Report on the analysis of national beach litter m onitoring data and proposal for establishing beach litter baselines Tamara Zalewska, Włodzimierz Krzymiński Institute of Meteorology and Water Management – National Research Institute Maritime Branch in Gdynia, Poland
“Implementation of the second cycle of the Marine Strategy Framework Directive: achieving coherent, coordinated and consistent updates of the determinations of Good Environmental Status, initial assessments and environmental targets” Theme 2: Marine litter baselines and assessment in the Baltic Sea, P 2.1 Development of baselines of marine litter
Contributors: Arūnas Balčiūnas 1 ; Eva Blidberg 2 , Dennis Gräwe 3 , Per Nilsson 4 , Marek Press 5 , Marta Ruiz 6 , Outi Setälä 7 , Jakob Strand 8 , Janis Ulme 9 1 Klaipeda University, Open Access Centre for Marine Research, H. Manto str. 84, LT 92294, Klaipeda, Lithuania 2 Håll Sverige Rent, Besöks- och postadress: Rosterigränd 4, 117 61 Stockholm, Sweden 3 State Agency for Environment, Nature Conservation and Geology, Mecklenburg-Vorpommern, Division 3 Geology, Water and Soil, Department 330 Water Quality Inland- and Coastal Water, Goldberger Straße 12, 18273 Güstrow, Germany 4 University of Gothenburg, Department of Marine Sciences, Carl Skottsbergs gata 22 B , 413 19 Göteborg, Sweden 5 Keep the Estonian Sea Tidy, Estonia 6 HELCOM Secretariat, Katajanokanlaituri 6 B, FI-00160 Helsinki, Finland 7 Finnish Environment Institute (SYKE), Marine Research Centre/Marine Assessments and Management, Mechelininkatu 34a, FI-00260 Helsinki, Finland 8 Aarhus University, National Centre for Environment and Energy (DCE) Frederiksborgvej 399, 4000 Roskilde, Denmark 9 Foundation for Environmental Education, Margrietas iela 16 - 3, Rīga,LV -1046, Latvia
Beach litter m onitoring Monitoring Number Length of monitored Frequency of Marine litter items Country Beach types (number) network period of monitoring sections section monitoring per year categorization 2015 - reference TG ML Denmark 3 100 3(4) 2016 (rural) (3) Master list peri-urban (5), 2012 - 300 – MARLIN/ Estonia 10 urban (1), 3 2016 3000 UNEP/IOC rural (4) peri-urban (3), 2012 - MARLIN/ Finland 12 100 – 326 urban (5), 3 2016 UNEP rural (4) reference (11), 2012 - OSPAR- Germany 26 100 urban (1), 4 2016 Guidelines rural (14) urban (12), rural (18), 2012 - peri-urban(5), MARLIN/ Latvia 42 100 1 2016 peri- UNEP urban(rural)(4), rural/remote (3) urban (1) 2012 - rural (1) Lithuania 4 100 4 2013 semi-urban (1) touristic (1) 2015 - urban (7), TG ML Poland 15 1000 4 2016 rural (8) Master list 2012 - peri-urban(6), MARLIN/ Sweden 10 100 3 2016 rural (4) UNEP
Statistical calculations • Data collection Data per 100m Artificial Processed Glass/ Country Monitoring Beach LONG HELCOM_ Rubber Cloth / Paper/ Unclas Lenght_m Width_m LAT Season Year polymer /worked Metal ceramic _area_ID type subasin textile cardboard s. materials wood s • The monitored beach litter is assigned to eight main material categories: artificial polymer materials, rubber, cloth/textile, paper/cardboard, processed/worked wood, metal, glass/ceramics and unclassified • The basic unit used for the calculations is the number of items in each category per 100 m (it could be called as the frequency of marine litter items per 100 m in each category and total number). If the monitoring is conducted on other distance than 100 meters, then the data is converted to 100m • Based on all data (from all countries and years), statistical calculations were carried out to determine mean, standard deviation, confidence levels, upper and lower, median, minimum, maximum, as well as lower and upper quartiles, as percentiles 10 and 90. Such statistical calculations were also carried out taking into account different aggregations ways. The determination of the percentile 10 was aimed at potential use as threshold values defining the boundary between the good and non-good state of the environment in the individual categories and their sum.
