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This paper presents a thorough examination of methane capture from Polish coal mines, contextualized within the framework of the European Union's (EU) climate policy objectives. Through a strategic analysis encompassing the interior of coal mines, the surrounding environment, and the macro environment, this study elucidates the complex dynamics involved in methane emissions and capture initiatives. The key findings include a declining trend in absolute methane emissions since 2008, despite fluctuations in coal extraction volumes, and a relatively stable level of methane capture exceeding 300 million m3/year since 2014. The analysis underscores the critical role of government support, both in terms of financial incentives and streamlined regulatory processes, to facilitate the integration of methane capture technologies into coal mining operations. Collaboration through partnerships and stakeholder engagement emerges as essential for overcoming resource competition and ensuring the long-term success of methane capture projects. This paper also highlights the economic and environmental opportunities presented by methane reserves, emphasizing the importance of investment in efficient extraction technologies. Despite these advancements, challenges persist, particularly regarding the low efficiency of current de-methanation technologies. Recommendations for modernization and technological innovation are proposed to enhance methane capture efficiency and utilization. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

The European Union is committed to a 55% reduction in greenhouse gas emissions by 2030, as outlined in the Green Deal and Climate Law initiatives. In response to geopolitical events, the RePowerEU initiative aims to enhance energy self-sufficiency, reduce reliance on Russian natural gas, and promote hydrogen utilization. Hydrogen valleys, localized ecosystems integrating various hydrogen supply chain elements, play a key role in this transition, particularly benefiting isolated regions like islands. This manuscript focuses on optimizing a Centralized Green Hydrogen Production Facility (CGHPF) on the island of Crete. A mixed-integer linear programming framework is proposed to optimize the CGHPF, considering factors such as land area, wind and solar potential, costs, and efficiency. Additionally, an in-depth sensitivity analysis is conducted to explore the impact of key factors on the economic feasibility of hydrogen investments. The findings suggest that hydrogen can be sold in Crete at prices as low as 3.5 EUR/kg. Specifically, it was found in the base scenario that, selling hydrogen at 3.5 EUR/kg, the net profit of the investment could be as high as EUR 6.19 million, while the capacity of the solar and wind installation supplying the grid hydrogen facility would be 23.51 MW and 52.97 MW, respectively. It is noted that the high profitability is justified by the extraordinary renewable potential of Crete. Finally, based on our study, a policy recommendation to allow a maximum of 20% direct penetration of renewable sources of green hydrogen facilities into the grid is suggested to encourage and accelerate green hydrogen expansion. [ABSTRACT FROM AUTHOR]

To align with climate initiatives, multiple reporting programs are transitioning from generic activity-based emission factors to site-specific measured emissions data to estimate greenhouse gas emissions at oil and gas facilities. This study contemporaneously deployed two top-down (TD) aerial methods across 14 midstream facilities, building upon previous research in the field. The methods produced multiple whole-facility estimates at each facility, resulting in 773 individual paired estimates (same facility, same day), and robust mean estimates for each facility. Mean estimates for each facility, aggregated across all facilities, differed by nearly 2:1 (49% [32% to 69%]). At 6 of 14 facilities, the methods produced mean estimates that differed by more than a factor of two. These data suggest that one or both methods did not produce accurate facility-level estimates at a majority of facilities and in aggregate across all facilities. The overall results are augmented with two case studies where TD estimates at two pre-selected facilities were coupled with comprehensive onsite measurements to understand the factors driving the divergence between TD and bottom-up (BU) emissions estimates. In 3 of 4 paired comparisons between the intensive onsite estimates and one of the TD methods, the intensive onsite surveys did not conclusively diagnose the difference in estimates. In these cases, our work suggests that the TD methods mis-estimate emissions an unknown fraction of the time, for unknown reasons. While two methods were selected for this study, it is unlikely that the issues identified here are confined to these two methods; similar issues may exist for other similar whole-facility methods on midstream and/or other facility types. These findings have important implications for the construction of voluntary and regulatory reporting programs that rely on emission estimates for reporting fees or penalties, or for studies using whole-facility estimates to aggregate TD emissions to basin or regional estimates. [ABSTRACT FROM AUTHOR]

The utilization of remote sensing soil moisture products in agricultural and hydrological studies is on the rise. Conducting a regional applicability analysis of these soil moisture products is essential as a preliminary step for their effective utilization. The triple collocation (TC) method enables the estimation of the standard deviation of errors in products when true soil moisture values are unavailable. It assesses data uncertainty and mitigates the influence of product errors on fusion, thereby enhancing product accuracy significantly. In this study, the TC uncertainty error analysis was employed to integrate Soil Moisture Active Passive (SMAP), the Advanced Microwave Scanning Radiometer 2 (AMSR-2), and the European Space Agency Climate Change Initiative (ESA CCI) active (ESA CCI A) and passive (ESA CCI P) products, with ground-based measurements serving as a reference. Traditional evaluation metrics, such as the correlation coefficient (R), bias, root mean square error (RMSE), and unin situed root mean square error (ubRMSE), were employed to evaluate the accuracy of the product. The findings indicate that SMAP and ESA CCI P products demonstrate strong spatiotemporal continuity within the research area and exhibit low uncertainty across various land types. The products derived from the Advanced Microwave Scanning Radiometer 2 (AMSR-2) exhibit a high level of temporal and spatial continuity; however, there is a requirement for enhancing their accuracy. The products of ESA CCI A exhibit notable spatiotemporal disjunction, contributing significantly to their elevated level of uncertainty. After fusion with TC analysis, the correlation coefficient (R = 0.7) of the TC-2 product derived from the fusion of SMAP, AMSR-2, and ESA CCI P products is significantly higher than the correlation coefficient of the TC-1 product (R = 0.65) obtained from the fusion of SMAP, AMSR-2, and ESA CCI A products at a 95% confidence level. The integration of data can efficiently mitigate the challenges associated with spatiotemporal gaps and inaccuracies in products, offering a dependable foundation for the subsequent utilization of remote sensing products. [ABSTRACT FROM AUTHOR]

GNSS Reflectometry (GNSS-R) is an emerging technique for the remote sensing of the environment. Traditional GNSS-R bio-geophysical parameter retrieval algorithms and deep learning models utilize observables derived from only the peak power of the delay-Doppler maps (DDMs), discarding the rest. This reduces the data available, which potentially hinders estimation accuracy. In addition, reflections from water bodies dominate the signal amplitude, and using only the peak power in those areas is challenging. Motivated by all the above, we propose a novel deep learning retrieval model for biomass estimation that uses the full DDM of surface reflectivity. Experiments using CYGNSS data have illustrated the improvements achieved when using the full DDM of surface reflectivity. Our proposed model was able to estimate biomass, trained using the ESA Climate Change Initiative (CCI) biomass map, outperforming the model that used peak reflectivity. Global and regional analysis is provided along with an illustration of how biomass estimation is achieved when using the full DDM around water bodies. GNSS-R could become an efficient method for biomass monitoring with fast revisit times. However, an elaborate calibration is necessary for the retrieval models, to associate GNSS-R data with bio-geophysical parameters on the ground. To achieve this, further developments with improved training data are required, as well as work using in situ validation data. Nevertheless, using GNSS-R and deep learning retrieval models has the potential to enable fast and persistent biomass monitoring and help us better understand our changing climate. [ABSTRACT FROM AUTHOR]

