Journal of Environmental Management最新文献

The aesthetic services of road landscapes provide recreational opportunities for the road environment, thereby supporting the designation, planning and design of scenic roads. Computer vision presents a methodology to investigate landscape aesthetic services by offering pixel-level tools to identify and analyse people's aesthetic attention. These tools can help overcome some of the limitations of examining attention through eye-tracking experiments. In this study, we constructed a dataset by collecting image data of road landscapes in Southwest China and creating aesthetic labels through public ratings. We employed a two-step deep transfer learning to train an aesthetic prediction model. The resultant model presented an accuracy of 0.88 in identifying landscapes with notable aesthetic features. Then we leveraged a class activation mapping to elucidate the model's aesthetic attention in the image samples. To interpret the visual features of aesthetic attention, we adopted image segmentation, colour extraction, depth estimation and edge detection to analyse the elements, colours, deepness and complexity of the attention areas in landscapes. Our results demonstrated the different patterns between positive and negative aesthetic attention. Negative attention is focused on unattractive objects, gravitating towards nearby artificial objects with dull colours and basic outlines. In contrast, positive attention displays a preference for distant, brightly coloured natural objects with complex shapes. Its pattern involves more than just the search for attractive objects, as it also includes a general focus on the landscapes around the road end and roadsides. The proposed approach can be used to estimate the aesthetic services of road landscapes, and the empirical findings offer implications for the planning and design of scenic roads.

The primary objectives of this study are the development of an urban traffic noise exposure assessment method considering temporal traffic demand and its applications in densely populated areas. Firstly, the temporal population distribution model is constructed through the different travel rates of residents based on the dispersion and aggregation characteristics of people in different periods and land use types. Next, the model of temporal traffic demand estimation is proposed via the Gravity Model and User Equilibrium Model considering the inbound and outbound traffic. Finally, the road traffic noise is predicted based on the temporal traffic flows, and noise exposure assessment is conducted via the proposed noise exposure metrics. The results of a case study show that the proposed method works well for densely populated urban areas with time-varying traffic demands. Temporal traffic demand, land use, POI categories and population distribution influence the traffic noise exposure. The type composition and spatial distribution of high-exposed buildings in different periods are very different. Accommodational buildings have a greater contribution to noise exposure due to the functional properties that enable a strong population-gathering ability.

Soil dissolved organic carbon (DOC) is the most active carbon pool, providing essential carbon and energy to soil microorganisms while playing a crucial role in carbon sequestration, transport, and stabilization in soils. Nitrogen (N) addition, a key factor influencing terrestrial carbon cycling, can significantly alter soil DOC dynamics. However, the global patterns and underlying drivers of DOC responses to N addition, particularly across regions with varying aridity indices, remain unclear. This study analyzed 1132 paired observations from 103 independent studies to quantify the response pattern of DOC to N addition in humid (554 observations) and non-humid (574 observations) regions and identify the factors driving these effects. The findings revealed an asymmetrical effect of N addition on soil DOC between humid and non-humid regions, rather than on microbial biomass carbon (MBC) or soil organic carbon (SOC). Specifically, N addition significantly decreased soil DOC (-2.49%) in humid regions, while it increased DOC (7.30%) in non-humid regions. The effect size of soil DOC decreased linearly with the ratio of MBC to SOC in humid regions but increased linearly in non-humid regions. In humid regions, soil DOC response was positively correlated with initial MBC and inversely correlated with initial soil pH, whereas the opposite trend was observed in non-humid regions. Seasonal precipitation variability was identified as a significant driver of soil DOC response, independent of temperature, soil properties, and N addition rates. Moreover, initial SOC content was the primary driving factor for soil DOC response in humid regions, while the N addition rates were the primary driver in non-humid regions. These findings have important implications for enhancing soil carbon pool management, improving global carbon models, and addressing climate change, particularly under varying climatic conditions.

