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Climate-induced increase in temperature and rainfall variability severely threaten the agricultural sector and food security in the Indian state of Odisha. Climate-smart agricultural (CSA) practices, such as crop rotation and integrated soil management, help farmers adapt to climate risk and contribute to a reduction in greenhouse gas (GHG) emissions. Therefore, this paper examines the impact of CSA practices on yield and income in vulnerable semi-arid districts of Odisha—Balangir, Kendrapara, and Mayurbhanj. We use primary survey data from 494 households collected in 2019–2020, using a multi-stage stratified sampling approach and structured questionnaire. Propensity score matching (PSM) and the two-stage least square method (2SLS) have been used to analyze the impact of CSA on income and productivity. Two instrument variables, namely distance to the extension office and percentage of adopters in a village, are used to control self-selection bias and endogeneity in our model. Both models show a positive and significant impact of the adoption of CSA on farmers’ productivity and income. The study sheds light on the significant contribution of CSA practices in fostering sustainable income growth amid environmental challenges. Overall, our results suggest that small and marginal farmers of Eastern India, a highly environmentally vulnerable area, can significantly improve their income and productivity by adopting CSA technology. Hence, policymakers should scale the adoption of CSA technology through effective extension programs. [ABSTRACT FROM AUTHOR]

In order to supply wholesome food and slow down climate change, this paper covers India’s agrogeological resources. The soils are the result of the weathering of rocks with ages ranging from more than a billion years to the most recent Holocene. Because they are severely deficient in vital minerals, many soils have low agricultural production. In addition to helping to fertilise soils, reduce atmospheric carbon dioxide levels, and stop the acidification of the Indian Ocean, rock powder weathering and biochar have significant positive effects on the productivity of Indian soils. The nutrient density of food is also increased which improves health and lowers the demand for and cost of medical treatment. Remineralization may help to solve Indian soil issues including soil infertility and texture. To improve soil and plant nutrition, dusts of carbonate, basic, and ultrabasic rocks are readily available at mining sites in India combined with biochar. Adding different grain sizes to the soil helps improve the texture of the soil. Silicate and carbonate rock powders enhance soil structure by promoting the creation of soil organic matter and fostering the growth of advantageous microbial communities. These processes offer a low-cost method of remineralizing soils with important macro- and micronutrients. For each significant soil/crop/climate system, an optimised application of India’s rock powder resources must be determined through a national research and development programme. India’s capacity to adapt to the mounting challenges of population expansion and climate change would be significantly improved by the findings of this study programme. [ABSTRACT FROM AUTHOR]

An effort is made to understand the role of El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events on the malaria transmission intensity over India during the period 1951–2020 (70 years) with the help of a realistically simulated dynamical malaria model. The results suggest that the La Nina years pose a greater threat of malaria disease, especially in the densely populated Indian states. During El Nino years, the malaria transmission intensity and distribution over India greatly reduce, except in the regions such as Orissa, Chhattisgarh, Jharkhand, Western Ghats, parts of Madhya Pradesh, and Andhra Pradesh. It is found that in the positive IOD years, the malaria transmission intensity increases (decreases) over the entire central Indian region and along coastal regions of Tamil Nadu and Kerala (southern peninsular states of India and northeast India). An almost opposite behavior is seen during the negative IOD years. The malaria transmission variability over India is becoming increasingly heterogeneous in recent decades during the El Nino and La Nina years as a result of global warming. The period of 1986–2020 witnessed a substantial decrease (increase) in the malaria transmission intensity during the positive (negative) IOD years, except for a few regions of India. The implications of the results presented in the paper linking the ENSO and IOD signals with the intensity and distribution of malaria over India in a warming world are enormous, especially for the densely populated Indian states. [ABSTRACT FROM AUTHOR]

India's economy is rooted in agriculture, and the majority of the farmers, being smallholders, are highly exposed to the adversities associated with climate change. It has been argued by several researchers that perceiving climate change is a pre-condition for the adoption of adaptation strategies to reduce vulnerabilities. In this regard, studies are limited to explore the question 'is the perceptions of changing climate primarily motivate the smallholders to take adaptation actions?' In this nexus, the present paper seeks to understand the linkages between smallholders' climate change perception and the changes in their farming practices. The study was conducted in the seven villages of Sub-Himalayan West Bengal, India, using participatory rural appraisal (PRA) tools. Key results show, (1) respondents perceived increased warming and decreased precipitation in accordance with the scientific analysis; (2) abundance of groundwater, misconceptions and lack of awareness shaped respondents' agricultural risk perception, and despite decreasing precipitation, water management appeared less risky (3) incorporation of irrigation, diversification towards high valued and high yielding crops, as well as farm mechanizations were the major changes in the farming practices; and, (4) except water management, rest of the changes were not necessarily made to adapt with climate change instead to increase crop yield and profit. It is noticed that the changes in farming practices perhaps made the farmers unconsciously adapted to climate change. Still, a prolonged continuation of some of those practices may lead to maladaptation. In this regard, we have given direction towards necessary policy formulation and future research to achieve sustainability. [ABSTRACT FROM AUTHOR]

