Environmental Sciences Europe最新文献

Wastewater treatment plants (WWTPs) contain a diverse array of microbes, underscoring the need for regular monitoring to ensure treatment efficacy and protect health. However, detailed studies on waste stabilization ponds (WSPs) are scarce. This study evaluates a full-scale WSP, located in Giza Governorate, Egypt, including anaerobic, facultative, and maturation ponds, examining an array of parameters such as enteric viruses, microeukaryotes (protozoa and algae), bacterial indicators, bacterial pathogens, and physicochemical characteristics. Utilizing multivariate statistical models, we identified significant distinctions in physicochemical parameters and microbial communities, primarily driven by treatment stages rather than temporal variations. In addition, seven viruses (human rotavirus, adenovirus, norovirus, astrovirus, hepatitis A virus, polyomavirus, and papillomavirus) were detected during the different stages (inlet, anaerobic, facultative, and outlet) of the WSP, except norovirus and papillomavirus were absent in the outlet stage. The viral log means reductions ranged from 1.24 to 5.94, depending on the stage and virus type. The removal efficiency of bacterial pathogens was more than 99%. High throughput 18S rRNA gene amplicon sequencing indicated the dominance of animal parasitic Apicomplexa species and Vermamoeba spp. in the WSP. Network analysis indicated significant roles for Ciliophora in virus reduction. Notably, the maturation pond's outlet was dominated by Spirulina maxima, whose mat-forming tendencies may inhibit pathogen removal by providing protective shelters. Although the WSP effectively reduced pathogen levels, the high initial loads resulted in considerable concentrations in the final effluent, posing ongoing public health concerns. This study highlights the imperative of including pathogen standards in national regulations for wastewater reuse.

Pesticides in surface freshwater primarily originate from their emissions in agricultural lands, potentially leading to violations of surface freshwater quality standards. To aid global regulatory agencies in effectively managing surface freshwater quality by estimating and controlling pesticide emission rates, this study proposes a hierarchical screening approach for countries and regions worldwide to select appropriate modeling tools. Hierarchical indicators are introduced to classify countries globally, considering their spatial distribution areas, pesticide emission conditions, and legislative systems. Consequently, different categories of countries are matched with suitable model groups, such as the standard model group for regulatory scenarios, the general model group for continental scenarios, and the advanced model group with high spatial resolution. Results indicated that a total of 193 countries worldwide were categorized into six country groups, of which 153, 34, and 6 countries were found to fit the standard, general, and advanced model groups, respectively, based on the model assignments for these country groups. Furthermore, 12 commonly used pesticides were selected to demonstrate the back-calculation process, which estimates the pesticide emission rate (input) by pesticide surface freshwater quality standards (output) by standard and general model groups. The Advanced model group was not applied in this process due to its intensive computation. An approximate approach was developed to simplify the calculation of the emission rate factor of pesticides using the PWC and TOXSWA selected in the standard model group as well as SWAT in the general model group, serving as a demonstration. This approach can be applied to control pesticide emission rates from surface freshwater quality standards across countries that fit in the standard and general model groups. The results highlight that pesticide fate models selected through the hierarchical screening approach, can assist global countries in establishing a quantitative relationship between pesticide emission rates and surface freshwater quality standards, which can help global agencies manage pesticide emissions and freshwater quality from a legal perspective. There is a need to update and simplify suitable advanced model for calculation demonstration in future studies to aid in pesticide management. Further research is needed to thoroughly investigate pesticide emissions and freshwater residue concentrations under varying conditions.

Background

Water bodies are affected by chemical contamination, including micropollutants, which is not fully captured by conventional chemical monitoring methods. The inclusion of integrative, effect-based in vivo and in vitro methods in standardized assessment procedures offers the possibility of bridging discrepancies between chemical and biological assessments and has already been proposed in several studies. However, there is a need to develop a comparable ecotoxicological assessment system for surface waters as for chemical and ecological status. This study aims to contribute to this discourse by investigating the temporal and spatial variation of ecotoxicological effects by assessing water grab samples of 15 different sites in central Germany over the course of 1 year using different in vitro assays.

