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Estimasi Emisi Gas Rumah Kaca (GRK) di TPA Benowo Menggunakan Model LandGem: Estimation of Green House Gas (GHG) Emissions at Benowo Landfill Using the LandGem Model Rimadhani Prilindatami; Okik Hendriyanto Cahyonugroho
JURNAL SAINS TEKNOLOGI & LINGKUNGAN Vol. 9 No. 4 (2023): JURNAL SAINS TEKNOLOGI & LINGKUNGAN
Publisher : LPPM Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jstl.v9i4.518

Abstract

Greenhouse gases (GHG) are one of the dangerous gases that cause global warming. Greenhouse gases include methane gas and carbon dioxide. In large quantities, this gas can cause damage to the atmosphere. Greenhouse gas emissions are dominated by waste management activities at landfills. Benowo Landfill is one of the Landfills that manages the waste of the residents of Surabaya City. The more waste that is piled up in the landfill, the more gas is produced. So it is necessary to estimate the occurrence of methane gas and carbon dioxide gas in landfills. LandGem is a model that is able to estimate greenhouse gases that will appear in landfills. In this research, greenhouse gas estimates were carried out at the Benowo landfill using 3 scenarios. This scenario is applied to determine the influence of weather (k value) on the landfill. The results showed that scenario 3 which uses a k value of 0.7 (wet area) has the highest estimate of methane and carbon dioxide compared to the other scenarios, namely 6.801 x 107 m3/year. This happens because the k value means that the landfill area has high rainfall and there is a bioreactor or leachate circulation system. This value is considered a good value for bacterial growth in landfills.
Comparison of DAF Pretreatment between Static Mixer and Impeller Mixer for Oil and Grease Reduction Rizka Novembrianto; Firra Rosariawari; Okik Hendriyanto Cahyonugroho; Syadzadhiya Qothrunada Zakiyayasin Nisa'; Praditya Sigit Ardisty Sitogasa; Restu Hikmah Ayu Murti
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4107

Abstract

The problem of domestic wastewater originating from restaurants is the largest contributor to organic wastewater in urban waters. Among them are waste water parameters, namely oil, and grease. Oils and grease are compounds that do not dissolve easily in water. However, it can be dissolved with non-polar organic solvents. The carbon chains of oils and grease are also long. So, it is difficult to decompose and takes a long time if processing uses the help of microorganisms. So, the alternative is to use physical-chemical processing. In this research, we tried using a static mixer and an impeller mixer. We conducted a systematic review of DAF techniques in wastewater treatment. We reviewed six indexed databases namely dissolved air flotation, microbubbles, wastewater treatment, and key operational and design parameters involved in the effectiveness of the flotation process. In this pre-treatment, the focus is on the withdrawal/discharge speed in collecting wastewater as a test and the effectiveness of mixing wastewater with coagulants and air pressure. These three aspects are used in equilibrium to achieve the optimum dose for the static mixer use scheme. Meanwhile, the impeller mixer scheme uses rotational speed in mixing with the coagulant, contact time, and Reynolds number to achieve the required turbulence. Apart from that, the use of electrical energy in the pump is also calculated in these two schemes. The results obtained were the amount of weight of oil and grease collected in the static mixer pretreatment of 9.12% w/v and the impeller mixer of 7.63% w/v and the results of the organic content of the Chemical Oxygen Demand (COD) parameter for the static mixer were 86.92 % and mixer impeller 78.86 %. From these results, static mixers have advantages over using impeller mixers in terms of the effectiveness of the oil and grease reduction process.