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This study delves into the critical nexus between wastewater treatment, energy consumption, and greenhouse gas emissions. Wastewater treatment is a linchpin of sustainable development, yet its energy-intensive processes contribute significantly to greenhouse gas emissions. The research focuses on wastewater treatment plants (WWTPs) in Mexico City (CDMX) and the Metropolitan Area of Barcelona (AMB), exploring the disparities between a developed country and a developing country. The study examines how factors such as water treatment technologies and electricity sources influence carbon emissions. The AMB exhibits superior performance by treating all wastewater, cogenerating energy from the biomass contained in the wastewater and generating 10% fewer emissions, in stark contrast to CDMX, which does not capture the CH4 produced during water treatment, on top of only treating the water of 14% of the city's agglomeration. It underscores the critical implications of WWTP efficiency on climate change and progress toward UN Sustainable Development Goals. Given the limited attention to the Global South, this research serves as a vital contribution to the discourse on sustainability and development.

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This paper investigates the intricate interplay between carbon emissions and foreign direct investment within the context of Brazil, Russia, India, China, and South Africa (BRICS) for the period spanning 2000 to 2022. In our comprehensive analysis, we incorporate ecological footprint, renewable energy, globalization, and technological innovations as exogenous variables. Employing a system of simultaneous equations across the BRICS panel, we aim to fully elucidate the proposed relationships. Our empirical findings underscore the following key insights: foreign direct investment, technological innovations, and the adoption of renewable energy sources significantly contribute to the mitigation of carbon emissions in these selected nations. However, it is essential to note that ecological footprints exhibit a positive association with carbon emissions, raising concerns on two fronts: escalating environmental degradation and increased land pressure, both of which contribute to rising ecological footprints in BRICS countries. Additionally, our analysis reveals that foreign direct investment is influenced by its capacity to reduce carbon emissions and bolster renewable energy adoption, while globalization amplifies investment trends within the BRICS nations. To address the environmental repercussions of mining activities, it is imperative to implement stringent control and regulation measures, given their potential adverse impacts, including soil pollution, acid mine drainage, erosion, biodiversity loss, excessive water resource consumption, and wastewater disposal challenges. Nevertheless, proactive steps such as recycling mining waste, adopting environmentally friendly mining equipment, combatting illegal mining, and enhancing overall mining sustainability offer promising avenues to mitigate the environmental footprint of mining operations.

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The development of an environment that is sustainable requires infrastructure matching this goal. Moreover, it is almost impossible to achieve this goal without the requisite energy structure. Devising an energy structure that is both effective and efficient must precede the desired infrastructure to achieve sustainability goals. Therefore, it is important to look into the nexus of energy structure, infrastructure, and carbon emissions in "Brazil, Russia, India, China, and South Africa (BRICS)" countries under the growth and environment hypothesis. To empirically estimate the said nexus, robust econometric techniques are adopted. This paper employs panel data analysis techniques to investigate the relationship between infrastructure, energy consumption, and carbon emissions in the BRICS countries. The econometric estimation methodology includes a cross-sectional dependence test, unit root attribute of the panel data using the cross-sectionally augmented Im Pesaran and Shin (CIPS) test, and estimation of co-integration among the variables, and to address the issues in the panel data, augmented mean group (AMG) technique and common correlated effects mean group (CCEMG) estimator were employed. Findings suggest the existence of a supportive role of infrastructure and energy structure in abating carbon emissions. It is suggested that the BRICS economies need to enhance their investment in infrastructure and energy structure for them to create a sustainable environment. Findings are also robust to short- and long-run policy implications. This study is a step forward toward the Sustainable Development Goals (SDGs).

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Studies have shown that energy consumption from economic development leads to an increase in carbon emissions. Emerging economies, as important sources of carbon emissions with high growth potential, play a crucial role in global decarbonisation efforts. However, the spatial pattern and evolution trend of carbon emissions in emerging economies have not been studied in depth. Therefore, this paper uses the improved gravitational model and carbon emission data from 2000 to 2018 to construct a spatial correlation network of carbon emissions in 30 emerging economies around the world, aiming to reveal the spatial characteristics and influencing factors of carbon emissions at the national level. The results show that the spatial network structure of carbon emissions in emerging economies is closely linked, forming a "big network" of interconnection. Amongst them, Argentina, Brazil, Russia, Estonia, etc. are at the centre of the network and play a leading role. Geographical distance, economic development level, population density, and scientific and technological level have a significant impact on the formation of spatial correlation between carbon emissions. Further use of GeoDetector shows that the explanatory power of two-factor interaction on centrality is greater than that of a single factor, indicating that a single economic development cannot well enhance the influence of countries in the carbon emission network, and needs to be combined with factors such as industrial structure and scientific and technological level. These results are helpful to understand the correlation between carbon emissions between countries from the perspective of the whole and part and provide a reference for optimizing the carbon emission network structure in the future.

