Measurement report: Long-term variations in surface NOx and SO2 mixing ratios from 2006 to 2016 at a background site in the Yangtze River Delta region, China

Yin, Qingqing; Ma, Qianli; Lin, Weili; Xu, Xiaobin; Yao, Jie

doi:https://doi.org/10.5194/acp-22-1015-2022

Articles | Volume 22, issue 2

https://doi.org/10.5194/acp-22-1015-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-22-1015-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 2

Measurement report

|

21 Jan 2022

Measurement report |

| 21 Jan 2022

Measurement report: Long-term variations in surface NO_x and SO₂ mixing ratios from 2006 to 2016 at a background site in the Yangtze River Delta region, China

Qingqing Yin, Qianli Ma, Weili Lin, Xiaobin Xu, and Jie Yao

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Final revised paper (published on 21 Jan 2022)
Supplement to the final revised paper
Preprint (discussion started on 07 May 2021)

Interactive discussion

Status: closed

RC1:
'Comment of Yin Q et al.: “Measurement report: Long-term variations in surface NOx and SO2 from 2006 to 2016 at a background site in the Yangtze River Delta region, China”', Anonymous Referee #1, 21 Jun 2021

Review of

Yin Q et al.:

“Measurement report: Long-term variations in surface NOx and SO2 from 2006 to 2016 at a background site in the Yangtze River Delta region, China”

General comments

This paper reports on NOx and SO₂ measurements at the background site in the Yangtse River Delta region in China.

The site, the instrumental setup, quality control and the data processing procedures have been described in detail. Data are compared to other data from other measurement sites. The long-term trend of both SO₂ and NOx, their diurnal and seasonal behavior are discussed and compared to emission data.

There are only few NOx and SO₂ datasets on background sites published and analyzed in depth so far so I would recommend this paper being accepted for publication after the following questions are answered.

Line 85

In the information and methods part, the instrumental setup is described. Here, an essential part is missing. The method to convert NO₂ into NO for detection should be given, as well as the method for determining the conversion efficiency. Has gas phase titration been used? Also, it should be mentioned if data were corrected for humidity and ozone effects.

Line 135

One major concern is that the paper describes trends and seasonal behavior of NOx. However, of the nitrogen oxides, NO₂ has the major impact on health. NO₂ data should be included into table 1 and discussed. What is the long-term trend of NO₂?

Line 167

As the authors point out satellite observations are a valuable tool when analyzing station data. How does the long-term trend of the OMI NO₂ observation compare to the NOx data at the site? Likewise, comparison of in situ observation with station data could help to differentiate between boundary layer effects and emission effects when discussing the diurnal behavior of NOx. How does the diurnal behavior of the satellite observation compare to the diurnal behavior of station data?

Line 207

The pollution roses in Figure 5 show that SO₂ and NOx mixing ratios depend not only on the windspeed but also on the wind direction. Is it possible to add a plot to figure 5 which shows the dependency on wind direction?

Line 220

Changes in relative humidity can often by explained with changes in airmasses which are advected from different sites. How does relative humidity change with wind direction? Can the wind direction explain the change of NOx and SO₂ with changing relative humidity?

Line 237

The authors write that the main source of SO₂ and NOx are east from the site as the show it in figure 7. However, in figure 6 it can be observed that highest mixing ratios were measured with wind coming from west. How can this discrepancy be explained?

Line 305

The diurnal behavior is already discussed in chapter 3.3. I would suggest merging chapter 3.3 with lines 305 to 341.

Line 327

If the disappearance of the NOx peak at 1:00 A.M. were due to reduction of industrial emissions, why should industrial emissions peak at 1:00 A.M.? Shouldn´t the effect be seen all over the night?

Line 337

To my knowledge, the impact of traffic on SO₂ emission in China is of minor importance. Have you considered residential sources, which are after industrial emissions and power plant emissions the third most important source of SO₂ according to the Multi-resolution Emission Inventory for China (MEIC)?

Line 369

Data availability: A link should be provided to where the data are stored in the GAW archive.

Technical corrections:

Title: Measurement report: Long-term variations in surface NOx and SO2

from 2006 to 2016 at a background site in the Yangtze River Delta

region, China

Better:

Title: Measurement report: Long-term variations in surface NOx and SO2 mixing ratios

from 2006 to 2016 at a background site in the Yangtze River Delta

region, China

Line 185: The seasonal average diurnal variation in NOX showed a morning peak of NOX in summer at 08:00, which is 1 to 2 h earlier than during other seasons (Fig. 4c).

