Mitigation and Adaptation Strategies for Global Change最新文献

The Chinese government has proposed new standards for the rural energy consumption structure in the context of rural regeneration. In the case where traditional energy still dominates the rural energy consumption structure, it is critical to investigate the key factors influencing rural energy transformation against the backdrop of rural revitalization in order to promote the transition from traditional to clean energy in rural areas. To identify the influential aspects, this paper conducts a literature analysis and an expert evaluation. Second, the decision-making experiment and evaluation laboratory (DEMATEL) technique is improved by studying the 24 influencing elements and their hierarchical relationships using the type-2 interval fuzzy number (IT2TrFN) and the maximum mean-decreasing entropy (MMDE) approach. A novel multi-criteria decision-making (MCDM) model is developed to give a theoretical foundation and recommendations for decision-making in areas such as rural energy policy formulation. The following are the primary conclusions: Energy technology service workers are the most profound factors, with the most driving force and dependence, and have the greatest impact on other factors. Environmental attitudes, perceptions, and societal green expectations are highly dependent and low-driver characteristics that are easily influenced by other factors. Based on this, related recommendations are made to encourage the advancement of rural clean energy as a replacement for traditional energy.

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.

Climate stabilization is crucial for restabilizing the Earth system but should not undermine biosphere integrity, a second pillar of Earth system functioning. This is of particular concern if it is to be achieved through biomass-based negative emission (NE) technologies that compete for land with food production and ecosystem protection. We assess the NE contribution of land- and calorie-neutral pyrogenic carbon capture and storage (LCN-PyCCS) facilitated by biochar-based fertilization, which sequesters carbon and reduces land demand by increasing crop yields. Applying the global biosphere model LPJmL with an enhanced representation of fast-growing species for PyCCS feedstock production, we calculated a land-neutral global NE potential of 0.20–1.10 GtCO₂ year⁻¹ assuming 74% of the biochar carbon remaining in the soil after 100 years (for + 10% yield increase; no potential for + 5%; 0.61–1.88 GtCO₂ year⁻¹ for + 15%). The potential is primarily driven by the achievable yield increase and the management intensity of the biomass producing systems. NE production is estimated to be enhanced by + 200–270% if management intensity increases from a marginal to a moderate level. Furthermore, our results show sensitivity to process-specific biochar yields and carbon contents, producing a difference of + 40–75% between conservative assumptions and an optimized setting. Despite these challenges for making world-wide assumptions on LCN-PyCCS systems in modeling, our findings point to discrepancies between the large NE volumes calculated in demand-driven and economically optimized mitigation scenarios and the potentials from analyses focusing on supply-driven approaches that meet environmental and socioeconomic preconditions as delivered by LCN-PyCCS.

The Indo-Gangetic Plains represents one of South Asia’s most productive agricultural regions, yet it is highly vulnerable to climate change and requires the widespread adoption of Climate-Smart Agriculture. Although farmers understand the benefits of such technologies, financial constraints often undermine adoption. Using a case study from Haryana, we assess the opportunities and challenges aligned with the different pathways available for farmers to adopt and finance two capital-intensive technologies: laser land levelers and happy seeders. Our analysis uses unique data from Karnal, where stakeholders have partnered in Climate-Smart-Villages, and combines a household survey from 120 farmers, interviews, and focus group discussions with banks and cooperatives. Our results indicate adoption rates of 77% for laser land levelers and 52% for happy seeders, with only 7% and 21% of farmers owning the technologies, respectively. Hiring is highly preferred over purchase, mainly due to the flourishing of Custom-Hiring Centers, which are vital in driving large-scale implementation. We find that farmers prefer funding from family, savings, and moneylenders (indirect pathways) rather than from commercial banks (direct pathways) to get immediate access to credit and avoid bureaucratic procedures. Our study offers broader insights into the state of agricultural finance in India and adaptation to climate change and reveals that institutional innovations can enhance the financing of CSA technologies for smallholder farmers. Our findings have important implications for decision-makers seeking to streamline credit access for CSA machinery rental. Future research should focus on the efficacy of different finance channels and their causal impact on pathways for technology adoption.

