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Journal articles on the topic 'Pollution – Terminologie'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Di Franco, S., V. De Santis, and P. Plini. "Pollution and Health terminology into the EARTh thesaurus." E3S Web of Conferences 1 (2013): 18004. http://dx.doi.org/10.1051/e3sconf/20130118004.

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2

Dean, R. B. "Editors Notes and Terminology." Waste Management & Research 5, no. 1 (January 1987): i—ii. http://dx.doi.org/10.1177/0734242x8700500133.

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3

DEAN, R. "Editor's note and terminology." Waste Management & Research 5, no. 3 (September 1987): i—ii. http://dx.doi.org/10.1016/0734-242x(87)90073-5.

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4

Gagné, Anne-Marie, and Marie-Claude L'Homme. "Opposite relationships in terminology." Terminology 22, no. 1 (May 19, 2016): 30–51. http://dx.doi.org/10.1075/term.22.1.02gag.

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This article studies a family of semantic relationships that is often ignored in terminological descriptions, i.e. opposite relationships that include, but are not limited to, antonymy. We analyze English and French terms classified in an environmental database as opposites (Eng. polluting; green, afforestation; deforestation; Fr. réchauffer; refroidir, atténuation; intensification) and revise this first classification based on typologies and criteria supplied by literature on lexical semantics, psycholinguistics and corpus linguistics. Our revised classification shows that diversified opposite relationships can be observed between terms. They also appear to display the same complexity as in general language. Finally, in some cases, the nature of concepts in the specific subject field must be taken into consideration.

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5

Haygarth, P. M., and A. N. Sharpley. "Terminology for Phosphorus Transfer." Journal of Environmental Quality 29, no. 1 (January 2000): 10–15. http://dx.doi.org/10.2134/jeq2000.00472425002900010002x.

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6

Lespes, Gaëtane, Tea Zuliani, and Dirk Schaumlöffel. "Need for revisiting the terminology about speciation." Environmental Science and Pollution Research 23, no. 15 (June 15, 2016): 15767–70. http://dx.doi.org/10.1007/s11356-016-6922-8.

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7

Brown, James L., T. Ferrell Miller, and Christopher Gussman. "Invited Commentary on Terminology for the International Journal of Phytoremediation." International Journal of Phytoremediation 4, no. 4 (October 2002): 331. http://dx.doi.org/10.1080/15226510208500091.

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8

Powlson, David S. "Is ‘soil health’ meaningful as a scientific concept or as terminology?" Soil Use and Management 37, no. 3 (May 14, 2021): 403–5. http://dx.doi.org/10.1111/sum.12721.

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9

Tueller, Paul T. "Terminology for Grazing Lands and Grazing Animals." Journal of Environmental Quality 21, no. 2 (April 1992): 293. http://dx.doi.org/10.2134/jeq1992.00472425002100020034x.

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10

DUBOIS, Alain. "The rich but confusing terminology of biological nomenclature: a first step towards a comprehensive glossary." Bionomina 3, no. 1 (April 21, 2011): 63–70. http://dx.doi.org/10.11646/bionomina.3.1.6.

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Biology deals with billions of living organisms, which display a great diversity but also share many characters, being the result of an evolution. Designating these organisms in a universal and unambiguous way is a basic need for communication, not only among taxonomists or even biologists, but with society as a whole. It is indispensable to have a unique system for distinguishing and naming the organisms that may be used for alimentary, agronomical, veterinary or medical purposes or for any other human needs, that may be responsible for diseases, pollutions, biotic invasions, that we may wish to protect, study or admire, etc. For all these purposes, we need a scientific discipline, taxonomy, dealing not only with the classification of living organisms into millions of classificatory units, the taxa, but also with the designation and indexation of these taxa (nomenclature). Biological nomenclature has to care for the scientific naming of millions of taxa (species and higher taxa like genera or families), the inventory of which is still very far from being finished.

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11

Christensen, Frans Møller, Ole Andersen, Nijs Jan Duijm, and Poul Harremoës. "Risk terminology—a platform for common understanding and better communication." Journal of Hazardous Materials 103, no. 3 (October 2003): 181–203. http://dx.doi.org/10.1016/s0304-3894(03)00039-6.

