Atmospheric pollution caused by fine particulate matter (PM_2.5) seriously damages human health. Urban forests have the ecological function of purifying the atmosphere, which can effectively reduce the ambient PM_2.5 concentration. This paper analyzed the ability of different forest types to mitigate PM_2.5 pollution and explored the effects of forest quality and morphological parameters on PM_2.5 concentration on the forest patch level. The results concluded that the PM_2.5 concentration of the Landscape and Relaxation Forest (LF) was significantly lower than that of the Roadside Forest (RF) and Affiliated Forest (AF) due to the environmental quality of their location. The effective distance of LF on PM_2.5 reduction was 80 m, which was significantly higher than RF and AF. The Normalized Difference Vegetation Index (NDVI), which indicated forest growth status, was the most effective parameter for improving the urban forest PM_2.5 mitigation ability. The concentration of PM_2.5 decreased linearly with the increase in NDVI. The area and perimeter of the forest patches had a significant nonlinear negative correlation with PM_2.5 concentration. In addition, the more irregular the shape of the forest patch, the lower the PM_2.5 concentration of the forest. Moreover, the simpler shape of RF and AF helped to alleviate PM_2.5 pollution. The round shape of AF more efficiently reduced PM_2.5 concentration. Our study demonstrated that the surrounding environment, forest growth status, and patch forms determined the PM_2.5 reduction capacity of an urban forest. The corresponding management and adjustment methods should be implemented in future urban forest management.

Quantifying the urban supply and demand of carbon sequestration services is an important prerequisite for achieving global carbon neutrality goals. However, the spatiotemporal patterns for balancing the supply and demand of carbon sequestration services in urban agglomerations remain unclear. In this study, NPP/VIIRS nighttime light data were used to identify the carbon sequestration service demand and were then combined with the carbon sequestration service supply to analyze the spatiotemporal patterns of supply and demand for carbon sequestration services in the Harbin-Changchun urban agglomeration (HCUA) in Northeast China. Our results indicate that both the supply and demand of carbon sequestration services showed increasing trends from 2012 to 2020 in the HCUA. The regions with increasing supply and demand trends were mainly located in the eastern mountainous and western urban areas, respectively. The total supply and demand of carbon sequestration services in the HCUA were 2080.3 Mt·C yr⁻¹ and 433.6 Mt·C yr⁻¹, respectively. Carbon surpluses (supply > demand) were found in most areas (98%), although particularly in the southeastern mountainous region. However, with rapid urbanization, in most cities, the supply–demand ratio decreased from 2012 to 2020, and the proportion of carbon deficit regions showed a continuous increase, which was mainly distributed in newly developed urban areas. The low supply–high demand (L-H) pattern showed significant spatial mismatching for supply and demand in the HCUA. The proportion of regions with the L-H pattern also showed a rapidly increasing trend from 2012 to 2020, indicating a more obvious carbon deficit trend in the future. This study provides important guidelines for formulating effective policies for energy consumption and carbon sequestration to combat global warming under China’s rapid urbanization.

Hunchun, a typical area suffering wild boar (Sus scrofa) damage, is an important region for the Siberian Tiger (Panthera tigris) in China. By incorporating the maximum entropy model with 22 variables in the home range scale (12 variables) and in the feeding site scale (10 variables), we predicted wild boar damage risks in this area of China and analyzed how spatial factors influence damage risk. Damage risk was found to be high in areas close to the forest edge, areas with a higher forest cover and lower to medium deciduous forest proportion, low road density, and a medium river density and farmland proportion. The proportion of farmland which was identified as being in the high damage risk zone was 23.55%, of which 38.68% was within the habitat area of the Siberian Tiger. Finally, we propose wild boar damage prevention based on different management goals.

As a symbol of urban civilization and history, old and notable trees (ONTs) are facing challenges brought by rapid urbanization. Changchun is the fastest growing city in Northeast China, and throughout its development process of over 100 years it has preserved many ONTs. This study investigated all the ONTs in Changchun, and analyzed the species diversity, spatial distribution characteristics, dimension, age, and health status of trees by using ecological index and mathematical statistics, and trying to find out the underlying factors regulating their distribution. The results showed that there were 773 old trees belonging to 25 species and 2 notable trees from 1 species in Changchun. Pyrus ussuriensis was the dominant species, followed by Salix matsudana and Ulmus pumila. The urban area, population density, greening rate, and construction history did not influence the species and quantity of ONTs, while the types of land use and tree protection planning were important factors affecting the richness, diversity, and growth conditions of trees. To explore the potential reasons for their existence, the ONTs’ data in Changchun was compared with two nearby cities—Harbin and Shenyang. The comparison indicated that the geographical location and climatic conditions also controlled the distribution of ONTs. The number and dimensions of trees were driven by the history and development process of the city. Our findings suggested that preserving favorable living environments and maintaining a low intensity of human disturbance are critical factors for the survival of ONTs in cities.

The rapid urbanization process and high-intensity construction mode have greatly changed the underlying surface structure and spatial distribution of the natural land surface, further amplified the possibility of urban floods, and made urban security face more serious threats. Urban forest could help to mitigate urban floods through water holding and interception by its unique structures, especially the litter layer. This paper compared the ability of different forest tree species on urban floods mitigation, through analyzing their litter accumulation, litter water holding characteristics, and water interception features of different decomposed layers. The results concluded that Quercus mongolica Fisch. ex Ledeb. (QM) forest, Betula platyphylla Sukaczev (BP) forest, Larix gmelinii (Rupr.) Kuzen. (LG) forest, and Picea koraiensis Nakai (PK) forest were the best choices for improving urban floods resistance in a high-urbanization winter city, for they had larger litter mass and higher maximum water holding and interception capacity. The corresponding results of this study could help environmental management departments worldwide in the selection of tree species in urban greening projects focusing on urban flood control.

Particulate pollutants, particularly PM_2.5 and PM₁₀, pose serious threats to human health and environmental quality. Therefore, effectively mitigating and reducing the concentrations of these pollutants is crucial for human survival and development. In this study, we analyzed the distribution characteristics of air particulate pollutants in a typical high-latitude city, extracted urban forest areas from high-resolution remote sensing images, and examined the changing characteristics of PM concentration and the relationship between landscape pattern indexes and PM at different scales. The results showed that the concentrations of PM_2.5 and PM₁₀ were highest in winter and lowest in summer. At the small scales of 0.5 km × 0.5 km to 1.5 km × 1.5 km, PM concentration decreased with the decrease in PARA (Perimeter–Area Ratio). At the mesoscales of 2 km × 2 km to 2.5 km × 2.5 km, both PARA and CIRCLE (Related Circumscribing Circle) were highly significant (p < 0.001) correlated with PM concentration. At the large scales of 3 km × 3 km to 4 km × 4 km, PARA and PAFRAC (Perimeter–Area Fractal Dimension) were positively correlated with PM concentration. Our study indicates that reducing the complexity of forest patches in small-scale planning can help mitigate particulate air pollution. In the medium scale of urban forest planning, the more regular the forest patch shape and the more similar the patch shape to the strip, the better PM can be alleviated, while in large-scale planning, increasing the forest area and making the patches more normalized and simplified can reduce PM concentration. Moreover, reducing the complexity of forest patches can significantly mitigate PM pollution at all scales. The results of this research provide theoretical support and guidance for improving air quality in urban forest planning at different scales.