Biological Treatment of Triclosan using a Novel Strain of Enterobacter cloacae and Introducing Naphthalene Dioxygenase as an Effective Enzyme

In recent years, triclosan (TCS) has been widely used as an antibacterial agent in personal care products due to the spread of the Coronavirus. TSC is an emerging contaminant, and due to its stability and toxicity, it cannot be completely degraded through traditional wastewater treatment methods. In this study, a novel strain of Enterobacter cloacae was isolated and identified that can grow in high TCS concentrations. Also, we introduced naphthalene dioxygenase as an effective enzyme in TCS biodegradation, and its role during the removal process was investigated along with the laccase enzyme. The change of cell surface hydrophobicity during TCS removal revealed that a glycolipid biosurfactant called rhamnolipid was involved in TCS removal, leading to enhanced biodegradation of TCS. The independent variables, such as initial TCS concentration, pH, removal duration, and temperature, were optimized using the response surface method (RSM). As a result, the maximum TCS removal (97%) was detected at a pH value of 7 and a temperature of 32 °C after 9 days and 12h of treatment. Gas chromatography-mass spectrometry (GC/MS) analysis showed five intermediate products and a newly proposed pathway for TCS degradation. Finally, the phytotoxicity experiment conducted on Cucumis sativus and Lens culinaris seeds demonstrated an increase in germination power and growth of stems and roots in comparison to untreated water. These results indicate that the final treated water was less toxic.

Optimizing the synthesis of yeast Beta-glucan via response surface methodology for nanotechnology application.

BACKGROUND: The production of biopolymers from waste resources is a growing trend, especially in high-population countries like Egypt. Beta-glucan (ß-glucan) belongs to natural polysaccharides that are derived from plant and microbial origins. In this study, following increasing demands for ß-glucan owing to its bioactive properties, a statistical model to enhance microbial ß-glucan production was evaluated for its usefulness to the food and pharmaceutical industries. In addition, a trial to convert ß-glucan polymer to nanostructure form was done to increase its bioactivity. RESULTS: Ingredients of low-cost media based on agro-industrial wastes were described using Plackett-Burman and central composite design of response surface methodology for optimizing yeast ß-glucan. Minerals and vitamin concentrations significantly influenced ß-glucan yield for Kluyveromyces lactis and nitrogen and phosphate sources for Meyerozyma guilliermondii. The maximum predicted yields of ß-glucan recovered from K. lactis and M. guilliermondii after optimizing the medium ingredients were 407 and 1188 mg/100 ml; respectively. For the first time, yeast ß-glucan nanoparticles (ßGN) were synthesized from the ß-glucan polymer using N-dimethylformamide as a stabilizer and characterized using UV-vis spectroscopy, transmission electron microscope (TEM), dynamic light scattering (DLS) and Fourier transform infrared spectroscopy (FT-IR). The average size of ßGN was about 300 nm as determined by DLS. The quantitative variation of functional groups between ß-glucan polymer and ßGN was evaluated by FT-IR for explaining the difference in their biological activity against Normal Homo sapiens-Hela contaminant and Hepatic cancer cell lines. CONCLUSIONS: Enriching the low-cost media based on agro-industrial wastes with nutritional ingredients improves the yield of yeast ß-glucan. The present study succeeds to form ß-glucan nanoparticles by a simple method.

Estimating Moisture Content of Sausages with Different Types of Casings via Hyperspectral Imaging in Tandem with Multivariate

The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of treatment 19. Spectral pre-treatments were employed to enhance the model's robustness. The raw and pre-processed spectral data, as well as moisture content, were fitted to a regression model. The RSM outcomes showed that the interactive effects of [soy lecithin concentration] × [soy oil concentration] and [soy oil concentration] × [orange extract addition] on moisture were significant (p < 0.05), resulting in an R2 value of 78.28% derived from a second-order polynomial model. Hesperidin was identified as the primary component of the orange extracts using high-performance liquid chromatography (HPLC). The PLSR model developed from reflectance data after normalization and 1st derivation pre-treatment showed a higher coefficient of determination in the calibration set (0.7157) than the untreated data (0.2602). Furthermore, the selection of nine key wavelengths (405, 445, 425, 455, 585, 630, 1000, 1075, and 1095 nm) could render the model simpler and allow for easy industrial applications.

