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Citation: Reijnders, L.
Climate-Neutral Agriculture?
Environments 2023,10, 72.
https://doi.org/10.3390/
environments10050072
Academic Editors: Shu-Yuan Pan,
Daeseung Kyung, Cheng-Hsiu Yu
and Yu-Pin Lin
Received: 14 March 2023
Revised: 12 April 2023
Accepted: 14 April 2023
Published: 26 April 2023
Copyright: © 2023 by the author.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
environments
Review
Climate-Neutral Agriculture?
Lucas Reijnders
IBED, Faculty of Science, University of Amsterdam, Science Park 904, 1090 GE Amsterdam, The Netherlands;
l.reijnders@uva.nl
Abstract:
Regarding the achievement of worldwide agricultural climate neutrality, the focus is
on a worldwide net-zero emission of cradle-to-farmgate greenhouse gases (GHGs), while, when
appropriate, including the biogeophysical impacts of practices on the longwave radiation balance.
Increasing soil carbon stocks and afforestation have been suggested as practices that could be
currently (roughly) sufficient to achieve agricultural climate neutrality. It appears that in both
cases the quantitative contributions to climate neutrality that can actually be delivered are very
uncertain. There is also much uncertainty about the quantitative climate benefits with regard to
forest conservation, changing feed composition to reduce enteric methane emission by ruminants,
agroforestry and the use of nitrification and urease inhibitors to decrease the emission of N
2
O. There
is a case for much future work aimed at reducing the present uncertainties. The replacing of animal
husbandry-based protein production by plant-based protein production that can reduce agricultural
GHG emissions by about 50%, is technically feasible but at variance with trends in worldwide food
consumption. There is a case for a major effort to reverse these trends. Phasing out fossil fuel inputs,
improving nitrogen-use efficiency, net-zero GHG-emission fertilizer inputs and reducing methane
emissions by rice paddies can cut the current worldwide agricultural GHG emissions by about 22%.
Keywords:
agricultural climate neutrality; greenhouse gases; net-zero emissions; longwave radiation
balance; practices; uncertainty
1. Introduction
Agriculture impacts climate. Contributions to the direct impact of agriculture on
climate can come from the emission of greenhouse gases (GHGs), which have an upward
effect on the tropospheric temperature, the generation of aerosols which have a cooling
effect and changes in albedo: the proportion of irradiation that is reflected [
1
]. Changes in
albedo can have a warming or cooling effect [
2
]. Changes in vegetation linked to agriculture
may, moreover, impact evapotranspiration and turbulence which in turn can affect the
longwave radiation balance [
3
]. Climate warming linked to agriculture can in turn have
impacts that additionally affect climate in ways that may quantitively add to the direct
impacts. These indirect agricultural impacts on climate can be changes in albedo (e.g., due
to reduced occurrence of ice in the Arctic), increased emissions of GHGs (e.g., due to higher
soil temperatures in permafrost areas), changes in cloud cover and increases in aerosol
emissions (e.g., due to increased numbers of forest fires) [1].
The climate neutrality of agriculture has emerged as a subject in the scientific liter-
ature [
4
–
10
]. The scope of the studies [
4
–
10
] is limited as to geographical coverage and
types of agricultural production, Climate neutrality has also emerged in the certification of
agricultural products [
11
]. Additionally, there are publications pointing out that specific
practices can be important contributors to climate-change mitigation regarding agricul-
ture [
12
–
25
]. These publications consider reducing the emissions of agricultural GHGs
and/or increasing carbon sequestration. Commonly, in these studies the direct emissions of
greenhouse gases due to agriculture are considered. Increases in GHG emissions due to the
contribution of agriculture to climate change are not commonly included in considerations
pertinent to agricultural climate neutrality or climate-change mitigation.
Environments 2023,10, 72. https://doi.org/10.3390/environments10050072 https://www.mdpi.com/journal/environments
Environments 2023,10, 72 2 of 16
System boundaries to agricultural systems considered in the context of climate neu-
trality (see Figure 1) can vary. Efforts to achieve climate neutrality may exclusively refer to
a farm or a set of farms (e.g., [
6
,
11
]). The term ‘farms’ here includes plantations, ranches
and greenhouses for horticulture. Changes in agroecosystem carbon stocks to establish
or operate farms are included within the system boundaries of farms. System boundaries
exclusively encompassing farms may be considered too limited. In farming, physical inputs
can be used that have been generated outside the farm. Examples of such physical inputs
are machinery, water, fuels, electricity, feed, fertilizers and pesticides. The production
and transport of these inputs can be associated with substantial-to-large contributions to
the cradle-to-farmgate emissions of greenhouse gases (e.g., [
26
–
29
]). The term ‘farmgate’
denotes the place where agricultural outputs leave the farm. In lifecycle assessments re-
garding animal husbandry [
27
,
28
], substantial-to-large contributions to cradle-to-farmgate
emissions of GHGs can originate in the feed acquired from outside the farm—in lifecycle
assessments of plant-based agriculture, inputs of energy and synthetic fertilizers can have
substantial-to-large contributions to cradle-to-farmgate emissions of GHG [
26
,
29
]. To de-
termine the net contribution of agriculture to climate change, system boundaries may be
drawn in such a way that physical inputs produced outside the farm are included in efforts
to achieve climate neutrality (see Figure 1). Such cradle-to-farmgate system boundaries
will be used here in assessing contributions to agricultural climate neutrality.
Environments 2023, 10, x FOR PEER REVIEW 2 of 16
to the contribution of agriculture to climate change are not commonly included in consid-
erations pertinent to agricultural climate neutrality or climate-change mitigation.
System boundaries to agricultural systems considered in the context of climate neu-
trality (see Figure 1) can vary. Efforts to achieve climate neutrality may exclusively refer
to a farm or a set of farms (e.g., [6,11]). The term ‘farms’ here includes plantations, ranches
and greenhouses for horticulture. Changes in agroecosystem carbon stocks to establish or
operate farms are included within the system boundaries of farms. System boundaries
exclusively encompassing farms may be considered too limited. In farming, physical in-
puts can be used that have been generated outside the farm. Examples of such physical
inputs are machinery, water, fuels, electricity, feed, fertilizers and pesticides. The produc-
tion and transport of these inputs can be associated with substantial-to-large contributions
to the cradle-to-farmgate emissions of greenhouse gases (e.g., [26–29]). The term ‘farm-
gate’ denotes the place where agricultural outputs leave the farm. In lifecycle assessments
regarding animal husbandry [27,28], substantial-to-large contributions to cradle-to-farm-
gate emissions of GHGs can originate in the feed acquired from outside the farm—in
lifecycle assessments of plant-based agriculture, inputs of energy and synthetic fertilizers
can have substantial-to-large contributions to cradle-to-farmgate emissions of GHG
[26,29]. To determine the net contribution of agriculture to climate change, system bound-
aries may be drawn in such a way that physical inputs produced outside the farm are
included in efforts to achieve climate neutrality (see Figure 1). Such cradle-to-farmgate
system boundaries will be used here in assessing contributions to agricultural climate
neutrality.
Figure 1. System boundaries for agricultural systems and their impacts on climate. For climate im-
pacts of farm(s), including changes in agroecosystem stocks for establishment: . For cradle-
to-farmgate climate impacts of agricultural product outputs: .
The greenhouse gases that are commonly considered in achieving agricultural cli-
mate neutrality are in Table 1. CO2, CH4 and N2O are the main GHGs linked to the cradle-
to-farmgate lifecycle stages of agricultural product outputs [17]. Table 1 shows the global
warming potentials (GWP) of these GHGs relative to the greenhouse gas CO2. Global
warming potentials are presented as values covering a period of 20 or 100 years. The val-
ues covering a period of 100 years (GWP100) are commonly used and will also be used in
what follows. It may be noted, though, that for the greenhouse gas CH4, which has a sub-
stantially lower atmospheric persistence than the other GHGs in Table 1 [30], the global
warming potential covering a period of 20 years (GWP20) is much larger than the GWP100.
If radiative forcing should be limited rapidly, there is, in view of Table 1, a case to priori-
tize the reduction in (agricultural) methane emissions (see Sections 4.1.4 and 4.1.7).
Figure 1.
System boundaries for agricultural systems and their impacts on climate. For climate
impacts of farm(s), including changes in agroecosystem stocks for establishment:
Environments 2023, 10, x FOR PEER REVIEW 2 of 16
to the contribution of agriculture to climate change are not commonly included in consid-
erations pertinent to agricultural climate neutrality or climate-change mitigation.
System boundaries to agricultural systems considered in the context of climate neu-
trality (see Figure 1) can vary. Efforts to achieve climate neutrality may exclusively refer
to a farm or a set of farms (e.g., [6,11]). The term ‘farms’ here includes plantations, ranches
and greenhouses for horticulture. Changes in agroecosystem carbon stocks to establish or
operate farms are included within the system boundaries of farms. System boundaries
exclusively encompassing farms may be considered too limited. In farming, physical in-
puts can be used that have been generated outside the farm. Examples of such physical
inputs are machinery, water, fuels, electricity, feed, fertilizers and pesticides. The produc-
tion and transport of these inputs can be associated with substantial-to-large contributions
to the cradle-to-farmgate emissions of greenhouse gases (e.g., [26–29]). The term ‘farm-
gate’ denotes the place where agricultural outputs leave the farm. In lifecycle assessments
regarding animal husbandry [27,28], substantial-to-large contributions to cradle-to-farm-
gate emissions of GHGs can originate in the feed acquired from outside the farm—in
lifecycle assessments of plant-based agriculture, inputs of energy and synthetic fertilizers
can have substantial-to-large contributions to cradle-to-farmgate emissions of GHG
[26,29]. To determine the net contribution of agriculture to climate change, system bound-
aries may be drawn in such a way that physical inputs produced outside the farm are
included in efforts to achieve climate neutrality (see Figure 1). Such cradle-to-farmgate
system boundaries will be used here in assessing contributions to agricultural climate
neutrality.
