A new satellite-based methodology for continental-scale disturbance detection.

The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance.     

Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data

This paper introduces an innovative modelling strategy aimed at simulating the main terms of net forest carbon budget (net primary production, NPP and net ecosystem exchange, NEE) in Tuscany (Central Italy). The strategy is based on the preliminary calibration and application of parametric and bio-geochemical models (C-Fix and BIOME-BGC, respectively), which simulate the behaviour of forest ecosystems close to equilibrium condition (climax). Next, the ratio of actual over-potential tree volume is computed as an indicator of ecosystem distance from climax and is combined with the model outputs to estimate the NPP and NEE of real forests. The per-pixel application of the new modelling strategy was made possible by the collection of several data layers (maps of forest type and volume, daily meteorological data and monthly normalized difference vegetation index (NDVI) images for the years 1999–2003) which served to characterize the eco-climatic and forest features of the region. The obtained estimates of forest NPP and NEE were evaluated against ground measurements of accumulated woody biomass and net carbon exchange. The results of these experiments testify the good potential of the proposed strategy and indicate some problem areas which should be the subject of future research.     

Self-sustained catalytic combustion of CO enhanced by micro fluidized bed: stability operation,fluidization state and CFD simulation

● Catalytic combustion in fluidized bed realizes efficient heat and mass transfer. ● Catalytic combustion in fluidized bed reduces the lean combustion limits. ● Catalytic combustion and flame combustion can be coupled. ● The diffusion/kinetics limited reaction model is suitable for catalytic combustion. A micro fluidized bed reactor was used to study the self-sustaining catalytic combustion of carbon monoxide (CO). The Cu_1−xCe_xO_y catalyst, as well as the pure CuO and CeO₂, are used to investigate the contributing mechanism of different active sites including dispersed CuO and Cu–Ce solid solutions. The ignition temperature (T_i) of CO over these catalysts at a flow rate of 2000 mL/min followed the order: 74 °C (Cu_0.5Ce_0.5O_y) < 75 °C (Cu_0.25Ce_0.75O_y) < 84 °C (Cu_0.75Ce_0.25O_y) < 105 °C (CuO) < 500 °C (CeO₂). Furthermore, the lean combustion limits (equivalence ratio ϕ) over these catalysts under the flow rates of 750–3000 mL/min (through fixed, bubbling, and fluidized bed) were also measured, which are Cu_0.5Ce_0.5O_y < Cu_0.25Ce_0.75O_y < Cu_0.75Ce_0.25O_y < CuO < CeO₂. The fluidized bed was simulated using the Eulerian two-fluid model (TFM) coupled with a diffusion/kinetic-limited reaction model to evaluate the influence of operation conditions on the self-sustained combustion of CO. The predicted maximum temperature agreed with the experimental measurements, demonstrating the validity of the kinetic model and simulation parameters. The results of catalytic combustion with increasing CO concentrations suggest that the catalytic combustion reaction could co-exist with the flamed combustion. When a high concentration of CO is used, a blue-purple flame caused by CO combustion appears in the upper part of the fluidized bed, indicating that the range of CO-containing exhaust gas purification could be expanded to a larger range using the fluidized-bed catalytic combustion technique.     

The Effects of Urbanization on Net Primary Productivity in Southeastern China

Net primary productivity (NPP) is one of the major ecosystem products on which human societies rely heavily. However, rapid urban sprawl and its associated dense population and economic conditions have generated great pressure on natural resources, food security, and environments. It is valuable to understand how urban expansion and associated demographic and economic conditions affect ecosystem functions. This research conducted a case study in Southeastern China to examine the impacts of urban expansion and demographic and economic conditions on NPP. The data sources used in research include human settlement developed through a combination of MODIS, DMSP-OLS and Landsat ETM+ images, the annual NPP from MODIS, and the population and gross domestic product (GDP) from the 2000 census data. Multiple regression analysis and nonlinear regression analysis were used to examine the relationships of NPP with settlement, population and GDP. This research indicates that settlement, population and GDP have strongly negative correlation with NPP in Southeastern China, but the outcomes were nonlinear when population or GDP reached certain thresholds.     