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The demand for more sustainable structures has been shown as a growing tendency, and engineers can use optimization techniques to aid in the design and sizing stage, achieving solutions that minimize its cost and environmental and social impacts. In pedestrian bridges, which are subjected to human-induced vibrations, it is also important to ensure the users' comfort, besides the security verifications. In this context, the objective of this paper is to perform a multi-objective optimization of a steel-concrete composite pedestrian bridge, minimizing cost, carbon dioxide emissions, and vertical acceleration caused by human walking. For this, the Multi-Objective Harmony Search (MOHS) was applied to obtain non-dominated solutions and compose a Pareto Front. Two scenarios were considered with different unit emissions obtained from a life cycle assessment in the literature. Results show that by increasing 15% the structure cost, the vertical acceleration is reduced from 2.5 to 1.0 m/s2. For both scenarios, the optimal ratio for the web height and total span (Le) lies between Le/20 and Le/16. The web height, the concrete strength, and the slab thickness were the design variables with more influence on the value of the vertical acceleration. The Pareto-optimal solutions were considerably sensitive to the parameters varied in each scenario, changing concrete consumption and dimensions of the welded steel I-beam, evidencing the importance of carrying out a sensitivity analysis in optimization problems.

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Global burned area has declined by nearly one quarter between 1998 and 2015. Drylands contain a large proportion of these global fires but there are important differences within the drylands, for example, savannas and tropical dry forests (TDF). Savannas, a biome fire-prone and fire-adapted, have reduced the burned area, while the fire in the TDF is one of the most critical factors impacting biodiversity and carbon emissions. Moreover, under climate change scenarios TDF is expected to increase its current extent and raise the risk of fires. Despite regional and global scale effects, and the influence of this ecosystem on the global carbon cycle, little effort has been dedicated to studying the influence of climate (seasonality and extreme events) and socioeconomic conditions of fire regimen in TDF. Here we use the Global Fire Emissions Database and, climate and socioeconomic metrics to better understand long-term factors explaining the variation in burned area and biomass in TDF at Pantropical scale. On average, fires affected 1.4% of the total TDF' area (60,208 km2 ) and burned 24.4% (259.6 Tg) of the global burned biomass annually at Pantropical scales. Climate modulators largely influence local and regional fire regimes. Inter-annual variation in fire regime is shaped by El Niño and La Niña. During the El Niño and the forthcoming year of La Niña, there is an increment in extension (35.2% and 10.3%) and carbon emissions (42.9% and 10.6%). Socioeconomic indicators such as land-management and population were modulators of the size of both, burned area and carbon emissions. Moreover, fires may reduce the capability to reach the target of "half protected species" in the globe, that is, high-severity fires are recorded in ecoregions classified as nature could reach half protected. These observations may contribute to improving fire-management.

El área global quemada se redujo en casi una cuarta parte entre 1998 y 2015. Los bosques secos contienen una gran proporción de esos incendios globales, pero existen diferencias importantes dentro de ellos, por ejemplo, las sabanas y los bosques secos tropicales (SBC). Las sabanas, son un bioma propenso y adaptado al fuego, y que en los últimos años han reducido su área quemada. Mientras que el fuego en la SBC es uno de los factores más críticos que impactan la biodiversidad y las emisiones de carbono. Además, bajo escenarios de cambio climático, se espera que la SBC aumente su extensión actual y aumente el riesgo de incendios. A pesar de los efectos a escala regional y global, y la influencia de este ecosistema en el ciclo global del carbono, se le ha dedicado poco esfuerzo a estudiar la influencia del clima (estacionalidad y eventos extremos) y las condiciones socioeconómicas del régimen de incendios. Aquí usamos la base de datos global de emisiones de incendios y métricas climáticas y socioeconómicas para comprender mejor los factores a largo plazo que explican la variación en el área quemada y la biomasa a escala Pantropical. En promedio, los incendios afectaron el 1,4% del área total de la SBC (60 208 km2 ) y quemaron el 24,4% (259,6 Tg) de la biomasa global quemada anualmente a escala Pantropical. Los moduladores climáticos influyen en gran medida en los regímenes de incendios locales y regionales. La variación interanual del régimen de incendios está determinada por El Niño y La Niña. Durante El Niño y el año subsecuente de La Niña, se produce un incremento en la extensión (35,2% y 10,3%) y en las emisiones de carbono (42,9% y 10,6%). Los indicadores socioeconómicos como la gestión de la tierra y la población fueron moduladores del tamaño tanto del área quemada como de las emisiones de carbono. Además, los incendios pueden reducir la capacidad de alcanzar el objetivo de "protección de la mitad de las especies" en el mundo, es decir, los incendios de alta gravedad se registran en ecorregiones clasificadas como naturaleza que podría alcanzar la protección de la mitad de su biodiversidad. Estas observaciones pueden contribuir a mejorar la gestión de incendios.

