Effective Climate Change Mitigation Research Articles

Prospective Roles of Extremophilic Fungi in Climate Change Mitigation Strategies.

Climate change and the resultant environmental deterioration signify one of the most challenging problems facing humankind in the 21st century. The origins of climate change are multifaceted and rooted in anthropogenic activities, resulting in increasing greenhouse gases in the environment and leading to global warming and weather drifts. Extremophilic fungi, characterized by their exceptional properties to survive extreme habitats, harbor great potential in mitigating climate change effects. This review provides insight into the potential applications of extremophilic fungi in climate change mitigation strategies. They are able to metabolize organic biomass and degrade carbon compounds, thereby safely sequestering carbon and extenuating its release into the environment as noxious greenhouse gases. Furthermore, they possess extremozymes, which break down recalcitrant organic species, including lignocellulosic biomass and hydrocarbons. Enzymatic machinery equips these extremophilic fungi to perform the bioremediation of polluted environments. Extremophilic fungi can also be exploited for various biological interventions, such as biofuels, bioplastics, and other bioprocessing applications. However, these fungi characterize a valued but underexplored resource in the arsenal of climate change mitigation strategies.

Climate-resilient building energy efficiency retrofit: Evaluating climate change impacts on residential buildings

Buildings have the potential to mitigate climate change effects by integrating energy-efficient solutions. Building resilient design strategies based on forthcoming weather predictions offers an effective means of adaptation. The study focuses on the impact of climate change on residential buildings in Istanbul and Izmir, two Turkish cities with distinctive climate characteristics. By creating future weather scenarios and conducting dynamic simulations, buildings’ and improvement measures’ performance under RCP 4.5 and RCP 8.5 climate scenarios and short- and long-term periods are evaluated. The findings reveal varying degrees of climate change impact on the two regions, with decreased heating degree days (HDDs) and increased cooling degree days (CDDs). Notably, the RCP 8.5 scenario projects significant temperature increases, with a rise of 4.3 °C in Istanbul and 5 °C in Izmir, leading to profound consequences for buildings. The CDD can be doubled in July and reach 292 in Izmir and quadrupled, reaching 158 in Istanbul. Without retrofit, in a well-naturally ventilated building, primary heating energy consumption can be decreased by 36–41 %, while primary cooling energy consumption tripled in both cities. With the aid of improvements, a ∼ 5–6 °C decrease was observed in the highest temperature predictions in naturally ventilated spaces in summer in Istanbul, while a ∼ 4–5 °C decrease was observed in Izmir.

Enhancing ecosystem productivity and stability with increasing canopy structural complexity in global forests.

Forest canopy structural complexity (CSC) plays a crucial role in shaping forest ecosystem productivity and stability, but the precise nature of their relationships remains controversial. Here, we mapped the global distribution of forest CSC and revealed the factors influencing its distribution using worldwide light detection and ranging data. We find that forest CSC predominantly demonstrates significant positive relationships with forest ecosystem productivity and stability globally, although substantial variations exist among forest ecoregions. The effects of forest CSC on productivity and stability are the balanced results of biodiversity and resource availability, providing valuable insights for comprehending forest ecosystem functions. Managed forests are found to have lower CSC but more potent enhancing effects of forest CSC on ecosystem productivity and stability than intact forests, highlighting the urgent need to integrate forest CSC into the development of forest management plans for effective climate change mitigation.

Spatial distribution of CH4 emissions from livestock farming in Poland: a comparison of 2010 and 2020

ABSTRACT Among greenhouse gases (GHGs), methane (CH4) is a major contributor to global warming. Agriculture accounts for about 40% of CH4 emissions, with livestock being a crucial source. CH4 emissions from livestock primarily arise during enteric fermentation and manure management in livestock. This study aims to estimate Poland’s CH4 emissions from enteric fermentation and manure management in 2010 and 2020 at the municipal level (LAU-2). Data from the National Agricultural Census (NAC) and the UNFCCC National Inventory Report (NIR) for 2010 and 2020 were used for the analysis. The results reveal a slight overall increase in total CH4 emissions from livestock farming in Poland over the decade. The highest emissions were observed in regions where livestock farming was predominant, while significant changes in emissions occurred in regions experiencing considerable livestock production growth. Conversely, the lowest emissions were found in areas where the decrease in livestock population was most prominent. Understanding the spatial distribution of CH4 emissions from livestock farming at the municipal level is essential for effective climate change mitigation efforts. This study highlights the importance of continuous monitoring and analysis of livestock farming in Poland to assess its impact on GHG emissions and facilitate informed policy-making for sustainable agricultural practices.

