Combining Upscaling and Downscaling of Methane Emissions from Rice Fields: Methodologies and Preliminary Results

The uncertainty in the methane (CH₄) source strength of rice fields is among the highest of all sources in the global CH₄ budget. Methods to estimate the source strength of rice fields can be divided into two scaling categories: bottom-up (upscaling) and top-down (downscaling). A brief review of upscaling and downscaling methodologies is presented. The combination of upscaling and downscaling methodologies is proposed as a potential method to reduce the uncertainty in the regional CH₄ source strength of rice fields. Some preliminary results based on upscaling and downscaling are presented and the limitations of the approaches are discussed. The first case study focuses on upscaling by using a field-scale model in combination with spatial databases to calculate CH₄ emissions for the island of Java. The reliability of upscaling results is limited by the uncertainty in model input parameters such as soil properties and organic carbon management. Because controlling variables such as harvested rice area may change on relatively short time scales, a land use change model (CLUE) was used to quantify the potential land use changes on Java in the period 1994–2010. The predicted changes were evaluated using the CH₄ emission model. Temporal scaling by coupling land use change models and emission models is necessary to answer policy-related questions on future greenhouse gas emissions. In a downscaling case study, we investigate if inverse modeling can constrain the emissions from rice fields by testing a standard CH₄ from rice scenario and a low CH₄ from rice scenario (80 and 30 Tg CH₄ yr^–1, respectively). The results of this study are not yet conclusive; to obtain fine-resolution CH₄ emission estimates over the Southeast Asian continent, the monitoring network atmospheric mixturing ratios need to be extended and located closer to the continental sources.     

Comparing the input, output, and validation maps for several models of land change

This paper applies methods of multiple resolution map comparison to quantify characteristics for 13 applications of 9 different popular peer-reviewed land change models. Each modeling application simulates change of land categories in raster maps from an initial time to a subsequent time. For each modeling application, the statistical methods compare: (1) a reference map of the initial time, (2) a reference map of the subsequent time, and (3) a prediction map of the subsequent time. The three possible two-map comparisons for each application characterize: (1) the dynamics of the landscape, (2) the behavior of the model, and (3) the accuracy of the prediction. The three-map comparison for each application specifies the amount of the prediction’s accuracy that is attributable to land persistence versus land change. Results show that the amount of error is larger than the amount of correctly predicted change for 12 of the 13 applications at the resolution of the raw data. The applications are summarized and compared using two statistics: the null resolution and the figure of merit. According to the figure of merit, the more accurate applications are the ones where the amount of observed net change in the reference maps is larger. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of models using scientifically rigorous, generally applicable, and intellectually accessible statistical techniques.     

Predicting metal toxicity revisited: general properties vs. specific effects.

The present paper addresses the prediction of metal toxicity by evaluation of the relationships between general metal properties and toxic effects. For this, metal toxicity data were taken from 30 literature data sets, which varied largely in exposure times, organisms, effects and effect levels. General metal properties were selected on basis of literature reviewing of basic metal property classifications: used were the electrochemical potential deltaE0; the ionization potential IP; the ratio between atomic radius and atomic weight AR/AW; and the electronegativity Xm. The results suggest that toxicity prediction may be performed on basis of these fixed metal properties without any adoption to specific organisms, without any division of metals into classes, or grouping of toxicity tests. The results further indicate that metal properties contribute to the observed effects in relative importances which depend on specific effects, effect levels, exposure times, selected organisms and ambient conditions. The discussion strongly suggests that prediction should be by interpolation rather than by extrapolation of calibrated toxicity data: the concept here is that unknown metal toxicities are predicted on basis of observed metal toxicities in calibration experiments. Considering the used metal properties, the calibration covers the largest number of metals by the simultanuous use of Ge(IV), Cs(I), Li(I), Mn(VII), Sc and Bi in toxicity studies. Based on the data from the 30 studies considered, metal toxicities could be ordered in a relative way. This ordering indicates that the natural abundance of metals or metal ions in the Earth's crust may be regarded as a general comparative measure of the metal toxicities. The problems encountered in toxicity interpretation and ordering of toxicities indicate that control of the solution acidity, the metal's solubility and the metal's oxidation state may be key problems to overcome in future metal ion toxicity studies.     

Cell-membrane damage and element leaching in transplanted Parmelia sulcata lichen related to ambient SO2, temperature, and precipitation

Measurements were performed in lichen (Parmelia sulcata) transplants, to gain insight into the lichen vitality as possibly affected by both element deposition or lichen element content and further ambient atmospheric conditions (temperature, precipitation, SO2 levels). The electrical conductivity of rinsing solutions was used to assess cell-membrane damage in Parmelia sulcata in an experiment, which ran from August 2001 until August 2002. Element contents of the solutions and lichens were determined by inductively coupled plasma-optical emission spectrometry and by k0-instrumental neutron activation analysis, respectively. Factor analysis (MCATTFA) was used to determine grouping of elements of similar origin and/ or behavior. All in all, the data indicate that, apartfrom lichen Na and Cl levels, and for temperature and precipitation, no clear relationships with conductivity could be observed. Conductivity was mostly related to released Na, Cl, K, Mg, and Cs. On the basis of concentrations, Na, Cl, and K could be considered as largely determining the conductivity. The data suggest a different origin for K than that for Na and Cl: the latter two are most probably due to effects from sea salt sprays. Parmelia sulcata was sensitive enough to reflect appreciable ambient rises in air SO2 and resistant enough to recover afterward. MCATTFA on selected elements (K, Sc, Cu, V, As, and Sb) indicated the absence of any comparability between K and V, As and Sb, suggesting differences in origin and/or chemico-physical occurrence. Generally speaking, the present data suggest that the comparability of lichen vitality in large geographical areas may be limited and governed by the area's variability in temperature and precipitation rather than by variability in metal deposition rates. The leaching data on all elements and element groups, however, strongly suggest that wet deposition may also severely affect lichen elemental levels. This latter observation means that comparing outcomes for time or spatial series of lichen samples should be accompanied by a comparably careful monitoring of (preceding) ambient conditions.     

