a multimedia activity model for ionizable compounds: validation study with 2,4-dichlorophenoxyacetic...
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Environmental Toxicology and Chemistry, Vol. 29, No. 4, pp. 789–799, 2010# 2009 SETAC
Printed in the USADOI: 10.1002/etc.115
A MULTIMEDIA ACTIVITY MODEL FOR IONIZABLE COMPOUNDS: VALIDATION STUDY
WITH 2,4-DICHLOROPHENOXYACETIC ACID, ANILINE, AND TRIMETHOPRIMANTONIO FRANCO* and STEFAN TRAPP
Department of Environmental Engineering, Technical University of Denmark, Miljoevej, Building 113, DK-2800 Kgs. Lyngby, Denmark
(Submitted 9 June 2009; Returned for Revision 11 August 2009; Accepted 4 November 2009)
All* To
(anf@ePub
(www.
Abstract—Fugacity models are widely adopted for the environmental exposure assessment of organic chemicals but are inconvenientfor nonvolatile substances, such as ionizable chemicals. The activity approach is a robust alternative to the fugacity concept and providesthe thermodynamically exact equations to describe the behavior of neutral and ionizable molecules in nonideal systems. A multimediaactivity model applicable to neutral and ionizable molecules (MAMI) was developed and tested for 2,4-dichlorophenoxyacetic acid andthe bases aniline and trimethoprim. The model features pH and ionic strength dependence and species-specific estimations of partitioncoefficients from physicochemical properties. Sorption estimates consider both lipophilic and electrical interactions. A realistic regionalexposure scenario was simulated for the three test compounds, and model results were compared with results obtained with aconventional fugacity model and with monitoring data. The better performance of MAMI indicates that the activity approach can enlargethe applicability domain and improve model predictions of existing regional models. Model results, supported by experimental evidence,showed the importance of dissociation, electrical interactions in solids, humidity in air, and to a lesser extent salinity in seawater todescribe the environmental fate of ionizable organic chemicals. Environ. Toxicol. Chem. 2010;29:789–799. # 2009 SETAC
Keywords—Chemical activity Ionizable chemicals pH Simplebox Multimedia models
INTRODUCTION
Multimedia models have been applied to assess the environ-
mental exposure of organic chemicals since the fugacity
approach was introduced thirty years ago [1]. Fugacity models
are now widely adopted for chemical risk assessment but are
based on algorithms and exposure pathways that were devel-
oped for neutral lipophilic chemicals and are not applicable to
ionizable chemicals. The fugacity approach is problematic in
particular for strong electrolytes, because fugacity refers to the
partial pressure in air, which cannot be established for charged
molecules.
Many pesticides, most pharmaceuticals, and industrial
chemicals ionize under environmental conditions. From among
a randomly selected sample of the 143,000 preregistered
REACH chemicals, we calculated, using ACD/Labs1 (ACD/
I-Lab, ver 6.01; Advanced Chemistry Development), that 33%
is mostly ionized at pH 7, i.e., has a pKa <7 (acids) or >7
(bases). Adjustments to the fugacity approach have recently
been proposed to enlarge the applicability domain to multi-
species chemicals, including ionics. Diamond et al. [2] defined
an aqueous equivalent formulation, named the aquivalenceapproach, to adapt the fugacity approach to multispecies sub-
stances, including species that do not partition appreciably to
air. The aquivalence approach was applied on surface aquatic
systems to model the fate of mercury and its species [3]. Toose
and Mackay [4] proposed a simpler multiplier method for
modeling chemicals with constant ratios of species concentra-
Supplemental Data may be found in the online version of this article.whom correspondence may be addressed
nv.dtu.dk).lished online 31 December 2009 in Wiley InterScienceinterscience.wiley.com).
789
tion. The method was applied on a multimedia model for Hg. In
the field of organic pollutants, Cahill et al. [5] adapted a fugacity
model to predict the fate of speciating chemicals with up to four
interconverting species. The model assumes constant pH in the
environment. It requires species interconvertion rates and
experimental species-specific partition coefficients measured
at pH sufficiently below and above their dissociation constant
(pKa). In air, only the neutral species is modeled, because
fugacity cannot be established for charged molecules. Ionic
reactions are faster than other environmental processes, so
sufficiently fast interconversion rates can be assumed. The mass
balance is then solved by numerical integration. The species-
specific description of partitioning improved model predictions
for lipophilic organic acids, such as pentachlorophenol [5].
However, species proportions in different compartments may
differ significantly, because the environmental pH ranges from
2 (aerosol) to 8 (seawater). In addition, species-specific data
may be unavailable or experimentally problematic, particularly
for strong electrolytes [6] (see also www.echa.eu). Finally, the
assumption that no ions are present in the atmosphere is
questionable: experimental analysis of aerosol samples showed
that sorption of ionic species into atmospheric particles at
typical environmental humidity contributes considerably to
the aerosol–air partition coefficient of ionizable chemicals
[7]. Recently, a multispecies, pH-dependent, multimedia fugac-
ity model was applied to perfluorooctanoic acid [8]. The model
features species-specific description of partitioning and expo-
sure pathways (e.g., volatilization only for neutral species).
However, it does not present a universally valid concept for
handling ionics, and, as with all fugacity models, it is not
applicable to pure ions.
In 1979, Mackay observed that chemical activity is prefer-
able to fugacity as a model variable for nonvolatile chemicals
790 Environ. Toxicol. Chem. 29, 2010 A. Franco and S. Trapp
[1]. Activity drives diffusion and correctly describes thermo-
dynamic equilibrium of charged and uncharged species in ideal
and nonideal solutions. The activity approach in multimedia
modeling has been successfully applied to plant uptake [9]
and bioaccumulation [10] models. A concise set of equations
based on the activity approach and describing transport
and partitioning of environmental chemicals in all relevant
compartments was recently suggested for use in multimedia
environmental transport models (S. Trapp et al., unpublished
data). The new approach was illustratively applied to
calculate the equilibrium distribution of monovalent drugs in
a lake system, but no attempt was made to verify or validate the
outcome.
