Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O3 pollution
Identifieur interne : 000060 ( PascalFrancis/Corpus ); précédent : 000059; suivant : 000061Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O3 pollution
Auteurs : Shiri Avnery ; Denise L. Mauzerall ; JUNFENG LIU ; Larry W. HorowitzSource :
- Atmospheric environment : (1994) [ 1352-2310 ] ; 2011.
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- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
We examine the potential global risk of increasing surface ozone (O3) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O3 pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O3 precursor emissions in 2030. We use simulated hourly O3 concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O3 exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O3 on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O3 exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth $17-35 billion USD2000 annually (an increase of +$6-17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of + 0.3-0.5%), with total losses worth $12-21 billion annually (an increase of +$1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our calculations of crop production and economic losses are highly conservative. Our results suggest that O3 pollution poses a growing threat to global food security even under an optimistic scenario of future ozone precursor emissions. Further efforts to reduce surface O3 concentrations thus provide an excellent opportunity to increase global grain yields without the environmental degradation associated with additional fertilizer application or land cultivation.
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| NO : | PASCAL 11-0255955 INIST |
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| ET : | Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O3 pollution |
| AU : | AVNERY (Shiri); MAUZERALL (Denise L.); JUNFENG LIU; HOROWITZ (Larry W.) |
| AF : | Program in Science, Technology, and Environmental Policy, Woodrow Wilson School of Public and International Affairs, 414 Robertson Hall, Princeton University/Princeton, NJ 08544/Etats-Unis (1 aut.); Woodrow Wilson School of Public and International Affairs, Department of Civil and Environmental Engineering, 445 Robertson Hall, Princeton University/Princeton, NJ 08544/Etats-Unis (2 aut.); NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University/Princeton, NJ 08540/Etats-Unis (3 aut., 4 aut.) |
| DT : | Publication en série; Niveau analytique |
| SO : | Atmospheric environment : (1994); ISSN 1352-2310; Royaume-Uni; Da. 2011; Vol. 45; No. 13; Pp. 2297-2309; Bibl. 1 p. |
| LA : | Anglais |
| EA : | We examine the potential global risk of increasing surface ozone (O3) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O3 pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O3 precursor emissions in 2030. We use simulated hourly O3 concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O3 exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O3 on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O3 exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth $17-35 billion USD2000 annually (an increase of +$6-17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of + 0.3-0.5%), with total losses worth $12-21 billion annually (an increase of +$1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our calculations of crop production and economic losses are highly conservative. Our results suggest that O3 pollution poses a growing threat to global food security even under an optimistic scenario of future ozone precursor emissions. Further efforts to reduce surface O3 concentrations thus provide an excellent opportunity to increase global grain yields without the environmental degradation associated with additional fertilizer application or land cultivation. |
| CC : | 001D16C |
| FD : | Ozone; Pollution; Trajectoire; Changement climatique; Prévision pollution atmosphérique; Précurseur; Modélisation; Traceur; Sol agricole; Production agricole; Agriculture; Industrie alimentaire; Engrais; Fertilisation; Phénomène transport; Localisation source |
