Author response comment to Referee #1 (citation https://doi.org/10.5194/egusphere-2025-2500-RC1)

Thank you for your time and effort to go through the manuscript and write the constructive feedback. The comments presented points that were indeed challenges in building the statistical testing and the storyline of the manuscript, and they are very helpful to further develop the manuscript for better usability by the readers and community. We answer each specific and technical comment below, the numbered answers being the same as those in the referee comments.

Specific comments:

1. We agree that the sampling schedule between the two cities, which was caused by technical limitations, is not suitable for comparisons. Direct comparisons between the two example cities were not within our initial aims, and during the data processing, we also decided against doing any direct comparisons between the two cities. Seeing the slightly differing results between the cities, we were, however, curious to explore whether some of the differences could be connected to the variations in city size and climate. As evoked by the referee, it is possible that the differing results were also influenced by seasonality on top of the effects of the city and species selection (which also differed between the two cities), and we agree that this is a valuable point to add to the discussion on the results by city.

2. The large tree-to-tree variation was an important lesson learnt through the research process and will be taken into account in any further projects. Yet, as we sampled 6 trees per species and in total 30 trees per city – in the field – we believe that the data is still interesting to the community. The statistical tests, while low in power, give indications of the potential trends within urban areas and directions for future research. To alleviate the small sample size per species and site type, we did pool all species in the ANOVA tests, and both site types for testing against BVOC database values, so in no case did we do tests with only three trees.

3. Our aim was, most importantly, to sample trees in both common urban environments in order not to bias the results by either street or by park and to gain more representative mean values per species. We will reformulate the relevant parts of the introduction, results and discussions to better reflect this aim rather than the street-park dichotomy as needed. However, we were of course interested in exploring whether the park and street differed in BVOC emission rates, i.e. if there was any fundamental site-type effect that would override the heterogeneity within each site type (as seen, for example, for urban tree water use and water potential in Montreal, https://doi.org/10.1016/j.ufug.2025.128690). We agree that to further understand the potential street-park along with smaller spatial scale differences, more environmental data (especially soil, temperature, light environment and pollutants) would be needed in each site to disentangle these effects. For this, a study with a single urban tree species would potentially be more fruitful.

As to the potential “street effect” not being uniform across cities, we found this interesting to report as it goes partly against the common intuitive opinion that street trees must be more stressed and thus, potentially larger sources of BVOCs. The non-uniformity is also reflective of the city-to-city variation reported elsewhere (see e.g. https://doi.org/10.1016/j.envpol.2013.04.003).  We think that reporting this result can encourage further research in other cities to potentially understand which city characteristics (climate, infrastructure..) may explain the BVOC emission patterns in different urban environments.

To extend our data analysis beyond the street-park dichotomy and explore more precisely the potential characteristics within each site type that could impact the tree-to-tree variations in BVOC emissions, we performed a cross-site correlation analysis with factors of local environment that can be regarded as sources of stress. We discuss the results more in the answer to referee #1 comment 4.

4. We agree that more measurements of physiological stress indicators, such as Fv/Fm or photosynthetic capacity, would have been interesting additions to try an explain a larger portion of the tree-to-tree variation, including the observed differences between park and street environments. Of potential sources of stress, we measured WP, which, as noted also by the referee, showed no substantial drought and ambient O3 concentrations that did vary between trees and in Montreal between street and park environments. We did not have reliable quantification of invisible mechanical stressors (such as trucks hitting the tree canopy), but we did note any visual signs, including stem wounding and dry branches. In two cases, the higher emission potentials of a tree individual did not match with visual signs of stress or damage: one street PC with high emission potentials of most measured compounds both in Periods I and II did have dry shoot tips in the canopy close to the measured branch (see in supplement Figure 3 alternative version and answer to referee #2 comment 2), and one street TC with relatively high monoterpenoid emissions in Period II had had a branch pruned in earlier summer. We will add these details in the results and discussion to deepen the analysis of the potential stress factors. 

Additionally, as mentioned in the answer to referee #1 comment 3, we performed a cross-site correlation analysis with factors of local environment that can be regarded as sources of stress (see in supplement Figure R1). With this analysis, we intend to bring into the analysis details on the specific growth conditions and potential sources of stress that were called upon in the referee #1 comments 3 and 4, and referee #2 comment 1.

The analysis shows that the correlations between the potential stress factors or indicators with the BVOC emission potentials seem species-specific. However, as a commonality, high sun exposure (measured as PAR) or ambient temperature often correlated with higher emission potentials of terpenoids, even though the emission potentials are standardised to a certain temperature and PAR using G97 algorithm. 

Among species-specific correlations was the correlation of higher O3 concentrations with higher sesquiterpenoid emission potentials among AP in Montreal, both in Periods I and II. This is even though O3 concentrations measured in the study were generally low.  Surface impermeability degree in 10-m radius around the tree (in Helsinki) or as a mean of the block (in Montreal) correlated positively with PC isoprene emission potentials that were higher on the street than park, but interestingly negatively with sesquiterpenoid and GLV emission potentials of BP in Helsinki.

