Assessing the nonlinear impact of green space exposure on psychological stress perception using machine learning and street view images.

Introduction: Urban green space (GS) exposure is recognized as a nature-based strategy for addressing urban challenges. However, the stress relieving effects and mechanisms of GS exposure are yet to be fully explored. The development of machine learning and street view images offers a method for large-scale measurement and precise empirical analysis. Methods: This study focuses on the central area of Shanghai, examining the complex effects of GS exposure on psychological stress perception. By constructing a multidimensional psychological stress perception scale and integrating machine learning algorithms with extensive street view images data, we successfully developed a framework for measuring urban stress perception. Using the scores from the psychological stress perception scale provided by volunteers as labeled data, we predicted the psychological stress perception in Shanghai's central urban area through the Support Vector Machine (SVM) algorithm. Additionally, this study employed the interpretable machine learning model eXtreme Gradient Boosting (XGBoost) algorithm to reveal the nonlinear relationship between GS exposure and residents' psychological stress. Results: Results indicate that the GS exposure in central Shanghai is generally low, with significant spatial heterogeneity. GS exposure has a positive impact on reducing residents' psychological stress. However, this effect has a threshold; when GS exposure exceeds 0.35, its impact on stress perception gradually diminishes. Discussion: We recommend combining the threshold of stress perception with GS exposure to identify urban spaces, thereby guiding precise strategies for enhancing GS. This research not only demonstrates the complex mitigating effect of GS exposure on psychological stress perception but also emphasizes the importance of considering the "dose-effect" of it in urban planning and construction. Based on open-source data, the framework and methods developed in this study have the potential to be applied in different urban environments, thus providing more comprehensive support for future urban planning.

Towards sustainable environment in North African countries: The role of military expenditure, renewable energy, tourism, manufacture, and globalization on environmental degradation.

Climate change resulting from increasing emissions has become a pressing concern in North African countries due to its significant environmental and socio-economic impacts. There is a need for extensive research on this topic to raise global awareness of the associated dangers. This study investigates the dynamic impact of economic growth, military expenditure, globalization, renewable energy, manufacturing, tourism, capital formation, and labor on CO2 emissions in North African countries from 1995 to 2021. The long-term results of the ARDL model reveal that globalization, renewable energy and capital formation have a negative impact on CO2 emissions, whereas economic growth, manufacturing, and tourism exhibit a positive impact. Pairwise Granger causality evidence indicates unidirectional causality from economic growth, globalization, military expenditure, manufacturing, tourism, and capital formation to CO2 emissions. These findings provide policymakers with critical insights to shape evidence-based interventions that promote renewable energy investments and globalization, enhance capital formation and high-skilled labor, and implement regulations to mitigate the environmental impacts of economic growth, military expenditure, manufacturing, and tourism. This guidance will help the region transition to a more environmentally friendly economic system.

Demand side management through energy efficiency measures for the sustainable energy future of Pakistan.

Pakistan is facing energy crises due to localized shortages, market manipulation, infrastructure disruption, rising demand, governance issues, climate and geopolitical events. In this situation Demand Side Management (DSM) is a promising solution to overcome the problem of energy crises. DSM strategy helps to manage consumer demand through energy conservation rather than to addition of new power capacity. In this study, Low Emissions Analysis Platform (LEAP) develops an energy model for Pakistan for the period 2022-2050. Three scenarios has been to constructed namely Baseline (BAS), Green Energy Policy (GEP), and Energy Efficiency (ENE) to predict the future energy demand, production, carbon emissions and the investment cost which covers capital, operational and maintenance costs. The model results suggest that DSM targets should be achieved through the implementation of ENE scenario. Predicted energy production and consumption under the ENE scenario are substantially less than those under the BAS scenario. The country can meet its 635.83,000 GWh energy demand with its 747.15,000 GWh energy production. Non-renewable sources produce 171.27,000 GWh, whilst renewable sources produce 575.88,000 GWh. According to this scenario, by 2050, CO2 emissions will be produced around 93.16 million metric tons, requiring an investment cost of $46.80 billion for building new power capacity. The study provides a roadmap with a suggestive optimal balance between energy saving with DSM approach and utilizing renewable energy production to meet energy demand for different sectors of the economy.

An enhanced approach for predicting air pollution using quantum support vector machine.

The essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement. Support vector machine (SVM) is widely recognized as one of the most effective classification machine learning techniques currently available. Since, in conventional systems, the SVM kernel technique tends to sluggish down and even fail as datasets become increasingly complex or jumbled. To compare the execution time and accuracy of conventional SVM classification to that of quantum SVM classification, the appropriate quantum features for mapping need to be selected. As the dataset grows complex, the importance of selecting an appropriate feature map that outperforms or performs as well as the classification grows. This paper utilizes conventional SVM to select an optimal feature map and benchmark dataset for predicting air quality. Experimental evidence demonstrates that the precision of quantum SVM surpasses that of classical SVM for air quality assessment. Using quantum labs from IBM's quantum computer cloud, conventional and quantum computing have been compared. When applied to the same dataset, the conventional SVM achieved an accuracy of 91% and 87% respectively, whereas the quantum SVM demonstrated an accuracy of 97% and 94% respectively for air quality prediction. The study introduces the use of quantum Support Vector Machines (SVM) for predicting air quality. It emphasizes the novel method of choosing the best quantum feature maps. Through the utilization of quantum-enhanced feature mapping, our objective is to exceed the constraints of classical SVM and achieve unparalleled levels of precision and effectiveness. We conduct precise experiments utilizing IBM's state-of-the-art quantum computer cloud to compare the performance of conventional and quantum SVM algorithms on a shared dataset.

A sustainable study of competitive industrial performance amidst environmental quality: New insight from novel Fourier perspective.

This paper uses the novel Fourier Augmented Autoregressive Distributed Lag within the load capacity curve framework to investigate the effects of economic growth, trade openness, renewable energy consumption, and competitive industrial performance on environmental sustainability. The results of the empirical analysis provide evidence that the load capacity curve is valid in Turkiye. Moreover, while trade openness jeopardizes environmental sustainability, renewable energy consumption and industrial competitiveness increase environmental quality. Policymakers should focus intensively on policies that can achieve SDG 9 and industrialization activities. It is essential to give privileges, especially to companies operating in the industrial sector, regarding the transition to renewable energy. Energy efficiency policies that will accelerate the transition to clean energy sources are also an alternative to escape from fossil energy immediately. Environmental factors should be considered when importing intermediate goods used in industry, and these policies should be guaranteed by law as soon as possible.

Impact of wildfire on soil characteristics and arbuscular mycorrhizal fungi.

This study explored whether wildfire alters the soil properties and arbuscular mycorrhizal fungi (AMF) community composition when compared with burnt rangeland, non-burnt rangeland and adjacent tilled in mesothermal ecosystems. The study was carried out in August 2020, 1 year later after wildfire. The results of this study showed that the wildfire played a key role in altering soil characteristics and AMF community composition in Bartin Province located in the Western Black Sea Region. Soil samples were made according to standard methods. AMF spores were isolated according to the wet sieving method, and the spores of AMF were identified according to their morphological characteristics. Analysis of variance was performed to determine the differences between the parameters, and correlation analysis was performed to determine the relationships between the parameters. The highest values of soil organic carbon (2.20%), total nitrogen (0.18%), K2O (74.68 kg/da), root colonization (87.5%) and the frequency of occurrence of Funneliformis geosporum (20%), Claroideoglomus claroideum (16%) and Claroideoglomus etunicatum (11%) were found in burnt rangeland. Sporulation of Acaulospora dilatata, Acaulospora morrowiae, Acaulospora tuberculata, Scutellospora castanea, Scutellospora coralloidea, Scutellospora scutata, Glomus coremioides and Glomus multicaule was either decreased or completely inhibited in the burnt rangeland. While species diversity of AMF (12) decreased, the number of AMF spores (325.6 (number/50 gr soil)) increased in burnt areas. In conclusion, the number of spores and root colonization of AMF increased but species diversity of AMF reduced after the wildfire. In ecosystems with high fire risk where AMF transfer is planned, it is suggested that it would be more appropriate to select species with an increase in spore number after fire.

Eco-consciousness to eco-consumption: unraveling the drivers of sustainable consumption behavior under the mediated-moderated Model.

