Data on the profile of organic contaminants in the L'Albufera Natural Park (2019–2020). Target and non-target screening

Abstract

This article presents a dataset on 71 pesticide levels and the identification of additional synthetic organic chemicals, including pharmaceuticals and industrial compounds, in L'Albufera Natural Park (Valencia, Spain). Sampling was conducted during May–June (spring) and end of September–October (autumn) 2019, timed to the rice cultivation cycle, the region's main agricultural activity. A total of 130 samples (100 water and 30 sediments) were collected from 51 strategically selected sites, including rivers, irrigation channels, Albufera Lake, and Mediterranean outlets, utilizing a combination of targeted and non-targeted screening (NTS) methods. The dataset encompasses physical-chemical parameters for both spring and autumn seasons. Advanced analytical techniques, such as high-resolution mass spectrometry (HRMS), were employed to detect contaminants beyond traditional methods, providing critical insights for environmental management and policy development. The findings contribute to addressing gaps in knowledge regarding contaminants of emerging concern (CECs) and their distribution across different environmental compartments. These data supplement the findings of the research article “Fingerprinting of Emerging Contaminants in L'Albufera Natural Park (Valencia, Spain): Implications for Wetland Ecosystem Health”.

Specifications Table

Subject	Environmental Sciences – Pollution
Specific subject area	Detection and quantification of pesticides by target and non-target screening (NTS) and identification of other CECs by non-target analysis in L´Albufera Natural Park in water and sediment samples.
Type of data	Raw, Analysed, Filtered Tables, Figures
Parameters for data collection	The mobile phase for pesticides was (A) Water and (B) methanol both with 0.1 % Formic Acid and 5 mM Ammonium formate. The mobile phase for polar compounds using NTS was (A) Water and (B) methanol both with 0.1 % formic acid for positive ionization and 2.5 mM NH4F for negative ionization
Data collection	Data was generated from the analysis of samples of water and sediment obtained in fifty-one sampling points during spring and autumn of 2019. Target analysis and NTS was conducted using a reversed-phase liquid-chromatography (LC) separation employing a Vanquish Flex UHPLC consisted of a binary pump, a split sampler and a column compartment and HRMS using Thermo Scientific™ Orbitrap Exploris™ 120 high-resolution mass spectrometer equipped with a heated electrospray ionization (HESI) source. Targeted compounds were checked manually using the vendor software TraceFinder (version 4.1, Thermo Scientific). NTS results were analysed using Compound Discoverer 3.2 (Thermo Fisher Scientific, Software for HRMS data treatment) implementing the workflow for environmental samples and using mzCloud (On-line) as MS-library. Default workflow was named “Environmental w Stats Unknown ID w Online and Local Database Searches”
Data source location	Institution: University of Valencia, Research Centre on Desertification (CIDE) City/Town/Region: Moncada, Community of Valencia Country: Spain
Data accessibility	Repository name: Mendeley Direct URL to data: https://data.mendeley.com/datasets/n44rpfms7b/1
Related research article	[1] Fingerprinting of Emerging Contaminants in L'Albufera Natural Park (Valencia, Spain): Implications for Wetland Ecosystem Health Yolanda Soriano1,*, Emilio Doñate2, Sabina Asins2, Vicente Andreu1, Yolanda Picó1. Chemosphere

1. Value of the Data

• •The dataset comprises the first detailed open access record of Non-Target Screening (NTS) in surface water and sediments samples in L´Albufera Natural Park.
• •Concentration values of pesticides and identification of anthropogenic chemicals such as industrial compounds and pharmaceuticals can be used by other researchers and local authorities.
• •This data is useful for clearly understand the spatial distribution of contaminants and will help researchers on planning for further research studies within this area and for comparison studies (temporal and spatial ones).
• •The datasets are relevant for performing a more appropriate environmental diagnostic. National and international authorities, wastewater treatment plant managers and researchers could estimate occurrence, transport and fate of emerging contaminants.

