1. TOAR Chapter 5: Present day tropospheric ozone distribution and trends relevant to vegetation Gina Mills 1, Zhaozhong Feng 2 Owen Cooper, Giacomo Gerosa, Allen Lefohn, Howie Neufeld, Elena Paoletti, Håkan Pleijel, Pallavi Saxena, Martin Schultz, David Simpson, Baerbel Sinha, Vinayak Sinha, Sverre Solberg, Xiaobin Xu 1 Centre for Ecology and Hydrology, UK 2 Chinese Academy of Sciences, Beijing

2. CONTENT  Introduction – evidence of damaging effects of ozone on vegetation  Ozone metrics for vegetation, AOT40, W126 and M12, including examples  Vegetation-specific considerations for TOAR data analysis and mapping Content

3. Cooper et al. (2014). Elem. Sci. Anth. 2: 000029 Dec – Feb Mar – May June – Aug Sep – Nov 20 30 40 50 60 70 Ground level ozone (ppb)  Globally, the highest concentrations are in central and southern Europe, S Asia and southern USA  Many of our most important crops are exposed to ozone pollution during their peak growing periods  Trees, grassland and other vegetation are also actively growing during the peak ozone periods Ozone is present during the main plant growth periods

4. Ozone damage to vegetation can be a response to : Short-term episodes Plants develop characteristic injury to the leaves which affects economic value for e.g. salad crops Cumulative exposure Reduction in yield quantity and quality of key food crops, including wheat, soybean, pulses, rice and tomato O 3 sensitive O 3 resistant Greece

5. Ozone Cell membrane damage Altered partitioning Reduced seed and root growth and altered response to other stresses such as drought Photosynthesis inhibited Once inside the plant….

6. Field evidence : Ozone damage on biomarkers China – ChangPing (Beijing Suburb) China - Quzhou Italy - Pisa Source: ICP Vegetation biomonitoring experiments http://icpvegetation.ceh.ac.uk/

7. Field evidence being compiled globally by LRTAP ICP Vegetation Incidences of ozone injury (2007 – 2014), data collection ongoing * * Locations not shown on map as yet

8. Beneficial effects for crops of filtering O 3 out of the air in India  Crop yield improved by 8 – 26% by filtration Note: Ozone is the dominant pollutant at these sites; other pollutants may also be present

9. Ozone exposure experiments in Sweden Wheat Threshold for significant yield effects Many staple food crops are ozone-sensitive M7 ozone conc. for a significant effect on yield From Mills and Harmens, 2011, ICP Vegetation Food Security Report, http://icpvegetation.ceh.ac.uk/http://icpvegetation.ceh.ac.uk/

10. Ozone reduces tolerance to other stresses e.g. drought  Ozone reduces drought tolerance in grassland species by interfering with hormonal control 1,2,3,  Is this happening in crop species? If yes, major implications for sustainability 1 Mills et al., 2009, Global Change Biology; 2, 3 Wilkinson and Davies (2009, 2010), Plant Cell and Env. Stomatal conductance Biomass allocation CEH O 3 exposure solardomes, UK

11. AOT40 (0800-1959h), accumulated over 3, 6, 7 and 12 months AOT40 (daylight over the period when clear sky radiation > 50 W/m 2 ), accumulated over 3, 6, and 7 months. AOT40 (nighttime over the period when clear sky radiation <5 W/m 2 ) accumulated over 3, 6, and 7 months. W126 (24-h), accumulated over 3, 6, 7 and 12 months W126 (12-h, 0800-1959h), accumulated over 3, 6, 7 and 12 months Daily 12-h (0800-1959h), average averaged over 3, 6, 7 or 12 months Flux-Based Indices will be externally generated for a selected number of sites and provided to the TOAR database for entry for the time periods specified in accompanying documentation. Seasonal percentiles of hourly average concentrations (March- May, June-August, September-November, December-February) (median, 5 th, 25 th, 75 th and 95 th, 98 th, and 99 th ) of hourly average. Note: metrics in blue bold font are included in chapter 5 Vegetation metrics for TOAR AOT40 W126 M12 PODy %ile

12. AOT40 Widely used globally and within the 50+ countries of the LRTAP Convention for mapping effects Used in LRTAP Convention critical levels and EU air quality targets Accumulated during daylight hours – when plants are actively taking up ozone daylight

13. AOT40 Pros Extensively used globally by LRTAP, EU, WHO in modelling of impacts Good correlation with effects Includes responses to peak ozone Cons Focusses only on ozone concentrations above 40 ppb Concentrations below 40 ppb are omitted, including ozone concentrations often experienced at background sites Sensitive to accuracy of measurements around 40 ppb

