Transport Of Pollutants Research Articles

Distinct drivers of bacterial community assembly processes in riverine islands in the middle and lower reaches of the Yangtze River.

Riverine islands are widespread alluvium wetlands developed in large rivers, and bacterial communities are crucial to their ecological function, yet their assembly processes are rarely addressed. The ecosystem services provided by the middle and the lower Yangtze are primarily threatened by pollution discharge from agricultural land use, and resource overutilization (e.g., embankments), respectively. Here, we assessed bacterial community assembly processes and their drivers within riverine islands in the middle Yangtze River (MR islands) and those in the lower reach (LR islands). A significant distance-decay relationship was observed, although the turnover rate was lower than that of the terrestrial ecosystem with less connectivity. Deterministic and stochastic processes jointly shaped community patterns, and the influence of stochastic increased from 26% in MR islands to 59% for those in LR islands. Meanwhile, the bacterial community in MR islands was controlled more by inorganic nitrogen availability, whereas those in LR islands were governed by pH and EC, although those factors explained a limited fraction of variation in the bacterial community. Potential indicator taxa (affiliated with Nocardioides and Lysobacter) characterized the waterway transport pollution. Overall, our study demonstrated that bacterial community dissimilarity and the importance of dispersal limitation increased concurrently along the flow direction, while distinct local factors further determined bacterial community compositions by selecting habitat-specificity taxa and particularly metabolism function. These findings enhanced our understanding of the mechanisms driving changes in bacterial communities of riverine islands subject to increased anthropogenic impacts.IMPORTANCERivers are among the most threatened ecosystems globally and face multiple stressors related to human activity. However, linkages between microbial diversity patterns and assembly processes in rivers remain unclear, especially in riverine islands developed in large rivers. Our findings reveal that distinct factors result in divergent bacterial community compositions and functional profiles in the riverine islands in the middle Yangtze and those in the lower Yangtze, with substantial differentiation in deterministic and stochastic processes that jointly contribute to bacterial community assemblages. Additionally, keystone species may play important metabolic roles in coping with human-related disturbances. This study provides an improved understanding of relationships between microbial diversity patterns and ecosystem functions under environmental changes in large river ecosystems.

Study of pollutant transport under linear sorption in a groundwater reservoir

Abstract Pollutant dispersion in a porous medium can be modelled mathematically to forecast its concentration distribution profile. The governing equation of pollutant transport is modelled as a partial differential equation. Effects of sorption, zero-order production rate and first-order decay rate on pollutant transport are incorporated in the present study. The temporarily dependent pulse-type input source decaying exponentially is assumed at the origin of the domain. The solution of the proposed transport equation is derived by Laplace transform method for the respective time split domain. Matlab algorithm is developed to illustrate the obtained analytical solutions graphically for various hydrological input data. The pollutant distribution profiles in the medium are obtained for different times and porosities. The pollutant transport nature is examined for various forms of velocity flow pattern in presence and absence of input source. Also, the derived solution is compared graphically under special case with the existing solution and found the results with good agreement.

Effects of mixed land use on urban stormwater quality under different rainfall event types

The joint effect of mixed land uses and rainfall event types was studied using a two-year field monitoring program in four urban catchments in Calgary, Alberta, Canada. Event mean concentration (EMC) and event pollutant load (EPL) were employed to evaluate the total suspended sediment (TSS), nitrogen and phosphorus. The correlation analysis showed that most nitrogen and phosphorus components (except for NO2−/NO3− and TDP) predominantly exist in particulate form in the study areas. The correlation for EPL was notably stronger than EMC, which can be attributed to varying rainfall characteristics. The differences in EMCs and EPLs of TSS, nitrogen and phosphorus across catchments indicated that the complexity and spatial distribution of mixed land use can influence the generation and transportation of pollutants in urban runoff. The impacts of rainfall characteristics on stormwater quality are integrated rather than driven by a single rainfall characteristic. Brief but intense events tended to elevate TSS, nitrogen and phosphorus concentrations, especially in complex land-use catchments. Events with long antecedent dry days and short duration also resulted in increased pollutant concentrations, while events with long duration and low intensity could result in higher EPLs. The effect of mixed land use on water quality can vary depending on rainfall event types. Seasonal variations were found in EMC and EPL of TSS, nitrogen and phosphorus, with higher values in the spring and summer than the fall. Seasonal variations are mainly influenced by rainfall conditions, temperature and anthropogenic activities (e.g. lawn fertilization and de-icing with sands). MLR considering rainfall characteristics is an effective method for predicting stormwater quality within a single catchment. Considering complexity and spatial distribution of mixed land use can improve the accuracy of the harmonized MLR model. This research provided insights into understanding the complexities introduced by mixed land use and rainfall event types in urban stormwater quality.

