Photocatalytic degradation of trinitrotoluene and other nitroaromatic compounds

The photocatalytic degradation of 2,4,6-trinitrotoluene and ten other nitroaromatic compounds in aerated TiO₂ suspensions has been studied. The following order of reactivity was observed: nitrotoluenes > nitrobenzene > dinitrotoluenes . dinitrobenzenes > 2,4,6-trinitrotoluene > 1,3,5-trinitrobenzene, which reflects the known influence of nitro groups towards the attack of electrophilic reagents on the aromatic molecule.     

(M)VOC and composting facilities. Part 1: (M)VOC emissions from municipal biowaste and plant refuse

GOAL, SCOPE AND BACKGROUND: Malodorous volatiles derived from the decomposition of biowaste within the process of composting might pose a risk to human health. Different techniques of process engineering have been developed to minimise the burden of malodorous compounds in air possibly affecting compost workers and residents in the vicinity. METHODS: In the present study, three different composting facilities were examined for the emission of volatiles to estimate the impact of process engineering on the dispersal of odorous compounds and to discuss its relevance for human health. RESULTS AND DISCUSSION: Concentrations of single compounds belonging to alcohols, ketones, furanes, sulfur-containing compounds and especially terpenes ranged from 10(2) up to nearly 10(6) ng/m3 depending on the sampling sites and the process engineering. The ratio of MVOC and total VOC measured changed throughout the process of biodegradation. A certain combination of volatile compounds coincided with the occurrence of typical compost odour. CONCLUSION: The type of process engineering seemed to have a major impact on the emission of volatiles, as amounts of (microbial) volatiles emitted were characteristic for the different techniques used. Thus, the MVOC emission basically depends on the degree of biodegradation. It is likely that the concentrations workers are exposed to can have an impact on human health. RECOMMENDATIONS AND OUTLOOK: It is obvious that less sophisticated types of process engineering give rise to greater amounts of bioaerosols and volatiles and, therefore, technical devices have to be improved and controlled regularly to minimise adverse health effects on workers.     

Analysis of particle-associated semi-volatile aromatic and aliphatic hydrocarbons in urban particulate matter on a daily basis

PM_2.5 Particle-associated semi-volatile organic compounds (SVOC) were determined in the city of Augsburg, Germany. Daily samples were collected at a central monitoring station from late summer to late autumn 2002. The concentrations of polycyclic aromatic hydrocarbons (PAH), oxidized PAH (O-PAH), n-alkanes, hopanes and long chain linear alkylbenzenes were determined by direct thermal desorption-gas chromatography-time of flight mass spectrometry (DTD-GC-TOFMS). Additionally, PM_2.5 particle mass and number concentrations were measured. The sampling campaign can be divided into two parts, distinguished by a lower temperature level in the second part of the campaign. The particulate mass concentration showed no significant changes, whereas most of the SVOC had significant higher mean and peak concentrations in the colder period. The analysis of the data showed an increased influence of non-traffic sources in the colder period, reflected by a weak shift in the PAH profile and a significant shift in the hopane pattern. Statistical analysis of the inter-group correlations was carried out. Eight clusters partly representing different sources of the aerosol have been identified.     

Communal nesting is explained by subsequent mating rather than kinship or thermoregulation in the Siberian flying squirrel

Research on group living in animals is concentrated on highly social species, but studying less social species may hint at the factors possibly leading to the evolution of increased sociality. Thermoregulation is often thought to explain communal nesting in solitarily breeding mammals but also other factors may be involved. For example, it is observed that even solitary species may have cryptic kin cooperation. We studied factors affecting communal nesting in the Siberian flying squirrel. Flying squirrels breed solitarily but, similar to most other rodents, adults may sometimes huddle in groups. Communal nesting in flying squirrels was most frequent during winter and autumn, but also occurred during other seasons. This pattern was explained by the breeding season, which took place in the spring–summer, when communal nesting was less common. Neither monthly temperature, after accounting for breeding season, nor daily temperatures in winter explained communal nesting. Group size was small, two to three individuals. In most cases the group was a pair consisting of unrelated male and female, possibly indicating that group formation was related to mating behavior. This study contributes to the understanding of mammalian group formation in two major ways. First, our study contributes to the understanding of the role of relatedness in rodent group formation, demonstrating a case where close relatedness is not related to group formation. Second, our study indicates that in a solitarily breeding, rodent huddling may be more driven by other factors than temperature.     

