Asymmetric role of green energy, innovation, and technology in mitigating greenhouse gas emissions: evidence from India.

The primary cause of environmental degradation, which poses a danger to the long-term viability of the ecosystem, is the emission of greenhouse gases (GHG). For this reason, the Glasgow Climate Pact (COP26) established a decarbonization goal in response to this ecological concern, for which all economic players have a responsibility. India is among the participants who have a target set for them to decarbonize their economies by the year 2060 via the use of green energy and the advancement of science and innovation. Nevertheless, the asymmetrical effect of green energy, technology, and innovation on India's decarbonization program was not sufficiently explored in the prior study; hence, this research aims to fill this literature vacuum by considering India's GHG emissions from 1990 to 2020 by leveraging the non-linear autoregressive distributed lag (NARDL) model. The findings reveal the asymmetric influences of variables of interest on GHG emissions during the short and long term and under positive and negative shocks. Regarding the positive shock, long-term findings demonstrate that innovation and technical know-how grow GHG emissions and accelerate environmental degradation. However, a negative shock in innovations and technological know-how is opposed to a positive shock and improving environmental conditions. Further, positive shocks in green energy boost environmental effectiveness by reducing GHG secretions in India. In contrast, the negative shock in green energy deteriorates the environment by triggering GHG releases. These factual findings compel the Indian government to prioritize green technologies in addition to green energy generation to decouple economic growth from greenhouse gas emissions and meet rising energy demands.

Effects of healthcare spending on public health status: An empirical investigation from Bangladesh.

The escalation of healthcare spending in many nations, particularly in emerging countries such as Bangladesh, may be largely attributed to the growing demand for healthcare services. Evidently, there has been a significant expansion in the public funding allocated to the health sector in Bangladesh, intending to enhance health outcomes. Therefore, the purpose of this study was to examine the impact of healthcare expenditure on health outcomes, specifically focusing on the reduction in different mortality rates and the transmission of various infectious diseases. A total of 30 years of data (1990-2019) on the health sector of Bangladesh were collected from different national and international sources. The Vector Autoregression with Exogenous Variables (VARX) model was employed to determine the effects of healthcare expenditure on health outcomes. Results revealed that the per capita health expenditure and the number of doctors showed a significant positive impact on life expectancy and maternal and child health. Also, the government's annual budget on the health sector and number of doctors had a significant positive impact on lowering deaths by Diphtheria, Cholera, Tuberculosis, and Malaria diseases. In order to develop a sustainable healthcare system within the nation, it is imperative for the government to prioritize the allocation of sufficient and effective healthcare funding to cater to the needs of the populace.

Green Coffee Bean Extract Assisted Facile Synthesis of Reduced Graphene Oxide and Its Dye Removal Activity.

To discharge the colored effluents from industries there needs to be effective and affordable treatment options. Adsorption using reduced graphene oxide (rGO) as an adsorbent is a prominent one. In this study, green coffee bean extract (GCBE) is utilized as a safe reducing agent for the reduction of graphene oxide (GO) to synthesize rGO. The formation of rGO is confirmed by a new peak in the UV-vis spectra at 275 nm and a diffraction peak in the XRD patterns at 22°. The effective formation of rGO is further substantiated by a change in the GO peak's properties in the FTIR, EDX, and Raman spectra and a weight loss change in TGA. The SEM and TEM analyses demonstrate the effective production of the nano-sheets of rGO having exfoliated and segregated in a few layers. Furthermore, the obtained rGO exhibited outstanding efficacy in wastewater cleanup, effectively adsorbing MB as a prototype organic dye. The kinetics and isotherm study suggested that the adsorption leads by the chemisorption and monolayer formation on the homogeneous surface of rGO. The maximum adsorption capacity is found to be 89.3 mg g-1. This process offers a fresh opportunity for the economical and safe production of rGO for wastewater treatment.

Towards green economy and sustainable development in Bangladesh: assessing the role of social and environmental indicators.

