Basic Facts about Numerical Simulations of Atmospheric Composition in the City of Sofia
Round 1
Reviewer 1 Report
Review Ivanov
The paper presents a statistically reliable assessment of the atmospheric composition of the city of Sofia. Extensive numerical simulations of the atmospheric composition in Sofia city were performed. WRF was used as a meteorological pre-processor, CMAQ as a Chemical Transport Model, and SMOKE as the emission pre-processor of Models-3 system. It is concluded that the daily concentration changes of NO2 and FPRM are essential and the total concentration change is different for each pollutant. The contributions of emissions to the concentrations of different species vary from 0% up to 100%. The contributions of different emission categories to other species surface concentrations have various diurnal courses. The sign of the contributions of some processes is evident and some signs depend on the type of emissions, and weather conditions, and topography.
General comments
The special focus of this study is to understand the atmospheric composition in relation to the air pollutants origin and behaviour. These processes are studied for different meteorological conditions as well as spatial and temporal emission characteristics.
The Conclusions are too general and not showing which new scientific results are presented. What is new from the study case Sofia for air pollution understanding and consequently air pollution reduction measures?
The paper addresses relevant scientific questions within the scope of the journal.
The paper presents novel concepts, ideas and tools.
The scientific methods and assumptions are valid and outlined mainly so that substantial conclusions are reached.
The results are sufficient to support the interpretations and conclusions.
The description of experiments and analyses is complete and precise to allow their reproduction by fellow scientists.
The quality and information of the figures and tables are fine. The captions must be improved to understand the content without the manuscript (esp. the abbreviations).
The related work is not completely cited. The references are mainly from studies in Sofia and Bulgaria. The scientific work of urban atmospheric composition studies by numerical simulations is missing.
Title and abstract reflect the whole content of the paper.
The overall presentation is well structured and clear. The language is fluent and precise.
The mathematical symbols, abbreviations, and units are generally correctly defined and used.
Specific Comments
In Materials and Methods it is not explained for which date the emission inventories are valid. A time period of numerical simulations is given at line 72 only. But also here and in the result dates are missing.
A map of Sofia and with the investigated locations and the topography including the surroundings would be helpful for reviewing. This must be provided to show the new scientific objectives and results of this study and is necessary for a scientific paper.
Technical corrections
FPRM in the abstract must be explained.
The style of references is not unique and must be improved.
Author Response
Open Review
(x) I would not like to sign my review report
( ) I would like to sign my review report
English language and style
( ) Extensive editing of English language and style required
( ) Moderate English changes required
(x) English language and style are fine/minor spell check required
( ) I don't feel qualified to judge about the English language and style
Yes Can be improved Must be improved Not applicable
Does the introduction provide sufficient background and include all relevant references?
( ) (x) ( ) ( )
Is the research design appropriate?
( ) (x) ( ) ( )
Are the methods adequately described?
( ) ( ) (x) ( )
Are the results clearly presented?
( ) ( ) (x) ( )
Are the conclusions supported by the results?
( ) (x) ( ) ( )
Comments and Suggestions for Authors
Review Ivanov
The paper presents a statistically reliable assessment of the atmospheric composition of the city of Sofia. Extensive numerical simulations of the atmospheric composition in Sofia city were performed. WRF was used as a meteorological pre-processor, CMAQ as a Chemical Transport Model, and SMOKE as the emission pre-processor of Models-3 system. It is concluded that the daily concentration changes of NO2 and FPRM are essential and the total concentration change is different for each pollutant. The contributions of emissions to the concentrations of different species vary from 0% up to 100%. The contributions of different emission categories to other species surface concentrations have various diurnal courses. The sign of the contributions of some processes is evident and some signs depend on the type of emissions, and weather conditions, and topography.
General comments
The special focus of this study is to understand the atmospheric composition in relation to the air pollutants origin and behaviour. These processes are studied for different meteorological conditions as well as spatial and temporal emission characteristics.
The Conclusions are too general and not showing which new scientific results are presented. What is new from the study case Sofia for air pollution understanding and consequently air pollution reduction measures?
