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Hydrothermal liquefaction (HTL) is an effective way to treat solid wastes with high moisture content. The co-hydrothermal liquefaction (co-HTL) experiments of oily scum and poplar sawdust biochar at the different hydrothermal temperatures were performed in this work. The changes of the appearance and components of the liquid products were comprehensively studied. The results showed that the addition of biochar into oily scum significantly reduced the moisture content of the residue hydrochars obtained after co-HTL. As the hydrothermal temperature increased, the liquid products obtained from co-HTL turned clearer and lighter in color, and the recovery rate of the liquid products significantly increased. The co-HTL of bi-ochar and oily scum could effectively improve the liquid quality and enhance the recovery rate of hydrochars. The carbon numbers of the liquid products obtained from co-HTL were concentrated in C5-C11, which were main compositions of gas-oline. This work can provide basic data and theoretical reference for oily scum efficient treatment and engineering practice.

Hydrothermal liquefaction (HTL) is an effective way to treat solid wastes with high moisture content. The co-hydrothermal liquefaction (co-HTL) experiments of oily scum and poplar sawdust biochar at the different hydrothermal temperatures were performed in this work. The changes of the appearance and components of the liquid products were comprehensively studied. The results showed that the addition of biochar into oily scum significantly reduced the moisture content of the residue hydrochars obtained after co-HTL. As the hydrothermal temperature increased, the liquid products obtained from co-HTL turned clearer and lighter in color, and the recovery rate of the liquid products significantly increased. The co-HTL of bi-ochar and oily scum could effectively improve the liquid quality and enhance the recovery rate of hydrochars. The carbon numbers of the liquid products obtained from co-HTL were concentrated in C5-C11, which were main compositions of gas-oline. This work can provide basic data and theoretical reference for oily scum efficient treatment and engineering practice.

Environmental particulate pollution is a major global environmental health risk factor, which is associated with numerous adverse health outcomes, negatively impacting public health in many countries, including China. Despite the implementation of strict air quality management policies in China and a significant reduction in PM2.5 concentrations in recent years, the health burden caused by PM2.5 pollution has not decreased as expected. Therefore, a comprehensive analysis of the health burden caused by PM2.5 is necessary for more effective air quality management. This study makes an innovative contribution by integrating the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), and Soil-Adjusted Vegetation Index (SAVI), providing a comprehensive framework to assess the health impacts of green space coverage, promoting healthy urban environments and sustainable development. Using Nanjing, China, as a case study, we constructed a health impact assessment system based on PM2.5 concentrations and quantitatively analyzed the spatiotemporal evolution of premature deaths caused by PM2.5 from 2000 to 2020. Using Multiscale Geographically Weighted Regression (MGWR), we explored the impact of greening improvement on premature deaths attributed to PM2.5 and proposed relevant sustainable governance strategies. The results showed that (1) premature deaths caused by PM2.5 in Nanjing could be divided into two stages: 2000–2015 and 2015–2020. During the second stage, deaths due to respiratory and cardiovascular diseases decreased by 3105 and 1714, respectively. (2) The spatial variation process was slow, with the overall evolution direction predominantly from the southeast to northwest, and the spatial distribution center gradually shifted southward. On a global scale, the Moran’s I index increased from 0.247251 and 0.240792 in 2000 to 0.472201 and 0.468193 in 2020. The hotspot analysis revealed that high–high correlations slowly gathered toward central Nanjing, while the proportion of cold spots increased. (3) The MGWR results indicated a significant negative correlation between changes in green spaces and PM2.5-related premature deaths, especially in densely vegetated areas. This study comprehensively considered the spatiotemporal changes in PM2.5-related premature deaths and examined the health benefits of green space improvement, providing valuable references for promoting healthy and sustainable urban environmental governance and air quality management.

Environmental particulate pollution is a major global environmental health risk factor, which is associated with numerous adverse health outcomes, negatively impacting public health in many countries, including China. Despite the implementation of strict air quality management policies in China and a significant reduction in PM2.5 concentrations in recent years, the health burden caused by PM2.5 pollution has not decreased as expected. Therefore, a comprehensive analysis of the health burden caused by PM2.5 is necessary for more effective air quality management. This study makes an innovative contribution by integrating the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), and Soil-Adjusted Vegetation Index (SAVI), providing a comprehensive framework to assess the health impacts of green space coverage, promoting healthy urban environments and sustainable development. Using Nanjing, China, as a case study, we constructed a health impact assessment system based on PM2.5 concentrations and quantitatively analyzed the spatiotemporal evolution of premature deaths caused by PM2.5 from 2000 to 2020. Using Multiscale Geographically Weighted Regression (MGWR), we explored the impact of greening improvement on premature deaths attributed to PM2.5 and proposed relevant sustainable governance strategies. The results showed that (1) premature deaths caused by PM2.5 in Nanjing could be divided into two stages: 2000–2015 and 2015–2020. During the second stage, deaths due to respiratory and cardiovascular diseases decreased by 3105 and 1714, respectively. (2) The spatial variation process was slow, with the overall evolution direction predominantly from the southeast to northwest, and the spatial distribution center gradually shifted southward. On a global scale, the Moran’s I index increased from 0.247251 and 0.240792 in 2000 to 0.472201 and 0.468193 in 2020. The hotspot analysis revealed that high–high correlations slowly gathered toward central Nanjing, while the proportion of cold spots increased. (3) The MGWR results indicated a significant negative correlation between changes in green spaces and PM2.5-related premature deaths, especially in densely vegetated areas. This study comprehensively considered the spatiotemporal changes in PM2.5-related premature deaths and examined the health benefits of green space improvement, providing valuable references for promoting healthy and sustainable urban environmental governance and air quality management.