The paper contributes to the growing literature highlighting the significance of assessing risk and vulnerability, micro-level perceptions and adaptation decision-making in building resilience of farm communities to climate change in dryland region of India. To select a region for grassroots enquiry, spatial differential in risk to climate change was assessed in Rajasthan, using IPCC AR5 framework. Among the highly vulnerable and risky districts, Bikaner district was selected for elicitation of micro-level imperatives. Rising atmospheric temperature, inter-seasonal displacements of rainfall and recurrence of extreme events were perceived by the farmers resulting in resource degradation, production risks and erosion of households' socio-economic dynamics. As risk preventive measures, suitable adjustment in agricultural practices, natural resource management, shift to off-farm activities and other relief measures were adopted by the farmers. Farmer's choice of adaptation was influenced by several climatic, socio-economic and infrastructural & institutional factors in varying degree. Moreover, several financial, economic, infrastructural and informational bottlenecks to adaptations were reported during household survey and FGDs. The results suggest that capturing grassroots evidence is crucial for directing locally tailored adaptation strategies, along with the improving deficiencies in the developmental pathways for climate-resilient agriculture. [ABSTRACT FROM AUTHOR]

The increasing concentrations of greenhouse gas emissions in the atmosphere along with the increasing temperatures exacerbate the situation, making it one of the major issues for food security. This research aims to explore the effects of climate change on food production in India. More specifically, this study investigates the impact of temperature, rainfall, CO2, methane, and N2O emissions and energy use on food production using a time spanning from 1990 to 2019 and explores the major critical factors impacting food production in India. The study used autoregressive distributed (ARDL) estimates for long-run and short-run cointegration. The empirical results demonstrated that energy use, rainfall, and methane emissions improve food productivity, whereas temperature and N2O emissions undermine food production in the long run and short run. However, the results revealed that CO2 emissions do not affect food production. Additionally, we used the dynamic ordinal least squared approach to verify the robustness of ARDL results. The results also demonstrate that N2O emissions and temperature are critical determinants of food production, indicating that a rise in temperature and N2O emissions significantly reduces food production in India. On the other hand, the findings show that methane emissions and rainfall significantly increase food production with a coefficient of 0.19 and 0.059, respectively. The most important adaptation strategies that should be considered due to climate change are reducing greenhouse gas emissions, expanding renewable energy investment, and adopting new technologies to combat environmental challenges. [ABSTRACT FROM AUTHOR]

Indian farmers are vulnerable to changing climate with unpredictable rainfall distribution, rising temperature, and complex socioeconomic conditions. The present study aims to assess livelihood vulnerability of farmers in two regions of the most populous State of Uttar Pradesh namely Bundelkhand and Central region. By using multistage random sampling technique, a total of 480 samples from 16 villages, 8 development blocks, 4 districts, and 2 regions were selected to elicit grass-root information on farmers' perception of climate change, their sensitivity and adaptive capacity to changing climate, and determinants of livelihood vulnerability. Further, this study has adopted methodology mentioned in the Intergovernmental Panel on Climate Change's fourth Assessment Report for the development of climate vulnerability index. The results show that farmers in Jhansi district were highly vulnerable to changing climate, while farmers in Barabanki district were relatively less vulnerable. The elevated degree of vulnerability to livelihood in Jhansi district attributed to its comparatively higher exposure and sensitivity to climatic change. The Binary Logistic Regression results show that illiterate farmers are relatively more vulnerable than literate farmers. On the contrary, higher income, assured irrigation, the use of certified seeds, and crop insurance are negatively associated with the LVI. In other words, farmers who have income from non-farm sources, use certified and recommended seed varieties, and avail themselves of crop insurance are relatively less vulnerable to climate change than those who do not have the aforesaid facilities. Hence, the present study suggests that farmers, must adapt to climate change to reduce its negative impact and reap the benefits of adaptation which can be achieved through capacity building, skill development (i.e., use of ultra-modern techniques), and capacity to strengthen the farmers' ability to adapt. Further, there is also a need to sensitize government officials on the dangers of climate change and to provide appropriate technical support to farmers for their adaptation. [ABSTRACT FROM AUTHOR]

