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This study explores the effect of green bonds, oil prices, and the coronavirus disease 2019 (COVID-19) pandemic on industrial carbon dioxide (CO2) emissions. In this context, this study examines the United States of America (USA), which is the biggest economy in the world, uses weekly data between March 6, 2020 and September 30, 2022, and applies a novel wavelet local multiple correlation (WLMC) approach under time-varying and frequency-varying perspective. The novel empirical findings shows that (i) there is a strong negative (positive) co-movement between industrial CO2 emissions and green bonds in the short-run (long-run);(ii) there is a strong positive (negative) co-movement between industrial CO2 emissions and oil price in the medium-run (long-run);(iii) there is a strong negative (positive) co-movement between industrial CO2 emissions and the COVID-19 pandemic in the medium-run (long-run);(iv) the oil price is the dominant factor, whereas there are changing effect of the variables on each other at different times and frequencies;and (vi) overall, there are long-run asymmetric and dynamic correlations between industrial CO2 emissions and variables. Hence, the empirical results highlight the asymmetric, time-varying, and frequency-varying effects of green bonds, oil prices, and the COVID-19 pandemic on industrial CO2 emissions by presenting fresh and novel evidence. Moreover, the study proposes policy implications for the USA government. © The Author(s) 2023.
ABSTRACT
Carbon dioxide (CO2) rate within the atmosphere has been rising for decades due to human activities especially due to usage of fuel types such as coal, cement, flaring, gas, oil, etc. Especially in 2020, COVID-19 pandemic caused major economic, production, and energy crises all around the world. As a result of this situation, there was a sharp decrease in the global CO2 emissions depending on the fuel types used during this pandemic. The aim of this study was to explore the effects of "CO2 emissions due to the fuel types"on "percentage of deaths in total cases"attributed to the COVID-19 pandemic using generalized linear model and generalized linear mixed model (GLMM) approaches with inverse Gaussian and gamma distributions, and also to obtain global statistical inferences about 169 World Health Organization member countries that will disclose the impact of the CO2 emissions due to the fuel types during this pandemic. The response variable is taken as "percentage of deaths in total cases attributed to the COVID-19 pandemic"calculated as "(total deaths/total confirmed cases attributed to the COVID-19 pandemic until December 31, 2020)∗100."The explanatory variables are taken as "production-based emissions of CO2 from different fuel types,"measured in tonnes per person, which are "coal, cement, flaring, gas, and oil."As a result of this study, according to the goodness-of-fit test statistics, "GLMM approach with gamma distribution"called "gamma mixed regression model"is determined as the most appropriate statistical model for investigating the impact of CO2 emissions on the COVID-19 pandemic. As the main findings of this study, 1 t CO2 emissions belonging to the fuel types "cement, coal, flaring, gas, and oil"per person cause increase in deaths in total cases attributed to the COVID-19 pandemic by 2.8919, 2.6151, 2.5116, 2.5774, and 2.5640%, respectively. © 2023 the author(s), published by De Gruyter.
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This study measures the total factor carbnon dioxide (CO2) emissions performance of the metal industry, iron and steel, nonferrous metal, and metal processing industries in 39 Japanese prefectures from 2008 to 2019. The true fixed-effects panel stochastic frontier model identifies regional carbon efficiency as well as the inefficiency determinants. The main results are as follows. First, a decrease in the coal ratio and an increase in the electricity ratio in total energy consumption improves efficiency. This result suggests that electrification in the metal industry, especially conversion from blast furnaces to electric furnaces in the iron and steel industry, contributes to reducing carbon emissions. Second, industrial agglomeration improves carbon emissions performance in the metal industry. This implies that agglomeration and decarbonization policies focusing on there are more effective, rather than a uniform national policy. Third, compared to the cumulative CO2 emissions over the sample period, 49,017 × 103 tons, the cumulative CO2 mitigation potential is 29,703 × 103 tons, indicating that CO2 emissions can be reduced by 60.6% without affecting the output. Forth, to examine the green economic recovery with efficiency in Japan's metal industry after COVID-19, we present a simple scenario analysis where a k% replacement coal ratio with an electricity ratio in total energy consumption, assuming that each prefecture will achieve the maximum CO2 emission amount during the sample period. By replacing 10% of the coal ratio with the electricity ratio, CO2 emissions can be reduced by 23.0%. In the case of a 20% replacement, CO2 emissions can be reduced by 33.0%. Our results show that Japan's targets in the post-COVID-19 green recovery process should be a decrease in coal consumption, an increase in electricity, and industrial agglomeration. © 2023 Elsevier Ltd
