环境科学最新文献

Changes in soil carbon， nitrogen， and phosphorus contents and their stoichiometric ratios play a crucial regulatory role in biogeochemical cycles and ecosystem functions. However， the response of soil carbon， nitrogen， and phosphorus stoichiometry to long-term nitrogen deposition， particularly the contrasting patterns between rhizosphere and bulk soils， remains insufficiently understood. Based on this， a ten-year field experiment was conducted in Metasequoia glyptostroboides plantations at Dongtai Forest Farm in Yancheng， Jiangsu Province， with five nitrogen addition gradients： N0 [0 kg·（hm²·a）^-1]， N56 [56 kg·（hm²·a）^-1]， N168 [168 kg·（hm²·a）^-1]， N280 [280 kg·（hm²·a）^-1]， and N336 [336 kg·（hm²·a）^-1]. The basic physical and chemical properties， nutrient stoichiometric characteristics， enzyme activity， and microbial biomass of both rhizosphere and bulk soils were measured. The results indicated： ① Compared to that in N0， the overall carbon to nitrogen ratio in rhizosphere and bulk soils under all nitrogen addition treatments decreased significantly by 29.0% and 13.1%， respectively. In the N336 treatment， total nitrogen content and nitrogen to phosphorus ratio in rhizosphere soil significantly increased by 25.4% and 28.4%， respectively. The responses of soil organic carbon and total phosphorus contents and the carbon to phosphorus ratio to nitrogen addition were not significant across all treatments and in each individual treatment. ② The response directions of carbon， nitrogen， and phosphorus stoichiometric characteristics in rhizosphere and bulk soils to nitrogen addition were relatively consistent， but the response intensity in rhizosphere soil was greater. ③ Significant positive correlations were found among the organic carbon， total nitrogen， and total phosphorus contents in bulk soil， whereas only organic carbon and total nitrogen contents showed significant positive correlation in rhizosphere soil. Organic carbon content showed a significant positive correlation with stoichiometric ratios in both rhizosphere and bulk soils. ④ Microbial biomass and enzyme activity predominantly influenced the carbon， nitrogen， and phosphorus stoichiometric characteristics in bulk soil， whereas chemical properties such as pH， nitrate nitrogen， and available phosphorus contents were the primary regulators of these characteristics in rhizosphere soil. Overall， the responses of carbon， nitrogen， and phosphorus stoichiometric characteristics in rhizosphere and bulk soils to long-term nitrogen addition were relatively consistent but were regulated to varying degrees by soil chemical and microbial properties. This study deepens our understanding of the mechanisms and response patterns of rhizosphere and bulk soil carbon and nutrients to environmental changes， offering valuable scientific insights for advancing biogeochemical cycling models.

Yuqiao Reservoir is an important drinking water source for Tianjin. As the source of the "Water Diversion Project from Luanhe River to Tianjin"， there are more than one hundred types of contamination of antibiotic resistance genes （ARGs） in the Panjiakou and Daheiting Reservoirs. However， the level of ARGs in the upstream water transfer chain of Yuqiao Reservoir （Linhe River， Shahe River， and Lihe River） has not yet been studied. It is necessary to characterize the dynamic mechanism of ARGs in this basin to gain a deeper understanding of water ecosystem security. In this study， metagenomic methods were used to investigate the distribution characteristics of ARGs and mobile genetic elements （MGEs） in the surface water of the water transfer chain from Luanhe River to Tianjin during different periods， combined with the correlation mechanisms among microbial community structure and environmental factors. The results showed that the water transfer chain of the Luan River to Tianjin contained 21 types of ARGs with 1 161 subtypes. The main types of ARGs were multidrug， macrolide-lincosamide-streptogramin b （MLSB）， and tetracycline， with macB and tetA58 being the dominant ARGs. The predominant types of MGEs were integration/excision （IE） and replication/recombination/repair （RRR）. Compared to that during the flood period， there was a significant positive correlation between ARGs and MGEs during the dry period. Correlation analysis indicated that temperature， dissolved oxygen， and nitrate showed significant correlation with various ARGs （P < 0.05）. The abundance of ARGs was more easily affected by multiple environmental factors， but the composition of ARGs showed correlations only with total phosphorus and dissolved total phosphorus. Proteobacteria was the most dominant phylum， and several dominant microbial genera， such as Acidovorax and Rhodoferax， also showed significant correlation with ARGs， especially during the dry period. The co-occurrence network analysis revealed the most significant co-occurrence relationship between ARGs and MGEs， and some microbial genera related to nutrient elements and photosynthesis also showed co-occurrence relationships with major ARGs. This project aims to profoundly understand the biogeochemical cycle mechanisms of ARGs in the upstream water transfer chain of the reservoir， and it can provide a scientific basis for decision-making to control the transmission of resistance genes within the regional basin.