The impact of climate change has malformed the world's ecosystem, thus making humans call for environmental protection. Climate change, the biggest trauma of the twenty-first century, has made humans switch towards natural consumption. In this regard, the growing phenomenon of industrialization has spurred consumers to invest more in ecological products. Consuming eco-friendly products has several benefits; however, countries are still unable to satisfy the consumer's concern for the environment. The current study presents literature on environmental concerns, psychological well-being, willingness to pay for pro-environmental products, pro-environmental self-identity, and pro-environmental consumer behavior, which are required to ensure the consumer's organic behavior. The research used a questionnaire-driven methodology to gather data from 379 participants. Data analysis was conducted using statistical software packages, specifically SPSS (Version: 4.1.0.0). The suitability of the measurement model was evaluated through structural equation modeling (SEM), which was performed utilizing the SmartPLS. According to the research findings, there is a positive relationship between variables in the study, and individuals with greater levels of psychological well-being are more likely to engage in behaviors that promote sustainable consumption. In order to foster more sustainable consumption patterns in society, policymakers, marketers, and educators may find these findings to be valuable insights. As a result of its empirical exploration of these relationships, the study contributes to the growing body of literature on environmental psychology and sustainable marketing, emphasizing the important role psychological factors play in promoting a greener environment.

Marine sediments in the Gulf of Gabes (Tunisia) heavily polluted by phosphogypsum and human microbiota bacteria: phytoremediation by Salicornia europaea as a natural-based solution.

A huge amount of phosphogypsum (PG) wastes generated from the processing phosphate ore in Tunisia Industrial Group Area-Gabes is getting discarded into the sea. Within this framework, the basic objective of this research is to elaborate and discuss a natural-based solution focused on phytoremediation of contaminated (PG) soils and marine sediments with the halophilic plant Salicornia europaea. A significant drop of the organic matter (53.09%), moisture (26.47%), and sediment porosity with (5.88%) was detected in the rhizosphere Salicornia europaea area (RS). Removal of hazardous elements concentrations, such as Pb, Fe, Cu, Cd, and Zn, between contaminated sediment (CS) and RS displayed a significant difference, ranging from 5.33 to 50.02% of hazardous elements removal concentration, which was observed in the rhizosphere zone. The microbiota of both areas (RS and CS) were analyzed by massive sequencing. In both samples, all the sequences belong to only four phyla: Firmicutes and, to a much lower extent, Proteobacteria, Bacteroidetes, and Actinobacteria. The CS sediment seems to be heavily polluted by human activities. Most of the found genera are inhabitants of the intestine of warm-blooded animals (Escherichia, Bacteroides, Prevotella, Faecalibacterium, Ruminococcus, Enterococcus); hence, activities in this area pose a health risk. On the other hand, it may be surprising that 76.4% of the total high-quality sequences retrieved from the RS sample were affiliated to the family Bacillaceae. The salinity of the studied soil exerts a stress on the microbial populations that inhabit it, directing the selection of halotolerant species.

Recent trends in the phytoremediation of radionuclide contamination of soil by cesium and strontium: Sources, mechanisms and methods: A comprehensive review.

This comprehensive review examines recent trends in phytoremediation strategies to address soil radionuclide contamination by cesium (Cs) and strontium (Sr). Radionuclide contamination, resulting from natural processes and nuclear-related activities such as accidents and the operation of nuclear facilities, poses significant risks to the environment and human health. Cs and Sr, prominent radionuclides involved in nuclear accidents, exhibit chemical properties that contribute to their toxicity, including easy uptake, high solubility, and long half-lives. Phytoremediation is emerging as a promising and environmentally friendly approach to mitigate radionuclide contamination by exploiting the ability of plants to extract toxic elements from soil and water. This review focuses specifically on the removal of 90Sr and 137Cs, addressing their health risks and environmental implications. Understanding the mechanisms governing plant uptake of radionuclides is critical and is influenced by factors such as plant species, soil texture, and physicochemical properties. Phytoremediation not only addresses immediate contamination challenges but also provides long-term benefits for ecosystem restoration and sustainable development. By improving soil health, biodiversity, and ecosystem resilience, phytoremediation is in line with global sustainability goals and environmental protection initiatives. This review aims to provide insights into effective strategies for mitigating environmental hazards associated with radionuclide contamination and to highlight the importance of phytoremediation in environmental remediation efforts.

A comprehensive review on anaerobic digestion with focus on potential feedstocks, limitations associated and recent advances for biogas production.

