Noise is one of the main parameters to be considered to achieve a healthy indoor ambience in ferries. Therefore, the noise standards need to be more specialized and specifically based on real sampled data and case studies. In the present research, the noise levels in a ship, under different working conditions, were sampled and compared with those specified in the new and old standards. An initial study showed two main noise sources- clients and main engine- that influence other indoor environments, reducing the quality of life on board. The real-time data revealed that the maximum noise level limits set by the International Maritime Organization (IMO) in the older Resolution A.468 (XII) was mostly respected, except in areas where maintenance of the noise level was difficult, owing to the continuous influx of people, especially at the time of boarding and disembarking of the passengers and at the food self-service areas. In this sense, under the new Resolution MSC.337 (91), the maximum noise level allowed in the accommodation has been reduced by 5 dB (A), but this environment does not meet the standard. More results show that future standards must not only consider the noise level in a working place and add another variable, such as, the number of working hours, to obtain a representative equivalent energy, and they must also consider that a simple modification of this standard implies a redesign of most of the indoor ambiences onboard.

Climatic condition, geology, and geochemical processes in an area play a major role on groundwater quality. Impact of these on the fluoride content of groundwater was studied in three regions-part of Nalgonda district in Telangana, Pambar River basin, and Vaniyar River basin in Tamil Nadu, southern India, which experience semi-arid climate and are predominantly made of Precambrian rocks. High concentration of fluoride in groundwater above 4 mg/l was recorded. Human exposure dose for fluoride through groundwater was higher in Nalgonda than the other areas. With evaporation and rainfall being one of the major contributors for high fluoride apart from the weathering of fluoride rich minerals from rocks, the effect of increase in groundwater level on fluoride concentration was studied. This study reveals that groundwater in shallow environment of all three regions shows dilution effect due to rainfall recharge. Suitable managed aquifer recharge (MAR) methods can be adopted to dilute the fluoride rich groundwater in such regions which is explained with two case studies. However, in deep groundwater, increase in fluoride concentration with increase in groundwater level due to leaching of fluoride rich salts from the unsaturated zone was observed. Occurrence of fluoride above 1.5 mg/l was more in areas with deeper groundwater environment. Hence, practicing MAR in these regions will increase the fluoride content in groundwater and so physica or chemical treatment has to be adopted. This study brought out the fact that MAR cannot be practiced in all regions for dilution of ions in groundwater and that it is essential to analyze the fluctuation in groundwater level and the fluoride content before suggesting it as a suitable solution. Also, this study emphasizes that long-term monitoring of these factors is an important criterion for choosing the recharge areas.

The sediment transport, involving the movement of the bedload and suspended sediment in the basins, is a critical environmental concern that worsens water scarcity and leads to degradation of land and its ecosystems. Machine learning (ML) algorithms have emerged as powerful tools for predicting sediment yield. However, their use by decision-makers can be attributed to concerns regarding their consistency with the involved physical processes. In light of this issue, this study aims to develop a physics-informed ML approach for predicting sediment yield. To achieve this objective, Gaussian, Center, Regular, and Direct Copulas were employed to generate virtual combinations of physical of the sub-basins and hydrological datasets. These datasets were then utilized to train deep neural network (DNN), conventional neural network (CNN), Extra Tree, and XGBoost (XGB) models. The performance of these models was compared with the modified universal soil loss equation (MUSLE), which serves as a process-based model. The results demonstrated that the ML models outperformed the MUSLE model, exhibiting improvements in Nash–Sutcliffe efficiency (NSE) of approximately 10%, 18%, 32%, and 41% for the DNN, CNN, Extra Tree, and XGB models, respectively. Furthermore, through Sobol sensitivity and Shapley additive explanation–based interpretability analyses, it was revealed that the Extra Tree model displayed greater consistency with the physical processes underlying sediment transport as modeled by MUSLE. The proposed framework provides new insights into enhancing the accuracy and applicability of ML models in forecasting sediment yield while maintaining consistency with natural processes. Consequently, it can prove valuable in simulating process-related strategies aimed at mitigating sediment transport at watershed scales, such as the implementation of best management practices.

Bibliometric network analysis has revealed that the widespread distribution of microplastics (MPs) has detrimental effects on marine organisms; however, the combined effects of MPs and climate change (e.g., warming) is not well understood. In this study, Prorocentrum donghaiense, a typical red tide species in the East China Sea, was exposed to different MP concentrations (0, 1, 5, and 10 mg L⁻¹) and temperatures (16, 22, and 28 °C) for 7 days to investigate the combined effects of MPs and simulated ocean warming by measuring different physiological parameters, such as cell growth, pigment contents (chlorophyll a and carotenoid), relative electron transfer rate (rETR), reactive oxygen species (ROS), superoxide dismutase (SOD), malondialdehyde (MDA), and adenosine triphosphate (ATP). The results demonstrated that MPs significantly decreased cell growth, pigment contents, and rETRₘₐₓ, but increased the MDA, ROS, and SOD levels for all MP treatments at low temperature (16 °C). However, high temperatures (22 and 28 °C) increased the pigment contents and rETRₘₐₓ, but decreased the SOD and MDA levels. Positive and negative effects of high temperatures (22 or 28 °C) were observed at low (1 and 5 mg L⁻¹) and high MP (10 mg L⁻¹) concentrations, respectively, indicating the antagonistic and synergistic effects of combined warming and MP pollution. These results imply that the effects of MPs on microalgae will likely not be substantial in future warming scenarios if MP concentrations are controlled at a certain level. These findings expand the current knowledge of microalgae in response to increasing MP pollution in future warming scenarios.

