) forecasting of one week following up with the improvement trends as per China and South Korea, and (iii) forecasting if followed up the progressive trends as per China and South Korea before a week. The results have shown that ANN can efficiently forecast the future cases of COVID 19 outbreak of any country. The study shows that the confirmed cases of India, USA, France and UK could be about 50,000 to 1,60,000, 12,00,000 to 17,00,000, 1,40,000 to 1,50,000 and 2,40,000 to 2,50,000 respectively and may take about 2 to 10 months based on progressive trends of China and South Korea. Similarly, the death toll for these countries just before controlling could be about 1600 to 4000 for India, 1,35,000 to 1,00,000 for USA, 40,000 to 55,000 for France, 35,000 to 47,000 for UK during the same period of study.
{"title":"Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique (Special Issue: Covid-19)","authors":"S. Tamang, P. Singh, B. Datta","doi":"10.22034/GJESM.2019.06.SI.06","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.06","url":null,"abstract":"Artificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs artificial neural network-based curve fitting techniques in prediction and forecasting of the Covid-19 number of rising cases and death cases in India, USA, France, and UK, considering the progressive trends of China and South Korea. In this paper, three cases are considered to analyze the outbreak of Covid-19 pandemic viz., (i) forecasting as per the present trend of rising cases of different countries (ii) forecasting of one week following up with the improvement trends as per China and South Korea, and (iii) forecasting if followed up the progressive trends as per China and South Korea before a week. The results have shown that ANN can efficiently forecast the future cases of COVID 19 outbreak of any country. The study shows that the confirmed cases of India, USA, France and UK could be about 50,000 to 1,60,000, 12,00,000 to 17,00,000, 1,40,000 to 1,50,000 and 2,40,000 to 2,50,000 respectively and may take about 2 to 10 months based on progressive trends of China and South Korea. Similarly, the death toll for these countries just before controlling could be about 1600 to 4000 for India, 1,35,000 to 1,00,000 for USA, 40,000 to 55,000 for France, 35,000 to 47,000 for UK during the same period of study.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41292431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.22034/GJESM.2019.06.SI.02
D. Yadav, Himani Maheshwari, U. Chandra
Origin of the coronavirus was the seafood market of Wuhan city, Hubei province in China. The cases of someone suffering from COVID-19 can be traced back to the end of December 2019 in China. This is the most infectious disease and spread worldwide within three months after the first case reported. The World Health Organization renames Coronavirus as COVID-19. COVID-19 is the β-Coronavirus family virus, effect on the lung of human and common symptoms are cough, fever, fatigue, respiratory problem, and cold. The full name of the coronavirus is severe acute respiratory syndrome SARS-CoV. It spread on humans as well as animals and infected more than 183 countries with 2959927 confirm cases and 202733 deaths till 28 April 2020. 84 days data is used to predict confirmed and death cases for the next 10 days by using prophet and daily average based algorithm. Predicted confirmed cases are 2886183 and death cases 190540 till 25 April 2020. This study introduces the spreading pattern of COVID-19 in the top ten infected countries. After China, European countries are the most infected ones. In this study, data was analyzed on the attributes confirmed, active, recovered and death cases, and next ten days outbreak prediction. Some countries state-wise data confirmed active and death cases also analyzed.