Abstract

The Kenyan dairy sector has economic potential to improve the welfare of rural households. However, the availability of feed resources, an essential input in dairy production, remains a significant constraint and is exacerbated by the effects of climate change. Using a sample of 665 dairy farmers from selected counties, this study assessed the determinants and impact of adoption of climate-smart feeding practices on milk productivity and output, dairy milk commercialization, and dairy and household income. The multinomial endogenous switching regression was used to account for self-selection bias from observable and non-observable factors. The study identified human and social capital, resource endowment, dairy feeding systems, the source of information about feeding practices, and perceived characteristics of these practices as factors that influenced the likelihood of adopting climate-smart feeding practices. The uptake of climate-smart fodder and feed concentrates together significantly increased milk productivity and output and dairy income. The uptake of climate-smart feed concentrates singly also increased dairy milk commercialization and household income. To facilitate the uptake of climate-smart feeding practices, pluralistic extension systems should be strengthened, practices made available, knowledge about climate change enhanced, and practice-oriented learning adopted. Further, the adoption of both climate-smart fodder and feed concentrates should be emphasized for improved household welfare.

In the face of unprecedented challenges arising from climate change, Climate-Smart Agriculture (CSA) emerges as a holistic solution for South Asia, addressing adaptation, mitigation, and Sustainable Development Goals (SDGs). However, a substantial knowledge gap exists regarding the current status of CSA practices, the factors influencing their adoption, and the specific SDGs that benefit from such adoption. Within this context, this study undertakes a systematic review of the literature (n = 78) concerning the adoption of CSA practices in South Asia, primarily drawing from three scholarly databases, viz. Web of Science, Scopus, and ScienceDirect. The results show that the widely adopted CSA practices in South Asia are climate-resilient seeds, zero tillage, water conservation, rescheduling planting, crop diversification, soil conservation, and water harvesting, agroforestry. Several factors, such as socio-economic factors (e.g. education, livestock ownership, age, landholding size, and market access), institutional factors (e.g. information and communication technology, credit availability, input subsidies, agricultural training and demonstration, direct cash transfer, and crop insurance), and climatic factors (e.g. increasing temperature, floods and droughts, decrease in rainfall, and delays in rainfall), are the major driving forces behind the adoption of CSA in South Asia. Implications of CSAs have positive impacts primarily on SDG-1, SDG-2, SDG-3, SDG-5, SDG-6, SDG-7, SDG-12, and SDG-13. The findings of this study hold important policy implications for creating an enabling environment that supports the widespread adoption of CSA practices. Key recommendations encompass establishing specialised training centres for women and elderly farmers, leveraging ICT tools, fostering collaboration between small and medium enterprises and agricultural agents, and enhancing market linkages and value chains for CSA products.

Agricultural production is affected by the threats of climate change, such as changes in the frequency of extreme events (such as flood and drought), changes in rainfall patterns, and increased pest attacks and diseases. As a result, the farmers face huge socio-economic losses in the form of loss of lives, loss of cultivable lands, loss in crop yield, and loss to infrastructure. The smallholder farmers who primarily depend on rainfed agriculture for a living bear major crop losses and threats to food security due to climate change. In order to enable the farmers to cope with the challenges associated with climate change, climate-smart agricultural (CSA) practices were introduced. It must be noted that CSA practices depend on economic, environmental, and social attributes; hence, location-specific studies are required to identify the determinants of CSA adoption. The present study aims to identify the factors influencing smallholder farmers’ adoption of CSA strategies in the highly vulnerable Nagaon district of India. Our study has incorporated six forms of capital: physical capital, social capital, human capital, financial capital, natural capital, and institutional capital in its analytical framework. The influence of these capitals is examined on the farmers’ adoption decision. We use a mixed-method approach to conduct the analysis. A multivariate probit model is used for the quantitative analysis, and excerpts from focus group discussions are presented as qualitative information gathered from field surveys. Three unique variables are included in the present study: the use of agricultural applications by smallholder farmers, the application of indigenous technical knowledge, and access to government-provided seeds. Each of the three variables was found to be statistically significant. Further, the study found the variables under social capital, physical capital, and institutional capital to be critical determinants affecting CSA adoption by smallholder farmers.