The evolution towards a green economy integrating social, economic, and environmental concerns has opened a new window to pursue the sustainable development goals (SDGs), especially for emerging nations. Nonetheless, despite being a pressing concern on a global scale, empirical research into the potential for green economy development in the context of Bangladesh has remained notably inadequate. To fill this void, this study is an attempt to evaluate the connection among economic growth, carbon dioxide (CO2) emissions, education, life expectancy, and technology to conclude the ecological and socio-economic repercussions of a green economy in Bangladesh's framework of achieving SDGs. Considering the statistical features of the annual data from 1990 to 2019, the autoregressive distributed lag (ARDL) method has been employed to analyze the connections between the chosen variables. The empirical outcomes show that an upsurge in CO2 is accompanied by a 3.66% increase in GDP over the long term, suggesting a positive and statistically significant relationship between the two variables. In addition, GDP increases by about 4.2% for every 1% increase in life expectancy. However, the relationship between technological innovation and education found an insignificant positive linkage with GDP. The most important takeaway from these findings is that the growth of Bangladesh's economy is occurring at the expense of the environment. Hence, this research recommends that, as a developing nation, Bangladesh should concentrate on environment-friendly alternatives, which can be done through the introduction of a green economy to achieve a sustainably developed economy.

Impact of banking development and renewable energy consumption on environmental sustainability in Germany: Novel findings using the bootstrap ARDL approach.

This study examines the effects of banking development, economic growth and consumption of renewable energy on carbon dioxide (CO2) emissions and load capacity factor (LCF). Previous empirical studies have assessed the interrelationship between banking development and CO2 emissions; however, these studies have ignored supply-side ecological issues. To overcome this issue, this study evaluates the effect of banking development on LCF, which is considered to be one of the most comprehensive ecological proxies to date, including both biocapacity and ecological footprint (EF). Using the bootstrap autoregressive distributed lag model, the study reveals that renewable energy improves ecological quality in Germany. The results of the investigation demonstrate that the environmental Kuznets curve hypothesis is valid in Germany using CO2 emissions and LCF indicators. Furthermore, this study demonstrates that banking growth and renewable energy in Germany correlate with improved environmental quality. These findings provide policymakers with important insights. In this context, the study advises the banking industry and government authorities to leverage banking expansion to support green energy to achieve the national goal of zero CO2 emissions by 2045.

Reinvigorating the environmental Kuznets curve hypothesis in the context of highly polluted nations: evidence using advanced panel estimation techniques.

China, United States, India, Russia, and Japan are regarded as the top five carbon dioxide-emitting nations in the world. These countries altogether account for more than half of the global annual discharges of carbon dioxide. Consequently, impeding the carbon emission-led environmental adversities in these countries is of critical emphasis for establishing environmental sustainability worldwide. In this regard, this study checks how economic progress, energy use intensification, and renewable energy use affect the annual growth rates of per capita carbon dioxide emission in these highly-polluted economies considering the study period from 1990 to 2021. Besides, for analytical purposes, advanced panel data estimation techniques have been utilized for detecting and neutralizing the impacts of cross-sectional dependency and slope heterogeneity-related problems in the data. Overall, the findings endorse that economic progress deteriorates environmental quality both in the short and long run. However, since the long-run unfavorable environmental impacts of economic growth are relatively lower compared with the short-run impacts, the environmental Kuznets curve hypothesis can be deemed valid. Besides, more intensive use of energy resources is witnessed to impose negative long-run environmental consequences while the adoption of renewable energy instead of fossil fuels is found to improve environmental well-being, both in the short and long run. Furthermore, the results affirm that economic progress and energy use intensification jointly degrade environmental conditions. By contrast, economic progress alongside greater adoption of renewable energy is observed to inflict an environmental quality-improving effect. Considering these findings, a couple of carbon dioxide mitigating policies are suggested to the concerned highly polluted developed and developing nations.

Spatial price transmission in the onion markets of Bangladesh: An application of NARDL approach.