Figure 1. System boundaries for agricultural systems and their impacts on climate. For climate im-
pacts of farm(s), including changes in agroecosystem stocks for establishment: . For cradle-
to-farmgate climate impacts of agricultural product outputs: .
The greenhouse gases that are commonly considered in achieving agricultural cli-
mate neutrality are in Table 1. CO2, CH4 and N2O are the main GHGs linked to the cradle-
to-farmgate lifecycle stages of agricultural product outputs [17]. Table 1 shows the global
warming potentials (GWP) of these GHGs relative to the greenhouse gas CO2. Global
warming potentials are presented as values covering a period of 20 or 100 years. The val-
ues covering a period of 100 years (GWP100) are commonly used and will also be used in
what follows. It may be noted, though, that for the greenhouse gas CH4, which has a sub-
stantially lower atmospheric persistence than the other GHGs in Table 1 [30], the global
warming potential covering a period of 20 years (GWP20) is much larger than the GWP100.
If radiative forcing should be limited rapidly, there is, in view of Table 1, a case to priori-
tize the reduction in (agricultural) methane emissions (see Sections 4.1.4 and 4.1.7).
. For cradle-to-
farmgate climate impacts of agricultural product outputs:
Environments 2023, 10, x FOR PEER REVIEW 2 of 16
to the contribution of agriculture to climate change are not commonly included in consid-
erations pertinent to agricultural climate neutrality or climate-change mitigation.
System boundaries to agricultural systems considered in the context of climate neu-
trality (see Figure 1) can vary. Efforts to achieve climate neutrality may exclusively refer
to a farm or a set of farms (e.g., [6,11]). The term ‘farms’ here includes plantations, ranches
and greenhouses for horticulture. Changes in agroecosystem carbon stocks to establish or
operate farms are included within the system boundaries of farms. System boundaries
exclusively encompassing farms may be considered too limited. In farming, physical in-
puts can be used that have been generated outside the farm. Examples of such physical
inputs are machinery, water, fuels, electricity, feed, fertilizers and pesticides. The produc-
tion and transport of these inputs can be associated with substantial-to-large contributions
to the cradle-to-farmgate emissions of greenhouse gases (e.g., [26–29]). The term ‘farm-
gate’ denotes the place where agricultural outputs leave the farm. In lifecycle assessments
regarding animal husbandry [27,28], substantial-to-large contributions to cradle-to-farm-
gate emissions of GHGs can originate in the feed acquired from outside the farm—in
lifecycle assessments of plant-based agriculture, inputs of energy and synthetic fertilizers
can have substantial-to-large contributions to cradle-to-farmgate emissions of GHG
[26,29]. To determine the net contribution of agriculture to climate change, system bound-
aries may be drawn in such a way that physical inputs produced outside the farm are
included in efforts to achieve climate neutrality (see Figure 1). Such cradle-to-farmgate
system boundaries will be used here in assessing contributions to agricultural climate
neutrality.
Figure 1. System boundaries for agricultural systems and their impacts on climate. For climate im-
pacts of farm(s), including changes in agroecosystem stocks for establishment: . For cradle-
to-farmgate climate impacts of agricultural product outputs: .
The greenhouse gases that are commonly considered in achieving agricultural cli-
mate neutrality are in Table 1. CO2, CH4 and N2O are the main GHGs linked to the cradle-
to-farmgate lifecycle stages of agricultural product outputs [17]. Table 1 shows the global
warming potentials (GWP) of these GHGs relative to the greenhouse gas CO2. Global
warming potentials are presented as values covering a period of 20 or 100 years. The val-
ues covering a period of 100 years (GWP100) are commonly used and will also be used in
what follows. It may be noted, though, that for the greenhouse gas CH4, which has a sub-
stantially lower atmospheric persistence than the other GHGs in Table 1 [30], the global
warming potential covering a period of 20 years (GWP20) is much larger than the GWP100.
If radiative forcing should be limited rapidly, there is, in view of Table 1, a case to priori-
tize the reduction in (agricultural) methane emissions (see Sections 4.1.4 and 4.1.7).
.
The greenhouse gases that are commonly considered in achieving agricultural climate
neutrality are in Table 1. CO
2
, CH
4
and N
2
O are the main GHGs linked to the cradle-to-
farmgate lifecycle stages of agricultural product outputs [
17
]. Table 1shows the global
warming potentials (GWP) of these GHGs relative to the greenhouse gas CO
2
. Global
warming potentials are presented as values covering a period of 20 or 100 years. The
values covering a period of 100 years (GWP
100
) are commonly used and will also be used
in what follows. It may be noted, though, that for the greenhouse gas CH
4
, which has a
substantially lower atmospheric persistence than the other GHGs in Table 1[
30
], the global
warming potential covering a period of 20 years (GWP
20
) is much larger than the GWP
100
.
If radiative forcing should be limited rapidly, there is, in view of Table 1, a case to prioritize
the reduction in (agricultural) methane emissions (see Sections 4.1.4 and 4.1.7).
The current worldwide yearly emissions of the GHGs linked to the cradle-to-farmgate
lifecycle of agricultural outputs has been estimated at about 25% of the yearly worldwide
emissions of greenhouse gases (as GWP
100
CO
2
equivalents) [
17
], which corresponds with
the emission of about 10 petagrams (Pg) of GWP100 CO2equivalents [14].
Environments 2023,10, 72 3 of 16
Table 1.
Greenhouse gases commonly considered in achieving agricultural climate neutrality with
their global warming potentials relative to CO2[31–34].
Greenhouse Gas
Global Warming Potential
over a Period of 100 Years
(GWP100) Relative to CO2
Global Warming over a
Period of 20 Years (GWP20)
Relative to CO2
CO21 1
CH428–36 83–85
N2O 265–298 264–289
In this review, practices that have been proposed as important contributions to miti-
gating the contribution of agriculture to climate change in scientific literature [
4
–
10
,
12
–
25
]
will be discussed to establish the contributions to agricultural climate neutrality that they
can deliver. To the best of my knowledge, this is the first time that this has been done. The
methodology used will be briefly presented in Section 2. Agricultural climate neutrality
is defined in various ways. This matter will be addressed in Section 3. Section 4will con-
sider practices that may contribute to worldwide agricultural climate neutrality. Section 5
presents the conclusions of this paper.
2. Methodology
The methodology for the gathering of information for this review from the databases
of Google Scholar and the publishers MDPI, Springer Nature, Elsevier and Wiley was as
follows. Firstly, a search was made using the terms agriculture, farming, crop production,
livestock production and climate neutral(ity). This generated a set of publications [
4
–
10
].
The practices presented for achieving climate neutrality in these publications are all dis-
cussed in this paper, with the practice of farm efficiency [
7
] restricted to energy efficiency
(Section 4.1.5) and fertilizer-use efficiency (Sections 4.1.8 and 4.1.9), without considering
rebound effects. With the exception of afforestation (Section 4.2), all practices in these stud-
ies [
4
–
10
] were within the cradle-to-farmgate system boundaries (Section 4.1). Secondly, the
databases were searched with the terms agriculture, climate-change mitigation and review.
This produced a set of publications [
12
–
25
] which included the following practices for
reducing net agricultural GHG emissions that were not covered in the publications [
4
–
10
]
found in the first search: forest conservation (Section 4.1.3), agroforestry (Section 4.1.6)
and reducing the methane emission from rice paddies (Section 4.1.7). The publications
collected [
4
–
10
,
12
–
25
] contained statements regarding potential quantitative climate ben-
efits relevant to the worldwide application of the practices considered in this paper. The
publications also contained quantitative information as to the worldwide net greenhouse
gas emissions within the system boundaries of Figure 1. An additional search was carried
out to obtain missing data regarding agricultural N
2
O emissions and the net emissions of
GHGs linked to fossil fuel and fertilizer inputs into farming and animal husbandry. Subse-
quently, the databases were searched for information shedding light on the correctness of
the statements in the publications [4–10,12–25] regarding potential climate benefits.
3. Definitions of Agricultural Climate Neutrality
Several definitions of climate neutrality for agriculture referring to greenhouse gases
are currently used (see Box 1).
Box 1. Definitions of climate neutrality for agriculture referring to greenhouse gases.
1. Net-zero emission of agricultural GHHG emissions (in CO2equivalents) [5,7,8,11]
2. Net-zero increase in radiative forcing by agricultural GHG emissions [6]
3. Net-zero change in current average temperature as impacted by agricultural GHGs [35]
Environments 2023,10, 72 4 of 16
A net-zero change in radiative forcing implies a commitment to a substantial additional
rise in temperature [
1
,
36
], which would seem at variance with climate neutrality. With that
in mind, the second definition will not be used here. The United Nations’ Paris Agreement
on climate change included a commitment to achieve net-zero GHG emissions in the second
half of the present century and the European Union have set a target for achieving this
goal by 2050 [
37
]. No allocation of targets to economic sectors has been made, as yet,
under the United Nations Framework Convention on Climate Change or by the European
Union. Still, for instance, Danish agricultural organisations have agreed on a net-zero
emission of agricultural greenhouse gases to be met by 2050 [
7
]. When the third definition
applies, a target for net-zero emission of worldwide agricultural GHGs should presumably
be met well before 2050. In addition, when appropriate, in Section 2the biogeophysical
impacts on the longwave radiation balance of practices that may contribute to achieving
agricultural climate neutrality will be considered. These impacts are linked to changes in
albedo, evapotranspiration and turbulence.