National variability in soil organic carbon stock predictions: Impact of bulk density pedotransfer functions

Accurate soil organic carbon storage (SOCS) estimation is crucial for sustaining ecosystem health and mitigating climate change impacts. This study investigated the accuracy and variability of SOCS predictions, focusing on the role of pedotransfer functions (PTFs) in estimating soil bulk density (BD). Utilizing a comprehensive dataset from the Korean Rural Development Administration (RDA database), which includes 516 soil horizons, we evaluated 36 widely-used BD PTFs, well-established formulas that estimate BD by considering soil properties, including soil organic carbon (SOC), soil organic matter (OM), sand, gravel, silt, and clay. These PTFs demonstrated varying levels of precision, with root mean squared errors (RMSE) ranging from 0.177 to 0.377 Mg m−3 and coefficients of determination (R2) from 0.176 to 0.658; hence, the PTFs have been classified into excellent, moderate, and poor-performing groups for predicting BD. Further, a novel PTF based on an exponential function of SOC was developed, showing superior predictive power (R2 = 0.73) compared to existing PTFs, using an independent validation dataset. Our findings reveal significant differences in SOCS predictions and observations among the PTFs, with a p-value <0.05. The highest concentrations of SOCS were noted in forest soils, considerably above the national average, highlighting the importance of tailored soil management practices to enhance carbon sequestration. These findings are crucial for refining PTF precision to improve the accuracy of national SOCS estimates, supporting effective land management and climate change mitigation strategies.

Impact of persistently high sea surface temperatures on the rhizobiomes of Zostera marina in a Baltic Sea benthocosms.

Persistently high marine temperatures are escalating and threating marine biodiversity. The Baltic Sea, warming faster than other seas, is a good model to study the impact of increasing sea surface temperatures. Zostera marina, a key player in the Baltic ecosystem, faces susceptibility to disturbances, especially under chronic high temperatures. Despite the increasing number of studies on the impact of global warming on seagrasses, little attention has been paid to the role of the holobiont. Using an outdoor benthocosm to replicate near-natural conditions, this study explores the repercussions of persistent warming on the microbiome of Z. marina and its implications for holobiont function. Results show that both seasonal warming and chronic warming, impact Z. marina roots and sediment microbiome. Compared with roots, sediments demonstrate higher diversity and stability throughout the study, but temperature effects manifest earlier in both compartments, possibly linked to premature Z. marina die-offs under chronic warming. Shifts in microbial composition, such as an increase in organic matter-degrading and sulfur-related bacteria, accompany chronic warming. A higher ratio of sulfate-reducing bacteria compared to sulfide oxidizers was found in the warming treatment which may result in the collapse of the seagrasses, due to toxic levels of sulfide. Differentiating predicted pathways for warmest temperatures were related to sulfur and nitrogen cycles, suggest an increase of the microbial metabolism, and possible seagrass protection strategies through the production of isoprene. These structural and compositional variations in the associated microbiome offer early insights into the ecological status of seagrasses. Certain taxa/genes/pathways may serve as markers for specific stresses. Monitoring programs should integrate this aspect to identify early indicators of seagrass health. Understanding microbiome changes under stress is crucial for the use of potential probiotic taxa to mitigate climate change effects. Broader-scale examination of seagrass-microorganism interactions is needed to leverage knowledge on host-microbe interactions in seagrasses.

Sorption of Soil Carbon Dioxide by Biochar and Engineered Porous Carbons.

CO2 is 45 to 50 times more concentrated in soil than in air, resulting in global diffusive fluxes that outpace fossil fuel combustion by an order of magnitude. Despite the scale of soil CO2 emissions, soil-based climate change mitigation strategies are underdeveloped. Existing approaches, such as enhanced weathering and sustainable land management, show promise but continue to face deployment barriers. We introduce an alternative approach: the use of solid adsorbents to directly capture CO2 in soils. Biomass-derived adsorbents could exploit favorable soil CO2 adsorption thermodynamics while also sequestering solid carbon. Despite this potential, previous study of porous carbon CO2 adsorption is mostly limited to single-component measurements and conditions irrelevant to soil. Here, we probe sorption under simplified soil conditions (0.2 to 3% CO2 in balance air at ambient temperature and pressure) and provide physical and chemical characterization data to correlate material properties to sorption performance. We show that minimally engineered pyrogenic carbons exhibit CO2 sorption capacities comparable to or greater than those of advanced sorbent materials. Compared to textural features, sorbent carbon bond morphology substantially influences low-pressure CO2 adsorption. Our findings enhance understanding of gas adsorption on porous carbons and inform the development of effective soil-based climate change mitigation approaches.

