Utilization of natural resources in the form of coal mines has a positive impact on economic and energy development, in addition to coal mining activities have a negative impact on the environment that result in environmental pollution in soil, water, and air. Pollution begins when clearing land, taking exploitation, transporting, stockpile and when the coal is burned. When land clearing causes damage to forest ecosystems. At the time of exploitation impact on air pollution by coal dust particles, the erosion, siltation of the river, the pollution of heavy metals and the formation of acid mine drainage (AMD). The high acid conditions cause the faster heavy metals such as Hg, Cd, Pb, Cr, Cu, Zn and Ni present in the coal dissolved and carried to the waters. Coal stockpile activity also causes pollution in the air, soil, and water. At the time the coal is burned as an energy source causes the emission of hazardous materials into the air of Hg, As, Se and CO 2 gas, NOx, SO 2. This condition has an impact on the environment and ultimately on human health.

Palm oil mill effluent (POME) contains high amounts of organic matter, potentially as a source of environmental pollution. The processing of POME in anaerobic ponds is produced by biomethane, which is a greenhouse gas and also is a potential as a renewable energy source. Indonesia is the world's largest CPO producer, but POME processing is still mostly done by conventional methods without methane capture. In this system, the value of methane emitted into the atmosphere is unknown. This research focused on estimating the methane emissions in anaerobic ponds (AP) multiple feeding wastewater treatment plants (WWTPs) for land applications, with CH 4-meter systems based on TGS2611 sensors, SHT11 and microcontrollers, and using closed static chambers. The sampling of wastewater and methane gas was carried out in October-November 2018. The results showed that the methane gas emissions in combined anaerobic ponds (AP2-AP1) and AP3 were 43,704 and 35,321 mg/m 2 /day respectively, and a total of 405.358 and 61.812 kg/day sequential on AP2-AP1 (9,275 m 2) and AP3 (1,750 m 2). It was obtained from the correlation between methane emissions with removed COD as a conversion coefficient of 0.2107 kg CH 4 /kg COD removed. On the basis of linear regression with R 2 0.9725, it was still below the theoretical value (stoichiometry) of 0.25 kg CH 4 /kg COD removed. From the conversion coefficient, COD removed, and the amount of POME in 2018, which was 104,179 m 3 , contributed to emitting 462 tons of methane from the entire anaerobic pond. This conversion coefficient can be used to quickly estimate the methane emissions in Indonesian palm oil mills.

A study on the adsorption of lead content in the leachate from the landfill by using solid waste of tofu. This study assed the effects of weight of the solid waste of tofu and the contact time on the efficiency of the Pb adsorption. The sample used in this study was artificial sample of a solution of Pb metal ion and the sample of the leachate of the landfill waste. The study was carried out with a batch system, with the variables of weight of waste of tofu of 0.5; 1.0; 1.5 g. While the variables of the contact time were 0, 30, 60, 90, 120 and 150 minutes. To determine the optimum conditions, the waste of tofu was dissolved in 50 mL of Pb metal ion solution with a concentration of 20.27 mg/L and stirred with a shaker for 30 minutes at a speed of 180 rpm. The same thing was done by varying the contact time. When the optimum condition was obtained, it was applied with varying concentrations of Pb metal ion solution and garbage landfill leachate. The initial and the final levels of the Pb metal ion solution were analyzed by using the Atomic Adsorption Spectroscopy (AAS). The initial and the final results of the heavy metals were analyzed for disclosing the adsorption efficiency. To reveal the effects of the weight of the waste of tofu and the contact time, the data were analyzed with graphs. The waste of tofu with a weight of 1.5 g and a contact time of 90 minutes, had an adsorption efficiency of 97.68% at a concentration of 20.27 mg / L for Pb ion solution and 28.57% for the leachate from the landfill waste in 100 mL of leachate. Abstrak (Indonesian):Telah dilakukan penelitian tentang adsorpsi kadar timbal dalam lindi dari sampah TPA dengan menggunakan limbah padat tahu. Penelitian ini akan mengkaji pengaruh berat ampas tahu dan waktu kontak terhadap efisiensi adsorpsi Pb. Sampel yang digunakan dalam penelitian ini adalah sampel buatan dari larutan ion logam Pb dan sampel dari lindi sampah TPA. Penelitian dilakukan dengan sistem batch, dengan variabel berat ampas tahu 0,5; 1,0; 1,5 g. Sedangkan variabel waktu kontak adalah 0, 30, 60, 90, 120 dan 150 menit. Untuk menentukan kondisi optimum, variabel berat ampas tahu dilarutkan dalam 50 ml larutan ion logam Pb dengan konsentrasi 20,27 mg/L lalu di aduk dengan shaker selama 30 menit dengan kecepatan 180 r.p.m. Hal yang sama dilakukan dengan variasi waktu kontak, setelah diperoleh kondisi optimum diaplikasikan dengan variasi konsentrasi larutan ion Pb dan lindi sampah TPA. Kadar larutan ion logam Pb awal dan akhir dianalisis dengan menggunakan Spektrofotometer Serapan Atom. Hasil awal dan akhir logam berat dianalisis untuk diketahui efisiensi adsorpsinya. Untuk mengetahui pengaruh berat ampas tahu dan waktu kontak data dianalisis dengan grafik. Ampas tahu dengan berat 1,5 g dan waktu kontak 90 menit, efisiensi adsorpsinya sebesar 97,68% pada konsentrasi 20,27 mg/L untuk larutan ion Pb dan 28,57% untuk lindi dari sampah TPA dalam 100 mL lindi. Kata kunci: limbah padat tahu, adsorben, adsorpsi, timbal, lindi.

Plant-based industries such as palm oil mills will generate wastewater rich in organic matter. Palm oil mill effluent (POME) treatment in Indonesia is still dominant with conventional methods without the capture of methane. This system does not know the value of methane emitted into the atmosphere. Measurement and testing of biomethane from anaerobic ponds of palm oil mills are relatively difficult because gas material is rapidly changing. An alternative methodology that is accurate through modeling with a radial basis function neural network (RBFNN) with abiotic variable input. The aim of this research is to find out an anaerobic pond methane emission model of POME and simulation to find out the dynamics of methane emissions. Methane emission data is measured by a TGS2611 methane gas sensor CH 4-meter system and using closed static chambers. A sampling of wastewater and methane gas was conducted in October-November 2018. The results showed that the methane gas emission model was obtained in the AP with RBFNN. The best RBFNN model had a 5-5-3 network architecture, spread 0.11 and error-goals 0.0005, R 0.940652 and MSE 0.003166. The reliability of RBFNN in determining models with non-linear field data variables was quite good, which was influenced by the number of data patterns, types and accuracy of the variables, network architecture, and the ANN model used. The simulation and prediction of methane emissions in the lowest-moderate-highest variable value scenario found that the COD-R and VS-R variables greatly affected the anaerobic pond WWTP emissions of multiple feeding systems. Even so, inlet wastewater temperature and rainfall variables had not significantly affected methane gas emissions, because the temperature was in a mesophilic range (30-40 o C) and the effect of rainfall would depend mainly on the high-low levels of organic matter (COD and VS).

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