Here, a dynamic multimedia activity model for ionics
(MAMI), applicable to neutral mono- and bivalent acids and
bases, amphoters, and zwitterions, was developed and tested for
the pesticide 2,4-dichlorophenoxyacetic acid (2,4-D), the aro-
matic amine aniline, and the antibiotic trimethoprim (TMP). A
realistic regional exposure scenario was simulated for each of
the three test chemicals. The chemical activity in water is the
reference state, and activities in all other compartments are
related to this. Species-specific partitioning is estimated from
physicochemical properties. The new activity model features
environmental pH and ionic strength dependence to predict
dissociation and the effect of variable acidity and salinity. A
dual-phase sorption model, considering air humidity, describes
partitioning into wet aerosols and into cloud water. Results were
compared with results of a conventional model and with
monitoring data collected from the literature.
MATERIALS AND METHODS
The activity approach
The concept of chemical activity was first introduced to
adjust thermodynamic equations for nonideal systems [11]. The
chemical activity is related to the chemical potential, m, which
quantifies the energetic state of a substance, referred to a
‘‘reference state,’’ m0 (J/mol)
m ¼ m0 þ RT lnðaÞ (1)
where R is the universal gas constant (8.314 J mol�1 K�1) and Tthe absolute temperature (K). For solutes, the activity is related to
the aqueous concentration (mol/m3) normalized to a reference
state
a ¼ gCW
CW;ref
or (2)
a CW;ref ¼ gCW (3)
where the coefficientg (adimensional) accounts for the deviation
from the ideal solution (i.e., pure water). The standard state,
CW,ref, can be selected at will, and it is convenient to chose an
ideal unimolar solution (1 mol/m3) for solutes. Thus, CW,ref is
unity for all species and can be incorporated in a for practical
purposes, so that
a ¼ gCW (4)
where a is activity in the unit mol/m3. For a monovalent ionizable
molecule, the activities of the neutral molecule (an) and of the ion
(ai) are the fractions fnW and fiW of the total activity in water
(at¼ an þ ai) and depend on the pH and on the dissociation
constant (pKa), according to the Hendersson–Hasselbalch
equation:
an ¼ at � fnW ¼ at
1 þ 10aðpH�pKaÞ
ai ¼ at � fiW ¼ at � an
(5)
where a is 1 for acids and �1 for bases. Although the degree of
dissociation slightly increases with ionic strength [6], this effect
is neglected in the model. From Equations 4 and 5, the total
concentration Ct of an ionizable molecule in water is
Ct ¼ Cn þX
i
Ci ¼an
gn
þX
i
ai
g i
¼ at
fnW
gn
þX
j
fiW
g i
!(6)
where gn and gi are the activity coefficients of the neutral and
ionic species, respectively. The activity coefficients depend on
the ionic strength of the media and on the valency (Supplemental
Data, Eqns. S7 and S8). No ions are present in the gas phase, and
concentration (of the neutral species) and chemical activity are
equal. The nondimensional Henry’s Law constant (KAW) is the
ratio of activities in pure water and gas. The KAW is often
confused with the concentration ratio, which is correct only
under ideal conditions. The same activity coefficient applied to
the fractions of species dissolved in water is applied in Equation 6
to the fractions sorbed to solids. This formulation does not take
account of the influence of ionic strength on the surface
chemistry of the solid matrix. In a mixed-phase compartment
with gaseous, aqueous, and solid phases, the concentrations in
each phase at equilibrium can be calculated from the activity in
water, using the activity coefficients and the partition coefficients
KAW (air–water) and Kd (solid–water) for each species. The total
concentration Ct of a substance in a mixed-phase compartment is
Ct ¼ at G � fnW � KAW;n þ WfnW
gn
þX
i
fiW
g i
!"
þ SfnS � Kd;n
gn
þX
i
fiS � Kd;i
g i
!# (7)
where G, W, and S are the volumetric fractions of gas, water, and
solids. The neutral and ionic fractions (fnW and fiW) are
calculated from the water-phase pH of the compartment. For
solids, fnS and fiS are the species fractions in water close to the
solid–water interface, where the local pH may differ from the
bulk pH of the medium. Generally, the total activity, at, is
proportional to the total concentration by the bulk apparent
activity capacity (B) of the compartment, defined by
Ct ¼ at � B (8)
The activity capacity defined by Equation 8 is called ‘‘bulk’’
because it refers to a generic multiphase compartment. It is
called ‘‘apparent’’ because it includes the contribution of all
species. The contribution of the neutral molecule to the B value,
Bn, includes the terms multiplied by fn in Equation 7; the
contributions of the ionic species, Bi, include the terms
multiplied by fi. The approach is similar to the traditional
fugacity approach. Analogously to the fugacity capacity Z(mol m�3 Pa�1) [1], the activity capacity B (m3/m3) quantifies
the capacity of a phase or compartment to absorb a compound.
Multimedia activity model for ionization chemicals Environ. Toxicol. Chem. 29, 2010 791
Model environment
The model consists of eight compartments (air, natural
soil, agricultural soil, other soil, freshwater and freshwater
sediments, and seawater and marine sediments), with a total
area of A1¼ 4.40 � 1010 m2 (Supplemental Data, Table S1). The
two marine compartments can be added or removed faculta-
tively. The dimensions and the phase compositions of each
compartment were taken from the regional environment, which
is described in the European Union (EU) technical guidance
document for risk assessment of chemicals [6] and implemented
in the EU model for environmental exposure assessment,
Simplebox [12]. Additionally, the following environmental
parameters were introduced in MAMI (see Supplemental Data,
Table S1, and accompanying text for references): the aerosol
content in air was defined as 2� 10�11 m3/m3 with an organic
carbon content ( fOC) of 0.1 g/g; humidity was introduced as
aqueous phase associated with the aerosol particles (aerosol
moisture) and as cloud water (cloud condensation nuclei).
The volumetric fraction of water associated with aerosol was
set equal to the volumetric fraction of solids in air
(2� 10�11 m3/m3) and is much smaller than the fraction of
cloud water in atmosphere estimated for average European
conditions (3� 10�7 m3/m3). The details on the derivation of
these parameters with relative references are reported in the
Supplemental Data. All compartments now include a water
phase, to which pH and ionic strength (I) refer. Typical values
were chosen within their environmental range. The pH of
cloud and rain water is 5.6, but it is lower in aerosol particles
(pH 0–4.5), depending largely on humidity [7]. The pH of
aerosol was set to 3 as a compromise. The pH of natural soil is 5,
representing the typical acidity of a forested soil. In agricultural
soil, other soil, freshwater, and freshwater sediments, the pH
is 7; in seawater and marine sediment, the pH is 8. The ionic
strength is 2 � 10�4 mol/L in rain water, 0.03 mol/L in soil pore
water, 0.003 mol/L in the freshwater system, and 0.5 mol/L in
the marine compartments.