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RESUMEN Las actividades académicas, como los congresos, son muy importantes para la investigación y el desarrollo; sin embargo, las emisiones de carbono derivadas de la realización de eventos presenciales han mostrado estar muy por encima de las que producen eventos en línea. El objetivo de este trabajo fue estimar las emisiones generadas por el 5º Congreso Nacional y 1º Internacional de Ciencias Ambientales "Las Ciencias Ambientales en el Antropoceno", celebrado virtualmente, en su mayor parte. Se estimaron las emisiones del uso directo de computadores y de software (emisiones de los computadores, emisiones de la transferencia de los datos) y las emisiones de otras fuentes (reuniones de los organizadores, búsquedas y visitas a la página Web, uso de monitores externos y lámparas), así como las emisiones evitadas por transporte aéreo y terrestre. El congreso emitió 4,8 tCO2eq y evitó 33 tCO2eq. El desarrollo de eventos online o híbridos es más sostenible ambientalmente y podría ser más accesibles, a un mayor número de personas.

ABSTRACT Academic activities such as conferences are very important for research and development, however, carbon emissions derived from face-to-face events have been shown to be much higher than those produced by online events. The aim of this work was to estimate CO2 emissions generated by the 5th National Congress and 1st International Congress of Environmental Sciences "Environmental Sciences in the Anthropocene". Emissions from direct use of computers and software (emissions from computers, emissions from data transfer) and emissions from other sources (meetings of the organizers, searches and visits to the website, use of external monitors and lamps), as well as emissions avoided by air and land transport. The congress emitted 4.8 tCO2eq and avoided 33 tCO2eq. The development of online or hybrid events is more environmentally sustainable and could be more accessible to a greater number of people.

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This paper attempts to model both static and dynamic dependence structures and measure impacts of energy consumptions (both renewable (EC) and non-renewable (REN) energies), economic globalization (GLO), and economic growth (GDP) on carbon dioxide (CO2) emissions in Argentina over the period 1970-2020. For analyses purpose, the current research deploys the novel static and dynamic copula-based ARIMA-fGARCH with different submodels. The static bivariate copula results show that the growth rates of the pairs EC-CO2 and GDP-CO2 are asymmetrically positive co-movements and have high left tail (extreme) dependencies, implying that the increase in non-renewable energy and economic growth can critically contribute to the environmental degradation, and the decrease in the consumption of non-renewable energy at a high level will consequently reduce the CO2 emissions at the same level. Based on several copula-based dependence measures, we document that between the two factors, the non-renewable energy has a stronger impact than the economic growth regarding the CO2 emissions. On the other hand, the growth rates of both economic globalization and renewable energy symmetrically negatively co-move with the growth rates of the CO2 emissions, but they have no extreme dependencies, indicating that these factors contribute to Argentina's environmental quality, in which the factor of renewable energy has a greater impact. Furthermore, the dynamic copula outcomes show that the (tail) dependencies of CO2 emissions on the non-renewable energy and economic growth are time-varying, while the pairs REN-CO2 and GLO-CO2 possess only dynamic dependencies, but no dynamic tail dependencies. Moreover, through the dynamic copula-based dependence, the environmental Kuznets curve (EKC) hypothesis can be estimated and illustrated explicitly. In addition, we leverage multivariate vine copulas for modelling dependence structures of the five variables simultaneously, which can reveal rich information regarding conditional associations among the relevant variables. Some policy implications are also provided to mitigate CO2 emissions.