2. Background

This dataset supports a related research article that examines the occurrence of pesticides and other compounds in surface water and sediments from L'Albufera Lake (Valencia, Spain). The assessment encompasses several innovative aspects of environmental significance: it establishes the pathways through which emerging pollutants enter the natural wetland using both target and non-target screening (NTS) methods for management purposes, and it identifies specific contamination hotspots through Geographic Information Systems (GIS).

3. Data Description

Samples were collected from fifty-one sampling sites along L´Albufera Natural Park, Valencia, in two sampling campaigns conducted during spring (May-June) and Autumn (September-October), tailored to the rice cultivation season, which is the primary activity in the region. Sampling sites were selected based on the type of land use in the surrounding area. This allowed us to characterize sites with different levels of anthropogenic impact. Fig. 1 shows the location of L´Albufera Natural Park, as well as the location of the fifty-one sampling points.

Fig. 1.

Location of L´Albufera Natural Park, as well as the location of the sampling points and agricultural land use.

The data were saved and stored in Mendeley Data. There are three excel raw data files. A complete folders structure can be seen in Table 1.

Table 1.

Folder structure from Mendeley data link.

File path	File description
Data of the physical-chemical parameters	Excel file that contains raw data on physical-chemical parameters, such as T: temperature, mV: oxidation–reduction potential, CE: conductivity, TDS: Total Dissolved Solids, DO: dissolved oxygen
Result Target and Non-Target WATER	Excel files that contain raw data on pesticides quantified in surface water samples, compounds identified using NTS, Risk Assessment, Modes of Action (MoA)
Result Target and Non-Target SEDIMENT	Excel files that contain raw data on pesticides quantified in sediment samples, compounds identified using NTS, and MoA

Furthermore, within the main text the following Figures and Tables summarizing most important information are provided:

• •Fig. 2 illustrates the grab water samples extraction.
• •Fig. 3 illustrates the sediment extraction for moderately polar compounds.
• •Fig. 4 illustrates the sediment extraction for polar compounds.
• •Table 2 provides information on the instrumentals characteristics used for pesticides (target) determination and Non-Target Screening (NTS).
• •Fig. 5 show the workflow “Environmental w Stats Unknown ID w Online and Local Database Searches” in Compound Discoverer software.
• •Fig. 6 exemplifies the total concentrations of fungicides, herbicides, insecticides, and other compounds by target analysis in water samples in spring (left), autumn (middle) and sediment samples (right).
• •Fig. 7 show the highest median concentrations of quantified pesticides in at least one sampling site in surface water samples.
• •Fig. 8 show the highest median concentrations of quantified pesticides in at least one sampling site in sediment samples.
• •Fig. 9, Fig. 10, Fig. 11 illustrates the spatial distribution of quantified pesticides in two seasons for water samples and in sediment samples for spring based on compound concentrations (ng L⁻¹ or ng g⁻¹) detected in the study sites.

Fig. 2.

Grab water samples extraction.

Fig. 3.

Sediment extraction for moderately polar compounds.

Fig. 4.

Sediment extraction for polar compounds.

Table 2.

Instrumental characteristics used for pesticides (target) determination and Non-Target Screening (NTS).

LC Conditions
Analytical column	Pesticides: Luna C18 (15.0 cm × 0.21 cm) with a 3 µm particle size (Phenomenex, USA) NTA (for positive and negative mode): Kinetex 1.7 µm Biphenyl, 1.7 µm. 50 × 2.1 mm, (Phenomenex, USA)
Column temperature	30 °C
Volume injected	5 µL
Mobile phase	Pesticides: (A) Water – (B) methanol both with 0.1 % Formic Acid and 5 mM Ammonium formate NTS (for positive mode): (A) Water – (B) methanol both with 0.1 % Formic Acid NTS (for negative mode): (A) Water – (B) methanol both with 2.4 mM Ammonium fluoride
Flow rate	Pesticides: 0.4 mL min-1 NTS (for positive and negative mode): 0.2 mL min-1
Linear gradient	Pesticides: 0 min (50 % B), 10 min (83 % B), 12 min (83 % B), 12.5 min (98 % B), 15.5 min (98 % B), 16 min (50 % B), and return to the initial conditions (equilibration time 10 min). NTS (for positive and negative mode): 0 min (30 % B), 12 min (95 % B), 20 min (95 % B), and return to the initial conditions (equilibration time 12 min).

