Climate Mitigation Strategies Research Articles

Exploring CO2 storage potential in Lithuanian deep saline aquifers using digital rock volumes: a machine learning guided approach

The increasing significance of carbon capture, utilization and storage (CCUS) as a climate mitigation strategy has underscored the importance of accurately evaluating subsurface reservoirs for CO2 sequestration [1]. In this context, digital rock volumes, obtained through advanced imaging techniques such as micro-Xray computed tomography (MXCT), offer intricate insights into the porous and permeable structures of geological formations [2]. This study presents a comprehensive methodology for assessing CO2 storage viability within Lithuanian deep saline aquifers, namely Syderiai and Vaskai, by utilizing petrophysical properties estimated from digital rock volumes [3, 4]. These petrophysical properties were derived from core samples collected from these formations. Utilizing machine learning algorithms, porosity was estimated while the Lattice Boltzmann method (LBM) was applied to determine permeability [5]. The methodology employed for estimating these petrophysical parameters was initially validated using samples from formations analogous to Lithuanian formations. Subsequently, it was applied to rock samples specifically obtained from Lithuanian formations. The estimated petrophysical properties were compared with peer-reviewed data from published literature. When fluids such as CO2 or H2 are injected into sub-surface reservoirs, they can alter pore and grain characteristics. Therefore, it is crucial to extract representative element volumes (REVs) from segmented volumes to study the impact of fluids on porosity and their distribution [6]. These mini models, representing small portions of the larger formation, assist in predicting fluid flow within the formation, which is vital for assessing the efficiency and safety of carbon capture and storage (CCS) operations. Subsequently, numerical modelling was conducted using the petrophysical parameters as inputs to assess the storage capacity of the Lithuanian formations using tNavigator software [7]. This research contributes to an enhanced understanding of pore space distribution and its role in various aspects of long-term CO2 storage. It also demonstrates the potential of integrating advanced imaging techniques, machine learning, and numerical modeling for accurate assessment and effective management of subsurface CO2 storage. This study shall aid in enhanced understanding of pore space distribution and their contribution towards various aspects of long-term storage. The results can be extended to study the geochemical reactions and geo-mechanical behaviour of the rocks. Such studies shall further facilitate identification of reservoir(s) wherein sequestration potential can be reliably explored.

Conservation, peasants and class: critical reflections on the political economy of climate change strategies in West Senegal

ABSTRACT Environmental conservation has become a key climate mitigation strategy in the last two decades. Through the multiplication of ‘conservation’ projects, Africa is one of the main centres of this kind of intervention. While scholars have shown conservation to be a vehicle for the advancement of capitalist interests, scarce attention has been paid to agrarian labour and class dynamics in the African countryside sustaining this development. Drawing on the authors’ research in West Senegal, this article develops a conceptual framework for integrating class and peasant labour in the study of capitalist conservation. It shows how conservation-related climate mitigation strategies in Africa nurture and are nurtured by neoliberal and imperialist processes of agrarian change, reinforcing the economic and political vulnerability of African peasants. Alternative, anti-imperial climate change mitigation strategies need to be centred around peasant environmentalisms and their liberation from labour oppression.

Global warming may significantly increase childhood anemia burden in sub-Saharan Africa

Childhood anemia constitutes a global public health problem, especially in low- and middle-income countries (LMICs). However, it remains unknown whether global warming has an impact on childhood anemia. Here, we examined the association between annual temperatures and childhood anemia prevalence in sub-Saharan Africa and then projected childhood anemia burden attributable to climate change. Each 1°C increment in annual temperature was associated with increased odds of childhood anemia (odd ratio = 1.138, 95% confidence interval: 1.134-1.142). Compared with the baseline period (1985-2014), the attributable childhood anemia cases would increase by 7,597 per 100,000 person-years under a high-emission scenario in the 2090s, which would be almost 2-fold and over 3-fold more than those projected in moderate- and low-emission scenarios. Our results reveal the vulnerabilities and inequalities of children for the excess burden of anemia due to climate warming and highlight the importance of climate mitigation and adaptation strategies in LMICs.