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This study aims to determine whether ESG funds can be used as an effective tool for environmental sustainability. ESG funds, which first appeared in the 2000s and were exported by environmentally friendly companies, are among the most effective tools for increasing firm value and managing environmental degradation. The causality relationship between the ESG funds, one of the environmentally friendly investment instruments, and the CO2 emission values, which are used as an environmental degradation criterion, was investigated in this study. The study used 209 daily data sets from July 31, 2020, to May 28, 2021. The symmetric developed by Hacker and Hatemi-J (Appl Econ 38:1489-1500, 2006), the asymmetric developed by Hatemi-J (Empir Econ 43:447-456, 2012), and time-varying asymmetric causality tests were used as models. According to the study results, while there is no symmetric causality between CO2 emissions and ESG funds, there is causality between CO2 emissions and ESG funds prices for negative shocks and between CO2 emissions and ESG funds trade volume for positive shocks. The results of a time-varying asymmetric causality test also support that this causality relationship varies by period. As a result, ESG funds can be used as a strategic financial tool to improve environmental quality during the COVID-19 period; however, this may vary for different sub-sample periods.
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The primary goals of this study are to determine if the datasets of positive COVID-19 test cases and CO2 emissions from Connecticut over the span of March 24th, 2020-October 31, 2021 are in any ways correlated. With climate change a prominent issue facing the entire world today, it is important to explore methods of providing records of past patterns of greenhouse gas emissions in order to inform decision making that could reduce future ones. Autoregressive integrated moving average (ARIMA) modeling is also implemented in this paper to provide forecasting based on CO2 emissions in CT starting from 2019. The most significant results from this paper are as follows: the CO2 emission data of transportation sectors including ground transportation, domestics aviation, and international aviation and weekly COVID-19 positive test cases data has a strong relationship during the first 28 weeks of the pandemic with a correlation of -86.34%. The CO2 emissions experienced on average a -22.96% change of pre-pandemic vs during initial quarantine conditions and at most a - 44.48% change when comparing the pre-pandemic mean to the during initial quarantine minimum value. Lastly, the ARIMA model found to have the lowest Akaike information criterion (AIC) was ARIMA (4,0,4). In conclusion, in the event of a collective global pandemic and lockdown conditions, less traveling resulting in a correlated decrease of CO2 emissions. This means that perhaps concentrated efforts on reducing unnecessary travel could help mitigate the levels of carbon dioxide emissions as a more long-term solution to climate change opposed to the pandemic's short-term example. © 2022 IEEE.
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The death of industrial civilization explains how the contemporary ecological crisis within industrial society is caused by the values inherent in unlimited economic growth and competitive materialism. It demonstrates the central role and importance of electricity, and what policy makers need to do in order to ensure that current and future systems remain reliable even as they are transformed by the rise of clean energy technologies. The novel COVID-19 pandemic has created an unprecedented global health and economic crisis. The result of such a scenario is that energy demand contracts by 6%, the largest in 70 years in percentage terms and the largest ever in absolute terms. The impact of COVID-19 on energy demand in 2020 would be more than seven times larger than the impact of the 2008 financial crisis on global energy demand, and this is what the Olduvai theory defined by e=energy production/population. It states that the life expectancy of industrial civilization is less than or equal to 100 years. © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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Purpose: The purpose of this paper is to investigate sustainable green economy in sub-Saharan African (SSA) countries over the period 1990–2019 using a quantile regression approach, considering the nexus between urbanization, economic growth, renewable energy, trade and carbon dioxide (CO2) emissions. Design/methodology/approach: The study used a dynamic panel quantile regression to investigate the conditional distribution of CO2 emissions along the turn-points of urbanization, economic growth, renewable energy, trade and the regressors via quadratic modeling specifications. Findings: The main findings are established as follows. There is strong evidence of the Kuznets curve in the nexus between urbanization, economic growth, renewable energy, trade and CO2 emissions, respectively. Second, urbanization thresholds that should not be exceeded for sustainability to reduce CO2 emissions are 0.21%, and 2.70% for the 20th and 75th quantiles of the CO2 emissions distribution. Third, growth thresholds of 3.64%, 3.84%, 4.01%, 4.36% and 5.87% across the quantiles of the CO2 emissions distribution. Fourth, energy thresholds of 3.64%, 3.61%, 3.70%, 4.02% and 4.34% across the quantiles of the CO2 emissions distribution. Fifth, trade thresholds of 3.37% and 4.47% for the 20th and median quantiles of the CO2 emissions distribution, respectively. Practical implications: The empirical shreds of evidence offer policy implications in such that building sustainable development and environment requires maintaining the critical mass, not beyond those insightful thresholds to achieving sustainable development and environmentally friendly SSA countries. Social implications: Sustainable cities and communities in an era of economic recovery path COVID-19 mitigate greenhouse gas. The policy relevance is of particular concern to the sustainable development goals. Originality/value: The study is novel considering the extant literature by providing policymakers with avoidable thresholds for policy formulations and implementations in the nexus between urbanization, economic growth, renewable energy and trade openness. © 2023, Emerald Publishing Limited.