BVOC emission potentials often did not correlate with WP, but higher monoterpene emission potentials among QM and AP in Montreal in Period I and higher sesquiterpene emission potentials among TE in Helsinki were related to higher (less negative) water potential. This suggests that we did not see drought-induced emissions (as there was no drought), but good water status potentially supported higher emission potentials in certain species. 

Even with the addition of this analysis, we are willing to reformat the discussion part to emphasise less the potential effects of stress factors on the measured BVOCs. However, as certain VOCs such as GLVs or sesquiterpenes are generally stress-induced, we find it reasonable to assume that their high peaks may relate to a stress event even without a detailed knowledge of the type and severity of the potential stress. 

5. We agree that the upscaling exercise is simple, and it is so because the introduction of a more complex models would not yield more accurate results due to the nature of the underlying data. The idea of the exercise was not to provide an accurate representation of the neighbourhood emissions, because as mentioned by the referee, it lacks the other tree species and importantly, any private trees, but to compare the effects of species emissions and the species density in the landscape. We thank the referee for noting that this may not have been worded clearly enough in the manuscript, and we will clarify the intent of the exercise in the methods, results and discussion parts to avoid misleading the reader to interpret the values as real neighbourhood scale BVOC emission potentials. We feel that even with the presented limitations, the exercise still provides an interesting insight into the importance of low BVOC emissions of trees that are present in large numbers. However, the exercise is not crucial to the conclusions of the manuscript, so if it is seen as not providing additional value to the manuscript, we are willing to submit the manuscript also without it if deemed necessary.

6. Adding more analysis on why certain trees deviate more from the mean than others is a good point, thank you. We can add to this analysis via the findings in Figure R1 (see supplement, presented in the answer to referee #1 comment 4), showing some of the specific conditions in which BVOC emission potentials can be higher than expected based on the database values. In addition, the alternative version of Figure 3 (see supplement and the answer to referee #2 comment 2) illustrates more clearly the single-tree deviations from the database estimates and can be used as a basis for deeper analysis, including the noticed potential effects of dry branches or pruning mentioned in the answer to referee #1 comment 3. We do also find that the mean emission potentials generally being close to database values is a useful result for further research, modelling efforts and urban planning, so we prefer also presenting this conclusion.

7. For all samples, the incoming replacement air going into the shoot chamber was not scrubbed for ozone (to allow for any effects of ozone on the tree leaves). However, we normally scrubbed ozone from air entering the adsorbent tubes (which was a side stream of the incoming replacement air or outgoing sample air), but in a portion of these samples, we could not use scrubber before the adsorbent tube taking air from incoming replacement air. As the theory-based and previously tested corrections (Helin et al. 2020) that we applied ended up being very small, and the terpene concentrations in the incoming air samples were in any case low in comparison to the outgoing sample air, we believe that any systematic bias left after the corrections would be a very minor effect on the final emission results.

7. We agree that taking into account the NOx regime (as well as O3 and NOx intake by leaves, and aerosol deposition on the leaves) would be crucial for modelling the realistic effects of BVOC emissions in urban atmosphere O3 or SOA concentrations. Our intent was to compare tree species and explore potential differences between site types in their potential to contribute to O3 and SOA formation, we think that it is reasonable to assume the same NOX regime for all species and sites and thus use the fixed MIR and FAC.

In further studies and as MIR and FAC (or other ways to represent a single BVOC potential to contribute to O3 or SOA formation) become available for more individual BVOCs, a more detailed representation of urban tree effects on air quality should become possible. We still had to rely on a mean MIR or FAC of the compound group for many monoterpenes and sesquiterpenes, although as seen in table S7, they can differ largely between two compounds of the same group.

9. Our study focused on the high-latitude cities as these remain somewhat underrepresented in studies on urban tree functioning and also BVOC emissions. We did address the generalisability of our results in the discussion (“the BVOC emission potential estimates do not appear to serve as a large source of error in creating urban BVOC emission budgets in cities like Montreal and Helsinki (small to mid-sized cities with cool, humid climates)”) and in the conclusions (“further direct measurements of urban tree BVOC emissions in various cities with differing sizes and climates, including during acute stress events such as high O₃ concentrations, heat waves, or prolongued droughts, are needed to scope where and when the database values can be applied”), but if deemed necessary we can state this even more clearly in both cases. Especially if it would encourage further studies from the mentioned regions with higher temperatures and aridity, or larger population densities.