With the escalating energy demand to accommodate the growing population and its needs along with the responsibility to mitigate climate change and its consequences, anaerobic digestion (AD) has become the potential approach to sustainably fulfil our demands and tackle environmental issues. Notably, a lot of attention has been drawn in recent years towards the production of biogas around the world in waste-to-energy perspective. Nevertheless, the progress of AD is hindered by several factors such as operating parameters, designing and the performance of AD reactors. Furthermore, the full potential of this approach is not fully realised yet due the dependence on people's acceptance and government policies. This article focuses on the different types of feedstocks and their biogas production potential. The feedstock selection is the basic and most important step for accessing the biogas yield. Furthermore, different stages of the AD process, design and the configuration of the biogas digester/reactors have been discussed to get better insight into process. The important aspect to talk about this process is its limitations associated which have been focused upon in detail. Biogas is considered to attain the sustainable development goals (SDG) proposed by United Nations. Therefore, the huge focus should be drawn towards its improvements to counter the limitation and makes it available to all the rural communities in developing countries and set-up the pilot scale AD plants in both developing and developed countries. In this regard, this article talks about the improvements and futures perspective related to the AD process and biogas enhancement.

Coagulation process for the removal of color and turbidity from wet coffee processing industry wastewater using bio-coagulant: Optimization through central composite design.

The growing problem of industrial pollution in developing countries, especially Ethiopia, has sparked serious issues about the quality of the water, particularly when it comes to the effluent from wet coffee processing industries. In response, this study investigates the potential of utilizing natural coagulants, Acanthus sennii C., Moringa stenopetala B., and Aloe vera L., either individually or in combination, for the treatment of coffee effluent. Methodologically, the study systematically varies operational parameters, including coagulant dose, pH levels, stirring speed, and stirring time, to evaluate their impact on coagulation efficiency. Experimental data undergo statistical analysis, employing ANOVA, while computational optimization techniques are employed using Design Expert software to determine optimal conditions. Notably, the blended form of the three coagulants emerges as particularly promising, yielding optimal conditions of 0.750 g/L coagulant dosage, pH 8.76, agitation speed of 80.73 rpm, and agitation time of 19.23 min. Under these optimized conditions, the blended coagulant achieves remarkable removal efficiencies, approximately 99.99% for color and 98.7% for turbidity. These findings underscore the efficiency of natural coagulants, particularly in blended form, for sustainable wastewater treatment in wet coffee processing.

The impact of eco-preneurship and green technology on greenhouse gas emissions - An analysis of East Asian economies.

The pressing need to address the effects of rising greenhouse gas emissions on the environment has become a global concern. Policymakers, governments, and stakeholders advocate a sustainable clean environment. Therefore, green technology and eco-entrepreneurship initiatives are being implemented to reduce these emissions. Despite their efforts in sustainable environments, there is insufficient research on how these initiatives impact economies. This study explores the impact of eco-entrepreneurship and green technology on reducing greenhouse gas emissions in East Asia. Using China and Japan, ranked the first and fifth highest greenhouse gas emitters globally, as case studies, the study employed ARDL and NARDL models for empirical analysis. The findings show that short-run linear estimates of eco-entrepreneurship are significant only in China, while nonlinear short-run estimates are significant for both China and Japan. Comparably, short-run linear estimates of green technology are significant for both China and Japan, while nonlinear coefficient estimates are significant only in Japan. The linear estimate of eco-entrepreneurship was significant and negative in both countries. The coefficient estimates for green technology are significant and negative for both countries. In the nonlinear model, the positive shock coefficient estimates for eco-entrepreneurship are negative and significant in China and Japan. These initiatives are vital for reducing greenhouse gas emissions and improving East Asian economies.

Assessing the role of green investments and green innovation in ecological sustainability: From a climate action perspective on European countries.

In recent years, economies have been increasingly focused on achieving the United Nations' Sustainable Development Goals, recognizing that their achievement is vital to ecological sustainability and green growth. In this context, this paper focuses on investigating the impact of green innovation, green investment, economic growth, and natural resources on ecological sustainability in the five best-performing European Union countries in terms of the Climate Change Performance Index. This study uses the load capacity factor as a comprehensive proxy of ecological sustainability and also assesses the load capacity curve hypothesis in sample nations. Continuously updated fully modified and continuously updated bias-corrected estimators are used to analyze the data from 1995 to 2020 in the context of climate action perspective. The econometric analysis revealed that the load capacity curve hypothesis is invalid in the sample countries. Natural resources decrease environmental sustainability. However, green investments and green innovations contribute to environmental quality and thereby, can be used for effective climate action. Based on these findings, the study recommends specific policies to achieve the Sustainable Development Goals, with a particular focus on target 13.

Determinants of fishing grounds footprint: Evidence from dynamic spatial Durbin model.

