Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: 4c,d respectively, and indicate that intraseasonal variations account for a large part of the total variance (Liebmann et al. 1999). Based on the spatial pattern of the OLRA variability, we defined a base region (solid lines) in which the magnitudes of the OLRA were used to characterize periods of weak (strong) SACZ. The extent of the base region is chosen to represent the mean position of the SACZ. A time series of 30–70-day OLRA spatially averaged in the base region was constructed and periods above (below) 0. 8 (−0. 8) standard deviation during the austral summer were selected. The weak events are denoted IS1 positive (IS1 pos), while the strong are IS1 negative (IS1 neg). In addition, periods of very inactive SACZ were selected when the magnitudes of the 30–70-day OLRA values in the base region were between ±0. 3 standard deviation (IS1 null). Likewise, a time series of 10–30-day OLRA was constructed over the base region. Periods of weak IS2 variability were selected when OLRA are above 0. 8 standard deviation (IS2 pos); strong when OLRA are below −0. 8 standard deviation (IS2 neg); and null events when OLRA are between ±0. 3 standard deviation (IS2 null). The frequency distributions of the selected IS1 and IS2 events per season are plotted in Fig. 5. For the IS1 type (top) there are a total of 27 (IS1 pos), 29 (IS1 neg), and 32 (IS1 null) pentads, which represent 11, 11, and 20 independent events, respectively. Similarly, for IS2 type there are 23 (IS2 pos), 23 (IS2 neg), and 34 (IS2 null) pentads, so that 20, 19, and 22 are independent events. We consider independent events nonconsecutive pentads. The skill of the MRF model in forecasting Z500 was examined for each sample of intraseasonal variability defined above (IS1 and IS2). Two skill measures, anomaly correlation and root-mean-square (rms) error, were computed for samples IS1 pos, IS1 neg, IS1 null, IS2 pos, IS2 neg, and IS2 null. [SEP] Justify:

Output: The text discusses variations in OLRA (Outgoing Longwave Radiation Anomaly) and its categorization into different events, but it does not address microclimates or their impact on weather variations over short distances. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: To interpret these scenarios, Pathways (IMPs) were described, which represent multiple pathways to achieve net-zero CO2 emissions. These pathways are generally characterized by decarbonization of energy systems, reduction of energy demand3,4, promotion of renewable energy sources and electrification5 or the offsetting of residual emissions through carbon dioxide removal (CDR) processes (e. g. , bioenergy carbon capture and storage [BECCS] and afforestation)6,7. In addition to the IMPs, various unique low-emission pathways have recently been analyzed, such as CDR-oriented scenarios based on direct air carbon capture and storage (DACCS)8,9 and degrowth scenarios10. Because each transformation pathway generally involves multiple risks associated with sustainability11,12, and rapid changes in energy systems are hindered by feasibility concerns 13,14, there is a need for exploration of a diverse portfolio of net-zero emissions pathways during the development of post-AR6 mitigation scenarios to facilitate the achievement of robust and flexible net-zero energy systems. In this context, carbon capture and utilization (CCU) is a promising alternative to the reduction of residual emissions15–18. Synthetic hydrocarbon fuels (synfuels) derived from carbon-neutral sources (e. g. , direct air capture [DAC], biomass, and low-carbon hydrogen) can provide low-carbon liquefied and gaseous energies. These energy carriers have advantages in terms of energy density relative to other energy carriers; they could be used with existing energy infrastructure and technology. Because of recent cost decreases in solar and wind power19,20 and increasing expectations for the commercialization of DAC21,22 to facilitate large-scale CCU implementation, the potential applications of these carriers have been explored in specific sectors23,24 (e. g. , transport fuels) and regions25,26 using Models. Nevertheless, their economy-wide potential and the challenges associated with achievement of stringent mitigation goals, such as 1. 5°C without overshoot, remain unclear. Here, we performed what-if scenario analysis to explore the potential of implementing CCU in the global energy system using the AIM/Technology (Asia-Model/Technology)27 model, which is a bottom-up global energy system model that accurately represents energy technologies in the energy demand and supply sectors. [SEP] Justify:

Output: The text corroborates the claim by discussing various pathways for achieving net-zero CO2 emissions, which include the promotion of renewable energy sources and the decarbonization of energy systems. It highlights that renewable energy can play a significant role in reducing reliance on fossil fuels and decreasing carbon emissions, evidenced by references to solar and wind power, as well as the development of carbon capture and utilization initiatives.


Input: Task: contrast the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: Unexpectedly, technological innovation has a significant positive association with CO2Es. This discovery is congruent with the findings of Alnafisah et al. (2024), Chen et al. (2024), Lee et al. (2024), Mehmood et al. (2024), Rahman and Ferdaous (2024), Rahman et al. (2024), Wang et al. (2024), Chaudhry (2023), Li et al. (2022), Villanthenkodath and Mahalik (2022), Rahman and Alam (2022), Xiaoyang et al. (2022), Dauda et al. (2021), and Khattak et al. (2020). Even though this discovery is against our intuition, it can be explained. is Africa's most technologically advanced, industrialised, and diversified country. Technological innovations in its heavy industrial sector increase industrial activity and production, leading to higher CO2Es. Even though has adopted some technologies to reduce CO2Es, it still relies on coal for electricity production. Technological innovations in coal-powered electricity plants (e. g. , carbon capture and storage) prolong dependence on coal, resulting in sustained CO2Es. In the transport sector, technological innovations (e. g. , the production of fuel-efficient vehicles) have resulted in increased mobility and transportation activity, and in construction and infrastructure development, technological innovations have promoted urbanisation and construction activity, leading to higher energy consumption and CO2Es. is rich in natural resources (e. g. , minerals), which are at the centre of technological innovations. Nevertheless, resource processing and extraction require much energy, resulting in higher CO2Es, mainly if fossil fuels are used. Technological innovations in electrical devices have increased electricity demand. This electricity is mainly generated from fossil fuel-powered electricity generation plants, leading to higher CO2Es. Technological advancement also results in the manifestation of wastes that are harmful to the environment. Our result can be an indication that most patent applications in have nothing to do with clean energy technology or energy-saving technology that can reduce CO2Es. That is to say, less attention is given to eco-friendly innovation. is chasing economic growth but must care more about the environment. Clean innovation is not a vital resolve of the country. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that despite some technological advancements aimed at reducing CO2 emissions, there is a significant continued reliance on fossil fuels, particularly coal, for electricity generation and industrial activities. It states that technological innovations in various sectors have led to increased mobility and energy consumption, resulting in higher CO2 emissions. Furthermore, the text implies that there is insufficient focus on clean energy technologies, indicating that rather than reducing reliance on fossil fuels or decreasing carbon emissions, these innovations can lead to an increase in CO2 emissions.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: The statistics were then averaged over the SACZ base region indicated in Fig. 4 (solid lines) and over the region defined by (40°S–20°N; 90°–20°W). Figure 6 shows the anomaly correlation averaged over the SACZ domain (top) and over the domain (bottom). The anomaly correlation during IS1 averaged over the SACZ domain (top left) indicates that the correlations start at about the same values (0. 65) for IS1 pos, IS1 neg, and IS1 null for 1-day lead time. Note that these values are averaged over the SACZ domain and the MRF model shows higher skill farther south (see Fig. 3). However, as forecast time progresses, the anomaly correlations for IS1 null are systematically smaller than IS1 pos and IS1 neg. Correlations of 0. 3 persist up to 10 days lead time for IS1 pos and IS1 neg. The anomaly correlations during IS2 averaged over the SACZ (top right) show similar magnitude (0. 65) for 1 day lead time. In contrast, as lead time increases, the anomaly correlations for IS2 pos and IS2 neg are smaller than for IS2 null. In particular, during periods of strong convective activity on 10–30 days (IS2 neg) forecasts are less skillful. The different behavior of the MRF forecasts during IS1 and IS2 periods are still noticeable in the averages over the domain (bottom right and left), although the differences in the magnitudes of the anomaly correlations among positive, negative, and null cases are significantly smaller. However, the differences in the magnitudes of the correlation coefficients do not pass the 95% significance level. The rms errors for the IS1 type averaged over the SACZ region (Fig. 7; top left) show that the MRF model has more skill in predicting Z500 during periods of strong convective activity (IS1 neg) as opposed to periods of suppressed (IS1 pos) or weak (IS1 null) activity. In addition, the growth rate of rms errors during IS1 pos is larger than in other periods. These results are consistent with the results of NPMP. In contrast, the rms errors for the IS2 type seem to exhibit a different behavior (Fig. 7; top right). [SEP] Justify:

Output: The text does not address the claim regarding microclimates and their effect on weather variations. Instead, it focuses on statistical correlations and model forecasting skills in relation to specific regions and periods without any mention of microclimates or their impact on short-distance weather variations.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: The model includes synthetic liquid fuels and synthetic methane production technologies such as CCU-based energy carriers, which can replace fossil fuel-based liquids and gases in energy demand sectors. Further details concerning the model structure and technological assumptions are provided in the Methods section. We analyzed three climate change mitigation scenarios to compare the roles and characteristics of CCU in residual emissions. First, as the central scenario in this study, a CCU-oriented scenario (1. 5C-CCU) was designed that avoids rapid technological changes in energy demand sectors (e. g. , moderate electrification). Furthermore, dependence on fossil fuels and bioenergy is reduced in a manner similar to the IMPs established to meet the 1. 5°C goal of AR6. Consequently, hydrocarbon-based energy is provided by alternative sources derived from atmospheric carbon, which is converted into synthetic fuels. This scenario has clear advantages in that it does not require drastic changes in energy demand structure and lifestyle; it uses current energy supply infrastructure without dependence on CDR. In contrast to 1. 5C-CCU, the other two scenarios phase out hydrocarbons from energy systems (regardless of source) or use CDR implementation to offset residual emissions. The second scenario is 1. 5C-DEC (DECarbonization), which involves decarbonization of energy systems to reduce residual emissions; this scenario includes demand-side electrification and the upscaling of solar and wind power without dependence on large-scale CDR or bioenergy, and the underlying assumptions are similar to the IMP-Ren scenario in AR6. The third scenario, 1. 5C-CDR, is characterized by extensive use of CDR options similar to the IMP-Neg scenario in AR6, whereby residual emissions from fossil fuel use persist. The quantification of each scenario was implemented in the AIM/Technology model with multiple energy system conditions, in accordance with the underlying scenario. In the 1. 5C-CCU scenario, considering the assumptions of low dependence on fossil fuels and bioenergy, constraints were imposed on CDR and CCS implementation, as well as bioenergy potential, because reliance on fossil fuels is generally determined by CDR availability28. Furthermore, based on moderate assumptions regarding technological changes in energy demand sectors, the diffusion of non-hydrocarbon-based technologies was limited, including the use of electricity- and hydrogen-based devices (see Methods for details). [SEP] Justify:

Output: The text corroborates the claim by discussing various scenarios, particularly the 1.5C-CCU scenario, which emphasizes reducing dependence on fossil fuels while utilizing alternative sources derived from atmospheric carbon. It highlights that the reliance on fossil fuels is diminished and that the model incorporates technologies to produce synthetic fuels, indicating a shift towards renewable energy solutions, which aligns with the objective of decreasing carbon emissions.


