Science of the Total Environment最新文献

Along some Mediterranean coastal areas and other world regions, nutrient and chlorophyll concentrations often show gradient increases of up to one order of magnitude perpendicular to the coast. This nearshore stripe, extending a few hundred meters from the coast, is enriched by submarine groundwater discharges (SGD) containing elevated nutrient concentrations that may eventually sustain high biomass phytoplankton blooms. During a survey carried out in the summer of 2018, we examined the short-term (hours) variability of the phytoplankton biomass (measured as chlorophyll; Chl) in response to environmental changes associated with SGD and wind forcing in the nearshore waters of Palma Beach (Mediterranean Sea). Continuous CTD records revealed a general salinity decline indicative of SGD along the shoreline. Large and pulsed salinity fluctuations (i.e. 2-3 psu variations, 1-4 h) were observed each day that were consistent with offshore advection episodes of the lower salinity water retained in the nearshore (peak crosshore velocity 5-6 cm s^-1). Chl near the shoreline was markedly higher than offshore (3.55 ± 1.29 and 0.68 ± 0.27 mg m^-3 respectively) but recurrently fluctuated in the afternoon to up to >7 mg m^-3. Primary production estimations showed that despite the higher production in the nearshore (50.29 ± 10.98 μmol O₂ L^-1 d^-1, 4-fold offshore values) productivity per unit chlorophyll did not significantly vary (p > 0.01) therefore suggesting that, at this time scales, high biomass episodes in the nearshore are driven by an accumulation mechanism. Statistical analysis (CCA) demonstrates that Chl variability is largely explained (93 %) by variations in wind and current velocity. Our results provide evidence that the dynamics of this nearshore environment are modulated by the interplay between the shoreward wind-induced flow and the offshore directed density flow. This mechanism could explain the occurrence and episodic nature of high biomass blooms in the nearshore, as well as be an important factor influencing the microbial community structure at the coastal zone.

Although woodpeckers are known to forage in decaying trees, their contribution to internal wood decay is not well known. In this sense, non-destructive techniques for structural wood degradation provide an opportunity to quantitatively assess the role of woodpeckers in tree decay. We used sonic tomography to test that the trunks of living trees pecked by Magellanic woodpeckers show pronounced decay, which accelerates under environmental conditions favorable to wood-decaying fungi. The internal decomposition of wood and its decay rate were measured over four years on 156 living southern beech (Nothofagus) trees belonging to four dominant species of southern temperate forests in northern Patagonia. Half of these live trees had woodpecker feeding holes, while the rest served as controls. The percentage of decayed wood, although not severely decayed, increased in sections with the presence of woodpecker holes, but was also influenced by temperatures and biophysical variables such as elevation and topography. The trunk sections with woodpecker holes and exposed to intensive foraging showed accelerated inter-annual decay. Woodpecker foraging activity interacted with vegetation characteristics, resulting in accelerated wood decay in forest sites with an open canopy and exposed to water stress. Thus, sonic tomography provided evidence of a close relationship between woodpeckers and internal wood decomposition, suggesting a positive feedback mechanism regulated by forest disturbance. The approach used here can be extended to gain insight into the influence of woodpeckers on tree decay and mortality in regions experiencing severe drought and forest degradation, such as northern Patagonia.

Corn straws can produce bioethanol via simultaneous saccharification and co-fermentation (SSCF). However, identifying optimal combinations of operating parameters from numerous possibilities through a cost-effective strategy to improve SSCF efficiency and yield remains challenging. The eXtreme Gradient Boost (XGB) and deep neural network (DNN) models were constructed to accurately predict ethanol yield from only five input variables, achieving >83 % accuracy. Subsequently, the XGB and the DNN models were merged with the genetic algorithm (GA) as the new optimization strategies. Experimental validation showed that the new strategy optimize the efficiency and yield of the SSCF ethanol production system quickly and accurately. Moreover, the potential optimization mechanism was investigated through the comprehensive interpretability analysis for XGB and the microbial ecology analysis. Enzyme Solution Volume (61.7 %) dominated, followed by time (12.9 %), substrate concentration (10.4 %), temperature (7.7 %), and inoculum volume (7.3 %). This efficient and accurate algorithm design strategy can significantly reduce the time required to optimize biochemical systems.