This sentence is not clear to me. What is it compared to?

Line 221: different periods are well consistent

Line 222: A blank is missing

Line 250: Please give a reference for the Ecological and Environmental Status Bulletin.

Line 254: smaller than those

Figure 5: The dependencies of SO₂ on meteorological parameters in the figure is blurred from the underlying trend. In figure 5h it cannot be seen if data for 2014-2016 change at all. Maybe it is better to plot changes relative to a mean value.

Figure 6: I would suggest using the same color for NOx in all the seasons in this plot and label the plots instead.

Figure 11: The different y scales in Figures 11a to Figures 11c makes comparison between the periods difficult. I would suggest using the same scale.

Figure 11: I would suggest naming the periods in the figure caption.

Citation: https://doi.org/10.5194/acp-2021-227-RC1
- AC1:
  'Reply on RC1', Qingqing Yin, 03 Aug 2021
  We thank for the constructive comments and suggestions. We revised our manuscript according to the comments and suggestions. The following list the point-to-point response to the comments. The changed texts were highlighted with yellow color.
  Response to comments by referee # 1
  General comments:
  This paper reports on NO_x and SO₂ measurements at the background site in the Yangtse River Delta region in China.
  The site, the instrumental setup, quality control and the data processing procedures have been described in detail. Data are compared to other data from other measurement sites. The long-term trend of both SO₂ and NO_x, their diurnal and seasonal behavior are discussed and compared to emission data.
  There are only few NO_x and SO₂ datasets on background sites published and analyzed in depth so far so I would recommend this paper being accepted for publication after the following questions are answered.
  Specific comments:
  Line 85 In the information and methods part, the instrumental setup is described. Here, an essential part is missing. The method to convert NO2 into NO for detection should be given, as well as the method for determining the conversion efficiency. Has gas phase titration been used? Also, it should be mentioned if data were corrected for humidity and ozone effects.
  
  Response: In Model 42C-TL trace-level chemiluminescent analyzer, NO₂ is converted to NO by a molybdenum NO₂-to-NO converter heated to about 325℃. The converter efficiency was checked annually using gas phase titration (GPT). If the converter efficiency is less than 96%, replace the converter. We add the information in the revised paper. Please see page 3, line 89 for the revision.
  Line 135 One major concern is that the paper describes trends and seasonal behavior of NO_x. However, of the nitrogen oxides, NO2 has the major impact on health. NO2 data should be included into table 1 and discussed. What is the long-term trend of NO2?
  
  Response: In this regional background station, NO₂ was the dominant form of NO_x, accounting for 82.2 % of NO_x, so we didn’t present the trends and seasonal behavior of NO₂. In the revised manuscript, we included the NO₂ in Table 1 and text, but trends and seasonal behavior of NO₂ in supplementary material.
  Line 167 As the authors point out satellite observations are a valuable tool when analyzing station data. How does the long-term trend of the OMI NO2 observation compare to the NO_x data at the site? Likewise, comparison of in situ observation with station data could help to differentiate between boundary layer effects and emission effects when discussing the diurnal behavior of NO_x. How does the diurnal behavior of the satellite observation compare to the diurnal behavior of station data?
  
  Response: Thanks for the suggestion. We think it would be a good idea to compare in situ observation with satellite observations to distinguish between boundary layer effects and emission effects. But, given our current level of knowledge, we need to learn further to complete the work. Here, we compare the monthly average satellite products for NO₂ with the monthly mean surface NO₂, since OMI covers a point on the ground about once every two days.
  Line 207 The pollution roses in Figure 5 show that SO₂ and NO_x mixing ratios depend not only on the windspeed but also on the wind direction. Is it possible to add a plot to figure 5 which shows the dependency on wind direction?
  
  Response: Thanks for the suggestion. Rose maps are often used to discuss the relationship between wind direction and pollutant concentration, which details had been plotted in Figure 6 and analyzed in section 3.4.
  Line 220 Changes in relative humidity can often by explained with changes in airmasses which are advected from different sites. How does relative humidity change with wind direction? Can the wind direction explain the change of NO_x and SO₂ with changing relative humidity?
  
