the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Jun 2024
Long-term variations of pH in coastal waters along the Korean Peninsula
Abstract. The decreasing seawater pH trend associated with rising atmospheric CO2 levels adversely affects marine organisms and ecosystems, posing significant concerns for coastal fisheries and economies. Despite this, long-term pH variation in coastal waters remains poorly understood. This study investigates pH variability in the coastal waters of Korea over 11 years (2010–2020) and identifies the principal drivers of pH fluctuations. Unlike the persistent pH decline observed in open oceans and other coastal systems, Korean coastal waters showed no significant pH variation, suggesting local biogeochemical processes may exert a greater influence than atmospheric CO2. Analysis of environmental data (temperature, salinity, chlorophyll a, and dissolved oxygen (DO)) revealed a strong correlation between pH and DO. However, instances of pH changes exceeding those predicted by DO depletion indicate additional biogeochemical factors at play. As global seawater warms, reduced dissolved gases, including oxygen, are expected to cause further pH decline in coastal waters. This trend could critically impact Korean coastal waters, which support extensive aquaculture operations integral to the local and national economy. Therefore, high-frequency monitoring is essential to extend current time series and predict future water quality.
-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
-
Preprint
(2281 KB)
-
Supplement
(2791 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2281 KB) - Metadata XML
-
Supplement
(2791 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1836', Anonymous Referee #1, 22 Jul 2024
General comments:
This manuscript investigates trends in pH over an 11-year period (2010-2020) in Korean coastal waters and claims to identify the principal drivers. The authors conclude that local biogeochemical processes are more important than ocean acidification driven by increasing atmospheric CO2, confirming what has been reported in several studies already – some of those referenced in the manuscript. Thus, I do not find any novel contributions in the manuscript, except that it presents data from a less well-studied area.
The authors never try to further investigate which biogeochemical processes are most important. They conclude that “biogeochemical factors such as nutrient levels, biological production, oxygen conditions, and contaminant inputs likely play significant roles”, although the causal linkages are not explained. In fact, I am not convinced about the contaminant inputs, which is only supported by stating that “greater contaminant inputs in Niigata, a megacity on the Japanese coast, may contribute to the observed differences” in primary production between the Korean and Japanese side of the East Japan Sea. This assertion is completely unsupported and most likely wrong, as the authors have not considered other explanations such as effects of upwelling. Not being an expert in the study area, I do think that the strong north-going current could drive upwelling along the Korean coast by Ekman transport. Dominant wind patterns could also drive upwelling along the Korean coast. Why haven’t the authors investigated the hydrography of the area in more detail before making such assertion?
Going back to the aim of identifying the drivers of pH trends, I do not think the authors have managed to do so. One of the final comments is that “our understanding of pH variability and ocean acidification in the carbonate system will remain incomplete until we fully characterize the CO2 systems in Korean coastal oceans”. This conclusion is somewhat disappointing, since the processes of the carbonate system are well described and it should be possible to tease out the importance of different processes by solving the equations in CO2SYS or similar program. The authors should be able to conduct a more thorough and detailed analysis of their data.
This brings me to my next general comment about the separation of data into three regions. If local conditions, particularly inputs of nutrients and organic matter from land, are more important then why pool sites together that have very different connectivity to land into three study regions? It would be more meaningful to separate the sites into different coastal types such as river-dominated estuaries, estuaries, lagoons, embayments, coast, etc. and perhaps use stratification patterns as another descriptor for separating sites into more similar groups. Given that the coastal systems included within each group are so diverse, averaging across these are likely to produce ‘no information’.
Following that, it appears that there is a lack of consistency in the sampling among cruises. Fig. 1 shows 356 sites that have been monitored, but looking at the figures in the SI it does not appear that all these sites have been monitored in each cruise. This would imply ~120 observations for each time point in each region. The consistency of monitoring is not described in the M&M, and in case that all stations are not monitored at each monitoring time point, averaging across different sites for each time point creates a bias in the time series. The authors need to address this issue more clearly.
