Atmospheric pollen survey: a metrological study between Hirst and Cour sampling methods

Transcription

1 Atmospheric pollen survey: a metrological study between Hirst and Cour sampling methods Farrera I. 1, M. Calleja 1, J. Belmonte 2, T. Almeras 1 & I. Plaisant 3 1 Unité de Palynologie. École Nationale Supérieure Agronomique Montpellier (ENSAM). France 2 Botany Unit. Autonomous University of Barcelona. Cerdanyola del Vallès. Spain 3 DRASS Languedoc Roussillon. France TESA Worcester 23 Hirst-Cour Comparison 1

2 Objectives To compare the Cour and Hirst aerobiological sampling methods from the point of view of the: advantages and disadvantages of each method evaluation of the repeatability of the measurements of each method analysis of the differences between results of the two methods TESA Worcester 23 Hirst-Cour Comparison 2

3 Study design Montpellier (Fr) Comparison Cour-Hirst From 31/12/1 to 5/8/2 31 weeks H C 1 1 Repeatability Cour and Hirst From 24/6/2 to 5/8/2 6 weeks H C 2 2 H Hirst sampler C Cour sampler Same experimental conditions TESA Worcester 23 Hirst-Cour Comparison 3

4 HIRST sampler Burkard Lanzoni RNSA counting methodology Light microscopic analysis of 12 transversal lines MON 22/2d4 N Number of pollen grains RNSA Réseau National de Surveillance Aérobiologique (France) TESA Worcester 23 Hirst-Cour Comparison 4

5 HIRST methodology calculations Light microscopic analysis of 12 transversal lines w a Slide area = l L = 14 mm x 48 mm = 672 mm 2 =.672 m 2 a Analyzed area = 12 (l w) = 12 (14 w) =168w =.168w m 2 Number of pollen grains per analyzed area Air volume analyzed per day = 14.4 m 3 1 l/min x (24h/day x 6min/h) x 1/1 m 3 /l MON 22/2d4 l L Mean dayly pollen concentration N x (Sa/Aa) / 14.4 m 3 Pollen grains per volume unit TESA Worcester 23 Hirst-Cour Comparison 5

6 COUR sampler Rain Protection Filter Filter Vane Wind Run Anemometer Axis TESA Worcester 23 Hirst-Cour Comparison 6

7 COUR methodology Gauze Filter Laboratory protocol: H 2 SO 4, HCl, HF, KOH Acetolysis (Erdtman 196) Slight pressure makes pollen turn over itself Adhesive border 2V MON S31 Known volumes: Glycerogelatin Pollen and spore sediment 5 ul V t V Light microscopic analysis of 5 longitudinal lines N Number of pollen grains TESA Worcester 23 Hirst-Cour Comparison 7

8 COUR methodology calculations (1) cm cm2 2 cm 2 cm S Filter Surface =.2 m 2 V t Total sediment volume v Slide volume = 5 ul 2V MON S31 w l L Aa Analyzed area = 5 (l l w) w Sa Slide area = l L Number of pollen grains per analyzed area = N Number of pollen grains per filter (week) N x (V t / v) x (Sa/Aa) / S Pollen grains per surface unit TESA Worcester 23 Hirst-Cour Comparison 8

9 COUR methodology calculations (2) Longitude of the air column (Wr( Wr) passing across the 2cmx2cm gauze filter during the exposition period Efficiency (filter resistance) 1/5 of wind run ind Run Anemometer Mean weekly pollen concentration N x (V t / v) x (Sa/Aa) / S x (Wr/5) Pollen grains per volume unit TESA Worcester 23 Hirst-Cour Comparison 9

10 Objective 1 Advantages and disadvantages of the Hirst and Cour methods TESA Worcester 23 Hirst-Cour Comparison 1

11 omparison Cour/Hirst (operational point of view) Hirst method!!! Key aspects Cour method Need of electricity Yes (Battery) No Dimension of the sampling surface 14mm x 2 mm 2 cm x 2 cm Facility to remove and install periodical samples Attention needed Easy Protocol previous to Laboratory protocol microscopic analysis Easy needed Pollen grain observation!!! Good Very good Fungal spore observation!!! Good Some of them lost Lost of slide sample Irreparable Reparable Frequency of sampling Daily (Hourly) Weekly ((Daily)) Economy Cost of the sampler Cost of functioning!!! Expensive Cheap Cheap Expensive Better option TESA Worcester 23 Hirst-Cour Comparison 11

12 Objective 2 Repeatability of the measurements Comparison Hirst 1 - Hirst 2 Cour 1 - Cour 2 Items Taxonomic richness Daily / Weekly concentrations Daily / Weekly abundance classes Observation period of 6 weeks TESA Worcester 23 Hirst-Cour Comparison 12

13 Comparison of the taxonomic richness 8 7 Hirst method Hirst 1 / Hirst Cour method Cour 1 / Cour Taxa number Taxa number Week number Mean = 27 Mean of the weekly differences = 8% Week number Mean = 58 Mean of the weekly differences = 8% Hirst and Cour methods are equally repeatable TESA Worcester 23 Hirst-Cour Comparison 13

