Future impacts of ozone driven damages on agricultural systems

Sampedro, Jon; Waldhoff, Stephanie; Ven, Dirk-Jan Van de; Pardo, Guillermo Orozco; Dingenen, Rita Van; Arto, Iñaki; Prado, A. del; Sanz, María José

doi:10.1016/j.atmosenv.2020.117538

Cited by 39 publications

(16 citation statements)

References 73 publications

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“…Phenotyping tolerance to gaseous pollutants Gaseous pollutants come from various sources, such as combustion (sulphur oxides [SO 2 ], carbon monoxide [CO], nitrogen oxides [NOx], fine particulate matter [PM]); agriculture (ammonia [NH 3 ] and methane [CH 4 ]); and paint and solvent use (non-methane volatile organic compounds [NMVOCs]) (European Environment Agency, 2019). These can be critical by themselves, or co-emerge and intermix to act as precursors for secondary pollutants such as tropospheric ozone (O 3 ), which is formed from CO, NMVOCs, NOx, and CH 4 (Monks et al, 2015;Sampedro et al, 2020). Pollutants vary extensively by region and can travel over wide areas, for example, CO, CH 4 , and NMVOCs can even cause hemispheric O 3 pollution (Ainsworth, 2017).…”

Section: Boxmentioning

confidence: 99%

Crop phenotyping in a context of global change: What to measure and how to do it

Araus

Kefauver

Vergara-Díaz

et al. 2022

JIPB

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High-throughput crop phenotyping, particularly under field conditions, is nowadays perceived as a key factor limiting crop genetic advance. Phenotyping not only facilitates conventional breeding, but it is necessary to fully exploit the capabilities of molecular breeding, and it can be exploited to predict breeding targets for the years ahead at the regional level through more advanced simulation models and decision support systems. In terms of phenotyping, it is necessary to determined which selection traits are relevant in each situation, and which phenotyping tools/ methods are available to assess such traits. Remote sensing methodologies are currently the most popular approaches, even when lab-based analyses are still relevant in many circumstances. On top of that, data processing and automation, together with machine learning/deep learning are contributing to the wide range of applications for phenotyping. This review addresses spectral and red-green-blue sensing as the most popular remote sensing approaches, alongside stable isotope composition as an example of a lab-based tool, and root phenotyping, which represents one of the frontiers for field phenotyping. Further, we consider the two most promising forms of aerial platforms (unmanned aerial vehicle and satellites) and some of the emerging data-processing techniques. The review includes three Boxes that examine specific case studies.

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Section: Boxmentioning

confidence: 99%

Crop phenotyping in a context of global change: What to measure and how to do it

Araus

Kefauver

Vergara-Díaz

et al. 2022

JIPB

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“…This study investigates future crop yield response climate change, O 3 and CO 2 and their interactions using JULES-crop over the period 2005-2100. Many existing studies (Fiore et al 2012, Schauberger et al 2019, Hayes et al 2020, Sampedro et al 2020 simulate crop response to climate projections spanning only a few years each due to computational limitations, while this study simulate long transient timeseries. This approach could help distinguish an actual anthropogenic-forced climate signal from internally generated climate variability (Nolte et al 2018).…”

Section: Ozone Impacts On Agriculturementioning

confidence: 99%

CO₂ fertilization of crops offsets yield losses due to future surface ozone damage and climate change

Leung

Sitch

Tai

et al. 2022

Environ. Res. Lett.