Results

The level of measured estrogenicity and anti-estrogenicity varied between the four measurement campaigns, while baseline toxicity, dioxin-like effects and mutagenicity showed relatively constant detectable effects over the study period. The impact of conventionally treated wastewater appeared to be one of the strongest influencing stressors, as direct comparisons of ecotoxicity upstream and downstream of wastewater treatment plant dischargers showed a significant increase for most of the conducted bioassays. Comparison of the measured estrogenicity with proposed threshold values showed effects within ecotoxicologically relevant ranges.

Conclusions

Bioassays record ecotoxicological effects on the basis of specific modes of action, allowing whole groups of substances to be identified as pollutants. Recording ecotoxicological status in this way is a useful complement to water assessment tools and can contribute to successful water management. Although most of the assays in this study were very consistent in detecting strong anthropogenic influences, possible temporal variations of individual assays should be taken into account when planning sampling strategies to improve the comparability of results.

Background

Insecticides are sprayed on external building walls for treatments against crawling and flying insects. These applications can lead to drift into non-target areas and thus to undesirable environmental pollution. This emission pathway needs to be considered during exposure assessments within product authorisations to assess potential environmental risks. However, now, there is only one default value for deposition that is used in all calculations based on the Emission Scenario Document of the Organization for Economic Co-operation and Development at a distance of 50 cm to the treatment area. This is not sufficient for a risk assessment.

Results

When applying a chemical barrier of 50 cm at the bottom of the building wall, wind direction had the greatest influence on drift, while changing the nozzle type had no significant effect. Compared with the measured ground sediments, the OECD default value was deemed to be realistic at a distance of 57 cm from the treatment area. When treating the entire building wall, the wind direction as well as the nozzle used show significant influence on the measured values of drift. The default value for deposition proposed for modelling environmental exposure in OECD document ESD PT18 No. 18 was exceeded. Thus, the exposure estimation might not be protective enough.

Conclusion

Drift values used for the environmental exposure assessment of biocidal products during treatments of building walls should be adapted. This is especially relevant for treatments of entire building walls, where the current default value was exceeded for all distances from the building wall. Wind direction and nozzle type can reduce environmental impact. This finding can be used as a measure to reduce unnecessary exposure in the environment in the future.

Background

Wastewater can contain a complex mixture of organic micropollutants, with both chemical analysis and effect-based methods needed to identify relevant micropollutants and detect mixture effects. Solid-phase extraction (SPE) is commonly used to enrich micropollutants prior to analysis. While the recovery and stability of individual micropollutants by SPE has been well studied, few studies have optimized SPE for effect-based methods. The aim of the current study was to develop and evaluate two standard operating procedures (SOPs) for the enrichment of micropollutants in preparation for chemical analysis and bioanalysis, one covering a broad range of chemicals and the other selective for estrogenic chemicals.

Results

Pristine surface water spiked with > 600 micropollutants was used to develop a generic extraction method for micropollutants with a wide range of physiochemical properties, while water spiked with estrogenic chemicals was used to identify a selective extraction method. Three different SPE sorbents were tested, with recoveries of individual chemicals and effect in assays indicative of mutagenicity, estrogenic activity, and fish embryo toxicity assessed. The sorbent HRX at pH 7 was selected for the generic extraction method as it showed the best recovery of both individual chemicals and effect in the bioassays. The sorbent HLB at pH 3 showed optimal recovery of estrogenic chemicals and estrogenic activity. The two optimal SPE methods were applied to spiked and unspiked wastewater effluents, with the concentrations of detected chemicals and observed effects similar to those of previous studies. The long-term storage of both extracts and SPE cartridges for estrogens and estrogenic activity after extraction with the HRX and HLB methods were evaluated, with estrogenic effectiveness close to 100% after 112 days when HLB was used.

Conclusions

HRX is recommended for generic extraction, while HLB is optimal for the selective extraction of estrogenic micropollutants. However, if a laboratory only wants to use a single SPE sorbent, HLB can be used for both generic and selective extraction as it yielded similar chemical and effect recovery as HRX for a wide range of micropollutants. This paper is supplemented by the final SOP that includes a variant for generic extraction and one for the extraction of estrogenic chemicals.