Impacts of climate change on cassava yield and lifecycle energy and greenhouse gas performance of cassava ethanol systems: An example from Guangxi Province, China

Significant shock of climate change on crop yield will challenge the performance of bio-crop on substituting fossil energy to mitigate climate change. Taking cassava-to-ethanol system in Guangxi Province of South China as an example, we coupled a random forest (RF) model with 10 Global climate models (GCMs) outputs to predict the future cassava yields. Subsequently, the net energy value (NEV) and greenhouse gas (GHG) emissions of the cassava-to-ethanol system across varied topographies are assessed using a life cycle analysis. We demonstrate that the abrupt increases in temperatures are the primary contributors to declining yields. Notably, cassava yields in hilly regions decline more than those in plains and display greater variability among concentration pathway scenarios over time. Future NEV and GHG performance of cassava-to-ethanol will undergo significant decreases over time, especially within the high concentration pathway scenario (NEV decrease 28%, GHG increase 3.4% from 2006 to 2100). The performance reductions in hilly area are exacerbated by more harvest loss and labor and material inputs during the “field-to-wheel”, negating its energy advantage over fossil fuels. Therefore, adopting a lower concentration pathway and favoring plantation in plains could maintain cassava-to-ethanol as a viable climate mitigation strategy. Our research also advances the methodological approach to climate change adaptation within the domain of life cycle assessment.

Global fossil fuel reduction pathways under different climate mitigation strategies and ambitions

The mitigation scenarios database of the Intergovernmental Panel on Climate Change’s Sixth Assessment Report is an important resource for informing policymaking on energy transitions. However, there is a large variety of models, scenario designs, and resulting outputs. Here we analyse the scenarios consistent with limiting warming to 2 °C or below regarding the speed, trajectory, and feasibility of different fossil fuel reduction pathways. In scenarios limiting warming to 1.5 °C with no or limited overshoot, global coal, oil, and natural gas supply (intended for all uses) decline on average by 95%, 62%, and 42%, respectively, from 2020 to 2050, but the long-term role of gas is highly variable. Higher-gas pathways are enabled by higher carbon capture and storage (CCS) and carbon dioxide removal (CDR), but are likely associated with inadequate model representation of regional CO2 storage capacity and technology adoption, diffusion, and path-dependencies. If CDR is constrained by limits derived from expert consensus, the respective modelled coal, oil, and gas reductions become 99%, 70%, and 84%. Our findings suggest the need to adopt unambiguous near- and long-term reduction benchmarks in coal, oil, and gas production and use alongside other climate mitigation targets.

Impacts of urban forests and landscape characteristics on land surface temperature in two urban agglomeration areas of China

Accurate characterization of urban forest change can help quantify its impact on the urban thermal environment. Taking Hangzhou City and Zhaoqing City, China as two cases, we proposed a deep learning-based approach to extract forest/non-forest types using China's Gaofen data and the labels it generates. We then explored the impacts of urban forest patterns on land surface temperature (LST). Our results indicate that Gaofen-1/6 images performed well for urban forest/non-forest mapping with an accuracy of over 90%. We found that afforestation and deforestation exerted a net cooling of -0.62±0.30°C and -1.23±0.26°C and warming of 1.71±0.16°C and 1.29±0.14°C in Hangzhou and Zhaoqing, respectively. Balancing the LST changes of both afforestation and deforestation found total warming due to deforestation, especially in Hangzhou. Latitudinal reduced cooling and enhanced warming were found from Zhaoqing to Hangzhou, which can be explained by strong evaporative effects and inconsistent albedo effects. Moreover, a more pronounced cooling when other types converted to landscape core type and a weaker warming when landscape core type converted to other types were detected, especially in Zhaoqing. This study highlights the importance of designing rational afforestation plans, avoiding deforestation activities, and reducing forest fragmentation in delineating effective climate mitigation strategies.

