Huanjing Kexue/Environmental Science最新文献

With the drying and warming of the climate and irrational grazing, various types of grasslands in Inner Mongolia have been degraded to different degrees, and different management modes will inevitably affect the plant diversity and vegetation carbon stock of soil grasslands. To clarify the changes and influencing factors of plant diversity and carbon stock in different types of grasslands under different management modes, plant species composition, aboveground biomass, and vegetation carbon were analyzed based on 18 sentinel monitoring stations across three different types of grasslands in Inner Mongolia. The results showed that grazing increased the dominance of typical grassland and desert grassland, whereas meadow grassland decreased, and the evenness index and Shannon Wiener diversity index increased less in meadow grassland and desert grassland. Grazing decreased graminaceous biomass in meadow grassland and typical grassland, whereas it increased in desert grassland. Above-ground vegetation and below-ground root carbon stocks were much higher than those in grazing areas, 1.5 and 1.2 higher, respectively, but vegetation carbon stocks in long-term grazing sites were significantly lower than those in short-term grazing. Further, the structural equations showed that the effects of geographic location, climatic factors, and soil factors on the biomass and vegetation carbon stocks of the three grassland types differed significantly. The results can provide a reference for the ecologically sustainable development of grassland and the optimization of management mode.

To understand the structure of the plankton community and the ecological niche characteristics of their dominant species, sampling surveys of plankton were conducted in Baiyangdian Lake in the spring （March）, summer （July）, and autumn （September） of 2022. The changes in the plankton community during the three seasons were analyzed by constructing ecological network diagrams, non-metric multidimensional scaling analysis （NMDS）, and the ecological niche width. The niche overlap of zooplankton dominant species was evaluated by the improved Levins' formula and Petraitis' index. The interspecific connectivity of dominant species was judged using the chi-square test and interspecies connectivity coefficients. The results showed that the niche width of plankton in the whole area was low. Zooplankton was dominated by rotifers, and phytoplankton was dominated by diatoms, cyanobacteria, and green algae. There were significant seasonal changes in the community structures of plankton. Compared with that in summer and autumn, there were fewer species of plankton in spring and lower interspecies connectivity. The overlap of dominant species of zooplankton was high in summer, and the interspecific competition was intensified, whereas the interspecific overlap of phytoplankton was at a low level in all three seasons. There was a significant positive correlation （W > χ²_0.05） between phytoplankton in summer and autumn, and the community structure was stable. The interdomain ecological network of zooplankton and phytoplankton showed a high negative correlation ratio in autumn, especially between copepods and cladoceras of zooplankton and chlorophyta and cyanophyta of phytoplankton. The plankton species in Baiyangdian Lake were abundant, with obvious seasonal differences. The dominant species were mainly a narrow ecological niche. The plankton community was generally in a stable state, and there was a strong predation relationship between copepods and cladoceras and green algae and cyanobacteria.

Exploring the spatiotemporal differentiation of the carbon budget and clarifying the zoning of carbon compensation based on the perspective of the main function-oriented zones is of great significance for promoting regional low-carbon development and achieving the "dual carbon" goal. This study was conducted using 550 counties in the Yellow River Basin as the basic unit, and based on the concentration index to examine the spatial distribution characteristics of carbon emissions and carbon absorptions in the main function-oriented zones of the Yellow River Basin, a four-dimensional benchmark framework for carbon compensation zoning was constructed by total scale, economic contribution, ecological carrying capacity, and land development intensity. The SOM-K-means algorithm was used to establish a differentiated carbon compensation zoning scheme. The results showed that： ① The carbon emissions and carbon absorptions and their growth trends of the main function-oriented zones in the Yellow River Basin were in line with the positioning of the main functional area, and the significant space-time distribution characteristics of the concentration level of carbon emissions and carbon absorptions were shown. ② Significant regional differences exist in the four attributes of total carbon emissions scale, economic contribution, ecological carrying capacity, and land development intensity. The overall scale of carbon emissions showed a growth trend, with obvious comparative advantages in the midstream and downstream. The overall comparative advantage of economic contribution increased first and then decreased, with the midstream and downstream being the attribute advantage areas of economic contribution. The overall ecological carrying capacity had been improved, and the upstream had obvious advantages in ecological carrying properties. The advantageous areas for land development were mainly concentrated in the midstream and downstream； in particular, the comparative advantage index in the midstream was showing a rapid upward trend. ③ Moreover, there were 287 compensated areas, 78 balanced areas, and 185 payment areas in the Yellow River Basin. Eleven types of carbon compensation zones were finally formed by combining the comparative advantage index of four types of attributes with the plan for main function-oriented zones, and corresponding low-carbon development strategies were proposed for each type of zone.