Optimization of Ultrasonic-Assisted Extraction of α-Glucosidase Inhibitors from Dryopteris crassirhizoma Using Artificial Neural Network and Response Surface Methodology.

Dryopteris crassirhizoma Nakai is a plant with significant medicinal properties, such as anticancer, antioxidant, and anti-inflammatory activities, making it an attractive research target. Our study describes the isolation of major metabolites from D. crassirhizoma, and their inhibitory activities on α-glucosidase were evaluated for the first time. The results revealed that nortrisflavaspidic acid ABB (2) is the most potent α-glucosidase inhibitor, with an IC50 of 34.0 ± 0.14 µM. In addition, artificial neural network (ANN) and response surface methodology (RSM) were used in this study to optimize the extraction conditions and evaluate the independent and interactive effects of ultrasonic-assisted extraction parameters. The optimal extraction conditions are extraction time of 103.03 min, sonication power of 342.69 W, and solvent-to-material ratio of 94.00 mL/g. The agreement between the predicted models of ANN and RSM and the experimental values was notably high, with a percentage of 97.51% and 97.15%, respectively, indicating that both models have the potential to be utilized for optimizing the industrial extraction process of active metabolites from D. crassirhizoma. Our results could provide relevant information for producing high-quality extracts from D. crassirhizoma for functional foods, nutraceuticals, and pharmaceutical industries.

Simultaneous removal of microplastics and benzalkonium chloride using electrocoagulation process: statistical modeling and techno-economic optimization.

Microplastics and benzyldimethyldodecylammonioum chloride (DDBAC) enter the environment more frequently during the COVID-19 pandemic and their co-occurrence will be a potential threat to the environment in the post-pandemic era. This study investigates the performance of an electrochemical system for the simultaneous removal of microplastics and DDBAC. During experimental studies, effects of applied voltage (3-15 V), pH (4-10), time (0-80 min), electrolyte concentration (0.01-0.0.09 M), electrode configuration, and perforated anode were investigated to identify their influence on DDBAC and microplastics removal efficiency. Eventually, the techno-economic optimization yielded to evaluate the commercial feasibility of this process. The central composite design (CCD) and analysis of variance (ANOVA) are employed for evaluation and optimization of the variables and response, DDBAC-microplastics removal, and for determining the adequacy and significance of mathematical models proposed by response surface methodology (RSM). Experimental results indicate that optimum conditions are pH = 7.4, time = 80 min, electrolyte concentration = 0.05 M, and applied voltage = 12.59, in which the removal of microplastics, DDBAC, and TOC reached the maximum level, which was 82.50%, 90.35%, and 83.60% respectively. The results confirm that the valid model is adequately significant for the target response. Overall, financial and energy consumption analyses confirmed that this process is a promising technology as a commercial method for the removal of DDBAC-microplastics complexes in water and wastewater treatment.

Optimization of gasification process parameters for COVID-19 medical masks using response surface methodology

Due to the COVID-19 pandemic, large amounts of medical wastes have been produced and their disposal has resulted in environmental and human health problems. This medical waste may include face masks, gloves, face shields, goggles, coverall suits, and other related wastes, such as hand sanitizer and disinfectant containers. To address this issue, the effect was investigated of gasification process parameters (type of COVID-19 medical mask based on the polypropylene ratio, pressure, steam ratio, and temperature) on hydrogen syngas and cold gas efficiency. The gasification model was developed using process modeling based on the Aspen Plus software. Response surface methodology with a 3k statistical factorial design was used to optimize the process aiming for the highest hydrogen yield and cold gas efficiency. Analysis of variance showed that both the steam ratio and temperature were significant parameters regarding the hydrogen yield and cold gas efficiency. Proposed models were constructed with very high accuracy based on their coefficient of determination (R2) values being greater than 0.97. The optimum conditions were: 65 % polypropylene in the mixture, a pressure of 1 bar, a steam ratio of 0.38, and a temperature of 900 °C, producing a maximum hydrogen yield of 40.61 % and cold gas efficiency of 81.43 %. These results supported the efficacy of the primary design for steam gasification using a mixture of plastic wastes as feedstock. The hydrogen could be utilized in chemical applications, whereas the efficiency could be used as a basis for further development of the process. © 2022 THE AUTHORS