A review of the effects of solar radiation management on hydrological extremes

Solar radiation management (SRM) is one of the proposed climate mitigation strategies to cool the planet rapidly. The injection of aerosol particles into the stratosphere for reflecting solar radiation back to the space is one of the SRM methods that are widely discussed. Theoretically, SRM might lower the earth’s temperature within a few months of deployment, reducing the impacts of climate change on natural disasters, i.e., floods and drought, which lead to huge losses in economic and human life. Solar radiation variability was identified to be a substantial factor that induced the hydrological changes, particularly in precipitation extreme. The effects of SRM on hydrological cycles, however, fluctuate depending on the location and environment. Hence, this article reviews the past SRM studies that related to the analysis of the hydrological cycle changes. A total of 17 articles were identified and collected from the Web of Science and Scopus databases. The results show that there have been an increasing number of articles in recent years studying the effects of SRM on the hydro-climatic changes. The Geoengineering Model Intercomparison Project (GeoMIP) and the Geoengineering Large Ensemble (GLENS) are two commonly used SRM-based general circulation models. In general, SRM is projected to slow down the global hydrological cycle. In comparison to the RCP 8.5 scenario, SRM generally tends to lower flood risk in many parts of the world. However, the majority of SRM research in hydrology has been conducted on a global scale, which results in a lack of robust basin-scale assessment needed for flood control policy formulation. In addition, more SRM climate models and scenario experiments should be considered to minimize the uncertainty in the framework for hydro-climatic modelling framework.

Rewilding Risks for Peatland Permafrost

Permafrost thaw is projected to reinforce climate warming by releasing large stocks of stored carbon. Rewilding northern high latitude regions with large herbivores has been proposed as a climate mitigation strategy to protect frozen soils and increase ecosystem resilience to climate warming. We explored the impact of summer reindeer density on subarctic peatlands by comparing 17 peatlands differing in reindeer density in Fennoscandia. We used a combination of high-resolution image analyses and field assessments along 50 transects to assess microtopography, surface water cover, vegetation, summer albedo, permafrost presence, soil temperature, soil nutrients and snow depth. Our results show that high summer reindeer densities fragment the characteristic bumpy topography of the peatlands, reducing the insulating soil properties and the probability of keeping permafrost in elevated hummocks. As a result, waterlogged lawns with surface water increase in size and reduce summer albedo. Furthermore, high reindeer density peatlands were associated with an increase in tall inedible shrubs and thicker snow layers. These changes may favor summer warming and reduce winter cooling of the soil thus accelerating permafrost loss. Our results suggest that high reindeer densities may reduce resilience of the peatland permafrost to climate warming. High densities of large herbivores will likely have different effects in well-drained uplands, but in the lowlands we studied, the complex cascading effects of summer trampling may well offset any climate-protection gained by browsing. Optimal use of wildlife management to mitigate global warming will thus require tuning herbivore densities to different ecosystem types across high northern landscapes.

Greenhouse gas emissions from U.S. crude oil pipeline accidents: 1968 to 2020

Crude oil pipelines are considered as the lifelines of energy industry. However, accidents of the pipelines can lead to severe public health and environmental concerns, in which greenhouse gas (GHG) emissions, primarily methane, are frequently overlooked. While previous studies examined fugitive emissions in normal operation of crude oil pipelines, emissions resulting from accidents were typically managed separately and were therefore not included in the emission account of oil systems. To bridge this knowledge gap, we employed a bottom-up approach to conducted the first-ever inventory of GHG emissions resulting from crude oil pipeline accidents in the United States at the state level from 1968 to 2020, and leveraged Monte Carlo simulation to estimate the associated uncertainties. Our results reveal that GHG emissions from accidents in gathering pipelines (~720,000 tCO2e) exceed those from transmission pipelines (~290,000 tCO2e), although significantly more accidents have occurred in transmission pipelines (6883 cases) than gathering pipelines (773 cases). Texas accounted for over 40% of total accident-related GHG emissions nationwide. Our study contributes to enhanced accuracy of the GHG account associated with crude oil transport and implementing the data-driven climate mitigation strategies.

