The annual course of TCA formation in the lower troposphere: a modeling study

We present a modeling study investigating the influence of climate conditions and solar radiation intensity on gas-phase trichloroacetic acid (TCA) formation. As part of the ECCA-project (Ecotoxicological Risk in the Caspian Catchment Area), this modeling study uses climate data specific for the two individual climate regimes, namely "Kalmykia" and "Kola Peninsula". A third regime has also been included in this study, namely "Central Europe", which serves as a reference to somehow more moderate climate conditions. The simulations have been performed with a box modeling package (SBOX, photoRACM), which uses Regional Atmospheric Chemistry Mechanism (RACM) as its chemistry scheme. For this model a mechanism supplement has been developed including the reaction pathways of methyl chloroform photooxidation. The investigations are completed by a detailed sensitivity study addressing the impact of temperature and relative humidity. Atmospheric OH and HO2 concentrations and the NOx/HO2 ratio were identified as the governing quantities controlling the TCA formation trough methyl chloroform oxidation in the gas phase. Model calculations show a TCA production rate ranging between almost zero and 6.5 x 10(3) molecules cm(-3) day(-1) depending on location and season. In the Kalmykia regime the model predicts mean TCA production rates of 1.3 x 10(-4) and 5.4 x 10(-5) microg m(-3) year(-1) for the urban and rural environment, respectively. From the comparison of model calculations with measured TCA burdens in the soil ranging between 130 g m(-3) and 1750 g m(-3) we conclude that TCA formation through methyl chloroform photooxidation in the gas-phase is probably not the principal atmospheric TCA source in this region.     

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.     

Chromosome damage in individuals exposed to heavy metals†

Testing the mutagenic activity of environmental pollutants has become an important area of modern environmental science and prophylactic medicine. The most suitable method for short‐term mutagenicity testing on man, at present, are chromosome studies on somatic cells of exposed individuals. Mutation types analyzed by such studies are of high practical relevance as indicator system of genetic damage induced in man under in vivo conditions. A rather large series of such studies has been dedicated to the action of heavy metals on individuals contacted with these metals under therapeutic, ecological or occupational conditions or by intoxication. Lead, cadmium, chromium, nickel, mercury, zinc and other metals as well as their compounds have been under study. Analyses of that kind, of course, are hampered by difficulties with the distinct estimation of the actual load as well as unclear conditions of exposition, e.g. simultaneous exposition to different metals.

Results obtained till now arouse some suspicion of a direct or indirect mutagenic activity in man by certain chromium and platinum compounds, arsenic, mercury, and combinations of lead with other heavy metals (cadmium, zinc, arsenic, antimony, etc.). Life style, above all smoking habits, well may act comutagenic. In most cases, however, mutagenic activity of metals and metal compounds apparently is clearly superposed by their toxic activity. In specific cases, chromosome studies also may contribute to discover sources of ecological exposition and to monitor occupational load by heavy metals.     

Spatial modelling for the development of agri-environmental programs

Spatial modelling of environmental indicators has been well established in landscape ecology and in nature conservation on regional and national scales over the recent past. Yet, using spatial information as a basis for the coordination of environmental measures on a trans-national European level reveals several shortcomings and hindrances, ranging from data quality issues and methodological aspects to discussions on how to define ecological indicators across Europe. This paper analyzes the potential of spatial modelling for the development and implementation of agri-environmental measures as part of rural development policies, discussing critical aspects of spatial environmental modelling as well as chances, trends and demands.     

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.