Abstract

Microplastics pose a severe threat to marine ecosystems; however, relevant mathematical modeling and analysis are lacking. This paper formulates two stoichiometric producer-grazer models to investigate the interactive effects of microplastics, nutrients, and light on population dynamics under different settings. One model incorporates optimal microplastic uptake and foraging behavior based on nutrient availability for natural settings, while the other model does not include foraging in laboratory settings. We establish the well-posedness of the models and examine their long-term behaviors. Our results reveal that in natural environments, producers and grazers exhibit higher sensitivity to microplastics, and the system may demonstrate bistability or tristability. Moreover, the influences of microplastics, nutrients, and light intensity are highly intertwined. The presence of microplastics amplifies the constraints on grazer growth related to food quality and quantity imposed by extreme light intensities, while elevated phosphorus input enhances the system’s resistance to intense light conditions. Furthermore, higher environmental microplastic levels do not always imply elevated microplastic body burdens in organisms, as organisms are also influenced by nutrients and light. We also find that grazers are more vulnerable to microplastics, compared to producers. If producers can utilize microplastics for growth, the system displays significantly greater resilience to microplastics.

Introduction

Plastic pollution has steadily increased due to widespread plastic use, insufficient disposal practices, and limited waste management capacity over decades. Plastic wastes discharged into terrestrial and aquatic habitats are considered a serious threat to biodiversity, due to their resistance to decomposition (Gall and Thompson, 2015, Carbery et al., 2018). The small plastic particles, ranging from 0.1 to 5 mm in size, are called microplastics (EFSA Panel on Contaminants in the Food Chain (CONTAM), 2016). Microplastics are observed almost in all aquatic habitats (Eerkes-Medrano et al., 2015, Peeken et al., 2018). Chronic exposure to microplastics presents several challenges for aquatic organisms (Cui et al., 2017, Duis and Coors, 2016, Nolte et al., 2017, Zhang et al., 2017, Khoironi et al., 2019, Sjollema et al., 2016, Besseling et al., 2014).

Studies have shown that microplastics can be absorbed, concentrated, and transported into various organisms, such as algae. This process significantly hampers algal growth, chlorophyll levels, and photosynthetic activity (Cao et al., 2022, Liu et al., 2019, Chae et al., 2019, Wu et al., 2021, Jiao et al., 2022, Gray and Weinstein, 2017, Zhang et al., 2017, Sjollema et al., 2016, Yang et al., 2020, Ferguson, 2011, Wang et al., 2020, Khoironi et al., 2019, Rodrigues et al., 2019, Salman et al., 2016). This inhibition may occur due to physical factors, such as the blockage of light and airflow (Bhattacharya et al., 2010, Wang et al., 2020, Salman et al., 2016, Bhattacharya et al., 2010), or interactions between microplastics and algae, including adsorption, aggregation (Zhang et al., 2017), and the destruction of algal cell walls through surface absorption (Liu et al., 2019). However, it is worth noting that some laboratory studies suggest that certain algae species may increase in the presence of smaller-sized microplastics, possibly because microplastic particles can be utilized as substrates for the growth of algae (Yokota et al., 2017, Mao et al., 2018, Jiao et al., 2022, Canniff and Hoang, 2018).

Discussion

Microplastics can be mistakenly ingested or adhere to the surfaces of marine organisms, resulting in significant adverse effects (Zhang et al., 2017, Liu et al., 2019, Sazli et al., 2023, Gregory, 1996, Derraik, 2002, Blarer and Burkhardt-Holm, 2016, Alomar et al., 2017). This paper presents two stoichiometric models to investigate population dynamics in the presence of microplastics in both field and laboratory settings. The interactive effects of light, nutrients, and microplastics on population dynamics have been rigorously studied.

For natural ecosystems, the OMUF model reveals complex dynamics. When the microplastic concentration is relatively low, the behavior of the system is strongly influenced by the initial conditions and can exhibit bistability or tristability. Conversely, when microplastics in the environment become excessively abundant, the only outcome is the extinction of grazers. Furthermore, the tolerance to microplastics of the producer-grazer system described in OMUF model (3.5) is significantly lower, compared to that of the system defined in NM model (2.11). This discrepancy potentially arises from the fact that in the natural ecosystem, grazers have to face more challenges and pay significant feeding costs, such as food scarcity, nutrient deficiencies, predation risk, multiple toxins, and human impact, making them more susceptible to microplastics.

