Pub Date : 2020-07-01DOI: 10.22034/GJESM.2020.03.04
M. Limon, C. Villarino
This study assessed the knowledge, attitudes and practices on food waste of selected households in the northern province of the Philippines. The results of the assessment were used as bases for formulation of a recycling system. A total of one hundred rural households were selected using stratified equal allocation sampling technique. Data were collected through the use of researcher-made questionnaire with Cronbach’s Alpha at .82, and was supplemented by observations. Factor analysis, Pearson r, and point-biserial correlation were used to yield findings in the study. Results show that a number of factors discourage the respondents’ participation in the reduction and recycling of food waste, such as lack of facilities, insufficient training, and information dissemination. Household size (r=.199, p<0.05), monthly income (r=.282, p<0.01; r=-.217, p<0.05), and planning (r=-.243, p<0.05) influences the way the participants manage household food waste. On the other hand, age, educational attainment, and sex, do not significantly affect the way the household-participants manage food waste. One strategic and feasible solution is a compulsory food waste recycling system (FWRS) for private households to combat this pressing issue on food waste. This proposed framework is composed of four major moves that require the collaboration of various sectors and stakeholders in the community, and is expected to suggest valuable policy amendments including significant decrease in wastage of consumable agricultural products. Without doubt, the ongoing over generation of food waste is a serious global setback that needs to be urgently addressed.
{"title":"Knowledge, attitudes and practices on household food waste: Bases for formulation of a recycling system","authors":"M. Limon, C. Villarino","doi":"10.22034/GJESM.2020.03.04","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.04","url":null,"abstract":"This study assessed the knowledge, attitudes and practices on food waste of selected households in the northern province of the Philippines. The results of the assessment were used as bases for formulation of a recycling system. A total of one hundred rural households were selected using stratified equal allocation sampling technique. Data were collected through the use of researcher-made questionnaire with Cronbach’s Alpha at .82, and was supplemented by observations. Factor analysis, Pearson r, and point-biserial correlation were used to yield findings in the study. Results show that a number of factors discourage the respondents’ participation in the reduction and recycling of food waste, such as lack of facilities, insufficient training, and information dissemination. Household size (r=.199, p<0.05), monthly income (r=.282, p<0.01; r=-.217, p<0.05), and planning (r=-.243, p<0.05) influences the way the participants manage household food waste. On the other hand, age, educational attainment, and sex, do not significantly affect the way the household-participants manage food waste. One strategic and feasible solution is a compulsory food waste recycling system (FWRS) for private households to combat this pressing issue on food waste. This proposed framework is composed of four major moves that require the collaboration of various sectors and stakeholders in the community, and is expected to suggest valuable policy amendments including significant decrease in wastage of consumable agricultural products. Without doubt, the ongoing over generation of food waste is a serious global setback that needs to be urgently addressed.","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":"46228398","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.2020.03.06
S. Kozlovskyi, L. Nikolenko, O. Peresada, O. Pokhyliuk, O. Yatchuk, N. Bolgarova, O. Kulhanik
In the context of globalization of economic development processes, the issue of determining the level of public welfare of economic agents is particularly burning. The object of ehis study is the process of assessing welfare of the economic entities system. The subject of the study is the instrumental and mathematical aspects of modeling and measuring the public welfare. The aim of the work is to develop the mathematical model for measuring the welfare of Ukraine using methods of intellectual analysis, namely, the theory of fuzzy sets. The output of the study is a new approach to objective estimation of public welfare of the state. It is proposed to assess the level of public welfare of the state on the basis of a mathematical model developed on the basis of the theory of fuzzy sets. Input factors of the model are international indices and indicators, such as Index of Economic Freedom, Global Peace Index, Democracy Index, Corruption Perceptions Index, Human Development Index, Prosperity Index, Global Competitiveness Index as well as an indicator that reflects the characteristic property of the Ukrainian economy, namely the minimum living wage. Developed mathematical model for assessment of the level of public welfare of Ukraine and made a prediction of the indicator by 2024 on the basis of the above indices. The results of the study allowed us to establish that the level of public welfare (units) in Ukraine on a scale from 0 to 100 will be equal to 25, 17, 32, 26, and 28 in 2020, 2021, 2022, 2023, and 2024, accordingly.