4. Practices That May Contribute to Agricultural Climate Neutrality
Practices have been suggested that, when applied worldwide, may be important
contributions to mitigating the agricultural contribution to climate change. These partly
regard increasing carbon sequestration and partly reducing greenhouse gas emissions. Such
practices, when within the cradle-to-farmgate system boundaries presented in Figure 1, are
addressed in Section 4.1. Section 4.2 discusses the suggested practice of afforestation for
achieving climate neutrality, which is outside the cradle-to-farmgate system boundaries
outlined in Figure 1. The focus in Sections 4.1 and 4.2 is on the feasibility of achieving
important contributions to agricultural climate neutrality. Much thereof is with regard to
the feasibility within the realm of the natural sciences. In several cases, matters outside
the realm of the natural sciences were found to be crucial as to the real-world feasibility
of achieving important contributions. These matters are briefly addressed. In all cases,
there are economic matters that impact the real-world feasibility of the proposed practices
(e.g., [
14
,
24
]), but a comprehensive discussion thereof is outside the scope of the present
review. Section 4.3 summarizes what may be concluded from Sections 4.1 and 4.2.
4.1. Practices within the Cradle-to-Farmgate System Boundaries
The practices that will be discussed here are ordered on the basis of quantitative
statements that have been made as to their potential contribution to climate neutrality,
starting with the practice with the largest claimed potential contribution.
4.1.1. Increasing Soil Carbon Stocks
Increasing soil carbon stocks by changing agricultural practices in field farming,
focused on reduced tillage (which can reduce the oxidation of soil organic carbon) and
increased inputs of organic materials such as harvest residues, has been advocated as a
major way to mitigate climate change and achieve carbon neutrality [
9
,
15
]. There is a ‘4
per 1000’ Initiative aimed at increasing the yearly accumulation of carbon in agricultural
soils, in a way that might offset a yearly GHG emission of about 8–11 petagrams (Pg)
of GWP
100
CO
2
equivalents [
38
]. In the context of carbon accumulation in agricultural
soils, the benefits of adding biochar (pyrolyzed biomass) to soils have been stressed [
12
,
39
].
As to the climate benefit of biochar, it must be noted that a cooling effect linked to an
expected increase in soil carbon is counteracted by a warming effect due to the impact of
biochar on albedo [
2
,
40
], the latter not being addressed by Woolf et al. [
39
] and Stavi and
Lal [
12
]. Whether efforts to increase carbon stocks in mineral soils by changes in agricultural
practices can be a major factor in mitigating climate change has been the subject of vigorous
debate [
15
,
38
,
41
,
42
]. A problem regarding predicting carbon sequestration by changed
agricultural practices is that the main mechanisms of carbon gains by mineral soils have as
yet not been properly identified [
43
]. All other things being equal, there may be scope for
increasing soil carbon stocks by reducing tillage and larger inputs of harvest residues, but
Environments 2023,10, 72 5 of 16
the quantitative estimates of actual accumulation are uncertain. In addition, not all other
things are equal: the current commitment to additional future warming of climate [
1
] may
impact soil carbon stocks, and the use of biochar to increase soil carbon stocks can lead
to additional warming of soils due to its impact on albedo [
2
]. Available studies suggest
that soil warming tends to substantially reduce soil carbon stocks, but the quantification of
future warming on carbon stocks is uncertain [
44
–
47
]. It may be concluded that, taking the
current commitment to global warming into account, additional soil carbon sequestration
in mineral soils by changing agricultural practices is not excluded but the quantification
thereof, and thus its contribution to achieving climate neutrality, is very uncertain.
There have been efforts to reverse the large carbon losses in drainage-based agriculture
on peatlands by rewetting the soils. To the extent that these efforts have been monitored, it
appears that greenhouse gas emissions (as GWP
100
CO
2
equivalents) can be reduced by
70–80%, if compared with drained peatland [
48
]. Re-wetting peatlands would not allow
for their traditional agricultural use, such as for animal husbandry and plantations, but
may allow for paludiculture, producing plant-biomass as a basis for potential product
outputs [
49
,
50
]. A study of GHG emissions for existing wet peatlands generating biomass
used as a proxy for re-wetted peatlands with paludiculture did show that net carbonaceous
greenhouse gas emissions were substantially lowered, if compared with drainage-based
agriculture, but only in one case out of six was a there a net-zero emission [
50
]. Though
data are limited, it would seem likely that the rewetting of peatland can lead to a large
reduction in the net emission of GHGs. Net increases in soil carbon of rewetted peatlands
have not been demonstrated.
All in all, a large accumulation of carbon in agricultural soils, as envisaged by the ‘4 per
1000’ Initiative, would seem very uncertain. Reducing the present quantitative uncertainty
about the scope for increasing soil carbon stocks requires much additional research.
4.1.2. Shifting from Protein Outputs Based on Animal Husbandry to Protein Outputs
Based on Crops
Proteins are an important output of agriculture. A large contributor to this output is
animal husbandry which contributes an estimated 14.5% to the worldwide emission of
greenhouse gases [
51
], corresponding with a yearly emission of about 5.8 Pg of GWP
100
CO
2
equivalents. The cradle-to-farmgate GHG emissions per kg of protein show large
variations [
7
,
52
]. On the basis of the available data, rough estimates may be made of relative
average cradle-to-farmgate greenhouse gas emissions (as GWP
100
CO
2
equivalents) per kg
of protein for outputs of animal husbandry, if compared with soybeans or pulses which
contain proteins of a quality similar to those of the outputs of animal husbandry. These are
shown in Table 2.
Table 2.
Rough estimates of relative average cradle-to-farmgate greenhouse gas emissions (as GWP
100
CO2equivalents) per kg of protein from different sources [7,52].
Protein Source Rough Estimates of Relative Average Cradle-to-Farmgate Greenhouse
Gas Emissions (as GWP100 CO2Equivalents) per kg Protein
Soybeans, pulses 1
Poultry (meat, eggs) 3–4
Pork 6
Lamb >20
Beef >20
The data in Table 2allow for predictions of reductions in GHG emissions linked to
changes in worldwide food consumption that are rather certain. Shifting from animal
husbandry to the production of pulses and soybeans might lead to a yearly reduction in
worldwide cradle-to-farmgate GHG emissions by about 5 Pg of GWP
100
CO
2
equivalents.
This would reduce the current worldwide cradle-to-farmgate GHG emission by about
Environments 2023,10, 72 6 of 16
50%. Shifting from beef to pork and poultry meat and eggs may also lead to a substantial
reduction in cradle-to-farmgate greenhouse gas emissions. Such shifts have the additional
potential climate benefit that they reduce the demand for land, which in turn might reduce
deforestation and/or make land no longer needed for agricultural production available
for increased carbon sequestration [
53
]. However, current and expected demographic
trends and developments in eating habits are at variance with such shifts [
17
]. Still, in
view of the large climate benefits linked to shifting from protein outputs based on animal
husbandry to protein outputs based on pulses and soybeans, there is a case for a major effort
to reverse the trend in food consumption leading to increased animal husbandry-based
cradle-to-farmgate GHG emissions.
4.1.3. Forest Conservation
The recent development of worldwide agriculture is linked to deforestation [
54
]. Most
of the deforestation is in the tropics, where >90% of deforestation is linked to agriculture [
55
].
Deforestation causes large emissions of GHGs and for this reason forest conservation has
been advocated as a substantial contributor to the reduction in agricultural greenhouse
gas emissions (e.g., [
14
]). Griscom et al. [
14
] have estimated that forest conservation might
reduce the yearly emissions of GHGs by about 3.5 Pg of GWP
100
CO
2
equivalents. A
large part thereof can be allocated as avoided emissions from agriculture. Real-world
conservation of forests has, however, proved problematical. It is estimated that of all
timber traded worldwide, 15–30% comes from illegal logging in protected forests [
56
]. The
weakness of national forest protection frameworks and neglect or even maltreatment of
local populations negatively impact the actual reduction in GHG emissions linked to forest
conservation [
57
]. There is also the occurrence of leakage: the induction of activities that
have the opposite effect of greenhouse gas emission reduction, as they are associated with
additional emissions of GHGs [
58
,
59
]. Leakage, in the case of forest conservation, is partly
linked to the migration of local people, who see their livelihoods negatively impacted
by forest conservation, and participate in deforestation elsewhere, and partly linked to
international and national shifts in the demand for wood and land that can increase
greenhouse gas emissions [
59
]. For instance, better forest conservation in Vietnam has been
associated with increased deforestation in neighboring countries [
59
]. Furthermore, there
is the risk that carbon stocks accumulated in protected forests may be lost by forest fires,
severe storms, drought and pests, which may be exacerbated by climate change [
60
–
65
].
Finally. there is the matter of expected further population growth, which increases the
demand for food and for that reason, especially in poor societies, tends to be a driver of
deforestation [
66
]. These factors make the real-world feasibility of reducing the yearly
emissions of GHGs by about 3.5 Pg of GWP
100
CO
2
equivalents by forest conservation
very uncertain.
4.1.4. Reducing Enteric Methane Emissions by Ruminants
Enteric methane emissions have a large contribution to the greenhouse gas emissions
associated with animal husbandry by ruminants (cows, sheep, goats) and are estimated
to contribute about 40% to the worldwide GHG emissions linked to animal husbandry
(in GWP
100
CO
2
equivalents) [
67
]. This amounts to a yearly emission of about 2.3 Pg
GWP
100
CO
2
equivalents. Most of the options to reduce CH
4
emissions focus on changes
in the composition of feed [
68
]. One may find estimates of nationwide enteric methane
emission reductions linked to changes in feed composition varying from 30–90% [7,20]. If
the latter estimate is taken, changes in feed composition could reduce the yearly emission
of greenhouse gases by about 2.1 Pg GWP
100
CO
2
equivalents. In experimental settings,
substantially reduced CH
4
emissions achieved by changing the composition of feed have
been shown, but these studies do not exclude the possibility that these reductions are
transient [
68
]. Research regarding the impact of persistent changes in feed composition
on methane emissions is lacking [
68
]. For this reason, quantitative reduction estimates
regarding future CH
4
emission by ruminants linked to changes in feed composition are
Environments 2023,10, 72 7 of 16
presently very uncertain. Long-term studies on the impact of changing feed composition
on enteric methane emissions by ruminants are necessary to reduce this uncertainty.
