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Exploring chemical variables in Ligustrum lucidum Ait. F. Tricolor (Rehd.) Rehd. in relation to air pollutants and environmental conditions

Pignata, María L., Cañas, Martha S., Carreras, Hebe A. and Orellana, Liliana 1997, Exploring chemical variables in Ligustrum lucidum Ait. F. Tricolor (Rehd.) Rehd. in relation to air pollutants and environmental conditions, Environmental management, vol. 21, no. 5, pp. 793-801, doi: 10.1007/s002679900068.

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Title Exploring chemical variables in Ligustrum lucidum Ait. F. Tricolor (Rehd.) Rehd. in relation to air pollutants and environmental conditions
Formatted title Exploring chemical variables in Ligustrum lucidum Ait. F. Tricolor (Rehd.) Rehd. in relation to air pollutants and environmental conditions
Author(s) Pignata, María L.
Cañas, Martha S.
Carreras, Hebe A.
Orellana, LilianaORCID iD for Orellana, Liliana orcid.org/0000-0003-3736-4337
Journal name Environmental management
Volume number 21
Issue number 5
Start page 793
End page 801
Total pages 9
Publisher Springer
Place of publication New York, N.Y.
Publication date 1997-09
ISSN 0364-152X
1432-1009
Keyword(s) L. lucidum Ait. f. tricolor (Rehd.) Rehd
air pollution
sulfur accumulation
pigments
urban environment
Argentina
Summary A diagnostic study was done on Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd. in relation to atmospheric pollutants in Cordoba city, Argentina. The study area receives regional pollutants and was categorized taking into account traffic level, industrial density, type of industry, location of the sample point in relation to the street corner, treeless condition, and topographic level. Dried weight/fresh weight ratio (DW/FW) and specific leaf area (SLA) were calculated, and concentrations of chlorophylls, carotenoids, total sulfur, soluble proteins, malondialdehyde (MDA), and hydroperoxy conjugated dienes (HPCD) were determined in leaf samples. Sulfur content correlates positively with traffic density and SLA correlates negatively with some combinations of the categorical variables; MDA correlates positively with topographic level and total protein concentration correlates negatively with treeless condition. On the basis of our results, traffic, location of trees, type of industry, situation of a tree with respect to others, and topographic level are the environmental variables to bear in mind when selecting analogous sampling points in a passive monitoring program. An approximation to predict tree injury may be obtained by measuring DW/FW ratio, proteins, pigments, HPCD, and MDA as they are responsible for the major variability of data.
Language eng
DOI 10.1007/s002679900068
Field of Research 111799 Public Health and Health Services not elsewhere classified
Socio Economic Objective 920499 Public Health (excl. Specific Population Health) not elsewhere classified
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©1997, Springer- Verlag New York
Persistent URL http://hdl.handle.net/10536/DRO/DU:30090726

Document type: Journal Article
Collection: Faculty of Health
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