In fact, there is no description of how data were processed, i.e. how were trends assessed (with or without seasonal adjustment), how was the pH in Fig. 7 estimated and what were the assumptions, the calculation of AOU, etc.? How were surface and bottom waters distinguished and was the water column always stratified? Data processing methods seem to be introduced along the way in the results and discussion section without clear explanation as why they were chosen and what was the hypothesis. This needs to be better structured. Moreover, I am surprised to see that there is no apparent connection between low DO and low pH in Figure S2, S4 and S6. There is an intricate relationship between DO and pH, since oxygen consumption (mainly) produces CO2. Many months have low DO without pH dropping at the same time. This is indeed surprising and makes me think that there could be issues with measuring pH (calibration?). Normally, low DO (<2-3 mg L-1) should be accompanied by pH less than ~7.5, but this does not seem to be the case. I recommend the authors to plot measurements of DO versus pH and check for consistency in the relationships across time and region. Similarly high pH (>8.5) without extremely high chla are also unusual, confirming my assertion that something could be wrong with the data.
Finally, the language is not always clear and it is difficult to see whether it is due to language difficulties or lack of understanding of the biogeochemistry. I found statements that were wrong, unclear and misleading, but the cause of this is not clear to me.
Specific comments:
- 67: High alkalinity would actually buffer against acidification, so this can hardly be an explanation to higher trends in the Mediterranean Sea!
- 86: Pristine implies a state before human disturbance. I doubt that the east coast is entirely undisturbed, so better to say “relatively undisturbed”.
- 145: The authors claim that OA is the foremost concern for coastal ecosystems. This claim is unsupported and in my view not correct. Eutrophication, food-web alteration from overfishing, physical disturbance from bottom trawling are pressures that are prominent in the coastal zone and have larger impact on organisms and habitats. This sentence should be deleted.
- 150: Differences between surface and bottom water pH is driven by production in the surface increasing pH and respiration in the bottom decreasing pH. This is not very clearly expressed here and it needs to be.
- 152: Was the trend exactly the same for surface and bottom? That seems odd.
- 153: F=00003 and not significant, but the slope was 0.00009±0.00001 which with an ordinary t-test gives a highly significant slope. This does not match and needs to be checked.
- 166-167: Coastal eutrophication stimulates production in the surface layer causing pH to rise and respiration in the bottom layer causing pH to decrease. The sentence does not articulate this very well and it is misleading or actually wrong.
- 180: Can this be elaborated more specifically? What biogeochemical properties are driving pH dynamics?
- 198: Elaborate how this will influence pH?
- 207: “long-term pH trends may exhibit a negative correlation with temperature”. The authors refer to CO2 solubility, but warmer water can contain less CO2 in equilibrium! This should cause a positive correlation. However, there is another factor that the authors have overlooked, the issue of shifting equilibrium constants in the carbonate system. As the water warms, the carbonate system shifts towards more dissolution, producing more H+ ions and thereby lowering pH. This might be more relevant than the equilibrium with the atmosphere due to the slower kinetics of the gas exchange.
- 242-246: This should be described under the Materials and methods section. The calculations are also based on the assumption that DO consumption results from respiration and nitrification?
- 248: “pH in Korean coastal waters is primarily controlled by oxygen conditions”. This is not correct. Both DO and pH result from an imbalance between respiration and production.
- 254: Why would atmospheric CO2 have increased more along the Korean coast? This does not make sense. The atmospheric concentration is relatively constant across the northern hemisphere as well as the southern hemisphere.
- 256: Is this because different periods are compared? The authors cannot compare trends based on different periods.
- 295: Same comment as for L. 248.
Technical comments:
- 37-38: “though land-based input can be significant in river-dominated estuaries”.
- 42-43: “Hawaii Ocean Time-series (HOT)”
- 43-44: “European Station for Time-series in the Ocean of the Canary Islands (ESTOC)”
- 52: delete “a” before “long-term”
- 53: “surface water pCO2”
- 56: replace “plankton” with “coccolithophores” to be more specific.
- 59: emphasize “affecting many trophic levels” – not all.
- 63: insert “atmospheric” at beginning of line.