As the price of local onions is greatly impacted by the price of imported onions at these two levels of the supply chain, the goal of this study was to ascertain whether onion prices in Bangladesh are transmitted asymmetrically at the wholesale and retail levels. To analyze asymmetry, the study employed the nonlinear autoregressive distributed lag (NARDL) model in the short and long run using monthly time series data from January 2006 to December 2020. The NARDL model captures the effects of both positive and negative shocks in the short as well as in the long run. The empirical results from the NARDL indicate that the wholesale price of local onion shares a short-run relationship with the wholesale price of imported onion while the local retail price of onion shares a long-run relationship with the imported retail price of onion. In addition, the short-run impact of local wholesale and imported wholesale prices is asymmetric. Long-run evidence supports the existence of an asymmetric effect between the local and imported retail onion prices. Using the Pairwise Granger causality test, we examined the causal relationships between wholesale and retail prices. The direction of the casual relationship indicates that the wholesale and retail prices of imported onions lead to the wholesale and retail prices of local onions. A clear understanding of the onion market, how prices move between market actors, and its role in determining market price interaction could be gained by analyzing the asymmetric relationship between the local and imported onion prices. As a result, significant policy recommendations could be made to control the onion price in Bangladesh.

Animal protein-soybean oil-based broiler diet optimizes net profit at the expense of desirable ω-6 fatty acids from the breast muscle of the broiler chicken.

Total 288 Ross-308-day-old male broiler chicks were randomly distributed into six dietary treatment groups in a two-way ANOVA with 2 × 3 factorial arrangements (two factors, i.e., dietary protein and energy having two types of protein, e.g., plant, animal and three different sources of energy, e.g., soybean oil, rice bran oil and sunflower oil) to justify if animal protein-soybean oil based broiler diet optimizes net profit at the expense of desirable ω-6 fatty acids in the breast muscle of the broiler chicken. Average daily feed intake (ADFI), final live weight (FLW), average daily gain (ADG), feed efficiency (FE), carcass characteristics, cardio-pulmonary morphometry, fatty acid profile of the breast muscle and cost-benefit analysis were measured. Results indicated that animal protein significantly increased 4.27% FLW, 6.13% ADFI, 4.31% ADG and 2.93% wing weight. Accordingly, soybean oil increased 4.76% FLW, 3.80% ADG and 1.36% dressing percentage at the expense of 12.07% proventriculus weight compared with sunflower oil. The generalized linear model identified no interaction effects of the sources of protein and energy on overall performance of the birds. Replacement of vegetable protein by animal protein decreased 14.01% ∑ω-3, 12.16% ∑ω-6 and 12.21% sum of polyunsaturated fatty acids (∑PUFA) and concomitantly increased 10.82% sum of saturated fatty acids (∑SFAs) in the breast muscle (Pectoralis major). Accordingly, replacement of sunflower oil by soybean oil decreased 29.17% ∑ω-3, 6.71% ∑ω-6, 11.62% sum of monounsaturated fatty acids (∑MUFAs) and 7.33% ∑PUFAs and concurrently increased 18.36% ∑SFAs in the breast muscle of the broiler birds. It was concluded that animal protein-soybean oil-based broiler diet optimized net profit at the expense of desirable ω-3 and ω-6 fatty acids in the breast muscle of the broiler chicken.

Investigating the nexus between trade policy uncertainty and environmental quality in the USA: empirical evidence from aggregate and disaggregate level analysis.

Worldwide, environmental sustainability is a hot topic, particularly in industrialized countries due to their higher emission intensity. Environmental conservation and equitable economic growth have been prioritized in economic debate and policy development. Over the past three decades, the USA's emissions of carbon dioxide (CO2e) have risen exponentially, as trade policy uncertainty (TPU). In this circumstance, this paper aims to contribute to the existing literature by exploring the effect of TPU on environmental quality by controlling the energy consumption, economic growth, and population in the USA over the period 1985M1 to 2022M3 employing the augmented ARDL and NARDL procedures in the presence of structural breaks. From our analysis, the results revealed that TPU affects negatively CO2e in the residential sector, and negative changes in TPU positively affect CO2e in the commercial sector both in the long and short run. On the other side, the outcomes show that energy consumption is a crucial key determinant factor in environmental degradation at the aggregate level and in all sectors. Furthermore, our findings clarify that economic growth upsurges the CO2e at the aggregate level precisely in the industrial and residential sectors. Juxtaposing, in the long run, the results indicate that population growth could make additional pressure on environmental quality at the aggregate level, especially in commercial, power generation, and residential sectors. Accordingly, it is clear from our results that the regulations put in place to encourage Americans to buy locally created goods instead of those imported, especially in light of the high levels of TPU, maybe the best option to decrease the long-term impact of international trade on the environment to achieve sustainable development goals (SDGs).

