Maejo International Journal of Energy and Environmental Communication

Influence of setting time and compressive strength for coal bottom ash as partial cement replacement in mortar

Mohammad I. Al Biajawi, Rahimah Embong — Sat, 23 Sep 2023 00:00:00 +0700

Environmental degradation from forestry practices to extract limestone from mountains, as well as subsequent calcination in cement factories and dumping of coal bottom ash (CBA) waste from thermal power plants, are among the wastes from industry. However, it is essential for the construction industry to look for sustainable solutions to mitigate the negative impact on the environment. In order to promote an environmentally friendly and sustainable ecosystem, the use of recycled CBA waste as a partial substitute for cement in the manufacturing process has significant potential to mitigate the environmental damage caused by the two distinct sectors of cement and waste management. A series of six mortar preparations were prepared, each containing varying percentages of CBA as a partial substitute for cement. The percentages used ranged from 0% to 50% by weight of cement. The time tests were performed on freshly prepared pastes. All samples were cured with water until the respective test time was reached. The experiment included the evaluation of the compressive strength of hardened mortar cubes at three different time intervals: 7, 14 and 28 days. The findings of the study demonstrate that the incorporation of CBA as a partial substitute for cement affects both the setting time and the compressive strength of the mortar. It has been shown that the use of up to 20% CBA as a cement replacement effectively increases the compressive strength of the mortar. Conclusively, the successful use of CBA as a partial substitute for cement in the manufacture of mortar has the potential to reduce the amount of cement consumed, eliminate the need for landfill space for waste disposal, and contribute to the production of a more sustainable environment, thereby promoting a better lifestyle for the surrounding population.

Predation properties of Rotifera Lecane isolated from an eutrophicated reservoir to toxic cyanobacteria Microcystis

Tue, 24 Oct 2023 00:00:00 +0700

A rotifer was isolated from a biofilm sample collected from a eutrophic reservoir in Kashima city, Saga, Japan. After morphological and molecular phylogenetic determination using 18S rRNA gene sequencing, the isolated rotifer was identified as a Lecane inermis. In a mixed culture of Lecane inermis and microcystin-producing toxic Microcystis aeruginosa (NIES102), the number of Microcystis cells decreased as the Lecane population increased. This suggests that Lecane preys on toxic Microcystis, resulting in a predator-prey interaction. By the 14th day of the mixed culture, 99.5% of the Microcystis cells were degraded. Data on the population dynamics of Lecane and Microcystis in this mixed culture were fitted to a predator-prey model, which was expressed by nonlinear differential equations. As a result, the model analysis suggested that Lecane could reveal the predation properties of Microcystis cells and may also consume bacteria as a food source. Lecane inermis is effective in promoting the degradation of microcystins (MCs) in the mixed culture. After 14 days of mixed culture, the degradation percentages of total MCs were 98.6% (MC-RR), 96.6% (MC-YR), and 93.9% (MC-LR).

Prediction of MBR operating parameter using LSTM neural network

Mon, 30 Oct 2023 00:00:00 +0700

This study investigated the forecasting ability of the long short-term memory neural network model (LSTM model), which is a type of recurrent neural network (RNN), for the dynamic character of membrane bioreactor (MBR). MBR is an advanced wastewater treatment system that combines activated sludge process with a membrane separation system. In this study, dissolved oxygen (DO), pH, trans membrane pressure (TMP), mixed liquor suspended solids (MLSS), and air flow rate of a bench-scale MBR were measured to obtain the time series data, and the time interval for each time series was unified to 1 hour. The training period of 640 hours was adopted for the LSTM model, and the remaining 160 hours were used as the testing period. The trained LSTM model predicted DO, pH, TMP, and MLSS one step ahead (one hour ahead), and multiple steps forecasts up to 6 hours ahead were also tested. The LSTM model succeeded in predicting MLSS one hour ahead with high accuracy. On the other hand, for DO and pH, the values predicted one hour ahead by the LSTM model reproduced their temporal fluctuation patterns to some extent. However, all of them tended to show predicted values that were lower than the actual values. The predicted values from the LSTM model did not reproduce the pattern of TMP changes well. In addition, the LSTM model was investigated the effect of forecasting horizons and look back period.

Organic farming management: A approach towards sustainable agriculture development towards green environment

Thu, 05 Oct 2023 00:00:00 +0700

This paper delves into the dynamic intersection of organic farming and technological innovation within the realm of sustainable agriculture. We explore the profound impact of modern technology on organic farming practices, shedding light on how precision agriculture, big data, and biotechnology are reshaping the organic landscape. Organic farming's integration of high-tech solutions not only enhances its eco-friendly credentials but also increases productivity and profitability. Furthermore, we embark on a journey into the future of sustainable agriculture, emphasizing the pivotal role of regenerative practices, agroforestry, and advanced technologies. The convergence of traditional wisdom and cutting-edge innovation holds the promise of nourishing a burgeoning global population while preserving the delicate balance of our planet's ecosystems. As we navigate the intricate tapestry of sustainable agriculture, one thing becomes clear: the future is bright, dynamic, and firmly rooted in our commitment to a healthier, more sustainable world.