Optimization of ultrasonication-assisted extraction conditions using RSM-I-Optimal experimental design to recover vitamin D2 and K1 from selected green leafy vegetable samples

This study employed the response surface methodology to optimize the extraction conditions for recovering vitamins D2 and K1 from green leafy vegetables using ultrasonication-assisted extraction. The vitamin content was determined using an Accucore C18 column and a UPLC-Q-ToF/MS method. An RSM-I-Optimal design was used for designing the experiment to find the best combination of solvent level (mL), sonication time (min), sonication frequency (kHz), and temperature (°C). The experimental data from a 25-sample set were fitted to a second-order polynomial equation using multiple regression analysis. The extraction models had R2 values of 0.895 and 0.896, respectively, and the probability values (p < 0.0001) indicated that the regression model was highly significant. The optimal extraction conditions were: solvent level of 65 mL, sonication time of 45 min, sonication frequency of 70 kHz, and temperature of 45 °C. Under these conditions, the predicted recovery (%) values for vitamins D2 and K1 were 90.7% and 90.4%, respectively. This study has the potential to use the reported extraction method for routine quantification of vitamins D2 and K1 in the laboratory using UPLC-Q-ToF/MS.

Enhanced Nasal Deposition and Anti-Coronavirus Effect of Favipiravir-Loaded Mucoadhesive Chitosan-Alginate Nanoparticles.

Favipiravir (FVR) is a repurposed antiviral drug for treating mild to moderate cases of the novel coronavirus disease 2019 (COVID-19). However, its poor solubility and permeability limit its clinical efficacy. To overcome its physicochemical and pharmacokinetic limitations, we statistically designed a mucoadhesive chitosan-alginate nanoparticles (MCS-ALG-NPs) as a new carrier for FVR using response surface methodology, which provided suitable characteristics for transmucosal delivery. The use of mucoadhesive polymers for intranasal administration promotes the residence time and contact of FVR in the mucus membrane. The optimized FVR-MCS-ALG-NPs demonstrated superior mucoadhesion, higher permeation and deposition in the nasal mucosa, and a significant increase in the inhibition of viral replication over 35-fold compared with free FVR. The overall results suggest that MCS-ALG-NPs could be used as an effective mucoadhesive carrier to enhance the activity of FVR against COVID-19.

Extraction of Lycopene from Tomato Using Hydrophobic Natural Deep Eutectic Solvents Based on Terpenes and Fatty Acids.

The present study proposes a green extraction approach for the recovery of lycopene from tomato fruits. Different hydrophobic natural deep eutectic solvents (HNADESs) based on terpenes (i.e., menthol and thymol) and fatty acids (i.e., decanoic acid and dodecanoic acid) were prepared at different molar ratios, characterised in terms of density, rheological properties, and Fourier transform-infrared (FT-IR) spectroscopy, and were examined for their effectiveness to extract lycopene from tomato. Response surface methodology (RSM) was employed to optimise the extraction parameters, namely duration (min) and solvent:solid ratio (v/w). Spectrophotometry and RP-HPLC-DAD were used in order to monitor the process efficiency. The combination of decanoic acid and dodecanoic acid was found to exhibit comparable extraction capacity to acetone. Taking into account that the HNADESs used in the present study are considered green, biodegradable and of low cost, the obtained carotenoid rich extracts are expected to be of use in industrial food applications.

Optimization of gasification process parameters for COVID-19 medical masks using response surface methodology

Due to the COVID-19 pandemic, large amounts of medical wastes have been produced and their disposal has resulted in environmental and human health problems. This medical waste may include face masks, gloves, face shields, goggles, coverall suits, and other related wastes, such as hand sanitizer and disinfectant containers. To address this issue, the effect was investigated of gasification process parameters (type of COVID-19 medical mask based on the polypropylene ratio, pressure, steam ratio, and temperature) on hydrogen syngas and cold gas efficiency. The gasification model was developed using process modeling based on the Aspen Plus software. Response surface methodology with a 3k statistical factorial design was used to optimize the process aiming for the highest hydrogen yield and cold gas efficiency. Analysis of variance showed that both the steam ratio and temperature were significant parameters regarding the hydrogen yield and cold gas efficiency. Proposed models were constructed with very high accuracy based on their coefficient of determination (R2) values being greater than 0.97. The optimum conditions were: 65% polypropylene in the mixture, a pressure of 1 bar, a steam ratio of 0.38, and a temperature of 900 °C, producing a maximum hydrogen yield of 40.61% and cold gas efficiency of 81.43%. These results supported the efficacy of the primary design for steam gasification using a mixture of plastic wastes as feedstock. The hydrogen could be utilized in chemical applications, whereas the efficiency could be used as a basis for further development of the process.

