258 research outputs found
Sistem Informasi Akuntansi Atas Penagihan dalam Menunjang Keefektifan Penerimaan Kas pada PT. Fadel Pelumas Indonesia
No full textPenelitian ini bertujuan Untuk mengetahui system informasi akuntansi atas penagihan piutang dalam menunjang keefektifan penerimaan kas pada PT. Fadel Pelumas Indonesia. Penelitian ini menggunakan analisis data deskriptif kualitatif. Penelitian dilakukan di PT. Fadel Pelumas Indonesia. Hasil penelitian . PT. Fadel Pelumas Indonesia telah menerapkan sistem informasi akuntansi dengan tepat dalam proses penjualan dan penagihan piutang. Metode dan tekhnologi informasi yang digunakan sangat mendukung keefektifan dalam penerimaan kas. Sistem pengendalian intern cukup memadai dalam operasional kegiatan Perusahaan. This study aims to determine the accounting information system for collection of accounts receivable in supporting the effectiveness of cash receipts at PT. Fadel Indonesian Lubricants. This study uses qualitative descriptive data analysis. The research was conducted at PT. Fadel Indonesian Lubricants. Research result. PT. Fadel Pelumas Indonesia has implemented an accounting information system appropriately in the process of selling and collecting receivables. The methods and information technology used strongly support the effectiveness of cash receipt
TINGKAT MOTIVASI BELAJAR SISWA PASCA COVID-19 PADA MATA PELAJARAN PENDIDIKAN AGAMA ISLAM DISEKOLAH MENENGAH ATAS NEGERI 12 PEKANBARU
No full textABSTRAK
Muhammad Fadel Rahman, (2023): Perbedaan Motivasi Belajar Siswa Masa Covid-19 dengan Pasca Covid-19 pada Mata Pelajaran Pendidikan Agama Islam di Sekolah Menengah Atas Negeri 12 Pekanbaru.
Penelitian ini bertujuan untuk mengetahuiperbedaan motivasi belajar Pendidikan Agama Islam pada masa covid-19 dengan pasca covid-19 di SekolahMenengah Atas Negeri 12 Pekanbaru. Subjek penelitian ini peserta didik SMAN 12 Pekanbaru tahun ajaran 2023/2024. Objek penelitian ini adalahmotivasi belajar siswa pada mata pelajaran Pendidikan Agama Islam di SMAN 12 Pekanbaru. Jenis penelitian ini ialah Kuantitatif. Populasi penelitian ini adalah peserta didik SMAN 12 Pekanbaru yang berjumlah 204 orang dan sampel penelitian berjumlah 102 orang. Teknik pengambilan sampel menggunakan Purposive Sampling. Teknik pengumpulan data menggunakan metode observasi, angket, dan dokumentasi. Teknik analisis data menggunakan uji-t. Berdasarkan hasil analisis data diperoleh bahwa adanya perbedaan signifikasi motivasi belajar pada mata pelajaran Pendidikan Agama Islam masa covid dan pasca covid. Dibuktikan dengan nilai thitung lebih besar dari ttabel pada taraf signifikansi 5%, 11,263 > 1,983. Mean skor siswapasca covid ialah 36,07 lebih tinggi dibandingkan mean skor siswa masa covid ialah 30,63.
