Atmospheric impacts of perennial crop cultivation as biomass and energy sources

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uef.fi

PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND Dissertations in Forestry and Natural Sciences

ISBN 978-952-61-2980-8 ISSN 1798-5668

Dissertations in Forestry and Natural Sciences

DISSERTATIONS | SAARA E. LIND | ATMOSPHERIC IMPACTS OF PERENNIAL CROP CULTIVATION AS BIOMASS... | No 32

SAARA E. LIND

ATMOSPHERIC IMPACTS OF PERENNIAL CROP CULTIVATION AS BIOMASS AND ENERGY SOURCES

PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND

Bioenergy can be used to replace fossil fuels as energy sources and thus mitigate climate change. Here, atmospheric impacts of two perennial cropping systems, timothy-meadow fescue and reed canary grass, were estimated using greenhouse gas exchange data and crop

yields. While timothy-meadow fescue system was a larger sink of greenhouse gases and used fertilizer nitrogen more efficiently, reed canary grass was the climate-smart bioenergy

production choice. Energy production from perennial biomass was more climate-smart

when compared with coal.

SAARA E. LIND

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ATMOSPHERIC IMPACTS OF PERENNIAL CROP CULTIVATION AS BIOMASS AND

ENERGY SOURCES

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Saara E. Lind

ATMOSPHERIC IMPACTS OF PERENNIAL CROP CULTIVATION AS BIOMASS AND

ENERGY SOURCES

Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences

No 326

University of Eastern Finland Kuopio

2018

Academic dissertation

To be presented by permission of the Faculty of Science and Forestry for public examination in the Auditorium TTA in Tietoteknia building at the University of

Eastern Finland, Kuopio, on December, 18, 2018, at 12 o’clock noon

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Saara E. Lind

ATMOSPHERIC IMPACTS OF PERENNIAL CROP CULTIVATION AS BIOMASS AND

ENERGY SOURCES

Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences

No 326

University of Eastern Finland Kuopio

2018

Academic dissertation

To be presented by permission of the Faculty of Science and Forestry for public examination in the Auditorium TTA in Tietoteknia building at the University of

Eastern Finland, Kuopio, on December, 18, 2018, at 12 o’clock noon

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Grano Oy Jyväskylä, 2018

Editors: Pertti Pasanen, Matti Vornanen, Jukka Tuomela, Matti Tedre

Distribution: University of Eastern Finland / Sales of publications www.uef.fi/kirjasto

ISBN: 978-952-61-2980-8 (nid.) ISBN: 978-952-61-2981-5 (PDF)

ISSNL: 1798-5668 ISSN: 1798-5668 ISSN: 1798-5676 (PDF)

Author’s address: Saara E. Lind

University of Eastern Finland

Depart. of Environmental and Biological Sciences P.O. Box 1627

70211 KUOPIO, FINLAND email: saara.lind@uef.fi

Supervisors: Professor Emeritus Pertti Martikainen, Ph.D.

70211 KUOPIO, FINLAND email: pertti.martikainen@uef.fi Docent Narasinha Shurpali, Ph.D. University of Eastern Finland

70211 KUOPIO, FINLAND email: narasinha.shurpali@uef.fi

Associate Professor Marja Maljanen, Ph.D.

70211 KUOPIO, FINLAND email: marja.maljanen@uef.fi

Reviewers: Professor Kristiina Regina, Ph.D Natural resources institute Finland Bioeconomy and environment unit Tietotie

31600 Jokioinen, FINLAND email: kristiina.regina@luke.fi

Senior Research Scientist Annalea Lohila, Ph.D Finnish Meteorological Institute

Climate System Research P.O. Box 503

00101 HELSINKI, FINLAND email: annalea.lohila@fmi.fi

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Grano Oy Jyväskylä, 2018

Editors: Pertti Pasanen, Matti Vornanen, Jukka Tuomela, Matti Tedre

Distribution: University of Eastern Finland / Sales of publications www.uef.fi/kirjasto

ISBN: 978-952-61-2980-8 (nid.) ISBN: 978-952-61-2981-5 (PDF)

ISSNL: 1798-5668 ISSN: 1798-5668 ISSN: 1798-5676 (PDF)

Author’s address: Saara E. Lind

70211 KUOPIO, FINLAND email: saara.lind@uef.fi

Supervisors: Professor Emeritus Pertti Martikainen, Ph.D.

70211 KUOPIO, FINLAND email: pertti.martikainen@uef.fi Docent Narasinha Shurpali, Ph.D.

70211 KUOPIO, FINLAND email: narasinha.shurpali@uef.fi

Associate Professor Marja Maljanen, Ph.D.

70211 KUOPIO, FINLAND email: marja.maljanen@uef.fi

Reviewers: Professor Kristiina Regina, Ph.D Natural resources institute Finland Bioeconomy and environment unit Tietotie

31600 Jokioinen, FINLAND email: kristiina.regina@luke.fi

Senior Research Scientist Annalea Lohila, Ph.D Finnish Meteorological Institute

Climate System Research P.O. Box 503

00101 HELSINKI, FINLAND email: annalea.lohila@fmi.fi

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Opponent: Professor Ülo Mander

Physical Geography and Landscape Ecology unit Ülikooli 18

50090 TARTU, ESTONIA email: ulo.mander@ut.ee

7 Lind, Saara E.

Atmospheric impacts of perennial crop cultivation as biomass and energy sources Kuopio: University of Eastern Finland, 2018

Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences 2018; 326 ISBN: 978-952-61-2980-8 (nid.)

ISBN: 978-952-61-2981-5 (PDF) ISSNL: 1798-5668

ISSN: 1798-5668 ISSN: 1798-5676 (PDF)

ABSTRACT

An increase in the atmospheric concentration of greenhouse gases (GHG) is thought to be responsible for the current and future global climate change. Emissions from the energy supply and agriculture sector form 50% of the anthropogenic emissions and thus, reduction of the emission load from these sectors is important for climate change mitigation. Replacing fossil fuels with bioenergy is one of the strategies to reduce the GHG emissions of energy sector. However, the benefits of bioenergy could be lost due to GHG emissions from fertilized agricultural soils. Thus, it is important to identify GHG emissions of such bioenergy cropping systems for developing proper GHG mitigation strategies in the future.

Two perennial cropping systems, timothy and meadow fescue mixture (TIM) and reed canary grass (RCG), were studied on a boreal mineral soil in 2009-2011.

Seasonal and annual exchange of carbon dioxide (CO²), methane (CH⁴) and nitrous oxide (N²O) were determined using both manual flux measurement methods (all gases and treatments) and continuous eddy covariance method (RCG for CO² and N2O),. The key climatic and plant related variables were also recorded in order to identify their role on controlling the GHG exchange. Life cycle assesment was done to compare the climatic impacts of the studied cropping systems.

During the three-year study period, TIM (-8600 kg CO²-eq ha^-1) was more climate-smart cropping system than RCG (-3500 kg CO2-eq ha^-1) when exchange of CO², CH⁴ and N²O between the systems and the atmosphere were considered. TIM was also more efficient in using the applied fertilizer N than RCG. When the carbon (C) in the harvested yield was considered, both systems turned into C sources. If the biomass from these crops is used for energy production based on biogas, LCA results indicate that the overall emissions per unit of energy produced were lower for the RCG system (65 kg CO²-eq per MWh of energy) than for TIM (92 kg CO²-eq per MWh of energy). However, both systems were more climate-smart energy sources than coal, showing the potential of boreal perennial biomass to be used as energy source and to mitigate climate change.

