General Comments:

This paper presents a modelling study that investigates the impact of the observed vertical aerosol distribution on the simulated photochemistry over Northern China. This paper builds on gaps in the field where few modelling studies using chemical transport models have considered actual observed vertical aerosol distributions when simulating the effects of the aerosol - photolysis interaction. Using combinations of lidar data and radiosonde observations the authors demonstrate that incorporating these into GEOS-Chem can help address the biases in AOD in the model and show the subsequent response on ozone levels and particulate matter. The authors test the sensitivities of aerosol photolysis interactions using numerous scenarios and robustly evaluate the effects of including the observational constraints including looking at impacts of on the atmospheric oxidising capacity and boundary layer effects. They also evaluate the effects in both the winter and summer seasons where the impacts of aerosols on atmospheric chemistry can behave very differently. Overall, the paper is well written and provides a valuable contribution to understanding photochemistry under changing pollutant regimes and the importance of representing the vertical distribution of aerosols in the model as accurately as possible. I recommend publication in ACP after the following minor comments are addressed.

Specific Comments:

This paper focuses on the impacts of aerosol optical depth on photochemistry. Whereas the authors provide evaluation of the model for aerosol optical depth (and identify and correct biases) they do not evaluate and benchmark how well it currently captures observed photolysis rates at the observational sites. I appreciate that measured photolysis rates (E.g. JNO2) may not be available at all sites but if there is data available it would be great if the authors could provide an observational comparison. Due to the potential of data limitations I would not suggest this is needed for publication but think it would greatly enhance the model evaluation if such data was available. 

Technical Corrections:

Page 3, line 64: Please remove 'the' between suppress and secondary

Page 3, line 94: This last sentence is not quite clear. Do you mean to investigate the response of photochemistry to observed constraints on vertical aerosol distributions?

Page 4, line 122: You mention the various schemes used here for boundary layer mixing, dry deposition, wet deposition and emissions but you don't mention the chemical scheme deployed in the model. Please add this here. 

Page 5, Figure 1: I am finding the red boxes in plots (b) and (c) a little hard to read, would it be possible for these to be made a little bolder and perhaps plotted in black to make them stand out better on the page?

The manuscript titled “Simulated photochemical response to observational constraints on aerosol vertical distribution over North China” investigate the response of photochemistry to observational constraints on aerosol vertical distribution by applying lidar and radiosonde observations and the chemical transport model (GEOS-Chem). This study provides better understanding on the impact of aerosols on O₃ pollution. The article is interesting. It can be accepted after fully considering the following suggestions.

The aerosol vertical distribution may differ among different sites such as urban areas and rural areas. This depends on meteorological factors and local emissions levels. Here the authors use the measurements at two sites to represent the whole North China region, which may lead to bias. According to Figure 2, it seems that the revised aerosol vertical distribution for the region is significant different from the measurements. More evidence should be given for the spatial representativeness of the measurements.

The methodology of the radiative transfer module you used should be depicted in detail.

Besides AOD, single scattering albedo (SSA) is another important aerosol optical property that affects photolysis rates. I suggest the authors to provide validation and discussion of SSA in the manuscript.

For the discussion of atmospheric oxidizing capacity, HONO is an important OH radical source. Nevertheless, HONO has multiple sources and most air quality models can not fully consider these sources and thus underestimate HONO concentrations. I wonder which sources of HONO are considered in the GEOS-Chem model, and the resulting potential uncertainty should be clarified.

For the change in PM_2.5, the authors have discussed the change of nitrate and HNO3. How about other secondary aerosol components such as sulfate and SOA?

Line 150, Line 195: For the correlation analysis, the time and spatial resolution of data point and the number of data should be depicted. This should be double checked in anywhere else in the manuscript.

The authors have validated O3 and PM2.5 by comparison with measurements. I suggest to additionally validate NO₂ given that NO₂ is a key precursor of O₃ and PM2.5.