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With the rapid developm the application of digital ent of the new generation of information and communication technologies (ICT), the state-level governance model has undergone profound changes. It is worth pondering whether this change will have an impact on the carbon peak and carbon neutrality goals. Therefore, we collected data from 51 global economies that have proposed carbon neutrality targets from 2003 to 2020 to build a series of spatial measurement models and explored the impact of e-government construction on carbon emission intensity (CEI). Then, we further considered regional heterogeneity factors, grouped the selected countries into Asian, European, and American countries, and verified the differences between e-government construction and CEI in different regions. Additionally, on the basis of the spatial mediation effect model, this paper analyzed the industrial structure which played an intermediary role in achieving target for reducing CEI through e-government construction. The main findings are as follows. (1) A higher level of e-government construction will result in lower-carbon emissions intensity. (2) Spatial spillover effect regression results showed that the construction of e-government in neighboring countries also significantly inhibits the carbon emission intensity of the host country. (3) There was significant regional heterogeneity in the impact of e-governments on CEI; in Asia, the construction of e-governments significantly reduced CEI, but no significant reductions were observed in Europe and America. (4) E-governments influenced CEI by optimizing the industrial structure. The construction of e-governments was effective in Asia and Europe, while intermediary effect test was failed to pass in the Americas. This study mainly focused on the environmental benefits brought by the construction of e-governments, and the obtained results would provide an important reference for the achievement of the dual-carbon goals in countries worldwide. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is twofold: to explore the interrelationships between FDI with growth and sustainability dimension; and to empirically analyze the four dimensions, namely, environmental, economic, social and governance of sustainable FDI for South Asia and West Asia. Design/methodology/approach: The data utilized in the paper is sourced from the World Development Indicators and the Worldwide Governance Indicators, covering South and West Asian region over the period 2011–2017. The paper employed both static and dynamic panel (two-step difference generalized methods of moments) estimation methods. Findings: The results established a significant and robust relationship of past year FDI inflows with the current year's value of FDI inflows for both the regions. Further, some variances in the relationships such as control of corruption, long-run carbon emissions, research and development, number of trademark applications as per the contextual factors have been detected. Research limitations/implications: The conclusions related to gender and governance found in this paper will be of interest to both researchers and policy makers for substantially reorienting the sustainability attributes to the foreign investment. Originality/value: The authors' main contributions are: to encapsulate the conceptual framework into an empirical model by combining all the four dimensions, namely, environmental, economic, social and governance; to have analyzed the possible differences and similarities in the study based on South and West Asia; to have explored the relationship between gender and FDI. [ABSTRACT FROM AUTHOR]

This two-dimensional study makes significant incursions into the health-environment literature by interrogating whether non-renewable energy moderates the impact of environmental degradation on mortality rates. It further aligns with the 2030 United Nations Sustainable Development Goals and 11, which aim to ensure healthy lives and promote well-being for all at all ages and make cities and human settlements inclusive, safe, resilient and sustainable. It contributes to the health-environment literature by investigating the intrinsic relationships among mortality rates, carbon emissions (environmental degradation), and non-renewable energy consumption. The study uses an unbalanced sample of 42 Asia and Pacific countries to determine (1) whether carbon emissions exaggerate the incidence of mortality rates and (2) if the interaction of non-renewable energy with carbon emissions enhances or alters the impact of carbon emissions on mortality rates. Consistent findings from the panel spatial correlation consistent least-squares dummy variables (PSCC-LSDV) and two-step system generalized method of moments (GMM) techniques reveal that (i) carbon emissions exacerbate mortality rates; (ii) non-renewable energy consumption exhibit mortality-reducing properties; (iii) non-renewable energy attenuates the impact of carbon emissions on mortality rates, (iv) persistency in mortalities occurs; and (v) the health-environment-energy dynamics differ across income groups. The paper's conjecture is expected to channel a new line of discourse on how non-renewable energy influences the environment and health outcomes. [ABSTRACT FROM AUTHOR]

