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2016 Environ. Res. Lett. 11 094003

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Environ. Res. Lett. 11 (2016) 094003 doi:10.1088/1748-9326/11/9/094003

LETTER

The importance of climate change and nitrogen use efficiency forfuture nitrous oxide emissions from agriculture

DavidRKanter1,7, XinZhang2,8, Denise LMauzerall3,4, SergeyMalyshev5 andElena Shevliakova6

1 Department of Environmental Studies, NewYorkUniversity, 285Mercer Street, 9thfloor, NewYork,NY, 10003,USA2 University ofMarylandCenter for Environmental Science, Appalachian Laboratory, 301 BraddockRoad, Frostburg,MD21532,USA3 WoodrowWilson School of Public and International Affairs, 445RobertsonHall, PrincetonUniversity, Princeton,NJ, 08544, USA4 Department of Civil and Environmental Engineering, E412 E-Quad, PrincetonUniversity, Princeton,NJ 08544,USA5 Department of Ecology and Evolutionary Biology, 106AGuyotHall, PrincetonUniversity, Princeton,NJ 08544,USA6 National Oceanic andAtmospheric AdministrationGeophysical FluidDynamics Lab, Climate andEcosystemsGroup, 201 Forrestal

Road, Princeton,NJ, 08540, USA7 Themajor portion of the research presented in this paper was done as part ofDavid RKanter’s PhD at theWoodrowWilson School of

Public and International Affairs at PrincetonUniversity, under the supervision of his PhD advisor, Denise LMauzerall.8 Themajor portion of the research presented in this paper was donewhile Xin Zhangwas a postdoctoral research associate at the

WoodrowWilson School of Public and International Affairs at PrincetonUniversity, under the supervision ofDenise LMauzerall.

E-mail: david.kanter@nyu.edu andmauzeral@princeton.edu

Keywords:nitrous oxide, agriculture, CO2, fertilization, nitrogen use efficiency

Supplementarymaterial for this article is available online

AbstractNitrous oxide (N2O) is an important greenhouse gas and ozone depleting substance. Previousprojections of agricultural N2O (the dominant anthropogenic source) show emissions changing intandem, or at a faster rate than changes in nitrogen (N) consumption.However, recent studies suggestthat the carbon dioxide (CO2) fertilization effectmay increase plantNuptake, which could decreasesoil N losses and dampen increases inN2O. To evaluate this hypothesis at a global scale, we use aprocess-based landmodel with a coupled carbon-nitrogen cycle to examine how changes in climaticfactors, land-use, andN application rates could affect agriculturalN2O emissions by 2050. Assuminglittle improvement inNuse efficiency (NUE), themodel projects a 24%–31% increase in globalagricultural N2O emissions by 2040–2050 depending on the climate scenario—a relativelymoderateincrease compared to the projected increases inN inputs (42%–44%) and previously publishedemissions projections (38%–75%). This occurs largely because theCO2 fertilization effect enhancesplantNuptake in several regions, which subsequently dampensN2O emissions. And yet,improvements inNUE could still deliver important environmental benefits by 2050: equivalent to10 PgCO2 equivalent and 0.6 Tg ozone depletion potential.

Introduction

Agrowingbodyof scientists andpolicy experts argue thatN2O, the third most important greenhouse gas (GHG)and the most abundantly emitted ozone depletingsubstance, requires more focused attention from theinternational policy community [1–3]. Humanity’s abil-ity to produce synthetic nitrogen (N) fertilizer via theHaber-Bosch process has dramatically increased Nconcentrations in agricultural soils, bolstering the majorbiogeochemical processes that produce N2O: nitrifica-tion (the conversion of ammonium +( )NH4 to nitrate

-( )NO3 ), and denitrification (the conversion of -NO3 to

atmospheric dinitrogen (N2)). Supplemented by non-agricultural emission sources such as industry, energyproduction and transport, atmospheric concentrationsof N2O have increased from mid-19th century levels ofapproximately 275 ppb to 328 ppb in 2015 [4]. Agricul-ture is the dominant source, responsible for two thirds ofgross anthropogenic emissions, and the focus of thisstudy [5].

