环境科学最新文献

Based on the greenhouse gas inventory guidelines proposed by the Intergovernmental Panel on Climate Change of the United Nations， the carbon emissions of Heilongjiang Province were calculated from aspects such as energy， industrial production processes， and land use. The correlation between different factors and carbon emissions was analyzed using grey relational theory and Tapio decoupling theory， and the STIRPAT model was used to explore the differences in the impact of various factors on carbon emissions. Future carbon emissions in Heilongjiang Province were predicted using scenario analysis. The results showed that： ① The total carbon emissions in Heilongjiang Province grew rapidly from 2005 to 2012， then showed a fluctuating downward trend from 2012 to 2020， with the decline gradually slowing. ② Energy carbon emissions dominated the carbon emissions in Heilongjiang Province， accounting for approximately 90%， far exceeding the other three categories of carbon emissions. ③ The order of influence of different factors on carbon emissions was as follows： land area > population > energy structure > wealth level > energy intensity. ④ During the study period， carbon emissions in Heilongjiang Province reached the peak in 2012 according to the STIRPAT model， effectively achieving the goal of "carbon peak." ⑤ In the scenario simulation， the optimal scenario was Scenario IV. In this scenario， the rate of change for each factor was based on the more optimal values between the recent actual data from Heilongjiang Province and the "14th Five-Year Plan."

Understanding of the spatiotemporal evolution characteristics of ecosystem services in key areas and the interaction effects of their drivers will help formulate precise ecosystem management plans and promote the sustainable supply of regional ecosystem services. Taking the Wuling Mountain Area as an example， the InVEST model was used to evaluate the four key ecosystem services in the area， and the MESLI was constructed. Then， the importance and interaction effects of MESLI drivers were analyzed using XGBoost-SHAP， and the influence threshold of the drivers was clarified by RCS. The results showed that： ① From 2001 to 2020， the ecosystem services in the Wuling Mountain Area showed an overall upward trend， and the mean value of MESLI increased from 1.768 to 1.992， and there was significant spatial heterogeneity， with a low spatial distribution in the southeast and west and a high distribution in the north and south. ② The main driving factor affecting MESLI was annual precipitation， which contributed 0.16， followed by the proportion of cultivated land with 0.11. ③ There was a significant interaction between the driving factors. In the area with a high proportion of cultivated land， with the increase in vegetation coverage and slope， the negative impact on MESLI weakened and gradually changed to a positive effect. In areas with many human footprints， the negative impact on MESLI weakened with the increase in slope and vegetation coverage and gradually changed to a positive impact. In areas with low vegetation coverage， the impact on MESLI changed from negative to positive when the slope increased by a certain value. ④ The thresholds of the driving factors on MESLI under the influence of interaction were as follows： cultivated land area proportion （22.91%）， annual precipitation （1 542.47 mm）， vegetation coverage （0.63）， slope （15.17°）， potential evapotranspiration （957.93 mm）， annual average temperature （15.26℃）， elevation （653.96 m）， and human footprint （11.56）. The results of this study provide a methodological reference and decision-making basis for the formulation of ecosystem management measures in the Wuling Mountain Area.

In order to explore the pollution status of emerging contaminants in groundwater around industrial enterprises in South China， four industries were selected， and a total of eight groundwater samples were collected around these industries. Ultra-high-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） was used to determine the concentrations of enrofloxacin， ofloxacin， sulfadiazine， sulfamethoxazole， and tetracycline in the samples. Combined with various analytical methods， the study investigated the spatial distribution characteristics， source analysis， and ecological risk assessment of the target antibiotics. The test results showed that enrofloxacin was detected in the range of 43.93 to 228.68 ng·L^-1， and ofloxacin was detected in the range of 100.18 to 199.26 ng·L^-1 in groundwater samples. The detected concentration levels were relatively high compared to some regions of China. There were significant concentration differences in the spatial distribution of the two antibiotics， which may be related to the pollution sources and intensity. The main sources of pollution at W6 and W7 sampling points were agricultural non-point source pollution from domestic sewage and livestock waste， while the main sources of pollution at W1 and W4 sampling points were industrial point source pollution from solid waste and medical waste treatment production wastewater and leachate. The ecological risk assessment results showed that RQ_sum of enrofloxacin and ofloxacin at sampling point W7 to Pimephales promelas was greater than 0.1， indicating a medium risk， and there was a low risk to P. promelas at sampling point W6. Based on the current situation of groundwater used for fish and shrimp aquaculture in the study area， there were certain ecological risks in the groundwater of sampling points W6 and W7 that require further attention. The human health risk assessment results showed that enrofloxacin and ofloxacin in the sampling points of the study area posed no risk to the health of adults and children. The health risk quotient for children was higher than that for adults. Currently， there are no acceptable daily intake standards for different populations in China， and further in-depth research is needed to conduct a more accurate health risk assessment.