  Response: Thanks for your suggestion. We plot the relative humidity change with wind direction together with NO_x and SO₂ rose maps (Figure R1). Also comparing them with figure 1, we think it cannot explain the change of NO_x and SO₂ with changing relative humidity.
  Figure R1. NO_x, SO₂, and RH rose maps
  Line 237 The authors write that the main source of SO₂ and NO_x are east from the site as the show it in figure 7. However, in figure 6 it can be observed that highest mixing ratios were measured with wind coming from west. How can this discrepancy be explained?
  
  Response: Thanks. The wind concentration rose diagram (Figure 6) is a method that can effectively identify short-range transport sources near the ground, while the CWT method (Figure 7) can effectively identify long-range transport sources. Based on a comparison of the two, it can be seen that from the perspective of local emissions, atmospheric NO_x and SO₂ at the LAN station are mainly from the northeast and southwest of the station, while long-range transport is influenced by the east.
  Line 305 The diurnal behavior is already discussed in chapter 3.3. I would suggest merging chapter 3.3 with lines 305 to 341.
  
  Response: Thanks for the suggestion. Chapter 3.3 aims to provide an overview of the characteristics of the diurnal behavior of NO_x and SO₂ over the observation period, while lines 305 to 341 focus on their long-term characteristics and causes. So, we kept to separate chapter 3.3 from lines 305 to 341.
  Line 327 If the disappearance of the NO_x peak at 1:00 A.M. were due to reduction of industrial emissions, why should industrial emissions peak at 1:00 A.M.? Shouldn´t the effect be seen all over the night?
  
  Response: Yes, NO_x peak at 1:00 AM also puzzled us. A small peak in NO_x and SO₂ occurred between 01:00 and 02:00, which might be related to nighttime emissions from unscrupulous enterprises (Fan et al., 2013) or the lower electricity prices after midnight in response to the financial pressure of the 2008 economic crisis and the corresponding increase in electricity prices for industrial users (Sun, 2008). But it's really hard to tell exactly why these small peaks dominate after midnight. These two causes also feel too speculative, so we just present the result here.
  We revised the sentences as (Page 11, line 334):
  The disappearance of the small peak around 01:00 at night during 2012–2016 may be related to the introduction of stricter air pollution control policies for factories that emit at night. Small peaks in NO_x and SO₂ occurred between 01:00 and 02:00, which might be related to nighttime emissions from unscrupulous enterprises (Fan et al., 2013) or more production activities the with lower electricity prices after midnight in response to the financial pressure of the 2008 economic crisis and the corresponding increase in electricity prices for industrial users (Sun, 2008). In spite of these two reasons, however, it's really hard to tell exactly why these small peaks dominate after midnight.
  Fan, Y., Fan, S., Zhang, H., Zu, F., Meng, Q., and He, J.: Characteristics of SO₂, NO₂, O₃ volume fractions and their relationship with weather conditions at Linan in summer and winter, J. Atmos. Sci., 121‒128, 2013.
  Sun, W.: "A two-pronged approach of "limiting coal prices" and "raising electricity prices, Yangtze River Delta, 58‒60, 2008.
  
  Line 337 To my knowledge, the impact of traffic on SO₂ emission in China is of minor importance. Have you considered residential sources, which are after industrial emissions and power plant emissions the third most important source of SO₂ according to the Multi-resolution Emission Inventory for China (MEIC)?
  
  Response: Thanks. You are right. For the evening peaks, the residential sources should be important for SO₂because it’s also in cooking hours. We revised sentence as: “The formation of the evening peaks of NO_x and SO₂ may be mainly related to the increase in motor vehicle and residential sources emissions, which are stronger in the rush and cooking hours and that of SO₂ may be probably more due to the reduction of power plants emissions.” Please see Page 12, line 348 for the revision.
  Line 369 Data availability: A link should be provided to where the data are stored in the GAW archive.
  
  Response: As far as I know, the data of NO_x and SO₂ data for this site are not available in the GAW archive. The specific reasons are complex.
  Technical corrections:
  Title: Measurement report: Long-term variations in surface NO_x and SO₂ from 2006 to 2016 at a background site in the Yangtze River Delta region, China
  
  Better:
  Title: Measurement report: Long-term variations in surface NO_x and SO₂ mixing ratios from 2006 to 2016 at a background site in the Yangtze River Delta region, China
  Response: Accepted. Please see page 1, line 1 for the revision.
  Line 185: The seasonal average diurnal variation in NO_x showed a morning peak of NO_x in summer at 08:00, which is 1 to 2 h earlier than during other seasons (Fig. 4c). This sentence is not clear to me. What is it compared to?
  