Partition coefficients
All phase partition coefficients of neutral and charged
molecules are estimated in MAMI from the pKa, the logKOW,n,
and the KAW,n (Supplemental Data, Part I). Ions are nonvolatile
(KAW,ion¼ 0); their lipophilicity is by default 3.5 log-units
lower than the logKOW,n [13], and their charge and degree of
dissociation are determined by the valency and the pKa.
Partitioning of the charged species from the water phase can
thus be calculated from the above-mentioned properties. The
solid–water partition coefficient normalized to organic carbon,
KOC, is used to calculate partitioning to soil, sediments, and
suspended particles in water. Species-specific KOC values are
estimated from the pH, the pKa, and the log KOW,n, using the
regressions recently developed for monovalent acids, bases, and
amphoters [14]. The optimal pH (pHOPT) for modeling sorption
to solids, which resulted from the calibration of the above-
mentioned regressions, was found to be lower than the bulk pH.
The parameter pHOPT may be interpreted as the local pH
experienced by ionizable compounds at the soild–water surface.
Based on the pH-dependent fit of the KOC regressions of Franco
and Trapp [14], the KOC of organic acids for soils and sediments
in MAMI is estimated at a corrected soil pH (pHOPT¼ pHSOIL �
0.6) [15]. The same approach was not successful for bases [15],
for which a fixed pHOPT is applied (pHOPT¼ 4.5) [14].
Compared with Simplebox, the air compartment was modi-
fied to consider the effect of humidity on the atmospheric
partitioning and equilibrium. A dual-phase aerosol–air sorption
model was implemented in MAMI, similar to the one suggested
by Arp et al. [7]. Humidity in air is considered as aqueous phase
associated with aerosol. From this aqueous phase, partitioning
equilibria are calculated. Neutral molecules volatilize and
partition from the gas phase into the organic matter of dry
aerosol. Ions in wet aerosol partition from the aqueous
phase into the solid organic matter (Supplemental Data, Fig. S2).
The KAW,n is calculated from vapor pressure and solubility
of the neutral molecule. The partitioning of the neutral molecule
between gas and aerosol particles (KP,n, in m3air/m
3aerosol) is
estimated from the octanol–air partition coefficient (KOA) using
the equation derived from Harner and Bidleman [16], corrected
as recommended by Gotz et al. [17].
KP;n ¼ 0:54 � KOA � fOC � rsol (9)
The partition coefficient of the neutral species between
solids and water in aerosols, Kd,n, in air is then the product
of KAW,n and KP,n. Ions in air are dissolved in the aqueous phase
of wet aerosol and partition directly into the organic matter of
aerosol according to the solid–water partition coefficient (Kd,j)
estimated by the KOC regressions for ionics [14,15]. Aerosol
moisture follows the physical fate of the aerosol, whereas cloud
water undergoes advection and wet deposition but not dry
deposition.
Intermedia transport and removal processes
The equations describing the mass balance of the chemical in
the system were written and solved using the total activity as
state variable. In the same way as the D values were defined in
the fugacity approach (in mol Pa�1 h�1), T values were defined
(m3/h) in the activity approach to describe intermedia and
removal fluxes (mol/h).
dm
dt¼ atT (10)
The same intermedia fluxes and removal processes as in
Simplebox are included in MAMI. The parameters describing
mass exchange, listed in Supplemental Data, Table S4 (diffu-
sion) and Table S3 (advection), stick to the EU technical
guidance document [6]. Equations for diffusive transport at
the water–air and at the soil–air interface were modified,
because this pathway only exists for the neutral molecule.
Continuous rainfall is assumed, and both cloud water and
aerosol particles are scavenged by rain droplets. Details of
all equations for the mass fluxes and for the T values are
described in the Supplemental Data.
Degradation was assumed independently from speciation,
because standard degradation tests refer to the total bulk
concentration. The uncertainty associated with the determina-
tion of biodegradation rates in soil and sediments is typically
high because of the variable and often limited bioavailability
of contaminants and other constraints. Rather than the
total concentration, it is the chemical activity of a chemical
(driving the diffusive uptake by degrading organisms) and its
792 Environ. Toxicol. Chem. 29, 2010 A. Franco and S. Trapp
bioaccessibility that govern bioavailability. Activity is therefore
more closely related to biodegradation than the total concen-
tration. It may therefore be advantageous to derive degradation
rates from measurements of activity, although this field is
mostly unexplored [18].
Chemical input data
The herbicide 2,4-D (acid), the aromatic amine aniline, and
the antibacterial agent trimethoprim (bases) were selected for
the validation study because of their widespread use. The
herbicide 2,4-D is one of the most widely used herbicides in
the world. Aniline, the precursor of a number of industrial
chemicals, is a typical industrial pollutant. Trimethoprim is
one of the most frequently used and detected antibiotics in
the environment in the United States as well as in Europe
[19,20]. The selected chemicals represent three different emis-
sion scenarios and exposure pathways; the first is typical for a
pesticide, the second for an industrial intermediate, and the
third for a veterinary and human antibiotic. Finally, they
contain three different ionizing moieties, namely, a carboxylic
group (–COOH), an amine (–NH2), and a pyrimidine (–N–), and
are all partially ionized in the environment.
The physicochemical properties and the degradation rates
for the three test compounds are listed in Table 1. The pKa and
the logKOW,n were calculated with the software ACD/Labs1 or
selected from literature. Degradation rates were taken from the
literature, preferably from simulation tests under environmen-
tally relevant conditions.
Emission scenarios
Realistic emission scenarios were simulated on a regional
scale for each test compound (Table 1). The simple model
scenario without marine compartments was used for 2,4-D and
Table 1. Chemical input properties (calculated with
2,4-D
Physicochemical propertiesMolar mass (g/mol) 221.04pKa 2.98 (acid)logKAW,n �7.62logKOW,n 2.83b
Degradation rates (h�1)kdegr,air 5.38� 10�3c
kdegr soil 5.21� 10�3c
kdegr,water 6.04� 10�4c
kdegr,sed 1.44� 10�3h
Emissions (mol/h)To air 4.04 (months 1–2)To agricultural soil 99.46 (months 1–2)To freshwater
To seawater
a European Chemical Bureau [24]. Aqueous photolysis in water is small and negb Jafvert et al. [13].c Gasser et al. [35]. The degradation rate in water includes aqueous photolysis.d Estimated with the AOPWIN (AOPWINTM, Atmospheric Oxidation Program for M
assuming OH radical concentration of 0.5� 10�5 molecules/cm3.e Boxall et al. [30].a Half-time >100 d, Benotti et al. [37]. Not subject to photolysis.g Hektoen et al. [38].h Chinalia et al. [39].
aniline; seawater and seawater sediments were included for the
simulation of trimethoprim.
