Huanjing Kexue/Environmental Science最新文献

The 25 counties along the Shandong section of the Yellow River are the core areas for promoting the ecological protection and high-quality development of the Yellow River in Shandong Province. Moreover, it is of great significance to study the current situation, sources, and potential risks of heavy metal pollution in the topsoil in this region. In this study, 103 soil samples were collected from the 25 counties along the Shandong section of the Yellow River, and the contents of eight heavy metals （As, Cu, Pb, Cr, Zn, Ni, Cd, and Hg） were determined. The pollution characteristics of heavy metals were analyzed and evaluated using the geological accumulation index and potential ecological risk index. Correlation analysis and the positive matrix factorization （PMF） model were used to analyze the sources of heavy metals. The results showed that the average contents of Cu and Cr were lower than that of the background values of soils, whereas the average contents of As, Pb, Zn, Ni, Cd, and Hg were 1.16, 1.42, 1.05, 1.14, 2.29, and 1.85 times higher than that of the background values, respectively, and the average contents of all eight elements were lower than the screening value of soil pollution risk in agricultural land. In terms of different heavy metal variations, the coefficient of variation （CV） of Cu and Cd was higher than 0.500, indicating high variations, whereas As, Pb, Cr, Zn, Ni, and Hg showed moderate variation. Cd and Hg were slightly polluted, whereas the other six elements were not polluted. Cd and Hg had a moderate potential ecological risk level, whereas the other six elements were at a low level. Correlation analysis and PMF model showed that the sources of heavy metals in the study area were influenced by four factors, i.e., agricultural activities, natural sources, industrial emissions, and atmospheric dust from coal combustion and vehicle exhaust emissions, and the relative contribution rates were 32.4%, 34.9%, 16.5%, and 16.2%, respectively.

This study investigated the impact of single and combined applications of three foliar inhibitors on the accumulation of cadmium （Cd） and arsenic （As） in rice grains. Two rice varieties, Songyazao 1 （for early rice） and Wuxiang Youyue （for late rice）, were selected for this experiment. We established nine treatments using a pot experiment method, including a control （CK） treated with no foliar inhibitor and three individual foliar inhibitors： cysteine （L-Cys）, potassium sulfide （K₂S）, and dipotassium hydrogen phosphate （K₂HPO₄）. We then combined the applications of two foliar inhibitors： L-Cys with low/high concentrations of K₂S, L-Cys with low/high concentrations of K₂HPO₄, and K₂S with a low concentration of K₂HPO₄. The results showed that the single and combined applications of foliar inhibitors reduced Cd and As concentrations in rice grains. The Cd content in brown rice treated with L-Cys and K₂S/K₂HPO₄ was reduced below the standard limit for food safety of 0.20 mg·kg^-1. Compared to the CK, the content of inorganic arsenic （IAs） in early and late rice decreased by 4.68%-56.75% and 2.84%-16.91%, respectively. Foliar inhibitors applied individually or in combinations facilitated the transport of Cd and As from the stem to the leaf while inhibiting their transport from the leaf to the rice grain. This resulted in the sequestration of Cd and As within the leaf cell wall, ultimately reducing the content of these elements in rice grains. Among the combination treatments, the application of L-Cys and high-concentration K₂S achieved the best results. The Cd content in early and late rice decreased by 37.64% and 26.37%, respectively, falling below 0.20 mg·kg^-1. The IAs content in early and late rice was reduced to 0.10 mg·kg^-1 （below 0.20 mg·kg^-1） and 0.24 mg·kg^-1, respectively. This study provides a valuable theoretical foundation and empirical data to support the achievement of safe rice production practices.

Regional groundwater recharge is a critical scientific issue for sustainable groundwater resource development and management. However, spatial variations in groundwater recharge in the Loess Plateau （LP） remain poorly understood. To fill this knowledge gap, a systematic sampling campaign and stable isotope analysis were carried out for groundwater （shallow aquifer） in 13 major catchments during July 2019. The main objectives of this study were： ① to understandthe spatial distribution and influencing factors of stable isotopes in groundwater and ② to reveal the groundwater recharge sources and pathways and their spatial variations, combined with the precipitation stable isotope datasets. Stable isotopes in groundwater had poor spatial variations at the regional scale； however, they became isotopically depleted with the increase in annual average precipitation on the catchment scale （r = -0.87）. Compared with the stable isotope of precipitation, stable isotopes of groundwater were generally depleted and were similar to the precipitation of the rainy season （July-September）. These together indicated that there was pronounced seasonality of groundwater recharge, and the main recharge period was the rainy season. In particular, the recharge seasonality index （δ_P/G） was closely related to the catchment's average annual precipitation （r = -0.77） and leaf area index （r = -0.63）. In addition, groundwater lc-excess was generally negative, with the catchment-mean value ranging from -4.3‰ to -0.7‰. Hydrologically, this indicated that groundwater recharge pathways （ratio of matrix flow vs. preferential flow） were different among these catchments, which should be quantitatively determined by combining the saturated zone （groundwater） and the unsaturated zone （soil） in future work. Our findings can improve the understanding of groundwater recharge in LP and provide a scientific basis for sustainable management of groundwater resources at the regional scale.