However, N2O is not only an important GHG thatexacerbates climate change; its emissions are alsoaffected by climate change. Rising temperatures, shift-ing precipitation patterns, and increasing atmosphericCO2 concentrations all impact N2O emissions in a

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variety ways that are still being studied [6]. Conse-quently, this study uses a process-based land model(Princeton-GFDL LM3 N.1, which captures vegeta-tion, hydrological, carbon (C) and N dynamics [7, 8])to examine both the potential climate and ozone bene-fits of reducing agricultural N2O emissions at a globalscale, and the direct and indirect effects of future cli-mate change scenarios onN2O emission rates.

The LM3N.1model allows us to simulate both theprocesses that directly control agricultural N2O emis-sions (such as temperature and soil water content),and the indirect effects such as crop N uptake thatchange under different climate, N consumption, andatmospheric CO2 concentration scenarios. Climatechange is expected to impact all of these effects. Risingsoil temperatures induced by climate change will likelyincrease the rate of soil organicmatter decomposition,releasing more mineral N into the soil, and therebymake more N available for nitrification and deni-trification—the major biogeochemical processes thatproduce N2O [9]. Meanwhile, nitrification and deni-trification are a function of oxygen levels in the soil,which are inversely proportional to soil water content.Soil water content is a function of soil topography, tex-ture, and the balance between precipitation and eva-potranspiration [10]. Therefore, the effect of shiftingprecipitation patterns and rising temperatures couldimpact nitrification and denitrification rates across theglobe.

In addition to these direct effects, there is evidenceto suggest that increasing atmospheric CO2 con-centrations have an indirect effect on N2O emissions[6]. The CO2 fertilization effect has been shown todecrease N2O emissions by increasing plant N and Cuptake, which can reduce N losses, including N2O[11]. Themagnitude and persistence of the CO2 fertili-zation effect depends on the availability of mineral Nand the ability of plants to acquire it. Hence, previousmodeling and empirical studies have focused on theeffects of N limitation on CO2 fertilization in naturalecosystems and pasturelands. These land systems areoften characterized by limited N inputs, and thus Nlimitation is believed to be the main limiting factor ontheir C storage capacity [9, 12–15]. N limitation is animportant issue, particularly for natural ecosystems,where the main sources of N inputs (biological N fixa-tion and N deposition) may not be able to sustainincreased plant demand forN stimulated by CO2 ferti-lization [6]. However, in intensive agricultural systems(the dominant source of anthropogenic N2O emis-sions), N limitation is usually not a concern; there is, infact, an excess supply of N, largely from synthetic ferti-lizers and manure [16]. Therefore, without N limita-tion cropping systems in certain regions could bemore able to take advantage of the CO2 fertilizationeffect and potentially increase their yields by up to20% [17], improving N use efficiency (NUE) andwater use efficiency [18] albeit with a possible dete-rioration in key micronutrient levels [19]. If certain

cropping systems can increase yields as a result of theCO2 fertilization effect, this could then reduce excessN in soils, thereby potentially reducing agricultural Nlosses and N2O emissions. This paper evaluates thishypothesis for the first time at a global scale under dif-ferent climate scenarios. It builds on previous studiesthat have analyzed future N2O emissions using otherprocess-based land models [20] by explicitly dis-aggregating the impacts of climate, CO2 concentra-tions andN inputs on agricultural biomass growth andagriculturalN2O emissions.