Conventional economic growth models treat production/consumption as abstractions linked only by money flows, disregarding their connection to the physical world. Nevertheless, the existing literature suggests that energy flows can influence production and links useful exergy prices with economic growth. Useful exergy is energy measured at the stage where it produces an end-use (and is a measurement of energy quality). Not all approaches in the literature use this metric and they often consider energy as a primary input (despite it being an intermediate input). We explore the relationship between energy flows and economic growth for the US through a framework where useful exergy, the output of an "extended energy sector" (where all effects of increasing primary-to-final-to-useful exergy efficiency are located), is an intermediate input for a "non-energy sector". Together, they encompass the entire economy. We conclude that the share of investment in the extended energy sector grew with the overall economic growth throughout 1960–2020, while the labour share decreased. The non-energy sector contributed the largest share of consumption, exports, imports and labour. In recent years, the energy sector has overtaken it in terms of investment. Our two-sector model has important implications for current climate policy, namely regarding the Integrated Assessment Models on which it is based. [ABSTRACT FROM AUTHOR]

Profile soil moisture (PSM), the soil water content in the whole soil layer, directly controls the major processes related to biological interaction, vegetation growth, and runoff generation. Its spatial heterogeneity, which refers to the uneven distribution and complexity in space, influences refined spatial management and decision-making in ecological, agricultural, and hydrological systems. Satellite instruments and hydrological models are two important sources of spatial information on PSM, but there is still a gap in understanding their potential mechanisms that affect spatial heterogeneity. This study is designed to identify the spatial heterogeneity and the driving factors of two PSM datasets; one is preprocessed from a satellite product (European Space Agency Climate Change Initiative, ESA CCI), and the other is simulated from a distributed hydrological model (the DEM-based distributed rainfall-runoff model, DDRM). Three catchments with different climate conditions were chosen as the study area. By considering the scale dependence of spatial heterogeneity, the profile saturation degree (PSD) datasets from different sources (shown as ESA CCI PSD and DDRM PSD, respectively) during 2017 that are matched in terms of spatial scale and physical properties were acquired first based on the calibration data from 2014–2016, and then the spatial heterogeneity of the PSD from different sources was identified by using spatial statistical analysis and the semi-variogram method, followed by the geographic detector method, to investigate the driving factors. The results indicate that (1) ESA CCI and DDRM PSD are similar for seasonal changes and are overall consistent and locally different in terms of the spatial variations in catchment with different climate conditions; (2) based on spatial statistical analysis, the spatial heterogeneity of PSD reduces after spatial rescaling; at the same spatial scale, DDRM PSD shows higher spatial heterogeneity than ESA CCI PSD, and the low-flow period shows higher spatial heterogeneity than the high-flow period; (3) based on the semi-variogram method, both ESA CCI and DDRM PSD show strong spatial heterogeneity in most cases, in which the proportion of C/(C0 + C) is higher than 0.75, and the spatial data in the low-flow period mostly show larger spatial heterogeneity, in which the proportion is higher than 0.9; the spatial heterogeneity of PSD is higher in the semi-arid catchment; (4) the first three driving factors of the spatial heterogeneity of both ESA CCI and DDRM PSD are DEM, precipitation, and soil type in most cases, contributing more than 50% to spatial heterogeneity; (5) precipitation contributes most to ESA CCI PSD in the low-flow period, and there is no obvious high contribution of precipitation to DDRM PSD. The research provides insights into the spatial heterogeneity of PSM, which helps develop refined modeling and spatial management strategies for soil moisture in ecological, agricultural, and hydrological fields. [ABSTRACT FROM AUTHOR]

In urban settings, trees and greenery play a vital role in environmental well-being and community vitality. This study explores the impact of Miami-Dade County's tree-planting initiative on urban greenness and considers the influence of climate dynamics. Using Landsat data from 2006 to 2019, we find stable overall greenness, with 5.64% of the Census blocks exhibiting significant changes. Seasonal analysis reveals winter as prominent, with 61.47% of Census blocks showing increased greenness. Temperature and precipitation, especially post-2010, correlate with greenness changes. Despite a reported increase in tree cover from 14% to 20%, our findings show only 5–6% of Census blocks with statistically significant changes, highlighting the complexity of achieving substantial improvements in green canopy coverage. The study raises questions about the efficacy of large-scale tree-planting initiatives in densely urbanized areas when human factors are not well understood. Implications for urban planning stress the importance of preserving green spaces and informed decision-making for enhancing vegetation cover in Miami-Dade County, emphasizing the need to consider local conditions, seasonal variations, policies, and human factors in urban greening efforts. [ABSTRACT FROM AUTHOR]

Accurate global monitoring of carbon dioxide (CO2) is essential for understanding climate change and informing policy decisions. This study compares column-averaged dry-air mole fractions of CO2 (XCO2) between ACOS_L2_Lite_FP V9r for Japan's Greenhouse Gases Observing Satellite (GOSAT), OCO-2_L2_Lite_FP V10r for the USA's Orbiting Carbon Observatory-2 (OCO-2), and IAPCAS V2.0 for China's Carbon Dioxide Observation Satellite (TANSAT) collectively referred to as GOT, with data from the Total Carbon Column Observing Network (TCCON). Our findings are as follows: (1) Significant data quantity differences exist between OCO-2 and the other satellites, with OCO-2 boasting a data volume 100 times greater. GOT shows the highest data volume between 30–45°N and 20–30°S, but data availability is notably lower near the equator. (2) XCO2 from GOT exhibits similar seasonal variations, with lower concentrations during June, July, and August (JJA) (402.72–403.74 ppm) and higher concentrations during December, January, and February (DJF) (405.74–407.14 ppm). XCO2 levels are higher in the Northern Hemisphere during March, April, and May (MAM) and DJF, while slightly lower during JJA and September, October, and November (SON). (3) The differences in XCO2 (ΔXCO2) reveal that ΔXCO2 between OCO-2 and TANSAT are minor (−0.47 ± 0.28 ppm), whereas the most significant difference is observed between GOSAT and TANSAT (−1.13 ± 0.15 ppm). Minimal differences are seen in SON (with the biggest difference between GOSAT and TANSAT: −0.84 ± 0.12 ppm), while notable differences occur in DJF (with the biggest difference between GOSAT and TANSAT: −1.43 ± 0.17 ppm). Regarding latitudinal variations, distinctions between OCO-2 and TANSAT are most pronounced in JJA and SON. (4) Compared to TCCON, XCO2 from GOT exhibits relatively high determination coefficients (R2 > 0.8), with GOSAT having the highest root mean square error (RMSE = 1.226 ppm, <1.5 ppm), indicating a strong relationship between ground-based observed and retrieved values. This research contributes significantly to our understanding of the spatial characteristics of global XCO2. Furthermore, it offers insights that can inform the analysis of differences in the inversion of carbon sources and sinks within assimilation systems when incorporating XCO2 data from satellite observations. [ABSTRACT FROM AUTHOR]

The accurate estimation of gross primary productivity (GPP) plays an important role in accurately projecting the terrestrial carbon cycle and climate change. Satellite-driven near-infrared reflectance (NIRv) can be used to estimate GPP based on their nearly linear relationship. Notably, previous studies have reported that the relationship between NIRv and GPP seems to be biome-specific (or land cover) at the ecosystem scale due to both biotic and abiotic effects. Hence, the NIRv-based estimation of GPP may be influenced by land cover changes (LCC) and the discrepancies in multisource products (DMP). However, these issues have not been well understood until now. Therefore, this study took the Yellow River basin (YRB) as the study area. This area has experienced remarkable land cover changes in recent decades. We used Moderate-Resolution Imaging Spectroradiometer (MODIS) and European Space Agency (ESA) Climate Change Initiative (CCI) land cover products (termed MCD12C1 and ESACCI, respectively) during 2001–2018 to explore the impact of land cover on NIRv-estimated GPP. Paired comparisons between the static and dynamic schemes of land cover using the two products were carried out to investigate the influences of LCC and DMP on GPP estimation by NIRv. Our results showed that the dominant land cover types in the YRB were grassland, followed by cropland and forest. Meanwhile, the main transfer was characterized by the conversion from other land cover types (e.g., barren) to grassland in the northwest of the YRB and from grassland and shrubland to cropland in the southeast of the YRB during the study period. Moreover, the temporal and spatial pattern of GPP was highly consistent with that of NIRv, and the average increase in GPP was 2.14 gCm−2yr−1 across the YRB. Nevertheless, it is shown that both LCC and DMP had significant influences on the estimation of GPP by NIRv. That is, the areas with obvious differences in NIRv-based GPP closely correspond to the areas where land cover types dramatically changed. The achievements of this study indicate that considering the land cover change and discrepancies in multisource products would help to improve the accuracy of NIRv-based estimated GPP. [ABSTRACT FROM AUTHOR]