Correlative Effects on Nanoplastic Aggregation in Model Extracellular Biofilm Substances Investigated with Fluorescence Correlation Spectroscopy.

Recent studies show that biofilm substances in contact with nanoplastics play an important role in the aggregation and sedimentation of nanoplastics. Consequences of these processes are changes in biofilm formation and stability and changes in the transport and fate of pollutants in the environment. Having a deeper understanding of the nanoplastics-biofilm interaction would help to evaluate the risks posed by uncontrolled nanoplastic pollution. These interactions are impacted by environmental changes due to climate change, such as, e.g., the acidification of surface waters. We apply fluorescence correlation spectroscopy (FCS) to investigate the pH-dependent aggregation tendency of non-functionalized polystyrene (PS) nanoparticles (NPs) due to intermolecular forces with model extracellular biofilm substances. Our biofilm model consists of bovine serum albumin (BSA), which serves as a representative for globular proteins, and the polysaccharide alginate, which is a main component in many biofilms, in solutions containing Na+ with an ionic strength being realistic for fresh-water conditions. Biomolecule concentrations ranging from 0.5 g/L up to at maximum 21 g/L are considered. We use non-functionalized PS NPs as representative for mostly negatively charged nanoplastics. BSA promotes NP aggregation through adsorption onto the NPs and BSA-mediated bridging. In BSA-alginate mixtures, the alginate hampers this interaction, most likely due to alginate-BSA complex formation. In most BSA-alginate mixtures as in alginate alone, NP aggregation is predominantly driven by weaker, pH-independent depletion forces. The stabilizing effect of alginate is only weakened at high BSA contents, when the electrostatic BSA-BSA attraction is not sufficiently screened by the alginate. This study clearly shows that it is crucial to consider correlative effects between multiple biofilm components to better understand the NP aggregation in the presence of complex biofilm substances. Single-component biofilm model systems based on comparing the total organic carbon (TOC) content of the extracellular biofilm substances, as usually considered, would have led to a misjudgment of the stability towards aggregation.

Evaluation of WRF-Chem PM2.5 simulations in Thailand with different anthropogenic and biomass-burning emissions

Thailand experiences severe air quality issues, predominantly due to PM2.5 pollution that surpasses WHO guidelines. The main sources are attributed to energy production, industrial activities, vehicular emissions, agricultural burning, and transboundary transport of pollutants. Understanding the transport and transformation of these pollutants is necessary for addressing air quality issues. The Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) provides information about meteorology, chemical reactions, and transport of trace gases and aerosols. The accuracy of WRF-Chem simulations greatly depends on the choice of anthropogenic and biomass burning emissions inventories. This study provides a detailed evaluation of these inventories to model PM2.5 concentrations in Thailand during both haze and off-haze seasons in 2019. We evaluated WRF-Chem using four anthropogenic emission inventories—CAMS-GLOB-ANT, ECLIPSE, HTAP, and REAS—and four biomass burning emissions inventories—FINN1.5, FINN2.5 MOD, FINN2.5 MODVAR, and QFED—using data from ground-based air quality stations, MODIS AOD, and MOPITT CO satellite data. Our findings suggest CAMS-GLOB-ANT performs optimally for North Thailand, while HTAP and REAS are more effective in Eastern Thailand. For biomass burning, FINN1.5 shows superior performance. The study also highlights the challenge in capturing PM2.5 diurnal variability, particularly due to inaccuracies in simulating the planetary boundary layer height during nighttime in complex terrains. Moreover, our analysis exhibits moderate model performances during the off-haze season while using global and regional anthropogenic emissions in Thailand, emphasizing the need for improving anthropogenic inventories for reliable air quality prediction. For biomass burning emissions, updating emission factors to reflect Thailand's specific vegetation types is recommended to improve WRF-Chem's representation of PM2.5 levels.