Long‐term changes in soil carbon and nitrogen fractions in switchgrass, native grasses, and no‐till corn bioenergy production systems

AbstractCellulosic bioenergy is a primary land‐based climate mitigation strategy, with soil carbon (C) storage and nitrogen (N) conservation as important mitigation elements. Here, we present 13 years of soil C and N change under three cellulosic cropping systems: monoculture switchgrass (Panicum virgatum L.), a five native grasses polyculture, and no‐till corn (Zea mays L.). Soil C and N fractions were measured four times over 12 years. Bulk soil C in the 0–25 cm depth at the end of the study period ranged from 28.4 (± 1.4 se) Mg C ha−1 in no‐till corn, to 30.8 (± 1.4) Mg C ha−1 in switchgrass, and to 34.8 (± 1.4) Mg C ha−1 in native grasses. Mineral‐associated organic matter (MAOM) ranged from 60% to 90% and particulate organic matter (POM) from 10% to 40% of total soil C. Over 12 years, total C as well as both C fractions persisted under no‐till corn and switchgrass and increased under native grasses. In contrast, POM N stocks decreased 33% to 45% across systems, whereas MAOM N decreased only in no‐till corn and by less than 13%. Declining POM N stocks likely reflect pre‐establishment land use, which included alfalfa and manure in earlier rotations. Root production and large soil aggregate formation explained 69% (p < 0.001) and 36% (p = 0.024) of total soil C change, respectively, and 60% (p = 0.020) and 41% (p = 0.023) of soil N change, demonstrating the importance of belowground productivity and soil aggregates for producing and protecting soil C and conserving soil N. Differences between switchgrass and native grasses also indicate a dependence on plant diversity. Soil C and N benefits of bioenergy crops depend strongly on root productivity and pre‐establishment land use.

Coupled high-resolution GCM downscaling framework for projecting dynamics and drivers of ecosystem services in Pearl River Basin, China

The projection of future ecosystem service (ES) dynamics under SSP-RCP scenarios would be beneficial for the development of effective climate mitigation strategies for policymakers. However, current projection frameworks generally neglect the downscaling of high-resolution climate and land use data, leading to uncertainties in the simulation of ESs under the SSP-RCP scenarios. To address this issue, this study proposes an integrated analysis framework to downscale climate and land use data. We first identified areas of high risk in terms of inadequate water-related ESs in the Pearl River Basin (PRB) of China. Subsequently, we analyzed key socio-environmental factors driving the dynamics of water-related ESs under future SSP-RCP scenarios. The results indicate that 1) water-related ESs in the PRB are expected to show an overall increasing trend, 2) the sub-watersheds located in the downstream is at a higher risk of experiencing insufficient supply capacity for water-related ESs, and 3) under the coupling effects of climate change, land use change, and socio-economic development, drastic changes in future land use are expected to have a stronger impact on watershed ESs than the climate (i.e., global warming). Our work provides valuable insights for policymakers and managers regarding future water and land resource planning. The proposed framework can be integrated with other hydrological or land surface models to project the spatial–temporal evolution characteristics of future watershed ESs with finer temporal resolution.

