International Journal of Environmental Research最新文献

Abstract

Eutrophication of fresh waterbodies is a global phenomenon that is exacerbated by increases in agricultural activities, industrialization, and urbanization, all driven by the global increase in human population. This paper reviews the state of inland waterbodies in South Africa, identifying the major drivers of eutrophication and discussing how different sectors of the economy are negatively impacted by eutrophication. Data indicate that up to 76% of major water impoundments and approximately 70% of major river systems are eutrophic to hypereutrophic and experience protracted periods of cyanobacterial blooms, particularly in the summer months. Negative impacts of eutrophication on the agricultural sector, potable water supply and tourism are well documented and are becoming more explicit. Evidently, nutrient loading patterns into water bodies have changed and become more complex. Although wastewater treatment plants remain the major contributors of nutrient loads to most waterbodies, non-point sources including agricultural runoff, untreated sewage from leaking and overflowing sewer systems, as well as runoff from informal settlements, also make substantial contributions. As a result, the strategies employed to prevent eutrophication, including within-waterbody remediation programs have fallen short in reducing the trophic status of water impoundments and thus ameliorating the symptoms of eutrophication. Tailor-made, integrated management initiatives that target point source, non-point source, and internal nutrient loads are, therefore, required.

Salinity and drought stress pose critical challenges to crop productivity, including roselle (Hibiscus sabdariffa L.). Using waste agriculture as a natural source of fertilizer to promote the activity of beneficial soil microorganisms has the potential to help agriculture in abiotic stress-affected areas by increasing plant nutrient uptake and ecological sustainability. We investigate the ability of BioSoy⁺ biofertilizer, which contains salt and drought stress-tolerant plant-growth-promoting rhizobacteria (PGPR) and soybean meal, to improve roselle growth under unfavorable conditions. Rhizobacteria tolerant to salt and drought stress were isolated, and evaluated for growth-promoting traits and pathogen inhibition under stress, and their identity confirmed by 16s rRNA gene sequencing. The impact of BioSoy⁺ on roselle growth and soil stability index during salt and drought stress was evaluated. Salt- and drought-tolerant PGPR strains Pseudomonas nicosulfuronedens AP01 and Bacillus velezensis CC03 were identified as the major component for biofertilizers. Under 2% NaCl stress, Pseudomonas nicosulfuronedens AP01 displayed outstanding phosphate solubilization and robust Sclerotium rolfsii pathogen suppression. BioSoy⁺ biofertilizer application significantly enhanced roselle growth under salt and water-limited conditions. BioSoy⁺ treatment, for example, boosted biomass by 194.74% and 68.29% at 25% field capacity and 100 mM NaCl conditions, respectively. BioSoy⁺ also increased relative water content, microbial activity, proline accumulation, and chlorophyll content, indicating stress reduction and better photosynthetic efficiency. This study highlights the importance of PGPR in alleviating the negative impacts of salt and drought stress. Furthermore, it emphasizes the feasibility of soybean meal as a biofertilizer carrier, fostering sustainable agricultural practices.

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Abstract

This article presents a method for evaluating the environmental benefits of implementing Product-Service Systems (PSSs) and Smart PSS with application to the heating systems field. The proposed PSS-oriented life cycle assessment method aims at addressing the specificities of PSS and Smart PSS, representing PSS variety and dealing with uncertainty sources resulting from the PSS context. Besides environmental analysis, the method supports decision-making by comparing different PSS scenarios. This study focuses on the challenges of a generic configuration of the life cycle assessment method and the rigorous handling of uncertainty sources, while an industrial case study reports a real case of PSS design decision-making.

Abstract

Ecological concrete has excellent water and air permeability, which not only is conducive to plant growth but also allows surface water to infiltrate underground and intercept pollutants. The performance of ecological concrete is largely determined by the nature of the raw materials and their relative content. Therefore, mastering the optimal design method for the mix proportion of ecological concrete is crucial to achieving good performance. In the current research, there is a lack of systematic intelligent decision-making models for predicting performance and optimizing mix proportions. In this paper, four factors, namely mechanical properties, water permeability, decontamination properties, and planting properties of ecological concrete, were considered when evaluating the comprehensive performance of ecological concrete. The evaluation was conducted using the analytic hierarchy process (AHP). The gray wolf optimizer (GWO) was introduced to enhance the backpropagation (BP) neural network, and an optimization model for finding the optimal ecological concrete mix proportion was established. The optimal mix proportion of two types of typical ecological concrete, one for filtration and one for plant growth, was discussed. The results indicate that the AHP-GWO-BP model calculates the optimal mixing proportion of filtration ecological concrete as follows: The diameter of coarse aggregate is 10–15 mm, with adsorbed coarse aggregate accounting for 49.7%, a component ratio is 118%, the water–cement ratio should be 28.7%, and the silica fume mix ratio should be 32.1%. According to the given parameters, the performance test of ecological concrete is conducted, with a coarse aggregate size of 12 mm. The results showed that under these parameters, the compressive strength was 12.3 MPa, the flexural strength was 3.35 MPa, the water permeability coefficient was 14.87 cm s⁻¹, the porosity was 27.23%, the removal rate of total nitrogen was 80.56%, the removal rate of total phosphorus was 67.33%, the pH was 9.16, and the plant dry weight was 9.37 g. The optimal mix proportion of the planting ecological concrete is as follows: The diameter of the coarse aggregate is 20–25 mm, the adsorbed coarse aggregate accounts for 49.7%, its component ratio is 138%, the water–cement ratio should be 27.3%, and the silica fume mix ratio should be 34.1%.