Despite a growing literature on fishing grounds footprint, there is no study analyzing fishing footprint regarding spatial effects between neighboring countries. Thus, we explored whether the fishing grounds footprint of 156 countries is spatially correlated. For this purpose, we applied the dynamic spatial Durbin model to examine the direct and indirect effects of GDP per capita, biological capacity, trade openness, population, and urbanization on fishing grounds footprint in the short-term and the long-term during 2001-2021. The results revealed that: (1) there exists a positive and significant spatial dependence in fishing grounds footprint between countries; (2) inverted U-shaped environmental Kuznets curve hypothesis is valid in the short-term and the long-term; (3) fishing grounds footprint is negatively influenced by biocapacity and urbanization in neighboring countries, while population directly increases the fishing footprint. Finally, some suggestions were put forward to reduce fishing grounds footprint and to achieve a sustainable fisheries environment.

Advanced oxidation and biological integrated processes for pharmaceutical wastewater treatment: A review.

The stress of pharmaceutical and personal care products (PPCPs) discharging to water bodies and the environment due to increased industrialization has reduced the availability of clean water. This poses a potential health hazard to animals and human life because water contamination is a great issue to the climate, plants, humans, and aquatic habitats. Pharmaceutical compounds are quantified in concentrations ranging from ng/Lto µg/L in aquatic environments worldwide. According to (Alsubih et al., 2022), the concentrations of carbamazepine, sulfamethoxazole, Lutvastatin, ciprofloxacin, and lorazepam were 616-906 ng/L, 16,532-21635 ng/L, 694-2068 ng/L, 734-1178 ng/L, and 2742-3775 ng/L respectively. Protecting and preserving our environment must be well-driven by all sectors to sustain development. Various methods have been utilized to eliminate the emerging pollutants, such as adsorption and biological and advanced oxidation processes. These methods have their benefits and drawbacks in the removal of pharmaceuticals. Successful wastewater treatment can save the water bodies; integrating green initiatives into the main purposes of actor firms, combined with continually periodic awareness of the current and potential implications of environmental/water pollution, will play a major role in water conservation. This article reviews key publications on the adsorption, biological, and advanced oxidation processes used to remove pharmaceutical products from the aquatic environment. It also sheds light on the pharmaceutical adsorption capability of adsorption, biological and advanced oxidation methods, and their efficacy in pharmaceutical concentration removal. A research gap has been identified for researchers to explore in order to eliminate the problem associated with pharmaceutical wastes. Therefore, future study should focus on combining advanced oxidation and adsorption processes for an excellent way to eliminate pharmaceutical products, even at low concentrations. Biological processes should focus on ideal circumstances and microbial processes that enable the simultaneous removal of pharmaceutical compounds and the effects of diverse environments on removal efficiency.

The impact of digital empowerment on the economic openness of the textile industry in Keqiao based on a sustainable environment.

Based on the framework theory of industrial digitization, digital industrialization, digital governance and digital value-added in a sustainable environment, this paper systematically studies the relevant elements of governance and value distribution in the sustainable environment of global trade, and its impact on the development path of human beings. This paper explores the way to embed digital technology into the global value chain to realize digital empowerment, measures the competitiveness index of Keqiao's textile industry in the global value chain, analyzes the technical and environmental challenges faced by China's textile industry in the digital age, and proposes the corresponding countermeasures to deal with the impact of global value chain participation and to improve the international competitiveness of China's textile industry.

Ecological footprint in the OECD countries: do energy efficiency and renewable energy matter?

Ecological footprint (EFP) measures the amount of area, that is land or sea, which is required to absorb the waste generated through human activities or to support the production of resources consumed by populations. EFP index therefore includes six dimensions that are cropland, forestland, carbon, fishing grounds, grazing land, and built-up area. Human activities have impacted the environment, leading to global warming, widespread droughts, and diseases. The present study aims to investigate the role of renewable energy (RE) and energy efficiency on the EFP index. Past researchers have widely used carbon emission (CE) to represent environmental impact, and recent studies have shown that EFP index is a better proxy of environmental degradation. Therefore, the present research differs from past studies in that it compares on how the determinants of environmental degradation affects EFP index and CE. Panel dataset of the OECD countries from 1990 to 2020 is employed. The CS-ARDL, DCCEMG, and AMG techniques, which overcome dynamics, heterogeneity, and cross-sectional dependence, are employed. The main findings depict that RE significantly reduces EFP and CE, while economic growth significantly exacerbates them. Energy efficiency reduces CE, but does not significantly affect EFP. Non-renewable energy and research & development significantly increase CE, while an insignificant positive effect is observed with EFP. This paper shows that factors that significantly influence CE may not always significantly affect the EFP index. Thus, to reduce environmental degradation it is fundamental to understand on how each dimension of EFP is influenced.