The regional carbon storage is profoundly affected by land use changes. In the context of the "dual carbon" goals， policy-oriented land use change prediction is crucial for optimizing land use patterns and enhancing carbon sequestration capacity. Based on the results of the "dual evaluation" and township-level main functional zoning， this study delineated suitable and unsuitable areas for urban construction and used the PLUS model to simulate land use changes in the Panxi dry valley region for 2035. Based on these simulation results， a policy-oriented scenario was constructed， and carbon storage changes under different scenarios were further estimated. Spatial autocorrelation analysis was also conducted to explore the spatiotemporal distribution characteristics of carbon storage. The results showed that： ① The western part of the Panxi dry valley region was primarily focused on ecological protection， while the central part emphasized agricultural production and urban development， with a clear spatial pattern. ② By 2035， although the overall land use patterns under both scenarios were similar， construction land expansion was significant under the natural development scenario， whereas the policy-oriented scenario effectively curbed construction land expansion and increased forest and cropland， highlighting the positive role of policies in ecological land protection. ③ In 2035， the carbon storage under the policy-oriented scenario was projected to be 6 517.22×10⁵ t， an increase of 3.50×10⁵ t compared to 6 494.75×10⁵ t under the natural development scenario， whereas the natural development scenario showed a decrease of 18.95×10⁵ t compared to that in 2020. ④ Local spatial autocorrelation analysis indicated that， the spatial distribution characteristics of carbon storage were similar under both scenarios， high-value areas were scattered， while low-value areas were mainly concentrated in river and low-altitude areas along their banks. These findings provide scientific support for the construction of the "Second Granary of Tianfu" and the implementation of the "carbon peak and carbon neutrality" strategy in the Panxi dry valley region.

The Jinsha River Basin， upstream of the Yangtze River， one of the critical regions for ecological protection in China， plays an important role for ecosystem stability and economic development in downstream areas， as well as in the whole Yangtze River Basin. Due to the ecosystem vulnerability， it is highly susceptible to natural factors and human activities. In order to better understand the spatiotemporal changes and trends of ecological quality and its driving factors， Theil-Sen trend analysis and the Hurst index were employed to assess the remote sensing ecological index （RSEI） from 2000 to 2023. Additionally， the XGBoost model combined with the SHAP algorithm was used to analyze the driving forces for the spatial heterogeneity of RSEI. The results showed that： ① The ecological quality of the Jinsha River Basin decreased gradually from south to north， the southern region exhibited relatively high ecological quality， and the northern and central regions had lower quality. In particular， the areas with high-altitude had significantly lower RSEI due to harsh climate and sparse vegetation. ② From 2000 to 2023， the areas with significant improvements in ecological quality accounted for 31.52%， primarily located in the northern part of Yushu Tibetan Autonomous Prefecture in Qinghai， Liangshan Prefecture in Sichuan， and Lijiang City in Yunnan. Conversely， the areas with significant degradation accounted for 3.36%， mainly concentrated in the central part of Ganzi Prefecture in Sichuan. In the future， 54.79% of the total area faces the risk of ecological degradation. ③ The spatial heterogeneity of ecological quality was mainly determined by natural factors， altitude and precipitation played the most influential role compared to other factors. The above conclusions would provide a scientific foundation for regional ecological protection and sustainable development.