Fig. 5.

Workflow “Environmental w Stats Unknown ID w Online and Local Database Searches” in Compound Discoverer software.

Fig. 6.

Distribution of the total concentrations of fungicides, herbicides, insecticides, and other compounds by target analysis in water samples in spring (left), autumn (middle) and sediment samples (right).

Fig. 7.

Median concentrations (ng L^-1) of quantified pesticides in at least one sampling site in surface water in spring (A) and autumn (B). The color white represents fungicides, blue denotes herbicides, and purple signifies insecticides. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 8.

Median concentrations (ng g^-1) of quantified pesticides in at least one sampling site in sediment samples. The color white represents fungicides, blue denotes herbicides, and purple signifies insecticides. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 9.

Spatial pollution patterns of quantified pesticides in water samples in spring based on compound concentrations (ng L⁻¹) detected in the study sites (data log-transformed, scaled and centered). The color of each cell indicates scaled intensity level increasing from blue to red. Heatmaps were created in R (version 4.3.1) (R package ‘gplots’, function heatmap.2). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 10.

Spatial pollution patterns of quantified pesticides in water samples in autumn based on compound concentrations (ng L⁻¹) detected in the study sites (data log-transformed, scaled and centered). The color of each cell indicates scaled intensity level increasing from blue to red. Heatmaps were created in R (version 4.3.1). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 11.

Spatial pollution patterns of quantified pesticides in sediment samples based on compound concentrations (ng g⁻¹) detected in the study sites (data log-transformed, scaled and centered). The color of each cell indicates scaled intensity level increasing from blue to red. Heatmaps were created in R (version 4.3.1). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

4. Experimental Design, Materials and Methods

4.1. Reagents and chemicals

Solvents used included HPLC grade methanol (LC grade, 99.8 % purity) were purchased from VWR Chemicals® (Radnor, PA, USA) and ammonium formate (NH₄HCO₂), formic acid (CH₂O₂), ammonium fluoride (NH₄F) and acetone (CH₃COCH₃) were purchased from Alfa Aesar (Karlsruhe, Germany). Acetonitrile (ACN) ≥ 99.9 % purity was from Merck (Darmstadt, Germany). High purity water was obtained using a Milli-Q water purification system (Millipore, Milford, MA, USA).

Primary-secondary amine (PSA) and C₁₈ were from Análisis Vínicos (Tomelloso, Spain), magnesium sulfate (MgSO₄) and sodium sesquihydrate citrate [HOC(COOH) (CH₂COONa)₂ 1.5 H₂O] from Alfa Aesar (Karlsruhe, Germany) and sodium chloride (NaCl) and trisodium citrate dihydrate (C₆H₅Na₃O₇ $·$ 2 H₂O) from Prolabovwr (Leuven, Belgium).

The 15 mL and 50 mL polypropylene centrifuge Falcon tubes were from VWR International Eurolab (Barcelona, Spain). Strata-X-33 µm polymeric reversed phase (200 mg/6 mL) were from Phenomenex (Torrance, CA, USA). The 1.5 mL amber glass vials with stoppers 99 mm + Septum Sil /PTFE used to inject the samples were from Análisis Vínicos S.L. (Tomelloso, Spain) and the 250 µL polypropylene inserts were from Agilent Technologies (Santa Clara, CA, United States). Nylon 0.22 µm filters were purchased from Membrane Solutions (Plano, TX, USA). Polypropylene/polyethylene syringes were manufactured by BRAUN and distributed by Scharlab S.L. (Barcelona, Spain). For the solid phase extraction (SPE) Phenomenex Strata-X-33 µm Polymeric Reversed Phase (200 mg/6 mL) cartridges and a vacuum manifold Supelco Visiprep 57,030- U (Sigma-Aldrich, St. Louis, Missouri, USA) were used.

4.2. Samples extraction

The extraction procedures used for the water and sediment samples are shown in Fig. 2, Fig. 3, Fig. 4.