One of the basic strategies to reduce vulnerability in social systems facing fluctuations or climate change is to increase the resilience of communities to the disturbance and turmoil created in ecological systems. The aim of this study was to investigate multi-level resilience based on social heterogeneity under climate fluctuations in Nodooshan watershed of Yazd province. The survey method and the questionnaire were used to determine the resilience of local beneficiaries. The sample size was calculated using the Cochran sampling formula, and 102 people were selected by random sampling method from 6 villages in Nodooshan watershed. In order to determine the degree of resilience of users in Nodooshan watershed, social network analysis (SNA) was used by the full network method in three ties of social capital (trust, collaboration, and information exchange). The result of the highest effect size in the collaboration network of Nodoushan watershed beneficiaries is 57.75, in the trust network is 45.41 and in the information exchange network is 44.17. Findings show that social capital has led to more resilience of beneficiaries in drought conditions, and the rate of resilience in villages that are more exposed to drought is higher than in villages less exposed to drought. However, the results, in general, show the unfavorable situation of beneficiaries in terms of social capital. In addition, the effect of social network metrics on resilience in the face of climate change in different layers of social heterogeneity, as well as the structure of the exploitation system, is distinct. As a result, developing trust-building programs that address priority issues, resolving people's conflicts through increased and established inter-sectoral communication, and implementing multilevel governance are strongly advised. Therefore, by exploiting these results, planners and policymakers can help and plan to improve the resilience of rural communities faced with drought, self-reliance, and rural development.

Partial nitritation is a promising technology for wastewater treatment systems and, in symbiosis with other nitrogen removal approaches (i.e., Anammox bacteria), is attractive for reducing costs compared to conventional technologies. However, the intrinsic problems related to the different characteristics of the effluent induce unstable process conditions, including the subsequent accumulation of nitrate, which also reduces the partial yield of nitritation. Several studies highlight the persistent obstacles in preventing nitrate accumulation by nitrite-oxidizing bacteria, identified as the main challenge in the partial nitritation process. Consequently, this study conducted a comprehensive literature review, exploring various strategies to overcome these bottlenecks. Addressing the suppression of ammonia-oxidizing bacteria and the inhibition of nitrite-oxidizing bacteria involved consideration of operational strategy. Notably, pH emerged as an essential factor affecting microbial activity and process stability, influencing the efficiency of biochemical reactions. In addition, other interferents, such as organic compounds and metals, can influence the health and activity of microorganisms, affecting the overall effectiveness of the nitrogen removal process. The systematic control of various environmental and operational variables is essential for the stability of the process, demonstrating that a single strategy does not define the control of partial nitritation in wastewater. To date, maintaining dissolved oxygen in the range of 0.4 to 1 mg O₂ L⁻¹ and temperatures between 25 and 35 °C remains the most viable strategy for promoting stable partial nitritation. Finally, it is imperative to carry out further studies to develop control strategies and technologies, guaranteeing the efficiency of large-scale nitrogen removal systems and maintaining environmental safety standards.

