1
Supplementary Information
2
Title: Impacts of reactive nitrogen on climate change in China
3
Authors: Yalan Shi1, Shenghui Cui1*, Xiaotang Ju2, Zucong Cai3 & Yong-Guan Zhu1,4*
4
Affiliation: 1 Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei
5
Road, Xiamen 361021, PR, 2 College of Resources and Environmental Sciences, China
6
Agricultural University, Beijing 100193, PR, 3 College of Geography Science, Nanjing
7
Normal University, Nanjing, 210023, PR, 4 Research Center for Eco-Environmental
8
Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Beijing 10085, PR, *
9
Correspondence and requests for materials should be addressed to S.H.C. (shcui@iue.ac.cn)
10
and Y.G.Z (ygzhu@iue.ac.cn).
11
Outline：
12
_Toc402920742Climate Generators Related to Nr .................................................................. S2
13
Common Metric for Climate Change ...................................................................................... S5
14
Emission Inventory of Anthropogenic Nr emissions ............................................................... S9
15
Literature analysis of N Deposition ....................................................................................... S12
16
N-induced CO2 and CH4 Flux Factors of Terrestrial Ecosystems ......................................... S16
17
Impacts of Nr Enrichment on GHG Fluxes ........................................................................... S22
18
Climate Impact of Nr with Uncertainty Analysis .................................................................. S26
19
Projection of the Impact of Nr on Climate Change ............................................................... S29
20
Supplementary Information References ................................................................................ S32
21
Figure: Figure S1
S1
22
Table: Table S1-S8
23
Climate Generators Related to Nr
24
Nitrogen (N) must be transformed from its molecular form (N2) into other forms for
25
using by living organisms. These other forms, collectively known as reactive nitrogen (Nr),
26
include all active N compounds [in general, including organic N, ammonium (NH4-N in
27
water and NH3 in air), NOx, N2O, and nitrite & nitrate] in the biosphere, pedosphere,
28
hydrosphere, and atmosphere. Nr is highly active in the environment1 and contributes to
29
several environmental and climatic effects as it cascades through these media2,3.
30
A characteristic feature of climate change is the long atmospheric residence time of
31
non-reactive greenhouse gas (GHG). However, historically, anthropogenic changes to the N
32
cycle and effects on the Nr flows are characterized mainly as short-lived, except for N2O.
33
Short-lived atmospheric substances such as NOx and NH3 are formed in numerous
34
processes2. Therefore, short-lived species are also believed to contribute significantly to the
35
earth’s radiative balance in the short term and to human-induced climate change4. Nr affects
36
the climate system by changing either the atmospheric constituents or the terrestrial N
37
dynamics5. These direct and indirect climate generators are summarized in Figure S1 and
38
explained in the following discussion, designated as E1-E6. Among them, E1-E3 are
39
categorized as direct links, while E4-E6 are categorized as indirect links.
40
E1: N2O is a strong GHG. One unit N2O molecule can yield about 300 times greater
41
global temperature increase compared with one unit CO2 molecule. N2O concentration in
42
the atmosphere is mainly and directly determined by the microbial conversion processes of
S2
43
44
nitrification and denitrification.
E2: NOx, on the one hand, is the precursor of ozone and can stimulate the production
45
of ozone, which is the third most powerful GHG, contributing to warming effects; on the
46
other hand, the atmospheric hydroxyl (OH) radical concentration as a result of NOx
47
emissions can reduce the lifetime of methane (CH4) and remove CH4 in the atmosphere,
48
contributing to a cooling effect. Furthermore, the ozone concentration in the upper
49
troposphere can be enhanced by CH4, which has a longer lifetime6. Ozone is short-lived
50
while CH4 is long-lived. The combined response of ozone and CH4, known as the
51
ozone-CH4 effect, takes the ozone, CH4 and CH4-induced ozone perturbations into account.
52
E3: NOx and NH3 can lead to the formation of oxidants, like the OH radical. These
53
oxidants enhance the sulfate or nitrate light-scattering aerosols, which have a cooling effect
54
through scattering incoming solar radiation. They also exercise a number of indirect cooling
55
effects by modifying the properties of clouds7. Considering that the indirect radiative
56
forcing (i.e., RF, represents the influence degree to the energy balance between
57
atmosphere-terrestrial system) effect of aerosol is quiet small8 and far more uncertain than
58
the direct RF9, only the direct effects of aerosols are considered here.
59
E4: N availability can influence C sequestration capacity in terrestrial ecosystems.
60
The enrichment of Nr affects the CO2 exchange between atmosphere and land, either
61
positively (CO2 uptake occurs by increasing productivity or reducing the decomposition rate)
62
or negatively (CO2 emission occurs by increasing mortality rate in excess N situations).
63
E5: N availability can influence CH4 production and consumption in terrestrial
S3
64
ecosystems through many microbial processes. On the one hand, the addition of N in the
65
form of nitrogenous salts and nitrite reduces and inhibits CH4 oxidation by increasing
66
osmotic pressure, which suppresses CH4 uptake. On the other hand, the activities of both
67
methanogenic archaea and methanotropic bacteria cause increases or decreases in CH4
68
emissions.
69
70
E6: Ozone formed in the troposphere as a result of NOx emissions can damage plant
productivity and further decrease CO2 uptake by the vegetation.
71
72
Figure S1. Effect dynamics of climate generators related to Nr. The framework is
73
adopted and modified from the study of Pinder et al.10. (+) represents a warming effect on
74
the climate, (-) represents a cooling effect on the climate.
