工业工程最新文献

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.

In recent decades， the misuse of antibiotics has contributed to a significant rise in antibiotic resistance among bacteria. Antibiotic resistance genes （ARGs）， carried by antibiotic-resistant bacteria and considered to be emerging pollutants， are primarily responsible for this phenomenon. ARGs have been extensively detected in various environmental media， including the atmosphere， soil， water， and sediments. Microplastics （MPs）， defined as plastic fragments with diameters less than 5 mm， pose a considerable threat due to their ease of ingestion by organisms， leading to adverse effects on ecosystems and human health. Moreover， microplastics exhibit a high affinity for organic pollutants， facilitating their migration through adsorption and desorption processes. The surfaces of microplastics can harbor bacterial pathogens and ARGs， thereby influencing the occurrence and dissemination of ARGs in the environment. Although numerous publications have reported the role of microplastics in the transmission of ARGs across diverse environments， there remains a gap in understanding the specific effects of microplastics on the accumulation and horizontal gene transfer of ARGs， including MPs types and surface characteristics， along with the underlying mechanisms. This review provides an overview of the ARGs enrichment by microplastics in various environment media and highlights how the type and surface characteristics of microplastics impact the concentration and subsequent spread of ARGs， while also clarifying the underlying mechanisms through which microplastics facilitate the horizontal transfer of ARGs. The review also outlines prospective research directions concerning microplastics and ARGs， offering valuable insights for the management and control of emerging pollutants.

The upper Yangtze River is an important water conservation area， and its hilly terrain is prone to soil erosion， which causes pollutants such as heavy metals to migrate into the water and then accumulate in the reservoir sediments. It may pose a potential threat to drinking water safety and water ecological health. In this study， the Quanmin Reservoir Basin of Sichuan Province located in the upper reaches of the Yangtze River was selected， and the basic sediment physicochemical properties as well as the spatial distributions and occurrence characteristics of heavy metals （including Cr， Mn， Ni， Cu， Zn， Cd， and Pb） in the main inflowing rivers and reservoir areas were investigated. The sources， correlations with environmental factors， and potential risks of heavy metals were analyzed using multivariate statistical methods. The results showed that： ① The average content of each heavy metal in sediments was higher in the downstream reservoir than that in the upstream rivers. Both in the river and the reservoir sediments， Mn and Cd mainly existed in the acid-soluble state in both the river and the reservoir， while the other five heavy metals mainly existed in the residual state. ② Combined with the results of the correlation analysis， principal component analysis， and the positive matrix factorization， the natural sources of Cr， Ni， Cu， Zn， Cd， and Pb contrabuted more than 60%， while the agricultural sources of Mn contrabuted more than 70%. ③ Organic matter， nitrogen， phosphorus， and redox potential in the sediments significantly affected the distribution and occurrence fractions of the studied heavy metals. ④ The pollution degrees and comprehensive potential ecological risks of heavy metals in the sediments were at the low level， but the average risk coding indexes of Mn and Cd reached 56.0% and 51.2%， respectively. Considering the different sources and the higher release potential of Mn when compared with those of the other metals， further attention should be paid to the potential impacts of Mn on the water environment and aquatic ecosystem.