Energy poverty is one of the most critical social challenges in the debate about energy transformation. Reducing the risk of this challenge and mitigating the effects are at the heart of public policies. However, not only the government sector can support people who experience or are at risk of energy poverty. The business sector, especially energy companies, which are the main actors in predefining energy systems in individual countries, can actively participate in this process, among others, through socially responsible activities. The article aims to examine to what extent the problem of energy poverty is an element of social responsibility projects undertaken by energy companies. In addition, it was examined to what extent national climate policies address this issue. The study was conducted using content analysis. The results indicate energy companies' weak interest and engagement in the energy poverty problem. They treat it very peripherally and do not include material topics on the list. The article ends with a set of conclusions for business sector representatives to help develop projects supporting energy poverty combat. [ABSTRACT FROM AUTHOR]

Climate change (CC) is a worldwide environmental issue affecting all economic sectors, especially agriculture. Pakistan is one of the countries most affected by CC due to the country's vulnerability to catastrophic events and limited ability to adapt. Assessing existing activities for adaptation to CC at the farm level is critical to understanding their success and recommending additional government measures. This study analyzes possible farming practice modifications that Pakistani farmers may adopt to reduce the loss of agricultural output due to the rising prevalence of dangerous weather events by CC. Data for the current research were gathered from 432 wheat farmers in rural Pakistan. This article investigates many factors that impact farmers' decisions to CC adaptation in crop production utilizing binary logit (BL) and multivariate probit (MVP) models. Gender, education level, farming experience, farm size, level of damage, access to finance, and training participation are characteristics that substantially affect farmers' likelihood of adapting to CC. Farm size and participation in CC training were the most critical factors influencing farmers' CC adaptation decisions. Policy recommendations were presented to increase the farmers' resilience in the study areas to CC. These comprise expanding CC training courses, developing regulations to encourage agricultural integration, and integrating CC and adaptation to CC principles into the operations of regional organizations. Finally, based on the findings, policymakers will be better equipped to address the challenges posed by CC and create a more resilient agricultural sector. This, in turn, will contribute to improving food security, ensuring sustainable agricultural growth. [ABSTRACT FROM AUTHOR]

The assessment of satellite-derived land surface temperature (LST) data is essential to ensure their high quality for climate applications and research. This study intercompared seven LST products (i.e., ATSR_3, MODISA, MODIST, SLSTRA, SLSTRB, SEVIR2 and SEVIR4) of the European Space Agency's (ESA) LST Climate Change Initiative (LST_cci) project, which are retrieved for polar and geostationary orbit satellites, and three operational LST products: NASA's MODIS MOD11/MYD11 LST and ESA's AATSR LST. All data were re-gridded on to a common spatial grid of 0.05° and matched for concurrent overpasses within 5 min. The matched data were analysed over Europe and Africa for monthly and seasonally aggregated median differences and studied for their dependence on land cover class and satellite viewing geometry. For most of the data sets, the results showed an overall agreement within ±2 K for median differences and robust standard deviation (RSD). A seasonal variation of median differences between polar and geostationary orbit sensor data was observed over Europe, which showed higher differences in summer and lower in winter. Over all land cover classes, NASA's operational MODIS LST products were about 2 K colder than the LST_cci data sets. No seasonal differences were observed for the different land covers, but larger median differences between data sets were seen over bare soil land cover classes. Regarding the viewing geometry, an asymmetric increase of differences with respect to nadir view was observed for day-time data, which is mainly caused by shadow effects. For night-time data, these differences were symmetric and considerably smaller. Overall, despite the differences in the LST retrieval algorithms of the intercompared data sets, a good consistency between the LST_cci data sets was determined. [ABSTRACT FROM AUTHOR]

The pathway, direction, and potential drivers of the evolution in global arid ecosystems are of importance for maintaining the stability and sustainability of the global ecosystem. Based on the Climate Change Initiative Land Cover dataset (CCILC), in this study, four indicators of land cover change (LCC) were calculated, i.e., regional change intensity (RCI), rate of change in land cover (CR), evolutionary direction index (EDI), and artificial change percentage (ACP), to progressively derive the intensity, rate, evolutionary direction, and anthropogenic interferences of global arid ecosystems. The LCC from 1992 to 2020 and from 28 consecutive pair-years was observed at the global, continental, and country scales to examine spatiotemporal evolution in the Earth's arid ecosystems. The following main results were obtained: (1) Global arid ecosystems experienced positive evolution despite complex LCCs and anthropogenic interferences. Cautious steps to avoid potential issues caused by rapid urbanization and farmland expansion are necessary. (2) The arid ecosystems in Australia, Central Asia, and southeastern Africa generally improved, as indicated by EDI values, but those in North America were degraded, with 41.1% of LCCs associated with urbanization or farming. The arid ecosystems in South America also deteriorated, but 83.4% of LCCs were in natural land covers. The arid ecosystems in Europe slightly improved with overall equivalent changes in natural and artificial land covers. (3) Global arid ecosystems experienced three phases of change based on RCI values: 'intense' (1992–1998), 'stable' (1998–2014), and 'intense' (2014–2020). In addition, two phases of evolution based on EDI values were observed: 'deterioration' (1992–2002) and 'improvement' (2002–2020). The ACP values indicated that urbanization and farming activities contributed increasingly less to global dryland change since 1992. These findings provide critical insights into the evolution of global arid ecosystems based on analyses of LCCs and will be beneficial for sustainable development of arid ecosystems worldwide within the context of ongoing climate change. [ABSTRACT FROM AUTHOR]

Simple Summary: Johne's disease is a global economic burden. The disease contributes to reduced milk yield, reduced fertility, higher rates of susceptibility to other diseases and eventual death. Unhealthy animals are less efficient, producing higher kg of greenhouse gases per kg of output (milk and meat). Therefore, prognosis and diagnosis are important in terms of animal welfare and future climate change policies by reducing the impact of livestock on climate change. In the past decade, our knowledge around the microbiome in health and disease has increased. Next generation sequencing technologies have provided a new understanding of the interactions between the host microbiome and pathogens. The microbiome is a target for treatment, prevention of disease and a source of novel biomarkers of disease risk. The potential to improve animal health is highly dependent on our ever growing knowledge of the gut microbiome and their interactions with the host. With the aim to gain knowledge in the early months of exposure to MAP in calves, we investigated the dynamics of the gut microbiome (using faecal sample) of calves 3, 6 and 9 months post inoculation with MAP relative to unexposed controls. Mycobacterium avium subspecies paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, a chronic enteritis which results in emaciation and eventual loss of the animal. Recent advances in metagenomics have allowed a more in-depth study of complex microbiomes, including that of gastrointestinal tracts, and have the potential to provide insights into consequences of the exposure of an animal to MAP or other pathogens. This study aimed to investigate taxonomic diversity and compositional changes of the faecal microbiome of cattle experimentally challenged with MAP compared to an unexposed control group. Faecal swab samples were collected from a total of 55 animals [exposed group (n = 35) and a control group (n = 20)], across three time points (months 3, 6 and 9 post-inoculation). The composition and functional potential of the faecal microbiota differed across time and between the groups (p < 0.05), with the primary differences, from both a taxonomic and functional perspective, occurring at 3 months post inoculation. These included significant differences in the relative abundance of the genera Methanobrevibacter and Bifidobacterium and also of 11 other species (4 at a higher relative abundance in the exposed group and 7 at a higher relative abundance in the control group). Correlations were made between microbiome data and immunopathology measurements and it was noted that changes in the microbial composition correlated with miRNA-155, miR-146b and IFN-ɣ. In summary, this study illustrates the impact of exposure to MAP on the ruminant faecal microbiome with a number of species that may have relevance in veterinary medicine for tracking exposure to MAP. [ABSTRACT FROM AUTHOR]

