Double-stranded RNA (dsRNA)-based biopesticides are a promising new method of pest management. These biopesticides leverage the endogenous RNA interference pathway to selectively regulate expression of key genes involved in growth and development in pests, providing the potential to minimize harmful environmental effects by highly specific targeting. As dsRNA-based biopesticides are presented for regulatory review, evaluating potential off-target effects on nontarget organisms (NTOs) in a manner that may be unique to this novel sequence-specific mode of action is crucial. To address this, we propose here a bioinformatics framework for consideration of sequence-specific off-target effects in NTOs. This framework includes careful consideration of NTOs based on potential exposure and susceptibility and recommends standardizing analyses to search for 21-nucleotide stretches of perfect identity and 80% overall identity between the dsRNA and off-target transcripts. We recommend a three-pronged approach to ensure a comprehensive risk assessment: (a) phylogenetic analysis of gene orthologs that defines the taxonomic scope of sequence similarity, (b) broad searches of large databases to identify potential unexpected similarity in distantly related species, and (c) full transcriptome analyses in NTO species of particular concern for a thorough understanding of all potential hazards. Finally, we recommend considering the results of bioinformatic analyses in the context of risk characterization, which means considering likely exposure to the dsRNA-based pesticide and potential susceptibility or barriers to dsRNA uptake. This approach enables a robust ecological risk assessment for dsRNA-based biopesticides and a regulatory path forward for this promising new pest management tool.

A comprehensive analysis of the bioaccumulation of three cyclic (namely, D4, D5, and D6) and five linear (namely, L2, L3, L4, L5, and L6) volatile methylsiloxanes (VMS) in biota was conducted by reviewing 50 published articles and laboratory reports on aquatic (82%) and terrestrial species (18%). A total of 178 bioaccumulation values were evaluated employing a quantitative weight-of-evidence (qWoE) approach provided by the Bioaccumulation Assessment Tool. Considerable variability of bioconcentration factor (BCF) and bioaccumulation factor (BAF) values was observed for VMS in aquatic organisms, which ranged from below to above their respective regulatory threshold values. The frequency of evidence for non-bioaccumulation (ie, BCF or BAF <2000) was ≥50% for D6, L2, L5, and L6. Conversely, laboratory biomagnification factor (BMF) values were generally (≥71%) less than 1, indicating low bioaccumulation potential through dietary uptake. Field BMFs displayed more variability but still suggested a low bioaccumulation potential. Despite the majority (≥65%) of trophic magnification factors (TMFs) in aquatic food webs being below 1, the broad range of TMF values for all VMS examined indicates potential uncertainties introduced by environmental factors in the target environments (e.g., chemical exposure gradient) and sampling bias. Overall, lines of evidence (≥71%) suggest that cyclic and linear VMS generally do not bioaccumulate in aquatic species, with dietary uptake being the primary pathway. For terrestrial species, primarily rats, predicted and field BMFs were less than 1 at 37 °C, primarily via respiratory elimination. Field TMFs for terrestrial food webs, including invertebrates and various bird species with body temperatures of 18 and 40 °C, respectively, were sourced from a single study, where D4 demonstrated trophic dilution, while D5 and D6 generally did not biomagnify in this terrestrial food web.

Driven by the high content of organic materials in municipal solid waste (MSW) of 70% in Iran and the growing demand for mineral fertilizer, refinement of composting technology is imperative. In the pursuit of environmental sustainability, further investigation into the life cycle assessment of the composting process and end-of-life waste management must be conducted. Hence, this study scrutinizes the environmental burdens of the composting plant operation from cradle to gate. Because 50% of raw MSW was not converted to compost, its final disposal was evaluated based on incineration, landfill, and integrated approaches. The results indicated marine and freshwater ecotoxicity of the composting process (>50.4 kg 1,4-DB eq). Heavy metal and gas emissions during the MSW decomposition were the pivotal parameters for most impact categories. Carbon dioxide emission intensified climate change by 3,523 kg CO2 eq; however, waste incineration led to emission savings of 98.75%. The environmental benefits of incineration were observed in 13 impact categories alongside a net-negative value for natural land transformation. Landfilling also induced savings in freshwater eutrophication and metal depletion by 98.67% and 99.08%, respectively. Unlike previous studies relying on generalized data, this study uses detailed plant-level operational data and scenario-based modeling from Sistan and Baluchistan province. This approach provides realistic impact estimates and decision-relevant insights.

