Environmental Science and Pollution Research https://doi.org/10.1007/s11356-021-13388-6

RESEARCH ARTICLE

Twenty-year sediment contamination trends in some tributaries of (Northern ): relation with anthropogenic factors

Laura Marziali1 & Licia Guzzella1 & Franco Salerno1 & Aldo Marchetto2 & Lucia Valsecchi 1 & Stefano Tasselli1,3 & Claudio Roscioli1 & Alfredo Schiavon1,4

Received: 3 November 2020 /Accepted: 8 March 2021 # The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021

Abstract Lake tributaries collect contaminants from the watershed, which may accumulate in lake sediments over time and may be removed through the outlets. DDx, PCB, PAH, PBDE, and trace element (Hg, As, Cd, Ni, Cu, Pb) contamination was analyzed over 2001– 2018 period in sediments of the 5 main tributaries and of the outlet of Lake Maggiore (Northern Italy). Sediment cores were collected in two points of the lake, covering 1995–2017 period. Concentrations were compared to Sediment Quality Guidelines (PECs), potential sources and drivers (land use, population numbers, industrial activities, hydrology) were analyzed, and temporal trends were calculated (Mann-Kendall test). PCB, PBDE, Pb, Cd, and Hg contamination derives mainly from heavy urbanization and industry. Cu and Pb show a temporal decreasing trend in the basin, likely as result of improved wastewater treatments and change in use. A recent PAH increase in the whole lake may derive from a single point source. A legacy DDx and Hg industrial pollution is still present, due to high persistence in sediments. Values of DDx, Hg, Pb, and Cu above the PECs in lake sediments and/or in the outlet show potential risk for aquatic organisms. Results highlight the key role of tributaries in driving contamination from the watershed to the lake through sediment transport.

Keywords Organic micropollutants . Trace elements . Sediments . Lake Maggiore . Contamination trend . River

Introduction hydro-geological factors, may influence pollutant diffusion and dynamics. Lake Maggiore is a large subalpine lake locat- Studying a wide lake basin can represent a great challenge ed between Northern Italy and . The lake catch- because anthropogenic sources of contamination, as well as ment covers an area of about 6500 km2, comprising mainly mountain areas, but also hosting more than 500,000 inhabi- Responsible Editor: Ester Heath tants. As most lakes in Italy and in Europe, Lake Maggiore has been affected by a number of human pressures in the last two Laura Marziali and Licia Guzzella contributed in equal mode to investigation and conceptualization of the paper. centuries. Beside eutrophication, which was counteracted by the improvement of wastewater treatment plant system in the * Laura Marziali second half of the twentieth century, industrial activities have [email protected] severely affected the water ecosystem (Guilizzoni et al. 2012). Since 1800, textile production and chemical industries led to 1 National Research Council - Water Research Institute (CNR-IRSA), the discharge in the lake and in its tributaries of several pollut- via del Mulino 19, 20861 Brugherio, MB, Italy ants, such as trace metals and organic compounds. A peculiar 2 National Research Council - Water Research Institute (CNR-IRSA), example is the case of the River, where DDT production Corso Tonolli 50, 28922 , VB, Italy and a mercury-cell chlor-alkali plant caused an intense DDT 3 Department of Environmental Sciences, University of Milano and mercury pollution in the last century (Marziali et al. 2017; Bicocca, Piazza della Scienza 1, 20126 Milano, Italy Guzzella et al. 2018). Pollutants were transported to the riverine 4 Department of Ecohydrology, IGB Leibniz-Institute of Freshwater and lake ecosystems and were accumulated in sediments and Ecology and Inland Fisheries, Müggelseedamm 310, biota. Concentrations in sediments in the Pallanza basin 12587 Berlin, Germany reached a peak of 13,000 μgkg−1 OCfortotalDDxinthe Environ Sci Pollut Res

1960s and of 26 mg kg−1 d.w. for total mercury in the 1940s. An important factor when considering sediment contami- Even if values in sediments are decreasing over time thank to nation in riverine sediments is the strong spatial and temporal transport of pristine sediments from the upstream river section variability of concentrations. This is mainly related to hydro- and to potential (bio)transformation into mobile forms logical features, which determine depositional areas character- (Quensen et al. 2001; Marziali and Valsecchi 2021), bioaccu- ized by higher concentrations of toxicants due to accumula- mulation in biota is still acting, with concentrations of mercury tion of fine sediments, and temporal variations due to changes in many fish species up to ten times above the European in river discharge (Chiffoleau et al. 1994; Smolders et al. Environmental Quality Standard (EQS of 0.02 mg kg−1 wet 2002; Grosbois et al. 2011). These factors may hamper the weight according to EU Directive 2013/39/EU on priority sub- analysis of contamination trends in riverine ecosystems. stances) (Guzzella et al. 2018; Marziali and Valsecchi 2021). However, long time series and sampling designs covering As well, commercial fishing is still partially banned because different hydrological periods may help disentangling those DDx values in some species exceed the threshold for human confounding effects. consumption (up to 3 mg kg−1 w.w. DDx in whiteshad fillet; In this framework, we focused on sediment contamination Guzzella et al. 2018). of the main tributaries of Lake Maggiore, i.e., , Bardello, This example shows the key role of tributaries in transfer- , , and Toce rivers, as source of toxicants for ring contamination from the watershed to the lake ecosystem. the lacustrine ecosystem and for the lake outlet (emissary), the While water quality of rivers is constantly monitored by the Ticino River, with the aim of analyzing temporal trends of Environmental Protection Agencies, sediment quality is rather pollution over the last 20 years, their sources, and their relations disregarded, since official EQSs for freshwater sediments are with natural (i.e., hydro-geochemical characters) and anthropic still lacking in Italy. This hampers the identification of poten- factors (i.e., land use and population numbers). tial risk for the ecosystem deriving from contaminated sedi- ments, via release of toxicants in the water column and/or bioaccumulation in benthic organisms (Pisanello et al. 2016). Study area The International Commission for the Protection of the Italian-Swiss Waters (CIPAIS) has been supporting a monitoring Lake Maggiore is a large (surface area = 213 km2,volume= program in Lake Maggiore and its tributaries from 1996 up to 38 km3), deep (maximum depth = 370 m), oligo-mesotrophic date, with a particular focus on priority substances in sediments lake, shared between Italy (about 80%) and Switzerland according to EU Directive 2013/39/EU. To cover potential pol- (20%) (Fig. 1). The Lake is considered holo-oligomictic as it lutants deriving from anthropogenic sources, organic chemicals rarely undergoes complete mixing (Guilizzoni et al. 2012; of industrial origin such as DDx, polychlorinated biphenyls Fenocchi et al. 2018). Mean theoretical lake water renewal (PCBs) and polybrominated diphenyl ethers (PBDEs), and poly- time was estimated as more than 4 years (Ambrosetti cyclic aromatic hydrocarbons (PAHs) were included. As well, et al. 2012). the main trace elements potentially deriving from industrial and The lake has a relatively large (6599 km2)watershed,with diffuse contamination are considered, i.e., Hg, As, Pb, Cu, Ni, a complex geological structure (Baudo 1989; Vignati and and Cd. These contaminants are mainly bound to particulate Guilizzoni 2011). A peculiarity is the presence of arsenopyrite matter in the water column and at the bottom, thus the sediment veins, located in the Toce catchment and close to Lake compartment acts as a sink for them, but, under certain hydro- , which determine high background levels (Pfeifer logical and/or chemical conditions, or because of biotransforma- et al. 2000, 2004;Guzzellaetal.2018).Thelakecatchment tion processes, it may behave as a source (Quensen et al. 2001; hosts several other lakes, among which Orta, Lugano, and Grosbois et al. 2011; Baran et al. 2019; Marziali and Valsecchi Varese. The basin is composed mainly of mountain areas with 2021). Being toxic and persistent, these substances may have very low population density, but the shores of the lakes host harmful effects on human health and on aquatic environment medium-sized (30,000–80,000 inhabitants) towns like (Eljarrat and Barceló 2003; Ruiz-Fernandez et al. 2014; Varese, Lugano, , , and Verbania. The ba- Marziali et al. 2017; Ahmed et al. 2018). For a provisional sin is inhabited by more than 500,000 people. Moreover, sea- screening assessment, site-specific concentrations of toxicants sonal tourism accounts for more than 300,000 additional in sediments can be compared to benchmarks considered protec- equivalent inhabitants. For industry, in the North tive for aquatic organisms, such as threshold effect concentra- (Switzerland), the electronics and mechanical sectors deserve tions (TECs, i.e., concentrations below which effects are not particular attention. An important industrial area is located in expected) and probable effect concentrations (PECs, i.e., the eastern part of the watershed ( Region), around values above which effects are likely to occur) Lake Varese, where electrical materials and domestic appli- (MacDonald et al. 2000), even if they do not consider ances have been produced since the 1930s. Smaller manufac- interaction between toxicants, bioavailability, and back- tures and tanneries are also located in this area. In the western ground levels (Simpson et al. 2011). part of the basin ( Region), the production of Environ Sci Pollut Res