Identifying manning roughness coefficient using automatic calibration method and simulation of pollution incidents in the Nile River, Egypt

Study regionA reach of the Nile River located between Naga Hammadi barrage and Asyut barrage, Egypt Study focusAn accurate representation of hydrodynamics of an important water source helps cope with expected future climate changes, pollution incidents and water quality problems. Here, a comparison between HEC-RAS 1D and TELEMAC-2D model was conducted by identifying different Manning coefficients. Moreover, an automatic calibration using Dual-Annealing optimization method was applied for first time to calibrate the model with non-uniform Manning coefficients. The transport of tracer (pollution) was simulated by computing tracer residence times. Pollution transport scenarios were discussed to draw a picture of pollution incidents which will continue to happen in the future. An equation indicating the relation between flow discharge and residence time was derived to hurriedly help decision makers in water management during sudden pollution incidents. New hydrological insights for the regionA model with spatially variable Manning coefficients using TELEMAC-2D was set up and calibrated achieving good accuracyies with average errors of approximately 4 cm and 7 cm between field and simulated water levels for two different discharge scenarios. Moreover, an equation for relation between flow discharge and residence time was derived producing a strong correlation coefficient of 0.95. This study, integrating advanced hydrodynamic models and automatic calibration techniques, provides a robust framework for assessing and managing water resource challenges under varying flow conditions.

Multi-process atmospheric particle number size distribution over the Bohai Sea: Insights from cruise and onboard unmanned aerial vehicle observations

A better understanding of the particle number size distribution aids to better assess the direct and indirect effects of particles on air quality and climate. In this study, particle number concentrations (PNCs) and size distribution along with chemical components, gaseous pollutants, and meteorological parameters were measured during a cruise campaign over the Bohai Sea. Four distinct periods were identified, showing significant impacts from continental outflows and ocean emissions on the particle number size distributions. Under the strong terrestrial pollution transport period, an obvious increase of PNCs below 1 μm was observed. The significant correlation between black carbon (BC) and PNCs in the size range of 0.35–1.0 μm suggested aging of aerosols during the long-range transport. An invaded dust pollution significantly reduced PNCs below 0.5 μm, while tripled the number concentration of particles larger than 0.5 μm. The ocean moisture facilitated the mixing between dust and secondary aerosols. An intense sea fog event observed during the cruise slightly increased PNCs smaller than 1 μm while decreasing larger ones. The correlations between PNCs below 0.5 μm and BC as well as SO2 demonstrated the impact of shipping activities on the formation of fresh particles. Aerosol vertical profiles in the marine boundary layer were measured by an unmanned aerial vehicle platform. The vertical patterns of particle number size distribution were largely governed by the origins of transported air masses and profiles of wind fields. Observations showed that the particle distribution in the lower marine boundary layer was typically inhomogeneous and rapidly evolving with time, highlighting the importance of strengthening the vertical observations of atmospheric parameters over the ocean.