To meet climate policy goals, it will be necessary to deploy a series of low-carbon energy technologies, including nuclear power. The small modular reactor (SMR) can potentially support climate change mitigation and energy security issues. Small modular reactors (SMRs) are gaining popularity; however, one crucial debate is whether SMRs can compete economically with conventional nuclear reactors or not. From a commercial point of view, SMRs will be able to provide process heat in various industrial applications, replace older nuclear, natural gas, and coal power facilities, and serve smaller energy markets with less established infrastructure. Realizing these advantages would rely heavily on the near-term quick up-scaling of SMRs; this paper, then, examines and identifies some of the most hindering constraints and barriers for the quick deployment of SMR such as the technology choice, licensing, economy of scale and financing, public acceptance, supply chain, and proliferation. A clear identification of the evident and more hidden bottlenecks preventing a quick deployment is made putting in evidence areas in need of much deeper analysis than the one conducted by the SMR community so far. [ABSTRACT FROM AUTHOR]

The implemented climate policy and the current geopolitical situation make us pay special attention to energy independence, both in the household and in the national dimension. One way to obtain inexpensive and environmentally friendly energy is the development of photovoltaic micro-installations. For positive changes to occur, correct state regulation and an appropriate set of administrative and economic instruments are necessary. The purpose of this article is to discuss changes in the accounting system for renewable energy prosumers and their consequences for the further development of renewable energy. The financial settlement methods favorable to prosumers were recently replaced with new solutions. According to the authors, this slows down the energy transformation. [ABSTRACT FROM AUTHOR]

The increasingly severe effects of climate change have resulted in a shift in countries' approach to climate policy. From an initial focus on mitigation efforts, adaptation to climate change is now given equal importance. Adaptation policies in individual countries provide for different sets of instruments owing to different natural conditions and climate change impacts and their resulting problems as well as different approaches related to the sociopolitical characteristics of the country. In the paper, we identify and classify adaptation policy instruments and then look for the differences and similarities in the adaptation instrument mixes included in the national adaptation strategic documents of selected European countries. We focused on Western European (WE) and Central and Eastern European (CEE) countries, as the latter are underrepresented in studies on adaptation policies. Based on text-mining methods, i.e., categorisation of policy instruments using a set of criteria and clustering, we looked for similarities and differences between the adaptation instrument mixes in the chosen European countries. We found similarities between the two CEE countries studied—Poland and Lithuania. These countries are also different from WE countries in this regard. The results indicate that CEE countries have a sectoral rather than systemic approach to adaptation policy, and instruments from the management sphere are less prominent. [ABSTRACT FROM AUTHOR]

Arctic climate change has already resulted in amplified and accelerated regional warming, or the Arctic amplification. Satellite observations have captured this climate phenomenon in its development and in sufficient spatial details. As such, these observations have been—and still are—indispensable for monitoring of the amplification in this remote and inhospitable region, which is sparsely covered with ground observations. This study synthesizes the key contributions of satellite observations into an understanding and characterization of the amplification. The study reveals that the satellites were able to capture a number of important environmental transitions in the region that both precede and follow the emergence of the apparent amplification. Among those transitions, we find a rapid decline in the multiyear sea ice and subsequent changes in the surface radiation balance. Satellites have witnessed the impact of the amplification on phytoplankton and vegetation productivity as well as on human activity and infrastructure. Satellite missions of the European Space Agency (ESA) are increasingly contributing to amplification monitoring and assessment. The ESA Climate Change Initiative has become an essential provider of long-term climatic-quality remote-sensing data products for essential climate variables. Still, such synthesis has found that additional efforts are needed to improve cross-sensor calibrations and retrieval algorithms and to reduce uncertainties. As the amplification is set to continue into the 21st century, a new generation of satellite instruments with improved revisiting time and spectral and spatial resolutions are in high demand in both research and stakeholders' communities. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) retrieved from satellite and spaceborn sensors provides useful parameters for earth system models (ESMs). The Climate Change Initiative (CCI) SM products released by the European Space Agency have been widely used in many humid/semi-humid climatic regions due to their relatively long-term record. However, the performance of these products in cold and arid regions, such as the Qinghai-Tibetan Plateau (QTP), is largely unknown, necessitating urgent evaluation and calibration in these areas. In this work, we evaluated the reliability and improved the accuracy of the active-passive combined CCI products (CCI-C) using in-situ measured SM contents (SMC) under different underlying surface conditions. First, some conventional models were used to investigate the relationship between the CCI-C and the in-situ observed SMC, yielding similar fitting performances. Next, the random forest method and multiple linear regression were used to contrast the conventional models to calibrate and validate the CCI-C SM product based on the in-situ observed SMC, and the random forest method was found to have the highest accuracy. However, calibration of the CCI-C SM data with the best-performed random forest method based on different spatial zonation methods, e.g., by climate, topography, land cover, and vegetation, resulted in distinct spatial patterns of SM. Compared to a widely-used satellite SM product, namely the Soil Moisture Active Passive (SMAP) SM dataset, the calibrated CCI-C SM data based on climatic and vegetation zonation were larger but had similar spatial patterns. This study also points to the value of the calibrated CCI-C SM product to support land surface studies on the QTP. [ABSTRACT FROM AUTHOR]

Phytoplankton phenology studies require a dataset that is continuous in time and space since missing data have been shown to affect the accuracy of seasonality metrics. The interpolated GlobColour product provided by the Copernicus Marine Environment Monitoring Service (CMEMS) meets these requirements by being 'gap filled', thus yielding the highest spatial coverage. Despite being validated on a global scale, a regional comparison to in situ Chl-a concentrations should be conducted to enable product application in optically complex waters. This study aims to evaluate the performance of the GlobColour interpolated product in British Columbia coastal waters via a statistical match-up analysis and a qualitative analysis to determine whether the data reflect the region's large-scale seasonal trends and latitudinal dynamics. Additionally, the statistical performance of the GlobColour interpolated product was compared to the original GlobColour and Ocean Colour Climate Change Initiative (OC-CCI) merged chlorophyll-a products based on in situ observations. The GlobColour interpolated product performed relatively well and was comparable to the best-performing product for each water type (RMSE = 0.28, r2 = 0.77, MdAD = 1.5, BIAS = 0.90). The statistics for all the products degraded in Case 2 waters, thus highlighting the dilemma of applying algorithms designed for Case 1 waters in Case 2 waters. Our results indicate how the quality of products can vary in different environmental conditions. [ABSTRACT FROM AUTHOR]

