Baseline scenarios of global environmental change

43 Pages·2003·3.31 MB·English

Pergamon
detmrP m Great .nuirB llA sthgir reserved
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enilesaB soiranecs fo
labolg latnemnorivne
egnahc
J Alcamo, G J J Kreileman, J C Bollen, G J van den
Born, R ,hgalreG M S Krol, A M C Toet and H J M
de seirV
tI is elbissopmi ot etaulave seicilop ot tcetorp eht labolg etamilc and
This paper presents three enilesab
tnemnorivne tuohtiw a kramhcneb fo on‘ .’noitca hcuS a kramhcneb is
soiranecs of no policy action computed
by the EGAMI 2 model. These soiranecs dedeen ot etaulave eht secneuqesnoc fo ton ,gnitca and ot assess eht
cover a wide range of coupled global dedda eulav fo gnitpoda seicilop ot tcetorp eht labolg .tnemnorivne ehT
change indicators, including: ygrene
main evitcejbo fo this repap is ot tneserp a tes fo enilesab soiranecs that
demand and consumption; food demand,
consumption, and production; changes in etartsulli eseht kramhcneb snoitidnoc fo labolg latnemnorivne .egnahc
land cover including changes in extent of eW llac meht ’detargetni‘ soiranecs esuaceb yeht evig an detargetni
agricultural land and forest; emissions of
erutcip fo labolg stnempoleved spanning a ediw egnar fo labolg egnahc
greenhouse sesag ozone ;srosrucerp
and climate change and its impacts on ,srotacidni hcae fo hcihw era ylticilpxe .delpuoc ehT soiranecs edulcni
aes level ,esir crop productivity and noitamrofni tuoba yteicos detaler gnivird secrof hcus as ygrene and
natural vegetation. oiranecS information
doof ,noitpmusnoc as llew as snoissime fo rojam labolg ria ,stnatullop
si available for the entire world with
regional and grid elacs detail, and covers and segnahc ni eht etats fo eht labolg ,cirehpsomta lairtserret and cinaeco
from 0791 to .0012 The soiranecs indicate .stnemnorivne fO ,esruoc eht soiranecs era raf morf gnieb a -neherpmoc
that the coming sedaced could be a
evis noitpircsed fo eht labolg ,tnemnorivne tub rieht ediw epocs and
period of relatively rapid global
environmental change sa compared to cihpargoeg noitpircsed fo eht labolg latnemnorivne egnahc is euqinu ni
the period before and .relfa The natural eht cifitneics .erutaretil yehT evah tneiciffus liated rof esu as ecnerefer
vegetation in industrialized regions could
soiranecs ni a ediw egnar fo ycilop and cifitneics ,snoitaulave and era
be threatened by climate change, but
abandonment of agricultural lands could desu rof this esoprup ni rehto srepap ni this ’.eussi
osla ekam new lands available for esuaceB fo eht taerg ytniatrecnu fo gnihsilbatse erutuf enilesab ,snoitidnoc
refore5taGon and revegetation. The
ew tneserp eerht evitanretla .soiranecs hcaE oiranecs senimaxe eht -esnoc
opposite si true for most of aisA and
.acirfA ereH the impacts of climate secneuq no labolg latnemnorivne egnahc fo a tnereffid tes fo ton‘ -isualpmi
change on vegetation yam not be sa ’elb stnempoleved fo ,noitalupop ,ymonoce and rehto gnivird :secrof
significant sa in temperate ,setamilc but
the demand for food will dael to a 0 is an etaidemretni oiranecs htiw muidem assumptions
Baseline A
significant expansion of agricultural lands
tuoba noitalupop ,htworg cimonoce ,htworg and cimonoce ;ytivitca
at the esnepxe of remaining forests and
other natural .saera Copyright ((1 6991 0 Baseline B has rewol setamitse fo all gnivird secrof derapmoc ot A;
reiveslE ecneicS Ltd has eht emas etamitse rof noitalupop htworg as A, tub
l Baseline C
rehgih setamitse fo cimonoce ,htworg and cimonoce .ytivitca
J Alcamo is with eht ytisrevinU fo Kassel,
;ynamreG R Gerlagh with eht Free ,retaL eht assumptions fo eseht soiranecs era denimaxe ni .liated
ytisrevinU fo Amsterdam dna eht rehto
A rojam egnellahc ni gnipoleved soiranecs fo labolg latnemnorivne
authors are with The National etutitsnI fo
Public Health dna ,tnemnorivnE The egnahc is woh ot maintain rieht .ycnetsisnoc sihT is yltrap devlos ni this
Netherlands. repap yb using an detargetni ledom fo eht labolg ,tnemnorivne EGAMI
2, rof gnitareneg eseht .soiranecs ehT ledom is a loot rof gnihsilpmocca
The authors are detbedni ot C Battjes, R
Leemans, dna F Kaspar for contributions a erusaem fo ynomrah neewteb eht ynam etarapsid stnenopmoc fo eht
ot this .repap This krow has neeb .soiranecs ehT laog fo EGAMI 2 is ot edivorp a yranilpicsid and
supported yb eht Dutch yrtsiniM fo
cihpargoeg weivrevo fo labolg latnemnorivne .segnahc ehT ledom is
Housing, Physical Planning dna eht
continued no egap 262 debircsed ni ’,omaclA and a feirb weivrevo is nevig .woleb
162
Baseline scenarios fo global environmental change: J Alcamo et la
dohteM dna assumptions rof gnitupmoc soiranecs
The IMAGE 2 model
Assumptions tuoba ,noitalupop ,ymonoce and cimonoce ytivitca era eht
gnivird secrof fo soiranecs ni this .repap desaB no eseht assumptions,
EGAMI 2 setupmoc erutuf segnahc ni eht noitpmusnoc fo ,ygrene ,doof
and .rebmit sihT noitpmusnoc sdael ot snoissime ot eht erehpsomta
morf leuf noitsubmoc and lairtsudni ,noitcudorp stfihs ni land esu and
land ,revoc and segnahc ni eht sexulf fo gases morf eht lairtserret -rivne
.tnemno ehT snoissime and sexulf fo gases dael ot segnahc ni eht -omta
cirehps noitisopmoc fo suoirav gases, as llew as segnahc ni eht xulf fo
taeh and erutsiom neewteb eht ,lairtserret cinaeco and cirehpsomta -rivne
.stnemno yllautnevE eseht sexulf tceffa lanoiger ,etamilc and eseht
continued from egap 162
,tnemnorivnE dna eht Dutch National segnahc ni lanoiger etamilc neht kcabdeef ot eht lairtserret and cinaeco
Research Programme no Global Air stnemnorivne ni tnereffid ,syaw rof ,elpmaxe yb gnignahc eht -vitcudorp
Pollution dna Climate .egnahC The yti fo sporc and yltneuqesnoc eht deriuqer tnuoma fo erutuf larutlucirga
Terrestrial tnemnorivnE metsyS fo EGAMI
land.
