Sampling Campaigns Research Articles

Habitat Assessment of Bocachico (Prochilodus magdalenae) in Ciénaga de Betancí, Colombia, Using a Habitat Suitability Index Model

This study evaluates the habitat of the Bocachico fish (Prochilodus magdalenae) in the Ciénaga de Betancí, Colombia, using a habitat suitability index (HSI) model. Wetlands like the Ciénaga de Betancí are under significant pressure from anthropogenic activities, affecting biodiversity and ecosystem health. The Bocachico, a species of immense cultural and economic importance, faces habitat degradation and fragmentation. Using hydrodynamic and water quality data, a numerical model (EFDC+ Explorer 11.5), and field data collected from multiple sampling campaigns, we assessed habitat suitability based on five key parameters: water temperature, dissolved oxygen, ammonia nitrogen, velocity, and depth. The model results indicated that environmental conditions in the wetland remained relatively stable during the dry season, with an average HSI score of 0.67, where 9% of the wetland area displayed acceptable conditions, and the remaining 91% displayed medium conditions. The wet season, on the other hand, had an average HSI score of 0.64, with 7.2% of the area in the acceptable suitability range, and the remaining 92.8% in the medium category. Variations in HSI were primarily driven by ammonia nitrogen levels, water velocity, and depth. Despite limited fluctuations in the HSI, areas of low suitability were identified, particularly in regions impacted by human activities. These findings have practical implications for conservation strategies, providing valuable insights for the sustainable management and conservation of the Ciénaga de Betancí, informing strategies for improving habitat conditions for the Bocachico, and supporting wetland restoration efforts.

Cytogenetic and photosynthetic responses of plants after exposure to water from a lake environment.

Plants are sensitive to environmental pollutants and are excellent organisms for genetic and physiological testing. Plant-based test systems are often used to study aquatic, aerial, and terrestrial pollution, especially Allium cepa, but studies with Tradescatia pallida specimens have gained prominence due to their sensitivity and applicability. Among the biomarkers, cytogenetic damage and chlorophyll levels are used in stress studies due to their responses to single or combined factors. The aim of this study was to evaluate cytogenetic and photosynthetic responses in T. pallida, and cytogenetic responses in A. cepa exposed to water from three sampling stations in the Juara lagoon (Municipality of Serra, ES, Brazil), collected in two sampling campaigns. The cytotoxic, genotoxic, and mutagenic potentials were analyzed using the T. pallida root tip mitosis assay and the Allium cepa test. Chloroplast pigment levels were measured in T. pallida leaves after chronic exposure to the lagoon water. The cytogenetic tests showed cytogenetic alterations at two sampling stations in at least one sampling campaign, suggesting the presence of potential pollutants, the effects of which were maximized during the rainy season. The study of photosynthetic metabolism in T. pallida showed a relationship between the levels of chloroplast pigments and the amount of nutrients present in the water.

Airborne DNA: State of the art - Established methods and missing pieces in the molecular genetic detection of airborne microorganisms, viruses and plant particles.

Bioaerosol is composed of different particles, originating from organisms, or their fragments with different origin, shape, and size. Sampling, analysing, identification and describing this airborne diversity has been carried out for over 100 years, and more recently the use of molecular genetic tools has been implemented. However, up to now there are no established protocols or standards for detecting airborne diversity of bacteria, fungi, viruses, pollen, and plant particles. In this review we evaluated commonalities of methods used in molecular genetic based studies in the last 23 years, to give an overview of applicable methods as well as knowledge gaps in diversity assessment. Various sampling techniques show different levels of effectiveness in detecting airborne particles based on their DNA. The storage and processing of samples, as well as DNA processing, influences the outcome of sampling campaigns. Moreover, the decisions on barcode selection, method of analysis, reference database as well as negative and positive controls may severely impact the results obtained. To date, the chain of decisions, methodological biases and error propagation have hindered DNA based molecular sequencing from offering a holistic picture of the airborne biodiversity. Reviewing the available studies, revealed a great diversity in used methodology and many publications didn't state all used methods in detail, making comparisons with other studies difficult or impossible. To overcome these limitations and ensure genuine comparability across studies, it is crucial to standardize protocols. Publications need to include all necessary information to enable comparison among different studies and to evaluate how methodological choices can impacts the results. Besides standardization, implementing of automatic tools and combining of different analytical techniques, such as real-time evaluation combined with sampling and molecular genetic analysis, could assist in achieving the goal of accurately assessing the actual airborne biodiversity.