4.1.5. Replacement of Fossil Fuel Inputs by Solar and Wind Energy
The GHG emissions linked to fossil fuel-powered agricultural machinery are sub-
stantial: the current use of fossil fuels by agricultural machinery can be estimated to be
responsible for a greenhouse gas emission of 1.0–1.1 Pg of GWP
100
CO
2
equivalents (based
on data provided by Scherer and Verberg [
69
] and Pellegrini and Fernandez [
70
]). Both
farm-based production of renewable energy and improved farm machinery could be con-
ducive to cutting this emission. Farms can be used for the production of renewable energy.
Currently, product outputs of agriculture which can serve the supply of food are used for
the production of liquid biofuels. Apart from the use of sugarcane for ethanol production,
this presently does not lead to a net reduction in GHG emissions when substituting for liq-
uid fossil fuels such as petrol and diesel [
35
]. Moreover, as the demand for food is expected
to increase greatly in the coming decades, the option of energy crops becomes even less
attractive [
7
]. As to the use of lignocellulosic harvest residues for biofuel, it should be noted
that there is a case for applying at least a part thereof to the soil to prevent a reduction in soil
carbon stocks, serve soil fertility and protect against soil erosion [
71
,
72
]. The remainder of
the harvest residues may be applied to the production of power and heating (e.g., [
7
,
72
,
73
]).
If these applications substitute fossil fuels, the resulting net reduction in the emission can
be used as an offset for greenhouse gas emissions linked to the cradle-to-farmgate lifecycle
of agricultural production [7].
Agricultural land is also used for the production of wind power and solar power.
Wind power and photovoltaic solar power tend to generate much more energy per m
2
of land than energy crop production. A study regarding three locations across Europe
found that, per m
2
, wind power generated about 100 times as much energy as energy
crops, and photovoltaic modules about 40 times as much as energy crops. [
74
], are currently
associated with substantial lifecycle GHG emissions, but such emissions are much lower
than for fossil fuel-based power production [
75
–
77
] and can be lowered further by a
general phase-out of fossil fuel use. Photovoltaic modules installed on farm buildings or
agricultural machinery do not compete with crop production. Wind power and photovoltaic
modules on agricultural soil can lead to reductions in crop yields. The cradle-to-farmgate
greenhouse gas emissions of crop cultivation elsewhere to meet the inelastic demand for
food [
78
,
79
] have to be accounted for in estimating the climate benefit of agricultural wind
power and solar parks on agricultural land. The installations involved can have other
owners, but to the extent farm-ownership applies, the installations can directly impact
agricultural GHG emissions as they may serve electricity demand on the farm. When the
farm owning the installations is a (net) exporter of electricity, the replacement of fossil
fuel-based electricity production can be used as an offset for greenhouse gas emissions
linked to the cradle-to-farmgate lifecycle of agricultural production. The capital costs of
installations for wind and photovoltaic power may be a challenge when implementing the
option of farm-owned installations.
Using all-electric farming machinery with improved energy-efficiency and powered
by solar power or wind power, to replace current machinery powered by fossil fuels,
could provide a substantial contribution to the reduction in cradle-to-farmgate agricultural
emissions of CO
2
[
16
]. It should be noted, though, that in the case of traction, the production
of such machinery is likely to be more energy-intensive than the production of the fossil-fuel-
powered machinery which is replaced [
80
]. A variety of all-electric agricultural machinery,
that could replace fossil-fuel-powered machinery, has become commercially available. For
crop production, this involves commercial electric tractors, multipurpose on-farm electric
vehicles and a variety of electric robots (for, e.g., weeding, spraying, seeding) [
16
]. The
development of electric harvesting machinery for cereals has been described [
81
] and
electrical machinery for combine-harvesting of wheat and rice has been designed [
82
].
Furthermore, there are applications of electric machinery in farming, which are currently
Environments 2023,10, 72 8 of 16
operating with an electricity supply based on fossil fuels, that can switch to solar or wind
power. There is, furthermore, the application of electric machinery in fruit harvesting [
83
].
In capital-intensive dairy farming, electric machinery for the harvesting and cooling of
milk is commonly used [
84
], while electric automated feeding systems are emerging [
85
].
A major effort is needed to increase the commercial availability of commercial electric
farm machinery [
16
] and to lower the GHG emissions linked to the production of such
machinery. The capital cost of electric machinery to replace machinery powered by fossil
fuels can be a challenge [
86
]. Indeed, it would seem that strong incentives are needed for
cutting emissions linked to farm-based energy consumption. Still, reducing the emission of
greenhouse gases linked to the current inputs of energy into farms by 1.0 Pg of GWP
100
CO2equivalents would not seem beyond technical feasibility.
4.1.6. Replacing Field Farming by Agroforestry
One option to increase the agroecosystem carbon stocks that has been advocated as
an important contribution to mitigating climate change is a shift from field farming to
agroforestry [
12
,
87
–
91
]. Agroforestry is a set of practices that intercrop trees or shrubs with
crops such as grains, vegetables and forages [
12
,
87
,
89
]. Actual gains in carbon stock may
concern increased root biomass in soils and increased aboveground biomass, if compared
with field farming [
12
,
90
,
91
]. Furthermore, the carbon stock in humus and (partly) decom-
posed litter can be substantial [
91
] and the emission of CO
2
from soils can be reduced [
88
].
The quantity of carbon stock gains depends on the type of agroforestry [
12
,
90
,
91
] and
on climate. In temperate climates and under arid conditions, carbon sequestration in
agroforestry tends to be lower than under warm and humid climate conditions [
92
]. Root
carbon stocks in agroforestry have been found to be 1.3
−
20
×
10
6
g per ha and carbon
stocks in aboveground biomass 6
−
172
×
10
6
g per ha [
12
]. Griscom et al. [
14
] estimated
that a shift to agroforestry might reduce yearly agricultural GHG emissions by about 0.9 Pg
of GWP100 CO2equivalents.
The real-world contribution of agroforestry to climate neutrality depends on crop
yields. Under comparable conditions, both higher and lower yields per ha of arable crops in
agroforestry have been reported [
88
,
93
–
95
]. In the case that trees or shrubs do not serve for
food production, and when yields of food crops per ha are lower than those of field farming
in comparable conditions, it should be taken into account that the difference between
the two systems is likely to be made up by farming elsewhere, as the demand for food is
inelastic [
78
,
79
]. The climate benefit from agroforestry with lower yields should be corrected
by greenhouse gas emissions linked to making up the difference elsewhere, which could
reduce the yearly climate benefit of 0.9 Pg of GWP
100
CO
2
equivalents claimed by Griscom
et al. [
14
]. An additional matter to consider is the location-specific impact of a shift from
field farming to agroforestry on albedo, evapotranspiration and turbulence that can affect
the longwave radiation balance [
89
,
96
,
97
]. Changes in the radiation balance are covered in
some agroforestry models, such as APSIM and DynACof [
96
], but comprehensive studies of
agroforestry on the longwave radiation balance have not been found. It would seem likely
that, in the tropics, longwave radiation balances biogeophysically impacted by agroforestry
do not invalidate the cooling effect of carbon sequestration, but elsewhere this would seem
less likely (cf. [
97
]). In view thereof, it might well be that the net cooling effect of worldwide
agroforestry could be substantially less than the cooling effect linked to a net decrease in
agricultural GHG emissions by 0.9 Pg of GWP
100
CO
2
equivalents. Comprehensive studies
are needed for better estimates regarding the impact of agroforestry on climate.
4.1.7. Reducing Methane Emissions from Rice Paddies
Methane emissions for rice paddies have been estimated to contribute about 30% to
worldwide agricultural methane emissions [
21
] and about 6% to worldwide agricultural
greenhouse gas emissions (as GWP
100
CO
2
equivalents), which corresponds to about 0.6 Pg
GWP
100
CO
2
equivalents. Changes in irrigation management aimed at reducing anaerobic
conditions in soils, reducing tillage and using rice varieties that can be cropped with
Environments 2023,10, 72 9 of 16
relatively low CH
4
emissions have been suggested as practices that can substantially reduce
CH
4
emissions [
21
,
98
]. Reduced tillage, dedicated rice varieties and changed irrigation
practices that do not negatively affect crop yields (which include alternate wetting and
drying, mid-season irrigation and intermittent irrigation) might allow for a reduction in
the current emissions by about 0.4 Pg GWP100 CO2equivalents [12,99].
4.1.8. Net-Zero GHG Emission Fertilizer Inputs into Farming
On the basis of data provided by Levi and Cullen [
100
], it may be estimated that
cradle-to-farm synthetic fertilizers are linked to a greenhouse gas emission of about
0.6 Pg of GWP
100
CO
2
equivalents. Improving the use efficiency of synthetic fertilizers
(cf. Section 4.1.9) can substantially cut this emission (e.g., [
25
]). Ouikhalfan et al. [
23
] have
reviewed a set of technological options that might contribute to a net-zero GHG emission
fertilizer industry. Some of these options are associated with relatively large reductions
in cradle-to-farm greenhouse gas emissions. A large share of the cradle-to farm GHG
emissions is linked to fixed-N fertilizers [
23
,
25
,
100
,
101
]. These originate in the Haber–
Bosch process for the generation of ammonia. The Haber–Bosch process currently uses
air, water and fossil CH
4
to generate N
2
/H
2
synthesis gas for the production of ammonia.
Pfromm [
102
] has proposed the production of N
2
/H
2
synthesis gas for the Haber–Bosch
process by cryogenic separation of N
2
from air and generating H
2
by electrolysis of water,
both powered by wind energy. Soloveichick [
103
] suggested the electrochemical synthesis
of ammonia as an alternative to the Haber–Bosch process. This process can be based on
solar or wind power. Both proposals would lead to a major reduction in cradle-to-farm
greenhouse gas emissions of synthetic fixed-N fertilizers. Concentrated solar thermal
systems can, when insolation is adequate, be used for the supply of process heat in fertilizer,
including fixed N and phosphate production [
104
,
105
]. Net-zero GHG emission fertilizer
inputs into farming would seem technically feasible. This would allow for a mitigation
potential of about 0.6 Pg of GWP
100
CO
2
equivalents. Realizing this potential would seem
to need strong incentives.