Today, the energy sector is characterized by a high degree of unsustainability in terms of sources and supply systems, infrastructure, and policies, including climate policy. Therefore, it is necessary to strengthen the functions of planning and to implement new energy strategies, which should lead to the sector's sustainability in the environmental, social, and economic dimensions. In this context, the aim of the article is to develop a model for the sustainability assessment process and to use it as a benchmarking framework for sustainability assessment indices used in energy problems. The study included 14 indices to assess various aspects of sustainable development. The indices were tested in terms of their sustainability dimensions, data sources, data normalization methods, index aggregation methods, and other elements of the sustainability assessment process. As a result of the research, it was found that none of the analyzed indices meet all the requirements for indices that are to be used for the assessment of sustainability. Therefore, the use of these indices in research problems related to energy sustainability requires a conscious analysis of their features and adaptation to specific research problems related to energy sustainability. [ABSTRACT FROM AUTHOR]

The European Union's relative disregard for the economic, geopolitical and climatic concerns of its peripheral Eastern countries has contributed to making the war in Ukraine possible. Its consequences are now returning in the form of energy dependence and economic instability on the Union as a whole and the risk of economic crisis and deindustrialisation. This should prompt a re-assessment of the EU's strategy towards its eastern neighbours, particularly in the energy and climate policy field. This evaluation starts from the issue of control over cheap energy as a key material foundation of state and interstate power. On this basis, we analyse the struggle between Russia and the European core states over Ukraine in terms of the ability to extract an economic surplus through the unequal exchange of energy. The current escalation should be understood as an attempt by the Russian petrostate to preserve the economic basis of its regime, which is threatened by the prospect of a low-carbon transition in Europe. We conclude that a massive acceleration of the transition away from fossil fuels is the key to economic, geopolitical and climate stabilisation, highlighting possible policy instruments the EU could use to secure its production system and protect citizens' security. [ABSTRACT FROM AUTHOR]

There are multiple extreme events underway in the Arctic that are beyond previous records: rain in Greenland, Alaska weather variability, and ecosystem reorganizations in the Barents and the northern Bering Sea associated with climate change and sea-ice loss. Such unique extreme events represent a philosophical challenge for interpretation, i.e., a lack of statistical basis, as well as important information for regional adaptation to climate change. These changes are affecting regional food security, human/wildlife health, cultural activities, and marine wildlife conservation. Twenty years ago, the Arctic was more resilient to climate change than now, as sea ice had a broader extent and was three times thicker than today. These new states cannot be assigned probabilities because one cannot a priori conceive of these states. They often have no historical analogues. A way forward for adaptation to future extremes is through scenario/narrative approaches; a recent development in climate change policy is through decision making under deep uncertainty (DMDU). [ABSTRACT FROM AUTHOR]

The paper focuses on developing an energy-modeling tool called ENECO2Calc, which allows the determination of current ecologic and economic footprints based on calculating the final energy demand within several sectors for municipalities. Furthermore, different energy transition paths until 2050 can be investigated and compared to the business-as-usual reference scenario. ENECO2Calc is the first municipality-based energy-modeling tool that allows the development of meaningful scenarios until 2050 by considering climate policy goals and RES potentials, and it involves the mobility emission forecast tool "PROVEM". ENECO2Calc is exclusively based on consistent statistical datasets. Additionally, the energy-modeling process was demonstrated as exemplary for the Austrian municipality St. Margareten im Rosental. For the selected municipality, three different scenarios were investigated. It could be concluded that a mix of decentral RES technologies and central cogeneration units in the heat sector, a mix of solar PV and cogeneration units in the electricity sector, and the use of synthetic biofuels coupled with a higher share of electrification in the fuel sector seemed to be most promising in the considered region. ENECO2Calc is a helpful energy-modeling tool toward climate neutrality to support municipalities in developing appropriate economic and ecological footprint strategies. [ABSTRACT FROM AUTHOR]

The trade impacts of the COVID-19 pandemic and the Russian invasion of Ukraine have raised questions about the role of trade and climate policies in energy security and global emissions. This study updates a widely used integrated assessment model (IAM), MESSAGEix-GLOBIOM, to represent complex trade networks to explicitly draw energy flows from their origins to their destination. It then examines the effects of (1) energy trade tariff policies, such as import tariffs, as a proxy to represent an unfriendly trade environment and (2) a global carbon emissions tax on the global energy trade network. Results indicate that trade tariff policies have marginal effects on the trade network, i.e., the size of trade and importing-exporting regions do not change significantly. While high import tariffs significantly reduce emissions due to reduced fossil fuel imports in the importing region, this effect does not translate to significant emission reductions globally, as trade policies only impact downstream of the energy supply chain. However, a carbon emission tax dramatically alters the trade network, by (1) reducing its size by up to 50% and (2) forming trade linkages that allow for a more complex and diverse network of suppliers. This diversity under the emissions tax scenario improves the energy security of major energy-importing regions. Moreover, under an emission tax scenario, a friendly trade environment reduces the energy system costs globally. However, trade friction, such as sanctions or high import tariffs, will increase the energy supply cost significantly, especially for energy-importing regions such as Europe, East and South Asia. [ABSTRACT FROM AUTHOR]

Improving energy efficiency and minimizing environmental concerns through environmental laws and green taxes are regarded as the primary motivating factors of climate change policy. This analysis clarifies the significance of green taxes in lowering energy use and intensity from 1994 to 2020. As part of our contribution to the literature on energy economics, this study examines how green taxes interact with energy intensity and consumption in four Nordic nations. Environmental policies and sustainable development goals (SDGs) are driving new research into the effects of green taxes on energy consumption and intensity. According to the outcomes of fully modified ordinary least square (FMOLS), panel dynamic ordinary least square (PDOLS), and panel quantile regression, a green tax helps to reduce total energy consumption. It increases energy efficiency by motivating governments, companies, and citizens to encourage innovation in environment-related technology. When it comes to creating a more sustainable environment, the study argues that regulations that ensure the displacement of non-renewable resources while increasing energy efficacy should be implemented. [ABSTRACT FROM AUTHOR]

The European transition to green economy is based on long-term strategies. The Europe 2020 Strategy was launched in 2010 in order to promote smart, sustainable, and inclusive growth in the region. Later, the ambitions regarding this strategy were followed by the Green Deal and Sustainable Development Goals. Now, the effort of countries towards the green economy is even more relevant than ever because of the context of today's global energy crisis and economic uncertainty due to many challenges such as the COVID-19 pandemic or Russia invasion of Ukraine. This paper seeks to assess the countries' achievements in seeking climate change and energy targets of the Europe 2020 Strategy by applying the innovative multi-criteria decision-making (MCDM) technique. The kernel-based comprehensive assessment (KerCA) method was applied for the calculations of the progress achieved and countries' rankings. It allows to evaluate countries' achievements and compare them using the mathematical models. The analysis of the national target implementation in the countries allows to determine the compliance of countries with their commitments and liability towards other countries and the European Union (EU). An analysis of the implementation of the strategy can serve as a guide to further develop climate change and energy policy in the region. Furthermore, the added value of the article is systematic overview of scientific studies proposing different methodologies for the analysis of target implementation at the whole region level. The novelty of this paper also relies on the approach, which considers not only the level of achievement of the target, but also assesses the excess. [ABSTRACT FROM AUTHOR]