75
S4
76
77
Common Metric for Climate Change
Different climate generators have different RF intensities and lifetimes. A key
78
challenge to quantifying the effects of climate generators is the development of a common
79
metric, which should take both RF intensities and lifetimes into account and make different
80
climate generators comparable on a common scale. Many metrics have been used to
81
characterize the climate effects11. Particular emphasis has been placed on global warming
82
potential (GWP) and global temperature potential (GTP). GWP is the time-integrated RF
83
due to a pulse or continuous emission of a unit mass of gas over a given time period
84
compared to the reference gas CO212. GTP is the end-point RF and shows the temperature
85
change at a particular time in the future13. The GWP was a key product of the
86
Intergovernmental Panel on Climate Change (IPCC)4 and has been used in the Kyoto
87
Protocol. However, the advantages and problems of the GWP have been vigorously
88
debated14,15. GWP is particularly useful in quantifying the climate impact of current
89
emissions of long-lived GHGs but is less suited to quantifying the impact of short-lived
90
agents. In addition, assessment using the GWP metric is hard to integrate with specific aims
91
in terms of climate change: for example, constraining the global mean RF or warming to
92
stay below given values at a particular time in the future13. Soon after, Shine et al.13
93
proposed GTP as a possible alternative to the GWP, which can explicitly represent the
94
impact of a change in emissions on temperature and is well targeted for policy making.
95
96
In this study, the GTP is used as the common metric to assess and inter-compare the
climate impacts of Nr compounds. The quantified results of GTP for climate forces E1-E6
S5
97
at different timescales (20-y and 100-y) were adopted from the extant studies and listed in
98
Table S1. Here, we interpreted and discussed only the E2 and E3 in detail.
99
NOx, is the most important precursor of tropospheric ozone, leads to the formation of
100
oxidants16 and has acted to double the global mean tropospheric ozone concentration 17.
101
It also hastens the destruction of CH4 by increasing OH concentrations18. The ozone RF has
102
two components with opposing signs. One is short-lived and driven by the direct effects of
103
NOx on ozone chemistry; the other is long-lived, controlled by the slower change in CH4
104
adjustment time19. The general characteristic is that the short-lived ozone forcing is always
105
positive, while the CH4 forcing and CH4-induced ozone forcing are always negative20. As a
106
result, NOx emissions exert a negative forcing from decreased CH4 that dominates over the
107
smaller positive forcing from increased ozone, implying a net cooling. The climate forcer
108
E2 has taken these components (i.e., short-lived ozone and CH4 and CH4-induced ozone
109
perturbations) into account, namely the ozone-CH4 effect. The responses of ozone and CH4
110
RF compensation effect to NOx emissions have varied greatly among sources and
111
regions21-23. Firstly, we considered the different effects between surface, shipping, and
112
aircraft sources24. In addition, we adopted the values of GTP for NOx from surface source
113
for East Asia from Collins et al.25 for time horizons of 20 and 100 years, respectively; while
114
the values of GTP for NOx from shipping and aircraft sources are from Fuglestvedt et al.
115
24
116
This effect works through interactions with NOx to alter the availability of oxidants,
117
influencing the sulfate and organic aerosols formation rates, or through sulfate-nitrate
.Both NOx and NH3 can enhance the formation of aerosols, forming the climate forcer E3.
S6
118
competition for NH324,26. Aerosols are known to have direct cooling effects through
119
scattering of the incoming solar radiation and to exercise a number of indirect cooling
120
effects by modifying the properties of clouds; (i) the cloud albedo effect: brightens the
121
clouds by increasing cloud condensation nuclei, and (ii) the cloud lifetime effect: enhances
122
cloud cover by reducing precipitation efficiency7. These aerosol indirect effects (AIE) have
123
been poorly quantified. Estimating the AIE from cloud albedo and lifetime effects is far
124
more tentative than the direct RF owing to the uncertainties from aerosol mass
125
concentration to cloud properties9. By contrast, the more recent study of Shindell et al.27
126
provided an improved approach allocating the direct RF to emissions, namely the
127
“emission-based” assessment. The emission-based forcing via NOx and NH3 effect on
128
aerosols (excluding AIE) are -0.18 and -0.09 W/m2, respectively, with the uncertainty 0.09
129
and 0.10 W/m2. We adopted the values of GTP20 and GTP100 based on the global direct
130
aerosol RF of Shindell et al.27, without considering the AIE on clouds.
131
Table S1. GTP of N-related Climate Generators
Species
N2O (E1)
NOx (E2: surface)a
NOx (E2: shipping)a
NOx (E2: aircraft)a
NOx (E3)b
NH3 (E3)b
CH4 (E4, E5)
CO2 (E4, E5, E6)
GTP20
+290 to +320
-79 to -32
-190 to -130
-590 to -200
-31 to -7.0
-9.5 to -2.2
+37 to +77
+1
GTP100
+260 to +290
-3.4 to -0.8
-6.1 to -4.2
-9.5 to +7.6
-0.0024 to 0
-0.022 to 0
+2.9 to +4.9
+1
Reference
7,13
25
24
24
10,27
10,27
28
132
a
includes impacts to short-lived ozone, CH4 and CH4-induced ozone; b includes impacts to
133
nitrate and sulfate aerosols direct RF, but not to clouds; c CO2 is defined as the reference gas
S7
134
with the value 1.
S8
135
Emission Inventory of Anthropogenic Nr emissions
136
The results of anthropogenic Nr emissions from many published materials show a
137
certain inconsistency due to the different approaches used. We compiled Nr emission data
138
from the existing regional and global emission inventories associated with China. These
139
inventory datasets are openly accessible, in most cases directly online, including the IIASA
140
GAINS (2000-2030), EDGAR v4.2 (1970–2008), RCPs (2005–2100), and MACCity
141
(1960–2020). The classifications of the sectors differ among inventory models. For example,
142
IIASA GAINS: N2O (combustion, transportation, industry, product use, soil, manure, waste);
143
NOx (power and heating plants, other energy-sector combustion, industrial combustion,
144
industrial processes, domestic, road transportation, non-road mobility, waste management);
145
NH3 (dairy cattle, other cattle, hogs, poultry, other livestock, N-fertilizer application,
146
stationary combustion, transportation, waste). EDGAR v4.2: energy (fuel combustion and
147
fugitive emissions from fuel, industrial processes, and product use); agricultural (manure
148
management, agricultural soils, agricultural waste burning); waste, biomass burning.