contributes ot IGBF-GCTE core research.
ehT EGAMI 2 ledom stsisnoc fo 13 laudividni labolg sledombus -agro
‘J Alcamo dna G J J Kreileman, ‘Emission
dezin otni eerht ylluf deknil :smetsysbus ,yrtsudnI-ygrenE lairtserreT
scenarios dna global climate protection’,
in this issue; J C Bollen, A M C Toet dna ,tnemnorivnE and naecO-erehpsomtA erugiF( .)1 ehT Energy-Zndustry
f-l J M ed Vries, gnitaulavE‘ cost-effective sledom etupmoc eht snoissime fo esuohneerg and rehto gases morf evif
strategies for meeting regional CO, srotces ni 13 dlrow snoiger erugiF( )2 desab no setamitse fo lairtsudni
,’stegrat in this issue; M Posch, J-P
Hettelingh, J Alcamo dna M Krol, noitcudorp and ygrene .noitpmusnoc ehT Terrestrial Environment
detargetnI‘ scenarios fo acidification dna sledom etalumis segnahc ni labolg land esu and revoc no a dirg elacs
climate egnahc in Asia dna ,’eporuE in taking otni tnuocca stfihs ni eht dnamed and laitnetop ytivitcudorp fo
this issue; R Leemans, A nav Amstel, C C
land. esehT sledom osla etupmoc eht tneuqesbus sexulf fo gases neewteb
Battjes, G J J Kreileman dna A M C Toet,
‘The land revoc dna carbon elcyc eht lairtserret tnemnorivne and .erehpsomta ehT Atmosphere-Ocean
consequences fo large-scale utilization fo sledom etaluclac eht segnahc ni cirehpsomta noitisopmoc fo esuohneerg
biomass as na ygrene source’, in this
and rehto gases, segnahc ni eht taeh and erutsiom ecnalab fo eht ,htrae
issue
*J Alcamo (ed) EGAM :0.2 integrated and tneuqesbus stfihs ni erutarepmet and noitatipicerp .snrettap hcaE
Modelling fo Global Climate ,egnahC ledombus has neeb detset rehtie htiw data morf 1970 ot 1990, ro -gnol
Kluwer Academic Publishers, Dordrecht,
mret ,segareva gnidneped no ytilibatius and ytilibaliava fo data. An -revo
4991
World regions in EGAMI 2
Figure 1. World regions in EGAMI 2
model. A list fo countries assigned ot 1 adanaC 6 Eastern eporuE 01 China + .P.C countries
2 ASU 7 SIC 11 tsaE Asia
each region is presented in
3 Latin America 6 elddiM tsaE 21 Oceania
xidneppA 1 fo Alcamo te al, po tit, 4 Africa 9 aidnI + SAsia 31 Japan
feR .62 5 OECO eporuE
262
Baseline scenarios of global environmental change: J Alcamo et al
Figure 2. Schematic diagram fo L’ OEmthseyr sRtiesmks a nd
EGAMI 2 model.
weiv fo ledom tnempoleved and gnitset is nevig ni omaclA te 3.fa sliateD
3J Alcamo, G J J Kreileman, M Krol dna
G Zuidema, gniledoM‘ eht global society- fo tnempoleved and gnitset fo eht yrtsudnI-ygrenE metsysbus era nevig
biosphere-climate system, traP :1 model ni ed seirV te at4 rof eht lairtserreT tnemnorivnE metsysbus ni nielK
description dna testing’, Water Air Soil
kjiwedloG te ~1,~ namelierK and 6namwuoB snameeL and nav ned
Pollution, Vol ,67 ,4991 pp 53-1
3f4 ed Vries. R nav ned Wijngaard, G J J ’,nroB and amediuZ te a1,8 and rof eht naecO-erehpsomtA metsysbus
Kreileman, J A Olivier dna S Toet, A‘ ni ed naaH te PU and lorK and nav red ”.dreoW
model for calculating regional ygrene use
nI eht esruoc fo eht repap ew discuss lacitirc stniop fo eht snoitaluclac
dna emissions for gnitaulave global
climate scenarios’, Water Air Soil desu ot etareneg eht soiranecs ni this .repap
Pollution, Vol ,67 ,4991 pp 131-97
K5 Klein Goldewijk, J G nav ,nenniM G J J
Kreileman, M Vloedbeld dna R Leemans. Primary driving forces and assumptions
‘Simulating eht carbon xulf neewteb eht As deton ,evoba eht main gnivird secrof fo labolg egnahc ni eseht -ranecs
terrestrial tnemnorivne dna eht
soi era noitalupop and cimonoce ,htworg and ytivitca ni cimonoce
atmosphere’, Water Air Soil Pollution,
Vol ,67 ,4991 pp 032-991 .srotces ereH ew discuss cihpargomed and cimonoce assumptions, and
6G J J Kreileman dna A F Bouwman, ni eht noitces no ygrene noitpmusnoc ew discuss assumptions tuoba
‘Computing land use emissions fo
cimonoce .ytivitca
esuohneerg gases.’ Water Air Soil
Pollution, Vol ,67 ,4991 .pp 852-132
R‘ Leemans dna G J nav ned ,nroB ehT etaidemretni and hgih enilesab soiranecs ni this
Population growth.
