Development of biomonitoring techniques of persistent airborne pollutants using native lichens Article Swipe
This PhD project has been focused on the improvement of the methods commonly used in biomonitoring surveys of persistent airborne pollutants based on native lichens. These protocols recommend to measure the content of pollutants in the outermost parts of foliose epiphytic thalli, which purportedly developed in the last year before sampling. This allows to associate the pollutant content to a known exposure period. Unfortunately, lichens are very sensitive to local environmental conditions, although the lack of data concerning most of the species used in biomonitoring surveys caused an underestimation of the problem. Therefore, in a first study, I investigated the influence of site-specific climatic factors on the inter-site variability of seasonal and long-term Radial Growth Rates (RaGR) of Xanthoria parietina, one of the most popular lichen biomonitor. For 17 months RaGR was monitored in 11 sites along an altitudinal transect by measuring the lobe length of 54 thalli, whereas site-specific climatic variables were monitored with thermo-hygrometric sensors. Results highlighted that site-specific climatic differences in terms of air water availability and wind frequency were strongly correlated to the observed inter-site variability of both RaGRs, with thalli of dry sites that had significantly lower seasonal RaGR with respect to those of moist ones. For this reason, it was concluded that biomonitoring surveys with native lichens should be limited to climatically homogeneous areas in order to ensure comparable exposure periods.\nIn a second study, the correct reference exposure period revealed itself as an important yardstick if we want to correctly use lichen data in the validation of atmospheric dispersion models (ADMs). In this study, I used the element concentrations measured in lichen samples from the surroundings of a coal-fired power plant as the core dataset for the validation of two alternative ADMs. These ADMs simulated the dispersion of Total Suspended Particulate emitted by the plant during the year 2005, selected by the authorities as reference meteorological period (ADM1), and, the six months preceding the lichen sample collection (ADM2), because this was the age of the collected lichen samples, as estimated using the above-mentioned RaGR. After normalization for the element soil content, results showed that the Cr content of lichen samples were more correlated with the outcomes of ADM2 rather than with those of ADM1. These results were confirmed by a PM10 survey, carried out by ARPA FVG, which revealed that in two successive periods of activity and inactivity of the putative source, concentration of Cr was significantly higher in the former.\nFinally, a third study was aimed at investigating the influence of lichen melanins in trace element retention. Most of the species used as biomonitor of airborne trace elements belong to the Parmeliaceae, a highly differentiated family characterized by a highly melanised lower cortex, whose adaptive value is unknown. Here, I tested the hypothesis that melanins can affect the content of selected elements. Macro- (Ca, K and S) and micro- (Fe, Mn and Zn) nutrients in melanized and non-melanized pseudotissues of nine species was first evaluated by micro-XRF analysis on either the upper and lower cortex, and on the artificially exposed medulla. Afterwards, the total concentration of the same elements was measured by ICP-AES, and a sequential elution experiment was performed on one heavily melanised and one lightly melanised species. In this way, I could demonstrate that native lichens with heavily melanised surfaces are more Fe- and Zn- enriched than lightly or non-melanised lichens, possibly increasing the bioavailability of both elements in favour of the photobionts. Therefore, in order to exclude any bias related to the different degree of melanisation, the proposal is to compose analytical samples with lichen material chara
Related Topics
- Type
- article
- Language
- en
- Landing Page
- http://hdl.handle.net/11368/2924758
- http://hdl.handle.net/11368/2924758