The other focus of this study is to better under-stand the mitigation potential of agricultural N2Oemissions via improvements in global NUE. Pre-viously published scenarios of global NUE improve-ments and their impacts on agricultural N2Oemissions in the 21st century have relied primarily onmodifiedN2O emission factors and projections of glo-bal N fertilizer demand based on assumptions that areoften opaque [3, 16, 20–22]. While these projectionsare useful in generating order of magnitude estimatesof future N2O emissions, they do not simulate theeffects of farmer N management practices that ulti-mately determineNUE. In the only other study to haveevaluated future NUE scenarios using a process-basedglobal landmodel [20], the assumptions underpinningthe ambitious NUE improvement scenario are notclear. By contrast, this study builds on previous workby representing the effects of farmer N managementpractices that underpin NUE improvements using theLM3-N.1 model. While this is by no means the firstprocess-based landmodel with a coupled C–N cycle tosimulate the effects of farmer Nmanagement practicesonN cycle dynamics [23], we believe it is the first to doso with the goal of projecting future agricultural N2Oemissions under different climate and NUE scenarios.This could lead to amore complete assessment of howimprovements in global NUE will affect N2O emis-sions, and thus the climate and stratospheric ozonebenefits that could follow.

PrincetonGFDL-LM3N.1model

To conduct our analysis we introduce a new N2O fluxfunction based on Xu-Ri and Prentice into the LM3-N.1 model [24]. This model captures vegetation, C, Nand water dynamics and was developed by PrincetonUniversity and the National Oceanic and AtmosphericAdministration’s (NOAA) GFDL [7]. The N sub-model couples each C pool in vegetation and the soilwith a N compartment [8]. The model allows for Nlimitation on plant growth and CO2 assimilation,includes processes such as N fixation, leaching (bothmineral and organic), N volatilization from fire, Nplant uptake, mineralization, nitrification, denitrifica-tion and hydrological and gaseous N export. Globalto site-scale evaluations of this model have beenpresented in previous work [7, 8]. The general

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Environ. Res. Lett. 11 (2016) 094003

denitrification function is adapted from Heinen [25]and was first introduced into LM3-N.1 and evaluatedin Lee et al [26]:

= ´ ´ ´ -D k W T C ,d d d NO3

kd=denitrification rate coefficient (yr−1)Wd=soil water content function (dimensionless)Td=soil temperature function (dimensionless)

-CNO3= soil -NO3 concentration (kg

-–NO N3 m−2).The focus on soil temperature, water content and-NO3 concentrations emulates the approach of several

other global denitrification models [27, 28]. The effectof labile C availability is reflected in the denitrificationrate coefficient [29–31]. Meanwhile, the N2O fluxfunction is adapted fromXu-Ri and Prentice [24]:

= ´ ´ + ´( ) ( )F T FN O D Nit ,2 denit N O nit2

Fdenit=Proportion of denitrification flux which isconverted to N2O (0.02) independent of the temper-aturemodifier (TN2O)

D=Denitrification rate (kgNm−2 yr−1)

=´ - +( )⎡

⎣⎢⎤⎦⎥T e TN O

308.56 168.02

146.02

2(T is in degrees

Celsius)Fnit=Proportion of nitrification flux which is

converted toN2O (fixed at 0.001)Nit=Nitrification rate (kgNm−2 yr−1).See supplementary information section 1 formore

detail on each individual parameter.To evaluate these functions, we simulate agri-

cultural N2O emissions from 1990 to 2000 and findthat our emission estimates are largely consistent withother model simulations and bottom-up inventories(see supplementary information section 1 for a modelevaluation and sensitivity analysis). The denitrificationfunction was also previously evaluated at the water-shed scale, comparingmodel output with data from 16monitoring stations in the Susquehanna River Basin.It was shown to capture fluxes well at multiple loca-tions within the basin with different climate regimesand land-use types [26].

We define agricultural N2O emissions as directand indirect N2O emissions (the latter fromN leachedinto waterways and N deposition) from cropland andpasture, excluding manure management. Manuremanagement is not currently simulated as emissionsfrom this sector occur during the collection, handling,storage, and treatment of manure, practices that arenot yet explicitly integrated into the model. The expli-cit simulation of indirect N2O emissions is currently indevelopment for LM3-N.1 and partially implementedin this study. While indirect N2O emissions from Ndeposition are currently simulated (as the N depositedon land becomes part of the soil NH4

+ and -NO3 poolswhich impact nitrification and denitrification fluxes),indirect emissions from N leaching are not. Conse-quently, for this study we follow a similar approach toother recent process-based land model simulations[20] and apply the IPCC emission factor for indirect

N2O emissions from N leaching (0.75% of leachedmineral N is emitted as N2O [32]). The dynamics offertilizer and manure N application to cropland andpasture used in this study are described in supplemen-tary information section 2.