Pallanza Basin Core 13

Land use Natural Agricultural Urban Industrial Sampling points Tributaries Core

Fig. 1 Lake Maggiore watershed area in Northern Italy. Sampling points and land cover are reported domestic appliances has been replaced in recent decades by in Bardello and Boesio basins (Fig. 1,Table1). The outlet of floriculture and agri-food industry. Smaller manufactures and Maggiore Lake is Ticino Emissary, with a mean annual dis- tanneries are also located in this area, in particular in the Toce charge of 248 m3 s−1. and Ticino valleys and on the hills close to Lake Orta. Due to the complex orography of the territory, a number of waste water treatment plants (WWTPs) are operational, close to the largest towns. Since the beginning of the 1980s, phos- Materials and methods phorus concentrations have declined in Lago Maggiore, partly due to the implementation of new WWTPs (Guilizzoni et al. Sampling design 2012). Lake Maggiore has many tributaries (Fig. 1): Toce River is Sediments of the main tributaries, i.e., Toce, Tresa, one of the most relevant, with a mean annual discharge of 62 Margorabbia, Boesio, and Bardello (Fig. 1;TableS1.1 m3 s−1. Other important inflows derive from Tresa River (20 in Online Resources 1), were sampled at the rivers’ m3 s−1), which flows out of , Margorabbia (1.7 mouth in 2001–2018 period from 2 to 4 times a year, m3 s−1), Boesio (1.0 m3 s−1), and Bardello (1.6 m3 s−1)rivers according to different seasons and/or hydrological pe- (Table 1; Figure S1.1 in Online Resources 1). Ticino Tributary riods: mostly in April (mean precipitation: 150 ± 17 (62.3 m3 s−1), which flows into the Swiss portion of the lake mm), July (140 ± 37 mm), and October (121 ± 33 (i.e., in the northernmost part), was not considered in the pres- mm), and in some cases in December, the driest period ent study, because previous research highlighted low anthro- of the year (90 ± 15 mm). The same sampling design pogenic inputs from this river (Guzzella et al. 1998). Toce and was used for Ticino Emissary, which was sampled some Margorabbia catchments, followed by Tresa one, are charac- kilometers downstream the lake outlet. The temporal terized mainly by natural land use, while urban areas and range of data and the number of analyses for each an- anthropic activities (industry, agriculture) are mainly located alyte in each river are reported in Table S1.2. Environ Sci Pollut Res

Table 1 Concentrations of contaminants (mean ± standard deviation) in also reported (mean ± standard deviation). n.a. = not analyzed. each tributary of Lake Maggiore and in the emissary. Data on land cover, Threshold and probable effect concentrations (TEC and PEC, population numbers, and annual cumulated precipitation in each respectively) are reported from MacDonald et al. (2000) watershed, and mean discharge of each river (2001–2018 period) are

Pollutant Unit Bardello Boesio Margorabbia Toce Tresa Ticino Emissary TEC PEC

DDx μgkg−1 d.w. 3.5 ± 4.5 7.3 ± 9.0 3.7 ± 3.5 31.9 ± 29.3 3.6 ± 4.4 119.6 ± 663.4 - - DDx μgkg−1 OC 1.3 ± 1.5 1.8 ± 2.7 1.1 ± 1.0 28.1 ± 40.0 1.3 ± 1.4 29.3 ± 147.0 5.28 572 PAHs μgkg−1 d.w. 478.5 ± 319.1 1296.1 ± 2791.4 422.7 ± 348.6 145.7 ± 77.1 4651.2 ± 22,198.3 2574.1 ± 4245.3 - - PAHs μgkg−1 OC 170.9 ± 104.5 228.5 ± 528.6 99.9 ± 84.5 84.9 ± 41.7 1982.2 ± 9656.6 547.1 ± 831.7 1610 22,800 PBDEs μgkg−1 d.w. 84.7 ± 54.4 136.3 ± 107.0 22.8 ± 23.8 12.1 ± 11.0 15.9 ± 11.0 45.7 ± 33.6 - - PBDEs μgkg−1 OC 29.8 ± 18.1 28.4 ± 26.2 7.5 ± 13.7 9.4 ± 12.9 6.4 ± 6.6 10.4 ± 6.9 - - PCBs μgkg−1 d.w. 16.9 ± 18.3 15.2 ± 14.7 7.1 ± 6.4 5.5 ± 7.1 7.7 ± 5.3 39.8 ± 60.5 - - PCBs μgkg−1 OC 5.6 ± 5.0 4.1 ± 7.4 1.9 ± 2.0 3.6 ± 3.5 2.9 ± 2.4 8.6 ± 11.2 59.8 676 As mg kg−1 d.w. 7.2 ± 4.3 6.0 ± 3.3 12.4 ± 8.4 21.2 ± 9.4 37.1 ± 13.7 19.4 ± 8.2 9.79 33.0 Cd mg kg−1 d.w. 0.60 ± 0.35 0.34 ± 0.13 0.34 ± 0.11 0.33 ± 0.17 0.41 ± 0.29 1.28 ± 1.1 0.99 4.98 Ni mg kg−1 d.w. 29.2 ± 9.7 27.1 ± 11.0 25.1 ± 10.3 39.5 ± 16.7 33.3 ± 14.9 57.0 ± 90.9 22.7 48.6 Pb mg kg−1 d.w. 28 ± 9.1 49.9 ± 20.2 37.9 ± 13.6 23.8 ± 17.1 50.2 ± 42.6 90.7 ± 42.9 35.8 128 Cu mg kg−1 d.w. 53.6 ± 17.4 76.3 ± 32 35.8 ± 14.6 47.8 ± 25.4 61.4 ± 55.7 253 ± 244.4 31.6 149 Hg mg kg−1 d.w. 0.24 ± 0.11 0.19 ± 0.08 0.07 ± 0.03 0.18 ± 0.20 0.11 ± 0.07 0.31 ± 0.26 0.18 1.06 OC % 2.9 ± 0.8 5.3 ± 2.2 4.4 ± 2.3 1.7 ± 1.1 3.3 ± 1.8 4.6 ± 1.7 Urban % 25.5 ± 1.7 14.4 ± 0.5 10.1 ± 0.0 1.9 ± 0.0 16.0 ± 0.0 n.a. Industrial % 3.1 ± 0.1 2.8 ± 0.0 1.3 ± 0.0 0.4 ± 0.0 0.5 ± 0.0 n.a. Agricultural % 14.9 ± 0.3 8.6 ± 0.4 8.5 ± 0.0 5.8 ± 0.0 7.1 ± 0.0 n.a. Natural % 56.5 ± 1.5 74.2 ± 0.2 80.2 ± 0.0 91.9 ± 0.0 76.3 ± 0.0 n.a. Population n 157,597 28,374 42,003 107,551 29,433 n.a. Discharge m3 s−1 1.6 ± 1.0 1.0 ± 0.7 1.7 ± 1.3 61.9 ± 28.4 20.0 ± 13.2 248.1 ± 105.5 Precipitation mm 1410 ± 258 1505 ± 307 1550 ± 154 1950 ± 304 1600 ± 128 n.a.

