Understanding the Cardiovascular and Metabolic Health Effects of Air Pollution in the Context of Cumulative Exposomic Impacts.

Poor air quality accounts for more than 9 million deaths a year globally according to recent estimates. A large portion of these deaths are attributable to cardiovascular causes, with evidence indicating that air pollution may also play an important role in the genesis of key cardiometabolic risk factors. Air pollution is not experienced in isolation but is part of a complex system, influenced by a host of other external environmental exposures, and interacting with intrinsic biologic factors and susceptibility to ultimately determine cardiovascular and metabolic outcomes. Given that the same fossil fuel emission sources that cause climate change also result in air pollution, there is a need for robust approaches that can not only limit climate change but also eliminate air pollution health effects, with an emphasis of protecting the most susceptible but also targeting interventions at the most vulnerable populations. In this review, we summarize the current state of epidemiologic and mechanistic evidence underpinning the association of air pollution with cardiometabolic disease and how complex interactions with other exposures and individual characteristics may modify these associations. We identify gaps in the current literature and suggest emerging approaches for policy makers to holistically approach cardiometabolic health risk and impact assessment.

Crater-Spectrum Feature Fusion Method for Panax notoginseng Cadmium Detection Using Laser-Induced Breakdown Spectroscopy.

Panax notoginseng (P. notoginseng) is a valuable herbal medicine, as well as a dietary food supplement known for its satisfactory clinical efficacy in alleviating blood stasis, reducing swelling, and relieving pain. However, the ability of P. notoginseng to absorb and accumulate cadmium (Cd) poses a significant environmental pollution risk and potential health hazards to humans. In this study, we employed laser-induced breakdown spectroscopy (LIBS) for the rapid detection of Cd. It is important to note that signal uncertainty can impact the quantification performance of LIBS. Hence, we proposed the crater-spectrum feature fusion method, which comprises ablation crater morphology compensation and characteristic peak ratio correction (CPRC), to explore the feasibility of signal uncertainty reduction. The crater morphology compensation method, namely, adding variables using multiple linear regression (MLR) analysis, decreased the root-mean-square error of the prediction set (RMSEP) from 7.0233 µg/g to 5.4043 µg/g. The prediction results were achieved after CPRC pretreatment using the calibration curve model with an RMSEP of 3.4980 µg/g, a limit of detection of 1.92 µg/g, and a limit of quantification of 6.41 µg/g. The crater-spectrum feature fusion method reached the lowest RMSEP of 2.8556 µg/g, based on a least-squares support vector machine (LSSVM) model. The preliminary results suggest the effectiveness of the crater-spectrum feature fusion method for detecting Cd. Furthermore, this method has the potential to be extended to detect other toxic metals in addition to Cd, which significantly contributes to ensuring the quality and safety of agricultural production.

Personal Strategies to Reduce the Cardiovascular Impacts of Environmental Exposures.

Ubiquitous environmental exposures increase cardiovascular disease risk via diverse mechanisms. This review examines personal strategies to minimize this risk. With regard to fine particulate air pollution exposure, evidence exists to recommend the use of portable air cleaners and avoidance of outdoor activity during periods of poor air quality. Other evidence may support physical activity, dietary modification, omega-3 fatty acid supplementation, and indoor and in-vehicle air conditioning as viable strategies to minimize adverse health effects. There is currently insufficient data to recommend specific personal approaches to reduce the adverse cardiovascular effects of noise pollution. Public health advisories for periods of extreme heat or cold should be observed, with limited evidence supporting a warm ambient home temperature and physical activity as strategies to limit the cardiovascular harms of temperature extremes. Perfluoroalkyl and polyfluoroalkyl substance exposure can be reduced by avoiding contact with perfluoroalkyl and polyfluoroalkyl substance-containing materials; blood or plasma donation and cholestyramine may reduce total body stores of perfluoroalkyl and polyfluoroalkyl substances. However, the cardiovascular impact of these interventions has not been examined. Limited utilization of pesticides and safe handling during use should be encouraged. Finally, vasculotoxic metal exposure can be decreased by using portable air cleaners, home water filtration, and awareness of potential contaminants in ground spices. Chelation therapy reduces physiological stores of vasculotoxic metals and may be effective for the secondary prevention of cardiovascular disease.

