3 research outputs found
Health Risk Assessment Based on Source Identification of Heavy Metal(loid)s: A Case Study of Surface Water in the Lijiang River, China
In this study, 24 surface water samples were collected from the main trunk/tributary of the Lijiang River during the wet season (April) and the dry season (December) in 2021. The total concentration of 11 heavy metal(loid)s (Al, Cu, Pb, Zn, Cr, Ni, Co, Cd, Mn, As, and Hg) was determined to investigate their physicochemical properties and spatial-temporal distribution characteristics. The heavy metal evaluation index (HEI) and the positive matrix factorization (PMF) model were employed to evaluate water quality and to reveal quantitatively identified pollution sources for further investigation to obtain a health risk assessment using the hazard index (HI) and carcinogenic risk (CR) of various pollution sources. The mean concentrations of heavy metal(loid)s in surface water in the wet and dry seasons were ranked as: Al > Mn > Zn > Ni > Cd > Cr > Cu > As >Hg = Pb > Co, with the mean concentration of Hg being higher than the national Class II surface water environmental quality standard (GB3838-2002). In terms of time scale, the concentration of most heavy metal(loid)s was higher in the wet season; most heavy metal(loid)s were distributed mainly in the midstream area. HEI index indicated that the main water quality status was “slightly affected” in the study area. Five potential sources of pollution were obtained from the PMF model, including industrial activities, traffic sources, agricultural activities, domestic waste emissions, and natural resources. The source-oriented risk assessment indicated that the largest contributions of HI and CR were agricultural sources in the Lijiang River. This study provides a “target” for the precise control of pollution sources, which has a broad impact on improving the fine management of the water environment in the basin
Effects of stand age on carbon storage in dragon spruce forest ecosystems in the upper reaches of the Bailongjiang River basin, China
Abstract At an ecosystem level, stand age has a significant influence on carbon storage (CS). Dragon spruce (Picea asperata Mast.) situated along the upper reaches of the Bailongjiang River in northwest China were categorized into three age classes (29–32 years, Y1; 34–39 years, Y2; 40–46 years, Y3), and age-related differences in total carbon storage (TCS) of the forest ecosystem were investigated for the first time. Results showed that TCS for the Y1, Y2, and the Y3 age groups were 323.64, 240.66 and 174.60 Mg ha−1, respectively. The average TCS of the three age groups was 255.65 Mg C ha−1, with above-ground biomass, below-ground biomass, litter, and soil in the top 0.6 m contributing 15.0%, 3.7%, 12.1%, and 69.2%, respectively. CS in soil and TCS of the Y1 age group both significantly exceeded those of the Y3 age group (P < 0.05). Contrary to other recent findings, the present study supports the hypothesis that TCS is likely to decrease as stand age increases. This indicates that natural resource managers should rejuvenate forests by routinely thinning older stands, thereby not only achieving vegetation restoration, but also allowing these stands to create a long-term carbon sink for this important eco-region