Search Results (42)

This paper reported the grey water footprint (GWF) mitigation resulting from a brewery industry wastewater treatment using malt dust-derived biochar. The GWF was assessed based on chemical oxygen demand (COD) and total suspended solids (TSS) removal. A new data-driven parametric index (GWFI_BP) was reported that uses the GWF tool. A data-driven model was designed in order to define the impact of the dual advantages of biochar application relative to the Conventional Activated Sludge (CAS) process. A GWF reduction of approximately 21.59% was found for the biochar application. Full article

Freshwater pollution by nutrients is a global concern. While agriculture is the largest contributor globally, domestic and industrial emissions are responsible for substantial emission hotspots worldwide. To this end, this paper presents the global grey water footprint (GWF) of nitrogen (N) and phosphorus (P) from domestic and industrial sources as a water pollution indicator. GWFs are displayed as gridded datasets with 5 × 5 arc minute resolution annually from 1990 to 2019, extending previous time series. Methodologically, the domestic GWF calculations were refined but were largely based on previous GWF studies. For industrial GWFs, this study presents a novel approach to estimating emissions based on country-specific industrial-to-domestic load ratios instead of the uniform ratios used in earlier studies. The global N-related GWF rose from 2.6 × 10¹² m³/yr to 6.3 × 10¹² m³/yr between 1990 and 2019. During the same period, the P-related GWF increased from 75.2 × 10¹² m³/yr to 194.5 × 10¹² m³/yr. Domestic wastewater is the dominant contributor, with hotspots in densely populated regions, such as East China, North India, and parts of Africa. Industrial contributions show relevance in heavily industrialized areas with limited wastewater treatment infrastructure. Population growth was the primary driver of increased GWFs, particularly in regions with limited sanitation and wastewater treatment. This reflects the need to improve these to mitigate nutrient pollution. Full article

This study evaluates nitrogen (N) and phosphorus (P) pollution in the Ankara River Sub-basin, Türkiye, using the grey water footprint (GWF) approach. A Tier-1 GWF approach was applied, complemented by a sensitivity analysis to assess the influence of key parameters, including leaching–runoff fractions and water quality thresholds. The results should be interpreted as indicative rather than absolute values, as they depend on assumptions related to leaching fractions and background concentrations. By integrating data from agricultural diffuse sources and municipal wastewater treatment plants (WWTPs), the research identifies critical pollution hotspots and sectoral pressures on water resources, causing water quality degradation. The results reveal that P is the primary limiting pollutant governing GWF magnitudes across the sub-basin. The total GWF was estimated at 8294 million m³ yr⁻¹ in the sub-basin outlet. Approximately 10% and 31% of the basin-wide GWF were associated with fertilizer-based diffuse sources and WWTP1, respectively. The study demonstrates that regulatory compliance alone does not guarantee the protection of a river’s assimilative capacity. These results provide a basis for policy development, emphasizing the need to move beyond concentration-based regulations toward management frameworks that explicitly consider assimilative capacity and cumulative basin-scale impacts. Full article

The grey water footprint (GWF) is a critical indicator for assessing the impact of socio-economic activities on the water resources environment. To address the dual challenges of economic growth and water pollution associated with Land Consolidation Projects (LCPs) in the Loess Plateau, this study systematically analyzes the spatiotemporal distribution of GWF in the Yan’an region from 2000 to 2023 and employs the eXtreme Gradient Boosting (XGBoost) model to comprehensively explore its driving mechanisms. The SHapley Additive Explanations (SHAP) method was employed to quantify the dynamic contributions of the driving factors of GWF, while the threshold effects of these factors were assessed using partial dependence plot analysis. Additionally, spatial matching patterns between agricultural GWF (GWF_agr) and economic factors were examined using the Gini coefficient and imbalance index. These findings indicate that the total GWF (TGWF) peaked at 1.347 billion m³ in 2004 and declined due to improvements in water management efficiency. Spatially, TGWF is higher in the central and eastern regions, where GWF_agr is predominant. The permanent population and per capita GDP are the key driving factors, accounting for 21.1% and 15% of the total change in TGWF, respectively. In the spatial coupling relationship between agricultural GDP and GWF_agr, the overall imbalance index has significantly decreased. The synergistic effect between the Grain for Green Project and LCPs is becoming increasingly evident. These insights provide scientific support and policy guidance for the ecological protection and high-quality development of the Yellow River Basin. Full article

