Hourly air pollution data for Graz, Austria
- 1. Centre for bioanthropology, Institute for Anthropological Research, Gajeva 32, HR-10000 Zagreb
- 2. Ascalia d.o.o., Trate 16, HR-40000, Čakovec
- 3. Know-Center, Sandgasse 36/4, AT-8010 Graz
- 4. Amt der Steiermärkischen Landesregierung, Referat Luftreinhaltung, Landhausgasse 7, 8010 Graz
- 5. European Center for Medium Range Weather Forecasts, Shinfield Park, Reading, UK-RG2 9AX
Description
The dataset spans from January 1, 2014, to March 15, 2020, with measurements recorded on an hourly basis.
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The environmental and pollutant data was provided by the Austrian government under the following license: CC-BY-4.0: Land Steiermark - data.steiermark.gv.at
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Air quality by means of NO2, NO, NOx, PM10 and O3 was measured at five sites in Graz, Austria (Süd (eng. South) - S, Nord (eng. North) - N, West (eng. West) - W, Don Bosco – D, Ost (eng. East) – O).
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Temperature, precipitation, relative humidity, pressure, and wind speed are among the weather conditions considered. To represent wind direction, the wind speed was multiplied by the sine and cosine of the wind direction.
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Lags were generated using weather data, considering the last 12 data points. The mean of these 12 values was then calculated to represent an hourly metric.
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The ERA5-Land data is subject to the Copernicus licence from following source https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.e2161bac?tab=overview
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it includes following variables :
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Snowfall - sf
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Surface latent heat flux - slhf
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Snowmelt - smlt
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Snow cover - snowc
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Windspeed - speed
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Surface latent heat flux sshf
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Soil temperature level 4 - stl4
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Skin temperature - str
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Surface thermal radiation downwards - strd
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Total precipitation - tp
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Temperature of snow layer - tsn
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10m u-component of wind - u10
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10m v-component of wind - v10
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Surface net radiation - rsn
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Snow depth - sd
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Snow depth water equivalent - sde
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2m dewpoint temperature - d2m
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Forecast albedo - fal
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Temporal values are also incorporated into this dataset, values such as holidays, weekdays, seasons, and months.
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The dataset includes Prophet values for all pollutants, which were determined by considering various metrics such as trend, seasonality (weekly, yearly, and daily), as well as yhat lower and upper bounds.
Files
20221227_final.csv
Files
(48.4 MB)
Name | Size | Download all |
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md5:d7104587475d68788697339e84da3d10
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Additional details
Related works
- Continues
- Dataset: 10.5281/zenodo.6812067 (DOI)