149
MACCity and RCPs: aviation, transportation, energy, solvents, waste, industrial, residential,
150
agricultural waste, agriculture, ships, biomass burning.
151
The sources of gaseous Nr can be incorporated into two major categories:
152
agriculture (including agricultural soils, animal manure, and biomass burning) and industry
153
(fossil fuel combustion, industry production, and waste management). Table S2
154
demonstrates the emission sources (including agricultural and industrial sources) and
155
chemical species (NOx, NH3, N2O) from different inventory models. We defined the
S9
156
uncertainty using the variation range of all these inventories and took the median value for
157
the years 2000 and 2005. As shown in Table S3, the estimated results in this study are
158
comparable and generally consistent with the published results from local studies, although
159
they cover different periods and employ different calculation methods. Hence, we finally
160
improve the estimated Nr emission data from online global or regional emission inventories
161
(e.g., http://gains.iiasa.ac.at/gains; http://edgar.jrc.ec.europa.eu;
162
http://ether.ipsl.jussieu.fr/eccad) in a universal time and more complete sources.
163
Table S2. Overview and Summary of Emission Inventories of Nr for China
Sector
N2O
Fossil fuel combustion
Product use
Agricultural soils
Animal manure
Waste treatment
Biomass burning
NOx
Fossil fuel combustion
Biomass burning
Industrial processes
Waste management
Agricultural soils
NH3
Fossil fuel combustion
Fertilizer application
Fertilizer production
Animal manure
Biomass burning
IIASA
GAINS
EDGAR v4.2
●
●
●
●
●
RCPs
●
●
●
●
●
●
●
●
●
●
●
●
MACCity
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
164
165
Table S3. Nr Emissions based on Review of Online Inventories and Published Studies, in
S10
166
Tg N.
167
(a) N2O (×10)
This study
Base year
Agricultural soils
Manure
management
Industry
production
Fuel burning
2000
6.59
1.62
2005
7.29
1.75
Chen and
Zhang29
2000-2007
4.0
2.14
0.64
0.70
0.67
0.83
168
Li, et al.30
SDRC31
2006
-
2005
4.28
1.61
0.75
0.55
0.67
0.68
-
0.85
(b) NOx
Base year
Agricultural soils
Fossil fuel
burning
Biomass burning
This study
2000
2005
0.17
0.17
Wang, et al.32
1997-1999
0.85
Ohara, et al.33
2000
-
Sun, et al.34
2000
-
3.45
5.06
3.72
3.4
3.38
0.03
0.02
0.08
-
-
Huang, et al.35
2006
3.2
Streets, et al.36
2000
5.5
Wang, et al.37
2005
4.2
169
(c) NH3
Base year
Agricultural soils
Manure
management
Biomass burning
Others
This study
2000
2005
3.27
3.75
4.95
5.2
5.3
4.1
5.8
1.0
1.06
0.16
1.1
0.65
0.89
1.07
170
S11
171
172
Literature analysis of N Deposition
We reviewed and collected the monitoring data of N deposition rates of different
173
sites around China, mainly covering different ecosystems and the period 2000–2005 from
174
the extant studies (Table S4). Through the application of ARCGIS 10, an explicit spatial
175
map (Figure 3a) of N deposition rates around China was developed using the spatial
176
interpolation technique (kriging). The interpolation results showed that the average N
177
deposition rate was 15.7 kg N/ha/yr across China, and the N deposition summed to 15.1 Tg
178
N/yr, which was consistent with the total estimated emissions of NOx and NH3 in 2005 in
179
our study (15.4 Tg N/yr). In addition, our result was comparable to the estimation of Liu et
180
al.38 (15 Tg N/yr in the 2000s). For an individual ecosystem, N deposition contributed 3.56,
181
5.28, 5.68, and 0.57 Tg N into cropland, forest, grassland, and wetland, respectively (Figure
182
3b-e), roughly consistent with the view of Liu et al. that about one fourth of N was
183
deposited into agro-ecosystems, and the remaining three fourths were deposited into forest,
184
grassland, and aquatic ecosystems39.
