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The analysis of risk awareness should be the initial stage in integrated natural hazard risk management to promote appropriate and effective measures for mitigating risks and strengthening social resilience inside the multi-risk framework. Nevertheless, earlier studies focused on cross-sectional data and overlooked the changes in risk awareness levels and associated independent variables with time. This study analyzes for the first time a balanced nationwide panel dataset of 1612 respondent-year observations from Switzerland (period 2015-2021, including the epidemic of COVID-19) to examine and compare the effects of potential independent variables on the four dimensions of natural hazard risk awareness (NHRA), ranging from the broadest dimension of Relevance to higher dimensions of Perceived Probability of an event, Perceived Threat to life and valuables, and Perceived Situational Threat. The analysis in this study incorporates multiple methods of Random-Effect Model (RE), Generalized Linear Model (GLM), and mediation analysis. Results show that NHRA increased in Switzerland to different extents (up to 23.24%) depending on the dimension. Event memory, perceived information impact and reported individual informed level appeared to be the most consistent independent variables positively influencing panel NHRA. Among these, perceived information impact as an important indicator of risk communication, was also found to serve as a mediator from risk preparedness to risk awareness. By encouraging residents to engage in "Begin Doing Before Thinking" (BDBT) programs to leverage subliminal effects and self-reflection, this study proposes that behavior-cognition feedback loops may facilitate a virtuous cycle. Our promising observations provide recommendations for an effective awareness-rising strategy design and suggest extensive insights from potential short-interval panel analysis in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A significant body of research has documented the profound changes in global atmospheric conditions during the COVID-19 pandemic. However, there is still an inadequate comprehensive comparison and assessment of countries before, during, and after the pandemic. Variations in restriction policies, human behaviors, and national traits lead to significant differences in how restriction policies affect atmospheric pollution. This study focuses on NO 2 , a pollutant with high temporal sensitivity, and utilizes the Oxford COVID-19 policy stringency index along with demographic information. Through spatial-temporal mapping, we analyzed NO 2 emission fluctuations and calculated the emission changes in each country. Drawing from this analysis, we explored the relationships among these factors and found that over the span of 2019-2022, across 193 countries, global NO2 emissions displayed a distinct trajectory: initially decreasing, subsequently rebounding, and eventually fluctuating. Most countries exhibited seasonal variations in NO2 emissions. Additionally, the study uncovered a correlation between the stringency of COVID-19 policies and the reduction in NO2 emissions: as policies became stricter, emissions significantly decreased in most countries. In contrast, in countries with lower population densities, stricter policies paradoxically led to an increase in emissions. These findings underscore the importance of considering demographic factors and geographical context in the formulation and implementation of environmental policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Improving the resilience of wastewater treatment facilities (WWTFs) has never been more important with rising risks of disasters under climate change. Beyond physical damages, non-physical shocks induced by disasters warrant attention. Human mobility is a vital mediator in transferring the stresses from extreme events into tangible challenges for urban sewage systems by reshaping influent characteristics. However, the impact path remains inadequately explored. Leveraging the stay-at-home orders during the COVID-19 pandemic as a natural experiment, this study aims to quantify and interpret the heterogeneous impacts of mobility reduction on the influent characteristics of WWTFs with different socio-economic, infrastructural, and climatic conditions. To achieve this goal, we developed a research framework integrating causal inference and interpretable machine learning techniques. Based on the empirical data from China, we find that 79.1% of the studied WWTFs, typically located in cities with well-developed drainage infrastructures and low per capita water usage, exhibited resilience against drastic mobility reduction. In contrast, 20.9% of the studied WWTFs displayed significant variations in influent characteristics. Large-capacity WWTFs in subtropical regions encountered challenges with low-load operations, and small-capacity facilities in suburban areas grappled with nutrient imbalances. This study provides valuable insights to equip WWTFs in anticipating and adapting potential variations in influent characteristics triggered by mobility reduction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The digital economy (DIE), a new economic form with digitalization at its core, has become an important driving force for promoting regional economy development. In the context of the COVID-19 pandemic, exploring the impact path of the DIE on carbon emission efficiency (CEE) is conducive to giving full play to the "carbon-reduction-and-efficiency-enhancement" role of the DIE, and to promoting the realization the "dual carbon" goal of carbon peak and carbon neutrality. In this paper, the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB) are taken as study areas, the panel Tobit model is used to explore the impact of the DIE on CEE, and the intermediary-effect model and threshold-effect model are constructed to test the intermediary and threshold effects of technological innovation, respectively. The results show that the DIE has a U-shaped nonlinear impact on CEE in both the YRB and the YREB and that the impact has regional heterogeneity. Technological innovation can play a mediating effect between the DIE and CEE, whereas the mediating effect in the YRB is stronger than that in the YREB. Technological innovation has a threshold effect on the DIE to improve CEE, while the threshold value in the YREB is higher than that in the YRB. Furthermore, this paper proposes some suggestions to guide regional low-carbon and sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Green finance is an essential instrument for improving the environment and addressing climate change. This study investigates the dynamic spillovers among green finance markets using time-varying parameter vector autoregression (TVP-VAR) spillover indices, and further investigates the impact of climate policy uncertainty and investor sentiment on spillovers based on the generalised