Academic literature on the topic 'Environmental quantification'
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Journal articles on the topic "Environmental quantification"
Bottausci, Sara, Elena-Diana Ungureanu-Comanita, Maria Gavrilescu, and Alessandra Bonoli. "ENVIRONMENTAL IMPACTS QUANTIFICATION OF PVC PRODUCTION." Environmental Engineering and Management Journal 20, no. 10 (2021): 1693–702. http://dx.doi.org/10.30638/eemj.2021.158.
Full textRobu, Brindusa Mihaela, and Gabriel Dan Suditu. "DIGITIZATION OF THE ENVIRONMENTAL IMPACT QUANTIFICATION PROCESS." Environmental Engineering and Management Journal 11, no. 4 (2012): 841–48. http://dx.doi.org/10.30638/eemj.2012.107.
Full textNARA, Matsunori. "Quantification of Concerns for Environmental Risk Evaluation." Proceedings of the Symposium on Global Environment 11 (2003): 183–88. http://dx.doi.org/10.2208/proge.11.183.
Full textHorneck, G. "Quantification of biologically effective environmental UV irradiance." Advances in Space Research 26, no. 12 (January 2000): 1983–94. http://dx.doi.org/10.1016/s0273-1177(00)00172-1.
Full textAllaire, Douglas, George Noel, Karen Willcox, and Rebecca Cointin. "Uncertainty quantification of an Aviation Environmental Toolsuite." Reliability Engineering & System Safety 126 (June 2014): 14–24. http://dx.doi.org/10.1016/j.ress.2014.01.002.
Full textYe, Ming, Philip D. Meyer, Yu-Feng Lin, and Shlomo P. Neuman. "Quantification of model uncertainty in environmental modeling." Stochastic Environmental Research and Risk Assessment 24, no. 6 (April 28, 2010): 807–8. http://dx.doi.org/10.1007/s00477-010-0377-0.
Full textFowler, Brian, Dale Hoover, and M. Coreen Hamilton. "The quantification of toxaphene in environmental samples." Chemosphere 27, no. 10 (November 1993): 1891–905. http://dx.doi.org/10.1016/0045-6535(93)90385-i.
Full textZENITANI, Kenji, and Hidefumi IMURA. "Quantification of the environmental load associated with construction." ENVIRONMENTAL SYSTEMS RESEARCH 22 (1994): 147–53. http://dx.doi.org/10.2208/proer1988.22.147.
Full textCartailler, Thomas, Anais Guaus, Alexandre Janon, Hervé Monod, Clémentine Prieur, and Nathalie Saint-Geours. "Sensitivity analysis and uncertainty quantification for environmental models." ESAIM: Proceedings 44 (January 2014): 300–321. http://dx.doi.org/10.1051/proc/201444019.
Full textEhling, U. H. "Quantification of the Genetic Risk of Environmental Mutagens." Risk Analysis 8, no. 1 (March 1988): 45–57. http://dx.doi.org/10.1111/j.1539-6924.1988.tb01153.x.
Full textDissertations / Theses on the topic "Environmental quantification"
Garraghan, Peter Michael. "Holistic cloud computing environmental quantification and behavioural analysis." Thesis, University of Leeds, 2014. http://etheses.whiterose.ac.uk/7192/.
Full textMondaca, Fernandez Iram. "Spectroscopy Techniques for quantification of Microorganisms in Environmental Samples." Tucson, Arizona : University of Arizona, 2006. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1416%5F1%5Fm.pdf&type=application/pdf.
Full textSpeak, Andrew Francis. "Quantification of the environmental impacts of urban green roofs." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/quantification-of-the-environmental-impacts-of-urban-green-roofs(6dc863d5-53bd-462b-b37f-37faa9ae3db0).html.
Full textMondaca, Fernandez Iram. "Spectroscopy Techniques for quantification of Microorganisms in Environmental Samples." Diss., The University of Arizona, 2005. http://hdl.handle.net/10150/194103.
Full textMohammadi, Ghazi Reza. "Inference and uncertainty quantification for unsupervised structural monitoring problems." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115791.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 261-272).