S12
Table S4. N Deposition over Terrestrial Ecosystems of China
X
Y
118°2′
116°17′
116°25′
116°08′
116°41′
106°41′
117°43′
117°-118
117°36′
30°33′
40°03′
39°50′
39°41′
40°03′
29°37′
26°31′
23.8°-25°
24°32′
N deposition
rate (kg
N/ha/yr)
23.4
38
38
25.1
16
42
53
53
14.9
Grassland Gansu
102°10′
34°01′
2
-
DHS
Forest
Guangdong
112°33′
23°10′
38.4
Wet
LXH
ZSHM
LCG
LGS
QZ
BD
WQ
SJ
ZJC
CJT
Forest
Guangdong
Guangdong
Guizhou
Guizhou
Hebei
Hebei
Hebei
Heilongjiang
Hubei
Hunan
113°35′
113°34′
106°43′
108°11′
115°01′
115°27′
116°36′
131°31′
110°58′
112°26′
23°33′
22°33′
26°38′
26°27′
36°52′
38°52′
37°36′
47°35′
30°49′
27°55′
9.3
35.8
8.1
9.5
22.5
28
23
7.57
10.3
21.6
Wet
Bulk
Wet
Wet
Bulk
Bulk
Bulk
Wet
Wet
Wet
ID
Site
Symbol
Type
Province
1
2
3
4
5
6
7
8
9
Fengxingzhuang
Dongbeiwang
Campus Experimental Farm
Fangshan
Shunyi
Tieshanping Forest Park
Shaxian
Zhangzhou
Jiulongjiang River
Maqu Grassland Research
Station
Dinghushan Biosphere
Reserve
Liuxihe
Zhongshanhengmen
Liuchongguan
Leigongshan
Quzhou
Baoding
Wuqiao
Sanjiang Plain
Zhangjiachong, zigui
Caijiatang
FXZ
DBW
CEF
FS
SY
TSP
SX
ZZ
JLJ
Forest
Cropland
Cropland
Cropland
Cropland
Forest
Forest
Forest
Cropland
Anhui
Beijing
Beijing
Beijing
Beijing
Chongqing
Fujian
Fujian
Fujian
MQ
10
11
12
13
14
15
16
17
18
19
20
21
Forest
Forest
Cropland
Cropland
Cropland
Cropland
Forest
S13
Deposition
type
Bulk
Bulk
Bulk
Bulk
Bulk
Bulk
Wet
Wet
Bulk
Reference
40
41
41
41
41
42
43
44
45
46,47
48 49
50
51
50
50
41
52
52
53
54
50
112°91′
27°87′
26.2
Wet
116°40′
43°32′
4
-
111°54′
41°47′
4
-
116°26′
42°05′
17
Bulk
YZ
TH
JR
YT
XJ
DGS
PYL
Hunan
Inner
Grassland
Mengonia
Inner
Grassland
Mengonia
Inner
Cropland
Mengonia
Cropland Jiangsu
Jiangsu
Cropland Jiangsu
Grassland Jiangxi
Cropland Jiangxi
Forest
Jiangxi
Cropland Jiangxi
119°13′
120°12′
120°27′
116°55′
117°00′
114°30′
116°00′
32°01′
31°15′
32°00′
28°12′
28°2′
27°30′
28°30′
30
89.7
33
26.3
62.6
33.3
74.1
Bulk
Bulk
Wet
Bulk
Bulk
Wet
Bulk
CBS
Forest
Jilin
127°42′
41°41′
12
Bulk
FS
DA
Forest
Cropland
Jilin
Liaoning
127°29′
121°43′
42°20′
38°52′
7
28
Bulk
Bulk
YWS
Grassland Ningxia
106°17′
36°00′
3
-
HB
QHL
HM
QD
SH
YL
LC
LFG
Grassland
Grassland
Cropland
Cropland
Wetland
Cropland
Cropland
Forest
101°19′
100°27′
117°32′
120°22′
121°28′
109°44′
109°25′
103°47′
37°37′
37°07′
37°29′
36°04′
31°13′
38°17′
35°45′
28°29′
2
2
38
22
78.4
22.7
17
18
Bulk
Bulk
Wet
Bulk
Bulk
-
22
Shaoshan
SS
23
Xilin River Basin
XRB
24
Siziwangqi
SZWQ
25
Duoluo
DL
26
27
28
29
30
31
32
Yangtze River
Taihu Basin
JuRong Basin
Yingtan Experimental Station
Xinjiang River
Dagangshan
Poyang Lake
Changbaishan Forest Research
Station
Fusong
Dalian
Yunwushan Grassland Natrual
Reserve
Haibei Research Station
Qinghai Lake
Huimin
Qingdao
Shanghai
Yulin
luochuan
Liangfenggao Forest Park
33
34
35
36
37
38
39
40
41
42
43
44
Forest
Qinghai
Qinghai
Shandong
Shandong
Shanghai
Shanxi
Shanxi
Sichuan
S14
55
56
57
52
58
59
60
61
62
63
64
65
65
52
66
46,47
67
41
68
69
70
70,71
72
45
46
47
48
49
50
51
Gonggashan
Linzhi
Changdu
Urumchi
Dongchuan Mudflow
Monitoring Station
Fenghua
Changlejiang Basin
101°52′
94°30′
97°21′
87°37′
29°35′
30°12′
30°10′
43°49′
33
7
4.5
5
Bulk
Wet
Wet
Bulk
52
52,73
73
52
Grassland Yunnan
103°10′
25°00′
4
-
74
Cropland
120°33′
120°37′
29°56′
29°31′
50
81.8
Bulk
Bulk
52
75
GGS
LZ
CD
UR
Forest
Forest
Grassland
Grassland
DC
FH
CLJ
Sichuan
Tibet
Tibet
Xingjiang
Zhejiang
Zhejiang
S15
159
N-induced CO2 and CH4 Flux Factors of Terrestrial Ecosystems
160
The addition of N into terrestrial ecosystems can alter the physiology of soil
161
microbes and vegetation and concomitantly alter the balance of biogenic fluxes of the three
162
main GHGs (CO2, CH4, and N2O), including creating both positive and negative effects on
163
the biogenic production and consumption of these GHGs76-78. Previous studies have
164
indicated that although N addition greatly stimulated terrestrial CO2 assimilation in both
165
natural vegetation and agricultural land, CH4 and N2O emissions caused by N simulation
166
largely offset N-induced CO2 uptake in terms of climate change79,80. These opposing
167
impacts of N enrichment are quite different depending on the land cover type79,81. The net C
168
exchange (NCE), defined to include the net fluxes of CO2 and CH4 between ecosystems and
169
the atmosphere, is calculated as:
170
NCE  FCO2  FCH 4
(1)
171
where FCO2 is the net C fluxes related to CO2, and FCH 4 is the net C fluxes related
172
to CH4. Local flux factors are preferred to get a precise estimation. In the following section,
173
we discuss and calculate FCO2 for China in detail (Table S5). Because of the lack of
174
available data, FCH 4 was directly adopted from the study of Liu and Greaver79, which
175
reviewed 109 studies and evaluated the effect of N addition on the flux of major GHGs.
