Emissions In Countries Research Articles

China's electric vehicles adoption: implications for sustainable electricity, transportation, and net-zero emissions

IntroductionThe rapid adoption of electric vehicles in China is a key strategy for decarbonizing the transportation sector, facilitating the transition to sustainable energy, and meeting the country's net-zero emissions goals. Notwithstanding this, limited research has explored how technological advancement influences electric vehicle adoption in the context of achieving sustainable electricity.MethodsThis study addresses this gap by integrating vehicle range, smart charging infrastructure, and battery electric vehicles into an econometric count framework utilizing countrywide data-driven insights.ResultsThe findings demonstrate that technological advancements-specifically in vehicle range and the expansion of charging infrastructure-are vital solutions in driving battery electric vehicles acceptance. These advancements are essential for revolutionizing the transportation industry and contributing to the country's emissions reduction targets.DiscussionHowever, this presents a dual challenge: balancing increased electricity demand while capitalizing on these technologies to meet net-zero goals. The study highlights critical policy implications, particularly the need to advance electric vehicle material technologies through the use of critical minerals including aluminum and lithium. By prioritizing these materials, producers can improve electric vehicles' efficiency and support the integration of renewable energy sources. The study concludes that incorporating renewable energy solutions, like solar-powered charging stations, is crucial for ensuring sustainable electricity. Policies encouraging public-private partnerships and investments in research on materials and smart charging technologies are crucial for reducing charging times and improving vehicle range. Additionally, fostering public-private collaborations to install smart charging infrastructure equipped with Internet-of-Things technology at parking slots can create a synergistic effect, significantly boosting electric vehicle adoption in China.

Research on factors influencing total carbon emissions of construction based on structural equation modeling: A case study from China

As a pillar industry in China, the construction sector plays a crucial role in advancing the country's carbon emission (CE) reduction initiatives. The factors influencing CE in the construction industry (CI) are numerous and complex. This paper analyzes the influencing factors of CE in the CI based on structural equation modeling. Firstly, by combining the relevant literature and actual situation of CE in the CI, 38 common influencing factors corresponding to the building, economic, social, technological and energy levels are initially selected, and the data corresponding to each influencing factor in each province and city in China for 10 years are collected and then processed without dimension. Secondlyd, 12 hypothetical relationships between building, economic, social, technological and energy and CE from the CI are established based on the actual situation, and the initial CE in the CI structural equation model is established after the data set is tested for normal distribution, reliability and validity. Thirdly, the model is evaluated for path significance and model fit, and the modified structural equation model of CE from the CI is obtained after the initial model is modified, and the modified model is evaluated again. Finally, based on the modified model, the influence degree and effect of CE influencing factors in the CI are analyzed. It is concluded that economy, technology, and energy are the main factors successively affecting the total CE of buildings.

Heterogeneous technology-induced global CO2 emission reduction and emission forecasting since the Kyoto era

While identifying the drivers of global CO2 emission is crucial for climate change mitigation, the heterogeneous technology-related drivers (e.g., technological change and efficiency of energy and CO2 emission) were ignored to a large extent at a global scale, hindering to formulate heterogenous climate policies. Moreover, the projection of CO2 emission was also not well compared for countries. Here, the study investigated the heterogeneous technology-related drivers of CO2 emissions in time and space simultaneously in 42 major emitter countries over 1998–2020 by extending the spatiotemporal production-theoretical decomposition models, and compared the different performances for forecasting CO2 emission by traditional time-series models and several machine learning models. Key findings as follows: first, drivers of CO2 emissions exhibit significant heterogeneity across countries where the effects of energy usage technology gap and CO2 emission technology gap were negative drivers for USA, South Korea, and the Czech Republic and potential energy intensity effect was the negative driver in countries like China, Russia, Japan, and India. Second, the effects of within-GDP per capita and within- population size were the important drivers affecting global CO2 emission difference. Third, general regression neural network achieved the best forecasting performance on average compared with other models in the study. The study highlights the importance of formulating climate policies based on heterogeneous technology and emission forecast modeling.