Climate andNUE scenarios

For model simulations from 1990–2000 to 2040–2050we use a global fertilizer and manure dataset fromBouwman et al (described in detail in supplementaryinformation section 2) under two climate and land-use change scenarios [33]. These scenarios are Repre-sentation Concentration Pathway (RCP) 2.6, repre-senting a highly ambitious climate mitigation scenariothat maintains the possibility of reaching the 2 °Ctarget, and RCP 8.5, a high emission/business-as-usual (BAU) scenario [34, 35]. The latter approximatesthe path theworld is currently following.

In addition to simulating BAU agricultural N2Oemissions, a central goal of this study is to betterunderstand the potential environmental benefits ofimproving global NUE. Here we evaluate the impactsof a moderate (20%) and an ambitious (50%) increaseinNUEby country by 2050 under both climate scenar-ios. These targets are based on results from previousstudies of NUE improvements in cereal production,using a combination of plant breeding, proper tech-nology and incentives [36–39]. NUE is measured inthis study using partial factor productivity(kg C kg N−1), one of the most widely used and easilymeasured NUE metrics, which measures the ratio ofcrop yield per unit of applied N [40]. All agriculturalbiomass in the model is represented as either a C3 orC4 grass type (determined as a function of climate,with C3 grasses more prevalent in temperate zonesand C4 grasses more prevalent in tropical zones [7]),which precludes crop-specific analysis, a drawbackshared by several similar models [6, 20] and an activearea of model development. Net primary productivityon agricultural land is currently considered propor-tional to crop yields in themodel, and is calculated as afunction of gross primary productivity, growth andmaintenance respiration, and N limitation [8]. Allaboveground C and N in leaves and labile stores oncropland is annually harvested and released back to theatmosphere the following year. In pasture, 25% of leafC and N is annually removed to represent livestockgrazing and partitioned between a livestock respira-tion fraction (0.9) and a grazing residue fraction (0.1)that is returned to the soil pools. Given this relativelysimplistic representation of agricultural activities cur-rently in LM3 N.1, it is not possible to explicitly simu-late specific agricultural management practices such asimproving crop cultivars or using enhanced efficiencyfertilizers. Instead, we evaluate three more basicapproaches for achieving global NUE improvementsof 20% and 50%, which represent the effects of a suite

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Environ. Res. Lett. 11 (2016) 094003

of improved Nmanagement strategies that better syn-chronize soil N supplywith cropNdemand:

(1)Reduced N inputs: fertilizer and manure applica-tion rates are reduced to achieve a 20% and 50%increase in NUE on a country-by-country basisby 2050.

(2) Increased N uptake: plant N uptake is increased by20%and 50%by 2050.

(3)Combined: a combination of the reduced N inputand increasedNuptake strategies.

See supplementary information section 4 for moredetail on these approaches, including a description ofthe most commonly used NUE-improving best man-agement practices and technologies. It should also benoted that we are focusing on NUE at the field-level(an approach taken by similar studies [20, 33]). How-ever, in reality N can continue to cascade through theenvironment, from field to feedlot and ultimately tothe consumer’s plate, with N losses throughout. Newmetrics are emerging to estimate NUE across theentire supply chain inwhichNuse occurs, notably ‘fullchain NUE’ [16]. While these efforts are important,the focus of this study is on in-field NUE given thecapacity of ourmodel.

