Supplementary Material s76

Supplementary Material

Biomonitoring study of airborne particulate matter emitted from a cement plant. Comparison with dispersion modelling results

Gabriela A. Abril, Eduardo D. Wannaz*, Ana C. Mateos, María L. Pignata

Content

- Meteorological data validation

- Biomonitoring species

- Foliar Damage Index

- Enrichment Factor calculation

- Emission rate calculations

Table S1. Quality control results (μg.g-1 DW) obtained from the analysis of tobacco leaves “CTA-OTL-1” (Institute of Nuclear Chemistry and Technology) by flame atomic absorption spectrometry (FAAS).

Table S2. Pseudototal metal concentrations in topsoils from Yocsina and at a local site in Córdoba, Argentina.

Table S3. Comparison of mean heavy metal accumulation values in T. capillaris exposed at two sites close to the clinker cooler stack, with the remaining sites situated in the vicinities of the cement plant (C) in Córdoba, Argentina.

Table S4. ANOVA analysis of physiological damage in T. capillaris exposed at the cement plant in Córdoba, Argentina, between the subareas NE, SW, E, W and C. The LSD Test was applied when significant differences were found (p < 0.05).

Table S5. Estimated emission rates obtained through the emission factor technique for point and area sources from the cement plant located in the Province of Córdoba, Argentina.

Figure S1. Linear regression models representing the correlation between temperature, wind direction and wind speed from Cordoba Airport station and Tropezón station.

Figure S2. Mean EFB values for heavy metals as a whole and between sites in exposed T. capillaris leaves.

Figure S3. Mean EFTS values for heavy metals as a whole and between sites in exposed T. capillaris leaves.

Figure S4. Maximum predicted PM10 concentration values (μg/m3) emitted from point and area sources of the cement plant for the 7 years of study (2006-2012). Results obtained from the application of the ISC3 model.

Meteorological data validation

Wind roses were elaborated to illustrate flow vectors (wind blowing to) for the period 2006-2012 from data provided by the National Weather Service (2012), Córdoba airport station, which is located at approximately 12 km NE of the study area. There is a closer meteorological station that collects diurnal data (Tropezón station, at 1 km from the study area); however these are not steady throughout each day. These meteorological gaps do not allow to undertake an adequate application of atmospheric dispersion models, therefore, in order to assess the accuracy of the meteorological data from Cordoba Airport station, the variables “temperature”, “wind speed” and “wind direction” were correlated with data from Tropezón station (n = 356) showing strong associations with correlation coefficients R2 >0.7 (Figure S1).

Figure S1. Linear regression models representing the correlation between temperature, wind direction and wind speed from Cordoba Airport station and Tropezón station.

Biomonitoring species

Species from the Tillandsia genus (epiphytic plants usually found in the Southern Hemisphere) are common biomonitors used in studying heavy metals in the air due to their particular physiological characteristics (Pignata et al., 2002). The morphology of most species of Tillandsia consists of trichomes in the epidermal leaf surfaces, which allow the efficient absorption of scarce nutrients and liquid water directly from the atmosphere into the leaf (Benz and Martin, 2006). Furthermore, a recent study from Papini et al. (2010) on the ultrastructure of Tillandsiatrichomes, described apoptotic mechanisms at maturity acting as a passive pump and thus achieving an important function in the absorption mechanism.

Tillandsia genus is completely epiphytic, permitting a strong independence from the soil; thereby the only function of the adventitious roots is to adhere to a substratum (Papini et al., 2010). For this reason, it is especially suitable for air pollution monitoring, since the symptoms presented are clearly independent from soil conditions, thus making it easier to establish patterns for biomonitoring studies (Segala Alves et al., 2008).