The application of laser­induced fluorescence in oil spill detection.

Over the past two decades, oil spills have been one of the most serious ecological disasters, causing massive damage to the aquatic and terrestrial ecosystems as well as the socio-economy. In view of this situation, several methods have been developed and utilized to analyze oil samples. Among these methods, laser-induced fluorescence (LIF) technology has been widely used in oil spill detection due to its classification method, which is based on the fluorescence characteristics of chemical material in oil. This review systematically summarized the LIF technology from the perspective of excitation wavelength selection and the application of traditional and novel machine learning algorithms to fluorescence spectrum processing, both of which are critical for qualitative and quantitative analysis of oil spills. It can be seen that an appropriate excitation wavelength is indispensable for spectral discrimination due to different kinds of polycyclic aromatic hydrocarbons' (PAHs) compounds in petroleum products. By summarizing some articles related to LIF technology, we discuss the influence of the excitation wavelength on the accuracy of the oil spill detection model and proposed several suggestions on the selection of excitation wavelength. In addition, we introduced some traditional and novel machine learning (ML) algorithms and discussed the strengths and weaknesses of these algorithms and their applicable scenarios. With an appropriate excitation wavelength and data processing algorithm, it is believed that laser-induced fluorescence technology will become an efficient technique for real-time detection and analysis of oil spills.

Multivariable Air-Quality Prediction and Modelling via Hybrid Machine Learning: A Case Study for Craiova, Romania.

Inadequate air quality has adverse impacts on human well-being and contributes to the progression of climate change, leading to fluctuations in temperature. Therefore, gaining a localized comprehension of the interplay between climate variations and air pollution holds great significance in alleviating the health repercussions of air pollution. This study uses a holistic approach to make air quality predictions and multivariate modelling. It investigates the associations between meteorological factors, encompassing temperature, relative humidity, air pressure, and three particulate matter concentrations (PM10, PM2.5, and PM1), and the correlation between PM concentrations and noise levels, volatile organic compounds, and carbon dioxide emissions. Five hybrid machine learning models were employed to predict PM concentrations and then the Air Quality Index (AQI). Twelve PM sensors evenly distributed in Craiova City, Romania, provided the dataset for five months (22 September 2021-17 February 2022). The sensors transmitted data each minute. The prediction accuracy of the models was evaluated and the results revealed that, in general, the coefficient of determination (R2) values exceeded 0.96 (interval of confidence is 0.95) and, in most instances, approached 0.99. Relative humidity emerged as the least influential variable on PM concentrations, while the most accurate predictions were achieved by combining pressure with temperature. PM10 (less than 10 µm in diameter) concentrations exhibited a notable correlation with PM2.5 (less than 2.5 µm in diameter) concentrations and a moderate correlation with PM1 (less than 1 µm in diameter). Nevertheless, other findings indicated that PM concentrations were not strongly related to NOISE, CO2, and VOC, and these last variables should be combined with another meteorological variable to enhance the prediction accuracy. Ultimately, this study established novel relationships for predicting PM concentrations and AQI based on the most effective combinations of predictor variables identified.

Sports and sustainable development: the troubling absence of meat sourcing policies in the sports sector.