Kata Kunci: Masa Covid-19, Pasca Covid-19, Motivasi Belaja
A comparative examination of MBR and SBR performance for the treatment of high-strength landfill leachate
No full textThe management of landfill leachate is challenging, with relatively limited work targeting high-strength leachate. In this study, the performance of the membrane bioreactor (MBR) and sequencing batch reactor (SBR) technologies are compared in treating high-strength landfill leachate. The MBR exhibited a superior performance with removal efficiencies exceeding 95percent for BOD5, TN, and NH3 and an improvement on SBR efficiencies ranging between 21 and 34percent. The coupled experimental results contribute in filling a gap toward improving the management of high-strength landfill leachate and providing comparative guidelines or selection criteria and limitations for MBR and SBR applications. While the sequencing batch reactor (SBR) technology offers some flexibility in terms of cycle time and sequence, its performance is constrained when considering landfill leachate associated with significant variations in quality and quantity. Combining membrane separation and biodegradation processes or the membrane bioreactor (MBR) technology improved removal efficiencies significantly. In the context of leachate management using the MBR technology, more efforts have targeted low-strength leachate with limited attempts at moderate to high strength leachate. In this study, the SBR and MBR technologies were tested under different operating conditions to compare and evaluate their feasibility for the management of high-strength leachate from a full-scale operating landfill. Such a comparison has not been reported for high-strength leachate. © 2014 Copyright © 2014 Aandamp;WMA.Afsharnia M, 2012, DESALIN WATER TREAT, V48, P344, DOI 10.1080-19443994.2012.702959; Ahmed FN, 2012, DESALINATION, V287, P41, DOI 10.1016-j.desal.2011.12.012; Ahn WY, 2002, DESALINATION, V149, P109, DOI 10.1016-S0011-9164(02)00740-3; Aloui F, 2009, WATER SCI TECHNOL, V60, P605, DOI 10.2166-wst.2009.377; APHA AWWA WPCF, 2005, STANDARD METHODS EXA; Aziz SQ, 2011, DESALINATION, V277, P313, DOI 10.1016-j.desal.2011.04.046; Bai Y., 2011, 3 INT C MEAS TECHN M, V1, P183, DOI DOI 10.1109-ICMTMA.2011.51; Berube P, 2010, SUSTAIN SCI ENG, V2, P255, DOI 10.1016-S1871-2711(09)00209-8; Bilad MR, 2011, SEP PURIF TECHNOL, V78, P105, DOI 10.1016-j.seppur.2010.12.005; Bodzek M, 2006, DESALINATION, V198, P16, DOI 10.1016-j.desal.2006.09.004; Campagna M, 2013, WASTE MANAGE, V33, P866, DOI 10.1016-j.wasman.2012.12.010; Cecen F, 2004, ENVIRON ENG SCI, V21, P303, DOI 10.1089-109287504323066941; Cecen F, 2001, BIOTECHNOL LETT, V23, P821, DOI 10.1023-A:1010317823529; Chen SH, 2006, CHINESE SCI BULL, V51, P2831, DOI 10.1007-s11434-006-2177-y; Clement B., 1995, P SARD 95 5 INT LAND, P315; ElFadel M, 1997, ENVIRON TECHNOL, V18, P669, DOI 10.1080-09593331808616586; El-Fadel M, 1999, ENVIRON TECHNOL, V20, P121, DOI 10.1080-09593332008616802; El-Fadel M., 2003, ENV STUD A, V60, P603, DOI [10.1080-0020723032000069187, DOI 10.1080-0020723032000069187]; El-Fadel M, 2002, WASTE MANAGE, V22, P269, DOI 10.1016-S0956-053X(01)00040-X; El-Fadel M, 2000, CRIT REV ENV SCI TEC, V30, P327, DOI 10.1080-10643380091184200; Feki F, 2009, CHEMOSPHERE, V75, P256, DOI 10.1016-j.chemosphere.2008.12.013; Guo JS, 2010, J HAZARD