Statistical analysis results for two periods aggregated data within categories and sum for the whole Baltic Sea area Average Total value of Standard Conf. Conf. Lower Upper Perc. Perc. Period number of number of Median Min Max deviation 95% +95% quartile quartile 10 90 data items /100 m 531 70.3 156.9 56.9 83.7 24.0 0.0 1964.0 8.7 79.0 3.6 151.0 2015 - 2016 Artificial polymer materials 1072 95.5 214.0 82.6 108.3 38.7 0.0 3815.0 12.0 101.0 4.9 216.0 2012 - 2016 2015 - 2016 531 2.1 10.2 1.2 3.0 0.4 0.0 211.0 0.0 2.0 0.0 4.0 Rubber 1072 2.3 8.0 1.8 2.8 1.0 0.0 211.0 0.0 3.0 0.0 5.1 2012 - 2016 2015 - 2016 531 1.7 3.5 1.4 2.0 0.3 0.0 47.0 0.0 2.0 0.0 4.0 Cloth/textile 1072 2.4 5.3 2.1 2.8 1.0 0.0 86.0 0.0 3.0 0.0 7.0 2012 - 2016 2015 - 2016 531 5.3 13.2 4.1 6.4 1.0 0.0 146.0 0.0 4.6 0.0 13.0 Paper/cardboard 1072 6.9 14.6 6.1 7.8 1.5 0.0 146.0 0.0 7.0 0.0 19.0 2012 - 2016 2015 - 2016 530 3.2 11.6 2.3 4.2 0.9 0.0 175.1 0.0 2.6 0.0 7.0 Processed /worked wood 1071 3.3 9.7 2.7 3.9 1.0 0.0 175.1 0.0 3.0 0.0 7.1 2012 - 2016 2015 - 2016 531 5.0 17.8 3.5 6.5 1.9 0.0 373.0 0.3 5.0 0.0 12.0 Metal 1072 7.3 38.3 5.0 9.6 2.0 0.0 1141.0 0.7 7.0 0.0 14.0 2012 - 2016 2015 - 2016 531 5.0 17.2 3.5 6.4 1.0 0.0 290.0 0.0 3.0 0.0 9.0 Glass/ceramics 1072 6.5 19.2 5.4 7.7 1.7 0.0 293.0 0.0 5.0 0.0 15.0 2012 - 2016 2015 - 2016 531 2.5 14.5 1.3 3.8 0.0 0.0 211.0 0.0 1.0 0.0 4.0 Unclassified 1072 2.4 12.5 1.6 3.1 0.0 0.0 211.0 0.0 1.0 0.0 4.0 2012 - 2016 2015 - 2016 531 95.1 179.2 79.8 110.3 38.0 0.0 2118.0 14.0 107.0 6.0 214.0 Sum 1072 126.6 242.9 112.1 141.2 58.1 0.0 4111.0 20.0 146.0 8.7 288.0 2012 - 2016
Aggregated results 8 Mean number of items / 100m 140 120 Mean number of items / 6 100 80 4 100 m 60 2 40 20 0 0 Artificial polymer materials Sum 250 14 Mean number of items / 100m Mean number of items / 100m 12 200 10 2012 150 2013 8 2012 2014 6 100 2013 2015 2014 2016 4 50 2015 2 2016 0 0 Artificial polymer materials Sum
Results aggregated by seasons 14 12 Mean number of Items / 100 m Rubber 10 Cloth/textile 8 Paper/cardboard Processed/worked wood 6 Metal 4 Glass/ceramics Unclassified 2 0 Spring Summer Autumn Winter 180 Mean number of items / 100m 160 140 120 100 Artificial polymer 80 materials 60 Sum 40 20 0 Spring Summer Autumn Winter
Results aggregated by country Sweden Sum without Poland cigarette Lithuania Artificial polymer materials without cigarette Latvia Sum Germany Artificial polymer materials Finland Estonia Denmark 0 50 100 150 200 250 300 350 400 Mean number of items / 100m Sweden Poland Rubber Cloth/textile Lithuania Paper/cardboard Latvia Processed/worked wood Germany Metal Glass/ceramics Finland Unclassified Estonia Denmark 0 10 20 30 40 50 60 70 80 90 Mean number of items / 100m
Results aggregated by country Sweden Poland Rubber Lithuania Cloth/textile Paper/cardboard Latvia Processed/worked wood Germany Metal Glass/ceramics Finland Unclassified Artificial polymer materials Estonia Denmark 0% 20% 40% 60% 80% 100% Sweden Poland Rubber Lithuania Cloth/textile Latvia Paper/cardboard Processed/worked wood Germany Metal Glass/ceramics Finland Unclassified Estonia Denmark 0% 20% 40% 60% 80% 100%
Results aggregated by beach type 14 areas hard to reach beaches Mean number of items / 100m which are frequented by few 12 visitors 10 beaches located outside the 8 urban environment; not readily reference accessible by public transport 6 rural and have virtually no facilities 4 urban peri-urban artificially-created environment 2 in an urban setting which 0 simulates a public beachfront, through the use of sand, beach umbrellas, and seating elements 300 Mean number of items / 100m beaches with (many) visitors but 250 which are not in or very close to a city 200 reference rural 150 urban 100 peri-urban 50 0 Artificial polymer materials Sum
350 Mean number of items / 100m Artificial polymer materials 300 250 200 Results aggregated 150 100 by sub-basins 50 0 25 Metal 20 Mean number of items / 100m 15 10 5 0
Beach litter prelim inary baselines settings Baselines is “a starting point that provides a first large scale comprehensive quantitative characterization of marine litter in a specific year and location”. Period for baselines study 2012-2016 or 2015-2016 Mean number of items /100m for each litter category for each station assigned to a particular beach category: reference, rural , urban and peri-urban Mean*, median* of Mean*, median* of Mean*, median* of Mean*, median* of number of items /100m number of items /100m number of items /100m number of items /100m with SD and RSD for with SD and RSD for with SD and RSD for with SD and RSD for each litter category for each litter category for each litter category for each litter category for REFERENCE BEACH RURAL BEACH URBAN BEACH PERI-URBAN BEACH
Recommend
More recommend