The excessive use of antibiotics in industrial meat production in the U.S. incurs severe health implications for animals, humans, and the environment, thereby threatening the integrated health of the ecosystem and sustainable development. While the consumption of meat, including hot dogs, chicken wings, and hamburgers, is a hallmark of attending professional sports events in North America, the sourcing policies for meat in the realm of professional sports remain relatively obscure. We conducted a content analysis case study on the four major sports leagues in North America, their teams and stadium practices. Our objective was twofold: first, to investigate existing sustainability initiatives at the league, team, and stadium levels; and second, to examine whether there are any food sourcing programs, specifically meat sourcing policies that might encourage the consumption of meat produced without the use of antibiotics, in the sports sector that are designed to mitigate ecological ramifications of meat consumption within sports contexts. Results show that existing sustainability initiatives at the three levels are focused primarily on reducing carbon emissions and waste. There is, however, a notable neglect of food sourcing policies, which is concerning given that industrial animal agriculture is a leading cause of antibiotic resistance and environmental degradation. This suggests that meat sourcing policy is a missing piece in current sustainability initiatives. The major sports leagues should therefore consider incorporating pertinent policies, such as procuring meat-based products produced without the use of antibiotics to help strengthen their existing efforts in achieving their sustainable development goals.

The promoting effects of soil microplastics on alien plant invasion depend on microplastic shape and concentration.

Both alien plant invasions and soil microplastic pollution have become a concerning threat for terrestrial ecosystems, with consequences on the human well-being. However, our current knowledge of microplastic effects on the successful invasion of plants remains limited, despite numerous studies demonstrating the direct and indirect impacts of microplastics on plant performance. To address this knowledge gap, we conducted a greenhouse experiment involving the mixtures of soil and low-density polyethylene (LDPE) microplastic pellets and fragments at the concentrations of 0, 0.5 % and 2.0 %. Additionally, we included Solidago decurrens (native plant) and S. canadensis (alien invasive plant) as the target plants. Each pot contained an individual of either species, after six-month cultivation, plant biomass and antioxidant enzymes, as well as soil properties including soil moisture, pH, available nutrient, and microbial biomass were measured. Our results indicated that microplastic effects on soil properties and plant growth indices depended on the Solidago species, microplastic shapes and concentrations. For example, microplastics exerted positive effects on soil moisture of the soil with native species but negative effects with invasive species, which were impacted by microplastic shapes and concentrations, respectively. Microplastics significantly impacted catalase (P < 0.05) and superoxide dismutase (P < 0.01), aboveground biomass (P < 0.01), and belowground/aboveground biomass (P < 0.01) of the native species depending on microplastic shapes, but no significant effects on those of the invasive species. Furthermore, microplastics effects on soil properties, nutrient, nutrient ratio, and plant antioxidant enzyme activities contributed to plant biomass differently among these two species. These results suggested that the microplastics exerted a more pronounced impact on native Solidago plants than the invasive ones. This implies that the alien invasive species displays greater resistance to microplastic pollution, potentially promoting their invasion. Overall, our study contributes to a better understanding of the promoting effects of microplastic pollution on plant invasion.

Phosphorus distribution in the water and sediments of the Ganga and Yamuna Rivers, Uttar Pradesh, India: insights into pollution sources, bioavailability, and eutrophication implications.

River nutrient enrichment is a significant issue, and researchers worldwide are concerned about phosphorus. The physicochemical characteristics and phosphorus (P) fractions of 36 sediment and water samples from the Ganga (Kanpur, Prayagraj, Varanasi) and Yamuna (Mathura, Agra, Prayagraj) rivers were examined. Among the physicochemical parameters, pH exceeded the permissible limit in Ganga and Yamuna River water and sediment samples. Electrical conductivity (EC) and alkalinity were within the permissible limits, whereas total nitrogen (TN) exceeded the limit in Yamuna water. The analysis of phosphorus fractions indicated the dominance of inorganic phosphorus (IP) (76% in Ganga and 96% in Yamuna) over organic phosphorus in both rivers, suggesting the mineralization and microbial degradation as major processes responsible for transforming OP to IP. The positive correlation of pH with IP, AP (apatite phosphorus), and NAIP (non-apatite inorganic phosphorus) explains the release of inorganic phosphorus under alkaline conditions. The correlation between total organic carbon (TOC), TN, and organic phosphorus (OP) indicated the organic load in the rivers from allochthonous and autochthonous sources. Phosphorus released from river sediments and the concentration of phosphate in overlying river water show a positive correlation, suggesting that river sediments may serve as phosphorus reservoirs. The average phosphorus pollution index (PPI) was above one in both rivers, with relatively higher PPI values observed in the Yamuna River, indicating the contamination of sediment with phosphorus, indicating the contamination of sediment with phosphorus. This study revealed variations in the P fractionation of the sediment in both rivers, primarily as a result of contributions from different P sources. This information will be useful for applying different mitigation techniques to lower the phosphorus load in both river systems.