- 70: “decreased only by”
- 74: “due to increasing atmospheric CO2”
- 81: “possibly related to decreasing nutrient input (Provoost et al., 2010)”
- 91-92: “impacts of atmospheric CO2, warming and changing environmental conditions”
- 95: Should be “Korean Marine Environment Management Corporation (KOEM)”?
- 96: replace “assessing” with “monitoring”
- 102: delete “a comprehensive 11-year dataset to assess” – it is repetitive
- 104: delete “of” before “< 10 m”
- 104: Should be “The sites”, not “These sites”
- 110: “Large river systems are found in the west and south”
- 115: “Korean Coastal Current receiving inputs from the Kuroshio warm current”
- 119: replace “provide” with “deliver”
L.131: “KOEM research vessel” and “were measured with a CTD”
- 141-142: “the chl a was extracted from the filters and measured with a fluorometer”
- 146: start with “OA is of particular concern along the”
- 149: “Monthly averages for February, May, “
- 154: “at least over the study period. The observed pH trend”
- 161: “driven by rising atmospheric CO2 and variations in local salinity and primary production”
- 172: delete last part of sentence. Does not convey anything.
- 178: “regional trends in pH fluctuations can differ substantially from OA.”
- 211: A temperature increase of 0.0009 yr-1 is nothing. This cannot be a clear increasing trend, i.e. significant?
- 214: Freshwater in Korea might have a lower alkalinity in freshwater input than the ocean end-member due to the geology, but this is not the case everywhere. Watersheds with limestone typically have higher alkalinity than the ocean end-member.
- 218: This lack of relationship is most likely due to comparing averages, which removes most of the variability between pH and salinity. Try look at the raw data!
- 221: Replace “increased” with “elevated”.
- 230: “Reduced DO concentration primarily results from biological respiration ….”
- 232: DO can degas from the surface water, if and only if DO is supersaturated.
- 238: “net DO consumption”
- 240: Actually, the correct term to use for this measure is Apparent Oxygen Utilisation (AOU). Please use this consistently.
- 245: “range of the obserserved”
Citation: https://doi.org/10.5194/egusphere-2024-1836-RC1 -
AC1: 'Reply on RC1', DongJoo Joung, 24 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1836/egusphere-2024-1836-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-1836', Anonymous Referee #2, 27 Jul 2024
Dear Authors,
This study entitled “Long-term variations of pH in coastal waters along the Korean Peninsula” uses data (including temperature, salinity, pH, and DO) collected by a government agency in Korea from 2010-2020. Long-term data is rare. The authors suggest that coastal biological effects are more important than increasing atmospheric CO2. The data quality is not described in this study. The application of linear regression can be improved. The discussion on biogeochemical processes involving pH should be reevaluated. The major comments are as follows.
- Though the pH probe itself can reach a higher resolution, the resolution of these three pH buffers is unclear. Therefore, the uncertainty for this long-term trend of pH is unclear. Data QA and QC are unclear. What is the standard deviation for these average numbers? Moreover, oceanographers usually use the spectrophotometric method to measure pH or pH calculated by total alkalinity and dissolved inorganic carbon to study long-term pH changes. The pH value measured by a probe can be affected by its salinity. As the salinity varied in the surface water, the effect of salinity changes on this probed pH may also involve the pH changes.
- The analysis method. There are already many new methods that can analyze multiple parameters. The authors only use linear regression. The authors can try to use a better method that can systematically analyze several variables at the same time, such as principle component analysis or similar statistic methods.
- The definition of pH should be listed here as this study tries to describe the change in pH. Furthermore, why should pH be linearly correlated with other parameters? How and why is pH correlated to DO? Can the authors list the chemical equations to show that they are linear?
- The effect of mixing between freshwater and sea (salinity gradient) on pH variation is non-linear.
- The authors separated their data into the surface and bottom water in this study. However, the authors did not separate their discussion. In Cai et al. (2011), synergistic acidification is for bottom water. Surface water in the coastal region has been known as a high-productivity region with a high pH value. Is it possible that, though the authors used a long-term dataset, the resolution of the sensor and their standard variation, as well as the analysis method, is not sensitive enough to quantify the effect of acidification?
- The grammar should be thoroughly checked.