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This review paper discusses the Stockholm Paradigm (SP) as a theoretical framework and practical computational instrument for studying and assessing the risk of emerging infectious diseases (EIDs) as a result of climate change. The SP resolves the long-standing parasite paradox and explains how carbon emissions in the atmosphere increase parasites' generalization and intensify host switches from animals to humans. The SP argues that the growing rate of novel EID occurrence caused by mutated zoonotic pathogens is related to the following factors brought together as a unified issue of humanity: (a) carbon emissions and consequent climate change; (b) resettlement/migration of people with hyper-urbanization; (c) overpopulation; and (d) human-induced distortion of the biosphere. The SP demonstrates that, in an evolutionary way, humans now play a role migratory birds once played in spreading parasite pathogens between the three Earth megabiotopes (northern coniferous forest belt; tropical/equatorial rainforest areas; and hot/cold deserts), i.e., the role of "super-spreaders" of parasitic viruses, bacteria, fungi and protozoa. This makes humans extremely vulnerable to the EID threat. The SP sees the +1.0-+1.2 °C limit as the optimal target for the slow, yet feasible curbing of the EID hazard to public health (150-200 years). Reaching merely the +2.0 °C level will obviously be an EID catastrophe, as it may cause two or three pandemics each year. We think it useful and advisable to include the SP-based research in the scientific repository of the Intergovernmental Panel on Climate Change, since EID appearance and spread are indirect but extremely dangerous consequences of climate change.
Subject(s)
Carbon Dioxide , Carbon , Animals , Humans , Greenhouse Effect , Climate ChangeABSTRACT
A warming climate is one of the most important driving forces of intensified wildfires globally. The unprecedented wildfires broke out in the Australian 'Black Summer' (November 2019-February 2020), which released massive heat, gases, and particles into the atmosphere. The total carbon dioxide (CO2) emissions from wildfires were estimated at â¼963 million tons by using a top-down approach based on direct satellite measurements of CO2 and fire radiative power. The fire emissions have led to an approximately 50-80 folds increase in total CO2 emission in Australia compared with the similar seasons of 2014-2019. The excess CO2 from wildfires has offset almost half of the global anthropogenic CO2 emission reductions due to the Corona Virus Disease 2019 in 2020. When the wildfires were intense in December 2019, they caused a 1.48 watts per square meter additional positive radiative forcing above the monthly average in Australia and the vicinity. Our findings demonstrate that vast ecosystem disturbance in a warming climate can strongly influence the global carbon cycle and hamper our climate goal of reducing CO2.