- OA Status
- green
- Cited By
- 1
- Related Works
- 6
- OpenAlex ID
- https://openalex.org/W2922945426
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2922945426Canonical identifier for this work in OpenAlex
- Title
-
Development of biomonitoring techniques of persistent airborne pollutants using native lichensWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-03-27Full publication date if available
- Authors
-
Lorenzo FortunaList of authors in order
- Landing page
-
https://hdl.handle.net/11368/2924758Publisher landing page
- PDF URL
-
https://hdl.handle.net/11368/2924758Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://hdl.handle.net/11368/2924758Direct OA link when available
- Concepts
-
Biomonitoring, Lichen, Pollutant, Environmental science, Environmental chemistry, Geography, Chemistry, Ecology, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2019: 1Per-year citation counts (last 5 years)
- Related works (count)
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6Other works algorithmically related by OpenAlex
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| abstract_inverted_index.lichens | 64, 212, 543 |
| abstract_inverted_index.lightly | 532, 555 |
| abstract_inverted_index.limited | 215 |
| abstract_inverted_index.measure | 29 |
| abstract_inverted_index.methods | 11 |
| abstract_inverted_index.period. | 62 |
| abstract_inverted_index.periods | 389 |
| abstract_inverted_index.popular | 124 |
| abstract_inverted_index.project | 2 |
| abstract_inverted_index.reason, | 203 |
| abstract_inverted_index.related | 578 |
| abstract_inverted_index.respect | 195 |
| abstract_inverted_index.results | 347, 371 |
| abstract_inverted_index.samples | 268, 355, 591 |
| abstract_inverted_index.source, | 397 |
| abstract_inverted_index.species | 81, 426, 487 |
| abstract_inverted_index.survey, | 377 |
| abstract_inverted_index.surveys | 16, 85, 209 |
| abstract_inverted_index.thalli, | 41, 147 |
| abstract_inverted_index.whereas | 148 |
| abstract_inverted_index.ICP-AES, | 518 |
| abstract_inverted_index.activity | 391 |
| abstract_inverted_index.adaptive | 450 |
| abstract_inverted_index.airborne | 19, 431 |
| abstract_inverted_index.although | 72 |
| abstract_inverted_index.analysis | 493 |
| abstract_inverted_index.climatic | 103, 150, 161 |
| abstract_inverted_index.commonly | 12 |
| abstract_inverted_index.content, | 346 |
| abstract_inverted_index.elements | 433, 514, 565 |
| abstract_inverted_index.enriched | 553 |
| abstract_inverted_index.exposure | 61, 225, 233 |
| abstract_inverted_index.lichens, | 558 |
| abstract_inverted_index.lichens. | 24 |
| abstract_inverted_index.material | 594 |
| abstract_inverted_index.measured | 265, 516 |
| abstract_inverted_index.medulla. | 506 |
| abstract_inverted_index.melanins | 418, 460 |
| abstract_inverted_index.observed | 177 |
| abstract_inverted_index.outcomes | 361 |
| abstract_inverted_index.possibly | 559 |
| abstract_inverted_index.problem. | 91 |
| abstract_inverted_index.proposal | 586 |
| abstract_inverted_index.putative | 396 |
| abstract_inverted_index.revealed | 235, 384 |
| abstract_inverted_index.samples, | 333 |
| abstract_inverted_index.seasonal | 110, 192 |
| abstract_inverted_index.selected | 305, 466 |
| abstract_inverted_index.sensors. | 156 |
| abstract_inverted_index.species. | 534 |
| abstract_inverted_index.strongly | 173 |
| abstract_inverted_index.surfaces | 547 |
| abstract_inverted_index.transect | 139 |
| abstract_inverted_index.unknown. | 453 |
| abstract_inverted_index.Suspended | 295 |
| abstract_inverted_index.Xanthoria | 118 |
| abstract_inverted_index.associate | 54 |
| abstract_inverted_index.collected | 331 |
| abstract_inverted_index.concluded | 206 |
| abstract_inverted_index.confirmed | 373 |
| abstract_inverted_index.correctly | 245 |
| abstract_inverted_index.developed | 44 |
| abstract_inverted_index.different | 581 |
| abstract_inverted_index.elements. | 467 |
| abstract_inverted_index.epiphytic | 40 |
| abstract_inverted_index.estimated | 335 |
| abstract_inverted_index.evaluated | 490 |
| abstract_inverted_index.frequency | 171 |
| abstract_inverted_index.important | 239 |
| abstract_inverted_index.influence | 100, 415 |