As the largest freshwater lake in China, Poyang Lake plays a key role in supporting the balance of aquatic ecosystems, and the water quality of its inlet rivers affects the lake's water quality. Le'an River, a typical inlet river of Poyang Lake, was selected as the research object. Based on the water quality data of six monitoring points in the upper, middle, and lower reaches of the mainstream of Le'an River from 2012 to 2020, the CCME-WQI method was used to evaluate the water quality of the river after systematically analyzing the spatiotemporal variation of the concentration of pollutants in the mainstream of the river. Finally, the main influencing factors of the water quality of the river were extracted and analyzed according to the PCA method. The results showed that： ① The water volume upstream and downstream of the river was more seriously polluted in the pre-study time period, which was due to the presence of Dexing Copper Mine in the upstream and small and medium-sized mines and farmland downstream. ② Before 2017, the water volume downstream of Le'an River had the worst water quality, with TP and NH₄⁺-N exceeding the standard rate of 43.3% and 85.0%, respectively, and the lowest WQI mean value of 86.2. After 2017, due to the effective management of pollutant discharges in the watershed, the water volume downstream of the river improved significantly and continued to be in an excellent state, and the mean value of the WQI reached 100.0. ③ The factors influencing the water quality of the mainstem of the Le'an River could be divided into four categories： human activities, seasonal factors, atmospheric deposition of pollutants, and the physical and chemical properties of the water volume itself, with human activities being the dominant factor for water quality changes at Dawuhekou and Shizhenjie, whereas the seasonal factors had the greatest influence at the remaining locations. ④ Organic matter pollution was obvious in the upper and lower Le'an River water volume, and the water volume at Dawuhekou was mainly affected by nearby mining activities, whereas the water volume at Shizhenjie was mainly affected by agriculture. Le'an River had serious organic matter pollution downstream before 2017, and mining and agricultural activities in the watershed had a high degree of impact on water quality. The treatment of mineral processing wastewater should be upgraded, and the discharge of pollutants from agriculture in the downstream of the watershed should be regulated.

The cause of ozone pollution is a complex scientific problem. Studying the spatiotemporal variation characteristics of O₃ at different time scales and analyzing the key influencing factors of O₃ concentration is of great significance for the precise formulation of urban air pollution control measures and the improvement of urban air quality. Based on the analysis of the spatiotemporal variation characteristics of O₃ concentration in Chuzhou City, we studied the 12 ozone-influencing factors of meteorology and pollutants at multiple time scales using Spearman correlation analysis and a random forest model. The results showed that： ① The O₃ pollution level of Chuzhou City showed an aggravating trend, and the O₃ concentration distribution showed a spatial pattern of "high in the southeast and low in the northwest." ② From February to May, SO₂ concentration had a strong impact on the increase in O₃ concentration. From June to September, PM_2.5 and PM₁₀ were significantly positively correlated with ozone and had a greater impact. ③ Relative humidity, temperature, and wind speed had a significant impact on O₃, whereas barometric pressure and hourly rainfall had a weak impact. ④ The O₃ pollution mechanism in Chuzhou City changed from "pollutant-controlled" to "meteorology-controlled." ⑤ Among meteorological and pollutant factors, the three influencing factors that had the greatest influence on O₃ concentration were temperature, wind speed, and relative humidity, with PM₁₀ concentration, PM_2.5 concentration, and SO₂ concentration also contributing. All of the above six influencing factors had a significant nonlinear relationship with the O₃ concentration.

