Britain Breathing 2016-2019 Air Quality and Meteorological Regional Estimates Dataset

This data set is a collection of estimated daily mean and maximum values for a range of air quality and meterological measurements and model forecasts for the <em>UK and crown dependencies</em> postcode districts (e.g. 'AB') for the years 2016-2019, inclusive. The paper describing this dataset is available here: https://www.nature.com/articles/s41597-022-01135-6 The data uses a 'concentric regions' method to estimate the measurement for all regions, as follows. If measurements exist within the region, the mean of those measurements is used, if not, then a ring of neighbouring postcode regions are selected, and the mean of their measurement values used. If no measurement sites/data are found in the first ring, the process continues, taking the next ring of postcode district regions, working outwards until one or more sensors are found in a ring. As well as the measurement estimations, the number of rings required to find site data and make the estimations is also published. <strong>As a result, please note that estimations with higher ring counts ('rings') are likely to be calculated from more distant sensors. This distance depends upon the size of the postcode regions surrounding the location being estimated. Please use the ring count ('rings') to limit/filter estimations based on your required level of confidence.</strong><br> <br> The meteorological, pollen and air quality measurement data used to make the regional estimations can be found at this Zenodo archive. The data there contains Temperature, Relative Humidity, and Pressure data, downloaded from the Met Office MIDAS archives via the MEDMI server (https://www.data-mashup.org.uk/). Also downloaded from the MEDMI server are daily pollen measurements for the UK. PM10, PM2.5, NO2, NOx (as NO2), O3, and SO2 measurements from the DEFRA AURN network, and also model forecasts of the same made using the EMEP model. The code used to make the estimations is available at this Zenodo archive. The postcode data in postcode_district_data.csv are collated from several sources: https://www.doogal.co.uk/UKPostcodes.php (population figures for the UK (UK Census 2011)) https://www.freemaptools.com/download-uk-postcode-outcode-boundaries.htm (postcode boundary polygons for UK and crown dependancies) https://www.gov.gg/population (Guernsey (GY) population data for end June 2020) https://www.gov.je/Government/JerseyInFigures/Population/Pages/Population.aspx (Jersey (JE) population data for end 2019) https://www.gov.im/media/1369690/isle-of-man-in-numbers-july-2020.pdf (Isle of Man (IM) population data for April 2016) The data-set is presented in CSV format, as six files: postcode_district_data.csv: location metadata (region_id, geometry, description, population, country) regional_site_counts.csv: a table showing the number of sites for each measurement (columns), for each region_id (rows). region_id's match those in the postcode_district_data.csv file. turing_regional_estimates_aq_daily_met_pollen_pollution_imputed_data.csv: uses imputed site data (timestamp, region_id, ...