Carbon stocks in terrestrial ecosystems are significantly affected by land use/cover change （LUCC）， and exploring the role of LUCC on carbon stocks of regional terrestrial ecosystems is of great importance for improving land use structure and achieving the goals of carbon peaking and carbon neutrality. Based on the land use data between 2000 and 2020， this study established four development scenarios， namely natural development （ND）， ecological protection （EP）， economic development （ED）， and comprehensive development （CD）， by integrating 13 key drivers. Combined with the PLUS and InVEST models， the dynamic adjustment of land use types and the spatial and temporal evolution of carbon stocks in the Sichuan-Chongqing Region were simulated. The study findings revealed that： ① From 2000 to 2020， the areas of grassland and cropland decreased by 83.65×10⁴ hm² and 46.41×10⁴ hm²， respectively， while the areas of forest land， construction land， and water increased by 65.37×10⁴， 50.55×10⁴， and 13.41×10⁴ hm²， respectively， and the area of unutilized land remained stable. ② In 2000， 2010， and 2020， the carbon stocks were 1 968.88×10⁷， 1 996.90×10⁷， and 1 998.59×10⁷ t， respectively， and the total carbon stock increased by 29.71×10⁷ t. The conversion of cropland and grassland to forest land was the primary driver for increased carbon stocks. ③ According to the study， compared to that in 2020， carbon stocks under the ND， ED， EP， and CD scenarios increased by 1.48×10⁷， 27.75×10⁷， 43.62×10⁷， and 50.32×10⁷ t， respectively. The CD scenario exhibited higher carbon stocks and a more excellent total value than the other scenarios， making it the optimal development model. The results of the study provide a reference for decision-makers on ecosystem carbon stock optimization from the perspective of land use， which will provide strong support for the formulation of future land use policies and the realization of the goal of carbon peaking and carbon neutrality.

In recent years， with the increasing use of antibiotics， various antibiotics are discharged into aquatic environments and pose serious hazards to the safety of aquatic ecosystems and human health. To investigate the pollution status in the Zaohe River in Xi'an， the residues of 15 antibiotics in the surface water of the Zaohe River were detected using high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS）， the sources of antibiotics were analyzed by the PCA-MLR model， and the ecological risk of typical antibiotics were evaluated by the risk quotient （RQ） method. The results showed that eight antibiotics belonging to four categories were detected at six sampling sites （two sampling sites in the upstream， midstream， and downstream of Zaohe River， respectively）， and the concentration ranged from 1.08 to 71.27 ng·L^-1 with detection frequencies ranging from 16.67% to 100%. The detection frequencies of ciprofloxacin （CIP）， roxithromycin （ROX）， and ofloxacin （OFX） were all 100%. The concentration of CIP was highest， followed by that of ROX. The concentration of antibiotics was higher in the dry season than that in the wet season. The main antibiotics were macrolides （Mas） in the wet season and fluoroquinolones （FQs） in the dry season. The PCA-MLR analysis indicated that antibiotics detected in Zaohe River mainly came from waste and wastewater discharged from hospitals， wastewater treatment plants， feed mills， livestock， and aquaculture plants. Redundancy analysis showed that there was a significant negative correlation between pH and ROX. The concentrations of norfloxacin （NOR） and ciprofloxacin （CIP） were significantly positively correlated with electrical conductivity （EC） and total nitrogen （TN）， while negatively correlated with water temperature. Ecological risk assessment based on the risk quotient showed that ROX and CIP posed high risk to green algae； NOR， OFX， and aureomycin （CTC） posed medium risk； and tetracycline （TC） and oxytetracycline （OTC） posed low risk. CIP， NOR， TC， OTC， and sulfamethoxazole （SMX） posed low risk to daphnia. All the antibiotics in water samples posed insignificant risk to fish. The health risk assessment results indicated that none of the antibiotics in the water samples presented potential health risks to humans. The resistance risk assessment results showed that ROX， CIP， and NOX had low resistance risk. Our results could provide scientific basis for the prevention and control of antibiotic pollution in the Zaohe River in Xi'an.