Citation: https://doi.org/10.5194/egusphere-2024-1836-RC2 -
AC2: 'Reply on RC2', DongJoo Joung, 24 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1836/egusphere-2024-1836-AC2-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1836', Anonymous Referee #1, 22 Jul 2024
General comments:
This manuscript investigates trends in pH over an 11-year period (2010-2020) in Korean coastal waters and claims to identify the principal drivers. The authors conclude that local biogeochemical processes are more important than ocean acidification driven by increasing atmospheric CO2, confirming what has been reported in several studies already – some of those referenced in the manuscript. Thus, I do not find any novel contributions in the manuscript, except that it presents data from a less well-studied area.
The authors never try to further investigate which biogeochemical processes are most important. They conclude that “biogeochemical factors such as nutrient levels, biological production, oxygen conditions, and contaminant inputs likely play significant roles”, although the causal linkages are not explained. In fact, I am not convinced about the contaminant inputs, which is only supported by stating that “greater contaminant inputs in Niigata, a megacity on the Japanese coast, may contribute to the observed differences” in primary production between the Korean and Japanese side of the East Japan Sea. This assertion is completely unsupported and most likely wrong, as the authors have not considered other explanations such as effects of upwelling. Not being an expert in the study area, I do think that the strong north-going current could drive upwelling along the Korean coast by Ekman transport. Dominant wind patterns could also drive upwelling along the Korean coast. Why haven’t the authors investigated the hydrography of the area in more detail before making such assertion?
Going back to the aim of identifying the drivers of pH trends, I do not think the authors have managed to do so. One of the final comments is that “our understanding of pH variability and ocean acidification in the carbonate system will remain incomplete until we fully characterize the CO2 systems in Korean coastal oceans”. This conclusion is somewhat disappointing, since the processes of the carbonate system are well described and it should be possible to tease out the importance of different processes by solving the equations in CO2SYS or similar program. The authors should be able to conduct a more thorough and detailed analysis of their data.
This brings me to my next general comment about the separation of data into three regions. If local conditions, particularly inputs of nutrients and organic matter from land, are more important then why pool sites together that have very different connectivity to land into three study regions? It would be more meaningful to separate the sites into different coastal types such as river-dominated estuaries, estuaries, lagoons, embayments, coast, etc. and perhaps use stratification patterns as another descriptor for separating sites into more similar groups. Given that the coastal systems included within each group are so diverse, averaging across these are likely to produce ‘no information’.
Following that, it appears that there is a lack of consistency in the sampling among cruises. Fig. 1 shows 356 sites that have been monitored, but looking at the figures in the SI it does not appear that all these sites have been monitored in each cruise. This would imply ~120 observations for each time point in each region. The consistency of monitoring is not described in the M&M, and in case that all stations are not monitored at each monitoring time point, averaging across different sites for each time point creates a bias in the time series. The authors need to address this issue more clearly.
In fact, there is no description of how data were processed, i.e. how were trends assessed (with or without seasonal adjustment), how was the pH in Fig. 7 estimated and what were the assumptions, the calculation of AOU, etc.? How were surface and bottom waters distinguished and was the water column always stratified? Data processing methods seem to be introduced along the way in the results and discussion section without clear explanation as why they were chosen and what was the hypothesis. This needs to be better structured. Moreover, I am surprised to see that there is no apparent connection between low DO and low pH in Figure S2, S4 and S6. There is an intricate relationship between DO and pH, since oxygen consumption (mainly) produces CO2. Many months have low DO without pH dropping at the same time. This is indeed surprising and makes me think that there could be issues with measuring pH (calibration?). Normally, low DO (<2-3 mg L-1) should be accompanied by pH less than ~7.5, but this does not seem to be the case. I recommend the authors to plot measurements of DO versus pH and check for consistency in the relationships across time and region. Similarly high pH (>8.5) without extremely high chla are also unusual, confirming my assertion that something could be wrong with the data.
Finally, the language is not always clear and it is difficult to see whether it is due to language difficulties or lack of understanding of the biogeochemistry. I found statements that were wrong, unclear and misleading, but the cause of this is not clear to me.