4.1.9. Reducing N2O Emissions
Based on data provided by Carlson et al. [
106
], yearly agricultural N
2
O emissions may
be estimated at about 0.45 Pg of GWP
100
CO
2
equivalents. N
2
O emissions linked to agricul-
ture originate in the microbial conversion of fixed N. Large amounts of the fixed-N input
into farming are lost to the environment [
25
,
107
]. One option to reduce N
2
O emissions is
improving nitrogen use efficiency by reducing the amount of fixed nitrogen not used by
crops. This amount can be in the order of 70% and may be reduced to an estimated 15–30%
by the use of precision agriculture tools, such as drip fertigation, guidance by indicators for
the presence of fixed N, optimized timing of fertilizer addition and polymer-coated fertiliz-
ers synchronizing fertilizer release with crop demand [
19
,
107
,
108
]. Improving nitrogen-use
efficiency might cut the yearly worldwide agricultural N
2
O emissions by about 50% or
0.2 Pg of GWP
100
CO
2
equivalents [
109
]. Another option, which has been advocated as a
major contribution to the reduction in N
2
O emissions, is to apply nitrification inhibitors and
urease inhibitors [
13
,
22
,
25
]. These inhibitors can be effective in reducing N
2
O emissions
when they are close to the fertilizer and are therefore usually integrated in fertilizer for-
mulations [
13
,
18
,
22
,
110
,
111
]. Most data (from relatively small-scale experiments of limited
duration) are available concerning the use of nitrification inhibitors. Woodward et al. [
111
],
reviewing such data, found that the impacts of nitrification inhibitors vary widely, depend-
ing on environmental conditions and management practices, and that climate benefits, in
practice, are not always achieved. Ruser and Schultz [
13
] concluded that N
2
O emission re-
ductions from agricultural soils of 35% by nitrification inhibitors seem realistic. A review of
available data by Adu-Poku et al. [
22
] rather suggests that the reduction in N
2
O emissions
by nitrification inhibitors might be about 9%, but estimates the N
2
O emission reduction by
urease inhibitors at about 47%. As to the possible emergence of resistance to nitrification
and urease inhibitors, available data are limited, but it is known that the microorganisms
Environments 2023,10, 72 10 of 16
involved in nitrification and urea hydrolysis vary greatly in their sensitivity to current
inhibitors [
111
–
114
]. As the long-term use of nitrification and urease inhibitors may well
create a strong selection pressure favoring more inhibitor-resistant microbes, there is the
possibility that in the longer term the effectiveness of these inhibitors will be reduced. For
this reason, the quantitative estimates of the future climate benefits linked to the long-term
use of nitrification and urease inhibitors is currently uncertain. Long term studies regarding
the impact of nitrification and urease inhibitors on N
2
O emissions are needed to reduce the
present uncertainty.
4.2. Afforestation Outside the Cradle-to-Farmgate System Boundaries
If it is not possible to achieve climate neutrality within the cradle-to-farmgate system
boundaries presented in Figure 1, there is the option of offsetting net cradle-to-farmgate
GHG emissions by activities outside the system boundaries. Kingwell [
5
] has suggested
afforestation projects in Western Australia to offset agricultural greenhouse gas emissions in
the same area. Griscom et al. [
14
] calculated that, worldwide, in 2030, carbon sequestration
by afforestation could offset an emission of about 10 petagrams (Pg) CO
2
equivalents,
corresponding with the current net yearly emission of agricultural emissions of GHGs (in
CO
2
equivalents). There are several problems that beset the estimates regarding the impact
of afforestation on climate change. Firstly, afforestation projects not only have a cooling
effect linked to carbon sequestration but may also affect the biogeophysical processes in a
way that causes warming. For instance, Breil et al. [
3
] simulated Europe-wide afforestation
on grassland and found a warming effect on the European climate. In a similar vein, Liu
et al. [
115
], simulating longwave radiation balances in an area with forests and agricultural
areas in the Nenjang river basin (China), found that the forests had a warming effect. In part,
the warming effect is linked to differences between agricultural land and forests regarding
evapotranspiration and turbulence that can impact the longwave radiation balance [
3
,
115
].
Furthermore, the warming effect is linked to changes in albedo [
97
]. The warming effect of
forests tends to be largest in boreal areas and has a decreasing tendency through temperate
to tropical regions [
97
]. The balances between warming and cooling linked to the change in
albedo by afforestation may differ considerably over short distances. Rohatyn et al. [
97
]
studied the balance between warming and cooling under dryland conditions in Israel over
a distance of 200 km, focusing on the impact of Aleppo pine trees, and found that it took
213 years for the cooling effect of afforestation with these pine trees to surpass the warming
effect due to changed albedo under dry conditions, 43 years under wet conditions and
73 years under intermediate conditions. Against this background, only focusing on carbon
sequestration when considering the impact of afforestation on climate, as in the studies of
Griscom et al. [
14
] and Kingwell [
5
], is inappropriate (also [
3
]). Furthermore, as in the case
of forest conservation, there is the matter of leakage, cf. Section 4.1.3. I have been unable to
find reliable estimates of leakage associated with recent or current afforestation projects.
The risk that carbon stocks may be lost by forest fires, severe storms, drought and pests,
which may be exacerbated by climate change [
60
–
65
], also applies to afforestation projects.
In view of these problems, quantifying the worldwide climate benefit of afforestation would
seem very uncertain.
4.3. Discussion
Regarding two of the practices, increasing soil carbon stocks and afforestation, dis-
cussed in Sections 4.1 and 4.2, quantitative claims have been made to suggest that they
could be currently (roughly) sufficient to achieve agricultural climate neutrality. It appears
that, in both cases, the quantitative contributions to agricultural climate neutrality that these
practices can actually deliver are very uncertain. There is also much uncertainty about quan-
titative climate benefits with regard to forest conservation (Section 4.1.3), changing feed
composition to reduce enteric methane emission by ruminants (with a claimed climate bene-
fit of about 2.1 Pg GWP
100
CO
2
equivalents) (Section 4.1.4), agroforestry (
Section 4.1.6
) and
the use of nitrification and urease inhibitors to decrease the emission of N
2
O (
Section 4.1.8
).
Environments 2023,10, 72 11 of 16
The replacement of animal husbandry-based protein production by plant-based protein
production, using soybean and pulses (which can reduce cradle-to-farmgate agricultural
greenhouse gas emissions by about 50%) is technically feasible but at variance with current
and expected trends in worldwide food consumption. There is a case for a major effort
to reverse these trends. Other practices discussed in Section 4.1 and the estimates of net
reductions in current yearly agricultural GHG emissions that might be achieved by their
worldwide implementation are summarized in Table 3. The sum of the net reductions
presented in Table 3is 2.2 Pg of GWP
100
CO
2
equivalents. It can be concluded that the
feasibility of achieving climate neutrality by the practices discussed in Sections 4.1 and 4.2
is presently uncertain.
Table 3.
Estimates of net reductions in current greenhouse gas emissions that might be achieved
when practices discussed in Section 4.1 are applied worldwide.
Practice Number of Section Where
This Practice Is Discussed
Estimate of Net Reduction in
Yearly Current GHG
Emissions That Might Be
Achieved When Applied
Worldwide in Pg of GWP100
CO2Equivalents.
Replacement of fossil fuel
inputs by solar and wind
energy
4.1.5 1
Reducing methane emissions
from rice paddies 4.1.7 about 0.4
Net-zero greenhouse gas
emission fertilizer inputs 4.1.8 about 0.6
Reducing N2O emission by
improving nitrogen efficiency 4.1.9 about 0.2
5. Conclusions
In determining agricultural greenhouse gas emissions and the impact of practices
aimed at achieving climate neutrality, a cradle-to-farmgate perspective is preferable. The
current worldwide yearly net cradle-to-farmgate emission of GHGs has been estimated at
about 25% of the yearly worldwide emission of greenhouse gases and amounts to about
10 Pg of GWP
100
CO
2
equivalents/year. As to achieving agricultural climate neutrality, the
focus here has been on a worldwide net-zero emission of cradle-to-farmgate greenhouse
gases while, when appropriate, including the biogeophysical impacts of practices on the
longwave radiation balance. Practices which have been mentioned as important contrib-
utors to mitigating the agricultural contribution to climate change have been discussed.
Increasing soil carbon stocks and afforestation have been suggested as practices that could
be currently (roughly) sufficient to achieve agricultural climate neutrality. It appears that in
both cases the quantitative contributions to climate neutrality which these practices can
actually deliver are very uncertain. There is also much uncertainty about the quantitative
climate benefits with regard to forest conservation, changing feed composition to reduce
enteric methane emission by ruminants, agroforestry and the use of nitrification and urease
inhibitors to decrease the emission of N
2
O. The replacement of animal husbandry-based
protein production by plant-based protein production, using soybean and pulses, that
reduces yearly agricultural GHG emissions by about 5 Pg of GWP
100
CO
2
equivalents, is
technically feasible but at variance with current and expected trends in worldwide food
consumption. There is a case for a major effort to reverse these trends; replacing fossil fuel
inputs by solar and wind energy and net-zero greenhouse gas emission fertilizer inputs
with a combined estimated net yearly GHG emission reduction of about 1.6 Pg of GWP
100
CO
2
equivalents seem technically feasible, but the realization thereof would seem to require
strong incentives. Reducing methane emissions from rice paddies and reducing N
2
O emis-
Environments 2023,10, 72 12 of 16
sions by improving nitrogen efficiency might have a combined estimated net yearly GHG
emission reduction of about 0.6 Pg of GWP
100
CO
2
equivalents. It can be concluded that
the feasibility of achieving climate neutrality, given the current worldwide net emissions of
about 10 Pg of GWP
100
CO
2
equivalents/year, by the practices discussed here is currently
uncertain. Much additional work is needed to reduce this uncertainty.
Funding: This research received no external funding.