Health monitoring is an essential functionality for smart and sustainable infrastructures that helps improving their safety and life span. A major element of such functionality is statistical inference and decision making which aims to process the dynamic response of structures in order to localize the defects in those systems as well as quantifying the uncertainties associated with such predictions. Accomplishing this task requires dealing with special constraints, in addition to the general challenges of inference problems, which are imposed by the uniqueness and size of civil infrastructures. These constraints are mainly associated with the small size and high dimensionality of the relevant data sets, low spatial resolution of measurements, and lack of prior information about the response of structures at all possible damaged states. Additionally, the measured responses at various locations on a structure are statistically dependent due to their connectivity via the structural elements. Ignoring such dependencies may result in inaccurate predictions, usually by blurring the damage localization resolution. In this thesis work, a comprehensive investigation has been carried out on developing appropriate signal processing, inference, and uncertainty quantification techniques with applications to data driven structural health monitoring (SHM). For signal processing, we have developed a feature extraction scheme that uses nonlinear non-stationary signal decomposition techniques to capture the effect of damages on the dynamic response of structures. We have also developed a general purpose signal processing method by combining the sparsity based regularization with the singularity expansion method. This method can provide a sparse representation of signals in complex-frequency plane and hence, more robust system identification schemes. For uncertainty quantification and decision making, we have developed three different learning algorithms which are capable of characterizing the statistical dependencies of the relevant random variables in novelty detection inference problems under various constraints related to the quality, size, and dimensionality of data sets. In doing so, we have mainly used the statistical graphical models and Markov random fields, optimization methods, kernel two sample tests, and kernel dependence analysis. The developed methods may be applied to a wide range of problems such as SHM, medical diagnostic, network security, and event detection. We have experimentally evaluated these techniques by applying them to SHM application problems for damage localization in various laboratory prototypes as well as a full scale structure.
by Reza Mohammadi Ghazi.
Ph. D. in Structures and Materials
Fugate, David C. "Quantification of Tidal Creek Network Patterns using Fractal Methods." W&M ScholarWorks, 1996. https://scholarworks.wm.edu/etd/1539617716.
Full textNkongolo, Nsalambi Vakanda. "Quantification of greenhouse gas fluxes from soil in agricultural fields." Thesis, Nelson Mandela Metropolitan University, 2010. http://hdl.handle.net/10948/1474.
Full textGalloway, P. W. "Performance quantification of tidal turbines subjected to dynamic loading." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/361524/.
Full textHe, Yang. "Quantification of Carbon Nanotubes in the Environmental Matrices by Using a Microwave Induced Heating Method." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin154392139689757.
Full textde, Luis Jorge. "A Process for the Quantification of Aircraft Noise and Emissions Interdependencies." Diss., Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24618.
Full textBooks on the topic "Environmental quantification"
Feng-bin, Sun, ed. Environmental stress screening: Its quantification, optimization and management. Upper Saddle River, N.J: Prentice Hall, 1995.
Find full textKececioglu, Dimitri. Burn-in testing: Its quantification and optimization. Upper Saddle River, N.J: Prentice Hall PTR, 1997.
Find full textCorporation, Concord Scientific. Quantification of hydrocarbon emissions from the Canadian gasoline marketing distribution system. Ottawa: Petroleum Association for Conservation of the Canadian Environment, 1986.
Find full textHall, John Christopher. Detection and quantification of herbicide residues in the environment using immunochemical techniques. [Toronto, Ont.]: Environment Ontario, 1990.
Find full textHall, John Christopher. Detection and quantification of herbicide residues in the environment using immunochemical techniques. [Toronto, Ont.]: Environment Ontario, 1990.
Find full textSpecified gas emitters regulation: Quantification protocol for landfill gas capture and combustion. [Edmonton]: Alberta Environment, 2007.
Find full textChing-Hung, Hsu, and Stedeford Todd, eds. Cancer risk assessment: Chemical carcinogenesis, hazard evaluation, and risk quantification. Hoboken, N.J: Wiley, 2010.
