Microplastic research, initially focusing on marine environments, left freshwater ecosystems largely unexplored. Freshwaters are also vulnerable to microplastics and are likely the largest microplastic supplier to the ocean. However, microplastic sources, transport pathways, and fluxes at the catchment level remain to be quantified, compromising efficient actions toward mitigation and remediation. Here we show that 70-90% of microplastics reaching Norway's largest lake, originating primarily from urban waste mismanagement and sludge application on crops, continue their journey toward the ocean without being buried. Indeed, our microplastic budget for the catchment shows that out of the 35.9 tons (7.4-119.4 t) of microplastics annually released into the lake, only 3.5 tons (1.3-8.8 t) are settling to the lake bottom. The spatial and vertical microplastic distribution and diversity in lake sediments, the socio-economic modeling of plastic fluxes and spatial information on land use and potential plastic sources all point toward urban and agricultural areas as emission hotspots of increasing importance. We conclude that the degree to which lake sediments represent a net microplastic sink is likely influenced by the nature of microplastics the lake receives, and ultimately on their origin.
Microplastic research, initially focusing on marine environments, left freshwater ecosystems largely unexplored. Freshwaters are also vulnerable to microplastics and are likely the largest microplastic supplier to the ocean. However, microplastic sources, transport pathways, and fluxes at the catchment level remain to be quantified, compromising efficient actions toward mitigation and remediation. Here we show that 70-90% of microplastics reaching Norway's largest lake, originating primarily from urban waste mismanagement and sludge application on crops, continue their journey toward the ocean without being buried. Indeed, our microplastic budget for the catchment shows that out of the 35.9 tons (7.4-119.4 t) of microplastics annually released into the lake, only 3.5 tons (1.3-8.8 t) are settling to the lake bottom. The spatial and vertical microplastic distribution and diversity in lake sediments, the socio-economic modeling of plastic fluxes and spatial information on land use and potential plastic sources all point toward urban and agricultural areas as emission hotspots of increasing importance. We conclude that the degree to which lake sediments represent a net microplastic sink is likely influenced by the nature of microplastics the lake receives, and ultimately on their origin.
Entities:
Keywords:
catchment; lake sediment; land use; microplastics; plastic sources
Originally
recognized as a problem in the marine environment, increasing
amounts of microplastics are now also reported in terrestrial environmental
samples around the world.[1] Developing methods
for microplastic source identification is a priority to enable actions
toward mitigation and remediation. However, the sources of these items
often lie on land where most of the plastic is used, rather than in
marine and coastal ecosystems.[2] Freshwater
systems can act as transporters and/or sinks for terrestrial microplastics.[3] Investigations into freshwater systems have been
receiving increased attention in the past few years, although most
of the focus is on reporting microplastic distribution.[4] Hence, source tracking methods are currently
limited[4] and the factors influencing the
behavior of freshwaters toward being transporters versus sinks are
ill-known. Therefore, microplastic research efforts need to move upstream
and improve catchment-level approaches to be able to identify the
main sources and quantify freshwater microplastic fluxes and stocks.Quantifying plastic release into surface waters is challenging
due to data sparsity and difficulties attributing microplastics to
their initial sources. Considering the standard waste mismanagement
rate of 2%,[5] and a release rate of 30%[6] for mismanaged waste from coastal areas, we estimate
that 106 tons of plastics could be annually released into Norway’s
largest lake, Lake Mjøsa (5300 t of plastic waste annually processed
in the catchment[7]). However, precise release
pathways are influenced by land use with emission hotspots as highly
populated areas[8] and industrial and agricultural
sites.[3,9] In addition, the amount of microplastics
deposited on the Lake bottom or that are transported downstream remain
to be quantified.Several studies investigated spatial variability
in microplastic
distribution in the Great Lakes and modeled the propagation of floating
plastics.[6,10,11] While these
approaches are relevant for understanding plastic flows within large
lakes, spatial information from the catchment were not included in
these assessments limiting their usefulness for identifying the sources
and release pathways.The distribution of sediment contaminants
can yield significant
spatial and temporal information on pollution, although, in the case
of plastics, a non-negligible fraction may not sink to the bottom
due to their low density. Nevertheless, lake sediments provide reliable
natural archives for estimating historical contamination of heavy
metals[12−14] and organic contaminants[15,16] but their use to describe microplastics pollution has been limited
so far.[17−19]Here we present an original approach to investigate
microplastic
stocks and fluxes and apply it to a Nordic catchment-lake ecosystem,
Lake Mjøsa. We quantify the different plastic morphologies identified
along sediment cores collected at 20 sites and explain their spatial
distribution with an innovative spatial data set. We report spatial
information on land use, wastewater treatment plant (WWTP), urban
and industrial services for the whole catchment as well as for delineated
subcatchments where higher microplastic concentrations are reported.
We further provide a first microplastic budget for the catchment where
top-down estimates of microplastic emissions from the modeling of
socio-economic activities are corroborated with sediment inventories.
