Waste respirator processing system for public health protection and climate change mitigation under COVID-19 pandemic: Novel process design and energy, environmental, and techno-economic perspectives

Abstract

The ongoing COVID-19 pandemic leads to a surge on consumption of respirators. This study proposes a novel and effective waste respirator processing system for protecting public health and mitigating climate change. Respirator sterilization and pre-processing technologies are included in the system to resist viral infection and facilitate unit processes for respirator pyrolysis, product separation, and downstream processing for greenhouse gas (GHG) emission reduction. We evaluate the system’s environmental performance through high-fidelity process simulations and detailed life cycle assessment. Techno-economic analysis results show that the payback time of the waste respirator processing system is seven years with an internal rate of return of 21.5%. The tipping fee and discount rate are the most influential economic factors. Moreover, the unit life cycle GHG emissions from the waste respirator processing system are 12.93 kg CO₂-eq per thousand waste respirators treated, which reduces GHG emissions by 59.08% compared to incineration-based system so as to mitigate climate change.

Nomenclature

Abbreviations

CAPEX

Capital expenditure

CDC

The Centers for Disease Control and Prevention

FCC

Fluid catalytic cracking

GHG

Greenhouse gas

GWP

Global warming potential

HEPA

High-Efficiency Particulate Arrestance

HEX

Heat exchangers

HHS

The Department of Health and Human Services

HP

High-pressure steam

IRR

Internal rate of return

LCA

Life cycle assessment

LCI

Life cycle inventory

LP

Low-pressure steam

MEA

Monoethanolamine

MP

Mid-pressure steam

MSDS

Material Safety Data Sheet

MSW

Municipal solid waste

NPV

Net present value

O&M

Operation and maintenance cost

OPEX

Operating expenditure

PSA

Pressure-swing adsorption

PT&I

Property tax and insurance

RMW

Regular medical waste

TEA

Techno-economic analysis

Variables

AR

Annualized revenue

CINC

Income from clinical sites

DPC

Depreciation cost

DR

Depreciation rate

GEC

General expense

IC

Indirect capital cost

INC

Income from the waste respirator processing system

LC

Land cost

PEC

Procurement cost for each equipment unit

PINC

Income from products

PT

Payback time

TAXC

Income tax

TCI

Total capital investment

TEIC

Total installation cost

TINC

Tipping fee

TPEC

Total equipment procurement cost

TW

Transportation cost

WC

Working capital cost

Parameters

cap

Base case respirator processing rate

capr

Real case respirator processing rate

cepcib

Chemical engineering indices of the base-case year

cepcir

Chemical engineering indices of the current year

dis

Distance of transportation

geci

Parameters for calculating the general expense

ptici

Parameters for calculating PT&I

scf

The exponential factor

scft

The exponential factor

txr

Parameters for calculating the income tax

utw

Unit cost of transporting RMW

wtt

Weight of waste respirators

yr

The project lifespan

Index

I

Index for state i

1. Introduction

The U.S. has entered a new phase of COVID-19 pandemic with no shutdown in sight. Nationwide, the death-toll in the U.S. passed 100,000 in May [1], and topped to 150,000 on July 29 [2]. Studies show that N95 respirators and facemasks can prevent an infected patient from spreading the virus [3], [4] and thus curtail the COVID-19 transmission in public. On this regard, public are encouraged or required to wear respirators or facemasks to help slow down the spread of coronavirus [5]. To satisfy the subsequently large demand of respirators, the Department of Health and Human Services (HHS) has recommended an annual production of 3.5 billion N95 respirators nationwide [6]. As a consequence, the many disposed waste respirators would pose a high risk of virus transmission to the public if not managed properly [7]. Even worse, discarded facemasks and respirators get into the surface water system can cause damages to the eco-system [8], [9]. Thus, an effective waste respirator processing system must be put forward to prevent those unintended consequences.

Discarded N95 respirators are often contaminated by various pathogens and notorious to the public. In the conventional incineration process, the regular medical wastes (RMWs) are first transmitted to the incinerator by a conveyor. However, if the RMWs are not properly packaged, viruses from the respirators can be exposed to the air and affect the public health. On the other hand, the greenhouse gases (GHGs) emitted from waste respirator incineration can contribute to climate change [10], [11]. Therefore, a novel and effective waste respirator processing system that can reduce the risk of viral infection and GHG emissions must be designed when fighting for the COVID-19 pandemic. An insulated and automatic sterilization system can kill virus and prevent viral infection. In addition, GHG emissions can be reduced by adopting closed-loop and open-loop recycling processes, which are used in plastic recycling, in the waste respirator processing system [12]. Moreover, the open-loop recycling process is versatile to produce products that are useful in other chemical processes [12] when compared with the costly closed-loop recycling process. On these regards, a viable strategy is integrating an automatic sterilization system with the open-loop recycling process, so that the viral infection and GHG emissions can be reduced.

Two major components of waste N95 respirators are the non-woven fiber and the melt-blown fiber made from polypropylene [13]. The chemical recycling process, which includes pyrolysis [14], [15], [16], [17], [18], gasification [19], [20], and fluid catalytic cracking (FCC) [21], [22], is a widely applied technology in the open-loop recycling of waste plastics. Since pyrolysis is often used in these methods for cracking plastics that are hard to depolymerize [23], such as polypropylene, the waste respirator can be cracked via pyrolysis as an open-loop recycling process. In this regard, the fast pyrolysis process can be integrated into the waste respirator processing system to improve its economic profitability [24], [25] due to the high yield of useful monomers and pyrolysis oil [26], [27], [28], [29].