Accurately mapping impervious-surface dynamics has great scientific significance and application value for research on urban sustainable development, the assessment of anthropogenic carbon emissions and global ecological-environment modeling. In this study, a novel and automatic method of combining the advantages of spectral-generalization and automatic-sample-extraction strategies was proposed, and then an accurate global 30 m impervious-surface dynamic dataset (GISD30) for 1985 to 2020 was produced using time-series Landsat imagery on the Google Earth Engine cloud computing platform. Firstly, the global training samples and corresponding reflectance spectra were automatically derived from prior global 30 m land-cover products after employing the multitemporal compositing method and relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with the migrated reflectance spectra of impervious surfaces from 2020 and transferred pervious-surface samples in each epoch for every 5∘×5∘ geographical tile, were applied to map the impervious surface in each period. Furthermore, a spatiotemporal-consistency correction method was presented to minimize the effects of independent classification errors and improve the spatiotemporal consistency of impervious-surface dynamics. Our global 30 m impervious-surface dynamic model achieved an overall accuracy of 90.1 % and a kappa coefficient of 0.865 using 23 322 global time-series validation samples. Cross-comparisons with five existing global 30 m impervious-surface products further indicated that our GISD30 dynamic product achieved the best performance in capturing the spatial distributions and spatiotemporal dynamics of impervious surfaces in various impervious landscapes. The statistical results indicated that the global impervious surface has doubled in the past 35 years, from 5.116×105 km2 in 1985 to 10.871×105 km2 in 2020, and Asia saw the largest increase in impervious surface area compared to other continents, with a total increase of 2.946×105 km2. Therefore, it was concluded that our global 30 m impervious-surface dynamic dataset is an accurate and promising product and could provide vital support in monitoring regional or global urbanization as well as in related applications. The global 30 m impervious-surface dynamic dataset from 1985 to 2020 generated in this paper is free to access at 10.5281/zenodo.5220816 (Liu et al., 2021b). [ABSTRACT FROM AUTHOR]

Continuous economic growth and the rise in energy consumption are linked with environmental pollution. Demand for health care expenditure increased after the COVID-19 pandemic. This study is interesting in modeling the nexus between public and private health expenditure, carbon dioxide emissions, and economic growth. To this end, the present study analyzed the nexus between public and private health care expenditure, economic growth, and environmental pollution for 36 Asian countries for the period 1991–2017. FMOLS, GMM, and quantile regression analysis confirm the EKC hypothesis in Asia. Besides, FMOLS and quantile regressions reached the reducing effects of government and private health expenditures on CO2 emissions. While quantile regression results show that public and private health expenditures can mitigate CO2 emissions; however, these results differ for various levels of CO2. Findings of quantile regression show a significant impact of both public and private health expenditures in reducing CO2 at the 50th and 75th quantiles but results are insignificant for the 25th quantile. Overall, the paper concludes that both government and private health sectors' expenditures caused CO2 emissions to decrease in Asia and that the negative impact of the private health sector on CO2 emissions is greater than that of the government health sector. The concluding remark is that the higher the health spending, the higher the environmental quality will be in Asia. Hence, the health administrators need to increase public and private health expenditures with an effective cost-service and energy-efficient management approach to reach sustainable health services and a sustainable environment in Asia. [ABSTRACT FROM AUTHOR]

Accurately mapping impervious surface dynamics has great scientific significance and application value for urban sustainable development research, anthropogenic carbon emission assessment and global ecological environment modeling. In this study, a novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral generalization method and time-series Landsat imagery, on the Google Earth Engine cloud-computing platform. Firstly, the global training samples and corresponding reflectance spectra were automatically derived from prior global 30 m land-cover products after employing the multitemporal compositing method and relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with the migrated reflectance spectra of impervious surfaces from 2020 and pervious surface samples in the same epoch for each 5° x 5° geographical tile, were applied to map the impervious surface in each period. Furthermore, a spatiotemporal consistency correction method was presented to minimize the effects of independent classification errors and improve the spatiotemporal consistency of impervious surface dynamics. Our global 30 m impervious surface dynamic model achieved an overall accuracy of 91.5 % and a kappa coefficient of 0.866 using 18,540 global time-series validation samples. Cross-comparisons with four existing global 30 m impervious surface products further indicated that our GISD30 dynamic product achieved the best performance in capturing the spatial distributions and spatiotemporal dynamics of impervious surfaces in various impervious landscapes. The statistical results indicated that the global impervious surface has doubled in the past 35 years, from 5.116 x 105 km2 in 1985 to 10.871 x 105 km2 in 2020, and Asia saw the largest increase in impervious surface area compared to other continents, with a total increase of 2.946 x 105 km2. Therefore, it was concluded that our global 30 m impervious surface dynamic dataset is an accurate and promising product, and could provide vital support in monitoring regional or global urbanization as well as in related applications. The global 30 m impervious surface dynamic dataset from 1985 to 2020 generated in this paper is free to access at http://doi.org/10.5281/zenodo.5220816 (Liu et al., 2021b). [ABSTRACT FROM AUTHOR]

