工业工程最新文献

The coupling and coordination relationship between provincial carbon emissions and new quality productivity in China is a key path to achieve the "dual carbon" goals and promote high-quality development in a coordinated manner. Based on panel data from 30 provinces in China from 2012 to 2022, a coupling coordination degree model, spatial autocorrelation analysis, and β convergence model were constructed to systematically measure the dynamic coordination and regional convergence characteristics of carbon emission intensity and new quality productivity. The results showed that: ① The national coupling coordination degree increased from 0.529 to 0.664, upgrading from "barely coordinated" to "primary coordinated, " with an average annual growth rate of 2.55%. ② The spatial differentiation presented a pattern of "high in the southeast and low in the northwest, " and the global Moran index verified a significant positive spatial correlation. The coupling coordination degree H-H agglomeration area expanded from 7 to 11 provinces, reflecting the radiation effect of the Yangtze River Delta and Pearl River Delta extending to the central and western regions, while the northwest and northeast L-L agglomeration areas are still constrained by "high carbon lock-in" and ecological vulnerability. ③ There were absolute β and conditional β convergences in the coupling coordination degree, and the convergence speed of underdeveloped provinces was significantly faster than that of developed provinces. The advantage of latecomers and the diffusion effect of technology drove the narrowing of regional differences. Based on this, it is recommended to strengthen the global technology sharing network, promote industrial structure transformation through differentiation, and improve cross regional ecological compensation mechanisms to promote the coordinated transition of low-carbon development and new quality productivity.

Exploring the carbon reduction pathways of the paper industry in key regions of China is of significant importance for achieving low-carbon sustainable development in the Chinese paper industry. Taking the paper industry in Guangdong Province as the research subject, this study employs the logarithmic mean Divisia index (LMDI) method to conduct continuous and phase-wise decomposition of the factors influencing carbon emissions based on its energy consumption characteristics. The Tapio decoupling model is used to analyze the decoupling status between the output of the paper industry and carbon emissions, and it is combined with the LMDI model to construct a decoupling effort model, thereby elucidating the extent of efforts made by each influencing factor towards achieving decoupling. The results indicate that during the period from 2007 to 2022, the effect of industrial output value was the main driving factor for the increase in carbon emissions in the paper industry, while the energy intensity effect served as the primary inhibitory factor. The energy structure effect and the carbon emission intensity effect of electricity were both secondary inhibitory factors. The paper industry predominantly experienced an evolutionary path from weak decoupling to strong decoupling and then to regressive decoupling. The carbon emission intensity effect of electricity and the energy structure effect primarily manifested as weak decoupling efforts. The decoupling effort index of energy intensity remained generally consistent with the changes in the overall decoupling effort index. Continuous improvement in various factors will play a positive role in promoting decoupling of carbon emissions. Therefore, it is necessary to enhance the guidance for the reform and optimization of the paper industry structure and its green transformation and upgrading, thus facilitating its transition to a technology-intensive industry and fully achieving a strong decoupling between paper industry output and carbon emissions.