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The energy sector of Argentina is predominantly reliant on fossil fuels. Consequently, such fossil fuel dependency within the nation's power sector, in particular, has aggravated the environmental quality in Argentina by amplifying the nation's energy production-based carbon emission levels. However, keeping into consideration the international commitments pledged by Argentina under the Paris Accord and the Sustainable Development Goals agenda, it is pertinent for this South American country to curb its energy production-based emission of greenhouse gases, especially carbon dioxide. Against this milieu, this study examines the impacts of renewable electricity generation, economic globalization, economic growth, and urbanization on carbon dioxide emissions generated from the production of electricity and heat in the context of Argentina. Using annual frequency data from 1971 to 2016, recent econometric methods are applied to control for multiple structural breaks in the data. The major findings from the ecnometric analyses affirmed long-run associations between renewable electricity generation, economic globalization, economic growth, urbanization, and energy production-based carbon dioxide emissions in Argentina. Besides, enhancing renewable electricity output shares is found to curb these emissions while economic globalization and urbanization are witnessed to boost them. Moreover, renewable electricity generation and economic globalization are found to jointly reduce the energy production-related carbon dioxide emissions in Argentina. The results also validate the authenticity of the Environmental Kuznets Curve (EKC) hypothesis. Finally, the causality analysis reveals evidence of unidirectional causalities running from renewable electricity generation, economic globalization, economic growth, and urbanization to energy production-related carbon dioxide emissions in Argentina. In line with these findings, this study recommends several viable policies which can be implemented to help Argentina control the growth of its energy production-based carbon dioxide emissions.

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Tourism is one of the fastest-growing sectors in the world with a shift from mass tourism to personalized travel. Nevertheless, it generates significant environmental impacts. The current events associated with quarantine measures generated by COVID-19 represent, however, a risk for this sector. It is hence necessary to create strategies that allow efficient decision-making for all echelons and actors for a rapid recovery. Tourists are key actors, which makes necessary to facilitate tourism trip planning according to tourists' preferences as a complex process. In this paper, we propose a novel model of tourist trip planning for heterogeneous preferences in a tourist group and selection of transport modes, in the first instance, while a second step seeks at minimizing the level of CO2 emissions. A comparison of the two models is made considering the objectives associated with individual tourist benefits and group profit equity, in contrast to the inclusion of the cost of CO2 emissions. A numerical comparison is carried out with a total of 546 data sets. Results illustrate the conflict between those objectives by generating an inverse relationship between the individual and group profit equity of tourists, in addition to individual benefit and emission minimization.

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The current research assesses the impact of political risk on carbon dioxide (CO2) emissions in Brazil while controlling the role of financial development, GDP growth, trade openness, and technological innovation. In doing so, the quarterly dataset from 1990 to 2018 is utilized with Bayer and Hanck cointegration, dynamic ordinary least square (DOLS) and canonical correlation regression (CCR), and frequency-domain causality tests. The cointegration test revealed a long-run association amongst the variables of interest. Furthermore, the outcomes from the DOLS and CCR revealed that increasing financial development, technological innovation, trade openness, and real growth increase CO2 emissions while a better political environment reduces environmental pollution.

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Amazonia experienced unusually devastating fires in August 2019, leading to huge regional and global environmental and economic losses. The increase in fires has been largely attributed to anthropogenic deforestation, but anomalous climate conditions could also have contributed. This study investigates the climate influence on Amazonia fires in August 2019 and underlying mechanisms, based on statistical correlation and multiple linear regression analyses of 2001-2019 satellite-based fire products and multiple observational or reanalyzed climate datasets. Positive fire anomalies in August 2019 were mainly located in southern Amazonia. These anomalies were mainly driven by low precipitation and relative humidity, which increased fuel dryness and contributed to 38.9 ± 9.5% of the 2019 anomaly in pyrogenic carbon emissions over the southern Amazonia. The dry conditions were associated with southerly wind anomalies over southern Amazonia that suppressed the climatological southward transport of water vapor originating from the Atlantic. The southerly wind anomalies were caused by the combination of a Gill-type cyclonic response to the warmer North Atlantic sea surface temperature (SST), and enhancement of the Walker and Hadley circulations over South America due to the colder SST in the eastern Pacific, and a mid-latitude wave train triggered by the warmer condition in the western Indian Ocean. Our study highlights, for the first time, the important role of Indian Ocean SST for fires in Amazonia. It also reveals how cold SST anomalies in the tropical eastern Pacific link the warm phase of the El Niño-Southern Oscillation (ENSO) in the preceding December-January to the dry-season fires in Amazonia. Our findings can develop theoretical basis of global tropical SST-based fire prediction, and have potential to improve prediction skill of extreme fires in Amazonia and thus to take steps to mitigate their impacts which is urgency given that dry conditions led to the extreme fires are becoming common in Amazonia.