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Opponent: Professor Ülo Mander

Physical Geography and Landscape Ecology unit Ülikooli 18

50090 TARTU, ESTONIA email: ulo.mander@ut.ee

7 Lind, Saara E.

Atmospheric impacts of perennial crop cultivation as biomass and energy sources Kuopio: University of Eastern Finland, 2018

ISBN: 978-952-61-2981-5 (PDF) ISSNL: 1798-5668

ISSN: 1798-5668 ISSN: 1798-5676 (PDF)

ABSTRACT

An increase in the atmospheric concentration of greenhouse gases (GHG) is thought to be responsible for the current and future global climate change. Emissions from the energy supply and agriculture sector form 50% of the anthropogenic emissions and thus, reduction of the emission load from these sectors is important for climate change mitigation. Replacing fossil fuels with bioenergy is one of the strategies to reduce the GHG emissions of energy sector. However, the benefits of bioenergy could be lost due to GHG emissions from fertilized agricultural soils. Thus, it is important to identify GHG emissions of such bioenergy cropping systems for developing proper GHG mitigation strategies in the future.

Two perennial cropping systems, timothy and meadow fescue mixture (TIM) and reed canary grass (RCG), were studied on a boreal mineral soil in 2009-2011.

Seasonal and annual exchange of carbon dioxide (CO²), methane (CH⁴) and nitrous oxide (N²O) were determined using both manual flux measurement methods (all gases and treatments) and continuous eddy covariance method (RCG for CO² and N2O),. The key climatic and plant related variables were also recorded in order to identify their role on controlling the GHG exchange. Life cycle assesment was done to compare the climatic impacts of the studied cropping systems.

During the three-year study period, TIM (-8600 kg CO²-eq ha^-1) was more climate-smart cropping system than RCG (-3500 kg CO2-eq ha^-1) when exchange of CO², CH⁴ and N²O between the systems and the atmosphere were considered. TIM was also more efficient in using the applied fertilizer N than RCG. When the carbon (C) in the harvested yield was considered, both systems turned into C sources. If the biomass from these crops is used for energy production based on biogas, LCA results indicate that the overall emissions per unit of energy produced were lower for the RCG system (65 kg CO²-eq per MWh of energy) than for TIM (92 kg CO²-eq per MWh of energy). However, both systems were more climate-smart energy sources than coal, showing the potential of boreal perennial biomass to be used as energy source and to mitigate climate change.

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Universal Decimal Classification: 502.174.3, 504.7, 582.546, 633.2

CAB Thesaurus: renewable resources; energy sources; bioenergy; biomass; perennials; crop production; mineral soils; grasslands; grasses; atmosphere; greenhouse effect; greenhouse gases; gas exchange; eddy covariance; emissions; carbon dioxide; methane; nitrous oxide;

Phleum pratense; Festuca pratensis; Phalaris arundinacea; life cycle assessment;

environmental impact; climate; climate change

9 Lind, Saara E.

Monivuotiset heinät biomassan ja energian lähteinä – Ilmastolliset vaikutukset Kuopio: Itä-Suomen yliopisto, 2018

ISBN: 978-952-61-2981-5 (PDF) ISSNL: 1798-5668

ISSN: 1798-5668 ISSN: 1798-5676 (PDF)

TIIVISTELMÄ

Kasvihuonekaasujen pitoisuuden nousu ilmakehässä johtaa globaaliin ilmastonmuutokseen. Energiatuotanto ja maataloussektori muodostavat yhdessä 50% ihmisperäisistä päästöistä. Näin ollen näiden sektoreiden päästöjen vähentämisellä voidaan hillitä ilmastonmuutosta. Fossiilisten polttoaineiden käytön korvaaminen bioenergialla on yksi tapa hillitä energiasektorin päästöjä.

Bioenergian tuotannon hyötyjä rajoittaa maatalousmaiden kasvihuonekaasupäästöt. Jotta kasvihuonekaasupäästöjä voidaan hillitä tulevaisuudessa, on tärkeää tuntea maatalouden systeemien todelliset kasvihuonekaasupäästöt.

Tässä tutkimuksessa oli mukana kaksi monivuotista heinää, timotei- nurminataseos ja ruokohelpi. Tutkimus tehtiin Itä-Suomessa sijaitsevalla mineraalimaapellolla vuosina 2009 – 2011. Kasvihuonekaasujen (hiilidioksidi (CO²), metaani (CH⁴) ja dityppioksidi (N²O)) kausivaihtelu ja vuositaseet määritettiin sekä jatkuvatoimisilla (ruokohelpi: CO2 ja N2O) että manuaalisilla mittaustekniikoilla (kaikki kaasut ja käsittelyt). Myös keskeiset ympäristö- ja kasvillisuusmuuttujat määritettiin. Elinkaarikaarianalyysillä verrattiin näitä kahta tutkittua heinää ja niiden ilmastollisia vaikutuksia.

Kasvihuonekaasutaseiden valossa timotei-nurminata (-8600 kg CO²-ekv ha^-1) oli ilmastoviisas valinta verrattuna ruohohelpeen (-3500 kg CO2-ekv ha^-1). Tämän lisäksi, timotei-nurminata käytti tehokkaammin lannoitetyppeä hyväkseen. Kun otettiin huomioon myös sadonkorjuun mukana pellolta poistunut hiili, molemmat heinät olivat hiilen lähteitä. Elinkaaritarkastelussa saatu sato käytettiin biokaasun tuotantoon ja sitä kautta energiantuotantoon. Kokonaispäästö oli tällöin timotei- nurminadasta tuotetulle energialle 65 kg CO²-ekv per MWh energiaa ja ruokohelvelle 92 kg CO²-ekv per MWh energiaa. Molempien heinien päästöt olivat kuitenkin pienemmät kuin hiilellä tuotettu energia, mikä osoittaa, että peltobiomassalla tuotetulla energialla voidaan vaikuttaa ilmastonmuutoksen hillintään.

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Universal Decimal Classification: 502.174.3, 504.7, 582.546, 633.2

CAB Thesaurus: renewable resources; energy sources; bioenergy; biomass; perennials; crop production; mineral soils; grasslands; grasses; atmosphere; greenhouse effect; greenhouse gases; gas exchange; eddy covariance; emissions; carbon dioxide; methane; nitrous oxide;

Phleum pratense; Festuca pratensis; Phalaris arundinacea; life cycle assessment;

environmental impact; climate; climate change

9 Lind, Saara E.

Monivuotiset heinät biomassan ja energian lähteinä – Ilmastolliset vaikutukset Kuopio: Itä-Suomen yliopisto, 2018

ISBN: 978-952-61-2981-5 (PDF) ISSNL: 1798-5668

ISSN: 1798-5668 ISSN: 1798-5676 (PDF)

TIIVISTELMÄ

Kasvihuonekaasujen pitoisuuden nousu ilmakehässä johtaa globaaliin ilmastonmuutokseen. Energiatuotanto ja maataloussektori muodostavat yhdessä 50% ihmisperäisistä päästöistä. Näin ollen näiden sektoreiden päästöjen vähentämisellä voidaan hillitä ilmastonmuutosta. Fossiilisten polttoaineiden käytön korvaaminen bioenergialla on yksi tapa hillitä energiasektorin päästöjä.

Bioenergian tuotannon hyötyjä rajoittaa maatalousmaiden kasvihuonekaasupäästöt. Jotta kasvihuonekaasupäästöjä voidaan hillitä tulevaisuudessa, on tärkeää tuntea maatalouden systeemien todelliset kasvihuonekaasupäästöt.

