ABSTRACT
The critical load is the maximal rate of contaminant addition that, over time, will result in environmental concentrations that do not exceed the highest acceptable concentration (i.e., the critical limit). Computationally, critical loads depend solely on critical limits and the expected rates at which contaminants are lost from the environmental media of concern. Losses include processes such as flushing (water bodies) or leaching (soils), sequestration in sediment, volatilization, and crop removal. A significant challenge is that loss rates will vary with time, especially in response to processes such as climate change. How should regulators deal with these changes with time? This Perspective compares the implications of three options where conditions are: (1) fixed to represent the present, (2) variable with no trend over time, and (3) variable with systematic trends (monotonic and cyclical) over time, and a fourth option using stochastic (probabilistic) evaluation of all plausible future conditions. Soil concentrations over 250 years were computed for each option. As expected, conditions that vary systematically with time can drastically change estimates of environmental concentration, and hence critical loads. However, if it is assumed that regulators periodically revisit critical load estimates taking into account changing conditions, long-term objectives can be achieved. One approach to changing conditions is to stochastically create a family of possible time series of conditions and outcomes. In the example developed here, the range of outcomes from the stochastic treatment encompassed those of the various time-series calculations. The regulatory implications of these findings are discussed.
ACKNOWLEDGMENTS
Funding for this analysis was provided by Environment Canada. Parameter values were made available from the National Agri-Environmental Health Analysis and Reporting Program (NAHARP) of Agriculture and Agri-Food Canada. Review of the manuscript by Dr. Pat Doyle and two anonymous reviewers resulted in important improvements.
Notes
aRelative concentration (RCss) is computed as RCSS = CSS/I where I is the input flux density (influx) of metal, and because the value chosen for influx was I = 1 mg kg−1 a−1, RCSS is numerically equal to CSS. The units of RCSS are years (a).
bThe relative reduction in critical load compares Case 1 and Case 3 with corrective action, and indicates the reduction in critical loads at steady state.