Investigating the nexus between carbonization and industrialization under Kaya's identity: findings from novel multivariate quantile on quantile regression approach.

Developing nations aim to industrialize and grow sustainably often ignoring the environmental consequences. However, few empirical studies have looked at the influence of industrialization-driven economic transition on carbon footprint in developing nations using a non-parametric approach. In this milieu, on the ground of Kaya's identity and the novel multivariate quantile-on-quantile regression (QQR) (extension of Sim and Zhou's (2015) bivariate QQR model), the present research studies the impact of industrial value-added (IGVA), population, energy intensity, and carbon intensity on CO2 emissions in India. This study is one of the first in the literature to evaluate the industrialization-carbonization nexus in the context of Kaya's identity for the Indian economy utilizing an innovative multivariate QQR approach, which makes a methodological and empirical addition to the literature. The outcomes of the multivariate QQR technique demonstrate that economic and environmental development requires continual long-run strategies. The empirical findings revealed that there is no authentication that India's carbon emissions increased due to its industrialization, which exhibited that IGVA has a negative and significant connection with CO2 emissions. In some quantiles, population size positively impacts CO2 emissions. On the other hand, carbonization in the Indian economy is asymmetrically affected by GDP per capita and energy and carbon intensity. The quantile Granger causality study further supported the aforementioned results. The current analysis also offers policy suggestions for environmentally friendly sustainable economic growth and to achieve the sustainable development goals (SDGs) of India.

Perception of and adaptation to climate change: the case of wheat farmers in northwest Bangladesh.

Climate change's impact on crop production is a global concern. A better understanding of farmers' perceptions of climate change and adaptation strategies will benefit farmers and policymakers in outlining an effective adaptation mechanism to climate change. Therefore, this study assessed wheat farmers' perceptions of climate change, identified major adaptation strategies, factors influencing adaptations, and barriers to effective adaptation by surveying 160 wheat farmers in northwest Bangladesh. The results revealed that farmers experienced more frequent droughts due to higher temperatures, decreased and irregular precipitation, reduced ground and surface water availability, and shorter winter seasons over the last two decades. Key adaptation strategies identified were more irrigation, switching to other crops, and changing fertilizer and insecticide usage. Multinomial logit model results indicate that farming experience, access to climate information and extension services, access to subsidies, farm size, family size, and electricity for irrigation were the significant factors influencing farmers' adaptation decisions. Limited access to climate information, inadequate knowledge of appropriate adaptation measures, and low price of wheat represented major adaptation barriers. The study recommends strengthening agricultural research and extension services to farmers, including education and training, to develop effective adaptation strategies to climate change.

Energy mix with technological innovation to abate carbon emission: fresh evidence from Mexico applying wavelet tools and spectral causality.

The global warming issue arises from climate change, which draws scientists' attention toward cleaner energy sources. Among clean sources, renewables and nuclear energy are getting immense attention among policymakers. However, the significance of nuclear energy in reducing CO2 emissions has remained ambiguous, necessitating further research. Therefore, the present study draws impetuous attention to the United Nations Sustainable Development Goals-7 (affordable clean energy) & 13 (climate change mitigation) by looking at the relationship between energy mix (fossil fuels, renewables, and nuclear), economic growth, technological innovation, and CO2 emissions in Mexico from 1980 to 2019 using the autoregressive distributed lag (ARDL) model. In addition, to assess the direction of causality, this study applied wavelet techniques and spectral causality. The findings affirm that renewable and nuclear energy use and technological innovation tend to curb CO2 emissions, whereas fossil fuel consumption and economic expansion trigger CO2 emissions. The study lends support to the environmental Kuznets curve (EKC) phenomenon in Mexico. The FMOLS and DOLS tests show that our long-run estimates are reliable. In different time scales, the wavelet coherence result is also consistent. Finally, the results of the spectral causality approach demonstrate a significant causal association between the variables tested at various frequencies. As a result, in order to achieve SDGs 7 and 13 and support an environmentally friendly ecosystem, Mexico's energy mix must be changed to renewables and nuclear.