Foliar Damage Index

This index has been statistically checked and used in previous biomonitoring studies with the same species, demonstrating that it is an adequate biomarker of pollutant effects (Wannaz and Pignata, 2006; Bermudez et al., 2009), and is given by the following equation:

[1] FDI = (Chl-b/Chl-a + S/Sb) . (MDA/MDAb + HPCD/HPCDb) . (DW/FW)

where:

Chl-b: chlorophyll b concentration in mg.g-1 DW

Chl-a: chlorophyll a concentration in mg.g-1 DW

S: sulfur content in mg.g-1 DW

MDA: malondialdehyde concentration in nmol.g-1 DW

HPCD: hydroperoxy conjugated dienes in μmol.g-1 DW

DW/FW: dry to fresh mass ratio

Parameters with subscript b in the denominator represent the arithmetic mean values calculated in the basal samples.

Enrichment Factor calculation

The EFs, which have been normalized with Fe, are given by the equations [1] and [2] shown below:

[1] EFB = (M/Fe)exposed/(M/Fe)basal

where [M] is the heavy metal concentration in the exposed and basal T. capillaris samples (mg kg–1 DW) and [Fe] is the total concentration of Fe using the same units and matrices. The values obtained from this equation were assessed according to the scale used by Frati et al. (2005), where values between 0.75-1.25 indicate normal EF; 1.25-1.75 accumulation and EF>1.75 indicate severe accumulation.

[3] EFTS = (M/Fe)sample/(M/Fe)topsoil

where [M] is the heavy metal concentration in T. capillaris samples and topsoil (mg kg–1 DW) and [Fe] is the total concentration of Fe using the same units and matrices (Olmez et al. 1985). Elements with EFTS values near unity may indicate a natural origin, while higher values reflect a potential anthropogenic source, especially for those elements with enrichment values of EFTS>3 (Dongarrá and Varrica, 1998).

Table S2. Pseudototal metal concentrations in topsoils from Yocsina and at a local site in Córdoba, Argentina.

Composite samples consisted of 9 subsamples each (Bermudez, 2011) and 2 subsamples each (Salazar et al, 2012 published and unpublished results). Coordinates:

Malagueño, Yocsina (-31°26'37.10'' S; -64°22'18.51''W)

South of Córdoba city (-31°30'36.06"S; -64°10'18.91"W).

Figure S2. Mean EFB values for heavy metals as a whole and between sites in exposed T. capillaris leaves.

Figure S3. Mean EFTS values for heavy metals as a whole and between sites in exposed T. capillaris leaves.

Emission rate calculations

The emission factor estimation technique was used to evaluate the emissions from the cement facility under study using the Australian Governments “Emission Estimation Technique Manual for Cement Manufacturing-National Pollution Inventory” (NPI, 2008) and the AP-42 guide “Compilation of Air Pollutant Emission Factors” (EPA, 1997), since no additional data were provided from the cement company. These manuals provide procedures and recommended approaches for estimating emissions from facilities engaged in cement manufacturing (Abdul-Wahab, 2006) with the emission factors obtained being the input data for modelling with ISCST3. The dispersion calculations obtained for the PM10 emissions were considered to be steady throughout each day, as cement plants only usually stop their activities for kiln cleaning. The annual operating time of this kiln was estimated to be 8040 hours, taking into consideration that rotary kilns work 24 hours a day, except for maintenance interruptions.

For the PM10 emission rate calculations for point sources, the following equation was used:

[4] EPM10 = AR . Ophs . EFPM10

where:

EPM10: PM10 Emission rate (kg/y)

AR: Activity Rate (ton/h)

Ophs: Annual operating hours (h/y)

EFPM10: Uncontrolled PM10 emission factor (kg/ton)

The equation for estimating the emission rates for limestone quarries and active stockpiles was the following:

[5] EPM10 = EFPM10 . area . ERPM10

where:

EPM10: PM10 Emission rate (kg/y)

EFPM10: PM10 emission factor (kg/ha/h)

Area: Emission area (ha)

ERPM10: PM10 emission factor reduction (%).

No information was available on site-specific factors, hence the default emission factor of EFPM10 = 0.3 kg/ha/h was used (Abdul-Wahab, 2006). At the cement plant under study, no emission reduction mechanisms are used to suppress dust.

Table S5. Estimated emission rates obtained through the emission factor technique for point and area sources from the cement plant located in the Province of Córdoba, Argentina.

References

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