Estimating nitrogen and sulfur deposition across China during 2005–2020 based on multiple statistical models
Abstract. Due to the rapid development of industrialization and substantial economy, China has become one of the global hotspots of nitrogen (N) and sulfur (S) deposition following Europe and the USA. Here, we developed a dataset with full coverage of N and S deposition from 2005 to 2020, with multiple statistical models that combine ground-level observations, chemistry transport simulations, satellite-derived vertical columns, and meteorological and geographic variables. Based on the newly developed random forest method, the multi-year averages of dry deposition of OXN, RDN and S in China were estimated at 10.4, 14.4 and 16.7 kg N/S ha−1 yr−1, and the analogous numbers for total deposition were respectively 15.2, 20.2 and 25.9 kg N/S ha−1 yr−1 when wet deposition estimated previously with a GAM model was included. The Rdry/wet of N stabilized in earlier years and then gradually increased especially for RDN, while that of S declined for over ten years and then slightly increased. RRDN/OXN was estimated to be larger than 1 for the whole research period and clearly larger than that of the USA and Europe, with a continuous decline from 2005 to 2011 and a more prominent rebound afterwards. Compared with the USA and Europe, a more prominent lagging response of OXN and S deposition to precursor emission abatement was found in China. The OXN dry deposition presented a descending gradient from east to west, while the S dry deposition a descending gradient from north to south. After 2012, the OXN and S deposition in eastern China declined faster than the west, attributable to stricter emission controls. Positive correlation was found between regional deposition and emissions, while smaller deposition to emission ratios (D/E) existed in developed eastern China with more intensive human activities.
Kaiyue Zhou et al.
Status: final response (author comments only)
- RC1: 'Comment on egusphere-2023-620', Anonymous Referee #1, 28 Apr 2023
- CC1: 'Comment on egusphere-2023-620', Lei Duan, 01 May 2023
- RC2: 'Comment on egusphere-2023-620', Lei Duan, 02 May 2023
- RC3: 'Comment on egusphere-2023-620', Anonymous Referee #3, 09 May 2023
Kaiyue Zhou et al.
Kaiyue Zhou et al.
Viewed (geographical distribution)
This study aims to develop a machine learning framework for estimating spatial distribution and long-term trend of N and S deposition across China. Estimated dataset during the period from 2005 to 2020 is valuable to understand effects of emission reductions on deposition and N and S input to ecosystems in China. On the other hand, the dataset has considerable uncertainties (as the authors mentioned in section 3.4). The authors should also take the uncertainties into account in other sections. In addition, there are some parts where discussion is insufficient. Specific comments are shown as follows:
To estimate dry deposition flux, deposition velocity (Vd) was calculated by CTM (GEOS-Chem). Current Vd models (resistant models) have large uncertainties, especially for gaseous and particulate Nr components. Therefore, the authors should open Vd calculation in detail. Although the authors indicate gaseous Vd parameterization in L255 (Wesely, 1989) used in this study, aerosol Vd parameterization should be indicated too. General aerosol models output Vd by size. On the other hand, monitored particulate NH4, NO3 do not have detailed size information (only the information of cutoff size: PM2.5, PM10, or TPM). It is necessary to explain how to treat the aerosol size to calculate the dry deposition based on equation (1). Moreover, calculated Vd values should be indicated. For example, average values of Vd for each land use are very informative for relevant researchers. This will be important information when comparing the dataset with the results of other studies.
This study uses wet deposition of SO4 (EANET) and wet or bulk deposition of NO3, NH4 (NNDMN). There is a need to discuss which regions the overestimation of NO3, NH4 by bulk sampling may affect in “3 Results and discussion”.