README
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Dataset title:
The International Cooperative Programme on Integrated Monitoring of Air Pollution Effects on Ecosystems (ICP IM)

Creators:
James Weldon
Adéla Holubová Šmejkalová 
Ainis Pivoras 
Algirdas Augustaitis 
Andrzej Kostrzewski
Angelika Kölbl
Anna Koukhta
Barbara Albiniak
Camilla Capelli
Carolina Santamaría
David Elustondo
Esther Lasheras
Filip Moldan
Giancarlo Papitto
Gisela Pröll
Hampus Markensten
Heidi Koger
Heleen de Wit
Ieva Baužienė
Ika Djukic
Iveta Indriksone
Jesús Miguel Santamaría
Johannes Kobler
Johannes Peterseil
Jussi Vuorenmaa
Karin Eklöf
Kairi Lõhmus
Krzysztof Skotak
Lieke E. Vlaar
Liisa Ukonmaanaho
Martin Forsius
Martyn Futter
Mercedes Valerio
Michael Mirtl
Mikołaj Majewski
Nicholas Clark
Nicole Wellbrock
Pavel Krám
Pernilla Rönnback 
Rafael Miranda
Ricardo Ibañez
Robert Kruszyk
Sara Jutterström 
Sarah Venier
Sergei Gromov
Thomas Cummins
Thomas Dirnböck
Thomas Plha
Ulf Grandin
Ulla Makkonen
Wenche Aas


Responsible organization:
Swedish University of Agricultural Sciences

See the Researchdata.se catalogue entry for this dataset for complete metadata, including the dataset description, recommended citation, contact information, and information about how to obtain the dataset. 

Description: The International Cooperative Programme on Integrated Monitoring of Air Pollution Effects on Ecosystems (ICP IM) presents a comprehensive long-term dataset of ongoing integrated ecosystem monitoring from European forested catchments. The dataset encompasses measurements from monitoring stations across 14 European countries, with temporal coverage extending in most cases from the 1990s to the present (sites have different completeness of data over the period, a few have much longer time series in one or two subprogrammes only). This initial release covers data up to 2020, more recent data will be released on a rolling basis with a new update every year.  The integrated monitoring approach applies over multiple monitoring subprogrammes to simultaneously measure physical, chemical, and biological properties across ecosystem compartments including atmosphere, precipitation, throughfall, soil, soil water, groundwater, runoff water, vegetation, and biota. All measurements follow standardised protocols detailed in the ICP IM Manual, ensuring data quality and comparability across sites and time periods. The dataset supports research on ecosystem responses to air pollution, climate change impacts, and biogeochemical cycling. Data is provided by subprogramme (all sites and all years with data in one file), geographic co-ordinates for sites are available in a separate file. Historical data from inactive sites in Belarus, Denmark, Iceland and the United Kingdom are currently available by request, as is data from Finland in sub-programmes TF,SF,SC,SW,FC,LF,FD,VG,EP and BV. The monitoring is done under the framework of the UN Convention on Long-Range Transboundary Air Pollution (CLRTAP) and also has an important role in reporting under the EU national emissions ceiling directive (NECD).

License: CC BY 4.0

Access restrictions: N/A

Essential information for dataset reuse.
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Users are strongly encouraged to refer to the ICP IM Monitoring Manual which describes in detail both the methods used to make measurements in the field and the laboratory, the data formats used, explanations of column headers and flags used in all subprogrammes and example files. This is provided alongside the data.

Also see https://www.slu.se/en/about-slu/organisation/departments/aquatic-sciences/environment/integrated-monitoring/

The IM monitoring programme is ongoing and an updated version of the dataset will be uploaded annually.


Dataset organization
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The data are organised as one CSV file (UTF-8 encoding) per subprogram, covering all sites and years for which data are available (e.g. VG_vegetation.csv contains all available data from the vegetation subprogramme). Geographic co-ordinates for sites are available in IM_sites_info.csv.
An overview table of which site/subprogramme/year combinations are included in the data can be found in ICP_IM_data_overview_table.