Thermal characterization of Ajmer City: Insights into urban heat dynamics

Human development, urbanization, and ongoing environmental issues have led to environmental disturbances and climate changes in Ajmer, a crucial rest station for migrating birds. Congested and poorly planned urban areas, reduced vegetation cover, and increasing emissions from industries and automobiles all contribute to climate challenges. The rise in land surface temperature (LST) has led to the formation of urban heat islands (UHI). The goal of this research is to investigate UHI in Ajmer City, India. Using remotely sensed LANDSAT data and Geographic Information System (GIS), we analyzed LST and Normalized Difference Vegetation Index (NDVI) for the summer months (March to June) in Ajmer from 2015 to 2022, including the period when nationwide curfews were implemented due to Covid-19. The extraordinary measures taken to restrict human activities during the pandemic resulted in remarkable temporary declines in aerosols and atmospheric pollutants (NO2, CO, SO2, and PM) mainly due to restrictions on fossil fuel burning and transportation emissions. The analysis reveals that Urban LST was 312.07 K in 2019 and decreased to 308.228 K in 2020 due to the strict Covid-19 lockdowns. With the gradual easing of restrictions and resumption of human activities, LST slightly increased to 308.27 K in 2021 and further to 311.71 K in 2022. Researchers can now explore the effects of reduced surface vehicle heat and air pollution on LST and UHI intensity in Western Indian cities, providing valuable insights for urban planning and climate mitigation strategies.

Impact of bias correction on climate change signals over central Europe and the Iberian Peninsula

Vegetation models for climate adaptation and mitigation strategies require spatially high-resolution climate input data in which the error with respect to observations has been previously corrected. To quantify the impact of bias correction, we examine the effects of quantile-mapping bias correction on the climate change signal (CCS) of climate, extremes, and biological variables from the convective regional climate model COSMO-CLM and two dynamic vegetation models (LPJ-GUESS and CARAIB). COSMO-CLM was driven and analyzed at 3 km horizontal resolution over Central Europe (CE) and the Iberian Peninsula (IP) for the transient period 1980–2070 under the RCP8.5 scenario. Bias-corrected and uncorrected climate simulations served as input to run the dynamic vegetation models over Wallonia. Main result of the impact of bias correction on the climate is a reduction of seasonal absolute precipitation by up to −55% with respect to uncorrected simulations. Yet, seasonal climate changes of precipitation and also temperature are marginally affected by bias correction. Main result of the impact of bias correction on changes in extremes is a robust spatial mean CCS of climate extreme indices over both domains. Yet, local biases can both over- and underestimate changes in these indices and be as large as the raw CCS. Changes in extremely wet days are locally enhanced by bias correction by more than 100%. Droughts in southern IP are exacerbated by bias correction, which increases changes in consecutive dry days by up to 14 days/year. Changes in growing season length in CE are affected by quantile mapping due to local biases ranging from 24 days/year in western CE to −24 days/year in eastern CE. The increase of tropical nights and summer days in both domains is largely affected by bias correction at the grid scale because of local biases ranging within ±14 days/year. Bias correction of this study strongly reduces the precipitation amount which has a strong impact on the results of the vegetation models with a reduced vegetation biomass and increases in net primary productivity. Nevertheless, there are large differences in the results of the two applied vegetation models.

Air quality equity in US climate policy

The United States government has indicated a desire to advance environmental justice through climate policy. As fossil fuel combustion produces both conventional pollutants and greenhouse gas (GHG) emissions, climate mitigation strategies may provide an opportunity to address historical inequities in air pollution exposure. To test the impact of climate policy implementation choices on air quality equity, we develop a broad range of GHG reduction scenarios that are each consistent with the US Paris Accord target and model the resulting air pollution changes. Using idealized decision criteria, we show that least cost and income-based emission reductions can exacerbate air pollution disparities for communities of color. With a suite of randomized experiments that facilitates exploration of a wider climate policy decision space, we show that disparities largely persist despite declines in average pollution exposure, but that reducing transportation emissions has the most potential to reduce racial inequities.

The nonexcludable function of sports stadiums in climate-changed cities

The unrelenting threat of climate change and extreme weather events on human settlements has prompted urban planners and public policymakers to develop robust climate mitigation and adaptation strategies for their cities. As part of these measures, they may identify existing or proposed infrastructure that could serve residents during a public emergency (e.g. as shelters). One such candidate is the modern professional sports stadium, which has demonstrated its versatility over the past several years by serving as field hospitals, COVID-19 testing and mass vaccination sites, and municipal voting centers. In this commentary, we consider the essential contribution sports stadiums may make to cities and regions impacted by extreme weather and climate change. Specifically, we examine the utility of a publicly funded stadium as a shelter in response to large-scale disasters. As part of our analysis, we identify the structural, geographical, organizational, and logistical factors that impact the feasibility of this proposal.