{"title":"Outbreak prediction of covid-19 in most susceptible countries","authors":"D. Yadav, Himani Maheshwari, U. Chandra","doi":"10.22034/GJESM.2019.06.SI.02","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.02","url":null,"abstract":"Origin of the coronavirus was the seafood market of Wuhan city, Hubei province in China. The cases of someone suffering from COVID-19 can be traced back to the end of December 2019 in China. This is the most infectious disease and spread worldwide within three months after the first case reported. The World Health Organization renames Coronavirus as COVID-19. COVID-19 is the β-Coronavirus family virus, effect on the lung of human and common symptoms are cough, fever, fatigue, respiratory problem, and cold. The full name of the coronavirus is severe acute respiratory syndrome SARS-CoV. It spread on humans as well as animals and infected more than 183 countries with 2959927 confirm cases and 202733 deaths till 28 April 2020. 84 days data is used to predict confirmed and death cases for the next 10 days by using prophet and daily average based algorithm. Predicted confirmed cases are 2886183 and death cases 190540 till 25 April 2020. This study introduces the spreading pattern of COVID-19 in the top ten infected countries. After China, European countries are the most infected ones. In this study, data was analyzed on the attributes confirmed, active, recovered and death cases, and next ten days outbreak prediction. Some countries state-wise data confirmed active and death cases also analyzed.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46893541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.22034/GJESM.2019.06.SI.05
O. Ouhsine, A. Ouigmane, Elhoucein Layati, B. Aba, R. Isaifan, M. Berkani
Houshold waste is the residue generated daily by people as a result of consuming goods and services. The qualitative and quantitative aspects depend on the lifestyle and standard of living of citizens. Hence a change in habits, following an economic or health crisis, can influence the production of waste and its composition. The objective of the present work is to assess the impact of lockdown on the generation of trash and on the habits related to the consumption of goods in two communes in Morocco. More specifically, this study would investigate the behavior of citizens with regard to protective equipment against the coronavirus COVID-19. The results of the survey show that there is an influence of lockdown on the items purchased during this period, with an increase in the purchase of disinfectant products and a decrease in the consumption of meat and canned goods. Thus, the results showed that the quantity of organic fractions had decreased in the domestic waste with the appearance of other fractions such as residues of cleaning products. In addition, the survey conducted showed that 87% of respondents mix coronavirus protective equipment with household waste, which may contribute to the spread of the virus. Concerning the quantitative aspect, the weigh-ups showed that the monthly rate of increase of waste production between the months of February and March 2019 and the corresponding period in 2020 have decreased from +11.41% to +3.8% in the city of Khenifra (from 2,572 ton in Mars 2019 to 2,456 ton in the correspondent period in 2020) and from +4.73% to -1.23% in the center of Tighassaline (from 136 ton in Mars 2019 to 123 ton in the correspondent period in 2020).
{"title":"Impact of COVID-19 on the qualitative and quantitative aspect of household solid waste","authors":"O. Ouhsine, A. Ouigmane, Elhoucein Layati, B. Aba, R. Isaifan, M. Berkani","doi":"10.22034/GJESM.2019.06.SI.05","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.05","url":null,"abstract":"Houshold waste is the residue generated daily by people as a result of consuming goods and services. The qualitative and quantitative aspects depend on the lifestyle and standard of living of citizens. Hence a change in habits, following an economic or health crisis, can influence the production of waste and its composition. The objective of the present work is to assess the impact of lockdown on the generation of trash and on the habits related to the consumption of goods in two communes in Morocco. More specifically, this study would investigate the behavior of citizens with regard to protective equipment against the coronavirus COVID-19. The results of the survey show that there is an influence of lockdown on the items purchased during this period, with an increase in the purchase of disinfectant products and a decrease in the consumption of meat and canned goods. Thus, the results showed that the quantity of organic fractions had decreased in the domestic waste with the appearance of other fractions such as residues of cleaning products. In addition, the survey conducted showed that 87% of respondents mix coronavirus protective equipment with household waste, which may contribute to the spread of the virus. Concerning the quantitative aspect, the weigh-ups showed that the monthly rate of increase of waste production between the months of February and March 2019 and the corresponding period in 2020 have decreased from +11.41% to +3.8% in the city of Khenifra (from 2,572 ton in Mars 2019 to 2,456 ton in the correspondent period in 2020) and from +4.73% to -1.23% in the center of Tighassaline (from 136 ton in Mars 2019 to 123 ton in the correspondent period in 2020).","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42610932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.22034/GJESM.2019.06.SI.04
N. Gupta, A. S. Tomar, V. Kumar
COVID-19 is a huge tragedy for the world community. Everything in the world is affected due to this pandemic right from economy to resources where the economy of major countries of the world are facing recession and resources are surplus with no takers at all. The measures to contain COVID-19 pandemic include lockdown, social distancing, isolation, and home quarantine. Lockdown adopted by the different governments which involve non-functioning of all the industry and manufacturing units. However, as a blessing in disguise, these measures have a positive effect on the environment in terms of reduction in toxic gasses like nitrogen dioxide, aerosols, atmosphere ozone, particulate matter, and improvement in air quality. In this paper, the effect on various environmental parameters like aerosol, ozone, particulate matter, nitrogen dioxide, sulfur dioxide, carbon monoxide, and temperature on India by lockdown due to COVID-19 as a preventive measure has been analyzed. The work involves the refining and preprocessing of raw data of this year and last year of various harmful pollutants present in the environment along with satellite images from National Aeronautics and Space Administration for comparison of different parameters. It has been observed that with the above adopted measures temperature has been reduced to near about 15 degree Celsius, there is also reduction in humidity i.e. it is reduced to 40%, particulate matter (PM2.5) reaches near about normal i.e. 40 g/m3 and carbon monoxide levels has also been reduced to 10 ppm. The main idea is to emphasize the fact that how the environment is self-healing during the lockdown. And this study will be beneficial to environmentalists and industry professionals to make the future strategy for improving the environment.