14 Comparison of the pollen concentrations Statistical approach: 1-WAY ANOVA or KRUSKAL-WALLIS (NPAR1 WAY) H There is not a method effect Applied to Hirst 1 / Hirst 2 and to 2*342 observations Cour 1 / Cour 2 2*666 observations Pvalue >,5 Pvalue >,5 H is accepted, the global variability observed in the data series is not explained by the method effect Hirst/Hirst and Cour/Cour show not significant differences TESA Worcester 23 Hirst-Cour Comparison 14

15 Comparison of the pollen concentrations Hirst daily data series an example 2 8 Daily data comparison - Poaceae - Montpellier 22 Hirst 1 Hirst J24 J26 J28 J3 JL2 JL4 JL6 JL8 JL1 JL12 JL14 JL16 JL18 JL2 JL22 JL24 JL26 JL28 JL3 AG1 AG3 Days Class daily data comparison - Poaceae - Montpellier 22 Hirst 1 Hirst 2 Concordant 71,4% J24 J26 J28 J3 JL2 JL4 JL6 JL8 JL1 JL12 JL14 JL16 JL18 JL2 JL22 JL24 JL26 JL28 JL3 AG1 AG3 Days TESA Worcester 23 Hirst-Cour Comparison 15

16 Comparison of the abundance classes Hirst daily and weekly data series - statistics 49 pollen taxa (present at least once in both methods in the 6 weeks) Relative mean of the differences (Rel mean dif) of repeatability per abundance classes with 5% confidence interval Hirst method - Daily data Abundance class Rel mean dif 1 <1 25% % % % 5 >1 19% Hirst method - Weekly data Abundance class Rel mean dif 1 <1 183% % % % Smaller differences when higher concentrations TESA Worcester 23 Hirst-Cour Comparison 16

17 Comparison of the abundance classes Cour weekly data series - statistics Cour method - Weekly data Abundance class Rel mean dif 1 <1 11% % % % Cour method - Weekly data Abundance class Rel mean dif 1''' <.5 211% 1'' % 1' % Smaller differences when higher concentrations TESA Worcester 23 Hirst-Cour Comparison 17

18 Objective 3 Analysis of the differences Comparison Hirst 1 - Cour 1 Items Taxonomic richness Weekly concentrations Weekly abundance classes Observation period of 31 weeks TESA Worcester 23 Hirst-Cour Comparison 18

19 Percentage period w1 - w31 Percentage period w1 - w31 Taxon HIRST COUR Taxon HIRST COUR ABIES, LIPPIA, ACACIA,4,49 LIQUIDAMBAR,1,9 ACER 1,159,796 MELIA,1 AESCULUS,48,36 MERCURIALIS,49,24 AILANTHUS,2,8 MONOCOTYLEDONEAE HERBS,5,24 ALNUS,394,239 MORACEAE 3,968 2,479 AMBROSIA,2,1 OLEA,633,68 ARTEMISIA,4,6 APIACEAE,16,36 BETULA,989,521 OSTRYA,1 To be revised BORAGINACEAE,2,6 OXALIS, BUDLEJA Not det.,2 PALM TREES,17, BUXUS,4,456 PAPAVERACEAE,4,36 CANNABACEAE,9,11 PAPILIONACEAE,4,119 CARPINUS,77,193 PARTHENIUM Not det.,7 CARYOPHYLLACEAE,,1 PHILLYREA,24,81 CASTANEA 2,224 2,62 PICEA,16,6 CEDRUS,3,2 PINUS 9,748 11,111 CELTIS,217,296 PISTACIA,187,19 CENTAUREA,1,1 PLANTAGO,681,558 CHENOPODIACEAE/AMARANT.,16,17 PLATANUS 7,187 6,726 CISTACEAE,5,1 POLYGONUM,2 CONVOLVULUS, POPULUS 2,4 2,698 ASTERACEAE ECHINATE,23,15 PRIMULACEAE Not det.,1 ASTERACEAE FENESTRATE,17,29 POTERIUM,6,6 CORIARIA,6,5 PUNICA,2 CORYLUS,625,37 QUERCUS TOTAL 18,45 15,81 CRASSULACEAE,4, RANUNCULACEAE,16,37 BRASSICACEAE,27,37 RESEDA,2,1 CUCURBITACEAE,1 RHAMNUS,16,15 CUPRESSACEAE 38,468 44,956 RHEUM Not det.,1 CYPERACEAE,53,56 RHUS Schinus?,5 DIOSPYROS Not det.,3 RICINUS, DIPSACACEAE,1,1 ROSACEAE lign.,2,29 ELAEAGNUS,2,1 RUBIACEAE,5,19 EPHEDRA,1 RUMEX,178,145 ERICACEAE TOTAL,113,8 SALIX,279,348 EUCALYPTUS (MYRTACEAE),9,1 SAMBUCUS,1,5 EUPHORBIA,2,2 SCHINUS,1 Rhus? FAGUS,152,126 SCROFULARIACEAE,,16 FRAXINUS 6,166 4,541 SOLANACEAE,,1 GINKGO Not det.,36 TAMARIX,64,114 POACEAE CEREAL,8,22 TAXODIUM Cupressaceae,3 POACEAE WILD 2,355 1,672 TAXUS Cupressaceae,514 HEDERA,2,1 TILIA,18,38 HELIANTHUS,,2 THIMELACEAE,, HYPERICUM,2 TSUGA Not det.,1 ILEX,7,1 TYPHA,17,18 JUGLANS,27,18 ULMUS,225,238 JUNCUS,16 Acetolysis!!! URTICACEAE 2,45 1,321 LAMIACEAE,7,3 VIBURNUM,2,37 LAGERSTROMIA, VITIS,136,155 LARIX Non det.,4 XANTHIUM,, LIGUSTRUM,29,85 ZIZIPHUS Non det.,1 BROKEN -UNKNOWN,95,46 Pollen Taxa number Hirst 84 Cour 112 TESA Worcester 23 Hirst-Cour Comparison 19