The Great Lakes Winter Grab: Limnological data from a multi‐institutional winter sampling campaign on the Laurentian Great Lakes

AbstractInterest in winter limnology is growing rapidly, but progress is hindered by a shortage of standardized multivariate datasets on winter conditions. Addressing the winter data gap will enhance our understanding of winter ecosystem function and of lake response to environmental change. Here, we describe a dataset generated by a multi‐institutional winter sampling campaign across all five Laurentian Great Lakes and some of their connecting waters (the Great Lakes Winter Grab). The objective of Winter Grab was to characterize mid‐winter limnological conditions in the Great Lakes using standard sample collection and analysis methods. Nineteen research groups sampled 49 locations varying widely in depth and trophic status, collecting a range of limnological data. This dataset includes physical, chemical, and biological measurements. These data can be used to examine diverse aspects of Great Lakes ecosystems or integrated with winter observations from other lakes to improve understanding of winter limnology across different aquatic systems.

Health Risk Assessment of Trace Elements in Surface Water from Dayat Roumi Lake, Morocco

To assess the human impact on the water of Dayat Roumi Lake and to develop effective management strategies to protect and restore this vital ecosystem in the region, seasonal sampling was carried out at six stations distributed around the lake. During these sampling campaigns, 24 parameters were measured, including 20 trace elements. Results showed that measured levels of trace elements increased in the following order: Cd < Be < Tl < Co < Sb < Mo < Cu < Zn < Ni < V < Rb < Mn < As < Cr < Pb < Li < Ba < Se < Pd < Sr in the lake water and that these recorded values were lower than those recommended by the Moroccan standard and the World Health Organization, except for Pb and Se. Correlation analysis revealed two principal water-contamination sources: natural geological origins and anthropogenic inputs. In addition, the Water Quality Index WQI showed that the lake’s water quality is poor, and its use can be dangerous for human and animal health. Health risk assessment associated with prolonged exposure to trace elements in lake water revealed that the Hazard quotient HQ and Hazard index HI of certain elements, such as Tl, Sb, V, As, Cr, Pb, Li, and Se, are higher than 1 in adult and children, indicating a significant risk for people living near the lake. Children are particularly vulnerable, with higher levels of HQ and HI, and selenium poses a substantial risk to their health through ingestion and skin absorption. In both adults and children, the total risk of cancer due to metals is classified as follows: CI (Cr) > CI (Ni) > CI (As) > CI (Pb) > CI (Cd). The Cr presents the highest carcinogenic risk—by ingestion or dermal route—in both groups. The total risk for these five metals exceeds 1 × 10−4, indicating a danger for residents who drink or swim in the lake.

Nitrate Loads From Land to Stream Are Balanced by In‐Stream Nitrate Uptake Across Seasons in a Dryland Stream Network

AbstractExploring nitrogen dynamics in stream networks is critical for understanding how these systems attenuate nutrient pollution while maintaining ecological productivity. We investigated Oak Creek, a dryland watershed in central Arizona, USA, to elucidate the relationship between terrestrial nitrate (NO3−) loading and stream NO3− uptake, highlighting the influence of land cover and hydrologic connectivity. We conducted four seasonal synoptic sampling campaigns along the 167‐km network combined with stream NO3− uptake experiments (in 370–710‐m reaches) and integrated the data in a mass‐balance model to scale in‐stream uptake and estimate NO3− loading from landscape to the stream network. Stream NO3− concentrations were low throughout the watershed (<5–236 μg N/L) and stream NO3− vertical uptake velocity was high (5.5–18.0 mm/min). During the summer dry (June), summer wet (September), and winter dry (November) seasons, the lower mainstem exhibited higher lateral NO3− loading (10–51 kg N km−2 d−1) than the headwaters and tributaries (<0.001–0.086 kg N km−2 d−1), likely owing to differences in irrigation infrastructure and near‐stream land cover. In contrast, during the winter wet season (February) lateral NO3− loads were higher in the intermittent headwaters and tributaries (0.008–0.479 kg N km−2 d−1), which had flowing surface water only in this season. Despite high lateral NO3− loading in some locations, in‐stream uptake removed >81% of NO3− before reaching the watershed outlet. Our findings highlight that high rates of in‐stream uptake maintain low nitrogen export at the network scale, even with high fluxes from the landscape and seasonal variation in hydrologic connectivity.