‘Determining eht potential global
repap enilesaB( A and C) esu s’cCPI muidem noitalupop setamitse
distribution fo natural ,noitategev crops
continued no egap 462 elbaT( ,)l and eseht setamitse era esolc ot muidem noitalupop setamitse fo
Table 1. Assumptions for population (mlllons)
BaealirbeAandC Basehe B
noiQeR 1970 1990 2010 2OQO 2100 2010 2oso 2100
Canada 21.3 26.6 30.2 31.8 31 5 27.2 22.8 15.4
ASU
205.1 249.9 283.0 298.2 295.2 263.6 234.9 166.0
Latin
America 283.8 445.0 603.2 819.6 872.0 587.7 770.9 772.9
Africa 359.8 693.3 1117.8 2198.3 2862.1 1022.2 1621.1 1611.4
OECD Europe 351.1 377.1 398.2 394.4 307.5 385.0 323.0 218.4
Eastern Europe 108.4 123.4 135.5 149.3 147.8 132.5 128.9 97.2
CIS 242.8 289.4 317.7 350.0 346.6 310.8 302.2 277.6
Middle East 114.9 202.1 364.3 762.2 931.7 325.0 439.4 345.3
India + S Asia 739.4 1170.9 1635.1 2374.5 2643.5 1549.0 1896.9 1478.6
ChIna + C P Asia 896.9 1242.1 1553.5 1806.3 1953.3 1460.6 1390.0 949.7
East Asia 239.5 368.0 513.9 746.2 830.8 486.8 596.1 464.7
Oceania 16.2 21.4 23.0 22.8 22.5 22.2 17.4 11.9
Japan 104.3 123.5 132.7 131.5 129.9 128.1 100.7 68.9
World 3685.7 5297.5 7108.0 10129.1 11455.2 6700.7 7844.3 6427.7
Source: Leggett et al. 1992.
362
Baseline scenarios of global environmental change: J Alcamo et al
eht detinU ’snoitaN ’ and fo eht lanoitanretnI etutitsnI fo deilppA smetsyS
sisylanA 21.)ASAII( ecneH ereht is emos lanoitanretni tnemeerga no eseht
continued from egap 362
dna agricultural ,’ytivitcudorp Water Air etaidemretni .snoitcejorp ehT wol enilesab oiranecs enilesaB( )B uses
Soil Pollution, Vol ,67 ,4991 pp 161-331 IPCC’s wol noitalupop etamitse hcihw is rewol than that desu rof yna CO2
‘G Zuidema, G J nav ned ,nroB J Alcamo
noissime oiranecs dnuof ni eht 31,erutaretil and tahwemos woleb eht wol
dna G J J Kreileman, ‘Simulating
changes in labolg land revoc as detceffa ASAII .etamitse gnimmuS up, ereht is erom lanoitanretni troppus rof eht
yb economic dna climatic factors’, Water muidem noitalupop setamitse than rof eht wol .setamitse
Air Soil Pollution, Vol ,67 ,4991 891-361
B‘ J ed ,naaH M Jonas, 0 Klepper,
J ,kebarK M S Krol dna K ,iknyzrdnelO A‘ ehT enilesab soiranecs ni this repap esu ssorG -semoD
Economic growth.
linked dynamics atmosphere-ocean cit tcudorP )PDG( assumptions fo IPCC elbaT( .)2 ,esehT ni ,nrut era
model for assessing climate policies’.
yltrap desab no reilrae IPCC krow and yltrap no mret-trohs setamitse
Water Air Soil Pollution, Vol ,67 ,4991
pp 813-382 fo eht dlroW 41.knaB
M“ S Krol dna H nav der Woerd, muideM setamitse morf IPCC era desu ni this repap rof enilesaB A,
‘Simplified calculation fo atmospheric
and era rewol than lacirotsih sdnert rof tsom .snoiger sselehtreveN eseht
concentration fo esuohneerg gases dna
rehto constituents for noitaulave fo assumptions ylpmi a substantial esaercni ni PDG rep .atipac roF -maxe
climate scenarios’, Water Air Soil ,elp PDG rep atipac ni nitaL aciremA and East Asia lliw deecxe tnerruc
Pollution, Vol ,67 ,4991 pp 182-952
slevel ni OECD eporuE ni tnatsnoc ”.srallod ,sselehtreveN a egral gap
“United Nations, egnar-gnoL worid
population projections, Population lliw niamer ni emocni neewteb dezilairtsudni and gnipoleved .snoiger
Division tropeR United Nations Population ehT wol and hgih setamitse desu ni senilesaB B and C era osla desab no
Division, New ,kroY 2991
eht IPCC and era evitatneserper fo eht wol and hgih egnar fo setamitse
‘*W ,ztuL C znirP dna J Langgassner, ‘The
ASAII World population scenarios’, in desu yb rehto srehcraeser ot etamitse labolg CO2 6‘.snoissime
W ztuL (ed), Alternative shtaP fo Future
Wortd Population Growth. lanoitanretnI
xoB 1. niaM factors affecting ygrene noitpmusnoc
etutitsnI for Applied smetsyS ,sisylanA
,ASAII ,grubnexaL 4991
Factors specified rof :oiranecs
13J Alcamo, A Bouwman, J Edmonds,
A Grubler, T atiroM dna A ,yhdnaguS nA‘ ytivitcA ni hcae cimonoce rotces
noitaulave fo eht CCPI 29SI emission larutcurtS egnahc fo ymonoce
scenarios’, in J T ,nothguoH L G arieM
lacigolonhceT egnahc gnidael ot stnemevorpmi ni ygrene
Filho, J Bruce, H ,eeL B A Callander. E
Haites, N Harris dna K lleksaM (eds), ycneiciffe
Climate egnahC :4997 Radiative forcing fo
climate egnahc dna na evaluation fo eht Factors detupmoc yllanretni yb IMAGE 2
iPCC is92 emission scenarios, leuF secirp
Cambridge ytisrevinU Press, Cambridge,
,5991 pp 403742
