This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples around Zambia. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS). These data were collected as part of the ZWAMPS: Quantifying methane emissions in remote tropical settings: a new 3D approach project funded by the Natural Environment Research Council (NERC) NE/S00159X/1.

This dataset contains CH4, CO2, CO, N2O and SF6 dry air molar fraction vertical profiles over the Pantanal, Mato Grosso do Sul, Brazil with air sampled using small aircraft and analysed at Laboratório de Gases de Efeito Estufa (LAGEE), Sao Jose dos Campos, Brazil. The air was sampled during ascent of small airplane from 4.4 km above surface down to close to the ground. A series of flasks (17 flasks) were filled sequentially. The flasks were contained in a suitcase. Valves of the flasks were opened and closed by a programmable microcontroller. After sampling the suitcase were sent by mail to the high precision gas analytics laboratory LAGEE at Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, Brazil where the dry air molar fractions of the air of each flask were measured. These data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1).

This dataset contains wind, temperature, pressure, humidity and ozone mixing ratio, given as the 20-minute mean of 10 Hz (ozone and wind) or 0.25 Hz (pressure, humidity and temperature) raw data. Ozone flux values calculated from the raw 10 Hz wind and ozone data are presented as mass fluxes and as molar fluxes. Deposition velocity is calculated from the molar flux. Data relevant to the data selection are also included, such as ozone variability, instrument sensitivity, wind stationarity and wind speed and direction. The Penlee Point Atmospheric Observatory (PPAO) site is best suited to observing fluxes over water. The north-west sector contains the sloping headland on which the observatory is built, making flux observations in this sector of limited value. The footprint area (where the measured flux is occurring) varies with wind conditions, but generally 90% of flux contribution occurs within 2-3 km of the observatory. The building itself sits 30-60m from the coast, depending on tide. Measurements were taken from 2018/04/10 - 2018/05/21 using a Gill WindMaster Pro sonic anemometer, a Gill MetPak Pro, and a high frequency chemiluminescence ozone detector from Eco Physics. A 2B 205 ozone monitor was used as a reference for the high frequency ozone instrument. Data collection was managed by David Loades (University of York), Thomas Bell (Plymouth Marine Laboratory) and Mingxi Yang (Plymouth Marine Laboratory). Data are missing where fluxes couldn't be calculated, most commonly due to heavy rain disrupting the anemometer or power outages. These data were collected for the Natural Environment Research Council (NERC) project Iodide in the ocean:distribution and impact on iodine flux and ozone loss.

This dataset contains wind speed and direction, air temperature, relative humidity, barometric pressure, nitric oxide, nitric dioxide, nitric oxides, sulphur dioxide, carbon dioxide, ozone and pm2.5 based on a newly built-up rural site at Xibaidian, Pinggu district, Beijing in winter 2016 and summer 2017. The data were taken for the APHH-Beijing campaign for the Effects of air pollutions on cardiopulmonary disease in urban and peri-urban residents in Beijing (AIRLESS) project as part of the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. Instruments were deployed on the roof of a one-story building in the far north end of a village, where most of the subjects resided nearby. Northern winds tend to bring relatively clean background air. In contrast, winds from the south are often contaminated by emissions from traffic and industries. The following instruments were used: 1. Meteorological parameter: TH16A meteorological station 2. NOx: TEI 42 trace level chemiluminescence NOx Analyzer; 3. SO2: Ecotech EC9850 Sulfur Dioxide Analyzer 4. CO: Ecotech EC9830 Carbon Monoxide Analyzer 5. O3: Ecotech EC9810 Ozone Analyzer 6. PM2.5: Met One BAM 1020 The dataset was collected in Xibaidian, Pinggu district, Beijing for the Effects of air pollutions on cardiopulmonary disease in urban and peri-urban residents in Beijing (AIRLESS) project can provide ambient level of air pollutant in rural Beijing, enabling better understanding of the exposure level for local residents and potential examination for the related health effects.

The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2017. For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information). This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.

This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'RCP45' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection. Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used. BITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record.

This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples on the Llanos de Moxos wetland near Trinidad, Bolivia. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS). These data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1).

This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Chacaltya Observatory Station, Bolivia. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS). These data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1).

The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2020. This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information). This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.

This dataset contains both the concentration of PM2.5 in ambient air sampled at a height of 8 metres and the concentrations of water-soluble Silicon/water-soluble organic Silicon/water-soluble inorganic Silicon found in the PM2.5 samples resulting from analysis by Ultraviolet-Visible Spectrophotometry. The PM2.5 samples were collected in the Institute of Atmospheric Physics, Chinese Academy of Sciences, China in August 2018 and January 2019. The data was collected to support the study of atmospheric chemistry and processes involving Silicon (Si) containing fine particles, which potentially contribute to atmospheric pollution. These data were collected as part of the Silicon-containing secondary organic aerosols in ambient air (Si-SOA) Natural Environment Research Council (NERC) funded project.