At each site, depositional areas were identified (i.e., sediments settle close to river mouths, while the accumulation pools) and different subsamples of freshly deposited of finer sediments is located at larger distance. The selection of sediments (up to 5–10 cm depth) were collected along coring sites considered both the areas of accumulation of fine the wadable portion of the river bank using a stainless- sediment and the need of finding areas with relatively undis- steel spoon and mixed in order to obtain a 2-L repre- turbed sedimentation. In fact, underwater landslides are fre- sentative sample. Those sediments are characterized by quent in Lake Maggiore due to the very steep slopes. finer grain size compared to erosional area (riffles) and Among the examined cores, we report results for one they may likely cover the temporal period after the last composite core collected in thePallanzaBasin(core13, rain events. The finest sediment fractions show the sedimentation rate 3.9–10 mm year−1) and one in the highest pollutant accumulation, so they are mainly con- Southern part of the lake (core 28, sedimentation rate ca. sidered when the aim of the study is sediment contam- 2.5–3.5 mm year−1) (details in Table S1.3). In particular, ination (Kersten and Smedes 2010). Sediments were in 2002–2017, short cores (28 to 77 cm long) were col- preserved in dark glass bottles at 4 °C until freeze- lected in each area and they were correlated among them. drying (72 h at 0.1 atm). Dry sediments were sieved As detailed in Marchetto et al. (2004), dating was carried to separate the finest fraction (< 63-μm grain size) for out by using marked changes in the diatom assemblages chemical analyses. (compared with the results of monthly phytoplankton In Lake Maggiore, several cores were collected using a non- analysis), by considering the evidence of the 2000 flood, commercial gravity corer composed by a steel cylinder and by comparison with previous cores dated with 210Pb supporting a plastic tube, 63 mm in diameter. The steel cylinder and 137Cs profiles. Only results concerning the late is closed at the top by a valve which closes after the supporting 1990s–2017 period are considered here to compare with rope leaves its tension. The corer can be charged with lead data from tributaries collected in the same temporal range. dishes to increase its weight. Previous studies (e.g., Damiani The whole profiles are reported in Guilizzoni et al. (2012) and Thomas 1974; Rossi et al. 1992) showed that larger size and Guzzella et al. (2018). Environ Sci Pollut Res

Target analytes a graphite atomization system (GF-AAS). Procedural blanks were regularly checked for ambient or reagent contamination. The list of pollutants of concern varied in agreement with each LOD values are reported in Table S2.1. For each sample, tributary contamination history (Table S1.2). The investiga- analysis was run in duplicate and precision expressed as var- tion began in 2001 with the evaluation of DDx and PCBs, iation coefficient resulted as ≤ 5%. The accuracy of recovery which were the contaminants of concern in the lake, and in was estimated by analysis of different CRMs (Table S2.7), 2008, PBDE and PAH quantification was added to the list of among which GBW07305 stream sediment (National contaminants. For trace elements (As, Hg, Pb, Cu, Cd, Ni), the Research Centre of Geoanalysis, Beijing, China) and BCR- investigation began in 2008 in all rivers. 320R channel sediment (Institute for Reference Materials and Target analytes were PAHs divided into low molecular Measurements, Joint Research Centre, European weight (LMW-PAHs), composed by 2 to 4 molecular rings: Commission, Belgium) best cover the 2008–2018 period. naphthalene (Na), acenaphthylene (Ayl), acenaphthene (Aen), For both materials and considering all elements, mean percent fluorene (F), phenanthrene (Pn), anthracene (An), fluoran- recovery was 94 ± 11% (range between 72 and 112%) thene (Fl), pyrene (Py); and high molecular weight (HMW- (Table S2.7). PAHs), composed by 5 and 6 rings: benz[a]anthracene (BaA), Total Hg concentrations in sediments were determined by chrysene (Ch), benzo[b]fluoranthene (BbF), benzo[j + k]fluo- thermal decomposition, amalgamation, and atomic absorption ranthene (BjkF), benzo[a]pyrene (BaP), perylene (Per), spectrometry according to the US-EPA method 7473 (US- indeno[1,2,3-cd]pyrene (InP), dibenz[a,h]anthracene (DhA), EPA 1998), using an Automated Mercury Analyzer and benzo[ghi]perylene(Bghi), 14 PCBs (PCB-18, -28, -31, (AMA254, FKV, Bergamo, Italy). After freeze-drying and -44, -52, -101, -118, -138, -149, -153, -170, -180, -194, and - homogenizing, each sample (0.1 g) was analyzed in triplicate, 209), 6 DDx (o,p′-DDE, p,p′-DDE, o,p′-DDD, p,p′-DDD, o,p obtaining ≤ 5% variation coefficients. Accuracy was checked ′-DDT, and p,p′-DDT), and 8 PBDEs (BDE-28, -47, -99, - using different CRMs and resulted within ± 15% of certified 100, -153, -154, -183, and -209). Further details are reported values (Table S2.7). in Guzzella et al. (2018) and in Online Resources 1. Organic micropollutant sums were calculated as sum of all congeners, considering values below limits of detection (< LOD) as 0. Data analysis For trace elements, As, Hg, Pb, Cu, Cd, and Ni were ana- lyzed as total element concentrations. Ecological risk

Sediment analysis Concentrations of organics were normalized to 1% OC to allow comparison with TECs and PECs (MacDonald et al. Regarding organic compounds, all samples were analyzed 2000)(Table1). according to Guzzella et al. (2016) (details in Online To analyze the potential toxicity risk for aquatic organisms Resources 1). Briefly, 0.5 g d.w. of freeze-dried sediments deriving from metal mixtures in sediments, mean PEC was extracted in a hot-Soxhlet apparatus. The extracts were Quotients (PECQs) were calculated according to the follow- concentrated, purified, and analyzed by GC-MS. The organic ing formula (Long et al. 2006): carbon (OC) content of sediments was determined according ∑n ½Š= ¼ i Mei PEC to Walkley-Black procedure (US-EPA 2002). Performances PECQ n of the methods were evaluated by analyzing different certifi- cate reference materials (CRMs) (Tables S2.2–S2.6 in Online where [Mei] is the concentration of the element i in the sam- Resources 2). The limits of detection (LODs) were estimated ple; PEC is the probable effect concentration according to as 0.02 ng g−1 d.w. for DDx, 0.1 ng g−1 d.w. for PCBs and MacDonald et al. (2000), i.e., the concentration above which PBDE,and1ngg−1 d.w. for PAHs in sediment samples adverse effects on benthic organisms are likely to occur; and n (Table S2.1). is the total number of elements considered (i.e., Cd, Cu, Hg, Trace element analysis was carried out on the finest sedi- and Pb). PECQs are here calculated excluding Ni and As, ment fraction (< 63-μm grain size) to reduce the variability since our geoaccumulation index (Igeo)analysis(Table2)con- due to grain size composition (Suh and Birch 2005; Kersten firmed dominant geochemical origin of these elements, while and Smedes 2010). For As, Ni, Cd, Cu, and Pb determination, our aim was to stress the ecotoxicological risk bound to a microwave-assisted digestion (Preekem EU Excel 2000) of human-altered elements. According to Long et al. (2006), freeze-dried samples (0.2 g) was performed, with concentrated PECQ values ≥ 0.34 may represent potential impact on native

HNO3 and ultrapure water. Concentrations were measured benthic communities, values ≥ 0.5 corresponded to ≥ 15% using atomic absorption spectrometry (AAS) with a Perkin probability of toxicity for Hyalella aztecaandChironomus Elmer AAnalyst 600 with Zeeman correction, equipped with dilutus in lab tests. It is generally accepted that PECQ values Environ Sci Pollut Res

Table 2 Igeo and PECQ values (median and, in brackets, range) sediments, 0 < Igeo ≤ 1 for uncontaminated/moderately contaminated calculated for each river. For Igeo, metal pollution intensities were sediments, 1 < Igeo ≤ 2 for moderately contaminated sediments, 2 < Igeo defined as in Barbieri (2016): Igeo ≤ 0 accounts for uncontaminated ≤ 3 for moderately/heavily contaminated sediments

Igeo As Igeo Cd Igeo Ni Igeo Pb Igeo Cu Igeo Hg PECQ

Bardello − 0.6 (− 1.3/0.8) 0.0 (− 0.8/1.1) − 1.3 (− 1.8/− 0.7) − 0.6 (− 1.2/0.0) 0.3 (− 0.8/0.7) 0.9 (0.3/2.0) 0.22 (0.10/0.36) Boesio − 0.7 (− 1.3/0.5) − 0.4 (− 2.3/0.1) − 1.3 (− 2.8/− 0.7) 0.0 (− 1.8/0.6) 0.6 (− 0.8/1.2) 0.7 (− 0.5/1.6) 0.28 (0.07/0.46) Margorabbia − 0.4 (− 1.3/0.9) − 0.5 (− 1.3/0.1) − 1.4 (− 2.7/− 0.8) − 0.2 (− 1.1/0.4) − 0.1 (− 1.7/0.5) − 0.2 (− 1.0/0.6) 0.14 (0.06/0.24) Toce − 0.9 (− 2.1/− 0.1) − 0.5 (− 1.4/0.3) − 1.0 (− 1.6/− 0.1) − 0.6 (− 2.3/0.6) 0.0 (− 1.2/1.0) 0.3 (− 0.6/2.4) 0.17 (0.05/0.5) Tresa − 0.7 (− 1.8/0.4) − 0.6 (− 1.1/0.9) − 1.1 (− 2.0/− 0.2) − 0.6 (− 1.1/1.2) 0.1 (− 1.0/2.0) 0.2 (− 0.9/1.4) 0.23 (0.05/1.04) Ticino Emissary 0.4 (− 0.5/1.2) 0.6 (− 0.6/2.1) − 1.0 (− 2.2/1.4) 0.6 (− 0.9/1.2) 1.4 (0.1/3.1) 1.1 (0.0/2.8) 0.69 (0.08/2.04)