14World ,knaB World development report
,1997 drofxO ytisrevinU Press, New ,kroY Computing energy consumption
1991 ehT gniwollof snoitaredisnoc dereets eht tnempoleved fo eht enilesab
15Alcamo te al, .po cit., .feR 31
ygrene .soiranecs ,tsriF eht etaidemretni oiranecs enilesaB( )A was
“Alcamo te al, po tit, feR 31
17J ,tteggeL W J reppeP dna R J .trawS dednetni ot tcelfer eht IPCC muidem etamitse fo labolg CO2 noissime
‘Emissions Scenarios for eht :CCPI na ”.sdnert Its ytilibitapmoc htiw eht IPCC muidem etamitse secnahne its
,’etadpU in J T ,notghuoH B A Callander
ssenlufesu yllanoitanretni as a ecnerefer tniop rof gnitaulave etamilc -ilop
continued no egap 562
lsbk 2. Assumptions for Gross Domeslk Product (USI per capita PW year)
Baseline A Bssellne B Basellne C
Region 0791 1990 2010 2050 2100 2010 2050 2100 2010 2050 2100
Canada 13001 21273 33599 65523 115454 29752 46102 64615 37993 69622 201262
ASU
15931 21866 38224 65531 114178 33884 48209 66522 43189 89709 199289
Latin America 2024 2569 3430 8425 25048 2840 5198 10762 4190 13626 59578
Africa 813 646 700 1956 6553 596 1205 2803 835 3087 14843
OECDEurope 12268 19065 30111 58722 103470 26664 41317 58088 34050 80320 180372
Eastern Europe 1213 1913 4194 9584 16768 3970 6047 7278 6054 15638 39408
CIS 1452 2476 3355 7666 13413 3136 4777 5749 4854 12540 31599
Middle East 2883 2823 3434 7018 19773 2912 4166 7893 4077 11306 46077
India + S Asia 220 327 563 1907 7436 480 1185 3240 683 3056 17103
China + C P Asia 127 369 807 3481 15226 675 2117 6552 977 5541 35352
tsaE aisA
569 1508 2597 8795 34293 2215 5465 14941 3151 14093 78871
Oceania 11670 15579 29600 58690 103093 26448 42862 59305 33684 82188 184012
Japan 12088 23734 45399 89411 157058 40293 65299 90349 51317 125210 280335
World 3073 3971 5595 9473 21319 4968 6566 10453 6481 13894 44485
Source: Leggett eta/ 1992
462
Baseline scenarios of global environmental change: J Alcamo et al
.seit ,dnoceS eht wol and hgih oiranecs enilesaB( B and C) erew dednetni
ot evig an tnednepedni weiv tuoba eht ytniatrecnu dnuora eht muidem
;etamitse erofereht yeht esu eht gnivird secrof fo eht wol and hgih IPCC
,soiranecs tub era ton detarbilac ot niatbo ralimis noissime .stluser
,drihT ecnis EGAMI 2 is ylriaf euqinu ni its ytiliba ot mrofrep lanoiger
ygrene and noissime ,snoitaluclac eht enilesab soiranecs erew dednetni
ot edivorp wen noitamrofni tuoba lanoiger ygrene esu and snoissime
that era tnetsisnoc htiw eht ’tseb‘ labolg noissime .setamitse
)1( segnahc ni eht level fo ni hcae cimonoce rotces detcennoc
activity
htiw segnahc ni emocni and ;noitalupop
)2( ‘structural changes’ fo eht ymonoce that dael ot segnahc ni ygrene
ytisnetni fo ;srotces
)3( that devorpmi eht ecnamrofrep fo secived
‘technological changes’
and secnailppa desu ot reviled ygrene ;secivres
)4( ni that etalumits ygrene noitavresnoc and stfihs
changes fief prices
ni leuf .xim
oT etaluclac a oiranecs fo ygrene noitpmusnoc rof hcae fo 13 dlrow
,snoiger EGAMI 2 sekat otni tnuocca ruof main srotcaf xoB( :)1
lacirotsiH data wohs that gnola htiw eht htworg fo
Economic activity.
noitalupop and emocni semoc an esaercni ni eht level fo cimonoce -vitca
yti ge( eht tuptuo fo yrtsudni and eht rebmun fo .)selcihev ehT enilesab
soiranecs assume that this dnert lliw eunitnoc otni eht .erutuf dniheB
this is eht lanoitnevnoc cimonoce gnikniht that as snezitic emoceb -laew‘
’reiht erehw( htlaew is ylroop denifed ni units fo PDG rep )atipac yeht
esahcrup and possess erom things. desaB no eseht spihsnoitaler and eht
soiranecs fo PDG rep atipac rof hcae noiger deton ,evoba ew etamitse
ytivitca ni hcae rotces and noiger rof hcae .enilesab ,sihT fo ,esruoc is
ylno eno weiv fo eht ,erutuf and ton ylirassecen eht tsom elbarised eno
yllaicepse gniredisnoc eht tcapmi fo cimonoce htworg no eht larutan
.tnemnorivne ,sselehtreveN ti is etairporppa rof a enilesab oiranecs ot
tcelfer lanoitnevnoc cimonoce .gnikniht
oT etamitse eht erutuf level fo cimonoce ytivitca ew tsrif etupmoc eht
pihsnoitaler neewteb PDG rep atipac and ytivitca srotacidni ni hcae fo
evif srotces ,yrtsudnI( ,tropsnarT ,laitnediseR ,secivreS and *‘)’rehtO‘
and ni hcae noiger rof eht doirep 1970 ot 1990. sihT pihsnoitaler is neht
desu htiw eht enilesab soiranecs fo PDG elbaT( )2 ot etamitse erutuf
ytivitca slevel elbaT( .)3
As seimonoce ,worg yeht og hguorht rojam stfihs ni
Structural change.