Assessing ammonium pollution and mitigation measures through a modified watershed non-point source model.

Watershed water quality modeling is a valuable tool for managing ammonium (NH4+) pollution. However, simulating NH4+ pollution presents unique challenges due to the inherent instability of NH4+ in natural environment. This study modified the widely-used Soil and Water Assessment Tool (SWAT) model to simulate non-point source (NPS) NH4+ processes, specifically incorporating the simulation of land-to-water NH4+ delivery. The Jiulong River Watershed (JRW) is the study area, a coastal watershed in Southeast China with substantial sewage discharge, livestock farming, and fertilizer application. The results demonstrate that the modified model can effectively simulate the NPS NH4+ processes. It is recommended to use multiple sets of observations to calibrate NH4+ simulation to enhance model reliability. Despite constituting a minor proportion (5.6 %), point source inputs significantly contribute to NH4+ load at watershed outlet (32.4∼51.9 %), while NPS inputs contribute 15.3∼17.3 % of NH4+ loads. NH4+ primarily enters water through surface runoff and lateral flow, with negligible leaching. Average NH4+ land-to-water delivery rate is about 2.35 to 2.90 kg N/ha/a. High delivery rates mainly occur at agricultural areas. Notably, proposed NH4+ mitigation measures, including urban sewage treatment enhancement, livestock manure management improvement, and fertilizer application reduction, demonstrate potential to collectively reduce the NH4+ load at watershed outlet by 1/4 to 1/3 and significantly enhance water quality standard compliance frequency. Insights gained from modeling experience in the JRW offer valuable implications for NH4+ modeling and management in regions with similar climates and significant anthropogenic nitrogen inputs.

Evidence of the protective effect of anti-pollution products against oxidative stress in skin ex vivo using EPR spectroscopy and autofluorescence measurements.

The concentration of air pollution is gradually increasing every year so that daily skin exposure is unavoidable. Dietary supplements and topical formulations currently represent the protective strategies to guard against the effects of air pollution on the body and the skin. Unfortunately, there are not yet enough methods available to measure the effectiveness of anti-pollution products on skin. Here, we present two ex vivo methods for measuring the protective effect against air pollution of different cream formulations on the skin: Electron paramagnetic resonance (EPR) spectroscopy and autofluorescence excited by 785 nm using a confocal Raman microspectrometer (CRM). Smoke from one cigarette was used as a model pollutant. EPR spectroscopy enables the direct measurement of free radicals in excised porcine skin after smoke exposure. The autofluorescence in the skin was measured ex vivo, which is an indicator of oxidative stress. Two antioxidants and a chelating agent in a base formulation and a commercial product containing an antioxidant mixture were investigated. The ex vivo studies show that the antioxidant epigallocatechin-3-gallate (EGCG) in the base cream formulation provided the best protection against oxidative stress from smoke exposure for both methods.

Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds.

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

Pollution indices of selected metals in tea (Camellia sinensis L.) growing soils of the Upper Assam region divulge a non-trifling menace of National Highway.

