Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.

Socio-environmental impact of idol immersion: dimensions and directions

India possesses a diverse and rich cultural heritage and is renowned as a 'land of festivals'. These festivals attract massive community involvement paving way to new materials such as 'Plaster of Paris' being used for 'modernizing' the representation of idols with very little thought given to the issues of toxicity and environmental impacts. Another dimension to the whole issue is the plight of the artisans and the workers involved in the trade. Owing to the unorganized nature of the industry there is minimal or no guidelines pertaining-to the worker safety and health risks of the people involved. This paper attempts to address the complexities of the inherent hazards as a consequence of these socio-environmental issues and trace the scientific rationale in addressing them in a practical and pragmatic way.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Environmental Management

Environmental Management has become one of the most used terms in recent times. But, what exactly does the term mean and entail? Environmental management helps to investigate and manage the environment within the context of human influences, incorporating an examination of economics, culture, political structure, and social equity, as well as natural processes and systems. This book discusses in detail the various issues relating to environmental management, including the fundamentals; the various environmental policies, legislations and international treaties; the concept of environmental impact assessment; environmental auditing; life cycle assessment; various environmental management system standards; issues and techniques, and environmental design and economics has become one of the most used terms in recent times. But, what exactly does the term mean and entail? Environmental management helps to investigate and manage the environment within the context of human influences, incorporating an examination of economics, culture, political structure, and social equity, as well as natural processes and systems. This book discusses in detail the various issues relating to environmental management, including the fundamentals; the various environmental policies, legislations and international treaties; the concept of environmental impact assessment; environmental auditing; life cycle assessment; various environmental management system standards; issues and techniques, and environmental design and economics.

SUPPORTING ENVIRONMENTALLY-BENIGN DESIGN ELUCIDATING ENVIRONMENTAL IMPACT PROPAGATION IN CONCEPTUAL DESIGN PHASE BY SAPPHIRE MODEL OF CAUSALITY

Conceptual Design Phase is the most critical for design decisions and their impact on the Environment. It is also a phase of many `unknowns' making it flexible and allowing exploration of many solutions. Thus, it is a challenge to determine the most Environmentally-benign Solution or Concept to be translated in to a `good' product. The SAPPhIRE Model captures the various levels of abstractions present in Conceptual Design by Outcomes and defines a Solution-variant as a set of verifiable and quantifiable Outcomes. The Causality explains the propagation of Environmental Impact across Outcomes at varying levels of abstraction, suggesting that the Environmental Impact of an Outcome at a certain level can be represented as a collation of Environmental Impact information of all the Outcomes at each of its subsequent lower levels of abstraction. Thus a ball-park impact value can be associated with the higher-levels of abstraction, thereby supporting design decisions taken earlier on in Conceptual Design directing towards Environmentally-benign Design.

A method for Estimating the Degree of Uncertainty With Respect to Life Cycle Assessment During Design

Life cycle assessment (LCA) is used to estimate a product's environmental impact. Using LCA during the earlier stages of design may produce erroneous results since information available on the product's lifecycle is typically incomplete at these stages. The resulting uncertainty must be accounted for in the decision-making process. This paper proposes a method for estimating the environmental impact of a product's life cycle and the associated degree of uncertainty of that impact using information generated during the design process. Total impact is estimated based on aggregation of individual product life cycle processes impacts. Uncertainty estimation is based on assessing the mismatch between the information required and the information available about the product life cycle in each uncertainty category, as well as their integration. The method is evaluated using pre-defined scenarios with varying uncertainty. DOI: 10.1115/1.4002163]

Solar energy decision support system

Energy plays a prominent role in human society. As a result of technological and industrial development,the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels.Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS)would help in estimating solar energy potential considering the region’s energy requirement.This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in time and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision making.

Combined toxicity of two crystalline phases (anatase and rutile) of Titania nanoparticles towards freshwater microalgae: Chlorella sp

In view of the increasing usage of anatase and rutile crystalline phases of titania NPs in the consumer products, their entry into the aquatic environment may pose a serious risk to the ecosystem. In the present study, the possible toxic impact of anatase and rutile nanoparticles (individually and in binary mixture) was investigated using freshwater microalgae, Chlorella sp. at low exposure concentrations (0.25, 0.5 and 1 mg/L) in freshwater medium under UV irradiation. Reduction of cell viability as well as a reduction in chlorophyll content were observed due to the presence of NPs. An antagonistic effect was noted at certain concentrations of binary mixture such as (0.25, 0.25), (0.25, 0.5), and (0.5, 0.5) mg/L, and an additive effect for the other combinations, (0.25, 1), (0.5, 0.25), (0.5, 1), (1, 0.25), (1, 0.5), and (1, 1) mg/L. The hydrodynamic size analyses in the test medium revealed that rutile NPs were more stable in lake water than the anatase and binary mixtures at 6 h, the sizes of anatase (1 mg/L), rutile NPs (1 mg/L), and binary mixture (1, 1 mg/L) were 948.83 +/- 35.01 nm, 555.74 +/- 19.93 nm, and 1620.24 +/- 237.87 nm, respectively]. The generation of oxidative stress was found to be strongly dependent on the crystallinity of the nanoparticles. The transmission electron microscopic images revealed damages in the nucleus and cell membrane of algal cells due to the interaction of anatase NPs, whereas rutile NPs were found to cause chloroplast and internal organelle damages. Mis-shaped chloroplasts, lack of nucleus, and starch-pyrenoid complex were noted in binary-treated cells. The findings from the current study may facilitate the environmental risk assessment of titania NPs in an aquatic ecosystem. (C) 2015 Elsevier B.V. All rights reserved.