rieht llarevo ,erutcurts rof ,ecnatsni morf ,yvaeh ygrene evisnetni indus-
seirt ot ,rethgil erom ygrene tneiciffe .seirtsudni sihT dnert lliw tceffa
eht llarevo ygrene ytisnetni fo eht srotces ni lanoiger .seimonoce roF
hcae ,oiranecs ew must yficeps woh eht ygrene ytisnetni fo hcae rotces
lliw egnahc gnidrocca ot hcus larutcurts stfihs ereh( ew refer ot eht
detabanu ygrene ,ytisnetni hcihw is denifed as eht ytisnetni tnednepedni
continued from egap 462
dna S K yenraV (eds), Climate egnahC fo ygrene .)noitavresnoc As a tsrif pets ew assume that hcae noiger
.2997 The Supplementary tropeR ot eht swollof eht lacipyt dnert nwohs ni erugiF 3, ,yleman as eht ytivitca level
FCC Scientific Assessment, Cambridge
fo a rotces sesaercni ge( as etavirp noitpmusnoc ro lairtsudni tuptuo rep
ytisrevinU Press, Cambridge, ,2991 pp
59-17 atipac )sesaercni neht eht egareva ygrene ytisnetni fo eht rotces tsrif
’rehtO‘“ stands for rehto‘ ygrene ,’esu ,sesaercni and sdrawretfa sesaerced and slevel ffo ot a .muminim ehT
dna this includes all ygrene use ton
dnoces pets is ot etamitse erehw hcae rotces fo hcae noiger yltnerruc
included yb eht rehto sectors. The ytivitca
sllaf no this .evruc sihT etamitse is desab no eht dnert fo ytivitca slevel
indicator for this sector is GDP
265
Baseline scenarios of global environmental change: J Alcamo et al
k&T .S snktpmuuA rof ytlvltca kevk In sukrav eoonomk sectors
paclSSU( )ry
Industry Sector: value added indu5trial output Servkes Sector: value added commercial servkes
PhSSU( OY
*lhda5 A mllmm5 n nrllnsa c enidsan A &ulim 5 &ullne c
1970 ISSO 2050 2100 2050 2100 2050 2100 IS70 1990 2050 2100 2050 2qoa 2050 2100
970a
Canada 4493 la740 33020 13185 18537 25632 57561 6382 12168 38002 67161 26660 37588 52075 117273
USA 4986 65M) 19501 33918 14367 19794 26666 59143 10593 14869 44720 77976 32878 45397 61249 136161
LatinA merica 770 928 2420 7114 1604 3064 3871 16920 1034 1399 5134 15768 3073 6628 8460 37866
Africa 229 217 a44 2397 526 1165 1265 5234 212 278 1073 4025 655 1582 1760 9312
OECDEurope 5176 6572 20259 35644 14254 20040 27690 62068 6241 11920 37260 65756 26136 36655 51023 114697
Eastern Europe 665 938 3973 6925 2588 3056 6459 16276 330 727 4571 a190 2792 3411 7620 19598
CIS a73 1358 4051 7016 2647 3110 6561 16526 228 553 1635 3401 1051 1314 3163 8364
Middle East 1211 995 2023 5536 1344 2247 3171 12902 1139 1249 3456 10196 1952 3918 5721 24111
India+ S Asia 45 ai 778 2562 465 1249 ii89 5746 68 122 1091 4725 677 1926 1606 11015
C tsaEhina aisA + C P Asia 30 120 1569 6147 1010 2731 2348 14156 26 103 ia42 6774 1065 3690 3082 20489
156 605 3004 11625 1968 5065 4778 26737 231 670 5001 20244 3013 6674 al67 46901
Oceania 4440 4973 17874 3x338 13075 la060 24999 55874 7066 10835 39642 69693 28930 40059 55545 124456
Japan 4682 9970 37436 65675 27371 37828 52360 117136 6788 13174 50187 a8242 36622 50714 70326 157592
World 1172 1392 3366 7352 2366 3670 4885 15255 1640 2314 5622 12656 3687 6250 6289 26856
Residential Sector: private consumption Transportaector:numberof passengervehicles
(UStka~ )ry
(vehicles per 1000 persons)
eadh A mhleaB B ti~line c enldasB A q mhd* q bdlnec
R.sb 1970 1990 2050 2100 2050 2100 2050 2100 IS70 ISSO 2050 2100 2oso 2100 2050 2100
Canada 7211 12613 38659 68118 27200 38241 52677 118745 326.7 472.4 587.5 6146 561.6 586.8 6043 629.5
USA 10054 14540 43250 75357 31818 43905 59208 131531 449.8 566.1 599.6 610.9 591.9 599.9 6064 619.4
LatinA merica 1133 1664 5139 15279 3171 6565 a312 36343 302 72.6 120.7 139.6 104.3 126.9 1317 1445
Africa 384 416 1252 4194 771 1794 1976 9500 11.6 15.1 44.0 60.8 30.6 51.6 533 63.2
OECDEurape 7142 11479 35233 62082 24790 34853 48192 106223 1971 375.0 409.5 4199 401.0 409.3 4157 427.0
Eastern Europe 754 lo64 5367 9390 3386 4076 8757 22068 344 145.0 225 7 2366 2110 2177 235.5 2444
CIS 1002 1783 5520 9657 3439 4139 9029 22751 16.3 59.0 206 5 2366 1508 176.0 234.5 2474
Mtddle East 1620 1818 4492 12655 2666 5052 7236 29489 117 40.7 63.5 75.0 51 6 655 705 77.8