autoregressive conditional heteroscedasticity mixed data sampling (GARCH-MIDAS) model. The results indicate that: (i) environmental, social and governance (ESG), clean energy and water markets are information transmitters in the green finance system, whereas green building, green transportation, green bond and carbon markets are mainly information receivers; (ii) green stock markets including clean energy, non-energy and ESG markets transmit and receive greater information in the green finance system, while green bond and carbon markets do less; (iii) the green bond market is more interconnected with other green finance markets after the COVID-19 outbreak; (iv) investor sentiment contributes more to the net total directional spillovers of green resource markets (water and clean energy), while climate policy uncertainty contributes more to total spillovers and the net total directional spillovers of other green finance markets. These findings offer invaluable guidance for both policymakers and environmental investors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Insights into COVID-19 antivirals' environmental fate and ecological risk are urgently required due to their increasing concentrations in aquatic environments, which have rarely been studied. Herein, we first investigated the photochemical transformation and the resulting alterations in toxicity of arbidol, an antiviral drug with relatively higher toxicity. The photolysis of arbidol was rapid with a rate constant of 0.106 min -1 due to its superior ultraviolet light absorption, in which the direct photolysis was predominated with a contribution of 91.5%. Despite its substantial photolysis, only 14.45% of arbidol was mineralized after 100 min, implying that arbidol and its products might have a long-term impact on aquatic environment. It was inferred that arbidol was photolyzed mainly via the loss of thiophenol, bromine, and alkylamine, based on twelve photolytic products identified. Notably, the experimental results demonstrated that the photolysis process increased the acute toxicity of arbidol, and the toxicity prediction indicated that the ecotoxicity of two photolytic products was very high with LC 50 values below 0.1 mg/L. Due to the co-effect of multiple constituents, the photolytic rate observed in wastewater treatment plant effluent and in river water was comparable to that in ultra-pure water, while it was slightly enhanced in lake water. The presence of dissolved organic matter suppressed arbidol photolysis, while NO 3 exhibited a promotion effect. These results would be of great significance to assess the fate and risk of COVID-19 antivirals in natural aquatic environments.- exhibited a promotion effect. These results would be of great significance to assess the fate and risk of COVID-19 antivirals in natural aquatic environments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

During the COVID-19 period, industrial production was slowed or halted due to COVID restrictions and lockdowns, followed by global tensions and conflicts, which created uncertainties for industrial production. Similarly, during this period, the growth in carbon emissions was seen shrinking. However, it is greatly important to explore whether this shrinking trend will continue or whether a new growth pattern could emerge. Considering this, the research was carried out to investigate the relationship between green innovation initiatives and environmental regulations in the process of environmental management and environmental performance in the industrial sector. To do so, the survey-based research methodology using PLS-SEM was adopted, and data was gathered from 279 managers working in the equipment manufacturing industry. Our empirical findings revealed that environmental regulation and green innovation efforts strengthen decarbonization efforts, which further improve environmental management and environmental performance. The mediating role of decarbonization efforts was found to be prominent among green process innovation, environmental management and environmental performance. Moreover, decarbonization serves as a mediator between green product innovation and environmental management. In contrast, we could not verify that decarbonization mediates the relationship between green product innovation and environmental performance. The key findings are greatly important and provide a fresh roadmap for environmental management in the post-COVID era., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The study aimed to investigate the PM 2.5 variations in different periods of COVID-19 control measures in Northern Taiwan from Quarter 1 (Q1) 2020 to Quarter 2 (Q2) 2021. PM 2.5 sources were classified based on long-range transport (LRT) or local pollution (LP) in three study periods: one China lockdown (P1), and two restrictions in Taiwan (P2 and P3). During P1 the average PM 2.5 concentrations from LRT (LRT-PM 2.5 - P1 ) were higher at Fuguei background station by 27.9% and in the range of 4.9-24.3% at other inland stations compared to before P1. The PM 2.5 from LRT/LP mix or pure LP (Mix/LP-PM 2.5 - P1 ) was also higher by 14.2-39.9%. This increase was due to higher secondary particle formation represented by the increase in secondary ions (SI) and organic matter in PM 2.5-P1 with the largest proportion of 42.17% in PM 2.5 from positive matrix factorization (PMF) analysis. A similar increasing trend of Mix/LP-PM 2.5 was found in P2 when China was still locked down and Taiwan was under an early control period but the rapidly increasing infected cases were confirmed. The shift of transportation patterns from public to private to avoid virus infection explicated the high correlation of the increasing infected cases with the increasing PM 2.5 concentrations in Northern Taiwan were either increased (P1 and P2) or decreased (P3) during the COVID-19 pandemic depending on control measures, source patterns and meteorological conditions.2.5-P3 was observed in P3 with the PM 2.5 biases of ∼45% at all the stations when China was not locked down but Taiwan implemented a semi-lockdown. The contribution of gasoline vehicle sources in PM 2.5 was reduced from 20.3% before P3 to 10% in P3 by chemical signatures and source identification using PMF implying the strong impact of strict control measures on vehicle emissions. In summary, PM 2.5 concentrations in Northern Taiwan were either increased (P1 and P2) or decreased (P3) during the COVID-19 pandemic depending on control measures, source patterns and meteorological conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The article is the first to employ a quantile vector autoregression (QVAR) to identify the connectedness between geopolitical risks and energy volatility from January 1, 2015, to April 03, 2023. This paper is also the first to examine the mediating roles of uncertain events like the COVID-19 pandemic and the Russia-Ukraine conflict on this interlinkage. Dynamic connectedness is 29% in the short term and approximately 6% in the long term. Dynamic net total directional connectedness over a quantile also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and negative changes (below the 20% quantile). In the short term, the geopolitical risks remained net receivers of shock, but they turned into net shock transmitters during 2020 in the long term. Clean energy, in the short term, transmits shocks to other markets, and it plays the same role in the long term. Crude oil was a net receiver of shocks during COVID-19 and turned into a net transmitter of shocks in early 2022. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or the Russia-Ukraine conflict influence the dynamic interlinkages between geopolitical risks and renewable energy volatility and change their roles in the designed system. These findings are critical since they help authorities develop effective policies to lessen the vulnerabilities of these indicators and minimize how widely the renewable and non-renewable energy market is exposed to risk or uncertainty., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The aim of this paper is to examine the return connectedness and multiscale spillovers between the Clean Energy Index and the grain commodity market around COVID-19. Using daily data from January 4, 2017 to July 1, 2022, a time-varying parametric vector autoregressive (TVP-VAR) connectedness approach is first used to reveal connectedness patterns before and during COVID-19. We further used Baruník and Křehlík (2018)'s frequency domain spillover method to assess connectedness in different domain horizons. Our results show spillover effects over time and frequency, with COVID-19 significantly affecting the connectedness of the whole system. Dynamic connectedness peaks significantly after sudden bursts of COVID-19, validating the reported uncertainty. We also documented higher spillover levels in the short term than in the medium and long term. In addition, We find that (i) most clean energy indices are positively affected by the COVID-19 outbreak; (ii) the NASDAQ OMX Bio/Clean Fuels Index and NASDAQ OMX Geothermal Index send spillovers to all grain commodities throughout the sample period, while the WilderHill Clean Energy Index and NASDAQ OMX Wind Energy Index indices are the largest recipients of spillovers from other markets regardless of time horizon; (iii) the OMX Bio/Clean Fuels and OMX Geothermal Energy indices dominate spillover shocks to grain commodity markets. This is the first study to analyse the connectedness and time-frequency dynamics of returns in the green energy index and the grain commodity market. These results provide valuable insights to investors and key policymakers, especially at a time of more significant uncertainty., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The COVID-19 pandemic, geopolitical risks and net-zero targets have created not only pressures but incentives for energy investors. The renewable energy has become the largest energy sector and provided significant investment opportunities. However, companies operating in this sector are highly risky due to economic and political barriers. Therefore, it is of crucial importance for investors to properly assess the risk-return dynamics of these investments. This paper examines the risk-return characteristics of clean energy equities at a disaggregate level using a battery of performance metrics. The main results provide evidence of significant heterogeneity across clean energy sub-sectors; for instance, fuel cell and solar stocks display higher downside risks than the others, while the developer/operator equities are the least risky. The findings further provide evidence of higher risk-adjusted returns during the coronavirus pandemic; as an example, energy management companies appear to provide the highest risk-adjusted returns in the wake of the COVID-19. Comparing the performance with traditional sectors, clean energy stocks outperform certain sectors, including dirty assets. These findings offer important implications for investors, portfolio managers, and policy makers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

To mitigate aviation's carbon emissions of the aviation industry, the following steps are vital: accurately quantifying the carbon emission path by considering uncertainty factors, including transportation demand in the post-COVID-19 pandemic period; identifying gaps between this path and emission reduction targets; and providing mitigation measures. Some mitigation measures that can be employed by China's civil aviation industry include the gradual realization of large-scale production of sustainable aviation fuels and transition to 100% sustainable and low-carbon sources of energy. This study identified the key driving factors of carbon emissions by using the Delphi Method and set scenarios that consider uncertainty, such as aviation development and emission reduction policies. A backpropagation neural network and Monte Carlo simulation were used to quantify the carbon emission path. The study results show that China's civil aviation industry can effectively help the country achieve its carbon peak and carbon neutrality goals. However, to achieve the net-zero carbon emissions goal of global aviation, China needs to reduce its emissions by approximately 82%-91% based on the optimal emission scenario. Thus, under the international net-zero target, China's civil aviation industry will face significant pressure to reduce its emissions. The use of sustainable aviation fuels is the best way to reduce aviation emissions by 2050. Moreover, in addition to the application of sustainable aviation fuel, it will be necessary to develop a new generation of aircraft introducing new materials and upgrading technology, implement additional carbon absorption measures, and make use of carbon trading markets to facilitate China's civil aviation industry's contribution to reduce climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The rapid urban development, the Agenda 2030, the climate change adaptation and the COVID 19 crisis highlight the need to increase investment in public infrastructure and improve water supply and sanitation services. For this, an alternative to traditional public procurement is the participation of the private sector under the public-private partnership (PPP) model. The objective of this article is to develop a tool based on critical success factors (CSFs) that allows for evaluation during early stages of the convenience of developing a PPP project for W&S in urban areas of Latin America and the Caribbean. The index was developed based on literature review (779 variables), review of cases (20 variables) and expert opinion to assign them an estimated value of importance. The results were analysed by exploratory and confirmatory factor analysis, selecting 17 main variables grouped into 6 CSFs, the most relevant of which are Convenience, Certainty, Leadership, Attraction, Performance and Reliability. The application of this index allows an early assessment of the feasibility of a PPP project and/or the selection of the alternatives with the best chances of success. On the other hand, this study contributes to the international discussion on the most relevant elements related to the success of PPP in W&S projects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Natural resource governance is inherently complex owing to the socio-ecological systems in which it is embedded. Working arrangements have been fundamentally transformed throughout the COVID-19 pandemic with potential negative impacts on trust-based social networks foundational to resource management and transboundary governance. To inform development of a post-pandemic new-normal in resource management, we examined trust relationships using the Laurentian Great Lakes of North America as a case study. 