Photovoltaic development （PVPPC） has gradually become an important way to address climate change and achieve energy transition. Under the influence of PVPPC， a unique photovoltaic ecosystem is formed by the interaction between biological communities and inorganic environments within the photovoltaic field. Maintaining carbon balance is crucial for achieving the sustainability and health of the photovoltaic ecosystem. Net ecosystem carbon exchange （NEE） helps measure the carbon cycle balance of photovoltaic ecosystems， which is influenced by various environmental factors such as meteorology and soil. Taking the Gonghe photovoltaic park on the Qinghai Tibet Plateau as the research area， field-measured meteorological， soil， and flux data were obtained to analyze the mutual feedback response relationship between ecological environmental factors and the NEE of desert photovoltaic ecosystems. It was found that net radiation， air temperature， wind speed， relative humidity， and average atmospheric pressure were the five driving factors that had the greatest impact on the NEE of the desert photovoltaic ecosystems. A support vector machine （SSA-SVM） optimized based on the sparrow search algorithm was used to construct an ecosystem NEE estimation model under the influence of desert photovoltaic development. The model was used to predict the changes in NEE of desert photovoltaic ecosystems under different climate scenarios. The results showed that the model had good simulation performance for the NEE of the desert photovoltaic ecosystem， with an error controlled within 2%. Under three climate scenarios （SSP126， SSP245， and SSP585）， the carbon sink of the desert photovoltaic ecosystem during the growing season was higher than that during the non-growing season. The average annual NEE （calculated as C） was -37.96， -41.32， and -47.68 g·（m²·a）^-1 and -12.69， -12.25， and -12.33 g·（m²·a）^-1. The impact of climate change on carbon cycling during the growing season was significantly higher than that during the non-growing season， indicating that the desert photovoltaic ecosystem will still maintain strong carbon sequestration potential in the future. This study provides a new perspective for predicting carbon exchange in desert photovoltaic ecosystems and also provides data support for fields such as ecosystem stability assessment， environmental restoration， and climate change trend analysis.

Microplastics， as emerging contaminants， are widely distributed in the hydrosphere of the Earth. They not only provide a new niche for microorganisms， including antibiotic-resistant bacteria， but also interact with other pollutants， such as heavy metals， antibiotics， disinfectants， etc. Moreover， they migrate with water flow and through the food chains， influencing the spread and dissemination of antibiotic-resistant bacteria and resistance genes. Therefore， microplastics may not only serve as a vector for the transmission of pathogens but also be a hotspot for the transfer of resistance genes， posing significant threats to both human health and urban ecosystems. This review summarizes the types and abundances of antibiotic resistance genes in the plastisphere of different waters areas （including seawater， freshwater， and wastewater） and explores the influencing factors for the spread and dissemination of antibiotic resistance genes in the plastisphere， as well as their potential risks to human health and ecosystems. Finally， the future research directions of antibiotic resistance in the plastisphere are prospected， aiming to provide new insights for a comprehensive understanding of relevant issues regarding antibiotic resistance in the plastisphere.

