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University of Gothenburg

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  • This work is focused on results from a recent controlled sub-seabed in situ carbon dioxide (CO2) release experiment carried out during May–October 2012 in Ardmucknish Bay on the Scottish west coast. Three types of pCO2 sensors (fluorescence, NDIR and ISFET-based technologies) were used in combination with multiparameter instruments measuring oxygen, temperature, salinity and currents in the water column at the epicentre of release and further away. It was shown that distribution of seafloor CO2 emissions features high spatial and temporal heterogeneity. The highest pCO2 values (~1250 µatm) were detected at low tide around a bubble stream and within centimetres distance from the seafloor. Further up in the water column, 30-100 cm above the seabed, the gradients decreased, but continued to indicate elevated pCO2 at the epicentre of release throughout the injection campaign with the peak values between 400 and 740 µatm. High-frequency parallel measurements from two instruments placed within 1 m from each other, relocation of one of the instruments at the release site and 2D horizontal mapping of the release and control sites confirmed a localized impact from CO2 emissions. Observed effects on the water column were temporary and post-injection recovery took <7 days. A multivariate statistical approach was used to recognize the periods when the system was dominated by natural forcing with strong correlation between variation in pCO2 and O2, and when it was influenced by purposefully released CO2. Use of a hydrodynamic circulation model, calibrated with in situ data, was crucial to establishing background conditions in this complex and dynamic shallow water system. This is a publication in QICS Special Issue - International Journal of Greenhouse Gas Control, Dariia Atamanchuk et. al. Doi:10.1016/j.ijggc.2014.10.021.

  • Modelled average percentage yield loss due to ground-level ozone pollution (per 1 degree by 1 degree grid cell) are presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum) for the period 2010-2012. Data are on a global scale, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. Modelled ozone data (2010-2012) needed for yield loss calculations were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Mapping the global crop yield losses due to ozone highlights the impact of ozone on crops and allows areas at high risk of ozone damage to be identified, which is one of the first steps towards mitigation of the problem. The yield loss calculations were done as part of the NERC funded SUNRISE project (NEC06476) and National Capability Project NC-Air quality impacts on food security, ecosystems and health (NEC05574). Full details about this dataset can be found at https://doi.org/10.5285/2a932995-f040-4724-ad21-3e92ae8a2540

  • [THIS DATASET HAS BEEN WITHDRAWN]. Modelled average percentage yield loss due to ground-level ozone pollution (per 1 degree by 1 degree grid cell) are presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum) for the period 2010-2012. Data are on a global scale, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. Modelled ozone data (2010-2012) needed for yield loss calculations were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Mapping the global crop yield losses due to ozone highlights the impact of ozone on crops and allows areas at high risk of ozone damage to be identified, which is one of the first steps towards mitigation of the problem. The yield loss calculations were done as part of the NERC funded SUNRISE project (NEC06476). Full details about this dataset can be found at https://doi.org/10.5285/181a7dd5-0fd4-482a-afce-0fa6875b5fb3

  • Modelled annual average production loss (thousand tonnes per 1 degree by 1 degree grid cell) due to ground-level ozone pollution is presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum), for the period 2010-2012. Data are on a global scale, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. Modelled ozone data (2010-2012) needed for production loss calculations were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Mapping the global crop production losses due to ozone highlights the impact of ozone on crops and allows areas at high risk of ozone damage to be identified, which is a step towards mitigation of the problem. The production loss calculations were done as part of the NERC funded SUNRISE project (NEC06476) and National Capability Project NC-Air quality impacts on food security, ecosystems and health (NEC05574). Full details about this dataset can be found at https://doi.org/10.5285/0aa7911a-ab5f-4b08-a225-28b1e8344d01