Specific comments:
- 67: High alkalinity would actually buffer against acidification, so this can hardly be an explanation to higher trends in the Mediterranean Sea!
- 86: Pristine implies a state before human disturbance. I doubt that the east coast is entirely undisturbed, so better to say “relatively undisturbed”.
- 145: The authors claim that OA is the foremost concern for coastal ecosystems. This claim is unsupported and in my view not correct. Eutrophication, food-web alteration from overfishing, physical disturbance from bottom trawling are pressures that are prominent in the coastal zone and have larger impact on organisms and habitats. This sentence should be deleted.
- 150: Differences between surface and bottom water pH is driven by production in the surface increasing pH and respiration in the bottom decreasing pH. This is not very clearly expressed here and it needs to be.
- 152: Was the trend exactly the same for surface and bottom? That seems odd.
- 153: F=00003 and not significant, but the slope was 0.00009±0.00001 which with an ordinary t-test gives a highly significant slope. This does not match and needs to be checked.
- 166-167: Coastal eutrophication stimulates production in the surface layer causing pH to rise and respiration in the bottom layer causing pH to decrease. The sentence does not articulate this very well and it is misleading or actually wrong.
- 180: Can this be elaborated more specifically? What biogeochemical properties are driving pH dynamics?
- 198: Elaborate how this will influence pH?
- 207: “long-term pH trends may exhibit a negative correlation with temperature”. The authors refer to CO2 solubility, but warmer water can contain less CO2 in equilibrium! This should cause a positive correlation. However, there is another factor that the authors have overlooked, the issue of shifting equilibrium constants in the carbonate system. As the water warms, the carbonate system shifts towards more dissolution, producing more H+ ions and thereby lowering pH. This might be more relevant than the equilibrium with the atmosphere due to the slower kinetics of the gas exchange.
- 242-246: This should be described under the Materials and methods section. The calculations are also based on the assumption that DO consumption results from respiration and nitrification?
- 248: “pH in Korean coastal waters is primarily controlled by oxygen conditions”. This is not correct. Both DO and pH result from an imbalance between respiration and production.
- 254: Why would atmospheric CO2 have increased more along the Korean coast? This does not make sense. The atmospheric concentration is relatively constant across the northern hemisphere as well as the southern hemisphere.
- 256: Is this because different periods are compared? The authors cannot compare trends based on different periods.
- 295: Same comment as for L. 248.
Technical comments:
- 37-38: “though land-based input can be significant in river-dominated estuaries”.
- 42-43: “Hawaii Ocean Time-series (HOT)”
- 43-44: “European Station for Time-series in the Ocean of the Canary Islands (ESTOC)”
- 52: delete “a” before “long-term”
- 53: “surface water pCO2”
- 56: replace “plankton” with “coccolithophores” to be more specific.
- 59: emphasize “affecting many trophic levels” – not all.
- 63: insert “atmospheric” at beginning of line.
- 70: “decreased only by”
- 74: “due to increasing atmospheric CO2”
- 81: “possibly related to decreasing nutrient input (Provoost et al., 2010)”
- 91-92: “impacts of atmospheric CO2, warming and changing environmental conditions”
- 95: Should be “Korean Marine Environment Management Corporation (KOEM)”?
- 96: replace “assessing” with “monitoring”
- 102: delete “a comprehensive 11-year dataset to assess” – it is repetitive
- 104: delete “of” before “< 10 m”
- 104: Should be “The sites”, not “These sites”
- 110: “Large river systems are found in the west and south”
- 115: “Korean Coastal Current receiving inputs from the Kuroshio warm current”
- 119: replace “provide” with “deliver”
L.131: “KOEM research vessel” and “were measured with a CTD”
- 141-142: “the chl a was extracted from the filters and measured with a fluorometer”
- 146: start with “OA is of particular concern along the”
- 149: “Monthly averages for February, May, “
- 154: “at least over the study period. The observed pH trend”
- 161: “driven by rising atmospheric CO2 and variations in local salinity and primary production”
- 172: delete last part of sentence. Does not convey anything.
- 178: “regional trends in pH fluctuations can differ substantially from OA.”