{"title":"Estimation level of public welfare on the basis of methods of intellectual analysis","authors":"S. Kozlovskyi, L. Nikolenko, O. Peresada, O. Pokhyliuk, O. Yatchuk, N. Bolgarova, O. Kulhanik","doi":"10.22034/GJESM.2020.03.06","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.06","url":null,"abstract":"In the context of globalization of economic development processes, the issue of determining the level of public welfare of economic agents is particularly burning. The object of ehis study is the process of assessing welfare of the economic entities system. The subject of the study is the instrumental and mathematical aspects of modeling and measuring the public welfare. The aim of the work is to develop the mathematical model for measuring the welfare of Ukraine using methods of intellectual analysis, namely, the theory of fuzzy sets. The output of the study is a new approach to objective estimation of public welfare of the state. It is proposed to assess the level of public welfare of the state on the basis of a mathematical model developed on the basis of the theory of fuzzy sets. Input factors of the model are international indices and indicators, such as Index of Economic Freedom, Global Peace Index, Democracy Index, Corruption Perceptions Index, Human Development Index, Prosperity Index, Global Competitiveness Index as well as an indicator that reflects the characteristic property of the Ukrainian economy, namely the minimum living wage. Developed mathematical model for assessment of the level of public welfare of Ukraine and made a prediction of the indicator by 2024 on the basis of the above indices. The results of the study allowed us to establish that the level of public welfare (units) in Ukraine on a scale from 0 to 100 will be equal to 25, 17, 32, 26, and 28 in 2020, 2021, 2022, 2023, and 2024, accordingly.","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":"48767241","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.2020.03.08
D. Setyawan
This study compares the energy intensity performance in Indonesia to other south-east Asia countries such as Vietnam, Thailand, Singapore, The Philippines and Malaysia for the period from 1971 to 2016. For this goal, this research employs a multiplicative Log Mean Divisia Index II method and Spatial-Temporal Index Decomposition Analysis. The manufacturing sector and commercial sector played a key role in the regions economic structures that accounted for around 60% to 80% of the total economic output from 1971 to 2016. The contribution of the manufacturing sector increased quite significantly, from 8% in 1971 to a peak of around 31% in 2001, before it fell to 28% in 2016. On the other hand, the contribution of agriculture sector dropped from 49% in 1971 to approximately 17% in 2016. It is demonstrated in this research that the aggregate trend of the changes in energy intensity in these countries in the past forty-five years has been decreasing. For Indonesia, aggregate energy intensity rose steadily by an average of 3% per year from 1971 to 1999, more than doubling over this period, while from 1999 to 2001 energy intensity fell by 1% per annum on average, falling by 17% overall in 2016. Overall, in terms of structure and industry effects on aggregate energy intensity, all these countries showed a shift in industry value added to more energy-intensive industries which also offset by falling within-industry energy intensity. However, the analysis shows that both element of this trend was most pronounced in Indonesia.
{"title":"Economy-wide energy efficiency using a comprehensive decomposition method.","authors":"D. Setyawan","doi":"10.22034/GJESM.2020.03.08","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.08","url":null,"abstract":"This study compares the energy intensity performance in Indonesia to other south-east Asia countries such as Vietnam, Thailand, Singapore, The Philippines and Malaysia for the period from 1971 to 2016. For this goal, this research employs a multiplicative Log Mean Divisia Index II method and Spatial-Temporal Index Decomposition Analysis. The manufacturing sector and commercial sector played a key role in the regions economic structures that accounted for around 60% to 80% of the total economic output from 1971 to 2016. The contribution of the manufacturing sector increased quite significantly, from 8% in 1971 to a peak of around 31% in 2001, before it fell to 28% in 2016. On the other hand, the contribution of agriculture sector dropped from 49% in 1971 to approximately 17% in 2016. It is demonstrated in this research that the aggregate trend of the changes in energy intensity in these countries in the past forty-five years has been decreasing. For Indonesia, aggregate energy intensity rose steadily by an average of 3% per year from 1971 to 1999, more than doubling over this period, while from 1999 to 2001 energy intensity fell by 1% per annum on average, falling by 17% overall in 2016. Overall, in terms of structure and industry effects on aggregate energy intensity, all these countries showed a shift in industry value added to more energy-intensive industries which also offset by falling within-industry energy intensity. However, the analysis shows that both element of this trend was most pronounced in Indonesia.","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":"46596877","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.2020.03.07
