ORIGINAL RESEARCH PAPER
Environmental engineering
E. N. Hidayah; L.W. Liang; O.H. Cahyonugroho; F. Rizqa
Articles in Press, Accepted Manuscript, Available Online from 01 December 2019
Abstract
A combination of high performance size exclusion chromatography with organic carbon detector and ultraviolet detector coupled with peak-fitting technique and fluorescence excitation-emission matrix spectrometry applied fluorescence regional integration method was conducted to determine the characteristics ...
Read More
A combination of high performance size exclusion chromatography with organic carbon detector and ultraviolet detector coupled with peak-fitting technique and fluorescence excitation-emission matrix spectrometry applied fluorescence regional integration method was conducted to determine the characteristics of organic matter during nitrification. The batch scale of bionet nitrification without organic carbon substrate under aerobic conditions was operated for around 150 minutes. Bulk organic parameters and NH4+-N concentration were analyzed. Five different molecular weights of organic matter were identified by using chromatography, and five different groups of fluorophores organic fractions detected by fluorescence. According to chromatography with carbon and ultraviolet detector, the main characteristics of organic matter shifted from building blocks aromatic compounds with percentage peak area of carbon/ultraviolet detector: 31%/53% to 14%/27.5% to humic-like substances with percentage peak area of carbon/ultraviolet detector 21%/17% to 27%/46.5% during nitrification. Those former compounds are biodegradable as well as properties of microbial products released during substrate utilization and endogenous phase, which are mainly identified as humic-like substances, thus underwent further biodegradation. However, there was significant change in the fluorophores organic fractions, which exhibited humic acid-like with percentage fluorescence regional index area 53% into 68%, as shown by fluorescence excitation-emission matrix analysis. A combination of these methods indicated that the organic matter released during nitrification mainly consists of humic compounds. These results conjecture that a combination of high performance size exclusion chromatography with carbon and ultraviolet detector and fluorescence excitation-emission matrix can be used to determine the characteristic of organic matter and water quality change during nitrification.
ORIGINAL RESEARCH PAPER
Urban and built environmental management
H.A. Khawaldah; I. Farhan; N.M. Alzboun
Articles in Press, Accepted Manuscript, Available Online from 07 December 2019
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 ...
Read More
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.
ORIGINAL RESEARCH PAPER
Sustainable agriculture management
V. Shcherbak; L. Ganushchak-Yefimenko; O. Nifatova; N. Fastovets; G. Plysenko; L. Lutay; V. Tkachuk; O. Ptashchenko
Articles in Press, Accepted Manuscript, Available Online from 11 December 2019
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 ...
Read More
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.
EndNote