Shaping India's climate future: A perspective on harnessing carbon credits from agriculture

Human activities are responsible for emitting greenhouse gases (GHGs) that contribute to global warming and climate change. As the world's second-largest producer of staple food and the third-largest emitter of GHGs, India has been witnessing an increase in demand for food and energy, resulting in increased emissions. Thus, to achieve net carbon neutrality by 2070, India must focus urgently on climate change mitigation. Its agriculture sector has the potential to transition from being a net emitter to a net absorber of GHGs by adopting sustainable farming practices such as zero tillage, laser-assisted precision land leveling, direct seeding of rice, intercropping, biochar application, use of solar energy, and more efficient management of irrigation water, soil nutrients, livestock feed, and manure. To incentivize climate consciousness, a voluntary carbon credit trading system could be utilized in agriculture, supported by a measurement, monitoring, reporting, and verification platform. This system would also bring about social, environmental, and financial co-benefits for its stakeholders. Specifically, the agriculture sector could substantially reduce the country's annual emissions by 84% from 2019 to 2070. But to realize their potential, the carbon markets must overcome the limitations currently set by policy, economic, cultural, and biophysical factors.

Reproducing Memories and Portrayal of the Concept of Virginity in Turkey through Orhan Pamuk’s The Museum of Innocence

The Museum of Innocence (2009) delves into love and everyday objects of love to explain the country's cultural emissions and political issues due to cultural contradiction with few characters in the novel. The novel is planned as a love story but is written in a decidedly unorthodox narrative style. The narrative is focused on the lovers' connection and revolves around Kemal's alterations due to his love for Fusun. He brings the supernatural close to the material, combining them most unexpectedly. Pamuk's construction of the actual museum in the memory of Fusun was discussed. Pamuk spoke about the memories of Fusun in Kemal's story narration with the portrayal of cultural indifference in Turkey. Further, this paper brings out the clash between fundamental traditional Islam and modern secularism by portraying the westernisation lifestyle of Istanbul's bourgeois society. The research paper concentrated on women's status and depicted the concept of virginity.

Green outward foreign direct investment and host country environmental effects: The home country's carbon emission reduction system is crucial

Studies on the environmental impacts of outward foreign direct investment (OFDI) with less attention paid to the relationship between gradually increasing green investment and carbon emissions in the host countries. Based on the background of global carbon emission reduction, this study constructs a STIRPAT and difference-in-differences model to analyze the environmental effects of China's OFDI in ASEAN countries using unique enterprise-level data of China's OFDI from 2005 to 2020. The results show that the impact of Chinese OFDI on carbon emissions in ASEAN countries varies with the investment sector, the home country's enterprise ownership type, and environmental policy. China's green OFDI shows a clear “Pollution Halo” effect regarding investment sectors. However, the “Pollution Halo” effect of green OFDI by Chinese state-owned enterprises (SOEs) is more pronounced when considering the home country's enterprise ownership type. In addition, from the home country's environmental policy perspective, implementing China's domestic low-carbon pilot policy has a “Pollution Haven” effect on host countries. This study provides policy implications to promote the green transformation of Chinese OFDI and carbon emission reduction in ASEAN countries.

Predictive modeling of energy‐related greenhouse gas emissions in Ghana towards a net‐zero future

