环境科学最新文献

Antibiotics are widely used to treat diseases such as bacterial infections. However, the abuse of antibiotics has led to the spread of antibiotic resistant bacteria and intracellular and extracellular antibiotic resistance genes, making China one of the countries with the highest incidence of antibiotic resistance and thus threatening public health. Extracellular antibiotic resistance genes, as one of the novel environmental pollutants, could exist in water for a long time and could be transmitted between different bacteria through horizontal gene transfer, resulting in the spread of antibiotic resistance. At present, due to the limitation of enrichment and recovery methods, the in-depth studies of extracellular antibiotic resistance genes in water have been rarely reported. Thus, it is impossible to carry out effective supervision and risk assessments. Based on literature analysis and investigation, the pollution sources, current situations, and characteristics of extracellular antibiotic resistance genes in water are expounded. Meanwhile, the advantages and disadvantages of their enrichment and recovery methods are compared and analyzed and the enrichment and recovery methods are verified and discussed through practical cases. These provide theoretical reference for studies such as examining extracellular antibiotic resistance genes in water on their transmission and provide a technical basis for antibiotic resistance control and health risk assessments of extracellular antibiotic resistance genes.

Based on the air quality and meteorological data in Suzhou from 2015 to 2022, the long-term variations in PM_2.5 and O₃, meteorological characteristics, and their correlations were analyzed in this study. The HYSPLIT model was used to explore the main transport pathways and potential source areas of PM_2.5 and O₃. The results showed that： ① The annual averaged concentrations of PM_2.5 in Suzhou decreased steadily during the study period, and the annual average concentration from 2020 to 2022 reached the national second-level standard limit. However, the annual average concentrations of O₃ all exceeded the national second-level standard limit. After 2017, the annual number of days that O₃ exceeded the standard was always higher than that for PM_2.5. The number of days of compound pollution continuously decreased from nine days in 2015 to zero days in 2020, and there was no compound pollution since then. ② The most severe pollution seasons for PM_2.5 and O₃ were winter and summer, respectively. PM_2.5 pollution was more likely to occur in low-temperature and high-humidity weather, while O₃ pollution was more frequent in high-temperature and low-humidity weather. Wind direction played an important role, with northwest winds amplifying PM_2.5 pollution and southeast winds boosting O₃. These two pollutants showed a strong correlation in summer with a coefficient reaching 0.73. ③ Cluster analysis revealed that trajectory two from Hebei Province in spring and trajectory four from Shaanxi Province in winter were prone to an increase in PM_2.5 concentration. The short to medium distance trajectory 1 from Shandong Province in summer and trajectory two from Hebei Province in spring were prone to an increase in O₃ concentration. ④ The analysis of potential source areas showed that transportation outside the province had a significant impact on PM_2.5 and O₃ pollution in Suzhou. The potential source areas of PM_2.5 in spring and winter were mainly distributed in Anhui Province, Henan Province, and Hubei Province； the potential source areas in autumn were mainly distributed in Hubei Province and Jiangxi Province； and the potential source areas of O₃ in spring and summer were mainly located in the Beijing-Tianjin-Hebei Region, Shandong Province, Henan Province, and Shanxi Province. Valuable management insights for the coordinated control of PM_2.5 and O₃ pollution in Suzhou were put forward based on this study.

With the economic development and the pace of urbanization, the rising living standard of the urban population has been accompanied with the increase in household carbon emissions in China, and it is of importance to understand the characteristics of the carbon emissions in order to support green energy transitions and sustainable development. Based on the household survey data and using the "Lifestyle calculator-for individuals" developed by the United Nations Climate Change Organization, this study analyzes urban household carbon emissions in Fengning County, Hebei Province, a typical county in North China. We applied the Lasso regression and Random Forest Models （RFMs）, assessing the impacts of relevant factors on household emissions. Through techno-economic analysis, we estimated the costs of various emission reduction measures. RThe results revealed that household carbon emissions were mostly related to energy use, transport, shopping, and dining, which accounted for 33.36%, 15.14%, 23.81%, and 27.90% of the total emissions, respectively. The factors affecting the household emission level included： the means of transport, household heating, efficiency of home appliances, household size, and the amount of electricity and natural gas consumed. Using new energy vehicles, centralized heating and energy-efficient appliances could cut carbon emissions significantly. In terms of the costs of emission abatement of different measures, choosing energy-efficient appliances and green transport were among the lowest-cost options； building energy-saving retrofitting could result in the highest reduction, and energy substitution required the highest investment. The emission reduction potential in Fengning was assessed, and discussions were made to draw policy recommendations supporting emission reduction in the household sector and facilitate low-carbon and green lifestyle development in Chinese counties.