MATER, V178, P699, DOI 10.1016-j.jhazmat.2010.01.144; Ince M, 2010, DESALINATION, V255, P52, DOI 10.1016-j.desal.2010.01.017; Jakopovic HK, 2008, FRESEN ENVIRON BULL, V17, P687; Jia H., 2009, INT C EN ENV TECHN I; Klimiuk E, 2006, WASTE MANAGE, V26, P1140, DOI 10.1016-j.wasman.2005.09.011; Kulikowska D, 2007, BIORESOURCE TECHNOL, V98, P1426, DOI 10.1016-j.biortech.2006.05.021; Laitinen N, 2006, DESALINATION, V191, P86, DOI 10.1016-j.desal.2005.08.012; Lin SH, 2000, WATER RES, V34, P4243, DOI 10.1016-S0043-1354(00)00185-8; Loizidou M, 1992, FRESEN ENVIRON BULL, V1, P748; Ministry of Environment, 2001, STAND DISCH SURF WAT; Monclus H, 2009, ENVIRON TECHNOL, V30, P283, DOI 10.1080-09593330802622105; Neczaj E, 2005, DESALINATION, V185, P357, DOI 10.1016-j.desal.2005.04.044; Nurisepehr M, 2012, WASTE MANAGE RES, V30, P883, DOI 10.1177-0734242X11433526; Puszczalo E, 2010, DESALIN WATER TREAT, V14, P16, DOI 10.5004-dwt.2010.1066; Renou S, 2008, J HAZARD MATER, V150, P468, DOI 10.1016-j.jhazmat.2007.09.077; Rodriguez DC, 2011, DESALINATION, V273, P447, DOI 10.1016-j.desal.2011.01.068; Santos A., 2010, DESALINATION, V273, P148, DOI 10.1016-j.desal.2010.07.063; Sethi S, 2013, INT J ENVIRON POLLUT, V51, P57, DOI 10.1504-IJEP.2013.053175; Singh M, 2011, ASIA-PAC J CHEM ENG, V6, P3, DOI 10.1002-apj.490; Tatsi AA, 2002, ADV ENVIRON RES, V6, P207, DOI 10.1016-S1093-0191(01)00052-1; Trabelsi I, 2013, ARAB J GEOSCI, V6, P2071, DOI 10.1007-s12517-011-0464-7; Trebouet D, 2001, WATER RES, V35, P2935, DOI 10.1016-S0043-1354(01)00005-7; Tsilogeorgis J, 2008, DESALINATION, V221, P483, DOI 10.1016-j.desal.2007.01.109; Tsonis S., 1998, P PROT REST ENV 4 HA, P667; Uygur A, 2004, J ENVIRON MANAGE, V71, P9, DOI 10.1016-j.jenvman.2004.01.002; Visvanathan C, 2007, DESALINATION, V204, P8, DOI 10.1016-j.desal.2006.02.028; Xiu-Fen L, 2011, ENVIRON CHEM LETT, V9, P71, DOI 10.1007-s10311-009-0248-4; Zhang J, 2007, DESALINATION, V207, P153, DOI 10.1016-j.desal.2006.07.009; Zouboulis AI, 2001, CHEMOSPHERE, V44, P1103, DOI 10.1016-S0045-6535(00)00343-X0
Enhanced solid waste stabilization in aerobic landfills using low aeration rates and high density compaction
No full textHistorically, municipal solid waste landfills have been designed and operated as storage facilities with suboptimal degradation under anaerobic conditions resulting in slow waste stabilization, gaseous emissions and leachate formation. This article examines the aerobic bioreactor alternative combining the recirculation of high strength leachate [chemical oxygen demand (COD): 89,000-95,600 mg-l; biological oxygen demand (BOD): 75,700-80,000 mg-l)] with low aeration rates (0.0125-0.05 l-min.kg) at high initial waste compaction (657-875 kg-m3) to promote and control biodegradation of solid waste in laboratory-scale columns (diameter = 60 cm, height = 1 m). Low aeration rates coupled with high initial density demonstrated improved performance with increased levels of stabilization with COD and BOD attenuation reaching up to 96percent, final C:N ratio of 25 and waste settlement up to 55percent. © The Author(s) 2013.Abichou T, 2006, WASTE MANAGE, V26, P1305, DOI 10.1016-j.wasman.2005.11.016; APHA, 1998, STANDARD METHODS EXA; Ballik I., 2009, CDM INVESTMENT NEWSL; Berge ND, 2005, CRIT REV ENV SCI TEC, V35, P365, DOI 10.1080-10643380590945003; Bilgili MS, 2007, J HAZARD MATER, V143, P177, DOI 