To investigate the spatial distribution and sources of heavy metal contamination in the surface sediments of the Yellow River， this study focused on the Shaanxi section of the river. Sediment samples were collected from 54 locations， and the quantities of nine heavy metals， Cu， Fe， Mn， Ni， Zn， Cd， Cr， Pb， and As， were measured. The results revealed that the average values of heavy metal content were ranked as follows： Fe>Mn>Zn>Cr>As>Ni>Pb>Cu>Cd. Among these， Zn， Pb， Cd， and As exceeded shale background values， with Cd showing a high coefficient of variation， and 42.5% of the samples had Cd content above the background level. Notably， the content of As was above background levels in 90% of the samples. In contrast， the levels of the other heavy metals remained within acceptable risk thresholds. Spatial distribution analysis indicated that the primary factors influencing heavy metal content included population density， pH， and salt content. These factors interacted in ways that enhanced their combined effects， contributing to complex environmental conditions that may exacerbate regional ecological risks. Risk area delineation identified Wubao County， Hancheng City， Huayin City， Dali County， Heyang County， and Tongguan County as the main pollution hotspots. Using methods such as correlation analysis， principal component analysis， and receptor modeling， pollution source analysis indicated distinct sources for the various heavy metals. Cu， Fe， Mn， and Cr were predominantly of natural origin， while Ni was derived from a combination of natural and anthropogenic sources. The primary source of Cd was of agricultural origin， whereas Zn， Pb， and As were more influenced by anthropogenic activities. The predominant sources of heavy metals in the surface sediments of the study area included natural sources， agricultural sources， industrial sources， transportation sources， and composite pollution sources of unknown origin.

Under the national "double carbon" target， it is essential to fully understand the present situation and characteristics of carbon emissions in the water resources field. In order to explore the structural characteristics of the spatial correlation network of carbon emissions from different water resource behaviors in China， research samples were obtained from thirty provinces in China in 2022. According to the four behaviors of water resources development， allocation， utilization， and protection， the carbon emission of each province was calculated， and the space matrix was constructed by using the modified gravity model. Combined with social network analysis， the study analyzed the characteristics of its spatial correlation network. The results showed that： ① Under water resources development， allocation， and utilization behavior， the carbon emissions in southeast China were larger， while under water resources protection behavior， the overall carbon emissions were negative and relatively small in southeast China. ② The carbon emission network of water resources utilization behavior had the highest degree of closeness and stability among the four behaviors. The dependence of each region in the water resources allocation network was the lowest， and the degree of hierarchy and inequality were small. ③ Shanghai， Jiangsu， Beijing， Fujian， and Zhejiang were at the center of the four behavioral networks. ④ The block model division structure of carbon emissions under different water resource behaviors in China was obvious， and there were many correlations among different plates.

As the cornerstone of economic and social development， county-level regions hold significant strategic importance for accurately assessing China's carbon source distribution and carbon sink capacity， as well as effectively guiding the precise implementation of carbon neutrality strategies. The Three Gorges Reservoir Region， as a critical ecological barrier and water regulation zone， represents a significant case study for exploring land use and dual-carbon management. Supported by spatial technologies， this study used Landsat TM/Landsat 8 OLI remote sensing images from the years 2000， 2005， 2010， 2015， and 2020 as data sources. It employed models and methods such as standard deviation ellipses， centroid analysis， spatial autocorrelation analysis， and integrated carbon management to measure and analyze the spatiotemporal evolution of land use， carbon budgets， and carbon balance management zoning in the study area. The results indicate： ① The study area was dominated by forest land and arable land. Construction land increased the most， reaching 1 769.13 km²， while grassland and arable land decreased by 1 677.67 km² and 810.15 km²， respectively. Other land categories remained relatively stable， exhibiting spatial heterogeneity and unevenness in land use changes. ② Carbon emissions in the Three Gorges Reservoir Region first increased sharply and then gradually decreased， peaking at 39.15 million tons in 2010 and subsequently declining annually to 35.56 million tons， a reduction of 9.19%. The turning point occurred in 2010， with significant differences in the rate of change before and after and a slower declining trend over the subsequent decade. ③ Carbon absorption in the Three Gorges Reservoir Region initially declined sharply （-9.50%）， then increased moderately （6.94% from 2005 to 2015）， followed by a slight decrease （-3.38% from 2015 to 2020）， with significant overall fluctuations. ④ The spatial pattern of carbon budgets was evident， with 55.00% of carbon emissions concentrated in 11 counties at the reservoir tail and efficient， annually increasing carbon absorption in 11 counties at the reservoir belly. The distribution of carbon absorption and emissions was uneven， with higher emissions at the reservoir tail and higher absorption at the reservoir head， warranting particular attention. ⑤ Carbon management zoning indicated that the reservoir tail mainly consisted of compensation payment zones， while the reservoir head and belly were balance zones， exhibiting clustering and heterogeneity in their distribution. There remains significant room for optimization in emission reduction and carbon sink enhancement. The study provides scientific basis and practical guidance for carbon management in the Three Gorges Reservoir Region and similar regions， while also contributing important insights to the ecosystem carbon cycle theory， addressing global climate change， and promoting green and low-carbon development.