Numerical simulation of hydraulic characteristics and pollutant transport in the channels with different ice coverages

ABSTRACT In winter, rivers at high latitudes often freeze and an ice cover emerges at the free surface of the river. According to the coverage degree of the ice cover, rivers can be divided into free-flowing, partially frozen, and completely frozen. The presence of ice cover can greatly alter the hydraulic conditions of rivers, complicating the transport of pollutants in river channels. The distribution of pollutants in rivers with different ice coverages was simulated using the Detached Eddy Simulation (DES) model in this paper. The velocity distribution, the pollutant diffusion coefficient distribution, the turbulent kinetic energy distribution, and the vortex distribution with different ice coverages were analyzed. The velocity in the ice cover zone is at a lower rate than in the open flow zone. With the increase of the ice coverage, the turbulent kinetic energy of the ice cover area in partially frozen conditions gradually increases, which makes the water flow turbulence increase. The diffusion coefficient of pollutants in the ice cover area is greater than that in the open flow area, so pollutants disperse more quickly in the ice cover area. The turbulence energy and the diffusion coefficient have similar distribution characteristics beneath the ice cover. The presence of the ice cover promotes the movement of the vortex from the open flow area to the ice cover area, which may be the reason for the larger turbulence energy and the diffusion coefficient. The simulation results can provide a reference for ice disasters and water quality remediation.

Island Water Management Cyprus Facts Finding Mission and Gap Identifications

Water management on islands faces unique challenges due to limited size, isolation, climate change impacts, and economic development needs. These factors intensify water scarcity, highlighting the need for sustainable resource development through multidisciplinary approaches. Cyprus, the third-largest Mediterranean island, exemplifies these challenges, with the lowest water availability per capita in the region and severe water scarcity exacerbated by climate change. Addressing these issues requires a comprehensive master plan that integrates technical, environmental, social, and economic factors, focusing on climate change impacts on the water cycle. The Energy, Environment, and Water Research Center (EEWRC) plays a pivotal role in global resource management, emphasizing sustainable development goals and Integrated Water Resources Management Policy. EEWRC’s key initiatives include hydrodiplomacy and WEF Nexus and Integrated Water Resource Management IWRM, monitoring sediment transport pollution, water quality monitoring of basins and aquifers, smart water management of conventional and non-conventional water, and nature-based solutions for water and land management integration. To improve water management in Cyprus, establishing a National Commission for Water Experts is recommended. This commission would provide a detailed roadmap for water management, aligning with Sustainable Development Goals (SDGs) and the Climate Change Initiative coordinated by the Cyprus Institute. Additionally, organizing a conference focused on “Cyprus Island Water Management” would help launch this concept. In conclusion, it is crucial to develop a long-term strategy for optimal water resource management in Cyprus, addressing water issues, promoting conservation, launching climate-resilient initiatives, and fostering collaboration with national and international entities for success.

Multi-laser nanoparticle tracking analysis (NTA): A unique method to visualize dynamic (shear) and dynamic (Brownian motion) light scattering and quantify nonliving natural organic matter (NNOM) in environmental water

Application of simultaneous multi-laser nanoparticle tracking analysis (NTA) to environmental water samples to investigate nonliving natural organic matter (NNOM) is introduced as an innovative method for observing particles directly in their native media. Multi-laser NTA results of particle visualization, particle number concentration, and particle size distribution elucidated particle dynamics in low and high total dissolved solids (TDS) aqueous environmental samples. A pond water sample and concentrate from a reverse osmosis (RO) treatment process (Stage 1) had 1.3 × 108 and 5.62 × 1019 particles/mL, respectively, (at time = 0) after filtration at 0.45 μm. Beyond the traditional applications for this instrument, this research presents novel evidence-based investigations that probe the existence of supramolecular structures in environmental waters during turbulence or quiescence. The pond water sample exhibited time-dependent aggregation as the volume distribution shifted to greater diameter during quiescence, compared to turbulence. Disaggregation (increased numbers of particles over time) was noted in the >250 nm to <600 nm region, and aggregation of >450 nm particles was also noted in the quiescent RO concentrate sample, indicative of depletion of small particles to form larger ones. Multi-laser NTA and dynamic light scattering (DLS) capabilities were compared and contrasted. DLS and NTA are different (complementary) particle sizing techniques. DLS yielded more information about the physical hydrogel in the NNOM hierarchy whereas multi-laser NTA better characterized meta-chemical and chemical hydrogel characteristics. Operationalization of innovation—moving from fundamental investigations to application—is supported by implementing novel analytical instrumentation as we address issues involving climate change, drought, and the scarcity of potable water. Multi-laser NTA can be used as a tool to study and optimize complex water and wastewater treatment processes. Questions about water treatment efficiencies, membrane fouling, assistance of pollutant transport, and carbon capture cycles affected by NNOM will benefit from insights from multi-laser NTA.