Climate change has a potentially negative impact on the overall vitality of vegetation in both forested and agricultural areas. A comprehensive understanding of the interaction between climate and vegetation across various land cover types holds significant importance from multiple perspectives. This research examined the current state of vegetation trends and their interplay with climate parameters, specifically temperature and precipitation. Additionally, it aimed to provide insights into the anticipated changes in these climate parameters in the future, across the entire area of the Republic of Serbia. The vegetation was observed using the Normalized Difference Vegetation Index (NDVI) obtained from AVHRR/NOAA 11 satellite for the vegetation season (May–October) from 1981 to 2021, while the climate data records used the examination of the relationship between climate indicators and vegetation were monthly mean 2m temperature and precipitation obtained from the ERA5-Land (from April to October). The nonparametric Mann–Kendall test implemented with the Sen's slope estimator and the Pearson correlation coefficient (r) was utilized to identify trends (for the NDVI and climate variables) and the strength of the correlation, respectively. To obtain the information of temperature and precipitation change in future (from 2071 to 2100), the ensemble mean of the eight climate models, for vegetation period and summer season (June–July–August) from the EURO-CORDEX database was used. Results show relatively high NDVI values (> 0.5) over the entire area and the statistically significant (p < 0.005) positive NDVI trend increasing (up to 0.0006 ({text{year}}^{-1}))from the north (mainly agriculture cover) to the south (forest cover). In agricultural areas, a positive statistically significant correlation (r = 0.4–0.6, p < 0.005) indicates that the quality of vegetation cover in rainfed agriculture is directly dependent on the amount of precipitation, which serves as the sole source of moisture input. In contrast, the situation differs in forested areas where the correlation between NDVI and precipitation is often statistically not significant (p > 0.005) indicating that forests, because of their characteristics, are less dependent on the amount of precipitation. Regarding temperature, in agricultural areas, there is a positive correlation with NDVI, although it does not reach statistical significance. Conversely, in forested areas, a significant positive correlation is observed between NDVI and temperature which even positively contributes to the development of forest vegetation. In future, the recorded decline in precipitation (a substantial 22.72% drop) and the concurrent rise in temperature (up to 4.39 °C) in vegetation period, until 2100 might impact the reduction of NDVI.

Abstract

Oil pollutants affect the mechanical properties of soils differently. The effect of the kind of oil pollutants on the geotechnical characteristics of a type of soil is an interesting subject that has been examined less in previous studies. The results of this research can be used in designing structures built on soils that are likely to be contaminated with oil pollutants. This study comprehensively investigated the effect of the type of pollutants on the mechanical properties of sandy clay soil to provide the necessary parameters in the remediation plan for soils contaminated with various oil pollutants. A series of laboratory tests, including pH, standard compaction, one-dimensional consolidation, unconfined compressive strength (UCS), ultrasonic pulse velocity (UPV), falling head permeability, and direct shear, was conducted on the clean and polluted samples. Scanning electron microscopy (SEM) micrographs confirmed that oil pollutants change the soil structure into a flocculated but dispersed one. In addition to the low dielectric constant of oil pollutants, their high viscosity played an important role in altering the geotechnical parameters of clayey sand. The higher the viscosity of the oil pollutant, the higher the maximum dry density (MDD), cohesion coefficient, compression index (Cc), swelling index (Cs), and permeability coefficient of oil-polluted soil. The samples polluted with used motor oil and crude oil, due to their high viscosity, had the greatest drop in compressive strength and shear strength, respectively; whereas the kerosene-polluted sample, due to its low viscosity compared to other oil pollutants, had the greatest rise in compressibility. Thus, in geotechnical plans, special attention should be paid to the bearing capacity and settlement of clayey sand contaminated with crude oil and kerosene, respectively.

This study used parallel factor method (PARAFAC), self-organizing map (SOM), and random forest models to study the dissolved organic matter (DOM) sources and characteristics in rivers with varying non-point source inputs. The artificial canal Cihuai New River (CH) and the Gouqu (GQ) which are heavily polluted by agricultural surface sources were selected as the study objects. The PARAFAC model resolved four chemical components. C1 comprises two peaks, C1 (T1) (UVC fulvic acid) and C1 (T2) (humic-like acid). C2 includes two peaks, C2 (T1) (tyrosine-like protein) and C2 (T2) (tryptophan-like protein). C3 has two peaks, C3 (T1) (humic-like) and C3 (T2) (UVA fulvic acid). C4 is identified as humic-like fulvic acid. The SOM model shows that the degree of humification in the GQ, which is influenced by agricultural non-point source pollution, is higher than that of the unaffected CH. The primary source of humic substances in the river is agricultural non-point source pollution. CH is influenced by surrounding human activities and the eutrophication of water bodies, resulting in a higher level of autochthonous characteristics and biological activity in DOM. Random Forest model indicated that the C3 was the most sensitive (R² = 0.88) to river’s changes and therefore it is a good indicator of river’s water quality. And NH₄⁺ has a strong driving effect on the water quality of both rivers. Principal Component Analysis (PCA) reveals that the agricultural river DOM (GQ) is mainly composed of humic substances, while the artificial river DOM (CH) is predominantly derived from autochthonous sources. The combination of PARAFAC, SOM, and random forest methods helps overcome the limitations of traditional approaches and provides a scientific basis for the management of river water quality pollution.