Materials
and Methods
Study Site
Mjøsa is a glacially excavated deep
lake, the largest lake in Norway and one of the deepest in Europe
with a volume of 56 km3 (Figure a; Table S1 of
the Supporting Information, SI). Its catchment (17 028 km2) includes large mountain areas in the north, and forest, urban,
and agricultural areas east and west of the lake. Most of the urban,
industrial, and agricultural lands are located along the lake shoreline
around the central part of the lake (Figure a). The river Gudbrandsdalslågen is
the main tributary into Lake Mjøsa, draining an area of 13 000
km2, i.e., 78% of the catchment, with a higher proportion
of natural land types than the areas around the lake (Figure a). Mjøsa is a drinking
water source for approximately 70 000 people through the municipal
and private water supply, as well as industry.
Figure 1
Land occupation, potential
plastic emission sources, and sampling
sites in the Mjøsa catchment and subcatchments. (a) Location
map of the Mjøsa catchment and subcatchment 1. (b) Close up map
of Lake Mjøsa showing subcatchment delineation, intensive and
moderate agricultural areas, as well as urban areas. Note that agriculture,
delineated by the purple color in panel a, is divided into two different
land types and colors here. (c) Close up map of Lake Mjøsa showing
sampling stations, agricultural and seminatural subcatchment delineation,
and location of airport/harbor, mines, large recycling facilities,
plastic industries, wastewater treatment plants (WWTP), and industrial
laundries. Hatched areas are the high urban influence areas where
sediment microplastic concentration is predicted using eq .
Land occupation, potential
plastic emission sources, and sampling
sites in the Mjøsa catchment and subcatchments. (a) Location
map of the Mjøsa catchment and subcatchment 1. (b) Close up map
of Lake Mjøsa showing subcatchment delineation, intensive and
moderate agricultural areas, as well as urban areas. Note that agriculture,
delineated by the purple color in panel a, is divided into two different
land types and colors here. (c) Close up map of Lake Mjøsa showing
sampling stations, agricultural and seminatural subcatchment delineation,
and location of airport/harbor, mines, large recycling facilities,
plastic industries, wastewater treatment plants (WWTP), and industrial
laundries. Hatched areas are the high urban influence areas where
sediment microplastic concentration is predicted using eq .The 20 sampling sites within Lake Mjøsa (Figure c; Table S2) were chosen to be representative of a range of diverse
lacustrine environments with some close to potential sources of microplastics,
as well as reference points in Lake Mjøsa’s natural sediment
accumulation areas. Several of the selected stations have been previously
described regarding location, depth, sediment dating, and content
of certain pollutants.[15]Lake Mjøsa
is subjected to internal sediment redistribution
as a result of sediment focusing[20,21] but also due
to unstable sediment flow along steep underwater slopes (reaching
locally 30°).[22] Multibeam bathymetry
and sub bottom profiler data are restricted to the surroundings of
the city of Gjøvik[22] (Figure a), which prevents any interpretation
of the processes leading to sediment movements. To avoid misinterpretation
of sediment microplastic concentrations, we only consider spatial
and vertical patterns that are supported by several stations. To account
for sediment focusing, however, we interpolated the sedimentation
rate from four cores taken at different depth and dated with 210Pb for the 20 sampling sites[23] (SI Note S1).
Microplastics Sampling
and Analyses
Sediment sampling
was conducted between August 6th and 9th, 2018.
Cores were collected from each of the 20 locations using a Kajak-Brinkhurst
sediment corer with an internal diameter of 8.5 cm. In the deepest
parts of the lake a Van Veen grab was used and a core was taken once
on the deck. Each sediment core was divided into 1 cm slices in the
field, within 30 s for each core slice. On return to the laboratory,
each core slice was freeze-dried for further processing by density
separation with sodium iodide (NaI, 1.7 g cm–3),
in some instances organic matter removal had to be included using
Fenton’s reagent.[24] Samples were
passed through a 75 μm sieve to remove smaller particles. The
retained material was then rinsed onto filter papers (GF/D, 47 mm,
pore size 2.7 μm).All particles found in each sample
were analyzed by visual identification and measured along their longest
and shortest dimension followed by chemical confirmation of the polymer
material. Suspected microplastics were analyzed using a PerkinElmer
Spotlight 400 μFT-IR in transmission mode. A diamond compression
cell (DC-2 Diasqueeze) was used to improve spectral quality. Background
scans were taken each time the compression cell was reloaded onto
the instrument (circa every 1–4 suspected microplastic particles).
All spectra were compared with a series of commercial (PerkinElmer
ATR Polymers library, STJapan Polymers ATR library), the BASEMAN library[25,26] and in-house libraries (including reference polymers, different
textile materials, and potential sources of laboratory contamination)
and manually inspected to confirm the match. Only 3% of the suspected
microplastics were rejected after FT-IR analysis because of no polymer
match. Procedural contamination was monitored throughout the sampling
and analysis with the use of a series of blank samples to allow for
results corrections based on presence of plastics in blanks. Only
1 out of 62 blanks contained one particle of pink polypropylene. Since
this microplastic type was absent in our samples, no bank correction
was performed. Data was presented as microplastics per gram dry weight
for each core slice. The upper size class of microplastics included
here is 5 mm. The lower limit of microplastics was defined by sample
processing method (75 μm).The diversity of microplastic
polymers found in sediment samples
was evaluated using the Shannon and Simpson diversity indexes, as
well as richness and evenness indexes.[27−29] We defined S as the richness, i.e., the total number of microplastic polymers
in a sample, n as the
number of microplastic of the ith polymer,
where i is an integer from 1 to S, N as the total number of microplastic in a sample (N = Σn), p as the proportion of the ith polymer () in a sample.