Tässä tutkimuksessa oli mukana kaksi monivuotista heinää, timotei- nurminataseos ja ruokohelpi. Tutkimus tehtiin Itä-Suomessa sijaitsevalla mineraalimaapellolla vuosina 2009 – 2011. Kasvihuonekaasujen (hiilidioksidi (CO²), metaani (CH⁴) ja dityppioksidi (N²O)) kausivaihtelu ja vuositaseet määritettiin sekä jatkuvatoimisilla (ruokohelpi: CO2 ja N2O) että manuaalisilla mittaustekniikoilla (kaikki kaasut ja käsittelyt). Myös keskeiset ympäristö- ja kasvillisuusmuuttujat määritettiin. Elinkaarikaarianalyysillä verrattiin näitä kahta tutkittua heinää ja niiden ilmastollisia vaikutuksia.

Kasvihuonekaasutaseiden valossa timotei-nurminata (-8600 kg CO²-ekv ha^-1) oli ilmastoviisas valinta verrattuna ruohohelpeen (-3500 kg CO2-ekv ha^-1). Tämän lisäksi, timotei-nurminata käytti tehokkaammin lannoitetyppeä hyväkseen. Kun otettiin huomioon myös sadonkorjuun mukana pellolta poistunut hiili, molemmat heinät olivat hiilen lähteitä. Elinkaaritarkastelussa saatu sato käytettiin biokaasun tuotantoon ja sitä kautta energiantuotantoon. Kokonaispäästö oli tällöin timotei- nurminadasta tuotetulle energialle 65 kg CO²-ekv per MWh energiaa ja ruokohelvelle 92 kg CO²-ekv per MWh energiaa. Molempien heinien päästöt olivat kuitenkin pienemmät kuin hiilellä tuotettu energia, mikä osoittaa, että peltobiomassalla tuotetulla energialla voidaan vaikuttaa ilmastonmuutoksen hillintään.

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Yleinen suomalainen asiasanasto: uusiutuvat energialähteet; bioenergia; biomassa;

kasvintuotanto; kasvinviljely; monivuotiset kasvit; boreaalinen vyöhyke; kivennäismaat;

ilmakehä; ilmasto; ilmastovaikutukset; elinkaariarviointi; kasvihuoneilmiö;

kasvihuonekaasut; päästöt; hiilidioksidi; metaani; dityppioksidi; heinäkasvit; timotei;

nurminata; ruokohelpi

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ACKNOWLEDGEMENTS

I would like to express my gratitude to my supervisors for their continuous support of my PhD study, their endless patience with my schedules and side quests and to their motivation on research. I also want to acknowledge all the co-authors who participated in preparing the manuscripts included in this thesis.

I would like to thank Natural Resources Institute Finland Maaninka station and their personnel for the invaluable help during the field campaign. Without their support, it would not be possible to conduct this research. My sincerely thanks the numerous students and trainees who helped to maintain the field and carry out the field measurements. Without their blood, sweat and tears there would be no data to publish. My sincere thanks also goes to the members of the Biogeochemistry research group and personnel at the Department of Environmental and Biological Sciences whose support made it possible to write this thesis.

I am grateful to Ülo Mander for serving as an opponent in the public defense of this thesis. Annalea Lohila and Kristiina Regina are acknowledged for pre- examination of this thesis. Their insightful comments further improved the thesis.

This PhD study would have not been possible without funding. The PhD study was part of a “Competitive and sustainable bioenergy production in Finnish agriculture (MINHELPI)” funded by Ministry of Agriculture and Forestry during 2009 – 2011.

Funding was received also from UEF infrastructure funding, strategic funding of Agrifood Research Finland and FiDiPro –funding from Academy of Finland and TEKES. I am also grateful of the support by Finnish Doctoral Programme in Environmental Science and Technology (EnSTe), Niemi-foundation and University of Eastern Finland. I also want to acknowledge the support from Teachers' Unemployment Fund.

Finally, I would like to thank my friends for their support throughout this process and on my life in general.

To Otto.

Kuopio, 1^st October 2018 Saara Lind

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Yleinen suomalainen asiasanasto: uusiutuvat energialähteet; bioenergia; biomassa;

kasvintuotanto; kasvinviljely; monivuotiset kasvit; boreaalinen vyöhyke; kivennäismaat;

ilmakehä; ilmasto; ilmastovaikutukset; elinkaariarviointi; kasvihuoneilmiö;

kasvihuonekaasut; päästöt; hiilidioksidi; metaani; dityppioksidi; heinäkasvit; timotei;

nurminata; ruokohelpi

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ACKNOWLEDGEMENTS

I would like to express my gratitude to my supervisors for their continuous support of my PhD study, their endless patience with my schedules and side quests and to their motivation on research. I also want to acknowledge all the co-authors who participated in preparing the manuscripts included in this thesis.

I would like to thank Natural Resources Institute Finland Maaninka station and their personnel for the invaluable help during the field campaign. Without their support, it would not be possible to conduct this research. My sincerely thanks the numerous students and trainees who helped to maintain the field and carry out the field measurements. Without their blood, sweat and tears there would be no data to publish. My sincere thanks also goes to the members of the Biogeochemistry research group and personnel at the Department of Environmental and Biological Sciences whose support made it possible to write this thesis.

I am grateful to Ülo Mander for serving as an opponent in the public defense of this thesis. Annalea Lohila and Kristiina Regina are acknowledged for pre- examination of this thesis. Their insightful comments further improved the thesis.

This PhD study would have not been possible without funding. The PhD study was part of a “Competitive and sustainable bioenergy production in Finnish agriculture (MINHELPI)” funded by Ministry of Agriculture and Forestry during 2009 – 2011.

Funding was received also from UEF infrastructure funding, strategic funding of Agrifood Research Finland and FiDiPro –funding from Academy of Finland and TEKES. I am also grateful of the support by Finnish Doctoral Programme in Environmental Science and Technology (EnSTe), Niemi-foundation and University of Eastern Finland. I also want to acknowledge the support from Teachers' Unemployment Fund.

Finally, I would like to thank my friends for their support throughout this process and on my life in general.

To Otto.

Kuopio, 1^st October 2018 Saara Lind

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LIST OF ABBREVIATIONS

BARE soil without vegetation BR belowground respiration

C carbon

CH4 methane

CO2 carbon dioxide

CO²-eq carbon dioxide equivalent GPP gross primary production GWP global warming potential

GWPtotal sum of annual NEE, CH4 and N2O as CO2 equivalents

LCA life cycle assessment

N nitrogen

N²O nitrous oxide

NEE net ecosystem CO² exchange RCG reed canary grass

RR root respiration SR soil respiration

TER total ecosystem respiration

TIM timothy and meadow fescue mixture

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LIST OF ABBREVIATIONS

BARE soil without vegetation BR belowground respiration

C carbon

CH4 methane

CO2 carbon dioxide

CO²-eq carbon dioxide equivalent GPP gross primary production GWP global warming potential

GWPtotal sum of annual NEE, CH4 and N2O as CO2 equivalents

LCA life cycle assessment

N nitrogen

N²O nitrous oxide

NEE net ecosystem CO2 exchange RCG reed canary grass

RR root respiration SR soil respiration

TER total ecosystem respiration

TIM timothy and meadow fescue mixture

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LIST OF ORIGINAL PUBLICATIONS

This thesis is based on data presented in the following articles, referred to by the Roman Numerals I-IV.

I Lind SE, Shurpali NJ, Peltola O, Mammarella I, Hyvönen N, Maljanen M, Räty M, Virkajärvi P and Martikainen PJ. (2016). Carbon dioxide exchange of a perennial bioenergy crop cultivation on a mineral soil. Biogeosciences 13:

1255-1268.