Extreme light condition, either too low or too high, restricts the growth of grazers. When light intensity is excessively low, producers can only survive at low densities due to weakened photosynthesis, and grazers go extinct because of insufficient food. When light intensity is excessively high, the P:C ratio in producers becomes very low, and grazers go extinct due to nutrient deficiency. However, when light intensity falls within a moderate range, coexistence of both species may occur, and the system demonstrates a greater ability to withstand microplastics.

Abstract

     Globally, to ensure food security bio-based fertilizers must replace a percentage of chemical fertilizers. Such replacement must be deemed sustainable from agronomic and greenhouse gas (GHG) emission perspectives. For agronomic performance several controlled protocols are in place but not for testing GHG emissions. Herein, a pre-screening tool is presented to examine GHG emissions from bio-waste as fertilizers. The various treatments examined are as follows: soil with added mineral nitrogen (N, 140 kg N ha−1) fertilizer (MF), the same amount of MF combined with dairy processing sludge (DS), sludge-derived biochar produced at 450 °C (BC450) and 700 °C (BC700) and untreated control (CK). These treatments were combined with Danish (sandy loam) or Irish (clay loam) soils, with carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions and soil inorganic-N contents measured on selected days. During the incubation, biochar mitigated N2O emissions by regulating denitrification. BC450 reduced N2O emissions from Danish soil by 95.5% and BC700 by 97.7% compared to emissions with the sludge application, and for Irish soil, the N2O reductions were 93.6% and 32.3%, respectively. For both soils, biochar reduced CO2 emissions by 50% as compared to the sludge. The lower N2O reduction potential of BC700 for Irish soil could be due to the high soil organic carbon and clay content and pyrolysis temperature. For the same reasons emissions of N2O and CO2 from Irish soil were significantly higher than from Danish soil. The temporal variation in N2O emissions was correlated with soil inorganic-N contents. The CH4 emissions across treatments were not significantly different. This study developed a simple and cost-effective pre-screening method to evaluate the GHG emission potential of new bio-waste before its field application and guide the development of national emission inventories, towards achieving the goals of circular economy and the European Green Deal.

Introduction

     Agricultural sources of greenhouse gas (GHG) emissions crucially influence climate change. During the period from 2007 to 2016, GHG emissions from agriculture, forestry and land use contributed about 23% of total net anthropogenic emissions, and emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) from agriculture accounted for 13%, 44% and 81% of the anthropogenic emissions, respectively (IPCC et al., 2019). In November 2016 the legally binding international treaty on climate change called the Paris Agreement was adopted by 195 Parties. The key messages of the Paris Agreement include 1) limiting global warming to well below 2 °C, preferably to 1.5 °C, compared to pre-industrial levels; 2) establishing climate resilience and mitigating GHG emissions without threatening food production; and 3) aligning financial flows with pathways for low GHG emissions and climate-resilient development (UNFCCC, 2015). Therefore, the reduction of GHG emissions from agricultural soils with new effective mitigation strategies within the framework of the Paris Agreement becomes vital for the achievement of global warming reduction goals.

Conclusions

     Addition of biochar from pyrolysis of dairy sludge (DS) to soils together with mineral N fertilizer instead of directly adding DS, substantially reduced emissions of N2O to a level near that of untreated soil. Biochar pyrolyzed at 450 °C (BC450) reduced emissions of N2O by 95.5% and CO2 by 59.4% when applied to a Danish sandy loam soil (DA), and from an Irish clay loam soil (IR), emissions were reduced by 93.6% and 57.1%, respectively. Biochar from 700 °C pyrolysis (BC700) suppressed 97.7% and 49.7% of N2O and CO2 emissions from DA soil, and 32.3% and 62.4% from IR soil. Biochar shows no effect on CH4 emissions. Pyrolysis conditions and soil properties significantly affect the suppression of N2O emissions by biochar. This study provides a simple and cost-effective tool to examine the GHG emission potential of bio-waste before applying it in agricultural lands and helps in developing national emission inventories.

Abstract

     This work suggests an optimal strategy to sort and recycle plastic waste as a renewable energy resource with maximizing economic feasibility and mitigating environmental pollution. To derive the optimal sorting and recycling strategies of plastic waste, a novel optimization model is developed; it calculates the overall profit by subtracting the profit of recycling plastic from the total annualized cost. Then the model is used to identify the optimal strategy to sort and recycle plastic waste as a renewable energy resource in mixed-integer nonlinear programming that maximizes the overall profit. In the derived optimal sorting and recycling strategy, high-density polyethylene is recycled to produce downgrade plastic; low-density polyethylene, polypropylene, and polystyrene are recycled as pyrolysis oil; and polyethylene terephthalate is recycled to produce refuse plastic fuel. The derived optimal case can significantly increase the overall profit by about 3,137% (i.e., 35 US$/1 kg of recycled plastic), and 492% (i.e., 29 US$/1 kg of recycled plastic) compared to conventional case in South Korea and Japan respectively.