10.1016-j.jhazmat.2006.09.012; Bilgili MS, 2007, J HAZARD MATER, V145, P186, DOI 10.1016-j.jhazmat.2006.11.014; Bilgili MS, 2006, ENVIRON MANAGE, V38, P189, DOI 10.1007-s00267-005-0179-1; Borglin SE, 2004, J AIR WASTE MANAGE, V54, P815; Borjesson G, 2000, ENVIRON SCI TECHNOL, V34, P4044, DOI 10.1021-es991350s; Donovan SM, 2010, SCI TOTAL ENVIRON, V408, P1979, DOI 10.1016-j.scitotenv.2009.12.011; Edgers L., 1992, P MED C ENV GEOT CES, P177; ElFadel M, 1997, J ENVIRON MANAGE, V50, P1, DOI 10.1006-jema.1995.0131; El-Fadel M, 2002, WASTE MANAGE, V22, P269, DOI 10.1016-S0956-053X(01)00040-X; El-Fadel M., 2001, MUNICIPAL SOLI UNPUB; El-Fadel M, 2000, CRIT REV ENV SCI TEC, V30, P327, DOI 10.1080-10643380091184200; Erses AS, 2008, BIORESOURCE TECHNOL, V99, P5418, DOI 10.1016-j.biortech.2007.11.008; Fricke K, 2005, WASTE MANAGE, V25, P799, DOI 10.1016-j.wasman.2004.12.018; Giannis A, 2008, WASTE MANAGE, V28, P1346, DOI 10.1016-j.wasman.2007.06.024; Hanashima M., 1999, P SARD 99 7 INT WAST, P313; He PJ, 2011, J ENVIRON SCI-CHINA, V23, P1011, DOI 10.1016-S1001-0742(10)60574-8; Hossain M. S., 2010, Geotechnical and Geological Engineering, V28, DOI 10.1007-s10706-009-9299-3; Hossain MS, 2003, J GEOTECH GEOENVIRON, V129, P1151, DOI 10.1061-(ASCE)1090-0241(2003)129:12(1151); IPCC, 2007, CLIM CHANG 2007 PHYS; Ishigaki T, 2005, ENVIRON GEOL, V48, P845, DOI 10.1007-s00254-005-0008-0; Jun D, 2007, J HAZARD MATER, V147, P240, DOI 10.1016-j.jhazmat.2007.01.001; Kim H., 2005, THESIS U FLORIDA US; Kossoy A., 2010, STATE TRENDS CARBON; Kumar S, 2011, CRIT REV BIOTECHNOL, V31, P77, DOI 10.3109-07388551.2010.492206; Larson D. F., 2008, 4761 WORLD BANK DEV; Li XJ, 2008, BIORESOURCE TECHNOL, V99, P359, DOI 10.1016-j.biortech.2006.12.009; Liu CF, 2008, BIORESOURCE TECHNOL, V99, P882, DOI 10.1016-j.biortech.2007.01.013; Mackie KR, 2009, ENVIRON MODELL SOFTW, V24, P1223, DOI 10.1016-j.envsoft.2009.04.003; Mehta R, 2002, J ENVIRON ENG-ASCE, V128, P228, DOI 10.1061-(ASCE)0733-9372(2002)128:3(228); Mertoglu B, 2006, PROCESS BIOCHEM, V41, P2359, DOI 10.1016-j.procbio.2006.06.014; Nikolaou A, 2010, ENVIRON TECHNOL, V31, P1381, DOI 10.1080-09593331003743104; Peterson C, 2009, CDM INVESTMENT NEWSL; Price GA, 2003, WASTE MANAGE, V23, P675, DOI 10.1016-S0956-053X(03)00104-1; Rendra S, 2007, ENVIRON TECHNOL, V28, P609, DOI 10.1080-09593332808618822; Rich C, 2008, WASTE MANAGE, V28, P1039, DOI 10.1016-j.wasman.2007.03.022; Spokas K, 2003, WASTE MANAGE, V23, P599, DOI 10.1016-S0956-053X(03)00102-8; Tchobanoglous G., 1993, INTEGRATED SOLID WAS; Thompson S, 2009, WASTE MANAGE, V29, P2085, DOI 10.1016-j.wasman.2009.02.004; Unnikrishnan, 2010, RESOURCES CONSERVATI, V54, P630; Vigneron V, 2005, WATER SCI TECHNOL, V52, P289; Warith M, 2002, WASTE MANAGE, V22, P7, DOI 10.1016-S0956-053X(01)00014-9; Warith M., 2003, EMIRATES J ENG RES, V8, P61; Yang YF, 2012, WASTE MANAGE RES, V30, P255, DOI 10.1177-0734242X11413328; Zhang HH, 2008, ATMOS ENVIRON, V42, P5579, DOI 10.1016-j.atmosenv.2008.03.01011
Variation of selected air quality indicators over the city of Beirut, Lebanon: Assessment of emission sources