II Shurpali NJ, Rannik Ü, Jokinen S, Lind S, Biasi C, Mammarella I, Peltola O, Pihlatie M, Hyvönen N, Räty M, Haapanala S, Zahnizer M, Virkajärvi P, Vesala T and Martikainen PJ. (2016). Neglecting diurnal variations leads to uncertainties in terrestrial nitrous oxide emissions. Scientific Reports 6:25739.

III Lind SE, Virkajärvi P, Hyvönen NP, Maljanen M, Kivimäenpää M, Jokinen S, Antikainen S, Latva M, Räty M, Martikainen PJ and Shurpali NJ. Carbon dioxide and methane exchange of a perennial grassland on a boreal mineral soil. Submitted to Agriculture, Ecosystems & Environment.

IV Lind SE, Maljanen M, Hyvönen NP, Kutvonen J, Jokinen S, Räty M,

Virkajärvi P, Martikainen PJ and Shurpali NJ. Nitrous oxide emissions from perennial grass cropping systems on a boreal mineral soil. Submitted to Biogeosciences.

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14 15

LIST OF ORIGINAL PUBLICATIONS

This thesis is based on data presented in the following articles, referred to by the Roman Numerals I-IV.

I Lind SE, Shurpali NJ, Peltola O, Mammarella I, Hyvönen N, Maljanen M, Räty M, Virkajärvi P and Martikainen PJ. (2016). Carbon dioxide exchange of a perennial bioenergy crop cultivation on a mineral soil. Biogeosciences 13:

1255-1268.

II Shurpali NJ, Rannik Ü, Jokinen S, Lind S, Biasi C, Mammarella I, Peltola O, Pihlatie M, Hyvönen N, Räty M, Haapanala S, Zahnizer M, Virkajärvi P, Vesala T and Martikainen PJ. (2016). Neglecting diurnal variations leads to uncertainties in terrestrial nitrous oxide emissions. Scientific Reports 6:25739.

III Lind SE, Virkajärvi P, Hyvönen NP, Maljanen M, Kivimäenpää M, Jokinen S, Antikainen S, Latva M, Räty M, Martikainen PJ and Shurpali NJ. Carbon dioxide and methane exchange of a perennial grassland on a boreal mineral soil. Submitted to Agriculture, Ecosystems & Environment.

IV Lind SE, Maljanen M, Hyvönen NP, Kutvonen J, Jokinen S, Räty M,

Virkajärvi P, Martikainen PJ and Shurpali NJ. Nitrous oxide emissions from perennial grass cropping systems on a boreal mineral soil. Submitted to Biogeosciences.

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AUTHOR’S CONTRIBUTION

I) Author contributed to the design of the study. She was responsible for the data collection at the site and processing of the data. She wrote the first version of the manuscript together with Narasinha Shurpali after which the co-authors contributed to the writing process.

II) Author contributed to the design of the study. She was responsible for the eddy covariance and supporting data collection. Narasinha Shurpali wrote the first version of the manuscript after which author together with the co- authors contributed to the writing process.

III) Author contributed to the study design and was mainly responsible for data collection, processing and writing the manuscript.

IV) Author contributed to the study design and was mainly responsible for data collection, processing and writing the manuscript.

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AUTHOR’S CONTRIBUTION

I) Author contributed to the design of the study. She was responsible for the data collection at the site and processing of the data. She wrote the first version of the manuscript together with Narasinha Shurpali after which the co-authors contributed to the writing process.

II) Author contributed to the design of the study. She was responsible for the eddy covariance and supporting data collection. Narasinha Shurpali wrote the first version of the manuscript after which author together with the co- authors contributed to the writing process.

III) Author contributed to the study design and was mainly responsible for data collection, processing and writing the manuscript.

IV) Author contributed to the study design and was mainly responsible for data collection, processing and writing the manuscript.

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1 GENERAL INTRODUCTION

1.1 CLIMATE CHANGE AND MITIGATION ACTIONS

An increase in the atmospheric concentration of greenhouse gases (GHG) is thought to be responsible for the current and future global climate change. The extent of climate change and its risks to natural and human systems depends on whether the GHG emissions can be reduced (Collins et al., 2013). To mitigate climate change, global actions are being taken. In 2015, the Paris agreement was adopted by 197 countries. The agreement aims at holding global warming to well below 2 °C compared to that of the preindustrial level and to pursue efforts to limit it to 1.5 °C (https://unfccc.int/). To date, 180 parties have ratified the agreement. European Union (EU) is amongst those parties. To mitigate climate change, EU targets to reduce the GHG emissions by 20 and 40% compared to 1990 level (https://ec.europa.eu/). In addition, the aim is to increase the share of the renewable energy use and energy use efficiency. In the long-term, the aim is to turn Europe into a high-energy efficient and low-carbon economy.

1.2 IMPORTANCE OF AGRICULTURE AND BIOENERGY IN GLOBAL GREENHOUSE GAS BUDGETS

Three of the most important GHGs are carbon dioxide (CO²), methane (CH⁴) and nitrous oxide (N²O). Their role in climate change is important since they amount 80% of the total radiative forcing, i.e. change in the net radiative flux, of the well- mixed gases (Ciais et al., 2013). Atmospheric concentration of all these three gases has been increasing since pre-industrial times and currently, the increase has been 2.2 ppm yr^-1 for CO² and 6.8 and 0.90 ppb yr^-1 for CH⁴ and N²O, respectively, during the last decade (WMO, 2017). In 2016, their global abundance was 403 ppm for CO2

and 1900 and 330 ppb for CH4 and N2O, respectively (WMO, 2017). These three GHGs have both natural and anthropogenic sources. Natural sources for CO² are respiration and fires, for CH⁴ wetlands and termites and for N²O soils with natural vegetation and lightning (Ciais et al., 2013). Anthropogenic sources for CO2 are e.g.

fossil fuel combustion and land use change, for CH4 e.g. rice cultivation and ruminants and for N²O agricultural soils and biomass combustion (Ciais et al., 2013). When these emissions are grouped based on economical sectors, 35% of the GHG emissions originate from energy supply sector (Bruckner et al., 2014) and 11

% from agriculture (Smith et al., 2014). These two categories comprise almost 50%

of the anthropogenic GHG emissions. Thus reducing the GHG load from these sectors is important in climate change mitigation.

Replacing fossil fuels with bioenergy is one of the strategies to reduce CO² emissions from energy sector. However, bioenergy is not considered carbon (C) neutral due to GHG emissions that can occur during the biomass production, field

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1 GENERAL INTRODUCTION

1.1 CLIMATE CHANGE AND MITIGATION ACTIONS

An increase in the atmospheric concentration of greenhouse gases (GHG) is thought to be responsible for the current and future global climate change. The extent of climate change and its risks to natural and human systems depends on whether the GHG emissions can be reduced (Collins et al., 2013). To mitigate climate change, global actions are being taken. In 2015, the Paris agreement was adopted by 197 countries. The agreement aims at holding global warming to well below 2 °C compared to that of the preindustrial level and to pursue efforts to limit it to 1.5 °C (https://unfccc.int/). To date, 180 parties have ratified the agreement. European Union (EU) is amongst those parties. To mitigate climate change, EU targets to reduce the GHG emissions by 20 and 40% compared to 1990 level (https://ec.europa.eu/). In addition, the aim is to increase the share of the renewable energy use and energy use efficiency. In the long-term, the aim is to turn Europe into a high-energy efficient and low-carbon economy.