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The anthropogenic CO2 emission is contributed to the rapid increase in CO2 concentration. In the current study the anthropogenic CO2 emission in the Middle East (ME) is investigated using 6 years column-averaged CO2 dry air mole fraction (XCO2) observation from Orbiting Carbon Observatory-2 (OCO-2) satellite. In this way, the XCO2 anomaly ((Formula presented.) XCO2) as the detrended and deseasonalized term of OCO-2XCO2 product, was computed and compared to provide the direct space-based anthropogenic CO2 emission monitoring. As a result, the high positive and negative (Formula presented.) XCO2 values have corresponded to the major sources such as oil and gas industries, and growing seasons over ME, respectively. Consequently, the Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emission and the gross primary productivity (GPP) were utilized in exploring the (Formula presented.) XCO2 relation with human and natural driving factors. The results showed the capability of (Formula presented.) XCO2 maps in detecting CO2 emission fluctuations in defined periods were detectible in daily to annual periods. The simplicity and accuracy of the method in detecting the man-made and natural driving factors including the main industrial areas, megacities, or local changes due to COVID-19 pandemic or geopolitical situations as well as the vegetation absorption and biomass burning is the key point that provides the environmental managers and policymakers with valuable and accessible information to control and ultimately reduce the CO2 emission over critical regions. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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Population confinement caused by the COVID-19 pandemic has led to an increase in household energy consumption. Electricity consumption in the residential sector in Latin America and the Caribbean increased by 20% during 2020 compared to 2019. Due to the sanitary emergency declaration in Ecuador, an upsurge in electricity consumption was observed at the residential level between March and August of 2020. In this context, residential customers of Cuenca have increased their consumption by around 13% during May 2020 compared to the same month of the previous year. Adopting energy efficiency and sufficiency measures could counteract this increase in energy and contribute to managing the demand in the residential sector. The present work aims to evaluate energy savings and emission reduction in the residential sector in Cuenca through the design and implementation of a web-based platform for estimating electricity power savings. To develop the platform, information was gathered through surveys on the average household’s energy consumption. Power consumption of appliances was obtained from various sources, mainly from a database provided by a local appliance retailer. Energy-saving strategies for electrical and electronic devices were taken from technical guidelines and academic sources. The functional and visual specifications of the platform were designed with specialized tools. The platform allows for calculating household electrical energy consumption and potential savings in energy, economic, and environmental terms in a simple and visually attractive manner. The study shows that a four-member family household consumes an average of 182 kWh/month, equivalent to 17.1 USD, and an annual environmental footprint of 1068.9 kg of CO2. From this energy consumption, 57% is consumed by household appliances, 31% corresponds to technology and entertainment, and 12% represents lighting. Nevertheless, it is possible to reduce monthly energy consumption by 45% if consumers apply energy sufficiency and efficiency measures. This reduction will produce a monthly saving of 7.9 USD and an annual reduction of 485 kg of emissions. By implementing this web-based tool, nonspecialized users can analyze and decide the best way to reduce energy consumption, creating an appropriate energy culture that positively impacts the household economy and promotes environmental sustainability. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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This research aimed to analyze the impact of financial development on environmental sustainability. Data was collected for 34 countries in Europe, covering the period from 2000 to 2020. Data analysis was conducted using the Feasible Generalised Least Squares (FGLS) model, a random-effects model (specified by the Hausman test), and the Generalised Method of Moments (GMM) approach. It was found that lending rates are negatively related to CO2 emissions per capita, total CO2, and CO2 by the transport industry. It was also found that bank credit to the private sector increases total CO2 emissions and CO2 emissions from the power and transport industries. This study found that domestic credit to the private sector increases total CO2 emissions. An important implication of these results is that borrowers should be selected and monitored using more stringent criteria to ensure compliance with environmental requirements. This study has made multiple contributions. It has extended knowledge about how the financial sector impacts the environment. It has used two models that can handle issues of collinearity and heteroscedasticity. Its findings are useful for understanding the financial development-environmental health association in this unique COVID-19 pandemic context. © 2022 Elsevier Ltd
