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4 results for “Large Urban Region”
Model results and configuration files for "Large modeling uncertainty in projecting decadal surface ozone changes over urban and industrial regions of China"
<p>This repository includes files as described below:</p> <p><strong>1. namelist_CBMZ09_example.input, namelist_MOZART202_example.input:</strong></p> <p>Two WRF-chem namelist files for CBMZ and MOZART simulation.</p> <p>They are modified according to the namelist from <a href="https://github.com/wrfchem-leeds/WRFotron">https://github.com/wrfchem-leeds/WRFotron</a>.</p> <p><strong>2. wps_namelist_example.wps:</strong></p> <p>namelist for WRF Preprocessing System (WPS)</p> <p><strong>3. temporal_hourly_scale_factor_emission.csv:</strong></p> <p>Hourly scale factors for emissions.</p> <p>Hourly allocation is applied to all emission data (i.e., emissions for 2017, 2030 and perturbated emissions of NOx, VOCs).</p> <p><strong>4. vertical_emission_ratio.csv</strong></p> <p>Vertical shares (ratios) of emissions.</p> <p>Emissions from sectors of power and industry are vertically allocated based on this file. Vertical allocation is conducted for all emission data.</p> <p>These shares are suggested by MICS-ASIA III intercomparison framework.</p> <p><strong>5. 01_2030_2017_simulations.zip: </strong></p> <p>Simulated MDA8 ozone under future (2030) and 2017 emission scenarios by the two chemical mechanisms (i.e., CBMZ, MOZART).</p> <p><strong>6. 02_perturbations_of_NOxVOCs.zip:</strong></p> <p>Simulated MDA8 ozone given perturbations of NOx and VOCs emissions by the two chemical mechanisms.</p> <p><strong>7. 03_hourly_diff_O3_NOx_OH_HNO3.zip: </strong></p> <p>Differences of hourly simulated concentrations of O3, NOx, OH and HNO3 during July in the Base-2017 scenario between CBMZ and MOZART (CBMZ - MOZART).</p>
Large Urban Regions of the world
<p>This database provides the construction of Large Urban Regions (LUR) in the world. A Large Urban Region (LUR) can be defined as an aggregation of continuous statistical units around a core that are economically dependent on this core and linked to it by economic and social strong interdependences. The main purpose of this delineation is to make cities comparable on the national and world scales and to make comparative social-economic urban studies. Aggregating different municipal districts around a core city, we construct a single large urban region, which allows to include all the areas of economic influence of a core into one statistical unit (see Rozenblat, 2020 or Rogov & Rozenblat, 2020 for Russia). In doing so we use four principal urban concepts (Pumain et al., 1992): local administrative units (Municipality or localities: MUNI), morphological urban area (MUA), functional urban area (FUA), and conurbation that we call Large Urban Region (LUR). The LURs are the spatial extensions of the influence of one or several FUAs or MUAs. MUAs and FUAs are defined by various national or international sources. We implemented LURs using criteria such as the population distribution among one or several MUAs or FUAs, road networks, access to an airport, distance from a core, and presence of multinational firms. FUAs and MUAs perimeters, if they form a part of a LUR, belong to a unique LUR. In this database, we provide the composition of the LURs in terms of local administrative units (MUNI), Morphological Urban Areas (MUA), and Functional Urban Areas (FUA).</p> <p>This last update provides new LURs for the 54 African Countries (see Rogromel & Rozenblat, 2024) and some corrections for China.</p> <p>It includes now 1'828 LURs composed of 130'283 localities. </p>
Surface hourly measurement data of O3, NO2 and PM2.5 for "Large modeling uncertainty in projecting decadal surface ozone changes over urban and industrial regions of China"
<p>Surface hourly measurement data of O3, NO2 and PM2.5 during summer of 2017.</p> <p>In the .csv files, the first column contains the ID for each measurement site. "lon", "lat" are longitude and latitude, respectively.</p> <p>Date format is "YYYYMMDD_hour".</p>
DATABASE: RUSSIAN LARGE URBAN REGIONS 2020
<p>This database provides construction of Large Urban Regions (LUR) in Russia. A Large Urban Region (LUR) can be defined as an aggregation of continuous statistical units around a core that are economically dependent on this core and linked to it by economic and social strong interdependences. The main purpose of this delineation is to make cities comparable on the national and world scales and to make comparative social-economic urban studies. Aggregating different municipal districts around a core city, we construct a single large urban region, which allows to include all the area of economic influence of a core into one statistical unit (see Rogov & Rozenblat, 2020 for more details) thus, changing a city position in a global urban hierarchy. In doing so we use four principal urban concepts (Pumain et al., 1992): political definition, morphological definition, functional definition and conurbation that we call Large Urban Region. We constructed Russian LURs using criteria such as population distribution, road networks, access to an airport, distance from a core, presence of multinational firms. In this database, we provide population data for LURs and their administrative units.</p>
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