1.2 IMPORTANCE OF AGRICULTURE AND BIOENERGY IN GLOBAL GREENHOUSE GAS BUDGETS

Three of the most important GHGs are carbon dioxide (CO²), methane (CH⁴) and nitrous oxide (N²O). Their role in climate change is important since they amount 80% of the total radiative forcing, i.e. change in the net radiative flux, of the well- mixed gases (Ciais et al., 2013). Atmospheric concentration of all these three gases has been increasing since pre-industrial times and currently, the increase has been 2.2 ppm yr^-1 for CO² and 6.8 and 0.90 ppb yr^-1 for CH⁴ and N²O, respectively, during the last decade (WMO, 2017). In 2016, their global abundance was 403 ppm for CO2

and 1900 and 330 ppb for CH4 and N2O, respectively (WMO, 2017). These three GHGs have both natural and anthropogenic sources. Natural sources for CO² are respiration and fires, for CH⁴ wetlands and termites and for N²O soils with natural vegetation and lightning (Ciais et al., 2013). Anthropogenic sources for CO2 are e.g.

fossil fuel combustion and land use change, for CH4 e.g. rice cultivation and ruminants and for N²O agricultural soils and biomass combustion (Ciais et al., 2013). When these emissions are grouped based on economical sectors, 35% of the GHG emissions originate from energy supply sector (Bruckner et al., 2014) and 11

% from agriculture (Smith et al., 2014). These two categories comprise almost 50%

of the anthropogenic GHG emissions. Thus reducing the GHG load from these sectors is important in climate change mitigation.

Replacing fossil fuels with bioenergy is one of the strategies to reduce CO² emissions from energy sector. However, bioenergy is not considered carbon (C) neutral due to GHG emissions that can occur during the biomass production, field

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management and transportation of yield. Additionally, field based biomass production is criticized for its potential for reducing soil C stocks and increasing N²O emissions (Crutzen et al., 2008; Creutzig et al., 2015). Agricultural soils are especially important as a source of atmospheric N²O since approximately 30% of the anthropogenic N²O emissions originate from them (Syakila and Kroeze, 2011;

Ciais et al., 2013). These emissions are affected by the fertilizer type, the amount of fertilizer applied and the crop type as well as climatic variables such as temperature and moisture (Hénault et al., 2012; Tian et al., 2015). In the future, the need for food and energy will increase due to population growth. This will affect agricultural practices and the amount of land used for agriculture. Therefore, it is important to determine the GHG budgets of the cropping systems in order to carry out robust life cycle assessments (LCA) while developing proper GHG mitigation strategies in the future.

1.3 PERENNIAL CROPPING SYSTEMS

In perennial agriculture, a cropping system is cultivated more than two years without the need of annual establishment. When compared with annual cropping system where the crop is planted annually, the positive impacts of perennial systems have been recognized. Due to the nature of perennial agriculture, it is less intense in terms of use of machinery and field work than annual systems as annual tilling and sowing are not required. This reduces both time that is required for the fieldwork and the emissions associated with the field machinery. Since annual establishment is not required, the perennial crops benefit from the early start of the seasonal growth and can grow over the entire growing season (Dohleman and Long, 2009). Owing to the year-around vegetation cover, the perennial systems reduce the risk of erosion and the nutrient run-off and can maintain more soil C and N than the annual crops (Saarijärvi et al., 2004; Glover et al., 2010). Perennial agriculture supports more sustainability (Glover et al., 2010) by more complex above- and below-ground food webs, higher plant diversity and greater belowground biomass. From the GHG view point, annual CO2 sequestration of perennial cropping systems, both on organic and mineral soils, is higher than that of the annual systems (In Chapter 4, Table 3). In addition, N²O emissions of perennial cropping systems tend to be lower when compared to annual systems (In Chapter 5, Figure 6). In Finland, amongst the most important perennial grassland species are timothy (Phleum prafense) and meadow fescue (Festuca pratensis Huds.). Reed canary grass (RCG, Phalaris arundinacea L.) is also a perennial grass, which has been considered as an important bioenergy crop in Finland. These plant species are well adapted to boreal climate.

1.3.1 Timothy and meadow fescue

Timothy is native to Europe, Asia and North Africa (Stewart et al., 2011). In Finland, timothy is a common archaeophyte with the exception of northern Finland

21 where it is considered neophyta (Hämet-Ahti et al., 1998). Natural habitats of timothy are meadows, urban areas and roadsides. Timothy grows up to 100 cm and it has up to 10 mm wide leaves. The panicle is easy to recognize as it is dense, green and up to 9 cm long (Hämet-Ahti et al., 1998; Casler and Kallenbach, 2007).

Timothy has the shallowest root system of the cool-season grasses with economical value (Casler and Kallenbach, 2007).

Meadow fescue is native to Europe and Asia (Fjellheim et al., 2006). In southern Finland, it is a common archaeophyte and a less common neophyte in northern Finland (Hämet-Ahti et al., 1998). Meadow fescue grows naturally on meadows, roadsides and wastelands. Meadow fescue grows up to 100 cm, width of the leaves is up to 8 mm and panicle with spikelet is up to 25 cm long. Its root system is fibrous and loose.

Timothy and meadow fescue are amongst the top grassland species cultivated in Finland. They are cultivated both as monocultures but also as mixtures (Nissinen and Hakkola, 1994; Casler and Kallenbach, 2007). The age of such grassland in Finland is short, in general, between 4 to 5 years (Virkajärvi et al., 2015). As the crop ages, the yield drops due to the winter damages and number of weeds increases (Nissinen and Hakkola, 1994). The harvested biomass is used as silage or hay in cattle farms and as a substrate for biogas reactors (Lehtomäki et al., 2008).

1.3.2 Reed canary grass

Reed canary grass (RCG) grows natively in temperate North America, Europe and Asia (Piper, 1942). Also in Finland, RCG is native across the country (Hämet-Ahti et al., 1998). Reed canary grass grows naturally in the vicinity of water systems such as oceans, lakes, rivers and streams but also along roadside ditches. It tolerates a range of conditions from flooding to drought and is adapted to different temperatures (Arny et al., 1929; Klebesadel and Dofing, 1991; Wilkins and Hughes, 1932). RCG can reach aboveground height up to 200 cm, with a leaf blade up to 20 mm wide and a stem diameter up to 6 mm. The inflorescence is a panicle up to 20 cm long. It overwinters with the help of underground rhizome and root networks, which can form up to 50% of the total biomass (Kätterer and Andrén, 1999).

RCG grassland has a long rotation cycle, up to 15 years. The agricultural practices vary depending on the use of the harvested biomass. When cultivated to be used as fuel in power plants, it is common in Nordic countries to follow the delayed harvest method. In this method, the yield is harvested in the following spring to improve the quality of the biomass for burning process (Burvall, 1997).

Reed canary grass is used also for fodder and bedding, bioenergy and biofuel production, wastewater disposal and pollution abatement (Pasila and Kymäläinen, 2000; Lewandowski et al., 2003; Powlson et al., 2005; Lehtomäki et al., 2008;

Lakaniemi et al., 2010).

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management and transportation of yield. Additionally, field based biomass production is criticized for its potential for reducing soil C stocks and increasing N²O emissions (Crutzen et al., 2008; Creutzig et al., 2015). Agricultural soils are especially important as a source of atmospheric N²O since approximately 30% of the anthropogenic N²O emissions originate from them (Syakila and Kroeze, 2011;

Ciais et al., 2013). These emissions are affected by the fertilizer type, the amount of fertilizer applied and the crop type as well as climatic variables such as temperature and moisture (Hénault et al., 2012; Tian et al., 2015). In the future, the need for food and energy will increase due to population growth. This will affect agricultural practices and the amount of land used for agriculture. Therefore, it is important to determine the GHG budgets of the cropping systems in order to carry out robust life cycle assessments (LCA) while developing proper GHG mitigation strategies in the future.

