the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Rapid Increases of Ozone Concentrations over Tibetan Plateau Caused by Local and Non-Local Factors
Abstract. Changes in tropospheric ozone over the Tibetan Plateau (TP) profoundly affect the local ecosystems and human health. Yet previous studies on the TP ozone have focused on the background regions, with much less attention on the urban ozone. Here we quantify the ozone trends over the whole TP from 2015 to 2019 in the context of its long-term trends, with a focus on urban ozone. We use ozone measurements from 30 urban stations in 17 cities, the Waliguan baseline station, and four satellite products of tropospheric ozone. We further analyze the drivers of ozone trends through a combination of chemical transport model simulations, back-trajectory calculations, a bottom-up emission inventory, and a satellite-derived emission dataset of nitrogen oxides (NOx). We find a strong increase in deseasonalized urban ozone at the MEE stations from 2015 to 2019 (by 1.71 ppb yr-1). The urban ozone trend far exceeds the trend at Waliguan (by 0.26 ppb yr-1) and the TP average trend (by up to 0.08 ppb yr-1) derived from the four satellite products. Interannual variations in meteorology do not produce significant ozone trends over the TP. Non-local factors contribute positively to the urban ozone trends, due mainly to more frequent transport passing through the footprint layers (0–300 m above the ground) of non-local high-emission regions. Another important contributor to the urban ozone growth is the 26.5 % increase in local anthropogenic NOx emissions. Emission reductions in both the local and non-local source regions can help mitigate the rapid urban ozone growth over the plateau.
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RC1: 'Comment on egusphere-2024-3471', Anonymous Referee #1, 05 Dec 2024
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This study employs ozone measurements from urban sites across 17 cities, a background site (Waliguan), four satellite products, and integrate two models (GEOS-Chem CTM and trajectory models) to analyze ozone variations over the TP region. The authors find a notable increase in ozone levels at urban stations, surpassing trends observed at Waliguan and those derived from satellite data. Analysis of model results and emission inventories suggests that this ozone rise is driven by increased local anthropogenic emissions and enhanced contributions from non-local sources. The study offers valuable new insights into understanding ozone changes in the region. The manuscript is well-written and structured. I recommend addressing the following points before publication:
Line 171: Please clarify the rationale behind selecting a 192-hour time frame for analysis.
Figure 2: Are all 30 sites consistently showing an increasing trend? If not, please elaborate on any variations.
Section 4.2: While generally reasonable, the discussions could be more informative. Why does the residence time show an increasing trend, and is it linked to changes in meteorological patterns? Could you present and discuss the non-local emission trends over TP, along with foreign source regions derived from the PHLET-OMI inventory? Additionally, since the PHLET-OMI only quantifies NOx emissions, and VOC emissions can differ significantly, do we have robust estimates of VOC emissions over TP and the surrounding source regions?
Line 341: The increase in NOx emissions is surprising, given that most regions in China have seen significant reductions in NOx emissions. Could the authors discuss possible reasons for this increase, possibly referencing relevant literature?
Lines 359-369: I am uncertain about the robustness of this method and its interpretation. First, it overlooks the non-linear interactions between meteorology, local, and non-local emissions. Second, Lines 364-367 assume that Waliguan and the 17 MEE cities share similar ozone formation mechanisms. Is this assumption reasonable? If the same method is applied individually to each of the 17 cities, would we obtain similar values for a and b for each city pair?
Citation: https://doi.org/10.5194/egusphere-2024-3471-RC1 -
RC2: 'Comment on egusphere-2024-3471', Anonymous Referee #2, 23 Dec 2024
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The manuscript presents a comprehensive analysis of ozone trends over the Tibetan Plateau, particularly highlighting urban areas, and successfully identifies the contributions of local emissions and regional transport to ozone changes, based on ground observation data, different satellite data, CTM model and HYSPLIT model. The authors concluded that the ozone trends at urban areas of TP were caused by a combination of local and non-local factors, especially from the local anthropogenic emissions. The multiple methods adopted in this study were appreciated. However, there were some logistic issues the authors need to address.
In this study, the authors did not use the CTM to quantify the contribution of non-local factors on ozone issues in TP but the HYSPLIT (the QNR method), quoting that there were large uncertainties for the VOCs (line 305-306). However, the QNR method also had uncertainties due to the fact it did not consider the nonlinearity in ozone formation chemistry (line 179). So how the authors justify their choices of one method over another? At least by using the CTM, the comparisons will be consistent. So in quantifying their contributions of ozone trends for cities and Waliguan (line 359-369), the simplified linear model were not acceptable since the three factors (𝑇𝑚𝑒𝑡, 𝑄𝑛𝑜𝑛𝑙𝑜𝑐𝑎𝑙, 𝑄𝑙𝑜𝑐𝑎𝑙 ) were not derived at the same ground.
Minor comments:
- Explain QNR.
- Line 93: put the abbreviation of NOX where it was first introduced in the main content. The same for O3 in line 102.
- Line 132: Please double check the OMI website. I think OMI ozone products start from 2004.
- Line 171: The authors chose 192 hours for their back-trajectory simulations; what was the basis for this time choice? Please provide a clear explanation of why 192 hours is sufficient to capture the majority of air mass transport influencing TP. For example, is this duration chosen based on previous studies, the lifetime of ozone precursors, or the distance from major emission source regions? Or discuss whether shorter or longer durations would significantly change the results of the transport analysis.
- Add a note on the accuracy of model simulations.
- Line 182: change to (Chen et al., 2022a)
- 请仔细检查用于 HYSPLIT 和 GEOS-Chem 模型的不同 MERRA2 分辨率。
- 从图 4 中,作者指出,没有卫星产品捕捉到在 MEE 站观察到的臭氧快速增长。因此,在我看来,这些多卫星产品是多余的,并没有为这项研究增加额外的价值。第 2.2 节真的没有必要。
- 在讨论 QNR 时,强调了 NOx 作为臭氧前体体的作用。然而,人们认识到,在某些条件下,尤其是在高 NOx 环境中或夜间,NOx 也可以通过 NO 滴定来降低臭氧浓度。考虑添加分析(卫星数据:HCHO 和 NOx)或参考文献来说明 O 的依赖性3研究区的 NOx 产量。
- 请根据需要在参考文献中统一期刊的缩写/全名。
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