Introduction

     The demand for plastics has rapidly increased in many industries because of their versatility, and easy production. Consequently, plastic waste is discharged in massive quantities; estimates of plastic waste discharged into rivers, lakes, and seas is 9–23 million t per year globally (Borrelle et al., 2020; Masuda et al., 2001). Thus, the importance of plastic waste recycling is increasing (Shah et al., 2015; Zhang et al., 2020). Plastic waste is a mixture of different types, so it must be sorted into before it is recycled (Gundupalli et al., 2017; Hearn and Ballard, 2005; Lim and Cho, 2003). Economically-viable sorting and recycling of plastic will yield a cheap and abundant source of valuable chemicals and renewable energy (Gadaleta et al., 2020). However, current systems to sort and recycle plastic waste are not optimized, so their costs are high. Thus, only 27.2 wt% of plastic waste is recycled, whereas 36.4 wt% is landfilled, and 36.4 wt% is incinerated (Vieira et al., 2022). Therefore, the soil and air pollution according to the landfilled plastic and the significant amount of SOx, NOx, and CO2 emitted in the incineration of waste plastic is serious. The types of recycled plastic have different uses depending on the product (e.g., downgrade plastic, pyrolysis oil, and refuse plastic fuel) that is produced (Kim et al., 2020; Krauklis et al., 2021; Shaha et al., 2020; Yaqoob et al., 2021). Methods to recycle plastic waste are classified into material, chemical, and thermal types (Zhuo and Levendis, 2014). They have very different capital and operating costs according to the throughput of the plastic waste of each method (Huang et al., 2002). Therefore, to improve plastic waste recycling, it is crucial to derive optimal sorting and recycling strategy for plastic waste that indicate which plastics will be sorted to be recycled and how the plastic will be recycled according to each recycling method considering economic feasibility.

Conclusion

     This study found an optimal strategy to sort and recycle plastic waste as a renewable energy resource for maximizing economic feasibility and mitigation of environmental pollution caused by landfilled plastic and air pollutants according to incineration of plastic. This study makes two major contributions to the literature. First, to the best of the author’s knowledge, it is the first attempt to optimize the plastic waste sorting and recycling system by deriving an optimal sorting and recycling strategy to improve the recycling of for plastic waste as a renewable energy resource maximizing economic feasibility and mitigating of environmental pollution. Also, the results allow us to increase the recycling of plastic waste by maximizing the overall profit of the plastic waste sorting and recycling system. In the derived optimal sorting and recycling strategy, HDPE is recycled to produce downgrade plastic; LDPE, PP and PS are recycled as pyrolysis oil; and PET is recycled to produce refuse plastic fuel. The derived optimal case can increase overall profit by ∼ 3,137% compared to CCS, and 492% compared to CCJ, and also emission of air pollutants. Thus, this study provides valuable insight into the many recycling industries of waste plastics to achieve clean production, cost-effectiveness, and environmental protection. In many literatures, strategies such as operating condition optimization were proposed to reduce the cost of each sorting method. Thus, in further study, it is crucial to consider the detailed proposed strategies in deriving the optimal solution to maximize economic feasibility.

