Nitrogen induced DOC and heavy metals leaching: Effects of nitrogen forms, deposition loads and liming
2020
Zia, Afia | van den Berg, Leon | Riaz, Muhammad | Arif, Muhammad | Zia, Dania | Khan, Shawana J. | Ahmad, Muhammad Nauman | Attaullah, | Ahsmore, Mike
Atmospheric nitrogen (N) deposition is believed to accelerate dissolved organic carbon (DOC) production and could lead to increased heavy metal mobility into water resources. We sampled intact soil cores from the Isle of Skye with low background N deposition history and having Serpentine rock known for its higher heavy metal concentrations including zinc (Zn), copper (Cu), nickel (Ni) and lead (Pb). The effects of 16 (16kgN) and 32 kg N ha⁻¹ year⁻¹ (32kgN), and liming with 32kgN (32kgN+Lime) on soil solution chemistry and heavy metal mobilization were investigated over the 15-month study. Nitrogen in deposition load was added at five ammonium (NH₄⁺) to nitrate (NO₃⁻) ratios of 9:1, 5:1, 1:1, 1:5 and 1:9 along NO₃⁻dominance. We found significant effects of load on Cu and NH₄⁺/NO₃⁻ ratio on pH, DOC and Zn in soil solution. However, under lime and ratio experimental factors, liming significantly influenced pH, DOC, Cu and Pb, and NH₄⁺/NO₃⁻ ratio pH, DOC, Ni and Zn whereas interactions between lime and ratio was significant for Ni and Cu. pH and DOC increased with N load, liming and NO₃⁻ dominance, and both correlated significantly positively. Liming under NH₄⁺ dominance enhanced DOC production due to supply of base cations in lime. Mobilization of Cu, Ni and Pb was driven by DOC concentrations and, therefore, increased with load, liming and NO₃⁻ dominance in deposition. However, in contrast, low pH and high NH₄⁺ dominance was associated with Zn mobilization in soil solution. On the contrary, despite of some patterns, heavy metals in soil HNO₃ extracts were devoid of any load, lime and NH₄⁺/NO₃⁻ ratio effects. Our study suggests that the effects of N load and forms in deposition on sites with high accumulated loads of metals need to be better quantified through soil solution partitioning models.
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