> 1 represent a probable risk of detrimental biological effects. To assess potential drivers bound to anthropogenic activi- The PECQ approach was not used with organics because the ties, percent land cover according to different land uses was set of target analytes was different for each river and/or sam- calculated in each river basin, except for Toce, for 2007, 2012, pling period. and 2015 using the shapefiles derived from Database of Land Use and Land Cover (DUSAF), published online by Lombardy Region (http://www.geoportale.regione. Contamination sources and drivers lombardia.it/); in Toce basin, which is located in Piedmont Region, it was calculated for 2012 using Corine Land Cover To assess potential contamination sources, different analytical (CLC) shapefile, published online by the Italian Institute for ratios were calculated. The diagnostic molecular ratios Environmental Protection and Research () (http:// (DMRs) were calculated to identify PAH pollution origin www.sinanet.isprambiente.it/it). Land use categories and sources (Li et al. 2006;Yunkeretal.2002). According included in the DUSAF and CLC databases were grouped as to this index, PAHs may derive mainly from petroleum source urban, agricultural, industrial, and natural land use. when Fl/(Fl + Pyr) ratio is < 0.4, while they are emitted mainly Calculations were performed using the software QGIS 3.8.3 from combustion of solid fuels (grass, wood, and coal) when (QGIS Development Team 2010. QGIS Geographic the ratio is > 0.5. Between these values (0.4 < Fl/(Fl + Pyr) < Information System. Open Source Geospatial Foundation 0.5), PAH contamination could be derived from Project. http://qgis.osgeo.org). Since values were rather bothcombustion of gasoline, diesel, fuel, and crude oil and constant in the study period, values calculated for 2012 were emissions from forest fires, cars, or diesel trucks. considered for further analysis. Diagnostic ratios can be calculated also for BaA/(BaA Numbers of total population in each tributary’s basin in +Chr)(Zhangetal.2017): for values < 0.2, petroleum 2008 and 2013 were derived from the National Institute of sources prevail; for values > 0.35, combustion sources Statistics (ISTAT) database (https://www.istat.it/). Values are dominant; for 0.2 < BaA/(BaA + Chr) < 0.35, were rather similar in the 2 years; thus, 2013 values were mixed sources can be supposed. considered for further analysis. I For metals, to measure pollution intensity, the geo was To evaluate the influence of river hydrology on con- calculated for each river according to the following formula tamination levels and transport, monthly discharges of (Barbieri 2016): the tributaries and precipitation data were considered C for 2001–2018 period. Data were provided by the I sample geo¼ ln CIPAIS (http://www.cipais.org/). For each river, mean 1:5 Cbackground discharge and cumulated precipitation of the 3 months where Csample is the concentration of the element in the sam- preceding each sediment sampling were calculated and ple, Cbackground is the background concentration in each river used for further analyses. These aggregations covered derived from the Geochemical Atlas of Europe (http://weppi. best the time lapse between sampling seasons. gtk.fi/publ/foregsatlas/) and from Vignati and Guilizzoni However, similar results were obtained even (2011), and 1.5 is a factor accounting for natural fluctuations considering also the 2- or 1-month period before each in the content of the element in the environment. Igeo provides sediment sampling. a measure of metal pollution by comparing concentrations To find relations between contaminants in tributary to the local geochemical background. To evaluate pol- sediments and between contaminants and drivers of nat- lution intensity, we adopted the classification reported ural and anthropogenic sources, a principal component by Barbieri (2016). analysis (PCA) was carried out considering 137 cases Environ Sci Pollut Res

(samples collected in the five tributaries from 2008 to Results and discussion 2017 analyzed for both organics and trace elements) and

15 variables (PCBsum, PCB-138, PCB-153, PCB-180, Contamination levels and sources PBDEsum, BDE-209, PAHsum,LMW-PAHs,HMW- PAHs, As, Cd, Ni, Pb, Cu, Hg). DDx data were exclud- Each tributary was characterized by a different contamination ed because the dataset was not complete for all tribu- pattern in sediments and contributed differently to lake pollu- taries (Table S1.2). For other organics, sums as well as tion (Table 1, Fig. 2;FiguresS1.2 and S1.3). On the other the main compounds/congeners were included. hand, Ticino Emissary collects fine particles transported to- Supplementary variables (i.e., which do not contribute ward the outlet of the basin because of hydraulic paths and to principal component calculation but are plotted into bathymetry of the lake (Ambrosetti et al. 2012). the resulting factorial plan to help interpretation of gra- Concerning DDx, contamination was confirmed to derive dients) comprised geographical data (latitude, longitude), mainly from the Toce River. A concentration peak in the river land use (natural, urban, agricultural, and industrial per- sediments was observed in October 2001 (147 μgkg−1,cor- cent land cover according to 2012 data), OC, hydrology responding to 142 μgkg−1 OC after normalization to percent (discharge, rainfall), and total population (2013 data). organic carbon), as a consequence of a high-flow event which Kolmogorov-Smirnov test emphasized a non-normal dis- occurred in October 2000 (Table 1,Fig.2; Figures S1.1 and tribution for most variables; thus, values were log10- S1.2). Ticino Emissary registered a DDx contamination peak transformed before PCA analysis. Calculations were per- 2 years later, in October 2003, suggesting that this time lapse formed using STATISTICA 8.0 Software (StatSoft Inc., was needed to transport contamination from the Toce to lake Tulsa, USA). emissary. This is in agreement with Ambrosetti et al. (2012), who used different tracers to determine the movements of the Toce River water toward the lake outlet, finding a resi- Temporal trends of contamination dence time from 1 to 3 years. Concentrations of DDx sum (o,p- + p,p-DDE, DDD, and DDT) in Ticino Temporal trends of contaminant concentrations were Emissary reached a concentration of 4786 μgkg−1,cor- evaluated with Mann-Kendall test in each river sedi- responding to 1040 μgkg−1 OC, i.e., almost twofold ments and in lake sediment cores. Mann-Kendall test the PEC value of 572 μgkg−1 OC, with potential toxic is a nonparametric test which allows for the detection effects for benthic organisms. The contamination peaks of a monotone trend in temporal data series (Wang in Toce and Ticino Emissary showed a peculiar DDx et al. 2019). The Theil-Sen estimator can be used as profile considering percent distribution of compounds, indication of the sign and slope of trends. In particular, with 80–90% of o,p′-DDT + p,p′ DDT, in agreement the Seasonal Kendall test (SKT) was performed using with the composition of the commercial technical mix- data of each river separately (considering a single con- ture produced by the industrial site located along the taminant at each analysis): in this case, the sampling Toce River (Guzzella et al. 1998). This proves that the month was considered as factor for intrablock correction point source of this pollutant was located along to Toce (Helsel and Frans 2006). The Regional Kendall test River. In fact, the TEC value for DDx (5.28 μgkg−1 (RKT) was performed using data of all rivers together OC) generally exceeded in most sediment samples of (considering a single contaminant at each analysis) and both Toce and Ticino Emissary (Table 1). considering the river as factor for intrablock correction As well, mercury pollution is well-known for the Toce (Helsel and Frans 2006). The latter analysis allows for River, as the chlor-alkali plant was completely stopped the correction of temporal trends by potential correlation only in 2018 and soil remediation is in progress in the between rivers, and it was performed to analyze the industrial area (Marziali et al. 2017). From this river, Hg overall temporal trends of contamination in the lake was transported into the Pallanza Basin and then to Ticino basin. Calculations were performed with R software (R Emissary. This transport toward South was proved by Core Team 2020)usingthe“rkt” package authored by analysis of Hg isotope ratios (d202Hg values) in sediment A. Marchetto. For organics, the sums and the main con- core 13 (Pallanza Basin), and core 28 (southern part of the geners where analyzed (i.e., variables with most values lake): similar temporal trends of Hg concentrations and > LOD). A total of 137 analyses were performed. P- comparable isotopic signatures were highlighted (Vignati values were corrected according to false discovery rate et al. 2014). Ticino Emissary showed the highest concen- calculating Benjamini-Hochberg formula (Benjamini and trations,upto1.31mgkg-1 d.w., exceeding the PEC Hochberg 1995) and considering a tolerance ≤ 0.1 for q thresholdof1.06mgkg-1 d.w. (Table 1). This peak was values. reached in October 2011, after the abundant precipitation of July 2011, which determined a high river discharge Environ Sci Pollut Res