Cultivating Value: Teaching a Job and Mitigating Climate Change Effects While Restoring a Landscape Heritage

Abstract In the degraded peri-urban areas, there are several traces of the agrarian landscape heritage: they are not relicts of the past but a resource for managing water, providing fauna and flora biodiversity, and mitigate climate change in the urban environment. A pilot experience of recovering the Milan medieval water meadows has been done in the last two years: the aim was to provide a new job to fragile people, while restoring an ancient landscape. The tangible permanencies have been recovered by unemployed people at the same time as the traditional art of managing water has been taught by ancient watermen. A course has been organized to transfer the knowledge. Several schools have been involved in the practical recovery of artifacts: students enjoyed to care an “ordinary” heritage in their neighbourhood, as a resource for a sustainable way of living, and a good quality landscape. The high social and cultural value provided increased Municipality’s attention to consider a joint management with the social cooperative of this productive landscape and to include didactical visit to water meadow in each student curricula.

Heat water and reptiles – do the hydro‐thermal properties of animals at the source location persist at the translocation site?

AbstractAssisted colonization to locations predicted to remain climatically suitable in the future is increasingly necessary to mitigate climate change effects in ectotherms such as reptiles. However, these future‐suitable locations are often currently cooler than those from which individuals are sourced. While species‐wide paradigms prevail, responses to thermal regimes may vary across a species range, affecting daily activity, colonization and survival in a new environment. Additionally, hydro‐regulatory behaviours are severely understudied, despite the need for understanding trade‐offs between thermoregulation and hydro‐regulation for successful assisted colonization strategies. We investigated behavioural responses to temperature and relative humidity in two latitudinally distinct lineages of pygmy bluetongue (Tiliqua adelaidensis), a cryptic, burrow‐dwelling endangered lizard, in the Mid‐North of South Australia. From spring 2020 to autumn 2021 we took monthly field‐based approach distance and behavioural footage at the source locations and at a southerly translocation site. Behaviours were matched to site‐specific microclimate data prior to principal component and generalized linear mixed model analysis. We found lineage differences in behaviour that persisted after translocation; southern lineage lizards showed significantly less daily activity and were active at lower temperatures and higher humidity than northern lineage lizards. Southern lineage lizards allowed a human observer to approach closer as base‐of‐burrow humidity increased, while northern lineage lizards were quicker to retreat into burrows, at both source and translocation sites. Novel, non‐invasive field‐based activity curves successfully identified lineage differences in humidity and temperature ranges for surface activity, implying environmental preferences of target populations that were reinforced by the models. Specifically, we found evidence for thermoregulation and adaptation/acclimation to higher temperatures in northern lizards and hydroregulation and adaptation/acclimation to cooler, more humid conditions in southern lizards. The limited behavioural plasticity shown by translocated individuals over the season demonstrates the importance of understanding lineage‐level behaviours, hydro‐regulation, and micro‐climate when selecting individuals for assisted colonization.

Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake

Abstract. Understanding the intricate hydrological interactions between lakes and their surrounding watersheds is pivotal for advancing hydrological research, optimizing water resource management, and informing climate change mitigation strategies. Yet, these complex dynamics are often insufficiently captured in existing hydrological models, such as the bi-direction surface and subsurface flow. To bridge this gap, we introduce a novel lake–watershed coupled model, an enhancement of the Simulator of Hydrological Unstructured Domains. This high-resolution, distributed model employs unstructured triangles as its fundamental hydrological computing units (HCUs), offering a physical approach to hydrological modeling. We validated our model using data from Qinghai Lake in China, spanning from 1979 to 2018. Remarkably, the model not only successfully simulated the streamflow of the Buha River, a key river within the Qinghai Lake basin, achieving a Nash–Sutcliffe efficiency (NSE) of 0.62 and 0.76 for daily and monthly streamflow, respectively, but also accurately reproduced the decrease–increase U-shaped curve of lake level change over the past 40 years, with an NSE of 0.71. Our model uniquely distinguishes the contributions of various components to the lake's long-term water balance, including river runoff, surface direct runoff, lateral groundwater contribution, direct evaporation, and precipitation. This work underscores the potential of our coupled model as a powerful tool for understanding and predicting hydrological processes in lake basins, thereby contributing to more effective water resource management and climate change mitigation strategies.