India+ S Asia 169 220 1278 4982 794 2171 2046 11459 1.4 2.9 364 1 569 227 49.4 48.2 61 3
China + C P Asia 80 202 1915 a374 1164 3604 3046 19444 02 27 47 59.3 369 551 53.5 606
East Asia 363 a32 4837 ia861 3006 8216 7751 43379 4.6 15.6 590 63.1 55.4 61.4 61 2 637
Oceania 7226 10109 38148 67010 27860 38546 53422 119608 307.0 413.0 4721 485.4 462.1 472.4 480.7 494.6
Japan 7041 13620 50964 89523 37220 51499 71370 159791 101.9 254.1 3049 315.4 296.7 305.2 311.8 322.1
World la53 2461 5806 12976 4027 6378 a512 27044 56.6 82.1 964 106.6 85.7 100.1 105.7 1096
and ygrene data morf 1970 ot 1990. retfA gnitamitse eht tnerruc noitacol
fo hcae rotces no this ,evruc ew neht esu eht data rof ytivitca slevel
elbaT( )3 ot etalopartxe ot eht dnert fo ygrene ytisnetni eud ot larutcurts
.egnahc sdnerT ni ygrene ytisnetni rof eht tnatropmi yrtsudni rotces fo
enilesaB A era detciped ni erugiF 4. ereH eht shapes fo eht sevruc era
erom tnatropmi than eht edutingam fo eht sevruc esuaceb serusaem fo
ytivitca era ton yltcerid elbarapmoc neewteb .snoiger etoN that eht
tnereffid snoiger era detcepxe ot eb ni tnereffid phases fo eht laciteroeht
evruc erugiF( )3 gnirud eht oiranecs .doirep owT snoiger detciped ni
erugiF 4 era ni eht ylrae trap fo eht laciteroeht ,evruc China plus
yllartneC dennalP Asia gnivom( morf dnuora tniop ’B‘ ot ,)’C‘ and
Structural egnahC
Figure 3. dezilaedI evruc fo
structural egnahc leading ot egnahc
in ygrene ytisnetni fo a sector in a
evitaleR ytivitcA level
regional .ymonoce
662
Baseline .scenarios of global environmental change: J Alcamo et al
ygrenE ytisnetni yrtsudnI - taeh
nitaL- aciremA
Figure .4 larutcurtS egnahc gnidael ot
egnahc ni ygrene ytisnetni rof eht
yrtsudni )taeh( rotces ni enilesaB .A
etoN taht eht latnoziroh sixa is ytivitca
level rehtar naht ,emit os eht laropmet
dnert fo eht demussa larutcurts
0 2 4 6 8 01 21 41
segnahc sdneped no woh tsaf ytivitca
slevel .esaercni eulaV deddA yrtsudnI 00ol[ US $ ].pac/
nitaL aciremA gnivom( morf dnuora tniop ’A‘ ot .)’C‘ ,elihwnaeM eht
SIC sevom hguorht eht elddim sdrawot eht dne fo eht evruc gnivom(
morf dnuora tniop ’B‘ ot .)’D‘ OECD eporuE is detcepxe ot eb ni eht
tsom decnavda esahp fo eht evruc dnuora( tniop .)’D‘
elihW elacs-egral larutcurts segnahc dael ot stfihs
Technological change.
ni eht llarevo ygrene ytisnetni fo eht ,ymonoce ydaets stnemevorpmi ni
ygolonhcet ekam wen ygrene using secnailppa erom ygrene ,tneiciffe
netfo at on ro neve evitagen stsoc and evitcepserri fo segnahc ni leuf
and yticirtcele .secirp esehT stnemevorpmi era nekat otni tnuocca ni eht
soiranecs yb gniyficeps eht etar at hcihw wen ygrene using secived
emoceb erom ygrene tneiciffe revo .emit sihT dellac-os lanigram‘ etar fo
suomonotua ygrene ycneiciffe ’tnemevorpmi must eb deificeps rof yreve
rotces and .noiger detceleS stluser era nevig ni erugiF 5. roF eht indus-
lairt rotces fo OECD ,eporuE tnerruc stnemevorpmi ni ygrene ycneiciffe
era assumed ot eunitnoc at tuoba %52.0 rep ,raey evitcepserri fo leuf
.secirp nI eht ,SIC erehw yrtsudni is erom ygrene evisnetni than OECD
,eporuE a rehgih etar %56.0( rep )raey is assumed. A hgih etar fo
tnemevorpmi is osla assumed rof China plus yllartneC dennalP Asia
lanigraM ygrenE ytisnetnI yrtsudnI - taeh
4.0
3.0
2.0
Figure 5. lacigolonhceT egnahc 1.0 nitaL- aciremA
gnidael ot egnahc ni lanigram ygrene
ytisnetni rof eht yrtsudni )taeh( rotces 0.0 --p I __ i
ni enilesaB .A 1990 2100
762
Baseline scenarios of global environmental change: J Alcamo et al
esU-dnE ygrenE secirP yrtsudnI - taeh
evitaler( ot
1990)
0.4 p,
- _ - anihC + .P.C aisA
nitaL- aciremA
Figure 6. dnE esu ygrene secirp rof
eht yrtsudni )taeh( rotces ni enilesaB
rep )raey hcihw stcelfer a nommoc weiv that this noiger lliw
(0.60%
evirts ot ylkciuq ezinredom its .seirtsudni nitaL ,aciremA ,revewoh is
assumed ot eunitnoc htiw its ylevitaler wol tnerruc etar fo tnemevorpmi
%53.0( rep .)raey
sremusnoC tcaer ot repeets ygrene secirp yb gnicuder
Energy prices.