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Biomonitoring of atmospheric pollution is an increasingly accepted practice. However, most existing biomonitors are usually epiphytic species from mesic environments. This work assessed the suitability of buffelgrass (Cenchrus ciliaris), an invasive C4 grass in northwestern Mexico, as a biomonitor, by means of the spatial distribution of the carbon and nitrogen content and isotopic signatures for grass samples collected from urban, agricultural, and natural areas throughout the state of Sonora. We found the highest tissue carbon content of 45.6% (on a dry weight basis) and highest nitrogen content of 3.31% for buffelgrass from the Yaqui Valley. We also found the lowest δ13C of -15.9‰, and the highest δ15N of 16.7‰ in the same region. In contrast, the lowest carbon and nitrogen content of 39.4 and 1.49% were found for Bahía de Kino and Río Sonora mountains, respectively. The lowest δ15N of 2.18‰ and the highest δ13C of -13.7‰ were measured for two remote locations. These results show the influence that pollutant emissions, including agriculture and transportation, have on elemental and isotopic composition of vegetation. Buffelgrass is most adequate for tracking carbon and nitrogen emissions in arid environments and for determining alterations on nitrogen soil reactions, as a first approximation for saturation.

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The greatest contribution to global CO2 emissions comes from the BRICS countries (Brazil, Russia, India, China, and South Africa). The building sector in these countries is one of the sectors that increases CO2 emissions significantly. Increasing CO2 emissions in the building sector adversely affects sustainable development. Therefore, measures to mitigate environmental damage become substantially important. Improvements in technological innovation can be among the measures considered to mitigate CO2 emissions. In this study, the effects of technological innovation on the carbon emissions caused by the building sector are examined by panel data methods for the BRICS countries in the period 1992-2018. It has been observed that there is a long-term relationship between the series. As the results of Dynamic Common Correlated Effects indicated, increased technological innovation reduces carbon emissions. This result is meaningful to encourage investments related to technological innovation.

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This research formulates a theoretical framework to investigate the impacts of trade on consumption-based carbon emissions (CCO2) and also takes into account the influence of financial development and renewable energy use utilizing panel data for Mexico, Indonesia, Nigeria, and Turkey (MINT) nations between 1990 and 2017. The study utilizes a series of second-generation techniques such as Westerlund cointegration, cross-sectional augmented autoregressive distributed lag (CS-ARDL), and augmented mean group (AMG) tests to capture the linkage between CCO2 emissions and the independent variables. The study aims to answer the following questions: (a) can exports and imports determine CCO2 emissions in the MINT nations? (b) Is there a long-run association among the variables under investigation? The results of the Westerlund cointegration reveal a long-run association among the variables. The CS-ARDL outcomes indicate that imports and economic growth increase CCO2 emissions, while renewable energy use and exports decrease CCO2 emissions. Moreover, the outcomes of the AMG test also give credence to the CS-ARDL results. Our key policy recommendations are that initiatives, rules, and regulatory mechanisms should be implemented that promote the transformation toward renewable energy.

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This research investigates the drivers of consumption-based carbon emissions in Brazil by using a dataset covering the period between 1990 and 2018. These dynamics were examined by employing the ARDL bounds, DOLS, and gradual shift causality tests. The ARDL long- and short-run estimation outcomes reveal that: (a) renewable energy use stimulates the sustainability of the environment; (b) economic growth increases environmental degradation; and (c) technological innovation enhances the quality of the environment. In addition, the gradual shift causality test results disclosed that renewable energy consumption, economic growth, technological innovation and public-private partnership investment in energy can predict consumption-based carbon emissions in Brazil. Therefore, Brazilian policymakers should actively encourage the R&D of low-carbon technologies and renewable energy consumption. Domestic consumption levels, on the other hand, should be targeted, specifically those that are more energy-intensive and cause a rise in CO2 emissions due to consumption.