Climate change impacts on agricultural trade and food security in emerging economies: case of Southern Africa

Climate change has been a significant threat to sustainable agriculture impacting trade and food security. This research investigates the impacts of climate change on agricultural trade and food security in emerging economies focusing on Southern Africa. The research employed the dynamic panel Generalised Method of Moments (GMM) using panel data for the period 2012 to 2021 obtained from a sample of 12 Southern African countries selected based on data availability. The main independent variables to the research were climate change variables (temperature and precipitation). Other control variables included were population growth, food inflation and agricultural growth. The study found significant negative effects of climate change on agriculture trade. Whilst temperature changes were found to have insignificant effects, precipitation changes were found to have significant positive effects. The research recommends concerted efforts towards climate change adaptation and mitigation for sustainable agriculture. Based on the Findings, sustainable food security and agricultural trade Southern African emerging economies may be attained through effective climate change mitigation and adaptation approaches particularly promoting climate-smart agriculture (CSA).

Both yields of maize and soybean and soil carbon sequestration in typical Mollisols cropland decrease under future climate change: SPACSYS simulation

Although Mollisols are renowned for their fertility and high-productivity, high carbon (C) losses pose a substantial challenge to the sustainable provision of ecosystem services, including food security and climate regulation. Protecting these soils with a specific focus on revitalizing their C sequestration potential emerges as a crucial measure to address various threats associated with climate change. In this study, we employed a modeling approach to assess the impact of different fertilization strategies on crop yield, soil organic carbon (SOC) stock, and C sequestration efficiency (CSE) under various climate change scenarios (baseline, RCP 2.6, RCP 4.5, and RCP 8.5). The process-based SPACSYS model was calibrated and validated using data from two representative Mollisol long-term experiments in Northeast China, including three crops (wheat, maize and soyabean) and four fertilizations (no-fertilizer (CK), mineral nitrogen, phosphorus and potassium (NPK), manure only (M), and chemical fertilizers plus M (NPKM or NM)). SPACSYS effectively simulated crop yields and the dynamics of SOC stock. According to SPACSYS projections, climate change, especially the increased temperature, is anticipated to reduce maize yield by an average of 14.5% in Harbin and 13.3% in Gongzhuling, and soybean yield by an average of 10.6%, across all the treatments and climatic scenarios. Conversely, a slight but not statistically significant average yield increase of 2.5% was predicted for spring wheat. SOC stock showed a decrease of 8.2% for Harbin and 7.6% for Gonghzuling by 2,100 under the RCP scenarios. Future climates also led to a reduction in CSE by an average of 6.0% in Harbin (except NPK) and 13.4% in Gongzhuling. In addition, the higher average crop yields, annual SOC stocks, and annual CSE (10.15–15.16%) were found when manure amendments were performed under all climate scenarios compared with the chemical fertilization. Soil CSE displayed an exponential decrease with the C accumulated input, asymptotically approaching a constant. Importantly, the CSE asymptote associated with manure application was higher than that of other treatments. Our findings emphasize the consequences of climate change on crop yields, SOC stock, and CSE in the Mollisol regions, identifying manure application as a targeted fertilizer practice for effective climate change mitigation.

Detecting Spatial Patterns of Peatland Greenhouse Gas Sinks and Sources with Geospatial Environmental and Remote Sensing Data.