WATERSHED RESPONSES TO CLIMATE CHANGE AT GLACIER NATIONAL PARK1

ABSTRACT: We have developed an approach which examines ecosystem function and the potential effects of climatic shifts. The Lake McDonald watershed of Glacier National Park was the focus for two linked research activities: acquisition of baseline data on hydrologic, chemical and aquatic organism attributes that characterize this pristine northern rocky mountain watershed, and further developing the Regional Hydro-Ecosystem Simulation System (RHESSys), a collection of integrated models which collectively provide spatially explicit, mechanistically-derived outputs of ecosystem processes, including hydrologic outflow, soil moisture, and snow-pack water equivalence. In this unique setting field validation of RHESSys, outputs demonstrated that reasonable estimates of SWE and streamflow are being produced. RHESSys was used to predict annual stream discharge and temperature. The predictions, in conjunction with the field data, indicated that aquatic resources of the park may be significantly affected. Utilizing RHESSys to predict potential climate scenarios and response of other key ecosystem components can provide scientific insights as well as proactive guidelines for national park management.     

Mapping and Modeling the Biogeochemical Cycling of Turf Grasses in the United States

Turf grasses are ubiquitous in the urban landscape of the United States and are often associated with various types of environmental impacts, especially on water resources, yet there have been limited efforts to quantify their total surface and ecosystem functioning, such as their total impact on the continental water budget and potential net ecosystem exchange (NEE). In this study, relating turf grass area to an estimate of fractional impervious surface area, it was calculated that potentially 163,800 km² (± 35,850 km²) of land are cultivated with turf grasses in the continental United States, an area three times larger than that of any irrigated crop. Using the Biome-BGC ecosystem process model, the growth of warm-season and cool-season turf grasses was modeled at a number of sites across the 48 conterminous states under different management scenarios, simulating potential carbon and water fluxes as if the entire turf surface was to be managed like a well-maintained lawn. The results indicate that well-watered and fertilized turf grasses act as a carbon sink. The potential NEE that could derive from the total surface potentially under turf (up to 17 Tg C/yr with the simulated scenarios) would require up to 695 to 900 liters of water per person per day, depending on the modeled water irrigation practices, suggesting that outdoor water conservation practices such as xeriscaping and irrigation with recycled waste-water may need to be extended as many municipalities continue to face increasing pressures on freshwater.     

Satellite Remote Sensing of Terrestrial Net Primary Production for the Pan-Arctic Basin and Alaska

We applied a terrestrial net primary production (NPP) model driven by satellite remote sensing observations of vegetation properties and daily surface meteorology from a regional weather forecast model to assess NPP spatial and temporal variability for the pan-Arctic basin and Alaska from 1982 to 2000. Our results show a general decadal trend of increasing NPP for the region of approximately 2.7%, with respective higher (3.4%) and lower (2.2%) rates for North America and Eurasia. NPP is both spatially and temporally dynamic for the region, driven largely by differences in productivity rates among major biomes and temporal changes in photosynthetic canopy structure and spring and summer air temperatures. Mean annual NPP for boreal forests was approximately 3 times greater than for Arctic tundra on a unit area basis and accounted for approximately 55% of total annual carbon sequestration for the region. The timing of growing season onset inferred from regional network measurements of atmospheric CO₂ drawdown in spring was inversely proportional to annual NPP calculations. Our findings indicate that recent regional warming trends in spring and summer and associated advances in the growing season are stimulating net photosynthesis and annual carbon sequestration by vegetation at high latitudes, partially mitigating anthropogenic increases in atmospheric CO₂. These results also imply that regional sequestration and storage of atmospheric CO₂ is being altered, with potentially greater instability and acceleration of the carbon cycle at high latitudes.