Experimental set-up

The model was spun up for 1000 years with preindus-trial climate forcing (using atmospheric CO2 concen-trations of 280 ppm) starting from bare groundwithout C–N coupling (i.e. a plant’s capacity tophotosynthesize was not limited by N concentrationsin the soil) in order to accelerate vegetation growth. C–N coupling was then initiated and the spin-upcontinued for an additional 400 years to reach steadystate. The model runs analyzed in this paper werebegun in 1860 using historical CO2 concentrations[41], high frequency forcings obtained from GFDL-ESM2 model output (temperature, wind, short- andlong-wave downward radiation, specific humidity,and precipitation [42]) and the Bouwman et al fertili-zer andmanure data beginning in 1900. Depending onthe run, forcings from RCP 2.6 or RCP 8.5 using theGFDL-ESM2 simulations were used from 2006onwards, and modified Bouwman et al fertilizer andmanure data were used to represent the various NUEscenarios (see supplementary materials section 1–3).Land usewas prescribed fromHurtt et al [43].

Results and discussion

Agricultural N2O emissions in 2040–2050 assuminglittle improvement inNUEUnder the baseline fertilizer andmanure consumptionscenario [33], which assumes little improvement in

global NUE by 2050 (see supplementary informationsection 2), our model projects a 24%–31% increase inagricultural N2O emissions: from 2.9 Tg N2O-N yr−1

in 1990–2000 to 3.6 and 3.8 Tg N2O-N yr−1 by2040–2050 for the RCP 2.6 and RCP 8.5 scenarios,respectively. Figure 1 globally maps the increases inemissions from 1990–2000 to 2040–2050 for the RCP8.5 scenario (equivalentmaps for RCP 2.6 are includedin supplementary information section 5). The mostsignificant increases in N2O emissions are concen-trated in regions with rapidly increasing N input rates,driven by sustained population growth and foodproduction (e.g. India, sub-Saharan Africa) over thefirst half of the 21st century.

Nevertheless, changes in N input rates only partlyexplain future emission trends. There are severalregions in figure 1 where N inputs are projected toincrease considerably, but N2O emissions are not. Alikely explanation is that the CO2 fertilization effectenhances agricultural biomass growth in regionswhere N is not limiting, which subsequently absorbs asignificant portion of the increased N inputs, leavingless excess N to be lost as N2O. In northeast China, forexample, N input rates are projected to increase by upto 50 kg N ha−1 yr−1 by 2040–2050 (a 30% increaserelative to 1990–2000 levels) and yet N2O emissionsare projected to rise less than 0.3 kg N2O-N ha−1 yr−1

(a 10% increase). Meanwhile, agricultural biomass isprojected to increase by over 0.2 kg Cm−2 yr−1 (a 50%increase relative to 1990–2000 levels), indicating thatmuch of the projected increase in N input is absorbedby an increase in crop yields. A similar dampeningeffect of agricultural biomass growth on agriculturalN2O emissions can be seen in other important agri-cultural regions such as northeastern and southernIndia, and southeastern SouthAmerica.

The LM3 model attributes approximately 80% ofthe globally projected agricultural biomass growth by2040–2050 to the CO2 fertilization effect and 24% toincreases in N inputs, while changes in soil temper-ature and precipitation patterns alone lead to a 4%decrease in global agricultural biomass growth (seesupplementary information section 8). The dom-inance of the CO2 fertilization response over thewarming response concurs with empirical experi-ments that have evaluated these effects [44]. The CO2

fertilization effect increases agricultural biomass levelsby about 20% in RCP 8.5 and 10% in RCP 2.6 by2040–2050 compared to model runs where atmo-spheric CO2 concentrations are kept at 1990–2000levels, which is within the range of previous estimates[17, 45, 46]. This increase in agricultural biomassgrowth takes upN that could otherwise be lost as N2O.Indeed, without the CO2 fertilization effect, we projectthat global agriculturalN2O emissionswould be 0.5 TgN2O-N yr−1 higher in 2040–2050, consistent with pre-viously reported values [6]. A similar phenomenon isseen for RCP 2.6 (supplementary information section5; see also section 6 for an analysis of the differences in