Acknowledgments:
The comments of three reviewers and the academic editor are grateful-
ly acknowledged.
Conflicts of Interest:
The author declares that he has no known competing financial interest or
personal relationships that could have appeared to influence the work reported in this paper.
References
1.
Masson-Delmotte, V.; Zhai, P.; Pirani, A.; Connors, S.L.; Pean, C.; Chen, Y.; Goldfarb, L.; Gomis, M.I.; Matthews, J.B.R.; Berger, S.;
et al. (Eds.) Climate Change 2021. The physical science base. In Working Group I Contribution to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change; Intergovernmental Panel on Climate Change: Geneva, Switzerland, 2021; Available
online: https://www.ipcc.ch (accessed on 11 February 2023).
2.
Zhang, X.; Jiao, Z.; Zhao, C.; Qu, L.; Liu, Q.; Zhang, H.; Tong, Y.; Wang, C.; Li, S.; Guo, J.; et al. Review of land surface albedo:
Variance characteristics, climate effect and management strategy. Remote Sens. 2022,14, 1382. [CrossRef]
3.
Breil, M.; Krawczyk, F.; Pinto, J.G. The response of the regional longwave radiation balance and climate system in Europe to an
idealized afforestation experiment. Earth Syst. Dynam. 2023,14, 243–253. [CrossRef]
4.
Chen, R.; Zhang, R.; Han, H. Climate neutral in agricultural production system: A regional case from China. Environ. Sci. Pollut.
Res. 2021,28, 33682–33697. [CrossRef] [PubMed]
5.
Kingwell, R. Making agriculture carbon neutral amid a changing climate: The case of South-Western Australia. Land
2021
,
10, 1259. [CrossRef]
6.
Ridoutt, B. Climate neutral livestock production -A radiative forcing-based climate footprint approach. J. Clean. Prod.
2021
,
291, 125260. [CrossRef]
7.
Searchinger, T.; Zionts, J.; Wirsenius, S.; Peng, L.; Beringer, T.; Dumas, D. Pathways to Carbon Neutral Agriculture in Denmark; World
Resources Institute: Washington, DC, USA, 2021. [CrossRef]
8.
Duffy, C.; Prudhomme, R.; Duffy, B.; Gibbons, J.; O’Donoghue, C.; Ryan, M.; Styles, D. GOBLIN version 1: A land balance
model to identify national agriculture and land use pathways to climate neutrality via backcasting. Geosci. Model Dev.
2022
,15,
2239–2264. [CrossRef]
9.
Litskas, V.; Ledo, A.; Lawrence, P.; Chrysargyris, A.; Giannopoulos, G.; Heathcote, R.; Hastings, A.; Tsortzakis, N.; Stavrinides, M.
Use of winery and animal waste to achieve climate neutrality in non-irrigated viticulture. Agronomy 2022,123, 2375. [CrossRef]
10. Nagothu, U.S. (Ed.) Climate Neutral and Resilient Farming Systems; Earthscan/Routledge: Abingdon, UK, 2023.
11.
Climate Neutral Group. Position Paper Certification. Available online: https://www.climateneutalgroup.com/ (accessed on 12
January 2023).
12. Stavi, I.; Lal, R. Agroforestry and biochar to offset climate change. Agron. Sustain. Develop. 2013,33, 91–96. [CrossRef]
13.
Ruser, R.; Schultz, R. The effect of nitrification inhibitors on the nitrous oxide (N
2
O) release from agricultural soils. J. Plant Nutr.
Soil Sci. 2015,178, 171–188. [CrossRef]
14.
Griscom, B.W.; Adam, J.; Ellis, P.W.; Houghton, R.A.; Lomax, G.; Mileva, D.A.; Schlesinger, W.H.; Shoch, D.; Slikamaki, A.V.;
Smith, P.; et al. Natural climate solutions. Proc. Natl. Acad. Sci USA 2017,114, 11645–11650. [CrossRef]
15.
Minasny, B.; Malone, B.P.; McBratney, A.-B.; Aners, D.J.; Arrouays, D.; Chambers, A.; Chaplot, V.; Chen, Z.; Cheng, K.; Das, B.B.;
et al. Soil carbon 4 per mille. Geoderma 2017,291, 59–80. [CrossRef]
16.
Gorjian, S.; Ebadi, H.; Trommsdorff, H.M.; Sharon, H.; Demant, M.; Schindele, S. The advent of solar powered electrical
agricultural machinery: A solution for sustainable farm operations. J. Clean. Prod. 2012,292, 126030. [CrossRef]
17.
Searchinger, T.; Waite, R.; Hanson, C.; Ranganathan, J. Creating a Sustainable Food Future; World Resources Institute: Washington,
DC, USA, 2019; Available online: www.wri.org (accessed on 18 February 2023).
18.
Byrne, M.P.; Tobin, J.T.; Forrestal, M.; Danaher, M.; Nkwonta, C.G.; Richards, K.; Cummins, E.; Horgan, S.A.; O’Callaghan, T.F.O.
Urease and nitrification inhibitors as mitigation tools for greenhouse gas emissions in sustainable dairy systems. Sustainability
2020,12, 6018. [CrossRef]
19.
Dimpka, C.O.; Fugice, J.; Singh, U.; Lewis, T.D. Development of fertilizers for enhanced nitrogen use efficiency- trends and
perspectives. Sci. Total Environ. 2020,731, 139111.
20.
Black, J.L.; Davison, T.M.; Box, I. Methane emissions from ruminants in Australia: Mitigation potential and applicability of
mitigation strategies. Animals 2021,11, 957. [CrossRef]
21.
Gupta, K.; Kumar, R.; Baruah, K.K.; Hazarika, S.; Karmakar, D.; Bordoloi, N. Greenhouse gas emissions from rice fields: A review
from Indian context. Environ. Sci. Pollut. Res. 2021,28, 30551–30572. [CrossRef]
Environments 2023,10, 72 13 of 16
22.
Adu-Poku, D.; Ackerson, N.O.B.; Devine, R.N.O.A.; Addo, A.G. Climate mitigation efficiency of nitrification and urease inhibitors:
Impact on N2O emission—A review. Sci. Afric. 2022,16, e01170. [CrossRef]
23.
Ouikhalfan, M.; Lakbita, O.; Delhali, A.; Assen, A.H.; Belmabkhout, Y. Towards net-zero emission fertilizers industry. Greenhouse
gas emissions analyses and decarbonization solutions. Energy Fuels 2022,36, 4198–4223. [CrossRef]
24.
Shukla, P.; Skea, J.; Reisinger, A. (Eds.) Climate Change 2022 Mitigation of Climate Change. In Working Group III Contribution to
the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Intergovernmental Panel on Climate Change: Geneva,
Switzerland, 2022; Available online: https://www.ipcc.ch (accessed on 10 February 2023).
25.
Gao, Y.; Serrenho, A.C. Greenhouse gas emissions from nitrogen fertilizers could be reduced by up to one fifth of current levels by
2050 with combined interventions. Nat. Food 2023,4, 170–178. [CrossRef]
26.
Holka, M.; Bienkowski, J. Carbon footprint and life cycle costs of maize production in conventional and non-inversion tillage.
Agronomy 2020,10, 1877. [CrossRef]
27.
Pazmino, M.L.; Ramirez, A.D. Life cycle assessment as methodological framework for the evaluation of the environmental
sustainability of pig and pork production.in Ecuador. Sustainability 2021,13, 11693. [CrossRef]
28.
Mosterd, P.F.; Bos, A.P.; van Harn, J.; de Jong, J.C. The impact of changing towards higher welfare broiler production systems on
greenhouse gas emissions: A Dutch case study using life cycle assessment. Poultry Sci. 2022,101, 102151. [CrossRef] [PubMed]
29.
Cabot, M.I.; Lado, J.; Sanjuan, N. Multi-season environmental life cycle assessment of lemons: A case study in South Uruguay. J.
Environ. Manag. 2023,326, 116719. [CrossRef]
30.
Solomon, S.; Daniel, J.S.; Sanford, T.J.; Murphy, D.M.; Plattner, G.; Knutti, S.; Friedlingstein, P. Persistence of climate changes due
to a range of greenhouse gases. Proc. Natl. Acad. Sci. USA 2010,107, 18354–18359. [CrossRef] [PubMed]
31.
Myrhe, G.; Shindell, D.; Bréon, F.; Fuglestvedt, J.; Huang, J.; Koch, D.; Lamarque, J.; Lee, D.; Mendoza, B.; Nakajima, T.; et al.
Anthropogenic and natural radiative forcing. In Climate change 2013: The physical science basis. In Contribution of Working Group I to
the Fifth Assessment Report on the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK; New
York, NY, USA, 2013.
32.
Huijbregts, M.A.J.; Steinman, Z.J.N.; Elshout, P.M.F.; Stam, G.; Verones, F.; Viera, M.D.M.; Hollander, A.; Zijp, M.; van Zelm, R.
ReCiPe 2016. In RIVM Report 2016-0104; RIVM: Bilthoven, The Netherlands, 2016; p. 191.
33.
Meyer, M. Desfurane should des-appear: Global and financial rationale. Anesthes. Analges.
2020
,131, 1317–1322. [CrossRef]
[PubMed]
34.
Mashruk, S.; Okafor, I.C.; Kovaleva, M.; Alnasif, A.; Pugh, D.; Hayakawa, A.S.; Valera-Medina, A. Evolution of N
2
O production
at lean combustion condition in NH3/H2/air premixed swirling flames. Combust. Flame 2022,244, 112299. [CrossRef]
35.
Reijnders, L. Positive and negative impacts of agricultural production of liquid biofuels. In Environmental Impacts of Modern
Agriculture; Harrison, R.M., Hester, R.E., Eds.; RSC Publishing: Cambridge, UK, 2012; pp. 150–167.
36. Zhou, C.; Zelinka, M.D.; Dressler, A.E.; Wang, M. Greater committed warming after accounting for the pattern effect. Nat. Clim.