Soils represent both a source of and sink for greenhouse gases (GHG). Elevated temperature (eT) affects both the physical and biological factors that drive GHG emissions from soil and thus understanding the effects of rising global temperatures on terrestrial GHG emission is needed to predict future GHG emissions, and to identify mitigation strategies. However, uncertainty remains about the interactive effects of multiple climate factors across different ecosystems, complicating our ability to develop robust climate change projections. Therefore, a global meta-analysis of 1337 pairwise observations from 150 peer-reviewed publications (1990-2023) was conducted to assess the individual effect of eT and its combined effects with eCO₂ (eT + eCO₂), drought (eT + drought) and increased precipitation (eT + ePPT) on soil N₂O and CH₄ fluxes, microbial functional genes, and soil extracellular enzyme activities across grassland, cropland, and forestland ecosystems. Across the dataset, eT significantly increased N₂O emissions (21%) and CH₄ uptake (36%). Nitrogen cycling was consistently stimulated by eT, with NO₃^- and NH₄⁺ and the abundance of amoA-AOB gene increasing by 6%, 10%, and 18%, respectively. Soil water content (SWC) was reduced, whereas increases of 9% in soil organic carbon (SOC), 14% in microbial biomass carbon (MBC), and 10% in total plant biomass were found under eT. The stimulation of soil N₂O emissions by eT was maintained for all ecosystems when combined with other global change factors (ie., eT + eCO₂, eT + ePPT, and eT + drought). By contrast, effects of eT on CH₄ uptake and emissions were more variable when combined with other factors; for instance, eT + eCO₂ and eT + ePPT suppressed CH₄ uptake in grasslands. This study highlights the urgent need to study the microbial mechanisms responsible for combined global change effects on N₂O and especially CH₄ fluxes.

Promoting the transformation of the energy structure and establishing a diversified clean energy system are essential for achieving China's goal of "dual carbon". It is worth noting that hydrogen energy plays a significant role in this energy structure transformation. This study aims to select the optimum green hydrogen supply chain mode and analyze the impact of key factors, considering the entire green hydrogen supply chain, including production, compression and storage, transportation, and refueling. A system dynamics model is constructed to simulate different green hydrogen supply chain modes, taking into account the levelized cost of hydrogen (LCOH), hydrogen production, and energy consumption of the green hydrogen supply chain as the objectives. Moreover, a sensitivity analysis is conducted to explore the impact of the key factors on the optimum green hydrogen supply chain mode including electricity prices, electricity consumption, and government subsidy policies. An empirical study is conducted on the green hydrogen supply chain from Inner Mongolia to Beijing, and the results indicate that, PEM + pipeline mode presents the optimum green hydrogen supply chain mode, as it achieves the lowest LCOH of 20.42 CNY/kg, the highest hydrogen production and lowest energy consumption by 2035. The costs of hydrogen production stage and refueling stage are the main components of the LCOH of the green hydrogen supply chain. The sensitivity analysis demonstrates that reducing electricity price, decreasing power consumption of energy-intensive equipment, and increasing infrastructure subsidies could significantly impact the optimum green hydrogen supply chain mode, with the greatest effect observed in the decrease of power consumption in energy-intensive equipment.

Climate change is anticipated to amplify the intensity and frequency of riverine floods, posing significant challenges to existing flood defense systems. This study assesses future flood risks in the Nakdong River Basin, South Korea's largest and most flood-prone basin, by integrating long-term climate, demographic, and economic projections with high spatial resolution. Using GIS-based damage assessment approaches with extensive spatial datasets, we quantify flood risks at the granular level of individual buildings and farmlands across different SSP-RCP scenarios. Results indicate that intensified extreme rainfall events combined with socioeconomic transformations will likely cause a substantial increase in expected annual damage, potentially tripling by 2100 under the SSP5-8.5 scenario. Moreover, the analysis reveals significant heterogeneity in vulnerability, with certain regions and asset categories disproportionately exposed. These findings highlight the critical need for forward-looking, region-specific flood defense strategies that address both spatial and temporal variability.

Urban forests, combining the characteristics of urban habitats and forest ecosystems, play an increasingly crucial role in enhancing urban environmental quality and maintaining ecological balance, emerging as vital areas for biodiversity. Bird monitoring effectively evaluates changes in urban habitats and serves as an important indicator for ecosystem services and biodiversity health. However, the relationship between bird community characteristics and urban forest environments across seasons is not fully understood. In this regard, we employed passive acoustic monitoring (PAM) combined with acoustic diversity index (ADI), normalized difference soundscape index (NDSI) and power spectral density (PSD), to explore how habitat features impact the acoustic activity intensity of forest bird community. Sound collection was conducted for 48 h at 30 monitoring points in spring, autumn, and winter. The results indicated that the acoustic bird community in autumn exhibited an obvious dominance. Seasonal variation significantly influenced the correlation between green space soundscapes and vegetation types. Average tree height and distance to the forest edge were identified as main factors affecting bird diversity and dominance changes. In addition, vegetation features accounted for most of the variation in the frequency band distribution of birdsong over different temporal scales. This study highlights the considerable potential urban forests hold for supporting avian diversity. The utility of acoustic monitoring method in tracking biodiversity in urban forests is demonstrated by the findings. Through this efficient monitoring approach, we conducted an in-depth evaluation of the acoustic characteristics of birds in urban forests, providing new insights into biodiversity conservation in rapidly urbanizing environments.