No full textIt is well established that the Mediterranean region experiences high pollution episodes as a result of its closed location and hot-humid long summers. However, few long-term field measurements have been conducted along the Eastern Mediterranean coast in general and in Arab countries, in particular. Hence, a six-month field study of major indicators like CO, SO2, PM10 and O3 were conducted in Beirut, Lebanon. Measurements on an upwind site showed that the monthly average concentrations of CO, SO2 and O3 were lower than the USEPA air quality standards while the monthly average concentrations of PM10 were higher. Diurnal variations showed that vehicle-induced emissions contribute significantly to CO levels while winter heaters constitute the major source of SO2. High diurnal and nocturnal levels of PM10 and O3 are the results of several local and long-range transport phenomena. © 2006 Elsevier Ltd. All rights reserved.Chaloulakou A, 2003, CHEMOSPHERE, V52, P1007, DOI 10.1016-S0045-6535(03)00263-7; Chaloulakou A, 2003, ATMOS ENVIRON, V37, P649, DOI 10.1016-S1352-2310(02)00898-1; Duenas C, 2002, SCI TOTAL ENVIRON, V299, P97, DOI 10.1016-S0048-9697(02)00251-6; Elbir T, 2000, ENVIRON INT, V26, P5, DOI 10.1016-S0160-4120(00)00071-4; El-Fadel M., 2002, ENV STUDIES A, V13, P471, DOI [10.1108-09566160210441780, DOI 10.1108-09566160210441780]; ELFADEL M, 2000, J TRANSPORTATION STA, V3, P85; El-Fadel M, 1999, TRANSPORT RES D-TR E, V4, P251, DOI 10.1016-S1361-9209(99)00008-5; El-Fadel M, 2000, SCI TOTAL ENVIRON, V257, P133, DOI 10.1016-S0048-9697(00)00503-9; El-Fadel M, 2001, ENERG POLICY, V29, P1031, DOI 10.1016-S0301-4215(01)00033-7; El-Hougeiri N, 2004, INDOOR BUILT ENVIRON, V13, P421, DOI 10.1177-1420326X04049344; Erduran AS, 2001, SCI TOTAL ENVIRON, V281, P205; Finlayson-Pitts B.J., 2000, CHEM UPPER LOWER ATM; Ganor E, 2000, ATMOS ENVIRON, V34, P3453, DOI 10.1016-S1352-2310(00)00077-7; Glavas S, 1999, ATMOS ENVIRON, V33, P3813, DOI 10.1016-S1352-2310(98)00393-8; Graham B, 2004, ATMOS ENVIRON, V38, P1593, DOI 10.1016-j.atmosenv.2003.12.015; Hashisho Z, 2004, ENVIRON MONIT ASSESS, V93, P185, DOI 10.1023-B:EMAS.0000016804.88534.34; He LY, 2004, ATMOS ENVIRON, V38, P6557, DOI 10.1016-j.atmosenv.2004.08.034; Kalabokas PD, 2000, ATMOS ENVIRON, V34, P5199, DOI 10.1016-S1352-2310(00)00298-3; Kourtidis KA, 2002, ATMOS ENVIRON, V36, P5355, DOI 10.1016-S1352-2310(02)00580-0; Kouvarakis G, 2000, J GEOPHYS RES-ATMOS, V105, P4399, DOI 10.1029-1999JD900984; Latha KM, 2004, ATMOS RES, V71, P265, DOI 10.1016-j.atmosres.2004.06.004; Lee SC, 2001, SCI TOTAL ENVIRON, V279, P181, DOI 10.1016-S0048-9697(01)00765-3; Lelieveld J, 2002, SCIENCE, V298, P794, DOI 10.1126-science.1075457; Liu YS, 2004, ENVIRON INT, V30, P189, DOI 10.1016-S0160-4120(03)00173-9; MOUSSA SG, 2005, IN PRES ATMOSPHERIC; Riga-Karandinos AN, 2005, CHEMOSPHERE, V59, P1125, DOI 10.1016-j.chemosphere.2004.11.059; Tov DA, 1997, ATMOS ENVIRON, V31, P1441; Tsitouridou R, 2003, CHEMOSPHERE, V52, P883, DOI 10.1016-S0045-6535(03)00313-8; Varinou M, 1999, PHYS CHEM EARTH PT C, V24, P507, DOI 10.1016-S1464-1917(99)00081-117202
Simulating industrial emissions using Atmospheric Dispersion Modeling System: Model performance and source emission factors
