the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
01 Jul 2021
01 Jul 2021
Mass concentrations of autumn bioaerosol in a mature temperate woodland Free Air Carbon Dioxide Enrichment (FACE) experiment: investigating the role of meteorology and carbon dioxide levels
- 1School of Geography, Earth & Environmental Sciences, University of Birmingham, Birmingham, B152TT, UK
- 2Birmingham Institute of Forest Research, University of Birmingham, Birmingham, B152TT, UK
- 1School of Geography, Earth & Environmental Sciences, University of Birmingham, Birmingham, B152TT, UK
- 2Birmingham Institute of Forest Research, University of Birmingham, Birmingham, B152TT, UK
Abstract. Forest environments contain a wide variety of airborne biological particles (bioaerosols), including pollen, fungal spores, bacteria, viruses, plant detritus and soil particles. Forest bioaerosol plays a number of important roles related to plant and livestock health, human disease and allergenicity, forest and wider ecology, and are thought to influence biosphere/atmosphere interactions via warm and cold cloud formation. Despite the importance of bioaerosols, there are few measurements of forest aerosol, and there is a lack of understanding of how climate change will affect forest bioaerosol in the future.
We installed low-cost optical particle counters (OPCs) to measure particles in the size range between 1 and 10 μm, where bioaerosols will likely dominate the particle mass concentration, for a period of two months in Autumn 2018 at the Birmingham Institute of Forest Research (BIFoR) Free Air Carbon Dioxide Enrichment (FACE) facility. The BIFoR FACE facility fumigates three 700 m2 areas of the forest with an additional 150 ppm CO2 above ambient with minimal impacts on other potential environmental drivers such as temperature, humidity, and wind. This experimental set-up enabled us to investigate the effect of environmental variables, including elevated CO2 (eCO2), on bioaerosol concentrations, and to evaluate the performance of the low-cost OPCs in a forested environment.
Operating the low-cost OPCs during Autumn 2018, we aimed to capture predominantly the fungal bioaerosol season. Across the experimental duration, the OPCs captured both temporal and spatial variation in bioaerosol concentrations. Aerosol concentrations were affected by changing temperatures and wind speeds, but, contrary to our initial hypothesis, not by relative humidity. We detected no effect of the eCO2 treatment on total bioaerosol concentrations, but a potential suppression of high concentration bioaerosol events was detected under eCO2. In-canopy atmospheric dispersion modelling indicates that the median spore dispersion distance is sufficiently small that there is little mixing between treatment and control experiments. Our data demonstrate the suitability of low-cost OPCs, interpreted with due caution, for use in forests, and so opens the possibility of forest bioaerosol monitoring in a wider range of habitats, to a wider range of researchers at a modest cost.
Aileen B. Baird et al.
Status: final response (author comments only)
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RC1: 'Comment on bg-2021-162', Branko Sikoparija, 19 Jul 2021
General Comments
The study aimed to compare quantity of fungal bioaerosols measured under forest canopy in plot with normal and elevated atmospheric CO2 concentrations. Also, the correlations to meteorological conditions (wind speed, relative humidity, temperature) are assessed. The study attempts to answer important research question of effects climate change could have on bioaerosol emissions in forests. The manuscript is well written, and scientific results and conclusions are presented in a clear, concise, and well-structured way. However, there are several concerns regarding methodology.
The authors should make additional effort to assure that data collected by used optical particle counters represent bioaerosols. Notable quantity of inorganic particles should be present in the size range analysed and there is no evidence that bioaerosols dominate. A notable amount of sand particles or plant debris can be suspended in the atmosphere, especially in Autumn.
The hypotheses are focused on fungal spores, and it should be better addressed in results what is efficiency of used methodology for sampling expected diversity of fungal spores in studied environments. The authors clearly indicated that the size range chosen for the analysis (1-10 μm) is just the fraction of typical size range for fungal spores (1-30 μm). But in my view this creates more serious issue than just missing the effect of eCO2 on some specific fungi. It can result in complete miss the quantity.
Also, there is a concern that in high humidity conditions optical particle counter could detect small water droplets enhancing positive correlation between RH and particle counts.
Actually failure to validate that record from optical particle counter (PM 1-10) corresponds to total bioaerosols (if not total fungal spores) severely undermines the possibility to test research questions set by authors. Without such validation the authors have results for PM 1-10 and the relation to bioaerosols or fungal spores can only be discussed.
Specific Comments
More details about setup of instruments would be needed. For how long particle samples were taken every 60s and what is the volume of air sampled? At what height the sensors were positioned?
If high resolution wind measurements are available, I would encourage authors to check also the effect of turbulent kinetic energy on particle concentrations since the atmospheric instability could have more pronounced effect on spore dispersion than the wind speed alone.