The study investigated the influence of a National Highway (NH) traversing tea estates (TEs) on heavy metal (HM) contamination in the top soils of Upper Assam, India. The dispersion and accumulation of six HMs, viz. cadmium (Cd), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn), within tea-growing soils were assessed using diverse indices: contamination factor (CF), degree of contamination (DC), enrichment factor (EF), geo-accumulation index (Igeo), modified degree of contamination (MDC), Nemerow pollution index (PINemerow), pollution load index (PLI), potential ecological risk factor (Eri), and potential ecological risk index (RI). The order of HM prevalence was Fe > Mn > Zn > Ni > Cu > Cd. Elevated Cd levels near the NH prompted immediate attention, while Cd and Zn showed moderate pollution in CF, EF, and RI. The remaining metals posed minimal individual risk (Eri< 40), resulting in an overall contamination range of "nil to shallow," signifying slight contamination from the studied metals. From MDC values for investigated metals, it was found to be "zero to very low degree of contamination" at all locations except the vicinity of NH. Soil pollution, as determined by PLI, indicated unpolluted soils in both districts, yet PINemerow values indicated slight pollution. The statistical analysis revealed that there is a significant decrease in most of the indices of HM as the distance from NH increases. The application of multivariate statistical techniques namely Principal Component Analysis and Cluster Analysis showed the presence of three distinct homogenous groups of distances based on different indices. This investigation underscores NH-associated anthropogenic effects on TE soil quality due to HM deposition, warranting proactive mitigation measures.

Assessment of heavy metals in rainfall as an indicator of air pollution from Erbil Steel Factory in Iraq.

The goal of the current study is to evaluate the heavy metal rainfall contamination in the vicinity brought on by the Erbil Steel Factory in Iraq during the study period. The study's findings revealed the concentration of all studied heavy metals in the precipitation near and around the factory is significantly higher than that of the rural area of Barzan village which is used as a control site. The average concentration of the metals is in descending order manganese (Mn) > lead (Pb) > iron (Fe) > arsenic (As) > cobalt (Co) > selenium (Se) > mercury (Hg) > and cadmium (Cd) for the polluted site. The geo-accumulation index (I-geo) of the heavy metal Mn in the rainfall around the steel factory site is 6.28 > 5 which indicates extreme contamination. While the Igeo values of Cd, As, and Fe are 4.87, 4.54, and 4.04 > 4 that indicate heavy to extreme contamination, for Pb, 3.80 > 3 indicates moderate to heavy contamination, Cd 1.68 > 1 indicates moderate contamination, Hg 0.46 > 0 indicates uncontaminated to moderate contamination, and Se - 0.36 < 0 indicates uncontaminated. The pollution load index (PLI) of the rainwater around the steel factory site is 13.46 > 1, demonstrating that the area is highly metal-contaminated.

Trace element levels in the muscles of three tern species (Aves: Laridae) from the western Arabian Gulf: environmental assessment and implications for conservation.

In the Arabian Gulf (called also Persian Gulf; hereafter 'the Gulf'), Jana and Karan Islands are recognized as one of the most Important Bird Areas in the region. Many migratory breeding seabirds, like the Greater Crested Tern Thalasseus bergii, White-cheeked Tern Sterna repressa and Bridled Tern Onychoprion anaethetus, depend on these islands during the breeding season. However, these aquatic wildlife species are suffering from intensified urban and industrial coastal development and various contamination events including wars and related oil spills. In this study, we used these three piscivorous top predator birds to analyse the levels of 19 trace elements (TEs; i.e. Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, Pb, Sr, V and Zn) in 15 muscular tissue samples from Jana and Karan Islands. PERMANOVA analysis showed no difference in contamination profile between sites nor between species probably due to their spatial and ecological proximity and therefore similar levels of exposure to TEs. Comparing these levels with existing literature, our results showed no particular concern for all elements, except for Al (maximum values recorded = 116.5 µg g-1 d.w.) and, in two samples, Ba (33.67 µg g-1 d.w.) and Pb (5.6 µg g-1 d.w.). The results can be considered as an initial step for supplementary evaluations with a larger number of samples and specified time intervals for the collection of specimens. This study provided baseline information on the pollution status of these two ecologically important sites which require a continuous biomonitoring programme.

Acetylcholinesterase activity in muscle tissue of Norway lobster Nephrops norvegicus: Importance of body size, season, sex and naturally occurring metals.

