环境科学最新文献

Emerging contaminants （ECs） pose a serious threat to ecology and human health because of their low concentration， difficult degradation， long-term residue， bioaccumulation， and high toxicity. The traditional biological and physicochemical methods cannot effectively remove ECs. Electro-Fenton （EF）， as a green， environmentally friendly and high efficiency means for removing pollutants technology， has been widely used in the field of water treatment. Among them， the development of an efficient cathode electrode has proven to be one of the most simple and cost-effective methods， and carbonaceous materials have become one of the most promising cathode materials because of their excellent performance. However， the EF process is still limited by insufficient oxygen reduction capacity， low efficiency of the Fe³⁺/Fe²⁺ cycle， and narrow pH work range in the practical application. Based on this， this paper comprehensively summarizes the bottleneck problems encountered by carbonaceous materials cathode EF technology at present and the corresponding solutions. The main contents include the means and principles involved in promoting the electro-generation of H₂O₂， enhancing the efficiency of the Fe³⁺/Fe²⁺ cycle， and broadening the pH working window， and the practical application status of EF technology is expounded. In the end， some problems existing in this type of research and the areas that need to be improved in the future are listed， and the future research direction of carbonaceous cathode EF technology in the field of ECs degradation is prospected. This will provide a scientific basis for the development of efficient EF technology.

Realizing the coordinated progress of carbon reduction and economic growth is an inevitable choice for China to promote low-carbon transformation and development. This article is based on panel data from 282 prefecture level and above cities from 2006 to 2022. Using the PVAR model to clarify the interaction between carbon emissions and economic growth， the modified Gruber Lloyd index is used to measure the degree of synergy between the two. ArcGIS and other tools are used to visualize the temporal characteristics and spatial distribution of the coordinated development of urban carbon emission reduction and economic growth. Kernel density estimation method is used to reveal its distribution dynamics and evolution rules， and the Dagum Gini coefficient and its subgroup decomposition method are used to explore the overall differences and their sources. The results indicated that： ① From the perspective of interactive relationships， both carbon emissions and economic growth had self-reinforcing mechanisms， but their cumulative effects gradually weakened. The impact of economic growth on carbon emissions conformed to the inverted "U" shape of the Environmental Kuznets Curve， while carbon emissions exhibited long-term negative effects on economic growth. In terms of spatiotemporal characteristics， the synergy level between urban carbon reduction and economic growth showed a significant upward trend， with an increase of 24.17% during the investigation period. The spatial distribution characteristics gradually evolved into a gradient distribution of "low in the west and high in the east." In terms of dynamic evolution， the core density curve of the synergy level between carbon emission reduction and economic growth in cities across the country and the four major regions generally shifted to the right， with the main peak height first increasing and then decreasing and the width widening. The phenomenon of a right tail was obvious， mainly in the form of a single peak， indicating that the synergy level in various regions improved. However， the overall differences within the regions widened， and the degree of dispersion intensified. There has not yet been a significant multipolar differentiation phenomenon. From the perspective of regional differences， the overall Gini coefficient of the country showed a slight fluctuation and upward trend， indicating that the differences in carbon reduction and economic growth synergy among Chinese cities expanded， but at the same time， they also maintained a relative balance. The overall differences within and between the four major regions also increased， but the dynamic characteristics of various regions were significantly different， and inter-regional differences constituted the main source of overall differences. The research conclusion is beneficial for each region to clarify its own advantages and shortcomings and to achieve low-carbon transformation and development according to local conditions.