Microplastics, defined as minuscule plastic particles measuring less than five millimeters （5 mm） in size, have become pervasive in various environments. Watershed areas, perpetually subjected to escalating human activities, face a growing and persistent threat from microplastic pollution. This study aimed to investigate the characteristics and ecological risk posed by microplastic pollution in the Houxi River watershed of Xiamen. A comprehensive analysis was conducted, employing field sampling, stereomicroscopy, Fourier transform infrared spectroscopy, as well as the risk index （H） and pollution load index （PLI） model. The findings revealed a 100% detection rate of microplastics at various points within the watershed. The average abundance of microplastics in water, sediment, and soil was found to be （3.65±0.51） n·L^-1, （354.56±18.22） n·kg^-1, and （1 509.55±69.90） n·kg^-1, respectively. Significantly lower microplastic abundance was observed in the upper reaches of the watershed, attributed to the enhanced ecological protection in this area. In contrast, the middle and lower reaches, characterized by dense populations, exhibited higher microplastic levels due to increased production and domestic pollution. The majority of microplastics had a particle size of < 0.5 mm, constituting an average proportion of over 70%. Larger particles exhibited a smaller proportion. Fragmented particles dominated in shape, comprising over 50%, followed by fibers and films, with foam having the lowest proportion. The predominant polymer type identified in microplastics was PE, accounting for over 50%, followed by PP, while PET and PA represented the least. The regional microplastic risk index （H） consistently fell within the low-risk level I, yet it approached the level II risk. The pollution load index （PLI） of microplastics indicated a low-risk level I. These findings contribute valuable insights for regional microplastic pollution prevention and risk assessment efforts.

To explore the future carbon emission peak scenarios of China's iron and steel industry as well as the effective pathways for carbon emission neutrality, the generalized Divisia index method （GDIM） was first used to analyze the influencing factors of carbon emission changes from 2001 to 2020, and then Monte Carlo simulation was used to conduct a dynamic scenario simulation of the carbon emission evolution trends from 2021 to 2035. The results showed that： ① Economic output and crude steel production were the most important factors contributing to the increase in carbon emission in the iron and steel industry； among the factors contributing to the decrease, the carbon intensity of economic output had the most significant effect, followed by the carbon intensity of production, and the energy consumption per ton of steel and the energy output rate did not have a significant effect on the decrease in carbon emissions. ② Under the scenario BAU, scenario L, and scenario S, the iron and steel industry could achieve carbon emission peaking in 2030, 2025, and 2020, respectively.

Based on the panel data of prefecture-level cities and above and provincial-level cities in the Yangtze River Economic Belt, respectively, this study measured the agricultural carbon emissions, carbon sinks, and carbon offset rates from 2006 to 2021 and analyzed their evolution characteristics. Based on the STIRPAT model and ridge regression analysis, this study identified the factors affecting agricultural carbon emissions in the 11 provinces and municipalities in the Yangtze River Economic Zone, combined them with the scenario analysis method to predict the agricultural carbon emissions under the baseline scenario in the period of 2022 to 2025, and analyzed the process of "carbon peaking." Simultaneously, this study predicted the agricultural carbon sinks of 11 provinces and cities from 2022 to 2025 and then speculated their agricultural "carbon neutral" process under the framework of agricultural carbon compensation rate, so as to summarize the effective paths for different provinces and cities to achieve agricultural "carbon peak and carbon neutral." The results showed that： ① Changes in agricultural carbon emissions in the Yangtze River Economic Zone during the observation period followed an inverted U-shape and peaked in 2015 at 33 312.65×10⁴ tons. The fluctuation of agricultural carbon sinks was relatively small, with an overall upward trend. The upward trend of the agricultural carbon offset rate was obvious, but it still belonged to the "net carbon emission" region. ② Regional differences of agricultural carbon offsetting rate were prominent, and there was a polarization phenomenon, with "net carbon sink" cities significantly less than "net carbon emission" cities. ③ Shanghai, Zhejiang, and Sichuan reached the peak of agricultural carbon emissions in 2006, which Anhui and Chongqing reached in 2012, and the rest of the provinces and municipalities showed a clear upward trend. ④ Anhui, Chongqing, Sichuan, and Yunnan crossed the "agricultural carbon neutral line" and achieved agricultural carbon neutrality. Jiangsu was expected to achieve this in 2026-2030, whereas the remaining provinces and municipalities faced greater difficulties.

