Environmental Management
S. Syafrudin; J.M. Masjhoer; M. Maryono
Abstract
BACKGROUND AND OBJECTIVES: Population growth and economic activity in rural areas are factors driving the waste generation rate. Rural waste management generally still applies conventional patterns and has the potential to damage the environment and threaten human health. Challenges and remedial measures ...
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BACKGROUND AND OBJECTIVES: Population growth and economic activity in rural areas are factors driving the waste generation rate. Rural waste management generally still applies conventional patterns and has the potential to damage the environment and threaten human health. Challenges and remedial measures for solid waste management in rural areas differ from urban ones. The first step in planning a waste management system is to identify the generation and characteristics of waste. Unfortunately, data on waste generation and characteristics in rural areas in developing countries are still minimal. The problems are mainly caused by the development of the tourism industry, and it certainly requires waste management as the solution. However, due to the unavailability of waste generation data, this study aims to measure and analyze waste characteristics in the southern zone of Gunungkidul Regency.METHODS: Primary data collection was taken from 16 randomly selected villages in six sub-districts in Gunungkidul Regency. A door-to-door survey was carried to 110 residential and 160 non-residential samples for eight consecutive days using the Indonesian National Standard 19-3964-1994 method. The processed data were analyzed using a quantitative descriptive method.FINDINGS: The results showed that the average waste generation was 0.29 kilograms per person per day. It shows that the waste generation in the study area is categorized in small-town classification. 75 percent of solid waste generated is food waste and leaves. Meanwhile, paper, plastic, glass, wood, other materials, and fabrics were calculated at 11.8 percent, 10.1 percent, 1.7 percent, 0.5 percent, 0.5 percent, and 0.4 percent respectively. Housing produced less recycled waste as indicated by a high density of 110.6 kilograms per cubic meter. Waste generation and composition are influenced by socioeconomic factors such as economic activity and lifestyle, geographic conditions, and downtown attractiveness.CONCLUSION: The characteristics of the waste produced by the southern zone of Gunungkidul Regency are not much different from most rural areas in developing countries. Rural waste management needs to see organic waste as the main management material. Organic waste processing through composting can be a future solution, but the active role of residents determines its success. In addition, this method can help extend the life of the landfill capacity because the volume of organic waste will be reduced by half.
Environmental Management
V. G. Shcherbak; I. Gryshchenko; L. Ganushchak-Yefimenko; O. Nifatova; V. Tkachuk; T. Kostiuk; V. Hotra
Abstract
BACKGROUND AND OBJECTIVES: A new wave of Covid-19 pandemic has worsened the epidemiological situation in Ukraine. This caused the need to tighten quarantine measures that have been introduced since 31.08.2020. The conducted analysis showed that there are 3 groups of technologies for digital contact tracing: ...
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BACKGROUND AND OBJECTIVES: A new wave of Covid-19 pandemic has worsened the epidemiological situation in Ukraine. This caused the need to tighten quarantine measures that have been introduced since 31.08.2020. The conducted analysis showed that there are 3 groups of technologies for digital contact tracing: from maximum (25%) to minimum (20%). Objective of the study is to develop an exchange platform to track the spread of COVID-19 in rural areas.METHODS: Factor analysis identified key factors of COVID-19 virus spread. Cluster analysis identified clusters of COVID-19 spread. Taxonomy method established the limits of using contact tracing methods. Discriminatory method makes it possible to change the applied contact tracing method.FINDINGS: The results showed that the identified factors (medico-demographic special features of Covid-19 virus spread; rural infrastructure to counteract the infection) describe in total 83.24% of the data processed. Specified 4 clusters differ in the level of susceptibility of the population to COVID-19 and infrastructure development: from minimum (33% of the united territorial communities) to maximum - 13% of the united territorial communities. The value of the integral indicator calculated provides means for establishing the maximum (8.5) and the minimum (2) limit of changes in the method of digital contact tracing.CONCLUSION: The developed methodology was implemented on the basis of the united territorial communities of Sumy region. Monitoring of changes in the epidemiological situation made it possible to justify the need to change the contact tracing model, which will reduce the epidemiological level in the region as a whole by 30%.
Environmental Management
V. G. Shcherbak; L. Ganushchak-Yefimenko; O. Nifatova; N. Fastovets; G. Plysenko; L. Lutay; V. Tkachuk; O. Ptashchenko
Abstract
This study provides a multidimensional analysis of sustainable socio-economic development and its challenges in the rural areas of Ukraine. The methodology of realization of sustainable development’s conceptual provisions was created. The advantages of using indicative assessment at the regional ...
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This study provides a multidimensional analysis of sustainable socio-economic development and its challenges in the rural areas of Ukraine. The methodology of realization of sustainable development’s conceptual provisions was created. The advantages of using indicative assessment at the regional level were justified. The methodical approach how to define the indicators of sustainable development (including economic, socio-demographic, labor and environmental domains) of rural areas was proposed. Statistical data, experts’ and rural residents’ evaluation were used to assess the level of socio-economic development of rural areas. The proposed system of indicators is applicable not only to the rural areas of the whole region, but also to its different parts. The tracking model is based on the consistent use of economic, mathematical and expert methods: SWOT-analysis, factor, cluster and discriminant analysis. The construction of the dendrogram allows to determine the type of representative for each cluster. The modeling of sustainable socio-economic development for each sample is applicable to all areas within same cluster. A representative sample from each cluster makes it possible to identify the presence in the region of the so-called "points of growth" and to forecast their development. Two scenarios are considered: maximum (the share of GRP accumulation growth 21.2%) and moderate (the share of GRP accumulation growth 10.6%). GDP Gross Domestic Product growth will differentiate by the type of activity: cluster 1 (agriculture, hunting and forestry) 13% increase; cluster 2 (trade, service and household services) 21% increase; cluster 3 (tourism and international cooperation) 18% increase; cluster 4 (processing industry) 8% increase. Therefore, the using of key indicators for monitoring the sustainable development of rural areas provides an opportunity to take into account the specifics of sustainable development of different specialization branches of rural areas that will support high economic and social growth in the future.