Highlights

Abstract

Graphical abstract

Keywords

1. Introduction

2. Methods used to conduct the mini-review

3. Composition of healthcare waste

4. Persistence rate of COVID-19 virus and its possible transmission through healthcare solid waste

5. Waste management strategies during the COVID-19 pandemic

6. Challenges

7. Potential for healthcare solid waste management strategies

8. Conclusions

Funding

Ethical approval

CRediT authorship contribution statement

Declaration of competing interest

Acknowledgments

References

Abstract

Healthcare waste comprises the waste generated by healthcare facilities, medical laboratories and biomedical research facilities. Improper treatment of this waste poses serious risks of disease transmission to waste pickers, waste workers, health workers, patients, and the community in general through exposure to infectious agents. Poor management of the waste emits harmful and deleterious contaminants into society. However, contamination of highly contagious agents such as the COVID-19 virus has created enormous instability in healthcare waste handling and subsequent recycling because of the volume of the waste generated and its contagious nature. Several countries have adopted safety measures to combat this contamination and manage healthcare waste; however, these measures are insufficient and vary depending on the context of the country. In addition, the WHO has set out guidelines for management of healthcare waste. These guidelines are helping to manage the highly contagious healthcare waste resulting from the current pandemic. Proper healthcare waste management may add value by reducing the spread of the COVID-19 virus and increasing the recyclability of materials instead of sending them to landfill. Disinfecting and sorting out healthcare waste facilitates sustainable management and allows their utilization for valuable purposes. This review discusses the different healthcare solid waste management strategies practiced in different countries, the challenges faced during this management, and the possible solutions for overcoming these challenges. It also provides useful insights into healthcare solid waste management scenarios during the COVID-19 pandemic and a possible way forward.

1. Introduction

After radiation waste, healthcare waste is considered the second most hazardous waste globally. It includes various forms of waste, both hazardous and non-hazardous, such as sharps, human body parts, blood, chemical waste, pharmaceutical waste, and medical devices (Rodriguez-Morales, 2013). All of this waste is produced mainly by hospitals, primary care facilities, laboratories, mortuaries, autopsy centers, laboratories, blood banks, nursing homes, and other medical locations (Pepin et al., 2014). It is generated during diagnosis, treatment, immunization of humans or animals, research, or the production or testing of biologicals. If not properly handled, it can have devastating effects on human health (Johannessen et al., 2000). During any infectious disease outbreak, the waste generated from healthcare facilities increases exponentially; as a result, special care must be taken by management in order to avoid troubling impacts (Ramteke and Sahu, 2020).

The outbreak of coronavirus disease 2019 (COVID-19) has arisen from the SARS-CoV-2 virus, which causes an acute respiratory disease (Mol and Caldas, 2020; WHO, 2019; WHO, 2020b); it was first reported in Wuhan, China (Wang et al., 2020) in December 2019. It has been acknowledged as a Public Health Emergency of International Concern (PHEIC) (Wilder-Smith and Osman, 2020), and the virus has spread to almost all countries across the globe. The pandemic continues to be a significant public health threat worldwide. The rapid increase in the number of COVID-19 infected patients and the highly transmissible nature of the disease have led to a high number of hospitalizations.

It is well known that Asia generates and receives large quantities of plastic waste. Through a detailed study of plastic waste generation and trade, the management and treatment of plastic waste in Asia were analyzed from the regional perspective. The amounts of plastic waste in municipal solid waste and in industrial solid waste were estimated to be 79 Mt and 42 Mt, respectively, in Asia. The overall treatment and recycling status in Asia are unsatisfactory. Asia imported 74% of the plastic waste in the world in 2016, and China (mainland) imported the most plastic waste until 2017, with 5.8 to 8.3 Mt. In 2017, about half the plastic waste imported by Asia came from other regions, and after subtracting the exported quantity, 98% of the plastic waste was left in Asia for treatment and disposal. The plastic waste imported by Asia declined about 72% in monetary value in 2018. There is still a large gap between the plastic waste quantity imported to Asia and that exported from Asia. China’s ban of plastic waste imports caused import quantities to drop to 52 kt in 2018, simultaneously, exports from the largest exporting countries or regions such as Hong Kong (China), the USA, Japan, and Germany decreased. While Vietnam, Malaysia and some other Asian countries and regions saw significant increases in plastic waste imports from 2016 to 2018. Considering this situation, countries in Asia are starting to strictly limit plastic waste imports from other countries.

1. Introduction

Plastics, with their remarkable properties, have become a major commodity on a global scale, and are now present in almost all types of commercial products. Global production of resins and fibers increased from 2 Mt in 1950 to 380 Mt in 2015 (Geyer et al., 2017). However, the use of plastics has also brought adverse environmental impacts associated with their production and disposal. It was reported that the world generated 242 Mt of plastic waste in 2016 (Kaza and Yao, 2018). From 1950 to 2015, an estimated total of 6.30 billion tons of plastic waste was generated, with only 9% recycled, leaving more than 80% to accumulate in landfills or in the natural environment (Brooks et al., 2018). Plastic waste now makes up the majority of marine litter. Under ultraviolet light from the sun, plastic is degrading into plastic fragments or even ‘‘microplastics” that are almost impossible to recover and that are disrupting food chains and degrading natural habitats (NOAA, 2017).