Advanced green capture of microplastics from different water matrices by surface-modified magnetic nanoparticles

The extensive production and application of plastic in recent decades has resulted in the presence of microplastics (MPs) in different water bodies. Considered as contaminants of emerging concern (CECs), MPs are accessible to a wide range of organisms and can act as vectors for the transport of other persistent organic pollutants. The existing technologies to remove microplastics from wastewaters and prevent their intrusion in nature, still present several limitations, resulting in an urgent need to develop novel, fast, cost-effective and greener alternatives. In this work, the magnetophoretic capture of MPs by their assembly with magnetic nanoparticles through either electrostatic interactions or molecular forces is investigated. For the experimental assessment, magnetic nanoparticles were synthesized by hydrothermal coprecipitation and solvothermal decomposition methods, while polyethylene (PE) microspheres were selected as model microplastic pollutants. As a noteworthy novelty, thermal decomposition and coprecipitation particles were functionalized with amino groups and sodium alginate (SA), respectively, resulting in a modification of their surface properties and enhanced electrostatic or molecular interactions with MPs. After preliminary experiments, a concentration of 1.3 g L-1 and a contact time of 20 min between magnetic nanoparticles and MPs, were selected as operating conditions to assess the influence of the functional groups on the capture performance. The influence of other variables in the process was also evaluated, including the magnetic nanoparticles synthesis method, the pH of the medium, varied in the range 4–8, and the water constituents that may be present in water bodies. Results demonstrated that the presence of different types of polar groups on the surface of the magnetic nanoparticles make them interact towards MPs through electrostatic attraction or molecular forces, considerably enhancing the capture performance of bare magnetic nanoparticles. This work represents a step forward in the development of new and reliable techniques for the environmentally friendly capture of microplastics from polluted waters.

Assessing PM2.5 Dynamics and Source Contributions in Southwestern China: Insights from Winter Haze Analysis

Despite enhancements in pollution control measures in southwestern China, detailed assessments of PM2.5 dynamics following the implementation of the Clean Air Action remain limited. This study explores the PM2.5 concentrations and their chemical compositions during the winter haze period of 2017 across four major urban centers—Chengdu, Chongqing, Guiyang, and Kunming. Significant variability in mean PM2.5 concentrations was observed: Chengdu (71.8 μg m−3) and Chongqing (53.3 μg m−3) recorded the highest levels, substantially exceeding national air quality standards, while Guiyang and Kunming reported lower concentrations, suggestive of comparatively milder pollution. The analysis revealed that sulfate, nitrate, and ammonium (collectively referred to as SNA) constituted a substantial portion of the PM2.5 mass—47.2% in Chengdu, 62.2% in Chongqing, 59.9% in Guiyang, and 32.0% in Kunming—highlighting the critical role of secondary aerosol formation. The ratio of NO3−/SO42− and nitrogen oxidation ratio to sulfur oxidation ratio (NOR/SOR) indicate a significant transformation of NO2 under conditions of heavy pollution, with nitrate formation playing an increasingly central role in the haze dynamics, particularly in Chengdu and Chongqing. Utilizing PMF for source apportionment, in Chengdu, vehicle emissions were the predominant contributor, accounting for 33.1%. Chongqing showed a similar profile, with secondary aerosols constituting 36%, followed closely by vehicle emissions. In contrast, Guiyang’s PM2.5 burden was heavily influenced by coal combustion, which contributed 46.3%, reflecting the city’s strong industrial base. Kunming presented a more balanced source distribution. Back trajectory analysis further confirmed the regional transport of pollutants, illustrating the complex interplay between local and distant sources. These insights underscore the need for tailored, region-specific air quality management strategies in southwestern China, thereby enhancing our understanding of the multifaceted sources and dynamics of PM2.5 pollution amidst ongoing urban and industrial development.

