『Abstract
The mechanism controlling Al solubility in Chinese acidic forest
soils is not clearly understood. This is the main limitation to
the ability to generate adequate dose-response prediction models
of the ecological effect of acid rain. To evaluate the relative
significance of possible processes, soils and soil solutions from
five forest catchments, located in southern and southwestern China,
were collected and analyzed for chemical parameters. Monitoring
showed that inorganic Al(Ali) was the dominant
fraction in most soil solutions; organic Al (Alo)
was usually less than 10% of total monometric Al (Ala).
Aluminum fractions varied significantly between and within the
different sites, though appearing to follow a similar pattern.
Over the entire pH range of 3.6-5.6, the pAl (i.e. -log of the
Al3+ activity) closely correlated with solution pH,
following regression slopes of 1.28 and 2.00 for upper and lower
soil horizons, respectively. The variations in Al3+
activity could not be explained satisfactorily using mineral dissolution
equilibria. Partial least square (PLS) regression showed that
soil acidity (quality) and ionic strength (intensity) of the solution
were the main explanatory variables for the variation in the concentration
of Al fractions. Aluminum in upper horizons originated from both
organic and inorganic solid Al pools, while aqueous Al in lower
horizons was dominantly of inorganic origin. Aluminum solubility
was strongly influenced by cation exchanges, especially in the
upper horizon. In the upper horizon, ionic strength (I )』
had a greater influence on Al solubility due to cation exchange
reaction. In the lower horizon, dissolution of inorganic Al pools
by the elevated H+ concentrations was the main Al release
mechanism. So Al activity was more dependent on H+
(or pH) in the lower horizon.
1. Introduction
2. Materials and methods
2.1. Site description
2.2. Sampling and analysis
2.3. Partial least square (PLS) regression and data compilation
3. Results and discussion
3.1. Aqueous aluminum fractions
3.2. Equilibria with possible mineral phases
3.3. PLS regression analysis
4. Conclusions
Acknowledgements
References