This research investigates the effects of tourism, GDP per capita, renewable energy, energy intensity, urbanization, and population on the environment in 40 Asian countries. Data from 1995 to 2019 are used in this analysis. Slope heterogeneity (SH), cross-sectional dependency (CSD), and the combination of level and first differenced stationary are all addressed using a new cross-sectionally autoregressive distributed lag (CS-ARDL) model in this work. Using Westerlund's cointegration method, these variables can be connected throughout time. To validate the findings, both augmented mean groups (AMG) and Common correlated effect mean groups (CCEMG) were utilized. The study results indicate that tourism helps slow the degradation of the natural environment. CO2 emissions increase as a result of variables such as population growth, energy use, and economic development. Only tourism and renewable energy can help cut CO2 emissions. As a consequence, CS-ARDL results are supported by results from AMG and CCEMG tests. Policymakers may be encouraged countries to adopt renewable energy and foster the expansion of the sustainable tourism industry. [ABSTRACT FROM AUTHOR]

This study explores how carbon emissions are affected by financial inclusion. Using a balanced panel data set of 26 Asian countries, we compute a composite index, through the principal component analysis (PCA) technique, of financial inclusion based on a set of attributes related to financial inclusion. Our main analysis also delineates the subsamples of developed and developing Asian economies. The results reveal a long (short)-run positive (negative) impact of financial inclusion on carbon emissions across the Asian countries. This finding is also true for the developed country subsample, implying nonlinearity in short- and long-run relationships. For the developing countries, a more pronounced long-run positive impact compared to developed countries is found. Furthermore, the pairwise causality test results indicate the existence of bi-directional causality between financial inclusion and carbon emissions. These findings have important policy implications, especially in the context of the strategic integration of financial inclusion and climate change strategies. [ABSTRACT FROM AUTHOR]

The purpose of this study is to test the relationship among green logistics, environmental degradation, and energy demand. The system generalized method of moment (system GMM) is used to study the data of Asian countries and four subregions in Asia. The estimation results show that logistics operation consumes nonrenewable energy such as fossil fuels, which has a negative impact on environmental sustainability and energy demand. The service quality and capability (LPITC) in the logistics performance index has a significant contribution to reducing carbon dioxide emissions. The logistics infrastructure (LPIIN) has significantly reduced the energy consumption in Asia, while the customs (LPIC) has significantly increased the energy demand. Other indicators of LPI also have a significant impact on the environment and energy in different subregions of Asia. Industrialization and urbanization both increase carbon emissions in Asia, while trade opening reduces carbon emissions. At the same time, these three variables have a positive impact on reducing energy consumption. The results show that logistics performance is significantly related to environmental degradation and energy, and renewable energy and green supply chain management can reduce the harmful effects of logistics activities on environment and energy. Therefore, Asian countries should give priority to environmental sustainability in supply chain management and encourage the application of green practices in logistics. [ABSTRACT FROM AUTHOR]

This study examines the impact of human capital and globalization on carbon dioxide (CO2) emissions for a sample of 78 developing countries, from Asia, Africa, and Latin America and the Caribbean, over the period from 1990 to 2016. As opposed to the existing studies in the literature, this study considers three types of globalization namely economic, social, and political globalization. The econometric analysis involves the use of the two-stage least squares-generalized method of moment method to account for endogeneity issues. The findings, overall, indicate that human capital development decreases CO2 emissions in developing countries across all regions. In contrast, social globalization increases CO2 emissions in all developing countries. Moreover, the empirical results also reveal that political globalization boosts CO2 emissions in the Latin American and Caribbean region, but helps to curb CO2 emissions in Asia, Africa, and in overall panel. Additionally, economic globalization significantly reduces CO2 emissions in the Latin American and Caribbean region but increases CO2 emissions in Asia, Africa, and in overall panel countries. Furthermore, human capital and globalization (in all three forms) jointly boost CO2 emissions. Hence, in line with this major finding, we recommend that the globalization policies should also incorporate the human capital development agenda of the developing countries in order to comprehensively tackle the aggravation of CO2 emissions. [ABSTRACT FROM AUTHOR]