The heavy metals present in sludge are very harmful to the environment and the human body. It is necessary to remove them before sludge disposal. In this study, an ex situ method for removing heavy metals from sludge using electroosmosis was designed, and experiments were conducted to study the effects of electroosmosis voltages (30 V, 40 V and 50 V), citric acid concentrations (0.03 mol/kg, 0.06 mol/kg, 0.09 mol/kg and 0.12 mol/kg) and the power supply (continuous and interrupted) on the removal rate of heavy metals (Cu, Cr, Cd, Zn and Pb). The study found that the combination of the citric acid pretreatment and electroosmosis can effectively improve the removal rate of heavy metals. An appropriate increase in the voltage and citric acid concentration can improve the removal rate of heavy metals. The best combination was determined to be 40 V and 0.09 mol/kg. Under these conditions, the removal rates of Cu, Cr, Cd, Zn and Pb, were 14.39%-41.28% (continuous power supply) and 21.78%-42.36% (interrupted power supply). The interrupted power supply effectively improved the removal rates of Cd and Zn but reduced the removal rates of Cr and Pb. The power supply mode had no significant effect on the removal rate of Cu. Heavy metal speciation was analyzed by the BCR method, and the relationship between the ratio of easily removed metal speciation and the removal rate was studied. The increase in the ratio of easily removed speciation was accompanied by an increase in the removal rate, indicating that citric acid and electroosmosis increased the removal rate by increasing the ratio of easily removed speciation. However, the high pH value around the cathode caused by the electrochemical reaction was not conducive to the removal of heavy metals.

Introduction

Sewage sludge, a byproduct of sewage treatment processes, is rich in nitrogen (N), phosphorus (P), potassium (K) and organic matter. It is a popular practice to dispose of sewage sludge via land use, and many countries currently use this method. However, it can be difficult to convince the government and land users to agree on this method because of the presence of toxic metals and bacteria in the sludge. Therefore, it is necessary to separate the heavy metals from the sludge [1,2]. The methods for the removal of heavy metals from sludge are chemical extraction, electrokinetic remediation, filtration, ion exchange, adsorption on activated carbon, membrane technologies, microbiological leaching, phytoremediation, etc. [3-9]. The electrokinetic process aims to remove the heavy metals using an electric field, which promotes several complex mechanisms such as electrodialysis electric migration, electrophoresis, and electrolysis. This approach is conducive to the transportation of pollutants [10,11]. These effects cause the heavy metals to concentrate around the cathode, which allows for their removal. The advantages of electrokinetic remediation are that it is simple (i.e., simple equipment), flexible (i.e., can be used for in situ or ex situ treatments), relatively inexpensive, effective and environmentally friendly [12,13].

The current Australian sugarcane industry transition towards adoption of an ‘alternative’ herbicide strategy as part of improved environmental stewardship is increasingly complicated by recent farming system, regulatory and herbicidal product changes. This study quantified and compared the efficacy, economic costs and environmental risk profile s of a range of established, emerging, and recently registered pre -emergent herbicides across field trials in the Wet Tropics region of North Queensland. Several herbicides were effective on certain weed species, but lacked broad spectrum control. Better efficacy results from products with multiple active ingredients (i.e., imazapic -hexazinone) demonstrated the benefits of using mixtures of active ingredients to widen the spectrum of weed control efficacy. All tested pre – emergent herbicides behaved quite similarly in terms of their propensity for off-site movement in water (surface runoff losses generally > 10 % of active applied), with their losses largely driven by their application rate . Herbicides with lower application rates consistently contributed less to the total herbicide loads measured in surface runoff. Results demonstrated alternative choices from the more environmentally problematic herbicides (such as diuron) are available with effective alternative formulations providing between 4 and 29 less risk than the traditional diuron -hexazinone ‘full rate’. However, considerable challenges still face canegrowers in making cost -effective decisions on sustainable herbicide selection. Additional research and effective grower extension are required to address information gaps in issues such as specific weed control efficacy of alternative herbicides and potential blending of some herbicides for more effective broad spectrum weed control, while also minimizing environmental risks.