1.3 PERENNIAL CROPPING SYSTEMS

In perennial agriculture, a cropping system is cultivated more than two years without the need of annual establishment. When compared with annual cropping system where the crop is planted annually, the positive impacts of perennial systems have been recognized. Due to the nature of perennial agriculture, it is less intense in terms of use of machinery and field work than annual systems as annual tilling and sowing are not required. This reduces both time that is required for the fieldwork and the emissions associated with the field machinery. Since annual establishment is not required, the perennial crops benefit from the early start of the seasonal growth and can grow over the entire growing season (Dohleman and Long, 2009). Owing to the year-around vegetation cover, the perennial systems reduce the risk of erosion and the nutrient run-off and can maintain more soil C and N than the annual crops (Saarijärvi et al., 2004; Glover et al., 2010). Perennial agriculture supports more sustainability (Glover et al., 2010) by more complex above- and below-ground food webs, higher plant diversity and greater belowground biomass. From the GHG view point, annual CO2 sequestration of perennial cropping systems, both on organic and mineral soils, is higher than that of the annual systems (In Chapter 4, Table 3). In addition, N²O emissions of perennial cropping systems tend to be lower when compared to annual systems (In Chapter 5, Figure 6). In Finland, amongst the most important perennial grassland species are timothy (Phleum prafense) and meadow fescue (Festuca pratensis Huds.). Reed canary grass (RCG, Phalaris arundinacea L.) is also a perennial grass, which has been considered as an important bioenergy crop in Finland. These plant species are well adapted to boreal climate.

1.3.1 Timothy and meadow fescue

Timothy is native to Europe, Asia and North Africa (Stewart et al., 2011). In Finland, timothy is a common archaeophyte with the exception of northern Finland

21 where it is considered neophyta (Hämet-Ahti et al., 1998). Natural habitats of timothy are meadows, urban areas and roadsides. Timothy grows up to 100 cm and it has up to 10 mm wide leaves. The panicle is easy to recognize as it is dense, green and up to 9 cm long (Hämet-Ahti et al., 1998; Casler and Kallenbach, 2007).

Timothy has the shallowest root system of the cool-season grasses with economical value (Casler and Kallenbach, 2007).

Meadow fescue is native to Europe and Asia (Fjellheim et al., 2006). In southern Finland, it is a common archaeophyte and a less common neophyte in northern Finland (Hämet-Ahti et al., 1998). Meadow fescue grows naturally on meadows, roadsides and wastelands. Meadow fescue grows up to 100 cm, width of the leaves is up to 8 mm and panicle with spikelet is up to 25 cm long. Its root system is fibrous and loose.

Timothy and meadow fescue are amongst the top grassland species cultivated in Finland. They are cultivated both as monocultures but also as mixtures (Nissinen and Hakkola, 1994; Casler and Kallenbach, 2007). The age of such grassland in Finland is short, in general, between 4 to 5 years (Virkajärvi et al., 2015). As the crop ages, the yield drops due to the winter damages and number of weeds increases (Nissinen and Hakkola, 1994). The harvested biomass is used as silage or hay in cattle farms and as a substrate for biogas reactors (Lehtomäki et al., 2008).

1.3.2 Reed canary grass

Reed canary grass (RCG) grows natively in temperate North America, Europe and Asia (Piper, 1942). Also in Finland, RCG is native across the country (Hämet-Ahti et al., 1998). Reed canary grass grows naturally in the vicinity of water systems such as oceans, lakes, rivers and streams but also along roadside ditches. It tolerates a range of conditions from flooding to drought and is adapted to different temperatures (Arny et al., 1929; Klebesadel and Dofing, 1991; Wilkins and Hughes, 1932). RCG can reach aboveground height up to 200 cm, with a leaf blade up to 20 mm wide and a stem diameter up to 6 mm. The inflorescence is a panicle up to 20 cm long. It overwinters with the help of underground rhizome and root networks, which can form up to 50% of the total biomass (Kätterer and Andrén, 1999).

RCG grassland has a long rotation cycle, up to 15 years. The agricultural practices vary depending on the use of the harvested biomass. When cultivated to be used as fuel in power plants, it is common in Nordic countries to follow the delayed harvest method. In this method, the yield is harvested in the following spring to improve the quality of the biomass for burning process (Burvall, 1997).

Reed canary grass is used also for fodder and bedding, bioenergy and biofuel production, wastewater disposal and pollution abatement (Pasila and Kymäläinen, 2000; Lewandowski et al., 2003; Powlson et al., 2005; Lehtomäki et al., 2008;

Lakaniemi et al., 2010).

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1.4 LIFE CYCLE ASSESSMENT (LCA) OF BIOENERGY

Life cycle assessment (LCA) is a framework for estimation of environmental impact associated with a product within its life cycle. Based on the LCA ISO standard (ISO 14040:2006) the life cycle includes all steps from raw material production to disposal of the product in order to select the least burdensome options. However, the LCAs are adopted to focus on selected environmental impacts such as climate change, eutrophication or land use along the life cycle (Rebitzer et al., 2004). LCA is being increasingly used to estimate environmental impacts of agriculture. Based on the Web of Science search results for “life cycle assessment agriculture”, number of publications has increased from 38 in 1999 to 686 in 2017. The assessments have been carried out for farms (e.g. Haas et al., 2000; Beauchemin et al., 2010), bioenergy (e.g. Shurpali et al., 2010; Järveoja et al., 2013; Dias et al., 2017) and animal based products (e.g. Thomassen et al., 2008; Peters et al., 2010; Pelletier, 2018; Thévenot et al., 2018). However, comparison between LCAs is complicated due to lack of consistency in the analyses (Cherubini and Strømman, 2011; Caffrey and Veal, 2013).

The system boundaries for a life cycle assessment determine which processes and activities are considered in the overall LCA. Such analysis take into account the material and energy flows of primary processes, together with the extraction of raw materials. The use of a product, such as crop biomass of grassland, is also an important factor in the LCA. In general, LCA of cropping systems includes GHG balance of the cropping system, machinery and different energy inputs and outputs (Shurpali et al., 2010; Hakala et al., 2012; Järveoja et al., 2013).

1.5 SITE DESCRIPTION

1.5.1 Background

The study site is located in Maaninka (63˚09'49"N, 27˚14'3"E, 89 m above the mean sea level) in eastern Finland (Figure 1). Mean annual air temperature is 3.2°C in the region (reference period 1981-2010; Pirinen et al., 2012). Annual air temperature was about the long-term mean in 2009 (3.4°C), cooler in 2010 (2.0°C) and warmer in 2011 (4.4°C). The coldest month is February (-9.4°C) and the warmest July (17.0°C).

Mean annual precipitation is 612 mm (reference period 1981-2010; Pirinen et al., 2012). At the site, annual precipitation was less in 2009 (420 mm) and 2010 (520 mm) than the long-term mean but higher in 2011 (670 mm).

23 Figure 1 Location of the study site. (Map: Google, 2018).

The site is a 6.3 ha agricultural field. Prior to this experiment, it was cultivated with grass (Phleum pratense L.; Festuca pratensis Huds), barley (Hordeum vulgare L.) or oat (Avena sativa L.) during the last ten years. In addition, a pilot field campaign was carried out in 2008. The field was fertilized with dairy cow slurry (40 tons ha^-1 containing 120 kg N ha^-1, 19 kg P ha^-1 and 112 kg K ha^-1) in April 2008. Reed canary grass (RCG, Phalaris arundinacea L., variety ’Palaton’) was sown in mid-June 2008.