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Environ. Res. Lett. 11 (2016) 094003

Figure 1.Changes in annual agricultural N2O emissions, N inputs, and biomass growth rates between 2040–2050 and 1990–2000 inthe BAURCP8.5 scenario (per hectare of agricultural area). The red (blue) coloring indicates greater (lesser) values in 2040–2050. Inseveral regions, such as northeast China,much of the increase inN inputs is absorbed by increased agricultural biomass growth,leading to relativelyminor increases (and even decreases) inN2Oby 2040–2050 relative to 1990–2000 levels. According to the LM3model, the primary explanation for this increase in biomass growth is CO2 fertilization; the effects of climate change (i.e. shiftingtemperature and precipitation patterns) have either aminimal or positive impact on agricultural biomass growth in these regions.

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Environ. Res. Lett. 11 (2016) 094003

Figure 2.Changes in agricultural N2O emissions, biomass growth andNUE across the differentNUE scenarios and the threeimplementation approaches for RCP 8.5 in 2040–2050.While the combined reducedN input/improvedNuptake scenarios aremosteffective in terms of reducingN2O and increasingNUE, the improvedNuptake scenarios aremost effective in terms of increasingagricultural biomass growth.Nevertheless, the effectiveness of the improvedNuptake scenario is limited by howNuptake isrepresented in themodel (supplementary information section 8).

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Environ. Res. Lett. 11 (2016) 094003

N2O emissions between RCP 2.6 and RCP 8.5). Acommon feature of the regionswhere CO2 fertilizationis most pronounced (e.g. northeast China)—and thuswhere N2O emissions are most dampened—is that theeffects of climate change (i.e. shifting temperature andprecipitation patterns) have either a minimal or posi-tive impact on agricultural biomass growth (figureS10). Nevertheless, it should be noted that CO2 fertili-zation only dampens N2O emissions during the grow-ing season; a significant proportion of annual N2Oemissions have been shown to occur during periodswhen agricultural land is bare (i.e. directly followingfertilizer application or off-season during freeze-thawsevents and post-harvest [47]), periods that are repre-sented in the LM3 model. However, intra-annualvariability is less important for the purposes of thisstudy given our focus on decadal time-scales.

The dampening effect that agricultural biomassgrowth has on agricultural N2O emissions in certainregions suggests that simply applying N2O emissionfactors to projected N input rates might overestimatefuture emissions. For example, applying the David-son emission factors (approximately 2% for manureand 2.5% for fertilizer) to the Bouwman et alN inputprojections suggests a 42%–44% increase in agri-cultural N2O emissions across the RCPs by 2040–2050relative to 1990–2000, which is substantially larger

than the 24%–31% increase projected in this study[33, 48]. Our results also contrast with the results pub-lished in Stocker et al using the LPX-Bern Earth Sys-temModel of intermediate complexity, which projectsthe relative increase in agricultural N2O emissions by2040–2050 (38%–75%) to be greater than the relativeincrease in N inputs (20%–60%) which is counter toour findings [20]. While they do not offer an explana-tion for this dynamic, we believe the differences stemfrom the fact that the balance in their model betweenclimatic factors that enhance N2O emissions (e.g. ris-ing surface temperatures that can increase soil Nmineralization and ultimately denitrification rates)and those that dampen emissions (i.e. the CO2 fertili-zation effect) skew towards the former, while the bal-ance in LM3-N.1 skews towards the latter. Moreresearch in this area is necessary to better understandwhich of the climatic drivers of N2O emissions can beexpected to dominate in the future.

Impact of globalNUE increases on futureagricultural N2O emissionsDespite the impact of the CO2 fertilization effect,improving NUE could still lead to significant reduc-tions in agricultural N2O emissions, depending on thetarget set and the implementation strategy used.Figure 2 shows the impact of each NUE improvement

Figure 3.Reductions in agricultural N2O emissions between the RCP 8.5 BAU scenario and theNUE50% scenario implementedusing the combined reducedN input/improvedNuptake approach. Reductions are concentrated in regions that are projected to havehighest N input rates in 2040–2050, such as India, China, eastern SouthAmerica, theMidwest US and sub-SaharanAfrica.