Building capacity of healthcare professionals and community members to address climate and health threats in The Bahamas: Analysis of a green climate fund pilot workshop

Climate change is a preeminent threat to health and health systems in The Bahamas. Climate and health resilience depends upon a knowledgeable and coordinated healthcare system and workforce that is highly connected and coordinated with a knowledgeable and empowered community. We present the methodology and results of a novel educational workshop, designed to increase the knowledge and awareness of health care professionals and community members with the goal of empowering them to engage in climate mitigation and adaptation strategies. Following the training, participants demonstrated increased knowledge of the causes of climate change, health exposures, climate-sensitive diseases, and vulnerable populations relevant to The Bahamas. Further, participants reported high levels of willingness and readiness to tackle climate change and its health consequences. Results from this workshop suggest that such a model may serve as a guide for building grass-roots resilience in communities worldwide.

Spatiotemporal variation and multivariate controls of short‐cycle drought–flood abrupt alteration: A case in the Qinling‐Daba Mountains of China

AbstractA comprehensive understanding of the patterns of drought and flood alternation in adjacent months is essential for enabling climate adaptation and mitigation strategies. However, there is a paucity of knowledge regarding short‐cycle drought–flood abrupt alteration (s‐DFAA) and its responses to multiple environmental factors at various timescales. This is because of the inadequate formula construction of the existing short‐cycle drought–flood abrupt alteration index (SDFAI), such as the inability to introduce drought standards. To accurately capture the s‐DFAA's characteristics in the Qinling‐Daba Mountains (Qinba Mountains), we proposed a revised SDFAI (R‐SDFAI), which incorporates the standardized precipitation index (SPI) and allows for the customization of drought standards. Next, we used wavelet transform coherence and multiple wavelet coherence to investigate the timescale relationships between s‐DFAA events and their influence factors such as relative humidity, sunshine duration, temperature, evaporation, Arctic Oscillation (AO), Niño3.4 SSTA Index (Niño3.4), Total Sunspot Number Index (TSNI) and Pacific Decadal Oscillation Index (PDO). Our results showed that the R‐SDFAI outperformed traditional SDFAI in capturing s‐DFAA events and characterizing their severity. Furthermore, s‐DFAA events identified by R‐SDFAI at different levels (i.e., mild, moderate, severe, extreme and total) displayed insignificant downward trends. Spatially, there were more s‐DFAA events in the east than the west. Wavelet analysis indicated that meteorological factors and teleconnections significantly impact s‐DFAA events at large timescales, though their driving mechanisms differed substantially. Among meteorological factors, single relative humidity and its related combinations exhibited relatively high percent area of significant coherence (PASC, ranging from 17.47 to 29.46). Each teleconnection and its combinations are irreplaceable, with PASC values always increasing with the number of variables. The PASC ranges from 8.3 to 10.29 for one factor, 12.38 to 18.65 for two factors, 24.02 to 30.58 for three factors and 40.88 for four factors, respectively.

Environmental Co‐Benefits of Maintaining Native Vegetation With Solar Photovoltaic Infrastructure

AbstractCo‐locating solar photovoltaics with vegetation could provide a sustainable solution to meeting growing food and energy demands. However, studies quantifying multiple co‐benefits resulting from maintaining vegetation at utility‐scale solar power plants are limited. We monitored the microclimate, soil moisture, panel temperature, electricity generation and soil properties at a utility‐scale solar facility in a continental climate with different site management practices. The compounding effect of photovoltaic arrays and vegetation may homogenize soil moisture distribution and provide greater soil temperature buffer against extreme temperatures. The vegetated solar areas had significantly higher soil moisture, carbon, and other nutrients compared to bare solar areas. Agrivoltaics in agricultural areas with carbon debt can be an effective climate mitigation strategy along with revitalizing agricultural soils, generating income streams from fallow land, and providing pollinator habitats. However, the benefits of vegetation cooling effects on electricity generation are rather site‐specific and depend on the background climate and soil properties. Overall, our findings provide foundational data for site preservation along with targeting site‐specific co‐benefits, and for developing climate resilient and resource conserving agrivoltaic systems.