Input: Task: contrast the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: Similarly, Tajudeen (2015) indicated that African economies need more funds to enforce greener technologies and effective regulations to decrease CO2Es. On the other hand, Bekun (2024), Dunyo et al. (2024), Ibrahim et al. (2024), Kharb et al. (2024), Li et al. (2024), Rahman and Ferdaous (2024), Wang et al. (2024), Raihan et al. (2023g), Raihan et al. (2022f), Raihan and Tuspekova (2022k), Khan et al. (2019), Mensah et al. (2018), and Yii and Geetha (2017) discovered that innovation reduces CO2Es. Our assessment shows that globalisation has a positive coefficient, indicating that CO2Es rise as globalisation increases. This indicates that globalisation has harmful environmental consequences in South Africa. Our discovery is supported by Elboghdadly (2024), Gyamfi et al. (2024), Kharb et al. (2024), Nadiri et al. (2024), Teklie and Yağmur (2024), Alam et al. (2023), Sultana et al. (2023), Xu et al. (2023), Rahman and Alam (2022), Wen et al. (2021), Khan et al. (2019), and Shahbaz et al. (2015). Globalisation results in economic growth via trade and investment flow expansion between economies. This economic growth through trade and investment flows can increase CO2Es. International trade results in increased transportation of people and goods across borders. partakes in global supply chains, exporting and importing goods via planes, ships, trains, and trucks. Since fossil fuels are used as the primary energy source, CO2Es are rising. Globalisation increases trade liberalisation and trade-linked activities, and since most services and goods produced in the economy need energy, usually fossil energy, CO2Es increase. [SEP] Justify:

Output: The text contrasts the claim by discussing the negative impacts of globalization on carbon emissions (CO2Es) and emphasizing that economic growth through trade and investment leads to increased transportation, which relies on fossil fuels. This reliance ultimately results in rising CO2Es, thereby undermining the assertion that renewable energy reduces reliance on fossil fuels.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: The MRF model has less skill in forecasting Z500 during periods of strong (IS2 neg) and suppressed (IS2 pos) convection than in periods of weak (IS2 null) activity. In particular, the growth rate of rms error during IS2 pos is larger than for IS1 neg. A somewhat similar behavior is observed when the rms errors for IS1 and IS2 are averaged over the domain (Fig. 7; bottom left and right, respectively). 4. Concluding remarksThe summer season in exhibits strong convective activity over the Amazon basin and SACZ, with significant intraseasonal variability found in the eastern part of the continent. The recent study of NPMP showed that intraseasonal variations in the 10–90 days band impact the skill of numerical weather forecasts over the PAN region. In particular, their results pointed out that initial forecast errors during periods of weak convective activity over the SACZ are smaller than for strong events. As is discussed in previous studies, intraseasonal variability over the SACZ is modulated by the MJO as well as by shorter period variations (10–30 days). The preliminary results discussed here indicate that the MRF model has more skill (i. e. , in terms of rms errors) during periods of strong convective activity associated with the MJO as opposed to periods of suppressed or weak activity. In contrast, the MRF model has less skill during periods of strong or suppressed convection associated with 10–30 days variations. Additional investigation in this research area should be useful to understand how remotely forced intraseasonal variability over the SACZ can impact local forecasts. This is especially important since the climatological position of the SACZ coincides with the densest demographic region in South America. 3555. Horel, J. D. , A. N. Hahmann, and J. E. Geisler, 1989: An investigation of the annual cycle of convective activity over the tropical Americas. J. Climate,2, 1388–1403. Jones, C. , 1990: An investigation of low-frequency variability of the large-scale circulation over South America. M. S. thesis, Department of Meteorology, University of Utah, 108 pp. ——, and J. D. Horel, 1991: High circulation and convective activity over (in Portuguese). Rev. [SEP] Justify:

Output: The text is irrelevant to the claim regarding microclimates creating weather variations over short distances. It discusses the skills of the MRF model in forecasting atmospheric conditions and the effects of convection in specific regions, without addressing the concept of microclimates or their impact on weather variability.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: Across these three scenarios, the emission pathways were equivalent to the 1. 5°C scenario without overshoot and to the C1 category in the 62, whereby CO2 emissions from energy sectors decreased to nearly net-zero status by 20501,29. We also performed sensitivity scenario analyses, as summarized in 1. Details of the scenario settings are provided in the Methods section. Technological changes in energy demand sectors In the 1. 5C-CCU scenario, CCU-based energy carriers, including synthetic liquid fuels and methane, supply approximately 30% of global energy demand by 2050, compared with approximately 5% and nearly zero in the 1. 5C-DEC and 1. 5C-CDR scenarios, respectively (Fig. 1a, 2). In contrast, the electrification rate is approximately 38% in the 1. 5C-CCU scenario, which is a unique characteristic of the 1. 5C-CCU scenario compared with the 1. 5C-DEC and 1. 5C-CDR scenarios, where electrification is approximately 50%. This unique trend is robust across all sensitivity scenarios of 1. 5C-CCU summarized in Supplementary Fig. 1. Because of the limited electrification level in the 1. 5C-CCU scenario, the share of hydrocarbon-based energies, including fossil fuels, biomass and synfuels, is 54% of the total final energy demand, whereas those shares in the 1. 5C-DEC and 1. 5C-CDR scenarios are only 29% and 41%, respectively. This unique trend is also present in the comparison with AR6 scenarios because hydrocarbon consumption in the 1. 5C-CCU scenario is above the 90th percentile range of category C1 scenarios. Figure 1b summarizes sectoral energy demand composition and the shares of electricity, synfuels, and hydrocarbon-based energies in 2050. Across all scenarios, the transport sector was the greatest consumer of synfuels, which replaced fossil fuel-based liquid fuels. In the 1. 5C-CCU scenario, the share of synfuels reaches nearly 60% of total transport energy demand in 2050. In the industry and buildings sectors, CCU-based energy carriers are mainly supplied as gaseous synthetic methane in the 1. 5C-CCU scenario, where they supply approximately 22% and 13% of sectoral energy demand, respectively. Figure 1c and Supplementary Fig. [SEP] Justify:

Output: The text corroborates the claim by detailing that in the '1.5C-CCU scenario,' there is a transition to CCU-based energy carriers which significantly influences the energy demand structure. It highlights that fossil fuel consumption remains high, particularly in the 1.5C-CCU scenario where hydrocarbon-based energies account for 54% of total energy demand, indicating that while some renewable energy technologies are being integrated, dependence on fossil fuels does not completely diminish. However, the transition towards alternatives like synfuels suggests a gradual reduction in reliance on traditional fossil fuels, supporting the claim that renewable energy initiatives contribute to decreasing overall fossil fuel dependency.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a - 10. 21203/rs. 3. rs-79754/v1This work is licensed under a CC BY 4. 0 LicenseStatus:PostedVersion 1posted You are reading this latest preprint versionAbstractChina is the world’s largest greenhouse gas (GHG) emitter, but declining wind and solar energy costs present opportunities to transform its electric power sector. In 2017, China launched a national emission trading scheme (ETS). Evidence to date suggests that the ETS mitigates CO2 emissions and promotes renewable energy deployment but constrains economic growth. These studies, however, do not account comprehensively for economic impacts. Ours is the first to account for three multiplier effects—shifting consumption patterns, job growth with elastic labor supply, and higher total factor productivity (TFP)—when modeling accelerated renewable electricity growth with the ETS in China. Results from a detailed economic forecasting model show low renewable energy costs interacting with the ETS to slash GHG emissions while directly stimulating incremental net positive economic growth by 2030, compared with a business-as-usual scenario that assumes slower renewable cost reductions and no ETS. Accounting for the multiplier effects reveals larger potential benefits, including up to 15. 6% of additional GDP growth (over business as usual) by 2030 when shifting consumption patterns, job growth with elastic labor supply, and higher TFP are all considered. These results suggest that China should accelerate its clean energy transition, not only for the air-quality and climate benefits, but also for the broad and positive impact on innovation, employment, and economic growth. 1Figure 2Figure 3Figure 4BackgroundThe People’s Republic of China is the world's largest emitter of greenhouse gases (GHGs), 44% (4. 14 billion metric tons of CO2) of which came from the electric power system in 2017. 1 According to its Contribution to the on Climate Change, the Chinese government pledged to lower CO2 emissions per unit of GDP by 60%–65% relative to 2005 emissions, increasing the share of non-fossil fuels in primary energy consumption to around 20%2 by 2030. Accelerating the replacement of traditional energy with renewable substitutes would help transform the power system and reduce carbon emissions. [SEP] Justify:

Output: The text contrasts the claim by describing the economic implications of transitioning to renewable energy in China. It notes that while the national emission trading scheme (ETS) mitigates CO2 emissions and promotes renewable energy, it also 'constrains economic growth.' Moreover, the text highlights that its findings reveal 'larger potential benefits' when accounting for various economic multiplier effects, suggesting that transitioning to renewable energy may not be without economic impacts, but could instead stimulate positive economic growth under certain conditions.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: Brasileira de Meteorologia,5-1, 379–387. ——, D. E. Waliser, J. E. Schemm, and W. K. Lau, 2000: Prediction skill of the Madden and in dynamical extended range weather forecasts. Climate Dyn. , in press. Kalnay, E. , and Coauthors, 1996: NCEP/NCAR 40-Project. Bull. Amer. Meteor. Soc. ,77, 437–471. Lenters, J. D. , and K. H. Cook, 1999: Summertime precipitation variability over South America: Role of the large-scale circulation. Mon. Wea. Rev. ,127, 409–431. Liebmann, B. , G. N. Kiladis, J. A. Marengo, T. Ambrizzi, J. D. Glick, 1999: Submonthly convective variability over and the Convergence Zone. J. Climate,12, 1877–1891. Madden, R. A. , and P. R. Julian, 1994: Observations of the 40–50 day tropical oscillation: A review. Mon. Wea. Rev. ,122, 814–837. Nogues-Paegle J. , K. Mo, and J. Paegle, 1998: Predictability of the NCEP/NCAR reanalysis model during austral summer. Mon. Wea. Rev. ,126, 3135–3152. Schemm, J. E. , H. Van den Dool, and S. Saha, 1996: A Multi-at NCEP. Preprints 11th Conf. on. Meteor. Soc. , 47–49. Size Fig. 1. Frequency response of Lanczos band-pass filters. The 30–70-day band is denoted intraseasonal type 1 (IS1), while variations of 10–30 days are designated intraseasonal type 2 (IS2). Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide Size Fig. 2. Mean geopotential height at 500 hPa (Z500) during austral summer (top). [SEP] Justify:

Output: The text does not address the claim regarding microclimates and their effects on weather variations. Instead, it consists of citations and references to meteorological studies and forecasts that are largely unrelated to the concept of microclimates specifically.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: 2 illustrate the diffusion rates of non-hydrocarbon-based technologies in terms of existing stock capacity. In all energy demand sectors, technological change is moderate in the 1. 5C-CCU scenario, particularly relative to the 1. 5C-DEC scenario, which requires drastic technological change to support rapid electrification. Energy supply and transformation associated with synfuel production Figure 2a shows a secondary energy flow diagram associated with synfuel production in 2050. In the 1. 5C-CCU scenario, electricity generation increases to nearly 700 EJ per year by 2050 to meet the energy demand for synfuel production, as well as the energy demands for direct electrification and hydrogen. Substantial energy losses occur between secondary and final energy conversion processes in the 1. 5C-CCU scenario. The main factor that drives such losses is electrolysis in the synfuel production process, which requires approximately 40% of generated electricity, along with other energy transformation losses, including transmission, storage losses, and curtailment (Supplementary Fig. 3). In the 1. 5C-CCU scenario, electricity consumption for DAC uses approximately 10% of the total electricity generated; CO2 capture via DAC reaches approximately 10 Gt-CO2 per year by 2050, mainly because of CCU demands (Fig. 3a). Considering the requirement for low-carbon electricity, the 1. 5C-CCU scenario poses multiple challenges to energy supply sectors despite moderate technological changes in energy demand sectors. First, the 1. 5C-CCU scenario is characterized by large-scale hydrogen production, reaching approximately 250 EJ per year by 2050, which includes hydrogen for synfuel production and the direct use of hydrogen, as well as hydrogen in the form of ammonia (Fig. 2b, Supplementary Fig. 4). In contrast, hydrogen production reaches approximately 40 EJ and 100 EJ per year by 2050 in the 1. 5C-CDR and 1. 5C-DEC scenarios, respectively; these values are similar to or greater than range in the AR6 scenario. Second, the 1. 5C-CCU scenario includes massive non-biomass renewable energy supply that mainly depends on solar and wind, which exceed 600 EJ per year by 2050 in the 1. 5C-CCU scenario (Fig. 2c, Supplementary Fig. 5); fossil fuel and biomass supplies are limited to approximately 60 EJ and 100 EJ per year, respectively (Supplementary Fig. [SEP] Justify:

Output: The text corroborates the claim by highlighting that in the 1.5C-CCU scenario, there is substantial reliance on non-biomass renewable energy sources, predominantly solar and wind, which exceed 600 EJ per year by 2050. This indicates a significant shift away from fossil fuel sources, which are limited to approximately 60 EJ per year. The emphasis on renewable energy sources supports the assertion that renewable energy can help decrease reliance on fossil fuels as well as potentially diminish carbon emissions through reduced fossil fuel consumption.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: China has already demonstrated rapid growth in renewable electricity generation, which increased from 736 TWh (17% of total electricity generation) to 1,931 TWh (26%) between 2010 and 2019. 3 Renewable energy costs have experienced an unprecedented decline. Over the past decade, the global weighted-average levelized cost of electricity has fallen by 82% for photovoltaics (PV), 38% for onshore wind, and 84% for battery storage. 4-7 Even without accounting for the social cost of carbon, all-inclusive costs of electricity from new PV and onshore wind are now below the marginal operating costs of an increasing number of existing coal-fired powerplants. 5,6 In market economies, this crossover cost trend will support autonomous power system transformation, reduce fossil fuel dependence and related environmental impacts,8-10 and reduce wholesale and retail electricity costs. 11 As a result, new opportunities will arise for cutting consumer and manufacturer energy costs, improving human welfare, and boosting economic growth. The computable general equilibrium (CGE) model is an important tool for studying these macroeconomic impacts. The progress of energy technology in the CGE model is generally characterized by homogeneous autonomous energy efficiency improvement (AEEI) across the economy12,13 or average AEEIs for different energy-consuming sectors,14,15 but neither approach distinguishes technological improvement for different energy sources. Huang et al. (2019) use an exogenously specified mix of fossil and renewable energy as a baseline to describe the process of renewable energy substitution along China’s future low-carbon development pathway. 16 However, the exogenous generation mix does not capture the recent cost crossover—with the cost of renewables dropping below the cost of coal power—nor does it evaluate the full economic impacts of technology improvement. Therefore, there is a need for studies that consider both the plummeting renewable energy costs and the associated economic and social impacts. Carbon emission trading scheme (ETS) is among the most potentially impactful approaches to driving the renewable transition. In 2011, China launched a pilot ETS covering seven leading provinces and cities including and Hubei. By the middle of 2019, the cumulative trading volume of the pilot ETS covered 330 million metric tons of CO2 equivalent emissions, with a cumulative transaction value of 7. 11 billion RMB. 17 2017, China officially launched its national ETS, and electric power was the first industry included in the system. [SEP] Justify:

Output: The text contrasts the claim by highlighting that while China has achieved rapid growth in renewable energy generation, it also points to the need for further studies to understand the full economic impacts of this transition. The mention of the computable general equilibrium (CGE) model and the necessity for analyses that consider both declining renewable energy costs and associated economic and social impacts indicates that transitioning to renewable energy may indeed have economic implications that cannot be disregarded.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: Contour interval is 20 m. Total standard deviation of Z500 (bottom). Contour interval is 5 m. Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide Size Fig. 3. Anomaly correlation between Z500 forecasts and verification fields. Skill is computed considering all days from the four austral summers during the DERF period. Skill is shown for 1, 4, 6, 8, and 11 days lead time. Correlations greater than 0. 50 are indicated by dark shading. Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide Size Fig. 4. (a) Mean outgoing longwave radiation (OLR) during austral summer (1 November–31 March). Contour interval is 5 W m−2 and shading indicates OLR is less than 220 W m−2. (b) Total OLR standard deviation during austral summer. Contour interval is 2. 5 W m−2 and shading indicates standard deviation greater than 20 W m−2. (c) Standard deviation of OLR anomalies for the IS1 type (30–70 days). Contour interval is 1. 0 W m−2 and shading indicates standard deviation greater than 10 W m−2. (d) Standard deviation of OLR anomalies for the IS2 type (10–30 days). Contour interval is 1. 0 W m−2 and shading indicates standard deviation greater than 15 W m−2. Region indicated with thick solid lines is used to characterize periods of strong (weak) convective activity over the (SACZ). Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide Size Fig. 5. Distribution of events (in pentads) selected according to the type of intraseasonal variability: 30–70 days (IS1; top) and 10–30 days (IS2; bottom). Events are selected when the magnitudes of the OLR anomalies averaged over the SACZ domain are less than 0. [SEP] Justify:

Output: The text is irrelevant to the claim as it does not discuss microclimates or their effects on weather variations over short distances. Instead, it focuses on meteorological measurements and anomalies related to outgoing longwave radiation and contour intervals, without any reference to microclimates.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: 6). The 1. 5C-CCU scenario is characterized by substantial availability of hydrocarbon-based energy for energy demand sectors, along with low dependence on fossil fuels. Conventional mitigation scenarios show a clear correlation of primary energy supply from fossil fuels and biomass with the consumption of hydrocarbon-based energy carriers (Fig. 2d). All AR6 scenarios, including IMPs, 1. 5C-DEC, and 1. 5C-CDR, show similar trends because hydrocarbon-based final energy carriers are generally supplied by fossil fuels or biomass. In the 1. 5C-CCU scenario, hydrocarbon-based energy usage in energy demand sectors reaches approximately 280 EJ per year, despite the reduction of fossil fuel and biomass primary energy supply to approximately 160 EJ by 2050, because DAC is a major carbon source for the energy system in this scenario. Carbon sources and utilization in energy systems The 1. 5C-CCU scenario requires CO2 capture from the atmosphere via DAC, reaching approximately 10 Gt-CO2 per year by 2050; the 1. 5C-DEC requires approximately 1 Gt-CO2 and the AR6 scenarios require < 2 Gt-CO2 (Fig. 3, Supplementary Fig. 7). In contrast to the extensive reliance on DAC, the implementation of CDR and CCS is lower in the 1. 5C-CCU scenario than in the 1. 5C-DEC, 1. 5C-CDR, and AR6 scenarios. CDR implementation is limited to 1 Gt-CO2 per year in the 1. 5C-CCU scenario, whereas it reaches 2. 3 and 6. 5 Gt-CO2 per year by 2050 in the 1. 5C-DEC and 1. 5C-CDR scenarios, respectively (Fig. 3b). CCS implementation, specifically geological storage, reaches approximately 3. 4 Gt-CO2 per year by 2050 in the 1. 5C-CCU scenario, even when CCS requirements for industrial process emissions are included; this value is lower than the values in the 1. 5C-DEC and 1. 5C-CDR scenarios, as well as the values in most AR6 scenarios (Fig. 3c). Figure 3d is a diagram of carbon flow in 2050 associated with energy systems; it includes DACCS, which is normally considered outside of the energy system. [SEP] Justify:

Output: The text supports the claim as it discusses the 1.5C-CCU scenario which is characterized by a low dependence on fossil fuels while still allowing for substantial hydrocarbon-based energy availability. This indicates a transition towards a reduced reliance on fossil fuels. Furthermore, the text mentions the implementation of CO2 capture from the atmosphere via Direct Air Capture (DAC) which is a method to decrease carbon emissions. Therefore, the text's descriptions of reduced fossil fuel supply and CO2 capture align with the assertion that renewable energy contributes to less reliance on fossil fuels and helps decrease carbon emissions.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: 18 To date, the research literature suggests that China’s ETS mitigates CO2 emissions and promotes renewable energy deployment but hinders the economy—although there is significant disagreement about the magnitude and direction of net economic impacts. Chen et al. (2020) find that a 1% carbon emission reduction would reduce GDP by 0. 06%,19 whereas Zhang et al. (2018) indicate that the ETS could reduce carbon intensity by 20% without GDP loss. 20 Most studies show a negative net impact on the economy due to the ETS, ranging from 0. 08% to 5. 61% of real GDP12,21 and depending on carbon pricing,22 the allowance allocation mechanism,15,23-25 revenue redistribution methods,16,26 government fines,27 and coverage considered. 13,14,28 The price-directed nature of the ETS still confers efficiency gains compared with mandated emission caps. 29,30 However, few studies focus on the comprehensive impact of renewable technology promotion and the ETS in the context of the renewable energy cost crossover. Further, the existing literature does not account for three critical multiplier effects that could magnify the impacts of accelerating China’s renewable electricity transition through technology improvement and the ETS. First, households can be expected to divert the electricity cost savings that result from rapidly declining renewable energy costs toward other expenditures, promoting broad-based economic growth from the demand side. Second, because China generally has a higher elasticity of labor supply compared with developed countries, this more accommodating labor supply will amplify economic gains due to the expenditure stimulus, particularly in the long term. Third, increasing renewable energy use may increase regional total factor productivity (TFP), supporting the anecdotal narrative of a virtuous productivity cycle linking renewable energy deployment to other technological innovation; although the exact mechanisms are difficult to disentangle, studies in diverse settings suggest a positive linkage. 31-33 Tugcu (2013) estimates long-run (short-run) growth elasticities are -2. 1 (-1. 7) and 0. 8 (0. 7) for fossil and renewable consumption, respectively. 34 Yan et al. (2020) study the relationship between renewable energy technology innovations and China’s green productivity growth, finding a significant effect in provinces where income is above a certain threshold. [SEP] Justify:

Output: The text contrasts the claim by outlining that there are economic impacts associated with transitioning to renewable energy, specifically noting that China's emissions trading system (ETS) has both mitigated CO2 emissions and hindered the economy, suggesting that a transition to renewable energy can indeed come at a cost to economic performance. For example, it mentions that most studies show a negative net impact on the economy due to the ETS, indicating potential GDP losses. While the text also presents some arguments for potential economic benefits through technological improvement and other factors, it fundamentally supports the view that there are economic trade-offs involved in shifting to renewable energy.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: 8 standard deviation (IS1 neg; IS2 neg), greater than 0. 8 standard deviation (IS1 pos; IS2 pos) and between ±0. 3 standard deviation (IS1 null; IS2 null). Numbers of events are displayed for each austral summer (S 85–86; S 86–87; S 87–88; S 88–89). Total number of pentads for each type of intraseasonal variability is indicated in parenthesis. Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide Size Fig. 6. Anomaly correlation between forecasts of Z500 and reanalysis averaged over the SACZ (top) and region (40°S–20°N; 90°–20°W) (bottom). Plots on the left are for IS1 type, while plots on the right are for IS2 type. Dashed, dotted, and solid lines indicate positive, negative, and null cases, respectively. Horizontal axis indicates lead time in days. Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide Size Fig. 7. Root-mean-square (rms) errors between forecasts of Z500 and reanalysis averaged over the SACZ (top) and region (40°S–20°N; 90°–20°W) (bottom). Plots on the left are for IS1 type, while plots on the right are for IS2 type. Dashed, dotted, and solid lines indicate positive, negative, and null cases, respectively. Horizontal axis indicates lead time in days. Citation: Review 128, 2; 10. 1175/1520-0493(2000)128<0486:>2. 0. CO;2Download FigureDownload figure as PowerPoint slide this content Copy this link, or click below to email it to a friend Email this content or copy the link directly: The link was not copied. Your current browser may not support copying via this button. Link copied successfullyCopy link Share on facebook Share on linkedin Share on twitter Abstract1. Introduction2. Methodology3. Results4. Concluding remarks 3555. Horel, J. [SEP] Justify:

Output: The text does not provide any information regarding microclimates or their effects on weather variations over short distances. Instead, it discusses statistical analyses related to intraseasonal variability and forecast errors, which are not directly relevant to the claim. Thus, it is categorized as irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: Although the mean production cost of electricity gradually decreases to approximately 15 US$ GJ− 1 in 2050 because of decreases in renewable costs, the cost of synfuels is approximately fourfold greater than the cost of electricity; it reaches approximately 60 US$ GJ− 1 by 2050 (Fig. 4c). According to the synfuel cost composition shown in the right panel of Fig. 4c, increases in synfuel cost are mainly driven by the hydrogen supply cost, which constitutes approximately two-thirds of synfuel costs because of the energy losses illustrated in Fig. 2a. Even under the AdvTech assumption, synfuel production cost exceeds 40 US$ GJ− 1 in 2050; thus, it is much more costly than hydrogen and electricity. The 1. 5C-CCU scenario shows unique characteristics in terms of sectoral energy investment, although all scenarios decrease investments in other energy supply, including fossil fuel extraction, relative to the no-policy scenario (Fig. 4d). In the 1. 5C-CCU scenario, investments in energy demand sectors in 2041–2050 are lower than in 1. 5C-DEC because of moderate energy demand technological changes; however, total energy investment reaches approximately 7 trillion US$ per year because of the upscaling of electricity, hydrogen, and CO2 capture via DAC. The regional investments illustrated in Supplementary Fig. 9c reveal similar trends among regions, although those trends are stronger in the OECD and Asian regions under 1. 5C-CCU than under other scenarios because of their high demand for synfuels (Supplementary Fig. 10). DiscussionWe assessed three illustrative scenarios for achieving net-zero CO2 emissions. In contrast to the 1. 5C-DEC, 1. 5C-CDR, and AR6 scenarios, where residual emissions are generally reduced through energy system decarbonization or CDR, the 1. 5C-CCU scenario exhibits distinct characteristics, which are summarized in Table 1. Here, we discuss these characteristics in greater detail. First, the CCU scenario makes hydrocarbon-based energy carriers available to energy demand sectors; this has the advantage of increasing energy density while lowering dependence on fossil fuels and bioenergy. Because most synfuels are derived from renewable-based hydrogen and carbon captured via DAC in this scenario, synfuels can be considered carbon-neutral hydrocarbons that reduce residual CO2 emissions in the energy sector. [SEP] Justify:

Output: The text corroborates the claim by explaining how the 1.5C-CCU scenario 'lowers dependence on fossil fuels and bioenergy' and indicates that synfuels, which can be derived from renewable-based hydrogen, are considered 'carbon-neutral hydrocarbons' that 'reduce residual CO2 emissions in the energy sector.' This supports the assertion that renewable energy can reduce reliance on fossil fuels and decrease carbon emissions.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: 35 Ours is the first study to account for the economic impacts of shifting consumption patterns, job growth in the context of elastic labor supply, and higher TFP when simulating accelerated renewable electricity growth with the ETS in China. We employ a dynamic recursive CGE model with a diverse portfolio of electric power technologies to evaluate scenarios designed for illuminating each of the three multiplier effects. Those scenarios are described in the next section, followed by our results and conclusions. section details our analytical approach. We evaluate six scenarios (Table 1). In the business as usual (BAU) scenario, the productivity of renewables (wind, solar, and electricity storage) is assumed to follow historical trends (He et al. 2020),11 with sustained but moderate cost reductions into the future. In the low-cost renewable scenario (R), more rapid productivity growth in renewables continues in alignment with recent indications, simulating how lower renewable energy costs provide direct stimulus to the economy. In the carbon constraint scenario (C50), total emissions from the power sector by 2030 are limited to 50% below the 2015 level by instituting an ETS for this sector. Table 1: productivity improvements in renewables R Rapid productivity improvements in renewables C50 R + ETS limiting CO2 emissions from the power sector to 50% of the 2015 emissions level Keynes C50 + shifting expenditure from energy savings EMP Keynes + more accommodating labor market + energy productivity spillovers (1% TFP growth) Our other three scenarios examine the multiplier economic impacts of renewable innovation and the ETS. scenario builds on the C50 scenario to elucidate the effects of demand-side aggregate stimulus resulting from energy cost savings due to renewable technology innovation. Previous economic assessments of renewable energy have focused on three component impacts: investment in technology production, technology purchasing, and installation. Technology production (e. g. , building and operating a solar panel factory) represents so-called “shovel ready” investment and is usually an unambiguous economic stimulus. Technology purchase and installation costs can have mixed economic effects, depending on the opportunity cost or alternative return to capital. In other words, technology adoption will stimulate the economy if it increases productivity, reduces resource costs, or both. If it reduces productivity or increases resource costs, it will be detrimental to growth. The shifting consumption patterns in the Keynes scenario begin with lower-cost electricity saving money for households and enterprises. [SEP] Justify:

Output: The text contrasts the claim by discussing the economic impacts associated with transitioning to renewable energy. It describes potential benefits, such as job growth and economic stimulus from lower energy costs, but also mentions that adopting renewable technologies may have mixed economic effects. Specifically, the text states that technology adoption can stimulate the economy if it increases productivity or reduces costs, whereas, if it reduces productivity or increases resource costs, it would be detrimental to growth. This indicates that there are indeed economic impacts related to the transition to renewable energy.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: D. , A. N. Hahmann, and J. E. Geisler, 1989: An investigation of the annual cycle of convective activity over the tropical Americas. J. Climate,2, 1388–1403. Jones, C. , 1990: An investigation of low-frequency variability of the large-scale circulation over South America. M. S. thesis, Department of Meteorology, University of Utah, 108 pp. ——, and J. D. Horel, 1991: High circulation and convective activity over (in Portuguese). Rev. Brasileira de Meteorologia,5-1, 379–387. ——, D. E. Waliser, J. E. Schemm, and W. K. Lau, 2000: Prediction skill of the Madden and in dynamical extended range weather forecasts. Climate Dyn. , in press. Kalnay, E. , and Coauthors, 1996: NCEP/NCAR 40-Project. Bull. Amer. Meteor. Soc. ,77, 437–471. Lenters, J. D. , and K. H. Cook, 1999: Summertime precipitation variability over South America: Role of the large-scale circulation. Mon. Wea. Rev. ,127, 409–431. Liebmann, B. , G. N. Kiladis, J. A. Marengo, T. Ambrizzi, J. D. Glick, 1999: Submonthly convective variability over and the Convergence Zone. J. Climate,12, 1877–1891. Madden, R. A. , and P. R. Julian, 1994: Observations of the 40–50 day tropical oscillation: A review. Mon. Wea. Rev. ,122, 814–837. Nogues-Paegle J. , K. Mo, and J. Paegle, 1998: Predictability of the NCEP/NCAR reanalysis model during austral summer. Mon. Wea. Rev. ,126, 3135–3152. Schemm, J. E. , H. Van den Dool, and S. Saha, 1996: A Multi-at NCEP. Preprints 11th Conf. on. Meteor. Soc. , 47–49. in gallery Fig. 1. [SEP] Justify:

Output: The text is irrelevant to the claim as it primarily consists of bibliographic references and descriptions of various studies without addressing the concept of microclimates or variations in weather due to them. It contains no information that corroborates or contrasts the idea that microclimates can lead to weather variations over short distances.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: The influence of economic growth, fossil and renewable energy, technological innovation, and globalisation on carbon dioxide emissions in 1, Asif Raihan2, Helper Zhou1 & …Mabutho Sibanda1 Show authors 451 all metrics AbstractCarbon dioxide (CO2), whose atmospheric volume has been increasing, is the principal greenhouse gas (GHG) that causes global warming and climate change. Climate change from increasing greenhouse gases (GHGs) has broad health and environmental influences. Human-emitted GHGs constitute a significant cause of global warming. The main objective of this 2020. Squares (DOLS) estimator was implemented to examine the relationship between the constituents. The study results indicate that economic growth, fossil energy use, technological innovation, and globalisation boost CO2Es, whereas renewable energy consumption reduces CO2Es. The output of the canonical cointegrating regression and fully modified least squares estimators also supports the output of the DOLS estimator. We concluded that, in South Africa, a rise in economic growth, fossil energy use, technological innovation, and globalisation results in an upsurge in CO2Es. In contrast, an increase in renewable energy consumption leads to a reduction in CO2Es. This research work contributes to the discourse on CO2Es in the context. The study recommends that policymakers in should design policies that foster the formation of a low-carbon country, the consumption of renewable energy, and the implementation of environment-friendly technological innovations that reduce the use of fossil energy. Highlights • This study assessed the impact of economic growth, technological innovation, fossil energy use, renewable energy consumption, and globalisation on CO2Es in South Africa. • The analysis revealed that economic growth, fossil energy use, technological innovation, and globalisation boost CO2Es, whereas renewable energy consumption reduces CO2Es. • There is a need to incorporate policies that promote the development of a low-carbon economy. Similar content being viewed by others The role of energy mix and financial development in greenhouse gas (GHG) emissions’ reduction: evidence from ten leading CO2 emitting countries 1950. GHGs originate from a multiplicity of human actions, such as fossil fuel burning for energy and heat, forest clearing, crop fertilising, livestock rearing, and the manufacturing of some types of commodities (EPA 2024; Raihan 2023a; Mensah et al. 2018). [SEP] Justify:

Output: The text corroborates the claim by indicating that 'renewable energy consumption reduces CO2Es,' which supports the idea that increasing renewable energy can lead to decreased carbon emissions, directly aligning with the claim regarding the benefits of renewable energy.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: These savings are diverted toward other expenditures, mostly domestic services that employ workers from all skill levels and demographics and that are non-tradable, meaning these new jobs cannot be outsourced. Because more than half of China's aggregate domestic demand is from household consumption and 70% of this goes to services, about half of energy cost savings diverted to other expenditures can be expected to go to this employment category—the most labor intensive and skill diverse in the economy. In contrast, the carbon fuel supply chain is among the least employment intensive; for example, the carbon fuel supply chain produces only 1%–10% as many jobs per unit of revenue compared with the service sector, differences far too large to be offset by wage inequality (Figure 1). Simply put, about two thirds of the money saved on cheaper electricity is spent on services, stimulating much stronger and more diverse domestic job growth. The EMP scenario builds on the Keynes scenario to examine the role of labor supply in economic adjustment. Based on China’s dynamism over most of the last two decades, the BAU, R, C50, and Keynes scenarios assume relatively “full employment,” which would limit the economy’s supply response to positive or negative stimulus. China’s reform period has seen dramatic economic growth and large-scale labor mobilization, but over the last decade growth and rates of job creation have moderated (particularly in the post-COVID economy). To reflect this, the EMP scenario assumes a low but nonzero elasticity of aggregate labor supply (0. 25), describing a more accommodating labor market. Finally, the PROD scenario builds on the EMP scenario to exemplify renewable energy productivity spillovers, assuming that accelerated renewable deployment confers an average of 1% higher TFP growth on the economy. This value is not a forecast; it merely illustrates the growth potential of induced innovation. ResultsAs expected, fossil fuel generation becomes increasingly small and renewable generation increasingly large as the renewable-promoting assumptions in our scenarios become increasingly aggressive (Figure 2). In the BAU scenario (moderate productivity improvement in renewables), coal’s share of generation declines from 65. 9% in 2017 to 51. 3% in 2030, while solar’s share increases by 8. 6 percentage points and wind’s share increases by 7. 6 percentage points. In the R scenario (more rapid productivity growth and larger renewable cost reductions), solar’s share rises by 18. [SEP] Justify:

Output: The text contrasts the claim by explaining how the transition to renewable energy impacts the economy. It states that savings from transitioning to cheaper electricity are expected to be redirected towards domestic services, which indicates economic changes in employment patterns. The discussion about job creation in the service sector versus the carbon fuel supply chain shows that while there may be job gains, the overall transition to renewables comes with significant economic implications. It highlights the issue of 'full employment' and the adjustments needed in the labor market, implicitly suggesting that not all countries may transition without economic impacts.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: Frequency response of Lanczos band-pass filters. The 30–70-day band is denoted intraseasonal type 1 (IS1), while variations of 10–30 days are designated intraseasonal type 2 (IS2). View in gallery Fig. 2. Mean geopotential height at 500 hPa (Z500) during austral summer (top). Contour interval is 20 m. Total standard deviation of Z500 (bottom). Contour interval is 5 m. View in gallery Fig. 3. Anomaly correlation between Z500 forecasts and verification fields. Skill is computed considering all days from the four austral summers during the DERF period. Skill is shown for 1, 4, 6, 8, and 11 days lead time. Correlations greater than 0. 50 are indicated by dark shading. View in gallery Fig. 4. (a) Mean outgoing longwave radiation (OLR) during austral summer (1 November–31 March). Contour interval is 5 W m−2 and shading indicates OLR is less than 220 W m−2. (b) Total OLR standard deviation during austral summer. Contour interval is 2. 5 W m−2 and shading indicates standard deviation greater than 20 W m−2. (c) Standard deviation of OLR anomalies for the IS1 type (30–70 days). Contour interval is 1. 0 W m−2 and shading indicates standard deviation greater than 10 W m−2. (d) Standard deviation of OLR anomalies for the IS2 type (10–30 days). Contour interval is 1. 0 W m−2 and shading indicates standard deviation greater than 15 W m−2. Region indicated with thick solid lines is used to characterize periods of strong (weak) convective activity over the (SACZ). View in gallery Fig. 5. Distribution of events (in pentads) selected according to the type of intraseasonal variability: 30–70 days (IS1; top) and 10–30 days (IS2; bottom). Events are selected when the magnitudes of the OLR anomalies averaged over the SACZ domain are less than 0. 8 standard deviation (IS1 neg; IS2 neg), greater than 0. 8 standard deviation (IS1 pos; IS2 pos) and between ±0. 3 standard deviation (IS1 null; IS2 null). [SEP] Justify:

Output: The text does not address the claim about microclimates creating variations in weather. Instead, it focuses on data related to intraseasonal variability and features of geopotential height and outgoing longwave radiation, which do not relate to the concept of microclimates.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: Since climate change and global warming are connected to a plethora of threats to the environment, human life, and development (Raihan et al. 2023a; Samour et al. 2022), reducing CO2Es and alleviating global warming are essential for human well-being. Raihan (2023b) articulated that to develop a progressive, sustainable, and well-off community where no person is left behind, the universal society should try to create a carbon-neutral future. Nations formulated Goals (SDGs) for 2030 that highlight the importance of reasonably priced and clean energy, technological innovation, sustainable management of forests, sustainable and comprehensive economic progress, and universal teamwork for sustainable development to deal with climate change (SDGs 7, 8, 9, 13, 15, and 17). Agreement aims to fortify the universal response to the climate change problem by keeping a universal temperature increase this century well under 2 degrees Celsius (ºC) above pre-industrial levels and by engaging in activities to restrict the temperature rise even to 1. 5ºC. Moreover, the enforces the on Climate Change. It requires industrialised and transition economies to regulate and decrease emissions of GHGs in conformity with the approved specified goals. This research contributes to the discourse on CO2Es by assessing the impact of economic growth, technological innovation, renewable energy utilisation, fossil energy use, and globalisation on CO2Es in South Africa. These factors are chosen because they each significantly shape South Africa's carbon emissions profile. is one of the fastest-expanding emerging economies in the world (Kwakwa et al. 2023; Ekwueme et al. 2021). Its GDP has amplified from US$ 159 billion to US$ 352 billion from 1980 to 2021 (2023). Industrialisation, which is typically associated with high levels of CO2Es due to the burning of fossil fuels, is what drives economic growth in South Africa. is one of the most carbon-intensive countries and is the 14th main CO2 discharger in the world (Salahuddin et al. 2019). Salahuddin et al. (2019) further posited that contributes the most significant level of CO2Es in Sub-(SSA). In the same vein, Ndoricimpa (2017) postulated that is responsible for 42. 8% of the total emissions in Africa. Samour et al. [SEP] Justify:

Output: The text corroborates the claim by discussing the necessity of reducing CO2 emissions to alleviate global warming and mentions that achieving sustainable development goals involves a focus on clean energy and technological innovation. It highlights the importance of transitioning towards a carbon-neutral future and regulating greenhouse gas emissions, which aligns with the goals of renewable energy to decrease reliance on fossil fuels.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: 7 percentage points compared with the BAU scenario in 2030, and wind’s share rises by 0. 5 percentage points, with coal’s share dropping below half. The rapid reduction in technology costs, especially solar costs, directly drives transformation of the power sector from fossil energy to renewable energy. In the C50 scenario (R scenario + ETS limiting power-sector CO2 emissions to 50% of 2015 levels), the substitution from fossil fuel to renewables in the power sector is further accelerated by the ETS policy. Solar and wind account for 54. 4% of generation in 2030, and coal falls to 21. 1%. In the Keynes, EMP, and PROD scenarios, changes in consumption patterns, labor supply, and productivity spillovers have relatively small impacts on the generation mix compared with the rapid renewable cost reductions and ETS implementation in the C50 scenario; thus, their electricity generation mixes are similar to the mix in the C50 scenario. CO2 power-sector CO2 emissions trends in each scenario correspond with the generation trends (Figure 3). In the BAU scenario, the moderate renewable productivity improvement decreases electricity prices, which increases electricity demand. Because coal generation remains the largest component, this rebound effect results in higher emissions. In the R scenario, total electricity demand is 2. 6% higher than in the BAU scenario owing to lower electricity prices. However, higher renewable penetration more than offsets this effect, and total annual carbon emissions are 4. 47 Gt in 2030, slightly larger than in 2017 but 23% lower than in the BAU scenario. The remaining scenarios show how transforming the power sector via renewables can reduce CO2 emissions while meeting electricity demand growth. In the C50, Keynes, EMP, and PROD scenarios, power-sector CO2 emissions are reduced by the cap of 50% below 2015 levels, at 1. 92 Gt in 2030. Compared with our BAU scenario, all of our other scenarios grow China’s economy (Tables 2 and 3). In the R scenario, sustained renewable cost improvements alone more than compensate for the cost of a significant renewable buildout, adding over 607 billion RMB or 0. 4% to China’s real GDP by 2030. Even the C50 scenario, with its aggressive CO2 mitigation strategies, results in positive growth owing to low-cost renewables. [SEP] Justify:

Output: The text contrasts the claim by detailing that the transition to renewable energy is associated with economic impacts, like the increase in China's real GDP due to renewable cost improvements. It notes that even with aggressive CO2 mitigation strategies, positive growth is a result of low-cost renewables, implying that economic impacts accompany the transition, thus refuting the claim that there would be no economic impacts.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: Numbers of events are displayed for each austral summer (S 85–86; S 86–87; S 87–88; S 88–89). Total number of pentads for each type of intraseasonal variability is indicated in parenthesis. View in gallery Fig. 6. Anomaly correlation between forecasts of Z500 and reanalysis averaged over the SACZ (top) and region (40°S–20°N; 90°–20°W) (bottom). Plots on the left are for IS1 type, while plots on the right are for IS2 type. Dashed, dotted, and solid lines indicate positive, negative, and null cases, respectively. Horizontal axis indicates lead time in days. View in gallery Fig. 7. Root-mean-square (rms) errors between forecasts of Z500 and reanalysis averaged over the SACZ (top) and region (40°S–20°N; 90°–20°W) (bottom). Plots on the left are for IS1 type, while plots on the right are for IS2 type. Dashed, dotted, and solid lines indicate positive, negative, and null cases, respectively. Horizontal axis indicates lead time in days. raw image Fig. 1. Frequency response of Lanczos band-pass filters. The 30–70-day band is denoted intraseasonal type 1 (IS1), while variations of 10–30 days are designated intraseasonal type 2 (IS2). View raw image Fig. 2. Mean geopotential height at 500 hPa (Z500) during austral summer (top). Contour interval is 20 m. Total standard deviation of Z500 (bottom). Contour interval is 5 m. View raw image Fig. 3. Anomaly correlation between Z500 forecasts and verification fields. Skill is computed considering all days from the four austral summers during the DERF period. Skill is shown for 1, 4, 6, 8, and 11 days lead time. Correlations greater than 0. 50 are indicated by dark shading. View raw image Fig. 4. (a) Mean outgoing longwave radiation (OLR) during austral summer (1 November–31 March). Contour interval is 5 W m−2 and shading indicates OLR is less than 220 W m−2. (b) Total OLR standard deviation during austral summer. [SEP] Justify:

Output: The text does not address the claim about microclimates and their effect on weather over short distances. Instead, it discusses statistical data and graphs related to meteorological forecasting and intraseasonal variability. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: (2022) propounded that the carbon intensity for has been constant at approximately 79 tCO2/TJ over the past years, which is greater than the average for the G20 countries. The authors further indicated that this high level emanates from the perpetual dominance of fossil fuels in South Africa. is hooked on fossil fuels (Winkler 2022). (IMF 2023) propounded that South Africa's energy industry was responsible for roughly 86% of the emissions in 2019 and was responsible for roughly 91% of the GHG emission upsurge over the past three decades. This is due to the fact that coal accounts for about 77% of South Africa's primary energy needs. Winkler (2022) postulated that 85% of all electricity generated in is manufactured in coal-powered plants, which is higher than in all the other countries except Mongolia and Kosovo. Further, Winkler (2022) specified that is presently ranked 8th in the world in terms of the total amount of coal used in electricity production. is one of the 196 parties that embraced the Paris Agreement, which launched a process for countries to design their plans to decrease emissions, dubbed Contributions (NDCs). Therefore, in 2021, devoted itself to setting targets for GHG emissions echelons of 350–420 MtCO2e by 2030 and 398–510 MtCO2e by 2025 (which are substantially less than targets outlined in 2016) and has gazetted in its Low-Strategy a target to attain net zero emissions by 2050. Moreover, South Africa's NDCs incorporate several policy instruments to achieve these targets, e. g. , the policy instrument on carbon tax. The 2021 Pact, established at the COP26 climate change summit, conceded that attaining net zero emissions by 2050 is essential and the key to repressing temperatures to 1. 5°C of warming. is under enormous pressure to curtail pollution because it is tied to the Kyoto Protocol, the Paris Agreement, and the 1992 on Climate Change. Consequently, it has been striving to reduce CO2Es and diversify its energy sources. Given that the burning of coal significantly contributes to GHG emissions and climate change, generating electricity from coal is a problem, with enormous pressure and incentives to scale this down (Winkler 2022). [SEP] Justify:

Output: The text corroborates the claim by indicating that South Africa is under immense pressure to curb emissions due to its reliance on fossil fuels, particularly coal, which contributes significantly to greenhouse gas emissions. The references to the country's commitments under international agreements like the Paris Agreement and their targets for reducing emissions suggest an acknowledgment of the necessity to transition away from fossil fuels, aligning with the claim that renewable energy can help decrease reliance on these fuels and reduce carbon emissions.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: In both these scenarios, aggregate investment grows more slowly than in the BAU scenario, but overall economic growth and real consumption are higher. Lower electricity costs also translate into greater Chinese competitiveness, with beneficial impacts on exports and (to a lesser extent) imports. In economics, general equilibrium, indirect, and induced effects often outweigh direct effects. This is apparent in the Keynes scenario, which accounts explicitly for expenditure diversion from electric power to other goods and services. This multiplier effect increases real GDP significantly. Compared with the C50 scenario on which it is based, the Keynes scenario adds 2,020. 5 billion RMB to GDP in 2030. scenario increases GDP by 1. 3% over the BAU scenario, compared with the C50 scenario’s 0. 1% increase over the BAU scenario. Table 2: in China (change from 2030 BAU in real billion RMB) R C50 607. 4 228. 6 2,249. 1 11,959. 7 26,998. 1 Consumption 490. 0 329. 1 1,051. 7 3,871. 5 8,697. 3 Investment -897. 8 -1,048. 1 1,984. 5 7,044. 2 14,426. 5 Exports 267. 0 229. 4 -518. 8 1,112. 3 4,450. 1 Imports 97. 9 113. 8 1,057. 6 1,278. 6 2,424. 3 Employment (million full-time equivalent jobs) 1. 2 0. 7 1. 7 66. 6 79. 0 Table 3: in China (percent change from BAU in 2030) R C50 0. 4% 0. 1% 1. 3% 6. 9% 15. 6% Consumption 0. 8% 0. 5% 1. 7% 6. 2% 13. 9% Investment -1. 3% -1. 6% 2. 9% 10. 5% 21. 4% Exports 0. 8% 0. 7% -1. 6% 3. 4% 13. 5% Imports 0. 5% 0. 6% 5. 4% 6. 6% 12. 5% Employment 0. 1% 0. 1% 0. 2% 7. 9% 9. [SEP] Justify:

Output: The text contrasts the claim by discussing the economic impacts of transitioning scenarios, such as lower investment growth compared to a Business-As-Usual (BAU) scenario as well as the complexities of indirect and induced effects on the economy. It mentions that even though overall economic growth and real consumption may increase, the need for investment adjustments suggests that economic impacts are inherent in the transition to renewable energy.


