TEKNOLOGI DAN METODE PENGOLAHAN LIMBAH CAIR SEBAGAI PENCEGAHAN PENCEMARAN LINGKUNGAN

Pengolahan limbah cair sebagai pencegahan pencemaran lingkungan, limbah cair memiliki tingkat pencemaran yang tinggi, limbah cair juga mempunyai kandungan BOD dan COD yang tinggi dan bila tidak diolah akan merusak lingkungan. Kegiatan pengolahan limbah cair bertujuan untuk mereduksi volume, agar mempermudah dalam penanganan dalam pengolahan selanjutnya. Pengolahan limbah cair harus dilengkapi dengan fasilitas yang menunjang sesuai dengan ketentuan, memenuhi frekuensi dalam pengambilan sampel limbah cair, memenuhi baku mutu efluen limbah cair, dan memenuhi penataan pelaporan hasil uji laboratorium limbah cair. Berbagai metode teknologi pengolahan limbah cair telah dikembangkan seperti elektrokoagulasi, advance oxidation process (AOP), reaktor microbial fuel cells (MFCs), elektrokoagulasi, proses film mikrobiologis (Biofilm), serta rotating biological contactors (RBC), Plasma Dielectric Barrier Discharge (DBD), teknologi membran.

Modeling of decolorisation dyes by ozonation techniques using Levenberg-Marquardt neural network

Acid Black 1 (AB1) and Acid Yellow 19 (AY19) are synthetic dyes widely used in industries such as textiles and cosmetics, which have complex structures. Special techniques are needed to degrade the dye before it goes out into the environment. One technique that has been done is to use Advance Oxidation Process (AOPs) using ozonation process. The process requires a combination of values of 4 parameters to obtain the optimum decolorization percentage. The parameters are dye concentration (mg / L), ozone concentration (mg / L), pH, and temperature (oC). In laboratory experiments to obtain a combination of parameters that yield the optimum decolorization percentage, requires relatively high time and cost. This research proposes modeling using Levenberg-Marquardt neural network (LM-NN) to obtain combination of parameters that can yield optimum decolorization percentage. The experimental results with the ozonation method obtained consecutive decolorization percentage values AB1 and AY19 were 93% and 98%. The percentage of decolorization was produced from a combination of 4 parameters, with values of 740 mg/L, 13 mg/L, 6.20, and 380C, while for the AY19 was 830 mg/L, 15 mg/L, 6.20, and 390C. The result of prediction of AB1 and AY19 by using LM-NN model in sequence is 95,25% and 99,99%. The condition was generated from the combination of the 4 parameters, for AB1 the values of each parameter were 707.50 mg/L, 12.70 mg/L, 7.50 and 380C, while the AY19 was 587.50 mg/L, 15.50 mg/L, 7,65, and 330C. The result of experimental and predicted using the LM-NN model, referring to statistical test results with 95% confidence level, indicating that the percentage of decolorization did not occur of difference significantly (p-value> 0.05), both for AB1 and AY19. It shows that modeling with LM-NN can be used to predict the optimum decolorization percentage with predetermined parameters.

Recovery Process of Condensate the Ammonia Wastewater Plant of PT.PIM with A Combination of Technology Air Stripping Jet Bubble Colum, Advance Oxidation process and Ion Exchange Resin

Study of reducing the content of ammonia, carbon dioxide and organic contaminants in wastewater process condensate using a combination of technologies of water Jet Stripping Bubble Colum, Advance Oxidation Process and Ion Exchange Resin have been done. The aims of this research is to look the effect of hydraulic resident time in Jet Stripping Bubble Colum and the amount of the addition of Ozon/H2O2 to reduction the content of carbon dioxide and organic contaminants as well as ammonia removal with ion exchange resin on the process condensate so that can be reuse as boiler feed water in ammonia plant of PT. PIM. This research was conducted using a combination Air Stripping Jet Bubble Colum, Advance Oxidation Process and Ion Exchange Resin which equipped with water and air flows adjustment. The water flow enter the column, pressure of the Colum and diameter of nozzle was maintained constantnts during experiment, while the air flow rate enter to the column, H2O2/O3 concentrations and the hydraulic retention time was vary respectively. The results showed that the water Jet Stripping Bubble Colum at 50 Psi air pressure capable of achieving CO2 lowers 87.60% and ammonia to 65.31%. AOP technology capable of lowering the content of organic contaminant to 80.71% with the addition of hydrogen peroxide 8,000 ppm with a residence time 180 minutes. While the ammonia remaining in the water the process of condensate action exchange resin using eliminated with a reduction of ammonia reached 98.57%, so that the recovery process of water condensate technology uses a combination of Air Stripping Jet Bubble Colum, Advance Hydrocarbon processes (AOP) and Ion Exchange Resins already meets the requirements of viable reuses boiler feed water. The ammonia reduction was determined by using ASTM-D 1426 method, the carbon dioxide by using ASTM-512 method, and the organic contaminants by using titrimetric method (SII-0071). Keyword : Air Stripping Jet Bubble Colum, Advance Oxidation Process (AOP), Ammonia Removal, Carbon Dioxide Removal.

Aplikasi Metode Advance Oxidation Process (AOP) Fenton pada Pengolahan Limbah Cair Pabrik Kelapa Sawit

Penelitian ini bertujuan untuk mengetahui kemampuan proses Fenton dalam menurunkan kadar chemical oxygen demand (COD) dan kadar total suspended solid (TSS) dari limbah cair pabrik kelapa sawit (PKS) dan menentukan kondisi optimum dari parameter yang digunakan dengan Response Surface Methodology menurut Box- Behnken design. Sampel diambil pada keluaran pertama kolam anaerobik ketiga dari instalasi pengolahan limbah cair kelapa sawit yang mengandung nilai COD berkisar antara 8.000 hingga 12.000 ppm. Pada penelitian ini, dilakukan pengujian pada berbagai pH, konsentrasi FeSO4.7H2O dan konsentrasi hidrogen peroksida. Hasil penelitian menunjukkan bahwa kemampuan proses AOP dengan metode Fenton dapat menurunkan konsentrasi COD dan TSS masing-masing adalah 70,7704% dan 88,3897% pada konsentrasi FeSO4.7H2O 3703,52 ppm, konsentrasi H2O2 5586,43 ppm, dan pH 3.