Scientific evaluation of spatio-temporal differentiation of landscape ecological risks and identification of driving factors in order to provide reference for regional ecological risk regulation and sustainable development. Based on land use data from 1990 to 2022， the ecosystem service value of the study area was calculated， and the characteristics of changes were analyzed. From the perspective of "loss" and "probability" accumulation， the landscape ecological risk assessment system based on ecosystem service value was constructed. Combined with spatial autocorrelation analysis and Geodetectors， the evolution trend and influencing factors of ecological risks in the areas along the Yellow River in Zhengzhou and Luoyang cities were explored. The results showed that： ① Cultivated land and construction land were advantageous landscape types in the study area. Land use conversion was mainly characterized by the transfer of cultivated land and construction land， while the overall fluctuation of forest land， grassland， and water was minimal. ② Over the past 32 years， the total value of ecosystem services declined， with the spatial distribution characterized by "high values on the north and south sides and low values in the middle." Regional ecosystems were dominated by regulating services， with cultivated land and water contributing the most to the value of ecosystem services. ③ From 2000 to 2022， the landscape ecological risk intensified， with a significant decrease in low risk areas and an increase in high and medium-high risk areas. Low and medium-low value areas were concentrated in the western hilly terrain， and the overall spatial distribution of ecological risk showed a significant positive correlation. ④ The proportion of construction land， nighttime light intensity， and vegetation coverage were the main factors driving changes in landscape ecological risk. During the research period， most of the interactions among the factors were increasing， and the interaction effects between the proportion of built-up land and nighttime light intensity had the most significant impact on landscape ecological risk. The results can provide scientific references for regional ecological risk regulation.

This study was conducted in 2010 in the irrigated aeolian sandy soil area of Hetian County， Xinjiang Uygur Autonomous Region to investigate the long-term effects of different organic amendments on the physicochemical properties and extracellular enzyme activities of aeolian sandy soil. Four treatments were established： no organic amendments （CK）， 1% biochar application （22.5 t·hm^-2， B1）， 10% biochar application （225.0 t·hm^-2， B2）， and 1% manure application （22.5 t·hm^-2， M）. Spring maize was cultivated during the experimental period， and the application rates of chemical fertilizers and agronomic practices were consistent with local agricultural practices. In 2023， soil samples from the 0-20 cm plow layer were collected to measure soil physicochemical properties and extracellular enzyme activities. The results showed that organic amendments significantly improved the physicochemical properties of aeolian sandy soil， with manure treatment demonstrating the most pronounced effects. Compared to those in the CK， manure application markedly increased soil organic carbon （43%， P<0.05）， total nitrogen （55%， P<0.05）， field water holding capacity （14%， P<0.05）， and microbial biomass carbon （154%， P<0.05）. The application of manure alleviated microbial carbon limitation and balanced nitrogen-phosphorus nutrient demands by providing available carbon and effective nitrogen. In contrast， biochar exacerbated microbial nitrogen limitation due to its high carbon-to-nitrogen ratio and nitrogen adsorption capacity. Based on the observed results， manure application is optimal for improving the physicochemical properties， enzyme activities， and microbial nutrient balance of aeolian sandy soil. For biochar， its application requires optimization of nitrogen fertilizer dosage to avoid aggravating nitrogen limitation. In conclusion， this study elucidates how organic amendments regulate soil enzyme activities and microbial nutrient limitations， thereby enriching the theoretical framework for aeolian sandy soil improvement. These findings provide a scientific basis and technical support for enhancing soil fertility and promoting sustainable agricultural development in aeolian sandy soil regions.

It is of great significance to clarify the evolution trend and key influencing factors of China's rural energy carbon emissions in order to promote the green development of agriculture and rural areas and to realize the goal of "double carbon" on schedule. On the basis of clarifying the current situation of rural energy carbon emission in China and 30 provinces， this study focused on analyzing the evolution trend of rural energy carbon emission and key influencing factors by using the kernel density estimation method and the random forest model. The study showed that： ① China's total rural energy carbon emission was on an upward trend from 2005 to 2022， and their evolution could be broadly categorized into three phases： "fluctuating increase， relatively stable， and continuous increase，" and the carbon intensity increased by more than 160% during the study period. In terms of provinces， the total amount of rural energy carbon emission was greatest in Guangdong， with Shanghai showing the least， and the intensity was greatest in Tianjin， with Guangxi showing the lowest. ② During the investigation period， rural energy carbon emission intensity increased significantly in both the country and the southern and northern regions， and the distribution of provinces in the low-value region decreased significantly. The rural energy carbon emission intensity in both the country and the northern regions still showed some polarization at the end of the investigation period. ③Rural energy carbon emission was influenced by factors at the economic， social， and governmental levels. Among the factors at the economic level， the structure of agricultural industry had an inverted U-shaped effect on rural energy and carbon emissions. Among the factors at the social level， the aging of the rural population， the degree of mechanization of agriculture， and the increase in the level of rural human capital all led to an increase in rural energy and carbon emissions， while the increase in the level of urbanization could play a restraining role. Among the governmental factors， the increase in the level of financial support for agriculture will help to realize the carbon emission reduction of rural energy. The results of the study can provide scientific references for the construction of the optimization path of emission reduction and carbon sequestration in rural areas.