Citizen-Based Water Quality Monitoring: Field Testing a User-Friendly Sensor for Phosphate Detection in Global Surface Waters.

Widespread concern over surface water pollution has led to interest in developing easy-to-use accurate tools for citizen-based measurements that provide high spatial and temporal resolution while maintaining accuracy. Excessive anthropogenic phosphate significantly contributes to global eutrophication and necessitates regular on-site phosphate monitoring in surface waters. Traditional instrumentation for quantifying phosphate is labor-intensive, expensive, and performed in laboratories. Existing on-site testing methods relying on phosphomolybdenum blue (PMB) have limited sensitivity and stability under ambient conditions. To overcome these limitations, a novel low-cost, rapid, and user-friendly sensor for citizen-led phosphate monitoring in surface water is introduced and demonstrated with a global sampling campaign. The fast-flow microfluidic device provides user-friendly operation, achieving an environmentally relevant limit of detection (LoD) of 190 ppb, which is near the EPA-recommended maximum for phosphate. The dip-and-read operation reduces procedural steps while delivering accurate sample volume, making it well-suited for citizen-led science initiatives. This sensor exhibits high selectivity and prolonged stability for two months under ambient conditions. The sensor's performance was validated using the industry-standard UV-Vis method with 90% correlation. More than 1000 sensors were deployed in different continents, facilitating phosphate mapping in diverse water sources across multiple continents. The initiative covered much of the globe, including Thailand, Nepal, Brazil, Chile, the USA, and Germany. In some cases, phosphate levels exceeded legislative guidelines by 100-fold. Through the collaboration of citizen scientists, we analyzed regional topography and socioeconomic practices near water sources, identifying potential sources that could contribute to eutrophication in these areas.

Spatial and seasonal variations in trace metals in marine sediments from the Dubai coastal environment.

This study was conducted to assess sediment trace metals (Cd, Cr, Cu, Pb, Ni and Zn) contamination using a systematic approach by collecting sediment samples from 8 transects along the Dubai coastline, each 10 km long, and each transect included its nearshore sediment sampling station. Additionally, 10 sediment samples were collected from the Dubai creek and other potential sources of metal pollution. The sediment samples were collected in December and again in August. However, no significant difference in sediment metal concentration was found between the two sampling campaigns. The sediment trace metal concentrations (0.92-1.31mg Cd/kg, 2.82-176.6mg Cr/kg, 2.27-621.67mg Cu/kg, 0.88-23.6mg Pb/kg, 1.92-192.2mg Ni/kg and 9.1-391.05mg Zn/kg) showed considerable variability, except for Cd (1.08 ± 0.06mg/kg, 5.55% variability). Despite this, no significant differences in sediment metal concentrations were found between the sampled transects. However, significant variations in Cr, Cu, Pb and Zn were evident between distances from the shoreline to offshore stations along the Dubai coast, and the nearshore locations presented clear evidence of elevated/maximum sediment metal concentrations. Most of the sediment trace metal concentrations, however, were found well within the sediment quality guidelines (SQGs) for nearshore sediments. Trace metal contamination hotspots, nonetheless, were identified at some nearshore stations as determined by metal level exceedance over the SQGs, background levels and the pollution load index, with limited potential ecological risk. Overall, the findings suggest that sediments in the Dubai coastal environment are mainly influenced by anthropogenic activities in stations located in the proximity of ship maintenance, ports, and industrial areas such as Dry Dock, Jaddaf, Jebel Ali Port, Wharfage, Hamriya and DUBAL.