Table 1.The cumulative environmental benefits generated from achieving the 20%and 50% improvements in global NUE (integrated overthe period 2015–2050) using the ‘improvedNuptake’, ‘reducedN input’ and ‘combined’ implementation approaches. These benefits arereported in terms of reductions inN2O emissions (TgN2O-N), climate forcing (PgCO2 eq.) and stratospheric ozone depletion (TgODP).The lower bound of the uncertainty rangemarks the benefits from achieving theNUE20% scenario and the upper boundmarks the benefitsfrom achieving theNUE50% scenario. The results represent the range of benefits achievable across bothNUE scenarios and the RCPscenarios.

NUE approach Nitrous oxide (TgN2O-N) Climate (PgCO2 eq.) Ozone (TgODP)

ImprovedNuptake 0.4–2.6 0.2–1.2 0.01–0.07

ReducedN inputs 13.7–17.5 6.4–8.2 0.4–0.5

Combined 14.0–21.2 6.6–9.9 0.4–0.6

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Environ. Res. Lett. 11 (2016) 094003

and implementation strategy on global N2O emis-sions, agricultural biomass growth, and NUE forthe RCP 8.5 scenario. RCP 2.6 has similar results(supplementary information sections 5 and 8). Thelargest N2O reductions are achieved with the scenariothat combines N input reductions and N uptakeincreases (reducing emissions to 2.8 Tg N2O-N yr−1

in 2040–2050, a 28% reduction in emissionscompared to the baseline scenario). In this scenario,agricultural biomass growth is slightly reducedrelative to the baseline scenario (25.3 Pg C yr−1 versus26.4 Pg C yr−1). However this is still a 24% increase inagricultural biomass growth from 1990–2000 levels,with 24% less N inputs (see figure 3 for spatialdistribution of N2O reductions). Reductions are con-centrated in regions that are projected to have thehighest N input rates in 2040–2050.

Stratospheric ozone and climate benefits

The different NUE approaches produce a range ofenvironmental benefits over 2015–2050 (table 1). Thehighest mitigation potential comes from a combina-tion of the reduced N inputs/improved N uptakeapproach and switching from a RCP 8.5 to a RCP 2.6forcing scenario. In this case, emissions in 2040–2050are 2.7 Tg N2O-N yr−1 (instead of 3.9 Tg N2O-N yr−1,a 31% reduction), with cumulative savings of 21.2 TgN2O-N over 2015–2050, equivalent to 9.9 Pg CO2 eq.and 0.6 Tg ODP. These estimates do not take intoaccount the other indirect environmental and healthbenefits that could result from reducing N pollution,namely improved water quality from less N leachingand a reduction in air pollution due to decreases inNH3 and NOx volatilization. A more holistic assess-ment of the entire N cascade is an area of active modeldevelopment. In addition, a better representation ofagricultural crops and practices is also being developedfor the LM3-N.1 model. This will allow for a morenuanced and realistic evaluation of NUE scenarios,with an ability to analyze the effect of different fertilizerbest management practices and technologies in differ-ent climates and growing cultures.

With growing calls for an effective internationalframework to manage N pollution, policy-makersrequire scientific information on a range of issues tobetter evaluate policy options. This study has attemp-ted to contribute to this need for policy-relevant sci-ence by demonstrating the importance of climaticfeedbacks in determining future agricultural N2Oemissions, and that increasing NUE can deliverimportant global environmental benefits. This is animportant step if humanity hopes to return within asafe planetary boundary for nitrogen.

Author contributionsDRK, XZ, DLM, SM and ES designed the study,

analyzed the data, and wrote the paper. DRK, SM andES designed the model experiments. DRK and XZ

designed and performed the model evaluation andsensitivity analysis. DRK wrote the new code and ranthemodel.

Competing interestsWehave no competing interests.

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