Peatlands play a key role in the circulation of the main greenhouse gases (GHG) - methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). Therefore, detecting the spatial pattern of GHG sinks and sources in peatlands is pivotal for guiding effective climate change mitigation in the land use sector. While geospatial environmental data, which provide detailed spatial information on ecosystems and land use, offer valuable insights into GHG sinks and sources, the potential of directly using remote sensing data from satellites remains largely unexplored. We predicted the spatial distribution of three major GHGs (CH4, CO2, and N2O) sinks and sources across Finland. Utilizing 143 field measurements, we compared the predictive capacity of three different data sets with MaxEnt machine-learning modeling: (1) geospatial environmental data including climate, topography and habitat variables, (2) remote sensing data (Sentinel-1 and Sentinel-2), and (3) a combination of both. The combined dataset yielded the highest accuracy with an average test area under the receiver operating characteristic curve (AUC) of 0.845 and AUC stability of 0.928. A slightly lower accuracy was achieved using only geospatial environmental data (test AUC 0.810, stability AUC 0.924). In contrast, using only remote sensing data resulted in reduced predictive accuracy (test AUC 0.763, stability AUC 0.927). Our results suggest that (1) reliable estimates of GHG sinks and sources cannot be produced with remote sensing data only and (2) integrating multiple data sources is recommended to achieve accurate and realistic predictions of GHG spatial patterns.

Development of Forest Carbon Offsetting: Challenges, Opportunities and Implications

The urgent need to mitigate climate change has led to the exploration of innovative strategies, with forest carbon offsetting emerging as a promising avenue for sequestering atmospheric carbon dioxide. This research paper provides a comprehensive review of the current state of development in forest carbon offsetting initiatives, examining both advancements and persistent challenges. The paper begins by elucidating the significance of forests in the global carbon cycle and their pivotal role in climate change mitigation. It subsequently explores the evolution of forest carbon offsetting projects, encompassing afforestation, reforestation, and conservation efforts. Despite the progress made in forest carbon offsetting, the paper addresses several critical challenges hindering its widespread implementation. Issues such as land tenure uncertainties, governance gaps, and the lack of standardized protocols for carbon accounting are discussed in detail. Furthermore, the paper sheds light on the importance of community engagement, emphasizing the need for projects to align with local needs and respect cultural practices. Biodiversity considerations and potential ecological impacts are also scrutinized, emphasizing the imperative of balancing carbon sequestration goals with biodiversity preservation. The research concludes by proposing recommendations for overcoming these challenges, including the establishment of clear and standardized protocols, fostering international collaboration, and enhancing community participation. The findings contribute to a nuanced understanding of the multifaceted landscape surrounding the development of forest carbon offsetting, offering valuable insights for policymakers, researchers, and practitioners striving to advance effective and sustainable climate change mitigation strategies.

Does increasing forest age lead to greater trade-offs in ecosystem services? A study of a Robinia pseudoacacia artificial forest on the Loess Plateau, China

Artificial forest ecosystems offer various ecosystem services (ES) and help mitigate climate change effects. Trade-offs or synergies exist among ES in artificial forests. Although forest age influences ES and ecosystem processes, the long-term dynamics of trade-offs among ES in artificial forests and during vegetation restorations remain unclear, complicating vegetation and sustainable management. We studied a Robinia pseudoacacia plantation on the Loess Plateau, China, with a restoration time of 10–44 years. The entropy weight method was used to assess five ES (carbon sequestration, water conservation, soil conservation, understory plant diversity, and runoff and sediment reduction) and investigate how ES change with forest age. The root mean square deviation (RMSD) was used to quantify the trade-offs among ES, and redundancy analysis (RDA) analysis was used to identify the key factors influencing the ES and trade-offs. The results showed that (1) as forest age increased, ES scores initially increased and then decreased. The optimal range for ES values was observed during the middle-aged to mature stages of the forest. (2) Before reaching maturity, the planted forests primarily delivered services related to water conservation and runoff and sediment reduction. (3) In young forests, ES showed a synergistic relationship (RMSD = 0.06), whereas trade-offs occurred in forests at other ages. The largest trade-off was observed in middle-aged forests. (4) The ES pairs with the dominant trade-offs in planted forests differed at different forest age stages. The largest trade-off occurred between carbon sequestration and water conservation (RMSD = 0.28). RDA analysis showed that understory vegetation coverage had a positive correlation with all ES. The ES indicators that significantly (P < 0.001) affected the water‑carbon trade-off were tree carbon storage, soil organic carbon storage, soil total nitrogen, and soil total phosphorus. Thus, the water and carbon relationship must be balanced, and the key factors affecting ES trade-offs in forest management must be regulated to support ES multifunctionality.