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Tropospheric ozone (O3) is harmful to plant productivity and negatively impacts crop yields. O3 concentrations are projected to decrease globally in the optimistic Representative Concentration Pathway of 2.6 W m–2 (RCP2.6) but increase globally following the high-emission scenario under the RCP8.5, with substantial implications for global food security. The damaging effect of O3 on future crop yield is affected by CO2 fertilization and climate change, and their interactions for RCP scenarios have yet to be quantified. In this study, we used the Joint UK Land Environment Simulator modified to include crops (JULES-crop) to quantify the impacts, and relative importance of present-day and future O3, CO2 concentration and meteorology on crop production at the regional scale until 2100 following RCP2.6 and RCP8.5 scenarios. We focus on eight major crop-producing regions that cover the production of wheat, soybean, maize, and rice. Our results show that CO2 alone has the largest effect on regional yields, followed by climate and O3. However, the CO2 fertilization effect is offset by the negative impact of tropospheric O3 in regions with high O3 concentrations, such as South Asia and China. Simulated crop yields in 2050 were compared with Food and Agriculture Organisation (FAO) statistics to investigate the differences between a socioeconomic and a biophysical process-based approach. Results showed that FAO estimates are closer to our JULES-crop RCP8.5 scenario. This study demonstrates that air pollution could be the biggest threat to future food production and highlights an urgent policy need to mitigate the threat of climate change and O3 pollution on food security.

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“…For agroecosystem, an accurate assessment of how elevated atmospheric O3 affects crop productivity, especially crop yield, is crucial for global food security 3,7 . Most researchers have focused on the total loss of crop yield caused by atmospheric O3 while turning out to have considerable variation and high uncertainty 8,9,10 . The value of 40 ppb O3 is generally considered a threshold.…”

Section: Introductionmentioning

confidence: 99%

“…Although individual experiments have reported average values of Yo based on the relationship between O3 dose (hour mean of O3 or accumulated O3 over a threshold concentration) and crop yield loss rate 3,14,15 , explicit quantification of the values under smaller O3 intervals is still scant and remains a major challenge in formulating dose-responses for crop yield assessment. Due to the lack of observational O3 data, part of this challenge has been met using atmospheric models to predict regional and global O3-induced crop yield losses 3,8,16 . However, with the establishment of numerous O3 monitoring stations in recent years, more accurate global real-time O3 concentration data could be obtained (Supplementary Fig.…”

Section: Introductionmentioning

confidence: 99%

Large crop production losses induced by global ozone stress based on interval evaluation

Cai

Wang

Ren

et al. 2022

Preprint

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Global crop yield loss due to ground-level ozone (O3) concentrations is a major challenge to food security, but a dose-response association is not easy to quantify. Here, we propose using a new metric, O3 sensitivity of crop yield (Yo), to estimate yield loss under different O3 time intervals using four observational databases. The Yo metric shows a non-linear parabola with elevated atmospheric O3 for wheat, maize, rice, soybean, and assorted vegetables. Spatial heterogeneity of yield loss varies as a function of crop type and O3 intervals. Estimates of yield loss from ozone suggest recent losses (2017-2019) may reach as high as 537 million tonnes, with a significant proportion coming with lower (30-40 ppb) exposure (325 million tonnes). Our results suggest that previous research, which only included higher (>40 ppb ozone), may have had grossly underestimated the negative effect of atmospheric O3 on crop production. Suppose these results are endemic to global crop production. In that case, additional research will be necessary to reassess ozone sensitivity and dose-responses, both spatially and temporally, to determine future air pollution impacts.

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Future impacts of ozone driven damages on agricultural systems

Cited by 39 publications

References 73 publications

Crop phenotyping in a context of global change: What to measure and how to do it

Crop phenotyping in a context of global change: What to measure and how to do it

CO₂ fertilization of crops offsets yield losses due to future surface ozone damage and climate change

Large crop production losses induced by global ozone stress based on interval evaluation

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Future impacts of ozone driven damages on agricultural systems

Cited by 39 publications

References 73 publications

Crop phenotyping in a context of global change: What to measure and how to do it

Crop phenotyping in a context of global change: What to measure and how to do it

CO2 fertilization of crops offsets yield losses due to future surface ozone damage and climate change

Large crop production losses induced by global ozone stress based on interval evaluation

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Product

Resources

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CO₂ fertilization of crops offsets yield losses due to future surface ozone damage and climate change