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Spatial analysis is essential to understand the spreading of the COVID-19 pandemic. Due to numerous factors of multi-disciplines involved, the current pandemic is yet fully known. Hence, the current study aimed to expand the knowledge on the pandemic by exploring the roles of forests and CO2 emission in the COVID-19 case-fatality rate (CFR) at the global level. Data were captured on the forest coverage rate and CO2 emission per capita from 237 countries. Meanwhile, extra demographic and socioeconomic variables were also included to adjust for potential confounding. Associations between the forest coverage rate and CO2 emission per capita and the COVID-19 CFR were assessed using spatial regression analysis, and the results were further stratified by country income levels. Although no distinct association between the COVID-19 CFR and forest coverage rate or CO2 emission per capita was found worldwide, we found that a 10% increase in forest coverage rates was associated with a 2.37‰ (95%CI: 3.12, 1.62) decrease in COVID-19 CFRs in low-income countries;and a 10% increase in CO2 emission per capita was associated with a 0.94‰ (95%CI: 1.46, 0.42) decrease in COVID-19 CFRs in low-middle-income countries. Since a strong correlation was observed between the CO2 emission per capita and GDP per capita (r = 0.89), we replaced CO2 emission with GDP and obtained similar results. Our findings suggest a higher forest coverage may be a protective factor in low-income countries, which may be related to their low urbanization levels and high forest accessibilities. On the other hand, CO2 can be a surrogate of GDP, which may be a critical factor likely to decrease the COVID-19 CFR in lower-middle-income countries. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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The world is still following an unsustainable development pathway, facing great challenges in global CO2 emissions reduction in the coming decades. In this study, we used Kaya identity model to project CO2 emissions. We considered three main scenarios (business-as-usual, BAU;post-Copenhagen-Paris, PCP;deglobalization (COVID-19), DGC), which explored different pathways for CO2 emissions of fuel combustion to 2050 from global to national level. The results show that industrialized countries have been the largest contributors to global CO2 emissions, but some emerging economies are now among the top emitters in absolute terms. For countries at all stages of development, it's going to be important to reduce the trajectory of global greenhouse gas emissions and boost resilience to mounting climate impacts. Among the global, regional, the United States and China CO2 emissions reduction scenarios, the PCP scenario is the best CO2 emissions reduction pathway, in this scenario global CO2 emissions will reach a peak by 2029 (31.813 Gt). Renewable energy leads the transition to a lower-carbon energy mix. The COVID-19 pandemic resulted in the largest-ever decline in global emissions. © 2022 The Authors
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The coronavirus pandemic has severely impacted our day-to-day activities and brought about significant change in all major sectors, especially surface passenger transport. Lockdowns and stay-at-home restrictions have significantly reduced energy demand and consequently CO2 emissions of surface passenger transport. The change in CO2 emissions is calculated from near-real-time activity change data as a function of 3 confinement levels. The activity change and related emission trends reflect changes in the mode of transport during different waves, this can be used to understand mobility trends and patterns when stringent measures are imposed. Consequently, constructive use of this data can help prepare and develop the transport sector in case of another epidemic outbreak or other unprecedented calamities and to build a resilient transport infrastructure post-COVID-19. This study estimates and analyzes the changes in CO2 emissions associated with the public (bus and rail) and private surface passenger transport from March 1(st), 2020 to Jan 31(st), 2021 in 21 countries. The research period covers the 1(st) and the 2(nd) waves of COVID-19 in these countries. A higher activity reduction and consequently CO2 emission reduction is displayed during the 1(st) wave compared to the 2(nd) for most countries despite implementing stringent measures during both waves. This is in line with countries adapting to the 'new normal' and restarting socio-economic activities. Similarly, public transport recovery is slower than private transport recovery, making it essential to focus on reinforcement and adaptation of public transport infrastructure for the future. The results show that a cumulative 510 Mt CO2 has been reduced over 11 months in 21 countries, compared to pre-pandemic levels. This reduction brings about a 6% drop in transport CO2 emissions and a 1.5% drop in global CO2 emissions. This analysis sheds light on mobility trends and travel behavior of surface passenger transport modes and related CO2 emissions in different countries which can be used to exemplify the path to recovery based on near-real-time data.
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There are myriad questions that remain to be answered in greenhouse gas (GHG) emissions trading. This article addresses carbon dioxide (CO2) emission factors and carbon losses from heavy equipment that is used to transport ores. Differences occurred between the Intergovernmental Panel for Climate Change (IPCC) emission factor and those that were obtained by considering incomplete combustion and on-site exhaust concentration measurements. Emissions from four off-road vehicles were analyzed. They operated at idle (loading, unloading, and queuing) and in motion (front and rear, loaded and unloaded). The results show that the average CO2 emission factors can be as low as 64.8% of the IPCC standard value for diesel fuel. On the other hand, carbon losses can be up to 33.5% and energy losses up to 25.5%. To the best of the authors’ knowledge, the method that was developed here is innovative, simple, useful, and easily applicable in determining CO2 emission factors and fuel losses for heavy machinery.