| FG : | Climatologie dynamique |
| ED : | Ozone; Pollution; Trajectory; Climate change; Atmospheric pollution forecasting; Precursor; Modeling; Tracers; Agricultural soil; Agricultural production; Agriculture; Food industry; Fertilizers; Fertilization; Transport process; Source localization |
| EG : | Dynamical climatology |
| SD : | Ozono; Polución; Trayectoria; Cambio climático; Previsión contaminación del ambiente; Precursor; Modelización; Trazador; Suelo agrícola; Producción agrícola; Agricultura; Industria alimenticia; Fertilizante; Fertilización; Fenómeno transporte; Localización fuente |
| LO : | INIST-8940B.354000192901550150 |
| ID : | 11-0255955 |
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Mauzerall</name><affiliation><inist:fA14 i1="02"><s1>Woodrow Wilson School of Public and International Affairs, Department of Civil and Environmental Engineering, 445 Robertson Hall, Princeton University</s1><s2>Princeton, NJ 08544</s2><s3>USA</s3><sZ>2 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Junfeng Liu" sort="Junfeng Liu" uniqKey="Junfeng Liu" last="Junfeng Liu">JUNFENG LIU</name><affiliation><inist:fA14 i1="03"><s1>NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University</s1><s2>Princeton, NJ 08540</s2><s3>USA</s3><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Horowitz, Larry W" sort="Horowitz, Larry W" uniqKey="Horowitz L" first="Larry W." last="Horowitz">Larry W. Horowitz</name><affiliation><inist:fA14 i1="03"><s1>NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University</s1><s2>Princeton, NJ 08540</s2><s3>USA</s3><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">11-0255955</idno><date when="2011">2011</date><idno type="stanalyst">PASCAL 11-0255955 INIST</idno><idno type="RBID">Pascal:11-0255955</idno><idno type="wicri:Area/PascalFrancis/Corpus">000060</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O<sub>3</sub> pollution</title><author><name sortKey="Avnery, Shiri" sort="Avnery, Shiri" uniqKey="Avnery S" first="Shiri" last="Avnery">Shiri Avnery</name><affiliation><inist:fA14 i1="01"><s1>Program in Science, Technology, and Environmental Policy, Woodrow Wilson School of Public and International Affairs, 414 Robertson Hall, Princeton University</s1><s2>Princeton, NJ 08544</s2><s3>USA</s3><sZ>1 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Mauzerall, Denise L" sort="Mauzerall, Denise L" uniqKey="Mauzerall D" first="Denise L." last="Mauzerall">Denise L. Mauzerall</name><affiliation><inist:fA14 i1="02"><s1>Woodrow Wilson School of Public and International Affairs, Department of Civil and Environmental Engineering, 445 Robertson Hall, Princeton University</s1><s2>Princeton, NJ 08544</s2><s3>USA</s3><sZ>2 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Junfeng Liu" sort="Junfeng Liu" uniqKey="Junfeng Liu" last="Junfeng Liu">JUNFENG LIU</name><affiliation><inist:fA14 i1="03"><s1>NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University</s1><s2>Princeton, NJ 08540</s2><s3>USA</s3><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Horowitz, Larry W" sort="Horowitz, Larry W" uniqKey="Horowitz L" first="Larry W." last="Horowitz">Larry W. Horowitz</name><affiliation><inist:fA14 i1="03"><s1>NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University</s1><s2>Princeton, NJ 08540</s2><s3>USA</s3><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14></affiliation></author></analytic><series><title level="j" type="main">Atmospheric environment : (1994)</title><title level="j" type="abbreviated">Atmos. environ. : (1994)</title><idno type="ISSN">1352-2310</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Atmospheric environment : (1994)</title><title level="j" type="abbreviated">Atmos. environ. : (1994)</title><idno type="ISSN">1352-2310</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Agricultural production</term><term>Agricultural soil</term><term>Agriculture</term><term>Atmospheric pollution