Rapid urbanization and the aggregation of human activities in cities have resulted in large amounts of anthropogenic heat (AH) emission, which affects urban climate. Quantifying and assessing the AH emission values accurately and analyzing their spatial distribution characteristics is important to understand the energy exchange processes of urban areas. In this study, the high spatial resolution anthropogenic heat flux (AHF) quantification and spatial distribution analysis were conducted using multi-source data in the Beijing-Tianjin-Hebei region (BTH region) of China. First, the AH emission in district and city level were estimated using inventory method based on energy consumption and socio-economic statistical data; Then, AHF spatial quantification models were constructed based on high spatial resolution nighttime light (NTL) data and Point of interests (POI) data, and 130 m × 130 m gridded AHF quantification result in BTH region was realized; Finally, the potential numerical and spatial distribution patterns of AHF were analyzed using various indicators including contribution rate and aggregation index. The results show that: (1) The parameterized index constructed based on NTL and POI data shows a strong correlation with AHF, with R² ranging from 0.79 to 0.94 and a mean absolute error (MAE) value of 0.72 w·m⁻², which can be applied to the quantification of gridded AHF values with high resolution. The highest total AHF in the study area is 214 w·m⁻², and the average value is 2.24 w·m⁻². (2) Considering the sources of AHF, industrial emission sources in BTH region contribute the most to the total AHF, but commercial building emission sources in Beijing have a higher contribution, which can reach 33.8%. (3) Different types of AHF have different spatial aggregation levels. Commercial building emission and human metabolic emission have the highest aggregation level, and transportation emission has the lowest aggregation level.

In this study, an interval two-stage fuzzy fractional programming (TFFP) method is developed to facilitate collaborative governance of economy and water resources. Methods of interval programming, fuzzy programming, two-stage programming, and fractional programming are integrated within a general system optimization framework. The main contribution of TFFP is simultaneously addressing various uncertainties and tackling trade-offs between environmental and economic objectives in the optimized schemes for water resources allocation. A case study of a highly urbanized coastal city (i.e., Shenzhen) in China is provided as an example for demonstrating the proposed approach. According to the results, industrial sectors should receive 34.8% of total water supply, while agricultural sectors should receive 1.5%. For the spatial allocation of water resources, Bao An, Long Gang, and Fu Tian districts should be allocated 21.6%, 20.5%, and 14.8% water to promote the economic development. The discharge analysis indicates that chemical oxygen demand (CODcᵣ) and total phosphorus (TP) would be key pollutants. Moreover, the optimized seawater desalination volume would be negligibly influenced by price, while the upper bounds of desalination would be increased with the raising acceptable credibility levels in the period of 2031–2035. Analysis of desalination prices also reveals that the decision-makers should increase the scale of desalination in the period of 2021–2025. In addition, the effectiveness and applicability of TFFP would be evaluated under economic maximization scenarios. The result showed that the economic maximization scenario could obtain higher economic benefits, but it would be accompanied by a larger number of pollutant discharges. It is expected that this study will provide solid bases for planning water resources management systems in coastal regions.

The negative influence of agrochemicals (pesticides: insecticide, fungicide, and herbicide) on biodiversity is a major ecological concern. In recent decades, many insect species are reported to have rapidly declined worldwide, and pesticides, including neonicotinoids and fipronil, are suspected to be partially responsible. In Japan, application of systemic insecticides to nursery boxes in rice paddies is considered to have caused rapid declines in Sympetrum (Odonata: Libellulidae) and other dragonfly and damselfly populations since the 1990s. In addition to the direct lethal effects of pesticides, agrochemicals indirectly affect Odonata populations through reductions in macrophytes, which provide a habitat, and prey organisms. Due to technical restrictions, most previous studies first selected target chemicals and then analyzed their influence on focal organisms at various levels, from the laboratory to the field. However, in natural and agricultural environments, various chemicals co-occur and can act synergistically. Under such circumstances, targeted analyses might lead to spurious correlations between a target chemical and the abundance of organisms. To address such problems, in this study we adopted a novel technique, “Comprehensive Target Analysis with an Automated Identification and Quantification System (CTA-AIQS)” to detect wide range of agrochemicals in water environment. The relationships between a wide range of pesticides and lentic Odonata communities were surveyed in agricultural and non-agricultural areas in Saga Plain, Kyushu, Japan. We detected significant negative relationships between several insecticides, i.e., acephate, clothianidin, dinotefuran, flubendiamide, pymetrozine, and thiametoxam (marginal for benthic odonates) and the abundance of lentic Epiprocta and benthic Odonates. In contrast, the herbicides we detected were not significantly related to the abundance of aquatic macrophytes, suggesting a lower impact of herbicides on aquatic vegetation at the field level. These results highlight the need for further assessments of the influence of non-neonicotinoid insecticides on aquatic organisms.