Soil mesofauna field studies conducted for ecological risk assessments of plant protection products (PPPs) require expertise for interpretation. The new statistical Closure Principle Computational Approach Test (CPCAT; introduced for Poisson-distributed count data) is proposed as alternative for established methods. However, the biological relevance of potential effects remains unclear. One aim was to investigate how to assess biological relevance. Biological Control Ranges (BCR) were calculated for each taxon and sampling time point within individual studies and it was compared whether the average abundance of a treatment group is in- or outside of the BCR. High control abundance variability of Collembola resulted in largely varying BCR values between studies. The second aim was to investigate performance of different statistical methods. Statistical analysis revealed that abundance data exhibited overdispersion in the majority of cases, instead of Poisson-distribution. Significant differences were observed in more than 50% of the comparisons using CPCAT, even before test item application happened in the field. Post-application, most statistical significances determined by CPCAT occurred despite the absence of a rate-response relationship and the arithmetic mean abundance values in the assigned treatment plots being within the BCR; thus, they should be considered as false positive results. In contrast, the Dunnett's test and Ranked Dunnett's test, either considering normally distributed data or being independent from the data distribution, barely detected a significant difference at pre-application when the abundance average values of assigned treatment plots were within the BCR pre- and post-application. In conclusion, pre-requisites for CPCAT (Poisson distribution, no over- or underdispersion of data) do not apply in the majority of the cases examined here. Holistic interpretation of field data needs to consider the ecological relevance of observations (via comparison with the BCR), presence of a rate-response-relationship, onset, scale, and pattern of the response, instead of solely focusing on statistics.

Understanding the removal of a chemical in a wastewater treatment plant (WWTP) is important when performing chemical risk assessments. Chemicals undergoing assessment often have limited experimental measurements of physicochemical properties, biodegradation rates, and WWTP removal efficiencies. Models available to risk assessors to predict WWTP removal efficiencies are best used with high-quality input data and knowledge of plant conditions, information often unavailable when performing chemical risk assessments. In this work, we outline the development of the Canadian A.I. Removal Rate Estimator (CAIRRE), an artificial intelligence (A.I.) model suite designed to estimate removal efficiencies from secondary WWTPs. CAIRRE was trained on median experimental removal efficiencies for 161 chemicals across 59 secondary WWTPs in Canada, the USA (California), and various other locations curated from literature. The CAIRRE regression model has a validation Pearson R2 of 0.81 based on leave-one-out-validation (LOOV) results. When used to predict effluent concentrations for a test set containing 53 chemicals not seen during model training, CAIRRE was able to reproduce experimental observations with a Pearson R2 of 0.91. The CAIRRE model outperformed existing mechanistic and fugacity WWTP models which rely on physical-chemistry and biodegradation data provided by the user. This work demonstrates that the A.I. modeling approach taken in the development of CAIRRE is a promising strategy for predicting removal efficiencies of chemicals from secondary WWTPs.

The European Union's (EU's) Green Deal initiatives, including the Farm to Fork Strategy and the Chemicals Strategy for Sustainability, emphasize the need for developing plant protection products (PPPs) that meet safety and sustainability goals. In the EU, PPPs are regulated under Regulation (EC) No. 1107/2009, which sets approval criteria to ensure human health and environmental safety. This legislation is complemented by the sustainable use of pesticides (Directive 2009/128), which aims to achieve sustainable pesticide use by minimizing risks to human health and the environment, while promoting use of integrated pest management and nonchemical alternatives. Although both legislations address the conditions of placing PPPs on the market and their use, neither directly addresses the broader aspects of sustainability, such as the life cycle impacts, resource efficiency during design and manufacture, and the socioeconomic dimensions of sustainability. The safe- and sustainable-by-design framework of the EU Commission's Joint Research Centre offers a holistic approach to chemical product innovation, minimizing risks and maximizing sustainability throughout a chemical's life cycle. This framework, combined with existing safety regulations, can advance the sustainability of PPPs in line with the European Green Deal and the Chemicals Strategy for Sustainability. Agrochemical manufacturers have embedded into their innovation pipelines practices that align with the safe- and sustainable-by-design framework, but approaches tend to be company specific and lack standardized metrics. Incorporating well-defined sustainability criteria and incentives for manufacturers would accelerate the development of PPPs that contribute to long-term agricultural sustainability, safeguard human health and the environment, and ensure food security in line with sustainable development goals.