176
Three main methods were used to estimate the terrestrial C balance in China and the
177
driving mechanisms during the past twenty years: biomass and soil C inventories
178
extrapolated by satellite greenness measurements, ecosystem models, and atmospheric
179
inversions. Based on the terrestrial ecosystem model, Tian et al. estimated that the NCE of
S16
180
land ecosystems in China was 215±78 and 260±110 Tg C/yr during 1981–2000 and
181
1996–2005, respectively, under the effect of multiple environmental factors 82. In the
182
simulations, N deposition and fertilizer application together accounted for about 60% (N
183
deposition: 40-45%, N fertilization: 15-20%) of the NCE. The simulated results of NCE
184
were comparable to the inventory estimates of 180±73 Tg C/yr and atmospheric inversion
185
of 350±330 Tg C/yr for the same period, respectively83. Lu et al. further indicated that
186
increased N deposition resulted in an NCE of 122±99 Tg C/yr and N deposition combined
187
with its interactive effects driven by changes in other environmental factors contributed to
188
45% of NCE84. We divided the N-induced C sink by the NCE driven by
189
multi-environmental factors to obtain the contribution rates of N enrichment to C
190
sequestration of different terrestrial ecosystems, which were 71%, 75%, 16%, and 77% for
191
forest, grassland, shrubland, and cropland biome, respectively. The flux factors of CO2 and
192
CH4 for any particular ecosystem were calculated by dividing FCO2 and FCH 4 by the
193
corresponding N addition mass into the system.
194
Cropland. The exchange of C in cropland refers to the stocks in soil and biomass.
195
However, C incorporated into plants is harvested at least once per year and released back as
196
CO2 into the atmosphere through the food web within the year85. This implies that the
197
increasing crop biomass does not contribute to a net long-term C sink. Hence, the NCE of
198
cropland only accounted for the change of soil C stocks excluding the biomass stocks.
199
Cropland in China functioned as a C sink with an average soil C sequestration rate (SCSR)
200
of 30.5 Tg C/yr, including the CO2 uptake and CH4 emission fluxes of 37.3 and 6.8 Tg C/yr
S17
201
during 2001-2005. The SCSR due to anthropogenic N input averaged 32 Tg C/yr during
202
2000-200886. Lu et al. repressed the linear relationship between the SCSR and the amount
203
of N fertilizer; as a result, the value of SCSR was around 22.3 Tg C/yr during 2001-200587.
204
Combined with these previous results, we can summarize the N fertilization-induced soil C
205
sink of 22-32 Tg C/yr in cropland. Lu et al. estimated the SCSR due to N deposition to be
206
around 3-13 Tg C/yr during 2001-200584. Therefore, the total N-induced SCSR in cropland
207
varied from 25-45 Tg C/yr, which was in the scope of 53±31 Tg C/yr estimated by Tian et
208
al., whose study considered the effects of multiple factors during 1996–200582, with the
209
contribution rates of 17% and 60% from N deposition and N fertilization, respectively88.
210
Therefore, the N-induced flux factor of CO2 for Chinese cropland is 1.08±0.63 kg C/kg N.
211
Forest. In our study, shrubland is included in the forest category. N deposition to
212
forest soils shows variable effects on the soil GHG fluxes from forest, depending on forest
213
type, N status of the soil, and the rate and type of atmospheric N deposition. For example,
214
the combination of high C, N ratios, and long lifetimes in wood may create a significant C
215
sink in forests. However, much of the N falls on cultivated areas and grasslands, where there
216
is limited capacity for long-term C storage89,90. In high N deposition areas, N addition may
217
lead to adverse growth effects due to impacts of N-induced eutrophication and acidification
218
on forest health91. Forests in China acted as a C sink, with an average NCE of 119±39 Tg
219
C/yr during 1996–200582 and a contribution rate of 71% from N deposition. Lu et al. further
220
estimated N-induced NCE at 84±59 Tg C/yr during 2001–200584. Our estimated fluxes
221
factor for forest biomes of 16±11 kg C/kg N was roughly consistent with previous results.
S18
222
For example, the fluxes factor of CO2 for forests was reviewed within the range of 15–44 kg
223
C/kg N79. Tian et al. found that the average N-induced C sequestration in China’s forest
224
ecosystems varied from 0 to 59 kg C/kg N simulated by TEM, and from 0 to 21 kg C/kg N
225
simulated by DLEM for the 1990s82.
226
Grassland and wetland. Compared to forest land, N-induced C sequestration in
227
grassland was less significant and responsive, partly because most grassland ecosystems are
228
distributed in high-latitude areas or in arid to semiarid regions, where plant growth is
229
limited more by low temperature and low soil moisture than by N availability. The C:N
230
ratios of non-woody tissue in grassland are far less than those of woody tissue in forest and
231
shrubland. In addition, the turnover rate in grassland is relatively high, resulting in more C
232
transfer into the soil84. The average NCE of grassland in China varied from 16 to 50 Tg C/yr
233
based on ecosystem modelling during 1996–200582, with the contribution rate of 75% from
234
N deposition. The estimation by Lu et al. of N-induced NCE was 25±23 Tg C/yr during
235
2001–200584. Grassland systems were estimated to function as a C sink due to CO2 uptake,
236
with an average flux factor of 4.4±2.3 kg C/kg N.