Background

Archaeological sites are increasingly threatened by climate-related hazards. In response, heritage management authorities initiated projects to document damage and plan risk assessment measures. We present a project initiated after the heavy rainfall and subsequent flood event of July 2021, which involved extensive fieldwork to document the damage to archaeological sites in the Rhineland. We use this database to characterise and assess the damage and investigate site-specific and geospatial factors to identify potential predictive parameters for site damage.

Results

During fieldwork, we found that the flood damaged 19% of the 538 archaeological sites surveyed. The majority of damaged sites are relatively recent, dating from the medieval or modern periods, and are associated with the use of water power. Damage was mainly caused by erosion, floating debris and washout, e.g. mortar. In a case study, we tested the option of comparing pre- and post-disaster Airborne Laser Scanning elevation data to identify damages. It showed that not only the damage detected during fieldwork was found but also additional areas of loss. In general, however, and quantified based on the entire dataset, the ordnance survey Airborne Laser Scanning data were of limited use for monitoring flood-related damage and could not replace fieldwork. Our statistical analysis of possible risk factors, including both site characteristics and geospatial parameters, using Naïve Bayes Modelling and chi-squared tests, showed that no set of parameters could consistently predict the preservation or damage of archaeological sites across all catchments. In contrast, some external geospatial factors correlated with the occurrence of damage.

Conclusions

The study highlights both the strengths and limitations of the approaches used to assess and predict the damage to the archaeological heritage in the 2021 flood zones of the Rhineland. It also demonstrates the complexity of the data and spatial processes involved, which limits generalisation but can still inform decision-making for archaeological site management and on-site protection measures in flood-prone areas. With the prospect of more frequent heavy rainfall due to climate change, the specific needs of the archaeological heritage should be integrated into broader prevention and disaster management plans.

Background

The flood in July 2021 is considered one of the largest flood disasters in Western Europe in decades, with massive socio-economic consequences. The potential emission and remobilization of anthropogenic pollutants can lead to additional environmental consequences, which need to be addressed in long-term mitigation strategies. The Inde River and its tributary, the Vichtbach River, form a catchment located at the transition from the low mountain ranges of the Eifel to the lowlands of the Lower Rhine Embayment in Germany. The area has been an industrial and mining hotspot for centuries, making it a high-risk area for flood sediment pollution. The present study provides an ecotoxicological screening of flood sediments of the Vicht–Inde catchment to gain an impression of the degree of contamination by organic pollutants by means of in vitro effect-based method. Sediment samples were collected within days after the flood and fractionated prior to biotesting, and supportive instrumental geochemical analysis was performed.

Results

Flood sediments did not reveal estrogenic potential, which was included in the testing strategy as a relevant endpoint for industrial chemicals and untreated wastewater. In contrast, moderate-to-high dioxin-like activity was observed in 70% of the sediment samples with a peak dioxin-like potential at the restored section of the Inde. Overall, four hotspot samples were identified as at risk, which aligned mostly with the high concentration of organic pollutants including PAHs and PCBs. The fractionation allowed the identification of PAHs and their derivates as the most likely toxicity drivers for dioxin-like activity in the sediments of the Vicht–Inde catchment.

Conclusion

The results provide first information on the prioritization of hotspot locations at risk for a detailed ecotoxicological profiling and a post-flood monitoring of organic contamination. The identified sinks of contamination in the floodplain areas can be considered a source for remobilization of pollution in future flood events, which is highly relevant for the receiving Rur River.

Background

Thermal upgrading is an important element in the economic transformation of Poland towards a low-emission economy. This paper presents the results of research into the current status and plans of inhabitants of rural areas in Poland with regard to thermal upgrading of residential buildings and other buildings used in the agricultural activity of the study participants. The main purpose of the article is to identify thermal modernization needs and to analyse factors influencing individual thermal modernization plans in terms of replacement or modernization of heating systems. A key element of the analyses was the issue of upgrading priorities and the dependency between declared intentions in terms of thermal upgrading work and the production and economic features of the farms studied.

Results

The main research material were surveys conducted with a randomly selected sample of 480 farming households in Poland. The analyses used, amongst others, multiple correspondence analysis (MCA) to determine and assess the relationships between the variables studied. Detailed correspondence analysis shows that there are strong dependencies between plans for thermal upgrading of farm buildings and the system of agricultural production (φ² = 0.1503), the economic size of farms (φ² = 0.1100), and the location of farms (φ² = 0.0947).

