A posetic based assessment of atmospheric VOCs

Lars Carlsen; Lars Carlsen

doi:10.3934/environsci.2017.3.403

AIMS Environmental Science

2017, Volume 4, Issue 3: 403-416. doi: 10.3934/environsci.2017.3.403

Previous Article Next Article

Research article Topical Sections

A posetic based assessment of atmospheric VOCs

Lars Carlsen ^,

Awareness Center, Linkøpingvej 35, Trekroner, DK-4000 Roskilde, Denmark

Received: 05 December 2016 Accepted: 09 April 2017 Published: 18 April 2017

The assessment of a series of volatile organic compounds (VOCs) based on partial order methodology is reported using available data from six sites in Yokohama, Japan as an exemplary case. The individual VOCs are mutually ranked according to their importance, the ranking being made both based on the recorded concentration and the concentrations adjusted for the possibility of the single VOCs to exhibit respiratory toxicity. The relative importance of the single sites is disclosed to verify the overall most problematic area from an air pollution point of view. The concentration profiles for the six sites are scrutinized for possible ‘peculiar’ profiles. As air pollution data typically are associated with significant uncertainty the possible effects of data noise/uncertainty is addressed.
- air pollution,
- VOC,
- partial ordering,
- ranking,
- peculiar VOCs,
- data uncertainty
Citation: Lars Carlsen. A posetic based assessment of atmospheric VOCs[J]. AIMS Environmental Science, 2017, 4(3): 403-416. doi: 10.3934/environsci.2017.3.403

Related Papers:

Abstract

The assessment of a series of volatile organic compounds (VOCs) based on partial order methodology is reported using available data from six sites in Yokohama, Japan as an exemplary case. The individual VOCs are mutually ranked according to their importance, the ranking being made both based on the recorded concentration and the concentrations adjusted for the possibility of the single VOCs to exhibit respiratory toxicity. The relative importance of the single sites is disclosed to verify the overall most problematic area from an air pollution point of view. The concentration profiles for the six sites are scrutinized for possible ‘peculiar’ profiles. As air pollution data typically are associated with significant uncertainty the possible effects of data noise/uncertainty is addressed.