Soil acidification is a critical global issue threatening agricultural productivity and ecosystem health. In recent years， human activities have intensified soil acidification， posing significant challenges to food security and sustainable agriculture. Acidified soils are characterized by a decline in pH， increased activity of toxic metal ions， and nutrient depletion， leading to soil structure degradation and restricted plant growth. This article systematically summarizes the main driving factors of soil acidification in farmland， including non-human factors （weathering and leaching， nutrient absorption， organic matter decomposition， root exudates release， lightning volcanic eruption and deposition， microbial activity， etc.） and human factors （unreasonable agricultural management， climate change， etc.）， and further analyzes the main processes of microbial-mediated soil acidification affecting nutrient cycling. To address soil acidification， existing mitigation strategies are summarized， such as lime application， balanced fertilization， organic matter management， biochar application， and the promotion of acid-tolerant crops. However， due to the diversity of soil types， the complexity of acidification processes， and variations in crop types and cultivation practices， the effectiveness of these measures varies significantly. By providing a comprehensive synthesis and outlook and considering the context of climate change， this study explores future research directions， offering both theoretical foundations and practical guidance for the scientific management of soil acidification and the advancement of sustainable agriculture.

Meteorological conditions have a significant impact on the concentration variations of ozone （O₃） and its precursors. Quantifying the impact of different meteorological factors on O₃ concentrations is crucial for formulating and optimizing prevention and control strategies for near-surface O₃ pollution. This study collected hourly near-surface O₃ concentration data and meteorological data from the main urban area of Lanzhou City during the summers from 2019 to 2023. Using an XGBoost-based meteorological normalization method， the impact of meteorological conditions on O₃ concentrations was decoupled and quantified. Subsequently， the XGBoost-SHAP model was introduced to quantitatively analyze the contributions of various meteorological factors to O₃ concentrations. The results indicate that the continuous increase in near-surface O₃ concentrations in the main urban area of Lanzhou City during the summers from 2019 to 2023 was due to a combination of meteorological conditions and precursor emissions. Meteorological conditions were the primary factor contributing to the continuous rise in O₃ concentration from 2019 to 2021. The relatively unfavorable meteorological conditions from 2019 to 2020 and from 2020 to 2021 resulted in increases in ambient O₃ concentrations of 3.828 and 7.378 μg·m^-3， respectively. The meteorological conditions improved between 2021 and 2022 and again between 2022 and 2023， resulting in decreases in O₃ concentrations by 0.348 and 0.768 μg·m^-3， respectively. The increase in O₃ concentration during these two years was mainly related to changes in precursor emissions. Through SHAP model analysis， it was found that boundary layer height （BLH）， 2-meter temperature （T2m）， downward surface ultraviolet radiation （UVB）， relative humidity （RH）， and surface net solar radiation （SSR） were the key meteorological factors influencing the summer near-surface O₃ concentrations in the main urban area of Lanzhou City. The annual contribution rates of these factors to O₃ concentrations remained stable within the range of 71.82% to 73.65%. T2m， BLH， and UVB were positively correlated with O₃ concentrations， while RH was negatively correlated with O₃ concentrations. The contribution of SSR to O₃ concentrations exhibited a unimodal pattern， with both excessively high and low levels inhibiting O₃ production. The contribution values of various meteorological factors to summer ozone concentrations in the main urban area of Lanzhou City changed over time. Fluctuations in T2m and RH were the main reasons for the interannual variations in the meteorological contribution to summer O₃ concentrations in the main urban area of Lanzhou City from 2019 to 2023.