The seeds germinated poorly and plant growth was low. Therefore, glyphosate, a systemic herbicide, was applied in September and the field was ploughed in November 2008. The field was left fallow during winter 2008 – 2009.

1.5.2 Soil characteristics

The soil is classified as a Haplic Cambisol/Regosol (Hypereutric, Siltic) (IUSS Working Group WRB, 2007), the topsoil being generally silt loam based on the U. S.

Department of Agriculture (USDA) textural classification system. Other soil related variables are given in Table 1. Details of the analyses are given in Chapter 2.

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1.4 LIFE CYCLE ASSESSMENT (LCA) OF BIOENERGY

Life cycle assessment (LCA) is a framework for estimation of environmental impact associated with a product within its life cycle. Based on the LCA ISO standard (ISO 14040:2006) the life cycle includes all steps from raw material production to disposal of the product in order to select the least burdensome options. However, the LCAs are adopted to focus on selected environmental impacts such as climate change, eutrophication or land use along the life cycle (Rebitzer et al., 2004). LCA is being increasingly used to estimate environmental impacts of agriculture. Based on the Web of Science search results for “life cycle assessment agriculture”, number of publications has increased from 38 in 1999 to 686 in 2017. The assessments have been carried out for farms (e.g. Haas et al., 2000; Beauchemin et al., 2010), bioenergy (e.g. Shurpali et al., 2010; Järveoja et al., 2013; Dias et al., 2017) and animal based products (e.g. Thomassen et al., 2008; Peters et al., 2010; Pelletier, 2018; Thévenot et al., 2018). However, comparison between LCAs is complicated due to lack of consistency in the analyses (Cherubini and Strømman, 2011; Caffrey and Veal, 2013).

The system boundaries for a life cycle assessment determine which processes and activities are considered in the overall LCA. Such analysis take into account the material and energy flows of primary processes, together with the extraction of raw materials. The use of a product, such as crop biomass of grassland, is also an important factor in the LCA. In general, LCA of cropping systems includes GHG balance of the cropping system, machinery and different energy inputs and outputs (Shurpali et al., 2010; Hakala et al., 2012; Järveoja et al., 2013).

1.5 SITE DESCRIPTION

1.5.1 Background

The study site is located in Maaninka (63˚09'49"N, 27˚14'3"E, 89 m above the mean sea level) in eastern Finland (Figure 1). Mean annual air temperature is 3.2°C in the region (reference period 1981-2010; Pirinen et al., 2012). Annual air temperature was about the long-term mean in 2009 (3.4°C), cooler in 2010 (2.0°C) and warmer in 2011 (4.4°C). The coldest month is February (-9.4°C) and the warmest July (17.0°C).

Mean annual precipitation is 612 mm (reference period 1981-2010; Pirinen et al., 2012). At the site, annual precipitation was less in 2009 (420 mm) and 2010 (520 mm) than the long-term mean but higher in 2011 (670 mm).

23 Figure 1 Location of the study site. (Map: Google, 2018).

The site is a 6.3 ha agricultural field. Prior to this experiment, it was cultivated with grass (Phleum pratense L.; Festuca pratensis Huds), barley (Hordeum vulgare L.) or oat (Avena sativa L.) during the last ten years. In addition, a pilot field campaign was carried out in 2008. The field was fertilized with dairy cow slurry (40 tons ha^-1 containing 120 kg N ha^-1, 19 kg P ha^-1 and 112 kg K ha^-1) in April 2008. Reed canary grass (RCG, Phalaris arundinacea L., variety ’Palaton’) was sown in mid-June 2008.

The seeds germinated poorly and plant growth was low. Therefore, glyphosate, a systemic herbicide, was applied in September and the field was ploughed in November 2008. The field was left fallow during winter 2008 – 2009.

1.5.2 Soil characteristics

The soil is classified as a Haplic Cambisol/Regosol (Hypereutric, Siltic) (IUSS Working Group WRB, 2007), the topsoil being generally silt loam based on the U. S.

Department of Agriculture (USDA) textural classification system. Other soil related variables are given in Table 1. Details of the analyses are given in Chapter 2.

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Table 1 General soil characteristics (mean ± standard deviation) of top soil (0-18 cm).

Soil characteristic Mean ± SD

Clay (%) 25 ± 5.6

Silt (%) 53 ± 9.0

Sand (%) 22 ± 7.8

pH (H²O) 5.8 ± 0.19

Electrical conductivity (mS m^-1) 14 ± 2.4 Soil organic matter (%) 5.2 ± 0.90 Particle density (g cm^-3) 2.7 ± 0.014 Bulk density (g cm^-3) 1.1 ± 0.11 Organic carbon (%) 3.0 ± 0.52 Total nitrogen (%) 0.2 ± 0.03

C/N 15 ± 0.40

K (mg dm^-3 soil) 100 ± 13

P (mg dm^-3soil) 5.4 ± 1.3 Field capacity (%, soil moisture (v/v)) 40 ± 1.2 Wilting point (%, soil moisture (v/v)) 22 ± 0.80 1.5.3 Experimental design

The experimental design consisted of the main field and three experimental plots therein (Figure 2a). The main field was cultivated with reed canary grass (RCG, Phalaris arundinacea L., Figure 3a). Masts for eddy covariance (EC) measurements and for weather station were located in the middle of the field (Figure 2b). The net radiometer mast was located further away in order to avoid shading from the masts and instrument cabin. The blue hut in the middle of the field housed the EC gas analyzers.

Each of the three experimental plots were divided into three subplots (Figure 2c) and cultivated with either mixture of timothy and meadow fescue (TIM, Phleum pratense and Festuca pratensis, Figure 3c) or RCG. Third subplot was kept without any vegetation (BARE, Figure 3b). The order of the vegetated treatments was randomized. However, the BARE treatment was always in the middle of the vegetated subplots in order to prevent plant and root spread from one treatment to another. Permanent collars for gas flux measurements were installed in plot areas.

Sampling for soil and biomass were done within the plot areas.

25 Figure 2 (a) Aerial view of the experimental design (Picture: Perttu Virkajärvi, 2010) with closer view of (b) the main field set-up and (c) plots and subplot design at the study site.

Figure 3 (a) Reed canary grass, (b) soil without vegetation and (c) timothy and meadow fescue mixture at the study site.

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Table 1 General soil characteristics (mean ± standard deviation) of top soil (0-18 cm).

Soil characteristic Mean ± SD

Clay (%) 25 ± 5.6

Silt (%) 53 ± 9.0

Sand (%) 22 ± 7.8

pH (H²O) 5.8 ± 0.19

Electrical conductivity (mS m^-1) 14 ± 2.4 Soil organic matter (%) 5.2 ± 0.90 Particle density (g cm^-3) 2.7 ± 0.014 Bulk density (g cm^-3) 1.1 ± 0.11

Organic carbon (%) 3.0 ± 0.52

Total nitrogen (%) 0.2 ± 0.03

C/N 15 ± 0.40

K (mg dm^-3 soil) 100 ± 13

P (mg dm^-3soil) 5.4 ± 1.3

Field capacity (%, soil moisture (v/v)) 40 ± 1.2 Wilting point (%, soil moisture (v/v)) 22 ± 0.80 1.5.3 Experimental design

The experimental design consisted of the main field and three experimental plots therein (Figure 2a). The main field was cultivated with reed canary grass (RCG, Phalaris arundinacea L., Figure 3a). Masts for eddy covariance (EC) measurements and for weather station were located in the middle of the field (Figure 2b). The net radiometer mast was located further away in order to avoid shading from the masts and instrument cabin. The blue hut in the middle of the field housed the EC gas analyzers.