Conversion from double rice cropping (RR) to maize-rice cropping (MR) have been occurring in recent years in Asia. However, effects on the environment by introducing maize into paddy still need more examination. The objective of this study was to assess differences in greenhouse gases emissions, carbon footprint and carbon neutrality between MR and RR cropping systems from 2016 to 2018. Results showed that the global warming potential (GWP) under MR cropping was 13.0 t CO2 eq ha−1, which was 20.0% higher than that of RR (10.8 t CO2 eq ha−1) due to its higher N2O emission. Although the GWP of MR increased, it significantly decreased carbon footprint by 17.3% in comparison with RR due to its higher gain yield. Simultaneously, MR had a substantial increase in net ecosystem economic efficiency by 62.5%. Nevertheless, carbon uptake was significantly higher in MR system, its carbon neutrality was lower than that of RR by 69.3% average. In conclusion, MR could be an effective sustainable cropping system with high yield and low carbon footprint in the subtropical regions. Considering the higher GWP of MR, further research is needed on appropriate agronomic practice to reduce carbon loss to realize higher carbon neutral potential. [ABSTRACT FROM AUTHOR]

Logistics performance is considered an important determinant of supply chain performance that results in carbon neutrality. The main aim of this study is to investigate the influence of logistics performance and green innovation on carbon emissions for selected Asian economies over the period 2007–2020. The 2SLS approach has been employed for empirical tasks, and the robustness of results has been confirmed through the GMM approach. The results indicate that logistics performance significantly reduces carbon emissions. Besides the logistics performance index, five other indicators of logistics performance have been used in the analysis. These indicators include quality of logistics services, tracking and tracing capability, logistics infrastructure quality, cargo transportation timelines, and customs clearance efficiency. All these indicators are negatively correlated with carbon emissions. The results further indicate that green innovation leads to a significant reduction in carbon emissions. Thus, our results emphasize the priorities of green innovation, logistics performance, and environmental sustainability in Asian economies. [ABSTRACT FROM AUTHOR]

Applying different regression estimators on balanced panel data, this article examines the impact of human capital and income inequality on climate change in Asian countries during the period 2007–2020. Results by the GMM estimator confirm that increases in income inequality and investments in human capital exacerbate environmental degradation in Asian countries. However, among the three variables that represent human capital, only HC3 (Gross enrollment ratio for tertiary school) plays a role in reducing the impact of income inequality on emissions of carbon dioxide. In addition, the study also provides evidence on the impact of other factors on CO2 emissions such as renewable energy, economic growth, population, output in the agricultural and services sectors, trade openness, government expenditure and total investment in the economy. Besides, some important policy implications have been suggested to aim at securing sustained economic growth in Asia. [ABSTRACT FROM AUTHOR]

All around the world, but particularly in developing nations, carbon dioxide emissions are on the rise, and climate change and global warming are brought on by an increase in CO2 emissions. This article provides an overview of the technological effect on energy consumption in the residential, transport, and industrial sector and its ultimate effect on the environment. Using the STIRPAT-Kaya-EKC model for the years 1990 to 2020, this study looked at the threshold impact of technological advancements on the link between disaggregated energy use and CO2 emissions for a panel of 10 Asian countries using the panel threshold regression. Findings demonstrate that the EKC phenomenon is present in the chosen Asian region. Findings also suggest that technology has a threshold influence on the relationship between energy use and carbon emissions; however, this effect varies across sectors. [ABSTRACT FROM AUTHOR]

Clean fuels and technology-based energy is an essential source to achieve sustainable economic growth and development. Therefore, the relationship between all types of poverty and other socioeconomic indicators has been studied extensively; nevertheless, clean fuels and technology-based energy poverty, adjusted for carbon emissions, has not been studied. The current study examines the impact of clean fuels and technology-based energy poverty on carbon emissions (Co2e). Using System-Generalized Method of Movement (SGMM) estimators, this study utilized panel data from eighteen developing countries in Asia from 2006 to 2017. The empirical findings obtained from econometric model suggest the presence of clean fuels and technology-based energy poverty and its curse on environment, i.e., energy poverty positively affects Co2e growth in Asian developing countries. Furthermore, economic growth (GDP), trade, and population are also positively associated with Co2e growth and negatively affect environmental quality. Based on the empirical findings of the current study, we recommend robust policy implications that the governments of targeted countries should invest more to increase clean fuels and technologies. [ABSTRACT FROM AUTHOR]

