suitable biomonitoring procedure for N deposition (Mohr et al. 2017). Based on the
biological variabilities of plants, their environmental interactions and response
delays, biomonitoring requires standardization to achieve consequential results.
Therefore, when utilizing just plants as N receptors, the possibility of accurately
quantifying total N deposition is limited. Moreover, the application of bioindicators
based on a single species is generally constrained to the geographic distribution of
that species. Through integration of species composition and leaf N stoichiometry of
understory vascular plants, Du (2017) proposed a community N indicator. Experimental results from a study in northeastern China revealed that the community N
indicator could be a useful tool to indicate N deposition, with the potential application across a wide range of terrestrial ecosystems (Du 2017).
3.2.4 Satellite-Based Monitoring
Dry and wet N deposition can be estimated using satellite data (Liu et al. 2017a, b, c;
Zhang et al. 2017). In general, the application of satellite-based monitoring to
estimate dry N deposition can be separated into two steps. First the satellite data
for NO 2 and NH 3 columns are converted to ground N r concentrations using the
vertical profiles from atmospheric chemistry transport models. These are obtained
from the MOZART-4. The MOZART-4 outputs for NO 2 and NH 3 include 56 vertical
levels, which were used to simulate the vertical profiles by a Gaussian function.
Second, dry N deposition is simulated using the satellite-derived ground N r concentration and modelled V d . For wet N deposition, a mixed effect model can be applied
to estimate it based on NO 2 or NH 3 columns and precipitation amounts. The mixed
effect model can be tuned using site observations, satellite-observed NO 2 and NH 3
columns and meteorological data (Liu et al. 2017a).
3.3 Ground-Level Monitoring Networks and Satellite
Monitoring Instruments
3.3.1 Ground-Level Monitoring Networks
Since the early 1980s, N deposition has been measured occasionally by the Chinese
National Environment Bureau across the country. At present, the Chinese Research
Academy of Environmental Sciences and the National Meteorological Bureau
operate two independent precipitation chemistry monitoring networks. In addition,
nine Chinese monitoring sites (Guanyinqiao, Haifu, Jinyunshan, Shizhan, Jiwozi,
Hongwen, Xiaoping, Xiangzhou, Zhuxiandong) entered the Acid Deposition Network in East Asia (EANET) in approximately 2000. China Agricultural University
organizes a Nationwide Nitrogen Deposition Monitoring Network (NNDMN) (Liu
3 Monitoring Atmospheric Nitrogen Deposition in China
49
biological variabilities of plants, their environmental interactions and response
delays, biomonitoring requires standardization to achieve consequential results.
Therefore, when utilizing just plants as N receptors, the possibility of accurately
quantifying total N deposition is limited. Moreover, the application of bioindicators
based on a single species is generally constrained to the geographic distribution of
that species. Through integration of species composition and leaf N stoichiometry of
understory vascular plants, Du (2017) proposed a community N indicator. Experimental results from a study in northeastern China revealed that the community N
indicator could be a useful tool to indicate N deposition, with the potential application across a wide range of terrestrial ecosystems (Du 2017).
3.2.4 Satellite-Based Monitoring
Dry and wet N deposition can be estimated using satellite data (Liu et al. 2017a, b, c;
Zhang et al. 2017). In general, the application of satellite-based monitoring to
estimate dry N deposition can be separated into two steps. First the satellite data
for NO 2 and NH 3 columns are converted to ground N r concentrations using the
vertical profiles from atmospheric chemistry transport models. These are obtained
from the MOZART-4. The MOZART-4 outputs for NO 2 and NH 3 include 56 vertical
levels, which were used to simulate the vertical profiles by a Gaussian function.
Second, dry N deposition is simulated using the satellite-derived ground N r concentration and modelled V d . For wet N deposition, a mixed effect model can be applied
to estimate it based on NO 2 or NH 3 columns and precipitation amounts. The mixed
effect model can be tuned using site observations, satellite-observed NO 2 and NH 3
columns and meteorological data (Liu et al. 2017a).
3.3 Ground-Level Monitoring Networks and Satellite
Monitoring Instruments
3.3.1 Ground-Level Monitoring Networks
Since the early 1980s, N deposition has been measured occasionally by the Chinese
National Environment Bureau across the country. At present, the Chinese Research
Academy of Environmental Sciences and the National Meteorological Bureau
operate two independent precipitation chemistry monitoring networks. In addition,
nine Chinese monitoring sites (Guanyinqiao, Haifu, Jinyunshan, Shizhan, Jiwozi,
Hongwen, Xiaoping, Xiangzhou, Zhuxiandong) entered the Acid Deposition Network in East Asia (EANET) in approximately 2000. China Agricultural University
organizes a Nationwide Nitrogen Deposition Monitoring Network (NNDMN) (Liu
3 Monitoring Atmospheric Nitrogen Deposition in China
49