14. W126 Used by US EPA to identify levels that are required to protect vegetation from O 3 exposure Features Cumulative index, accumulates weighted hourly O 3 concentrations during the period 0800 - 1959 for a fixed period (3, 6 months) representing main growth period of vegetation Concentrations below 40 ppb are not included Conc. between 40 ppb and 100 ppb are reduced by W126 function Conc. above 100 ppb have weighting of 1 O 3 conc (ppb) W126 modified conc (ppb) 505.5 6018.2 7042.4 8067.5 W126 weighting function

15. W126 Pros Extensively used in the USA, some use in global modelling of impacts Good correlation with effects, especially where experiments have used high peak ozone treatments Informative on risk to vegetation from high peaks of ozone Cons Focusses on high ozone concentrations Concentrations below 40 ppb are omitted Concentrations in range 40 – 80 ppb, common range for current ozone episodes globally have relatively little impact on W126

16. M12  Mean ozone concentration between 0800 and 1959  Represents average concentration when plants are most actively taking up ozone Pros This metric includes all concentrations of ozone between the specified hours i.e. it has no cut off or weighting of concentrations Gives indication of background ozone and is sensitive to changes in ozone concentration profile Fits well with recent experimental data with reduced peak and higher background ozone treatments Easy to understand and calculate Cons Less used as a policy metric Does not include cumulative effects

17. AOT40, W126 and M12 for two example sites with contrasting profiles AOT40, ppm h0.11 W126, ppm h0.71 M12, ppb31.8 AOT40, ppm h19.3 W126, ppm h28.4 M12, ppb56.06 Strathvaich, N Scotland, 270m 1 Data from: 1 Uk-air.defra.gov.uk; 2 Giacomo Gerosa, Italy Arconate, Italy 2 Data is for May-July, 2010

18. 40 ppb 100 ppb 40 ppb 100 ppb AOT40, W126 and M12 for two example sites with contrasting profiles AOT40, ppm h0.11 W126, ppm h0.71 M12, ppb31.8 AOT40, ppm h19.3 W126, ppm h28.4 M12, ppb56.06 Data is for May-July, 2010

19. [O 3 ] in air Stomatal ozone flux* Takes into account: [O 3 ] in air temperature light humidity (VPD) soil moisture plant development Ozone metrics explained http://www.sei-international.org/do3se * Stomatal ozone flux is biologically the most relevant metric but cannot be routinely calculated within the TOAR database as met. data is also required

20. PODy – Phytotoxic Ozone Dose (stomata flux index) http://www.sei-international.org/do3se DO 3 SE Deposition of Ozone for Stomatal Exchange Developed by Lisa Emberson and Patrick Büker

21. PODy Pros Biologically more meaningful – represents uptake of ozone by plants rather than concentration above plants Better fit to field evidence of ozone damage than AOT40 (Mills et al., Global Change Biology, 2011) Recommended by LRTAP Convention for risk assessment and being considered by the EU Cons Complex to determine Requires meteorological data Not currently included in this phase of the TOAR database as met. data not readily available, however, a map with PODy values for example sites could be included Phototoxic Ozone Dose above a flux-threshold of Y nmol m -2 s -1

22. Wheat yield reduction due to ozone, calculated using POD 3 IAM ICP Vegetation study http://icpvegetation.ceh.ac.uk /publications/thematic.html

23. Vegetation-specific considerations for TOAR data analysis and mapping

24. (1) Defining rural areas  Night-time brightness index being considered but rules needed e.g. the Netherlands shows as very bright, therefore urban but has extensive agricultural areas

25. (2) Representative species – landcover data Wheat growing areasRice growing areas Deciduous trees: Landcover data source to be decided, suggestions include: Phytoclimatic/bioclimatic regions Alex Gunthers' Megan model for BVOC emissions GLC data-sets (GLC2000 is used in EMEP): www.glcn.orgwww.glcn.org Crowther et al. Nature, 2015 Mapping tree density at a global scale Crop maps: Source GAEZ

26. (3) Timing of window for metric Example: Climate zones in the wheat growing areas and three month windows: Northern Hemisphere: Boreal, moist/dry: June, July, Aug; Cool Temperate: Apr, May, June; Warm Temperate: Mar, Apr, May; Tropical, wet/moist/montane: Jan, Feb, Mar; Tropical, dry: Jan, Feb, Mar. Southern hemisphere: Cool, Temperate, 0 - 30 degrees south: Feb, Mar, Apr; Cool, Temperate, > 30 degrees south: Nov, Dec, Jan; Warm Temperate, dry: Aug – Oct; Warm Temperate, moist: Mid-Aug, to mid Nov; Tropical, wet/moist/montane: July, Aug, Sep; Tropical, dry: Aug, Sep, Oct 3 month windows for crops 6 and 12 month windows for crops and trees

