Promoting e-mobility in India: challenges,framework, and future roadmap

The purpose of the research is to identify the critical challenges that are impeding the adoption of e-mobility in India. It also aims to give a roadmap how to address these challenges while taking into considerations concerns of all the relevant stakeholders. Based on an in-depth literature review, an exploratory research design is employed to delve deep into various aspects of e-mobility. This is followed by a three-phase Delphi technique to identify and rate the e-mobility challenges in the Indian context. The study successfully identifies four different categories of challenges and proposes integrative framework for e-mobility. Further, the research goes on to lay out the future roadmap for mass adoption of electric vehicles (EVs) in India. The research is novel in terms of presenting a holistic viewpoint on e-mobility in India. Its originality lies in identifying the major inhibitors obstructing EVs adoption in India and then suggesting the roadmap how to overcome these impediments for mass adoption of e-mobility.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

Combined influence of food level and inoculation density on competition between <Emphasis Type="Italic">Anuraeopsis fissa</Emphasis> and <Emphasis Type="Italic">Brachionus patulus</Emphasis> or <Emphasis Type="Italic">Brachionus macracanthus</Emphasis> (Rotifera: Brachionidae)

We tested separately the effect of two taxonomically related rotifers (B. patulus and B. macracanthus) on the population dynamics of another species (A. fissa) at low (0.5 ×10 ⁶) and high food levels (1.5 × 10⁶ cells/ml of Chlorella vulgaris) using different inoculation densities (0–100%). We also quantified the impact of A. fissa on the two brachionid species. Regardless of the presence of the competing species, an increase in the availability of food led to increase in the abundances of the three rotifers. The population growth of B. patulus, B. macracanthus, or A. fissa was affected negatively when cultured together with another species. An increase in the initial density of any one of the competing species became advantageous to maintain a certain population size. At a low algal food level, B. patulus was able to suppress A. fissa more strongly than B. macracanthus. On the other hand, at a high food level, B. macracanthus suppressed the population of A. fissa more strongly than B. patulus. Peak population densities for A. fissa varied from about 150 to 1000 ind./ml, depending on food density and the presence of competitors. The rate of population increase (r) of A. fissa, B. patulus, and B. macracanthus increased with an increase in food availability but decreased with increasing initial density of the competitor. Both Brachionus spp. experienced negative growth rates in the presence of A. fissa, especially at a high initial density of the latter. Published in Russian in Ekologiya, 2007, Vol. 38, No. 5, pp. 381–390. The article was submitted by the authors in English.     

Assessment of the natural-cultural resources in Çanakkale for nature-based tourism

While the world is going into different tourism expectations, the tourism understanding in Turkey is defined as tourism in the sea-sand-sun triangle. However, it is possible to contribute to the income and local development of the indigenous people by developing nature-based tourism. Besides, with the sustainable use and preservation of the natural-cultural assets, the damage of the traditional tourism industry on the natural and cultural environment could be reduced. In this study, it is aimed to bring up the nature-based tourism concept in Çanakkale by evaluating the nature-based tourism industry in the general of Turkey and assessing the natural-cultural resources that Çanakkale comprehends. The most important areas that have a nature-based tourism potential in Çanakkale and the tourism activities that are most suitable for these areas have been determined.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

Barriers Beyond the Partners: Bureaucratic and Political Constraints to Implementing Joint Forest Management in Tamil Nadu,India

Whereas past research has treated co-management of common pool resources as if villagers and project implementing authorities were the only relevant actors, numerous external factors beyond the control of these two partners create barriers to successful co-management. This paper draws on discussions with Forest Department officials to examine the influence of these forces on the outcomes of Joint Forest Management (JFM) in Tamil Nadu, India. An empirical inquiry into the operational aspects of JFM indicates the important roles of political parties, powerful people, and other state institutions and functionaries as well as the flow of foreign funding. Further, the strong demand by local people for socio-economic development interventions as opposed to improvement of degraded forests belittles the role of the Forest Department relative to other departments. Numerous other conditioning factors and relationships are explored. The authors call for reforms in public governance to allow better participation of all the actors involved for this participatory management approach to succeed and sustain.