Jianjun Sheng

The transfer of heavy metals (HMs) from industrial park soils to edible crops is strongly crop-specific; however, these differences have not been considered in probabilistic dietary health risk assessments. This study examined agricultural fields surrounding a high-altitude industrial park in southwestern China, where paired samples of surface soil, Chinese cabbage, and maize were collected and analyzed for Cd, Pb, Cr, Ni, Cu, Zn, Hg, and As. Spearman rank correlation and principal component analysis (PCA) were applied to identify elemental associations and probable sources; bioaccumulation factors (BAFs) were calculated to compare HM transfer and accumulation across the two crops; and Monte Carlo simulation was used to estimate probabilistic dietary health risks across age groups. The results showed that soil HMs in the study area displayed mixed-source characteristics, with marked enrichment of Pb, Cd, and Hg. After multiple comparison correction, only soil Ni showed a significant positive correlation with Ni in maize. Chinese cabbage had a relatively high accumulation capacity for Cd, whereas maize grains showed relatively limited transfer of most HMs, indicating pronounced crop-specific differences. Cd, Pb, Cr, Hg, and As concentrations in Chinese cabbage remained within permissible limits. For health risk, P95 hazard index (HI) values stayed below 1 across all age groups, indicating that non-carcinogenic risk was generally acceptable under the exposure scenarios evaluated; adults, however, carried higher estimated lifetime carcinogenic risk than other age groups. Sensitivity analysis revealed that As and Cd in Chinese cabbage were the dominant contributors to non-carcinogenic and carcinogenic risks, respectively, while the contribution of Cr to risk estimates was highly dependent on its speciation and toxicological parameter assumptions. By combining soil–crop monitoring, bioaccumulation analysis, and probabilistic risk assessment, this study characterizes crop-specific HM transfer patterns and identifies the principal drivers of health risk in industrially influenced agricultural systems, providing a scientific basis for risk-oriented monitoring, food safety management, and the long-term sustainable use of agricultural land in industrial–agricultural interface regions.

Systematic assessment of the potential for realizing the value of ecological products in plateau lake basins, together with the identification of differentiated pathways, is essential for addressing structural tensions between ecological protection and regional development and for improving the precision of value-realization practices. Taking the nine major plateau lake basins in Yunnan Province as the study area, this study constructs a comprehensive indicator system covering three dimensions: supply potential, transformation conditions, and market demand. The k-means clustering method is then applied to classify basin types and identify dominant value-realization pathways. The results indicate that: (1) the VPPI ranges from 0.1594 to 0.7679, with the highest value in Dianchi Lake Basin and the lowest in Chenghai Lake Basin; the high-, medium-, and low-potential zones have mean VPPI values of 0.6928, 0.4033, and 0.2106, respectively; (2) four distinct types are identified, namely the regulatory service trading type, cultural tourism empowerment type, characteristic provisioning product premium type, and protection-priority reserve type; and (3) low-potential basins are mainly constrained by weak market demand, with a mean market-demand contribution of only 0.0386. These findings provide quantitative decision support for context-specific pathway design in plateau lake basins.

As a critical decision–support tool for sustainable development in alpine lake watersheds, ecosystem service valuation requires scientifically robust accounting systems to inform environmental management. This study addresses the significant interference caused by multi-source heterogeneity in indicator selection, methodology application, and parameter determination within current valuation systems. We innovatively developed a multi-dimensional accounting framework. Through establishing standardized systems for indicators, methods, and parameters, taking Xingyun Lake as the research area, we systematically elucidated the differential impact mechanisms of accounting elements on valuation outcomes. Empirical results demonstrate that structural differences in indicator systems induce 11.61% of valuation fluctuations. Methodological choices lead to 13.86% of deviations. Insufficient parameter localization generates errors up to 18.48%. The refined framework improved valuation accuracy by 16.22%. This study quantitatively evaluates the influencing factors of ecosystem services and confirms a cascading amplification effect of element sensitivity (parameters > methods > indicators) on valuation outcomes, establishing methodological foundations for alpine lake watershed ecological accounting benchmarks. It has important decision-making reference value for applying ecosystem service function evaluation to sustainable development.