No full textIn this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM10) and sulfur dioxide (SO2)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement 'd' values reaching 0.58, fractional bias 'FB' and geometric mean bias 'MG' values approaching 0 and 1, respectively, and normalized mean square error 'NMSE' values as low as 2.17. However, median ratios of predicted to observed concentrations 'Cp-Co' at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NOX, CO, PM10 and SO2, respectively, and the fraction of predictions within a factor of two of observations 'FAC2' values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability. Implications: In the absence of site-specific source emission factors, the use of internationally reported emission factors without testing their validity may generate significant errors. Instead, recorded field measurements and meteorological data may be combined with atmospheric transport and dispersion models to better estimate source emissions, particularly in regulatory compliance studies. In this context, lower model performance is expected at higher wind speeds for most indicators such as CO, PM10, and SO2. © 2012 Aandamp;WMA.Barratt R, 2001, BUSINESS ENV PRACTIT; Cambridge Environmental Research Consultants (CERC), 2007, ADMS4 ATM DISP MOD S; Carruthers D., 2008, P 12 INT C HARM CAVT; Carruthers D, 2010, ADMS US GROUP M VILN; Chang JC, 2004, METEOROL ATMOS PHYS, V87, P167, DOI 10.1007-s00703-003-0070-7; EEA (European Environment Agency), 2009, 92009 EEA; El-Fadel M, 2001, ENERG POLICY, V29, P1031, DOI 10.1016-S0301-4215(01)00033-7; El-Fadel M, 2009, ATMOS ENVIRON, V43, P5015, DOI 10.1016-j.atmosenv.2009.06.056; Environmental Protection Agency (EPA), 2009, AIR DISP MO IN PRESS; Hanna SR, 2001, INT J ENVIRON POLLUT, V16, P301; Hill R., 2003, CLEAN AIR, V33, P44; Holmes NS, 2006, ATMOS ENVIRON, V40, P5902, DOI 10.1016-j.atmosenv.2006.06.003; Irwin JS, 2003, INT J ENVIRON POLLUT, V20, P4; Kukkonen J, 2001, ATMOS ENVIRON, V35, P949, DOI 10.1016-S1352-2310(00)00337-X; Leroy C, 2010, J ENVIRON RADIOACTIV, V101, P937, DOI 10.1016-j.jenvrad.2010.06.011; Mazzoldi A., 2009, ATMOS ENVIRON, V42, P8046; Oettl D, 2001, ATMOS ENVIRON, V35, P2123, DOI 10.1016-S1352-2310(00)00492-1; Rigby M, 2008, ATMOS ENVIRON, V42, P4932, DOI 10.1016-j.atmosenv.2008.02.031; Righi S, 2009, ATMOS ENVIRON, V43, P3850, DOI 10.1016-j.atmosenv.2009.05.016; US Environmental Protection Agency, 1994, AP42 OFF AIR QUAL PL; VENKATRAM A, 1994, ATMOS ENVIRON, V28, P3665, DOI 10.1016-1352-2310(94)00190-V22
Determinants of optimal aerobic bioreactor landfilling for the treatment of the organic fraction of municipal waste
No full textHistorically, municipal solid waste landfills have been designed and operated as disposal facilities with suboptimal degradation under anaerobic conditions, resulting in slow waste stabilization and generation of landfill gas rich in methane and high strength leachate. Recently, aerobic bioreactor landfilling is being promoted as a promising method that enhances waste stabilization while producing a relatively weaker leachate and no methane generation. The authors review transformation processes and benefits associated with aerobic bioreactor landfilling. Factors affecting the operation of aerobic bioreactor landfills were detailed and performance indicators were defined with technical and operational considerations. 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Pressure transient analysis to investigate a coupled fracture corridor and a fault damage zone causing an early thermal breakthrough in the North Alpine Foreland Basin