The emission scenario for 2,4-D was based on the consump-
tion in the Canadian province of Saskatchewan, 537 t/y [21].
The yearly consumption was normalized to the area of MAMI,
considering that the land use of Saskatchewan is similar to the
European regional model environment. This scenario was
simulated to compare results with the large number of data
from monitoring campaigns ongoing throughout the Canadian
prairies for more than 10 years. The herbicide 2,4-D is typically
applied in May–June and occasionally later in summer. A
one-year period was simulated, assuming constant emission
during the first two months, corresponding to the late spring
season, followed by ten months of nonapplication. The herbi-
cide is typically dissolved in an aqueous solution as iso-octyl or
butoxyethyl ester or as dimethylamine salt and is mostly applied
by ground sprayers [22]. According to the EU guidance docu-
ment for pesticide spray emissions, 4% is released to air by
spray drift and 96% to soil [23].
The regional emission scenario described in the EU risk
assessment report for aniline was simulated [24]. Although
aniline is a degradation product of other, larger amines, only
primary sources were considered. A constant emission (steady
state) to freshwater (36%) and to air (64%) was simulated.
Trimethoprim is used as an antibacterial for pigs, cattle,
poultry, and aquaculture as well as for human therapy.
The exposure of TMP in Denmark was simulated, including
the coastal marine ecosystem. The area of Denmark
(43,098 km2) is comparable to the area of the regional model
environment (40,000 km2). A one-year dynamic simulation was
run, covering four months of intense application via manure to
soil and aquaculture to water and a constant emission to water
throughout the year from human use via wastewater treatment
plants (WWTPs). Sludge and slurry from terrestrial husbandry
ACD/Labs1 unless specified) and emissions
Aniline Trimethoprim
93.13 290.324.61 (base) 7.20 (base)�4.35a �13.17
0.94 0.79
0.21a 0.37d
8.25� 10�5a 7.00� 10�4e
1.92� 10�3a 1.44� 10�4fg
8.25� 10�6a 1.44� 10�4g
25.7 (steady-state)0.405 (months 1–4)
14.7 (steady-state) 0.217 (months 1–4)0.018 (months 5–12)0.193 (months 1–4)0.015 (months 5–12)
lected.
icrosoft Windows, Version 1.92a, U.S. Environmental Protection Agency).
Multimedia activity model for ionization chemicals Environ. Toxicol. Chem. 29, 2010 793
is typically applied to agricultural soil from early spring to May.
Treatments in aquaculture are more frequent in spring and
summer. The yearly emissions from veterinary use were then
assumed to be concentrated in four months to simulate a period
of intense application. The estimated emission from veterinary
use was based on species-specific animal consumption data
from 2006 including husbandry and freshwater and marine
aquaculture [25]. The fraction of chemical excreted unchanged
was assumed to be 60% for fish and 18% for pigs [26].
The emission to agricultural soil from terrestrial husbandry
amounted to 344 kg/year, to freshwater from aquaculture
to 169 kg/year, and to seawater from marine aquaculture to
151 kg/year. No further degradation was assumed (e.g., in
sludge treatment plants) after excretion. The total load into
the aquatic compartments resulting from human consumption
was extrapolated from the load measured at the effluent of
the biggest WWTP in Copenhagen, serving 10% of the total
Danish population. The total emission was input to freshwater
(45 kg/year) and to seawater (38 kg/year), assuming that 46% of
the Danish WWTPs discharge into the sea [27].
Comparison with ther conventional model
A conventional fugacity model [1] based on the regional
scale of Simplebox [12] was implemented for comparison with
MAMI. In the conventional model, only the neutral species is
assumed to be present in air. Compared with Simplebox, the
Junge model was replaced with the KOA-based regression
Equation 9 for the calculation of the aerosol–air partition
coefficient. Thus, the same partition model was implemented
in MAMI and in the conventional model for neutral species in
air to make the approaches comparable. The volumetric fraction
and organic carbon content of aerosol set for MAMI were also
used for the conventional model. All partition coefficients were
then estimated from the physicochemical input properties,
despite the availability of measured values, to compare the
models’ predictive power. Partitioning to solids was calculated
with the KOC regressions derived by Sabljic et al. [28] for
organic acids (2,4-D), anilines (aniline), and nonhydrophobic
compounds (TMP). Chemical-dependent soil depth, which is
implemented in Simplebox, was not included. The two models
consider the same transport processes and were identically
parameterized, but the fugacity model simulated only one
species.
Comparison with monitoring data
Model outputs were compared with monitoring data col-
lected from the literature (Supplemental Data, Tables S6–S11).
More than 450 measurements of 2,4-D from the Canadian
prairie provinces were collected from 29 monitoring stations
in air (height¼ 1 to 30 m) and 24 in freshwater (rivers, drainage
creeks, ponds, wetlands). The stations are located throughout
the region on agricultural, urban, forested, and mixed areas. For
each station, the average concentration over the summer season
(May to September) was taken. Monitoring usually ends in late
summer, when concentrations drop below the detection limit.
Measured seasonal bulk and dry deposition fluxes were also
collected for comparison. Concentrations in soils are rarely
reported [29], and variability in space and time is too dependent
on local emission patterns for a statistically sensible data
treatment.
Yearly average concentrations of aniline were collected
from 10 stations along the Rhine river basin. Detections are
related mostly to upstream production sites, whose emissions
are considered in the simulated emission scenario. The available
measurements of aniline in air stem from urban areas and do not
reflect the regional exposure [24].
Environmental concentrations of TMP were collected from
monitoring studies from Denmark, England, Wales, France, and
Germany. Most monitoring campaigns targeted areas of
expected contamination from husbandry or WWTP effluents.
These data were compared with the model results at the end of
the simulated period of intense application (t¼ 120 d). The
monitoring campaigns typically covered one river catchment.
In total, more than 350 measurements were collected from
27 rivers. Concentrations in sediments, measured in mg/kg
dry solid matter, were converted into g/m3 according to the
sediment properties of Supplemental Data, Table S1.