237
Wetland and paddy land were the largest contributors to CH4 emissions, because
238
they have a high capacity for CH4 production under the conditions of wet climate and
239
higher biological activity. The flux factors of CH4 for wetland and cropland based on the
240
terrestrial ecosystem model reported by Tian et al. were 2.54±0.89 and 0.16±0.02 Tg C/Tg
241
N92. Local flux factors are preferred to get a precise estimation. Nonetheless, because Nr
242
enrichment has both positive and negative effects on CH4 emission, it is difficult to
S19
243
distinguish the effect of Nr enrichment from other factors. To solve this problem, the review
244
data from Liu and Greaver79 were directly adopted as alternative data for the CH4 flux
245
factor.
S20
Table S5. N-induced GHG Flux Factors of Different Terrestrial Ecosystems
Item
Driving factor
Net C exchange
(NCE) (Tg C/yr)
Multiple factors
N deposition
N fertilization
Contribution rate
N enrichment (Tg)
FCO2 (Tg C/yr)
CO2 Flux factor a (kg
C/kg N)
CH4 Flux factor a (kg
C/kg N)
a
N addition
GHG fluxes from Chinese terrestrial ecosystems
Cropland
Forest
Grassland Shrubland
Process-based ecosystem modeling
44±22
98±28
27±12
46±16
53±31
119±39
33±17
55±23
Inventory–satellite-based estimation
26±11
75±34
13±4
58±14
Atmospheric inversion
Process-based ecosystem modeling
8±5
84±59
25±23
8±5
84±59
25±23
27±5
77%
71%
75%
38
5.28
5.68
-
Wetland
1981-2000
1996-2005
82
82
-
180±73
1981-2000
83,93-95
350±330 1996-2005
0.57
85±28
25±13
9±3.7
-1.08±0.63
-16±11
-4.4±4
-
-
0.02±0.01
0.016±0.004
-
-
0.008±0.004
S21
Total
215±78
260±110
41±24
-represents uptake, + represents emission
Reference
-
9±7
9±7
16%
-
Period
83
122±99
122±99
27±5
57%
1981-1990
2001-2005
2001-2005
84
84
86-88
206±88
1996-2005
All
combined
79
240
Impacts of Nr Enrichment on GHG Fluxes
241
The creation of anthropogenic Nr through agriculture and industrial activities
242
resulted in substantial N addition into the terrestrial ecosystems in the form of both N
243
fertilization and N deposition. Ecosystem N availability plays an important role in
244
controlling the productivity, structure, and dynamics of terrestrial ecosystems. It has not
245
only strong effects on responses of the terrestrial net C balance96 but also a suite of
246
detrimental effects on ecosystem services associated with environmental quality97. By
247
nature, N-induced climate change is governed by the interactions between terrestrial C and
248
N98. Results of Liu and Greaver79 indicated that N addition increased C content of forest
249
ecosystems by 6% and marginally increased soil organic C of agricultural systems by 2%,
250
but had no significant effect on soil C for non-forest natural ecosystems. Reay et al.
251
projected that the land and ocean sinks may sequester an additional 10% of anthropogenic C
252
emissions by 2030 owing to increased N inputs, but a more conservative estimate of 1 to
253
2% is more likely99. Based on the above flux factors of CO2 and CH4 for China, N-induced
254
GHGs emission/uptake and the resulting climate impact were estimated for different
255
ecosystem types in Table S6.
256
As the response to N deposition, forests in China became the single largest C sink
257
(31.9 to 136 Tg C), followed by grassland (4.5 to 45 Tg C) and cropland (1.8 to 5.6 Tg C).
258
Throughout China, the terrestrial system displayed a net C sink of 27 to 176 Tg, although
259
the C sequestration capacity varied among regions. However, only a small area in western
260
China was the N-induced C source (Figure 3f). In general, N-induced NCE is considered a
S22
261
cooling agency in the long term. However, the increasing forest and crop biomasses do not
262
always contribute to a net long-term C uptake. For forest biomass, not all the C
263
sequestration is stored and retained on a long timescale due to annual harvest removal or
264
mortality. We adopted and assumed a C retention rate between 40-60% on a 20-y basis and
265
between 20-40% on a 100-y basis10 as suitable for forest in China. As a result, N-induced
266
NCE in forest ecosystems contributed a cooling effect of -37±19 and -25±11 Tg CO2e on a
267
20-y and a 100-y basis, respectively. For crop biomass, C incorporated into plants will also
268
be harvested and then released back into atmosphere85. We only considered the soil C
269
storage change in crop fields in order to avoid overestimating the C uptake. As a result,
270
N-deposition induced NCE in cropland ecosystem contributed a warming effect of 0.3±3.7
271
Tg CO2e and a cooling effect -3.5±2.3 Tg CO2e on a 20-y and a 100-y basis. The grassland
272
and wetland ecosystems in China were the net cooling and warming agencies by the
273
responses of CO2 uptake and CH4 emissions to N deposition, respectively (Table S6).
274
Overall, N deposition has a cooling effect of 61.6±38.5 and 53.2±30.2 Tg CO2e on a 20-y
275
and a 100-y basis, respectively.
276
For fertilized cropland, we needed to consider the effect of N fertilization in addition
277
to N deposition. N fertilizer application to the cropland can be divided into chemical
278
fertilizer and organic fertilizer (i.e., manure and crop residue returned to fields). These
279
fertilizers can alter CO2 and CH4 fluxes just as N deposition can. Drawing on the extant
280
results of Cui et al.100, the total amount of N fertilizer applied to the cropland was 35.7 Tg
281
in 2005. N inputs from chemical fertilizer amounted to 26.3 Tg; while N inputs from the
S23
282
manure and crop residue returned to fields were estimated at 7.36 and 1.97 Tg N,
283
respectively. A net CO2 uptake of 14 to 58 Tg C and CH4 emission of 0.40 to 1.06 Tg C for
284
cropland was generated at the national scale, resulting in a warming effect with 12±47 Tg
285
CO2e and a cooling effect with -33±22 Tg CO2e on a 20-y and a 100-y basis. Together with
286
the impact of N deposition on NCE, cropland contributed 12±50 and -37±24 Tg CO2e to
287
climate change on a 20-y and a 100-y basis, respectively. N fertilization played a more
288
significant role than N deposition in C sequestration because of the nationwide application
289
of chemical fertilizer and intensive agricultural production in China.