The asymmetric influence of environmental-related technological innovation on climate change mitigation: what role do FDI and renewable energy play?

This study aims to provide a new perspective on environmental studies by examining the influence of environmental-related technological innovation, foreign direct investment, renewable energy consumption, and economic growth on the climate change index (CCI), a novel proxy for environmental quality indicators. From the econometric standpoint, this study employs the "non-linear autoregressive distributed lag" model and spectral causality over the period of 1999-2018 for India. The results show that positive shocks to economic growth have detrimental long- and short-term effects on environmental quality, whereas negative shocks have no effect. While a positive shock has an insignificant impact, a negative shock to environmental technology innovation has a long-term negative impact on environmental quality. This study provides evidence for the pollution halo hypothesis in India. Besides, a long-term negative shock to the usage of renewable energy fosters environmental degradation. Furthermore, in short-, medium-, and long-term frequency, spectral causality demonstrates unidirectional causation from CCI to environmental-related technological innovation. Bidirectional causation is demonstrated between the CCI and renewable energy consumption in the short and medium term. In addition, environmental-related technological innovation and foreign direct investment are demonstrating a bidirectional relationship in the short term. This study has advocated the Sustainable Development Goals (SDGs)-centric policy paradigm, which can assist the Indian government in achieving SDG-13 (mitigating climate change) and SDG-7 (clean energy consumption).

Study on the coupling and coordination degree between urban tourism development and habitat environment in the Yangtze River Delta in China.

By constructing the two evaluation systems of urban tourism development (TD) and habitat environment (HE), the dynamic response relationship between the two systems in the Yangtze River Delta urban agglomeration from 2001 to 2020 is explored by using panel vector autoregression (PVAR) model and coupled coordination degree model. The study unearthed four intriguing findings: (1) the level of TD in the study area has been continuously rising from 2001 to 2020, with an initial slow growth rate and then fast. The level of HE is increasing steadily at an average annual rate of 7.05%. There exists a reciprocal response relationship between the two systems, with a strong shock effect in the short term and a synergistic evolution in the long term. (2) The coupling degree between the urban TD and HE has an increasing trend, and the coupling coordination degree of the two systems has an average annual rate of 4.165%, implying the interaction and promotion effect between the two systems is improving. (3) Most of the cities in the Yangtze River Delta gradually realize the evolution from dysfunctional type to coordinated type, but the overall coordination intensity is low. (4) The barrier degrees of TD system indicators show a small annual increasing trend, while the barrier degrees of HE system indicators show a substantial and continuous decreasing trend. In terms of the barrier degree factors, some important factors that restrict the coupled and coordinated development of the two systems are also reported. This research can provide a useful reference for the synergistic improvement of urban tourism economy and habitat environment.

COVID-19's effects and adaptation strategies in fisheries and aquaculture sector: An empirical evidence from Bangladesh.

The COVID-19 pandemic has wreaked havoc on the aquaculture and fisheries sector all around the world, with the impact being exacerbated in developing countries. This study is an endeavor to identify consequences of the COVID-19 on fisheries and aquaculture sectors based on primary data collected from Bangladesh as an empirical case study. The data were collected through face-to-face interviews with different supply chain actors while analyzed using descriptive statistics and a problem confrontation index. As results depicted, income and employment across fish farmers, fishers, and traders were severely hurt, with a drastic fall in the market demand, coupled with a severe drop in their fish consumption. As market demand declined, fish farmers must be stocked mature fish for an extra period, and feed costs raised, eventually increasing the overall production cost. Besides, inaccessibility to inputs also made fish production and catch more troublesome. The price of all the major cultured and captured species plunged, leading to a depressing return to farmers, while inputs price underwent a significant increase except for labor and fingerling. However, traders seemed to be the worst sufferers amid striking disruption in fish value chain, which ostracized the preponderance of the traders from the chain. Some of the prime obstacles that constrained the production and trading process were but not limited to higher transportation costs, labor shortage, inability to pay for the wage, and reduced consumer demand across fish farmers, fishers, and traders. Nevertheless, our article further identified a myriad of strategies that the fish farmers, fishers, and traders followed to heal the scar of the fisheries and aquaculture sector with hands-on actions.