The Shannon index H is defined as follows:The Simpson index D is defined
as follows:The evenness EH is defined as follows:Mann–Whitney Rank Sum tests were performed
to compare the diversity, evenness, and richness indexes reported
for two sample groups. The Pearson and Spearman correlation coefficients
were calculated to determine any significant linear relationship of
these indexes with time.
Sediment Age Model
The sediment
age model developed
with four dated sediment cores taken at various water depths[15] provided an approximate date of deposition for
each sediment layer at each station (see SI Note S1). As a result of sediment focusing,[20] the sedimentation rate was higher for deeper sites although the
variability in deposition dates was not significant compared to the
duration of the studied time period. For clarity, we use only deposition
dates averaged for all sites in our assessment. To look for spatially
consistent temporal patterns rather than isolated signals, we calculated
indexes with samples from a given sediment depth interval for a group
of sites (all, urban or natural, as defined below).
Catchment and
Subcatchments Delineation
Mjøsa
catchment and selected subcatchments (Figure ) have been delimited using a 10 × 10
m2 Digital Elevation Model publicly available from hoydedata.no
which was reclassified to 25 × 25 m2 for computational
efficiency. The reclassified DEM was then processed with the TauDEM
package[30] in order to fill depressions
and then obtain the D8 flow direction raster (all water from one cell
flows to the lowest adjacent one). The NVE river network[31] was burned into the DEM with filled depressions.
The consolidated DEM was then used to derive the catchments which
were further used in a GIS application (QGIS v.3.6.0) to retrieve
land cover data.
Land Cover Data
Land use data has
been retrieved from
a Jupyterhub intersecting the catchment and subcatchment polygons
with the land use data from CORINE landcover from 2000 to 2018 (Copernicus
European program of Earth observation). The various CORINE land classes
have been reclassified as shown in Table S3. The total length of urban shoreline and the shortest distance from
each sampling station to the nearest upstream town (>2000 inhabitants)
was manually computed. Municipalities at least partly located in the
catchment were identified; however, to construct a representative
data set, only municipalities for which at least 50% of their territory
was located within the catchment were included. The total surface
area represented by the selected municipalities was only 7% larger
than that of the catchment. Missing or added areas were mostly natural
land types and all urban settlements with more than 2000 inhabitants
were included. Official data on plastic industries, waste sorting
facilities, waste production and management, population estimates,
wastewater volume, driving distances and road length from the selected
municipalities were then downloaded from Statistics Norway.[7] The average water outflow was reported for each
WWTP as provided in Snilsberg et al. (2005).[32]Plastic industries were normalized according to the number
of employees in the company, e.g., 1 and 0.5 normalized plastic industry
are equivalent to a company of more than 100 employees and 50 to 99
employees, respectively. Plastic industries were then associated with
the “Industrial and commercial unit” polygon found within
the municipality boundary. In only one case, several industrial polygons
were located within the municipality boundary. We therefore performed
a web search for the main plastic industries in this municipality
to confirm their location.We identified five urban and industrial
zones close to sites 2,
4, 7, 11, and 13 of which only three included plastic industries (close
to sites 2, 4 and 13; Figure c). Subcatchments S3 and S5 are the most agricultural, with
28% and 45% agricultural areas, respectively. Most importantly, about
90% of their agricultural land is used for intensive agriculture (>75%
of cultivation; Figure b). Some other subcatchments (S2, S4, S6, S7, and S8) also have a
significant fraction of agricultural land (15 to 20%), but most of
it falls into land types with <75% of cultivated land and considerable
natural attributes. Other potential sources of microplastics, i.e.,
mines, airports, harbors, large recycling facilities, industrial laundry,
and WWTP, represented in Figure c, also show a higher density close to sites 7 and
13, within the two largest urban centers, i.e., Gjøvik and Hamar.
Top-Down Plastic Flux Estimates
The plastic fluxes
for the Mjøsa catchment were estimated following a top-down approach
with statistics on socio-economic activities within the catchment
similar to Boucher et al. (2019).[3] This
procedure included the estimation of: (i) the magnitude of different
sources in the plastic consumption and production processes; (ii)
the losses to the environment; and (iii) the releases into surface
waters and Lake Mjøsa.Annual national and municipal data
on waste production and management, population estimates, wastewater
volume, plastic industries, driving distances, and road lengths were
retrieved from Statistics Norway.[7] Other
data sources included PlasticsEurope[33] and
scientific literature (Tables S4 and S5).
Step 1: Quantification of the Magnitude of Plastic Sources within
the Catchment
The plastic life-cycle assessment included
three phases: production (including primary production and plastic
conversion), use, and end-of-life. The production of plastic was downscaled
from European and national statistics on plastic production and sales
taking into account the number of plastic producers and their size
(i.e., number of employees) within the watershed. The total amount
of plastics in use was estimated from French and Swiss estimates from
Boucher et al. (2019)[3] and population within
the catchment, and usage by market was downscaled from data given
by PlasticsEurope 2019.[33] Plastic end-of-life
treatment was obtained from official statistics on household plastic
waste and treatment from municipalities within the watershed and on
plastic waste by sector at the national level.