  Response: We revised the sentence. “In summer, the seasonal average diurnal variation in NO_x showed a morning peak at 08:00, which time is 1 to 2 h earlier than that occurred in other seasons (Fig. 4c).” Please see Page 7, line 192 for the revision.
  Line 221: different periods are well consistent
  
  Response: Accepted. Please see Page 7, line 224 for the revision.
  Line 222: A blank is missing
  
  Response: Accepted. Please see Page 8, line 225 for the revision.
  Line 250: Please give a reference for the Ecological and Environmental Status Bulletin.
  
  Response: Accepted. Please see Page 8, line 225 for the revision.
  Line 254: smaller than those
  
  Response: Accepted. Please see Page 9, line 258 for the revision.
  Figure 5: The dependencies of SO₂ on meteorological parameters in the figure is blurred from the underlying trend. In figure 5h it cannot be seen if data for 2014-2016 change at all. Maybe it is better to plot changes relative to a mean value.
  
  Response: Accepted. Please see Page 24, figure 5 for the revision.
  Figure 6: I would suggest using the same color for NO_x in all the seasons in this plot and label the plots instead.
  Response: Accepted. Please see Page 25, figure 6 for the revision.
  Figure 11: The different y scales in Figures 11a to Figures 11c makes comparison between the periods difficult. I would suggest using the same scale.
  
  Response: Accepted. Please see Page 29, figure 11 for the revision.
  Figure 11: I would suggest naming the periods in the figure caption.
  
  Response: Accepted. Please see Page 29, figure 11 for the revision.
  
  Citation: https://doi.org/10.5194/acp-2021-227-AC1
RC2:
'Comment on acp-2021-227', Anonymous Referee #2, 28 Jun 2021

General comments

The authors present a concise study on long-term trends of NOx and SO2 in the region of the Yangtze River Delta

based on data acquired at the global GAW station Lin'an.

They interpret diurnal, seasonal and long-term changes and put them in context with trends measured in several other regions or cities in China and across the globe.

They assess correlations with meteorological parameters and emissions by different sources.

To identify source regions a potential source analysis of NOx and SO2 is applied on the YRD region.

Changes in average diurnal patterns of NOx and SO2 from 2006 to 2016 where found and attributed to long-term changes of vehicle emissions and industrial emissions, respectively.

Specific comments

l.30, l.307, table 1: Why not denoting it SO2/NOx or Sulph./Nitrog.? S/N might be mixed up with signal-to-noise ratio.

l.85: For NOx: The method of NO2 to NO conversion is missing and must be explained. Furthermore, were corrections for humidity (respective quenching for CLD technique)

and ozone reaction within the inlet line applied on the presented data?

l.97: Item (4) might describe more specifically what kind of checks, testings are done and what self-diagnosis does comprise of or even better give a reference where it is explained in more detail.

For example, I'm wondering what self-diagnosis means: Is it applying internal thresholds for operating parameters and, if yes, which one and what are the consequences for the instrument or measurements? Is this automatically done by the instrument or by the data acquisition sytem?

l.215: Is it adequate to call it already "effect" if this is an investigation of correlations? Is causality approved yet?

l.328: Reference for a change of (specific) air pollution control measures?

Technical corrections

Figure 2: P (hPa), factor 10 missing?

Citation: https://doi.org/10.5194/acp-2021-227-RC2
- AC2: 'Reply on RC2', Qingqing Yin, 03 Aug 2021
  
