Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Power sector development in India with CO2 emission targets: Effects of regional grid integration and the role of clean technologies

The power sector in India at present comprises of five separate regional electricity grids having practically no integrated operation in between them. This study analyses the utility planning, environmental and economical effects of integrated power sector development at the national level in which the regional electric grids are developed and operated as one integrated system. It also examines the effects of selected CO₂ emission reduction targets in the power sector and the role of renewable power generation technologies in India. The study shows that the integrated development and operation of the power system at the national level would reduce the total cost including fuel cost by 4912 million $, total capacity addition by 2784 MW, while the emission of CO₂, SO₂ and NO_x would be reduced by 231.6 (1.9%), 0.8 (0.9%), 0.4 (1.2%) million tons, respectively, during the planning horizon. Furthermore, the study shows that the expected unserved energy, one of the indices of generation system reliability, would decrease to 26 GWh under integrated national power system from 5158 GWh. As different levels of CO₂ emission reduction targets were imposed, there is a switching of generation from conventional coal plants to gas fired plants, clean coal technologies and nuclear based plants. As a result the capacity expansion cost has increased. It was found that wind power plant is most attractive and economical in the Indian perspective among the renewable options considered (Solar, wind and biomass). Copyright © 2003 John Wiley & Sons, Ltd.     

Small-scale CDM projects in a competitive electricity industry: How good is a simplified baseline methodology?

Setting baseline emissions is one of the principal tasks involved in awarding credits for greenhouse gas emission (GHG) mitigation projects under the Clean Development Mechanism (CDM). An emission baseline has to be project-specific in order to be accurate. However, project-specific baseline calculations are subject to high transaction costs, which disadvantage small-scale projects. For this reason, the CDM-Executive Board (CDM-EB) has approved simplified baseline methodologies for selected small-scale CDM project categories. While the simplified methods help reduce the transaction cost, they may also result in inaccuracies in the estimation of emission reductions from CDM projects. The purpose of this paper is to present a rigorous economic scheduling method for calculating the GHG emission reduction in a hypothetical competitive electricity industry due to the operation of a renewable energy-based power plant under CDM and compare the GHG emission reduction derived from the rigorous method with that obtained from the use of a simplified (i.e., standardized) method approved by the CDM-EB. A key finding of the paper is that depending upon the level of power demand, prices of electricity and input fuels, the simplified method can lead to either significant overestimation or substantial underestimation of emission reduction due to the operation of renewable energy-based power projects in a competitive electricity industry.     

A new technique for on-line and off-line high speed computation

A novel technique for both online and offline computation is presented. With this technique, a reconstruction analysis in elementary particle physics, otherwise prohibitively long, has been accomplished. It will be used online in an upcoming Fermilab experiment to reconstruct more than 100000 events per second and to trigger on the basis of that information. The technique delivers 40 gigaoperations per second, has a bandwidth on the order of gigabytes per second, and has a modest cost. An overview of the program, details of the system, and performance measurements are presented     

Near-field optical imaging of unstained bacteria: comparison with normal atomic force and far-field optical microscopy in air and aqueous media

Simultaneous near-field scanning optical and atomic force imaging of bacteria is presented. The bacteria imaged in these studies were unstained. The near-field optical images had excellent signal-to-noise and showed excellent contrast even in these unstained specimens. The images obtained were interpreted in terms of the images that have been obtained by transmission electron microscopy and X-ray imaging. The results show that bacterial near-field optical imaging is going to be a very important tool in the arsenal of the bacteriologist both in terms of understanding the fundamental processes in the life cycle of bacteria with and without cytochemical staining and in terms of clinical diagnostic applications.     