Step 2: Quantification
of Environmental Losses
Environmental
losses included all microplastics released into the various compartments
of the environment. Note that at this stage, some plastics, e.g.,
from household waste mismanagement, are still macroplastics but show
a high potential for microplastic generation.
Wastewater Treatment Plants
Losses during wastewater
treatment were calculated from data on microplastics removal efficiency
from several wastewater treatment plants in Norway, including one
within the watershed.[34,35] Since microplastics from household
laundry represent a significant fraction of those contained in wastewater
influents,[35] microplastic losses from textile
were estimated considering generic washing habits per household and
standard share of synthetic clothes and shredding rate reported in
the literature.[36]
Agriculture
Microplastic losses from agriculture included
two main processes: (i) the weathering of mulching films and (ii)
the application of sewage sludge. Most of microplastics originating
from household and laundry, industrial processes (e.g., blasting and
shredding of plastics), and from the decomposition of plastic surfaces
(e.g., polymeric paints) will be conveyed to municipal effluents and
mainly be collected by wastewater treatment plants. Existing wastewater
treatment processes effectively removes most of the microplastics
from water and retain them in the sludge.[37] In Europe and North America about 50% of sewage sludge is used as
a fertilizer in agriculture.[9] In Norway,
a total of 71 505 tons (dry weight) of sewage sludge has been
applied to agriculture in 2018.[7] Data on
wastewater microplastic concentration and removal efficiency from
several wastewater treatment plants in Norway, including one within
the watershed,[34,35] and wastewater volumes from municipalities
within the catchment are used to estimate the amount of microplastic
applied to agricultural soils. Additional estimates are derived from
official municipal statistics on agricultural sludge application and
typical microplastic content in sludge reported in the literature.[38] Plastic losses from mulching were downscaled
from national mulching surface area and typical rates of mulch application
and mulch recovery reported in the literature.[3]
Construction
Microplastic losses from construction
primarily occurs during the building phase[3] assuming that once plastics have been integrated into a building,
losses are negligible and that during the demolition phase, waste
is properly managed. Expanded polystyrene (EPS) represents the main
losses from construction sites,[3] and is
used for its expanding property for insulation and typically undergoes
a polishing step which emits plastic dust.[39] Losses were estimated using typical EPS usage in construction, plastics
used for construction in the catchment and typical EPS loss rate reported
in the literature.[3]
Plastic
Industry
Losses in production were estimated
from standard rates of losses during delivery of primary plastic within
the watershed as a function of the total plastic produced in the watershed.
Car and Lorry Tires
Plastic emissions from tires have
been calculated from emission rates estimated for Norway[40−42] using official statistics on driving distances within the watershed
for four categories of vehicles and standard synthetic rubber composition
of tires.[43]
Road Marking
Road
paint is a major source of synthetic
polymers such as methyl methacrylate.[40,41] Road marking
losses were quantified using official statistics on road length within
the watershed and downscaling the amount of paint annually applied
on Norwegian roads[41] considering that old
paint was not gathered prior to new paint application.
Household
Waste Mismanagement
Even if the Norwegian
waste management system is among the most efficient in the world,[44] involuntary spill and illegal littering is still
a probable and important source of microplastics for the environment.
Tons of plastic waste, mainly from private use, are recurrently collected
on lake beaches in Norway, including along Lake Mjøsa.[45] Jambeck et al. (2015)[5] considered a standard rate of 2% of waste mismanagement for plastics
in occidental countries. Here, we take this 2% rate as the most pessimistic
rate for microplastic losses and consider a rate, 1 order of magnitude
lower, as a more realistic estimate for microplastic losses from waste
mismanagement.[3] These rates are typically
used for macroplastic losses, attributing them to microplastics comes
with the assumption that the amount of plastic present in the environment
is at steady state, i.e., that the amount of macroplastics losses
equals microplastic generation through degradation. We applied these
rates to annual amounts of household plastic waste generated within
the watershed, i.e., mainly food packaging. While the underlying assumption
that macroplastic stocks in the environment are at steady state (losses
equal microplastic generation) cannot be supported by our data set,
it helps taking into account microplastics generated from illegal
littering, which would have been ignored otherwise.This analysis
excluded microplastics from cosmetics, recreational products, medical
waste, toys, household appliances, and furniture. Most of these items
are likely not the dominant sources of microplastics for the environment,
although, Boucher et al. (2019)[3] considered
equestrian gear as a major source, as well as balloons and fishing
gear. Altogether, we consider that the top-down environmental loss
estimates are conservative given the nonexhaustive list of sources.
Step 3: Release Pathways to Surface Waters
Once in
the environment, microplastics can reach surface waters through several
pathways described in detail elsewhere.[3,46]
Mismanaged
Waste
Leaching of mismanaged waste, e.g.,
resulting from littering or forgotten plastics in agriculture, to
adjacent surface water has been previously estimated at 15–40%,
with a mean value of 25%.[5,6] We used these values
for microplastic releases from agriculture, construction, the plastics
industry, and household waste mismanagement. Note that a recent study
showed that >99% of microplastics applied from biosolids were likely
exported to the aquatic environment.[47] Given
that, to our knowledge, only one study has specifically looked at
microplastic agricultural runoff, and they argue that release rates
are likely influenced by local properties and weather events,[47] we used the mismanaged waste release rate for
agriculture microplastic releases, although it is likely conservative.