To evaluate the chemical status of groundwater bodies (GWB) according to the European Groundwater Directive, EU Member States are required to take into account natural background levels (NBLs) where needed. Assessing the NBLs in coastal GWBs is complicated by seawater intrusion which can be amplified by groundwater withdrawals increasing the salinization of such groundwater systems. This paper proposes a new method for the NBLs assessment in coastal areas based on a double pre-selection (PS) with fixed/dynamic limits. A case study in the Apulia region, located in southeastern Italy, is proposed, where we investigated four adjacent GWBs which form the complex karst, fractured Murgia aquifer, hosted in the Jurassic-Cretaceous carbonate platform, bounded by two seas and sustained by saltwater of marine intrusion in the coastal areas. Data related to 139 monitoring stations (MSs) of the regional groundwater monitoring network were used. The first PS, “static”, based on a fixed limit of anthropogenic contamination markers (NO₃ and NH₄), allows for the elimination of MSs impacted by human activities. On these, the second PS, “dynamic”, based on the identification of Cl anomalous values, allows for the identification of additional MSs affected by saline contamination. The residual dataset of MSs was used for the definition of NBLs of Cl, SO₄, F and B. A statistical comparison with historical Cl observations finally allowed us to verify if the salinity of current groundwater is representative of pristine conditions. The calculated NBLs of salinity parameters are higher for the two coastal GWBs, with chloride values between 0.8 and 2 mg/L. Conversely, fluorides always show very low NBLs. The double PS approach seems more effective for NBLs calculation in coastal aquifers affected by saline contamination, where the use of a fixed Cl limit fails. It may respond to the international needs for a standardized procedure for NBL assessment.

The 7th Military World Games held in Wuhan (WH) in Oct 2019 provided an opportunity to clarify the impact of short-term control measures on air quality. Fine particulate matters (PM₂.₅) were collected in WH, Huangshi (HS), and Huanggang (HG) during the control (Oct 13–28, 2019) and non-control periods (Oct 29- Nov 5, 2019). The results showed that air quality was good during the control period, with the concentrations of PM₂.₅ and gaseous pollutants being below the Grade Ⅱ of China Ambient Air Quality Standard. Concentrations of PM₂.₅ and its major chemical components in the control period were significantly lower than those in the non-control period, with reductions ranging from 17% (trace elements) to 46% (elemental carbon). However, higher contributions of secondary components such as SO₄²⁻, NO₃⁻, NH₄⁺ and secondary organic carbon (SOC) to PM₂.₅ were observed during the control period, suggesting the important role of secondary transformation. Potential source contribution function (PSCF) of PM₂.₅ showed that the main source regions were potentially located in surrounding cities Hubei Province, but regional transport can't be ignored. Six sources were identified by positive matrix factorization (PMF) for both control and non-control period. The contributions of combustion emissions and vehicle emissions were amplified in the control period, while the contribution of construction dust increased significantly when the control measures ended. Emission reductions contributed more to PM₂.₅ concentration decrease in WH (55%) than that in HS (51%) and HG (49%), which was consistent with the stricter control measures implemented in WH. These results indicated that short-term controls were effective at lowering PM₂.₅ concentration. However, the elevated contributions of secondary aerosols and the influence of regional transport on the study areas also need to be paid attention for air quality improvement in the future.

The distinct spatial variability in microplastic concentrations between marine regions and habitats calls for a better understanding about the transport pathways of this omnipresent pollutant in the marine environment. This study provides empirical evidence that a sessile filter feeder, the Blue mussel M. edulis, accelerates microplastic deposition by aggregating them into sinking particulate faeces and pseudofaeces. After settling to the seafloor, the bioturbation of benthic fauna quickly buries these microplastics. Collectively, these results suggest that if such biologically-mediated benthic-pelagic coupling would be integrated into hydrodynamic transport models, the spatial variability and source-sink dynamics of microplastics would be better understood. It is proposed that microplastic pollution is monitored through sampling that takes into account faeces and pseudofaeces underneath filter feeders. The implications of this detrital pathway for microplastic transfer to the seafloor, and the role of shellfish mariculture in this process, are discussed. Studies that consider filter feeders and benthic communities from other regions, and during different seasons, are needed to validate the proposed biological pump mechanism across space and time.