The coordinated development of the carbon neutral peak target and dual cycle strategy is an important link to realize the transformation of ecological green and low carbon and also an important carrier of high-quality economic development. Based on the inherent requirements of the synergistic effect of pollution control and carbon emission reduction and high-quality economic development, the coupling mechanism of pollution control and carbon emission reduction and high-quality economic development was discussed. Taking the three major urban agglomerations in China as examples, the comprehensive index system of the synergistic effect of pollution control and carbon emission reduction and high-quality economic development were constructed, respectively. The comprehensive evaluation model, coupling coordination degree model, and panel vector autoregression （PAVR） model were used to empirically analyze the coupling and interaction between the synergistic effect of pollution control and carbon emission reduction and high-quality economic development in the three major urban agglomerations in China from 2010 to 2020. The research showed that： ① The comprehensive development index of pollution control and carbon emission reduction and high-quality economic development showed an overall growth trend. The comprehensive level of pollution control and carbon emission reduction synergy in the Yangtze River Delta urban agglomeration was better than that in the Pearl River Delta urban agglomeration and Beijing-Tianjin-Hebei urban agglomeration. There were significant differences in the level of high-quality economic development among cities, and the overall level was high. ② From the perspective of the coupling relationship, during the study period, the level of reluctant coordination entered the primary coordination level and finally evolved into the intermediate coordination level. The spatial characteristics showed the characteristics of contiguous development centered on cities with higher administrative levels, such as municipalities and provincial capitals. ③ From the perspective of the dynamic relationship, there was a positive interaction between pollution control and carbon emission reduction and high-quality economic development, that is, the development of the two could promote each other. The response of pollution control and carbon emission reduction in the Yangtze River Delta and Pearl River Delta urban agglomerations to the positive impact of high-quality development was higher than that in the Beijing-Tianjin-Hebei urban agglomeration.

To maintain ecosystem functions and ensure ecological security, estimating the value of ecosystem services and constructing an ecological security pattern are necessary. Considering the lack of systematic research on the estimation of ecosystem service value and the construction of ecological security pattern, this study extracted the ecological source based on the analysis of ecosystem service value and morphological spatial pattern. According to the natural conditions such as geographical location and altitude, land use type, landscape pattern type, elevation, slope, and normalized difference vegetation index were selected to establish the resistance surface. The minimum cumulative resistance model was used to identify potential ecological corridors, so as to construct the ecological security pattern of Heilongjiang Province, and longitudinal analysis was conducted from 2000 to 2020. The results showed that： ① The overall value of ecosystem services in Heilongjiang Province showed an upward trend （with an amplitude of 42%）, the value of hydrological regulation services accounted for the largest proportion among different service types （approximately 30%）, and the value of forest land services accounted for the largest proportion among different land use types （up to 70%）. ② Eight ecological source areas were extracted, mainly distributed around Greater Khingan Mountains, Lesser Khingan Mountains, Changbai Mountain, and Wanda Mountain, with the largest area of ecological source in Greater Khingan Mountains. ③ Twenty-eight potential ecological corridors were identified, mainly distributed in the northeastern side of the line from Heihe City to Mudanjiang City, forming densely populated areas in Qitaihe City, northern Mudanjiang City, and southern Jixi City. ④ An ecological security network pattern in Heilongjiang Province was constructed with Greater Khingan Mountains Region, Mudanjiang City, and Shuangyashan City as endpoints and Yichun City as the center, finding that the main problem faced at that time was uneven spatial distribution. The research results are helpful to formulate and establish more reasonable ecological environment protection measures and policies and can provide reference value and scientific basis for provincial ecosystem protection and optimization.

Nitrogen oxide （NO_x） is an important air pollutant in the atmosphere, and nitrogen dioxide （NO₂） is one of its main components. The monitoring and estimation of NO₂ concentration is very important for environmental protection and public health. The near-real-time nitrogen dioxide concentration data （NRTI NO₂）, ERA5 meteorological reanalysis data, and DEM data provided by Sentinel-5P atmospheric pollution monitoring satellite were used as estimation variables to estimate the near-surface NO₂ concentration in Guangdong Province based on the Catboost model. The results showed that： ① The Catboost model estimated the near-surface NO₂ concentration with the highest accuracy, with the coefficient of determination （R²）, root mean square error （RMSE）, and mean absolute error （MAE） of the model fit reaching 0.91, 4.89 μg·m^-3, and 3.45 μg·m^-3 and the cross-validated R², RMSE, and MAE reaching 0.90, 4.91 μg·m^-3, and 3.43 μg·m^-3, with good stability on the monthly and quarterly scales. ② The monthly average NO₂ concentration near the surface of Guangdong Province showed a U-shaped trend, with the highest value of 43.8 μg·m^-3 in January and the lowest value of 14.37 μg·m^-3 in July. The seasonal distribution of the near-surface NO₂ concentration was characterized by "high during winter and low during summer and transitional during spring and autumn," and the NO₂ concentration in each season was in the following order： winter （27.53 μg·m^-3） > spring （20.77 μg·m^-3） > autumn （18.77 μg·m^-3） > summer （14.85 μg·m^-3）. ③ From a spatial distribution perspective, areas with high near-surface NO₂ values in Guangdong Province were mainly located in rapidly developing and densely populated areas, while areas with low values were mainly distributed in areas focusing on port economy, agriculture, and new energy sources.