82.9% (n = 97/117) of Great Lakes fishery managers and scientists surveyed indicated that virtual engagement was effective for maintaining well-established relationships during the pandemic; however, 76.7% (n = 89/116) of respondents indicated in-person engagement to be more effective than virtual engagement for building and maintaining trust. Despite some shortcomings, virtual or remote engagement presents opportunities, such as: (1) care and nurturing of well-established long-term relationships; (2) short-term (1-3 years) trust maintenance; (3) peer-peer or mentor-mentee coordination; (4) supplemental communications; (5) producer-push knowledge dissemination; and, if done thoughtfully, (6) enhancing diversity, equity, and inclusion. Without change, pre-pandemic trust-based relationships foundational to cooperative, multinational, resource management are under threat., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Understanding whether and how wildfires exacerbate COVID-19 outcomes is important for assessing the efficacy and design of public sector responses in an age of more frequent and simultaneous natural disasters and extreme events. Drawing on environmental and emergency management literatures, we investigate how wildfire smoke (PM 2.5 ) impacted COVID-19 infections and deaths during California's 2020 wildfire season and how public housing resources and hospital capacity moderated wildfires' effects on COVID-19 outcomes. We also hypothesize and empirically assess the differential impact of wildfire smoke on COVID-19 infections and deaths in counties exhibiting high and low social vulnerability. To test our hypotheses concerning wildfire severity and its disproportionate impact on COVID-19 outcomes in socially vulnerable communities, we construct a county-by-day panel dataset for the period April 1 to November 30, 2020, in California, drawing on publicly available state and federal data sources. This study's empirical results, based on panel fixed effects models, show that wildfire smoke is significantly associated with increases in COVID-19 infections and deaths. Moreover, wildfires exacerbated COVID-19 outcomes by depleting the already scarce hospital and public housing resources in local communities. Conversely, when wildfire smoke doubled, a one percent increase in the availability of hospital and public housing resources was associated with a 2 to 7 percent decline in COVID-19 infections and deaths. For California communities exhibiting high social vulnerability, the occurrence of wildfires worsened COVID-19 outcomes. Sensitivity analyses based on an alternative sample size and different measures of social vulnerability validate this study's main findings. An implication of this study for policymakers is that communities exhibiting high social vulnerability will greatly benefit from local government policies that promote social equity in housing and healthcare before, during, and after disasters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Household food management behavior changed considerably during the COVID-19 pandemic. A growing body of work has quantified the impact of lockdowns on household food waste. Yet, previous studies used a retrospective study design which undermines the accuracy of the causal effect on household food waste. This paper investigates the causal impact of the COVID-19 pandemic on household food management and food waste using a natural experiment approach. Using two large national-scale longitudinal data sets (n = 8157), this study quantifies the impact of COVID-19 on food waste and food behavior of Australian households. Propensity score matching (PSM) was carried out to address potential endogeneity issues and to select control and treatment groups for analysis. Findings reveal that Australian households reduced food waste by 9% on average in 2020 (during COVID-19) compared to the pre-pandemic (2019) level. The use of a grocery list, discount purchases, and 'just-in-case' purchases, and food refrigeration have recorded a marked increase during the pandemic compared to pre-pandemic times. The changes to food management and food discard behavior during the pandemic offer important insights for behavior change campaigns to reduce household food waste. Interventions to sustain good food planning and storage practices and involving food retailers are promising entry points in addressing household food waste. The study also highlights the considerable challenge in achieving SDG 12.3 target by 2030., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Lockdowns enforced amid the pandemic facilitated the evaluation of the impact of emission reductions on air quality and the production regime of O 3 under NOx reduction. Analysis of space-time variation of various pollutants (PM10, PM2.5, NOx, CO, O 3 and VOC or TNMHC) through the lockdown phases at eight typical stations (Urban/Metro, Rural/high vegetation and coastal) is carried out. It reveals how the major pollutant (PM10 or PM2.5 or O 3 , or CO) differs from station to station as lockdowns progress depending on geography, land-use pattern and efficacy of lockdown implementation. Among the stations analyzed, Delhi (Chandnichowk), the most polluted (PM10 = 203 μgm -3 ; O 3  = 17.4 ppbv) in pre-lockdown, experienced maximum reduction during the first phase of lockdown in PM2.5 (-47%), NO 2 (-40%), CO (-37%) while O 3 remained almost the same (2% reduction) to pre-lockdown levels. The least polluted Mahabaleshwar (PM10 = 45 μgm -3 ; O 3  = 54 ppbv) witnessed relatively less reduction in PM2.5 (-2.9%), NO 2 (-4.7%), CO (-49%) while O 3 increased by 36% to pre-lockdown levels. In rural stations with lots of greenery, O 3 is the major pollutant attributed to biogenic VOC emissions from vegetation besides lower NO levels. In other stations, PM2.5 or PM10 is the primary pollutant. At Chennai, Jabalpur, Mahabaleshwar and Goa, the deciding factor of Air Quality Index (AQI) remained unchanged, with reduced values. Particulate matter, PM10 decided AQI for three stations (dust as control component), and