Zusammenhang zwischen dem Wasser- und Festfettgehalt und der Austrocknungsgeschwindigkeit beim Auskanten von Margarine

Relationship between Water- und Fat-Content and the Drying-out Rate During Edging of Margarine A mathematical equation has been derived for the correlation between the water and solid fat contents and the drying-out rate of margarine and other plasticised W/O emulsions. A model has been used indicating that under the surface of the product, a completely dried out layer is formed which continuously thickens towards the interior of the product. During this process, the diffusion of the water dissolved in the fat towards the surface, is rate-determining. The experimentally found relations between moisture loss and storage time as well as between moisture loss and water content are in agreement with the formula derived. Using these experimental values, a correction factor has been calculated being dependent on the amount and the particle size of the solid fat phase. With the aid of this factor, the water and solid fat contents and physical constants, the expected moisture loss of plasticised W/O emulsions can be calculated.     

A multi-scale, multi-model approach for analyzing the future dynamics of European land use

Europe’s rural areas are expected to witness massive and rapid changes in land use due to changes in demography, global trade, technology and enlargement of the European Union. Changes in demand for agricultural products and agrarian production structure are likely to have a large impact on landscape quality and the value of natural areas. Most studies address these changes either from a macro-economic perspective focusing on changes in the agricultural sector or from a local perspective by analyzing recent changes in landscapes for small case studies. This paper describes a methodology in which a series of models has been used to link global level developments influencing land use to local level impacts. It is argued that such an approach is needed to properly address the processes at different scales that give rise to the land use dynamics in Europe. An extended version of the global economic model (GTAP) and an integrated assessment model (IMAGE) are used to calculate changes in demand for agricultural areas at the country level while a spatially explicit land use change model (CLUE-s) was used to translate these demands to land use patterns at 1 km² resolution. The global economic model ensures an appropriate treatment of macro-economic, demographic and technology developments and changes in agricultural and trade policies influencing the demand and supply for land use related products while the integrated assessment model accounts for changes in productivity as result of climate change and global land allocation. The land use change simulations at a high spatial resolution make use of country specific driving factors that influence the spatial patterns of land use, accounting for the spatial variation in the biophysical and socio-economic environment. Results indicate the large impact abandonment of agricultural land and urbanization may have on future European landscapes. Such results have the potential to support discussions on the future of the rural area and identify hot-spots of landscape change that need specific consideration. The high spatial and thematic resolution of the results allows the assessment of impacts of these changes on different environmental indicators, such as carbon sequestration and biodiversity. The global assessment allows, at the same time, to account for the tradeoffs between impacts in Europe and effects outside Europe.     

Alprazolam premedication and 35% carbon dioxide vulnerability in panic patients

A group of 20 patients who met the DSM-III-R criteria for panic disorder with or without agoraphobia underwent a 35% carbon dioxide (CO2) challenge after either 1 mg alprazolam or placebo in a double-blind, randomized, cross-over design. Despite the anxiolytic potential of alprazolam, it produced no significant effects on CO2-induced anxiety and panic symptomatology when compared to placebo.     

Spatially explicit modelling of biofuel crops in Europe

This paper describes a methodology to explore the (future) spatial distribution of biofuel crops in Europe. Two main types of biofuel crops are distinguished: biofuel crops used for the production of biodiesel or bioethanol, and second-generation biofuel crops. A multi-scale, multi-model approach is used in which biofuel crops are allocated over the period 2000-2030. The area of biofuel crops at the national level is determined by a macro-economic model. A spatially explicit land use model is used to allocate the biofuel crops within the countries. Four scenarios have been prepared based on storylines influencing the extent and spatial distribution of biofuel crop cultivation. The allocation algorithm consists of two steps. In the first step, processing plants are allocated based on location factors that are dependent on the type of biofuel crop processed and scenario conditions. In the second step, biofuel crops are allocated accounting for the transportation costs to the processing plants. Both types of biofuel crops are allocated separately based on different location factors. Despite differences between the scenarios, mostly the same areas are showing growth in biofuel crop cultivation in all scenarios. These areas stand out because they have a combination of well-developed infrastructural and industrial facilities and large areas of suitable arable land. The spatially explicit results allow an assessment of the potential consequences of large-scale biofuel crop cultivation for ecology and environment.     

Atmospheric metal deposition in a moss data correlation study with mortality and disease in the Netherlands

The present paper addresses the correlations between moss metal concentrations and epidemiological data on health and mortality rates in The Netherlands. Attention was given to both total and fractionated metal concentrations in the moss tissues, the latter by factor-analytical (mathematical) approaches, and to both grouped and specific diseases. Better than 95% probability correlations were found both for total moss elements and mortality due to specific diseases and for fractionated moss elements and mortality rates summed for grouped diseases. Overall, the presented data suggest that correlation studies between biomonitoring data on metal air pollution and (epidemiological) health data may prove valuable in turning attention to specific metal-health issues and in directing further study into possible dose-response mechanisms in air-associated metal epidemiology.