Road Runoff
Microplastic emissions from tire dust and
road paint are mainly released to surface waters through road runoff.
Previous studies have estimated that 2–18% of these particles
reached the surface waters.[40,48] We considered a mean
value of 6%.[3]
Sewage System
We used reported microplastic capture
rates for wastewater treatment plant in Norway including one in the
watershed.[34,35] Microplastic removal efficiency
was reported to be as high as 90 to 99% for these WWTP with a mean
value of 95%. This release pathway is likely to provide a conservative
estimate since we neglected any microplastic release caused by storm
overflow.
Direct Release
This pathway was
only applied to WWTP
effluents, as microplastic capture rates were already applied during
the calculation of the associated environmental losses (step 2).
Microplastic Stock in Lake Mjøsa Sediments
To
estimate the total mass of microplastic in the top 5 cm of the sediment
column in L. Mjøsa, two cases have been considered: (i) sediment
located within 2 km downstream of urban areas, defined as high urban
influence areas; and (ii) sediment located in the rest of the lake
bottom defined as natural areas. Mean sediment microplastic concentration
([MP]) in high urban influence areas has been modeled with the following
equation:where x (in m) is the distance
to the nearest upstream town.For the rest of the lake, i.e.,
for natural areas, given that mean sediment microplastic concentrations
from the relevant stations were relatively consistent (e.g., ranging
between 0.02 and 0.12 microplastic g–1), the mean,
minimum, and maximum concentrations obtained have been extrapolated.
Note that, out of the 20 stations sampled in this study, nearly half
of them were located in high urban influence areas, defined as “urban
sites”, while the rest were “natural sites”.
The surface area under high urban influence (37 km2) has
been manually computed in QGIS using land cover data. As a minimum
and maximum estimate for the high urban influence areas, we considered
a total length of urban coastline from 6.5 to 13 km as estimated above.
To simplify calculations, the high urban influence areas have been
idealized as a trapeze whose width and surface area were 6.5–13
km and 37 km2, respectively. This procedure yielded the
total mass of microplastic over the top 5 cm of the sediment column.
Considering the sedimentation rates and the temporal trend in microplastic
deposition, we also estimated microplastic deposition in 2016 in the
whole lake (Table S6).
Results and Discussion
Microplastic
Abundance, Composition, And Diversity
Microplastics (75–5000
μm) were found in each sampled
sediment core, even in more remote locations (Table ). Size distribution shows that 60% of plastic
particles were less than 1 mm in size, 36% of plastics were between
1–5 mm in size, and 4% of plastics were greater than 5 mm in
size (not considered as microplastics; Figure S1). The sediment microplastic concentration averaged over
each core ranged between 0.01 and 1.46 microplastic g–1 which is consistent with typical concentrations reported from freshwater
sediments.[49,50] Half of the selected sites, located
in urban (and/or agriculturally) influenced areas (Table and Figure c), showed mean concentrations above 0.20
microplastic g–1 and significantly higher concentrations
than the other sites (Mann–Whitney rank sum test, P < 0.001). These sites are referred to as urban sites hereafter,
while the remaining are so-called natural sites.
Table 1
Sediment Microplastic Concentration
([MP]) and Richness (S), Diversity (H and D) and Evenness (EH) Indexes at Each Sampling Site
sites
[MP] (microplastic
g–1)
S
H
D
EH
0–1 cm
1–2 cm
2–3 cm
3–4 cm
7–8 cm
average per site
urbana
2
0.78
0.14
0.13
0.03
0.23
0.26
9
1.84
5.0
0.84
4
2.54
0.36
0.85
0.10
0.04
0.78
6
1.46
3.5
0.82
5
0.91
0.45
0.63
0.03
0.41
10
1.83
3.9
0.80
7
1.18
1.44
0.20
0.38
0.18
0.68
11
2.05
6.0
0.85
8
0.58
0.06
0.67
0.08
0.28
7
1.91
6.5
0.98
9
0.93
0.07
0.29
0.09
0.03
0.28
8
1.80
4.6
0.86
13
1.15
1.25
2.03
2.17
0.71
1.46
11
1.94
5.6
0.81
14
0.75
0.93
0.92
0.52
6
1.39
3.0
0.78
15
0.86
0.08
0.96
0.10
0.40
7
1.85
5.8
0.95
16
0.20
0.37
0.18
0.41
0.06
0.25
8
1.87
5.7
0.90
natural
1
0.14
0.08
0.12
0.07
3
0.95
2.3
0.86
3
0.04
0.15
0.04
4
1.33
3.6
0.96
6
0.05
0.10
0.06
0.04
3
0.95
2.3
0.86
10
0.24
0.20
0.07
0.10
3
1.05
2.8
0.96
11b
0.13
0.24
0.24
0.12
4
1.24
3.0
0.90
12
0.19
0.04
1
0.00
1.0
17
0.04
0.01
1
0.00
1.0
18
0.13
0.03
1
0.00
1.0
19
0.33
0.14
0.46
0.18
5
1.55
4.5
0.96
20
0.05
0.15
0.04
3
1.04
2.7
0.95
average per depth
0.54
0.29
0.37
0.22
0.08
Sites showing average sediment microplastic
concentrations greater than 0.20 microplastic g–1. All these sites, except one (site 16) which is located in an agriculture
influenced area, are located in high urban influenced areas (Figure c).