AbstractGhana is determined to reduce greenhouse gas (GHG) emissions by at least 15% by 2030 and attain net‐zero emissions by 2070. However, like many developing countries, Ghana must utilize its limited resources effectively to actualize its climate goals. Currently, climate policies in the country are not driven by emission data, which has important implications on effective utilization of resources and selection of efficient mitigation techniques. We analyzed energy consumption and GHG emission data between 1990 and 2016 from Ghana's energy sector which is responsible for about 36% of the country's total emissions. Predictive models were then developed using machine learning to forecast energy related emissions up to 2030. Based on the analysis and projections, attainable data‐driven recommendations were proposed to direct climate policies in the country. We found that between 1990 and 2016, petroleum fuel consumption increased by about 64.5% and the corresponding GHG emissions increased by 303%. The projections suggests that by 2030, energy sector emissions could increase by 131% compared to 2016 levels. Transport sector emission is also projected to increase by a whopping 219% and fuel consumption could hit 6742 ktoe by 2030, which is about 106% increase from the 2016 benchmark. The findings from this work will direct policy for effective mitigation of GHG emissions in the country while ensuring effective utilization of climate resources to pursue its net‐zero targets. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Striving towards 2050 net zero CO2 emissions: How critical are clean energy and financial sectors?

The development of clean energy and financial sectors have been highlighted as critical factors in tackling climate change and achieving net zero emissions goals. Hence, using a dataset for the top 20 emitter countries from 1990 to 2019, this study examines whether clean energy consumption, financial development, human capital, population, and economic growth are connected with environmental quality through a reduction in carbon emissions. The long-run estimates show that renewable energy utilization, financial development, and human capital are significant in reducing CO2 emissions in the quest for net zero emissions. Contrarily, economic growth and population have a increases CO2 emissions. The results of the causality test show a two-way causality between renewable energy use, financial development, economic growth, population, and CO2 emissions. Moreover, one incidence of unidirectional causality is observed from CO2 emissions to human capital. Based on the findings, policy implications are suggested.

Impacts of Environment-Related Technology, Structural Change, and Globalization on Greenhouse Gas Emissions: Evidence from Top Twenty Emitter Countries

The issues of environmental degradation, climate change, and rising temperatures are a real and growing concern for humanity at the level of individuals, groups, and societies. Reducing greenhouse gas is an important element for nations to achieve their ambitious climate-resilient growth goals. The purpose of this research is to investigate the impact of environment-related technology, structural change, income, and globalization on greenhouse gas (GHG) emissions in the top twenty emitter countries from 1997 to 2019. To this end, this study has applied the new and widely used method of moment quantile regression (MMQREG) to permit the estimation of relationships across the distribution of an outcome. In order to test the reliability of the benchmark estimation results, this article uses three different methods for robust testing, the PCSE, FGLS and the linear regression with Driscoll–Kraay standard errors. The main findings of this paper show that environment-related technology, structural change, and globalization helps to boost ecological quality. Moreover, there is strong evidence on the existence of an N shape EKC. Based on the findings of this paper, governments should encourage investment in environment related technology and post the transition to services-based economies.

Investigation of Thermal Comfort for ANaturally Ventilated House: Correlation between Climatic Design Strategy and Thermal Data Analysis

One of the main factors contributing to climate change and global warming is architecture, which accountsfor about 50% of the country's greenhouse emissions due to construction and the energy needed to keep buildings operational. Sustainable architecture is believed to reduce emissions, andthisapproach has been practisedwithtraditional buildings. In Malaysia, a traditional Malay house (TMH) is one of thetraditional buildings, and it is initially naturally ventilated with occupant-controlled air ventilation to condition the space. Numerous experimental studies claimed that TMHhas demonstrated a good model for contemporary designers to understand climatic and environmental design, building systems, and design adaptability.One of the approaches is to practiseclimatic design strategies. However, there is a lack of study to determine if TMH is still relevant as a sustainable design that can adapt to current climate conditions. Thus, the study aims to investigate the adaptive indoor thermal comfort of a Negeri Sembilan Malay house in a hot-humid climate determinedby the correlation betweenclimatic design strategy and thermal data analysis. This study employed the Predictive Adaptivemodel by executing two stages of fieldwork: i) local climate background and ii) physical measurement (case study description and environmental data). The data were thenanalysed using the ACS of ASHRAE 55 and MS 2680:2017. The primary results revealed that 62% of the hourly indooroperative temperatureof the case study house waswithin 80 to 90 % of the acceptability limit. The optimal comfort hourly indooroperative temperaturewasbetween25.5 to 29.5 °C with a prevailing mean outdoor air temperaturebetween23 to 30 °C, which represents 90% of the acceptability limitrange. Moreover, the results also complied with the standards of ACS, where the average hourly indooroperative temperature was less than 31 °C,with a prevailing mean outdoor air temperatureless than32 °C, which wasan acceptable indoor state for occupants' comfort. The findingscompliedwith RMK 12 Theme 3, which aims to be a carbon-neutral country by practising sustainable architecture and construction. The design of naturally ventilated houses, such as Negeri Sembilan Malay houses in hot-humid climates, can be a model reference for modern housing design development.