Estimation of the Hydraulic Parameters of a Stratified Alluvial Soil in the Region of El Haouareb—Central Tunisia. Experiments, Empirical, Analytical and Inverse Models

Modeling water flow and contaminant transport in the unsaturated zone is a difficult task that relies heavily on good hydrodynamic soil characterization. This article presents a complementarity between experimentation, direct modeling and inverse modeling in order to provide a better estimate of the hydrodynamic parameters of stratified alluvial soil in the El Haouareb region of the Kairouane plain in Tunisia. A field sampling campaign was carried out. The samples collected underwent particle size analysis, bulk density measurements and infiltration tests using a mini-Muntz. In parallel, simple evaporation tests were applied to separate strata. In addition, a 2 m soil column was reconstituted and fitted with sensors to monitor water content, tension, temperature and electrical conductivity. An internal drainage test was performed on this monolith. Three methods were applied using experimental data to estimate soil hydrodynamic parameters. In the first method, pedotransfer functions were used (Rosetta platform) based on granulometric results and bulk density. In the second, water tension and water content monitored during the simple evaporation test were used to plot the soil–water retention curve (SWRC) using SWRC-Fit. In the third method, inverse modeling was applied to the internal drainage test. A comparison of the results showed that the inverse method had the lowest RMSE. Uncertainty analysis has been implemented for both the experimental and numerical set up.

Enhancing Soil Texture and Bulk Density Mapping Using Soil Grids and Machine Learning: A Comparative Analysis with Observed Data

Digital soil mapping plays a crucial role in understanding soil variability and informing sustainable land management practices. This study focuses on the Kurdistan Region of Iraq (KRI), evaluating the accuracy of SoilGrids, a global-scale soil mapping initiative, and exploring the efficacy of machine learning algorithms in refining soil properties estimations. The aim of this research was to assess and represent the physical parameters of soils effectively by comparing ground truth soil sampling data with data obtained from SoilGrids regarding clay, silt, and sand fractions and bulk density. Comparative analyses were conducted between ground truth soil sampling data and SoilGrids predictions, revealing significant differences across soil mineral fractions including clay, silt, sand fractions, and bulk density. The results showed that the mean clay fraction in the ground truth dataset differed notably from SoilGrids estimation, with a Mean Absolute Deviation (MAD) of 124.0 g kg-1 and Root Mean Square Error (RMSE) of 152.5. However, the integration of machine learning algorithms, particularly the Extreme Gradient Boosting (XG Boost) algorithm, showed promising results in improving accuracy. The XG Boost algorithm exhibited a relatively low MAD of 97.9 g kg-1 for clay fractions, indicating a better approximation of observed values compared to SoilGrids. Significant percent improvements in RMSE and Mean Absolute Percentage Error (MAPE) values were observed across soil fractions and bulk density measurements, ranging from approximately 15% for clay to 35% for sand fractions and 20% for bulk density. These findings highlight the importance of integrating advanced mapping techniques and machine learning algorithms to enhance soil mapping methodologies. Moving forward, efforts to expand ground truth datasets through targeted soil sampling campaigns and develop international collaboration initiatives will be crucial for improving the accuracy and reliability of soil mapping products in the KRI. By incorporating advanced mapping approaches, we can better support sustainable land management practices and environmental conservation efforts in the region.

Diversity of fish otoliths from the Gulf of Mexico and the Caribbean Sea: Report on the first digital collection of fish otoliths (Actinopterygii) from the Atlantic region of Mexico

The Otolith Collection of Fishes from the Gulf of Mexico and Caribbean Sea was created with the objective to conserve and illustrate the diversity of these structures from species living in the Gulf of Mexico, the Caribbean Sea, and the freshwater and brackish systems of the Yucatan Peninsula, incorporating morphological descriptions and morphometric data. Otoliths, non-skeletal calcareous structures that develop in the inner ear of fish, are essential for balance and hearing. They have become pivotal tools for age and growth determination, population analysis, and ecological, trophic, and archaeological studies due to their resistance to degradation and the extensive information they provide about the environment and physiology of fish. The collection now includes otoliths from 214 species, representing 67 families, obtained through sampling campaigns and collaborations with local fishermen. The otoliths are extracted using techniques that ensure the integrity of the structures for later preservation. High-resolution images were obtained using optical and scanning electron microscopy, and these images are stored in an online database. This database facilitates research and teaching by providing public access to digital specimens and associated data. In addition to fostering academic development, this collection represents a significant step towards the creation of a national platform for otolith data analysis, aligned with international efforts to digitize biological collections. Despite the financial and logistical challenges involved in building and maintaining biological collections, this collection demonstrates its value as an essential resource for taxonomic, systematic, and ecological studies, as well as for biodiversity education and awareness. The online availability of the collection not only facilitates access to data but also promotes innovation and international collaboration in the study of fishes and their habitats.

Quantification, characterization, and source identification of macro- and mesoplastics in the water column of Rivers Sabaki and Tana.