To study the heavy metal pollution and influencing factors of soils and crops in different parent material areas and provide the basis for the classification and control of cultivated land, a total of 1 326 soil surface samples and 46 crop seed-root soil samples were collected from Xingye County in the southeast of Guangxi. The enrichment characteristics of heavy metals in the soil-crop system of four soil-forming parent materials were compared and analyzed, and the influencing factors of Cd absorption by rice were studied. The comprehensive quality impact index method was used to evaluate the soil and crops in the study area, and the safe use of cultivated land was proposed according to the evaluation results. The results showed that in the four soil-forming parent material areas, only the carbonate rock parent material area showed obvious enrichment of heavy metals in the soil, especially Cd. According to the "National Food Safety Standard for the Limit of Pollutants in Food" （GB 2762-2022）, the excess rate of heavy metal Cd in rice seeds was 35.7%, and the other heavy metal rates were not exceeded. The bioconcentration coefficient of heavy metal Cd in rice from different parent material areas was as follows： quaternary sediment area > carbonate parent material area > clastic parent material area > granite parent material area. The enrichment of Cd in rice was affected by soil pH and CaO. When the soil pH value was in the range of 5.5-6.5, the Cd content and exceeding rate of rice seed increased significantly. The evaluation results of soil-crop heavy metal pollution showed that the overall heavy metal risk in the study area was high, and the proportions of clean, mild, light, moderate, and heavy pollution were 23.91%, 10.87%, 17.39%, 17.39%, and 30.43%, respectively. Combined with the distribution of the comprehensive quality influence index and the pollution characteristics of different parent materials, the classification and control suggestions were put forward, which provided ideas for the safe utilization of polluted cultivated land.

To examine the underlying determinants of ozone （O₃） in Yinchuan's urban park during varying seasons and to ascertain the role played by meteorological events and air contaminants in influencing O₃ concentrations at high altitudes, data on O₃, meteorological factors, and air pollutants were collected through prolonged positional observations carried out at the Ningxia Yinchuan National Urban Ecosystem Research Station. Pearson correlation analysis and a structural equation model were utilized to investigate the spatio-temporal distribution patterns, trends, and the primary factors influencing O₃. The findings demonstrated a notable seasonal variability in O₃ levels in Yinchuan's urban park, displaying an "unimodal type" with the O₃ concentration peaking in summer （131.18 μg·m^-3） and bottoming out in winter （71.45 μg·m^-3）. Among the meteorological factors, the highest impact on O₃ was attributed to temperature and wind speed （temperature mainly through direct effects and wind speed mainly through indirect effects）. Conversely, air pollutants such as NO_x and SO₂ greatly affected O₃ primarily through direct effects. Wind speed was identified as the primary influencing factor on O₃ during spring and summer, potentially contributing 29% and 24.7%, respectively. Conversely, NO₂ was implicated as the primary factor during autumn and winter, with an estimated contribution of 26.6% and 29.7%, respectively. Thus, a structural equation model can efficiently reveal the primary determinants behind O₃ variations throughout various seasons, which could furnish a scientifically rigorous foundation and technical aid for mitigating and managing O₃ levels in high-altitude regions.