12622 525 20 350 160 250

18

d.w.) 140 300 -1 16 200 OC

d.w.) 120 1 -1 - OC) 14 250 -1 g k

g 100 OC), Hg (µg kg OC), Hg (µg µ 12 150 ( -1

s 200 B -PAHs (µg kg (µg -PAHs C 80 P 10 d.w.) Hg (µg kg d.w.) 1 -

150 LMW 8 100 60

6 100 40 Cu, Pb (mg kg Cu, Pb (mg 50

4 kg (µg LMW-PAHs d.w.) -1 50 20 2

0 0 0 0 Cu, Pb (mg kg Cu, Pb (mg 2009 Jul 2009 Jul 2018 2010 Jul 2010 Jul 2011 Jul 2016 2008 Jul 2008 Jul 2012 Jul 2014 Jul 2015 Jul 2017 2013 Jul 2013 2009 Jul 2009 2011 Jul 2011 2013 Jul 2013 2015 Jul 2015 2017 Jul 2017 2009 Oct 2009 Oct 2011 Oct 2018 2008 Oct 2008 Oct 2012 Oct 2016 Oct 2017 2010 Oct 2010 Oct 2013 Oct 2014 Oct 2015 2004 Oct 2006 Oct Oct 2008 2012 Oct 2010 Oct 2001 Oct 2001 Oct 2002 Oct 2003 Oct 2005 2014 Oct 2014 2018 Oct 2016 Oct 2016 2012 Apr 2010 Apr 2010 Apr 2011 2013 Apr 2008 Apr 2008 2009 Apr 2014 Apr 2015 Apr 2017 Apr Apr 2018 2016 Apr 2001 Apr 2001 Apr 2002 Apr 2004 Apr 2005 Apr 2006 Apr 2008 2010 Apr 2010 2003 Apr Apr 2012 2014 Apr 2014 2016 Apr 2016 2018 Apr 2018 a) PCBs LMW-PAHs Pb Cu Hg b) Pb Cu Hg LMW-PAHs

70 450 120 2000

400 60 100 ) .

w 350 . d 1500 50 -1 OC) g k -1

300 80 OC) g -1 µ ( d.w.) g

-1 40 H 250 , ) .

w 60 . 1000 d 1 - 200 30 g k g Cd, Hg (µg kg PBDEs, PCBs (µg kg (µg PCBs PBDEs, m

( 150 40 PBDEs ,PCBs kg (µg b

P 20 ,

u 500

C 100 20 10 50

0 0 0 0 2002 Jul 2002 2003 Jul 2003 Jul 2004 Jul 2005 Jul 2006 Jul 2013 2015 Jul 2015 2017 Jul 2017 2009 Oct 2009 Oct 2012 2008 Oct 2008 Oct 2010 Oct 2011 2014 Oct 2014 Oct 2018 2016 Oct 2016 2002 Jul 2002 Jul 2003 Jul 2005 Jul 2006 2009 Jul 2009 2013 Jul 2013 2017 Jul 2017 2004 Jul 2004 2011 Jul 2011 2015 Jul 2015 2014 Apr 2014 2016 Apr 2016 2018 Apr 2018 2002 Dec 2003 Dec 2004 Dec 2005 Dec 2006 Dec 2011 Oct 2013 Oct 2015 Oct 2017 Oct 2009 Oct 2010 Apr 2010 Apr 2012 2014 Apr 2014 Apr 2016 2018 Apr 2018 2008 Apr 2008 2003 Dec 2004 Dec 2006 Dec c) d) 2002 Dec 2005 Dec Pb Cu Hg PCBs PBDEs Cd Hg PCBs PBDEs

1040

) 1600 60 1000 250 1

900 1400 50 )

. 800 200 .

w 1200 . d -1

700 kg-(mg Cu, Pb d.w.)

g 40 k -1 OC)

g 1000 -1 µ

( 600 150 OC) g 1 - H , ) . 500 800 30 w . d 1 - OC), Hg (µg kg (µgOC), Hg

g 400 100 k -1 600 DDx (µg kg g

20 kg PCBs, DDx (µg m ( 300 b P

, 400 u

C 200 50 10 200 100 LMW-PAHs (µg kg (µg LMW-PAHs

0 0 0 0 2002 Jul 2003 Jul 2009 Jul 2011 Jul 2014 Jul 2016 Jul 2018 Jul 2001 Jul 2004 Jul 2005 Jul 2006 Jul 2016 Jul 2016 2018 Jul 2018 2012 Oct 2012 2008 Oct 2008 Oct 2010 2015 Oct 2015 Oct 2017 2014 Jul 2014 2015 Oct 2015 2017 Oct 2017 2013 Apr 2013 2008 Apr 2008 Apr 2010 Apr 2012 2015 Apr 2015 2017 Apr 2017 2001 Dec 2001 Dec 2002 Dec 2003 Dec 2004 Dec 2005 Dec 2006 2017 Apr 2001 Oct 2002 Oct 2003 Oct 2004 Oct 2005 Oct 2006 Oct 2013 Oct 2001 Apr 2001 Apr 2002 2004 Apr 2004 Apr 2006 Apr 2009 Apr 2010 2003 Apr 2003 Apr 2005 Apr 2008 Apr 2011 Apr 2012 Apr 2013 Apr 2015 e) Hg Pb Cu DDx f) LMW-PAHs Cu Hg PCBs DDx Fig. 2 Temporal trends of the main pollutants in each tributary of Lake Maggiore and in Ticino emissary. a Tresa. b Margorabbia. c Boesio. d. Bardello. e Toce. f Ticino Emissary. See axis legends for unit scale of each pollutant. Concentrations of organics are normalized to 1% OC

(475 m3 s−1) (Figure S1.1). In that period, in the Toce Boesio and Bardello basins are located in the most River concentrations reached 0.73 mg kg−1 d.w., i.e., sev- anthropized area of the lake watershed (Fig. 1). Bardello en times the TEC value (Table 1,Fig.2). River is characterized by poor water quality: it is emissary of Environ Sci Pollut Res