Chang. 2021,11, 132–136. [CrossRef]
37.
Rogelj, J.; Geden, O.; Cowie, A.; Reisinger, A. Three ways to improve net-zero emission targets. Nature
2021
,591, 365–368.
[CrossRef]
38.
Baveye, P.C.; Berthelin, J.; Tessier, D.; Lemaire, G. The ‘4 per 1000
´
initiative: A credibility issue for the soil science community?
Geoderma 2018,309, 116–123. [CrossRef]
39.
Woolf, D.; Amonette, J.F.; Street-Perrott, A.; Lehmann, J.; Joseph, S. Sustainable biochar to mitigate global climate change. Nat.
Commun. 2010,1, 56. [CrossRef]
40.
Verheijen, F.G.A.; Jeffery, S.; van der Velde, M.; Penizek, V.; Beland, M.; Bastos, A.C.; Keizer, J.J. Reduction in soil surface albedo as
a function of biochar application rate: Implications for global radiative forcing. Environ. Res. Lett. 2013,8, 044008.
41.
Minasny, B.; Malone, B.P.; McBratney, A.-B.; Aners, D.J.; Arrouays, D.; Chambers, A.; Chaplot, V.; Chen, Z.; Cheng, K.; Das, B.B.;
et al. Rejoinder to comments on Minasny et al. 2017 soil carbon 4 per mille, Geoderma 292. 59-86. Geoderma
2018
,309, 124–129.
[CrossRef]
42.
Bradford, M.A.; Carey, C.J.; Atwood, L.; Bossio, D.; Fenichel, I.D.; Gennet, S.; Fargione, J.; Fisher, J.R.B.; Fuller, E.; Kane, D.A.; et al.
Soil carbon science for policy and practice. Nat. Sustain. 2019,2, 1070–1072. [CrossRef]
43.
Basile-Doelsch, I.; Balesdent, J.; Pellerin, S. Review and syntheses: The mechanisms underlying carbon storage in soil. Biogeo-
sciences 2020,17, 5222–5242.
44.
Bradford, M.A.; Wieder, W.E.; Bonan, G.B.; Fierer, N.; Raymond, P.A.; Crowther, T.W. Managing uncertainty in soil carbon
feedbacks to climate change. Nat. Clim. Chang. 2016,6, 751–758.
45.
Nottingham, A.T.; Meir, P.; Velasquez, E.; Turner, R.L. Soil carbon loss by experimental warming in a tropical forest. Nature
2020
,
584, 234–237. [CrossRef]
46.
Lugato, E.; Lavallee, J.M.; Haddix, M.L.; Panagos, D.; Cotrufo, M.F. Different climate sensitivity of particulate and mineral
associated soil organic matter. Nat. Geosci. 2021,14, 295–300. [CrossRef]
47.
Heikkinen, J.; Keskinen, R.; Kostensalo, J.; Nuutinen, V. Climate change induces carbon loss of arable soils in boreal conditions.
Glob. Chang. Biol. 2022,28, 3960–3973. [CrossRef]
48.
Bianchi, A.; Larmola, I.; Kekkonen, H.; Saarnio, S.; Lang, K. Review of greenhouse gas emissions by rewetted agricultural soils.
Wetlands 2021,41, 108. [CrossRef]
Environments 2023,10, 72 14 of 16
49.
Tan, Z.D.; Lupascu, M.; Wijedasa, L.S. Paludiculture as a sustainable use alternative for tropical peat lands. Sci. Total Environ.
2021,753, 142111.
50.
Tanneberger, F.; Birr, F.; Couwenberg, J.; Kaiser, M.; Luthardt, V.; Nerger, M.; Pfister, S.; Oppermann, R.; Zeitz, J.; Beyer, C.; et al.
Saving soil carbon, greenhouse gas emissions biodiversity and the economy: Paludiculture as sustainable land use options for
German fern peatlands. Region. Environ. Chang. 2022,69, 22. [CrossRef]
51.
FAO (Food and Agricultural Organization of the United Nations). Global Livestock Environmental Assessment Model. 2018.
Available online: https//www.fao.org./gleam (accessed on 15 February 2023).
52.
Clune, S.; Crossin, E.; Verghese, K. Systematic review of greenhouse gas emissions for different fresh food categories. J. Clean
Prod. 2017,140, 766–781.
53.
Wirsenius, S.; Azar, C.; Berndes, G. How much land is needed for global food production under scenarios of dietary change and
terrestrial productivity increases in 2030. Agric. Syst. 2010,103, 621–638.
54.
Franco-Solis, A.; Montania, C.V. Dynamics of deforestation worldwide: A structural decomposition analysis of agricultural land
use in South America. Land Use Policy 2021,109, 105619.
55.
Pendrill, F.; Garner, T.A.; Meyerfroid, P.; Persson, U.M.; Adams, J.; Azevedo, T.; Lima, M.G.; Baumann, M.; Curtis, P.G.; de Sy, V.;
et al. Disentangling numbers behind. agriculture-driven tropical deforestation. Science 2022,377, 1168.
56.
Interpol. Forest Crime. 2023. Available online: https://www.interpoö.int/crime7environmental-crime/forestry-crime (accessed
on 7 March 2023).
57.
Muthee, K.; Duguma, L.; Wainana, P.; Minang, P.; Nzyoka, J. A review of global policy mechanisms designed for tropical forest
conservation and climate risks management. Front. For. Glob. Chang. 2022,4, 748170.
58.
Bastos Lima, M.G.; Persson, U.M.; Meyfroidt, P. Leakage and boosting effects in environmental governance: A framework for
analysis. Environ. Res. Lett. 2019,14, 105026.
59.
Streck, C. 2021, REDD+ and leakage: Debunking myths and promoting integrated solutions. Clim. Policy
2021
,21, 843–854.
[CrossRef]
60.
Arnold, A.I.M.; Grüning, M.; Simon, J.; Reiinhardt, A.; Lamersdorf, N.; Thies, C. Forest defoliator pests alter carbon and nitrogen
cycles. Roy. Soc. Open Sci. 2016,3, 160361. [CrossRef]
61.
Fei, S.; Morin, R.S.; Ostwalt, C.M.; Liebhold, A.M. Biomass losses resulting from insect and disease invasions in US forests. Proc.
Natl. Acad. Sci. USA 2019,116, 17371–17376.
62. Brodribb, T.; Power, J.; Cochard, H.; Choat, B. Hanging by a thread? Forests and drought. Science 2020,368, 261–266. [CrossRef]
63.
Holzwarth, S.; Thonfeld, F.; Abdullahi, S.; Asam, S.; Da Ponte Canova, E.; Gessner, U.; Huth, J.; Klaus, T.; Leutner, B.; Kuenzer, C.
Earth observation based monitoring of forests in Germany: A review. Remote Sens. 2020,12, 1310.
64.
Van Wees, D.; Van der Werf, G.R.; Randerson, J.T.; Andela, N.; Chen, Y.; Morton, D.C. The role of fire in global forest loss dynamics.
Glob. Chang. Biol. 2021,27, 2377–2391. [CrossRef] [PubMed]
65.
Bendall, E.R.; Bedward, M.; Boer, M.; Clarcke, H.; Collins, L.; Leigh, A.; Bradstock, R.A. Mortality and resprouting responses in
forests driven more by ecosystem characteristics than drought severity and fire frequencies. Forest Ecol. Manag.
2022
,509, 12007.
[CrossRef]
66.
Maja, M.M.; Avano, S.F. the impact on population growth on natural resources and farmer
´
s capacity to adapt to climate change.in
low-income countries. Earth Syst. Environ. 2021,5, 271–283.
67.
Rojas-Downing, M.M.; Nejadhashemi, A.P.; Harrigan, T.; Woznicki, C.A. Climate change and livestock; impacts, adaptation and
mitigation. Clim. Risk. Manag. 2017,16, 145–167.
68.
Palangi, V.; Taghizadeh, A.; Abachi, S.; Lackne, M. Strategies to mitigate enteric methane emissions in ruminants: A review.
Sustainability 2022,14, 132229.
69.
Scherer, L.; Verberg, P.H. Mapping and linking supply- and demand-side measures in climate-smart agriculture. Agronomy
Sustain. Develop. 2017,37, 66.
70.
Pellegrini, P.; Fernandez, R.J. Crop intensification. land use and on-farm energy use efficiency during the worldwide spread of
the green revolution. Proc. Natl. Acad. Sci. USA 2018,115, 2335–2340. [CrossRef]
71.
Reijnders, L. Sustainability of soil fertility and the use of lignocellulosic crop harvest residues for the production of biofuels.: A
literature review. Environ. Technol. 2013,34, 1725–1734.
72.
Sarkar, S.; Skalicky, M.; Hossain, A.; Brestic, M.; Saha, S.; Garai, S.; Ray, K.; Brahmachari, K. Management of crop residues for
improving impact use efficiency and agricultural sustainability. Sustainability 2020,12, 9808. [CrossRef]
73.
Mahlia, T.M.I.; Ismail, N.; Hossain, N.; Silitonga, A.S.; Shamsuddin, A.H. Palm oil and its wastes as bioenergy sources: A
comprehensive review. Environ. Sci. Pollut. Res. 2019,26, 14849–14866.
74.
Dijkman, T.J.; Benders, R.M.J. Comparison of renewable fuels based on their land use using energy densities. Renew. Sustain.
Energy Rev. 2010,14, 3148–3155. [CrossRef]
75.
Nugent, D.; Sovacool, B.K. Assessing the life cycle greenhouse gas e missions from solar PV and wind energy: A critical
meta-survey. Energy Policy 2014,65, 229–244. [CrossRef]
76.
Wang, S.; Wang, S.; Liu, J. Life cycle green-house gas emissions from onshore and offshore wind turbines. J. Clean. Prod.
2019
,210,
804–810. [CrossRef]
77.
Bhandari, R.; Kumar, B.; Mayer, F. Life cycle greenhouse gas emissions from wind farms in reference to turbine size and capacity
factors. J. Clean. Prod. 2020,277, 123385.