The impact of lake discontinuities on nitrogen biogeochemistry in river networks

River networks connect terrestrial and marine ecosystems through transport of pollutants and nutrients. Lakes represent discontinuities within these river networks, which can be important biogeochemical hotspots, introducing substantial changes to the aquatic environment. Nitrogen is a key macronutrient that can potentially limit or co-limit primary production, but the processes that determine the fate of nitrogen during transport through river-lake networks are poorly understood. We studied three river systems and their lake discontinuities, spanning a range of trophic states and average water residence times, to understand the changes introduced to riverine nitrogen biogeochemistry by lake discontinuities. In-lake processes noticeably altered the concentration and speciation of nitrogen. Annually, lakes reduced up to 44% of nitrate compared to main inflow concentrations, while there was large variability in nitrate dynamics seasonally. The drawdown in surface nitrate concentrations resulted at times in phytoplankton co-limitation by nitrogen in-lake, as well as in the downstream river, where altered nitrogen patterns could persist for several kilometers. However, lakes occasionally subsidized N to downstream rivers as ammonium or dissolved organic nitrogen. Assimilation of nitrate in lake surface waters was one of the dominant processes impacting nitrogen availability; however, stable isotope data revealed an unexpected contribution of nitrification on nitrogen cycling in the epilimnion throughout the year and across trophic gradients. These changes in nitrogen concentration, as well as speciation introduced by lake discontinuities have potentially important consequences for the composition and metabolism of communities in downstream rivers and contribute to our fundamental understanding of freshwater processes.

The Effect of Model Input Uncertainty on the Simulation of Typical Pollutant Transport in the Coastal Waters of China

Route planning to evade potential pollution holds critical importance for aquaculture vessels. This study establishes a fish-feed pollutant drift model based on the Lagrangian particle tracking algorithm and designs four sets of sensitivity experiments in the East China Sea. The research investigates the impact of model input uncertainties on the drift trajectory, centroid position, and sweeping area of the fish-feed pollutants. Numerical results indicate that the uncertainty in the background flow field significantly affects the uncertainty in the centroid position and sweeping area in the numerical simulations. Specifically, when a 35% random error is added to the background flow field, the centroid shift distance reaches its maximum, and the sweeping area also attains its largest value. The uncertainty in the background wind field affects the centroid position of particles but to a much lesser extent compared to the background flow field. When considering only the uncertainty of the background wind field, the sweeping area does not significantly differ from the control experiment as the uncertainty of the background wind field increases. The initial release position has little effect on the drift direction of the fish-feed pollutants but does affect the drift distance; it has minimal impact on the trajectory but significantly affects the final position of the pollutant centroid. By analyzing the model uncertainties, this study reveals the key factors influencing the drift of fish-feed pollutants. This information is crucial for aquaculture vessels in planning routes, considering environmental factors, and reducing potential pollution risks.