Seasonal variation and source estimation of organic compounds in urban aerosol of Augsburg, Germany

This study reports a general assessment of the organic composition of the PM_2.5 samples collected in the city of Augsburg, Germany in a summer (August-September 2007) and a winter (February-March 2008) campaign of 36 and 30 days, respectively. The samples were directly submitted to in-situ derivatisation thermal desorption gas chromatography coupled with time of flight mass spectrometry (IDTD-GC-TOFMS) to simultaneously determine the concentrations of many classes of molecular markers, such as n-alkanes, iso- and anteiso-alkanes, polycyclic aromatic hydrocarbons (PAHs), oxidized PAHs, n-alkanoic acids, alcohols, saccharides and others.The PCA analysis of the data identified the contributions of three emission sources, i.e., combustion sources, including fossil fuel emissions and biomass burning, vegetative detritus, and oxidized PAHs. The PM chemical composition shows seasonal trend: winter is characterized by high contribution of petroleum/wood combustion while the vegetative component and atmospheric photochemical reactions are predominant in the hot season.     

Three-dimensional characterization of the ammonia plume from a beef cattle feedlot

In Canada approximately 45% of ammonia (NH₃) emissions are attributed to dairy and beef cattle industries. The present study focused on NH₃ emissions from a beef feedlot with a one-time capacity of 17,220 head. The aim was to improve the Canadian NH₃ emission inventories and air quality forecasting capabilities. A Cessna 207, equipped with a fast-response NH₃/NO_y detector and a quadrupole aerosol mass spectrometer, was flown in a grid pattern covering an area of 8 × 8 km centered on a feedlot (800 × 800 m) at altitudes ranging from 30 to 300 m above ground. Stationary ground measurements of NH₃ concentration and turbulence parameters were made downwind of the feedlot. Three flights were conducted under varying meteorological conditions, ranging from very calm to windy with near-neutral stratification. NH₃ mixing ratios up to 100 ppbv were recorded on the calm day, up to 300 m above ground. An average feedlot NH₃ emission rate of 76 ± 4 μg m^?2 s^?1 (equivalent to 10.2 g head^?1 h^?1) was estimated. Characteristics of the measured NH₃ plume were compared to those predicted by a Lagrangian dispersion model. The spatially integrated pattern of NH₃ concentrations predicted and measured agreed but the measured was often more complex than the predicted spatial distribution. The study suggests that the export of NH₃ through advection accounted for about 90% of the emissions from the feedlot, chemical transformation was insignificant, and dry deposition accounted for the remaining 10%.     

Climate change adaptation and sustainable regional development: a case study for the Federal State of Brandenburg, Germany

Located in a relatively dry region and characterized by mainly sandy soils, the German Federal State of Brandenburg (surrounding the capital city of Berlin) is especially vulnerable to climate change impacts (e.g., summer droughts) and cascading effects on ecological systems (e.g., decreasing ground water tables, water stress, fire risk, productivity losses) with socioeconomic implications. Furthermore, a complex interplay of unemployment, rural exodus, and an aging population challenges this structurally weak region. We discuss adaptation measures that are either implemented or planned, as well as research into adaptation strategies to climate change for the sectors forestry, agriculture, and water management as well as in nature conservation in light of socioeconomic and ecological challenges and benefits. In doing so, we adopt a systemic view of Brandenburg where the sectors discussed are seen as subsystems embedded in a larger regional system. This at least partially holarchical approach enables the identification of conflicts between adaptation measures, but also of synergies among the sectors that pertain to successful adaptation to climate change. The insights gained ultimately highlight the need for cross-sectoral, adaptive management practices that jointly target a sustainable regional development.     

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.