Environmental Engineering
H. Herdiansyah; E. Frimawaty
Abstract
BACKGROUND AND OBJECTIVES: From August to October 2019, several provinces in Sumatra and Kalimantan had faced severe forest fires, causing thousands of citizens to suffer respiratory disorders. This study aims to assess waste handling in palm oil plantation manage by smallholders and the correlation ...
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BACKGROUND AND OBJECTIVES: From August to October 2019, several provinces in Sumatra and Kalimantan had faced severe forest fires, causing thousands of citizens to suffer respiratory disorders. This study aims to assess waste handling in palm oil plantation manage by smallholders and the correlation palm oil plantation waste handling with the fireland in Sumatera, especially on Jambi province.METHODS: Primary data collection was conducted in September 2019, and a purposive random sampling method was used to select respondents. Primary data collection was applied for four hundred smallholders in five districts in Jambi using a mixed method. FINDINGS: Out of 400 correspondents that handle their waste, 50% of respondents handle the residues by stacking the waste on their field, 25% of correspondents stack the waste between trees, 17.25% of correspondents stack the waste on piles, 5% of them bury the posts, and 2.75% incinerate the waste. The average distance from home to the field for 200 correspondents is 8.825 kilometres, and they have the highest harvest quantity with a mean of 1.0940 tons. Most of them are common smallholders and self-subsistent smallholders. The 298 correspondents join a farming association. About 50% of smallholders in Jambi handle the residues by stacking the wastes on their field instead of incinerating the waste. CONCLUSION: Out of the overall samples collected in this study, only 2.75% smallholders in Jambi incinerate their residues. Hence, the fire breakouts happened on several provinces in Sumatera and Kalimantan in late 2019 did not happen due to crude palm oil waste-handling activities.
J.A. Araiza-Aguilar; M.N. Rojas-Valencia; R.A. Aguilar-Vera
Abstract
The objective of this study was to develop a forecast model to determine the rate of generation of municipal solid waste in the municipalities of the Cuenca del Cañón del Sumidero, Chiapas, Mexico. Multiple linear regression was used with social and demographic explanatory variables. The ...
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The objective of this study was to develop a forecast model to determine the rate of generation of municipal solid waste in the municipalities of the Cuenca del Cañón del Sumidero, Chiapas, Mexico. Multiple linear regression was used with social and demographic explanatory variables. The compiled database consisted of 9 variables with 118 specific data per variable, which were analyzed using a multicollinearity test to select the most important ones. Initially, different regression models were generated, but only 2 of them were considered useful, because they used few predictors that were statistically significant. The most important variables to predict the rate of waste generation in the study area were the population of each municipality, the migration and the population density. Although other variables, such as daily per capita income and average schooling are very important, they do not seem to have an effect on the response variable in this study. The model with the highest parsimony resulted in an adjusted coefficient of 0.975, an average absolute percentage error of 7.70, an average absolute deviation of 0.16 and an average root square error of 0.19, showing a high influence on the phenomenon studied and a good predictive capacity.
M. Camara; N.R.B. Jamil; F.B. Abdullah
Abstract
Rapid development and population growth have resulted in an ever-increasing level of water pollution in Malaysia. Therefore, this study was conducted to assess water quality of Selangor River in Malaysia. The data collected under the river water quality monitoring program by the Department of environment ...
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Rapid development and population growth have resulted in an ever-increasing level of water pollution in Malaysia. Therefore, this study was conducted to assess water quality of Selangor River in Malaysia. The data collected under the river water quality monitoring program by the Department of environment from 2005 to 2015 were used for statistical analyses. The local water quality indices were computed and a trend detection technique and cluster analysis were applied, respectively, to detect changes and spatial disparity in water quality trends. The results showed that the river water is of good quality at all stations, with the exception of 1SR01 and 1SR09 located upstream, which recorded moderate water quality indices of 68 and 71, respectively. The results of trend analysis showed downward trends in dissolved oxygen, biochemical oxygen demand and ammonia nitrogen, for most water quality stations, as well as increasing trends in chemical oxygen, suspended solids, pH and temperature for most stations. In addition, the results of cluster and time series analyses showed that the trend variation in dissolved oxygen, pH, and temperature between the station clusters is relatively low as compared to chemical oxygen demand, biochemical oxygen demand, suspended solids, and ammonia nitrogen. With the peak concentration of 13 mg/L for dissolved oxygen observed in cluster 2 in 2014, and the highest decrease in suspended solids (8 mg/L) observed in cluster 1 for 2015. This finding demonstrates that these combined statistical analyses can be a useful approach for assessing water quality for adequate management of water resources.
G.A. Aliyu; N.R.B. Jamil; M.B. Adam; Z. Zulkeflee
Abstract
The analysis of changes in water quality in a monitoring network system is important because the sources of pollution vary in time and space. This study utilized analysis of the water quality index calculation, hierarchical cluster analysis, and mapping. This was achieved by assessing the water quality ...
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The analysis of changes in water quality in a monitoring network system is important because the sources of pollution vary in time and space. This study utilized analysis of the water quality index calculation, hierarchical cluster analysis, and mapping. This was achieved by assessing the water quality parameters of the samples collected from Galma River in Zaria, Northwestern Nigeria in wet and dry seasons. The Analysis shows that sampling point number 15 located downstream of the river has the largest number of water quality index of 105.77 and 126.34, while sampling points 1 located upstream of the river has 62.71 and 78.09 in both wet and dry seasons respectively. This indicates that all the monitoring sites were polluted and the water could be utilized for industrial and irrigation specified due to the purposes only. Hierarchical cluster analysis and mapping revealed consistency and variations. For both networks, cluster 1 is located in the middle of the river watershed, while clusters 2, 3 and 4 show variations within the river watershed. 3 sampling points in wet season located at the upstream of the river were specified for Irrigation and Industrial uses, while the rest of the sampling points in both seasons were specified for irrigation purpose only. From this study, water quality index and multivariate techniques for environmental management can be employed in monitoring river resources, and research of this kind can help inadequate planning and management of the river system.