On ozone's weekly cycle for different seasons in Arizona

This study advances insights on ozone (O3) concentration temporal cycles in Arizona, exploring differences between weekdays and weekends to understand the impact of anthropogenic activities on O3 fluctuations. By examining data from six areas across Arizona and with a more detailed look across the Phoenix metropolitan area, this study compares O3 and NO2 levels based on day of the week and time of day as well as during five distinct seasons between January 2015 and December 2021: fall (Sep–Nov), winter (Dec–Feb), spring (Mar–May), dry summer (June), and monsoon summer (Jul–Aug). Results highlight associations between O3 levels and O3 precursor levels, particularly for nitrogen oxides (NOx) and volatile organic compounds (VOCs). Results show that O3 levels are contingent on diurnal, day-of-week, and seasonally-dependent factors. This dependence influences the phenomena called the “weekend effect”, which is most clearly observed at urban sites across Arizona in fall and winter seasons, wherein O3 concentrations exhibit higher levels during weekends compared to weekdays. This study reveals opposing features during Arizona's warmer months and especially the monsoon summer period in which O3 regimes reverse from VOC-sensitive (in fall and winter) to transition and NOx-sensitive regimes. A specific case study for Phoenix during the first COVID-19 lockdown (spring 2020) accounting for planetary boundary layer height normalization of gas concentrations shows that although NO2 was reduced in March–April compared to other years, O3 was also reduced due to a regional O3 response as most areas surrounding western U.S. were typically either transitioning to, or already under, a NOx-limited regime. These findings provide insights into understanding the intricate relationship among anthropogenic emissions, seasonal fluctuations, and pollutant emissions and transport that influence O3 levels across Arizona, potentially providing guidance for future study designs focused on effective control strategies for the sensitive months with most exceedances (∼June–August).

Identification of illicit discharges in sewer networks by an SWMM-Bayesian coupled approach.

Illicit discharges into sewer systems are a widespread concern within China's urban drainage management. They can result in unforeseen environmental contamination and deterioration in the performance of wastewater treatment plants. Consequently, pinpointing the origin of unauthorized discharges in the sewer network is crucial. This study aims to evaluate an integrative method that employs numerical modeling and statistical analysis to determine the locations and characteristics of illicit discharges. The Storm Water Management Model (SWMM) was employed to track water quality variations within the sewer network and examine the concentration profiles of exogenous pollutants under a range of scenarios. The identification technique employed Bayesian inference fused with the Markov chain Monte Carlo sampling method, enabling the estimation of probability distributions for the position of the suspected source, the discharge magnitude, and the commencement of the event. Specifically, the cases involving continuous release and multiple sources were examined. For single-point source identification, where all three parameters are unknown, concentration profiles from two monitoring sites in the path of pollutant transport and dispersion are necessary and sufficient to characterize the pollution source. For the identification of multiple sources, the proposed SWMM-Bayesian strategy with improved sampling is applied, which significantly improves the accuracy.

Progress in Research on Microplastic Prevalence in Tropical Coastal Environments: A Case Study of the Johor and Singapore Straits

Microplastics are contaminants in marine ecosystems, posing great threats to biota and human health. In this work, we provide an overview of the progress made in understanding microplastic prevalence in tropical coastal environments, focusing on the Johor and the Singapore Straits as a case study. We examine the sources, distribution, transport, and ecological impact of microplastic pollution in this region through a systematic review. All papers relating to marine microplastics in Singapore’s sand and benthic sediments, seawater, and marine biota were used for analysis, from 2004 to 2023. In addition, we discuss the influence of envi-ronmental factors such as coastal morphology and anthropogenic activities on patterns of microplastic accumulation. We emphasize that microplastic pollution is more prevalent along the eutrophic Johor Strait compared to the Singapore Strait due to hydrological conditions. Rainfall is also a key factor that influences mi-croplastic abundance during the monsoon seasons. Furthermore, the bacterial and plankton assemblages of organisms on microplastic surfaces are diverse, with eutrophic waters enhancing the diversity of organisms on microplastic surfaces. Novel harmful cyanobacteria and bloom species of phytoplankton were also found on microplastic surfaces. By synthesizing existing research findings and highlighting regional characteristics, this paper contributes to ongoing efforts to mitigate microplastic pollution in tropical regions.