References

[1]	WHO (2014) Air quality deteriorating in many of the world's cities. News release. Available from: http://www.who.int/mediacentre/news/releases/2014/air-quality/en/.
[2]	Caselli M, de Gennaro G, Marzocca A, et al. (2010) Assessment of the impact of the vehicular traffic on BTEX concentration in ring roads in urban areas of Bari (Italy). Chemosphere 81: 306-311. doi: 10.1016/j.chemosphere.2010.07.033
[3]	Gallego E, Roca FJ, Perales JF, et al. (2016) Impact of formaldehyde and VOCs from waste treatment plants upon the ambient air nearby an urban area (Spain). Sci Tot Environ 568: 369-380. doi: 10.1016/j.scitotenv.2016.06.007
[4]	Halliday H, Thompson A, Wisthaler A, et al. (2016) Atmospheric benzene observations from oil and gas production in the Denver-Julesburg Basin in July and August 2014. J Geophys Res-Atmos 121: 11055-11074. doi: 10.1002/2016JD025327
[5]	Petracchini F, Paciucci L, Vichi F, et al. (2016) Gaseous pollutants in the city of Urumqi, Xinjiang: spatial and temporal trends, sources and implications. Atmos Pollut Res 7: 925-934. doi: 10.1016/j.apr.2016.05.009
[6]	Environmental Protection Department, The Government of the Hong Kong Special Administration Region (2017) Volatile Organic Compounds and Smog. Available from: http://www.epd.gov.hk/epd/english/environmentinhk/air/prob_solutions/vocs_smog.html
[7]	Tiwari V, Hanai Y, Masunaga S (2010) Ambient levels of volatile organic compounds in the vicinity of petrochemical industrial area of Yokohama, Japan. Air Qual Atmos Health 3: 65-75.
[8]	PASS online, 2016. Available from: http://www.way2drug.com/PASSOnline/.
[9]	Munda G (2008) Social multi-criteria evaluation for a sustainable economy (Operation, p. 227). New York: Springer. Available from: http://www.springer.com/us/book/9783540737025.
[10]	Bruggemann R, Carlsen L (2006) Partial Order in Environmental Sciences and Chemistry, Springer, Berlin. Available from: http://www.springer.com/us/book/9783540339687.
[11]	Bruggemann R, Carlsen L (2006) Introduction to partial order theory exemplified by the evaluation of sampling sites, In: Partial Order in Environmental Sciences and Chemistry, R. Bruggemann and L. Carlsen, eds, Springer, Berlin, 61-110. Available from: http://link.springer.com/chapter/10.1007/3-540-33970-1_4.
[12]	Bruggemann R, Patil GP (2011) Ranking and prioritization for multi-indicator systems-Introduction to partial order applications, Springer, New York. Available from: http://www.springer.com/gp/book/9781441984760.
[13]	Carlsen L (2015) Partial Ordering as Decision Support to Evaluate Remediation Technologies, AIMS Environmental Science 2: 110-121.
[14]	Carlsen L (2015) Data analysis by partial order methodology. Chem Bull Kazakh Natl Univ 2015(2): 22-33.
[15]	Brüggemann R, Münzer B (1993) A graph-theoretical tool for priority setting of chemicals, Chemosphere 27: 1729-1736.
[16]	Brüggemann R, Voigt K (1995) An Evaluation of Online Databases by Methods of Lattice Theory. Chemosphere 31: 3585-3594. doi: 10.1016/0045-6535(95)00207-O
[17]	Carlsen L, Bruggemann R (2016) Partial ordering and metrology. Analyzing analytical performance, Partial Order Concepts in Applied Sciences, Springer.
[18]	Bruggemann R, Carlsen L (2011) An Improved Estimation of Averaged Ranks of Partially Orders. MATCH-Commun Math Comput Chem 65: 383-414.
[19]	Bruggemann R, Carlsen L (2014) Incomparable-what now? MATCH-Commun Math Comput Chem 71: 694-716.
[20]	Zar JH, Biostatistical Analysis, Upper Saddle River, Prentice Hall, 4^th ed., 1999. Available from: https://www.amazon.com/Biostatistical-Analysis-4th-Jerrold-Zar/dp/013081542X.
[21]	Brunner E, Munzel U (2002) Nichtparametrische Datenanalyse, Berlin: Springer. Available from: http://link.springer.com/book/10.1007/978-3-642-37184-4.
[22]	Bruggemann R, Halfon E, Welzl G, et al. (2001) Applying the concept of partially ordered sets on the ranking of near-shore sediments by a battery of tests. J Chem Inf Comp Sci 41: 918-925. doi: 10.1021/ci000055k
[23]	Carlsen L, Bruggemann R (2016) On the influence of data noise and uncertainty on ordering of objects, described by a multi-indicator system. A set of pesticides as an exemplary case. J Chemometrics 30: 22-29.
[24]	Bruggemann R, Carlsen L (2016) An attempt to understand noisy posets. MATCH-Commun Math Comput Chem 75: 485-510.
[25]	Bruggemann R, Carlsen L, Voigt K, et al. (2014) PyHasse Software for Partial Order Analysis, In: R. Bruggemann, L. Carlsen, J. Wittmann, eds, Multi-Indicator Systems and Modelling in Partial Order, Springer, New York, 389-423.
[26]	Ernesti J, Kaiser P (2008) Python-Das umfassende Handbuch, Galileo Press, Bonn. Available from: http://python.haas.homelinux.net/.
[27]	Hetland ML (2005) Beginning Python-From Novice to professional, Apress, Berkeley. Available from: http://www.apress.com/9781590599822.
[28]	Langtangen HP (2008) Python Scripting for Computational Science. Springer, Berlin. Available from: http://www.springer.com/us/book/9783540739159.
[29]	Weigend M (2006) Objektorientierte Programmierung mit Python, mitp-Verlag, Bonn. Available from: http://diebuchsuche.de/buch-isbn-9783826615719.html.
[30]	Python (2015) Python, Available from: https://www.python.org/.
[31]	Miller L, Xu X, Wheeler A, et al. (2011) Spatial Variability and Application of Ratios between BTEX in Two Canadian Cities. The Scientific World J 11: 2536-2549. doi: 10.1100/2011/167973
[32]	Perry R, Gee IL (1995) Vehicle emissions in relation to fuel composition. Sci Tot Environ 169: 149-156. doi: 10.1016/0048-9697(95)04643-F
[33]	Uria-Tellaetxe I, Navazo M, de Blas M, et al. (2016) Gas-phase naphthalene concentration data recovery in ambient air and its relevance as a tracer of sources of volatile organic compounds. Atmos Environ 131: 279-288. doi: 10.1016/j.atmosenv.2016.01.047
[34]	Van de Walle B, De Baets B, Kerre EE (1995) Fuzzy multi-criteria analysis of cutting techniques in a nuclear dismantling project. Fuzzy set Syst 74: 115-126. doi: 10.1016/0165-0114(95)00017-F
[35]	Carlsen L, Bruggemann R, Kenessov B (subm) Use of partial order in environmental pollution studies demonstrated by urban BTEX air pollution in 20 major cities worldwide.

Reader Comments

Your name:*

Email:*
© 2017 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)