Site 11 is located near an urban
zone (Figure c) but
does not display patterns regarding microplastic sediment concentration,
diversity, evenness, and richness that are similar to the other urban-influenced
sites. It was therefore considered as a natural site.
Sites showing average sediment microplastic
concentrations greater than 0.20 microplastic g–1. All these sites, except one (site 16) which is located in an agriculture
influenced area, are located in high urban influenced areas (Figure c).Site 11 is located near an urban
zone (Figure c) but
does not display patterns regarding microplastic sediment concentration,
diversity, evenness, and richness that are similar to the other urban-influenced
sites. It was therefore considered as a natural site.This finding is in line with recent
freshwater studies also reporting
higher microplastic concentrations closer to urban areas.[49,50] Most of the cores show increasing concentrations with decreasing
sediment depth although local trends may differ. Variability within
the reported cores arise from differences from one layer to another.
These differences can be caused by changes in plastic inputs to the
lake, but they also likely reflect local depositional and erosional
processes. Our data set and the absence of high-resolution bathymetric
data does not enable us to resolve any of these processes. Hence,
we thereafter focus on the microplastic concentrations averaged for
each site and spatial and temporal patterns that are supported by
several stations.A total of 13 polymers were found (Figure S2) with contrasting microplastic diversity
across sites, but consistent
patterns among urban and natural sites. Microplastic polymers were
dominated by acrylic and polyester representing nearly 50%, followed
by polyethylene, polypropylene, polyethylene terephthalate, polystyrene,
viscose, and polyamide, while synthetic rubber, poly methyl methacrylate,
polyurethane, polyvinyl chloride, and polycarbonate were quasi absent
(Figure S2). The polymer density of sediment
microplastics ranged from 0.9 to 1.5 g cm–3 with
an average of 1.15 g cm–3. Only two polymers were
less dense than water: polyethylene and polypropylene. In total, fibers
accounted for 50%, fragments 49% and beads 1%. The urban sites, showing
higher mean concentrations (>0.25 microplastic g–1), also displayed higher richness (S, see Methods for a definition of the indexes) and diversity
(H and D) indexes as well as lower
evenness (EH) than the natural sites.
Indeed, urban sites had H, D, and S indexes significantly higher (P <
0.001) than natural sites, while EH indexes
were significantly higher (P < 0.05) for natural
sites (Figure a-d).
All these indexes are consistent with urban sites being closer to
the microplastic pollution source(s) compared to natural sites. Indeed,
higher diversity and richness are expected closer to the source. In
addition, higher evenness at more distal natural sites also supports
this interpretation since these sites receive microplastics following
transport and redistribution during storm events. These random-like
transport processes have the effect of dispatching microplastic across
space, homogenizing their spatial distribution.
Figure 2
Sediment samples from
urban sites showed higher microplastic concentrations
and diversity indices than those from natural sites, as well as significant
increasing trends with time. (a–d) Box plots of the diversity
(H and D in panels a and b, respectively),
evenness (EH in panel c) and richness
(S in panel d) indexes for sites located in natural
and urban (and/or agricultural) influenced areas. (e) Temporal evolution
of the diversity (H and D), evenness
(EH) and richness (S)
indexes. (f) Average sediment microplastic concentrations ([MP] microplastics
g–1) for natural and urban (and/or agricultural)
influenced sites. In panel (f), sediment concentrations are also shown
for the sum of all sites. ****, ***, **, and * indicate significant
difference following Mann–Whitney Rank Sum test (panels a–d),
or significant positive relationship between a given index and time
according to Pearson and Spearman correlation coefficients (panels
e and f) at a level of 0.001, 0.01, 0.05, and 0.1, respectively.
Sediment samples from
urban sites showed higher microplastic concentrations
and diversity indices than those from natural sites, as well as significant
increasing trends with time. (a–d) Box plots of the diversity
(H and D in panels a and b, respectively),
evenness (EH in panel c) and richness
(S in panel d) indexes for sites located in natural
and urban (and/or agricultural) influenced areas. (e) Temporal evolution
of the diversity (H and D), evenness
(EH) and richness (S)
indexes. (f) Average sediment microplastic concentrations ([MP] microplastics
g–1) for natural and urban (and/or agricultural)
influenced sites. In panel (f), sediment concentrations are also shown
for the sum of all sites. ****, ***, **, and * indicate significant
difference following Mann–Whitney Rank Sum test (panels a–d),
or significant positive relationship between a given index and time
according to Pearson and Spearman correlation coefficients (panels
e and f) at a level of 0.001, 0.01, 0.05, and 0.1, respectively.
Temporal Trends in Sediment Microplastic
Concentrations in Lake
Mjøsa
Figure e,f displays the sediment microplastic diversity, richness,
and evenness indexes for urban, natural, and all sites, as well as
the sediment microplastic concentrations from the 1980s to 2017 for
the three groups of sites. The Shannon diversity index, the richness
and concentration significantly increased at the urban sites since
the 1980s. Further, the concentration for all sites showed significant
increasing trends, while no significant trends were associated with
the natural sites. Hence, the increase in the accumulation rate of
microplastic over time in the Mjøsa sediments (+ 1.2 ± 0.4%)
seems to mainly be caused by increased deposition at the urban sites
(+ 2.2 ± 0.7%).