In Lijiang City, as a typical example, 93 soil samples were collected from the study area, and soil pH； organic matter； and heavy metals arsenic （As）, mercury （Hg）, copper （Cu）, zinc （Zn）, lead （Pb）, cadmium （Cd）, and chromium （Cr） were determined. We explored the sources of heavy metals in the study area by means of Positive Definite Matrix Factorization （PMF） modeling and analyzed the impact of influencing factors by combining seven heavy metals with 13 influencing factors in a GeoDetector. The results showed that the mean values of soil heavy metals ω（As）, ω（Hg）, ω（Cu）, ω（Zn）, ω（Pb）, ω（Cd）, and ω（Cr） in the study area were 17.55, 0.19, 86.75, 164.84, 28.95, 0.39, and 167.87 mg·kg^-1, respectively, which were greater than the background values of soils in Yunnan Province （except for As and Pb）. Regarding spatial distribution, the high values of Cu and Cr content were mainly concentrated in Yulong Naxi Autonomous County； the high value areas of As, Hg, Pb, and Cd were mainly concentrated in Ninglang Yi Autonomous County； and the high value of Zn content was mainly concentrated in Huaping County. Correlation analysis and PMF modeling revealed that the main sources of heavy metals As and Hg in the study area were industrial sources, Zn was from transportation pollution sources, Cr and Cu were from natural sources, and Cd and Pb were from agricultural sources. Further, the factor detector of the GeoDetector found that soil pH and organic matter （OC） had strong explanatory power for the content of seven heavy metals, and the interaction detector found that the results following the interaction of different influencing factors were nonlinear enhancement or two-factor enhancement, in which the interaction of OC and pH was the dominant factor for the spatial differentiation of heavy metals. This provides an important scientific basis for the protection of the soil environmental health and sustainable development in Lijiang City.

To study the level of heavy metal pollution and ecological risks in the soil around typical mining areas in Tongling, a total of 150 soil samples were collected from the study area. The content characteristics of 10 elements, namely, As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Fe, and Zn, in the soils were analyzed. Methods including enrichment factor, the geo-accumulation index, single-factor pollution index, Nemero comprehensive pollution index, and potential ecological risk index were used to evaluate the pollution status of heavy metals in the soil of the study area. The pollution sources of heavy metals in the soil were also analyzed using correlation analysis, cluster analysis, and principal component analysis. The results showed that except for Cr and Fe, the average contents of the other eight heavy metal elements were higher than the soil background values in the study area. Pb, Zn, As, Cu, and Cd had a high degree of variation and were significantly affected by external interference. The spatial distribution showed that both Cr and Ni showed a decreasing trend from the edge to the central region, whereas the other eight heavy metals showed a decreasing trend from the central region to the surrounding areas. The pollution level of Cd and Cu in the soil of the research area was relatively severe. The overall ecological risk was at a medium to low level. Cd and Hg were the main contributing factors. As, Cd, Cu, Fe, Mn, Pb, and Zn mainly came from agricultural, industrial, and transportation sources, whereas Cr and Ni were mainly from natural sources. However, the sources of Hg were relatively complex. The research results can provide a scientific basis for the prevention and control of soil heavy metal pollution in metal mining areas, as well as the remediation of mine pollution.

To investigate the characteristics of grassland degradation on a regional scale in Xizang, data on grassland degradation from the second grassland survey of Xizang and 12 vegetation and soil indicators from the National Tibetan Plateau Data Center were collected. Using ArcMap, 10 000 random sample points were selected on raster data （excluding non-grassland, desertification, and salinization data, leaving 7 949 valid sample points）. The multi-value extraction to-point method was applied to extract degradation and indicator data for each sample point. The characteristics of degraded grassland vegetation and soil and their relationships were analyzed in Xizang. Moreover, random forest modeling was conducted to predict the trend of grassland ecosystem changes. The results indicated that： ① The grasslands in Xizang were primarily composed of alpine steppe and alpine meadow types, accounting for 45.83% and 41.15% of the valid sample points, respectively. ② With the intensification of grassland degradation, the number of steppe-type species among the 17 grassland types gradually decreased, and the proportion of steppe dominated by species such as Stipa purpurea and Carex moorcroftii decreased, whereas the proportion of miscellaneous grasses and Dasiphora fruticosa increased. ③ As the degree of degradation increased, vegetation indicators generally showed a declining trend, with soil total nitrogen, total phosphorus, total potassium, and organic carbon decreasing, whereas soil pH and bulk density increased, and soil moisture content was not significant. ④ A positive correlation exists between soil moisture content, total nitrogen, total phosphorus, total potassium, organic carbon, vegetation cover, net primary productivity of vegetation, normalized difference vegetation index, aboveground biomass, and habitat quality. However, there was a negative correlation between pH and soil bulk density, and the correlation coefficients among various indicators decreased with the intensification of degradation. ⑤ The random forest simulation results showed that during the degradation process, the contribution rates of soil bulk density and habitat quality both exceeded 12%, with the model prediction accuracy reaching 78%. The study revealed that grassland degradation in Xizang was closely related to soil bulk density and habitat quality, indicating that higher soil bulk density or lower habitat quality may correspond to more severe grassland degradation. This provides a scientific basis for future grassland conservation and management.

