This study examines the association between transportation services (i.e., passenger and freight) and carbon emissions concerning the US economy. The monthly data for this study were collected for the period from 2000 M1 to 2019 M8. In this study, QARDL econometric approach as discussed by Cho et al. (2015) has been used to tests the relationship between transportation services and CO2 emissions. Due to the chaotic and nonlinear behavior of our concerning variables, it was quite difficult to gauge the principle properties of their variations. Therefore, we relied on QARDL, which has been missing in previous researches. By utilizing the QARDL method, this research assesses the long-term stability of the nexus across the quantiles to provide an econometric framework that is more flexible than the traditional ones. In particular, the authors have analyzed how the quantiles of transportation (i.e., passenger and freight) influence the quantiles of CO2 emissions (environmental degradation). The empirical evidence revealed the negative significant relationship of both the transportation system (i.e., passenger and freight) with carbon emissions; however, this relationship holds at low quantiles of freight transport, whereas the same relationship has been observed at the majority of quantiles of passenger transport. So, this depicts that the transportation system of the USA helps to reduce CO2 emissions. Therefore, to maintain this situation, the government shall introduce more technologies that are fuel-efficient and promote clean consumption, thus reducing CO2 emissions, boosting economic growth, and making green transportation services.
Climate change-related environmental challenges are prompting an increasing number of countries to set carbon-neutral targets. Since 2007, China has pursued numerous initiatives to attain carbon neutrality by 2060, including increasing the percentage of non-fossil energy, developing zero-emission and low-emission technologies, and taking actions that reduce CO2 emissions or boost carbon sinks. As a result, utilizing quarterly data from 2008/Q1 to 2021/Q4, and applying the nonlinear autoregressive distributed lag (NARDL) approach, this study evaluates the effectiveness of the measures taken by China to improve the ecological situation. The results of the study show that the measures enacted to reduce CO2 emissions did not accomplish their ultimate purpose. Specifically: (i) high-speed railways and new energy vehicles do not improve the environment in the long run; (ii) investments and patents in the energy sector, as well as low-carbon sources, will degrade the environment; (iii) only investments in the treatment of environmental pollution will improve the ecological situation. Various policy implications are suggested based on the empirical results in order to attain environmental sustainability.
This study analyzes the relationship between globalization, energy consumption, and economic growth among selected South Asian countries to promote the green economy and environment. This study also finds causal association between energy growth and nexus of CO2 emissions and employed the premises of the EKC framework. The study used annual time series analysis, starting from 1985 to 2019. The data set has been collected from the World Development Indicator (WDI). The result of a fully modified ordinary least square (FMOLS) method describes a significantly worse quality environment in the South Asian region. The individual country as Bangladesh shows a positively significant impact on the CO2 emissions and destroys the level of environment regarding non-renewable energy and globalization index. However, negative and positive growth levels (GDP) and square of GDP confirm the EKC hypothesis in this region. This study has identified the causality between GDP growth and carbon emission and found bidirectional causality between economic growth and energy use.
Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.
The amount of carbon stored in deadwood is equivalent to about 8 per cent of the global forest carbon stocks1. The decomposition of deadwood is largely governed by climate2-5 with decomposer groups-such as microorganisms and insects-contributing to variations in the decomposition rates2,6,7. At the global scale, the contribution of insects to the decomposition of deadwood and carbon release remains poorly understood7. Here we present a field experiment of wood decomposition across 55 forest sites and 6 continents. We find that the deadwood decomposition rates increase with temperature, and the strongest temperature effect is found at high precipitation levels. Precipitation affects the decomposition rates negatively at low temperatures and positively at high temperatures. As a net effect-including the direct consumption by insects and indirect effects through interactions with microorganisms-insects accelerate the decomposition in tropical forests (3.9% median mass loss per year). In temperate and boreal forests, we find weak positive and negative effects with a median mass loss of 0.9 per cent and -0.1 per cent per year, respectively. Furthermore, we apply the experimentally derived decomposition function to a global map of deadwood carbon synthesized from empirical and remote-sensing data, obtaining an estimate of 10.9 ± 3.2 petagram of carbon per year released from deadwood globally, with 93 per cent originating from tropical forests. Globally, the net effect of insects may account for 29 per cent of the carbon flux from deadwood, which suggests a functional importance of insects in the decomposition of deadwood and the carbon cycle.