The labile components （LOC） of soil total organic carbon （TOC）， easily oxidizable carbon （EOC）， and dissolved organic carbon （DOC） are extremely sensitive to the changes of soil environment. Numerous studies have demonstrated that the increase of atmospheric nitrogen （N） deposition significantly affects the contents of soil LOC. As the difference in the chemical properties of various types of N fertilizers， however， their effects on LOC may be different. In this work， a typical temperate forest soil was selected， while sodium nitrate （NaNO₃）， ammonium nitrate （NH₄NO₃）， ammonium chloride （NH₄Cl）， and urea [CO（NH₂）₂] were added for four years at the rate of 10 g·（m²·a）^-1. Then， soil LOC， physicochemical properties， and extracellular enzymatic activity were assayed to compare the effects of different N fertilizers on soils. The results showed that the contents of EOC and DOC and their proportion in TOC decreased significantly after N addition （P<0.05）. Among them， the effect of NH₄Cl was the most significant （the reductions of EOC/TOC and DOC/TOC were -80.0% and -69.8%， respectively）， followed by NaNO₃， while LOC changed less after the addition of NH₄NO₃ and CO（NH₂）₂. The random forest model revealed that soil physicochemical properties， specifically pH and total nitrogen （TN）， along with extracellular enzymes involved in LOC decomposition （invertase and β-glucosidase）， constituted the crucial determinants driving the alterations in the proportion of LOC allocation. After the addition of NH₄Cl， the pH decreased by 0.8 units. The activities of soil invertase and β-glucosidase increased by 22.3% and 69.1%， respectively. These accelerated the decomposition of LOC components， resulting in a decrease in the ratios of EOC/TOC and DOC/TOC. Nitrate was easily leached， and its effects on total inorganic N （TIN） content were minimal. Furthermore， the degree of soil acidification was weak after the addition of CO（NH₂）₂， resulting in limited effects on soil extracellular enzymatic activities. In summary， nitrogen addition could affect the allocation proportion of LOC， yet the responses to different nitrogen sources were not entirely consistent. Therefore， when accurately assessing， predicting， and analyzing the effects of N deposition on soil LOC， the effects of N types should be considered.

Carbon capture， utilization， and storage （CCUS）， which aims to reserve fossil fuel uses in a low-carbon manner， is indispensable for carbon neutrality in China. However， the excess use of CCUS will distract the focus on energy transitions to renewables and in turn hamper the expected air quality co-benefits by carbon neutrality. As such， it is essential to identify how CCUS acts in the context of air quality co-benefits so as to fully facilitate the synergic reductions of CO₂ and air pollutants. Here， we set several CCUS-deployed scenarios and conducted machine learning algorithms with Latin hypercube sampling and evaluated the impacts of CCUS on the air quality co-benefits during carbon neutrality by region， industry， and pollutant. We showed that nitrogen oxide （NO_x） and particulate matter （PM） from power and nonpower sectors were most directly linked to CO₂ emissions. Air pollutant emissions from industrial sectors exhibited significant increments due to CCUS deployment， where increases in ammonia （NH₃）， NO_x， PM_2.5， sulfur dioxide （SO₂）， and volatile organic compounds （VOC） were up to 209.4%， 208.4%， 183.7%， 272.6%， and 250.5%， respectively. With regard to region， central provinces such as Shandong and Henan suffered from the major negative impacts of CCUS. To mitigate the negative impacts of CCUS， it is necessary to facilitate control measures for air pollutants that are not directly linked to fossil fuel-related CO₂ as well as carbon neutrality.