[measurement name, rings]) ('rings' is the number of rings required to make the estimation) turing_regional_estimates_aq_daily_met_pollen_pollution_original_data.csv: uses original site data (timestamp, region_id, ...[measurement name, rings]) ('rings' is the number of rings required to make the estimation) turing_regional_estimates_aq_loc_type_daily_imputed_data.csv: uses imputed site data. Air quality regional estimates are calculated using specific AQ site location types* separately. (To prevent, for example, 'Traffic Urban' type sites being used to estimate 'non-traffic' or rural regions.) turing_regional_estimates_aq_loc_type_daily_original_data.csv: uses original data. Air quality regional estimates are calculated using specific AQ site location types* separately. (To prevent, for example, 'Traffic Urban' type sites being used to estimate 'non-traffic' or rural regions.) * Air quality site types: Industrial: comprises 'urban industrial' (9 sites) and suburban industrial (2 sites) 'Rural background' (14 sites) 'Urban background' (48 sites) 'Urban traffic' (47 sites)本数据集收录了2016年至2019年（含首尾年份）英国及皇家属地（UK and crown dependencies）各邮政编码片区（如‘AB’）的一系列空气质量、气象观测数据估算值，以及模型预报结果的日均值与日最大值。介绍本数据集的相关论文可查阅：https://www.nature.com/articles/s41597-022-01135-6。 本数据集采用「同心区域法」估算所有片区的观测数据，具体流程如下：若片区内存在观测数据，则直接取其均值作为估算值；若片区内无观测数据，则选取相邻邮政编码片区构成的环状区域，以该环状区域内的观测数据均值作为估算值。若首轮环状区域未找到观测站点或数据，则继续向外扩展选取下一层环状邮政编码片区，重复该流程直至某一环内找到一个或多个传感器观测数据。 除观测数据估算值外，本数据集还公开了获取站点数据并完成估算所需的环状层数（rings）。**请注意：环状层数（rings）更高的估算值，其数据源很可能来自距离目标片区更远的传感器，该距离取决于待估算位置周边邮政编码片区的面积。请根据您所需的置信度水平，通过环状层数（rings）对估算结果进行限制或筛选。** 用于生成片区估算值的气象、花粉及空气质量观测数据，可在以下Zenodo存档中获取：该存档包含从英国气象局MIDAS档案通过MEDMI服务器（https://www.data-mashup.org.uk/）下载的气温、相对湿度与气压数据；同时也包含从MEDMI服务器下载的英国每日花粉观测数据。此外，还包含来自DEFRA AURN网络的PM10、PM2.5、NO2、NOx（以NO2计）、O3及SO2观测数据，以及使用EMEP模型生成的上述污染物的模型预报结果。 用于生成上述估算值的代码，可在该Zenodo存档中获取。 `postcode_district_data.csv`中的邮政编码数据整合自多个来源： 1. https://www.doogal.co.uk/UKPostcodes.php（英国2011年人口普查的英国人口统计数据） 2. https://www.freemaptools.com/download-uk-postcode-outcode-boundaries.htm（英国及皇家属地的邮政编码边界多边形数据） 3. https://www.gov.gg/population（根西岛（GY）2020年6月末人口数据） 4. https://www.gov.je/Government/JerseyInFigures/Population/Pages/Population.aspx（泽西岛（JE）2019年末人口数据） 5. https://www.gov.im/media/1369690/isle-of-man-in-numbers-july-2020.pdf（马恩岛（IM）2016年4月人口数据） 本数据集以CSV格式存储，共包含6个文件： 1. `postcode_district_data.csv`：区域元数据文件，包含字段：区域ID（region_id）、几何信息（geometry）、区域描述（description）、人口数（population）、所属国家/地区（country） 2. `regional_site_counts.csv`：站点数量统计表，行代表区域ID（region_id），列代表各类观测指标，展示对应片区各指标的监测站点数量。区域ID与`postcode_district_data.csv`中的区域ID保持一致。 3. `turing_regional_estimates_aq_daily_met_pollen_pollution_imputed_data.csv`：基于插补后站点数据生成的估算数据集，包含字段：时间戳（timestamp）、区域ID（region_id）、……[观测指标名称、环状层数（rings）]（注：环状层数（rings）指完成估算所需的环状扩展层数） 4. `turing_regional_estimates_aq_daily_met_pollen_pollution_original_data.csv`：基于原始站点数据生成的估算数据集，包含字段：时间戳（timestamp）、区域ID（region_id）、……[观测指标名称、环状层数（rings）]（注：环状层数（rings）指完成估算所需的环状扩展层数） 5. `turing_regional_estimates_aq_loc_type_daily_imputed_data.csv`：基于插补后站点数据生成的空气质量区域估算数据集，该数据集按照特定的空气质量（AQ）站点类型分别进行估算，以避免例如将「城市交通类」站点的数据用于估算「非交通类」或乡村片区的空气质量。 6. `turing_regional_estimates_aq_loc_type_daily_original_data.csv`：基于原始站点数据生成的空气质量区域估算数据集，该数据集按照特定的空气质量（AQ）站点类型分别进行估算，以避免例如将「城市交通类」站点的数据用于估算「非交通类」或乡村片区的空气质量。 * 空气质量站点类型说明： - 工业类：包含「城市工业区」（9个站点）与「郊区工业区」（2个站点） - 乡村背景类（14个站点） - 城市背景类（48个站点） - 城市交通类（47个站点）