Pharmaceutical residues in aquatic environments pose a growing concern, mainly driven by the increasing use of medications. This study investigated the occurrence of four pharmaceutical compounds, namely azithromycin (AZI), prednisolone (m-PRD), prednisone (PRD), and dexamethasone (DEX) in surface waters across eight different sites in the Free State Province, South Africa, during summer and winter 2024. Samples were collected from upstream, downstream, and the wastewater point of discharge at each site. Using a validated liquid chromatography-mass spectrometric (LC-MS) method, all target analytes were detected, with DEX (41.79 µg/L) and AZI (19.32 µg/L) recording the highest mean concentrations in summer and winter, respectively. Moreover, AZI showed the highest detection frequency across all sites and seasons. Spatial variation was evident, with concentrations of analytes differing among upstream, downstream, and points of discharge, revealing the influence of wastewater input and other site-specific factors. The consistent presence of these pharmaceutical residues in surface waters pinpoints a potential risk to aquatic ecosystems and raises concerns about human health implications resulting from the long-term environmental presence of these compounds. The findings underscore significant seasonal fluctuations in pharmaceutical residue levels, highlighting potential risks to aquatic ecosystems and public health. These results call for targeted monitoring efforts and evidence-based regulatory frameworks to mitigate contamination and guide sustainable water resource management in South Africa.

Pesticide residues in soil samples were analyzed by a gas chromatograph-mass spectrometer. To evaluate the ecological risks posed to significant soil organisms, including earthworms (Eisenia fetida), springtails (Folsomia candida), and nitrogen-mineralizing microorganisms, we employed toxicity exposure ratios and risk quotients to assess potential impacts. The rank order of pesticides in soil based on their concentration was p,p'-DDE (dichlorodiphenyldichloroethylene) (M ± SD; 37.48 ± 16.76 μg kg-1) > propoxur (23.94 ± 10.71 μg kg-1) > propargite (22.09 ± 9.88 μg kg-1) > α-endosulfan (11.56 ± 5.17 μg kg-1) > malathion (10.22 ± 4.57 μg kg-1) > fenthion (7.78 ± 3.48 μg kg-1) > … > fenitrothion (0.11 ± 0.05 μg kg-1). Exposed soil organisms of F. candida and nitrogen mineralization are at risk due to chronic exposure to chlorpyrifos and fenthion, with TERmax toxicity exposure ratios of 0.86 and 1.20, respectively. The cumulative risk quotient of 5.3 indicates that the detected pesticide mixtures would pose significant ecological risks in traditional farming study areas. Therefore, to preserve soil quality and mitigate the risks associated with pesticide use, it is crucial to develop targeted integrated crop protection strategies.

There is a growing recognition that sediments dredged to maintain navigation and port infrastructure are valuable resources that can be placed in the aquatic environment to achieve ecological benefits if managed appropriately. However, specific interactions and long-term influences of placement on local aquatic ecosystems, particularly fisheries, remain to be fully explored. Therefore, the aim of this review was to identify and synthesize key factors influencing the outcomes of stable underwater features (e.g., berms, reefs, mounds) created from open water placement (OWP) of dredged sediments on fish habitat. Emphasizing ecological, biological, and artificial habitat perspectives, the review explored historical OWP techniques and features and their habitat alterations and identified reported physical, biological, and chemical factors that influence fish. Results from this review suggest that underwater features can influence fish habitat by changing benthic relief, voids, and rugosity while altering hydrology through upwelling, velocity shelters, and lee waves. Additionally, as short-term disturbances to resident benthic fauna and flora can occur, recolonization rate and successional stages are important biological factors to consider at OWP sites aimed at ecological improvement. Collectively, these data provide insight into integrating intentional design features to improve locally diversified and enhanced aquatic habitats beneficial to fish and other organisms, through attributes such as height, shape, side slope, sediment grain size, microeffects on hydrodynamics, and benthic prey resources.