Based on the environmental monitoring data and meteorological observational data in Hainan Island from 2015 to 2021, the PM_2.5-polluted characteristics, influencing factors, and potential contributing regions were analyzed using the backward trajectory simulation, cluster analysis, potential source analysis function （PSCF）, and concentration weight trajectory （CWT） methods. The results showed that PM_2.5 in Hainan Island had an obvious seasonal variation, with the highest in winter （22.6 μg·m^-3）, followed by that in autumn and spring （17.38 and 16.53 μg·m^-3, respectively）, with the lowest in summer （9.79 μg·m^-3）. In the past seven years, there were 30 days in Hainan Island in which PM_2.5 concentration exceeded the standard. The annual average and four seasons of PM_2.5 showed a significant downward trend, and the climatic change rates were -0.97 （annual mean）, -1.09 （spring）, -0.61 （summer）, -0.83 （autumn）, and -1.25 （winter） μg·（m³·a）^-1. PM_2.5 in Hainan Island was highly correlated with gaseous pollutants, with correlation coefficients of 0.471 （SO₂）, 0.633 （NO₂）, 0.479 （CO）, and 0.773 （O₃-8h）, all passing a significance level of 0.01. PM_2.5 was positively correlated with average wind speed and atmospheric pressure and negatively correlated with precipitation, relative humidity, sunshine duration, average temperature, and total solar radiation. Among them, average temperature, relative humidity, and total solar radiation were the main dominant meteorological factors on PM_2.5 in Hainan Island. Backward trajectory and potential source analysis revealed that PM_2.5 concentration was high （≥20 μg·m^-3） in winter and autumn, which was influenced by airflow from inland regions, and Fujian, Zhejiang, Hunan, Jiangxi, Guangdong, and Guangxi provinces were the main potential sources of PM_2.5 in Hainan Island.

Soil heavy metals in karst areas have obvious high background value characteristics. Conducting county-level soil heavy metal ecological risk assessment and identifying heavy metal sources in karst areas are of great significance for soil pollution control and land resource management. Taking Pingguo City, a typical karst county in Guangxi Province, as the study object, 3 151 surface and deep soil samples were collected using the grid method and combined to form 785 analytical samples. The contents of eight heavy metal elements, including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were determined. The content characteristics and sources of heavy metals were analyzed using statistical analysis, interpolation analysis, factor analysis, and the absolute principal component-multiple linear regression model （APCS-MLR）. Using the content of heavy metal elements in deep soil （150-200 cm） as background values, the ecological risk assessment of heavy metals in surface soil （0-20 cm） in the study area was conducted using the geo-accumulation index （I_geo） and potential ecological risk index （RI） methods. The results showed that the average content of heavy metal elements in the deep soil of the study area was significantly higher than the background value of the C layer soil in Guangxi Province, and the average content of heavy metal elements in the surface soil was significantly higher than the background value of the A layer soil in Guangxi Province. The spatial distribution of soil heavy metal element content generally showed the characteristics of high in karst areas and low in non-karst areas. The main sources of As, Cr, Ni, Pb, and Zn were soil parent materials, with contribution rates of 74.36%, 84.59%, 93.69%, 79.67%, and 78.17%, respectively. The main sources of Cd were soil parent material sources and unknown sources, with contribution rates of 37.33% and 31.05%, respectively. The main sources of Cu were soil parent materials and unknown sources, with contribution rates of 59.07% and 40.23%, respectively. The main sources of Hg were tectonic activity and mineralization, as well as unknown sources, with contribution rates of 52.49% and 30.65%, respectively. The geo-accumulation index （I_geo） showed that the surface soil was mainly polluted by Cd, with mild or above pollution accounting for 47.78%. The potential ecological risk index （RI） showed that the proportion of surface soil heavy metal comprehensive potential ecological hazards with mild, moderate, strong, and very strong levels was 80.78%, 14.97%, 2.51%, and 1.64%, respectively.

As the forefront of implementing China's "Yellow River Major National Strategy," the lower Yellow River area has caused irreversible "constructive destruction" to the regional natural ecosystem and ecological functions while accelerating the process of urbanization and has become an area of sharp contradiction between ecological protection and high-quality development of the river basin. Therefore, based on ArcGIS and MATLAB software, this study used the InVEST and RUSLE models to quantitatively assess water yield, habitat quality, and soil conservation services of the lower Yellow River Region from 1990 to 2020 and analyzed the spatial and temporal characteristics and their interaction relationships of various ecosystem services. The results showed that： ① In the period from 1990 to 2020, the land urbanization process accelerated significantly, with the expansion of construction land increasing by 39.89%, whereas the area of other major land types had declined to varying degrees. ② From 1990 to 2020, the distribution patterns on the county scale and grid-scale in the lower Yellow River Region were relatively consistent. The water yield and soil conservation experienced a changing trend of first decreasing and then increasing, and the spatial distribution pattern of water yield gradually shifted to more in the east and less in the west. The spatial distribution patterns of soil conservation and habitat quality remained unchanged throughout the period, with the high values distributed in the hilly or mountainous regions of the higher terrain and the low values mainly in the plains of the gentle terrain. ③ At both the grid scale and county scale, the interaction relationships between various ecosystem services had been dominated by synergy and showed significant spatial heterogeneity. Especially at the county level, strong trade-offs were occurring in a few counties. For example, the relationship between water yields and habitat quality was a significant and strong trade-off between Weishan County and Huaiyin District. The study quantified the spatial and temporal evolution characteristics of ecosystem services in the lower Yellow River Region and clarified the trade-off synergistic relationships between ecosystem services, which can provide a scientific basis for ecological protection and watershed management under the rapid urbanization process.