10. Our conclusion was indeed that 1) there seems to be large tree-to-tree variation in BVOC emissions by urban trees, a part of which seems to be related to the site conditions (street or park), but that 2) across all trees per species, the mean does not importantly deviate from database values. This means that, in our results overall, there is no consistent bias towards much higher or lower emissions despite the large tree-to-tree variability. Although at first read they may seem in opposition, those are not, in fact, contradictory or mutually excluding, and are both important. However, to avoid confusion and to relate the two conclusions to each other, we will word these conclusions more clearly in the discussion and conclusions sections – thank you for pointing out the apparent inconsistency.  We will more explicitly note why, in some cases, we think using non-urban databases is generally fine in cities similar to our study cities, and why, in other cases, it may be more important to note the variability within urban environment. 

Technical corrections:

1. We assume the referee means O3, where the 3 was accidentally superscript instead of subscript, and we will correct this, thank you for pointing out the typo.

2. This would indeed be very helpful; we will add a table of abbreviations.

Author response comment to Referee #2 (citation )

Thank you for your time and effort put in reviewing the manuscript and pointing out the potential sources of confusion and inconsistencies. The comments will greatly help us to make the manuscript more readable and to deepen the data analysis regarding the potential sources of stress and their effects on BVOC emissions. We answer the major and minor below, so that the answer numbers refer to the comment numbers. 

Major comments:

1. Even though we discuss the potential for higher emission potentials with “urban stress” in the introduction, our study was not designed to test this as a formal hypothesis (accordingly we did not formulate such hypothesis), but rather to first test whether the urban tree BVOC emissions are in line with database values or not (regardless of reason for higher / lower emissions). We also discuss in the introduction the potential error coming from BVOC emission estimates that are not species-specific but rather at a genus level. To avoid confusion regarding the study questions, we will modify the introduction to emphasise the stress discussion less in comparison to the other potential sources of deviation.

Yet we agree that adding other measures of physiological stress indicators, such as Fv/Fm or photosynthetic capacity would have been interesting to deeper explore the data and something to consider in further studies. Based on this comment and the referee #1 comments 3 and 4, we did perform a correlation analysis to better pinpoint which potential sources of stress could correlate with higher emission potentials of BVOCs (see answer to Referee #1 comment 4 and Figure R1 in supplement). The analysis showed species-specific relations between BVOC emission potentials and O3 concentrations, high temperatures or sun exposure. 

2. Indeed, our conclusion was that 1) we see large tree-to-tree variation in BVOC emissions by urban trees, a part of which seems to be related to the site (street or park) conditions, but that 2) across all trees per species, the mean does not deviate importantly from database values. Therefore, there is no consistent bias towards much higher or lower emissions despite the large tree-to-tree variability. To avoid confusion (referee #1 had the same comment) and to better relate the two conclusions to each other, we will address the seeming inconsistency and word these conclusions more clearly in the discussion and conclusions sections.

To illustrate the differences from the database values by site type, we created an alternative version of Figure 3 (see supplement). In certain cases, such as in Montreal, PC isoprene emissions in Period II, TC monoterpene emissions in Period II and TC isoprene emissions in Period I, and in Helsinki BP monoterpene emissions and UG sesquiterpenoid emissions, the deviations from the database values were different between the site types (often driven by large emissions by one tree individual). Given the number of repetitions, we are hesitant to do further statistical testing with these data without pooling the park and street, but the figure will allow discussing the effect of park vs street on the deviations from the database values (and potential cases where database values are not useful), along with the impacts of potential sources of stress that could play into the larger emission potentials of certain individual trees.

3. Thank you for the suggestion; we will do this to help the readability of the paper.

Minor comments:

L. 155: We will add in the methods that high-latitude cities in the northern temperate/boreal zones are a type of city where little research has been done on the study questions, and the two cities were chosen as examples of mid-sized cities representative of this city type.  The two cities being on two separate continents also gave the study some geographical width and a larger selection of tree species used in urban areas. We will also precise that the species selected are common within the climate zone, as suggested. 

L. 153: The flow rate through the shoot enclosure was always 2 L/min, providing a change of the enclosure air approximately every 3 minutes. The flow rate of 0.08 L/min was used in the side streams of incoming and outgoing air that were sampled into the adsorbent tubes. To avoid confusion in this regard, we will clarify the methods section about the flow rates. 

L. 211: The incoming ambient air was sampled during every measurement (we drew adsorbent tube samples as a side stream of both the incoming and outgoing air always). Thus, the local ambient background per tree was always subtracted in calculating the emission rate (concentration in “out” sample – concentration in “in” sample). The compound-wise variability in the incoming ambient air sample can be approximated from the Table S3, where the sapling system detection limit was calculated as the “in” sample mean concentration + 3*standard deviation. We will review the methods section to ensure the clarity of this procedure and avoid confusion.

The daily empty bag sampling was done especially to control for any impurities within the sampling system. This build-up of impurities within tubing, pumps or filters is a slower process than the variation in ambient background between sites, so we regarded once a day sufficient.

Methods S2: Thank you for pointing out this inconsistency, we will correct this and the following sentence.