  We thank for the constructive comments and suggestions. We revised our manuscript according to the comments and suggestions. The following list the point-to-point response to the comments. The changed texts were highlighted with yellow color.
  Response to comments by referee # 2
  General comments
  The authors present a concise study on long-term trends of NO_x and SO₂ in the region of the Yangtze River Delta based on data acquired at the global GAW station Lin'an.
  They interpret diurnal, seasonal and long-term changes and put them in context with trends measured in several other regions or cities in China and across the globe.
  They assess correlations with meteorological parameters and emissions by different sources.
  To identify source regions a potential source analysis of NO_x and SO₂ is applied on the YRD region.
  Changes in average diurnal patterns of NO_x and SO₂ from 2006 to 2016 where found and attributed to long-term changes of vehicle emissions and industrial emissions, respectively.
  Specific comments
  l.30, l.307, table 1: Why not denoting it SO₂/NO_x or Sulph./Nitrog.? S/N might be mixed up with signal-to-noise ratio.
  Response: Accepted. We use SO₂/NO_x instead of S/N in the revised version.
  l.85: For NO_x: The method of NO2 to NO conversion is missing and must be explained. Furthermore, were corrections for humidity (respective quenching for CLD technique) and ozone reaction within the inlet line applied on the presented data?
  Response: In model 42C-TL trace-level chemiluminescent analyzer, NO₂ is converted to NO by a molybdenum NO₂-to-NO converter heated to about 325℃. The converter efficiency was checked annually using gas phase titration (GPT). If the converter efficiency is less than 96%, replace the converter. We add the information in the revised paper. Please see Page 3, line 89 for the revision.
  l.97: Item (4) might describe more specifically what kind of checks, testings are done and what self-diagnosis does comprise of or even better give a reference where it is explained in more detail.For example, I'm wondering what self-diagnosis means: Is it applying internal thresholds for operating parameters and, if yes, which one and what are the consequences for the instrument or measurements? Is this automatically done by the instrument or by the data acquisition system?
  Response: Mostly, the instrument self-diagnosis is applying internal thresholds for operating parameters, which can alert people to carry out manual testing, checking, and maintenance on the instrument. It can't be described in a few words. Technical report from U.S. Environmental Protection Agency can be a reference here. We add a reference of US EPA (2017) in the text.
  US EPA：Quality Assurance Handbook for Air Pollution Measurement Systems, Volume II, Ambient Air Quality Monitoring Program, EPA-454/B-17-001, 2017.
  l.215: Is it adequate to call it already "effect" if this is an investigation of correlations? Is causality approved yet?
  Response: Thanks. We have corrected "effect" to "correlation". Please see Page 8, line 218 for the revision.
  l.328: Reference for a change of (specific) air pollution control measures?
  Response: You might mean what specific air pollution control measures causing the disappearance of the NO_x peak at 1:00 A.M? PLS see our response to referee #1, question 8.
  Technical corrections
  Figure 2: P (hPa), factor 10 missing?
  Response: Thanks. The factor of 10 is missing. The unit is kPa. Please see Page 21, Figure 2 for the revision.
  
  Citation: https://doi.org/10.5194/acp-2021-227-AC2
AC3:
'Comment on acp-2021-227', Qingqing Yin, 03 Aug 2021
We thank for the constructive comments and suggestions. We revised our manuscript according to the comments and suggestions. The following list the point-to-point response to the comments. The changed texts were highlighted with yellow color.
Response to comments by referee # 1
General comments:
This paper reports on NO_x and SO₂ measurements at the background site in the Yangtse River Delta region in China.
The site, the instrumental setup, quality control and the data processing procedures have been described in detail. Data are compared to other data from other measurement sites. The long-term trend of both SO₂ and NO_x, their diurnal and seasonal behavior are discussed and compared to emission data.
There are only few NO_x and SO₂ datasets on background sites published and analyzed in depth so far so I would recommend this paper being accepted for publication after the following questions are answered.
Specific comments:
Line 85 In the information and methods part, the instrumental setup is described. Here, an essential part is missing. The method to convert NO2 into NO for detection should be given, as well as the method for determining the conversion efficiency. Has gas phase titration been used? Also, it should be mentioned if data were corrected for humidity and ozone effects.

Response: In Model 42C-TL trace-level chemiluminescent analyzer, NO₂ is converted to NO by a molybdenum NO₂-to-NO converter heated to about 325℃. The converter efficiency was checked annually using gas phase titration (GPT). If the converter efficiency is less than 96%, replace the converter. We add the information in the revised paper. Please see page 3, line 89 for the revision.
Line 135 One major concern is that the paper describes trends and seasonal behavior of NO_x. However, of the nitrogen oxides, NO2 has the major impact on health. NO2 data should be included into table 1 and discussed. What is the long-term trend of NO2?

Response: In this regional background station, NO₂ was the dominant form of NO_x, accounting for 82.2 % of NO_x, so we didn’t present the trends and seasonal behavior of NO₂. In the revised manuscript, we included the NO₂ in Table 1 and text, but trends and seasonal behavior of NO₂ in supplementary material.
Line 167 As the authors point out satellite observations are a valuable tool when analyzing station data. How does the long-term trend of the OMI NO2 observation compare to the NO_x data at the site? Likewise, comparison of in situ observation with station data could help to differentiate between boundary layer effects and emission effects when discussing the diurnal behavior of NO_x. How does the diurnal behavior of the satellite observation compare to the diurnal behavior of station data?