Whenever possible, we represented the geographical varia-
bility of measured environmental concentrations. For 2,4-D (air
and freshwater) and aniline (freshwater), the median and the 5th
and the 95th percentiles were calculated from time-averaged
concentrations measured at the monitoring stations. For TMP,
the median and the maximum concentrations were first calcu-
lated for each monitoring campaign; next, the median of these
values over the different campaigns was calculated.
RESULTS
Calculation of B values
The bulk apparent activity capacities (B values) of the three
test compounds in each compartment are reported in Supple-
mental Data, Table S5. The apparent bulk B value is the sum of
the contributions of the species-specific B values, also reported
in Supplemental Data, Table S5. Total activities in freshwater
are all close to 1. For comparison, the activity capacity of a
substance dissolved in pure water is B¼ 1 m3/m3.
The anionic form of 2,4-D makes up the larger part of the Bvalues in all compartments, including air, where 2,4-D is mostly
dissolved in cloud water (pH 5.6). The activity capacity in the
natural soil (pH 5) is slightly higher than in the other soil
compartments (pH 7) because of the contribution to sorption of
the neutral molecule at lower pH.
Aniline is a weak base, and the activity capacity in water (pH
7 and 8) and in air is determined by the neutral species. In soils
and sediments, however, the cationic species contributes mostly
to the B values because of the strong sorption to solids of the
protonated molecule.
Trimethoprim tends to sorb to solids, as can be seen from the
high B values for soils and sediments. The cation dominates in
all phases, except seawater, in which pH > pKa. The salinity of
the marine compartments affects the B values via the activity
coefficients (gn is 1.41 and gion is 0.74). The activity capacity of
bulk seawater (B¼ 0.80 m3/m3) is lower than the activity
capacity of an ideal solution (B¼ 1 m3/m3). Conversely, the
activity capacity in sediments increases from 68.8 m3/m3 to
92.9 m3/m3 when ionic strength is taken into account.
Simulation of 2,4-D
Figure 1 shows the concentrations of 2,4-D calculated by
MAMI for the dynamic simulation covering two months of
Fig. 1. Concentrations of 2,4-D calculated by the model MAMI (dynamicsimulation) covering three months of application followed by three months ofnonapplication.
794 Environ. Toxicol. Chem. 29, 2010 A. Franco and S. Trapp
application followed by four months of nonapplication. After
two months (t¼ 60 d) of emission to agricultural soil and to air,
concentrations in the environment reach approximately steady
state. The highest concentration is found in the agricultural
soil (1.93� 10�3 g/m3). In air, a constant concentration of
6.45� 10�11 g/m3 is rapidly reached. At the end of the appli-
cation period (t¼ 60 d), steady-state is almost reached in
freshwater (3.13� 10�5 g/m3). Accumulation in sediments fol-
lows, with delay and peaks at t¼ 72 d with 3.51� 10�5 g/m3.
After the application period, 2,4-D is rapidly removed from air.
The concentration in soil drops below the typical detection limit
in soil (0.2 ng/g, corresponding to 3.2� 10�4 g/m3) 14 d after
the last application, which explains why the herbicide was not
detected in agricultural soils throughout the year [29]. As
Fig. 2. Simulation results for 2,4-D at the end of the application period (t¼ 60 d). ([empty] and anionic fraction [�]) compared with the concentrations calculated by thepercentiles (upper and lower bars) of the monitoring data measured during the agricullinear scale (relative area of bars). (b) Mass fluxes (kg/h) calculated by MAMI and
indicated by the slope of the curves for t > 60 d (Fig. 1),
2,4-D is removed at slower rates from freshwater and sediments.
Figure 2 shows the predicted species-specific concentrations
and the mass fluxes calculated by MAMI at the end of the
application period (t¼ 60 d), compared with the results
obtained with the conventional model and with the monitoring
data. The concentrations predicted by MAMI and by the con-
ventional model are almost identical for agricultural soil,
similar in freshwater and sediments, but significantly different
for air, natural soil, and other soil (Fig. 2a). The predicted
concentration in air is 6.45� 10�11 g/m3 with MAMI. The
results obtained with MAMI agree with the median concen-
trations measured in air (1.34� 10�10 g/m3) and in freshwater
(4.50� 10�5 g/m3). The conventional model gives similar esti-
mates for freshwater. In contrast, it underestimates the concen-
tration in air (2.48� 10�12 g/m3) by almost 2 orders of
magnitude compared with the median measured concentration
and falls outside the lower 5th percentile of all observations
(1� 10�11 g/m3; Supplemental Data, Table S6). For the natural
soil and the other soil, MAMI predicts lower concentrations
than the conventional model. The anionic species is dominant in
all compartments: fion >0.99 in air, agricultural soil, other soil,
freshwater, and sediments; fion¼ 0.85 in natural soil (Fig. 2a).
Figure 2b shows the calculated mass fluxes at t¼ 60 d.
Whereas MAMI predicts that 17% of the emission to air leaves
the compartment by advection, the conventional model predicts
that 2,4-D is immediately washed out by wet deposition. The
fate of 2,4-D in agricultural soil is similar with the two models.
The pesticide is rapidly biodegraded, and only a small amount
leaches to groundwater and freshwater, while soil erosion is
negligible. In freshwater, degradation is slower, and 2,4-D is
removed mostly by advection.
The predicted annual bulk deposition on the soils,
2.65� 10�5 g m�2 y�1 (3.23� 10�5 g m�2 y�1 with the
a) Concentrations (g/m3) calculated by the model MAMI (white bars; neutralconventional model (gray bars) and with the median (lozenges), 5th and 95th
tural season. Concentrations in log scale (left y axis); fractions neutral–ionic inby the conventional model (in parenthesis). Fluxes <10�4 kg/h not shown.
Fig. 3. Simulation results for aniline (steady-state simulation). (a) Concentrations (g/m3) calculated by the model MAMI (open bars, neutral [empty fill] andcationic fraction [þ]) compared with the concentrations calculated by the conventional model (gray bars) and with the median (lozenges), 5th and 95th percentiles(upper and lower bars) of the monitoring data. Concentrations in log scale (left y axis); fractions neutral–ionic in linear scale (relative area of bars). (b) Mass fluxes(kg/h) calculated by MAMI and by the conventional model (in parenthesis). Fluxes < 10�4 kg/h not shown.