Waste derived modified biochar as promising functional material for enhanced water remediation potential.

The waste management and water purification are daunting environmental challenges. Biochar, a carbonaceous material prepared from diverse organic waste (agricultural, household residues and municipal sewage sludge) has garnered substantial attention due to its excellent attributes, including carbon content, cation exchange efficacy, ample specific surface area, and structural robustness. Thus, the present review comprehensively analyzes bio waste-derived biochar with a particular emphasis on water remediation applications. This article primarily delves into various strategies for modifying biochar, elucidating the underlying mechanisms behind these modifications and their potential for bolstering pollutant removal efficiency. Furthermore, it addresses the impact of functionalization on both biochar stability and cost for commercialization. Lastly, the article outlines key developments, SWOT analysis, and future prospects, offering insights into the practical execution of biochar applications at a larger scale. Therefore, this article paves the way for future research to deepen the understanding of modified biochar with mechanisms for exploring water remediation applications in a more sustainable manner.

Advancements in adsorption based carbon dioxide capture technologies- A comprehensive review.

The significant increase in energy consumption has facilitated a rapid increase in offensive greenhouse gas (GHG) and CO2 emissions. The consequences of such emissions are one of the most pivotal concerns of environmental scientists. To protect the environment, they are conducting the necessary research to protect the environment from the greenhouse effect. Among the different sources of CO2 emission, power plants contribute the largest amount of CO2 and as the number of power plants around the world is rising gradually due to increasing energy demand, the amount of CO2 emission is also rising subsequently. Researchers have developed different potential technologies to capture post-combustion CO2 capture from powerplants among which membrane-based, cryogenic, absorption and adsorption-based CO2 processes have gained much attention due to their applicability at the industrial level. In this work, adsorption-based CO2 technologies are comprehensively reviewed and discussed to understand the recent advancements in different adsorption technologies and several adsorbent materials. Researchers and scientists have developed and advanced different adsorption technologies including vacuum swing adsorption, temperature swing adsorption, pressure swing adsorption, and electric swing adsorption, etc. To further improve the CO2 adsorption capacity with a compact CO2 adsorption unit, researchers have integrated different adsorption technologies to investigate their performance, such as temperature vacuum swing adsorption, pressure vacuum swing adsorption, electric temperature pressure swing adsorption, etc. Different adsorbent materials have been tested to evaluate their applicability for CO2 adsorption and among these adsorbents, advanced carbonaceous, non-carbonaceous, polymeric, and nanomaterials have achieved much attention due to their suitable characteristics that are required for adsorbing CO2. Researchers have reported that higher CO2 adsorption capacity can be achieved by integrating different adsorption technologies and employing suitable adsorbent material for that system. This comprehensive review also provides future directions that may assist researchers in developing novel adsorbent materials and gaining a proper understanding of the selection criteria for effective CO2 adsorption processes with suitable adsorbents.

Do the asymmetric effects of eco-digitalization amidst energy transition make or mar the strides toward environmental sustainability in the USA?

The present era faces adverse effects of the strides recorded in economic advancements of the prior generations thus leading the present generation to growth dilemma. Consequently, there is a conscientious consideration for the ecological effects of economic growth. To resolve the preceding issue, due consideration must be given to harmless growth of which eco-digitalization, green financing, green technology, energy transition, and regularity quality are key determinants. Despite the aforesaid importance, empirical studies advancing this nexus are scarce. Hence, this study contributes to environment empirics by providing empirical evidence for the impacts of the highlighted indicators on sustainable environment in the USA. The study explores quarterly data from 1996Q1 to 2019Q4 based on the novel non-linear autoregressive distributed lag (ARDL) model. The pretests' outcomes show that long-run nexus exists among the variables, whereas the Zivot-Andrew uncovers breakpoint years in the observations. The main findings show that eco-digitalization, green financing, green technology, and renewable energy promote sustainable environment. On the flip side, non-renewable energy and regulatory quality hinder the pathways to sustaining the environment in the USA. Robustness analyses conducted based on FMOL, DOLS, and CCR provide substantial support and validity for the main results. Furthermore, the causality nexus lends empirical support for the existence of bidirectional and unidirectional causalities in the empirical model. Policy insights that drive the paths to sustainability in the US are suggested based on the findings.