Climate change, food insecurity, and epidemics affect all population sub-groups. This article reviews the current evidence on the relationships between climate change, food insecurity, and the COVID-19 pandemic in the context of newborn and child health. The authors searched Medline, PsycINFO, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Scopus databases using a structured approach. Food insecurity, particularly from the lack of food access and affordability, increased amidst the COVID-19 pandemic. Factors such as nationwide lockdowns, increased unemployment and financial instability, and school closures precipitated food insecurity. Children born to immigrant parents, belonging to racial and ethnic minority groupsor low-income families, and those who were Autistic were highly vulnerable. Climate change also contributes to food insecurity, with increased susceptibility among neonates and children compared to adults. There is a need for further research on the relationships between climate-linked exposures and COVID-19 transmission. Multisectoral collaborations and multilevel interventions are necessary to mobilize local and national resources for mitigating and preventing the synergistic effects of the three concurrent crises. The evidence-informed discourse on this topic can help in improved preparedness and response for future outbreaks and epidemics. The policy interventions for newborn and child survival need to factor in climate change, food insecurity, and emerging diseases. [ABSTRACT FROM AUTHOR]

We investigate the extent to which climate change will result in insurable and uninsurable losses for farmers in India. Changes in temperature and precipitation patterns may increase the volatility of farmers' yields, leading to rising but insurable risk. These changes may also reduce the expected yield in an 'average year', causing uninsurable reductions in the returns to farming. We use a multi-run climate model to predict the future distribution of potential yields at the district level for sixteen major crops. For the average district, we project a sharp decline in expected agricultural revenue, but small shifts in volatility. This is because weather draws resulting in extremely low agricultural returns—what had once been 1-in-100-year events—are predicted to become the norm by the end of the century. Our projections therefore imply substantial uninsurable losses from the changing climate for Indian farmers. [ABSTRACT FROM AUTHOR]

The rapidly changing climatic conditions are adversely impacting the Indian agricultural sector. Farmers are frequently seen adopting several adaptation measures, which are neither equally efficient nor mutually exclusive. Based on the primary data collected from 300 farming households of the Indian Eastern Himalayan foothills, the present study attempts to examine the efficiency of local farmers' adaptation by developing indices combining the feasibility, effectiveness, and sustainability of the adaptation measures with the scale of actual adoption. Further, by employing multiple linear regression, the study analyzes the internal (psychological) and external (physical and socio-economic) factors influencing higher scores of these indices. Results show that local farmers are well aware of climate change and are responding through implementing at least one and up to seven adaptation measures. Farmers preferred agroforestry, a shift from cereals to low water-intensive commercials, irrigation, and intensification of winter crops as the most efficient. There was, however, a misalignment between the perceived efficiency of adaptation measures and their scale of adoption. Farmers' perceptions of pest infestation, satisfaction with farming, soil characteristics, farm size, remittances, and access to credit were found to be positively and significantly influencing the adaptation indices, while open-mindedness toward changing farming practices and crop-raiding by elephants were found to be negatively and significantly associated with adaptation indices. Lastly, the study made relevant recommendations for improving farmers' efficiency in adopting appropriate adaptation measures and strengthening the "State Action Plan on Climate Change". [ABSTRACT FROM AUTHOR]

In the twenty-first century, land use changes, massive expansion of urbanization, population growth, economic crisis, environmental issues are the main challenges of developing countries. Climate change and its effects on human health are the major concerns for the different age groups of the population. The study delved into the causes associated with climate change and climate change-related myriad health impacts on the study population. This study has used a concurrent mixed-method research design. The quantitative and qualitative data were collected from the study area. Perception and knowledge about climate change and its consequences on health was based on a quantitative approach of Bi-variate analysis and Chi-Square test and Fisher's exact test; this study also used qualitative data analysis. Study results show that most respondents pointed out that temperature increases throughout the year and 90% of the respondents reported that rainfall pattern has also changed. Similarly, 65% of respondents agreed in their statements in favour of increased natural calamities in this region. The study findings show that more than 40% of population faces dengue fever and 10% of people also suffer from malaria. More than 60% of the urban population suffered from asthma. Similarly, more than 70% of the population also got affected by cold and cough due to weather variability. Focus Group Discussion (FGD) and In-depth interviews of the participants also affirmed the fact that climate variability induced diseases and health problems in Kolkata Metropolitan areas. Urban residents perceived that excessive urbanization contributes to the changes in regional climate and human health. The study will encourage the policy-makers and local government to mitigate adverse health effects driven by climate change in the Kolkata Metropolitan Region. [ABSTRACT FROM AUTHOR]

