Review of “Climatological assessment of the vertically resolved optical and microphysical aerosol properties by lidar measurements, sunphotometer, and in-situ observations over 17 years at UPC Barcelona” by Lolli et al.

Large Picture:

This work introduces 17 years of observations of atmospheric aerosols using active observations from a ground-based lidar and passive observations using a ground-based sunphotometer. The significant length of this dataset allows for climatological interpretation to be made. Unlike satellite studies, the active nature of the lidar, and the high-quality nature of the sunphotometer allow for a signal to be more easily interpreted and quantified through the noise. This work then explores how there are significant impacts from biomass burning, dust, and other long-range transported sources. It shows clearly that there are both locally and long-range transported forcings which are present in the site studied. It also shows that while some of the observed changes are based more on season, that others are based on changes in the climate and/or anthropogenic emissions over the times being analyzed. Overall, the science is sound and the implications are clear. It is hoped that a bit more analysis can be added to address the influence of higher-frequency events, extreme events, and the possibility that May may be more like summer than spring in this region of the world. Some additional additions are recommended to strengthen the literature and background review. Overall, this is a worthy piece, which with a small amount of additional work, may yield one or two additional and stronger scientific findings.

Specific Details:

Line 50: Perhaps you can add some references and some comments to deepen the analysis with respect to the issue of emissions uncertainty. As pointed out, there has been a significant change in emissions due to the changes in human sources of aerosols since the start of the industrial revolution. However, there is a second and very important issue. The current databases of aerosol emissions is also highly uncertain, especially so for absorbing aerosols, such as biomass burning and dust, which are emphasized in this paper. For example, there are papers indicating that the emissions of absorbing aerosols inverted from remotely sensed observations can be 2 to 4 times higher than those from bottom-up approaches currently used by the IPCC and most modeling studies. Interestingly, these top-down inverted emissions studies tend to produce results which are more consistent with AERONET and LIDAR, and therefore should be far more closely aligned with the results from this paper. Such high-temporal-and-spatial constrained top-down emissions datasets may help aid in discovery of and attribution for extreme events and/or long-range transport, such as in the cases of wildfire and long-range transported mixed anthropogenic and dust source events which are analyzed in this work.

Line 165: Averaged Monthly and Seasonally? How many different higher frequency values of the Raman Lidar are there? Is there sufficient data that if the top less than 10% of events were analyzed separately, or if some other extreme analytical approaches were used, that it would be possible to detect high frequency changes? Again, this topic seems aligned with the overall results in this work, and may include a mixture of very intense but short-duration events such as fires, long-range transported pollution, and/or dust storms?

Line 190: Perhaps add in a sentence or two and additional details about how aerosols in the environment which are not locally source tend to be mixed. This is especially so for smaller sized particles (say under 2um), in which small carbon containing cores are slowly coated in-situ with organic and inorganic shells. There also are cases in which dust is coated with anthropogenic pollution observed in-situ. This could also be relevant for when collisions between dust and anthropogenic sources occur. Such analysis using a core/shell or other MIE based mixing approaches is already used by AERONET and therefore would yield a consistent result with your paper herein.

Line 200/201: While this is true, it also could be indicative of heavily aged anthropogenic or fire-based aerosol, which has been in the atmosphere for a very long time, and slowly grown in size to near the fine/coarse mode boundary.

Line 217: Using different metrics to weight the various independent wavelengths, it may also be possible to find out information about various mixed aerosol types.

Line 240: sensible?

Line 333: Other long-range transport of biomass burning papers as observed through multiple absorbing aerosol observations are available.

Line 346-348: Perhaps repeating the same analysis, but focusing on the 90^th or 95^th percentile of the data could yield additional interesting findings? The points made in this sentence could specifically be used to analyze if or how high pollution events are changing from a climatological perspective. Such a sensitivity test should be able to be done rapidly, while adding scientific value overall.

Figure 4: The MAM data has a flatter profile overall, and looks somewhat similar to the JJA data. If May were separated from MAM, would it look more like March and April, or more like JJA? Is it possible that the traditional division of seasons may not be the best way to analyze the groupings in this region of the world?

Lines 375-384: As mentioned above, the results from this paragraph with respect to transported BB may also be consistent with the May results being more similar to the JJA results than to the March and April results. Has this been checked?

This paper quantitatively evaluated long-term temporal trends and seasonal variability from a climatological point of view of the optical and microphysical properties of atmospheric particulate matter at the Universitat Politècnica de Catalunya, Barcelona, Spain, over the past 17 years, through a synergy of lidar, sunphotometer, and in situ concentration measurements. The topic is very interesting and has important climate and environment implications. The manuscript is well written and organized. While I found some minor issues need to be addressed before publish.

1. All the number in PM10, PM2.5 and PM1 in the main text, tables and figures should be subscripted
2. What is Lidar detection blind zone?
3. Sens->Sen’s in figure 2a
4. Brackets is not full in caption of table 4
5. Color bar is missed in figure 5
6. The present findings should be compared with previous studies.