Biodegradable mulching films （BMPs） have been widely used as an alternative to conventional plastic mulching films （CMPs）. However， the long-term effects of BMPs on soil microbial community structure remain unclear. Therefore， in this study， we set up two treatments， CMPs and BMPs， and conducted a field experiment with 26 a of CMPs and 11 a of BMPs coverage. Using metagenomics technology， the effects of BMPs on soil microbial community structure in cotton fields in arid areas were investigated. The results showed that compared with those under the CMPs treatment， the BMPs treatment significantly reduced soil water content （SWC）， bulk density （BD）， and available phosphorus （AP） by 25.00%， 12.50%， and 12.09%， respectively， but significantly increased soil porosity （SP） by 10.07%. The BMPs treatment （124） significantly reduced the number of unique species compared with that in the CMPs treatment （182）. At the phylum level， the BMPs treatment significantly increased the relative abundance of Proteobacteria and significantly decreased the relative abundance of Actinobacteria. At the genus level， the BMPs treatment significantly increased the relative abundances of Nocardioides， Solirubrobacter， and Nitrospira and significantly decreased the relative abundance of Sphingomonas. Meanwhile， the proportion of positive correlations and the average degree between microbial communities in the BMPs treatment were increased significantly by 16.32% and 8.71% compared with those in the CMPs treatment， respectively， reducing the modularization degree of the microbial community by 1.89% and promoting the symbiotic relationship and stability of the microbial community. The BMPs treatment significantly increased the relative abundance of genes such as xylA， narG/nxrA， and nasA and significantly decreased the relative abundance of genes such as accA， frdA， nirB， nrtA， gcd， and phoR， promoting carbon degradation， denitrification， and assimilative nitrate reduction processes and inhibiting dissimilatory nitrate reduction and inorganic phosphorus solubilization processes. Soil SWC and AP were the key environmental factors affecting microbial community composition. Biodegradable mulching film increased the complexity and stability of soil microbial communities compared with traditional mulching film， and soil SWC and AP were the key environmental factors affecting the composition of microbial communities.

Microplastics （MPs） are widely present in terrestrial ecosystems， but the impact of their accumulation on microbial necromass and their contribution to soil organic carbon （SOC） in different land use types is unclear. In this study， 5 mm×5 mm polyethylene microplastics （PE-MPs） sourced from plastic film were added to the grassland， farmland， and facility soil at the dosages of 0% （CK）， 0.03%， and 0.3% （w/w）， respectively， for an eight-week indoor culture experiment. The changes in soil organic carbon and microbial residue carbon were analyzed after the culture was completed. The results showed that： ① The addition of 0.03% and 0.3% PE-MPs reduced the soil MNC content of the three land use types by 5.4%-11.1% and 2.1%-37.1%， respectively， compared with those of CK. Among them， the addition of 0.3% PE-MPs significantly reduced soil MNC content by 19.8% and 37.1% in farmland and facility soils， respectively， and had no significant effect on grassland soil. ② The addition of 0.03% and 0.3% PE-MPs significantly reduced the contribution of soil MNC to SOC by 20.6% and 25.0% in the farmland and by 4.8% and 18.8% in the facility soils， respectively （P<0.05）. The addition of 0.3% PE-MPs increased the contribution of soil MNC to organic carbon in grassland by 5.9%. ③ Soil nitrate nitrogen， dissolved organic nitrogen， and pH were important factors affecting the accumulation of microbial necromass carbon. In conclusion， the accumulation of soil MNC and its contribution to SOC were reduced in both farmland and facility soils after the addition of 0.3% PE-MPs， which was detrimental to soil carbon sequestration.

The formation of new quality productivity has provided new impetus for the synergistic development of the digital economy and green innovation. Based on the provincial panel data of China from 2012 to 2022， this study applied the coupling coordination model， Theil index decomposition method， and spatial Durbin model to explore the spatio-temporal evolution characteristics， regional differences， and spatial spillover effects of the synergistic development level of the digital economy and green innovation. The results showed that： ① In terms of chronological development， the synergistic degree of digital economy and green innovation showed a rugby ball-shaped distribution pattern. Most regions were still in the medium synergy stage. ② In terms of spatial pattern， the collaborative development level between the two showed a "high-low" two-tier distribution characteristic from east to west. The overall difference in the level of synergistic development between the two was a fluctuating downward trend， mainly stemming from the diversity and imbalance within the region. ③ In terms of influencing factors， new quality productivity had a significant positive spillover effect on the synergistic development of digital economy and green innovation and helped to improve the level of synergistic development in neighboring regions. Government support， economic development， industrial upgrading， and foreign investment were indispensable factors in this process. Therefore， it is recommended that each province should construct development programs according to local conditions and establish a linkage pattern for the synergistic development of the digital economy and green innovation， so as to provide decision-making references for the promotion of sustained， healthy， and efficient development of the economy.