J. D. Palermo, Kevin L. Labrador, Jhunrey Follante, Altair B. Agmata, Ma. Josefa R. Pante, R. Rollon, L. David
Marine microplastics are emerging pollutants that impact across levels of marine food chain at a global scale. Its presence was determined on Sardinella lemuru, a commercial pelagic fish that are harvested generally in the Northern Mindanao, consumed locally, and exported worldwide as bottled or canned sardine products. The stomach contents of 600 sardines were examined visually under a microscope, stained with Rose Bengal, and tested with hot needle technique to identify ingested microplastics. These anthropogenic particles were measured and physically classified into fibers, fragments, and films. Results of this study showed that 85% of S. lemuru were already contaminated with 3.74 ± 3.92 # of microplastics even before being processed into various sardine products. These microplastics ranged from 0.12 to 21.30 mm and 80 % were mostly < 2.5 mm size classes. The dominant microplastics were 97.94 % in the form of fibers while 1.52 % and 0.54 % were respectively classified into fragments and films. Method validation by isolating microplastics from spiked samples (n = 30) with three retrieval attempts showed 100% recovery efficiency. While results from Canonical Correspondence Analysis of ingested microplastic data had no relationship with the standard lengths of the sardine and the masses of ingested food materials at varying size classes, the total number of ingested microplastics from 2014 to 2016 were directly correlated (r2=0.91, p=0.003) with the human population at the landing sites along the coastline of northern Mindanao.
{"title":"Susceptibility of Sardinella lemuru to emerging marine microplastic pollution","authors":"J. D. Palermo, Kevin L. Labrador, Jhunrey Follante, Altair B. Agmata, Ma. Josefa R. Pante, R. Rollon, L. David","doi":"10.22034/GJESM.2020.03.07","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.07","url":null,"abstract":"Marine microplastics are emerging pollutants that impact across levels of marine food chain at a global scale. Its presence was determined on Sardinella lemuru, a commercial pelagic fish that are harvested generally in the Northern Mindanao, consumed locally, and exported worldwide as bottled or canned sardine products. The stomach contents of 600 sardines were examined visually under a microscope, stained with Rose Bengal, and tested with hot needle technique to identify ingested microplastics. These anthropogenic particles were measured and physically classified into fibers, fragments, and films. Results of this study showed that 85% of S. lemuru were already contaminated with 3.74 ± 3.92 # of microplastics even before being processed into various sardine products. These microplastics ranged from 0.12 to 21.30 mm and 80 % were mostly < 2.5 mm size classes. The dominant microplastics were 97.94 % in the form of fibers while 1.52 % and 0.54 % were respectively classified into fragments and films. Method validation by isolating microplastics from spiked samples (n = 30) with three retrieval attempts showed 100% recovery efficiency. While results from Canonical Correspondence Analysis of ingested microplastic data had no relationship with the standard lengths of the sardine and the masses of ingested food materials at varying size classes, the total number of ingested microplastics from 2014 to 2016 were directly correlated (r2=0.91, p=0.003) with the human population at the landing sites along the coastline of northern Mindanao.","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":"45642345","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.2020.03.09
M. Camara, N. Jamil, A. F. Abdullah, Rohasliney Hashim
Predicting land use change is an indispensable aspect in identifying the best development and management of land resources and their potential. This study used certified land-use maps of 1997, 2006, and 2015 combined with ancillary data such as road networks, water bodies and slopes, obtained from the Department of Agriculture and the Department of Surveying and Mapping in Malaysia, respectively. The prediction of future land use changes in the Selangor River basin in Malaysia was performed using the Cellular Automata Markov model. The transition probability matrices were computed using the land use conditions of the periods 1997-2006, 2006-2015, 1997-2015. The performance of the model was very good in its overall ability to simulate the actual land use map of 2015, with the index values of 0.92% and 0.97%, respectively for Kappa for no information and Kappa for grid-cell level location which indicated the reliability of the model to successfully simulate land use changes in 2024 and 2033. Based on the expected results, the future urban area will grow faster (33%) over the next two decades, leading to a decline in forest area that is expected to lose 8% of its total space during these periods. Agricultural land will increase to 4%, while water bodies will change slightly increasing to 1%, and other areas of land use will likely become reservoirs of water, topsoil or new green spaces shrinking at 30%. Given the importance of knowledge of future land use in addressing the problems of uncontrolled development on environmental quality, this study could be valuable for land use planners of the river basin largely covered by natural forest. The study however, suggests future research to integrate geospatial techniques with biophysical and socio-economic factors in simulating land use trends.