Regarding the effects of eCO2 the authors should indicate what direct and what indirect effects are expected to increase fungal bioaerosol concentrations. It is not clear whether the CO2 increase is expected only in canopy layer or also at the ground layer where notable number of fungal spore sources could be growing. In my view eCO2 is expected to increase the vegetative mass of plants but such direct effect is not so straightforward for fungal spore sources since for many the growth and sporulation might have started only after the fumigation has ended. So if the most feasible is indirect effect through increase in amount leaf litter (as discussed) would not then be meaningful to have information about the quantity of leaf litter. This way the authors speculate twice: that the leaf litter is increased and that such increase relates to airborne fungal spore emission.
Finally, since the dispersion model indicated threshold wind conditions under which mixing between plots is neglectable I suggest looking into differences in particle concentrations after wind speeds above that threshold is eliminated.
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AC1: 'Reply on RC1', Francis Pope, 23 Jul 2021
The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2021-162/bg-2021-162-AC1-supplement.pdf
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AC1: 'Reply on RC1', Francis Pope, 23 Jul 2021
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CC2: 'Comment on bg-2021-162', Matt Smith, 24 Jul 2021
The manuscript is well written, and the topic is important because low-cost optical particle counters (OPCs) are likely to have a place in aerobiological monitoring. However, the authors make a number of assumptions about the data that should be addressed.
There are several inherent problems with the use of PM data as a proxy for bioaerosols, as there will be both organic and inorganic particles in the air, even in rural settings. Although the levels of dust in the air during autumn in the UK will not be as noticeable as other parts of the world, such as in Continental or Mediterranean climates, this should also be accounted for. It is even more problematical to say that the particles are 'fungal spores' as there are no fungal spore data available for comparison.
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AC2: 'Reply on CC2', Francis Pope, 05 Nov 2021
Thank you to all the reviewers for your comments and feedback on “Mass concentrations of autumn bioaerosol in a mature temperate woodland Free Air Carbon Dioxide Enrichment (FACE) experiment: investigating the role of meteorology and carbon dioxide levels”. In addition to our earlier response to RC1, we address each of the comments in turn below.
In the short comment (CC2), the reviewer raises a concern that PM data cannot be used as a proxy for bioaerosols (or fungal spores), as both organic and inorganic particles will be present in the air. As noted in our earlier response to reviewer 1, it is correct that the optical particle counters do not explicitly discriminate between bioaerosols and other aerosol types, however we believe that due to the size of particles we are investigating (1-10 µm), the location of the measurements that are within a woodland, the timing of the measurement period, as well as the low hygroscopicity of the particles measured, it is very likely we are predominantly measuring a biological source. Whilst we do believe that the dominant source of particles in the PM10-PM1 size fraction is composed of bioaerosols, any non-biological aerosols in the PM10-PM1 fraction should be very similar between each pair of experimental plots due to their close proximity to each other (<100 m).
In response to the earlier comment from Reviewer 1 who also expressed concern regarding the possibility of dust inclusions during the measurement period, we compared our PM data with the CAMS global reanalysis (EAC4) and there was no correlation present, and this is therefore unlikely to be a confounding factor.
We will adjust the text to highlight our responses to above points.
This study was designed to investigate the possibilities of using low-cost sensors to measure bioaerosols, with the hope of opening up the field to enable use of such sensors in a wider variety of environments by a wider range of researchers. We hope that the study will lead to further research using a variety of concurrent measurement instruments, so that the ability to use PM as a proxy for either anthropogenic emissions or bioaerosols can be further assessed.
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AC2: 'Reply on CC2', Francis Pope, 05 Nov 2021
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RC2: 'Comment on bg-2021-162', Madeleine Petersson Sjögren, 18 Oct 2021
I believe this manuscript addresses relevant and interesting scientific questions within the scope of BG. In general, the aim, the methods and the conclusions for the study are clearly presented. I believe the authors refer to relevant references. The paper presents a novel method for measurement of biological aerosol particles. I believe you could consider including the use of low-cost sensors in the title since this is an important concept of the paper.
The abstract is clear and straight-forward. I believe the references in the introduction are relevant. When reading the introduction I was curious if the type of sensors you are using have ever been used in the same way before? I’m also wondering if it can be made clearer why you hypothesize that the fungal bioaerosol concentration should increase with increasing CO2?
The methods section is extensive. I believe the confirmation done with the macro-fungi survey is important but I’m not sure you explain this survey thoroughly: Would it be possible to extend on this matter? I work with aerosols and bioaerosols but I am not familiar with this type of macro-fungi survey. Or put in a reference?
In the instrumentation section you make assumptions about the particle density and the refractive index, how did you chose those? Do you have a reference for the choice?
Did you look into the literature how the presumed concentrations of bioaerosols that you measure compare to the concentrations measured with other more specific instruments (e.g. WIBS and UV-APS) in forests?