Reply: We extend the Conclusion and next text is added:
“The estimation of the contribution of emissions from different source categories is apparently a valuable information, which can be useful for the definition of measures for improving the air quality in Sofia by reducing the emissions. Moreover, knowing the diurnal course of the contributions for a specific time period can suggest an optimal emission temporal regime, in order again to mitigate the air pollution for the given episode.
The “Integrated Process Rate Analysis” is not so often applied in urban air quality simulations, so in the case of the present study, it enriches the whole picture of the atmospheric composition climate of the city of Sofia. This ensemble treatment of the contribution of different processes, however, does not give an easy answer of how the processes interact and how exactly they form the air composition. Probably it will be more fruitful to consider the process contribution for a given episode, together with the specific meteorological conditions for the episode.
The obtained results and the corresponding conclusions made in the paper are in good agreement with the general idea of how urban atmospheric composition is formed, so they do not add general knowledge on the subject. The research and applied contribution of the paper are that it presents quantitative estimations, specific to the city of Sofia. Such an extensive and comprehensive study for the city of Sofia had not been made before.
The models and the whole procedure, used in the present paper, can, of course, be applied to other cities. Such studies have been made for many cities. A crucial point, however, is the emission inventory, and the activities for preparing it are very specific for each city, depending on the raw data available.”
The paper addresses relevant scientific questions within the scope of the journal.
The paper presents novel concepts, ideas and tools.
The scientific methods and assumptions are valid and outlined mainly so that substantial conclusions are reached.
The results are sufficient to support the interpretations and conclusions.
The description of experiments and analyses is complete and precise to allow their reproduction by fellow scientists.
The quality and information of the figures and tables are fine. The captions must be improved to understand the content without the manuscript (esp. the abbreviations).
Reply: Done
The related work is not completely cited. The references are mainly from studies in Sofia and Bulgaria. The scientific work of urban atmospheric composition studies by numerical simulations is missing.
Reply: Some scientific works of urban atmospheric composition studies by numerical simulations are added in the references, and the next sentence in the introduction:
The next step in studying the atmospheric composition climate is performing simulations on an urban scale. Research works dealing with that topic include domains with different sizes and scales from meters to kilometers [26-34]. The models’ simulations in the smallest scales usually deal with sub-urban- sized areas as streets and neighborhoods.
Title and abstract reflect the whole content of the paper.
The overall presentation is well structured and clear. The language is fluent and precise.
The mathematical symbols, abbreviations, and units are generally correctly defined and used.
Specific Comments
In Materials and Methods, it is not explained for which date the emission inventories are valid. A time period of numerical simulations is given at line 72 only. But also here and in the result dates are missing.
Reply: the next sentences are added to the text (Methodology section):
The TNO inventory with resolution 0.25ºx0.125º in 10 SNAP categories for 2010 [39-41] is exploited for the territories outside Bulgaria in the mother CMAQs domain. For the Bulgarian domains the National inventory for 2010 as provided by Bulgarian Executive Environmental Agency is used. All the simulations are performed for 7 years period from 2008 to 2014 with the Two-Way Nesting mod on.
The period is also added to all figure captions.
A map of Sofia and with the investigated locations and the topography including the surroundings would be helpful for reviewing. This must be provided to show the new scientific objectives and results of this study and is necessary for a scientific paper.
Reply: The next picture is added to the text with explanation.
The next text is added in Methodology section:
As the NCEP Global Analysis Data with the 1-degree resolution is used as meteorological background, the system nesting capabilities were applied for downscaling the simulations to a 1 km resolution Fig.1
Results for the Sofia city domain (D5) and 2 points - Orlov most and Bistrica are presented in the paper. The Orlov most is located in the center of the city and represents the typical urban polluted site. The Bistrica is located on semi-mountain outskirts and represents a rural site of the domain.
Fig. 1. Five computational domains (CMAQ domains are nested in WRF ones) - D1 81x81 km (Europe), D2 27x27 km (Balkan Peninsula), D3 9x9 km (Bulgaria), D4 3x3 km (Sofia municipality) and D5 1x1 km (Sofia city).