20 Comparison of the taxonomic richness Number of taxa Cour 2 1 Hirst Weeks Cour method shows higher taxonomic richness TESA Worcester 23 Hirst-Cour Comparison 2

21 Comparison of the pollen concentrations Statistical approach: Wilcoxon signed rank text (non parametric) with paired data H There are no differences between the mean results from Hirst and Cour methods Applied to Hirst 1 / Cour 1 2*1984 observations Pvalue <,5 H is rejected, the two methods give mean different results Hirst and Cour methods give different mean results TESA Worcester 23 Hirst-Cour Comparison 21

22 Comparison of the abundance classes Hirst - Cour weekly data series - statistics Hirst and Cour methods - Weekly data Abundance class Mean concentration Differences Mean values Hirst Cour respect Cour 1 <1,147,299-51% ,961 2,892-32% ,423 1,213-8% ,977 52,54-41% 5 >1 352, ,467-33% Cour method shows higher mean concentrations maller differences in the abundance class 3 (5-2 P/m³) TESA Worcester 23 Hirst-Cour Comparison 22

23 Comparison of the pollen concentrations Hirst/Cour data series examples Cour Hirst Cupressaceae Mean H 161,3 P/m³ Mean C 266,7 P/m³ Dif. r. Cour -4% P/m³ Cour Poaceae Hirst Mean H 9,9 P/m³ Mean C 1,4 P/m³ Dif. r. Cour -5% Cour Platanus Hirst Mean H 3,1 P/m³ Mean C 39,4 P/m³ Dif. r. Cour -24% TESA Worcester 23 Hirst-Cour Comparison 23 P/m³ Cour Hirst Urticaceae Mean H 1,3 P/m³ Mean C 8,4 P/m³ Dif. r. Cour +23%

24 Comparison of the pollen concentrations Hirst/Cour data series a proposal Efficiency (filter resistance) 1/6 of wind run (instead 1/5) Cour Hirst Cupressaceae Mean H 161,3 P/m³ Mean C 222,2 P/m³ Dif. r. Cour -27% Cour Platanus Hirst Mean H 3,1 P/m³ Mean C 32,8 P/m³ Dif. r. Cour -8% TESA Worcester 23 Hirst-Cour Comparison 24 P/m³ P/m³ Cour Poaceae Hirst Mean H 9,9 P/m³ Mean C 8,7 P/m³ Dif. r. Cour +14% Cour Hirst Urticaceae Mean H 1,3 P/m³ Mean C 7, P/m³ Dif. r. Cour +47%

25 Hirst/Cour data series other considerations Cour Hirst Cupressaceae Montpellier 22 P/m³ Weeks TESA Worcester 23 Hirst-Cour Comparison 25

26 Hirst/Cour data series other considerations Cour Week Hirst Week Hirst Day Cupressaceae Montpellier D31 Ja1 Ja2 Ja3 F9 F19 M1 M11 M21 M31 A1 A2 Days A3 My1 My2 My3 Ju9 Ju19 Ju29 Jl9 Jl19 Jl29 TESA Worcester 23 Hirst-Cour Comparison 26

27 Hirst/Cour data series other considerations Cour Week Hirst Week Hirst Day Cupressaceae Montpellier P/m³ F1 F3 F5 F7 F9 F11 F13 F15 F17 F19 F21 F23 F25 F27 M1 M3 M5 M7 M9 M11 M13 M15 M17 M19 M21 M23 M25 M27 M29 19 Week 8 Days TESA Worcester 23 Hirst-Cour Comparison 27

28 Conclusions More investigation is needed on metrological aspects (i.e. per pollen type) Hirst and Cour methods showed: - to be metrologically acceptable - to estimate atmospheric pollen content quite similarly The election of the method to be used should be based on the objectives of the study TESA Worcester 23 Hirst-Cour Comparison 28