5.1 Introduction
Nitrogen (N) is one of the critical elements for all living systems including human
being (Fowler et al. 2013; Galloway et al. 2008). Reactive N (Nr) emitted to the
environment cascades among different pools including air, soils, vegetation, and
groundwater with changes on forms and locations through multiple processes
(Galloway et al. 2008). Despite such complex cascade, N cycles follow the principle
of mass balance, i.e. the N input to and output from a system such as air should be
balanced (Gu et al. 2015). Through the budget study, the changes in detailed sources
of Nr emission to the environment and their driving forces can be quantified to help
the understanding on global N biogeochemical cycles (Fowler et al. 2013; Leach
et al. 2012; Galloway et al. 2008). In this context, national N budget is critical for
policy-making on sustainable N management, which currently is only conducted in
few countries (De Vries et al. 2011; EPA 2011), leading to huge knowledge gaps for
the understanding of global N cycles (Fowler et al. 2013).
China uses about one third of global Nr to produce food and energy for its
increasingly wealthy population. However, a large amount of this input Nr is lost
to the environment due to low N use efficiency (NUE) in China (Gu et al. 2015).
Serious air pollution occurred in China because of these Nr emissions (Liu et al.
2013), along with the enormous changes of socioeconomy since 1980 (Hui et al.
2010). Currently, the monitoring of air pollution is mainly in urban areas, and data
from rural areas are lacking in China (Meng et al. 2010). To remedy the deficiency of
data from rural area, remote sensing data are used to reflect the changes in air
pollution across China (Zhang et al. 2007). Nevertheless, the abovementioned
approaches do not track the sources of N pollutants to the air and thus contribute
little to the development of mitigations. To fill the gaps, we finished our first version
of Chinese N budget with research period of 1980 to 2010 (Gu et al. 2015).
However, some calculations in our previous version are with large uncertainty due
to lack of N flux validation. Meanwhile, China is undergoing rapid changes on its
socioeconomy and environment, which might change the N budget post 2010.
Therefore, this chapter aims to update the N budget and atmospheric Nr fluxes on
both spatial and temporal scales in China during the past 35 years (1980–2015).
5.2 Methodology
Based on the coupled human and natural systems (CHANS) modelling, this study
analysed all the Nr sources and their interactions within China, which were quantified on subsystem level (Fig. 5.1). The principle of the CHANS modelling is mass
balance of N input and output for the whole CHANS system and each subsystem. A
detailed description of the CHANS model can be found in Gu et al. (2015). We
updated the datasets and method of the CHANS model to improve the accuracy and
enhance the credibility of N flux analysis. Specifically, we quantified the changes of
88
B. Gu and X. Zhang
Nitrogen (N) is one of the critical elements for all living systems including human
being (Fowler et al. 2013; Galloway et al. 2008). Reactive N (Nr) emitted to the
environment cascades among different pools including air, soils, vegetation, and
groundwater with changes on forms and locations through multiple processes
(Galloway et al. 2008). Despite such complex cascade, N cycles follow the principle
of mass balance, i.e. the N input to and output from a system such as air should be
balanced (Gu et al. 2015). Through the budget study, the changes in detailed sources
of Nr emission to the environment and their driving forces can be quantified to help
the understanding on global N biogeochemical cycles (Fowler et al. 2013; Leach
et al. 2012; Galloway et al. 2008). In this context, national N budget is critical for
policy-making on sustainable N management, which currently is only conducted in
few countries (De Vries et al. 2011; EPA 2011), leading to huge knowledge gaps for
the understanding of global N cycles (Fowler et al. 2013).
China uses about one third of global Nr to produce food and energy for its
increasingly wealthy population. However, a large amount of this input Nr is lost
to the environment due to low N use efficiency (NUE) in China (Gu et al. 2015).
Serious air pollution occurred in China because of these Nr emissions (Liu et al.
2013), along with the enormous changes of socioeconomy since 1980 (Hui et al.
2010). Currently, the monitoring of air pollution is mainly in urban areas, and data
from rural areas are lacking in China (Meng et al. 2010). To remedy the deficiency of
data from rural area, remote sensing data are used to reflect the changes in air
pollution across China (Zhang et al. 2007). Nevertheless, the abovementioned
approaches do not track the sources of N pollutants to the air and thus contribute
little to the development of mitigations. To fill the gaps, we finished our first version
of Chinese N budget with research period of 1980 to 2010 (Gu et al. 2015).
However, some calculations in our previous version are with large uncertainty due
to lack of N flux validation. Meanwhile, China is undergoing rapid changes on its
socioeconomy and environment, which might change the N budget post 2010.
Therefore, this chapter aims to update the N budget and atmospheric Nr fluxes on
both spatial and temporal scales in China during the past 35 years (1980–2015).
5.2 Methodology
Based on the coupled human and natural systems (CHANS) modelling, this study
analysed all the Nr sources and their interactions within China, which were quantified on subsystem level (Fig. 5.1). The principle of the CHANS modelling is mass
balance of N input and output for the whole CHANS system and each subsystem. A
detailed description of the CHANS model can be found in Gu et al. (2015). We
updated the datasets and method of the CHANS model to improve the accuracy and
enhance the credibility of N flux analysis. Specifically, we quantified the changes of
88
B. Gu and X. Zhang