The molecular binding sequence transformation of soil organic matter and biochar dissolved black carbon antagonizes the transport of 2,4,6-trichlorophenol

Dissolved organic matter (DOM) and dissolved black carbon (DBC) are significant environmental factors that influence the transport of organic pollutants. However, the mechanisms by which their molecular diversity affects pollutant transport remain unclear. This study elucidates the molecular binding sequence and adsorption sites through which DOM/DBC compounds antagonize the transport of 2,4,6-trichlorophenol (TCP) using column experiments and modelling. DBC exhibits a high TCP adsorption rate (kn = 5.32 × 10−22 mol1–n∙Ln–1∙min−1) and conditional stability constant (logK = 5.19–5.74), indicating a strong binding affinity and antagonistic effect on TCP. This is attributed to the high relative content of lipid/protein compounds in DBC (25.65 % and 30.28 %, respectively). Moreover, the small molecule lipid compounds showed stronger TCP adsorption energy (Ead = −0.0071 eV/−0.0093 eV) in DOM/DBC, combined with two-dimensional correlation spectroscopy model found that DOM/DBC antagonized TCP transport in the environment through binding sequences that transformed from lipid/protein small molecule compounds to lignin/tannin compounds. This study used a multifaceted approach to comprehensively assess the impact of DOM/DBC on TCP transport. It reveals that the molecular diversity of DOM/DBC is a critical factor affecting pollutant transport, providing important insights into the environmental trend and ecological effects of pollutants.

Assessing the effectiveness of PM2.5 pollution control from the perspective of interprovincial transport and PM2.5 mitigation costs across China

Due to the transboundary nature of air pollutants, a province's efforts to improve air quality can reduce PM2.5 concentration in the surrounding area. The inter-provincial PM2.5 pollution transport could bring great challenges to related environmental management work, such as financial fund allocation and subsidy policy formulation. Herein, we examined the transport characteristics of PM2.5 pollution across provinces in 2013 and 2020 via chemical transport modeling and then monetized inter-provincial contributions of PM2.5 improvement based on pollutant emission control costs. We found that approximately 60% of the PM2.5 pollution was from local sources, while the remaining 40% originated from outside provinces. Furthermore, about 1011 billion RMB of provincial air pollutant abatement costs contributed to the PM2.5 concentration decline in other provinces during 2013–2020, accounting for 41.2% of the total abatement costs. Provinces with lower unit improvement costs for PM2.5, such as Jiangsu, Hebei, and Shandong, were major contributors, while Guangdong, Guangxi, and Fujian, bearing higher unit costs, were among the main beneficiaries. Our study identifies provinces that contribute to air quality improvement in other provinces, have high economic efficiency, and provide a quantitative framework for determining inter-provincial compensations. This study also reveals the uneven distribution of pollution abatement costs (PM2.5 improvement/abatement costs) due to transboundary PM2.5 transport, calling for adopting inter-provincial economic compensation policies. Such mechanisms ensure equitable cost-sharing and effective regional air quality management.

Chasing parts in quadrillion: applications of dynamical downscaling in atmospheric pollutant transport modelling during field campaigns

Atmospheric transport and dispersion models (ATDMs) are widely used to study and forecast pollution events. In the frame of the “Effect of Megacities on the transport and transformation of pollutants on the regional to global scales” (EMeRGe) project, ATDM forecasts were carried out to identify potential airborne sampling areas of perfluorocarbons (PFCs) emanating from controlled PFC releases. The forecasts involved short-distance transport over small-scale topographic maxima (Manilla; Philippines), short-distance transport over large-scale topographic maxima (Taipei, Taiwan) and long-distance transport over mixed topography (Nanjing, China, sampled over Taiwan). In situ aircraft measurements of PFC mixing ratios down to a few parts per quadrillion (ppqv) provide us with a unique dataset to explore the added benefits of dynamical downscaling. Transport simulations were repeated using FLEXPART driven by ERA5 and IFS meteorological data and FLEXPART-WRF with dynamically downscaled IFS data down to 1.1 km and four PBL parametrisations. Of the three cases studied, dynamical downscaling led to significant differences for the Manilla and Taipei releases that can be interpreted through changes in the modelled orographic flow regimes. The choice of PBL scheme also significantly impacted accuracy, but there was no systematically better-performing option, highlighting the benefits of ensemble forecasting. Results show how convergence and divergence between ensemble members can be utilised to help decision-making during field campaigns. This study highlights the role that dynamical downscaling can play as an important component in campaign planning when dealing with observations over orographically complex areas.