TY - JOUR
T1 - The importance of mineral determinations to PROFILE base cation weathering release rates
T2 - A case study
AU - Casetou-Gustafson, Sophie
AU - Akselsson, Cecilia
AU - Hillier, Stephen
AU - Olsson, Bengt A.
PY - 2019
Y1 - 2019
N2 -
Accurate estimates of base cation weathering rates in forest soils are crucial for policy decisions on sustainable biomass harvest levels and for calculations of critical loads of acidity. The PROFILE model is one of the most frequently used methods to quantify weathering rates, where the quantitative mineralogical input has often been calculated by the A2M ("Analysis to Mineralogy") program based solely on geochemical data. The aim of this study was to investigate how uncertainties in quantitative mineralogy, originating from modeled mineral abundance and assumed stoichiometry, influence PROFILE weathering estimate, by using measured quantitative mineralogy by X-ray powder diffraction (XRPD) as a reference. Weathering rates were determined for two sites, one in northern (Flakaliden) and one in southern (Asa) Sweden. At each site, 3-4 soil profiles were analyzed at 10cm depth intervals. Normative quantitative mineralogy was calculated from geochemical data and qualitative mineral data with the A2M program using two sets of qualitative mineralogical data inputs to A2M: (1) a site-specific mineralogy based on information about mineral identification and mineral chemical composition as determined directly by XRPD and electron microprobe analysis (EMPA), and (2) regional mineralogy, representing the assumed minerals present and assumed mineral chemical compositions for large geographical areas in Sweden, as per previous published studies. Arithmetic means of the weathering rates determined from A2M inputs (W
A2M
) were generally in relatively close agreement with those (W
XRPD
) determined by inputs based on direct XRPD and EMPA measurements. The hypothesis that using site-specific instead of regional mineralogy will improve the confidence in mineral data input to PROFILE was supported for Flakaliden. However, at Asa, site-specific mineralogies reduced the discrepancy for Na between W
A2M
and W
XRPD
but produced larger and significant discrepancies for K, Ca and Mg. For Ca and Mg the differences between weathering rates based on different mineralogies could be explained by differences in the content of some specific Ca-and Mg-bearing minerals, in particular amphibole, apatite, pyroxene and illite. Improving the accuracy in the determination of these minerals would reduce weathering uncertainties. High uncertainties in mineralogy, due for example to different A2M assumptions, had surprisingly little effect on the predicted weathering of Na-and K-bearing minerals. This can be explained by the fact that the weathering rate constants for the minerals involved, e.g. K feldspar and micas, are similar in PROFILE. Improving the description of the dissolution rate kinetics of the plagioclase mineral group as well as major K-bearing minerals (K feldspars and micas) should be a priority to help improve future weathering estimates with the PROFILE model.
AB -
Accurate estimates of base cation weathering rates in forest soils are crucial for policy decisions on sustainable biomass harvest levels and for calculations of critical loads of acidity. The PROFILE model is one of the most frequently used methods to quantify weathering rates, where the quantitative mineralogical input has often been calculated by the A2M ("Analysis to Mineralogy") program based solely on geochemical data. The aim of this study was to investigate how uncertainties in quantitative mineralogy, originating from modeled mineral abundance and assumed stoichiometry, influence PROFILE weathering estimate, by using measured quantitative mineralogy by X-ray powder diffraction (XRPD) as a reference. Weathering rates were determined for two sites, one in northern (Flakaliden) and one in southern (Asa) Sweden. At each site, 3-4 soil profiles were analyzed at 10cm depth intervals. Normative quantitative mineralogy was calculated from geochemical data and qualitative mineral data with the A2M program using two sets of qualitative mineralogical data inputs to A2M: (1) a site-specific mineralogy based on information about mineral identification and mineral chemical composition as determined directly by XRPD and electron microprobe analysis (EMPA), and (2) regional mineralogy, representing the assumed minerals present and assumed mineral chemical compositions for large geographical areas in Sweden, as per previous published studies. Arithmetic means of the weathering rates determined from A2M inputs (W
A2M
) were generally in relatively close agreement with those (W
XRPD
) determined by inputs based on direct XRPD and EMPA measurements. The hypothesis that using site-specific instead of regional mineralogy will improve the confidence in mineral data input to PROFILE was supported for Flakaliden. However, at Asa, site-specific mineralogies reduced the discrepancy for Na between W
A2M
and W
XRPD
but produced larger and significant discrepancies for K, Ca and Mg. For Ca and Mg the differences between weathering rates based on different mineralogies could be explained by differences in the content of some specific Ca-and Mg-bearing minerals, in particular amphibole, apatite, pyroxene and illite. Improving the accuracy in the determination of these minerals would reduce weathering uncertainties. High uncertainties in mineralogy, due for example to different A2M assumptions, had surprisingly little effect on the predicted weathering of Na-and K-bearing minerals. This can be explained by the fact that the weathering rate constants for the minerals involved, e.g. K feldspar and micas, are similar in PROFILE. Improving the description of the dissolution rate kinetics of the plagioclase mineral group as well as major K-bearing minerals (K feldspars and micas) should be a priority to help improve future weathering estimates with the PROFILE model.
U2 - 10.5194/bg-16-1903-2019
DO - 10.5194/bg-16-1903-2019
M3 - Article
AN - SCOPUS:85065540455
SN - 1726-4170
VL - 16
SP - 1903
EP - 1920
JO - Biogeosciences
JF - Biogeosciences
IS - 9
ER -