Nature-Based Solutions for Carbon Neutral Climate Resilient Buildings and Communities: A Review of Technical Evidence, Design Guidelines, and Policies

The building sector is responsible for nearly 40% of the total global direct and indirect CO2 emissions. Urban green infrastructure, which includes features such as urban trees, vegetation, green roofs, and green facades, are examples of nature-based solutions often employed as municipal climate mitigation and adaptation strategies. This approach offers a range of cost-effective strategies for reducing municipal CO2 emissions and presents compelling public policy co-benefits such as improved urban livability and enhanced environmental conditions. For municipalities to confidently deploy these solutions at a scale necessary to achieve climate benefits, acquiring knowledge of quantifiable and demonstrated outcomes is an essential requirement. The objectives of this paper are to (1) provide a comprehensive analysis of the advantages and limitations of nature-based solutions (NBS) to address the challenge of reducing CO2 emissions; (2) evaluate existing design guidelines and policies as may be available across Canada, and that that support the of implementation of NBS in urban agglomerations; (3) identify knowledge gaps and research needs to address challenges to the implementation of NBS. In this review, suggestions and requirements as presented in these documents are examined while giving due consideration to the scientific evidence available in research papers. It was found that the adoption of NBS can contribute to carbon neutral communities through reduced building energy consumption and carbon sequestration. Supportive guidelines and policies have been developed, or are in development, to promote the implementation of NBS at the city scale, despite challenges in assessing, quantitatively, their impact due to uncertainties in data, methods, and scale. Nonetheless, existing research provides sufficient evidence to qualify the measures and suggestions outlined in the guidelines and policies described in this paper.

Why “formal” climate adaptation strategies fail in sub‐Saharan Africa: Ignoring adapters’ agency in the case of smallholding agriculture farming practices in Bono East Region of Ghana

AbstractThis paper reviewed a body of literature on climate adaptation options in sub‐Saharan Africa's (SSA) smallholding agriculture and complemented it with a case study involving experts interviews, focus group discussions, large‐scale household surveys, and farmer practices observation while drawing insight from the concept of “everyday adaptation and interrupted agency” and agency theory to assess farmer perceived limitations with climate‐smart agriculture (CSA) and climate‐wise food systems (CWFS) practices for climate adaptation in the SSA. The study noted that the narrow focus on CSA and/or CWFS as a silver bullet for climate change adaptation suitable for smallholding agriculture ignores food producers’ agency to undermine sustainable and inclusive adaptation solutions. Moreover, smallholder farmers’ everyday climate adaptation practices could be grouped into three categories; on‐farm adaptation, off‐farm adaptation, and Indigenous agroecological adaptation options. The on‐farm adaptation options are usually agriculture intensification and extensification. The off‐farm adaptation options include livelihood diversification activities, petty trading, seasonal labor jobs, and migration. The Indigenous agroecological adaptation strategy uses observing nature and weather elements to predict the onset of the rainy season. The study noted that smallholders’ adaptation options, which is an expression of their agency, are motivated by smallholders’ desire to be resilient to changing climate, increase productivity and income, and social network influence but not necessarily because the strategy is being promoted by the government or Non‐Governmental Organizations (NGOs). Therefore, we propose a sustainable food agency (SFA)—a multifaceted blended constellation of climate adaptation and mitigation strategies, as the best approach to addressing the climate crises in the SSA. The SFA allows individuals or groups to decide what climate change adaptation options best work for them to adapt to changing climate and produce and distribute their food without undermining the economic, social, and environmental bases that generate food security and nutrition for present and future generations.