Land Surface Temperature (LST) is a crucial parameter in studies of urban heat islands, climate change, evapotranspiration, hydrological cycles, and vegetation monitoring. However, conventional satellite-based approaches for LST retrieval often require additional data like land surface emissivity (LSE). Meanwhile, traditional machine learning (ML) techniques face challenges in acquiring representative training data and leveraging data from varied sources effectively. To address these issues, we introduce a novel transfer-learning (TL) neural network approach for LST retrieval using top-of-atmosphere (TOA) reflective and emissive data from Landsat. This method not only improves LST retrieval by integrating various data types but also demonstrates the potential of shortwave data in surrogating LSE information, thereby reducing dependence on explicit LSE data. Our TL approach utilized extensive simulations from the radiative transfer model (RTM) and measurements from the real world. The simulations are comprehensive, covering a wide range of atmospheric and surface scenarios, and the inclusion of real-world data mitigates the discrepancy between simulations and actual observations. When applied to a decade of Landsat-8 observations and ground measurements from 241 stations across diverse regions, our TL method significantly outperforms ML, single-channel (SC), and split-window (SW) algorithms in terms of root mean square error (RMSE), with improvements of 0.46 K, 0.84 K, and 0.57 K, respectively. This superiority underscores the advantage of integrating simulated and observed data, as well as the benefit of utilizing both reflective and emissive data without relying on uncertain LSE inputs. Our findings present a promising new TL framework for estimating LST directly from TOA data, offering a robust approach that we have made publicly available through Google Earth Engine (GEE) for broader use. The LST data retrieved by our proposed method can provide valuable insights for environmental research.

The immobilization of phosphorus (P) in sediments plays a pivotal role in managing lake eutrophication over the long term. Therefore, key factors that may cause uncertainties in P fixation are of increasing interest to researchers. Calcium‑aluminum composites (CA) can passivate sediment P well; however, the effect of cyanobacterial bloom decline on their sediment P remediation remains unclear. In this study, CA addition significantly reduced P equilibrium concentration as well as augmented P adsorption capacity of sediment characterized as cyanobacterial dominance zone (CDZ). The results of the simulated experiments on cyanobacterial bloom decline indicated that the algae decomposition led to a rapid decrease in dissolved oxygen (DO) level, and to release amounts of P, thus increasing the P concentration in the overlying water. The released algal P into the sediment primarily encouraged the formation of iron-bound phosphorus (Fe-P), followed by calcium-bound phosphorus (Ca-P). The subsequent anaerobic incubation led to a notable release of the newly formed Fe-P, strengthening the anaerobic P release from sediments. Conversely, CA-capping accelerated the adsorption of algal P by sediments, and promoted the formation of Ca-P in sediment from cyanobacterial P, hindering the generation of reactive Fe-P. Moreover, during subsequent anaerobic incubation, the P forms in sediments capped with CA remained stable, showing no obvious P release. These findings suggested that CA capping induced the formation of stable P from algal P and disrupted the positive feedback effect between P contamination in sediments and cyanobacterial blooms, which would provide valuable insights for the remediation of sediments in CDZ.

Runoff variations shape the dynamics of the estuarine environmental factors, profoundly influencing the nitrogen cycle in estuarine sediments. However, our understanding of how these changes regulate microbially-mediated nitrogen removal processes remains limited. In this study, the impacts of changes in environmental factors caused by normal and low runoffs on denitrification and anammox in sediments of the Liao River Estuary in China, were investigated, using continuous-flow experiments combined with ¹⁵N tracing techniques and molecular methods. Results indicated that denitrification was the main nitrogen removal process in estuarine sediments under both runoff conditions. Elevated salinity under low runoff condition increased the abundance of nitrifying bacteria (Nitrospina, Nitrosomonas and Nitrosomonadaceae), thereby promoting the coupled nitrification-denitrification nitrogen removal process. Furthermore, seawater intrusion under low runoff contributed to dilute nitrite concentrations, resulting in decreased denitrification rates in sediments. Overall, this study highlighted the impacts of runoff variations on biological nitrogen removal process through affecting environmental factors, gene abundance and microbial community in the estuary.

Numerous studies have shown that the cooling efficiency (CE) of urban trees varies by cities with different climate backgrounds, and recent research further indicated that there may be large within-city variations in CE. However, how such within-city variations differ across cities, and their relations to the local percent of urban tree canopy (Ptree) remain poorly understood. This study aims to fill this gap based on a comparison study across 118 cities with different biomes and climates in the continental USA. We used the tree canopy layer of the National Land Cover Dataset (NLCD) 2011 to measure urban tree canopy (UTC), and calculated land surface temperature (LST) based on Landsat thermal bands. We found: 1) CE had larger within-city and cross-city spatial variations in cities located in arid and semi-arid biomes. 2) CE was related to Ptree in nonlinear ways in >90 % of the study cities. In most cities (approximately 70 %), CE had an L-shaped relationship with Ptree, showing that CE first declined quickly with the increase of Ptree, but then gradually dropped in a slower way or became relatively stable after Ptree reached a certain threshold. 3) While there was no significant difference in the types of CE-Ptree relationship among biomes and climates, the threshold of Ptree in CE-Ptree nonlinear ways was smaller in arid cities. The results of this threshold linking cooling benefits and current UTC can serve as a useful tool to prioritize locations for urban planting to maximize cooling benefits.