Environments 2023,10, 72 15 of 16
78. Tiffin, A.; Tiffin, R. Estimates of food elasticities for Great Britain: 1972–1994. J. Agric. Econ. 1999,50, 140–147. [CrossRef]
79.
Hoang, H.K. Analysis of food demand in Vietnam and short-term impacts of market shocks on quantity and calorie consumption.
Agric. Econ. 2018,49, 83–95. [CrossRef]
80.
Del Pero, F.; Delogu, M.; Pierini, M. Life cycle assessment in the automotive sector: A comparative case study of the internal
combustion engine (ICE) and electric car. Proced. Struct. Integrit. 2018,12, 521–537. [CrossRef]
81. Sahoo, A.U.; Raheman, H. Development of an electric reaper: Clean harvesting machine for cereal crops. Clean Technol. Environ.
Policy 2020,22, 955–964.
82.
Yang, Z.; Wang, H.; Sun, H.; Wang, P.; Cao, Q. Experimental study on electrical harvesting of combine harvester. J. Phys. Conf. Ser.
2022,2218, 012064. [CrossRef]
83.
Zhou, H.; Wang, X.; Au, W.; Kang, H.; Chen, C. Intelligent robots for fruit harvesting; recent developments and future challenges.
Precis. Agric. 2022,23, 1856–1907.
84.
Shine, P.; Upton, J.; Sefeedpari, P.; Murphy, M.D. Energy consumption in dairy farming: A review of monitoring, prediction,
modelling, and analyses. Energies 2020,15, 1288. [CrossRef]
85.
Tangorra, F.M.; Calcante, A. Energy consumption and technical-economic analysis of an automatic feeding system for dairy
farming.: Results of a field test. J. Agric. Engin. 2018,869, 228–232. [CrossRef]
86. Malik, A.; Kohli, S. Electric tractors: Survey of challenges and opportunities in India. Mater. Today Proc. 2020,28, 2318–2324.
87.
Dhyani, S.; Murthy, I.K.; Kadaverugu, R.; Dasgupta, R.; Kumar, M.; Gadpayle, K.A. Agroforestry to achieve global climate
adaptation and mitigation targets. Are South Asian countries sufficiently prepared. Forests 2021,12, 30. [CrossRef]
88.
Giannitsopoulos, M.L.; Graves, A.R.; Burgess, P.J.; Crous-Daran, J.; Moreno, G.; Herzog, F.; Palma, J.H.N.; Kay, S.; de Jalon, S.G.
Whole system valuation of arable, agroforestry and tree-only systems at three case study sites in Europe. J. Clean. Prod.
2020
,
269, 122283. [CrossRef]
89.
Cardinael, R.; Cadish, G.; Gosme, M.; Oelbermann, M.; van Noordwijk, M. climate change mitigation and adaptation in
agriculture: Why agroforestry should be a part of the solution. Agric. Ecosyst. Environ. 2021,318, 107555.
90.
Nath, A.J.; Sileshi, G.; Laskar, S.Y.; Pathal, K.; Rean, D.; Nath, A.; Das, A.K. Quantifying carbon stock and sequestration potential
in agroforestry systems under different management scenarios relevant to India
´
s nationally determined contribution. J. Clean.
Prod. 2021,281, 124831. [CrossRef]
91.
Ma, Z.; Bork, E.W.; Carlyle, C.; Tieu, J.; Gross, C.D.; Chang, S.X. Carbon stocks differ among land uses in agroforestry systems in
Western Canada. Agric. Forest Meteorol. 2022,313, 108756. [CrossRef]
92.
Agevi, H.; Onwonga, R.; Kuyah, S.; Tsingalia, H. Carbon stocks and stock changes in agroforestry practices: A review. Tropic.
Subtropic. Agroecoyst. 2017,20, 101–109.
93.
Kaczan, D.; Arslan, A.; Lipper, L. Climate Smart Agriculture. A Review of Current Practice in Agroforestry and Conservation
Agriculture in Malawi and Zambia. 2013. ESA Working Paper 13-07. Available online: www.fao.org/economic/esa (accessed on
17 January 2023).
94.
Rodenburg, J.; Mollee, E.; Coe, R.; Sinclair, F. Global analysis of yield benefits and risks from integrating trees with rice and
implications for agroforestry research in Africa. Field Crop. Res. 2022,281, 108504. [CrossRef]
95.
Staton, F.; Breeze, T.D.; Walters, R.J.; Smith, J.; Girling, R.D. Productivity, biodiversity trade-offs and farm income in agroforestry
versus an arable system. Ecol. Econ. 2022,191, 107214. [CrossRef]
96.
Kraft, P.; Rizaei, E.E.; Breurer, L.; Ewert, E.; Große-Stoltenberg, A.; Kleinebecker, T.; Seserman, D.M.; Nendel, C. Modelling
agroforestry contributions to people- a review of available models. Agronomy 2021,11, 2106. [CrossRef]
97.
Rohatyn, S.; Rotenberg, E.; Taratinov, E.; Carmel, Y.; Yakir, D. Large variation in afforestation- related cooling and warming effects
across short distances. Commun. Earth Environ. 2023,4, 18. [CrossRef]
98.
Liu, Y.; Tang, H.; Muhammad, A.; Huang, G. Emission mechanism and reduction countermeasures of agricultural greenhouse
gases—A review. Greenhouse Gas. Sci. Technol. 2019,9, 160–174.
99.
Liu, X.; Zhou, T.; Liu, Y.; Zhang, X.; Li, L.; Pan, G. Effect of mid-season irrigation on CH
4
and N
2
O emissions and grain yield in
rice ecosystem: A meta-analysis. Agric. Water Manag. 2019,213, 1028–1039. [CrossRef]
100.
Levi, P.G.; Cullen, J.M. Mapping global flows of chemicals from fossil fuel feedstocks to chemical products. Environ. Sci. Technol.
2018,52, 1725–1734. [CrossRef]
101.
Walling, E.; Vaneeckhaule, C. Nitrogen fertilizers and the environment. In Nitrate Handbook; Tsadilas, C., Ed.; CRC Press: Boca
Raton, FL, USA, 2022; pp. 103–136.
102. Pfromm, P.H. Towards sustainable agriculture: Fossil-free ammonia. J. Renew. Sustain. Energy 2017,9, 034702. [CrossRef]
103.
Soloveichik, G. Electrochemical synthesis of ammonia as potential alternative to the Haber-Bosch process. Nat. Catal.
2019
,2,
377–380. [CrossRef]
104.
Chaanaoui, M.; Abderafi, S.; Vaudreuil, S.; Bounahmidi, T. Prototype of phosphate sludge rotary dryer coupled to a parabolic
trough collector solar loop; integration and experimental analysis. Solar Energy 2021,216, 365–376. [CrossRef]
105.
Beath, A.; Meybodi, M.A.; Drewer, G. Techno-economic assessment of application of particle-based solar thermal systems in
Australian industry. J. Renew. Sustain. Energy 2022,14, 0333702. [CrossRef]
106.
Carlson, K.M.; Gerber, J.; Mueller, N.D.; Herrero, M.; MacDonald, G.K.; Bauman, K.A.; Havlik, P.; O’Connel, C.S.; Johnson, J.A.;
Saatchi, S.; et al. Greenhouse gas emissions intensity of agricultural crop land. Nat. Clim. Chang. 2017,7, 63–68. [CrossRef]
Environments 2023,10, 72 16 of 16
107.
Anas, M.; Liao, F.; Verma, K.K.; Sarwar, A.-A.; Mahmood, A.; Chen, Z.; Li, Q.; Zeng, X.; Liu, Y.; Li, Y. Fate of nitrogen in agriculture
and environment: Agronomic, eco-physiological and molecular approaches to improve nitrogen use efficiency. Biol. Res.
2020
,
53, 47. [CrossRef]
108.
Sharma, L.K.; Bali, S.K. A review of methods to improve nitrogen use efficiency in agriculture. Sustainability
2018
,10, 51.
[CrossRef]
109.
Zhang, X.; Davidson, I.A.; Mauzerall, D.L.; Searchinger, T.D.; Dumas, P.; Shen, Y. Managing N for sustainable development.
Nature 2015,528, 51–59. [CrossRef] [PubMed]
110.
Folina, A.; Tataridas, A.; Mavroeidis, A.; Kausta, A.; Katsenios, N.; Efthimiadou, A.; Travlos, I.S.; Roussos, I.; Darawsheh, M.K.;
Papastylianou, P.; et al. Evaluation of various nitrogen indexes in N fertilizers with inhibitors in field cops. Agronomy
2021
,
11, 418. [CrossRef]
111.
Woodward, E.E.; Edwards, T.M.; Givens, C.E.; Kolpin, D.W.; Hladik, M.L. Widespread use of the nitrification inhibitor nitrapyrin;
assessing benefits and costs to agriculture, ecosystems, and environmental health. Environ. Sci. Technol.
2021
,55, 1345–1353.
[CrossRef]
112.
Beeckman, F.; Motte, M.; Beeckman, T. Nitrification in agricultural soils: Impact, actors and mitigation. Curr. Opin. Biotechnol.
2018,50, 166–173. [CrossRef]
113.
Li, W.; Xiao, Q.; Hu, C.; Sun, R. A comparison of the efficiency of different urease inhibitors on soil prokaryotic community in a
short-term incubation experiment. Geoderma 2019,354, 113877. [CrossRef]
114.
Jiang, D.; Jiang, N.; Jiang, H.; Chen, L. Urease inhibitors increased soil ureC gene abundance and intracellular urease activity
when extracellular urease activity was inhibited. Geoderma 2023,430, 116295. [CrossRef]
115.
Liu, T.; Zheng, S.; Yu, L.; Bu, K.; Yang, J.; Chang, L. Simulation of regional temperature change effect on land cover change in
agroforestry ecotone of Nenjang river basin in China. Theoret. Appl. Climatol. 2017,128, 971–981. [CrossRef]
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