forecasting</term><term>Climate change</term><term>Fertilization</term><term>Fertilizers</term><term>Food industry</term><term>Modeling</term><term>Ozone</term><term>Pollution</term><term>Precursor</term><term>Source localization</term><term>Tracers</term><term>Trajectory</term><term>Transport process</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Ozone</term><term>Pollution</term><term>Trajectoire</term><term>Changement climatique</term><term>Prévision pollution atmosphérique</term><term>Précurseur</term><term>Modélisation</term><term>Traceur</term><term>Sol agricole</term><term>Production agricole</term><term>Agriculture</term><term>Industrie alimentaire</term><term>Engrais</term><term>Fertilisation</term><term>Phénomène transport</term><term>Localisation source</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We examine the potential global risk of increasing surface ozone (O<sub>3</sub>) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O<sub>3</sub> pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O<sub>3</sub> precursor emissions in 2030. We use simulated hourly O<sub>3</sub> concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O<sub>3</sub> exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O<sub>3</sub> on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O<sub>3</sub> exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth $17-35 billion USD<sub>2000</sub> annually (an increase of +$6-17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of + 0.3-0.5%), with total losses worth $12-21 billion annually (an increase of +$1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our calculations of crop production and economic losses are highly conservative. Our results suggest that O<sub>3</sub> pollution poses a growing threat to global food security even under an optimistic scenario of future ozone precursor emissions. Further efforts to reduce surface O<sub>3</sub> concentrations thus provide an excellent opportunity to increase global grain yields without the environmental degradation associated with additional fertilizer application or land cultivation.</div></front></TEI><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>1352-2310</s0></fA01><fA03 i2="1"><s0>Atmos. environ. : (1994)</s0></fA03><fA05><s2>45</s2></fA05><fA06><s2>13</s2></fA06><fA08 i1="01" i2="1" l="ENG"><s1>Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O<sub>3</sub> pollution</s1></fA08><fA11 i1="01" i2="1"><s1>AVNERY (Shiri)</s1></fA11><fA11 i1="02" i2="1"><s1>MAUZERALL (Denise L.)</s1></fA11><fA11 i1="03" i2="1"><s1>JUNFENG LIU</s1></fA11><fA11 i1="04" i2="1"><s1>HOROWITZ (Larry W.)</s1></fA11><fA14 i1="01"><s1>Program in Science, Technology, and Environmental Policy, Woodrow Wilson School of Public and International Affairs, 414 Robertson Hall, Princeton University</s1><s2>Princeton, NJ 08544</s2><s3>USA</s3><sZ>1 aut.</sZ></fA14><fA14 i1="02"><s1>Woodrow Wilson School of Public and International Affairs, Department of Civil and Environmental Engineering, 445 Robertson Hall, Princeton University</s1><s2>Princeton, NJ 08544</s2><s3>USA</s3><sZ>2 aut.</sZ></fA14><fA14 i1="03"><s1>NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University</s1><s2>Princeton, NJ 08540</s2><s3>USA</s3><sZ>3 aut.</sZ><sZ>4 aut.</sZ></fA14><fA20><s1>2297-2309</s1></fA20><fA21><s1>2011</s1></fA21><fA23 i1="01"><s0>ENG</s0></fA23><fA43 i1="01"><s1>INIST</s1><s2>8940B</s2><s5>354000192901550150</s5></fA43><fA44><s0>0000</s0><s1>© 2011 INIST-CNRS. All rights reserved.</s1></fA44><fA45><s0>1 p.