In order to clarify the effects of flood irrigation （FI）， sprinkler irrigation （SI）， and drip irrigation （DI） on the accumulation of cadmium （Cd） and arsenic （As） in wheat grains， a mini-plot experiment was carried out to investigate the variations of soil Cd and As bioavailability in the rhizosphere under three irrigation treatments （DI and SI with the same irrigation volume， both equal to two-thirds of FI） and the distribution， migration， and accumulation of Cd and As in various parts of winter wheat. The results showed that the DI treatment reduced grain-Cd by 22.14% and grain-As by 17.46% and the accumulation of Cd by 32.09% and As by 27.77% in wheat grains and did not decrease the hundred-grain weight and grain number per spike compared with that in FI. Furthermore， it was found that the DI treatment decreased soil Eh and then regulated the composition of dominant rhizobacterial genera. DI reduced the relative abundance of unclassified_o__Rokubacteriales and increased the relative abundances of Bacillus and Skermanella， which resulted in the proportions of exchangeable-Cd （F1-Cd） being reduced by 8.13%-24.54%. Further， the DI treatment increased the relative abundances of Bacillus， unclassified_ f__JG30-KF-CM45， and unclassified_ f__A4b， which enlarged the proportions of specifically adsorbed-As （F2-As） by 9.73%-31.36%. Therefore， the variation of the above-mentioned genera has driven the bio-transformation of Cd and As in soil， and DI decreased Cd concentrations in the soil solution by 73.78% maximally compared with that of FI and further inhibited Cd transport from glume to grain. However， the DI treatment improved the concentrations of As in the soil solution by 171.73% maximally but inhibited As translocation from rachis and glume to grain compared with those in FI and SI， respectively. Additionally， DI alleviated the accumulation rates of Cd and As in wheat grain and finally reduced the concentrations and accumulation of Cd and As in the grains. In summary， drip irrigation is a better pathway to save water resources and reduce Cd and As accumulation in wheat grain cultivated in calcareous soil with moderate Cd and As co-contaminated agricultural land， which could provide a new strategy for the safe utilization of heavy metal-contaminated farmland.

Conducting detailed investigations and precise tracing of soil heavy metal pollution in specialty agricultural product cultivation areas is of significant practical importance for fully advancing rural revitalization， promoting high-quality and sustainable agricultural development， and supporting national ecological security. This investigation focuses on the soil of the Guazhou melon cultivation area， systematically analyzing the pollution profiles of the heavy metals As， Cd， Cr， Cu， Hg， Ni， Pb， and Zn using methods such as the geo-accumulation index， enrichment factor， modified Nemerow pollution index， and pollution load index. Correlation-cluster analysis， the absolute principal component scores-multiple linear regression （APCS-MLR） model， and the random forest （RF） model were employed to comprehensively identify and quantify the sources and contributions of soil heavy metal pollution. The results indicate that： ① The average levels of As， Cd， Cr， Cu， Hg， Ni， Pb， and Zn in the study area soil were 10.83， 0.28， 51.19， 20.93， 0.03， 25.62， 14.88， and 62.48 mg·kg^-1， respectively. Except for Cd， the average concentrations of As， Cr， Cu， Hg， Ni， Pb， and Zn were below the soil background levels for Gansu Province. Moreover， except for 3.4% of samples in which Cd levels exceeded the screening value set by the "soil environmental quality risk control standard for agricultural land （Trial）" （GB 15618-2018） for soils with pH > 7.5， the concentrations of As， Cr， Cu， Hg， Ni， Pb， and Zn in all other samples were below the screening threshold. ② Cd and Hg were the most severely polluted heavy metals in the melon cultivation soil， with highly contaminated samples located near transportation， industrial， and mining areas. ③ The accumulation of soil heavy metals in the melon cultivation area was influenced by combined sources： agricultural-traffic， industrial， and atmospheric deposition. The APCS-MLR model identified contributions of 43.56% from agricultural-traffic sources， 31.77% from industrial sources， and 19.33% from atmospheric deposition， while the RF model identified contributions of 46.55%， 26.03%， and 27.42% from these sources， respectively. The findings provide a scientific basis for managing soil heavy metal pollution risks and ensuring the safe and high-quality development of the melon industry in the region.

Exploring the impacts of spatial and temporal land use evolution on carbon stock in the urban agglomeration around Taihu Lake is of great significance for the management of regional ecosystem carbon pools and the realization of regional low-carbon and high-quality development. Using the PLUS-InVEST-Geodetector model， we explored the spatial and temporal patterns of land use and carbon stock and their different characteristics from 2000 to 2020； predicted and simulated the distribution characteristics of spatial patterns of land use and carbon stock under the scenarios of natural development， urban development， and ecological protection in 2030； and revealed the reasons for the impacts on the changes of carbon stock. The results showed that： ① From 2000 to 2020， the cultivated land area of the urban agglomeration around Taihu Lake decreased by 26.3%， and the built-up land area increased by 147.5%， with the main driving factors being the population size， elevation， and the relative distance to secondary roads. ② The carbon stock in the urban agglomeration around Taihu Lake showed a spatial distribution characteristic of high in the southwest and low in the northeast， with an overall decrease of 8.17%， in which cropland and forest land lost 48.84 and 5.36 Mt， respectively. The shift in land use type was the main reason for the decrease in carbon stock. ③ Based on the comparison of the three scenarios in 2030， the ecological protection scenario had higher carbon stock （469.865 Mt） and lower carbon loss （-11.545 Mt）. The high carbon stock areas were mainly distributed in the western and southern parts of Taihu Lake， while the low value areas were concentrated in the eastern and northern parts. ④ The attribution analysis showed that the natural environmental factors had a significantly higher influence on carbon stock than the socioeconomic factors.