Lake Varese, which is a heavily anthropized and eutrophic significantly lower, due to discharge values 50 times lower water body.Besides, it also receives both civil and industrial (Table 1; Figure S1.1). Conversely, Pb in sediments proved wastewaters (Rossi et al. 1988). As well, Boesio is still char- to be mainly geogenic in the lake basin, with some values acterized by high industrial load, despite a recent decrease of exceeding the PEC threshold (128 mg kg−1 d.w.) only in the urban wastewater load compared to the previous decades, as Ticino Emissary, e.g., with 160 mg kg−1 d.w. in April 2013 proved from 27% decrease in chloride in the period 1990– (Table 1). In this river, Igeo showed the presence of moderate 2010 (Rogora et al. 2015) and of TP values from around anthropic enrichment for this element (Table 2, Figure S1.3). 400 μgL−1 in 2003–2007 (CIPAIS 2013) to about 200 μg However, data from official monitoring highlighted some L−1 in 2008–2015 (CIPAIS 2016). values in water of Boesio and Bardello exceeding the For PBDEs, the main inputs in the lake derive from those Environmental Quality Standard (ARPA Lombardia 2014). rivers (Table 1,Fig.2;FigureS1.2). Concentrations in Boesio Thus, anthropogenic inputs may derive mainly from those were very variable in time, with maximum values up to rivers. Past mining activities, atmospheric pollution, and metal 445 μgkg−1 (corresponding to 100 μgkg−1 OC). PBDE con- industry may be the main sources. Considering the overall risk tamination derives mainly from recent industrial production of deriving from metal mixtures in sediments, the PECQ ap- flame-retardant compounds (Liu et al. 2018). In fact, the prev- proach shows that potential alteration of benthic communities alent congener was BDE-209 (90–96% of the total PDBEs), could be likely in Bardello and Boesio, where the highest which is the main component of the Deca-BDE commercial values were > 0.34 threshold and, most of all, Toce, Tresa, mixtures, still available for limited applications, while the use and Ticino Emissary, where values were > 0.5 (Table 2) of Penta-BDE and Octa-BDE mixture was forbidden in Italy (Long et al. 2006). For Toce, in a previous study (Marziali in 2008, in agreement with Stockholm Convention. The et al. 2017), we highlighted that 5% of total variation of in- Canadian Environmental Quality Guideline for PBDEs in sed- vertebrate community was bound to sediment contamination. iments (BDE-209 value of 19 μgkg−1 OC; Canadian For Tresa River, a strong increase for trace elements Environmental Protection Act 1999) generally exceeded in such as Hg, Cu, and Pb in 2015–2016 was shown, with Boesio and Bardello, and, in some cases, also in Ticino values twofold higher than in the previous period (Fig. 2). Emissary, showing a potential risk for the aquatic ecosystem. As well, PAH analysis showed that Tresa was the most Concerning PCBs, Boesio and Bardello were the most pollut- polluted river of the basin, along with Ticino Emissary ed rivers in the 2001–2018 period, along with Ticino (Fig. 2;FigureS1.2). Also, PAH levels in recent years Emissary (Fig. 2, Table 1; Figure S1.2). Maximum values showed a strong increase, with a peak in July 2015 were observed in Ticino Emissary (up to 312.6 μgkg−1 and (122,133 μgkg−1, corresponding to 53,102 μgkg−1 OC) 55.8 μgkg−1 OC for PCBs), in Boesio (up to 85.5 μgkg−1 and exceeding thirtyfold the TEC value (1610 μgkg−1 OC for 49.7 μgkg−1 OC), and in Bardello (up to 104.0 μgkg−1 and total PAHs), probably due to a local point source. This 20 μgkg−1 OC). However, concentrations remained below general increase of pollution levels may derive from the TEC value (59.80 μgkg−1 OC for PCBs) and may not leaching or combustion of mixed contaminated materials. represent a risk for aquatic organisms. In those rivers, PCB Recent data (2014–2017) on Tresa sediments showed an levels varied greatly in time (Table 1; Figure S1.2), highlight- average of 59% of LMW-PAHs (Na, Ace, Acy, Fl, Phe, ing that pollution sources are likely of multiple origin, deriv- An) to the total PAHs, while the mean percentage of ing mainly from industrial diffuse contamination (Minh et al. HMW-PAH (> C4) was 41%. DMR calculation was used 2007; Combi et al. 2016). to identify PAH pollution origin, showing a Fl/(Fl + Pyr) Regarding metals, sediments in Bardello showed moderate ratio mean value of 0.52 ± 0.09; thus, contamination could Cd enrichment, even if concentrations were below the PEC derive mainly from combustion of solid fuels (grass, threshold (4.98 mg kg−1 d.w.) (Tables 1 and 2,Fig.2; wood, and coal). The mean BaA/(BaA + Chr) ratio was Figure S1.3). Similar concentrations were observed in Ticino 0.52 ± 0.08, confirming that combustion sources are dom- Emissary. This metal may derive from phosphate fertilizers, inant. Similarly, the analysis of recent PAH distribution in waste incineration, and metal production, as well as from at- Ticino Emissary (2014–2018) evidenced a prevalence of mospheric deposition (Roberts 2014). Also, Hg in Bardello LMW-PAHs (74% of the total amount) in comparison to showed moderate enrichment, as well as in Boesio (Table 2, HMW-PAHs (26%); therefore, a main contribution from Fig. 2;FigureS1.3). The presence of Hg-contaminated soil is combustion of solid fuels and/or atmospheric transport of well-known in Lake Maggiore watershed, due to past indus- contaminated particles can be supposed. Here also, Fl/(Fl trial hat and leather productions, which used mercury com- + Pyr) and BaA/(BaA + Chr) ratio values resulted in > 0.5 pounds in the tannery process. In these rivers, Hg values were in recent years (0.53 ± 0.06 and 0.53 ± 0.07, respective- generally above the TEC value (0.18 mg kg−1 d.w.) (Table 1). ly), confirming a main origin from combustion. On the Even if concentrations may be comparable to those found in contrary, direct petrogenic sources seem to be limited or Toce, the contribution to lake contamination should be absent in Lake Maggiore basin. Environ Sci Pollut Res

Another pollutant of concern in the lake basin was Cu, with minor extent, Pb levels were higher where industrial land showing in Ticino Emissary moderate/heavy enrichment and use showed the highest numbers. Their origin is likely bound exceeding the PEC of 149 mg kg−1 d.w. (Tables 1 and 2;Fig. to specific industrial processes or products. 2;FigureS1.3). The main contributors were Boesio, Tresa, The second axis accounted for 18.5% of total variability and Toce, where electric production industry, wastewaters, and represented a gradient bound to natural factors, such as agriculture, and floriculture could likely be the main sources. hydrology and, at the opposite, sediment fine fractions (TOC) As for Hg, the highest concentrations were reached in those (Fig. 3). Toce and Tresa were characterized by the highest rivers in 2010–2011, in correspondence to high-flow condi- discharge and precipitation, Boesio by the lowest ones tions. Soil leaching and remobilization of contaminated sedi- (Table 1). PAHs and As were positively related to precipita- ments may be the main mechanisms. In April 2010, a peak in tion and river discharge. This confirmed for PAHs a potential Ticino Emissary reached 949 mg kg−1 d.w., i.e., sixfold the contribution from atmospheric transport of LMW-PAHs, but PEC threshold. Higher sediment inputs from the lake during also the key role of hydrological factors in driving contami- high-flow events may explain the observed peaks in the outlet. nated particles to the lake. For As, the positive correlation with For what concerns other trace elements, arsenic showed the discharge (Pearson’s correlation coefficient r =0.68,p <0.05) highest values in Tresa (up to 74.6 mg kg−1 d.w.) and Toce (up emphasized the role of solid fractions, e.g., amorphous Al, to 48.4 mg kg−1 d.w.), with concentrations exceeding the PEC Mn, and Fe oxides, hydroxides, and oxyhydroxides, as absor- threshold (33 mg kg−1 d.w.) (Table 1). However, this element bent and carriers of As derived from natural weathering derives mainly from natural weathering of As-rich rocks, i.e., (Pfeifer et al. 2004;Grosboisetal.2011). On the contrary, containing arsenopyrite and calchopyrite minerals, even if a Pb was correlated with TOC, i.e., with the finest solid frac- slight anthropic contribution was reported for Toce River tions, being likely bound onto suspended and colloidal parti- (Pfeifer et al. 2004; Marziali et al. 2017). Normalizing con- cles (Rothwell et al. 2007). centrations to background levels (Igeo)(Table2,FigureS1.3), moderate enrichment was found only in Ticino Emissary, which receives fine sediments from the lake (Ambrosetti Temporal trends of contaminants in sediments et al. 2012) and where values reach the PEC threshold. Similarly, nickel in the lake watershed is bound mainly to Temporal trends of pollutant concentrations in sediments were local geochemistry, i.e., mafic and ultramafic rocks (Amorosi evaluated for each river and sediment core (SKT analysis) and et al. 2002), as confirmed by Igeo values and by similar con- in the whole lake basin, considering all river data together centrations in all tributaries (Tables 1 and 2; Figure S1.3). (RKT analysis) (Tables S1.4–S1.6). River sediment trends However, strong variability in Ticino Emissary (Table 1)led to exceedance of PEC threshold (48.6 mg kg−1 d.w.). The −1 Projection of the variables on the factor-plane (1 x 2) highest values were 103.5 mg kg d.w. in April 2010 and 1.0 412.2 in October 2011 mg kg−1 d.w., corresponding to two- LMW-PAHs and fourfold the PEC concentration, respectively. A similar PAHsum increase was highlighted also in Tresa in the same period, up HMW-PAHs As −1 to 80.6 mg kg d.w. in October 2010. In both rivers, these 0.5 *Latitude peaks corresponded to high hydrological conditions. *Longitude *Discharge *Rain *Natural % 1 5

Contamination drivers .

8 PCBsum 1 PCB180

: 0.0 PCB153

2 PCB138 *Urban To summarize the contamination patterns of tributaries and r Cd Ni o Pb t relate them to potential drivers, PCA was carried out (Fig. c *Population a 3). The first component accounted for 29.8% of total variabil- F *Agricultural Cu *TOC ity and represented a gradient of anthropization level in the BDE209 -0.5 Hg watersheds. Axis 1 was inversely related to population num- PBDEsum *Industrial bers and urban land use and positively to natural land use. The most anthropized watershed was represented by Bardello; the Active most natural one was Margorabbia basin, as shown by percent Supplementary -1.0 urban and industrial land use (Table 1). While arsenic was -1.5 -1.0 -0.5 0.0 0.5 1.0 mostly related to natural land use, PCBs (and main congeners) Factor 1 : 29.78% and Cd were likely bound to urban land use and to population Fig. 3 PCA results: active (contaminant concentrations) and numbers, proving that their origin may be multiple and gen- supplementary variables (geographical, hydrological factors, land use, erally bound to diffuse contamination. PBDE, Hg, Cu, and, population) according to axes 1 and 2 Environ Sci Pollut Res were compared to those of lake sediments (cores 13 and 28), high levels ofmany contaminants potentially affecting micro- to assess the impact of tributary inputs on the lake ecosystem. bial communities (Quensen et al. 2001; Ahmed et al. 2018). Core 13 was sampled near the Toce mouth, and it was directly Surprisingly, Hg in Toce did not show a clear decreasing influenced by inputs deriving from this river (Figs. 1 and 4). trend, with a low slope of − 0.01, not significant according to Core 28 was collected in the southern part of the lake, and it FDR analysis (Tables S1.4 and S1.6). The result was con- was composed mainly of fine particles potentially deriving firmed by core 13 analysis. Notwithstanding the efforts made from the whole basin (Figs. 1 and 5). The latter can be com- in stabilizing contaminated soils and groundwater close to the pared with sediments of Ticino Emissary. chlor-alkali industrial area (Marziali et al. 2017), concentra- DDx showed a strong decreasing trend in Toce River be- tions in sediments downstream the factory remained stable tween 2001 and 2018 (Theil-Sen’s slope = − 205.3, p < over the last decade. This means that active contribution of 0.001), as mirrored in core 13 (slope = − 304.3, p < 0.05) Hg is still present, at least until 2018, and buffered the reme- (Tables S1.4 and S1.5). This decrease was not significant in diation effect due to natural capping of contaminated sedi- core 28 and in Ticino Emissary, showing that DDx removal ments with pristine sediments transported from upstream. As from the lake may be slower, due to trapping of fine contam- for DDx, a Hg decontamination process in Ticino Emissary inated sediments into the lake cuvette (Ambrosetti et al. 2012). was not observed between 2008 and 2018. A slight reduction Moreover, biodegradation may show low efficiency due to in time was found in core 28, which comprised a longer time