Urban Areas as the Main Sources of Microplastics
Figure shows that
there
is a clear decreasing trend in sediment microplastic concentration
as the distance from the nearest town increases. This observation
is also supported by the three littoral-distal transects (stations
4–5–6, 7–8–9, and 13–14–15)
showing a clear decreasing trend. The variability in sediment microplastic
concentration ([MP] in microplastic g–1) can be
well predicted (R2 = 0.77) using a simple
inverse regression (eq ).
Figure 3
Sediment
microplastic concentration ([MP]) shows a significant
inverse correlation to the distance of the nearest upstream city.
Depth-average [MP] at all sites as a function of distance to the upstream
nearest town. Gray dashed lines connect stations along a littoral-distal
transect, e.g., stations 13, 14, and 15. Note the systematic decrease
in [MP] along these transects.
Sediment
microplastic concentration ([MP]) shows a significant
inverse correlation to the distance of the nearest upstream city.
Depth-average [MP] at all sites as a function of distance to the upstream
nearest town. Gray dashed lines connect stations along a littoral-distal
transect, e.g., stations 13, 14, and 15. Note the systematic decrease
in [MP] along these transects.This finding points toward near-shore towns acting as the main
source of microplastics to Lake Mjøsa which is consistent with
similar findings in coastal ecosystems[51−54] and the current view that a significant
fraction of microplastics comes from urban waste mismanagement.[3,5,6,8,55,56] Sediments
collected at urban sites have a microplastic content with higher diversity
and richness, as well as lower evenness which are all consistent with
this interpretation. Similarly, richness and diversity increase with
time at urban sites, but not at natural sites, suggesting that microplastic
releases increase mainly from urban areas.
Modeled Plastics Environmental
Losses and Releases into Surface
Water
Our socio-economic top-down modeling reveals that about
10.1 kt of plastic are annually introduced into the market in Mjøsa
catchment, while between 15.2 and 27.6 kt are estimated to be currently
in use and only 9.0 kt discarded (Figure ; Table S4). The
imbalance between production and end-of-life fluxes can be explained
by the increasing use of plastics as well as their increasing lifetime,
or by unaccounted export fluxes.
Figure 4
Annual (micro)plastic budget for Lake
Mjøsa Catchment showing
that most of incoming microplastics are not buried but that microplastic
deposition increases exponentially following trends in Global plastic
production. The magnitude of plastic sources within the catchment,
environmental losses, and releases to the lake were calculated following
a top-down modeling approach considering socio-economic activities
within the catchment. Microplastic depositional rates show a significant
fit to an exponential growth curve with a simple exponent and two
parameters (Adjusted R2 = 0.87, P < 0.05). The doubling time of microplastic deposition
in L. Mjøsa is about 12 years. Microplastic deposition is significantly
correlated to world plastic production (Pearson’s correlation, r = 0.92, P < 0.05) and population in
the catchment (Pearson’s correlation, r =
0.90, P < 0.05). World and european plastic production
numbers are from PlasticsEurope[33,39] while population date
are from Statistics Norway.[7] Microplastics
from tires (4.5 t) were omitted from the microplastic flux potentially
reaching the ocean because they are considered to be trapped in road
verges, sedimentation ponds, or very littoral sediments.[60,61]
Annual (micro)plastic budget for Lake
Mjøsa Catchment showing
that most of incoming microplastics are not buried but that microplastic
deposition increases exponentially following trends in Global plastic
production. The magnitude of plastic sources within the catchment,
environmental losses, and releases to the lake were calculated following
a top-down modeling approach considering socio-economic activities
within the catchment. Microplastic depositional rates show a significant
fit to an exponential growth curve with a simple exponent and two
parameters (Adjusted R2 = 0.87, P < 0.05). The doubling time of microplastic deposition
in L. Mjøsa is about 12 years. Microplastic deposition is significantly
correlated to world plastic production (Pearson’s correlation, r = 0.92, P < 0.05) and population in
the catchment (Pearson’s correlation, r =
0.90, P < 0.05). World and european plastic production
numbers are from PlasticsEurope[33,39] while population date
are from Statistics Norway.[7] Microplastics
from tires (4.5 t) were omitted from the microplastic flux potentially
reaching the ocean because they are considered to be trapped in road
verges, sedimentation ponds, or very littoral sediments.[60,61]Total microplastic losses in the
watershed are 308 (235–441)
t yr–1 with microplastics from tire abrasion, agriculture
(mainly from wastewater sludge), laundry, household waste, and road
markings as the main contributors (Figure ; Table S5). Total
releases into the catchment waters are 36 (7–119) t yr–1 with mismanaged waste being the main release pathway,
mainly through the application of sludge on agricultural soils (16.3
t yr–1) and household waste littering (5.9 t yr–1). Releases from road runoff (5.5 t yr–1), including microplastic from tire and road paint, and from WWTP
(3.8 t yr–1) represent about 20% and 12% of the
total, respectively. Microplastic releases, totalling 160 g inhabitant–1 yr–1, are more than twice larger
than those reported for Lake Geneva.[3] However,
about half of these releases are due to sludge application, a practice
that has been banned in Switzerland since 2006.[57]Release estimates from tires and road marking are
robust since
the tire weight before and after use, the amount of road paint that
is applied and their release pathway are well constrained.[40,41] Other fluxes, such as releases from sludge application on agricultural
land or from household waste, have an intermediate level of uncertainty
since initial stocks/fluxes are based on official municipal statistics
but some losses and releases rates are taken from the literature,
e.g., littering rate of 2%[5] and 0.1%[3] for household wastes. These uncertainties did
not compromise the consistency of our budget since we used conservative
release and loss rates. In particular, despite the use of a conservative
release rate, both independent methods used to estimate microplastic
releases from sludge application showed that this flux was the largest
(Table S5).Besides corroborating
the importance of urban areas as microplastic
sources, the top-down modeling highlights agricultural practices as
potential considerable microplastic emission pathways as recently
pointed out.[9] Indeed, sludge application
is the most important release within Mjøsa catchment (Figure ) which is consistent
with the fact that sites located at the outlet of most agricultural
subcatchments, e.g., sites 13–16, show the highest sediment
microplastic concentrations when normalized to the distance to the
nearest town (Figure ).