A country's financing system is essential in addressing sustainable development requirements. National sources and international financial flows contribute to economic growth and environmental quality in many ways, and their impact can be critical. This paper applied panel data analysis using a comparative approach of Pooled Mean Group Auto Regressive Distribute Lags (PMG-ARDL) and Cross Sectionally ARDL (CS-ARDL) to estimate the effects of FDI, renewable energy, and remittance on environmental quality in the top remittance-receiving countries, during 2000-2021. The study emphasized the positive relationship between FDI and carbon emissions. Moreover, renewable energy and remittances revealed an inverted U-shaped relationship with carbon emissions. In the case of developing countries from the panel, remittance improves environmental quality after reaching the threshold. Moreover, for some of the developing countries included in the panel, we found that they do not achieve the desired carbon mitigation effect in their early stages of renewable energy implementation. However, renewable energy becomes a key factor for tackling environmental pollution after a certain threshold. The mixed results determined diverse policy recommendations for various stakeholders.
Globalization persists the tendency to alter numerous aspects of today's world including religion, transport, language, living styles, and international relations; however, its potential to influence quality of environment is the prime concern for trade and environmental policies guidelines (Audi and Ali 2018). In response to the growing interest for identifying the dynamic relationship between globalization and environmental performance, the present study seeks to investigate the critical link between globalization and ecological footprints in top 15 globalized countries between 1970 and 2016. Applying the novel methods of quantile-on-quantile regression (QQ) and Granger causality in quantiles, the findings examine the manners in which quantiles of globalization affect the quantiles of ecological footprints and vice versa. The empirical results suggest that globalization has a long-term positive effect on ecological footprint and vice versa in case of Belgium, the Netherlands, Sweden, Switzerland, Denmark, Norway, Canada, and Portugal. On the other hand, the estimated results indicate a negative effect between globalization and ecological footprint in the case of France, Germany, the UK, and Hungary. These results extend the recent findings on the globalization-environment nexus implying that the magnitude of relationship among both variables varies with countries demanding individual focus and cautions for postulating environmental and trade policies.
Being a prominent tourist destination, the hotel industry's demand in Malaysia has been increasing day by day. There is still a shortage of studies focusing on how hotels can make environmental management routine work, take environmental laws seriously and be more responsive to the environment. This study focused on the connections between green employee involvement, green performance management and green dynamic capability in implementing environmental law in the hospitality industry. The study also evaluates the mediating role of implementing environmental law between green employee involvement, green performance management, green dynamic capability and organisational citizenship behaviour to reduce pollution. This study employed a quantitative approach to test the hypotheses and a convenient sampling method to collect the data from hotel employees. Out of 600 distributed questionnaires, useable responses were 253 to proceed with data analysis. Data were analysed through structural equation modelling (SEM) using the Smart-PLS and SPSS. The relationship between green employee involvement, green performance management, green dynamic capability and implementation of environmental laws was discovered and considered unique in the hotel industry in Malaysia. The study further established the mediating role of environmental law between independent and dependent variables.
The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.
This paper assesses the Environmental Kuznets curve based on quantile behavior of the relationship between economic growth, forest area, agriculture production, renewable energy, and environmental degradation. The current literature generally used a single indicator to address environmental issues; however single indicator neither measures overall environmental conditions nor does specify that the environment issue is generally diminishing. Our study is the first one that used ecological footprint (EF) as an indicator to test environmental Kuznets curve (EKC) hypothesis for Pakistan by employing recent approach of quantile autoregressive distributed lag (QARDL) initiated by Cho et al. (J Econ 188(1):281-300, 2015). The result of this study validates the EKC hypothesis for Pakistan and shows quantile-dependent relationship, and in that case, using the conventional methods may somewhat lead to biased results. Moreover, the rejection of the null hypothesis of parameter constancy is also confirmed by Wald test. In the long run, the findings of renewable energy consumption and forest area show significant negative effects on ecological footprints, which indicates that by increasing renewable energy usage and forest area, ecological footprints can be minimized. Interestingly, the short-term effects of agricultural production findings on EF show statistically negative results. This illustrates that EF can also be reduced in the agriculture sector by adopting environment-friendly technologies. In order to create efficient policies for environment deterioration, the empirical findings of the current analysis can be used as a guideline for policy implications.
A key objective of renewable energy development in the USA is to reduce CO2 emissions by decreasing reliance on fossil fuels in the coming decades. Using quantile-on-quantile regressions, this research examines the relationship between disaggregated sources of renewable energy (biomass, biofuel, geothermal, hydroelectric, solar, wind, wood, and waste) and CO2 emissions in the USA during the period from 1995 to 2017. Our findings support the deployment of various types of renewables in combating CO2 emissions for each quantile. In particular, a negative effect of renewable energy consumption on CO2 emissions is observed for the lower quantiles in almost all types of renewables. The effect of all the renewable energy sources taken together is significant for the lower and upper quantiles of the provisional distribution of CO2 emissions. The effect of renewable energy becomes stronger and more significant in the middle quantiles, where a pronounced causal effect of return and volatility is detected for the lower and upper middle quantiles. At the same time, heterogeneity in the findings across various types of renewable energy sources reveals differences in the relative importance of each type within the energy sector taken as a whole. Future US initiatives in renewable energy deployment at both the federal and the state levels should take into consideration the relative importance of each type, so as to maximize the efficacy of renewable energy policies in combating CO2 emissions.