Technical corrections
FPRM in the abstract must be explained.
Reply: The sentence: “The daily concentration changes of the two essential air pollution species - NO2 and FPRM have different magnitudes. “
Is changed to: “The daily concentration changes of the two essential air pollution species – Nitrogen dioxide (NO2) and Fine particle matters (FPRM - Particulate Matter (PM2.5) which are fine with a diameter between 0 and 2.5 micrometers.) have different magnitudes. “
The style of references is not unique and must be improved.
Reply: Done
Author Response File: 
Author Response.pdf
Reviewer 2 Report
These interesting paper shows some interpretations from numerical simulations of NO2 and particulate matter in the Sofia region. The authors discuss the results in terms of diurnal and seasonal variabilities, and of concentration variations, considering the different sources of pollution. The paper can be published if the following comment are considered:
Can you give a plot showing the 3 locations you have used for the analysis, and can you better explain the difference between them?
Line 59 : Can you justify the 0.8 factor ?
Line 79: It is unusual to speak of FPRM for fine particular matter. We currently use “PM”.
Line 151: The acronym VDIF is not defined before. Can you explain its meaning?
Line 164-169 are unnecessary since the information are presented above.
Line 173: Can you give figures’ numbers on which the results are presented?
All figures: Can you add the legend for the x-axis (I suppose it is hour) and for the y-axis?
Figures 3 and 4: The label of the x-axis is difficult to read, because the curve are partly superimposed on it. Can you improve the visualization?
Figure 6: The legend at lower right is difficult to read.
Line 305-307 is unclear; what do you mean by “a factor”?.
Conclusion: Perhaps the authors could provide some ideas on how to extend such work to other cities in the world.
Author Response
Open Review
(x) I would not like to sign my review report
( ) I would like to sign my review report
English language and style
( ) Extensive editing of English language and style required
( ) Moderate English changes required
(x) English language and style are fine/minor spell check required
( ) I don't feel qualified to judge about the English language and style
Yes Can be improved Must be improved Not applicable
Does the introduction provide sufficient background and include all relevant references?
(x) ( ) ( ) ( )
Is the research design appropriate?
(x) ( ) ( ) ( )
Are the methods adequately described?
( ) (x) ( ) ( )
Are the results clearly presented?
( ) ( ) (x) ( )
Are the conclusions supported by the results?
(x) ( ) ( ) ( )
Comments and Suggestions for Authors
These interesting paper shows some interpretations from numerical simulations of NO2 and particulate matter in the Sofia region. The authors discuss the results in terms of diurnal and seasonal variabilities, and of concentration variations, considering the different sources of pollution. The paper can be published if the following comment are considered:
Can you give a plot showing the 3 locations you have used for the analysis, and can you better explain the difference between them?
Reply: The next text is added in Methodology section:
As the NCEP Global Analysis Data with the 1-degree resolution is used as meteorological background, the system nesting capabilities were applied for downscaling the simulations to a 1 km resolution Fig.1
Results for the Sofia city domain (D5) and 2 points - Orlov most and Bistrica are presented in the paper. The Orlov most is located in the center of the city and represents the typical urban polluted site. The Bistrica is located on semi-mountain outskirts and represents a rural site of the domain.
Fig. 1. Five computational domains (CMAQ domains are nested in WRF ones) - D1 81x81 km (Europe), D2 27x27 km (Balkan Peninsula), D3 9x9 km (Bulgaria), D4 3x3 km (Sofia municipality) and D5 1x1 km (Sofia city).
Line 59 : Can you justify the 0.8 factor ?