This study aimed to explore the spatiotemporal patterns and balance characteristics of land use carbon budget, measure the value of carbon compensation, and delineate carbon compensation type zoning to provide scientific reference for further strengthening the connection between the construction of an ecological compensation system and the "dual carbon" target task. Based on the land cover data of Chongqing from 2000 to 2020, this study analyzed the spatiotemporal dynamics and balance relationship characteristics of the land use carbon budget. By using the revised carbon compensation model to measure the horizontal compensation standards, the normalized revealed comparative advantage （NRCA） index and K-means clustering analysis method were used to divide the carbon compensation area. The research results demonstrated that： ① the total land use carbon sequestration in Chongqing grew slowly from 2000 to 2020, whereas carbon emissions continued to increase significantly, and the net carbon emissions showed a distribution pattern of "high in the center and low in the two wings." ② The average coefficient of variation in Chongqing was 0.602, and the carbon emission economy contributive coefficient and carbon ecological support coefficient were concentrated between 0.64-1.14 and 0.00-32.86, respectively. The difference in the contribution of carbon emissions and economic benefits between districts and counties was relatively small, but there was a mismatch between carbon supply and demand. ③ A significant spatial difference existed in the value of carbon compensation, with a total of 1.098 billion yuan in carbon payment and 634 million yuan in carbon compensation, respectively. Moreover, it was ultimately determined that there were eight key payment areas, seven general payment areas, three key compensation areas, and 20 general compensation areas. In conclusion, the research results can provide a reference for implementing differentiated development strategies in different types of carbon compensation regions, improve the collaborative governance capacity of the regional ecological environment, and promote the achievement of carbon neutrality goals.

Airborne microbes are affected by natural environmental factors and have become a global issue due to their potential threat to human health. To explore the effects of altitude on the communities of microbes and potential pathogenic bacteria, we sampled airborne microbes and soils at sites with different altitudes in Shigatse of Xizang. The results showed a significant difference in bacterial communities between air and soil and a decrease in the contribution of soil to airborne bacteria from the sites with a lower altitude to the sites with a higher altitude. The Chao1 indexes of airborne bacteria were significantly higher in the sites with a lower altitude compared to those with a higher altitude, and the bacterial Bray-Curtis distances between sites with a lower altitude were significantly lower than those between sites with a lower altitude and high altitude. These results indicated that altitude would affect the community patterns of airborne bacteria, and the transport of air would decrease the variations in airborne microbial communities between different sites. Proteobacteria, with 84%-91% of average abundance, predominated in the airborne bacterial communities, but different taxa were enriched in sites with different altitudes. For example, the genera of Flavobacterium and Lactobacillus were enriched in sites with a lower altitude and a higher altitude, respectively. A total of 78 potential bacterial pathogens were detected across all samples, and the relative abundance of them in bacterial communities ranged from 2.69% to 38.19%. These findings indicated that altitude would affect the community compositions of airborne bacteria and potential pathogenic bacteria and suggested the potential threat of airborne bacteria to human health. This study provided a scientific basis for better understanding the distributions of airborne microbes and for air quality improvement and disease prevention in China.