Large-scale water network projects are a crucial approach for the rational allocation of water resources and addressing water resource crises. Reliable sustainability evaluation is essential to ensure the sustainable operation of large-scale water network projects. This study develops an improved Fuzzy Comprehensive Evaluation (FCE) method based on Game Theory weight fusion (GWF) for the quantitative evaluation of the sustainability of water network projects. By combining the Analytic Hierarchy Process (AHP), Entropy Weight Method (EWM), and Game Theory approach, the study integrates the advantages of both subjective and objective weighting methods to achieve the allocation of indicator weights; the sustainability of the Jiaodong Water Network Project was quantitatively evaluated by employing the improved FCE method. The results indicate that the resource and management dimensions are the two most critical factors affecting the sustainability of large-scale water network projects. Indicators with high weight such as per capita water resources, the rationality of the management system, and level of management intelligence are the primary risk factors affecting the sustainable operation of large-scale water network projects. The sustainability evaluation value of the Jiaodong Water Network Project is 82.83 points, which is classified as “high” sustainability. This validates the reliability of the evaluation indicator system and the method used. Full article

To evaluate water pollution status and sustainable development potential in the Huai River Basin, this study focused on the spatiotemporal evolution and influencing factors of the grey water footprint (GWF) across 35 cities in the basin from 2005 to 2020. This study quantifies the GWF from agricultural, industrial, and domestic perspectives and analyzes its spatial disparities by incorporating spatial autocorrelation analysis. The Tapio decoupling model was applied to explore the relationship between pollution and economic growth, and geographic detectors along with the STIRPAT model were utilized to identify driving factors. The results revealed no significant global spatial clustering of GWF in the basin, but a pattern of “high in the east and west, low in the north and south” emerged, with high-value areas concentrated in southern Henan and northern Jiangsu. By 2020, 85.7% of cities achieved strong decoupling, indicating improved coordination between the environment and economy. Key driving factors included primary industry output, crop sown area, and grey water footprint intensity, with a notable interaction between agricultural output and grey water footprint intensity. The quantitative analysis based on the STIRPAT model demonstrated that seven factors, including grey water footprint intensity and total crop sown area, exhibited significant contributions to influencing variations. Ranked by importance, these factors were grey water footprint intensity > total crop sown area > urbanization rate > population size > secondary industry output > primary industry output > industrial wastewater discharge, collectively explaining 90.2% of the variability in GWF. The study provides a robust scientific basis for water pollution control and differentiated management in the river basin and holds significant importance for promoting sustainable development of the basin. Full article

With climate change, the spatial and temporal patterns of precipitation are altered to a certain degree, which potentially affects the grey water footprint (GWF) of total nitrogen (TN) in agriculture, thereby threatening water security in the Yangtze River Basin (YRB), the largest river in China. The current study constructs an assessment framework for climate change impacts on the GWF of agricultural TN by coupling Shared Socioeconomic Pathways (SSPs) with the InVEST model. The framework consists of four components: (i) data collection and processing, (ii) simulating the two critical indicators (L_TN and W) in the GWF model based on the InVEST model, (iii) calculating the GWF and GWF index (GI) of TN, and (iv) calculating climate change impact index on GWF of agricultural TN (CI) under two SSPs. It is applied to the YRB, and the results show the following: (i) GWFs are 959.7 and 961.4 billion m³ under the SSP1-2.6 and SSP5-8.5 climate scenarios in 2030, respectively, which are both lower than that in 2020 (1067.1 billion m³). (ii) The GI values for TN in 2030 under SSP1-2.6 and SSP5-8.5 remain at “High” grade, with the values of 0.95 and 1.03, respectively. Regionally, the water pollution level of Taihu Lake is the highest, while that of Wujiang River is the lowest. (iii) The CI values of the YRB in 2030 under SSP1-2.6 and SSP5-8.5 scenarios are 0.507 and 0.527, respectively. And the CI values of the five regions in the YRB are greater than 0, indicating that the negative effects of climate change on GWFs increase. (iv) Compared with 2020, L_TN and W in YRB in 2030 under the two SSPs decrease, while the GI of TN in YRB rises from SSP1-2.6 to SSP5-8.5. The assessment framework can provide strategic recommendations for sustainable water resource management in the YRB and other regions globally under climate change. Full article

Under the influence of water resource conservation policies, the annual water diversion volumes in irrigation areas have been steadily decreasing, leading to substantial changes in regional cropping systems. These shifts have profoundly impacted agricultural reactive nitrogen (Nr) emissions and surface water quality. This study focuses on the Yellow River Irrigation area of Ningxia, China, and employs a life cycle assessment method to quantitatively analyze fluctuations in the nitrogen footprint (NF) and gray water footprint (GWF) across three cropping systems—rice-maize intercropping, rice monoculture, and maize monoculture—during 2021–2023. The results indicate that rice monoculture exhibited significant variability in NF values (197.89–497.57 kg Neq·ha⁻¹), with NO₃⁻ leaching identified as the primary loss pathway (102.33–269.48 kg Neq·ha⁻¹). The GWF analysis revealed that in 2021, the region’s GWF peaked at 23.18 × 10⁴ m³·ha⁻¹, with water pollution predominantly concentrated in Pingluo County (8 × 10⁴ m³·ha⁻¹). LMDI analysis identified nitrogen fertilizer application as the main contributor to variations in NF, while surface water pollution was indirectly influenced by crop yield. Furthermore, gray correlation analysis highlighted a significant coupling relationship between NF and GWF, with nitrogen fertilizer application having the most pronounced impact on GWF. Therefore, in the face of the gradual tightening of water resources in the irrigation areas, the current situation of reduced water diversion should be adopted as early as possible, and initiatives such as the reduction of nitrogen fertilizer application and the adjustment of the planting area of dryland crops should be accelerated to cope with the problem of nitrogen pollution brought about by changes in the cropping system. Full article