The First Optimization Process from Cultivation to Flavonoid-Rich Extract from Moringa oleifera Lam. Leaves in Brazil

Flavonoids are significant antioxidant and anti-inflammatory agents and have multiple potential health applications. Moringa oleifera is globally recognized for its nutritional and pharmacological properties, correlated to the high flavonoid content in its leaves. However, the bioactive compounds found in plants may vary according to the cultivation, origin, season, and extraction process used, making it difficult to extract reliable raw material. Hence, this study aimed to standardize the best cultivation and harvest season in Brazil and the best extraction process conditions to obtain a flavonoid-rich extract from M. oleifera as a final product. Firstly, ultrasound-assisted extraction (UAE) was optimized to reach the highest flavonoid content by three-level factorial planning and response surface methodology (RSM). The optimal cultivation condition was mineral soil fertilizer in the drought season, and the optimized extraction was with 80% ethanol and 13.4 min of extraction time. The flavonoid-rich extract was safe and significantly decreased reactive oxygen species (ROS) and nitric oxide (NO) in LPS-treated RAW 264.7 cells. Lastly, the major flavonoids characterized by HPLC-ESI-QTRAP-MS/MS were compounds derived from apigenin, quercetin, and kaempferol glycosides. The results confirmed that it was possible to standardize the flavonoid-rich extract leading to a standardized and reliable raw material extracted from M. oleifera leaves.

SPREAD PREDICTION OF COVID-19 IN ANDHRA PRADESH BASED ON ENVIRONMENTAL CHEMISTRY

COVID-19 had already spread throughout the world, and the novel coronavirus continues to pose a threat to the majority of countries. The current study uses the Susceptible-Exposed-Infectious-Recovered idea to assess the effects of social and economic factors, particularly the use of a medical mask, on the spread of COVID-19 in Andhra Pradesh. The influence of environmental parameters such as temperature and relative humidity on the number of COVID-19 cases per day is also investigated using numerical methods such as the Response surface methodology model. We provide the results of the curfew lockdown started by the Government of Andhra Pradesh for COVID-19, as compared to a total lockdown scenario. As a result of the irresponsibility and crowded gatherings, the number of cases increases, stretching the mitigation period of the second wave COVID-19 spread, prolonging the curve's straightening. The Susceptible-Exposed-Infectious-Recovered model's predictions have been put to the test in a number of real-world scenarios. The fast spread of second-wave COVID-19 cases in Indian cities is similarly connected to temperature, as indicated by the well function of higher temperatures in breaking the lipid layer of coronavirus, but is severely inhibited by the critical component of social distancing, leading to uncertainty. As a result, it's critical to incorporate environmental factors into epidemiological models like Susceptible-Exposed-Infectious-Recovered, as well as methodically design managed laboratory tests and modeling experiments to catch conclusive findings, assisting decision-makers and investors in developing comprehensive action plans to combat COVID-19's second wave. © 2022, Rasayan Journal of Chemistry, c/o Dr. Pratima Sharma. All rights reserved.

Research on Airflow Optimization and Infection Risk Assessment of Medical Cabin of Negative-Pressure Ambulance

Medical cabins within negative-pressure ambulances currently only use the front air supply, which causes poor emission of infectious disease droplets. For this problem, based on the classification and design methods of airflow organization, the side and top supply airflow organization model has been designed to study the influence of these airflow organization models on the spread of droplet particles. The distribution of droplet particles within airflow organization models, under conditions in which the patient is coughing and sneezing, is analyzed. According to the comparison and analysis of this distribution, the state of droplet particles, the emission efficiency, and the security coefficient are studied. The response surface method is used to optimize the emission efficiency and security coefficient of the airflow organization. According to the characteristics of the medical cabin within negative-pressure ambulances, a dose-response model is used to evaluate the infection risk of medical personnel and then the infection probability is obtained. These research results can be used to improve the ability of negative-pressure ambulances to prevent cross-infection.

