Macroalgae are often referred as seaweed and could be significant biomass resource for the production of numerous energy carriers including biofuels. In this study, the chemical composition of Gracilaria changii (G. changii) and Gelidium pusillum (G. pusillum)were determined through proximate and ultimate analysis and the thermal degradation behaviour of G. changii and G. pusillum were investigated via thermogravimetric analysis (TGA) in determining the important main composition to be considered as biomass fuels. It has found the pyrolysis of G. changii and G. pusillum consists of three stages and stage II is the main decomposition stage with major mass loss of around 52.16% and 44.42%, respectively. The TGA data were then used for determination of kinetic parameters of the pyrolysis process using three model-free methods: Kissinger, Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO). The apparent activation energy calculated by using Kissinger method for G. changii was lower than G. Pusillum, i.e.173.12 kJ/mol and 193.22 kJ/mol, respectively. The activation energies calculated from KAS and FWO methods were increased with increasing the pyrolysis conversion with average activation energies of 172.32 kJ/mol and 181.19 kJ/mol for G. changii while for G. pusillum (177.42 kJ/mol and 187.4 kJ/mol). G. pusillum has lower and wider distribution of activation energy and revealed that the pyrolysis process for G. changii was easier than G. pusillum. These data provide information for further application for designing and modelling in thermochemical conversion system of macroalgae biomass.
Preliminary pyrolysis studies of macroalgae biomass (Ulva cf. flexuosa and Hy. edulis) which were collected from several coastlines of Peninsular Malaysia were performed by using thermogravimetric analysis (TGA). The corresponding kinetic parameters were calculated through three model-free methods, namely Kissinger, Kissinger-Akahira-Sunose (KAS), and Flynn-Wall-Ozawa (FWO). The TGA curves of both species exhibited three degradation stages: dehydration, devolatilization, and residual decomposition. The devolatilization stage is where the main pyrolysis occurred at a temperature around 150-590oC and released the total volatiles of 56.93% and 54.92% for Ulva cf. flexuosa and Hy. Edulis. The calculation of activation energy from Kissinger method for Ulva cf. flexuosa was 180.24 kJ/mol while 194.86 kJ/mol for Hy. edulis. The apparent activation energies for KAS and FWO methods are increased by increasing the pyrolysis conversion with average activation energies of 241.17 kJ/mol and 253.65kJ/mol for Ulva cf. flexuosa, while for Hy. edulis, are 244.75 kJ/mol and 258.9 kJ/mol. This study provides the basis for the further application for designing and modeling in thermochemical conversion system of macro algae biomass.
14 October 2023 in Journal of Advanced Research in Applied Sciences and Engineering Technology
The new Covid-19 pandemic is affecting many economic sectors, such as the agricultural industry. The farmers faced many challenging constraints during the pandemic due to the enforcement of the Movement Control Order (MCO), resulting the unproductive crops. This paper proposed smart agriculture adopted with the Internet of Things (IoT) and Low Power Wide Area Networks (LPWAN) technology to be one of the possible solutions for the problems. Early precautions will minimize unproductive crops by monitoring the soil for healthy crops by monitoring the moisture and the pH level of the soil in real time. In this paper, a soil monitoring system using (Long-range) LoRa technology as one of the solutions for LPWAN to monitor the soil for agriculture has been set up. The soil moisture and pH sensors used to monitor the condition of the soil. The monitoring system uses LoRa as the communication network for the two sensors integrated into the Arduino Uno microcontroller as the transmitter and a receiver to monitor the status of the soil. This project enables the user to monitor the soil conditions and control the watering of the crops. The result concludes that this system shows 100% accuracy of the packet data received by the receiver, where the location of transmitter to the receiver was 1.4 meters apart.