Microplastic Lake Retention
Only about 10% of the microplastics
emitted settles into Lake Mjøsa sediments (Figure ), making the lake more of a pipe than a
sink, in contrast to the interpretation for Lake Geneva.[3] Our sediment microplastic stock estimate is likely
conservative since size fractions <75 μm were not collected.
Also, urban-influenced sediments showing higher sediment microplastic
concentration might cover a larger proportion of the lake bottom than
estimated here. However, this underestimation is likely not several
fold ensuring that most of the plastics emitted in the catchment is
not buried in Lake Mjøsa sediments. While the fate of those microplastics
cannot be completely resolved, we can say with confidence that they
are still available for further downstream transport or remobilization,
potentially all the way to the ocean. The important contributions
of sludge application (about 50%) and tire abrasion (about 15%) to
microplastic releases in Mjøsa can partly explain the contrasted
behavior of L. Mjøsa and Geneva. First, most of microplastics
found in sludge from eight Norwegian WWTPs, including the largest
one in Mjøsa catchment, are expected to float after remobilization
since those are beads and fragments of low density (<1 g cm–3).[34] In Switzerland, by
contrast, sludge application was banned in the 2000s.[57] Second, microplastics emitted from tires, e.g., Styrene
Butadene Rubber,[42] are associated with
higher density components resulting in composite particles of very
high density (1.5–2.2 g cm–3)[48,58,59] that are expected to be trapped
in road verges, sedimentation ponds or very littoral sediments.[60,61] This interpretation is also consistent with the quasi-absence of
synthetic rubber in our sediment samples (Figure S1). Furthermore, the dominant presence of high density (1.2–1.5
g cm–3) synthetic textile fibers in our sediment
samples agrees well with synthetic textile fibers being the most abundant
high-density microplastic in sludge.[34] In
contrast, fragments and films of polyethylene, polyethylene terephthalate
or polyvinyl-chloride were the dominant microplastics found in Lake
Geneva sediments.[62]Microplastic
deposition follows a similar exponential increase in Santa Barbara
basin (doubling time of about 15 years)[63] and Lake Mjøsa sediments (doubling time of ∼12 years; Figure ), and shows significant
correlations with increases in Global plastic production and local
population in both cases[63] (Figure ). These relationships suggest
a tight coupling between microplastic sedimentation and global production
as well as household plastic usage and waste. This coupling is also
highlighted in the microplastic budget for Mjøsa catchment where
microplastics from municipal sewage sludge and from household mismanaged
waste are the main environmental releases. However, the proportions
of terrestrial microplastics being transported downstream or buried
in freshwater sediments may differ from one catchment to another.
Indeed, Lake Geneva was argued to represent a considerable sink for
terrestrial microplastics,[3] whereas Lake
Mjøsa primarily acts as a transporter of microplastics which
potentially reach the ocean (Figure ). As discussed above, the microplastic emission pathways
differ among both, Geneva and Mjøsa, catchments resulting in
contrasted microplastic sedimentation processes. Hence, the proportion
of terrestrial microplastics being trapped in freshwater sediments
seems to be partly controlled by the nature of the local microplastics,
and by extension, by their origin.
Authors: Jenna R Jambeck; Roland Geyer; Chris Wilcox; Theodore R Siegler; Miriam Perryman; Anthony Andrady; Ramani Narayan; Kara Lavender Law Journal: Science Date: 2015-02-13 Impact factor: 47.728
Authors: K M Unice; M P Weeber; M M Abramson; R C D Reid; J A G van Gils; A A Markus; A D Vethaak; J M Panko Journal: Sci Total Environ Date: 2018-07-27 Impact factor: 7.963
Authors: Lei Su; Simon M Sharp; Vincent J Pettigrove; Nicholas J Craig; Bingxu Nan; Fangni Du; Huahong Shi Journal: Water Res Date: 2019-09-30 Impact factor: 11.236
Authors: Marcus Eriksen; Laurent C M Lebreton; Henry S Carson; Martin Thiel; Charles J Moore; Jose C Borerro; Francois Galgani; Peter G Ryan; Julia Reisser Journal: PLoS One Date: 2014-12-10 Impact factor: 3.240