Multimedia activity model for ionization chemicals Environ. Toxicol. Chem. 29, 2010 795
conventional model), is smaller but still close to the median
annual bulk deposition (10.3� 10�5 g m�2 y�1) measured over
the Canadian prairies (Supplemental Data, Table S8). The
geographic variability of measured deposition fluxes is rela-
tively small, indicating extensive mixing in the atmosphere
before deposition. The contribution of each deposition process
in order of importance, indicated by the T values, is rain
dissolution > rain scavenging > diffusion > dry deposition.
Rain dissolution accounts for >99% of the total T value for
deposition, according to both models. Some field observations
reported contributions of dry deposition to the total deposition
of about 19% (Supplemental Data, Table S8).
Simulation of aniline
Figure 3 shows the predicted species-specific concentration
and the mass fluxes calculated by MAMI compared with
the results obtained with the conventional model and with
the monitoring data. The predicted concentration in air
(�2.3� 10�10 g/m3) is similar for both models. The predicted
concentrations in water are also almost identical (�1.2�10�4 g/m3) and very close to the median of concentrations
measured in river water samples collected from the lower Rhine
catchment (1� 10�4 g/m3; Fig. 3a). The model MAMI predicts
higher concentrations than the conventional model in all soils
and in sediments. The neutral species dominates in freshwater
and in air, where it is present mostly in the free gaseous phase
(fn > 0.99). Although the pKa (4.61) is below the pH of soils
and sediments (pH 5–8), the protonated form dominates the
overall mass because it sorbs more strongly than the neutral
species. The contribution of the cation to the total concentration
is 85% in soils and 77% in sediments.
Most of the emission to air is removed by advection and
degradation; the remaining (<0.02 kg/h) is deposited to the
ground (Fig. 3b). In MAMI, approximately 1% of the total
concentration of aniline in air is associated with cloud water,
whereas, with the conventional model, aniline is present only in
the neutral (more volatile) form, and the fraction associated
with particles is negligible (<0.0001%). The impact of this
difference on the predicted fate of aniline in air is negligible.
The two models predict a similar fate also in freshwater, in
which degradation and advection are the main removal proc-
esses. According to MAMI, aniline is only moderately mobile
and slowly degraded in soils. A moderate accumulation in
sediment is expected because of the significant contribution
of the cation to sorption. The conventional model predicts
higher mobility in soils and sediments, based on the hydro-
philicity of the compound. The highest T value for removal
from soil is for leaching. Accordingly, aniline would be trans-
ported to ground- and freshwater and would not accumulate in
sediments.
Simulation of trimethoprim
Figure 4 shows the concentrations of TMP calculated by
MAMI for the 12-month dynamic simulation. The simulation
covers four months of intense emission (veterinary and human
use) and a constant background emission (human use only). At
the start of the simulation, TMP is emitted from veterinary use
to agricultural soil, freshwater, and seawater. Trimethoprim
does not volatilize and therefore neither comes into the air
compartment nor comes into the other soils. At the end of the
period of intense application (t¼ 120 d), the concentration of
TMP peaks in agricultural soil and in freshwater (Fig. 4).
Trimethoprim reaches the highest concentration in freshwater
sediments, with a peak of 2.78� 10�4 g/m (278 ng/L) at t¼ 147 d.
The peak concentration in seawater, reached at t¼ 120 d, is
2.23� 10�6 g/m3. In the marine sediments, TMP reaches the
peak concentration of 4.99� 10�6 g/m3 at t¼ 175 d. From
t> 120 d, TMP decays exponentially in soil. In freshwater
and seawater, concentrations decrease to the constant level
resulting from human use. At the end of the simulation
Fig. 4. Concentrations of trimethoprim calculated by the model MAMI(dynamic simulation) covering 4 months (t¼ 0 to 120 d) of intense emission(husbandry and human use) followed by eight months of low emission(human use only; t> 120 d).
796 Environ. Toxicol. Chem. 29, 2010 A. Franco and S. Trapp
(t¼ 365 d), concentrations in freshwater sediments and in
marine sediments are still approximately 40 and 60% of the
respective peaks.
Figure 5 shows the predicted species-specific concentrations
and the mass fluxes calculated by MAMI at t¼ 120 d, compared
with the results obtained with the conventional model and with
Fig. 5. Simulation results for trimethoprim at the end of the period of intense emiss(open bars, neutral [empty fill] and cationic fraction [þ]) compared with the concentdata. The median of measured concentrations (lozenges) and the median of the masediments, the median of detections is reported (lozenges, detection frequency 27%quantification (5� 10�4 g/m3). Measured concentrations in sediments (g/kg, dry wSupplemental Data, Table S1. Concentrations in log scale (left y axis); fractions neutwith MAMI and the conventional model (in parenthesis). Fluxes < 0.01 g/h not sh
the monitoring data. In agricultural soil, the predicted concen-
tration at t¼ 120 d (Fig. 5a) is a little bit higher with
MAMI (6.73� 10�5 g/m3) than with the conventional model
(5.61� 10�5 g/m3). Consequently, the concentration in fresh-
water is lower with MAMI (1.33� 10�5 g/m3 vs. 1.66� 10�5 g/
m3). The predicted concentrations in freshwater is well
within the observed range, though higher than the median
(0.6� 10�5 g/m3). The difference between the two models is
most evident for sediments. The concentration in freshwater
sediment predicted with MAMI (2.55� 10�4 g/m3) is 10 times
higher than that calculated with the conventional model
(2.20� 10�5 g/m3). The monitoring data collected for fresh-
water sediments (detection frequency 27%, median of detec-
tions 6.1� 10�4 g/m3) suggest that MAMI correctly estimates
the water–sediment distribution, whereas the conventional
model seems to underestimate the concentration in sediments.
The cationic species, bound to solids, dominates in soil and
in sediments (>99%; Fig. 5a). In freshwater, both the neutral
(37%) and the cationic (63%) species are present. The neutral
species is most abundant in seawater (86%), where the pH (8) is
above the pKa of 7.20.
Figure 5b shows the mass fluxes calculated at t¼ 120 d.
According to MAMI, only 0.17 g/h of TMP is transported from
soil to freshwater. The loss from leaching is much smaller than
the loss by degradation. Emissions to soil are therefore not a
likely source for TMP in the freshwater ecosystem. In contrast,
20% of the TMP emission into soil is released, according to the
conventional model, partially to groundwater (12 g/h) and
partially to freshwater (12 g/h) by surface runoff, whereas soil
erosion is negligible. The difference between the two models
ion (t¼ 120 days). (a) Concentrations (g/m3) calculated by the model MAMIrations calculated by the conventional model (gray bars) and with monitoringximum measured concentrations (upper bar) are shown for freshwater. For). The lower variation bar is interrupted below at the typical reported limit oft) were converted to g m�3 (bulk volume) using the properties reported in
ral–ionic in linear scale (relative area of bars). (b) Mass fluxes (g/h) calculatedown.
