Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

Application of the Active Soda Process for Removing Sulphur Dioxide from Flue Gases

The active soda process1 was applied for desulfurlzatlon of flue gases emitted by a plant burning heavy fuel oil In a rotary drum drier for stone aggregate. The flue gas capacity of the plant was about 6,7 m³/s at normal conditions. The SO₂ concentration varied between 400– 500 ppm. The solid, dry and fine-grained NaHCO₃ of good quality was fed directly into the hot gas stream at the outlet of the rotary drier In two variants—with and without grinding. The mean particle size was 0.180 m^-3 or 0.070 m^-3, respectively. The achieved desulfurizatlon degree was shown to be directly dependent on the flue gas temperature and on the grinding effect, as well as on the normalized stoichiometric ratio. The highest achieved desulfurization degree amounted up to 74 percent. During the design of the desulfurization process no pilot plant installations and tests were necessary, and for the final process no special chemical reactor was used.     

Near Surface Soil Vapor Clusters for Monitoring Emissions of Volatile Organic Compounds from Soils

ABSTRACT

The overall objective of this research was to develop and test a method of determining emission rates of volatile organic compounds (VOCs) and other gases from soil surfaces. Soil vapor clusters (SVCs) were designed as a low dead volume, robust sampling system to obtain vertically resolved profiles of soil gas contaminant concentrations in the near surface zone. The concentration profiles, when combined with a mathematical model of porous media mass transport, were used to calculate the contaminant flux from the soil surface. Initial experiments were conducted using a mesoscale soil remediation system under a range of experimental conditions. Helium was used as a tracer and trichloroethene was used as a model VOC. Flux estimations using the SVCs were within 25% of independent surface flux estimates and were comparable to measurements made using a surface isolation flux chamber (SIFC). In addition, method detection limits for the SVC were an order of magnitude lower than detection limits with the SIFC. Field trials, conducted with the SVCs at a bioventing site, indicated that the SVC method could be easily used in the field to estimate fugitive VOC emission rates. Major advantages of the SVC method were its low detection limits, lack of required auxiliary equipment, and ability to obtain realtime estimates of fugitive VOC emission rates.     

(−)-Acetylcarnitin und Succinatoxydation

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