Among all the natural and human forces acting on the land surface and shaping Landuse and Landcover (LULC), anthropogenic actions have been a dominant force, which has caused dramatic changes to the LULC throughout the globe. The situation of Kashmir Himalayas is no different. LULC changes are rampant and a cause for several environmental problems in the region. Under the changing climate regime and ever-growing anthropogenic pressures, the long-term analysis of LULC has become a necessity. The present study attempts to track the LULC change through a systematic review of literature, to analyse and discuss the trends and patterns of LULC dynamics in Kashmir Valley. The findings from several studies concerning the region that have applied geospatial technology to detect changes in LULC reveal that the changes have occurred at a faster pace in the last 20 years. Major landuse classes such as agriculture, forest, water, snow, and glaciers have shown a declining trend, in comparison to horticulture and built-up that has shown an increasing trend. These changes in LULC have far-reaching impact on the economy of the region. Climate change, population growth, economic compulsion, and unplanned development among others are the major causes /drivers of intensified LULC changes in the region. [ABSTRACT FROM AUTHOR]

Climate change and indebtedness have been repeatedly highlighted as major causes of distress for rural households in India. However, despite the close connection between climate conditions and rural livelihoods, there has been little attempt to systematically examine the association between the two. To address this gap, we combine national-level longitudinal data from IHDS, MERRA-2, and the Indian Ministry of Agriculture to study the impact of climate anomalies on household indebtedness across rural India. Using a multilevel longitudinal approach that accounts for potential confounders at household, village, and district levels, we find pervasive effects of season-specific, 5-year climate anomalies on multiple dimensions of household debt, particularly in arid and semi-arid areas. Most notably, temperature anomalies in the winter cropping season in arid and semi-arid areas are associated with increasing household indebtedness. We further find that climate change interacts with existing socioeconomic differences—caste and landholding in particular—to deepen both the size and the depth of indebtedness for rural households. [ABSTRACT FROM AUTHOR]

Velocity of climate change (VoCC), also known as climate velocity, has been widely used as a climate change metric to inform the past and projected impacts of climate change on biodiversity globally. It is a generalized climate-landscape metric that does not involve any biological assumptions and is beneficial for regions with a lack of extensive species presence/absence data. In the current study, the contemporary (1951–2018) climate velocity for India at the annual and seasonal timescales has been assessed using observational and reanalysis datasets for mean near-surface temperature. The associated coverage uncertainty and influence of the resolutions of the datasets have been identified and an attempt has been made to address them. The central, north-western, and southern peninsular regions, along with some parts of the Indo-Gangetic plains, were identified as having experienced the highest annual climate velocities, in the range of 3–8 km/year in the last five decades. The velocities in the post-monsoon (October and November) were found to be the highest (> 4 km/year) as compared to the other seasons owing to the higher temporal, lower spatial gradients and regional dynamics. Finer resolution dataset presents a more realistic estimate of climate velocities owing to better representation of local topographical features and associated microclimate. [ABSTRACT FROM AUTHOR]

Statistical crop models, using observational data, are widely used to analyze and predict the impact of climate change on crop yields. But choices in model building can drastically influence the outcomes. Using India as a case study, we built multiple crop models (rice, wheat, and pearl millet) with different climate variables: from the simplest ones containing just space and time dummy variables, to those with seasonal mean temperature and total precipitation, to highly complex ones that accounted for within-season climate variability. We observe minimal improvement in overall model performance with increasing model complexity using standard accuracy metrics like the root mean square error and adjusted R2, suggesting the simplest models, also the most parsimonious, are often the best. However, we find that simpler models, such as those including only seasonal climate variables, fail to fully capture impacts of climate change and extreme events as they can confound the influence of climate on crop yields with space and time. Automated model and variable selection based on parsimony principles can produce predictions that are not fit for purpose. Statistical models for estimating the impacts of climate change on crop yields should therefore be based on a conjunctive use of domain theory (for example plant physiology) with accuracy and performance metrics. [ABSTRACT FROM AUTHOR]