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The COVID-19 pandemic suddenly changed the lifestyle of billions of people. Face masks became indispensable to protect from the contagion providing a significant environmental impact. The aim of this work is to propose possible solutions to decrease masks' impact on the environment. For this reason, different masks (surgical and fabric) were considered, and the CO2 emissions associated with the mask materials production were calculated. Carbon Footprint (CF) for each material composing the masks was evaluated through the database Ces Selector 2019. The software Qgis (version 2.18.20) allows us to elaborate the CO2 emissions maps for each Italian region. Finally, for surgical masks, which are often imported from abroad, the CF related to transport was considered. It results that fabric masks are a sustainable solution to prevent contagion. The total CO2 emission associated with the use of fabric masks from the beginning of the pandemic (March 2020) to December 2021 resulted in about 7 kton compared to 350 kton for surgical masks.
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The COVID-19 pandemic has caused great shocks on economic activities and carbon emissions. This paper aims to monitor the CO2 emission trajectory in China before and after the pandemic outbreak, and analyze the emission reduction effects by ETS and its market performances, which are important determinants underlying the trajectory and key drivers for emission reductions. We firstly find out a rather consistent trajectory of CO2 emissions in pre- and post-pandemic China over a 2-year time horizon, using the near-real-time datasets of daily CO2 emissions by Carbon Monitor and applying the Cox-Stuart trend test and mean equality test. We then examine the emission reduction effects by China's carbon ETS and its pilot market performances, using the methodologies of DID and PSM-DID as well as pre-pandemic region-level emission datasets by CEADs. Furthermore, it's found that the ETS pilot markets, which are immature with defects, have been performing more vulnerably in terms of liquidity and transaction continuity under pandemic shocks, thus undermining the emission reduction effects by ETS. These findings are providing insights into further mechanism design of the carbon ETS to the end of steady emission reductions even under shocks for post-pandemic China. It's of particular importance now that the nationwide market has been launched and needs to be enhanced based on lessons learned.
Subject(s)
COVID-19 , Carbon Dioxide , COVID-19/epidemiology , China/epidemiology , Humans , Industry , Pandemics , SARS-CoV-2ABSTRACT
In this paper we describe the systems developed at Ixa for our participation in WMT20 Biomedical shared task in three language pairs, en-eu, en-es and es-en. When defining our approach, we have put the focus on making an efficient use of corpora recently compiled for training Machine Translation (MT) systems to translate Covid-19 related text, as well as reusing previously compiled corpora and developed systems for biomedical or clinical domain. Regarding the techniques used, we base on the findings from our previous works for translating clinical texts into Basque, making use of clinical terminology for adapting the MT systems to the clinical domain. However, after manually inspecting some of the outputs generated by our systems, for most of the submissions we end up using the system trained only with the basic corpus, since the systems including the clinical terminologies generated outputs shorter in length than the corresponding references. Thus, we present simple baselines for translating s between English and Spanish (en/es);while for translating s and terms from English into Basque (en-eu), we concatenate the best en-es system for each kind of text with our es-eu system. We present automatic evaluation results in terms of BLEU scores, and analyse the effect of including clinical terminology on the average sentence length of the generated outputs. Following the recent recommendations for a responsible use of GPUs for NLP research, we include an estimation of the generated CO2 emissions, based on the power consumed for training the MT systems. © 2020 Association for Computational Linguistics
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The vaccine innovation is a ubiquitous preventive measure to the transmission of highly infectious SARS-COV-2. The ongoing mass coronavirus vaccination programmes have inadvertently become the bulk producers of biomedical and plastic waste triggering severe impact on the environment. The sustainable management of bio hazardous vaccine waste in particular; syringes, needles, used/un-used vials and single-use plastic equipment is of utmost importance. This perspective presents a critical point of view in terms of the generated vaccine waste and the subsequent knock-on effect on all aspects of ecosystem. The discussion includes dire consequences due to the release of huge amount of plastic-based personal protective equipment into marine environment. The pivotal crisis of CO2 emission during the manufacture and storage of different vaccines has contributed to global warming. The unavoidable generation of microfibers upon incineration, autoclaving, pyrolysis and open dumping of vaccine waste has further jeopardized the environment. In this vein, exploration of biodegradable materials for vaccine inoculation and development of green technologies for sound waste management is suggested to mitigate the environment pollution.