- 211: A temperature increase of 0.0009 yr-1 is nothing. This cannot be a clear increasing trend, i.e. significant?
- 214: Freshwater in Korea might have a lower alkalinity in freshwater input than the ocean end-member due to the geology, but this is not the case everywhere. Watersheds with limestone typically have higher alkalinity than the ocean end-member.
- 218: This lack of relationship is most likely due to comparing averages, which removes most of the variability between pH and salinity. Try look at the raw data!
- 221: Replace “increased” with “elevated”.
- 230: “Reduced DO concentration primarily results from biological respiration ….”
- 232: DO can degas from the surface water, if and only if DO is supersaturated.
- 238: “net DO consumption”
- 240: Actually, the correct term to use for this measure is Apparent Oxygen Utilisation (AOU). Please use this consistently.
- 245: “range of the obserserved”
Citation: https://doi.org/10.5194/egusphere-2024-1836-RC1 -
AC1: 'Reply on RC1', DongJoo Joung, 24 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1836/egusphere-2024-1836-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-1836', Anonymous Referee #2, 27 Jul 2024
Dear Authors,
This study entitled “Long-term variations of pH in coastal waters along the Korean Peninsula” uses data (including temperature, salinity, pH, and DO) collected by a government agency in Korea from 2010-2020. Long-term data is rare. The authors suggest that coastal biological effects are more important than increasing atmospheric CO2. The data quality is not described in this study. The application of linear regression can be improved. The discussion on biogeochemical processes involving pH should be reevaluated. The major comments are as follows.
- Though the pH probe itself can reach a higher resolution, the resolution of these three pH buffers is unclear. Therefore, the uncertainty for this long-term trend of pH is unclear. Data QA and QC are unclear. What is the standard deviation for these average numbers? Moreover, oceanographers usually use the spectrophotometric method to measure pH or pH calculated by total alkalinity and dissolved inorganic carbon to study long-term pH changes. The pH value measured by a probe can be affected by its salinity. As the salinity varied in the surface water, the effect of salinity changes on this probed pH may also involve the pH changes.
- The analysis method. There are already many new methods that can analyze multiple parameters. The authors only use linear regression. The authors can try to use a better method that can systematically analyze several variables at the same time, such as principle component analysis or similar statistic methods.
- The definition of pH should be listed here as this study tries to describe the change in pH. Furthermore, why should pH be linearly correlated with other parameters? How and why is pH correlated to DO? Can the authors list the chemical equations to show that they are linear?
- The effect of mixing between freshwater and sea (salinity gradient) on pH variation is non-linear.
- The authors separated their data into the surface and bottom water in this study. However, the authors did not separate their discussion. In Cai et al. (2011), synergistic acidification is for bottom water. Surface water in the coastal region has been known as a high-productivity region with a high pH value. Is it possible that, though the authors used a long-term dataset, the resolution of the sensor and their standard variation, as well as the analysis method, is not sensitive enough to quantify the effect of acidification?
- The grammar should be thoroughly checked.
Citation: https://doi.org/10.5194/egusphere-2024-1836-RC2 -
AC2: 'Reply on RC2', DongJoo Joung, 24 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1836/egusphere-2024-1836-AC2-supplement.pdf
Peer review completion
Journal article(s) based on this preprint
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 398 | 185 | 33 | 616 | 52 | 20 | 25 |
- HTML: 398
- PDF: 185
- XML: 33
- Total: 616
- Supplement: 52
- BibTeX: 20
- EndNote: 25
Viewed (geographical distribution)
| Country | # | Views | % |
|---|---|---|---|
| United States of America | 1 | 282 | 45 |
| South Korea | 2 | 69 | 11 |
| China | 3 | 40 | 6 |
| Australia | 4 | 19 | 3 |
| France | 5 | 18 | 2 |
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
- 282
Yong-Woo Lee
Mi-Ok Park
Seong-Gil Kim
Tae-Hoon Kim
Yong-Hwa Oh
Sang Heun Lee
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2281 KB) - Metadata XML
-
Supplement
(2791 KB) - BibTeX
- EndNote
- Final revised paper