Optimizing Procedures of Ultrasound-Assisted Extraction of Waste Orange Peels by Response Surface Methodology.

The simultaneous effects of three continuous factors: solvent concentration (50-100%), treated times (25-85 min), treated temperatures (25-55 °C), and two categorical factors: type of solvents (methanol or ethanol) and ultrasonic frequency (28 kHz or 40 kHz) on ultrasonic-assisted extraction yield from waste orange peels were evaluated and optimized by response surface methodology. Fourier Transform Infrared (FTIR) spectroscopy with a wavelength of 500 cm-1 to 4000 cm-1 was employed to rapidly identify the orange extracts. The significant polynomial regression models on crude extraction, sediments after evaporation, and precipitation yield were established (p < 0.05). Results revealed that solvent concentration affected crude extraction and precipitation yield linearly (p < 0.01). The optimal and practical ultrasound-assisted extraction conditions for increasing the precipitation yield were using 61.42% methanol with 85 min at 55 °C under 40 kHz ultrasonic frequency. The spectra of extracts showed a similar fingerprint of hesperidin.

Impact parameter evaluation of nano Al2O3 dielectric in wire cut-electrical release machining in a COVID-19 environment

The present paper focuses on wire electric discharge machine in a COVID-19 environment. It can be considered as an attempt to develop models of response variables, using different liquids, one of which is nanoparticle (Al2O3), in the use of a ratio of (2 mg) and the function of comparison. In both cases they are the rate of material removing, in the wire electric discharge machine process using the response surface methodology. The pilot plan is based on the concept of the Box-Behnken, and the study conveys the six main parameters. To evaluate the value of the advanced model, ANOVA was applied;the test results support the validity and suitability of the advanced RSM model. Optimum settings for the parameters are improved work safety in COVID-19 environments.

Development of Antioxidant and Nutritious Lentil (Lens culinaris) Flour Using Controlled Optimized Germination as a Bioprocess.

Germination is an efficient and natural strategy that allows the modification of the nutritional value and the nutraceutical properties of seeds, enabling one to tailor the process according to its final use. This study aimed at optimization of germination conditions to produce novel lentil flours with improved nutritional and functional features. Response Surface Methodology (RSM) was applied to model the effect of temperature (15-27 °C) and time (1-5 days) on different nutritional and quality parameters of lentil flours including proximate composition, content and profile of fatty acids, content of phytic acid, ascorbic acid and γ-aminobutyric acid (GABA), content and profile of phenolic compounds, antioxidant activity, expected glycemic index (GI) and color during germination. As shown by RSM polynomial models, sprouting promoted the reduction of phytic acid content and enhanced the levels of ascorbic acid, GABA, insoluble phenolic compounds, antioxidant activity and expected GI, and modified the color of the resultant lentil flours. RSM optimization of germination temperature and time using desirability function revealed that the optimal process conditions to maximize the nutritional, bioactive and quality properties of sprouted lentil flours were 21 °C for 3.5 days.

Green and Non-conventional Extraction of Bioactive Compounds from Olive Leaves: Screening of Novel Natural Deep Eutectic Solvents and Investigation of Process Parameters.

ABSTRACT: Olive leaf as an agricultural waste contains valuable bioactive compounds that are mainly used for pharmaceutical and cosmetic industries. Lately the major component, oleuropein, has gained extra attention due to the anti-viral activity against SARS-CoV-2 that causes Coronavirus disease (Covid-19). In this study, extraction of the bioactive compounds from olive leaves was conducted using a non-conventional and green method. New generation green solvents, natural deep eutectic solvents (NADES) were used in combination with ultrasound assisted extraction. Screening of NADES type, temperature, and particle size were investigated using one-pot-at-a-time method while, NADES amount and liquid-to-solid ratio were optimized using experimental design. The results were evaluated in terms of total polyphenol yield (YTP), total flavonoid yield (YTF) and antiradical activity (AAR). At the optimized conditions, the highest total polyphenol yield and the highest total flavonoid yield were achieved with choline chloride-fructose-water (CFW) (5:2:5) as 187.31 ± 10.3 mg gallic acid equivalent g-1 dw and 12.75 ± 0.6 mg apigenin equivalent g-1 dw, respectively. The extracts were also analyzed for oleuropein, caffeic acid and luteolin contents. The highest amount of oleuropein and caffeic acid were extracted by glucose-fructose-water (GFW) (1:1:11) as 1630.80 mg kg-1 dw and 112.77 mg kg-1 dw, respectively. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s12649-021-01411-3) contains supplementary material, which is available to authorized users.