Response: Thanks for the suggestion. We think it would be a good idea to compare in situ observation with satellite observations to distinguish between boundary layer effects and emission effects. But, given our current level of knowledge, we need to learn further to complete the work. Here, we compare the monthly average satellite products for NO₂ with the monthly mean surface NO₂, since OMI covers a point on the ground about once every two days.
Line 207 The pollution roses in Figure 5 show that SO₂ and NO_x mixing ratios depend not only on the windspeed but also on the wind direction. Is it possible to add a plot to figure 5 which shows the dependency on wind direction?

Response: Thanks for the suggestion. Rose maps are often used to discuss the relationship between wind direction and pollutant concentration, which details had been plotted in Figure 6 and analyzed in section 3.4.
Line 220 Changes in relative humidity can often by explained with changes in airmasses which are advected from different sites. How does relative humidity change with wind direction? Can the wind direction explain the change of NO_x and SO₂ with changing relative humidity?

Response: Thanks for your suggestion. We plot the relative humidity change with wind direction together with NO_x and SO₂ rose maps (Figure R1). Also comparing them with figure 1, we think it cannot explain the change of NO_x and SO₂ with changing relative humidity.
Figure R1. NO_x, SO₂, and RH rose maps

Line 237 The authors write that the main source of SO₂ and NO_x are east from the site as the show it in figure 7. However, in figure 6 it can be observed that highest mixing ratios were measured with wind coming from west. How can this discrepancy be explained?

Response: Thanks. The wind concentration rose diagram (Figure 6) is a method that can effectively identify short-range transport sources near the ground, while the CWT method (Figure 7) can effectively identify long-range transport sources. Based on a comparison of the two, it can be seen that from the perspective of local emissions, atmospheric NO_x and SO₂ at the LAN station are mainly from the northeast and southwest of the station, while long-range transport is influenced by the east.
Line 305 The diurnal behavior is already discussed in chapter 3.3. I would suggest merging chapter 3.3 with lines 305 to 341.

Response: Thanks for the suggestion. Chapter 3.3 aims to provide an overview of the characteristics of the diurnal behavior of NO_x and SO₂ over the observation period, while lines 305 to 341 focus on their long-term characteristics and causes. So, we kept to separate chapter 3.3 from lines 305 to 341.
Line 327 If the disappearance of the NO_x peak at 1:00 A.M. were due to reduction of industrial emissions, why should industrial emissions peak at 1:00 A.M.? Shouldn´t the effect be seen all over the night?

Response: Yes, NO_x peak at 1:00 AM also puzzled us. A small peak in NO_x and SO₂ occurred between 01:00 and 02:00, which might be related to nighttime emissions from unscrupulous enterprises (Fan et al., 2013) or the lower electricity prices after midnight in response to the financial pressure of the 2008 economic crisis and the corresponding increase in electricity prices for industrial users (Sun, 2008). But it's really hard to tell exactly why these small peaks dominate after midnight. These two causes also feel too speculative, so we just present the result here.
We revised the sentences as (Page 11, line 334):
The disappearance of the small peak around 01:00 at night during 2012–2016 may be related to the introduction of stricter air pollution control policies for factories that emit at night. Small peaks in NO_x and SO₂ occurred between 01:00 and 02:00, which might be related to nighttime emissions from unscrupulous enterprises (Fan et al., 2013) or more production activities the with lower electricity prices after midnight in response to the financial pressure of the 2008 economic crisis and the corresponding increase in electricity prices for industrial users (Sun, 2008). In spite of these two reasons, however, it's really hard to tell exactly why these small peaks dominate after midnight.
Fan, Y., Fan, S., Zhang, H., Zu, F., Meng, Q., and He, J.: Characteristics of SO₂, NO₂, O₃ volume fractions and their relationship with weather conditions at Linan in summer and winter, J. Atmos. Sci., 121‒128, 2013.
Sun, W.: "A two-pronged approach of "limiting coal prices" and "raising electricity prices, Yangtze River Delta, 58‒60, 2008.

Line 337 To my knowledge, the impact of traffic on SO₂ emission in China is of minor importance. Have you considered residential sources, which are after industrial emissions and power plant emissions the third most important source of SO₂ according to the Multi-resolution Emission Inventory for China (MEIC)?

