Sediment phosphorus (P) is an active component of the P cycle in lakes and its availability and movement could play an important role in eutrophication. Sediments from different depths in five representative sites of Dianchi Lake China, i.e., Haigeng, Dounan, Luojiacun, Xinjie, and Kunyang, were studied from January to December to evaluate the spatial and temporal dynamics in available-P and soluble-P and their impacts on algal growth. The results showed that the average sediment available-P and soluble-P were 41.2 mg kg⁻¹ and 0.27 mg kg⁻¹, respectively. Sediment available-P and soluble-P concentrations varied significantly among seasons, sites, and layers, with the following order: surface (0–5 cm) > middle (5–10 cm) > bottom (10–20 cm). The release and transformation characteristics of available-P and soluble-P at the sediment–water interface varied among sites. The Haigeng site, with the most severe algae blooms, had significantly higher average available-P and soluble-P in sediment than other sites. This indicated that phosphorus release and availability were associated with algal growth, and that the sediment surface (0–5 cm) is an important internal source that supports algal growth in Dianchi Lake.

Soil heavy metal pollution is frequent around areas with a high concentration of heavy industry enterprises. The integration of geostatistical and chemometric methods has been used to identify sources and the spatial patterns of soil heavy metals. Taking a county in southwestern China as an example, two subregions were analyzed. Subregion R1 mainly contained nonferrous mining, and subregion R2 was affected by smelting. Two factors (R1F1 and R1F2) associated with industry in R1 were extracted through positive matrix factorization (PMF) to obtain contributions to the soil As (64.62%), Cd (77.77%), Cu (53.10%), Pb (75.76%), Zn (59.59%), and Sb (32.66%); two factors (R2F1 and R2F2) also related to industry in R2 were extracted to obtain contributions to the As (53.35%), Cd (32.99%), Cu (53.10%), Pb (56.08%), Zn (67.61%), and Sb (42.79%). Combined with PMF results, cokriging (CK) was applied, and the z-score and root-mean square error were reduced by 11.04% on average due to the homology of heavy metals. Furthermore, a prevention distance of approximately 1800 m for the industries of concern was proposed based on locally weighted regression (LWR). It is concluded that it is necessary to define subregions for apportionment in area with different industries, and CK and LWR analyses could be used to analyze prevention distance.