The pine caterpillar (Dendrolimus spectabilis Bulter, Lepidoptera: Lasiocampidae) is a destructive insect threatening forest communities across Eurasia. The pest is polyvoltine, and under global warming, more favorable temperatures can lead to additional generations. Here, we simulated the pine caterpillar voltinism under current and future climatic scenarios based on insect thermal physiology and cumulative growing degree day (CGDD) model. Subsequently, we revealed the future change patterns of the voltinism along elevational and latitudinal gradients. The results showed that both CGDD and pine caterpillar voltinism are increasing. The current voltinism of pine caterpillar ranges from 1.26 to 1.56 generations (1.40 ± 0.07), with an increasing trend of 0.04/10a. Similar trends are expected to continue under the future climate scenarios, with values of 0.01/10a, 0.05/10a, 0.07/10a, and 0.09/10a for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. At the elevation and latitudinal gradients, voltinism increases across all ranges, peaking at 500–1000 m and latitudes of 34–34.5° N. This study highlights that the increase in voltinism is not limited to low-elevation and -latitude regions but is predicted across various elevations and latitudes. These findings can enhance our understanding of how climate change affects pine caterpillar voltinism and contribute to forest pest management strategies, although this study assumes a linear relationship between temperature and voltinism, without considering other ecological factors.

The pine caterpillar (Dendrolimus spectabilis Bulter, Lepidoptera: Lasiocampidae) is a destructive insect threatening forest communities across Eurasia. The pest is polyvoltine, and under global warming, more favorable temperatures can lead to additional generations. Here, we simulated the pine caterpillar voltinism under current and future climatic scenarios based on insect thermal physiology and cumulative growing degree day (CGDD) model. Subsequently, we revealed the future change patterns of the voltinism along elevational and latitudinal gradients. The results showed that both CGDD and pine caterpillar voltinism are increasing. The current voltinism of pine caterpillar ranges from 1.26 to 1.56 generations (1.40 ± 0.07), with an increasing trend of 0.04/10a. Similar trends are expected to continue under the future climate scenarios, with values of 0.01/10a, 0.05/10a, 0.07/10a, and 0.09/10a for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. At the elevation and latitudinal gradients, voltinism increases across all ranges, peaking at 500–1000 m and latitudes of 34–34.5° N. This study highlights that the increase in voltinism is not limited to low-elevation and -latitude regions but is predicted across various elevations and latitudes. These findings can enhance our understanding of how climate change affects pine caterpillar voltinism and contribute to forest pest management strategies, although this study assumes a linear relationship between temperature and voltinism, without considering other ecological factors.

Slurry transportation is an essential process in numerous industrial applications, widely studied for its efficiency in material conveyance. Despite substantial research, the impact of pipe wall roughness on critical metrics such as pressure drop, specific energy consumption (SEC), and the Nusselt number remains relatively underexplored. This study provides a detailed analysis using a three-dimensional computational model of a slurry pipeline, with a 0.0549 m diameter and 3.8 m length. The model employs an Eulerian multiphase approach coupled with the RNG k-ε turbulence model, assessing slurry concentrations Cw = 40–60% (by weight). Simulations were conducted at flow velocities Vm = 1–5 m/s, with pipe roughness (Rh) ranging between 10 and 50 µm. Computational findings indicate that both pressure drop and SEC increase proportionally with roughness height, Vm, and Cw. Interestingly, the Nusselt number appears unaffected by roughness height, although it rises corresponds to Vm, and Cw. These insights offer a deeper understanding of slurry pipeline dynamics, informing strategies to enhance operational efficiency and performance across various industrial contexts.

Slurry transportation is an essential process in numerous industrial applications, widely studied for its efficiency in material conveyance. Despite substantial research, the impact of pipe wall roughness on critical metrics such as pressure drop, specific energy consumption (SEC), and the Nusselt number remains relatively underexplored. This study provides a detailed analysis using a three-dimensional computational model of a slurry pipeline, with a 0.0549 m diameter and 3.8 m length. The model employs an Eulerian multiphase approach coupled with the RNG k-ε turbulence model, assessing slurry concentrations Cw = 40–60% (by weight). Simulations were conducted at flow velocities Vm = 1–5 m/s, with pipe roughness (Rh) ranging between 10 and 50 µm. Computational findings indicate that both pressure drop and SEC increase proportionally with roughness height, Vm, and Cw. Interestingly, the Nusselt number appears unaffected by roughness height, although it rises corresponds to Vm, and Cw. These insights offer a deeper understanding of slurry pipeline dynamics, informing strategies to enhance operational efficiency and performance across various industrial contexts.