Application of the PnET-BGC – An integrated biogeochemical model – To assess the surface water ANC recovery in the Adirondack region of New York under three multi-pollutant proposals

SummaryWe applied an integrated biogeochemical model PnET-BGC to predict the response of acid neutralizing capacity (ANC) in lakes – a measure of the ability of water to neutralize inputs of strong acid – from 2001 to 2050 in the Adirondack region of New York, USA under three multi-pollutant proposal scenarios. Through model predictions, we assessed the impacts of these proposals on ecosystem recovery for research and policy initiatives.Our analysis indicated that the predicted recovery rates of surface water ANC obtained from the PnET-BGC model show low spatial autocorrelation. Predicted recovery rates are also closely related with the percentage of watershed areas of coniferous vegetation and deciduous vegetation, elevation and lake area, which turn out not to be significantly different from each other over the entire period of future scenarios (2001–2050). We applied a Geographic Weighted Regression model (GWR) to study the spatial patterns of predicted lake ANC in the Adirondacks through 2050 due to its high spatial autocorrelation. These results showed that lake depth and square of elevation can explain 40% of variation in the predicted ANC, which is 26% more variation than explained by the non-spatial Ordinary Least-Squares Regression (OLS). Our calculations also suggest that even under the Carper Bill, the most aggressive air pollutant control scenario considered, not all Adirondack lakes will recover (i.e., ANC > 50 μeq/L) from elevated acidic deposition by 2050. The research provides a basis for more informed emission controls and land use/land cover (LULC) policy-making in the north-eastern USA and elsewhere.