PM2.5 decided the same for two but within acceptable limits for stations. Improvement of AQI through control of dust would prove beneficial for Chennai and Patiala; anthropogenic emission control would work for Chandani chowk, Goa and Patiala; emission control of CO is required for Mahabaleshwar and Thiruvanathapuram. Under low VOC/NOx ratio conditions, O 3 varies with the ratio, NO/NO 2 , with a negative (positive) slope indicating VOC-sensitive (NOx-sensitive) regime. Peak O 3 isopleths as a function of NOx and VOC depicting distinct patterns suggest that O 3 variation is entirely non-linear for a given NOx or VOC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Quality air to breathe is the basic necessity for an individual and in recent times, emission from various sources caused by human activities has resulted in substantial degradation in the air quality. This work focuses to study the inadvertent effect of COVID-19 lockdown on air pollution. Pollutants' concentration before- and during- COVID-19 lockdown is captured to understand the variation in air quality. Firstly, multi-pollutant profiling using hierarchical cluster analysis of pollutants' concentration is performed that highlights the differences in the cluster compositions between before- and during-lockdown time periods. Results show that the particulate matter (PM 10 and PM 2.5 ) in air that formed the primary cluster before lock-down, came down to close similarity with other clusters during lockdown. Secondly, predicting air quality index (AQI) based on the forecasts of pollutants' concentration is performed using neural networks, support vector machine, decision tree, random forest, and boosting algorithms. The best-fitted models representing AQI is identified separately for before- and during-lockdown time periods based on its predictive power. While deterministic method reactively evaluates present AQI when current pollutants' concentration at a particular time and place are known, this study uses the best fitted data-driven model to determine future AQIs based on the forecasts of pollutant's concentration accurately (overall RMSE<0.1 for before lockdown scenario and <0.3 for during lockdown scenario). The study contributes to visualize the variation in pollutants' concentrations between the two scenarios. The results show that the reduced economic activities during lockdown period had led to the drop in concentration of PM 10 and PM 2.5 by 27% and 50% on an average. The findings of this study have practical and societal implications and serve as a reference mechanism for policymakers and governing bodies to revise their actions plans for regulating individual air pollutants in the atmospheric air., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Although net-zero greenhouse gas emission targets continue to gather burgeoning streams of research, there is a lacuna in current literature on the pathway challenges towards operationalizing decarbonization. The study advanced 2 × 2 matrix of an organizing framework of challenges in accomplishing net-zero emissions targets. Using the global airline industry as an illustrative context, the study provided deep insights on the pivotal industry, institutional, and organizational challenges in the era of COVID-19 such as fleet modernization, over-reliance on fossil fuel, slow progress in the development of hydrogen and electric aircraft, risk of corporate greenwashing, and divergent approaches adopted by airlines. The challenges can be classified into policy-oriented, organization-specific, and external/macro-environment factors. The contributions to theory and practices were identified and examined., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The abundance of synthetic polymers has become an ever-increasing environmental threat in the world. The excessive utilization of plastics leads to the accumulation of such recalcitrant pollutants in the environment. For example, during the COVID-19 pandemic, unprecedented demand for personal protective equipment (PPE) kits, face masks, and gloves made up of single-use items has resulted in the massive generation of plastic biomedical waste. As secondary pollutants, microplastic particles (<5 mm) are derived from pellet loss and degradation of macroplastics. Therefore, urgent intervention is required for the management of these hazardous materials. Physicochemical approaches have been employed to degrade synthetic polymers, but these approaches have limited efficiency and cause the release of hazardous metabolites or by-products into the environment. Therefore, bioremediation is a proper option as it is both cost-efficient and environmentally friendly. On the other hand, plants evolved lignocellulose to be resistant to destruction, whereas insects, such as wood-feeding termites, possess diverse microorganisms in their guts, which confer physiological and ecological benefits to their host. Plastic and lignocellulose polymers share a number of physical and chemical properties, despite their structural and recalcitrance differences. Among these similarities are a hydrophobic nature, a carbon skeleton, and amorphous/crystalline regions. Compared with herbivorous mammals, lignocellulose digestion in termites is accomplished at ordinary temperatures. This unique characteristic has been of great interest for the development of a plastic biodegradation approach by termites and their gut symbionts. Therefore, transferring knowledge from research on lignocellulosic degradation by termites and their gut symbionts to that on synthetic polymers has become a new research hotspot and technological development direction to solve the environmental bottleneck caused by synthetic plastic polymers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Most studies have explored the Covid-19 outbreak by mainly focusing on restrictive public policies, human health, and behaviors at the macro level. However, the impacts of built and socio-economic environments, accounting for spatial effects on the spread at the local levels, have not been thoroughly studied. In this study, the relationships between the spatial spread of the virus and various indicators of the built and socio-economic environments are investigated, using Florida ZIP-code data on accumulated cases before large-scale vaccination campaigns began in 2021. Spatial regression models are used to account for the spatial dependencies and interactions that are core factors in Covid-19 spread. This study reveals both the spillover dynamics of the coronavirus spread at the ZIP code level and the existence of spatial dependencies among the unobserved variables represented by the error term. In addition, the findings show a positive association between the expected number of Covid-19 cases and specific land uses, such as education facilities and retail densities. Finally, the study highlights critical socio-economic characteristics causing a substantial increase in Covid-19 spread. Such results could help policymakers, public health experts, and urban planners design strategies to mitigate the spread of future Covid-19-like diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