The study examined the impact of macroeconomic performance and energy consumption on carbon emissions in Asian developing countries. Although, macroeconomic performance is a critical measure for the determination of development in societies. Thus, the examination of macroeconomic performance variables is a core issue for policymakers. The panel quantile regression model assesses the macroeconomic performance at several quantiles, ranging from 0.05 to 0.95. The effect of macroeconomic performance and energy consumption on CO2 emissions has also been established. The findings indicate that CO2 emissions and macroeconomic performance are negatively associated in all quantiles of macroeconomic performance. Though, fossil fuel energy and population growth positively influence carbon emissions in all low and medium quantiles but this relationship becomes weaker in the upper quantiles. In addition, hydroelectricity consumption and carbon emissions are negatively and significantly associated in the quantile ranges of low and higher. Based on the aforementioned results, the study suggests the formulation of such policies that can improve macroeconomic performance in the region and the promotion of hydel energy instead of fossil fuels to reduce environmental pollution in developing Asian countries. Moreover, the population control program, promotion of renewable energy, and dangers of fossil fuel consumption should be a part of public policies to control environmental issues by reducing carbon emissions at the regional level. [ABSTRACT FROM AUTHOR]

Asia is one of the fastest-growing regions in international tourism, economic growth, and CO2 emissions around the globe. However, the relationships between tourism and CO2 emissions are little and unclearly identified. The purpose of the study is to explore the asymmetric nexus between tourism and CO2 emissions in a panel of five high emitters Asian countries covering the period of 1995–2019 by using panel-NARDL-AMG. The empirical results reveal that a positive shock in tourism arrivals increases CO2 emissions, while a negative shock also increases CO2 emissions in the long run. Moreover, a negative shock has a greater effect on CO2 emissions than a positive shock in Asia in the long run. Tourism receipts are expected to maintain the robustness of CO2 emissions in the long run in Asian economies. The authorities should develop and design green international tourism activities in the Asian economies. [ABSTRACT FROM AUTHOR]

This study uses annual data to detect the nexus between urbanization, energy use, and carbon emissions in a panel of Association of Southeast Asian Nations (ASEAN) countries spanning the period 1980–2009. The study contributes to the increasing empirical literature by investigating the effects of urbanization and detecting causal links between the variables. Results from the Pedroni panel cointegration tests show evidence for the existence of a long-term equilibrium relationship between urbanization, energy use, and carbon emissions for the ASEAN countries. Using the panel fully modified ordinary least squares technique, the effect of urbanization on carbon emissions is further revealed; i.e., a 1% rise in urban population results in a 0.20% increase in carbon emissions. Unilateral short-run causal relationships from urbanization to energy use and from urbanization to carbon emissions have been found by Granger causality tests. Also, the results clearly indicate that in the long term, urbanization together with energy use Granger causes carbon emissions. The paper concludes with main findings and provides recommendations toward rational planning of urban development and energy-efficiency improvement strategies for the ASEAN countries. [ABSTRACT FROM AUTHOR]

Environmental degradation has been a major concern for nations globally in recent years as carbon emissions have increased. Environmental degradation, if not controlled, is one of the dangers faced by humankind, and achieving sustainable development goals is not possible without improving environmental quality. Thus, reliable carbon emission measurement plays an important role in developing an effective climate strategy to address the current environmental issues. Following the trade-adjusted carbon emission measure, an effective climate strategy can be formulated especially following the 17 United Nation Sustainable Development Goals that are intended to lead to improvements toward a sustainable future. To fill the gap in the literature, we empirically explore the interrelationship between foreign capital flows and environmental quality measured by trade-adjusted consumption-based carbon dioxide (CCO2) emissions for a panel of 125 countries in 1990–2018 by revisiting the pollution haven hypothesis (PHH). The results obtained using system GMM analysis show that FDI has a significantly positive link with CCO2 in Asia and Africa, but the links between these two variables are insignificant in the Latin American, Caribbean, and European regions. In the cases of the full-sample and developing countries, a significantly positive relationship is found between FDI and CCO2. In the case of income-based samples, results reveal that FDI is the cause of environmental degradation in low-income, lower-middle-income, and upper-middle-income countries. These findings suggest that developing countries should adopt environmentally friendly policies to attract foreign investors by setting strict regulations on environmental pollution control to achieve sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