Input: Task: pass the claim using the given text. Claim: Microclimates can create variations in weather over short distances. [SEP] Text: Contour interval is 2. 5 W m−2 and shading indicates standard deviation greater than 20 W m−2. (c) Standard deviation of OLR anomalies for the IS1 type (30–70 days). Contour interval is 1. 0 W m−2 and shading indicates standard deviation greater than 10 W m−2. (d) Standard deviation of OLR anomalies for the IS2 type (10–30 days). Contour interval is 1. 0 W m−2 and shading indicates standard deviation greater than 15 W m−2. Region indicated with thick solid lines is used to characterize periods of strong (weak) convective activity over the (SACZ). View raw image Fig. 5. Distribution of events (in pentads) selected according to the type of intraseasonal variability: 30–70 days (IS1; top) and 10–30 days (IS2; bottom). Events are selected when the magnitudes of the OLR anomalies averaged over the SACZ domain are less than 0. 8 standard deviation (IS1 neg; IS2 neg), greater than 0. 8 standard deviation (IS1 pos; IS2 pos) and between ±0. 3 standard deviation (IS1 null; IS2 null). Numbers of events are displayed for each austral summer (S 85–86; S 86–87; S 87–88; S 88–89). Total number of pentads for each type of intraseasonal variability is indicated in parenthesis. View raw image Fig. 6. Anomaly correlation between forecasts of Z500 and reanalysis averaged over the SACZ (top) and region (40°S–20°N; 90°–20°W) (bottom). Plots on the left are for IS1 type, while plots on the right are for IS2 type. Dashed, dotted, and solid lines indicate positive, negative, and null cases, respectively. Horizontal axis indicates lead time in days. View raw image Fig. 7. Root-mean-square (rms) errors between forecasts of Z500 and reanalysis averaged over the SACZ (top) and region (40°S–20°N; 90°–20°W) (bottom). Plots on the left are for IS1 type, while plots on the right are for IS2 type. [SEP] Justify:

Output: The text does not provide information relevant to the claim about microclimates and their impact on weather variations. Instead, it discusses technical details regarding standard deviations and anomaly correlations related to intraseasonal variability without any mention of microclimates or short-distance weather variations.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: Even though the effectiveness of the policies to alleviate CO2Es and to diversify energy sources needs to be analysed, has designed policies such as the Strategy, the Response Policy, the on Policy, the on Renewable Energy, and the Policy (IMF 2023; Government 2022; Akinbami et al. 2021; Salahuddin et al. 2019). The present power manufacturing plants in have been overpowered by the growing energy demand (Akinbami et al. 2021). These electricity-producing plants contribute a lot to the high emissions of GHGs witnessed in the economy. Therefore, to reduce the level of CO2Es and offer dependable electricity to the people, the government is progressively improving the renewable energy industry (Akinbami et al. 2021). Africa, the electricity crisis, climate change issues, and reduction of CO2Es have highlighted the importance of renewable energy. As a result, South Africa's investment in the renewable energy industry as a portion of GDP in 2012 was one of the greatest globally (Salahuddin et al. 2019). The authors further propounded that has several renewable energy sources, e. g. , wind, solar, geothermal, biomass, and hydropower. Renewable energy curtails conventional energy consumption while conserving lasting universal economic output (Raihan et al. 2023b). Also, renewable energy is clean, safe, and plentiful compared to conventional energy (Raihan and Tuspekova 2023a). It has been said by some authors (Mujtaba et al. 2022; Raihan and Tuspekova 2022a; Mehmood 2021; Mehmood and Mansoor 2021; Mensah et al. 2018) that economic growth lowers CO2Es. However, most scientists agree that CO2Es are linked to economic growth in both developed and developing countries (Alaganthiran and Anaba 2022; Raihan and Bari 2024; Li et al. 2021; Ren et al. 2021; Feng et al. 2015; Yue et al. 2013). Many economies have a lot of natural resources, including fossil fuels, at their disposal. Since economic growth results in an upsurge in energy consumption due to industrialisation, it results in high levels of CO2Es. Several researchers have looked into the link between using fossil fuels and CO2 emissions and found that it is positive (Huang et al. [SEP] Justify:

Output: The text corroborates the claim by discussing how renewable energy is being developed to reduce CO2 emissions ('to reduce the level of CO2Es and offer dependable electricity to the people, the government is progressively improving the renewable energy industry'). It highlights the effectiveness of renewable energy in curtailing conventional energy consumption ('renewable energy curtails conventional energy consumption') and mentions its benefits, indicating that renewable energy is clean, safe, and plentiful ('renewable energy is clean, safe, and plentiful compared to conventional energy'). Furthermore, the text references how the growing energy demand is leading to high greenhouse gas emissions and emphasizes the necessity of increasing renewable energy usage to address these issues.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: 4% Although the economic stimulus in the R, C50, and Keynes scenarios is positive, the growth dividend from lower-cost energy is less than 1. 5% in 2030. To a significant extent, this is due to assumed resource constraints, particularly in labor markets. China can import natural resources without difficulty (but possibly with terms of trade effects), but we assume a very inelastic (0. 125) aggregate labor supply in the R, C50, and Keynes scenarios. When we relax this constraint modestly (to 0. 25) in the EMP scenario, the benefits of renewable energy stimulus increase dramatically. Incremental GDP in 2030 rises from 1. 3% in the Keynes scenario to 6. 9% in the EMP scenario, adding 9. 7 trillion RMB and 64. 9 million full-time equivalent jobs to the overall economy. In other words, renewable electricity can be growth positive but also strongly counter-cyclical, contributing even more to growth in adverse labor markets, such as during the pandemic-induced economic downturn. Finally, the PROD scenario demonstrates the substantial growth potential of productivity spillovers from an economywide renewable energy transition—for illustrative purposes only, because evidence is insufficient to estimate such induced productivity effects econometrically for China. The 1% annual TFP increase in the PROD scenario more than doubles economic growth compared with the EMP scenario, adding 15. 6% to real GDP in just over a decade. This scenario is a reminder that China’s most dynamic growth experiences—extending from the 1990s to 2005—depended not only on massive infrastructure investments, but also on significant technological progress. In the case of electric power, infrastructure also grew very rapidly, but technological progress has still been limited. New, clean energy technology can be instrumental in helping the economy achieve its full potential, improving material living standards and quality of life across China. ConclusionIn the wake of two decades of renewable energy innovations, it has become increasingly clear that the perceived tradeoff between economic growth and climate risk reduction is based on a fallacy. Low- and zero-emission electricity generation costs are falling below costs of carbon-fueled generation, and renewable energy co-benefits such as air-quality improvements are becoming ever more apparent. Nowhere is the issue more compelling than in China, which for several decades has developed electric capacity faster than any other country and now has the world’s largest renewable energy sector. [SEP] Justify:

Output: The text contrasts the claim by suggesting that while renewable energy can stimulate positive economic growth, there are underlying complexities and potential economic impacts when considering resource constraints, especially in labor markets. For example, it notes that assumptions about labor supply significantly affect the economic benefits attributed to renewable energy. Moreover, it implies that the relationship between economic growth and renewable energy transition is nuanced and affected by varying scenarios, thus disputing the simplicity of the claim that no economic impacts exist.