Does deprivation of assets imply an increased likelihood of vulnerability to climate change? Our study attempts to answer this question by analyzing the multidimensional poverty in rural Bihar, followed by deciphering the link between the developed poverty index and vulnerability of agriculture to climate change. Vulnerability index used in the present study was developed under the National Initiative on Climate Resilient Agriculture (NICRA) by the Government of India. As most people in rural areas and those dependent on rural based livelihood activities (such as agriculture, forestry and livestock) are more vulnerable to vagaries of weather, related attributes (i.e. land ownership, livestock ownership as well as access to agriculture equipments) are included in our analysis. We found that the extent of multidimensional poverty in rural Bihar was 0.278 indicating that rural poor were deprived in 27.8 percent of the total potential deprivations that they could experience overall. It varied from 0.19 to 0.39 across districts. The findings highlight that a majority of the population were deprived in living standard dimension, followed by health and education dimensions. Further, the districts where the multidimensional poverty was high were also more vulnerable to climate change. The study advocates for formulation of district specific programs that can target major contributing factors resulting in reducing the extent of multidimensional poverty and vulnerability. [ABSTRACT FROM AUTHOR]

Changes in precipitation pattern can lead to widespread impacts across natural and human systems. This study assesses precipitation variability as well as anthropogenic and natural factors responsible for the precipitation variability over India in the twentieth and twenty-first centuries using the Coupled Model Intercomparison Project (CMIP5) and observational data sets. We specifically quantify the impact of natural (volcanic and solar radiation) (NAT), greenhouse gas (GHG), anthropogenic aerosol (AA), and land use (LU) forcings on precipitation changes over India. In the observational record, a decrease in precipitation is observed during monsoon and winter seasons, whereas an increase is noticed in pre- and post-monsoon seasons. These observed changes are likely dominated by changes to GHGs and a reduction in AA during the twentieth century compared to those of the LU and NAT forcings. Anthropogenic aerosol plays a dominant role in reducing rainfall in the summer monsoon, leading to drying trends over the second half of the twentieth century in India. The projected simulations indicate an increasing trend during the twenty-first century. The temporal and spatial variability of precipitation displays substantial changes over India during different seasons at different periods under the Representative Concentration Pathway (RCP) 2.6 and 8.5 emission scenarios. Overall, model simulations based on RCP 8.5 show increases in future precipitation throughout the twenty-first century over India. [ABSTRACT FROM AUTHOR]

India is predominantly a fossil fuel-intensive South Asian country that has traditionally settled for higher economic gains at the expense of lower environmental quality. However, in the contemporary era, it has become essential for India to come up with viable solutions that can enable the nation to transform its economy into a low-carbon one. Although replacing fossil fuel use with renewable energy sources is assumed to be the ideal pathway to decarbonizing the Indian economy, achieving this clean energy transition involves a long-term process. Thus, the Indian government should rather consider adoption of interim solutions to the environmental pollution problems faced by the nation. Against this backdrop, this study looks at whether enhancing the consumption level of liquefied petroleum gas, a relatively cleaner fossil fuel, can help India reduce its carbon dioxide emissions figures and attain environmentally sustainable economic growth. The econometric analysis is designed as per the theoretical framework of the environmental Kuznets curve hypothesis whereby the effects of economic growth on carbon dioxide emissions are examined controlling for liquefied petroleum gas consumption in the context of India between 1990 and 2018. Based on the findings from the autoregressive distributed lag model bounds test analysis, it is witnessed that there are long-run cointegrating relationships among per capita levels of carbon dioxide emissions, real gross domestic product, and liquefied petroleum gas consumption of India. Besides, the environmental Kuznets curve hypothesis is found to be valid only in the short run; however, it does not sustain in the long run since the economic growth-carbon dioxide emissions nexus is observed to follow a U-shaped relationship in the long run. Moreover, higher liquefied petroleum gas consumption is found to boost carbon dioxide emissions in the short run while reducing it in the long run. Furthermore, the findings from the wavelet and partial wavelet coherence and causality analyses also advocate in favor of promoting the use of liquefied petroleum gas in India in order to significantly curb the energy use-related carbon dioxide emission figures of the nation. Hence, considering these important findings, this study recommends that the Indian government should design policies for augmenting liquefied petroleum gas into the national energy mix and also adopt relevant green economic growth strategies in order to facilitate environmentally-sustainable growth of its economy. [ABSTRACT FROM AUTHOR]

In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991–2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems. [ABSTRACT FROM AUTHOR]

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965–2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals. [ABSTRACT FROM AUTHOR]