This study uses a consumer-based accounting approach to evaluate the CO2 emission factors of 17 countries in Asia and the Pacific region by including all emissions in the supply chain from commodity location to final consumption location in country consumption patterns. In addition, the number of emissions connected with each country's consumption of products and services in Asia and the Pacific region has received little attention. This study contributes to understanding the effects of countries' consumption of products and services on carbon emission peaks and formulates efficient carbon mitigation plans for governments and decision-makers. Accelerating economic growth and industrialization have posed significant challenges to global carbon mitigation efforts and climate change responses. The Monte Carlo simulation technique was used to create a dynamic scenario simulation model to investigate possible future peaks in the carbon emissions of countries in Asia and the Pacific region while taking into account factor uncertainties. The results show that total consumption-based CO2 emissions are remarkable in three Asian countries, including China (387,451.95 metric tons Mt CO2), Japan (185,259.60 Mt CO2), and India (100,720.46 Mt CO2). In South Korea, Brunei, and Taiwan, annual consumption emissions are 1.77, 1.62, and 1.49 tons of CO2 per person, respectively. In terms of final consumption, the household sector is the most noteworthy contributor to consumption-based emissions, accounting for 27–56%. The household sector probably peaks at 19.7 Gt CO2 as per the dynamic scenario simulation. For the three other types of final demand, government expenditure will possibly reach a maximum of 44.0 Gt CO2 in the next 30 years, while capital formation will probably reach its highest emission level at 149.5 Gt CO2. [ABSTRACT FROM AUTHOR]

Huge areas of tropical forests are degraded, reducing their biodiversity, carbon, and timber value. The recovery of these degraded forests can be significantly inhibited by climbing plants such as lianas. Removal of super‐abundant climbers thus represents a restoration action with huge potential for application across the tropics. While experimental studies largely report positive impacts of climber removal on tree growth and biomass accumulation, the efficacy of climber removal varies widely, with high uncertainty as to where and how to apply the technique. Using meta‐analytic techniques, we synthesize results from 26 studies to quantify the efficacy of climber removal for promoting tree growth and biomass accumulation. We find that climber removal increases tree growth by 156% and biomass accumulation by 209% compared to untreated forest, and that efficacy remains for at least 19 years. Extrapolating from these results, climber removal could sequester an additional 32 Gigatons of CO2 over 10 years, at low cost, across regrowth, and production forests. Our analysis also revealed that climber removal studies are concentrated in the Neotropics (N = 22), relative to Africa (N = 2) and Asia (N = 2), preventing our study from assessing the influence of region on removal efficacy. While we found some evidence that enhancement of tree growth and AGB accumulation varies across disturbance context and removal method, but not across climate, the number and geographical distribution of studies limits the strength of these conclusions. Climber removal could contribute significantly to reducing global carbon emissions and enhancing the timber and biomass stocks of degraded forests, ultimately protecting them from conversion. However, we urgently need to assess the efficacy of removal outside the Neotropics, and consider the potential negative consequences of climber removal under drought conditions and for biodiversity. [ABSTRACT FROM AUTHOR]

While climate change is having serious impacts on agriculture and may require ongoing adaptation, short-run threats to global food security are also crucial for developing countries. We use dynamic and asymmetric panel autoregressive distributed lag estimators to investigate how the effects of climate change on agricultural productivity vary depending upon the short run and long run in Asia over the period of 1980–2016. The results confirmed that there is a long-run relationship between agricultural productivity and climate change variables; however, only CO2 emissions could be linked to agricultural productivity in the short run. Moreover, while the direction of this effect is positive for the short run, it turns into negative in the long run confirming that carbon fertilization in the atmosphere can to some extent have a positive effect on agricultural productivity. [ABSTRACT FROM AUTHOR]