In the post-COVID scenario, the annual increase in plastic waste has taken an upsurge due to the disposal of plastic masks, gloves and other protective equipment. To reduce the plastic load ending up in landfills and oceans or dumped at roadsides, the potential of using plastic polymers in different sectors has been investigated over the years leading to their potential application in pavement laying, concrete industry, fuel generation and production of carbon-based compounds among which activated carbons (AC) is a prime example. As one of the most recommended adsorbents for removing contaminants from water and adsorbing greenhouse gases, AC creates a potential sector for using discarded plastic to further treat pollutants and approach closer to a circular economy for plastics. This paper analyses the production process, the effect of production parameters on AC characteristics and properties that aid in adsorption. The interdependence of these factors determines the surface area, porosity, relative micropore and mesopore volume, thereby defining the utility for removing contaminant molecules of a particular size. Furthermore, this work discusses the application of AC along with a summary of the earlier works leading to the existing gaps in the research area. Production costs, formation of by-products including toxic substances and adsorbate selectivity are the major issues that have restricted the commercial application of this process towards its practical use. Research aimed at valorization of plastic waste into ACs would minimize the solid waste burden, along with treating other pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Recent years have witnessed a landmark shift in global food prices due to the frequency of extreme weather events caused by temperature anomalies as well as the overlapping risks of COVID-19. Notably, the threat posed by temperature anomalies has spread beyond agricultural production to all aspects across food supply and demand channels, further amplifying volatility in food markets. Exploring trends in global food prices will give nations early warning signs to ensure the stability of food market. Accordingly, we utilize the Distributed Lag Non-Linear Model (DLNM) to simultaneously establish the exposure-lag-response associations between global temperature anomalies and food price returns in two dimensions: "Anomaly Degree" and "Response Time". Meanwhile, we also examine the cumulative lagged effects of temperature anomalies in terms of different quantiles and lag times. Several conclusions have been drawn. First, global food price returns will continue to decrease when the average temperature drops or rises slightly. While it turns up once the average temperature rises more than 1.1 °C. Second, major food commodities are more sensitive to temperature changes, and their price returns may also trend in a directional shift at different lags, with the trend in meat price being more particular. Third, food markets are more strongly affected in the case of extreme temperature anomalies. Many uncertainties still exist regarding the impact of climate change on food markets, and our work serves as a valuable reference for international trade regulation as well as the creation of dynamic climate risk hedging strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Green bonds are becoming increasingly important in sustainable investments since their environmental protection attributes allow them to benefit from environmental degradation. However, the mechanism of environmental degradation on green bonds has not yet been studied. This study proposes a mediation model to analyze air pollution's influence on green bonds. Theoretically, air pollution leads to increased public concern through public environmental awareness and perceptions of physical health risks. Enhanced public concern drives investors' green preference and environmental responsibility, thus expanding green bond demand, in which public concern plays an important mediation role. To verify the mediating effect, causal stepwise regression and bootstrap methods are used. The empirical results confirm this theoretical mechanism. Air pollution is significantly positively related to public concern. Public concern is positively linked with green bond investment willingness, resulting in increased volatility. The total positive effect of air pollution on green bonds is partly absorbed by the mediating effect of public concern that is significantly positive and reaches 30.21% of the total effect. In addition, major crisis events (e.g., COVID-19) may hinder the positive mediation process by generating a negative trend and distracting the public. This means that the government could propose appropriate measures to minimize the negative aspects in order to promote green finance. The mediation model is also useful for investors wishing to increase green assets in their portfolios and provides an incentive for businesses to promote green finance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Under the strict control measures, China has achieved phased victory in combating with the COVID-19, production activities have gradually returned to normal. This paper examined whether air pollution was rebounded or realized green recovery in the post-COVID-19 era with a dataset of weather normalized pollutant concentrations using difference-in-differences models. Results showed that air pollution experienced a significant decline due to the wide range of control measures. With entering the post-epidemic period, air pollution raised due to the orderly production resumption. Specifically, production resumption increased the PM 2.5 concentrations of lockdown cities and non-lockdown cities by 43.2% (22.3 μg/m 3 ) and 35.9% (17.3 μg/m 3 ) compared with that in the period of COVID-19 breakout. Although the economic activities of China have been gradually recovered, PM 2.5 concentrations were 8.8-11.2 μg/m 3 lower than the level of pre-epidemic period. In addition, the environmental effects varied across cities. With the process of production resumption, the PM 2.5 concentrations of cities with higher GDP, higher secondary industry output, more private cars and higher export volume rebounded less. Most developed cities realized green recovery by economy growth and air quality improvement, such as Beijing and Shanghai. While cities with heavy industry reflected pollution rebound with slow economy recovery, such as Shenyang and Harbin. Understanding the environmental effects of control measure and production resumption can provide crucial information for developing epidemic recovery policies and dealing with pollution issues for both China and other countries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The usage of