A Review on Mechanistic Insight of Plant Derived Anticancer Bioactive Phytocompounds and Their Structure Activity Relationship.

Cancer is a disorder that rigorously affects the human population worldwide. There is a steady demand for new remedies to both treat and prevent this life-threatening sickness due to toxicities, drug resistance and therapeutic failures in current conventional therapies. Researchers around the world are drawing their attention towards compounds of natural origin. For decades, human beings have been using the flora of the world as a source of cancer chemotherapeutic agents. Currently, clinically approved anticancer compounds are vincristine, vinblastine, taxanes, and podophyllotoxin, all of which come from natural sources. With the triumph of these compounds that have been developed into staple drug products for most cancer therapies, new technologies are now appearing to search for novel biomolecules with anticancer activities. Ellipticine, camptothecin, combretastatin, curcumin, homoharringtonine and others are plant derived bioactive phytocompounds with potential anticancer properties. Researchers have improved the field further through the use of advanced analytical chemistry and computational tools of analysis. The investigation of new strategies for administration such as nanotechnology may enable the development of the phytocompounds as drug products. These technologies have enhanced the anticancer potential of plant-derived drugs with the aim of site-directed drug delivery, enhanced bioavailability, and reduced toxicity. This review discusses mechanistic insights into anticancer compounds of natural origins and their structural activity relationships that make them targets for anticancer treatments.

Willingness to pay for adopting conservation tillage technologies in wheat cultivation: policy options for small-scale farmers.

Traditional farming involves intensive tillage causing soil degradation and erosion. On the contrary, conservation tillage technologies are expensive to purchase for small-scale farmers. However, the adoption of these technologies reduces soil tillage costs which lead to reduced overall production costs. In this milieu, this study assessed the willingness to pay (WTP) for adopting conservation tillage technologies in terms of individual and cooperative payment systems using the primary data collected from 320 wheat farmers in Bangladesh. The contingency valuation method (CVM) was followed to estimate their WTP, and factors affecting WTP were identified through the logistic regression model. The results elicited farmers perceived that conservation tillage technologies would facilitate by reducing costs, timely land preparation, seed sowing and planting, appropriate positioning of seed and fertilizers, and higher soil moisture. Nevertheless, most of the farmers wanted to adopt conservation tillage technologies, while about 79% would like to pay for it. Although farmers' average WTP for individual purchases was higher, most were interested in the cooperative systems for adopting conservation tillage machines. Farmers' WTP for both individual and cooperative purchases was influenced by location of wheat production, farming experience, and demonstration plots. Additionally, individual payment system was affected by the amount of wheatland and training while credit affected the cooperative purchase system. Besides, the farmers would like to expand their wheat farms by approximately 73.33% after adopting conservation tillage technologies. The refusal to pay for conservation tillage technologies was mostly due to low-quality spare parts, lack of technical understanding, and unawareness of the technology. This study suggests that providing training among farmers and operators, credit support, and making machines and spare parts available in the nearest markets would support adopting conservation technologies. Besides, cooperative-based payment system should be formed to help small-scale farmers adopt conservation tillage techniques for sustainable agriculture in an environment-friendly way.

Environmental consequences of foreign direct investment influx and conventional energy consumption: evidence from dynamic ARDL simulation for Turkey.

The preponderance of emerging economies confronts significant trade-offs between economic growth and environmental sustainability considerations, and Turkey is no exception. This study draws strength from the United Nations Sustainable Development Goals (UN-SDGs-7,11,12 & 13). To this end, the present study explores the role of the environmental Kuznets curve (EKC) hypothesis for the case of Turkey for annual frequency data from 1970 to 2020. The present study leverages on the novel dynamic autoregressive-distributed lag (DARDL) methodology and Bayer and Hanck combined cointegration test. The combined Bayer and Hanck cointegration test alongside ARDL bounds test traces equilibrium relationship between economic growth, urbanization, FDI, energy use, and CO2 emission over the investigated period. Empirical results from the DARDL simulation analysis validates the EKC hypothesis. These results suggest that environmental quality is being compromised for economic growth at the earlier stage of economic growth (scale stage). The EKC phenomenon is affirmed as a 1% increase in economic growth increase emission level by 0.1580% and quadratic economic growth decrease emission by 0.1095% in the short and long run, respectively. Similarly, urbanization and energy used in both the short and long run also worsen environmental quality while FDI influx in the long run improves environmental quality in Turkey. These outcomes have far-reaching environment-urbanization growth implications. From a policy lens, the current study subscribed to the environmental stick policies and investment on strategies on a paradigm shift from fossil-fuel energy consumption base to renewables. Further insights are highlighted in the concluding section.