Five sampling campaigns were conducted in the water columns of River Sabaki and Tana in Kenya, Between October 2021 and January 2023, covering a 1-year cycle, at four sites in River Sabaki (2.5km, 3.05km, 3.51km, and 4.52km) and River Tana (1.5km, 1.8km, 2.0km, and 2.5km) distant from the river mouth. The ebb and flood tides were sampled to calculate net plastic litter fluxes. Two 6350-µm seine nets were deployed in two replicates per sampling point. Factor and cluster analysis were used to investigate plastic litter sources for both rivers. The influences of rainfall on plastic abundance and mass were explored using permutational linear models. A total of 15,318 plastic litter items weighing 1.37kg were recorded in River Sabaki, and 3741 plastic litter items weighing 0.95kg in River Tana. The top ten captured plastic litter types sorted by abundance and mass were mostly plastic fragments. The annual net plastic litter flux to the ocean through River Sabaki amounted to 1,277,120.63 items year-1 by abundance and 22.30kgyear-1 by mass. For River Tana, the same fluxes were 207,550.76 items year-1, and 28.09kgyear-1, respectively. In River Sabaki, significant impacts of rainfall on plastic abundance and mass were found. River Sabaki's pollution sources included upstream reaches, fishing activities, and littering by locals and tourists. River Tana's major pollution sources were illegal dumpsites, littering, fishing, and recreational activities. This research can guide combat plastic pollution in the rivers and ultimately the ocean.

Exploring Spatial Dynamics of Water Quality in a Tropical Lake Affected by Aquaculture

Lake Maninjau, like many surface water bodies worldwide, faces significant water pollution challenges due to extensive aquaculture activities, making it an ideal site to study the impact of fish farming on water quality, which has contributed to eutrophication and declining water quality. This study investigates the physicochemical parameters and pollution levels in the lake, aiming to provide insights into its environmental health. In August 2022, a comprehensive sampling campaign was undertaken at nine stations within the upper layers of open water and littoral zones of Lake Maninjau. In situ measurements, including temperature, dissolved oxygen, and pH, were conducted, accompanied by water sample collection for laboratory analysis of trace elements and heavy metals. Our study revealed notable variability in water parameters across different sites, with surface water layers exhibiting the greatest differences. While certain parameters such as temperature and conductivity remain relatively stable, pH levels show a decreasing trend with increasing water depth. Dissolved oxygen levels vary widely, while oxidation–reduction potential indicates water pollution, particularly in littoral zones. Potassium dominance within cations likely suggests anthropogenic influences, notably from aquaculture activities, that may also contribute to nutrient enrichment and heavy metal pollution. Elevated levels of total nitrogen and ammonia underscore the lake’s moderate pollution levels, with heavy metals such as mercury exceeding permissible limits, posing risks to aquatic life and human health.

Estimation of carbon stocks in the areas of a seasonally dry tropical forest in the Brazilian semi-arid region

In addition to its ecological importance, the Caatinga biome, one of the most extensive seasonally dry tropical forests (SDTF) in the world, has a relevant socioeconomic role as it is used as a primary natural resource by local communities. However, inadequate ecosystem management practices have resulted in gradual loss of natural vegetation in this ecosystem. Carbon stock estimation is a parameter that can contribute as a support tool for managing and maintaining the few remaining natural vegetated areas. In this study, we calibrated and validated the CENTURY model to simulate carbon stocks in areas of the Caatinga, in the state of Pernambuco, and compared the predictive capacity of the CENTURY model with available estimates. In the validation dataset, the average for biomass stocks was 33.1 Mg C ha−1, this value is close to those observed in the literature for the region. The model also performed well when estimating carbon stocks in the soil (r2 = 0.79, p = 0.017). Ecosystem modeling combined with Geographic Information Systems (GIS) is a promising tool for estimating carbon stocks in the Caatinga, where field sampling campaigns are generally expensive and have scarce research funding opportunities. Furthermore, it also allows the evaluation of the effect of environmental changes on C stocks in long-term studies, which is essential for creating and implementing public policies to mitigate and adapt to the impacts of climate change on the ecosystem. However, additional efforts are needed to improve C estimates, especially in areas with a strongly negative water balance.