Wastewater discharge from wastewater treatment plants （WWTPs） is one of the major sources of emerging contaminants （ECs） in the aquatic environment. To comprehensively evaluate the occurrence characteristics and ecological risks of ECs in Chinese WWTPs， this study employed a Meta-analysis （Meta） approach. A total of 849 data selected by screening 71 publications from two major databases-one in English and one in Chinese-focused on the contamination levels of ECs in the influent and effluent of Chinese WWTPs. The study characterized the occurrence properties of ECs by analyzing their average concentrations， while risk quotient （RQ） evaluations served as a key indicator for risk assessment during the in-depth Meta. The results indicate that EC contamination is widespread in Chinese WWTPs， with regional variations in pollutant concentrations and types influenced by local industrial structures and residential habits. The risk assessment showed that a variety of ECs in water presented medium and high ecological risks in several regions， including central， southern and northwestern China. On this basis， the removal ways and process improvement strategies of ECs in WWTPs in China are expounded， which can provide scientific basis for regional ecological environment protection and treatment process optimization and improvement.

The extended KAYA-LMDI calculation model was employed to analyze the impact effects of CO₂， NO_x， and SO₂ emissions in Huaibei City from 2016 to 2021. The LEAP model and scenario analysis were combined to predict the emission trends and peak times of the three gases （CO₂， NO_x， and SO₂） in 2021-2040. The earliest peak times and the optimal degree of emission reduction were obtained. The synergistic emission reduction effect between CO₂-NO_x and CO₂-SO₂ under different scenarios was evaluated using carbon pollution synergistic emission reduction analysis. The findings indicate that the predominant impact on CO₂， NO_x， and SO₂ emissions in Huaibei City was the economic effect. CO₂， NO_x， and SO₂ were diminished under the three policy scenarios of industrial restructuring， clean energy substitution， and comprehensive enhancement in comparison to those under the status quo scenario. Notably， SO₂ was projected to reach its peak in 2030 under the industrial restructuring scenario， while under the clean energy substitution scenario， CO₂ and NO_x emissions would reach their peak in 2025， with SO₂ reaching its peak in the initial scenario year. The most efficacious emission reduction for all three gases was observed in the integrated intensification scenario. The electric power production sector contained all the most important emitting industries of CO₂， NO_x， and SO₂， and coal was the most important energy emission source. The reduction of coal use and the cleaner transformation of power production were powerful ways to reduce pollution and carbon in Huaibei City. The integrated and enhanced scenarios had optimal emission reduction effects on CO₂， NO_x， and SO₂， as well as strong synergistic effects on CO₂， NO_x， and SO₂ emission reduction. The synergistic emission reduction effect between CO₂-SO₂ was better than that of CO₂-NO_x. In CO₂-NO_x synergistic emission reduction， the implementation of emission reduction policies will contribute more to the reduction in CO₂， and these policies will have a different effect on CO₂-SO₂ synergistic emission reduction. In conclusion， a comprehensive and enhanced scenario combining industrial restructuring and clean energy substitution represents the optimal path for pollution and carbon reduction in Huaibei City. This scenario also provides policy recommendations for Huaibei City to achieve the goal of "double carbons."