| abstract_inverted_index.long-term | 112 |
| abstract_inverted_index.measuring | 141 |
| abstract_inverted_index.melanised | 446, 529, 533, 546 |
| abstract_inverted_index.melanized | 481 |
| abstract_inverted_index.micro-XRF | 492 |
| abstract_inverted_index.monitored | 132, 153 |
| abstract_inverted_index.nutrients | 479 |
| abstract_inverted_index.outermost | 36 |
| abstract_inverted_index.performed | 525 |
| abstract_inverted_index.pollutant | 56 |
| abstract_inverted_index.preceding | 318 |
| abstract_inverted_index.protocols | 26 |
| abstract_inverted_index.recommend | 27 |
| abstract_inverted_index.reference | 232, 310 |
| abstract_inverted_index.sampling. | 50 |
| abstract_inverted_index.sensitive | 67 |
| abstract_inverted_index.simulated | 290 |
| abstract_inverted_index.variables | 151 |
| abstract_inverted_index.yardstick | 240 |
| abstract_inverted_index.Therefore, | 92, 571 |
| abstract_inverted_index.analytical | 590 |
| abstract_inverted_index.biomonitor | 429 |
| abstract_inverted_index.coal-fired | 274 |
| abstract_inverted_index.collection | 322 |
| abstract_inverted_index.comparable | 224 |
| abstract_inverted_index.concerning | 77 |
| abstract_inverted_index.correlated | 174, 358 |
| abstract_inverted_index.dispersion | 254, 292 |
| abstract_inverted_index.experiment | 523 |
| abstract_inverted_index.hypothesis | 458 |
| abstract_inverted_index.inactivity | 393 |
| abstract_inverted_index.increasing | 560 |
| abstract_inverted_index.inter-site | 107, 178 |
| abstract_inverted_index.parietina, | 119 |
| abstract_inverted_index.persistent | 18 |
| abstract_inverted_index.pollutants | 20, 33 |
| abstract_inverted_index.retention. | 422 |
| abstract_inverted_index.sequential | 521 |
| abstract_inverted_index.successive | 388 |
| abstract_inverted_index.validation | 251, 283 |
| abstract_inverted_index.Afterwards, | 507 |
| abstract_inverted_index.Particulate | 296 |
| abstract_inverted_index.alternative | 286 |
| abstract_inverted_index.altitudinal | 138 |
| abstract_inverted_index.atmospheric | 253 |
| abstract_inverted_index.authorities | 308 |
| abstract_inverted_index.biomonitor. | 126 |
| abstract_inverted_index.conditions, | 71 |
| abstract_inverted_index.demonstrate | 540 |
| abstract_inverted_index.differences | 162 |
| abstract_inverted_index.highlighted | 158 |
| abstract_inverted_index.homogeneous | 218 |
| abstract_inverted_index.improvement | 8 |
| abstract_inverted_index.purportedly | 43 |
| abstract_inverted_index.variability | 108, 179 |
| abstract_inverted_index.artificially | 504 |
| abstract_inverted_index.availability | 168 |
| abstract_inverted_index.climatically | 217 |
| abstract_inverted_index.investigated | 98 |
| abstract_inverted_index.periods.\nIn | 226 |
| abstract_inverted_index.photobionts. | 570 |
| abstract_inverted_index.surroundings | 271 |
| abstract_inverted_index.Parmeliaceae, | 437 |
| abstract_inverted_index.biomonitoring | 15, 84, 208 |
| abstract_inverted_index.characterized | 442 |
| abstract_inverted_index.concentration | 398, 510 |
| abstract_inverted_index.environmental | 70 |
| abstract_inverted_index.investigating | 413 |
| abstract_inverted_index.melanisation, | 584 |
| abstract_inverted_index.non-melanised | 557 |
| abstract_inverted_index.non-melanized | 483 |
| abstract_inverted_index.normalization | 341 |
| abstract_inverted_index.pseudotissues | 484 |
| abstract_inverted_index.significantly | 190, 402 |
| abstract_inverted_index.site-specific | 102, 149, 160 |
| abstract_inverted_index.Unfortunately, | 63 |
| abstract_inverted_index.concentrations | 264 |
| abstract_inverted_index.differentiated | 440 |
| abstract_inverted_index.meteorological | 311 |
| abstract_inverted_index.above-mentioned | 338 |
| abstract_inverted_index.bioavailability | 562 |
| abstract_inverted_index.underestimation | 88 |
| abstract_inverted_index.former.\nFinally, | 406 |
| abstract_inverted_index.thermo-hygrometric | 155 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5009562751 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.6100000143051147 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.76901785 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |