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Timeseries summaries of contaminants in sediment in the 2020 assessment of the UK's Clean Seas Environment Monitoring Programme (CSEMP)

The file sediment_summary.csv summarises the assessment results for each timeseries of contaminants in sediment in the 2020 assessment of the UK's Clean Seas Environment Monitoring Programme (CSEMP). The results come from timeseries models fitted to the contaminant data in sediment_data.csv which in turn are based on data extracted from the MERMAN database on 30 March 2022. Details of the modelling procedures can be found here.

The file sediment_summary.csv is UTF-8-BOM encoded so can be read directly into Excel, or into R using the function read.csv with the argument fileEncoding = “UTF-8-BOM”.

The variables in the file are:

series
Description: timeseries identifier
Unit:
Type: categorical
Levels: 5619
Note: links to the timeseries data in sediment_data.csv

CSEMP_region
Description: CSEMP region where the monitoring station is located
Unit:
Type: categorical
Levels: 17
Note: see map of CSEMP regions

CSEMP_stratum
Description: subdivision of CSEMP region where the monitoring station is located
Unit:
Type: categorical
Levels: 53
Note: there are 818 CSEMP strata, most of which are WFD water bodies, but only 53 with data

biogeographic_region
Description: biogeographic region where the monitoring station is located
Unit:
Type: categorical
Levels: Northern North Sea, Southern North Sea, Eastern Channel, Western Channel & Celtic Sea, Irish Sea, Minches & Western Scotland, Scottish Continental Shelf
Note: see map of biogeographic regions

station
Description: monitoring station
Unit:
Type: categorical
Levels: 99
Note:

station_name
Description: name associated with the monitoring station
Unit:
Type: categorical
Levels: 92
Note:

latitude
Description: station latitude
Unit: decimal degrees
Type: continuous
Range: 49.97, 61.03
Note: this is a nominal position: sampling occurs in a pre-defined area broadly centred on this position

longitude
Description: station longitude
Unit: decimal degrees
Type: continuous
Range: -8.58, 2.33
Note: this is a nominal position: sampling occurs in a pre-defined area broadly centred on this position

MSTAT
Description: type of monitoring station
Unit:
Type: categorical
Levels: B, RH, IH
Note: baseline (B), reference (RH) or impacted (IH)

WLTYP
Description: station typography
Unit:
Type: categorical
Levels: Estuary, Coast, Open Sea
Note:

determinand_group
Description: contaminant group
Unit:
Type: categorical
Levels: Metals, Organotins, PAH parent compounds, PAH alkylated compounds, Polybrominated diphenyl ethers, Organobromines (other), Polychlorinated biphenyls, Dioxins, Organochlorines (other)
Note:

determinand
Description: contaminant
Unit:
Type: categorical
Levels: 76
Notes:
* see ICES reference codes for PARAM
* TEQDFP is the code used for the WHO TEQ_DFP (where DFP indicates dioxins, furans and planar polychlorinated biphenyls)

basis
Description: basis of the assessment
Unit:
Type: discrete
Levels: dry weight (D)
Note:

unit
Description: unit of measurement
Unit:
Type: discrete
Levels: mg/kg, TEQ ug/kg, ug/kg
Note:

shape
Description: the symbol used to summarise the fitted trend
Unit:
Type: categorical
Levels: upward_triangle, downward_triangle, large_filled_circle, small_filled_circle, small_open_circle
Notes:
* upward_triangle: significant (p < 0.05) increase in concentration in the last 20 years
* downward_triangle: significant (p < 0.05) decrease in concentration in the last 20 years
* large_filled_circle: no significant (p > 0.05) change in concentration in the last 20 years
* small_filled_circle: insufficient years of data to test for trends
* small_open_circle: only 1-2 years of data (or a time series dominated by less-than values for which no assessment criteria is available)
* the relevant significance level is given in prtrend

colour
Description: the colour used to summarise the status assessment
Unit:
Type: categorical
Levels: blue, green, red, orange, black
Notes:
* blue: the mean concentration is significantly below the Background Assessment Concentration (BAC) or equivalent (p < 0.05)
* green: the mean concentration is significantly below the Environmental Assessment Criterion (EAC) or equivalent (p < 0.05)
* red: the mean concentration is not significantly below the EAC or equivalent (p > 0.05)
* orange: the mean concentration is not significantly below the BAC or equivalent (p > 0.05) and there is no EAC or equivalent
* black: no assessment critieria

n_year_all
Description: number of years with data
Unit:
Type: integer
Range: 1, 20
Note:

n_year_fit
Description: number of years included in the statistical analysis
Unit:
Type: integer
Range: 1, 20
Note: some early years might be excluded because they are separated from the bulk of the data by large gaps in time, or because they are dominated by 'less-than' values

n_year_positive
Description: number of years included in the analysis that have at least one concentation measurement above the limit of detection
Unit:
Type: integer
Range: 0, 20
Note:

first_year_all
Description: first year with data
Unit: y
Type: integer
Range: 1999, 2019
Note:

first_year_fit
Description: first year included in the statistical analysis
Unit: y
Type: integer
Range: 1999, 2019
Note: see n_year_fit for explanation

last_year
Description: last year of data
Unit: y
Type: discrete
Range: 2014, 2019
Notes:
* the last year is always included in the statistical analysis
* only timeseries with some data in the last six monitoring years are included in the assessment (i.e. 2014-2019 for the 2020 assessment)

p_nonlinear
Description: the significance of the nonlinear component of the trend
Unit:
Type: continuous
Range: 0, 0.066
Notes:
* this assesses whether log concentrations changed nonlinearly over the monitoring period
* it is based on a likelihood ratio test comparing the smooth model with a linear model and is only given if a smooth model is selected by AICc

p_linear
Description: the significance of the linear component of the trend
Unit:
Type: continuous
Range: 0, 1
Notes:
* this test only has a simple interpretation when the trend is linear (rather than smooth) in which case it assesses whether concentrations changed (log-linearly) over the monitoring period
* it is based on a likelihood ratio test comparing the linear model with the null model (in which only an intercept if fitted)
* for smooth models, the terms p_linear_trend and p_recent_trend are more relevant

p_overall
Description: the overall significance of the trend
Unit:
Type: continuous
Range: 0, 1
Notes:
* this assesses whether mean concentrations changed over the monitoring period
* it is based on a likelihood ratio test comparing the fitted model (smooth or linear) with the null model
* p_overall is identical to p_linear if the fitted model is linear

p_linear_trend
Description: a test of whether the mean concentrations at the start and end of the monitoring period are the same
Unit:
Type: continuous
Range: 0, 1
Notes:
* for linear models, p_linear_trend is identical to p_linear
* for smooth models, p_linear_trend is based on a Wald test that compares the fitted values at the start and end of the monitoring period
* p_linear_trend can be non-significant even if p_overall is highly signficant; for example, if concentrations have increased and then decreased by the same amount

linear_trend
Description: an estimate of the change in mean concentration between the start and end of the monitoring period
Unit:
Type: continuous
Range: -29, 19.9
Notes:
* loosely, linear_trend can be interpreted as the percentage annual change in concentration between first_year_fit and last_year assuming the trend in concentration is log-linear
* more information can be found here

p_recent_trend
Description: a test of whether the mean concentrations 20 years ago is the same as it is today
Unit:
Type: continuous
Range: 0, 1
Notes:
* p_recent_trend assesses whether the mean concentration in 2000 (or first_year_fit whichever is later) is the same as the mean concentration in 2019 (or last_year whichever is earlier)
* for linear models, p_recent_trend is identical to p_linear
* for smooth models, p_recent_trend is based on a Wald test that compares the fitted values in 2000 (or first_year_fit) and 2019

recent_trend
Description: an estimate of the change in mean concentration in the last 20 years
Unit:
Type: continuous
Range: -29, 19.9
Notes:
* loosely, recent_trend can be interpreted as the percentage annual change in concentration in the last 20 years assuming the trend in concentration is log-linear
* more information can be found here

detectable_trend
Description: a measure of the power of the time series to detect changes over time
Unit:
Type: continuous
Range: 1.9, 145
Notes:
* the annual change in log concentration (multiplied by 100) that would be detected with 90% power based on a (two-sided) test at the 5% significance level given 10 years of annual monitoring and variability typical of the time series
* loosely, detectable_trend can be interpreted as the percentage annual change in concentration detectable with 90% power in 10 years of annual monitoring
* more information can be found here

mean_last_year
Description: the fitted mean concentration in last_year
Unit: see unit
Type: continuous
Range: 0.0002, 2613
Note:

climit_last_year
Description: the upper one-sided 95% confidence limit on the fitted mean concentration in last_year
Unit: see unit
Type: continuous
Range: 0.011, 31522
Note:

BAC_type
Description: the name of the Background Assessment Concentration (BAC) or equivalent
Unit:
Type: categorical
Levels: BAC
Note:

BAC_value
Description: the value of the BAC (or equivalent)
Unit: see unit
Type: continuous
Range: 0.05, 122
Note: more details can be found in the help file on assessment criteria for contaminants in sediment

BAC_diff
Description: the difference between climit_last_year and the BAC (or equivalent)
Unit: see unit
Type: continuous
Range: -97, 31517
Note: a negative value means that the mean concentration in the final monitoring year is significantly (p < 0.05) below the BAC

BAC_achieved
Description: the first year (moving forward) in which the mean concentration is predicted to be below the BAC (or equivalent)
Unit: y
Type: integer
Range: 2014, 3000
Notes: there are four cases
* mean_last_year &le BAC: the mean concentration is already below the BAC and BAC_achieved is set to last_year
* mean_last_year > BAC and recent_trend < 0: concentrations are predicted to decrease and BAC_achieved is set to the first year that the predicted concentration is below the BAC, assuming the rate of decrease is given by recent_trend; the year is truncated at 3000 to prevent values getting silly
* mean_last_year > BAC and recent_trend &ge 0: concentrations are predicted to increase and the mean concentration will never be below the BAC, so BAC_achieved is arbitrarily set to 3000
* mean_last_year > BAC and no trend is estimated: BAC_achieved is left blank

BAC_below
Description: the result of a non-parametric test of whether mean concentrations are below the BAC (or equivalent)
Unit:
Type: categorical
Levels: above, below
Notes:
* a one-sided sign-text, based on the last five monitoring years, is used to test whether mean concentrations are below the BAC; this provides a non-parametric alternative to the parametric test of status based on cl_last_year, and is useful when the data are dominated by less-than measurements
* the status of the time series (colour) is determined by BAC_diff if a parametric model has been fitted, and by BAC_below otherwise

EAC_type
Description: the name of the Environmenal Assessment Criterion (EAC) or equivalent
Unit:
Type: categorical
Levels: EAC, EQS, ERL, FEQG
Notes:
* EAC = Environmental Assessment Criterion
* EQS = Environmental Quality Standard
* ERL = Effects Range Low
* FEQG = Federal Environmental Quality Guideline

EAC_value
Description: the value of the EAC (or equivalent)
Unit: see unit
Type: continuous
Range: 0.15, 14000
Note: more details can be found in the help file on assessment criteria for contaminants in sediment

EAC_diff
Description: the difference between climit_last_year and the EAC (or equivalent)
Unit: see unit
Type: continuous
Range: -14000, 31437
Note: a negative value means that the mean concentration in the final monitoring year is significantly (p < 0.05) below the EAC

EAC_achieved
Description: the first year (moving forward) in which the mean concentration is predicted to be below the EAC (or equivalent)
Unit: y
Type: integer
Range: 2014, 3000
Notes: there are four cases
* mean_last_year &le EAC: the mean concentration is already below the EAC and EAC_achieved is set to last_year
* mean_last_year > EAC and recent_trend < 0: concentrations are predicted to decrease and EAC_achieved is set to the first year that the predicted concentration is below the EAC, assuming the rate of decrease is given by recent_trend; the year is truncated at 3000 to prevent values getting silly
* mean_last_year > EAC and recent_trend &ge 0: concentrations are predicted to increase and the mean concentration will never be below the EAC, so EAC_achieved is arbitrarily set to 3000
* mean_last_year > EAC and no trend is estimated: EAC_achieved is left blank

EAC_below
Description: the result of a non-parametric test of whether mean concentrations are below the EAC (or equivalent)
Unit:
Type: categorical
Levels: above, below
Notes:
* a one-sided sign-text, based on the last five monitoring years, is used to test whether mean concentrations are below the EAC; this provides a non-parametric alternative to the parametric test of status based on cl_last_year, and is useful when the data are dominated by less-than measurements
* the status of the time series (colour) is determined by EAC_diff if a parametric model has been fitted, and by EAC_below otherwise

Data Preview: Note that by default the preview only displays up to 100 records. Use the pager to flip through more records or adjust the start and end fields to display the number of records you wish to see.

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Additional Information

FieldValue
mimetypetext/csv
filesize1.51 MB
resource typefile upload
timestampDec 02, 2022