Extreme climate events undoubtedly have essential impacts on terrestrial ecosystems, but the spatiotemporal patterns of extreme climate events at regional scales are unclear. In this study, based on observations and 14 CMIP6 global climate models, we analyzed the spatiotemporal changes in extreme temperature events at the mainland China scale and different basin scales in historical and future periods, and their relative importance for the changes in mean temperature (Tmean). The results show that at the mainland China scale in the historical period, extreme cold days and extreme cold nights significantly decreased, while Tmean, extreme warm days, and extreme warm nights significantly increased. However, the rates of increase in Tmean and extreme temperature events in the Continental Basin, Southwest Basin and Yellow River Basin are higher than that at the mainland China scale. The multi-model ensemble is the best model for simulating extreme temperature events in mainland China. At the mainland China scale in the future, the trends of Tmean and extreme temperature events are slow, rapid, and extremely rapid under SSP1-2.6, SSP2-4.5 and SSP5-8.5, respectively. In addition, the changes in the Continental Basin and Songhua and Liaohe River Basin are larger than those at the mainland China scale. In the historical and future periods, the extreme temperature events that have a great influence on the Tmean at the Chinese mainland scale and different basin scales are all related to the minimum temperature. The findings from this study can provide references for formulating scientific and reasonable regional-scale climate change policies. [ABSTRACT FROM AUTHOR]

Infeasible solutions or negative expected values of future climate information are undesired problems if climate policies are adopted under Cost-Effectiveness Analysis (CEA) to reach uncertain temperature targets. Cost-Risk Analysis (CRA) was developed to resolve these issues. It allows for a trade-off between expected welfare losses of mitigation and avoided risk of transgressing a climate target with a certain probability of compliance (Safety). Some of the significant contributions of this paper are: (i) It updates the Probabilistic Integrated model of Climate and the Economy (PRICE) as a probabilistic version of the latest version of the Dynamic Integrated Climate-Economy model (DICE) 2016, and it extends the model to run welfare-maximizing decision analytic frameworks readily. (ii) It highlights that the standard method of applying CRA (Old CRA) leads to an extra welfare cost. (iii) It proposes revised instruction on how to use CRA. (iv) It simulates and compares welfare-maximizing decision analytic frameworks on the level of risk, damages, and carbon prices. (v) It measures the value of information using risk-based methods and compares them with the value of information calculated using the damage-based method. (vi) It measures the carbon prices for the CRA scenarios for the first time. The results show that the choice of the disutility function governs the magnitude of the value of information. Using a damage function or Old CRA, the value of information is significantly high for new information arriving between 2020 and 2060. If the New CRA is applied, however, such benefits are negligible. [ABSTRACT FROM AUTHOR]

This study introduces Pakistan's multidimensional energy security index (PMESI) and indices across dimensions from 1991 to 2020 through indicator optimization. Based on criteria, expert participation, and reliability testing, 27 indicators were identified and weighted based on dimension reduction utilizing the Varimax Rotation technique. As a result of robust evaluation framework, there has been a considerable change in Pakistan's energy security when compared to other studies such as the energy security indicator of Pakistan (ESIP) and the energy security index of Pakistan (ESIOP). According to the findings, energy security decreased by 25% between 1991 and 2012, followed by a modest increase through 2020. During the study period, the "Affordability" dimension improved; however, the other four dimensions, namely "Availability," "Technology," "Governance," and "Environment," regressed. Few goals under the petroleum policy (1991), petroleum policy (2012), and power policy (2013) were partially met, while conservation programs, such as the renewable policy (2006) and national climate change policy (2012), fell short. Indicators such as price, reserves, governance, corruption, and consumption contributed to PMESI across five dimensions. Thus, PMESI and indices guiding policymakers to focus on improving governance and exploiting local energy resources in order to provide affordable and sufficient energy in the long run. [ABSTRACT FROM AUTHOR]

To obtain the price return and price volatility spillovers between renewable energy stocks, technology stocks, oil futures and carbon allowances under different investment horizons, this paper employs a frequency-dependent method to study the dynamic connectedness between these assets in four frequency bands. The results show that, first, there is a strong spillover effect between these assets from a system-wide perspective, and it's mainly driven by short-term spillovers. Second, in the time domain, technology stocks have a more significant impact on renewable energy stocks compared to crude oil. However, through the study in the frequency domain, we find renewable energy stocks exhibit a more complex relationship with the other two assets at different time scales. Third, renewable energy stocks have significant spillover effect on carbon prices only in the short term. On longer time scales, other factors such as energy prices, climate and policy may have a greater impact on carbon allowance prices. Fourth, the spillover effect of the system is time-varying and frequency-varying. During the European debt crisis, the international oil price decline and the COVID-19 pandemic, the total spillover index of the system has experienced a substantial increase, mainly driven by medium, medium to long or long term spillovers. [ABSTRACT FROM AUTHOR]

Increasing awareness of climate change has induced demand for action most notably. As public demand for action on climate change increases, conversion to energy sources with lower greenhouse gas (GHG) intensity will accelerate. Experience during the COVID-19 pandemic provided insight into how atmospheric conditions will respond to lower GHG emissions. A low-carbon future will require decarbonization of the energy supply mix for electrical production and industrial processes. Coal demand likely will decrease more rapidly than other fossil energy sources, replaced by natural gas and renewable energy sources that have lower GHG intensity and that will be available readily and economically. This decline will accelerate as China focuses on its carbon neutrality goals, the U.S. re-engages in the Paris Agreement, and India moves to a lower carbon future. However, perturbations in the decline will inevitably occur in response to global issues (e.g., pandemic, military conflict). Carbon capture, utilization, and storage (CCUS) technologies can reduce GHG emissions from coal as an energy source, but the capital and operation costs of CCUS remain high, which translates to slow commercial deployment. In this study, a literature review and interviews with industry experts and business leaders were conducted to understand the current and projected role of fossil fuels, primarily coal, in the global energy matrix; present their contributions to GHGs; analyze the effects of social expectations and climate policy on energy choices and coal demand; and describe the expected impacts on coal production for decades to come. [ABSTRACT FROM AUTHOR]

Studies from the United States (U.S.) show that opposition to climate policy is strong among some Christian groups, especially White evangelical Protestants. Much of this opposition is channelled through organisations such as the Cornwall Alliance, which argue against climate measures on religious, economic and what they claim to be science-based grounds. In the present study, we investigated to what extent these convictions were present among Swedish evangelical denominations. Representatives from the Evangelical Free Church, the Pentecostal Alliance, the Swedish Alliance Mission, and the Seventh-day Adventist Church were interviewed to identify the denominations' views on the scientific underpinnings of climate change and the moral implications of climate policy. Our data show that the denominations' views differ markedly from those expressed by climate-oppositional evangelical groups in the U.S. The denominations held homogenous views on the legitimacy of climate science, expressed a clear biblical mandate for climate policy based on the notion of human stewardship, and believed that climate change was inextricably linked to poverty and, thus, had to be addressed. Our results point to the need for further studies on the factors behind acceptance and denial of climate science within and between faith-based and other communities in different countries. [ABSTRACT FROM AUTHOR]

Climate change, as well as the challenges that come with it, is one of the main issues in international and national politics today. Addressing the threats posed by climate change requires close cooperation at the international level and within each country, creating a dialogue between the political elite and society, thus promoting a common understanding and action across the European Union (EU). The aim of this research is to (1) identify what climate policy narratives are projected to the Latvian electorate (public) and (2) assess how these narratives are aligned with the EU-defined strategic climate policy narrative. The theoretical basis and methodological approach of the study is based on the concept of strategic narrative. It is assumed that the viability and impact of a strategic narrative is enhanced when there is coherence between all stages of the narrative life cycle (i.e., the EU level and the national policy level). The empirical basis of the study is based on the identification of the EU climate policy narrative in the sector's regulatory documents, as well as an analysis of the election programmes of Latvian political parties (the last European Parliament (2019) and parliamentary (2018) election programmes). The results show that the narrative that the Latvian public receives from its political elite through the European Parliament and the national pre-election programmes is significantly different from the EU strategic narrative on climate policy. Based on the theoretical concept of strategic narrative, it can be concluded that the observed dissimilarity of narratives does not stimulate the inclusion of the Latvian public in the common EU space of climate policy understanding and action. [ABSTRACT FROM AUTHOR]