Reply: The used SNAP categorization of emissions and reduced by some factor allow to evaluate the contribution of road transport, energetic, industrial, and non-industrial combustions to the atmospheric composition in the city. The concentrations for each scenario of reduced SNAP’s were calculated for each day of the period, and the relative contribution of the emissions for each of the scenarios are calculated in the following way:
If an arbitrary pollution characteristic (concentration, deposition, process contribution, etc.) for a given grid point, or averaged over chosen domain, obtained with all the emissions accounted for, is denoted by , that m is the respective characteristic obtained when the emissions form source category m is reduced by a factor of α. In such a case the quantity φm can be interpreted as the relative (in %) contributions of emission category m to the formation of the characteristic φ:
(1)
More than one Selected Nomenclature for sources of Air Pollution (SNAP) category emissions can be reduced by a factor of α and so the joint contribution of several or all SNAP categories to the formation of the pollution characteristic can be evaluated. Thus obtained relative source contributions can also be averaged for the whole ensemble, thus providing the “climate” of the emission contributions, in particular the “typical” annual and seasonal contributions.
The reason why the emissions from a given category are reduced by a chosen factor and not simply put to zero is that by totally removing the emissions from a given category we can obtain much smaller concentrations, which may change the rate of some nonlinear chemical reactions. Moreover, the significant reduction of the concentrations may change the compound diffusion through the domain boundaries. That is why it is a general practice for the simulations for evaluating the contribution of the emissions from a given category to be performed applying not removed, but reduced emissions from this category which is normally done in such studies. The reduction of 20% is preferred by many authors in atmospheric pollution studies.
Line 79: It is unusual to speak of FPRM for fine particular matter. We currently use “PM”.
Reply: Two groups of dust pollutants CPRM and FPRM (Coarse and Fine Particulate Matter) are considered in this work;
FPRM = SO4 + NH4 + NO3 + EC + (ORGA + ORGB) +PM2.5 – Particulate Matter (PM) which are fine with a diameter between 0 and 2.5 micrometers.
CPRM (ACOARSE) = ACORS + ASEAS + ASOIL - Particulate Matter (PM) which are coarse with a diameter between 2.5 and 10 micrometers.
In the current paper are presented results only for FPRM, which is the reason why we prefer to not use only the “PM” abbreviation.
Line 151: The acronym VDIF is not defined before. Can you explain its meaning?
Reply: In the sentence on line 136: “The processes which influence the formation of the air pollution patterns are HADV – Horizontal advection, ZADV – Vertical advection, HDIF – Horizontal diffusion, ZDIF – Vertical diffusion, EMIS – Emissions, DDEP – Dry deposition, CLDS – Cloud processes, CHEM – Chemical processes, and AERO – Aerosol processes.”
ZDIF – Vertical diffusion is replaced by VDIF - Vertical diffusion
Line 164-169 are unnecessary since the information are presented above.
Reply: The section is deleted.
Line 173: Can you give figures’ numbers on which the results are presented?
Reply: Done - Graphics of the diurnal evolution of the “typical” relative contribution annually and seasonal emissions of SNAP categories 1, 2, 3, 7 and all the emissions to the surface concentrations of NO2, FPRM, averaged for the territory of Sofia city and for „Orlov most and „Bistrica“, are shown in figures 3,6,9,12,15,18.
All figures: Can you add the legend for the x-axis (I suppose it is hour) and for the y-axis?
Reply: Done, x, y-axis label is added to all the figures.
Figures 3 and 4: The label of the x-axis is difficult to read, because the curve are partly superimposed on it. Can you improve the visualization?
Figure 6: The legend at lower right is difficult to read.
Reply: We tried to do our best for better visualization!
Line 305-307 is unclear; what do you mean by “a factor”?.
Reply: The sentence is changed to:
Probable reasons for that maximum are the stable atmosphere and intensive traffic early morning, which probably have a role in the results for the ensemble annual and seasonal average contributions of different sources for the formation of FPRM (figure 12).
Conclusion: Perhaps the authors could provide some ideas on how to extend such work to other cities in the world.
Reply: The models and the whole procedure, used in the present paper can, of course, be applied to other cities. Such studies have been made for many cities. A crucial point, however, is the emission inventory, and the activities for preparing it are very specific for each city, depending on the raw data available.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors revised the manuscript according to the reviewer comments. It would be better readable if most figures are presented in an annex or supplementary.