Caseous lymphadenitis (CLA) caused by Corynebacterium pseudotuberculosis is characterized by the development of abscesses, mainly in superficial and internal lymph nodes, visceral and reproductive organs in small ruminants. This study aims to examine the histopathological changes in reproductive organs of goats immunized with killed vaccine of C. pseudotuberculosis. In this study, twenty four (24) clinically healthy bucks and does were divided into four groups A, B, C and D. Animals in groups A and B were immunized with 0.5 and 1% formalin killed vaccine, respectively; followed by a booster dose. After the booster dose of immunization, groups A, B and C were challenged with C. pseudotuberculosis at 106 cfu/ml. Goats in group D were immunize and unchallenged and left as control group. All C. pseudotuberculosis infected animals were euthanized humanely 12 weeks post-challenged. Tissue samples such as testes, epididymis, spermatic cord, penis, pituitary gland, mammary gland, vulva, vagina, cervix, uterus, fallopian tube and ovaries were collected for histopathology study. Microscopic examination of all tissues (testes, seminiferous tubules, spermatic cord, penile tissues and the pituitary gland) in the male reproductive organs of the bucks that were inoculated with 2 ml of 0.5% and 1.0% of C. pseudotuberculosis killed vaccine showed normal (animals inoculated with 1.0%) to mild (animals inoculated with 0.5%) histopathological changes when compared with those from group C which showed varying degrees of histopathological changes (p
The aim of this paper is to examine immigration and environmental degradation using bibliometric analysis. This paper also analyzes sources of publication, authorship, citations, distributions publications and other bibliometric indicators. The study focuses on a total of 1372 articles published from 2000 to 2020. These articles were collected through an automated process from the Scopus database and later analyzed using techniques such as bibliometric indicators analysis, VOSviewer, and Perish or Publish. The research identified 991 articles from varieties of published sources. The topic of immigrants and environmental degradation has been an emerging topic since 1981. Starting in 2000, most of the scholars actively producing an articles pertinent to this topic. Most of the articles were published in journals, and English is the primary language of research. United States is the leading country in contributing the publications. Meanwhile, the most significant fields in which the sources were produced were environmental science, agricultural and biological sciences, arts and humanities and earth and planetary sciences. However, some limitations has been found. It has been suggested for future research, to lengthen this work to other databases, as well as bibliometric analyses of immigration and environmental degradation in developed and developing countries by adding a new keyword such as energy consumption and climate change. This paper aims to assess recent trends in the expansion of academic literature on immigration and environmental degradation using the bibliometric analysis method. Network visualization and bibliometric indicators are used in this paper to present the results.
The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.
The present paper implements the quantile autoregressive lagged (QARDL) approach of Cho et al. (2015) and the Granger causality in quantiles tests of Troster et al. (2018) to explore the nonlinear effects of US energy consumption, economic growth, and tourist arrivals on carbon dioxide (CO2) emission. Our results unveil the existence of substantial reversion to the long-run equilibrium connectedness between the variables of interest and CO2 emissions. The outcomes show that tourist arrivals decrease CO2 emissions in the long term for each quantile. In addition, we found that the output growth positively influences the carbon emissions at lower quantiles but negatively influences the carbon emissions at upper quantiles. Moreover, our findings of short-term dynamics validate an asymmetric short-run effect of tourist arrivals and economic growth on CO2 emissions in the US economy. Further results and their corresponding policy implications are discussed.
Energy is one of the prime factors in influencing the sustainable development of a country. Different energy sources play important roles in driving the income growth of different economic sectors such as industrial, agricultural, and services. Fossil fuels, however, have come under strong criticism for actively accelerating climate change. As such, it is imperative to investigate the contributions of various energy sources toward sustainable growth. With Malaysia as the test-bed, the present study analyzes the impact of energy prices on economic stability using the novel wavelet-based analysis. Specifically, the study analyzed the impact of crude oil, natural gas, and gasoline prices on the economic (brown) and green growth from 1995 to 2020. The results show that in continuous wavelet transform, the cone of influence of all five factors exhibits strong short-run variance and fluctuations from 2005 to 2013. However, the intensity of brown growth is more influential than green growth. Similarly, in wavelet coherence graphs, the downward right arrows indicate positively significant associations between crude oil prices, natural gas prices, and gasoline prices with brown and green growth. Additionally, wavelet-based Granger causality reveals a bidirectional causal relationship between all variables. The results thus strongly suggest that energy prices predominantly affect the economic (brown) and green growth progression of the Malaysian economy. The study concludes with some suggested implications to augment the country's sustainable growth.
Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.