To effectively mitigate climate change, it is crucial to better understand the reaction of fossil-fuel demand to price and tax changes, and more precisely to climate policy instruments such as a carbon levy. The Swiss CO2 levy on heating fuels was introduced in 2008 at CHF 12/tCO2eq, and was increased steadily up to CHF 84/tCO2eq during the period of 2016/2017. This paper investigated the effectiveness of the levy as an instrument to reduce heating fuel demand, and hence carbon emissions, of private real estate owners. The Swiss Household Budget Survey 2006–2017 constituted the main data source. Before–after and pseudo-panel regressions were used to capture the CO2 levy's effects, and a large set of household characteristics, as well as climatic conditions, were controlled for. No significant effects in the first two policy periods of 2008–2013 were found. Over the period of 2014–2017, a significant reduction in house owners' heating fuel demand of up to 14% with respect to 2006–2007 was detected. The effect was less significant and smaller in magnitude for flat owners. A significant CO2 levy semielasticity of heating fuel demand of −1.3% for house owners was further estimated. Hence, the results confirmed the effectiveness of the CO2 levy under the conditions that the levy was sufficiently high, as during the years of 2014–2017, and households directly paid the levy and were responsible for decisions concerning heating and insulation, as was the case for house owners. [ABSTRACT FROM AUTHOR]

The study shows that the current network of hydrometeorological observation in the permafrost zone of Russia is insufficient to provide data for the statistical approaches adopted at the state level for engineering surveys and calculations. The alternative to the financially costly and practically impossible expansion of the monitoring network is the development of hydrological research stations and the implementation of new methods for calculating streamflow characteristics based on mathematical modeling. The data of the Kolyma Water-Balance Station, the first research basin in the world in a permafrost environment (1948–1997), and the process-based hydrological model Hydrograph are applied to simulate streamflow hydrographs in remote mountainous permafrost basins. The satisfactory results confirm that mathematical modeling may substitute or replace statistical approaches in the conditions of extreme data insufficiency. The improvement of the models in a changing climate requires the renewal of historical observations at currently abandoned research stations in Russian permafrost regions. The study is important for forming the state policy in climate change adaptation and mitigation measures. [ABSTRACT FROM AUTHOR]

Recent decades have shown significant changes to the hydrological cycle over East Asia (EA), and further changes are expected due to future global warming. This study evaluates projected seasonal changes in the EA hydrological cycle using simulations that are 1.5 °C, 2.0 °C and 3.0 ∘ C warmer than pre-industrial, from the Met Office Unified Model (MetUM) Global Ocean Mixed Layer model version 2.0 (GOML2.0), compared against present-day conditions. The moisture sources of the warming-induced precipitation changes are identified over five hydrologically unique regions within EA. Precipitation over EA increases with warming (except over southeastern EA in the spring and autumn) due to the intensified hydrological cycle. The projected seasonal changes in the hydrological cycle are usually nonlinear, with the rate of change between 1.5 ∘ C and 2.0 ∘ C larger than the rate of change between 2.0 ∘ C and 3.0 ∘ C of warming. The warming-induced precipitation increases are mainly associated with an increase in remote moisture convergence rather than local moisture recycling, except over the Tibetan Plateau. Decomposition of the changes in moisture sources by direction and flux component indicate that changes from the west are dominated by changes to moisture and changes from the north are more circulation driven. The changes from the south are moisture driven over southern EA and driven by moisture and circulation change over northern EA. Our results highlight the regionally and seasonally diverse projected changes to the EA hydrological cycle due to global warming, which will be useful for region-specific climate mitigation policies and the implementation of seasonally varying adaptation methods. [ABSTRACT FROM AUTHOR]

For decades, combating climate change has been a global challenge, which requires jointly coordinated efforts by numerous, international actors. However, it has been shown time and again that agreeing on globally binding agreements without a global government proves difficult. To this end, this paper examines the possibility of a tolerance premium. This means a transfer payment in exchange for accepting and complying with the associated agreement. The provider of this tolerance premium determines the conditions of its payment to set desired incentives. Thus, collective decision making can also be self-enforced without a higher authority. This scenario is studied analytically based on Dixit's conflict model. The study shows that the optimal tolerance premium depends only on the value of the prize to the transferee and that this can result in a stalling of the conflict. The implications of this model shed light on the design of global climate agreements that are self-enforcing without the need for a global government. For this purpose, the upfront payment of funds and their reimbursement as a tolerance premium serve as an incentive to comply with collectively agreed rules in climate policy. [ABSTRACT FROM AUTHOR]

I estimate the cost of meeting the EU 2030 targets for greenhouse gas emission reduction, using statistical emulators of ten alternative models. Assuming a first-best policy implementation, I find that total and marginal costs are modest. The statistical emulators allow me to compute the risk premiums, which are small, because the EU is rich and the policy impact is small. The ensemble of ten models allows me to compute the ambiguity premium, which is small for the same reason. I construct a counterfactual estimate of recent emissions without the climate policy and use that to test the predictive skill of the ten models. The models that show the lowest cost of emission reduction also have the lowest skill for Europe in recent times. [ABSTRACT FROM AUTHOR]

The main aim of the research is to evaluate the innovativeness of Polish municipalities in the field of energy. The study was carried out as a part of the First National Competition for the Most Innovative Local Government in Poland, taking into account the original method of assessing the innovativeness of local governments. From all over Poland, 30 communes participated in the research: 14 urban communes, 8 rural communes, and 8 urban–rural communes. The study analyzes the activities of municipalities in the field of energy-related construction and transport innovations and inventories innovative social campaigns in the area of climate and energy policy implementation. The second part of the article presents a case study of innovations recognized as exemplary. As a result of the conducted research, it was found that 50% of the surveyed local governments are innovative and the remaining are moderately innovative. No commune has been assigned to the non-innovative category. In terms of the type and size of the local government, it has been observed that smaller municipalities, mainly rural local governments, allocate much higher financial resources per capita to the implementation of modern solutions in the field of climate and energy policy implementation. In some cases, commune heads spend several times higher funds per capita than mayors and city presidents. The use of the developed innovation research method in practice may motivate local government authorities to increase innovative activities for energy transformation. [ABSTRACT FROM AUTHOR]

The greatest challenge in accelerating the realisation of a sustainable and competitive bioeconomy is to demonstrate that enshrining sustainability principles at the very heart of a production line can generate value and improve its overall system. Strategies for reducing emissions, pollutants, indirect land use change or soil depreciation are all perceived as costs or necessary inconveniences to comply with stringent, climate change-focused policy frameworks. System dynamics modelling and competitive priorities are tools that can accurately and intelligently expand on the cross-value chain approach, which integrates both technical and environmental performances, to address the issue of harmonising sustainability and technical operations as one overall dimension of performance. A stock-and-flow model is developed to map a full biofuel value chain and quantitatively and coherently integrate factors of emissions, carbon, land, production, and technology. As such, environmental and operational impacts of innovative practices are measured, and subsequently linked to a qualitative framework of competitive priorities, as defined by transparency, quality, innovation and flexibility. Sustainability and productivity functions are found to reinforce each other when all competitive priorities are optimised. Equally, the framework provides a clear understanding of trade-offs engendered by value chain interventions. Advantages and limitations in the accessibility, scope and transferability of the multi-pronged analytical approach are discussed. [ABSTRACT FROM AUTHOR]