Strategies to balance output growth and global warming are an important matter of discussion in the current environmental management literature. A decrease in energy prices encourages energy consumption. As energy subsidies and oil prices are a major influence on the overall energy price, they also influence the level of CO2 emissions associated with output growth. In this article, we investigate the asymmetric impact of energy subsidies, oil prices, and economic output on CO2 emissions. We used a panel dataset of 20 selected oil producing countries in Asia from 2010 to 2018. We employed threshold analysis to acquire further knowledge concerning the asymmetric impact of energy subsidies, oil prices, and output on CO2 emissions. Our findings suggest that while an energy subsidy was significant in terms of resultant CO2 emissions, energy subsidies had a greater impact on CO2 emissions when the oil price is low. However, energy subsidies are not expected to cause significantly higher CO2 emissions when the value of the subsidy is at a low level. Third, these relationships follow the pattern consistent with the environmental Kuznets curve hypothesis only when the energy subsidy is relatively high. We consider an energy subsidy rationalisation program could serve to meet environmental management goals in energy use. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas, and its concentration is continuously increasing, mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and for designing mitigation strategies aimed at stabilizing CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of the column-averaged dry-air mole fraction of CO2 , i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2), and the net primary productivity (NPP) provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the anthropogenic CO2 emissions using the Generalized Regression Neural Network (GRNN) over East and West Asia. OCO-2 XCO2 , MODIS NPP, and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variability. The XCO2 anomaly, NPP, and ODIAC emission datasets from 2015 to 2018 were then used to train the GRNN model, and, finally, the anthropogenic CO2 emissions were estimated for 2019 based on the NPP and XCO2 anomalies derived for the same year. The estimated and the ODIAC CO2 emissions were compared, and the results showed good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional-scale anthropogenic CO2 emissions, and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets. [ABSTRACT FROM AUTHOR]

Earth is in the Anthropocene era and humankind deteriorates the global environment; thus, there is a dire need for sustainable policies at all levels. This study investigates the causal and long-run association between financial development, research and development expenditures, and carbon dioxide emission including energy intensity and income level for selected West Asia and Middle East (WAME) economies along the belt and road. The long-run panel estimation findings reveal that the research and development expenditures (R&D) are negatively associated with environmental degradation, as they significantly mitigate carbon emissions. In contrast, financial development contributes to environmental degradation. The findings validated the environmental Kuznets curve (EKC) phenomenon for the WAME economies considering R&D and financial development. Further, energy intensity exacerbates environmental quality. Additionally, the findings from Dumitrescu-Hurlin (DH) causal approach reveal bidirectional causal associations between financial development and carbon emissions and between R&D and emissions. The findings have implications for policy and practice to attain environmental sustainability in the selected WAME countries. [ABSTRACT FROM AUTHOR]

This study examines the effects of energy use, financial development, and globalization on carbon dioxide emissions for Asian countries comprising the panel data over the period 1990–2017. To account for cross-sectional dependence, Pesaran cross-sectional dependence test is used. The second-generation tests are used to determine the stationarity level of the variables. Furthermore, the Westerlund panel cointegration test confirms cointegration among the variables. For long-run association, fully modified ordinary least squares approach is used. The study also used Dumitrescu and Hurlin's (Econ Model 29:1450-1460, 2012) panel causality test to explore the causal relationship among the variables. The results suggest that financial development contributes to carbon emissions, whereas globalization helps to mitigate emissions. As financial development deteriorates environmental quality, therefore, the government should monitor the disbursement of loans for research and development, green financing, and efficient products that reduce resource consumption and improves environmental quality. Financial development should not compromise environmental quality and endanger sustainability. Such findings show that both renewable energy industries and financial development in the Asian economies are not meeting the maturity level in terms of leading to changes in environmental quality. Furthermore, Asian countries should promote globalization to support the inflow of green technologies to enhance environmental quality. [ABSTRACT FROM AUTHOR]

The logistics played an important role in the economic excellence of any country and region. However, being a major consumer of energy it also has adverse effects. Therefore there is a need to understand the role of logistics from economic and environmental aspects. By grounding on the theoretical foundations of IPAT and STIRPAT, the dataset of the present study is comprised of top Asian countries having 540 observations from the year 2010 to 2018 (quarterly). After applying multiple preliminary tests, including cross‐section dependence, unit root tests, and cointegration, the long run and short‐run relationship among the studied variables are explored by employing the Cross‐sectionally augmented autoregressive distributed lags (CS‐ARDL). The study confirms the significance of logistic performance index (LPI) in complementing economic growth (EG) and countering carbon emission (CE) along with the other theoretical determinants of IPAT and STIRPAT. Based on the findings, the results are discussed whereas policy implications are also proposed which states the transformation of existing logistical infrastructure towards more environment friendly operations. Lastly the limitations are discussed, on which future research directions are also recommended. [ABSTRACT FROM AUTHOR]