Recently, research on hyperspectral image classification (HSIC) methods has made significant progress. However, current models commonly only focus on the primary features, overlooking the valuable information contained in secondary features that can enhance the model’s learning capabilities. To address this issue, an adaptive feature enhanced gaussian weighted network (AFGNet) is proposed in this paper. Firstly, an adaptive feature enhancement module (AFEM) was designed to evaluate the effectiveness of different features and enhance those that are more conducive to model learning. Secondly, a gaussian weighted feature fusion module (GWF2) was constructed to integrate local and global feature information effectively. Finally, a multi-head collaborative attention (MHCA) mechanism was proposed. MHCA enhances the feature extraction capability of the model for sequence data through direct interaction and global modeling. Extensive experiments were conducted on five challenging datasets. The experimental results demonstrate that the proposed method outperforms several SOTA methods. Full article

The water resources carrying capacity (WRCC) is a crucial indicator for assessing the sustainability of regional development. This study integrates the gray water footprint (GWF) into the WRCC evaluation, constructing a comprehensive framework that encompasses five subsystems: water resources, society, economy, ecology, and climate. Using the CRITIC-TOPSIS model, the WRCC of Yunnan Province from 2012 to 2022 is analyzed, and a dynamic assessment is conducted through spatiotemporal hotspot and obstacle factor coupling analyses. The results show that the comprehensive WRCC of Yunnan decreased from 0.489 in 2012 to 0.477 in 2022, displaying an overall fluctuating downward trend with uneven spatial distribution. The per capita GWF and GWF load significantly impacted the WRCC within the social and ecological subsystems, respectively, highlighting the importance of water quality in the WRCC evaluation. The results reveal differing development trends in the dynamic changes of WRCC cold- and hotspots across various regions in Yunnan. Through coupling the obstacle factors of each regional subsystem, the main challenges and key measures for sustainable water resource development in each area are identified. This study optimizes the traditional evaluation framework by addressing shortcomings in water quality considerations, enriching the WRCC assessment, and providing a more comprehensive and accurate decision-support tool for regional development. Full article

The implementation of differentiated governance for agricultural water pollution (AWP) plays a significant role in alleviating the pressure on agricultural water resources. However, research that comprehensively assesses AWP and its influencing factors from a multidimensional perspective remains relatively limited. This study utilized the grey water footprint (GWF) model to quantify the agricultural grey water footprint (AGWF), agricultural grey water footprint efficiency (AGWFE), agricultural grey water footprint intensity (AGWFI), and agricultural water pollution level (AWPL) in Zhejiang from 2010 to 2020. Subsequently, we applied the standard deviational ellipse (SDE), the kernel density estimation (KDE), and the Dagum Gini coefficient to delve into the dynamic evolution and regional disparities of these indicators. Ultimately, we leveraged both the random forest model and the panel regression model to identify and examine the key factors shaping AGWF-related indicators. The results show that: (1) From 2010 to 2020, in Zhejiang, both AGWF and AGWFI exhibit a trend of first increasing and then decreasing, peaking in 2012. In contrast, AGWFE has consistently increased over the years, reaching an increase of 54.56 CNY/m³ by 2020. Meanwhile, despite fluctuations, AWPL in Zhejiang shows an overall gradual decline. (2) The centroids of relevant indicators for AWP in Zhejiang are primarily located in Jinhua (for AGWF and AGWFI), Shaoxing (for AWPL), and in the area where AGWFE converge. (3) Compared to 2010, the regional disparities in AGWF and AWPL have shrunk significantly in 2020, whereas the regional differences in AGWFE and AGWFI have increased to some extent. In most years, the regional disparities in AGWF, AGWFI, and AWPL are more pronounced in Northeastern Zhejiang compared to the southwestern part. (4) The influencing factors of AGWF, AGWFE, and AGWFI exhibit significant regional heterogeneity. In Northeastern Zhejiang, the primary factors influencing them are technological innovation, resource endowment, and crop-cultivation methods. Conversely, in the southwestern region, the primary factors exerting the same influence are the application intensities of fertilizers, pesticides, and agricultural film application. The primary drivers of AWPL in Zhejiang are grain yield, water resource availability, and crop-planting structure. Notably, these factors do not exhibit regional heterogeneity. The paper proposes AWP control policies from both a comprehensive and multi-dimensional perspective. Full article