Modeling Urban Temperature Using Measurements from Mobile and Stationary Monitoring Stations

Heat waves are occurring more frequently worldwide as global warming continues, and urban heat islands can threaten conventional life in cities. Measuring, analyzing, and simulating weather data at fine spatial and temporal scales are essential to prevent and reduce the damage caused by extreme heat waves. In urban environments, handling complex micrometeorological situations using current meteorological stations and global simulation models (e.g., weather research forecasting models) is challenging. In this study, the thermal environments of urban areas were measured using a mobile meteorological measurement platform. Both mobile and stationary datasets were incorporated into the meteorological modeling process to simulate the spatial and temporal distribution of temperature. Additionally, various mobile observation implementation scenarios for temperature modeling were examined. We compared simulation combinations with the temperature field generated from the total dataset to obtain a better sampling campaign and properly incorporate mobile data scenarios. When collecting mobile data, it is important to consider spatial features to improve the efficiency of sampling programs. This can substantially reduce the cost of mobile data collection, together with the sensor error bound.

Domestic and irrigation water quality on the southern slopes of Mount Kilimanjaro

This study assessed the water quality for drinking and irrigation purposes on the southern slopes of Mt. Kilimanjaro during the dry season under low flow conditions. Fifty-one samples covering eight different water sources (i.e., stream water from natural and anthropogenic impacted streams, domestic water, spring water, rainfall, groundwater, lake water and water from irrigation canals) were collected in a snapshot sampling campaign over 10 days in February 2023. First, physical, chemical and biological parameters were analysed and compared with Tanzanian and international drinking and irrigation water quality requirements. The samples were then ranked according to their suitability for drinking and/or irrigation using water quality indices (WQI). All drinking water quality parameters except for E. coli and turbidity were within the permissible limits. A generalised problem of faecal contamination was found in the study area, including in domestic water, highlighting the need to identify sources of contamination and remediate them before distribution. The drinking water quality index (DWQI) classified 89% of the samples as unsuitable and 11% as excellent for drinking. Irrigation water quality parameters were within the guidelines of restriction of use except for pH in 5 samples. In contrast to the DWQI, the vast majority of the water samples (88%) can be used for irrigation without restrictions according to the irrigation water quality index (IWQI). The suitability of water for irrigation was also assessed using three indices, i.e., Kelley’s Index, Soluble Sodium Percentage and Magnesium Ratio, which indicated potential problems with excess of sodium (about 30% of the samples) and magnesium (about 20%). Further studies combining suitability indices, soil characteristics and crop types are recommended to assess water quality for irrigation use.

Origin and distribution of clay minerals in semi-arid Sahelian soils: case of Kori Ouallam watershed, south-western Niger

Abstract This study examines the origin and distribution of clay minerals of the pedological horizons of Kori Ouallam watershed (south-western Niger). It is based on field sampling campaigns and a series of laboratory analyses. A total of 49 samples were analysed, 28 from surface horizons (0–10 cm depth) and 21 from pedological profiles (0–1 m depth). The samples were analysed by X-ray diffraction on bulk and clay (<2 μm) fractions, X-ray fluorescence spectrometry, laser granulometry, organic matter and calcium carbonate content, macroscopic observations (binocular loupe) and scanning electron microscopy equipped with an energy-dispersive spectrometry system. The pedological horizons are characterized by low organic matter contents (<1%) and no calcium carbonate. The particle-size distribution shows net textural differentiation, with a predominance of sandy loam to sandy clay loam textures in the upper horizons and clay loam to clay in the deep horizons. The main major oxides were SiO2 (46.3–89.0%), Al2O3 (5.0–24.2%) and Fe2O3 (1.0–27.9%). Kaolinite (64–98%) is the predominant clay mineral at all horizons, associated with low to moderate proportions of illite (1–34%) and traces of chlorite. Kaolinite is essentially inherited from the parent rock, whereas illite results from chemical alteration by bisialitization of the primary minerals initially rich in potassium feldspar contained in the parent rock. However, soil texture and organic matter vary independently with clay mineralogy. An extended study of all of the pedological facies that make up south-western Niger, combined with supplementary analyses, would further improve our understanding of clay mineralogy in the Sahelian zone.

