Heavy metal pollution in soils and sediments is becoming a matter of wide concern, this study was carried out in Dawa County of the Liaohe River Delta, with the aim of exploring the impacts of land use levels on heavy metal contamination of soil and sediment. A total of 129 soil samples were collected in different land use intensities (LUI). Soil metals (Fe, Mn, Cd, Cr, Cu, Ni, Pb and Zn) and soil salinity, pH, soil organic carbon (SOC), nitrate nitrogen (NO₃⁻-N), available phosphorus (AP) and grain sizes were analyzed. Correlation analysis indicated that SOC and grain size played important roles in affecting the heavy metal distribution. The factor analysis results indicated that heavy metal contamination was most probably caused by industrial and agricultural wastewater discharges, domestic sewage discharge and atmospheric deposition. Using ANOVA, it found that human activities significantly changed soil physic-chemical properties through soil erosion, leaching and fertilizer application, further affecting the behaviors of heavy metals in the soil and sediments. The anthropogenic factors could lead to potential environmental risk, as indicated by the Geo-accumulation index (I_geo) results of heavy metals. Overall, the heavy metals generally had approached or even exceeded moderately polluted (0 < I_geo < 1, 1 < I_geo < 2), but the Pb and Cu pollution level was low (I_geo < 0), and the Cd pollution level was moderately or strongly polluted (2 < I_geo < 3, 3 < I_geo < 4) in the five land use levels. This study will provide valuable information for appropriately determining how land should be used in future reclamation areas, as well as for the sustainable management of estuarine areas around the world.

Studying the spatiotemporal distribution pattern of carbon storage, balancing land development and utilization with ecological protection, and promoting urban low-carbon sustainable development are important topics under China’s “dual carbon strategy” (Carbon emissions stabilize and harmonize with natural carbon absorption). However, existing research has paid little attention to the impact of land use changes under different spatial policies on the provincial-scale ecosystem carbon storage. In this study, we established a carbon density database for Liaoning Province and obtained the spatial and temporal distribution of carbon storage over the past 20 years. Then, based on 16 driving factors and multiple spatial policies in Liaoning Province, we predicted land use and land cover changes (LUCC) under three scenarios for 2050 and analyzed the spatiotemporal distribution characteristics and response mechanisms of carbon storage under different scenarios. The results showed that (1) LUCC directly affected carbon storage, with a 35.61% increase in construction land and a decrease in carbon storage of 0.51 Tg over the 20-year period. (2) From 2020 to 2050, the carbon storage varied significantly among the natural trend scenario (NTS), ecological restoration scenario (ERS), and economic priority scenario (EPS), with values of 2112.05 Tg, 2164.40 Tg, and 2105.90 Tg, respectively. Carbon storage in the ecological restoration scenario exhibited positive growth, mainly due to a substantial increase in forest area. (3) The spatial pattern of carbon storage in Liaoning Province was characterized by “low in the center, high in the east, and balanced in the west”. Therefore, Liaoning Province can consider rationally formulating and strictly implementing the spatial policy of ecological protection in the future land planning so as to control the disorderly growth of construction land, realize the growth of ecological land area, effectively enhance carbon storage, and ensure the realization of the goal of “dual carbon strategy”.

This study investigates the relationship between urban block spatial morphology and microclimate in severe cold regions, using Shenyang, China as a case study. We employed computational fluid dynamics theory-based numerical simulation software and a controlled variable approach to analyze the microclimate effects of four key aspects: street conforming line ratio, street interface density, street aspect ratio, and building roof forms. The primary findings are as follows: Decreasing conforming line ratios initially increase average wind speed and temperature. Lower interface densities reduce average wind speed but raise temperature. Higher aspect ratios correspond to increased wind speed and decreased temperature. Additionally, upward sloping roofs correlate with higher average wind speed and temperature. This research provides a perspective for evaluating urban microclimates, considering human perception of urban block space. It also suggests spatial layout design strategies for different types of streets in severe cold regions, considering the climate environment.

The interactions between landscape patterns and ecological processes have become more complex with rapid urbanization. In China, urban haze pollution has become increasingly apparent. Elucidating the relationship between urban landscape patterns and haze effects is essential for understanding the formation and development of haze and implementing effective mitigation measures. In-depth studies of the effects of three-dimensional urban landscape patterns on haze are hindered by data limitations, unreliable methods, and complex processes. This study reviews the use of landscape indices, with the aim of advancing understanding of the impacts of three-dimensional urban landscape patterns on the distribution and diffusion of haze pollution. The literature is examined to assess the status and progress of research on the use of landscape indices, and a summary of case studies in which landscape indices have been used in haze pollution modeling is presented. Furthermore, a feasible perspective based on a landscape pattern index is presented. In light of this review focusing on the relationship between urban landscape patterns and processes, new approaches for determining the spatial and temporal heterogeneity of haze distribution and diffusion and haze-prone areas, and for optimizing landscape patterns, are identified.

The serious pollution of PM_2.5 caused by rapid urbanization in recent years has become an urgent problem to be solved in China. Annual and daily satellite-derived PM_2.5 datasets from 2001 to 2020 were used to analyze the temporal and spatial patterns of PM_2.5 in China. The regional and population exposure risks of the nation and of urban agglomerations were evaluated by exceedance frequency and population weight. The results indicated that the PM_2.5 concentrations of urban agglomerations decreased sharply from 2014 to 2020. The region with PM_2.5 concentrations less than 35 μg·m⁻³ accounted for 80.27% in China, and the average PM_2.5 concentrations in 8 urban agglomerations were less than 35 μg·m⁻³ in 2020. The spatial distribution pattern of PM_2.5 concentrations in China revealed higher concentrations to the east of the Hu Line and lower concentrations to the west. The annual regional exposure risk (RER) in China was at a high level, with a national average of 0.75, while the average of 14 urban agglomerations was as high as 0.86. Among the 14 urban agglomerations, the average annual RER was the highest in the Shandong Peninsula (0.99) and lowest in the Northern Tianshan Mountains (0.76). The RER in China has obvious seasonality; the most serious was in winter, and the least serious was in summer. The population exposure risk (PER) east of the Hu Line was significantly higher than that west of the Hu Line. The average PER was the highest in Beijing-Tianjin-Hebei (4.09) and lowest in the Northern Tianshan Mountains (0.71). The analysis of air pollution patterns and exposure risks in China and urban agglomerations in this study could provide scientific guidance for cities seeking to alleviate air pollution and prevent residents’ exposure risks.