Multimedia activity model for ionization chemicals Environ. Toxicol. Chem. 29, 2010 797
arises from the T values for leaching, which are much higher
with the conventional model, although the T values for degra-
dation are almost identical. Degradation in freshwater is slow,
and TMP is mostly transported to seawater. The direct emission
into seawater (56 g/h from marine aquaculture and WWTPs) is
comparable to the total load from freshwater (50 g/h). In sea-
water, the concentration decreases mainly as a result of dilution.
The second major difference between the two models (Fig. 5b)
is the predicted net mass exchange between water and sedi-
ments. Accumulation in sediments is still ongoing at t¼ 120 d
with MAMI (4.6 g/h from freshwater) and would last for three to
four months more, under constant intense emissions, until 0 net
exchange is reached at a peak concentration about twice as high
as that shown in Figure 4. In contrast, the conventional model is
faster at steady state, as indicated by the net sedimentation flux
of only 0.3 g/h at t¼ 120 d (Fig. 5b). The same discrepancy,
though less remarkable, can be observed for the marine eco-
system.
DISCUSSION
Differences between MAMI and the conventional model
The results of the activity model MAMI differ from the
results of the conventional fugacity model in several cases
(Figs. 2, 3, and 5). The largest disagreements in the predicted
concentrations were found for air (2,4-D) and soils and sedi-
ments (aniline and TMP). The concentration in air calculated
with MAMI is much higher for 2,4-D. This is due to the effect of
humidity in air, which is not considered in the conventional
model.
The predicted concentrations in soil and sediment of aniline
and TMP are higher with MAMI, mainly because of the differ-
ent estimations of solid–water partitioning normalized to
organic carbon (KOC). In the conventional model, sorption is
based on a single KOC value estimated from the KOW; in MAMI,
it is based on species-specific and pH-dependent KOC estima-
tions. The distribution of TMP between marine seawater and
sediments is also influenced by salinity, which is not considered
in the conventional model. The three elements of MAMI that
appreciably affect the output, compared with a conventional
model, are the species-specific and pH-dependent description of
partitioning and the effects of humidity in air and of salinity in
the marine compartments.
Effect of pH and pKa on partitioning of 2,4-D, aniline,and trimethoprim
The pKa and the pH determine the fractions of neutral and
ionic species in the water phase of each compartment. Ions are
nonvolatile, but neutral species may be. Anions are generally
more mobile in solids than their corresponding neutral mole-
cule, whereas cations are generally less mobile [14]. The
variability of environmental pH and the different partitioning
properties of neutral and ionic species resulted in extremely
variable species concentration ratios across MAMI compart-
ments. The acid 2,4-D is mostly ionized, the neutral species
being present only in natural soil (Fig. 2a). Neither species is
volatile, and in air both are dissolved in the aqueous phase. In
natural soil (pH 5), the presence of the neutral molecule slightly
decreases mobility. This trend was experimentally observed for
2,4-D at pH < 5 [15]. Species concentration ratios vary, in
particular for substances with a pKa within the typical
environmental pH, such as aniline and TMP. Aniline
(Fig. 3a) is almost completely neutral in water and in air. In
soil and sediments, it is mostly bound to solids as cation
(apparent KOC¼ 309 L/kg). Aniline is known to adsorb electri-
cally (cation exchange) to the negatively charged colloids of
soils and sediments [24]. It was already noted that the KOW
regression, suggested by Sabljic et al. [28] for anilines, under-
estimates sorption of aniline [24]. Therefore, the conventional
model (KOC ¼ 26 L/kg) underestimates concentrations in the
solid phases. Species concentration ratios of TMP vary even
more sharply across compartments (Fig. 5a). Based on a
calculated apparent KOC of 2,692 L/kg, MAMI predicts very
low mobility in soil. Based on the regression for nonhydro-
phobic chemicals implemented in the EU technical guidance
document (KOC¼ 27 L/kg), the conventional model predicts
high mobility. The values reported by Boxall et al. [30]
(KOC¼ 1,680–3,990 L/kg) are in line with the estimates of
MAMI. Predicted fluxes are consistent with the results of a
target monitoring campaign carried out in Danish rivers [20]. In
the study of Mogensen et al. [20], TMP was monitored in rivers
downstream of aquacultures, downstream of WWTPs, and in
rivers where potential TMP contamination was foreseeable
from intense application of pig slurry to surrounding fields.
Trimethoprim was detected downstream of aquacultures, even
at high concentrations, and downstream of WWTPs. In contrast,
it was never detected in rivers sensitive to pig slurry contam-
ination, although samples were collected after rain events.
These observations agree with MAMI predicting negligible
surface runoff of TMP.
Effect of air humidity on the fate of 2,4-D and aniline
In the conventional model, as in other traditional models
[1,12], although adapted to ionizable compounds [5], no ions
are present in air because of their negligible vapor pressure. The
fugacity capacity of air for nonvolatile molecules is much lower
compared with the capacity of solid particles or water droplets
[1], so rain-out is very efficient. The level of humidity typical of
temperate climate zones, as considered in MAMI, considerably
increases the activity capacity of hydrophilic molecules in air
(Supplemental Data, Table S5). Thus, advection is a relevant
removal process for 2,4-D in air, according to MAMI (Fig. 2b).
In agreement with this result, it was observed that 2,4-D can
undergo mid- to long-range transport in the atmosphere [22,31].
Significant levels of 2,4-D were detected in air (Supplemental
Data, Table S6) and in rain-water samples collected in areas
where 2,4-D was not applied, including a natural reserve up
to 50 km away from the closest arable land [21,31,32].
Donald et al. [31] reported no statistical difference between
wetland water samples collected in areas where 2,4-D was
applied and samples collected in areas with no pesticide appli-
cation. The authors proposed that 2,4-D drifted to air may be
entrained in local convective clouds and evenly redistributed by
rainfall over the region. Yao et al. [29] claimed that the higher
variability in measured gas–particle distribution of acidic pes-
ticides, including 2,4-D, compared with neutral pesticides,
possibly was due to variable atmospheric humidity.