Achieving sustainable emissions in China: Techno-economic analysis of post-combustion carbon capture unit retrofitted to WTE plants

China's aims of achieving CO2 emissions peak by 2030 and carbon neutrality by 2060 are crucial in guiding international efforts to mitigate climate change. Amine-based solvent technologies for capturing CO2 on a large scale have been implemented as retrofits in various industrial facilities, with a particular focus on coal-fired power plants. Nonetheless, its implementation within the waste-to-energy (WTE) industry is considerably limited and non-existent in China. This work presents a technical and economic evaluation of retrofitting a generic WTE facility in China with a carbon capture system. A rate-based process simulation model of the capture plant was developed in Aspen Plus, and the effect of equipment installation factors on capital cost was evaluated via the enhanced detailed factor (EDF) method. A set of key performance indicators were evaluated. The findings indicate that the energy demand linked to the capture system caused a decrease in efficiency by 13.17%, 14.85%, and 16.56% at 85%, 90%, and 95% capture rates, respectively, and the overall exergy efficiency of the system was reduced by 5.5%, 8.27%, and 10.63%, respectively. The estimated CO2 captured costs range from €56.41/tCO2 to €58.95/tCO2, while CO2 avoided costs range from €153.33/tCO2 to €236.47/tCO2. Retrofitting a CO2 capture unit at WTE facilities has the potential to substantially contribute to achieving the country's emission reduction targets. However, the successful implementation requires a comprehensive policy structure. This work offers some insights into the prospective integration of CO2 capture technology in China's WTE industry.

Structural attribution of emissions along the global supply chain and implications for climate policy

AbstractTo develop and implement effective policies to mitigate climate change, it is important to understand the emission profile of sectors that comprise the network of global supply chains. Focusing on the relationship between sectors’ positions in the global supply chain, this study develops a structural position analysis framework based on input–output analysis. Our framework reveals the highest‐priority sectors and transactions, and the best strategies for CO2 emission reduction in the global supply chain. The strategies identified focus on cross‐border transactions and highlight the need for inter‐sectoral and international collaboration. The results indicate that the United States and China have different priorities and characteristics (even vis‐à‐vis the same industry), and that joint emission reduction policies should be coordinated to take advantage of each country's emission reduction potential. Our findings suggest that, in the United States and Europe, policies to promote the reduction of direct emissions from production of goods for exports through carbon taxes are important. Contrarily, in Asian countries, carbon emissions originate mainly from intermediate goods trades, suggesting the need for mandatory life cycle assessment reporting and emissions disclosure. Our analytical framework thus proposes specific policies that could effectively reduce specific sectors' and transactions’ carbon footprints.

The price is not right

The 2015 Paris Agreement requires all nations to combat climate change and to adapt to its effects. Countries promise to reduce their greenhouse gas (GHG) emissions through their Nationally Determined Contributions. Pledges to reduce emissions, however, have implications for economic growth. We estimate the link between economic growth and CO2 pollution levels and find that this relationship is highly non-linear. A country's GHG emissions rise rapidly as its economic activity rises, relative to global activity, meaning that fast-growing countries contribute most heavily to current GHG emissions. Then, using real per-capita GDP as our metric, we estimate how much the carbon price should be in order to remove the economic growth benefit from excess GHG emissions. We find that the implied prices are far higher than the prices on any existing market for emissions as well as estimates of the social cost of carbon. Our findings also have important implications for the global dialogue regarding responsibility for climate mitigation as well as for the choice of policies to support mitigation efforts.