Response: Thanks. You are right. For the evening peaks, the residential sources should be important for SO₂because it’s also in cooking hours. We revised sentence as: “The formation of the evening peaks of NO_x and SO₂ may be mainly related to the increase in motor vehicle and residential sources emissions, which are stronger in the rush and cooking hours and that of SO₂ may be probably more due to the reduction of power plants emissions.” Please see Page 12, line 348 for the revision.
Line 369 Data availability: A link should be provided to where the data are stored in the GAW archive.

Response: As far as I know, the data of NO_x and SO₂ data for this site are not available in the GAW archive. The specific reasons are complex.
Technical corrections:
Title: Measurement report: Long-term variations in surface NO_x and SO₂ from 2006 to 2016 at a background site in the Yangtze River Delta region, China

Better:
Title: Measurement report: Long-term variations in surface NO_x and SO₂ mixing ratios from 2006 to 2016 at a background site in the Yangtze River Delta region, China
Response: Accepted. Please see page 1, line 1 for the revision.
Line 185: The seasonal average diurnal variation in NO_x showed a morning peak of NO_x in summer at 08:00, which is 1 to 2 h earlier than during other seasons (Fig. 4c). This sentence is not clear to me. What is it compared to?

Response: We revised the sentence. “In summer, the seasonal average diurnal variation in NO_x showed a morning peak at 08:00, which time is 1 to 2 h earlier than that occurred in other seasons (Fig. 4c).” Please see Page 7, line 192 for the revision.
Line 221: different periods are well consistent

Response: Accepted. Please see Page 7, line 224 for the revision.
Line 222: A blank is missing

Response: Accepted. Please see Page 8, line 225 for the revision.
Line 250: Please give a reference for the Ecological and Environmental Status Bulletin.

Response: Accepted. Please see Page 8, line 225 for the revision.
Line 254: smaller than those

Response: Accepted. Please see Page 9, line 258 for the revision.
Figure 5: The dependencies of SO₂ on meteorological parameters in the figure is blurred from the underlying trend. In figure 5h it cannot be seen if data for 2014-2016 change at all. Maybe it is better to plot changes relative to a mean value.

Response: Accepted. Please see Page 24, figure 5 for the revision.
Figure 6: I would suggest using the same color for NO_x in all the seasons in this plot and label the plots instead.
Response: Accepted. Please see Page 25, figure 6 for the revision.
Figure 11: The different y scales in Figures 11a to Figures 11c makes comparison between the periods difficult. I would suggest using the same scale.

Response: Accepted. Please see Page 29, figure 11 for the revision.
Figure 11: I would suggest naming the periods in the figure caption.

Response: Accepted. Please see Page 29, figure 11 for the revision.

Response to comments by referee # 2
General comments
The authors present a concise study on long-term trends of NO_x and SO₂ in the region of the Yangtze River Delta based on data acquired at the global GAW station Lin'an.
They interpret diurnal, seasonal and long-term changes and put them in context with trends measured in several other regions or cities in China and across the globe.
They assess correlations with meteorological parameters and emissions by different sources.
To identify source regions a potential source analysis of NO_x and SO₂ is applied on the YRD region.
Changes in average diurnal patterns of NO_x and SO₂ from 2006 to 2016 where found and attributed to long-term changes of vehicle emissions and industrial emissions, respectively.
Specific comments
l.30, l.307, table 1: Why not denoting it SO₂/NO_x or Sulph./Nitrog.? S/N might be mixed up with signal-to-noise ratio.
Response: Accepted. We use SO₂/NO_x instead of S/N in the revised version.
l.85: For NO_x: The method of NO2 to NO conversion is missing and must be explained. Furthermore, were corrections for humidity (respective quenching for CLD technique) and ozone reaction within the inlet line applied on the presented data?
Response: In model 42C-TL trace-level chemiluminescent analyzer, NO₂ is converted to NO by a molybdenum NO₂-to-NO converter heated to about 325℃. The converter efficiency was checked annually using gas phase titration (GPT). If the converter efficiency is less than 96%, replace the converter. We add the information in the revised paper. Please see Page 3, line 89 for the revision.
l.97: Item (4) might describe more specifically what kind of checks, testings are done and what self-diagnosis does comprise of or even better give a reference where it is explained in more detail.For example, I'm wondering what self-diagnosis means: Is it applying internal thresholds for operating parameters and, if yes, which one and what are the consequences for the instrument or measurements? Is this automatically done by the instrument or by the data acquisition system?
Response: Mostly, the instrument self-diagnosis is applying internal thresholds for operating parameters, which can alert people to carry out manual testing, checking, and maintenance on the instrument. It can't be described in a few words. Technical report from U.S. Environmental Protection Agency can be a reference here. We add a reference of US EPA (2017) in the text.
US EPA：Quality Assurance Handbook for Air Pollution Measurement Systems, Volume II, Ambient Air Quality Monitoring Program, EPA-454/B-17-001, 2017.
l.215: Is it adequate to call it already "effect" if this is an investigation of correlations? Is causality approved yet?
Response: Thanks. We have corrected "effect" to "correlation". Please see Page 8, line 218 for the revision.
l.328: Reference for a change of (specific) air pollution control measures?
Response: You might mean what specific air pollution control measures causing the disappearance of the NO_x peak at 1:00 A.M? PLS see our response to referee #1, question 8.
Technical corrections
Figure 2: P (hPa), factor 10 missing?
Response: Thanks. The factor of 10 is missing. The unit is kPa. Please see Page 21, Figure 2 for the revision.
Citation: https://doi.org/10.5194/acp-2021-227-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Qingqing Yin on behalf of the Authors (03 Aug 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (20 Aug 2021) by Steven Brown