No full textThe heterogeneity of the Upper Jurassic carbonate reservoir (Malm reservoir) beneath the North Alpine Foreland Basin has a significant influence on the mass and heat flow processes during geothermal exploitation. Geophysical borehole data revealed that sub-seismic scale fractures and karstified fractures occur at the inflow zones of deep geothermal wells. However, pressure transient analysis (PTA) in some previous studies concluded that it is difficult to detect the influence of sub-seismic scale features, suggesting that radial flow regime is dominant. Accordingly, a regional thermal-hydraulic model adopted the equivalent porous medium (EPM) approach, homogenizing the sub-seismic scale reservoir heterogeneities; however, unable to detect an early thermal breakthrough (ETB) in a geothermal doublet located SE of Munich. We apply PTA on three buildup tests belonging to that doublet following a deterministic approach to constrain the reservoir type by interpreting the pressure derivative (PD) plots constrained by geophysical and geological data. We derive the magnitudes of the reservoir hydraulic parameters by matching the PD plots with the selected interpretation models. We find that clustered fractures have a significant influence on the reservoir hydraulics, evidenced by trough-shaped curves in the PD plots. Linear flow regime interpreted from the interference test between the two wells indicates permeability anisotropy, which may have caused the ETB. Geophysical data interpretations indicate that these fractures correspond to a coupled fault damage zone and a fracture corridor. Finally, we present a fit-for-purpose 2D discrete fracture network model utilizing the PTA results to match our analytically calibrated model. Our study offers a potential hydraulic explanation to the cause of the ETB highlighting the importance of integrating multi-scale/disciplinary data sets to improve the reliability of dynamic reservoir models, based on which, economic-related decisions are made.Applied Geolog
Climate change and temperature rise: Implications on food- and water-borne diseases
No full textThis study attempts to quantify climate-induced increases in morbidity rates associated with food- and water-borne illnesses in the context of an urban coastal city, taking Beirut-Lebanon as a study area. A Poisson generalized linear model was developed to assess the impacts of temperature on the morbidity rate. The model was used with four climatic scenarios to simulate a broad spectrum of driving forces and potential social, economic and technologic evolutions. The correlation established in this study exhibits a decrease in the number of illnesses with increasing temperature until reaching a threshold of 19.2. °C, beyond which the number of morbidity cases increases with temperature. By 2050, the results show a substantial increase in food- and water-borne related morbidity of 16 to 28percent that can reach up to 42percent by the end of the century under A1FI (fossil fuel intensive development) or can be reversed to ~0percent under B1 (lowest emissions trajectory), highlighting the need for early mitigation and adaptation measures. © 2012 Elsevier B.V.