To investigate the hydrochemical characteristics and genesis mechanisms of typical river wetlands in the Xi'an section at the northern foothills of the Qinling Mountains, this study focused on three types of wetlands, including the bedrock mountain wetland(upper Heihe River wetland), the agricultural activity area wetland(lower Heihe River wetland), and the urban residential area wetland(Bahe Baqiao wetland). A total of 26 surface water samples were collected in January 2024 (dry season) and August 2024 (wet season). Piper trilinear diagrams, Gibbs diagrams, ion ratios, and principal component analysis were comprehensively used to clarify the distribution characteristics of major ions, further identify their sources, and reveal the formation mechanisms of surface water hydrochemistry. The results showed that the surface water in the study area was slightly alkaline. Compared with that during the dry season, the total dissolved solids (TDS) and the concentrations of major ions in the surface water of each wetland were lower during the wet season. The dominant cation was Ca²⁺, followed by Na⁺ or Mg²⁺. The dominant anion was HCO₃^-, while the remaining anions exhibited significant variability across different wetlands and periods. The hydrochemical types of the Heihe River wetlands were mainly HCO₃-Ca and HCO₃·SO₄-Ca, while the Bahe Baqiao wetland was dominated by HCO₃-Ca·Na. The hydrochemical characteristics of the upper Heihe River wetland were mainly controlled by the weathering of carbonate rocks and evaporite salts. The main controlling factors for the hydrochemical characteristics of the lower Heihe River wetland, from strongest to weakest, were carbonate rock weathering, agricultural fertilizer application, and evaporite salt weathering. The hydrochemical components of the Bahe Baqiao wetland were primarily controlled by rock weathering, followed by domestic sewage discharge, with evaporation having a stronger impact compared to the other two wetlands. The impact of agricultural non-point source activities and domestic sewage discharge in the plain area on the wetland water environment in Xi'an cannot be ignored, and it is also necessary to prevent pollutant inputs from human activities into the surface water of the bedrock mountain wetlands. These findings can provide scientific basis for improving wetland ecological environments and system restoration and further ensuring water safety of Xi'an as a "dual-center" city and the function of the Qinling Central Water Tower.

Under the background of the continuous advancement of the digital Yangtze River Delta construction and the "dual carbon" goals, the digital economy, as a new driving force integrating digitalization and low-carbon development, helps the construction industry achieve green and low-carbon transformation and high-quality development by directly reducing carbon emissions and indirectly promoting green technological innovation. Based on the data of 41 cities in the Yangtze River Delta region from 2011 to 2022, this study analyzes the current situation and spatial-temporal characteristics of carbon emissions in the construction industry and further explores the impact and mechanism of digital economy and green technological innovation on carbon emission reduction in the construction industry by combining panel data regression models and mediation effect tests. The results showed that: ① From 2011 to 2022, although the carbon emissions from the construction industry in Yangtze River Delta cities increased in a low-amplitude wave pattern and spatial agglomeration weakened, the level of digital economy development in various provinces and cities has significantly improved, with an overall cumulative increase of nearly 1.3 times, among which Anhui had the fastest growth, and most cities had achieved positive growth. ② There was a significant positive correlation between the digital economy and carbon emission intensity, and this influence remained after robustness and endogeneity tests. The impact varied with urban resource endowments, with resource-based cities showing significant effects. ③ In the context of digital economy promoting the low-carbon development of the construction industry, green technological innovation played a positive mediating role. The research results are of great significance for formulating relevant policies of digital economy in the field of construction emission reduction and provide theoretical support for achieving the goal of green and low-carbon development.

Accurate identification of habitat quality sensitive areas and analysis of their driving mechanisms is crucial for ecological protection and governance. Traditional methods for identifying sensitive areas primarily rely on static assessments, which fail to consider the dynamic characteristics of habitat quality and its full response to environmental changes. Therefore, this study used Yunnan Province as a case study, employing the InVEST model, Sen's slope estimator, and the Mann-Kendall trend test to evaluate habitat quality and its changing trends from 1990 to 2020. A novel frequency-amplitude sensitivity framework was constructed to identify sensitive areas, followed by an analysis of spatial differentiation characteristics and driving mechanisms using spatial autocorrelation and the optimal parameters-based geographical detector (OPGD). The results show that from 1990 to 2020, habitat quality was high in the southeast and northwest and low in the east and west of Yunnan Province, with an overall favorable condition. However, habitat quality has shown a significant degradation trend over the past 30 years, with degraded areas accounting for 12.91%, primarily concentrated in economically active regions in central Yunnan and around lakes. Additionally, 59.27% of Yunnan Province was identified as a habitat quality sensitivity area, with H-H clusters concentrated in the central, eastern, and western regions. Shifts in population distribution were identified as the dominant factor affecting habitat quality sensitivity. Moreover, the interaction between population distribution and DEM primarily determined the spatial distribution of habitat quality sensitivity in Yunnan Province. The new method proposed in this study provides an innovative approach for the dynamic assessment and early warning of regional habitat quality. The research findings offer a scientific basis for habitat protection and sustainable development in Yunnan Province and beyond.