REVIEW OF CARBON PRICING MECHANISMS: EFFECTIVENESS AND POLICY IMPLICATIONS

The escalating threat of climate change has intensified the need for robust strategies to reduce greenhouse gas emissions. Carbon pricing mechanisms have emerged as pivotal tools in this endeavor, aiming to internalize the external cost of carbon emissions and incentivize cleaner, more sustainable practices. This review provides a comprehensive analysis of various carbon pricing mechanisms, evaluating their effectiveness and exploring the policy implications for future implementations. The review categorizes carbon pricing mechanisms into three main types: Carbon Taxes, Cap-and-Trade Systems, and Hybrid Approaches. Each mechanism is examined in terms of its characteristics, case studies from jurisdictions that have implemented them, and a critical assessment of their effectiveness and challenges. The paper evaluates the impact of carbon pricing mechanisms on economic sectors, assessing their influence on industry and their role in stimulating innovation. Furthermore, it scrutinizes the effectiveness of these mechanisms in achieving emission reductions, considering their impact on greenhouse gas emissions. Additionally, the review delves into the social and distributional impacts of carbon pricing, analyzing its equity aspects and identifying potential challenges. Drawing from implemented policies, the review extracts valuable lessons and insights. It explores the integration of carbon pricing with other climate policies, examining synergies and coordination possibilities. The discussion also includes the potential for global cooperation and harmonization, recognizing challenges and opportunities for aligning international efforts. As a forward-looking aspect, the paper explores innovative approaches to carbon pricing, considering technological advancements and market-based solutions. It concludes with policy recommendations aimed at enhancing the effectiveness of carbon pricing mechanisms, addressing challenges, and providing insights for policymakers and stakeholders. This review consolidates current knowledge on carbon pricing mechanisms, shedding light on their effectiveness and unveiling important policy implications. By synthesizing lessons learned from implemented policies, the paper contributes to the ongoing discourse on effective climate change mitigation strategies, emphasizing the role of dynamic, adaptable, and equitable carbon pricing mechanisms.&#x0D; Keywords: Carbon Pricing, Mechanisms, Climate change mitigation, Effectiveness, and Policy Implications.

From carbon-neutral to climate-neutral supply chains: a multidisciplinary review and research agenda

PurposeWe conduct a multidisciplinary systematic literature review on climate neutrality in the supply chain. While carbon neutrality has gained prominence, our study argues that achieving carbon neutrality alone is not enough to address climate change effectively, as non-CO2 greenhouse gases (GHG) are potent contributors to global warming.Design/methodology/approachWe used multiple databases, including EBSCO, ProQuest, Science Direct, Emerald and Google Scholar, to identify articles related to climate neutrality in the context of non-CO2 gases. A total of 71 articles in environmental science, climate change, energy systems, agriculture and logistics are reviewed to provide insights into the climate neutrality of supply chains.FindingsWe find that, in addition to CO2, other GHG such as methane, nitrous oxide, ozone and fluorinated gases also significantly contribute to climate change. Our literature review identified several key pillars for achieving net-zero GHG emissions, including end-use efficiency and electrification, clean electricity supply, clean fuel supply, “GHG capture, storage and utilization,” enhanced land sinks, reduced non-CO2 emissions and improved feed and manure management.Originality/valueWe contribute to the literature on climate neutrality of supply chains by emphasizing the significance of non-CO2 GHG along with CO2 and highlighting the need for a comprehensive approach to climate neutrality in addressing climate change. This study advances the understanding of climate neutrality of supply chains and contributes to the discourse on effective climate change mitigation strategies. It provides clear future research directions.

Green hydrogen production from photovoltaic power station as a road map to climate change mitigation

Abstract The increasing recognition of hydrogen as a critical element in the global net-zero transition and its clear role in decarbonizing challenging sectors coincide with the growing urgency to address climate change. Africa's favourable renewable-energy capacity, ranging from 28% to 36% for solar, has been reported by the global solar irradiance index. However, the majority of hydrogen production today relies on fossil fuels (96%), with only a small fraction (4%) being produced through water electrolysis. Even though there have been many studies on climate change mitigation with a focus on Africa, a green hydrogen production from a photovoltaic power station approach has not been reported. Also, literature with a focus on Nigeria is lacking. This study focuses on the African green hydrogen production industry, utilizing Nigeria as a case study to explore the feasibility of generating clean hydrogen vectors from a percentage of photovoltaic power output in various regions of the country through stand-alone solar grid electrification projects. Analyses of the usage and effectiveness of the produced hydrogen fuel in each region are carried out, with the highest region having an annual output of 12 247 278 kg of green hydrogen and 8 573 094 kg of ammonia and the lowest region having an output of 511 245 kg of green hydrogen and 357 871 kg of ammonia, and the expected production from the proposed usage of 50% of the power generation output of the installed 1.6-MWp and 80-kWp solar power minigrids in the regions is calculated. The analyses were repeated for the other considered regions in the country. The results showcased the enormous advantages of the electrolytic production of hydrogen and how the greener economy project can play a major role in mitigating climate change effects and overreliance on fossil fuels as the driver of the economy in many African countries.