{"title":"The effect of COVID-19 lockdown on the air environment in India","authors":"N. Gupta, A. S. Tomar, V. Kumar","doi":"10.22034/GJESM.2019.06.SI.04","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.04","url":null,"abstract":"COVID-19 is a huge tragedy for the world community. Everything in the world is affected due to this pandemic right from economy to resources where the economy of major countries of the world are facing recession and resources are surplus with no takers at all. The measures to contain COVID-19 pandemic include lockdown, social distancing, isolation, and home quarantine. Lockdown adopted by the different governments which involve non-functioning of all the industry and manufacturing units. However, as a blessing in disguise, these measures have a positive effect on the environment in terms of reduction in toxic gasses like nitrogen dioxide, aerosols, atmosphere ozone, particulate matter, and improvement in air quality. In this paper, the effect on various environmental parameters like aerosol, ozone, particulate matter, nitrogen dioxide, sulfur dioxide, carbon monoxide, and temperature on India by lockdown due to COVID-19 as a preventive measure has been analyzed. The work involves the refining and preprocessing of raw data of this year and last year of various harmful pollutants present in the environment along with satellite images from National Aeronautics and Space Administration for comparison of different parameters. It has been observed that with the above adopted measures temperature has been reduced to near about 15 degree Celsius, there is also reduction in humidity i.e. it is reduced to 40%, particulate matter (PM2.5) reaches near about normal i.e. 40 g/m3 and carbon monoxide levels has also been reduced to 10 ppm. The main idea is to emphasize the fact that how the environment is self-healing during the lockdown. And this study will be beneficial to environmentalists and industry professionals to make the future strategy for improving the environment.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48743556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-01DOI: 10.22034/GJESM.2019.06.SI.03
H. Abu-Qdais, Al-Ghazo, E. M. Alghazo
One of thesources of infection as a result of coronavirus disease treatment is the medical waste generated during the health care activities. Since the registration of the first infected case of coronavirus in Jordan the daily number of patients fluctuated from as low as zero to as high as 40 with a recovery ratio and case fatality risk of 39% and 1.7%, respectively. The main objective of the present study is to carry out statistical analysis and assess the generation rates and the composition of the medical waste generated during the treatment of coronavirus pandemic with reference to a major tertiary care hospital in Jordan. Data onthe daily generated waste, number of the admitted patients and on the amounts of consumables like various personal protective equipment, testing kits, and disinfectant used during the treatment of coronavirus disease was obtained. Data was subjected to descriptive statistical analysis to find the average generation rates, 3 days moving average, as well as the frequency distribution of the generated amounts. During 25 days' period, King Abdullah University Hospital has admitted 95 infected patients by coronavirus. The amount of the average rate of the medical waste generated as a result of coronavirus treatment was found to be 14.16 kg/patient/day and 3.95 kg/bed/day, which are more than tenfold higher than the average generation rate during the regular operational days of the hospital. Frequency analysis of the data revealed that the medical waste generation follows log normal distribution with correlation coefficient of 0.89. The distribution is distorted to the right and flatter than the normal distribution curve as judged by the skewness and kurtosis coefficients, respectively, which indicates deviation from normality.