The aim of the present study was to determine the levels of acetylcholinesterase (AChE) activity in the tail muscle tissue of wild populations of Nephrops norvegicus from the Northern Adriatic, and correlate it to body size, seasons, sex and the content of mercury, arsenic, cadmium, lead and copper. The animals of both sexes were collected in spring and autumn from two relatively distant fishing grounds. A marked variability of muscle AChE activity was found (0.49 to 11.22 nmol/min/mg prot.), displaying the opposite seasonal trend between two sampling sites. Small, but significant negative correlation has been found between AChE activity and carapace length (rs = - 0.35, p < 0.05). Data reported here provide an essential baseline for future studies of neurotoxicity in crustaceans. The study highlights the necessity for continuous monitoring of potentially toxic metals in edible marine species to avoid possible repercussions of seafood consumption on human health.

Enhancing phosphorus source apportionment in watersheds through species-specific analysis.

Phosphorus (P) is a pivotal element responsible for triggering watershed eutrophication, and accurate source apportionment is a prerequisite for achieving the targeted prevention and control of P pollution. Current research predominantly emphasizes the allocation of total phosphorus (TP) loads from watershed pollution sources, with limited integration of source apportionment considering P species and their specific implications for eutrophication. This article conducts a retrospective analysis of the current state of research on watershed P source apportionment models, providing a comprehensive evaluation of three source apportionment methods, inventory analysis, diffusion models, and receptor models. Furthermore, a quantitative analysis of the impact of P species on watersheds is carried out, followed by the relationship between P species and the P source apportionment being critically clarified within watersheds. The study reveals that the impact of P on watershed eutrophication is highly dependent on P species, rather than absolute concentration of TP. Current research overlooking P species composition of pollution sources may render the acquired results of source apportionment incapable of assessing the impact of P sources on eutrophication accurately. In order to enhance the accuracy of watershed P pollution source apportionment, the following prospectives are recommended: (1) quantifying the P species composition of typical pollution sources; (2) revealing the mechanisms governing the migration and transformation of P species in watersheds; (3) expanding the application of traditional models and introducing novel methods to achieve quantitative source apportionment specifically for P species. Conducting source apportionment of specific species within a watershed contributes to a deeper understanding of P migration and transformation, enhancing the precise of management of P pollution sources and facilitating the targeted recovery of P resources.

Formaldehyde Exposure Racial Disparities in Southeast Texas.

Formaldehyde (HCHO) exposures during a full year were calculated for different race/ethnicity groups living in Southeast Texas using a chemical transport model tagged to track nine emission categories. Petroleum and industrial emissions were the largest anthropogenic sources of HCHO exposure in Southeast Texas, accounting for 44% of the total HCHO population exposure. Approximately 50% of the HCHO exposures associated with petroleum and industrial sources were directly emitted (primary), while the other 50% formed in the atmosphere (secondary) from precursor emissions of reactive compounds such as ethylene and propylene. Biogenic emissions also formed secondary HCHO that accounted for 11% of the total population-weighted exposure across the study domain. Off-road equipment contributed 3.7% to total population-weighted exposure in Houston, while natural gas combustion contributed 5% in Beaumont. Mobile sources accounted for 3.7% of the total HCHO population exposure, with less than 10% secondary contribution. Exposure disparity patterns changed with the location. Hispanic and Latino residents were exposed to HCHO concentrations +1.75% above average in Houston due to petroleum and industrial sources and natural gas sources. Black and African American residents in Beaumont were exposed to HCHO concentrations +7% above average due to petroleum and industrial sources, off-road equipment, and food cooking. Asian residents in Beaumont were exposed to HCHO concentrations that were +2.5% above average due to HCHO associated with petroleum and industrial sources, off-road vehicles, and food cooking. White residents were exposed to below average HCHO concentrations in all domains because their homes were located further from primary HCHO emission sources. Given the unique features of the exposure disparities in each region, tailored solutions should be developed by local stakeholders. Potential options to consider in the development of those solutions include modifying processes to reduce emissions, installing control equipment to capture emissions, or increasing the distance between industrial sources and residential neighborhoods.