Introduction

The decline of fresh and marine water quality associated with land -based runoff from adjacent agricultural catchments is a major cause of the poor state of many of the coastal ecosystems of Australia’s Great Barrier Reef (GBR) World Heritage Area (Waterhouse et al., 2017). Pesticides have been specifically identified as among the most important diffus e source pollutants from catchment areas of the GBR (Brodie et al., 2012). High value freshwater, estuarine and inshore waters of the GBR lagoon are regularly exposed to pesticide runoff from agricultural lands, particularly during wet season riverine flood events (December to April) (e.g. Lewis et al., 2009 ; Davis et al., 2012). The pesticides that have been most commonly detected in the GBR lagoon are herbicides that inhibit electron transport at photosystem II (PSII) in plants and include diuron, atrazine, hexazinone, ametryn, simazine and tebuthiuron (Haynes et al., 2000a ; Shaw and Müller, 2005 ; Shaw et al., 2010). Concentrations during elevated stream flow events can at times exceed ecological water quality protection guideline trigger values for up to several weeks for some of these PSII herbicides (Lewis et al., 2009 ; 2012 ; Brodie et al., 2012 ; Davis et al., 201 3 ; O’Brien et al., 2016; Novic et al., 2018).

In sugarcane crops, several agricultural pesticides are applied simultaneously, and a set of these can be detected in groundwater and surface waters, characterizing a contamination by pesticides mixtures with different concentrations in these bodies of water. Thus, the aim of this work is to estimate the gray water footprint of the pesticide mixture (herbicides) used in a dystrophic Yellow Ultisol in a sugarcane cultivation system, in Pernambuco, Brazil, based on the toxicity of each pesticide used in the mixture. For this objective, the model proposed by Paraiba et al. (2014) was used, where the gray water footprint is determined by physicochemical characteristics of the soil and pesticides, the pesticide application rates (dose), and the lowest value of the effective mean dose of these substances in a population of organisms (EC50). The gray water footprint of the pesticide mixture was 1.32
105 m3 ha1 . The highest volumes of gray water and higher ranks of the mixture were due to Amicarbazone and Hexazinone, with 1.05
105 m3 ha1 (r ¼ 5) and 3.71
104 m3 ha1 (r ¼ 4.6), respectively, and the lowest values were due to Paraquat and Glyphosate, with gray water footprint of 1.64 and 8.43 m3 ha1 , respectively. The gray water footprint for the yield of the sugarcane crop was estimated at 1731.1 m3 t 1 , considered a high value for the gray water footprint of the sugarcane, demonstrating how much this crop can demands water resources to dilute its load of contaminants.

Introduction

There is currently a strong and unavoidable commitment to protecting water and its natural characteristics, as well as the fulfillment of human needs, such as: obtaining food in quantity and quality, fibers, fossil fuels, biofuels and biomass, industry, among others. Moreover, the global production of biological energy resources is expanding and accelerating the growth of agricultural production. As a consequence of these demands, water scarcity represents a major commercial and environmental concern worldwide (Popp et al., 2014). In the agricultural sector, the increased use of technology to produce food, fiber and fuel, for example, has contributed greatly to the productivity gains of agricultural crops (Brodt et al., 2011). However, the inappropriate use of these same technologies as, for example, pesticides, could jeopardize the developments observed in the Agricultural sector (Damalas and Eleftherohorinos, 2011). About the sugarcane culture, Brazil is the world’s largest sugarcane producer, being responsible together with India, for more than half of the production of this commodity on the world. Despite the relevance of the sugarcane crop and its economic results for Brazil in terms of trade balance and also GDP, it is necessary to take into account the environmental aspects resulting from the cultivation of this crop. Studies have shown that the sugarcane crop has negatively impacted the environmental compartments, as well as its biotic and abiotic components (Liboni and Cezarino, 2012; Pignati et al., 2017).

In this paper, the spatial-temporal characteristics of green travel behavior in public bike-sharing system are studied. From the vector perspective, a coarse graining method of green travel direction is proposed, the methods and steps of analyzing the spatial characteristics and temporal window of green travel behavior are established, which opens up new horizons in the study of green travel behavior, develop the existing coarse granulation methods and temporal network theory, and provides a new way of route optimization and high-frequency task window recognition for the dynamic rebalancing scheme. At the same time, we conduct an empirical analysis by the travel data of the public bike-sharing system in Nanjing from March 20, 2017 to March 26, 2017, and verify the dynamic spatial characteristics and timevarying of green travel behavior based on vector perspective.