{"title":"Integrating cellular automata Markov model to simulate future land use change of a tropical basin.","authors":"M. Camara, N. Jamil, A. F. Abdullah, Rohasliney Hashim","doi":"10.22034/GJESM.2020.03.09","DOIUrl":"https://doi.org/10.22034/GJESM.2020.03.09","url":null,"abstract":"Predicting land use change is an indispensable aspect in identifying the best development and management of land resources and their potential. This study used certified land-use maps of 1997, 2006, and 2015 combined with ancillary data such as road networks, water bodies and slopes, obtained from the Department of Agriculture and the Department of Surveying and Mapping in Malaysia, respectively. The prediction of future land use changes in the Selangor River basin in Malaysia was performed using the Cellular Automata Markov model. The transition probability matrices were computed using the land use conditions of the periods 1997-2006, 2006-2015, 1997-2015. The performance of the model was very good in its overall ability to simulate the actual land use map of 2015, with the index values of 0.92% and 0.97%, respectively for Kappa for no information and Kappa for grid-cell level location which indicated the reliability of the model to successfully simulate land use changes in 2024 and 2033. Based on the expected results, the future urban area will grow faster (33%) over the next two decades, leading to a decline in forest area that is expected to lose 8% of its total space during these periods. Agricultural land will increase to 4%, while water bodies will change slightly increasing to 1%, and other areas of land use will likely become reservoirs of water, topsoil or new green spaces shrinking at 30%. Given the importance of knowledge of future land use in addressing the problems of uncontrolled development on environmental quality, this study could be valuable for land use planners of the river basin largely covered by natural forest. The study however, suggests future research to integrate geospatial techniques with biophysical and socio-economic factors in simulating land use trends.","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":"42580670","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 : 2020-06-08DOI: 10.22034/GJESM.2019.06.SI.10
X. Xie, E. Naminse, S. Liu, Q. Yi
The coronavirus disease 2019 (COVID-19) has been identified as the main cause of the outbreak of the respiratory disease in Wuhan, Hubei Province of China in December 2019. Since then, the epidemic has spread rapidly throughout China and many other countries in the world. This study, therefore, examines the spatiotemporal distribution of the confirmed cases of COVID-19 and its effect on human development in China, and suggested social and non-pharmaceutical preventive interventions to help curb the further spread of the disease. The public open data available from January to February 2020, from the National Health Commission of the People’s Republic of China and a medical knowledge sharing website were used, and spatial analysis was performed to visualize the spatial distribution pattern of COVID-19 in China. The results showed among others that COVID-19 had entered a dispersed spatial pattern, resulting in increased pressure to control the spread of the disease. In early March, there was a significant reduction in the existing number of cases, and the number of deaths also decreased. At the provincial level, the spatial distribution of the number of cumulative confirmed cases in China was divided into four patterns: Hubei was the initial core region; the eastern provinces adjacent to Hubei formed the second concentrated pattern; the western provinces adjacent to Hubei and the northeastern and southeastern provinces which were separated from Hubei by one province belonged to the third distribution pattern; while the rest of the provinces in the north, south and west showing sporadic distribution patterns formed the fourth. It has been estimated that about 80% of students’ online learning at all schools were not effective due to lack of access to reliable and uninterrupted internet services especially in the rural areas of China.