While direct anammox implementation is attractive when treating wastewater, nitrite (NO₂^--N) availability and excess organic matter significantly limit its practical application. This study proposed partial nitrification and endogenous partial denitrification/anammox (PN/A-EPD/A) for the treatment of real municipal wastewater (COD/N ratio: 2.8) within a single-stage reactor under anaerobic/aerobic/anoxic mode. Interestingly, with reducing dissolved oxygen concentration (5.0 ± 1.0 → 1.0 ± 0.5 mg-O₂/L) during aerobic phase, Comammox Nitrospira clade A became dominated and introduced vast nitrate (NO₃^--N) into the subsequent anoxic stage. Both in-situ and ex-situ tests confirmed that sufficient NO₃^--N as electron acceptors were in favor of the EPD/A occurrence with endogenous organics utilization, which was obtained by anaerobic endogenous transformation. Metagenomic results confirmed the role of Thauera in facilitating NO₃^--N→NO₂^--N process, and further supporting AnAOB. As a result, Ca. Brocadia gradually enriched on granules (from 0.08% to 3.51%) and contributed up to 51.5 % to total inorganic nitrogen removal through the PN/A-EPD/A process. Optimized carbon utilization pathway promoted the re-cooperative balance of microorganisms and this process achieved efficient nitrogen removal (93.5%) and desirable quality of effluent (3.2 mg-N/L) when treating real municipal wastewater.

The electrochemical filtration process (ECFP), which integrates the benefits of membrane separation with electrochemical advanced oxidation, exhibits significant potential for water decontamination. A key aspect in realizing practical applications of ECFP lies in the development of cost-effective, high-performance reactive electrochemical membranes (REM). In this work, a novel carbon-based REM (MCM-30) was prepared by coating the low-cost coal-based carbon membrane (CM) with MnOOH nano-catalyst through a simple and environmentally friendly electrochemical deposition method. Results indicated that the nano-MnOOH catalyst significantly improved the hydrophilicity and electrochemical properties of the CM, thereby enhancing its permeability and removal efficiency towards bisphenol A (BPA). The effects of deposition time, applied voltages, flow rates, electrolyte concentrations, and water matrixes on BPA removal efficiency were systematically investigated. Under optimal conditions, 30 min deposition, 2.0 V applied voltage, 2 mL min^-1 flow rate, 0.1 mol L^-1 Na₂SO₄ electrolyte concentration, the BPA removal efficiency of the MCM-30 reached to over 95%, which is much higher than that of the CM. The improved water treatment performance of MCM-30 during the electrochemical filtration could be attributed to the enhancement in both direct and indirect oxidation owing to the nano MnOOH deposition. Furthermore, the MCM-30 is recyclable and can be applied across various water backgrounds and pollutant types.

Antibiotic resistance genes (ARGs) have become a major focus in environmental safety and human health, with concerns about non-antibiotic substances like microplastics facilitating their horizontal gene transfer. Phthalate esters (PAEs), as ubiquitous plastic additives, are prevalent in aquatic environments, yet there remains a dearth of studies examining their impacts on ARG dissemination. This study focuses on dibutyl phthalate (DBP), a prototypical PAE, to assess its potential influence on the conjugative transfer of ARGs along with the related molecular mechanisms. The results revealed that DBP exposure at environmentally relevant concentrations significantly promoted the conjugative transfer of RP4 plasmid-mediated ARGs by up to 2.7-fold compared to that of the control group, whereas it severely suppressed the conjugation at a high concentration (100 μg/L). The promotion of conjugation transfer by low-concentration DBP (0.01-10 μg/L) was mainly attributed to the stimulation of ROS, enhanced membrane permeability, increased energy synthesis, increased polymeric substances secretion, and upregulation of conjugation-related genes. Conversely, high DBP exposure induced oxidative damage and reduced ATP synthesis, resulting in the suppression of ARG conjugation. Notably, donor and recipient bacteria responded differently to DBP-induced oxidative stress. This study explores the environmental behavior of DBP in the water environment from the perspective of ARG propagation and provides essential data and theoretical insights to raise public awareness about the ecological security risks of PAEs.