Introduction

As a sustainable, efficient, economical, flexible and environmentally friendly transportation mode, public bike has become an increasingly powerful way to alleviate the last-mile problem. Around the world, public bike-sharing system has been operated in about 1500 cities at present (Ahmadreza et al., 2017; Haider et al., 2018), and green travel behavior has been widely concerned by scholars (Si et al., 2019). Travel data records green travel behavior in time and space, and contains a large amount of potentially valuable information. The improvement of data acquisition and analysis of public bike system promotes the research of green travel behavior. In order to capture the characteristics of green travel behavior, travel speed (Jensen et al., 2010), travel time (Jappinen et al., 2013), the gendered travel behavior (Zhao et al., 2015), travel type (Bordagaray et al., 2016), trip chains (Zhang et al., 2018) and spatial structure (Boss et al., 2018) are studied. At the same time, the relationships between green travel behavior and site selection (Wang et al., 2016), the sustainability and efficient functioning of cities (Bullock et al., 2017), dynamic repositioning (Zhang et al., 2017), built environments (Liu and Lin, 2019), job accessibility (Pritcharda et al., 2019) are analyzed according to the spatial-temporal characteristics of the data. Spatial-temporal characteristics are the eternal research theme of the objective world. Although there are many literatures on green travel behavior, the researches focus on spatial-temporal characteristics by travel data are limited, and there are some imperfections: 1) spatial characteristics are mostly based on statistical pattern (Zhao et al., 2015; Wang et al., 2016; Zhang et al., 2018; Boss et al., 2018), and lack of dynamic analysis from the vector perspective; 2) temporal characteristics are mostly based on artificial time windows with equal intervals (Wang et al., 2016; Bordagaray et al., 2016; Pritcharda et al., 2019), and lack of high frequency temporal windows which are based on dynamic spatial characteristics to describe green travel behavior with tidal phenomena (Chardon et al., 2016).

Vehicle routing problem (VRP) research has recently improved dramatically to simulate more real-life circumstances. Nevertheless, the typical VRP models proposed have been isolated from the most important factor determining the success of the VRP plan on the ground, i.e. the human factor (driver). Thus, this research investigates the effect of drivers’ behaviours on the optimal VRP plan by integrating the level of autonomy of both planner and drivers as represented by risk-taking parameters. To enhance the model configuration’s practicability, the concept of ‘ridesharing’ e which has been introduced before e has also been integrated to expand the logistical services, improve customer satisfaction, and compensate for shortages in service. Moreover, to ensure environmentally-friendly logistical practices, a velocity maximisation policy and environmental penalty enforcement on the chosen velocity range have been considered. In general, the model improves drivers’ satisfaction, customers’ perceived quality, and the firm’s financial objectives. Additionally, it achieves a better supply chain strategic fit by planning at the three levels: strategic, tactical, and operational. A numerical example was solved using the Eclipse Java 2018-09 solver through two heuristic methods, the Greedy and the Intra-route neighborhood heuristic, and both revealed the same near-optimal solutions. Sensitivity analyses showed that the resulting insignificant increase in the VRP costs due to assigning autonomy for drivers is still reasonable, and the total costs’ objective function weight has an insignificant effect on the total near-optimal solution, while that of the energy consumption objective function has the largest impact.

Introduction

One of the most popular applications of operation research science is the VRP, which was defined by Clarke and Wright (1964) as serving customer networks distributed at different geographic points, using fleets of trucks from different capacities. VRP-related studies have exponentially grown by around 6% per year in the research literature (Eksioglu et al., 2009). Furthermore, VRP has grasped its importance due to its wide usage in logistic and transportation aspects. Moreover, the literature has concentrated on different variants related to VRP, in which scholars set models and solutions for many real-life problems to control difficulties associated with different stages of transportation, such as travel times, pick-up and delivery time windows, and information input (Braekers et al., 2016). Paraskevopoulos et al. (2017) stated that the routing and scheduling planning processes confront some challenges in allocating scarce resources for certain services. On the other hand, the VRP topic has been widely analysed due to its impact on various industries (Lahyani et al., 2017). Based on a taxonomic review related to the VRP topic during the period 2009e2015, it was revealed that the literature focused on some important VRP aspects, and different models were suggested to solve the problems of different objectives, including the capacitated VRP, periodic VRPs, the VRP with time windows, and others (Braekers et al., 2016). Additionally, a very crucial aspect that considerably affects the near-optimal results required for such a VRP case is augmenting the human factor in VRP models.

Studying the impact of a carbon tax on household demand can be relevant in terms of securing public acceptance of a carbon tax and clarifying the implications for policy design. This paper aims to fill a gap in the academic literature by simulating carbon tax scenarios and estimating distributional effects of the tax on household welfare, income inequality, and poverty rates based on household consumption in Thailand. The study employs a microsimulation model incorporating the economy-wide effects of the tax on prices and consumers’ behavioral responses to changes in prices. The results indicate that a carbon tax is progressive in Thailand under revenue-recycling scenarios by expanding social transfer programs. When carbon tax revenues are recycled through pensions for elderly people, the carbon tax could reduce the poverty rate and improve the welfare of households in the lowest quintile. The results imply that the distributional impacts of environmental taxes could result in favorable outcomes for income inequality and poverty reduction in developing countries.