Based on the goal of "dual-carbon" strategy, it is important to explore the impacts of land use change on carbon stock and the drivers of spatial differentiation of carbon stock in Xinjiang. Here, we predicted the land use types in Xinjiang in 2035 under different scenarios and analyzed the impacts of land use on carbon stock, which is of great theoretical and practical importance for policy formulation, land use structure adjustment, and carbon neutrality target achievement in Xinjiang. The coupled PLUS-InVEST-Geodector model was used to explore the spatial and temporal patterns of carbon stock change under the scenarios of rapid development, natural change, arable land protection, and ecological protection in Xinjiang in 2035 and to quantitatively reveal the attribution of influences on the changes in carbon stock from the perspectives of land use change and the combination of nature-socioeconomic-accessibility. The results showed that： ① From 1990 to 2020, the area of arable land and construction land in Xinjiang increased, and in terms of the transfer direction, it was mainly shifted from unutilized land to grassland. ② On the time scale, the carbon stock in Xinjiang showed the fluctuation of "decrease-increase-decrease," with an overall increasing trend. The transfer of unutilized land to grassland was the main reason for the increase in carbon stock； on the spatial scale, the carbon stock in the Altai Mountains in the north, the Tianshan Mountains in the middle, and the Kunlun Mountains in the south was higher, whereas the carbon stock in the Tarim Basin and the Junggar Basin was lower. ③ In 2035, the carbon stock of the natural development and rapid development scenarios decreased by 27.24 Tg and 71.17 Tg compared with 2020, respectively, and the ecological protection and arable land protection scenarios increased by 492.55 Tg and 46.67 Tg. The ecological protection scenario could significantly increase the carbon stock of the Xinjiang Region compared with that in the other scenarios, and the distribution pattern of the carbon stock in the four scenarios was more or less the same as that in 2020. In addition to land transformation, soil erosion intensity was the main driver of spatial differentiation of carbon stocks in Xinjiang （q value of 0.3501）, followed by net primary productivity of vegetation. The results of multifactor interactions showed that the spatial differentiation of carbon stocks in Xinjiang was the result of the joint action of multiple factors. All the factors had a synergistic enhancement under the interactions. The interaction between soil erosion intensity and the net primary productivity of vegetation was the main driver of the spatial differentiation of carbon stocks in Xinjiang.

Analyzing the spatiotemporal differences in land use carbon emissions systematically and exploring their influencing factors for the rational allocation of land resources is of great importance and promoting collaborative emission reduction in this region. Based on the calculation of land use carbon emissions in Ningxia and its prefecture-level cities from 2000 to 2021, the regional differences in carbon emissions, economic efficiency, and carbon sink capacity were reflected through the difference index, carbon emission intensity, economic contribution rate, and carbon sink ecological carrying capacity. The results were as follows： ① From 2000 to 2021, the land use carbon emissions in Ningxia showed a significant increase by 110 919 400 t. Construction land was the main carbon source land, accounting for 99.57% of the total carbon emissions in 2021, and forest land was the main type of carbon absorption, accounting for 79.22% of the total carbon absorption in 2021. ② During the research period, the carbon emission difference among prefecture-level cities showed a trend of first rising and then slightly falling, with the gap reaching the maximum in 2016. ③ Although the overall difference in carbon emission intensity among prefecture-level cities showed a trend of narrowing and convergence, the economic contribution coefficient and carbon sink ecological carrying coefficient had significant differences, and the economic contribution rate and carbon emission contribution rate were both in a relatively unbalanced state, with obvious regional differences. ④ Land use carbon emission intensity, land use structure, economic development level, and population all played a promoting role in land use carbon emission, with contribution rates of 56.48%, 41.27%, 85.20%, and 9.29%, respectively. The contribution value of land use carbon intensity per unit GDP was negative, which inhibited the increase of land use carbon emission.