The surface waters (250 mL) were vacuum filtered by a 0.6-µm glass fiber filter (GA-55, 90 mm - Advantec MFS, Dublin, CA, USA) and stored at −20 °C until the analysis. Water samples were extracted using the method previously reported by [2]. The sediments were lyophilized with a Virtis lyophilizer (SP Scientific, Gardiner, NY, USA) and the sediment samples were sieved, and air-dried in the dark at 20 °C to reduce the moisture content. Sediment samples were extracted using the method previously reported by [2,3].

The water quality parameters were measured in situ using a portable multiparametric meter (model HI9829, HANNA Instruments): pH, temperature (T, °C), oxidation–reduction potential (ORP, mV), conductivity (CE, in dS m^-1), Total Disolved Solids (TDS, mg L^-1), NaCl (mg L^-1), Resistivity (Ω) and dissolved oxygen (DO, % and mg L^-1) (These parameters for each sampling points in spring and in autumn are listed in “Data of the physical-chemical parameters”).

Target screening and non-target screening was conducted using a Thermo Scientific™ Orbitrap Exploris™ 120 high-resolution mass spectrometer equipped with a heated electrospray ionization (HESI) source [4]. More information about the instrumental characteristics used for pesticides (target) determination and NTS as well as in the workflow used in NTS in Table 2 and Fig. 5.

5. Results

Out of the 71 compounds included in the target analysis, 43 and 59 pesticides were quantified at least once in water and sediment samples respectively. Herbicides and fungicides represented up to 50 % of the quantified chemicals. The number of quantified pesticides varied across sampling sites with an increase of herbicides from spring to autumn. However, the number of insecticides was higher in the sediment samples than in the water samples (Fig. 6). From a basin-specific perspective, sampling points 38, 40, 42, 48 and 29 exhibited the highest number of quantified pesticides with 26, 26, 26, 27 and 27 quantified pesticides in spring, respectively. While sampling points 42, 44 and 46 exhibited the highest number of quantified pesticides with 27, 26 and 26 quantified pesticides in autumn, respectively. Conversely, sampling points 22 and 39 exhibited the lower number of quantified pesticides (2 and 3 quantified pesticides respectively, in spring). While sampling point 41 exhibited the lower (8 quantified pesticides in autumn).

The highest measured environmental median concentrations of pesticides quantified for the spring are plotted in Fig. 7(A), with the insecticide chlorpyrifos reaching highest concentrations followed by fungicide omethoate and insecticide imazalil as the second and third TOP concentrations, respectively. However, the highest measured environmental median concentrations of pesticides quantified for autumn are plotted in Fig. 7(B), with the insecticide chlorpyrifos reaching highest concentrations followed by fungicide omethoate and herbicide propazine as the second and third TOP concentrations, respectively. The boxplot representation reveals a comparable pattern between the spring and autumn datasets. Instead, the highest measured environmental median concentrations of pesticides quantified in sediment samples are plotted in Fig. 8, with the fungicide azoxystrobin reaching highest concentrations followed by insecticide etofenprox and fungicide tebuconazole as the second and third TOP concentrations, respectively.

Limitations

The list of target chemicals for pesticide analysis in this study was primarily derived from compounds frequently detected in rice fields and citrus crops, as well as those commonly observed within L'Albufera Natural Park.

Ethics Statement

The authors have read and follow the ethical requirements for publication in Data in Brief and confirming that the current work does not involve human subjects, animal experiments, or any data collected from social media platforms.

Credit Author Statement

Yolanda Soriano: Conceptualization, Methodology, Data curation, writing – original draft preparation, Writing – review & editing, Visualization. Emilio Doñate: Writing – review & editing, Visualization. Sabina Asins: Writing – review & editing, Visualization. Vicente Andreu: Methodology, Resources, Writing – review & editing. Yolanda Picó: Conceptualization, Methodology, Reviewing and Editing, Supervision, Project Administration; Funding acquisition.

Data Availability

• Mendeley DataDataset of emerging contaminants in L´Albufera Natural Park (2019–2020) by target and non-target screening using high resolution mass spectrometry (Original data).