The coordinated advancement of pollution reduction， carbon reduction， and the development of new-quality productive forces is significant for addressing ecological and environmental issues and promoting high-quality economic development in the Yangtze Economic Belt. This study employs a revised coupling coordination model， kernel density estimation， Theil index， and spatio-temporal geographically weighted regression models to explore the spatio-temporal evolution patterns and influencing factors of the coupling coordination effects between pollution reduction， carbon reduction， and the development of new-quality productive forces in the provinces and cities of the Yangtze Economic Belt from 2010 to 2022. The results indicate that： （1） The coupling coordination levels of pollution reduction， carbon reduction， and the development of new-quality productive forces in the provinces and cities of the Yangtze Economic Belt showed an upward trend year by year， with the coupling coordination grades gradually evolving from mild disorder and near disorder to primary coordination. The spatial distribution exhibited characteristics of "higher in the north and lower in the south" and an "increasing stepwise gradient from upstream to downstream." （2） The regional differences in coupling coordination levels among the provinces and cities of the Yangtze Economic Belt initially decreased continuously and then fluctuated within a narrow range. Inter-regional differences were the dominant factor of overall differences， while intra-regional differences contributed increasingly. （3） Environmental protection， industrial structure， technological innovation， and economic development primarily had positive impacts on the coupling coordination effects of pollution reduction， carbon reduction， and the development of new-quality productive forces. Energy consumption mainly had a negative impact， and there was significant spatio-temporal heterogeneity in the influence of various factors.

Constructing a stable and healthy ecological network is an important means to promote the sustainable development of oasis cities. This study adopts the research model of 'ecological source identification-resistance surface construction-ecological corridor extraction-ecological network optimization' to analyze the spatial and temporal evolution of the ecological network in Yinchuan City in 2000， 2010， and 2020 and the multi-scenario ecological network simulated by PLUS model in 2030. The results showed that： ① The area of ecological sources has been declining over the past 20 years. Ecological sources were larger in the ecological protection scenario than in the natural development and economic development scenarios. ② Over the past 20 years， the length of ecological corridors has been decreasing， but the ecological network index has been increasing， and the ecological network structure is more solid. The corridor length and ecological network index of the ecological protection context had the best performance. ③ The optimal width of the ecological corridor in Yinchuan City was 100 m， at which time the area of the ecological corridor was 55.07 km²， and the areas of the ecological pinch points and ecological obstacles were 1.18 km² and 2.38 km²， respectively. ④ The improved ecological network based on the optimization countermeasures was more stable and healthier， with the length and area of ecological corridors increasing by 15.27 % and 25.24 %， respectively. The results of the study can guide the spatial construction of the ecological network in Yinchuan City from a systematic perspective， promote the implementation of ecological protection and restoration projects， and reduce the interference of human activities on the ecosystem from a theoretical perspective. They also provide a basis and reference for the ecological protection of the national land space and the construction of a high-quality development pioneer zone in the Yellow River Basin.

To improve model estimation accuracy and obtain hourly-scale PM_2.5 concentration data， a spatiotemporal XGBoost （STXGBoost） model incorporating data heterogeneity was developed， integrating multi-source datasets including Himawari-8 hourly apparent reflectance， ground-level PM_2.5 measurements， meteorological variables， population density， DEM， and forest coverage. The model was applied to estimate hourly PM_2.5 concentrations across the Guanzhong region in 2022 and analyze their spatiotemporal characteristics. The results showed that： ① The STXGBoost model demonstrated superior estimation accuracy and generalization capability compared to the SVM， RF， and XGBoost models. Ten-fold cross-validation on the full dataset achieved an R² of 0.96， with RMSE and MAE values of 7.17 μg·m^-3 and 3.82 μg·m^-3， respectively. The model exhibited robust hourly-scale estimation precision and stability， confirming its applicability for PM_2.5 monitoring in the Guanzhong region. ② Annual PM_2.5 concentrations from 08：00 to 17：00 local time displayed an "M-shaped" diurnal curve. Seasonal variations were pronounced， with winter exhibiting the highest pollution levels （characterized by a "morning-peak， evening-trough" diurnal pattern） and the most severe air quality degradation. ③ Spatially， elevated PM_2.5 concentrations clustered predominantly in the central Guanzhong Plain， while lower values prevailed in the western， northern， and southern mountainous areas.