Empty cells in the data should be interpreted as N/A rather than zero. However, it should be noted that "NA" is not a missing-value marker in this dataset. In the SUBST and PARAM columns, NA is the substance code for sodium. While most CSV readers treat NA as missing by default (this is true of read.csv() and readr in R, and of pandas.read_csv() in Python), applying that default here will remove the sodium code ("NA") and leave the affected measurements without any indication of what was measured. Users are strongly advised to check that this does not occur (e.g. one solution is to read files with the missing-value string set to the empty string, for example read_csv(path, na = "") in R). 



Datafile descriptions
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Explanations of column names-

AREA: Country code and area number of the monitoring site (e.g. SE14 is Sweden, site 14)
CLASS: Classification code (e.g., diameter, height, decomposition, vitality classes)
COUNTRY: Country in which the site is located, given as the full name (e.g. Czech Republic). The two-letter ISO code for the country forms the first two characters of AREA, and is also given as CountryCod in IM_sites_info.csv
DAMAGE: Code describing cause/type of damage (for tree condition)
DAY: Day of the month (normally not given; used mainly if daily data are reported)
DETER: Code for determination method (used for chemical data)
FLAGQUA: Data quality flag (“L” less than detection, “E” estimated value)
FLAGSTA: Status flag indicating how the value was derived
X = Arithmetic average, mean
W = Weighted mean
S = Sum
SE = Standard Error
M = Mode
A = Monthly minimum
Z = Monthly maximum
XA = Average monthly minimum
XZ = Average monthly maximum
SZ = Maximum daily sum
Primary values are reported without a status flag. 
INST: Two-letter institute or office code responsible for measurements
LEVEL: Measurement or sampling level (e.g., height or depth in cm)
LISTMED: Medium code list for GBIF, soils, etc.
LISTSUB: Parameter code list (e.g., for biochemical or IM parameters)
MEDIUM: Code for sampled substrate
MEDIUM_NAME_GBIF: GBIF accepted scientific name of sample medium/species 
MEDIUM_TAXONKEY_GBIF: GBIF Taxon key ID of sample medium/species 
NAME_GBIF: GBIF accepted scientific name of sampled taxon 
NEEDLES: number of needles on shoots in some subprogrammes
PARAM: Parameter code identifying the measured variable (e.g., DBH, COVEF)
PARLIST: Parameter list code indicating type/list of parameters reported
PFLAG: Flag for permanent/non-permanent trees (e.g., in epiphytes subprogramme)
PRETRE: Pretreatment method code used in chemical sample preparation
SCODE: Four-character station or sample plot code
SIZE: Size of observed area (e.g., hectares)
SPOOL: Spatial pool size—number of samples pooled for reported values
SUBPROG: Subprogramme code or file identifier (2-letter code)
SUBPROG_COLLECTION: Collection code for grouped subprogrammes or data hub context
SUBST: Chemical substance code (e.g., NO3N for nitrate-N)
TAXONKEY_GBIF: GBIF Taxon key ID for taxon/sample medium 
TREE_OR_QUARTER: Tree identifier or sampling quarter/plot ID (NOTE! Before 2010, subplot data in VG were reported as a per species mean value over each quarter of the intensive plot. This variable is now used to identify the subplot (i.e. raw data of per species coverage at each subplot are reported, and “TREE_OR_QUARTER" is the subplot ID). 
UNIT: Measurement unit (e.g. cm, m, kg)
VALUE: Measured or calculated value, in the unit given in UNIT. Values are reported to at most four decimal places
YYYYMM: Year and month of measurement in "YYYYMM" format. Where a value refers to a year rather than to a single month, the month is given as 00 (e.g. 200100)

Codes
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Where codes are referenced, these are provided in the files determination_codes.csv, parameters_and_codes_by_subprogramme.csv, pretreatment_codes.csv and substance_codes.csv



Reference information
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Data Quality:
Quality assurance procedures are noted in the ICP IM Monitoring Manual. Given the long time series there are disturbances that occurred that may have an impact on the data. Users are advised to assess all compartments for a full picture. For example a change in ground vegetation  may be due to increased light after a bark beetle attack but this reason will not be apparent from looking at the VG Vegetation subprogramme in isolation. 

Some data are not included in the openly published dataset at the request of the data owners, or for some historical data because it was not possible to get a decision on consent to publish openly. We hope to add these data in future versions, but for now these data are available by request from the IM Programme Centre, who can also advise on best practice for using data im-database@slu.se