The predicted effect of humidity on the concentration of
aniline in air is less significant. In the conventional model,
aniline emitted to air is neutral, and the fraction associated with
798 Environ. Toxicol. Chem. 29, 2010 A. Franco and S. Trapp
aerosol particles is only 0.00004%. In MAMI, approximately
1% is dissolved in cloud water (pH 5.6) but this does not
impact significantly the predicted air concentration. This
scenario, however, is very sensitive to changes of humidity
and pH. The fraction of aniline associated with aerosol
particles increases at higher humidity and lower pH. Arp
et al. [7] measured the gas–particle equilibrium partitioning
of aniline and other ionizable compounds at different
humidity (50–90% relative humidity) in urban and rural
areas. The authors concluded that sorption of ionizable
compounds is substantially influenced by humidity at RH >50%. In the sorption model proposed by the same authors, the
apparent (non-species-specific) partition coefficient between
the water-insoluble fraction of aerosol and air is estimated
by using a polyparameter linear-free energy relationship
based on Abraham descriptors. Additionally, ions’ dissolution
into the aqueous phase of aerosol is calculated [7]. Compared
with this model, the one implemented in MAMI is strictly
species-specific and does not require additional parameters, but
it may overlook H-bond interactions of neutral hydrophilic
species. A particle–air sorption model based only on lipophi-
licity, such as the one implemented in the conventional model,
overlooks sorption of hydrophilic, nonvolatile chemicals into
the aqueous phase of cloud water and aerosol.
It was recently argued that assumptions of dry air and
continuous rain may cause a severe overestimation of wet
deposition and an underestimation of the concentration in air
and of travel distances for very hydrophilic chemicals [33]. The
inclusion of cloud water in air limits the drawbacks of the
assumption of continuous rain, as illustrated by the simulated
fate of 2,4-D.
Effect of ionic strength on the fate of trimethoprim in themarine ecosystem
Typical levels of ionic strength in the marine ecosystem
decrease the capacity of seawater to absorb neutral molecules
(salting out) but increase the capacity to absorb ions (salting in).
The magnitude of salting out and salting in is described
by the activity coefficients, gn and gi (Eqn. 7). For TMP,
the overall effect on partitioning can be seen from the distri-
bution coefficient between seawater and marine sediments,
expressed by the ratio of bulk activity capacities. With MAMI
(I¼ 0.5 mol/L), this ratio is 116 m3/m3; by setting I¼ 0, the
same ratio is lower (69 m3/m3). The overall effect of ionic
strength is thus to increase accumulation of TMP in sediments.
An increase by a factor of 1.55 was calculated at t¼ 120 d
compared with the result obtained assuming ideal conditions.
This factor combines the effect of salting out of uncharged
molecules and salting in of ions and is a little higher than the
factor typically observed for neutral compounds [34].
MAMI: Applicability and limitations
The activity approach is analogous, in its mathematical
formulation, to the well-known fugacity approach. The fugacity
approach refers to the gas phase, whereas the activity approach
refers to the ideal aqueous phase. The applicability domains of
the two models complement each other: fugacity is preferable
for volatile chemicals; activity is preferable for nonvolatile and
ionizable chemicals. The activity approach might also be con-
venient for the exposure assessment of a parent compound and
its degradation products, because all metabolic pathways com-
prise ionizable intermediates [35].
The activity approach enables us to describe the behavior of
chemicals in nonideal solutions. However, as the activity refers
to chemical species in the water phase, the model only considers
the effect of ionic strength in the aqueous phase. The same
activity coefficient calculated for water is assumed for solids in
a given compartment. This means that the feedback effects of
dissolved ions on the lipophilicity and on the electrical proper-
ties of a solid surface are not considered in the present for-
mulation. Examples of such effects are the salting out of the
organic matter in suspended particles and sediments or the
neutralization of negative binding sites by seawater cations
[36]. In addition, interactions of ionic species with other water
solutes are not considered in MAMI. Ionizable chemicals can be
emitted as salts or can form complexes in the environment.
Complexes may modify speciation and partitioning equilibria in
water.
CONCLUSIONS
The performance of the MAMI model tested on realistic
regional exposure scenarios for 2,4-D, aniline, and TMP were
satisfying and superior to a conventional fugacity model. Model
results showed that air humidity, in the form of cloud water, can
absorb and transport nonvolatile chemicals in the atmosphere,
which explains the ubiquitous occurrence in the environment
of organic electrolytes, such as 2,4-D, on a regional scale.
Humidity is therefore a key parameter in correctly describing
the fate of polar and ionizable chemicals in air. Environmental
partitioning of ionizable chemicals is best described by a
species-specific sorption model that considers both lipophilic
and electrical interactions. The effect of salinity is negligible in
the terrestrial ecosystem but has an impact in the marine
compartments, where neutral species are salted out and ions
are salted in.
The activity approach provides a thermodynamically exact
model framework for describing the behavior of neutral and
ionizable substances under environmental conditions, with
variable pH and ionic strength. The approach is analogous to
and compatible with the well-known fugacity approach, to
which it represents a useful extension.
SUPPLEMENTAL DATA
Figure S1. The model environment of MAMI: air (1),
natural soil (2), agricultural soil (3), other soil (4), freshwater
(5) and freshwater sediment (6), seawater (7), and marine
sediment (8).
Figure S2. How partitioning equilibria of wet aerosol in air
are calculated.
Table S1. Environmental parameters.
Table S2. List of chemical input data required for MAMI III.
Table S3. List of phase-specific permeabilities used for
diffusive exchange between compartments.
Table S4. List of parameters used for advective processes.
Table S5. Species-specific and apparent bulk activity
capacities (B values, m3 m�3) of test chemicals.
Table S6. Measured concentrations of 2,4-D in air in the
Canadian prairie provinces.
Multimedia activity model for ionization chemicals Environ. Toxicol. Chem. 29, 2010 799
Table S7. Measured concentration in freshwater in the
Canadian prairie provinces.
Table S8. Measured bulk and dry deposition fluxes meas-
ured in the Canadian prairie provinces.
Table S9. Measured concentrations of aniline in river water
samples from the Rhine catchment.
Table S10. Measured concentrations of trimethoprim in
water samples collected from European rivers.
Table S11. Measured concentrations in streambed sediments
(276 KB PDF).
Acknowledgement—The present study received financial support from theEuropean Union 6th Framework Program of Research, Thematic Priority 6(Global change and ecosystems), contract GOCE 037017, project OSIRIS.Support for this work was also provided through a PhD grant of the TechnicalUniversity of Denmark for A. Franco.
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