Adoption of improved livestock breeds requires, as with other climate-smart agricultural (CSA) practices, upfront investments, which might be a significant barrier for smallholders. For this reason, the climate-smart village (CSV) approach not only includes CSA interventions, but also interventions to improve access to savings and credit among smallholders by means of a community-based approach. In this paper we study smallholders in CSVs in Kenya who were encouraged, among others, to adopt improved livestock breeds for crossbreeding with indigenous breeds to improve their resilience to climate change and variability. The farmers were also encouraged to become part of savings and credit groups to improve smallholder access to finance. The objective of this paper is thus to determine the (distributional) impact of CSVs on access to savings and credit and the adoption of improved CSA practices. Due to the as good as random selection of CSVs, we are able to estimate the treatment effects on the treated for the smallholders who decided to participate in the CSA intervention by means of a linear probability model. The analysis is based on a balanced panel of 118 farm households interviewed in 2017, 2019, and 2020. The main findings of this study are that the CSV intervention increased the adoption of improved livestock breeds. It also stimulated the membership of savings and credit groups which in turn stimulated the adoption of improved livestock breeds. These findings point to the importance of community-based savings and loan initiatives to mobilize finance among farmers enabling them to invest in CSA practices. Also, the introduction of improved breeds in CSVs has benefited especially the larger livestock owners. However, the availability of credit is found to have mitigated the concentration of improved livestock ownership since the diffusion of improved livestock in CSVs was somewhat more equitable than the (spontaneous) spill-over diffusion in the non-CSVs (reducing the Gini by 0.04).

This study reviews the literature published between 2013 and 2023 to comprehensively understand the consequences of adopting climate-smart agricultural (CSA) practices. We categorize the literature into three categories based on the scopes of climate-smart agriculture: (a) sustainably increase agricultural productivity and incomes; (b) adapt and build the resilience of people and agrifood systems to climate change; and (c) reduce or where possible, avoid greenhouse gas emissions. The review demonstrates that adopting CSA practices, in many instances, improves farm productivity and incomes. This increase manifests in increasing crop yields and productivity, income and profitability, and technical and resource use efficiency. Moreover, adopting CSA practices reinforces the resilience of farmers and agrifood systems by promoting food consumption, dietary diversity, and food security and mitigating production risks and vulnerabilities. Adopting CSA practices is environmentally feasible as it reduces greenhouse gas emissions and improves soil quality. An integrative strategy encompassing diverse CSA practices portends an optimized avenue to chart a trajectory towards agrifood systems fortified against climatic change.

Future configurations of the power system in the central region of the USA are dependent on relative costs of alternative power generation technologies, energy and environmental policies, and multiple climate-induced stresses. Higher demand in the summer months combined with compounding supply shocks in several power generation technologies can potentially cause a “perfect storm” leading to failure of the power system. Potential future climate stress must be incorporated in investment decisions and energy system planning and operation. We assess how projected future climate impacts on the power system would affect alternative pathways for the electricity sector considering a broad range of generation technologies and changes in demand. We calculate a “potential supply gap” metric for each pathway, system component, and sub-region of the US Heartland due to climate-induced effects on electricity demand and power generation. Potential supply gaps range from 5% in the North Central region under mild changes in climate to 21% in the Lakes-Mid Atlantic region under more severe climate change. We find increases in electricity demand to be more important in determining the size of the potential supply gap than stresses on power generation, while larger shares of renewables in the power system contribute to lower supply gaps. Our results provide a first step toward considering systemic climate impacts that may require changes in managing the grid or on potential additional capacity/reserves that may be needed.