[Anonymous], DIARRH DIS; Auld H, 2004, J TOXICOL ENV HEAL A, V67, P1879, DOI 10.1080-15287390490493475; Black R. E., 1995, INFECT GASTROINTESTI, P13; Cameron A. C., 1998, REGRESSION ANAL COUN; Checkley W, 2000, LANCET, V355, P442; Checkley W, 2003, AM J EPIDEMIOL, V157, P166, DOI 10.1093-aje-kwf179; Chou WC, 2010, SCI TOTAL ENVIRON, V409, P43, DOI 10.1016-j.scitotenv.2010.09.001; Dessai S, 2003, INT J BIOMETEOROL, V48, P37, DOI 10.1007-s00484-003-0180-4; D'Souza RM, 2008, EPIDEMIOL INFECT, V136, P56, DOI 10.1017-S0950268807008229; Ebi KL, 2008, GLOBALIZATION HEALTH, V4, DOI 10.1186-1744-8603-4-9; Ebi KL, 2010, CURR PROB PEDIATR AD, V40, P2, DOI 10.1016-j.cppeds.2009.12.001; El-Fadel M., 2003, Management of Environmental Quality, V14, P353, DOI 10.1108-14777830310479441; El-Fadel M., 2010, CLIMATE CHANGE RES C, P83; El-Zein A, 2004, SCI TOTAL ENVIRON, V330, P71, DOI 10.1016-j.scitotenv.2004.02.027; Evans JP, 2009, CLIMATIC CHANGE, V92, P417, DOI 10.1007-s10584-008-9438-5; Fleury M, 2006, INT J BIOMETEOROL, V50, P385, DOI 10.1007-s00484-006-0028-9; Food and Agriculture Organization (FAO), FAOSTAT; Gualdi S, 2012, REGIONAL ASSESSMENT; Haines A, 2006, PUBLIC HEALTH, V120, P585, DOI 10.1016-j.puhe.2006.01.002; Hashizume M, 2008, EPIDEMIOL INFECT, V136, P1281, DOI 10.1017-S0950268807009776; Hashizume M, 2007, INT J EPIDEMIOL, V36, P1030, DOI 10.1093-ije-dym148; Kovats RS, 2004, EPIDEMIOL INFECT, V132, P443, DOI 10.1017-S0950268804001992; Massoud M, 2002, INT S WORKSH ENV POL, P598; McMichael AJ, 2004, COMP QUANTIFICATION, P1543; MoPH (Lebanese Ministry of Public Health), 2010, EP SURV REP; Pachauri R. K., 2007, CLIMATE CHANGE 2007; Patz JA, 2008, AM J PREV MED, V35, P451, DOI 10.1016-j.amepre.2008.08.026; Qian S. S., 2010, ENV ECOLOGICAL STAT; R Development Core Team, 2009, R LANG ENV STAT COMP; Ragab R, 2002, BIOSYST ENG, V81, P3, DOI 10.1006-bioe.2001.0013; Semenza JC, 2012, CRIT REV ENV SCI TEC, V42, P378, DOI 10.1080-10643389.2010.518520; Shaban A, 2009, WATER RESOUR MANAG, V23, P1875, DOI 10.1007-s11269-008-9358-1; Singh RBK, 2001, ENVIRON HEALTH PERSP, V109, P155, DOI 10.2307-3434769; UN, WORLD POP PROSP 2010; UNICEF, CHILD MON SIT CHILDR; WHO, 2002, WORLD HLTH REP 2002; WHO (World Health Organization), DIS INJ COUNTR EST T; WHO (World Health Organization), 2003, HLTH GLOB ENV CHANG; World Bank, WORLD DAT; Yamout G, 2005, WATER RESOUR MANAG, V19, P791, DOI 10.1007-s11269-005-3280-6; Zhang Y, 2010, SCI TOTAL ENVIRON, V408, P524, DOI 10.1016-j.scitotenv.2009.10.06835
See through walls with Wi-Fi
No full textThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 61-64).Wi-Fi signals are typically information carriers between a transmitter and a receiver. In this thesis, we show that Wi-Fi can also extend our senses, enabling us to see moving objects through walls and behind closed doors. For example, we can identify the number of people in a closed room and their relative locations. We can also identify simple gestures made behind a wall. Further, by combining a sequence of gestures, a human can communicate messages to a wireless receiver without carrying any transmitting device. The thesis introduces two main innovations. First, it shows how one can use MIMO interference nulling to eliminate reflections off static objects and focus the receiver on a moving target. Second, it shows how one can track a human by treating the motion of a human body as an antenna array and tracking the resulting RF beam. We demonstrate the validity of our design by building it into USRP software radios and testing it in office buildings.by Fadel Adib.S.M
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