µg kg-1 1%OC µg kg-1 1%OC 0 10203040 0 100 200 300 400

05/2016-05/2017 05/2016-05/2017 DDx 05/2014-05/2016 PCBs 05/2014-05/2016 PBDEs 05/2011-05/2014 05/2011-05/2014 PAHs Date 2008-2011 Date 2008-2011

1999-2008 1999-2008 a)

mg kg-1 d.w. µg kg-1 d.w. 0 50 100 150 200 0 500 1000 1500 2000

05/2016 - 05/2017 05/2016 - 05/2017 As Cd 05/2014 - 05/2016 05/2014 - 05/2016 Cu Hg 05/2011 - 05/2014 05/2011 - 05/2014 Pb 05/2009-02/2011 05/2009-02/2011 Ni 07/2007-05/2009 07/2007-05/2009 05/2006-07/2007 05/2006-07/2007 10/2005-04/2006 10/2005-04/2006 04/2005-09/2005 04/2005-09/2005 Date Date 09/2004-03/2005 09/2004-03/2005 04-2004-09/2004 04-2004-09/2004 10/2003-03/2004 10/2003-03/2004 04/2003-09/2003 04/2003-09/2003 10/2002-03/2003 10/2002-03/2003 05/2001-09/2002 05/2001-09/2002 12/1999-04/2001 12/1999-04/2001 07/1998-11/1999 07/1998-11/1999 b)

Fig. 4 Trends of the main pollutants in sediment core 13, collected in Lake Maggiore, Pallanza Basin. a Organic pollutants. b Trace elements Environ Sci Pollut Res

µg kg-1 1%OC µg kg-1 1%OC 010203040 0 100 200 300 400

05/2016-05/2017 05/2016-05/2017 DDx PAHs 05/2014-05/2016 PCBs 05/2014-05/2016 e t PBDEs a D 05/2011-05/2014 Date 05/2011-05/2014 45 2004-2011 2004-2011

1995-2004 1995-2004 a) mg kg-1 d.w. µg kg-1 d.w. 0 50 100 150 200 0 500 1000 1500 2000

05/2016-05/2017 As 05/2016-05/2017 Cd Cu Hg Pb 05/2014-05/2016 05/2014-05/2016 Ni

05/2011-05/2014 05/2011-05/2014

02/2011-01/2009 02/2011-01/2009 Date Date 03/2008-03/2007 03/2008-03/2007

03/2007-03/2005 03/2007-03/2005

03/2005-11/2001 03/2005-11/2001

b) 1995-2004 1995-2004

Fig. 5 Trends of the main pollutants in sediment core 28, collected in Lake Maggiore, southern basin. a Organic pollutants. b Trace elements

lapse, covering about 20 years (1995–2017), even if the slope Margorabbia and in Ticino Emissary (slope = 636.6, p was low (slope = − 0.19, p < 0.05, however not significant < 0.001), as well as in lake basin (slope = 3.86, p < according to FDR; Tables S1.4 and S1.6). 0.001) (Tables S1.4 and S1.5). These patterns could be On the contrary, Cu and Pb showed negative trends in Toce bound to an increased anthropic contribution in recent (slopes = − 3.84 and − 3.00, respectively, p = 0.008) time, which influenced the whole lake. On the contrary, (Tables S1.4 and S1.6). A significant decreasing trend for no temporal trends were evidenced for HMW-PAHs. Cu could be likely in Ticino Emissary as well (slope = − PCBs proved to be increasing in Bardello (for PCB- 14.82, p < 0.05), and for the whole lake basin (slope = − 52, PCB-138 and for PCB-180, p < 0.001) and in 3.33, p < 0.001). Pb showed a reduction in time in core 28 Tresa (for PCB-138, p < 0.001, even if concentrations (slope = − 3.66, p < 0.05). This trend may follow a general Pb remained low in the latter river). Considering PCBs in decontamination pattern of the basin, as proved for Toce and sediment cores, values did not show any tendency and for Bardello in 2001–2017 (slopes = − 3.00 and − 1.54, re- were comparable to those of Ticino Emissary (Figs. 4 spectively, p ≤ 0.01). These results may be bound to lower Cu and 5). and Pb inputs from the whole catchment, and from Toce in PBDEs (composed by more than 95% of BDE-209 particular. A clear explanation in relation to local sources was congener) and Cd did not show clear trends in rivers not found. However, similar Cu and Pb decontamination pat- since concentrations, even if high in Bardello e Boesio, tern were observed in other rivers, as result of stricter environ- were very variable in time. However, levels in lake mental regulations but also for local changes in the use, for Cu sediments showed the highest contamination in the in particular (e.g., Sharley et al. 2016). oldest layers of both cores (Fig. 4 and 5). Lastly, arse- Concerning PAHs, LMW compounds showed a nic and Ni, as expected, did not show any significant strong increasing trend (slope = 443.9, p <0.001)in trend, deriving mainly from geogenic origin. Environ Sci Pollut Res

Comparison with other case studies Camusso and Gasparella (2006) reported concentration in pore water < 5 μgL−1 Cu in Toce, Tresa, and Boesio and up Results for Lake Maggiore and its main tributaries can be to 35 μgL−1 Cu in Pallanza Basin, with even lower bioavail- compared with other case studies, to evaluate contamination able fractions (< 0.1 μgL−1, as estimated using DGT passive levels and temporal trends. samplers), thus posing a low environmental risk (Simpson Papers published on Chinese lakes and rivers regarding et al. 2011). However, in our case study, bioavailability should micropollutants in sediments are very numerous. For example, be further assessed in Ticino Emissary, where concentrations DDx contamination in sediments of Yangtze River was ana- in sediments largely exceed the PEC threshold. Here, chang- lyzed in the lower stretch of the river, located in one of China’s ing redox conditions and sediment characteristics (OC, % silt, most economically developed areas, and resultedup to 8.97 ± AVS) in the shift from lake to river dynamics may alter chem- 11.1 ng g−1 d.w. (Tang et al. 2013). In comparison, levels in ical speciation, with potential release from the solid phase Toce River and Ticino Emissary in the same period (2010) (Simpson et al. 2011). were generally much higher (Figure S1.2), but it must be The comparison with Lake Chapala, Mexico, is reported in considered that Lake Maggiore contamination was caused Online Resources 1. by direct DDT industrial discharges. Yang et al. (2009)ana- Considering some case studies in Europe, a sediment core lyzed trace element contamination in Yangtze River, its trib- was sampled downstream from the heavily urbanized and in- utaries, and lakes in Wuhan catchment. Mercury was one pol- dustrialized area of Paris, dating 1950–2005 (Lorgeoux et al. lutant of concern, with concentrations up to 1.93 mg kg−1 2016). Considering only the most recent period (1995–2005), d.w., potentially deriving from fuel and coal combustion. PAH (10–20 mg kg−1 d.w.) and PBDE (0.02–0.04 mg kg−1 Speciation partitioning highlighted limited bioavailability for d.w.) levels were similar to those found in Tresa and Ticino this metal, with a residual fraction > 95%. As well, in Lake sediments, respectively, while PCBs (0.5–1mgkg−1 d.w.) Maggiore, we analyzed MeHg fractions in sediments of the were 1–2 order of magnitude higher than our data. A sediment Pallanza Basin, finding a maximum of 2.6% on total mercury, core collected in Greifensee, a small eutrophic lake close to even if most samples showed MeHg values below the LOD Zürich (Switzerland) (Kohler et al. 2008), confirmed for (0.7 μgkg−1, Valsecchi et al. 2020). In Toce sediments, where PBDEs, as in Lake Maggiore, a decreasing pattern of technical the point source is located, a maximum fraction of 3.8% Penta-BDE and Octa-BDE mixtures until the mid-1990s, and MeHg was found, with resulting significant bioaccumulation increasing concentrations of Deca-BDE until 2000 (7.6 μg in benthic invertebrates and potential risk of secondary poi- g−1) Values were lower than those registered in core 28 (up soning in top predators (Pisanello et al. 2016;Marzialiand to 45 μgg−1). The PCB vertical profile evidenced high con- Valsecchi 2021). centration peaks in the 1960s–1970s, followed by a decreas- As regards PBDEs, Liu et al. (2018) reported contamina- ing trend to a few micrograms per gram, i.e., comparable to tion in sediments of the Chinese Chaohu Lake in its tribu- levels found in Lake Maggiore (Figure S1.2). taries, located in a heavily urbanized catchment. As in our Data on trace element contamination in different European study, the congener profile was dominated by BDE-209, and rivers show a general decreasing sediment contamination values,upto4.95ngg−1, were significantly lower than levels from the 1970s-1980s up to date, thanks to change in indus- found in lakes of the provinces of Guangdong, Jiangsu, and trial processes, development of more restrictive environmental Zhejiang with rapid industrial and economic levels (Yu et al. regulations and of wastewater collection and treatment sys- 2016). Bardello and Boesio rivers showed concentrations sim- tems (e.g., Meybeck et al. 2007;Grosboisetal.2012). ilar to those reported in these latter areas, with levels up to one Considering only the last 10–15 years, to compare with our hundredfold higher than those of Chaohu Lake. Similarly, results, concentrations seem generally to further decrease. For