The storm runoff management strategy based on agricultural ditch nutrient loss characteristics in Erhai Lake, China.

Initial flush management is an effective measure to control non-point source pollution (NPSP) in storm runoff. However, determining the parameter of the initial flush in different areas may pose challenges in storm runoff management strategies. To address this issue, Erhai Lake in China, Yunnan-Guizhou Plateau, was selected as an example for the study. Erhai Lake is a typical mesotrophic lake with the profound influence of NPSP. The NPSP control strategy in this area will provide a valuable reference for other lakes. In 2021, 289 storm events and 190 ditchwater samples were detected around Erhai Lake. The average flow in the ditches ranged from 0.004 to 0.147 m3/s, the instant total nitrogen (TN) concentration ranged from 0.28 to 91.43 mg/L, and the instant total phosphorus (TP) concentration ranged from 0.26 to 7.35 mg/L in the storm events. It was found that the concentration of pollutants was lower than expected in the initial flush period. Instead, the event mean concentrations of TN and TP were 9.3 and 2.1 times higher than in the wet seasons, showing high nutrient concentration levels throughout the entire rainfall period. To manage storm runoff effectively, a flow-processes-division method was proposed to analyze the inflow condition and pollutant removal rate in different runoff periods. The peak flow interception strategy was recommended as the optimal stormwater management plan, as it showed the highest inflow conditions and 50% pollutant removal rate. Considering the need to reduce the constant flush of stormwater runoff, it is essential to establish a healthy water cycle system to alleviate NPSP and raise the Erhai water level. The storm runoff management method can serve as a practical tool for lake areas that do not exhibit initial flush characteristics.

Metal bioaccumulation and histological alterations in Oreochromis andersonii at Itezhi-tezhi Dam downstream of a mining area in the Central Province of Zambia.

The Itezhi-tezhi Dam on the Kafue River in Zambia is a major capture fishery. However, the upstream reaches of the Kafue River receive effluents from copper mines. It was unclear whether fish health in the dam is adversely affected due to the mining effluents. We investigated the health status of fish in Itezhi-tezh Dam using a histology-based fish health assessment protocol with Oreochromis andersonii as a bioindicator. Fish were sampled in the Itezhi-tezh Dam and at a reference site further upstream on the Kafue River before it enters the mining region. Metal bioaccumulation, biometric indices and histological alterations in the gills, gonads, hearts, kidneys and livers were assessed. The findings revealed significantly higher copper and selenium sediment concentrations (p = 0.02843 and p = 0.02107 respectively), bioaccumulation of copper and selenium, and increased histological alterations in the gills, kidneys and livers of fish in the Itezhi-tezhi Dam.

Microbial functional heterogeneity induced in a petroleum-polluted soil profile.

Microbial taxonomic diversity declines with increasing stress caused by petroleum pollution. However, few studies have tested whether functional diversities vary similarly to taxonomic diversity along the stress gradient. Here, we investigated soil microbial communities in a petrochemically polluted site in China. Total petroleum hydrocarbon (TPH) concentrations were higher in the middle (2-3 m) and deep soil layer (3-5 m) than in the surface soil layer (0-2 m). Accordingly, microbial taxonomic α-diversity was decreased by 44% (p < 0.001) in the middle and deep soil layers, compared to the surface soil layer. In contrast, functional α-diversity decreased by 3% (p < 0.001), showing a much better buffering capacity to environmental stress. Differences in microbial taxonomic and functional ß-diversities were enlarged in the middle and deep soil layers, extending the Anna Karenina Principle (AKP) that a community adapts to stressful environments in its own way. Consistent with the stress gradient hypothesis, we revealed a higher degree of network connectivity among microbial species and genes in the middle and deep soil layers compared to the surface soil layer. Together, we demonstrate that microbial functionality is more tolerant to stress than taxonomy, both of which were amenable to AKP and the stress gradient hypothesis.