Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
6 results
Search Results
Item A Review of the Green Climate Fund and Its Implications on Sustainable Development Goals for Developing Countries(Springer Science and Business Media Deutschland GmbH, 2025) Datta, K.; Jena, P.R.The Green Climate Fund (GCF), established within the United Nations Framework Convention on Climate Change (UNFCC), is a pivotal force in addressing climate change mitigation and adaptation. As climate change worsens into a worldwide disaster, the need to address its consequences gets more urgent. In response, the GCF emerges, as one of the primary climate finance mechanisms, providing a solid platform for mobilizing climate finance and facilitating transformative projects in developing nations to help them address climate-related concerns. Our systematic literature review rigorously examines the GCF’s global impact by delving into its organizational structure, funding mechanisms, and project efficacy. Employing the PRISMA methodology, we meticulously evaluate 39 peer-reviewed articles from Scopus. This review enriches the understanding of the GCF’s central role in global climate finance and sustainability, its contributions, and the challenges it faces. Our analysis reveals that the GCF demonstrates potential in balancing mitigation and adaptation through innovative approaches, including private sector engagement and equitable fund distribution. However, issues persist regarding adaptation finance accessibility for vulnerable states. To enhance effectiveness, we advocate for increased investment in decentralized, community-led solutions aligned with long-term development goals. A probable shortfall in meeting mitigation targets outlined in the Copenhagen Agreements, emphasizing the urgent need for increased financial resources. Diversifying funding sources and improving transparency are crucial for effective climate financing. This study provides vital insights to guide the GCF’s evolution and improve its efficacy in addressing climate change while advancing sustainable development globally. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item Impact of climate change on crop yields: Evidence from irrigated and dry land cultivation in semi-arid region of India(L and H Scientific Publishing, LLC, 2020) Kalli, R.; Jena, P.R.With population pressure constantly growing in India the crop productivity is struggling hard to catch up. Erratic rainfall and steady rise in temperature create widely uncertain outcomes for the farming communities. Against this backdrop, the present study has used a climate dataset constructed at a finer spatial level from a southern Indian state namely Karnataka to analyze the yield response of rice and maize crops to climate change. Using a time period from 1992 to 2012, a panel dataset has been made at the district level. The fixed effect regression results show that rice and maize productivity has been impacted adversely due to a steady rise in temperature in the state. The extent of damage is found to be 7% to 10%. Further, the study has also probed the role of irrigation as a climate adaptation strategy and has found out that adverse yield impact is reduced in the presence of irrigation. These findings provide some specific directions for policy framing to curb yield damage arising from climate variability. © 2020 L&H Scientific Publishing, LLC.Item Forecasting the CO2 emissions at the global level: A multilayer artificial neural network modelling(MDPI, 2021) Jena, P.R.; Managi, S.; Majhi, B.Better accuracy in short?term forecasting is required for intermediate planning for the national target to reduce CO2 emissions. High stake climate change conventions need accurate predictions of the future emission growth path of the participating countries to make informed decisions. The current study forecasts the CO2 emissions of the 17 key emitting countries. Unlike previous studies where linear statistical modeling is used to forecast the emissions, we develop a multilayer artificial neural network model to forecast the emissions. This model is a dynamic nonlinear model that helps to obtain optimal weights for the predictors with a high level of prediction accuracy. The model uses the gross domestic product (GDP), urban population ratio, and trade openness, as predictors for CO2 emissions. We observe an average of 96% prediction accuracy among the 17 countries which is much higher than the accuracy of the previous models. Using the optimal weights and available input data the forecasting of CO2 emissions is undertaken. The results show that high emitting countries, such as China, India, Iran, Indonesia, and Saudi Arabia are expected to increase their emissions in the near future. Currently, low emitting countries, such as Brazil, South Africa, Turkey, and South Korea will also tread on a high emission growth path. On the other hand, the USA, Japan, UK, France, Italy, Australia, and Canada will continuously reduce their emissions. These findings will help the countries to engage in climate mitigation and adaptation negotiations. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Item Combining agriculture, social and climate indicators to classify vulnerable regions in the Indian semi-arid region(IWA Publishing, 2022) Kalli, R.; Jena, P.R.Climate change vulnerability is highly counter-productive for agriculture among the arid and semi-arid regions. The study constructs the agriculture vulnerability index for Karnataka, a south Indian state. The state has faced frequent climate-related shocks in the last decade. The district-wise vulnerability index is estimated using longitudinal data considering exposure, sensitivity and adaptive capacity as sub-indices. The results show that the districts in the north interior region of Karnataka are highly vulnerable to the climate change followed by the districts in the south interior and coastal regions. There is an urgent need to prioritize the most vulnerable districts while formulating the development policies to minimize the risk of climate change on agriculture. Specific technical knowledge and support need to be made available to the farmers for informative climate resilience action. © 2022 The Authors.Item How large is the farm income loss due to climate change? Evidence from India(Emerald Group Holdings Ltd., 2022) Kalli, R.; Jena, P.R.Purpose: Climate change is the most concerned issue in the global economy; increase in climate variability and uncertain climate events have caused distress in agriculture sector. The study estimates economic effect of climate change on agriculture income for the Indian state of Karnataka. The study reports the difference of result from past studies, where estimates from present study indicate higher negative impact of rise in temperature. Design/methodology/approach: Fixed effect panel regression method was used to examine change in agriculture revenue to climate response. Climate variables were classified based on the crop calendar to capture the damage caused by climate change. The authors use fine scale climate data set constructed at regional context for 20 districts and time period of 21 years (1992–2012). Findings: The result showed that with 1-degree rise in average maximum temperature, the revenue declined by 17–21%. The prediction behavior of the different models was evaluated using out-of-sample forecast approach by training and testing historical data set. Originality/value: The study adopts recent data sets on agriculture and the updated climate variables to estimate the climate change impact on agriculture. The study yields the better results when compared to previous traditional models applied in literature in Indian context. The study further evaluates the prediction behavior and robustness of the estimated models using out-of-sample forecast method. © 2022, Emerald Publishing Limited.Item Effect of irrigation on farm efficiency in tribal villages of Eastern India(Elsevier B.V., 2024) Kalli, R.; Jena, P.R.; Timilsina, R.R.; Rahut, D.B.; Sonobe, T.Irrigation is an important adaptation strategy to cope with climate change which reduces vulnerability to water stress and improves crop productivity to feed millions. There is evidence of crop yield stagnation in many developing countries, and irrigation efficiency is claimed to increase crop productivity. Therefore, this paper uses data envelopment analysis to evaluate the farmer's productivity through technical efficiency (TE), i.e., the relationship between resource inputs and outputs of 513 paddy farmers in Eastern India. The results show that the farms are, on average operating at 14% TE, leaving a considerable scope to improve up to 86% to reach the optimal level. A significant difference is observed between irrigated and rain-fed paddy farmers, such that10% of the irrigated farms achieved efficiency scores over 40% and only 2% of rain-fed farms achieved the same. The tobit and beta fit regression models are estimated to find out the factors that influence the TE. Both surface water and groundwater sources of irrigation are used as predictors, along with other socio-demographic factors. Access to surface water irrigation is identified to be a significant determinant of farm efficiency, however, surface water irrigation, such as canal irrigation, is accessible only to farmers living on plain land. Farmers living on highlands need to explore other sources of irrigation practices, such as drip and sprinkler, that can increase TE and farm productivity. Therefore, this paper calls for government intervention to provide extensive training and facilities for these micro-irrigation practices. © 2023 The Authors