Each of the three experimental plots were divided into three subplots (Figure 2c) and cultivated with either mixture of timothy and meadow fescue (TIM, Phleum pratense and Festuca pratensis, Figure 3c) or RCG. Third subplot was kept without any vegetation (BARE, Figure 3b). The order of the vegetated treatments was randomized. However, the BARE treatment was always in the middle of the vegetated subplots in order to prevent plant and root spread from one treatment to another. Permanent collars for gas flux measurements were installed in plot areas.

Sampling for soil and biomass were done within the plot areas.

25 Figure 2 (a) Aerial view of the experimental design (Picture: Perttu Virkajärvi, 2010) with closer view of (b) the main field set-up and (c) plots and subplot design at the study site.

Figure 3 (a) Reed canary grass, (b) soil without vegetation and (c) timothy and meadow fescue mixture at the study site.

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1.5.4 Agricultural practices

The field was levelled before and after the sowing in June 2009 (Table 2). Barley was used as a protection crop on TIM and removed during the first harvest in August 2009. Germination gaps were filled on RCG areas in 2009. Mineral fertilizer was applied with the seeds in the first year and as a surface application during later years. Herbicide (Ariana-S, mixture of MPCA 200 g l^-1, clopyralid 20 g l^-1 and fluroxypyr 40 g l^-1, 2 l with 200 l of water ha^-1) was applied at the end of July 2009 to control the weeds on TIM and RCG. Biomass was harvested on TIM once in 2009 and twice during latter years on TIM (Table 3). RCG was harvested first time in spring 2011 to improve the crop growth and biomass quality for combustion (Burvall, 1997). On BARE, plants were removed weekly by hand.

Table 2 Sowing of the plants and corresponding seed rates (kg ha^-1) on mixture of timothy and meadow fescue (TIM) and reed canary grass on main field (RCGmain) and at plot areas (RCGplot) in 2009.

Sowing

date Plant

(common name, Latin name, cultivar) Seed rate

TIM June 9 Timothy, Phleum pratense, Tuure 12

Meadow fescue, Festuca pratensis Huds., Antti 10

Barley, Hordeum vulgare, Voitto 120

RCG^plot June 9 Reed canary grass, Phalaris arundinacea L., Palaton 11 RCG^main June 8 Reed canary grass, Phalaris arundinacea L., Palaton 11 Table 3 Use of fertilizers (kg ha^-1), timing of harvesting events and corresponding yields (kg DW ha^-1) on mixture of timothy and meadow fescue (TIM) and reed canary grass on main field (RCGmain) and at plot areas (RCGplot) during 2009 – 2011.

Year Fertilization N P K Harvesting Yield

TIM 2009 June 9 60 30 45 Aug 21 6400

2010 May 21 100 15 25 June 22 7200

June 30 100 0 35 Aug 23 5700

2011 May 27 100 15 23 June 22 7400

July 7 100 0 35 Sep 5 6400

RCG^plot 2009 June 9 60 30 45 -

2010 May 21 80 12 20 -

2011 May 27 80 12 20 Apr 29 7300

2012 May 9 5700

RCG^main 2009 June 8 60 30 45 -

2010 May 21 70 11 18 -

2011 May 23 76 11 19 Apr 28 6200

2012 May 9 6700

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1.6 METHODS

The main methods are described here shortly. Details of the methods, except for LCA, are given in the Chapters 2 through 5 and the references therein.

1.6.1 Climatic variables

Data logger (model: CR 3000, Campbell Scientific Inc.) was used to collect weather data (Table 4) at 30 minute intervals except for air pressure, which was collected hourly. Data was checked for quality and 30-min gaps were filled using linear interpolation. When data for air temperature, relative humidity, pressure or precipitation was missing for longer periods, data from nearby Maaninka weather station operated by Finnish meteorological institute (FMI) was used to fill the gaps.

Table 4 Weather station instruments. Measurement height of air temperature and net radiation sensor varied with the height of the EC mast due to plant height.

Variable Instrument Height (m)/Depth (cm)

Air temperature and

relative humidity HMP45C, Vaisala Inc 2.0, 2.4 or 2.5 m Photosynthetically

active radiation SKP215, Skye instruments Ltd. 2.0, 2.4 or 2.5 m Net radiation CNR1, Kipp&Zonen B.V. 2.0, 2.4 or 2.5 m Snow depth SR50A(h), Campbell Scientific Inc. 2.0, 2.4 or 2.5 m Wind speed and

wind direction 03002-5, R.M. Young Company 2.0, 2.4 or 2.5 m Rainfall 52203, R.M. Young Company 1 m

Air pressure CS106 Vaisala PTB110 Barometer 0.6 m Soil heat flux HPF01SC, Hukseflux 7.5 cm

Soil temperature 107, Campbell Scientific Inc. 2.5, 5, 10, 20 and 30 cm Soil moisture CS616, Campbell Scientific Inc. 2.5, 5, 10 and 30 cm 1.6.2 Greenhouse gas exchange

Closed-path eddy covariance method (EC, Baldocchi, 2003) was used to determine CO² and N²O fluxes as well as the latent (LE) and sensible heat (H) fluxes of RCG cropping system at the main field. Instrumentation consisted of an infrared gas analyzer (IRGA) for CO² and water vapor (H²O) concentrations (model: Li-7000 or Li-6262, LiCor), of a pulsed quantum cascade laser spectrometer for N²O, CO² and H²O concentrations (Model: QC-Tildas-76-CS, Aerodyne Research Inc., USA) and a sonic anemometer (model: R3-50, Gill Instruments Ltd, UK) for wind velocity components and sonic temperature. The measurement heights were 2, 2.4 or 2.5 m depending on plant heights. Further details can be found from chapter 2 for CO² and from chapter 3 for N²O and Rannik et al. (2015).

Season specific manual gas flux measurement methods were used in order to determine the annual GHG exchange of TIM, RCG and BARE in the plot areas. A snow-gradient method (Sommerfeld et al., 1993) was used during winter. Gas

Atmospheric impacts of perennial crop cultivation as biomass and energy sources

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ENERGY SOURCES

Saara E. Lind

ATMOSPHERIC IMPACTS OF PERENNIAL CROP CULTIVATION AS BIOMASS AND

ENERGY SOURCES

ABSTRACT

ABSTRACT

TIIVISTELMÄ

TIIVISTELMÄ

ACKNOWLEDGEMENTS

ACKNOWLEDGEMENTS

LIST OF ABBREVIATIONS

LIST OF ABBREVIATIONS

LIST OF ORIGINAL PUBLICATIONS

LIST OF ORIGINAL PUBLICATIONS

AUTHOR’S CONTRIBUTION

CONTENTS

AUTHOR’S CONTRIBUTION

CONTENTS

1 GENERAL INTRODUCTION

1.1 CLIMATE CHANGE AND MITIGATION ACTIONS

1.2 IMPORTANCE OF AGRICULTURE AND BIOENERGY IN GLOBAL GREENHOUSE GAS BUDGETS

1 GENERAL INTRODUCTION

1.1 CLIMATE CHANGE AND MITIGATION ACTIONS

1.2 IMPORTANCE OF AGRICULTURE AND BIOENERGY IN GLOBAL GREENHOUSE GAS BUDGETS

1.3 PERENNIAL CROPPING SYSTEMS

1.3 PERENNIAL CROPPING SYSTEMS

1.4 LIFE CYCLE ASSESSMENT (LCA) OF BIOENERGY

1.5 SITE DESCRIPTION

1.4 LIFE CYCLE ASSESSMENT (LCA) OF BIOENERGY

1.5 SITE DESCRIPTION

1.6 METHODS