Are cities ready for climate change? Exploring the spatial discrepancies between urban vulnerability and adaptation readiness

Climate change is an increasingly severe global crisis, posing threats to ecosystems, economies, and human lives. To address these threats, different cities around the world have adopted various levels of adaptation strategies to cope with varying degrees of negative impact, such as increasing water efficiency and enhancing health response systems. Despite some progress, there is a spatial discrepancy among cities in terms of their vulnerability to climate change and their adaptation readiness. Uncovering the reasons behind this spatial discrepancy could help us formulate better policies to address climate issues. To this end, we conduct an empirical analysis using city response data from 2020, sourced from the Carbon Disclosure Project (CDP), focusing on a dataset that encompasses 421 cities worldwide. Specifically, we first formulate a “vulnerability index” to measure the propensity of cities to suffer negative effects in the event of climate hazards and a “readiness index” to represent their adaptation readiness level. Then we introduce the “discrepancy score” to quantify discrepancies across cities and discover the spatial distribution of the discrepancies through spatial visualization. Further, we employ a clustering analysis method named k-means to group different cities based on vulnerability index and readiness index. Finally, we perform Geographically Weighted Regression (GWR) to quantitatively analyze the spatial correlation between the economy and the discrepancy score of different cities. Our research mainly reveals several findings: (1) European cities tend to exhibit high levels of adaptation readiness with low degrees of vulnerability. In contrast, African cities consistently display heightened degrees of vulnerability combined with limited adaptation readiness. (2) Economic factors play a significant role in the spatial discrepancies between levels of adaptation readiness and degrees of vulnerability of cities; (3) The impact of the economy on the discrepancy scores exhibits significant spatial heterogeneity, with its influence being greater in European and African regions compared to other areas. Our study contributes both theoretically and practically to the comprehension of global climate change. It provides evidence-based support for the development of more effective climate change mitigation strategies and lays the foundation for fostering worldwide collaboration and initiatives.

Estimating Sugarcane Aboveground Biomass and Carbon Stock Using the Combined Time Series of Sentinel Data with Machine Learning Algorithms

Accurately mapping crop aboveground biomass (AGB) in a timely manner is crucial for promoting sustainable agricultural practices and effective climate change mitigation actions. To address this challenge, the integration of satellite-based Earth Observation (EO) data with advanced machine learning algorithms offers promising prospects to monitor land and crop phenology over time. However, achieving accurate AGB maps in small crop fields and complex landscapes is still an ongoing challenge. In this study, the AGB was estimated for small sugarcane fields (&lt;1 ha) located in the Kumphawapi district of Udon Thani province, Thailand. Specifically, in order to explore, estimate, and map sugarcane AGB and carbon stock for the 2018 and 2021 years, ground measurements and time series of Sentinel-1 (S1) and Sentinel-2 (S2) data were used and random forest regression (RFR) and support vector regression (SVR) applied. Subsequently, optimized predictive models used to generate large-scale maps were adapted. The RFR models demonstrated high efficiency and consistency when compared to the SVR models for the two years considered. Specifically, the resulting AGB maps displayed noteworthy accuracy, with the coefficient of determination (R2) as 0.85 and 0.86 with a root mean square error (RMSE) of 8.84 and 9.61 t/ha for the years 2018 and 2021, respectively. In addition, mapping sugarcane AGB and carbon stock across a large scale showed high spatial variability within fields for both base years. These results exhibited a high potential for effectively depicting the spatial distribution of AGB densities. Finally, it was shown how these highly accurate maps can support, as valuable tools, sustainable agricultural practices, government policy, and decision-making processes.