Nutrient enrichment—but not warming—increases nitrous oxide emissions from shallow lake mesocosms

AbstractShallow lakes and ponds play a crucial role in the processing of carbon and other nutrients. However, many lakes and ponds worldwide are affected by climate change and nutrient pollution. How these pressures affect the emission of the greenhouse gas nitrous oxide (N2O) is unclear. Warming and eutrophication are expected to increase the production and emission of N2O in lakes and ponds, but changes in ecological structure and function may complicate these seemingly straightforward relationships. In this study, we used the world's longest running, mesocosm‐based, freshwater climate change experiment to disentangle the effect of nutrient enrichment and warming on N2O emissions. We gathered a large dataset on N2O concentrations and ancillary variables, comprising three sampling campaigns between 2011 and 2020 and a total of 687 individual mesocosm measurements. Our results demonstrated that nutrient enrichment increased N2O emissions, while warming (+2.5–4.0°C and +3.75–6.0°C) had no discernable effect. Our study indicates that curtailing nitrogen influxes into lakes and ponds is the most effective strategy to minimize N2O emissions, and while warming may influence N2O emissions, it does not appear to be a direct driver. These findings underscore the importance of prioritizing nitrogen mitigation efforts to curb N2O emissions from shallow lakes and ponds.

An Integrated Field Study of Turbulence and Dispersion Variations in Road Microenvironments.

Traffic-related air pollutants (TRAPs) emitted from vehicle tailpipes disperse into nearby microenvironments, posing potential exposure risks. Thus, accurately identifying the emission hotspots of TRAPs is essential for assessing potential exposure risks. We investigated the relationship between turbulent kinetic energy (TKE) and pollutant dispersion (D) through an integrated field measurement. A five-year near-road sampling campaign (5 min based) near a light-duty vehicle-restricted roadway and an on-road sampling campaign (5 s based) on isolated proving grounds were conducted. The D was first calculated based on vehicle emission and pollutant concentrations and then paired with TKE measurements. Here, 198 near-road and 377 on-road measurement pairs were collected. In the near-road measurements, TKE and D showed a positive relationship (R2 ≥ 0.69) with the vehicle flow rate, while they showed similar decay patterns and sensitivity to vehicle types in the on-road measurements. A relationship between TKE and D (TKE-D) was developed through these measurements, demonstrating a robust correlation (R2 ≥ 0.61) and consistent slope values (1.1-1.3). These findings provide field evidence for the positive association between TKE and D, irrespective of the measurement techniques or locations. The TKE-D relationship enables vehicle emission estimation with TKE as the sole input, facilitating the identification of emission hotspots with high spatiotemporal resolution.

Assessing pesticide residue occurrence and risks in the environment across Europe and Argentina

The widespread and extensive use of pesticides in European crop production to reduce losses from weeds, diseases, and insects may have serious consequences on the ecosystem and human health. This study aimed to identify 20 active substances of high health risk, based on their detection frequency within and across the environmental matrices (soil, crop, water, and sediment) and to identify their associated hazardous effects. A sampling campaign was conducted across 10 case study sites in Europe and 1 in Argentina and included conventional and organic farming systems. In 31% of cases, the detected substances were found at a higher concentration in the soil than in the corresponding crops, 93% of the compounds were fungicides, and the remainder were insecticides. 43% of the substances, 57% of which were insecticides, were detected only in soil. There was a clear relationship between soils and crops in terms of contamination, but not between water and sediment. Portuguese soil (wine grapes) had the highest number of substances (12) with average concentrations (AC) varying between 1 and 162 μg/kg, followed by French (11 substances in wine grapes) (1≤AC≤64 μg/kg) and Spanish soils (9 substances in vegetables) (3≤AC≤59 μg/kg). The crops corresponding to these soils contained a relatively high number of detected substances and several in high average concentrations (AC). The risk quotient was consistently higher for conventional farms than for organic farms. For the soils from conventional farms, 5 active substances (chlorpyrifos, glyphosate, boscalid, difenoconazole, lambda-cyhalothrin, and one metabolite: AMPA) were considered high risk. For water samples, 2 substances (dieldrin and terbuthylazine) found were high risk, and for sediment, there were 3 substances (metalaxyl-M, spiroxamine, and lambda-cyhalothrin). There were 6 substances detected in crops that are suspected to cause human health effects. Uncontaminated soil is a prerequisite for the adoption of sustainable alternatives to pesticides. Efforts are needed to elucidate the unknown effects of mixtures, including biocides and banned compounds in addition to the substances used in agriculture.