27. (4) Data availability  We will work with agreed TOAR process for dealing with gaps in data  Such gaps are especially important for cumulative indices like AOT40 and W126 Example rural site at Arconate near Milan, Italy Weeks 6-8 have missing data out of the 13 week period MetricComplete data 2 weeks missing % change AOT4019.3 ppm h17.6 ppm h8.7% decrease W12628.4 ppm h26.2 ppm h7.8 % decrease M1256.1 ppb57.9 ppb3.2% increase

28. (5) Measurement height  For vegetation, this is an important consideration. The ozone concentration decreases with height and will need modifying for vegetation height, standardised as 20m for trees and 1m for crops. LRTAP Convention methods exist, including a tabulated gradient and use of neutral stability profiles Data from Jürgen Bender, Germany

29. MetricAmbient(5m)Ambient (3m) – 3 ppb Ambient (1m) -6 ppb AOT40, ppm h19.317.1 (11%)14.9 (23%) W126, ppm h28.424.7 (13%)21.3 (25%) M12, ppb56.0653.06 (5%)50.06 (11%) Arconate rural site near Milan, Italy, 2010, May-July MetricAmbient – 3 ppb Ambient -6 ppb AOT40, ppm h0.110.130.05 W126, ppm h0.710.450.28 M12, ppb31.828.825.8 Strathvaich, upland site, Scotland, 2010, May-July This matters because… * 6 or 3 ppb removed from each hour to simulate decrease in O 3 conc from 5m or 3m to 1m

30. (6) Consideration of disproportionate representation of data TOAR datasers Need to also decide on which sites to select for each region for trends analysis

31. Present day ozone Figures to be made for chapter Averaged metric (M12) Include: Maps: global distribution in wheat, rice and tree growing areas Accumulated indices (AOT40, W126) Include: Maps: global distribution in wheat, rice and tree growing areas Flux-based indices (PODy) Include map with bar charts showing values at specific locations. Offers of sites wishing to contribute so far are fairly limited and are primarily from Europe.

32. Trends in vegetation metrics (1) Global trends Show vector plots for metrics on a global scale such as this one from Cooper et al., 2014: Figures to be made for chapter

33. (2) Trends in seasonal variation and relevance to plant growth cycles E.g. show that spring peak is now earlier in Europe and USA and discuss implications Discuss need for all year round metrics in some biogeographic zones, and include these for tropical/sub-tropical regions? Figures to be made for chapter Trends in vegetation metrics (3) Trends in percentile changes Discuss in relation to AOT40, W126 and M12

34. Chapter 5: Present day tropospheric ozone distribution and trends relevant to vegetation Summary  Ozone causes visible damage, growth and yield reductions and altered sensitivity to other stresses in vegetation in many areas of the world  The ozone metrics we will focus on in Chapter 5 are: AOT40, W126 and M12  These have been selected to be globally representative and to inform the reader about different aspects of ozone concentration distribution that plants respond to  At this meeting, and in correspondence with other co-authors unable to attend, we need to discuss/decide on: Relevant to all of TOAR: Defining rural areas, dealing with missing data and disproportionate data availability Vegetation-specific: Sources of landcover data for trees, measurement height vs vegetation height, representative sites per region, figures and tables to include, include ozone flux data for selected locations

35. TOAR Chapter 5: Present day tropospheric ozone distribution and trends relevant to vegetation Gina Mills and Zhaozhong Feng wish to thank all contributors to this Chapter: Owen Cooper, Giacomo Gerosa, Allen Lefohn, Howie Neufeld, Elena Paoletti, Håkan Pleijel, Pallavi Saxena, Martin Schultz, David Simpson, Baerbel Sinha, Vinayak Sinha, Sverre Solberg,Xiaobin Xu

36. Spares

37. Field evidence of effects: Influencing policy This study showed that: (1)There is widespread occurrence of ozone damage to crops across Europe (2)Effects occur in areas where health less likely to be impacted (SOMO35 not exceeded) (3)More biologically–relevant flux-based risk assessments were better indicators of effects than AOT40, a concentration-based index Impacts on UN policy 1)Flux-based method accepted for Protocol Revision 2)Impacts of O 3 on vegetation now also considered (as well as health) AOT40 Stomatal flux POD 6 1994 to 2006 (mmol m-2) 1994 to 2006 (ppm h)

38. Larger effect of peak than background ozone for wheat (cv Skyfall)  Weekly mean ozone concentration was the same for each pair of treatments  The effect on photosynthesis was larger for peaks of ozone exposure than for elevated background  This response is reflected in yield (data being analysed) Effects on light saturated photosynthesis NERC Quota PhD student Stephanie Osborne: Yield, flux modelling NC Air quality impacts: N cycle effects 6