Find full textSpecified gas emitters regulation: Quantification protocol for reducing slaughter age of cattle. [Edmonton]: Alberta Environment, 2007.
Find full textAccardi-Dey, AmyMarie. Black carbon in marine sediments: Quantification and implications for the sorption of polycyclic aromatic hydrocarbons. Cambridge, Mass: Massachusetts Institute of Technology, 2003.
Find full textSpecified gas emitters regulation: Quantification protocol for nitrous oxide abatement from nitric acid production. [Edmonton]: Alberta Environment, 2009.
Find full textBook chapters on the topic "Environmental quantification"
Iannone, A. Pablo. "Risk Assessment Beyond Quantification." In Practical Environmental Ethics, 115–26. Title: Practical environmental ethics / A. Pablo Iannone. Description: New Brunswick : Transaction Publishers, 2016. |: Routledge, 2017. http://dx.doi.org/10.4324/9781315127200-4.
Full textGradinaru, Giani. "Environment Benefits Quantification Through Statistical Indicators." In Environmental Indicators, 225–36. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9499-2_13.
Full textInghels, Dirk. "Quantification of the Environmental Impact." In Introduction to Modeling Sustainable Development in Business Processes, 89–107. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58422-1_5.
Full textKumagai, Hiroyuki. "Volcano Seismic Signals, Source Quantification of." In Extreme Environmental Events, 1179–206. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-7695-6_59.
Full textFriedrich, Rainer, and Peter Bickel. "Quantification of Total and Average Externalities (Aggregation)." In Environmental External Costs of Transport, 161–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04329-5_12.
Full textBemow, Stephen, Bruce Biewald, and Donald Marron. "Environmental Externalities Measurement: Quantification, Valuation and Monetization." In External Environmental Costs of Electric Power, 81–102. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76712-8_7.
Full textDey, Sudip, Tanmoy Mukhopadhyay, and Sondipon Adhikari. "Effect of Environmental Uncertainties on the Free Vibration Analysis of Composite Laminates." In Uncertainty Quantification in Laminated Composites, 145–64. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2018] | “A science publishers book.”: CRC Press, 2018. http://dx.doi.org/10.1201/9781315155593-7.
Full textGrimm, Daniel, Björn Schödwell, Koray Erek, and Ruediger Zarnekow. "Conceptualizing the Quantification of the Carbon Footprint of IT-Services." In Environmental Science and Engineering, 77–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36011-4_7.
Full textIsaac-Olivé, Keila, Eunice Olivé-Alvarez, Amado E. Navarro-Frómeta, Ninfa Ramírez-Durán, Enrique Morales-Avila, Liliana Aranda-Lara, Horacio Sandoval-Trujillo, and Pablo Moreno-Pérez. "Quantification of Non-steroidal Anti-inflammatory Drug in Water." In The Handbook of Environmental Chemistry, 83–103. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/698_2020_543.
Full textHerrmann, L., R. Jahn, and K. Stahr. "Identification and Quantification of Dust Additions in Perisaharan Soils." In Environmental Science and Technology Library, 173–82. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-017-3354-0_16.
Full textConference papers on the topic "Environmental quantification"
Schultz, N. U., D. M. Wood, V. Adderly, and D. Bennett. "RDI/I Quantification Research Results." In World Water and Environmental Resources Congress 2001. Reston, VA: American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40569(2001)28.
Full textAnderson, Brooke, Steve Blattnig, and Martha Clowdsley. "Numerical Uncertainty Quantification for Radiation Analysis Tools." In International Conference On Environmental Systems. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2007. http://dx.doi.org/10.4271/2007-01-3110.
Full textPreis, Ami, Lina Perelman, and Avi Ostfeld. "Uncertainty Quantification of Contamination Source Identification." In World Environmental and Water Resources Congress 2008. Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)505.
Full textMattley, Yvette D., and Luis H. Garcia-Rubio. "Multiwavelength spectroscopy for the detection, identification, and quantification cells." In Environmental and Industrial Sensing, edited by Yud-Ren Chen and Shu-I. Tu. SPIE, 2001. http://dx.doi.org/10.1117/12.418743.