{"title":"Statistical analysis and characteristics of hospital medical waste under novel Coronavirus outbreak","authors":"H. Abu-Qdais, Al-Ghazo, E. M. Alghazo","doi":"10.22034/GJESM.2019.06.SI.03","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.03","url":null,"abstract":"One of thesources of infection as a result of coronavirus disease treatment is the medical waste generated during the health care activities. Since the registration of the first infected case of coronavirus in Jordan the daily number of patients fluctuated from as low as zero to as high as 40 with a recovery ratio and case fatality risk of 39% and 1.7%, respectively. The main objective of the present study is to carry out statistical analysis and assess the generation rates and the composition of the medical waste generated during the treatment of coronavirus pandemic with reference to a major tertiary care hospital in Jordan. Data onthe daily generated waste, number of the admitted patients and on the amounts of consumables like various personal protective equipment, testing kits, and disinfectant used during the treatment of coronavirus disease was obtained. Data was subjected to descriptive statistical analysis to find the average generation rates, 3 days moving average, as well as the frequency distribution of the generated amounts. During 25 days' period, King Abdullah University Hospital has admitted 95 infected patients by coronavirus. The amount of the average rate of the medical waste generated as a result of coronavirus treatment was found to be 14.16 kg/patient/day and 3.95 kg/bed/day, which are more than tenfold higher than the average generation rate during the regular operational days of the hospital. Frequency analysis of the data revealed that the medical waste generation follows log normal distribution with correlation coefficient of 0.89. The distribution is distorted to the right and flatter than the normal distribution curve as judged by the skewness and kurtosis coefficients, respectively, which indicates deviation from normality.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42180872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.22034/GJESM.2020.03.01
R. Isaifan
The outbreak of coronavirus disease (COVID-19) was first reported from Wuhan, China, on December 31st, 2019. As the number of coronavirus infections has exceeded 100,000 with toll deaths of about 5000 worldwide as of early March, 2020, scientists and researchers are racing to investigate the nature of this virus and evaluate the short and long term effects of this disease. Despite its negative impacts that obliged the World Health Organization to declare COVID-19 epidemic as a Public Health Emergency of International Concern, the rate of mortality of this infection has not exceeded 3.4% globally. On the other hand, the mortality rate caused by ambient air pollution has contributed to 7.6% of all deaths in 2016 worldwide. The outbreak of COVID-19 has forced China to lockdown its industrial activities and hence dropped its NO2 and carbon emissions by 30 and 25%, respectively. This work reports on the first case study that compares the air quality status before and after the crisis. It sheds light on the facts related to the demographics of deaths by gender, age and health status before infection. The historical data on air quality, estimates of annual deaths and its economic burden have been presented and analyzed. The actual daily deaths due to COVID-19 have been obtained from the official records of the daily Situation Reports published by World Health Organization as of March 11th. The rate of mortality due to COVID-19 was impacted by two factors: age and health status. Results show that 75% of deaths were related to cases that had underlying present diseases with the majority aged of 80+ years. The reported figures were compared with the average daily mortality due to poor air quality which reached up to 3287 deaths due to high levels of NO2, O3 and PM. The air quality status before the crisis was compared with the current situation showing that COVID-19 forced-industrial and anthropogenic activities lockdown may have saved more lives by preventing ambient air pollution than by preventing infection.
{"title":"The dramatic impact of coronavirus outbreak on air quality: Has it saved as much as it has killed so far?","authors":"R. Isaifan","doi":"10.22034/GJESM.2020.03.01","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.01","url":null,"abstract":"The outbreak of coronavirus disease (COVID-19) was first reported from Wuhan, China, on December 31st, 2019. As the number of coronavirus infections has exceeded 100,000 with toll deaths of about 5000 worldwide as of early March, 2020, scientists and researchers are racing to investigate the nature of this virus and evaluate the short and long term effects of this disease. Despite its negative impacts that obliged the World Health Organization to declare COVID-19 epidemic as a Public Health Emergency of International Concern, the rate of mortality of this infection has not exceeded 3.4% globally. On the other hand, the mortality rate caused by ambient air pollution has contributed to 7.6% of all deaths in 2016 worldwide. The outbreak of COVID-19 has forced China to lockdown its industrial activities and hence dropped its NO2 and carbon emissions by 30 and 25%, respectively. This work reports on the first case study that compares the air quality status before and after the crisis. It sheds light on the facts related to the demographics of deaths by gender, age and health status before infection. The historical data on air quality, estimates of annual deaths and its economic burden have been presented and analyzed. The actual daily deaths due to COVID-19 have been obtained from the official records of the daily Situation Reports published by World Health Organization as of March 11th. The rate of mortality due to COVID-19 was impacted by two factors: age and health status. Results show that 75% of deaths were related to cases that had underlying present diseases with the majority aged of 80+ years. The reported figures were compared with the average daily mortality due to poor air quality which reached up to 3287 deaths due to high levels of NO2, O3 and PM. The air quality status before the crisis was compared with the current situation showing that COVID-19 forced-industrial and anthropogenic activities lockdown may have saved more lives by preventing ambient air pollution than by preventing infection.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42300652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.22034/GJESM.2020.03.10
C. Odiji, O. Aderoju, M. C. Ekwe, D. T. Oje, J. O. Imhanfidon
Runoff assessment and estimation is crucial for watershed management as it provides information that is needed to expedite the course of watershed planning and development. The most commonly used model due to its simplicity and versatility in runoff estimation is the soil conservation service curve number developed by the United States Department of Agriculture. The study estimates the surface runoff of Upper Benue watershed using a geospatial based soil conservation service curve number model. Datasets utilized for this purpose are; Rainfall, land use, digitial elevation model and FAO-Soil. The soil and land use data were intersected to create the curve number grid and database. The curve number grid combined with the mean annual rainfall data from 1990 – 2017 was used to estimate runoff. The result revealed that 61.5% of rainfall was direct runoff while 38.5% of the rainfall was retained by tree/plant cover and soil. The average curve number for the normal condition was calculated to be 80.1 while the dry and wet season was 59.6, and 93.2 respectively. The average runoff volume for 27 years was estimated to be 69,887.43mm3. A correlation coefficient of 0.79 was found for the relationship between rainfall and runoff. The research highlights the importance of geospatial technique when integrated with soil conservation service curve number to estimate runoff conditions in Upper Benue Watershed.