PCB contamination in sediments of Bardello, Boesio, and example, Igeo data on Pb, Cu, and Cd in French rivers (Seine, Ticino Emissary are in the same order of magnitude than Loire, and Rhône) after 2000 show a lowering trend toward values in the Yangtze River Estuary (Chen et al. 2017). moderately polluted or unpolluted sediments, while Hg seems Also, Pb and Cd in Boesio, Bardello, and Ticino Emissary more persistent, showing high-to-moderate sediment contam- showed values comparable to the industrial area of the ination (Meybeck et al. 2007;Grosboisetal.2012). In Lake

Yangtze, where these elements were proved to be mostly in Maggiore tributaries, Igeo values for Pb in the last decade are bioavailable forms (Yang et al. 2009). Here we did not ana- generally below 1, as well as for Loire and Rhône (Grosbois lyze chemical speciation. However, exceedance of EQS for Pb et al. 2012) and show a general decreasing trend toward values in both tributaries’ water, as well as for Cd in Ticino Emissary below 0, corresponding to unpolluted sediments water (ARPA Lombardia 2014), may point out a similar sce- (Figure S1.3). This may be attributed to significant changes nario. On the contrary, Cu showed low bioavailability in in environmental policies and to elimination of lead products. Yangtze River (Yang et al. 2009). As well, in Lake A different situation is observed for Hg in Toce and in the Maggiore, Cu may be mostly in non-bioavailable forms, since southern part of Lake Maggiore, where decontamination is Environ Sci Pollut Res

very slow, with Igeo values up to 2.4 in Toce and 2.8 in Ticino relation to the persistence capacity of each compound Emissary after decades from the peak of industrial production in the sediment compartment. (Figure S1.3). For this metal, several works emphasized high geochemical persistence in the sediment compartment, even if industrial uses have been drastically reduced after the 1960s Supplementary Information The online version contains supplementary (Meybeck et al. 2007). For example, sediments in Loire River material available at https://doi.org/10.1007/s11356-021-13388-6. I in the last decade show geo values around 2.5 (Grosbois et al. Acknowledgements We would like to thank Marzia Ciampitello (CNR- 2012), close to those found in Toce. Also, the other tributaries IRSA Verbania, Italy) for her support in recovery of river flow data and of Lake Maggiore do not show any significant decreasing Hg Andrea Lami of the same Institute for sediment core dating. trend in one decade, and only Margorabbia shows Igeo values generally below 0 (Figure S1.3). On the contrary, fast Cu Author contribution Laura Marziali: investigation, conceptualization, writing, formal analysis. Licia Guzzella: investigation, conceptualization, decontamination has been reported in several case studies af- writing. Franco Salerno: formal analysis. Aldo Marchetto: investigation, ter the removal of the pollution source (Sharley et al. 2016; review. Lucia Valsecchi: investigation, data curation. Stefano Tasselli: Gardes et al. 2020; Meybeck et al. 2007), as observed also in investigation, data curation. Claudio Roscioli: investigation, data curation. Alfredo Schiavon: formal analysis, figure editing. Ticino Emissary and in most tributaries, showing Igeo values mostly below 0 (Figure S1.3). Lower inputs may result mostly Funding This work was supported by the International Commission for from improved wastewater treatments, better fume the Protection of Italian-Swiss Waters (CIPAIS), Research Programs trapping, and, potentially, reduced use in local agricultural 2001–2007, 2008–2012, 2013–2015, and 2016–2018 (www.cipais.org). applications. Sequential extraction would help understanding the mechanisms which drive a faster decontamination than Data Availability The datasets generated and/or analyzed during the cur- observed for other elements. rent study are available in the reports regarding Lake Maggiore at the website www.cipais.org.

Conclusions Declarations

Ethics approval and consent to participate Not applicable. The sediment compartment plays a crucial role as an accumu- lation site for toxicants with high affinity for the solid phase Consent for publication Not applicable. and may determine a risk for aquatic ecosystems. The com- parative assessment of some persistent organic Competing interests The authors declare no competing interests. micropollutants and trace elements in the sediments of the main tributaries of Lake Maggiore in 2001–2008 period con- firmed a DDx and Hg residual contamination in the References basin, which isof the highest concern due to very slow decon- tamination processes and high toxicity and biomagnification Ahmed AM, Lyautey E, Bonnineau C, Dabrin A, Pesce S (2018) potential. Moreover, increasing concentrations of LMW- Environmental concentrations of copper, alone or in mixture with PAHs in the whole basin, potentially bound to local point arsenic, can impact river sediment microbial community structure sources, would deserve a deeper investigation because of the and functions. Front Microbiol 9:1852. https://doi.org/10.3389/ fmicb.2018.01852 strong impact on the whole lake basin. Urbanization and in- Ambrosetti W, Barbanti L, Rolla A, Castellano L, Sala N (2012) dustrial activities, especially in Bardello and Boesio basins, Hydraulic paths and estimation of the real residence time of the resulted as the main pollution sources for the lake for PCBs, water in Lago Maggiore (N Italy): application of massless markers PBDEs, and Cd, while a general Pb and Cu decreasing pattern transported in 3D motion fields. J Limnol 71:23–33. https://doi.org/ 10.4081/jlimnol.2012.e2 seems likely, as potential effect of lower inputs and improved Amorosi A, Centineo MC, Dinelli E, Lucchini F, Tateo F (2002) wastewater treatment systems. Geochemical and mineralogical variations as indicators of prove- Results highlight the key role of tributaries in driving con- nance changes in Late Quaternary deposits of SE plain. tamination from the watershed to the lake through sediment Sediment Geol 151:273–292. https://doi.org/10.1016/S0037- transport and the strong influence of river hydrology in deter- 0738(01)00261-5 ARPA Lombardia (2014) Stato delle acque superficiali bacino del Fiume mining remobilization of contaminated sediments. The com- Ticino e Lago Maggiore. Rapporto annuale 2012. Agenzia parison with other water bodies in Asia and Europe evi- Regionale per la Protezione dell’Ambiente (ARPA) Lombardia, denced significant contamination levels for DDx, Hg, Settore Monitoraggi Ambientali Marzo 2014:31 pp Cd, PBDEs, and LMW-PAHs in Lake Maggiore. Baran A, Mierzwa-Hersztek M, Gondek K, Tarnawski M, Szara M, Temporal trends seem comparable to those described Gorczyca O, Koniarz T (2019) The influence of the quantity and quality of sediment organic matter on the potential mobility and in other European aquatic ecosystems, as result of com- toxicity of trace elements in bottom sediment. Environ Geochem mon environmental regulation and uses, but also in Health 41:2893–2910. https://doi.org/10.1007/s10653-019-00359-7 Environ Sci Pollut Res

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