Effects for global agriculture of country-specific climate policy regimes with a focus on methane

Abstract While countries have agreed in the Paris-agreement on common rules to report greenhouse gas emissions, the design of domestic climate policy regimes remains in the national domain. This may cause different carbon prices for climate gasses across countries, between a country's emission sectors, and within the same sector. Our focus is on methane, which is a major emitter from agriculture, but also linked to livestock farming which is a core activity in agriculture worldwide. We analyse the potential effects of domestic carbon pricing regimes for agriculture in a non-cooperative game theoretic setting using a global agricultural sector model. Our results indicate no ‘race to the bottom’ to apply carbon pricing regimes that result in lowest implicit carbon prices for methane. Enforcing a uniform regime can reduce additional global warming with up to 0.02 °C, but runs the risk of agreeing to lower emission cuts than a nationally determined choice would suggest.

Carbon footprints in pork production and consumption in China from 2005 to 2020

Livestock farming accounts for 14.5% of global total anthropogenic greenhouse gas (GHG) emissions. China has been a major contributor to global GHG emissions from livestock and is the biggest pork producer and consumer worldwide. However, those factors driving GHG emissions from pork production and consumption in China have not been thoroughly assessed. Here, we used the Global Livestock Environmental Assessment Model (GLEAM) and the Logarithmic Mean Divisia Index (LMDI) method to identify and assess the major drivers contributing to the life-cycle carbon emissions embodied in China's pork production and consumption from 2005 to 2020. Our results show that CO2 emissions accounted for 99% of the total GHG emissions in the pig industry, primarily released from the processing and transporting of pig feed. These two sectors contributed more than 90% to the total CO2 emission. CH4 was mainly emitted from enteric fermentation and manure management of pigs, which accounted for a tiny portion of total carbon emissions in the pork industry. Among the primary factors driving pork-induced carbon emissions in China, the reduction of pork emission intensity (PPE) significantly slowed down growing carbon emissions, attributed to the improvements in pork production technology and the promotion of green farming. Our finding reveals that the growing population primarily contributed to elevated carbon emissions before 2015 due to increasing demands for pork meat. Since 2015, the rapid growth of the aged population in China has decreased pork consumption capacity and carbon emissions from pork consumption. The result indicates, for the first time, that the population aging in China, the largest pork consumer in the world, would play a vital role in reducing pork consumption-induced carbon emissions. Such an effect would become more significant in the future, along with the growing aged population in China, favoring the country's GHG emission mitigation increasingly.

The viability of energy efficiency in facilitating Saudi Arabia's journey toward net-zero emissions

Assessing the contribution of energy efficiency to climate change mitigation is crucial as global warming continues to persist. This study assesses the impact of energy efficiency on carbon intensity in Saudi Arabia and evaluates its potential contributions to the country's net-zero emissions target. We analyze time-series data for Saudi Arabia from 1971 to 2020 and estimate a quantile regression model. The results show that energy efficiency is critical for mitigating carbon dioxide emissions, indicating the importance of activating this lever to accelerate the decarbonization process. The model is robust to changes in the proxy for energy efficiency, confirming energy efficiency's ability to mitigate environmental degradation in Saudi Arabia. Moreover, energy efficiency has a greater impact on the twenty-fifth to seventy-fifth quantiles of carbon intensity than on the tenth and ninetieth quantiles. These heterogeneous effects across carbon intensity quantiles should be considered when the Saudi government discusses and sets its decarbonization objectives. We further extend the analysis by forecasting carbon intensity through 2060 under a scenario in which energy efficiency improves. The results show that energy efficiency improvements may account for up to one-fifth of Saudi Arabia's decarbonization by 2060. This finding underscores energy efficiency's importance for achieving climate stability and building a better future.