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12

Mazurski, Krzysztof R. "Suggestions for a terminology for changes in the natural environment." Biological Wastes 22, no. 1 (January 1987): 1–9. http://dx.doi.org/10.1016/0269-7483(87)90095-4.

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13

Reynolds, C. M. "Response to the letter from Brown, Miller, Gussman, Nadeau, and Allen on Terminology for treating petroleum-contaminated soils." International Journal of Phytoremediation 4, no. 4 (October 2002): 332–34. http://dx.doi.org/10.1080/15226510208500092.

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14

Grady, C. P. Leslie, Barth F. Smets, and Daniel S. Barbeau. "Variability in kinetic parameter estimates: A review of possible causes and a proposed terminology." Water Research 30, no. 3 (March 1996): 742–48. http://dx.doi.org/10.1016/0043-1354(95)00199-9.

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15

Castellar, J. A. C., L. A. Popartan, J. Pueyo-Ros, N. Atanasova, G. Langergraber, I. Säumel, L. Corominas, J. Comas, and V. Acuña. "Nature-based solutions in the urban context: terminology, classification and scoring for urban challenges and ecosystem services." Science of The Total Environment 779 (July 2021): 146237. http://dx.doi.org/10.1016/j.scitotenv.2021.146237.

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16

Pöschl, U., Y. Rudich, and M. Ammann. "Kinetic model framework for aerosol and cloud surface chemistry and gas-particle interactions: Part 1 – general equations, parameters, and terminology." Atmospheric Chemistry and Physics Discussions 5, no. 2 (April 11, 2005): 2111–91. http://dx.doi.org/10.5194/acpd-5-2111-2005.

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Abstract. Aerosols and clouds play central roles in atmospheric chemistry and physics, climate, air pollution, and public health. The mechanistic understanding and predictability of aerosol and cloud properties, interactions, transformations, and effects are, however, still very limited. This is due not only to the limited availability of measurement data, but also to the limited applicability and compatibility of model formalisms used for the analysis, interpretation, and description of heterogeneous and multiphase processes. To support the investigation and elucidation of atmospheric aerosol and cloud surface chemistry and gas-particle interactions, we present a comprehensive kinetic model framework with consistent and unambiguous terminology and universally applicable rate equations and parameters. It allows to describe mass transport and chemical reactions at the gas-particle interface and to link aerosol and cloud surface processes with gas phase and particle bulk processes in systems with multiple chemical components and competing physicochemical processes. The key elements and essential aspects of the presented framework are: a simple and descriptive double-layer surface model (sorption layer and quasi-static layer); straightforward flux-based mass balance and rate equations; clear separation of mass transport and chemical reactions; well-defined rate parameters (uptake and accommodation coefficients, reaction and transport rate coefficients); clear distinction between gas phase, gas-surface, and surface-bulk transport (gas phase diffusion correction, surface and bulk accommodation); clear distinction between gas-surface, surface layer, and surface-bulk reactions (Langmuir-Hinshelwood and Eley-Rideal mechanisms); mechanistic description of concentration and time dependencies; flexible inclusion/omission of chemical species and physicochemical processes; flexible convolution/deconvolution of species and processes; and full compatibility with traditional resistor model formulations. Exemplary practical applications and model calculations illustrating the relevance of the above aspects will be presented in a companion paper (Ammann and Pöschl, 2005). We expect that the presented model framework will serve as a useful tool and basis for experimental and theoretical studies investigating and describing atmospheric aerosol and cloud surface chemistry and gas-particle interactions. In particular, it is meant to support the planning and design of laboratory experiments for the elucidation and determination of kinetic parameters; the establishment, evaluation, and quality assurance of comprehensive and self-consistent collections of rate parameters; and the development of detailed master mechanisms for process models and the derivation of simplified but yet realistic parameterizations for atmospheric and climate models.

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17

Pöschl, U., Y. Rudich, and M. Ammann. "Kinetic model framework for aerosol and cloud surface chemistry and gas-particle interactions – Part 1: General equations, parameters, and terminology." Atmospheric Chemistry and Physics 7, no. 23 (December 10, 2007): 5989–6023. http://dx.doi.org/10.5194/acp-7-5989-2007.