A total of 180 paired soil-rice samples were collected from two districts in the western grain-producing area of Chongqing， using a systematic stratified sampling method. The study evaluated the contamination status of five heavy metals-cadmium （Cd）， lead （Pb）， chromium （Cr）， mercury （Hg）， and arsenic （As）-in both the regional soil and rice. The study also analyzed key soil physical and chemical properties， such as soil pH， organic matter （OM）， and cation exchange capacity （CEC）， to explore the critical soil factors that constrain the accumulation of heavy metals in rice. The results showed that among the five heavy metals， only Cd and Pb exceeded the standard limits， with exceedance rates of 9.4% and 0.5%， respectively. The spatial distribution map of soil heavy metals generated through the spatial interpolation method indicated that Cd exhibited significant spatial variation within the study area， showing a "dual-core" pattern of high-concentration areas in the northeast and southwest. Cr concentrations were higher in the northern and central areas， but overall， the concentrations were close to background values， while the distribution of other elements was more uniform. In rice grains， the exceedance rate of Cd was 10%， indicating a higher bioaccumulation potential and greater potential harm. The exceedance rate of Cr was 2.23%. The comprehensive quality index of the soil-rice system showed that the overall pollution level of the region was relatively low， with no severe pollution observed. The majority of areas were classified as clean or lightly polluted， accounting for 49% and 31%， respectively. In the correlation analysis of Cd accumulation in rice， it was found that soil organic matter （OM） was the main factor for reducing the bioavailability of Cd （r=-0.27， P<0.001）， and total phosphorus （TP） also exhibited a significant inhibitory effect on Cd accumulation （r=-0.15， P<0.05）. Therefore， managing soil organic matter and applying phosphorus fertilizer appropriately could reduce the transfer of Cd to rice grains. The comprehensive quality evaluation of the soil-rice system showed that the regional pollution level was generally controllable， but some areas require dynamic monitoring and remediation measures to ensure food safety and ecological health.

In the current era， the rapid development of environmental science and computer technology complement each other. Among them， the application of machine learning in the research field of water quality purification in constructed wetlands has become increasingly prominent， showing vigorous vitality and broad prospects. This paper focuses on this aspect and systematically reviews the main research progress of machine learning in water quality purification in constructed wetlands in recent years， striving to comprehensively and deeply analyze its key threads. On the one hand， an in-depth exploration of the diverse application directions of machine learning algorithms in constructed wetlands is carried out， covering key links in water quality purification such as microbial metabolism and pollutant degradation， plant absorption and transformation processes， substrate adsorption and filtration mechanisms， and hydraulic conditions， accurately grasping the adaptation patterns of algorithms in each link. At the same time， the characteristics of constructed wetland data are deeply excavated to lay a solid foundation for algorithm optimization. Further， it is elaborated from three core dimensions， in which we： ① focus on the key processes of water purification assisted by machine learning and clarify the complex interaction mechanisms among microorganisms， plants， substrates， and hydraulic conditions； ② commit to multi-dimensional data fusion to reshape the architecture of water purification mechanisms and drive in-depth understanding with data； and ③ explore the practical applications of machine learning in the design optimization and operation control of constructed wetlands to enhance wetland efficiency. In addition， the article takes a long-term view and looks ahead to future research directions from five aspects， namely model improvement and innovation， data fusion and sharing， real-time monitoring and intelligent control， integration with other technologies， and environmental impact assessment and ecological restoration. To summarize， machine learning injects new vitality into the research on water quality purification in constructed wetlands， opens up new perspectives， and effectively promotes the efficiency of water quality purification and management levels. However， at present， continuous efforts still need to be made in the in-depth optimization of algorithms and solving practical application problems to fully release its potential.