disposable face mask to control the spread of COVID-19 disease has led to the alarming generation of a huge amount of plastic waste in a short span of time. On other hand, face masks are made of high-quality thermoplastic polymers that could be recovered and converted into valuable products. The aim of this study is to investigate a complementary approach for the recycling of face mask in lab-scale plants: the mechanical recycling of the filter in polypropylene (PP) and the chemical recycling of the whole face mask. For this purpose, a new designed surgical face mask was chemically and physically characterized. The results shows that the face mask was composed of 92.3 wt% high grade PP (filter), very similar to virgin PP but with a high melt volume index (MVI, 385 cm 3 /10 min) due to its non-woven manufacturing. The PP from face mask was mixed with recycled virgin PP in order to obtain a MVI suitable for the extrusion process and recycled as filament for 3D printing. This filament was used to print a specimen with a very similar visual quality of that printed with a commercial PP filament. Simultaneously, the whole face mask underwent a pyrolysis process to produce new feedstocks or fuels. Low-cost catalysts derived from coal fly ash (CFA) were employed to enhance the production of light hydrocarbons. In particular, the synthetized acid X zeolite (HX/CFA) improved the yield of light fractions up to 91 wt% (79 wt% for thermal pyrolysis) and the quality of the light oil with the 85% of C 6 -C 10 (55% for thermal pyrolysis). Furthermore, HX/CFA decreased the degradation temperature of PP to 384 °C versus 458 °C of thermal cracking., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Due to the extensive manufacturing and use of brominated flame retardants (BFRs), they are known to be hazardous, bioaccumulative, and recalcitrant pollutants in various environmental matrices. BFRs make flame-resistant items for industrial purposes (textiles, electronics, and plastics equipment) that are disposed of in massive amounts and leak off in various environmental matrices. The consumption of plastic items has expanded tremendously during the COVID-19 pandemic which has resulted into the increasing load of solid waste on land and water. Some BFRs, such as polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecane (HBCDs), are no longer utilized or manufactured owing to their negative impacts, which promotes the utilization of new BFRs as alternatives. BFRs have been discovered worldwide in soil, sludge, water, and other contamination sources. Various approaches such as photocatalysis-based oxidation/reduction, adsorption, and heat treatment have been found to eradicate BFRs from the environment. Nanomaterials with unique properties are one of the most successful methodologies for removing BFRs via photocatalysis. These methods have been praised for being low-cost, quick, and highly efficient. Engineered nanoparticles degraded BFRs when exposed to light and either convert them into safer metabolites or completely mineralize. Scientific assessment of research taking place in this area during the past five years has been discussed. This review offers comprehensive details on environmental occurrence, toxicity, and removal of BFRs from various sources. Degradation pathways and different removal strategies related to data have also been presented. An attempt has also been made to highlight the research gaps prevailing in the current research area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Wastewater monitoring as a public health tool is well-established and the SARS-CoV-2 (COVID-19) pandemic has seen its widespread uptake. Given the significant potential of wastewater monitoring as a public health surveillance and decision support tool, it is important to understand what measures are required to allow the long-term benefits of wastewater monitoring to be fully realized, including how to establish and/or maintain public support. The potential for positive SARS-CoV-2 detections to trigger enforced, community-wide public health interventions (e.g., lockdowns and other impacts on civil liberties) further emphasises the need to better understand the role of public engagement in successful wastewater-based monitoring programs. This paper systematically reviews the processes of building and maintaining the social license to operate wastewater monitoring. We specifically explore the relationship between different stakeholder communities and highlight the information and actions that are required to establish a social license to operate and then prevent its loss. The paper adds to the literature on social license to operate by extending its application to new domains and offers a dynamic model of social license to help guide the agenda for researcher and practitioner communities., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The sorting of Construction and Demolition (C&D) waste is a critical step to linking the recycling system and to the macro prediction, which helps to promote the development of the circular economy. Moreover, the effective classification and automated separation process will also help to stop the spreading of pathogenic organisms, such as virus and bacteria, by minimizing human intervention in the sorting process, while also helping to prevent further contamination by COVID-19 virus. This study aims to develop an efficient method to sort C&D waste through deep learning combined with knowledge transfer approach. In this paper, CVGGNet models, that is four VGG structures (VGGNet-11, VGGNet-13, VGGNet-16, and VGGNet-19), based on knowledge transfer combined with the technology of data augmentation and cyclical learning rate, are proposed to classify ten types of C&D waste images. Results show that 2.5 × 10 -4 , 1.8 × 10 -4 , 0.8 × 10 -4 , and 1.0 × 10 -4 are the optimum learning rate for CVGGNet-11, CVGGNet-13, CVGGNet-16, and CVGGNet-19, respectively. Knowledge transfer helped shorten the training time from 1039.45 s to 991.05 s, and while it improved the performance of the CVGGNet-11 model in training, validation, and test datasets. The average training time increases as the number of the layers in the CVGGNet architecture rises: CVGGNet-11 (991.05 s) ˂ CVGGNet-13 (1025.76 s) ˂ CVGGNet-16 (1090.48 s) ˂ CVGGNet-19 (1337.81 s). Compared to other CVGGNet models, CVGGNet-16 showed an excellent performance in various C&D waste types, in terms of accuracy (76.6%), weighted average precision (76.8%), weighted average recall (76.6%), weighted average F1-score (76.6%) and micro average ROC (87.0%). In addition, the t-distributed Stochastic Neighbor Embedding (t-SNE) approach can reduce the dataset to a lower dimension and distinctly separate each type of C&D waste. This study demonstrates the good performance of CVGGNet models that can be used to automatically sort most of the C&D waste, paving the way for better C&D waste management., (Copyright © 2022. Published by Elsevier Ltd.)