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Abstract. Aerosols and clouds play central roles in atmospheric chemistry and physics, climate, air pollution, and public health. The mechanistic understanding and predictability of aerosol and cloud properties, interactions, transformations, and effects are, however, still very limited. This is due not only to the limited availability of measurement data, but also to the limited applicability and compatibility of model formalisms used for the analysis, interpretation, and description of heterogeneous and multiphase processes. To support the investigation and elucidation of atmospheric aerosol and cloud surface chemistry and gas-particle interactions, we present a comprehensive kinetic model framework with consistent and unambiguous terminology and universally applicable rate equations and parameters. It enables a detailed description of mass transport and chemical reactions at the gas-particle interface, and it allows linking aerosol and cloud surface processes with gas phase and particle bulk processes in systems with multiple chemical components and competing physicochemical processes. The key elements and essential aspects of the presented framework are: a simple and descriptive double-layer surface model (sorption layer and quasi-static layer); straightforward flux-based mass balance and rate equations; clear separation of mass transport and chemical reactions; well-defined and consistent rate parameters (uptake and accommodation coefficients, reaction and transport rate coefficients); clear distinction between gas phase, gas-surface, and surface-bulk transport (gas phase diffusion, surface and bulk accommodation); clear distinction between gas-surface, surface layer, and surface-bulk reactions (Langmuir-Hinshelwood and Eley-Rideal mechanisms); mechanistic description of concentration and time dependences (transient and steady-state conditions); flexible addition of unlimited numbers of chemical species and physicochemical processes; optional aggregation or resolution of intermediate species, sequential processes, and surface layers; and full compatibility with traditional resistor model formulations. The outlined double-layer surface concept and formalisms represent a minimum of model complexity required for a consistent description of the non-linear concentration and time dependences observed in experimental studies of atmospheric multiphase processes (competitive co-adsorption and surface saturation effects, etc.). Exemplary practical applications and model calculations illustrating the relevance of the above aspects are presented in a companion paper (Ammann and Pöschl, 2007). We expect that the presented model framework will serve as a useful tool and basis for experimental and theoretical studies investigating and describing atmospheric aerosol and cloud surface chemistry and gas-particle interactions. It shall help to end the "Babylonian confusion" that seems to inhibit scientific progress in the understanding of heterogeneous chemical reactions and other multiphase processes in aerosols and clouds. In particular, it shall support the planning and design of laboratory experiments for the elucidation and determination of fundamental kinetic parameters; the establishment, evaluation, and quality assurance of comprehensive and self-consistent collections of rate parameters; and the development of detailed master mechanisms for process models and derivation of simplified but yet realistic parameterizations for atmospheric and climate models.

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18

Pendrill, L. R., A. Allard, N. Fischer, P. M. Harris, J. Nguyen, and I. M. Smith. "Software to Maximize End-User Uptake of Conformity Assessment With Measurement Uncertainty, Including Bivariate Cases. The European EMPIR CASoft Project." NCSL International Measure 13, no. 1 (February 2021): 58–69. http://dx.doi.org/10.51843/measure.13.1.6.

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Facilitating the uptake of established methodologies for risk-based decision-making in product conformity assessment taking into account measurement uncertainty by providing dedicated software is the aim of the European project EMPIR CASoft(2018–2020), involving the National Measurement Institutes from France, Sweden and the UK, and industrial partner Trescal (FR) as primary supporter. The freely available software helps end-users perform the required risk calculations in accordance with current practice and regulations and extends that current practice to include bivariate cases. The software is also aimed at supporting testing and calibration laboratories in the application of the latest version of the ISO/IEC 17025:2017 standard, which requires that“…the laboratory shall document the decision rule employed, taking into account the level of risk […] associated with the decision rule and apply the decision rule.” Initial experiences following launch of the new software in Spring 2020 are reported.

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19

"Nucleation terminology." Journal of Aerosol Science 16, no. 6 (January 1985): 575–76. http://dx.doi.org/10.1016/0021-8502(85)90009-6.

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20

Ishmatov, Alexander. "“SARS-CoV-2 is transmitted by particulate air pollution”: Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception." Environmental Research, September 2021, 112116. http://dx.doi.org/10.1016/j.envres.2021.112116.

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