Yellow sticky traps (YSTs) are common tools for monitoring the greenhouse whitefly (GWF), Trialeurodes vaporariorum Westwood (Hemiptera: Aleyrodidae), which can cause significant yield reduction in different greenhouse crops such as cucumber and tomato. In recent years, sticky traps equipped with green light-emitting diodes (LEDs) have also been (successfully) tested for catching GWFs. However, no study has observed GWF population dynamics at low population densities using such LED traps for early pest detection in crop stands. Therefore, a greenhouse experiment was conducted aiming to investigate the correlation between GWF populations on tomato crops (Solanum lycopersicum L. (Solanaceae)) and the numbers caught on yellow sticky traps and green LED traps, respectively. A small number of whiteflies was released into two pest-free greenhouse cabins, and populations on plants and traps were monitored for the duration of two months. The results show that the GWFs caught on LED traps correlate significantly positive with the population density on the tomato crops. Such a correlation was not found for standard YSTs. Moreover, the results indicate the possibility of early pest detection using LED traps. The findings are discussed in the context of the whiteflies’ ecology and population dynamics in greenhouses. Full article

This article revisits Feuerbach’s “break with speculation” in the early 1840s in light of issues raised by the original Pantheism Controversy, initiated in 1785 by the publication of Friedrich Heinrich Jacobi’s Letters on the Doctrine of Spinoza. The article first describes the concerns underlying Jacobi’s repudiation of Spinozism, and rationalism more generally, in favor of a personalistic theism that disclaims the possibility of philosophical knowledge of God. It goes on to reconstruct Hegel’s alternative to Jacobi’s famous salto mortale before considering how Feuerbach’s critique of Hegel’s philosophy of religion, as well as the personalism of the so-called Positive Philosophy (inspired by the late Schelling), was influenced by both Spinoza and Jacobi in ways that have not yet received sufficient attention. Full article

Agricultural non-point source (ANPS) pollution has emerged as a significant factor influencing water quality within watersheds. Understanding the spatial distribution and composition of ANPS is crucial for effective river water quality management. Based on the statistical data of 28 districts and counties in the Tuojiang River Basin (TJRB), the load distribution characteristics of total nitrogen (TN) and total phosphorus (TP) from ANPS were studied in this work by using the pollutant discharge coefficient method. In 2018, ANPS contributed 60,888.92 tons of TN and 20,085.98 tons of TP to the TJRB. By 2019, the TN load had decreased to 57,155.44 tons, while the TP load increased to 21,659.91 tons. Spatially, TN and TP loads follow a pattern of being lowest in the upstream, intermediate in the downstream, and highest in the middle reaches. Planting sources emerged as the primary contributors to TN and TP loads from ANPS in the TJRB, accounting for 61.43% and 77.39%, respectively. Rural living sources made a lesser contribution, at 20.23% for TN and 9.15% for TP, while poultry and livestock farming sources accounted for 18.34% of TN and 13.46% of TP loads. The analysis of grey water footprint (GWF) and water pollution level (WPL) revealed that TN and TP loads continued to exert significant pressure on the TJRB’s water environment throughout the study period. These findings offer valuable insights for enhancing water quality management in the TJRB. Full article

Water resources management and planning traditionally focus on visible liquid or blue water. However, green water also maintains social development and ecosystem services. Therefore, blue and green water should be incorporated into the watershed management system for evaluating water resources. To analyze the water resources of the Hanjiang River Basin, the SWAT model was set up using long-term and high-precision geographic data. The methods of wavelet analysis and Pearson’s correlation analysis were used to explore the influence mechanism of climate and vegetation changes on the blue and green water flow (BWF and GWF) of the main ecosystems in the basin. The results showed that: (1) The spatial–temporal distribution of the BWF and GWF in the main ecosystems of the basin over the past 50 years was uneven. Forest ecosystems and farmland ecosystems have a greater concentration of water resources in the south, while grassland ecosystems have a greater concentration of water resources in the east. (2) Climate dominates the BWF and GWF changes in the main ecosystems of the basin. The BWF and the precipitation change cycle are synergistic, and the GWF and the temperature change cycle are synergistic. (3) The correlation between vegetation and BWF and GWF in the farmland ecosystem is significant. Vegetation affects the hydrological change process of the BWF and GWF at the microscale. This study can provide data support and scientific rules for ecosystem water resource management in the basin. Full article