In general I believe you do not report on the statistical methods used extensively enough. For instance, the Loess curve you fit is only mentioned in figure captions but not in the text. Why did you fit a Loess curve? What relationships did you expect? In row 309 a linear relationship is mentioned but I find no account of how the linearity of the relationship was assessed. What statistical tests were used to assess if there is a difference or not in row 339? When listing your conclusions, could you include significance? For instance for the decrease in bioaerosol at lower temperatures? How was this decrease measured? In scatter plots you show prediction intervals/confidence intervals: can you explain them in the text?
On row 256 you mentioned that RH was high throughout the measurement period, clarify what you mean by high?
Text in Figure 2-Figure 7 are too small. Legends are also missing and should be put in. Make sure you clearly explain the difference between colors in the plots. For Figure 2 a difference in color intensity is mentioned in the caption but I can’t detect this intensity difference, can you clarify this? For panel E and F in Figure 2, is the data hourly or daily? What is the resolution for the data displayed in Figure 3A?
At row 296-297, there is a sentence “Detecting events..”, is this a conclusion you’re making about the sensors? I’m not sure I follow the reasoning, can you extend on it?
When listing your conclusions, could you include significance? For instance for the decrease in bioaerosol at lower temperatures? How was this decrease measured btw?
Technical issues:
r. 34: Missing/redundant parenthesis bracket?
r. 93 (first row of method) add , UK. after “Staffordshire”.
Figure 1: can you possibly mark the array pairs in some way? (to make it obvious that they are pairs)
r. 145 Perhaps you would like to include a reference for the OPC Mie scattering since you are mentioning this
r. 177 reference missing
r. 177 maybe you can refer to Table 1 here so it’s clear that the OPC:s were moved around among the different arrays.
Table 1: To make the table easier to read, can possibly leave out the year and just have month and day for the date range?
Figure 4: Reference is missing here. Also check that the caption is correctly written.
Figure 5: Can these figures be adjusted to fit into one and the same frame. As they are now presented they take up a lot of space.
r. 343 reference missing.
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AC3: 'Reply on RC2', Francis Pope, 05 Nov 2021
Thank you to all the reviewers for your comments and feedback on “Mass concentrations of autumn bioaerosol in a mature temperate woodland Free Air Carbon Dioxide Enrichment (FACE) experiment: investigating the role of meteorology and carbon dioxide levels”. In addition to our earlier response to RC1, we address each of the comments in turn below.
Regarding the 2nd review, we respond to your comments in turn below. Regarding the introduction, to the best of our knowledge low-cost optical particle counters have not been used in a forested environment or a FACE experiment before, so this study is a novel method. You also ask about the hypothesized mechanism by which fungal bioaerosol would increase. We believe we have listed the appropriate literature for this topic, however we will include a clarifying sentence on line 77, explicitly stating the link between fungal sporocarp production, spore production, and airborne fungal bioaerosol concentrations: “All of these demonstrated changes in fungal phenology, sporocarp production, and sporulation suggest that bioaerosol concentrations are also likely to change under eCO2. Even if these findings are fungal species-specific, they have potentially wide-ranging effects for forested habitats.”
You note that readers may be unfamiliar with macro-fungal survey methodology, we will add an appropriate reference to improve clarity e.g. (Van Norman et al., 2008)
Regarding assumptions made about particle density and refractive index, the values used are typical for instrumentation of this type, a reference to studies using the same assumptions will be added here. Implications of the assumptions will also be assessed.
We researched the literature for bioaerosol concentrations and believe we have referenced the relevant papers (lines 53 to 59), however it is challenging to make a direct comparison between bioaerosol concentrations measured in different forests because of the use of varying methodologies. As we described above, we hope that future studies will do direct instrumentation comparisons in the same location and measurement period in order to investigate this question further.
We appreciate your comments regarding ambiguity of the statistical methods used. We will clarify the methodology used and the rationale for using it in the text and figure legends.
You ask about the RH being described as “high” on line 256, and we think this sentence is adequately clear, as the specific RH results are stated within the same sentence.
Regarding the figure edits, we will address these along with the other technical issues listed.
Regarding the line 296, the use of “events” refers to periods of time with high PM recorded, presumed as high sporulation events, which is described on line 294, we will clarify the two sentences to: “Peaks in bioaerosol concentration (presumed high sporulation events) are visible in red, with some events being replicated across both eCO2 treatment and control (e.g. the SW quadrant event in A5 and A6), and other high PM events only occurring in a single array (e.g. the SE quadrant event in A4). By detecting high PM events in a single array at a distinct time shows that the OPCs can detect differences between the BIFoR FACE arrays.”.
Finally, you suggest adding the statistical significance values into the conclusion, and query the bioaerosol decrease at lower temperatures. Good idea. The relationship between temperature and PM values is described in lines 308 – 311 and Figure 6. We will summarise this information and put in conclusions.
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AC3: 'Reply on RC2', Francis Pope, 05 Nov 2021
Aileen B. Baird et al.
Aileen B. Baird et al.
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