RR by Anonymous Referee #1 (17 Nov 2021)

Suggestions for revision or reasons for rejection

This paper reports on NOx and SO2 measurements at the background site in the Yangtse River Delta region in China. The site, the instrumental setup, quality control and the data processing procedures have been described in detail. Data are compared to other data from other measurement sites. The long-term trend of both SO2 and NOx, their diurnal and seasonal behavior are discussed and compared to emission data.
The authors have answered all the questions from the referees.
There are only few NOx datasets on background sites published so far so I would recommend this paper being accepted for publication after a minor revision.
Line 90:
In the first version of paper the method for conversion of NO2 to NO was not mentioned. In the revised version the authors write that NO2 is converted on heated molybdenum. It is well known that this type of converter produces artefacts which leads to an overestimation of NOx, e.g., (Jung et al., 2017;Steinbacher et al., 2007). Therefore, molybdenum converters should not be used at GAW sites for NO2 conversion (WMO, 2011).
In the paper, the authors should discuss possible interferences caused from this conversion method and their possible consequences with respect to the major findings of their paper.
Line 380:
NOx Data from GAW station should be submitted to the global data archive. For nitrogen oxides data this is the World Data Centre for Reactive Gases (WDCRG) maintained by the Norwegian Institute for Air Research (NILU, https://www.gaw-wdcrg.org/). This is a general requirement for GAW stations; and stations that do not report data to the central database should not be termed GAW stations. On the other hand, I understand that there are different obstacles which take time to be overtaken. So, I can agree with the statement on data availability at this point. Still, I strongly recommend to foster the efforts to submit the data to the World Data Centre.

References:
Jung, J., Lee, J., Kim, B., and Oh, S. (2017). Seasonal variations in the NO2 artifact from chemiluminescence measurements with a molybdenum converter at a suburban site in Korea (downwind of the Asian continental outflow) during 2015–2016, Atmos. Environ., 165, 290-300, doi: https://doi.org/10.1016/j.atmosenv.2017.07.010.
Steinbacher, M., Zellweger, C., Schwarzenbach, B., Bugmann, S., Buchmann, B., Ordóñez, C., Prevot, A. S. H., and Hueglin, C. (2007). Nitrogen oxide measurements at rural sites in Switzerland: Bias of conventional measurement techniques, Journal of Geophysical Research: Atmospheres, 112, doi: https://doi.org/10.1029/2006JD007971.
WMO (2011). WMO/GAW Expert Workshop on Global Long-term Measurements of Nitrogen Oxides and Recommendations for GAW Nitrogen Oxides Network, Geneva, Switzerland, GAW Report 195.

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ED: Publish subject to minor revisions (review by editor) (25 Nov 2021) by Steven Brown

AR by Qingqing Yin on behalf of the Authors (01 Dec 2021) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (11 Dec 2021) by Steven Brown

AR by Qingqing Yin on behalf of the Authors (13 Dec 2021) Author's response Manuscript

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Short summary

China has been experiencing rapid changes in emissions of air pollutants in recent decades. NO_x and SO₂ measurements from 2006 to 2016 at the Lin’an World Meteorological Organization Global Atmospheric Watch station were used to characterize the seasonal and diurnal variations and study the long-term trends. This study reaffirms China’s success in controlling both NO_x and SO₂ in the Yangtze River Delta but indicates at the same time a necessity to strengthen the NO_x emission control.