Cement rotary kiln temperature prediction based on time-delay calculation and residual network and bidirectional novel gated recurrent unit multi-model fusion

China's cement production energy consumption accounts for more than 10% of the country's total energy consumption, and its emissions account for about 60% of the country's industrial emissions. The temperature of a cement rotary kiln directly affects the quality of the final product, the energy consumption of a plant, and emissions. Therefore, it is necessary to measure, to a high degree of accuracy, the temperature of a cement rotary kiln to reduce energy consumption, emissions, and improve product quality. However, the conditions in cement kilns are complex and variable; and there are large time-delays, while temperatures are affected by historical working conditions, making temperature measurement extremely difficult. In this paper, a modelling algorithm with a residual network and a bidirectional novel gated cycle unit is used to predict the clinker exit temperature of the rotary kiln. In addition, to solve the problem of large time-delays in cement kilns, a dynamic time-delay calculation algorithm based on Mutual information and adaptive sliding windows is proposed for time series data reconstruction, and finally a Gaussian-weighted multi-model fusion is applied to the prediction results for cement rotary kilns that produce a wide range of working conditions. To verify the advantages and feasibility of the proposed method, experimental validation is carried out using original production data from a large cement manufacturing enterprise in South China. The results demonstrate that the single step prediction time of the presented approach is 0.66 s, which can predict cement kiln temperatures quickly and accurately, compared to a single conventional forecasting algorithm, the average temperature difference dropped from 11.76 °C to 3.51 °C, R2 increased from 0.43 to 0.89, 94% of the depicted temperature errors are at ± 10 °C This will provide an effective solution for online decision-making during actual cement production.

Innovation for renewable energy and energy related greenhouse gases: Evaluating the role of green finance

Environmental degradation is one of the many unintended consequences of industrialization, which has resulted in misery for humans, and biodiversity around the world. These environmental concerns require consideration in order to gain a better understanding of how to design policy around climate change. In this regard, a number of deals have been reached with the objective of reducing pollutants in the environment so as to keep an average temperature that below 2 degrees Celsius. In order to effectively reduce greenhouse gas emissions, nations all over the world have been putting more of their attention on investments in R&D for renewable energy, often known as green financing. This study explores the influence of green finance in the presence of GDP, human capital, and economic risk on GHG emissions in G7 countries for the period of 1990–2020. We find that green finance and economic risk abates GHG emission intensity. It is interesting that the impact of green finance is stronger for countries with high emissions level and lower for low emitter countries. Human capital and GDP increase GHG emissions. The results of the present study have important consequence for G7 nations because majority of these countries have been facing high oil demand. Policies to enhance green financing during the period of high energy demand are vital. It is imperative that policies be put in place to maintain the development in green financing.

The effect of financial development and economic growth on ecological footprint: evidence from top 10 emitter countries.

This study investigates the effect of financial development and economic growth on ecological footprint by including non-renewable energy consumption and trade openness as additional determinants. For this purpose, annual data of 10 countries with the highest ecological footprint (China, the USA, India, Japan, Brazil, Indonesia, Mexico, Korea, Turkey, and the UK) for the period 1992-2017 is used. The Westerlund and Edgerton (2007) Panel LM bootstrap test results reveal that there is cointegration between the variables. Additionally, the results obtained from the Common Correlated Effects (CCE) coefficient estimator show that financial development, economic growth, and non-renewable energy consumption negatively affect environmental quality by increasing ecological footprint. On other hand, the effect of trade openness on ecological footprint is found to be statistically insignificant. In addition, according to the panel causality test results, a unidirectional causality from financial development to ecological footprint is found while bidirectional causality between economic growth and ecological footprint exists. Therefore, it would be beneficial for policymakers in such countries to direct financial resources to green energy production and consumption and to encourage projects and practices.

Social, economic, and technical factors affecting CO2 emissions in Iran.

Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region.