{"title":"The spatial and temporal pattern of COVID-19 and its effect on humans development in China","authors":"X. Xie, E. Naminse, S. Liu, Q. Yi","doi":"10.22034/GJESM.2019.06.SI.10","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.10","url":null,"abstract":"The coronavirus disease 2019 (COVID-19) has been identified as the main cause of the outbreak of the respiratory disease in Wuhan, Hubei Province of China in December 2019. Since then, the epidemic has spread rapidly throughout China and many other countries in the world. This study, therefore, examines the spatiotemporal distribution of the confirmed cases of COVID-19 and its effect on human development in China, and suggested social and non-pharmaceutical preventive interventions to help curb the further spread of the disease. The public open data available from January to February 2020, from the National Health Commission of the People’s Republic of China and a medical knowledge sharing website were used, and spatial analysis was performed to visualize the spatial distribution pattern of COVID-19 in China. The results showed among others that COVID-19 had entered a dispersed spatial pattern, resulting in increased pressure to control the spread of the disease. In early March, there was a significant reduction in the existing number of cases, and the number of deaths also decreased. At the provincial level, the spatial distribution of the number of cumulative confirmed cases in China was divided into four patterns: Hubei was the initial core region; the eastern provinces adjacent to Hubei formed the second concentrated pattern; the western provinces adjacent to Hubei and the northeastern and southeastern provinces which were separated from Hubei by one province belonged to the third distribution pattern; while the rest of the provinces in the north, south and west showing sporadic distribution patterns formed the fourth. It has been estimated that about 80% of students’ online learning at all schools were not effective due to lack of access to reliable and uninterrupted internet services especially in the rural areas of China.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45596932","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 : 2020-06-04DOI: 10.22034/GJESM.2019.06.SI.08
M. H. Masum, S. Pal
Air pollution has become a serious concern for its potential health hazard, however, often got less attention in developing countries, like Bangladesh. It is expected that worldwide lockdown due to COVID-19 widespread cause reduction in environmental pollution in particularly the air pollution: however, such changes have been different in different places. In Chittagong, a city scale lockdown came in force on 26 March 2020, a week after when first three cases of COVID-19 have been reported in Bangladesh. This study aims to statistically evaluate the effects of COVID-19 lockdown (26 March to 26 April 2020) on selected air quality pollutants and air quality index s. The daily average concentrations of air pollutants PM10, PM2.5, NO2, SO2 and CO of Chittagong city during COVID-19 lockdown were statistically evaluated and were compared with dry season data averaging over previous 8 years (2012 to 2019). During lockdown, except NO2, all other pollutants studied showed statistically significant decreasing trend. During the COVID-19 shutdown notable reduction of 40%, 32% and 13% compared to the daily mean concentrations of these previous dry season were seen for PM2.5, PM10 and NO2, respectively. The improvement in air quality index value was found as 26% in comparison to the previous dry season due to less human activities in COVID-19 shutdown. The factor analysis showed that AQI in Chittagong city is largely influenced by PM10 and PM2.5 during COVID-19 shutdown. The lesson learnt in this forced measure of lockdown is not surprising and unexpected. It is rather thought provoking for the decision makers to tradeoff the tangible air quality benefits with ongoing development strategies’ that was often overlooked directly or indirectly.
{"title":"Statistical evaluation of selected air quality parameters influenced by COVID-19 lockdown","authors":"M. H. Masum, S. Pal","doi":"10.22034/GJESM.2019.06.SI.08","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.08","url":null,"abstract":"Air pollution has become a serious concern for its potential health hazard, however, often got less attention in developing countries, like Bangladesh. It is expected that worldwide lockdown due to COVID-19 widespread cause reduction in environmental pollution in particularly the air pollution: however, such changes have been different in different places. In Chittagong, a city scale lockdown came in force on 26 March 2020, a week after when first three cases of COVID-19 have been reported in Bangladesh. This study aims to statistically evaluate the effects of COVID-19 lockdown (26 March to 26 April 2020) on selected air quality pollutants and air quality index s. The daily average concentrations of air pollutants PM10, PM2.5, NO2, SO2 and CO of Chittagong city during COVID-19 lockdown were statistically evaluated and were compared with dry season data averaging over previous 8 years (2012 to 2019). During lockdown, except NO2, all other pollutants studied showed statistically significant decreasing trend. During the COVID-19 shutdown notable reduction of 40%, 32% and 13% compared to the daily mean concentrations of these previous dry season were seen for PM2.5, PM10 and NO2, respectively. The improvement in air quality index value was found as 26% in comparison to the previous dry season due to less human activities in COVID-19 shutdown. The factor analysis showed that AQI in Chittagong city is largely influenced by PM10 and PM2.5 during COVID-19 shutdown. The lesson learnt in this forced measure of lockdown is not surprising and unexpected. It is rather thought provoking for the decision makers to tradeoff the tangible air quality benefits with ongoing development strategies’ that was often overlooked directly or indirectly.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48430017","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 : 2020-06-02DOI: 10.22034/GJESM.2019.06.SI.07