</s0></fA45><fA47 i1="01" i2="1"><s0>11-0255955</s0></fA47><fA60><s1>P</s1></fA60><fA61><s0>A</s0></fA61><fA64 i1="01" i2="1"><s0>Atmospheric environment : (1994)</s0></fA64><fA66 i1="01"><s0>GBR</s0></fA66><fC01 i1="01" l="ENG"><s0>We examine the potential global risk of increasing surface ozone (O<sub>3</sub>) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O<sub>3</sub> pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O<sub>3</sub> precursor emissions in 2030. We use simulated hourly O<sub>3</sub> concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O<sub>3</sub> exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O<sub>3</sub> on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O<sub>3</sub> exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth $17-35 billion USD<sub>2000</sub> annually (an increase of +$6-17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of + 0.3-0.5%), with total losses worth $12-21 billion annually (an increase of +$1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our calculations of crop production and economic losses are highly conservative. Our results suggest that O<sub>3</sub> pollution poses a growing threat to global food security even under an optimistic scenario of future ozone precursor emissions. Further efforts to reduce surface O<sub>3</sub> concentrations thus provide an excellent opportunity to increase global grain yields without the environmental degradation associated with additional fertilizer application or land cultivation.</s0></fC01><fC02 i1="01" i2="X"><s0>001D16C</s0></fC02><fC03 i1="01" i2="X" l="FRE"><s0>Ozone</s0><s2>NK</s2><s2>FX</s2><s5>01</s5></fC03><fC03 i1="01" i2="X" l="ENG"><s0>Ozone</s0><s2>NK</s2><s2>FX</s2><s5>01</s5></fC03><fC03 i1="01" i2="X" l="SPA"><s0>Ozono</s0><s2>NK</s2><s2>FX</s2><s5>01</s5></fC03><fC03 i1="02" i2="X" l="FRE"><s0>Pollution</s0><s5>02</s5></fC03><fC03 i1="02" i2="X" l="ENG"><s0>Pollution</s0><s5>02</s5></fC03><fC03 i1="02" i2="X" l="SPA"><s0>Polución</s0><s5>02</s5></fC03><fC03 i1="03" i2="X" l="FRE"><s0>Trajectoire</s0><s5>03</s5></fC03><fC03 i1="03" i2="X" l="ENG"><s0>Trajectory</s0><s5>03</s5></fC03><fC03 i1="03" i2="X" l="SPA"><s0>Trayectoria</s0><s5>03</s5></fC03><fC03 i1="04" i2="X" l="FRE"><s0>Changement climatique</s0><s5>04</s5></fC03><fC03 i1="04" i2="X" l="ENG"><s0>Climate change</s0><s5>04</s5></fC03><fC03 i1="04" i2="X" l="SPA"><s0>Cambio climático</s0><s5>04</s5></fC03><fC03 i1="05" i2="X" l="FRE"><s0>Prévision pollution atmosphérique</s0><s5>05</s5></fC03><fC03 i1="05" i2="X" l="ENG"><s0>Atmospheric pollution forecasting</s0><s5>05</s5></fC03><fC03 i1="05" i2="X" l="SPA"><s0>Previsión contaminación del ambiente</s0><s5>05</s5></fC03><fC03 i1="06" i2="X" l="FRE"><s0>Précurseur</s0><s5>06</s5></fC03><fC03 i1="06" i2="X" l="ENG"><s0>Precursor</s0><s5>06</s5></fC03><fC03 i1="06" i2="X" l="SPA"><s0>Precursor</s0><s5>06</s5></fC03><fC03 i1="07" i2="X" l="FRE"><s0>Modélisation</s0><s5>07</s5></fC03><fC03 i1="07" i2="X" l="ENG"><s0>Modeling</s0><s5>07</s5></fC03><fC03 i1="07" i2="X" l="SPA"><s0>Modelización</s0><s5>07</s5></fC03><fC03 i1="08" i2="X" l="FRE"><s0>Traceur</s0><s5>08</s5></fC03><fC03 i1="08" i2="X" l="ENG"><s0>Tracers</s0><s5>08</s5></fC03><fC03 i1="08" i2="X" l="SPA"><s0>Trazador</s0><s5>08</s5></fC03><fC03 i1="09" i2="X" l="FRE"><s0>Sol agricole</s0><s2>NT</s2><s5>09</s5></fC03><fC03 i1="09" i2="X" l="ENG"><s0>Agricultural soil</s0><s2>NT</s2><s5>09</s5></fC03><fC03 i1="09" i2="X" l="SPA"><s0>Suelo agrícola</s0><s2>NT</s2><s5>09</s5></fC03><fC03 i1="10" i2="X" l="FRE"><s0>Production agricole</s0><s5>10</s5></fC03><fC03 i1="10" i2="X" l="ENG"><s0>Agricultural production</s0><s5>10</s5></fC03><fC03 i1="10" i2="X" l="SPA"><s0>Producción agrícola</s0><s5>10</s5></fC03><fC03 i1="11" i2="X" l="FRE"><s0>Agriculture</s0><s5>11</s5></fC03><fC03 i1="11" i2="X" l="ENG"><s0>Agriculture</s0><s5>11</s5></fC03><fC03 i1="11" i2="X" l="SPA"><s0>Agricultura</s0><s5>11</s5></fC03><fC03 i1="12" i2="X" l="FRE"><s0>Industrie alimentaire</s0><s5>12</s5></fC03><fC03 i1="12" i2="X" l="ENG"><s0>Food industry</s0><s5>12</s5></fC03><fC03 i1="12" i2="X" l="SPA"><s0>Industria alimenticia</s0><s5>12</s5></fC03><fC03 i1="13" i2="X" l="FRE"><s0>Engrais</s0><s5>13</s5></fC03><fC03 i1="13" i2="X" l="ENG"><s0>Fertilizers</s0><s5>13</s5></fC03><fC03 i1="13" i2="X" l="SPA"><s0>Fertilizante</s0><s5>13</s5></fC03><fC03 i1="14" i2="X" l="FRE"><s0>Fertilisation</s0><s5>14</s5></fC03><fC03 i1="14" i2="X" l="ENG"><s0>Fertilization</s0><s5>14</s5></fC03><fC03 