ygrene .esu sihT tceffe is detalumis ni eht ledom .ylticilpxe ehT leuf
ecirp segnahc that etalumits ygrene noitavresnoc era detupmoc yllanretni
ni eht ledom as a noitcnuf fo leuf ylppus and era desab no ecnegrevnoc
sdrawot labolg leuf .secirp nI eht elpmaxe rof eht yrtsudni )taeh( rotces
nwohs ni erugiF 6, evitaler ecirp segnahc era esolc rof OECD eporuE
and China plus yllartneC dennalP Asia and yllaitnatsbus rehgih rof
nitaL aciremA and .SIC ehT secnereffid ni sdnert rof tnereffid snoiger
era ylniam eud ot eht ecnegrevnoc fo leuf secirp sdrawot labolg .secirp
oT nur eht ,ledom rehto ygrene detaler data must osla eb .deificeps
ehT tsom tnatropmi seno era doowleuf ,noitpmusnoc laicremmoc
sleufoib noitpmusnoc and eht noitareneg xim rof cirtcele rewop -areneg
.noit
ehT EGAMI 2 ledom senibmoc eht gnidecerp srotcaf ni gnitamitse
segnahc ni eht llarevo ygrene seitisnetni fo hcae ,noiger and rieht erutuf
ygrene .noitpmusnoc esehT era detroper gnola htiw rehto oiranecs stluser
retal ni eht .repap
xoB niaM factors affecting larutlucirga noitcudorp
2.
Factors specified rof :oiranecs
edarT fo larutlucirga stcudorp
Animal yrdnabsuh
gnipporC ytisnetni
lacigolonhceT stnemevorpmi ni porc dleiy
Factors detupmoc yllanretni yb IMAGE 2
larutlucirgA dnamed
laitnetoP ytivitcudorp fo land eud ot etamilc
862
Baseline scenarios fo global environmental :egnahc J Alcamo te al
Computing change in agricultural production and land use
dnaL revoc egnahc is an laitnesse tcepsa fo labolg latnemnorivne .egnahc
roF ,elpmaxe noitatserofed sdael ot sesaeler fo esuohneerg and rehto
gases, noisnapxe fo larutlucirga and nabru land sregnadne larutan
metsysoce habitats, and noitatserof sesaercni eht ekatpu fo CO2 morf
eht .erehpsomta EGAMI 2 setupmoc segnahc ni land revoc yb taking
otni tnuocca eht deen rof larutlucirga land desu( ereh ot naem erutsap
and ,dnalporc and deganam .)stserof ehT ledom setupmoc eseht segnahc
ni land esu yb gnitupmoc eht gnignahc dnamed ni 13 dlrow snoiger rof
,kcotsevil ,sporc and tserof stcudorp and eht tnuoma fo ,porc ,erutsap
and tserof land deriuqer ot edivorp eseht .stcudorp
oT etaluclac a oiranecs fo larutlucirga ,noitcudorp EGAMI 2 sekat
otni tnuocca eht srotcaf detneserp ni xoB 2. ehT deen rof larutlucirga
land lliw ,dneped tsrif and ,tsomerof no lanoiger larutlucirga sdnamed
hcihw era detupmoc as debircsed .woleb ,revewoH rof emos ,snoiger eht
tnuoma fo larutlucirga land lliw osla dneped no eht tnuoma fo doof
dedart htiw rehto ,snoiger and this must osla eb deificeps rof hcae
.oiranecs nI ,noitidda ereht era a rebmun fo srotcaf that era tnatropmi
ot gnitamitse stnemeriuqer rof larutlucirga land esuaceb yeht ecneulfni
eht tnuoma fo doof that nac eb decudorp rep eratceh fo land. enO fo
eseht srotcaf is eht tceffe fo etamilc no laitnetop porc ,ytivitcudorp and
this is detupmoc yllanretni yb eht .ledom ehT rehto eerht srotcaf fo this
epyt must eb deificeps rof hcae .oiranecs yehT :era animal ,yrdnabsuh
gnipporc ,ytisnetni and lacigolonhcet stnemevorpmi ni porc .dleiy
larutlucirgA dnamed stsisnoc fo eht deen rof all -irga
Agricultural demand.
larutluc ,seitidommoc yllacificeps taem and sporc demusnoc yb humans,
and deef deriuqer yb kcotsevil dnamed( rof tserof stcudorp era detupmoc
yletarapes ni eht ,ledom elihw eht dnamed rof laicremmoc sleufoib is -reneg
deta yb eht ygrenE ymonocE .)ledom oT etupmoc lanoiger ,sdnamed eht
ledom seilpitlum rep atipac noitpmusnoc fo doof semit noitalupop -itse
.setam ehT main task, ,erofereht is ot etupmoc rep atipac noitpmusnoc fo
.doof EGAMI 2 setupmoc this noitpmusnoc rednu eht main esimerp that
elpoep tae erom doof as rieht emocni ,sesaercni up ot a ralucitrap
’derreferp‘ noitpmusnoc .level fO ,esruoc ni ytilaer doof secirp osla evah a
rojam ecneulfni no noitpmusnoc slevel - esehT era nekat otni tnuocca
yltceridni ni eht ledom yb making doof noitpmusnoc tnedneped no eht
ytivitcudorp and ytilibaliava fo wen larutlucirga lands - ehT aedi is that
as doog land is desu up, secirp esaercni and noitpmusnoc is .denepmad
gnimmuS up ot this ,tniop EGAMI 2 setupmoc rep atipac doof
noitpmusnoc desab no )1( ,emocni )2( land ytivitcudorp and ,ytilibaliava
and )3( derreferp level fo doof .noitpmusnoc ehT tsrif rotcaf is nekat
morf eht PDG rep atipac assumptions rof hcae ,noiger deificeps ni
elbaT 2. ehT dnoces rotcaf is detupmoc yllanretni ni eht EGAMI 2