290
S24
291
Table S6. Impacts of N Deposition and N Fertilization on GHGs fluxes and the Climate
292
System
N deposition
Forest
Grassland
Wetland
Cropland
Total
CO2 (Tg C)
-136 to -32
-45 to -4.5
0
-6.0 to -1.6
-176 to -27
GTP20 (Tg CO2e)
-42±18
-25±20
0
-3.8±2.2
-71±36
GTP100 (Tg CO2e)
-25±11
-25±20
0
-3.8±2.2
-54±30
Forest
Grassland
Wetland
Cropland
Total
CH4 (10-3Tg C)
66 to 103
0
2.5 to 6.5
39 to 103
113 to 208
GTP20 (Tg CO2e)
4.8±1.2
0
0.26±0.10
4.1±1.5
9.1±2.5
GTP100 (Tg CO2e)
0.33±0.07
0
0.02±0.01
0.28±0.09
0.63±0.17
Forest
Grassland
Wetland
Cropland
Total
NCE (Tg C)
-136 to -31.9
-45 to -4.5
0.0025 to 0.0065
-5.6 to -1.8
-176 to -27
GTP20 (Tg CO2e)
-37.2±19.2
-25±20
0.26±0.10
0.3±3.7
-61.6±38.5
GTP100 (Tg CO2e)
-24.7±11
-25±20
0.02±0.01
-3.5±2.3
-53.2±30.2
CO2 (Tg C)
-58 to -14
CH4 (Tg C)
0.40 to 1.06
NCE (Tg C)
-57 to -13.6
GTP20 (Tg CO2e)
-36±22
GTP20 (Tg CO2e)
48±30
GTP20 (Tg CO2e)
12±47
GTP100 (Tg CO2e)
-36±22
GTP100 (Tg CO2e)
3.2±1.9
GTP100 (Tg CO2e)
-33±21
N fertilization
Cropland
293
S25
294
295
Climate Impact of Nr with Uncertainty Analysis
As discussion above, compared to the GWP, the GTP produces equivalent climate
296
responses at a given time, which is suited to evaluating not only near-term climate
297
fluctuations caused by emissions of short-lived species such as NOx or NH3, but also the
298
long-term climate effects caused by emissions of long-lived species like N2O. The GTP
299
retains transparency and relative ease of use, which are attractive features of the GWP;
300
moreover, the GTP includes a dependence on the target of climate policy. Therefore, the
301
metric GTP is more suitable for assessing the significance of Nr on climate systems.
302
During our calculation, two main limitations gave rise to some uncertainty. First,
303
there is considerable variation in gaseous Nr emissions due to the different calculation
304
models, data sources, and parameter settings; in addition, the application of the metric GTP
305
increases the uncertainty that comes from relying on the properties of the emitted compound
306
and of the climate system. Therefore, we used the Monte Carlo Sampling (MCS) and Latin
307
Hypercube Sampling (LHS) method to simulate and propagate the uncertainties through the
308
calculation, respectively.
309
The principle behind MCS and LHS is that the behavior of a statistic in random
310
samples can be assessed by the empirical process of actually drawing lots of random
311
samples and observing the outcomes. The uncertainties of parameters, activity data, and
312
formulas are propagated through the sequence of calculations. In the MCS approach, we
313
assumed that each value in the uncertainty range had equal likelihood and that there was no
314
correlation among the variables. A population of 10,000 estimates was built and ranked in
S26
315
order. The median and 90% confidence intervals were reported. The LHS approach was
316
further used to calculate the uncertainties in our research. All variables were divided into
317
300 equal intervals. An ensemble of 300 sets of all parameters was selected randomly and
318
ranked in order. The mean and standard deviation (SD) were reported. The results of
319
uncertainty analysis using MCS and LHS were similar (Table S7). Hence, we discuss only
320
the result using LHS in the main text.
321
S27
322
Table S7. Climate Impact of Nr with Uncertainty Analysis in terms of GTP (Tg CO2e)
323
(a) Monte Carlo Sampling (MCS)
E1
E2
Species
Climate generator
GTP20
Range
GTP100
Range
N2O
NOx
N2O effect
Ozone-CH4 effect
(Surface)
(Shipping)
(Aircraft)
Aerosol effect
345
316 to 374
311
283 to 340
-298
-36
-9.8
-152 to -450
-53 to -23
-15 to -5.3
-12
-1.2
-0.02
-19 to -4.6
-1.8 to -0.75
-0.22 to 0.14
-97
-57
-71
8.8
-36
48
111
-164 to 41
-98 to -25
-111 to -46
5.3 to 14
-60 to -16
14 to 82
11 to 211
-0.01
-0.11
-54
0.61
-36
3.2
111
-0.01 to 0
-0.22 to -0.01
-86 to -17
0.39 to 0.9
-60 to -16
1.1 to 5.3
11 to 211
E3
E4
NOx
NH3
N deposition
E5
N fertilization
E6
NOx
324
CO2 effect
CH4 effect
CO2 effect
CH4 effect
Ozone-CO2 effect
(b) Latin Hypercube Sampling (LHS)
E1
E2
Species
Climate generator
GTP20
SD
GTP100
SD
N2O
NOx
N2O effect
Ozone-CH4 effect
(Surface)
(Shipping)
(Aircraft)
Aerosol effect
345
19
311
17
-303
-37
-9.8
153
28
3
-12
-1.2
-0.02
7.6
0.32
0.12
-97
-59
-71
9.1
-36
48
111
39
23
40
2.8
22
30
100
-0.006
-0.11
-54
0.63
-36
3.2
111
0.004
0.13
33
0.17
22
1.9
100
E3
E4
NOx
NH3
N deposition
E5
N fertilization
E6
NOx
CO2 effect
CH4 effect
CO2 effect
CH4 effect
Ozone-CO2 effect
325
S28
326
327
Projection of the Impact of Nr on Climate Change
The scientific projection of future climate change is one important work of the IPCC.