Parameter setting of meta-heuristic algorithms: a new hybrid method based on DEA and RSM.

The parameter setting of meta-heuristic algorithms is one of the most effective issues in the performance of meta-heuristic algorithms and is usually done experimentally which is very time-consuming. In this research, a new hybrid method for selecting the optimal parameters of meta-heuristic algorithms is presented. The proposed method is a combination of data envelopment analysis method and response surface methodology, called DSM. In addition to optimizing parameters, it also simultaneously maximizes efficiency. In this research, the hybrid DSM method has been used to set the parameters of the cuckoo optimization algorithm to optimize the standard and experimental functions of Ackley and Rastrigin. In addition to standard functions, in order to evaluate the performance of the proposed method in real problems, the parameter of reverse logistics problem for COVID-19 waste management has been adjusted using the DSM method, and the results show better performance of the DSM method in terms of solution time, number of iterations, efficiency, and accuracy of the objective function compared to other.

Electrocatalytic Degradation of Levofloxacin, a Typical Antibiotic in Hospital Wastewater.

Presently, in the context of the novel coronavirus pneumonia epidemic, several antibiotics are overused in hospitals, causing heavy pressure on the hospital's wastewater treatment process. Therefore, developing stable, safe, and efficient hospital wastewater treatment equipment is crucial. Herein, a bench-scale electrooxidation equipment for hospital wastewater was used to evaluate the removal effect of the main antibiotic levofloxacin (LVX) in hospital wastewater using response surface methodology (RSM). During the degradation process, the influence of the following five factors on total organic carbon (TOC) removal was discussed and the best reaction condition was obtained: current density, initial pH, flow rate, chloride ion concentration, and reaction time of 39.6 A/m2, 6.5, 50 mL/min, 4‱, and 120 min, respectively. The TOC removal could reach 41% after a reaction time of 120 min, which was consistent with the result predicted by the response surface (40.48%). Moreover, the morphology and properties of the electrode were analyzed. The degradation pathway of LVX was analyzed using high-performance liquid chromatography-mass spectrometry (LC-MS). Subsequently, the bench-scale electrooxidation equipment was changed into onboard-scale electrooxidation equipment, and the onboard-scale equipment was promoted to several hospitals in Dalian.

Optimization of COVID-19 face mask waste fibers and silica fume as a balanced mechanical ameliorator of fat clay using response surface methodology.

The balanced amelioration of mechanical characteristics of fat clay with an additive refers to the attainment of high strength without compromising ductility, which is unattainable by solitary usage of a cementing additive. For this purpose, an amalgamated binary admixture (ABA) is proposed by assimilating shredded face mask (FM) waste, which is posing serious environmental concerns these days, with a cementitious waste material, i.e., silica fume (SF). However, for such ABA, the optimization of mix design is desirable because an excessive amount of one component could disturb the required balance. To address this issue, response surface methodology (RSM) is used in the current study, which is a strong technique used during the process of production to develop, improve, and optimize product inputs. Several experiments are designed and conducted to evaluate mechanical responses, i.e., unconfined compressive strength (qu), brittleness index (IB), deformability index (ID), and California bearing ratio (CBR) value, of treated fat clay by varying mix designs of ABA. Based on the test results, mathematical models are developed which are found to be statistically valid to predict the subjected responses using SF and FM as inputs. Afterward, an optimized mix design is determined by integrating developed models with a desirability function model and setting maximization of strength and ductility as the optimization goals. An ABA having 7.9% SF and 1.2% FM is observed to provide the highest strength and ductility for multiple applications, i.e., road and buildings, with desirability factor close to unity; responses of which are also validated by performing tests. Furthermore, analysis of cleaning aspect shows that the use of optimized ABA in place of cement for subgrade improvement of 1 km two-lane road could avoid CO2 emission of around 79,032 kg of C, save 42,720 kWh and 1174.8 GJ of electrical and thermal energy, respectively, and clean 43 Mg of FM waste; however, astute protocols of COVID-19 FM waste handling and disinfection are needed to be established and followed.