R. Caraka, Youngjo Lee, R. Kurniawan, R. Herliansyah, P. A. Kaban, B. I. Nasution, Prana Ugiana Gio, R. Chen, T. Toharudin, B. Pardamean
COVID-19 has a severe and widespread impact, especially in Indonesia COVID-19 was first reported in Indonesia on March 03, 2020 then rapidly spread to all 34 provinces by April 09, 2020 Since then, COVID-19 is declared a state of national disaster and health emergency This research analyzes the difference of CO, HCHO, NO2, and SO2 density in Jakarta, West Java, Central Java, and South Sulawesi before and during the pandemic Also, this study assesses the effect of large scale restrictions on the economic growth during COVID-19 pandemic in Indonesia In a nutshell, the results on Wilcoxon and Fisher test by significance level alpha=5% as well as odds ratio showed that there are significant differences of CO density in all regions with highest odds ratio in East Java (OR=9 07), significant differences of HCHO density in DKI Jakarta, East Java, and South Sulawesi There are significant differences of NO2 density before and during public activities limitation in DKI Jakarta, West Java, East Java, and South Sulawesi However, the results show that there are no significant differences of SO2 density in all regions In addition, this research shows that there are significant differences of retail, grocery and pharmacy, and residental mobility before and during the COVID-19 pandemic in Indonesia This research also shows that during the COVID-19 pandemic there are severe economic losses, industry, companies, and real disruptions are severe for all levels of life due to large scale restrictions (C) 2020 GJESM All rights reserved
{"title":"Impact of COVID-19 large scale restriction on environment and economy in Indonesia","authors":"R. Caraka, Youngjo Lee, R. Kurniawan, R. Herliansyah, P. A. Kaban, B. I. Nasution, Prana Ugiana Gio, R. Chen, T. Toharudin, B. Pardamean","doi":"10.22034/GJESM.2019.06.SI.07","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.07","url":null,"abstract":"COVID-19 has a severe and widespread impact, especially in Indonesia COVID-19 was first reported in Indonesia on March 03, 2020 then rapidly spread to all 34 provinces by April 09, 2020 Since then, COVID-19 is declared a state of national disaster and health emergency This research analyzes the difference of CO, HCHO, NO2, and SO2 density in Jakarta, West Java, Central Java, and South Sulawesi before and during the pandemic Also, this study assesses the effect of large scale restrictions on the economic growth during COVID-19 pandemic in Indonesia In a nutshell, the results on Wilcoxon and Fisher test by significance level alpha=5% as well as odds ratio showed that there are significant differences of CO density in all regions with highest odds ratio in East Java (OR=9 07), significant differences of HCHO density in DKI Jakarta, East Java, and South Sulawesi There are significant differences of NO2 density before and during public activities limitation in DKI Jakarta, West Java, East Java, and South Sulawesi However, the results show that there are no significant differences of SO2 density in all regions In addition, this research shows that there are significant differences of retail, grocery and pharmacy, and residental mobility before and during the COVID-19 pandemic in Indonesia This research also shows that during the COVID-19 pandemic there are severe economic losses, industry, companies, and real disruptions are severe for all levels of life due to large scale restrictions (C) 2020 GJESM All rights reserved","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42074474","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 : 2020-06-01DOI: 10.22034/GJESM.2019.06.SI.09
S. Kozlovskyi, D. Bilenko, M. Kuzheliev, R. Lavrov, Volodymyr Kozlovskyi, Hennadii Mazur, A. Taranych
At the end of 2019, the new virus called coronavirus disease (Covid-19) spread widely from China all over the world. In March 2020 the World Health Organization declared a new virus outbreak as "a global pandemic", and recommended social distancing and quarantine. Most countries in Europe have been quarantined. The social aspect of this issue is complicated by the fact that Europe nowadays hosts 82 million international migrants. If migrant workers leave the host country, it reduces the Covid-19 spread. Nevertheless, if migrant workers do not return, it will worsen the situation with the economic crisis. The subject of the study is the instrumental and mathematical aspects of impact simulation of labor migrants' policy on the economic growth of the host country affected by COVID-19 pandemic. The aim of the work is to develop the system dynamics model for assessing labor migrants' policy impact on the economic growth of the host country during COVID-19 pandemic. It examined through hypotheses of different scenarios of labor migrants policy impact on the host country economic growth in Covid-19 pandemic. The proposed model combines epidemiological and the economic growth models and relies upon real statistical data. The analysis was carried out in four European countries. The results of the study enabled to state that without migrant workers the gross domestic product may fall to 43% in Italy, 45% in Netherlands, 37% in Spain and 200% in Switzerland in 2020.