328
The IPCC Special Report on Emission Scenarios (SRES) create major GHG emission
329
scenarios based on specific economic, social and environmental objectives101. According to
330
“storyline” approach used in the IPCC SRES, we establish a new set of scenarios to project
331
the climate effect of Nr based on emissions. Projections depend on many different driving
332
forces, including driver-oriented and effect-oriented factors. N2O and NH3 emissions are
333
strongly related to N fertilizer application and manure management, along with their use
334
efficiencies. N use efficiency of cropland in China was relatively low, only 23.5% in
335
2005100; thus, increasing N use efficiency as a driver-oriented factor has a great potential for
336
mitigating Nr emissions. NOx emission is related to energy structure and combustion
337
technology. In China’s “Twelfth Five-Year Plan” for energy saving and emission reduction
338
working plan, “denitration” has been added as a constraint index; thus, NOx reduction can
339
be regarded as an effect-oriented factor. Based on the above analysis, we set up three
340
scenarios to depict future climate change (Table S8). The situation in 2005 was used as the
341
reference, and those in 2020 and 2050 as the target years. (i) SRES I–Business as usual
342
(BAU) scenario is based on the assumption that Nr emissions and Nr addition will maintain
343
the increase rate of 2000–2005 with no change. (ii) SRES II–Improvement scenario, is built
344
on the assumption that the N use efficiency of cropland will increase by 20% in 2020102 and
345
another 20% in 2050, which approaches the level of developed countries103. Accordingly,
346
the N input will decrease 46% and 63% in 2020 and 2050, respectively. In this situation,
S29
347
both the N2O and NH3 emissions from the agricultural soils will decrease at the same rate.
348
(iii) SRES III-Abatement scenario is built on the assumption of total quantity control for
349
NOx in 2020 and an improved NOx removal rate in 2050, respectively. The situation in 2020
350
is designed to further cut 10% of NOx emission on the basis of the reduction target of the
351
“Twelfth Five-Year Plan” namely 5.61 Tg N, while the situation in 2050 assumes that the
352
nationwide NOx removal rate (i.e., the denitration level) reaches 80%. It should be noted
353
that the N addition level and the chemical form of N addition influence the direction and
354
magnitude of GHG fluxes79. For the Chinese terrestrial ecosystem, the relative contribution
355
rate of N addition on C sequestration decreased from 73% to 64% during 1960 and 200582;
356
in addition, the ratio of NCE to N deposition increased with time and peaked in the
357
mid-1980s, then leveled off or declined because more areas have reached N saturation84. For
358
Chinese fertilized cropland, the C sequestration rate also represented a declining trend
359
during 1980–200588. Particularly, the N fertilizer application showed a limited potential of
360
C sequestration compared with other measures, including tillage and straw return87.
361
Therefore, if the increasing N addition trend continues without taking any action, the
362
N-induced C sequestration potential can be assumed to decline 50% in 2020 and approach
363
zero in 2050. Recently, the Representative Concentration Pathway (RCP) are widely viewed
364
as the next iteration of SRES, with four scenarios based on different RF levels (RCP 2.6, 4.5,
365
6.0 and 8.5) rather than emissions104. The detailed Nr emission and Nr enrichment data of
366
China under the RCP scenarios are derived from the online RCP inventory
367
(http://eccad.sedoo.fr/eccad_extract_interface/JSF/page_login.jsf ) and database
S30
368
369
(http://tntcat.iiasa.ac.at:8787/RcpDb/dsd?Action=htmlpage&page=welcome).
Table S8. Parameter Setting in Scenario Analysis for the Years of 2020 and 2050
Item
Gaseous Nr emission (Tg N)
N2O
NOx
NH3
Scenario
SRES I: BAU
scenario
SRES II:
Improvement
scenario
SRES III:
Abatement
scenario
RCP2.6
RCP4.5
RCP6.0
RCP8.5
Description
Value 2020
Value 2050
Description
Value 2020
Value 2050
Description
Value 2020
Value 2050
Description
Value 2020
Value 2050
Description
Value 2020
Value 2050
Description
Value 2020
Value 2050
Description
Value 2020
Value 2050
Nr enrichment (Tg N)
N
N
deposition
fertilizer
Business as usual
1.44
10.2
12.4
22.5
2.07
19.9
17.1
37
Driver-oriented: enhancing N use efficiency a
0.87
10.2
6.69
16.8
0.95
19.9
6.33
26.2
Effect-oriented: reducing NOx emission b
1.44
5.61
12.4
18.0
2.07
3.98
17.1
21.1
2
RF level at 2.6 w/m
1.26
3.64
4.7
8.34
1.58
1.52
8.46
9.98
2
RF level at 4.5 w/m
1.28
3.53
4.24
7.77
1.31
1.13
6.84
7.97
2
RF level at 6.0 w/m
1.19
3.43
3.7
7.13
1.03
5.02
5.9
10.9
2
RF level at 8.5 w/m
1.39
5.41
5.44
10.9
1.85
2.32
10.6
12.9
39.0
45.6
21.1
16.9
39.0
45.6
14.8
26.6
13.4
21.5
11.7
18.6
17.1
33.3
370
a
N use efficiency represents the ratio of crop harvest N to N applied to cropland;
371
b
based on the policy target of China.
372
S31
373
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374
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375
376
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