Full textChamberland, M., P. Lagueux, P. Tremblay, S. Savary, M. A. Gagnon, M. Kastek, T. Piątkowski, and R. Dulski. "Standoff gas detection, identification and quantification with a thermal hyperspectral imager." In ENVIRONMENTAL IMPACT 2014. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/eid140571.
Full textNowak Da Costa, Joanna, Elzbieta Bielecka, and Beata Calka. "Uncertainty Quantification of the Global Rural-Urban Mapping Project over Polish Census Data." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.221.
Full textHill, D. J. "Pervasive Sensing for Real-Time Rainfall Quantification." In World Environmental and Water Resources Congress 2013. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784412947.137.
Full textPeterson, B. V., B. R. Linnell, K. B. Brooks, and T. P. Griffin. "Electronic Nose for Toxic Vapor Detection, Identification, and Quantification." In International Conference On Environmental Systems. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2005. http://dx.doi.org/10.4271/2005-01-2879.
Full textWavering, Thomas A., Jennifer L. Elster, Shufang Luo, Mishell K. Evans, Charles Pennington, Roger Van Tassell, and Mark E. Jones. "Fiber optic affinity ligand sensor for quantification of petroleum and bioremediation." In Environmental and Industrial Sensing, edited by Tuan Vo-Dinh and Stephanus Buettgenbach. SPIE, 2001. http://dx.doi.org/10.1117/12.417446.
Full textRoma, Gerard, Waldo Nogueira, and Perfecto Herrera. "Recurrence quantification analysis features for environmental sound recognition." In 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). IEEE, 2013. http://dx.doi.org/10.1109/waspaa.2013.6701890.
Full textReports on the topic "Environmental quantification"
Lee, A. D., J. M. Callaway, C. S. Glantz, M. C. Baechler, and L. O. Foley. Information and issues related to the quantification of environmental externalities for new powerplants. Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/6455883.
Full textYe, Ming. Computational Bayesian Framework for Quantification and Reduction of Predictive Uncertainty in Subsurface Environmental Modeling. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1491235.
Full textDumas, Melissa, Binita Kc, and Colin I. Cunliff. Extreme Weather and Climate Vulnerabilities of the Electric Grid: A Summary of Environmental Sensitivity Quantification Methods. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1558514.
Full textSchipani, Salvatore P., Richard S. Bruno, Michael A. Lattin, Bobby M. King, and Debra J. Patton. Quantification of Cognitive Process Degradation While Mobile, Attributable to the Environmental Stressors Endurance, Vibration, and Noise. Fort Belvoir, VA: Defense Technical Information Center, April 1998. http://dx.doi.org/10.21236/ada346416.
Full textTomasko, Maria S. Evaluating open-path FTIR spectrometer data using different quantification methods, libraries, and background spectra obtained under varying environmental conditions. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/587725.
Full textCorriveau, Elizabeth, Ashley Mossell, Holly VerMeulen, Samuel Beal, and Jay Clausen. The effectiveness of laser-induced breakdown spectroscopy (LIBS) as a quantitative tool for environmental characterization. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40263.
Full textFurman, Alex, Jan Hopmans, Shmuel Assouline, Jirka Simunek, and Jim Richards. Soil Environmental Effects on Root Growth and Uptake Dynamics for Irrigated Systems. United States Department of Agriculture, February 2011. http://dx.doi.org/10.32747/2011.7592118.bard.
Full textMcKay, S., Nate Richards, and Todd Swannack. Ecological model development : evaluation of system quality. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45380.
Full textHaeckel, Matthias, and Peter Linke. RV SONNE Fahrtbericht/Cruise Report SO268 - Assessing the Impacts of Nodule Mining on the Deep-sea Environment: NoduleMonitoring, Manzanillo (Mexico) – Vancouver (Canada), 17.02. – 27.05.2019. GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, November 2021. http://dx.doi.org/10.3289/geomar_rep_ns_59_20.
Full textRycroft, Taylor, Kerry Hamilton, Charles Haas, and Igor Linkov. A quantitative risk assessment method for synthetic biology products in the environment. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41331.
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