The article presents an innovative method of analyzing energy companies' strategies, which aims to identify the strategic orientation of the entities subject to the research and, thus, to initially define the directions of strategic changes in the analyzed sector. The aim of the research, the results of which were used in this publication, was to identify the features of energy sector companies' strategies in the European Union in the period of sector transformation caused by the new climate policy. The analysis area is the energy sector, i.e., the sector whose fundamental strategic goal is energy production. The research used a critical analysis of the subject literature and desk research method with the use of the researchers' own analytical equipment, developed for the needs of this analysis. It was assumed in the conducted research that the primary source of information in the empirical study, the information subject to subsequent analysis, was the analysis of official documents (strategies, financial reports, etc.) posted on the websites of the surveyed corporations. The research results indicate the dominance of the resource-based approach in implementing strategic postulates of the surveyed companies. Nevertheless, the operational activity focuses on the implementation of innovative solutions towards decarbonization and climate neutrality. [ABSTRACT FROM AUTHOR]

This paper contributes to the climate policy discussion by focusing on the challenges and opportunities of reaching net zero emissions by 2050 in Italy. To support Italian energy planning, we developed energy roadmaps towards national climate neutrality, consistent with the Paris Agreement objectives and the IPCC goal of limiting the increase in global surface temperature to 1.5 °C. Starting from the Italian framework, these scenarios identify the correlations among the main pillars for the change of the energy paradigm towards net emissions by 2050. The energy scenarios were developed using TIMES-RSE, a partial equilibrium and technology-rich optimization model of the entire Italian energy system. Subsequently, an in-depth analysis was developed with the sMTISIM, a long-term simulator of power system and electricity markets. The results show that, to achieve climate neutrality by 2050, the Italian energy system will have to experience profound transformations on multiple and strongly related dimensions. A predominantly renewable-based energy mix (at least 80–90% by 2050) is essential to decarbonize most of the final energy consumption. However, the strong increase of non-programmable renewable sources requires particular attention to new flexibility resources needed for the power system, such as Power-to-X. The green fuels produced from renewables via Power-to-X will be a vital energy source for those sectors where electrification faces technical and economic barriers. The paper's findings also confirm that the European "energy efficiency first" principle represents the very first step on the road to climate neutrality. [ABSTRACT FROM AUTHOR]

The consequences of climate change are an important point of contention in the current policy debate on the sustainability of economic development and growth. Climate change contributes to many socio-economic disadvantages and risks. The primary objective of global policy 2050 is to fully understand the negative externalities of environmental change. Goal and methodology: the main goal of the study is to examine convergence to the steady green growth state for a sample of 130 countries from 1990 to 2019. Setting up an efficient and consistent policy to fight climate change demands empirical knowledge on green growth. Using log (t) test methodology, we investigate convergence in green growth indicators for selected samples based on available country data. Findings: our assumptions are: (1) economies are not motivated and eager to foster energy transition; instead, they accept it as a random policy goal and (2) economies want to foster energy transition, but they are limited by a significant trade-off factor pulling their efforts down. Convergence testing shows the existence of two significant convergence clubs, one with countries moving to energy transition and the second still promoting national output based on fossil fuels. The findings indicate future divergence between the two clubs and significant convergence within identified convergence clubs. Conclusions: the energy transition is moving forward at two-tier speed with green leaders and green follower clubs. Policymakers and practitioners must closely monitor the dynamics of green growth to assess the risk and uncertainties of climate change. [ABSTRACT FROM AUTHOR]

Few challenges pose a greater threat to a healthy planet and people than air pollution and climate change. Over the past three decades, research has demonstrated that integrated solutions to air pollution and climate change can yield co-benefits that support cost-effective, coherent policies. However, research on co-benefits has yet to generate policy responses consistent with this promise. This paper argues that realizing this potential requires more rigorous research on how governance affects the opportunities and incentives to align the interests of government agencies, scientists, and other stakeholders at multiple levels. The article proposes a "One Atmosphere approach" consisting of three building blocks to strengthen that alignment: (1) continually incorporating and strategically timing the introduction of integrated visions; (2) reforming governance arrangements to encourage interagency collaboration and multi-stakeholder cooperation; and (3) supporting integrated visions and institutional cooperation with standardized metrics and assessment methods. This article is also the introduction to the Special Issue 'One Atmosphere: Integrating Air Pollution and Climate Policy and Governance', aimed at fostering the multidisciplinary dialogue needed for more integrated air pollution and climate change policies. [ABSTRACT FROM AUTHOR]

This article presents the historical progression of changes and arguments indicating the need to move from fossil energy sources to the green economy in the European Union (EU) countries. It shows trends in the EU's climate and energy policy compared to the rest of the world. At the same time, it points to the elements of the necessary compromise between the climate requirements and the energy security of countries and their economies. The aim of the article is to present the main quantitative challenges for the development of the green economy in the EU, which are analyzed from the perspective of the year 2030. For this year, specific values have been established to be achieved by European countries in several fundamental areas. On the other hand, the strategic goals and further development perspective are included until 2050. This undoubtedly indicates the complexity of the issue, which is intensified as a result of the various economic and political strategies of many European Union members. At the same time, as part of the analysis carried out, efforts are made to develop concepts and practical recommendations for the development of a green European economy. [ABSTRACT FROM AUTHOR]

The ongoing climate changes necessitate an effective climate policy. The energy transition is now an important topic and problem, especially in Poland. (1) The undertaken analysis of the problem of energy transition is important for political, social and technological reasons. Political, because it shows the weakness of the implementation of Polish energy policy in regards to climate change. Social, because energy transition will bring about significant social changes in the largest industrial region of Poland. Technological, as the departure from fossil fuels requires the introduction of other sources of energy on a massive scale, for which Poland is not prepared. The aim of the study was to critically analyse the activities to date in the field of energy transition in Poland. The second goal of the analysis was an attempt to answer the question of whether the process of energy transition and achieving the goals set in the EU's European Green Deal are possible at all until 2050. (2) To achieve the goals, the system method and the decision-making method were primarily used. These methods allowed for an examination of the main determinants of the Polish energy transformation. (3) The main results include the confirmation, contrary to the announcements of the Polish government, that despite the adoption in Poland of the strategy "Poland's energy policy until 2040", the effective implementation of the energy transition before 2050 is not only very difficult, but may even be impossible to implement in the assumed time. This is due to political, economic, social and technological conditions. Coal energy is outdated, expensive and ineffective. Due to natural conditions, wind energy is not able to meet the energy demand of the industry. The development of nuclear energy is only in the planning phase. (4) To sum up, in the next thirty years, Poland will not be able to achieve the assumed effects of the energy transition, which is in contradiction with the official declaration of the government. [ABSTRACT FROM AUTHOR]

The energy sector is expected to face fundamental challenges in the near future. On the one hand, it is experiencing a rapidly increasing demand for energy. At the same time, it is subject to the pressure of the climate policy due to environmental issues. For the same reason, the energy sector is forced to undertake costly investments to transform production from black to green energy. The issue of financing has become one of the key problems of the energy sector, especially in those countries in which energy production traditionally is based on fossil fuels, i.e., coal. The paper aims to investigate the impact of corporate governance on the capital structure of companies from the energy industry. We use three proxies of corporate governance quality: institutional investors, the board size, and state ownership and investigate their impact on capital structure. Our findings suggest that the latter two negatively impact debt levels. In our model, we control for financial factors and CEO personal characteristics. We use a Polish setting since transformational problems of the energy sector in Poland are especially visible. At the same time, energy companies in Poland are subject to the strict EU climate policy. [ABSTRACT FROM AUTHOR]