This paper examines and projects the water use and wastewater generation during and after the SARS-CoV-2 (COVID-19) in China, and discussed the water use/wastewater generation pattern changes among different sectors. Existing studies on the impact of pandemic spread-prevention measures on water consumption and wastewater treatment during the pandemic are reviewed. The water use and wastewater discharge in China through the COVID-19 period are then projected and analyzed using Multivariate Linear Regression. The projection is carried out for years 2019-2023 and covers an (estimated) full process of pre-pandemic, pandemic outbreak, and recovery phase and provides essential information for determining the complete phase impact of the COVID-19. Two scenarios, i.e. the recovery scenario and the business as usual scenario, are set to investigate the water use and wastewater generation characteristics after the pandemic. The results imply that in both scenarios, the water use in China shows a V-shaped trend from 2019 to 2023 and reached a low point in 2020 of 5,813✕10 8  m 3 . The wastewater discharge shows an increasing trend throughout the COVID period in both scenarios. The results are also compared with the water consumption and wastewater generation during the SARS-CoV-1 period. The implication for policymakers is the possible increase of water use and wastewater discharge in the post COVID period and the necessity to ensure the water supply and control of water pollution and wastewater discharge., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The impact of the SARS-CoV pandemic has gone well beyond health concerns, reaching the maritime industry. The study on the environmental impact of shipping industry during COVID-19 pandemic can provide useful insights to propose new management policies regarding shipping operations, both in-port and on the route. We present a case study centred in the Port of Barcelona covering a 30 nautical miles range in the period March to July 2020, during which different levels of restrictions and stringent lockdown measures were enforced. In this paper, we assess the impact of COVID-19 on maritime traffic and its related emissions in port cities using real-time Automatic Identification System (AIS) data. Interestingly, results show that the decline in maritime traffic is not correlated with a decrease in maritime emissions due to changes in vessel operation. During lockdown (March to June 2020), we observed a 27.9% reduction in the number of port calls compared to the pre-lockdown scenario, whereas pollutant emissions show a moderate decrease (1.8% for CO 2 ), no significant reduction (SO 2 and PM) or a slight increase (1.3% for NO x ). This can be directly assigned to changes in vessel operation mode, i.e. vessels switched from Underway to At Anchor or Moored status, during which auxiliary engines are used at higher loads., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Hospitals release significant quantities of wastewater (HWW) and biomedical waste (BMW), which hosts a wide range of contaminants that can adversely affect the environment if left untreated. The COVID-19 outbreak has further increased hospital waste generation over the past two years. In this context, a thorough literature study was carried out to reveal the negative implications of untreated hospital waste and delineate the proper ways to handle them. Conventional treatment methods can remove only 50%-70% of the emerging contaminants (ECs) present in the HWW. Still, many countries have not implemented suitable treatment methods to treat the HWW in-situ. This review presents an overview of worldwide HWW generation, regulations, and guidelines on HWW management and highlights the various treatment techniques for efficiently removing ECs from HWW. When combined with advanced oxidation processes, biological or physical treatment processes could remove around 90% of ECs. Analgesics were found to be more easily removed than antibiotics, β-blockers, and X-ray contrast media. The different environmental implications of BMW have also been highlighted. Mishandling of BMW can spread infections, deadly diseases, and hazardous waste into the environment. Hence, the different steps associated with collection to final disposal of BMW have been delineated to minimize the associated health risks. The paper circumscribes the multiple aspects of efficient hospital waste management and may be instrumental during the COVID-19 pandemic when the waste generation from all hospitals worldwide has increased significantly., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The impact investing literature largely focuses on private equity investing and overlooks the investments made through debt financing that actually dominate the market. To address this research gap, this paper investigates whether impact financing is associated with financial benefits. By using COVID-19 as an exogenous shock to China's stock market, this paper applies fixed effects panel data analysis with a difference-in-differences research design to provide robust empirical outcomes. The results reveal those financial institutions that better integrated environmental impacts into their financing process experienced positive stock return changes in response to the shock. This study answers the question of how well an impact scales. The findings suggest that impact financing is an effective model, as the impacts incorporated in the debt can be scaled up compared to impact investing funds with low volumes. Impact financing has enormous potential for financial institutions to engage in the green transition since they can derive pecuniary utility while delivering environmental impacts. The revelation of financial benefits also contributes to overcoming the lack of knowledge about impact financing and helps to remove the barriers that advance industry growth. • This paper studies whether impact financing is associated with financial benefits. • Financial firms that better integrate environmental impact in financing have positive stock return changes during COVID-19. • Financial firms can derive pecuniary utility from pursuing impact financing. • The findings suggest that impact financing can be an effective model to bring impact to a substantial scale. [ABSTRACT FROM AUTHOR]