Snowpack response in the Assiniboine-Red River basin associated with projected global warming of 1.0 °C to 3.0 °C

This study assesses snow response in the Assiniboine-Red River basin, located in the Lake Winnipeg watershed, due to anthropogenic climate change. We use a process-based distributed snow model driven by an ensemble of eight statistically downscaled global climate models (GCMs) to project future changes under policy-relevant global mean temperature (GMT) increases of 1.0 °C to 3.0 °C above the pre-industrial period. Results indicate that basin scale seasonal warmings generally exceed the GMT increases, with greater warming in winter months. The majority of GCMs project wetter winters and springs, and drier summers, while autumn could become either drier or wetter. An analysis of snow water equivalent (SWE) responses under GMT changes reveal higher correlations of snow cover duration (SCD), snowmelt rate, maximum SWE (SWE_max) and timing of SWE_max with winter and spring temperatures compared to precipitation, implying that these variables are predominantly temperature controlled. Consequently, under the GMT increases from 1.0 °C to 3.0 °C, the basin will experience successively shorter SCD, slower snowmelt, smaller monthly SWE and SWE_max, earlier SWE_max, and a transition from snow-dominated to rain-snow hybrid regime. Further, while the winter precipitation increases for some GCMs compensate the temperature-driven changes in SWE, the increases for most GCMs occur as rainfall, thus limiting the positive contribution to snow storage. Overall, this study provides a detailed diagnosis of the snow regime changes under the policy-relevant GMT changes, and a basis for further investigations on water quantity and quality changes.     

Assessing terrestrial wildlife populations in the Toronto and Region Area of Concern

Beneficial use impairments (BUIs) under the Great Lakes Water Quality Agreement identify environmental issues requiring remedial action within the Great Lakes Areas of Concern (AOCs). We conducted this study to support the assessment of the wildlife component of BUI 3: degradation of fish and wildlife populations. We compared bird and amphibian (frogs and toads) data from the Toronto and Region Conservation Authority’s Terrestrial Long-term Monitoring Program in the Toronto and Region AOC to an adjacent, but otherwise similar, reference watershed, Duffins Creek. Twelve of 13 targets were met within the AOC for forest bird, wetland bird, meadow bird and amphibian populations based on averages of mean annual values at sites within the AOC that were within two standard deviations of averages at sites in the Duffins Creek reference watershed between 2008 and 2017. Even though wildlife populations within the AOC were within the normal range of variability expected from a reference watershed, they were often at lower levels than within the Duffins Creek reference watershed. In addition, forest bird and amphibian populations were negatively affected by urbanization within the AOC and meadow bird indices declined. We conclude that while wildlife populations within the AOC currently meet targets for BUI 3, they continue to be negatively impacted by numerous stressors that are primarily related to past and ongoing urbanization. Thus, continued restoration of wildlife habitat and protection of existing habitat within the AOC is highly recommended.     

Seasonal variation in light penetration and subsurface chlorophyll-α in southern Lake Michigan observed by a glider

The Cooperative Institute for Great Lakes Research (CIGLR) in collaboration with the Great Lakes Observing System and National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory (NOAA GLERL) deployed an autonomous underwater glider in southern Lake Michigan several times per year between 2012 and 2019 to collect offshore (>30 m depth) limnological measurements, including temperature, photosynthetically active radiation (beginning during 2015), and chlorophyll-α fluorescence. From these data, we calculated mixed layer depth, several measures of light penetration (diffuse attenuation coefficient, first optical depth, euphotic zone depth), and depth of the subsurface chlorophyll-α maxima. During summer, mean offshore mixed layer depth was typically 10–15 m, K_d for PAR was 0.1–0.17 m^?1, first optical depth was 6–9 m, euphotic zone depth was 35–40 m, and depth of subsurface chlorophyll-α maxima was 30–35 m. We also observed substantial spatial and temporal variation in these values across the basin and within and among seasons. Glider-based observations provide a wider horizontal and vertical perspective than other methods (e.g., ship- and satellite-based observations, buoys, and fixed moorings), and are therefore a valuable, complementary tool for Great Lakes limnology. The set of observations reported here provide seasonal and basin-scale information that may help to identify anomalies useful for future glider-assisted investigation into the role of biophysical processes in Great Lakes limnology and ecology.