{"title":"Surface runoff estimation in an upper watershed using geo-spatial based soil conservation service-curve number method.","authors":"C. Odiji, O. Aderoju, M. C. Ekwe, D. T. Oje, J. O. Imhanfidon","doi":"10.22034/GJESM.2020.03.10","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.10","url":null,"abstract":"Runoff assessment and estimation is crucial for watershed management as it provides information that is needed to expedite the course of watershed planning and development. The most commonly used model due to its simplicity and versatility in runoff estimation is the soil conservation service curve number developed by the United States Department of Agriculture. The study estimates the surface runoff of Upper Benue watershed using a geospatial based soil conservation service curve number model. Datasets utilized for this purpose are; Rainfall, land use, digitial elevation model and FAO-Soil. The soil and land use data were intersected to create the curve number grid and database. The curve number grid combined with the mean annual rainfall data from 1990 – 2017 was used to estimate runoff. The result revealed that 61.5% of rainfall was direct runoff while 38.5% of the rainfall was retained by tree/plant cover and soil. The average curve number for the normal condition was calculated to be 80.1 while the dry and wet season was 59.6, and 93.2 respectively. The average runoff volume for 27 years was estimated to be 69,887.43mm3. A correlation coefficient of 0.79 was found for the relationship between rainfall and runoff. The research highlights the importance of geospatial technique when integrated with soil conservation service curve number to estimate runoff conditions in Upper Benue Watershed.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47143181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.22034/GJESM.2020.03.03
J. Petersen, C. P. Colon, J. Joyner
Plumb Beach, Brooklyn, New York in USA is an important horseshoe crab breeding and nursery ground that has experienced substantial anthropogenic influence, including pollution, erosion and subsequent restoration. Since little is known about the relationship between sediment microbial communities and juvenile horseshoe crab survival, next generation sequencing was used to characterize and compare the sediment microbiome of three distinct areas of Plumb Beach:- a tidal creek with abundant juveniles, East Beach with moderate number of juveniles, and West Beach- a highly disturbed area where juvenile crabs are rarely seen. The microbiome of juvenile crab intestinal content (both dissected gut content and fecal flush content) from the tidal creek site was also examined. The results showed that in our 2017 survey, the overall dominant sediment orders at all beach sites were Vibrionales (30%), Flavobacteriales (22%) and Alteromonadales (21%). Although alpha diversity was similar among the three beach sites, Bray-Curtis distances assessed by Permanova revealed significant differences in Beta diversity, with a unique microbial assemblage found in the tidal creek. Both crab gut and fecal flush samples did not sequence well, showing low species diversity and very high variability. This study is the first to use next generation sequencing to characterize Plumb Beach sediment microbes and the first attempt to examine the gut microbiome of juvenile horseshoe crabs. This information will contribute to understanding the relationships between sediment microbial assemblages and juvenile crab populations within this important urban habitat.