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In recent years, a growing number of scholars have employed various proxies of environmental degradation to understand the reasons behind rising environmental degradation. However, very few studies have considered consumption-based carbon emissions, even though a clear understanding of the impact of consumption patterns is essential for redirecting the pattern to more sustainable consumption. Thus, this study takes a step forward by using consumption-based carbon emissions (CCO2) as a proxy of environmental degradation using the novel non-linear ARDL technique for Chilefrom 1990 to 2018. To the best understanding of the investigators, no prior studies have investigated the drivers of consumption-based carbon emissions utilizing non-linear ARDL. The study employed ADF and KSS (non-linear) tests to check the data series' stationary level. Additionally, the symmetric and asymmetric ARDL approaches are utilized to explore cointegration and long-run linkages. According to the results, there is no symmetric cointegration among the variables; however, the empirical estimates reveal a long-run asymmetric connection between the indicators and CCO2 emissions. The novel results from the asymmetric ARDL indicate that negative and positive changes in economic growth deteriorate the quality of the environment. Interestingly, a reduction in economic growth makes a more dominant contribution to environmental degradation. Moreover, positive changes in renewable energy usage improve the quality of Chile's environment, inferring that the country can achieve a reduction in environmental degradation by boosting renewable energy consumption. Surprisingly, the study found that technological innovation is ineffective in reducing consumption-based carbon emissions, which implies that Chile's technological innovation is not directed towards manufacturing green technology. Finally, the policy implications are discussed with respect to reducing consumption-based carbon emissions.

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The effect of financial development measured by banks, bonds, and stocks on carbon dioxide emissions (CO2E) has been widely studied while not much is known about the effect of the insurance sector development on CO2E. Thus, this study fills this void by estimating the effect of insurance consumption on CO2E for BRICS (Brazil, Russia, India, China, and South Africa) from 2000 to 2016 using the instrumental variable generalized method of moments model. The findings indicate that, generally, insurance sector development spurs CO2E in BRICS. Specifically, a 10% rise in life insurance development increases BRICS CO2E by 1%. Also, a 10% rise in non-life insurance development increases BRICS CO2E by 4%. Finally, a 10% rise in the composite insurance development index increases BRICS CO2E by 2%. The study further finds that population size, trade openness, and energy consumption drive CO2E in BRICS, while economic growth mitigates CO2E. These results were robust to alternative econometric estimators, and alternative CO2E proxy. Policies that promote green insurance consumption are recommended.

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This work presents a weekly carbon isotope composition analysis (June 2017-January 2018) of carbon dioxide (CO2) and methane (CH4) in a tropical urban atmosphere (Central Valley, Costa Rica). δ13C values of CO2 and CH4 ranged from -12.2 to -5.9 ‰, and from -51.6 to -46.3 ‰, respectively. Mixing ratios of CO2 and CH4 varied from 384.2 to 528.5 ppmv, and from 1.860 to 2.613 ppmv, respectively. δ13C spatial variation and mixing ratios of CO2 and CH4 were influenced by the atmospheric stability and air circulation patterns in the metropolitan area. Low δ13C values and large mixing ratios were observed in the southwestern area of the valley during the rainiest period (September-November). Preliminary linear relationships between reciprocal CO2 mixing ratios and δ13C values indicate that CO2 emissions in the Central Valley are probably related to respiration processes and fossil fuel combustion, although CO2 enriched in 13C from volcanic degassing was also detected. Under stable atmospheric conditions, CH4 data seems to reflect the influence of emissions near the sampling sites. These preliminary results based on the carbon isotope technique demonstrate potential for carrying out atmospheric studies at tropical urban locations with different terrain characteristics and atmospheric mixing conditions.

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In all countries, the priority of policymakers is to reduce carbon emissions without reducing economic growth performance. Progress in innovation is one of the main measures that can be used to reduce carbon emissions. It is important to demonstrate the impact of innovation at the sectoral level, in terms of more realistic data on policy measures. The aim of this study is to investigate the effects of innovation on carbon emissions on a sectorial basis for fourteen countries in the G20, for the period between 1991 and 2017. The selected countries are Argentina, Brazil, Canada, France, Germany, India, Indonesia, Japan, Korea, Mexico, South Africa, Turkey, the United Kingdom, and the United States for which data is available. The results show that the Environmental Kuznets Curve (EKC) hypothesis is invalid and, in the long-term, innovations did not have a statistically significant effect on the energy sector, transport sector, and other sectors. It was also found that while an increase in innovation in the industrial sector leads to a reduction in carbon emissions, an increase in innovation in the construction sector increases carbon emissions. Therefore, it can be recommended that, in addition to national policies to reduce CO2 emissions, specific policies should be implemented for each sector separately.

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