.ledom ehT driht ,rotcaf derreferp level fo ,noitpmusnoc is yrev tluciffid
“FAO, Agrostat .CP dnaL Use,
ot yficeps esuaceb ti seirav yltaerg morf noiger ot ,noiger and sdneped
Computerized noitamrofnI Series l/7,
dooF dna Agriculture Organization fo eht no tluciffid ot yfitnauq larutluc and lacihpargoeg .srotcaf ecneH ew
United Nations, Rome, 1991 ekat a citamgarp hcaorppa and nur eht EGAMI 2 ledom ’sdrawkcab‘
M“ W Rosegrant. M Agcaoili-Saombilla
morf 1970 ot 2010 ni redro ot niatbo eht dnert fo this .rotcaf sihT is
dna N D ,zereP Global dooF Projections
ot :0202 implications for ,tnemtsevnI dooF enod yb gniyficeps rof this doirep what eht ledom is desoppus ot
Agriculture dna eht Environment, etupmoc ~ rep atipac noitpmusnoc fo tnereffid sdoof morf 1970 ot
Discussion repaP ,5 lanoitanretnI dooF
2010. Data rof doof noitpmusnoc semoc morf 91TATSORGA rof 1970
yciloP Research etutitsnI ,)IRPFI(
ot 1990, and morf dnert setamitse fo ”IRPFI morf 1990 ot 2010. ehT
Washington, DC, 5991
269
Baseline scenarios of global environmental change: J Akamo et af
rehto tnatropmi srotcaf - emocni and land ,ytilibaliava/ytivitcudorp era
assigned ro yllanretni detaluclac as ew deton .evoba ,eroferehT ew nac
kcab etaluclac morf eht ledom a hguor etamitse fo eht derreferp
noitpmusnoc level fo eht tnereffid sdoof ni tnereffid snoiger rof this
.doirep eW neht etalopartxe eseht sdnert morf 2010 ot 2100. ehT( emas
setamitse fo derreferp noitpmusnoc era desu rof all eerht enilesab -ranecs
).soi ehT derreferp noitpmusnoc level rehtegot htiw eht detupmoc
noitpmusnoc level rof enileaB A ni nitaL aciremA era nwohs retal ni
erugiF 11. ehT last pets ni gnitupmoc larutlucirga dnamed is ot ylpitlum
eht detupmoc lanoiger rep atipac noitpmusnoc yb noitalupop data ni
elbaT 1 ot niatbo eht sennot fo larutlucirga stcudorp fo hcae epyt
dedeen ni hcae noiger and emit .pets
ehT enilesab soiranecs fo dlrow doof edart era desab no eerht
Food trade.
yrev elpmis selur desab no fles‘ ycneiciffus ’soitar latot( noitcudorp
dedivid yb latot :)noitpmusnoc )1( snoigeR that yltnerruc tropxe a -itrap
raluc larutlucirga ytidommoc lliw eunitnoc ot od os ni eht ,erutuf )2( eht
noitcarf fo this tropxe evitaler ot eht latot noitcudorp fo this ytidommoc
sniamer eht emas ei eht fles‘ ycneiciffus ’soitar niamer eht ,emas and
)3( yltnerruc gnitropmi seirtnuoc maintain rieht tnerruc ecnedneped no
.stropmi ehT emas assumptions era desu rof all eerht enilesab .soiranecs
,ecneH fi larutlucirga noitcudorp ni a noiger ,sesaercni neht eht latot
tnuoma fo stropxe lliw osla .esaercni fO ,esruoc this is just eno fo ynam
elbissop syaw fo gniyficeps a oiranecs fo doof ,edart tub gniredisnoc eht
ytixelpmoc fo eht tcejbus ti has eht eutriv fo gnieb .elpmis
emoS srotcaf denrecnoc htiw eht tnempoleved fo -evil
Animal husbandry.
kcots nac evah an tnatropmi tceffe no gnitamitse erutuf deef -eriuqer
stnem and erutsap and .dnalegnar enO rotcaf ni ralucitrap is animal
,ytivitcudorp ei eht tnuoma fo taem decudorp rep animal. roF this
rotcaf ew assume that dezilairtsudni seirtnuoc era esolc ot rieht -ixam
mum eulav and that rehto snoiger lliw hcaer eht tnerruc OECD eporuE
level nehw rieht PDG rep atipac sehcaer eht tnerruc OECD level
elbaT( .)4 ,ecneH eht dnert fo this rotcaf seirav morf oiranecs ot oiranecs
gnola htiw cimonoce assumptions fo eht .soiranecs
An tnatropmi elbairav gnitceffa eht llarevo land
Cropping intensity.
dedeen ni a noiger rof dnalporc is eht rebmun fo sporc nworg rep eratceh
fo land revo a radnelac .raey sihT must eb deificeps rof hcae oiranecs and
Table .4 Assumptions for Improvement In productlvlty of boo1 osttle
Productivity (kghnlmsl yr) Rate fo esaercnI nI ytlvftcudorp (Wyr)
Bsseli- A enllessB A 2asellne 2 enllessB C
is70 **so 2010 2050 2100 1w+2100 ieoo-2100 iso+2ioo
Canada 86 99 135 163 163 0.45 0.36 0.53
ASU 99 121 145 163 163 0.27 0.18 0.35
nitaL America 35 36 41 75 162 1.38 0.80 1.36
acirfA 16 24 24 30 57 0.79 0.31 1.19
DCEO Europe 123 148 156 162 162 0.09 0.00 0.17
Eastern Europe 100 119 125 138 156 0.25 0.07 0.22
SIC 95 117 119 130 146 0.20 0.05 0.22
elddiM East 23 46 49 73 162 1.16 0.47 0.67
aidnI + S aisA 7 9 10 15 47 1.53 0.77 2.01
anihC + C P aisA 5 14 16 29 121 1.95 1.04 1.90
East aisA 16 27 34 76 162 1.63 1.31 1.66
Oceania 53 81 124 162 162 0.63 0.54 0.71
Japan 113 155 159 162 162 0.04 0.00 0.12
270