Microphytobenthos (MPB) contributes significantly to estuarine primary production, so that quantifying its biomass is crucial for assessing their ecosystem functioning. Conventional sampling methods are labour-intensive, logistically challenging, and cannot provide a comprehensive spatial distribution map of MPB biomass. Satellite imagery has offered a feasible alternative for mapping large areas at various temporal and spatial resolutions. However, no imaging device with a spatial resolution consistent with the few square centimetres sampled in-situ has been used in the field. This makes it challenging to accurately relate field biomass measurements with remotely sensed radiometric observations. In this study, two similar multispectral sensors were mounted on an unmanned aerial vehicle (UAV) at different altitudes, as well as on a custom-built device specifically designed to acquire images at ∼1 m altitude, in order to collect very-high spatial resolution reflectance data of MPB biofilms at the Guadalquivir Estuary (Spain) mudflats. In addition, a hyperspectral spectroradiometer acquiring in-situ field reflectance was used for validation. Simultaneously, MPB samples were collected using a 2 mm depth contact corer method, which were analysed through high-performance liquid chromatography (HPLC) to measure the concentrations of major MPB pigments. To assess the relationship between the MPB pigments and different reflectance-based spectral indices, generalised linear mixed effects models (GLMMs) were used, achieving a significant positive relationship between chlorophylls and all spectral indices tested. These models were used to map microphytobenthic biomass, yielding a mean biomass in the range of 30-50 mg Chl-a m^-2 in the Guadalquivir estuary during late winter. This study demonstrates the potential of low-altitude/high spatial resolution radiometric imaging as an efficient, rapid, and non-destructive addition to in-situ measurements of MPB biomass, providing exciting perspectives for the monitoring of estuarine systems on a millimetric scale of variability.

Terrestrial runoff is a key pathway for the transmission of the terrestrial pathogen Toxoplasma gondii from land to sea, posing a significant threat to marine ecosystems. Understanding the mechanisms by which T. gondii is transported from terrestrial to marine environment is crucial for developing effective prevention and control strategies for toxoplasmosis in marine organisms. This study investigates the transport of T. gondii through terrestrial runoff in the Sow River, a representative watershed in Weihai, China. Surface water, bottom water and sediment samples were collected and analyzed for T. gondii DNA using PCR methods. Out of 5328 samples, the prevalence of T. gondii was found to be 8.61 % in surface water, 9.80 % in bottom water and 16.61 % in sediment, with sediment identified as a significant reservoir. Additionally, estuarine zones showed a higher prevalence of T. gondii (16.80 %) compared to riverine areas (9.00 %). The study further revealed that seasonal climate variations, such as temperature and precipitation, had no significant impact on the distribution of T. gondii. However, there was significant spatial variability, with estuarine conditions facilitating increased pathogen transmission. These findings highlight the importance of estuaries and sediments as key conduits for T. gondii entry in marine food webs. The results provide a theoretical basis for designing infection prevention and control strategies aimed at protecting marine ecosystems.

Population growth, economic growth, and changes in societal habits have led to significant changes in resource consumption. Therefore, it's crucial to accelerate the "reduce, reuse, recycle, and recover" of resources to ensure the balance of ecosystems, and water is surely one of the most fundamental resources. The acceleration of this approach in the water cycle makes sense only if we combine a circular economy (CE) transition with a sustainable perspective. In this context, more rational usage of water resources (which are under pressure) and more sustainable wastewater practices are expected to be a way towards the CE in the water and wastewater sector. This study provides a description and evaluation of existing frameworks that can be used to measure and assess the level of circularity of the wastewater treatment plant (WWTP). The treatment of urban wastewater requires new concepts of management and operation for the adaptation of existing plants, which lack robustness and flexibility, to face these new challenges and requirements because we can no longer continue to look at the WWTP only as treatment units, but as wastewater resource recovery facilities. This transformation must be transposed according to a matrix that allows the assessment to describe the current situation, analyse the problem, identify vulnerabilities and opportunities, identify, and evaluate measures, and identify and evaluate strategies. Considering that decision-makers face profound uncertainties such as climate change, population growth, population needs, innovative technologies, economic developments, ecosystem preservation and the impacts of human and natural activities.