i1="14" i2="X" l="SPA"><s0>Fertilización</s0><s5>14</s5></fC03><fC03 i1="15" i2="X" l="FRE"><s0>Phénomène transport</s0><s5>35</s5></fC03><fC03 i1="15" i2="X" l="ENG"><s0>Transport process</s0><s5>35</s5></fC03><fC03 i1="15" i2="X" l="SPA"><s0>Fenómeno transporte</s0><s5>35</s5></fC03><fC03 i1="16" i2="X" l="FRE"><s0>Localisation source</s0><s5>36</s5></fC03><fC03 i1="16" i2="X" l="ENG"><s0>Source localization</s0><s5>36</s5></fC03><fC03 i1="16" i2="X" l="SPA"><s0>Localización fuente</s0><s5>36</s5></fC03><fC07 i1="01" i2="X" l="FRE"><s0>Climatologie dynamique</s0></fC07><fC07 i1="01" i2="X" l="ENG"><s0>Dynamical climatology</s0></fC07><fC07 i1="01" i2="X" l="SPA"><s0>Climatología dinámica</s0></fC07><fN21><s1>171</s1></fN21><fN44 i1="01"><s1>OTO</s1></fN44><fN82><s1>OTO</s1></fN82></pA></standard><server><NO>PASCAL 11-0255955 INIST</NO><ET>Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O<sub>3</sub> pollution</ET><AU>AVNERY (Shiri); MAUZERALL (Denise L.); JUNFENG LIU; HOROWITZ (Larry W.)</AU><AF>Program in Science, Technology, and Environmental Policy, Woodrow Wilson School of Public and International Affairs, 414 Robertson Hall, Princeton University/Princeton, NJ 08544/Etats-Unis (1 aut.); Woodrow Wilson School of Public and International Affairs, Department of Civil and Environmental Engineering, 445 Robertson Hall, Princeton University/Princeton, NJ 08544/Etats-Unis (2 aut.); NOAA Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Princeton University/Princeton, NJ 08540/Etats-Unis (3 aut., 4 aut.)</AF><DT>Publication en série; Niveau analytique</DT><SO>Atmospheric environment : (1994); ISSN 1352-2310; Royaume-Uni; Da. 2011; Vol. 45; No. 13; Pp. 2297-2309; Bibl. 1 p.</SO><LA>Anglais</LA><EA>We examine the potential global risk of increasing surface ozone (O<sub>3</sub>) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O<sub>3</sub> pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O<sub>3</sub> precursor emissions in 2030. We use simulated hourly O<sub>3</sub> concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O<sub>3</sub> exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O<sub>3</sub> on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O<sub>3</sub> exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth $17-35 billion USD<sub>2000</sub> annually (an increase of +$6-17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of + 0.3-0.5%), with total losses worth $12-21 billion annually (an increase of +$1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our calculations of crop production and economic losses are highly conservative. Our results suggest that O<sub>3</sub> pollution poses a growing threat to global food security even under an optimistic scenario of future ozone precursor emissions. Further efforts to reduce surface O<sub>3</sub> concentrations thus provide an excellent opportunity to increase global grain yields without the environmental degradation associated with additional fertilizer application or land cultivation.</EA><CC>001D16C</CC><FD>Ozone; Pollution; Trajectoire; Changement climatique; Prévision pollution atmosphérique; Précurseur; Modélisation; Traceur; Sol agricole; Production agricole; Agriculture; Industrie alimentaire; Engrais; Fertilisation; Phénomène transport; Localisation source</FD><FG>Climatologie dynamique</FG><ED>Ozone; Pollution; Trajectory; Climate change; Atmospheric pollution forecasting; Precursor; Modeling; Tracers; Agricultural soil; Agricultural production; Agriculture; Food industry; Fertilizers; Fertilization; Transport process; Source localization</ED><EG>Dynamical climatology</EG><SD>Ozono; Polución; Trayectoria; Cambio climático; Previsión contaminación del ambiente; Precursor; Modelización; Trazador; Suelo agrícola; Producción agrícola; Agricultura; Industria alimenticia; Fertilizante; Fertilización; Fenómeno transporte; Localización fuente</SD><LO>INIST-8940B.354000192901550150</LO><ID>11-0255955</ID></server></inist></record>Pour manipuler ce document sous Unix (Dilib)
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