Input: Task: pass the claim using the given text. Claim: The study of extremophiles helps us understand potential life on other planets. [SEP] Text: Skip to content Menu AGU. org to by AGU for dropdown menu Space & & & & dropdown menu ’ Highlights Editors’ Eos en Español Eos 简体中文版 to for: inEditors' in Earth’s Recent progress in the analysis of seismic waves enables us to determine where, and sometimes how, the base of the mantle deforms. by 1 July 20241 July 2024 Share this:Click to print (Opens in new window)Click to email a link to a friend (Opens in new window)Click to share on Twitter (Opens in new window)Click to share on Facebook (Opens in new window)Click to share on LinkedIn (Opens in new window) The image was taken during fieldwork to monitor previously installed seismometers. Seismometer installation and monitoring are conducted by hundreds of scientists worldwide, allowing the recorded signals to be used to study Earth's deep interior. Credit: Editors’ Vox is a blog from AGU’s Publications Department. Earthquake waves travel through Earth’s interior and can be recorded by seismometers at distances of thousands or even tens of thousands of kilometers. These seismic waves traverse different parts of the mantle at different speeds, which depends on the material they are traveling through. Sometimes, the speed of shear waves – in the same material – depends on their vibrational direction, a phenomenon called seismic anisotropy. Figure 1: Schematic illustration of shear wave splitting due to lowermost mantle anisotropy. Shear wave splitting is illustrated for the SKS wave (top left), which travels as P (black wiggles) through the liquid outer core (gray shading) and then transforms to an SV wave at the core-mantle boundary. SKS splits into fast (blue) and a slow (red) traveling waves, which are polarized in orthogonal planes (slow: red; fast: blue). These components accumulate a time lag (delay time), which can be measured along with the polarization of the fast-traveling wave (fast polarization direction). Credit: Wolf et al. [2024], Figure 1 If seismic anisotropy is present, analogous to optical birefringence, the shear wave can split up into a fast and a slow traveling component. This primarily happens when waves travel through the lowermost mantle and upper mantle or crust. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on seismic waves, their behavior in Earth's mantle, and the installation of seismometers. It does not mention extremophiles, their study, or their implications for understanding potential life on other planets.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: (2021) articulated that innovation is an effective instrument for addressing CO2Es since it boosts cleaner production and energy efficiency. Several countries, including South Africa, have prioritised reducing carbon emissions by implementing new climate and energy finance technologies. The expectation is that can reduce its CO2Es to attain carbon neutrality by mid-century through adopting technology and making substantial green investments. South Africa’s 2011 Plan (NDP) shows the government's obligation to reduce emissions via the amplified adoption of renewable energy technologies. Specifically, the changeover to a green and climate-resilient economy is part of the Plan 2030 for (Government 2012). It is widely documented that technological innovations can decrease carbon emissions (Li et al. 2022; Udeagha and Ngepah 2022; Rafique et al. 2022; Anser et al. 2021; Erdogan 2021; Guo et al. 2021; Mensah et al. 2018; Long et al. 2018; Yii and Geetha 2017). Nevertheless, some studies have discovered that innovation increases CO2Es (Villanthenkodath and Mahalik 2022; Demir et al. 2020). Recently, there have been deliberate efforts to encourage economies to invest in renewable energy sources to reduce CO2Es (Raihan 2023d). Several authors have discovered that renewable energy use reduces carbon emissions (Ali et al. 2023; Chen et al. 2023; Ghosh et al. 2023; Huang et al. 2023; Kuldasheva and Salahodjaev 2023; Raihan and Tuspekova 2023b; Dauda et al. 2021; Voumik et al. 2023; Li et al. 2021; Yuping et al. 2021; Vural 2020; Mensah et al. 2018; Yue et al. 2013). From the discussion above, it is essential to analyse the influence of economic growth, technological innovation, renewable energy, fossil energy, and globalisation on CO2Es in South Africa. Even though the topic of CO2Es and their drivers is a hot topic for debate among policymakers, researchers, and scholars globally, research related to it has been limited in South Africa. Therefore, further research is required to consider the context. [SEP] Justify:

Output: The text corroborates the claim by stating that 'renewable energy use reduces carbon emissions.' It discusses the commitment of countries, like South Africa, to reduce emissions through the adoption of renewable energy technologies, which directly supports the assertion that such energy sources decrease reliance on fossil fuels and lower carbon emissions.


Input: Task: contrast the claim using the given text. Claim: All countries can transition to renewable energy without economic impacts. [SEP] Text: Recognizing the need for a low-carbon transition, China is experimenting with aggressive mitigation policies, including technology standards, ETS policies, and carbon taxation. Using a detailed forecasting model for China’s economy, we show how falling renewable energy technology costs can interact with a market-based ETS to deliver dramatic GHG reductions with net positive aggregate economic growth. This finding supports plentiful recent evidence of the impacts from renewable electricity costs dropping below grid parity, but we extend the economic analysis to identify other growth drivers. These include as-yet unrecognized multiplier and productivity spillovers. First, energy cost savings for households and enterprises permit expenditure shifting toward more diverse, labor-intensive goods and services, compared with the carbon fuel supply chain. Because the new expenditure focuses on services, this process stimulates new, broad-based domestic income and job creation—especially when labor supply is relatively elastic. Second, economic benefits brought about by technological progress have been neglected or underestimated in previous studies, yet modernization of the energy system can be expected to yield productivity benefits via technology spillovers. Although the exact magnitude of such impacts is an empirical question, the pervasiveness of energy services suggests it will be substantial. These results have two important implications. First, the economic benefits of renewable energy substantially exceed their direct costs, and adoption of renewable technologies can proceed without the still-controversial interventions needed to recognize the social cost of carbon in the coming decade. Second, modernizing the electric power system can support a new generation of more diverse domestic job creation, facilitating an essential transition for millions of workers in the carbon fuel supply chain, one of the last great artifacts of the Industrial Age. Overall, our results suggest that China should accelerate its clean energy transition, not only for the air-quality and climate benefits, but also for the broad and positive impact on innovation, employment, and economic growth. considers its post-COVID recovery measures, building green energy infrastructure should simultaneously support sustained economic growth and climate mitigation. MethodsWe use the (PANDA) model, a dynamic CGE model of the Chinese economy constructed at the University of California, Berkeley, which has been used to analyze China’s energy and climate policies. *16,38 The current version of the PANDA model is calibrated to the 2017 China Input-Output table,36 with 42 aggregated production sectors. [SEP] Justify:

Output: The text contrasts with the claim by explaining that while transitioning to renewable energy may have benefits, it also entails complex economic dynamics that are not without impact. For instance, it highlights that energy cost savings could shift expenditures, yet such a shift is only beneficial if certain economic conditions (like labor supply elasticity) are met. The text also indicates that economic benefits from renewable energy come at a cost, implying that the transition does affect the economy in various ways. Thus, the assertion that all countries can transition without economic impacts is challenged by the nuanced economic interactions described in the text.


Input: Task: pass the claim using the given text. Claim: The study of extremophiles helps us understand potential life on other planets. [SEP] Text: The effects of seismic anisotropy in the lowermost mantle on an SKS seismic wave are displayed in Figure 1. A new 2. Our current understanding is that these locations do not strongly correlate with any deep Earth structures, indicating that different mechanisms and deformation scenarios can cause it. Figure 2: Locations in which lowermost mantle seismic anisotropy has been found in previous studies (violet), compiled in the database of Wolf et al. [2023]. Gray background colors show large-low velocity zone locations based on work by Lekic et al. [2012]. Credit: Wolf et al. [2024], Figure 2b What are the main causes of seismic anisotropy? Seismic anisotropy in Earth’s mantle can be caused by two potential mechanisms. In the deep Earth, materials may have elastic properties significantly different from the surrounding material. If their shapes are directionally oriented, so-called shape-preferred orientation can be induced, and seismic waves can travel faster in certain directions than in others (e. g. , Kendall & Silver, 1998). Additionally, deformation can lead to the preferential alignment of individual crystals in an aggregate, so-called crystallographic-preferred orientation, which can also be cause of seismic anisotropy (e. g. , Kocks et al. , 2000). We believe that either of these mechanisms can potentially cause seismic anisotropy in the lowermost mantle, but that crystallographic-preferred orientation may be the dominant mechanism. Why is it hard to infer seismic anisotropy in the lowermost mantle? And what has led to recent progress? The main challenge when studying lowermost mantle anisotropy is that the seismic waves that are commonly used for this also potentially sample upper mantle anisotropy. Therefore, we must infer where exactly the seismic anisotropy is sampled, but the measurements that we are usually making integrate the effects of seismic anisotropy over the whole raypath. This is why techniques have been developed which use seismic phases that have very similar upper mantle raypaths and different lowermost mantle raypaths. In such cases, it is often argued that if the phases show a different anisotropic signature, seismic anisotropy must be present in the lowermost mantle. In other cases, seismic waves are used that have particularly long raypaths through the lowermost mantle. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses exclusively on seismic anisotropy in the Earth's lowermost mantle and does not address extremophiles or their significance in understanding potential extraterrestrial life. There are no references or connections made to extremophiles or the concept of life on other planets.


Input: Task: corroborate the claim using the given text. Claim: Renewable energy reduces reliance on fossil fuels and helps decrease carbon emissions. [SEP] Text: We used the (DOLS) estimator in this study to look at how economic growth, new technologies, fossil fuel use, renewable energy use, and globalisation have affected CO2Es in from 1990 to 2020, a period of 31 years. The DOLS estimator was adopted because of its capability to deal with issues linked to serial correlation and endogeneity in time series data with dynamic relationships. This assessment indicates that economic growth, fossil energy utilisation, technological innovation, and globalisation boost CO2Es, whereas renewable energy utilisation reduces CO2Es in South Africa. The results of the canonical cointegrating regression (CCR) and fully modified least squares (FMOLS) techniques also back up the results of the DOLS estimator, of course. This study adds our voice to the existing body of literature in many ways. It examines the impact of technological innovation, economic growth, fossil energy, renewable energy, and globalisation on CO2Es in implementing the DOLS technique over an elongated observation period of 31 years, i. e. , 1990–2020. Given that a unique set of features characterises the economy and that is one of the leading players in the coal energy industry, this study provides an assessment of the specific influences of the adopted variables on CO2Es in South Africa. More than that, the DOLS results were checked against the FMOLS and CCR results to get a more complete picture of how technological progress, economic growth, fossil fuels, renewable energy, and globalisation affect CO2Es. 2 Data and methodology2. 1 DataIn this study, we implemented the data set for extracted from the Indicators (WDI) data set. The data set adopted is for the years 1990–2020, i. e. , 31 years. This data set is comparable to other data sets adopted in the existing literature. For instance, Raihan and Tuspekova (2022c) used time series data for the period 1990–2019 for Brazil, and Raihan and Tuspekova (2022d) implemented Turkey’s time series data from 1990–2020, using CO2Es as the dependent variable, and the independent variables are fossil fuel energy utilisation, economic growth, globalisation, renewable energy utilisation, and technological innovation. [SEP] Justify:

Output: The text corroborates the claim by indicating that renewable energy utilization contributes to a reduction in CO2 emissions (CO2Es) in South Africa. It states that while economic growth, fossil energy utilization, technological innovation, and globalization tend to increase CO2 emissions, renewable energy utilization has the opposite effect, thereby supporting the assertion that renewable energy helps decrease carbon emissions.