{"title":"The system dynamic model of the labor migrant policy in economic growth affected by COVID-19","authors":"S. Kozlovskyi, D. Bilenko, M. Kuzheliev, R. Lavrov, Volodymyr Kozlovskyi, Hennadii Mazur, A. Taranych","doi":"10.22034/GJESM.2019.06.SI.09","DOIUrl":"https://doi.org/10.22034/GJESM.2019.06.SI.09","url":null,"abstract":"At the end of 2019, the new virus called coronavirus disease (Covid-19) spread widely from China all over the world. In March 2020 the World Health Organization declared a new virus outbreak as \"a global pandemic\", and recommended social distancing and quarantine. Most countries in Europe have been quarantined. The social aspect of this issue is complicated by the fact that Europe nowadays hosts 82 million international migrants. If migrant workers leave the host country, it reduces the Covid-19 spread. Nevertheless, if migrant workers do not return, it will worsen the situation with the economic crisis. The subject of the study is the instrumental and mathematical aspects of impact simulation of labor migrants' policy on the economic growth of the host country affected by COVID-19 pandemic. The aim of the work is to develop the system dynamics model for assessing labor migrants' policy impact on the economic growth of the host country during COVID-19 pandemic. It examined through hypotheses of different scenarios of labor migrants policy impact on the host country economic growth in Covid-19 pandemic. The proposed model combines epidemiological and the economic growth models and relies upon real statistical data. The analysis was carried out in four European countries. The results of the study enabled to state that without migrant workers the gross domestic product may fall to 43% in Italy, 45% in Netherlands, 37% in Spain and 200% in Switzerland in 2020.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47395307","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 : 2020-04-01DOI: 10.22034/GJESM.2020.02.07
H. Khawaldah, Ibrahim Farhan, N. Alzboun
This study analyzes the characteristics of land use/land cover change in Jordan’s Irbid governorate, 1984–2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful planning. Satellite images of Landsat 5-thematic mapper and Landsat 8 operational land imager for the years 1984, 1994, 2004, 2015 and 2018 were used to explore the characteristics of land use/land cover for this study. The results indicate that the built-up area expanded by 386.9% during the study period and predict further expansion by 19.5% and 64.6% from 2015 to 2030 and 2050 respectively. The areas around the central and eastern parts of the governorate are predicted to have significant expansion of the built-up area by these dates, which should be taken into consideration in future plans. Land use/land cover change and urban expansion in Irbid are primarily caused by the high rate of population growth rate as a direct result of receiving large numbers of immigrants from Syria and Palestine in addition to the natural increase of population and other socio-economic changes.
{"title":"Simulation and prediction of land use and land cover change using GIS, remote sensing and CA-Markov model.","authors":"H. Khawaldah, Ibrahim Farhan, N. Alzboun","doi":"10.22034/GJESM.2020.02.07","DOIUrl":"https://doi.org/10.22034/GJESM.2020.02.07","url":null,"abstract":"This study analyzes the characteristics of land use/land cover change in Jordan’s Irbid governorate, 1984–2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful planning. Satellite images of Landsat 5-thematic mapper and Landsat 8 operational land imager for the years 1984, 1994, 2004, 2015 and 2018 were used to explore the characteristics of land use/land cover for this study. The results indicate that the built-up area expanded by 386.9% during the study period and predict further expansion by 19.5% and 64.6% from 2015 to 2030 and 2050 respectively. The areas around the central and eastern parts of the governorate are predicted to have significant expansion of the built-up area by these dates, which should be taken into consideration in future plans. Land use/land cover change and urban expansion in Irbid are primarily caused by the high rate of population growth rate as a direct result of receiving large numbers of immigrants from Syria and Palestine in addition to the natural increase of population and other socio-economic changes.","PeriodicalId":46495,"journal":{"name":"GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49298389","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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