Conclusions

The research showed that there is a need for thermal upgrading in the examined area of study, especially with regard to the replacement or modernisation of heating systems. The issue of thermal upgrading of residential and farm buildings in rural areas in Poland requires support and engagement at all levels of administration, as well as the modernisation of assistance programmes.

Pharmaceutically active compounds (PACs) are ubiquitous contaminants that can pollute the environment. This study critically analyzes the sorption of PACs to soil materials based on 137 published papers encompassing 106 PACs and 212 soil materials. The batch technique is commonly employed for sorption studies of PACs to soil, but the experimental setups vary in terms of the type and number of PACs, mixing time, solid to liquid (S/L) ratio, solution type, range of initial concentration, and bio-inhibition method. Sorption competition among PACs or between PACs and dissolved organic matter occurs for certain cases. Linear or close to linear behavior was reported for sorption of many PACs to soil, but sorption of some PACs deviates from linearity. The reaction of PACs to soil is fast at the initial stages but slows down as it approaches equilibrium. PACs characteristics, soil properties, and solution attributes intricately influence the sorption process. Zwitterionic PACs exhibit the highest sorption affinity, whereas neutral PACs display increased sensitivity to soil hydrophobicity. The average sorption coefficient (K) ranges from 0.0915 mL/g for anionic sulfonamides to 84725.5 mL/g for zwitterionic norfloxacin. An increase in the molar volume corresponds to heightened sorption for cationic PACs and reduced sorption for anionic PACs. Increasing solubility, soil organic carbon, cation exchange capacity, S/L ratio, and soil surface area while decreasing pH, ionic strength, and temperature result in an increase in K. The values of K determined by the batch technique are higher than their column-determined counterparts, possibly due to variations in the employed residence times between the two systems. Several models have been developed to estimate K of PACs, but they are limited in their applicability to specific PACs and soil types. Future research related to sorption of PACs to soils has been suggested.

This study highlights drought forecasting for understanding the semi-arid area in India, where drought phenomena play vital role in the irrigation, drinking water supplies, and sustaining the ecological with economic balance for every nation. Therefore, drought forecasting is important for the future drought planning based on the machine learning (ML) models. Hence, The Standardized Precipitation Index (SPI) at 3- and 6-month periods have been selected and used for future drought forecasting scenarios in area. The combinations of ten inputs SPI-1- and SPI-10 were used for predicting modeling for SPI-3 and SPI-6 timescales, that modeling developed based on the historical SPI datasets from 1989 to 2019 years. The SPI-3 and SPI-6 maximum and minimum values are shown SPI-3 (2.03 and -5.522) and SPI-6 (1.94 and -6.93). The SPI is a popular method for estimating the drought analysis and has been used everywhere at global level. The developed models have been compared with each other, with the best combination of input variables selected using subset regression models and sensitivity studies. After that, the active input parameters were used for forecasting of SPI-3 and SPI-6 values to understanding of drought in semi-arid area. The finest input variables combination have been used in the Ml models and established the novel five models such as robust linear regression, bagged trees, boosted trees, support vector regression (SVM-Linear), and Matern Gaussian Process Regression (Matern GPR) models. Such kind of models first time has been applied for the forecasting of future drought conditions. Whole models were fine and improved modeling by using hyperparameters tuning, bagging, and boosting models. Entire ML models’ accuracy was compared using different statistical metrics. Compared with five ML models accuracy, we have found that the Matern GPR model better accuracy than other ML models. The best model accuracy is R² = 0.95 and 0.93, RMSE, MSE, MAE, MARE, and NSE values, respectively, for predicting SPI-3 and SPI-6 values in the area. Therefore, the Matern GPR model was identified as the finest ML algorithm for predicting SPI-3 and SPI-6 associated with other algorithms. This research demonstrates the Matern GPR model's efficacy in predicting multiscale SPI-3 and SPI-6 under climate variations. It can be helpful in soil and water resource conservation planning and management and understanding droughts in the entire basin areas of the country India.