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Thomas A. Clair

Publications and source records attributed to Thomas A. Clair.

2 recordsLinked to original sources

Comparisons of watershed sulfur budgets in southeast Canada and northeast US: New approaches and implications

Most of eastern North America receives elevated levels of atmospheric deposition of sulfur (S) that result from anthropogenic SO 2 emissions from fossil fuel combustion. Atmospheric S deposition has acidified sensitive terrestrial and aquatic ecosystems in this region; however, deposition has been declining since the 1970s, resulting in some recovery in previously acidified aquatic ecosystems. Accurate watershed S mass balances help to evaluate the extent to which atmospheric S deposition is retained within ecosystems, and whether internal cycling sources and biogeochemical processes may be affecting the rate of recovery from decreasing S atmospheric loads. This study evaluated S mass balances for 15 sites with watersheds in southeastern Canada and northeastern US for the period 1985 to 2002. These 15 sites included nine in Canada (Turkey Lakes, ON; Harp Lake, ON; Plastic Lake, ON; Hermine, QC; Lake Laflamme, QC; Lake Clair, QC; Lake Tirasse, QC; Mersey, NS; Moosepit, NS) and six in the US (Arbutus Lake, NY; Biscuit Brook, NY; Sleepers River, VT; Hubbard Brook Experimental Forest, NH; Cone Pond, NH; Bear Brook Watershed, ME). Annual S wet deposition inputs were derived from measured bulk or wet-only deposition and stream export was obtained by combining drainage water fluxes with SO 4 2− concentrations. Dry deposition has the greatest uncertainty of any of the mass flux calculations necessary to develop accurate watershed balances, and here we developed a new method to calculate this quantity. We utilized historical information from both the US National Emissions Inventory and the US (CASTNET) and the Canadian (CAPMoN) dry deposition networks to develop a formulation that predicted SO 2 concentrations as a function of SO 2 emissions, latitude and longitude. The SO 2 concentrations were used to predict dry deposition using relationships between concentrations and deposition flux derived from the CASTNET or CAPMoN networks. For the year 2002, we compared the SO 2 concentrations and deposition predictions with the predictions of two continental-scale air quality models, the Community Multiscale Air Quality (CMAQ) model and A Unified Regional Air-quality Modeling System (AURAMS) that utilize complete inventories of emissions and chemical budgets. The results of this comparison indicated that the predictive relationship provides an accurate representation of SO 2 concentrations and S deposition for the region that is generally consistent with these models, and thus provides confidence that our approach could be used to develop accurate watershed S budgets for these 15 sites. Most watersheds showed large net losses of SO 4 2− on an annual basis, and the watershed mass balances were grouped into five categories based on the relative value of mean annual net losses or net gains. The net annual fluxes of SO 4 2− showed a strong relationship with hydrology; the largest net annual negative fluxes were associated with years of greatest precipitation amount and highest discharge. The important role of catchment hydrology on S budgets suggests implications for future predicted climate change as it affects patterns of precipitation and drought. The sensitivity of S budgets is likely to be greatest in watersheds with the greatest wetland area, which are particularly sensitive to drying and wetting cycles. A small number of the watersheds in this analysis were shown to have substantial S sources from mineral weathering, but most showed evidence of an internal source of SO 4 2− , which is likely from the mineralization of organic S stored from decades of increased S deposition. Mobilization of this internal S appears to contribute about 1–6 kg S ha −1 year −1 to stream fluxes at these sites and is affecting the rate and extent of recovery from acidification as S deposition rates have declined in recent years. This internal S source should be considered when developing critical deposition loads that will promote ecosystem recovery from acidification and the depletion of nutrient cations in the northeastern US and southeastern Canada.

Connecticut, Maine, New Hampshire, New Jersey, New

Distribution patterns of mercury in Lakes and Rivers of northeastern North America

We assembled 831 data points for total mercury (Hg t ) and 277 overlapping points for methyl mercury (CH 3 Hg + ) in surface waters from Massachussetts, USA to the Island of Newfoundland, Canada from State, Provincial, and Federal government databases. These geographically indexed values were used to determine: (a) if large-scale spatial distribution patterns existed and (b) whether there were significant relationships between the two main forms of aquatic Hg as well as with total organic carbon (TOC), a well know complexer of metals. We analyzed the catchments where samples were collected using a Geographical Information System (GIS) approach, calculating catchment sizes, mean slope, and mean wetness index. Our results show two main spatial distribution patterns. We detected loci of high Hg t values near urbanized regions of Boston MA and Portland ME. However, except for one unexplained exception, the highest Hg t and CH 3 Hg + concentrations were located in regions far from obvious point sources. These correlated to topographically flat (and thus wet) areas that we relate to wetland abundances. We show that aquatic Hg t and CH 3 Hg + concentrations are generally well correlated with TOC and with each other. Over the region, CH 3 Hg + concentrations are typically approximately 15% of Hg t . There is an exception in the Boston region where CH 3 Hg + is low compared to the high Hg t values. This is probably due to the proximity of point sources of inorganic Hg and a lack of wetlands. We also attempted to predict Hg concentrations in water with statistical models using catchment features as variables. We were only able to produce statistically significant predictive models in some parts of regions due to the lack of suitable digital information, and because data ranges in some regions were too narrow for meaningful regression analyses.

Maine, Massachusetts, New Brunswick, New Hampshire