To achieve the goal of carbon neutrality, it is necessary to comprehensively and accurately check the regional carbon budget and its evolution characteristics. Accordingly, taking Jiangsu Province as an example, this study constructed a carbon budget accounting system from the perspective of the "natural-human" binary structure. The major anthropogenic carbon emission items, carbon sources/sinks of the ecosystem, and the changes of the carbon storage in Jiangsu Province from 2000 to 2020 were calculated, and the pressure of carbon neutrality was evaluated entirely. The results showed that during 2000-2020, the anthropogenic carbon emissions in Jiangsu Province increased from 54.380 6 to 233.841 9 million tons. Carbon emissions associated with industrial energy consumption consistently dominated, accounting for 61% to 72% of total emissions. Emissions from industrial production processes represented the second-largest source, with a fluctuating upward trend in its proportion. Moreover, 11.25% of the land in Jiangsu Province was transferred, resulting in a reduction of ecosystem carbon storage by 2.638 9 million tons. Although the ecosystems functioned as a carbon sink overall, with an annual average carbon sequestration of 6.63 million tons, this capacity has shown fluctuations and a declining trend in recent years. As a whole, Jiangsu Province had high carbon emissions coupled with relatively low carbon sequestration capacity, with carbon sinks offsetting only approximately 4.17% of anthropogenic emissions during the study period, which demonstrates high pressure on realizing the goal of carbon neutrality.

To explore the benefit of soil improvement and restoration models in typical counties of Shandong Province，we constructed a multi-dimensional system of "soil condition-ecological environment-economic society" comprehensive benefit evaluation index system and utilized the entropy-weighted TOPSIS comprehensive evaluation model，Kernel density estimation，coupling coordination model，and obstacle factor diagnostic model to fully analyze the comprehensive benefits of soil improvement and restoration model in typical counties of Shandong Province from 2019 to 2022. The results showed that：① The comprehensive benefit level of soil improvement and restoration model in typical counties showed a fluctuating upward trend，the gap between counties was narrowing，and there was a non-synchronization in the development of subsystems. ② The coupling coordination degree of soil improvement and restoration model in various counties showed a fluctuating increasing trend，which revealed a strong "Matthew effect." ③ The influence of each system layer on the level of comprehensive benefits，in descending order，was the economic and social system，the soil condition system，and the ecological environment system，and the main obstacles were the use of agricultural plastic film，the use of agricultural fertilizers，the effective phosphorus of the soil，and the total power of agricultural machinery. The results of the study have important reference value for enhancing the comprehensive benefits of soil ecological remediation，promoting the safe utilization of contaminated arable land，and contributing to the guarantee of national food security.

A total of 242 sampling points were established around a typical industrial park in central-southern China, where 726 soil samples were collected from three depths. The contents of Cd, Pb, Zn, As, and Ni were measured, followed by spatial distribution pattern mapping and potential pollution zoning using sequential Gaussian simulation. Source apportionment was quantitatively analyzed through positive matrix factorization. The results indicated that surface layer contents of Cd, Zn, Pb, and As were significantly higher than those in the lower layers, with high-value areas concentrated in the southern and eastern parts of the study area. In contrast, Ni exhibited similar concentrations across all three depths, showing predominantly high values in northern and western regions. Pollution zoning revealed high-risk areas predominantly in southern and eastern sectors, where Cd demonstrated the highest contamination risk. Notably, the probability of Cd exceeding the regulatory threshold for soil pollution risk in agricultural land exceeded 95% across 80.45% of the total study area. Source apportionment showed that industrial activities and transportation collectively contributed 87.86%, 76.47%, and 68.68% to Cd, Zn, and Pb pollution, respectively. Agricultural practices involving irrigation and agrochemical application accounted for 69.23% of As contamination, while natural sources dominated Ni inputs with an 85.62% contribution.