Introduction

The importance of mitigation policies in resolving energy and climate problem has become obvious around the world over the past few decades. Thailand submitted its intended nationally determined contributions (INDCs) proposal in October 2015, outlining a plan to reduce its greenhouse gas emissions by 2030. The choice of mitigation mechanisms to achieve climate mitigation targets will impose policy challenges in terms of the policies’ effectiveness and sustainability. The use of market-based mechanisms, such as carbon pricing, has long been a strategy to reduce carbon emissions in developed countries. This approach has been receiving more attention in developing countries in recent years. Following the Paris Agreement in 2015, experts from the International Monetary Fund recommended the use of carbon taxes to fulfill INDC plans in developing economies (Farid et al., 2016). Singapore proposed a plan to impose a carbon tax in 2019, which will be the first national carbon tax introduced in Southeast Asia. Nurdianto and Resosudarmo (2016) recommended implementing a carbon tax in Association of Southeast Asian Nations (ASEAN) countries as an effective mechanism to reduce carbon emissions and a corrective measure for energy price distortions (e.g., heavy energy subsidies in some ASEAN countries). Energy subsidies can worsen the wealth gap, and poorer people tend to receive fewer subsidies than richer people, for example, in China (Chen, 2017). A carbon tax can be an instrument for policy reform to narrow the wealth gap. Compared to cap-and-trade, which is another carbon pricing mechanism, a carbon tax is easier to implement because it can rely on existing administrative energy tax structures and does not require the establishment of an emission trading market under cap-and-trade, which is nascent in most developing countries.

In an era of increased stakeholder pressure for sustainable environmental management practices at workplace, organization should adopt and implement environmental ethics for seamless synergy amongst the needs of the business, the society, and the planet. Our study used resource-based view (RBV) and dynamic capabilities (DC) theoretical lenses to examine hypotheses derived from extant literature on the linkages amongst environmental ethics, environmental training, environmental performance and competitive advantage. Using survey questionnaire, we employed structural equation modeling (SEM) on 364 valid responses from managers to examine the hypotheses. The findings of our study will stir up researcher’s curiosity to unravel the human side of environmental management and that will surely steer future researches in significant directions. Results suggest that environmental ethics influences environmental training, environmental performance and competitive advantage. We also found that environmental training to employees mediates the influence of environmental ethics on firm’s environmental performance and competitive advantage. The findings of the study implies that organizational approach towards environmental ethical practices at workplace should be not be reactive but proactive with intentions to create and sustain synergy amongst the triads namely, profits, the society, and the environment. Environmental training should not be one-off event but a continuous process to beat competitions and improve environmental performance in the organization.

Introduction

The economic activities of firms always have other side to it – the ecological imbalance. Lately the firms have been witnessing greater stakeholders pressure to reduce the environmental impact created out of their business related activities (Longoni et al., 2018; Yu et al., 2017). As a result, firms are not only supposed to espouse environmental values to secure sustainable economic success (Tate and Bals, 2018) but they should view environmental management as measure of their ‘social performance’ (Short et al., 2016; Yawar and Seuring, 2017). That calls upon organizational leaders to be committed to environmental ethics through policy formulation and their implementation in day-today operations to reduce the environmental impact of business operations, if any (El-Kassar and Singh, 2018; Singh and El-Kassar, 2019). Several studies suggest that firm’s environmental performance depends upon their human resources’ sensitivity to environmental issues & possess specific green competencies related to core businesses for organizational usages in their value creation processes (El-Kassar and Singh, 2018; Guerci et al., 2016; Singh and El-Kassar, 2019). Therefore, we contemplate that the implementation of organizational intentions to ‘go green’ and manage environmental performance depends largely upon human resources across functions along with supportive HR systems & processes to effectively manage employee-related issues (Guerci et al., 2016; Nejati et al., 2017; Renwick et al., 2013). The extant literature also suggest for hiring candidates who demonstrate environmental knowledge and motivation (Jabbour et al., 2010) useful enough to enhance environmental performance as the later influences firm’s competitive advantage (Chuang and Huang, 2018; Famiyeh et al., 2018).