Keyword

O3

6 record(s)
 
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  • Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast. This datasets contains O3 measurements using TEI49C UV ozone analyser.

  • Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 1 took place in July and August 2003 at Writtle College, near Chelmsford, Essex. This datasets contains O3 measurements using TEI49C UV ozone analyser.

  • The data presented are growth and physiological measurements from an ozone exposure experiment, during which grassland forbs, Leontodon hispidus and Succisa pratensis were exposed to low, medium and high ozone treatments over three growing seasons, using an outdoor Free Air Ozone Enrichment system, and with and without the addition of nitrogen during the first year. The plants were planted in April 2016 and were exposed to Low, Medium and High ozone treatments over three growing seasons (May to September 2016-2018). Measurements were taken of light-saturated photosynthesis, stomatal conductance, chlorophyll index, number of flowering stems, leaf ground cover, and the dried weight of litter. All measurements were made by members of the project. The experiments were carried out in the UKCEH Bangor Air Pollution Facility. Work was funded by the UK Centre for Ecology & Hydrology under the Natural Environment Research Council (UK) grant/award NEC05574. For L. hispidus a lower leaf cover was observed with elevated ozone, and there was an increase in litter with added nitrogen. For S. pratensis, elevated ozone reduced flowering and increased foliar damage. Increased litter and accelerated winter die-back with both ozone and nitrogen were also recorded for S. pratensis. These effects have implications for inter- and intra-specific competition, seed establishment, nutrient cycling, as well as the provision of general pollinator resources and highlight the need for concerted action to reduce pre-cursor ozone emissions to go alongside habitat management efforts to protect biodiversity. Full details about this dataset can be found at https://doi.org/10.5285/382baaf2-7795-4aa8-a434-56c9e6bd1516

  • This dataset contains O3, CO, NO, NO2, NOy and SO2 concentration measurements from the University of York's Thermo 49i O3 analyser, Aero Laser 5002 CO analyser, Air Quality Design (AQD) NOx analyser, Thermo 42c Trace Level NOx analyser with AQD NOy converter and a Thermo 43i SO2 analyser. These instruments were located at the Indira Gandi Delhi Technical University for Women (IGDTUW). The instruments sampled from a common sample line, initially at 7 m above ground level, then were moved to 35 m above ground on the 5th of November 2018. The data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme.

  • This dataset is a model output from the European Monitoring and Evaluation Programme (EMEP) model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology (WRF). It provides UK estimates daily averaged atmospheric composition at approximately 5 km grid for the years 2001 to 2015. The data consists of atmospheric composition and deposition values of various pollutants; including PM10, PM2.5, secondary organic aerosols (SOA), elemental carbon (EC), secondary inorganic aerosols (SIA), sulfur dioxide (SO2), ammonia (NH3), nitrogen oxides (NOX) , and ozone (O3). The EMEP model version used here is rv4.17 and the WRF model version is the 3.7.1. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/b0545f67-e47c-4077-bf3c-c5ffcd6b72c8

  • A Yield Constraint Score (YCS; scale of 1-5) was developed for the effect of five key crop stresses (ozone, pests and diseases, soil nutrients, heat stress and aridity) on the production of the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum). Data are on a global scale at 1° by 1° resolution, 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. To derive the YCS for each crop stress, spatial data on a global scale were gathered. Modelled ozone data (2010-2012) were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Pests and diseases data (2002-2004) were downloaded from a Centre for Agriculture and Biosciences International (CABI) database providing estimates for pre-harvest crop losses due to weeds, animal, pathogens and viruses, compiled from the literature. Soil nutrient classifications (for 2009, derived using soil attributes from the Harmonized World Soil Database (HWSD)) were downloaded from the GAEZ data portal. A heat stress index was calculated using daily temperature data (1990-2014) to determine whether the temperature within a 30-day thermal-sensitive period exceeded crop tolerance thresholds. Global Aridity Index data (1950-2000) were downloaded from the Consultative Group for International Agricultural Research’s Consortium for Spatial Information (CGIAR-CSI). The Yield Constraint Score provides an indication of where each stress is predicted to be affecting crop yield globally and the magnitude of the effect. The YCS data were developed as part of the NERC funded SUNRISE project (NEC06476) and the 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/d347ed22-2b57-4dce-88e3-31a4d00d4358