the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Towards an integrated inventory of anthropogenic emissions for China
Abstract. Despite ongoing efforts to reduce pollution, persistent ozone pollution in China remains a public health concern. To better understand the causes of ozone pollution in China and to assess and evaluate the effectiveness of past, current, and planned targeted pollution control strategies, estimates of the amounts of pollutants emitted from various sources are needed. To this end, we have developed harmonized and integrated anthropogenic emission inventories for China, incorporating information from the existing national inventory for mainland China (MEIC) and three global inventories (CEDS, CAMS, HTAP) to cover areas outside of China. The newly developed China INtegrated Emission Inventory (CINEI) includes emissions in China from sectors currently omitted from the MEIC (ships, aviation, waste, and agriculture) that we incorporate from the global inventories. To ensure harmonized emissions data, we performed mapping between different inventories, a process used to achieve consistency between sectors, spatial resolution, and speciation of non-methane volatile organic compounds (NMVOCs). These harmonized and integrated inventories for China were used to drive WRF-Chem simulations for January (winter) and July 2017 (summer). Through a detailed evaluation of model results against available observations, we show that while the direct use of global inventories alone can lead to severe over- or underestimation of pollutant mixing ratios, CINEI inventories perform satisfactorily in simulating ozone (12 % in summer and 43 % in winter normalized mean bias) and its precursors, including nitrogen dioxide (NO2, -0.5 % in summer and 40 % in winter) and carbon monoxide (CO, -50 % in both seasons). Based on the comparison and modeling of this study, valuable insights into the spatio-temporal variability of ozone and the subsequent design of future ozone mitigation strategies in China were provided.
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Status: open (until 03 Aug 2025)
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RC1: 'Comment on egusphere-2025-268', Anonymous Referee #1, 27 Jun 2025
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Zhang et al. developed an integrated anthropogenic emissions inventory for China (CINEI) by incorporating the regional-scale MEIC inventory along with three global-scale emission inventories. They evaluate the performance of this new inventory by comparing WRF-Chem simulations driven by CINEI against observations. The results show that CINEI performs reasonably well in simulating ozone (O₃) and its precursors. The manuscript is well written and provides sufficient technical detail, fitting well within the scope of GMD.
Major comment:
Why does the study rely solely on MEIC for China in all harmonized emission inventories instead of using global inventories? The paper devotes substantial effort to harmonizing emission sectors, VOC speciation, and spatial resolution, but these harmonized datasets are not fully utilized to produce the final emissions inventory. Does MEIC significantly outperform the global inventories in China? I did not see supporting evidence for this in Figures 6–7.
Additionally, the key distinction between CINEI and MEIC lies in the inclusion of previously missing sources in CINEI, such as agricultural, waste, and marine sectors. While MEIC has been evaluated in previous studies, the current evaluation of CINEI essentially serves to assess the impact of these additional sources. This important insight should be emphasized more clearly and consistently throughout the manuscript.
Other comments:
- Table 2: What criteria were used to select the emission inventory for each source sector?
- Section 3.2 and Figure 4a: What causes the large year-to-year fluctuations in ozone formation potentials (OFPs)?
- How are VOC emissions from volatile chemical products (VCPs) treated in the CINEI inventory?
Citation: https://doi.org/10.5194/egusphere-2025-268-RC1 -
RC2: 'Comment on egusphere-2025-268', Anonymous Referee #2, 02 Jul 2025
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Review Comment:
This study by Zhang et al. integrates multiple emission inventories, using MEIC as the foundation while incorporating missing sources such as aviation, international shipping, waste, and agriculture from global datasets. The authors also evaluate the performance of different inventories through WRF-Chem simulations, demonstrating that the integrated emission is generally robust and reliable. However, as the authors mentioned, similar efforts have recently emerged in emission integration. It is necessary to further clarify how this work compares to and advances beyond existing inventories.
- Recent efforts such as HTAP v3.1 (https://essd.copernicus.org/preprints/essd-2024-601/) have also incorporated MEIC for China. It is suggested that the authors compare CINEI with HTAP v3.1 over China to highlight differences and improvements.
- Similarly, MIX v2 has integrated MEIC emissions. What are the methodological advancements and advantages of CINEI relative to MIX v2?
- Table 2: When the same emission source exists in multiple global inventories, how is the choice made? For instance, international shipping emissions are available in CEDS, CAMS, and HTAP. Why is CAMS selected in this case? A clearer explanation of the selection principles is needed.
- What are the exact differences between HMEI and CINEI? Is it solely the inclusion of previously missing sectors (e.g., ships, aviation, waste, agriculture), or are there additional improvements in sectoral mapping, NMVOC speciation, or spatial harmonization?
- Line 115–119: The CAMS dataset is extended from 2018 to 2022 using linear slopes from CEDS. How are uncertainties introduced by this extrapolation process quantified and propagated? More detailed treatment or discussion is recommended.
Citation: https://doi.org/10.5194/egusphere-2025-268-RC2
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