Mangroves have among the highest carbon densities of any tropical forest. These 'blue carbon' ecosystems can store large amounts of carbon for long periods, and their protection reduces greenhouse gas emissions and supports climate change mitigation. Incorporating mangroves into Nationally Determined Contributions to the Paris Agreement and their valuation on carbon markets requires predicting how the management of different land‐uses can prevent future greenhouse gas emissions and increase CO2 sequestration. We integrated comprehensive global datasets for carbon stocks, mangrove distribution, deforestation rates, and land‐use change drivers into a predictive model of mangrove carbon emissions. We project emissions and foregone soil carbon sequestration potential under 'business as usual' rates of mangrove loss. Emissions from mangrove loss could reach 2391 Tg CO2 eq by the end of the century, or 3392 Tg CO2 eq when considering foregone soil carbon sequestration. The highest emissions were predicted in southeast and south Asia (West Coral Triangle, Sunda Shelf, and the Bay of Bengal) due to conversion to aquaculture or agriculture, followed by the Caribbean (Tropical Northwest Atlantic) due to clearing and erosion, and the Andaman coast (West Myanmar) and north Brazil due to erosion. Together, these six regions accounted for 90% of the total potential CO2 eq future emissions. Mangrove loss has been slowing, and global emissions could be more than halved if reduced loss rates remain in the future. Notably, the location of global emission hotspots was consistent with every dataset used to calculate deforestation rates or with alternative assumptions about carbon storage and emissions. Our results indicate the regions in need of policy actions to address emissions arising from mangrove loss and the drivers that could be managed to prevent them. [ABSTRACT FROM AUTHOR]

The purpose of this study is to determine the navigation efficiency for transiting from various ports in Asia and Rotterdam in Europe via the Northern Sea Route. Navigation efficiency was derived from fuel consumption ratios. Preliminary research results showed that fuel consumption and the amount of carbon dioxide emissions was reduced by transiting from various ports through the European Sea Route, and the navigation efficiencies of the various ports ranked in the following descending order: Yokohama - Busan - Shanghai - Kaohsiung - Hong Kong - Singapore. The higher the ratio was, the lower the navigation efficiency of using the Northern Sea Route, i.e. more fuel was consumed and travel costs were higher. In contrast, the lower the ratio was, the higher the navigation efficiency, i.e. less fuel was consumed and travel costs were lower. Recommendations were discussed in the study. [ABSTRACT FROM AUTHOR]

The Asia–Europe liner service often calls at a number of Europe-continent ports and one UK port. An alternative is to skip the UK port by using feeder services to reach the UK market. This article aims to quantitatively analyze the carbon dioxide (CO2) emissions of these two alternatives, and to identify which is preferable in different scenarios. We adopt a detailed service activity-based method to calculate the CO2 emissions for two alternatives in a range of scenarios. The study is expected to provide shipping companies with useful insight into policy merits and service route design from a CO2 emissions perspective. [ABSTRACT FROM PUBLISHER]

The way urbanization unfolds over the next few decades in the developing countries of Asia will have profound implications for sustainability. One of the more important opportunities is to guide urbanization along pathways that begin to uncouple these gains in well-being from rising levels of energy use. Increasing energy use for transport, construction, climate control in houses and offices, and industrial processes is often accompanied by increasing levels of atmospheric emissions that impact human health, ecosystem functions, and the climate system. Agriculture, forestry, and animal husbandry alter carbon stocks and fluxes as carbon dioxide, methane, and black carbon. In this article we explore how carbon management could be integrated into the development strategies of cities and urbanizing regions. In particular, we explore how changes in urban form, functions, and roles might alter the timing, aggregation, spatial distribution, and composition of carbon emissions. Our emphasis is on identifying system linkages and points of leverage. The study draws primarily on emission inventories and regional development histories carried out in the regions around the cities of Manila, Jakarta, Ho Chi Minh City, New Delhi, and Chiang Mai. We find that how urban functions, such as mobility, shelter, and food, are provided has major implications for carbon emissions, and that each function is influenced by urban form and role in distinct ways. Our case studies highlight the need for major "U-turns" in urban policy. [ABSTRACT FROM AUTHOR]