Water pollution in rivers is still a crucial problem for the countries that use river water as the primary water source. This study aimed to determine the water quality of the Musi river and the content of heavy metals in water, sediment and mussels as well as to predict the water quality of the Musi river in the next five years. The water samples were taken from 18 stations (sampling points) from upstream to downstream to be checked physically, chemically and biologically. Prediction of the river water quality was made using the QUAL2Kw software. The research results show that the Musi River water is categorized as lightly polluted with concentrations of TSS and DO that have passed the threshold. The heavy metals in river water, such as Pb and Cr have also passed the quality standard. The Fe, Mn, and Zn concentrations are pretty high in the sediment. In turn, in mussels, the metals measured were Fe, Cu, and Zn. The prediction results reveal that several values of the river quality parameters will pass the threshold value with the same pattern tendency from each station.
It needs to become a source of renewable energy raw materials derived from biomass, through revegetation reclamation activities. Therefore, this study aims to analyze the differences in the quality of the wood pellets derived from distinguished raw materials and ages. It also aims to evaluate the relationship between raw material and wood pellet parameters. In this process, the method used emphasized the measurements of the chemical-physical and quality parameters of the materials and pellets, respectively. These analyses were subsequently carried out through a comparative test with the quality standards of SNI (Indonesian National Standard) 8021-2014 and SNI 01-6235-2000. To analyze the relationship between raw material and wood pellet quality parameters, a statistical test of Pearson correlation (product-moment) was conducted. Based on the results, the pellets produced from post-mining land revegetation reached SNI quality limits on the parameters of water content, density, fixed carbon, and heat. This proved that all the chemical-physical features of the raw materials had a relationship in improving the quality of wood pellets. Regarding the comparison between types, the Acacia mangium pellets relatively had the best quality.
This present study contribute to provide a simple technology to early detect the phenomenon of spontaneous coal combustion. A new prototype is designated to detect the CO gas formation as a product of initial coal oxidation. Moreover, several parameters including coal quality, coal weight sample, ambient temperature, and air flow were employed to investigate the effects of each parameter to the CO formation time. The results show that the coal characterisation have a significant effect in the CO formation time where the coal having a higher fixed carbon and high grass calorific values provide the high liability of spontaneous coal combustion. However, these finding only occurred in low weight sample where in the high coal weight sample only fixed carbon plays the main role in determining the CO formation time. Furthermore, the prototype ambient temperature become the important parameter in the boosting of CO formation time where airflow only enhance the CO formation time in low temperature condition (below 29°C). Moreover, these findings opens a new sight in coal management, especially in Indonesia, where controlling the coal and atmosphere temperature could effectively prevent the spontaneous coal combustion especially in coal stockpile. Nevertheless, the other factor including airflow and coal weight sample also need perfect controlling because all of these factors potentially create a perfect environment to combust the coal spontaneously.
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