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Pub Date : 2020-07-01DOI: 10.22034/GJESM.2020.03.02
F. Torres-Bejarano, A. Torregroza-Espinosa, Eliana Martínez-Mera, D. Castañeda-Valbuena, M. P. Tejera-Gonzalez
Cienaga de Mallorquin is a coastal lagoon designated as a RAMSAR site due to its ecological regional and international importance. In this work, the environmental fluid dynamics code explorer modeling system was implemented to determine the spatio-temporal distribution of temperature, dissolved oxygen, chemical oxygen demand and nutrient levels, and assess the trophic status of Cienaga de Mallorquin. The model was set up with field measurement data taken during transition period and wet season, and secondary information obtained from local authorities and environmental agencies. The results of model simulations were calibrated and verified by the root mean square error method, achieving a consistent fit for all considered variables. Average velocities were between 0.006 m/s and 0.013 m/s during the analyzed periods. The temperature was higher in the wet season than in the transition period (29°C and 31.5°C, respectively). The dissolved oxygen was similar in both periods (6.6 and 6.7 mg/L). NO3 concentrations were higher during the transition period (3.28 mg/L), with a minimum of 1.76 mg/L and a maximum of 5.09 mg/L. The lowest NO3 concentrations were found in the area influenced by the connection with the Caribbean Sea. PO4 concentrations in the wet season were lower than in the transition period (0.20 mg/L). Finally, Cienaga de Mallorquin exhibits high productivity levels with Trophic State Index > 50 and temporal variations of mesotrophic to eutrophic. The use of Trophic State Index is useful for the management of water body eutrophication and productivity, making it particularly important in aquatic ecosystems.
Cienaga de Mallorquin是一个沿海泻湖，由于其生态区域和国际重要性而被指定为RAMSAR遗址。本文利用环境流体动力学代码explorer建模系统，确定了Cienaga de Mallorquin的温度、溶解氧、化学需氧量和营养水平的时空分布，并对其营养状况进行了评估。该模型的建立采用了过渡时期和雨季的野外测量数据，以及当地政府和环境部门提供的二次信息。模型模拟结果通过均方根误差方法进行校准和验证，实现了所有考虑变量的一致拟合。在分析期间，平均速度在0.006 ~ 0.013 m/s之间。雨季气温高于过渡期，分别为29°C和31.5°C。溶解氧在两个时期相似(6.6和6.7 mg/L)。过渡时期NO3浓度较高，为3.28 mg/L，最低为1.76 mg/L，最高为5.09 mg/L。NO3浓度最低的地区是受与加勒比海连接影响的地区。雨季PO4浓度低于过渡期(0.20 mg/L)。最后，Cienaga de Mallorquin在营养状态指数bb50和中营养化到富营养化的时间变化中显示出较高的生产力水平。营养状态指数的使用有助于水体富营养化和生产力的管理，使其在水生生态系统中尤为重要。
{"title":"Hydrodynamics and water quality assessment of a coastal lagoon using environmental fluid dynamics code explorer modeling system.","authors":"F. Torres-Bejarano, A. Torregroza-Espinosa, Eliana Martínez-Mera, D. Castañeda-Valbuena, M. P. Tejera-Gonzalez","doi":"10.22034/GJESM.2020.03.02","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.02","url":null,"abstract":"Cienaga de Mallorquin is a coastal lagoon designated as a RAMSAR site due to its ecological regional and international importance. In this work, the environmental fluid dynamics code explorer modeling system was implemented to determine the spatio-temporal distribution of temperature, dissolved oxygen, chemical oxygen demand and nutrient levels, and assess the trophic status of Cienaga de Mallorquin. The model was set up with field measurement data taken during transition period and wet season, and secondary information obtained from local authorities and environmental agencies. The results of model simulations were calibrated and verified by the root mean square error method, achieving a consistent fit for all considered variables. Average velocities were between 0.006 m/s and 0.013 m/s during the analyzed periods. The temperature was higher in the wet season than in the transition period (29°C and 31.5°C, respectively). The dissolved oxygen was similar in both periods (6.6 and 6.7 mg/L). NO3 concentrations were higher during the transition period (3.28 mg/L), with a minimum of 1.76 mg/L and a maximum of 5.09 mg/L. The lowest NO3 concentrations were found in the area influenced by the connection with the Caribbean Sea. PO4 concentrations in the wet season were lower than in the transition period (0.20 mg/L). Finally, Cienaga de Mallorquin exhibits high productivity levels with Trophic State Index > 50 and temporal variations of mesotrophic to eutrophic. The use of Trophic State Index is useful for the management of water body eutrophication and productivity, making it particularly important in aquatic ecosystems.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45805087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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