Towards a clean production by exploring the nexus between agricultural ecosystem and environmental degradation using novel dynamic ARDL simulations approach.

Agriculture, which serves as a lifeline for us, is unequivocally vital for an agriculture-dependent economy like Bangladesh, not only for its food supply but also because of its significant contribution towards achieving Sustainable Development Goals (SDGs) 1 and 2. However, in a third-world nation like Bangladesh, where farming practices largely circumvent the environmental consequences, raised our concern. In this milieu, this study is a novel attempt to explore the association between agricultural ecosystem and environmental degradation in Bangladesh using a long time spanning from 1972 to 2018. We observed a long-run association between the agroecosystem and CO2 emission. Further, findings from the dynamic autoregressive distributed lag (DARDL) simulation model revealed that the environmental quality of Bangladesh is heavily distorted by total cereal production, total livestock head, enteric methane emissions, N2O emissions from manure application, and CO2 equivalent N2O emissions from synthetic fertilizers in the short and long run, whereas agricultural technology, pesticide use in agriculture, and burned biomass crop residue deteriorated the environmental quality only in the long run. The counterfactual diagram entailed from the DARDL model projected the trend of CO2 emission in response to positive and negative changes in the analyzed variables. Lastly, this study established a causal relationship between the agroecosystem and environmental degradation using frequency domain causality. Indeed, our study will aid in reshaping agricultural practices in an eco-friendly manner to mitigate environmental degradation and help formulate pragmatic policy actions so that agro-lead nations can thrive in the race of achieving SDGs 1, 2, and 13.

NaHCO3, L-arginine, and vitamin C supplemented vegetable diet ameliorates tachycardia and polycythemia in the broiler chicken.

The study aimed to investigate if vegetable-based high-energy mash diets supplemented with NaHCO3, L-arginine + vitamin C, and vegetable oils were effective against tachycardia and polycythemia in the broiler chicken. A total of 256 Ross-308 day-old male broiler chicks were randomly distributed into eight dietary treatment groups in a three-way ANOVA with 2 × 2 × 2 factorial arrangement (three factors, i.e., NaHCO3, L-arginine + vitamin C, and vegetable oil each with two levels, e.g., 0 and 0.1% of NaHCO3 and L-arginine + vitamin C; 3 and 4% of vegetable oil supplemented with basal diet) for a period of 35 days. Iso-caloric and iso-nitrogenous diets were formulated and supplied ad libitum. The final live weight (FLW), average daily feed intake (ADFI), average daily gain (ADG), feed efficiency (FE), carcass traits, cardio-pulmonary morphometry, total protein (TP), hemoglobin (Hb), triiodothyronine (T3), incidence of tachycardia, and polycythemia were examined. Supplementation of NaHCO3 increased 2.2% ADFI, 5.5% FE, and 23.2% TP. The L-arginine + vitamin C increased 2.4% FLW and decreased 1.9% heart rate. Vegetable oil increased 1.3% ADFI, 4.2% ADG, 8.6% FE, 23.1% Hb, and 15.5% PCV. The NaHCO3, L-arginine + vitamin C, and vegetable oil additively interacted to increase 31.5% T3 at the expense of 21.1% of the weight of the right ventricle (RV). The RV:TV, carcass traits, and hemato-biochemical indices remained within normal range irrespective of the levels of the supplementations of the test ingredients. It was concluded that vegetable-based high-energy mash diets were not susceptible to tachycardia and polycythemia. The addition of NaHCO3 and L-arginine + vitamin C ameliorated the propensity of tachycardia and polycythemia without deteriorating performance, carcass traits, and hemato-biochemical indices of the broiler chicken in a dose-dependent manner.