While some publications focus on the economic profitability and environmental sustainability of processing regulated medical waste [30], [31], process design and modeling of an effective, safe, and environmentally friendly waste respirator processing system remain a knowledge gap that this study aims to fill. The first challenge is to design the waste respirator recycling process system with safe operation and effective waste respirator treatment. In this system, the viral infection is prevented by waste respirator sterilization, and the improved economic profitability is achieved via manufacturing high-purity products from waste respirators. Maximum energy-savings are realized in this system for reducing GHG emissions from energy production. The second challenge is the acquisition of the detailed life cycle inventory, so that the impacts on GHG emissions and other environmental impact categories are systematically quantified to examine the potential of the waste respirator processing system in mitigating climate change. Many key parameters corresponding to the life cycle inventory, such as the utility usage and product distribution of the waste respirator processing system, are unavailable in the existing literature. To fill this data gap, rigorous process simulations for the waste respirator processing system are then performed to extract the detailed life cycle inventory and economic parameters.

In this work, we develop a novel and effective waste respirator processing system that includes respirator sterilization and pre-processing technology to protect the public health and facilitate the unit processes of pyrolyzing respirators, separating and processing downstream products that can reduce GHG emissions. Seven sections, namely respirator preprocessing, pyrolysis, light hydrocarbon separation, CO₂ separation, hydrogenation, hydrogen production, and onsite combustion, are integrated into this system. We incorporate a commercially available sterilization process into this system to shred, sterilize, and dehydrate the waste N95 respirators, so that the respirators are disinfected and prone to be cracked in the pyrolysis section [32]. A life cycle assessment (LCA) is conducted to systematically quantify the potential of the waste respirator processing system in mitigating climate change and other environmental impacts from cradle-to-gate. High-fidelity process simulations of the waste respirator processing system are performed based on the experimental data on pyrolyzing waste respirator, and the results are integrated with the data from Ecoinvent V3.6 [33] to compile the detailed life cycle inventory. Techno-economic analysis (TEA) is also performed to estimate the profit to evaluate economic profitability by calculating the capital and operating expenses [34]. We illustrate the economic feasibility of establishing respirator processing systems and their potential for climate change mitigation via two case studies. Specifically, the proposed respirator processing system is applied to treat 582 million waste N95 respirators, corresponding to the HHS’s recommended annual production amount in eight northeastern states in the U.S. [6], namely New York, New Jersey, Pennsylvania, Massachusetts, New Hampshire, Vermont, Rhode Island, and Connecticut, which can be treated by a commercialized medical waste disposal company, namely BioSERV [35].

The major novelties of this work are summarized below:

• •The first process design of the waste respirator processing system with seven sections, including the sterilization process, processes of pyrolyzing waste respirators and separating downstream products;
• •A novel and effective waste respirator processing system that can protect public health by treating waste respirators and alleviate climate change via GHG emissions reduction under COVID-19 pandemic.
• •A sustainable process design of the waste respirator processing system with a payback time of seven years, an internal rate of return (IRR) of 21.5%, and a reduction by 59% in unit life cycle GHG emissions compared to the incineration-based system conventionally used in treating waste respirators.

The rest of the paper is organized as follows. We describe each section of the process design and modeling for the waste respirator processing system in Section 2. Based on the proposed process design, LCA and TEA methodologies are presented in Section 3. We then present the results of two case studies in Section 4 to assess the economic profitability and environmental sustainability of setting up the waste respirator processing system. The conclusion is given in Section 5.

2. Process design and modeling for the waste respirator processing system

In this work, we develop and model a novel waste respirator processing system that can effectively protect public health and mitigate climate change, as presented in Fig. 1 . The process flowsheet includes seven sections, namely respirator preprocessing, pyrolysis, light hydrocarbon separation, CO₂ separation, hydrogenation, hydrogen production, and onsite combustion. We perform process simulation of this system via using the Peng-Robinson thermodynamic package due to its widely application in the processing systems of cracking mixed plastics or processing small gaseous molecules [36]. The chemical compositions of products from the respirator processing system are shown in Table B1 in Appendix B, and the detailed description of the process simulation for each section are presented in following subsections.

Fig. 1.

Overview of the flowsheet of the waste respirator processing system.

2.1. Respirator preprocessing

New York State requires that the waste respirator, which is a type of RMW, needs to be sterilized before being sent to the municipal solid waste (MSW) treatment site [37]. In this regard, an insulated and automatic respirator preprocessing system, STI-Chem-Clav, is commercially used in medical waste disposal sites in New York State to reduce the risk of viral infection [38]. This system combines disinfection, dehydration, and shredding process, which can eliminate pathogens and facilitates the cracking of respirators before the pyrolysis section.

Detailed inner structure and function for each component of STI-Chem Clav are presented in Fig. 1 [32], [39]. The waste respirators are collected from clinical sites and transported by trucks, which are specially designed for shipping medical wastes. Waste respirators are then directly sent to the lid, which can insulate the whole preprocessing system and prevent the viral infection to the public when the lid folds. Saturated steam (147.7 °C, 44.61 bar) is fed into the system to sterilize respirators, and the air output from the system is filtered by High-Efficiency Particulate Arrestance (HEPA) for capturing pathogens and reduce the risk of viral infection. The waste respirators are then ground into small particles in the shredder, and the spore test port is used for detecting the concentration of pathogens. The respirator particles are transmitted by the steam conveyor to the dehydration section inside the STI-Chem Clav. Saturated steam (147.7 °C, 44.61 bar) is fed into the system to provide hydraulic force for the conveyor, and to maintain the high-temperature and high-pressure environment used for viral disinfection. The respirator particles are treated under 95–120 °C for 60 min in this process to effectively kill the SARS-COV-2 virus that contributes to the COVID-19 pandemic [40]. In the dehydration section, the saturated steam removes the moisture contained in the respirator particles. The high-temperature condition in this process is maintained by a heat-insulated dehydration chamber jacket. At the end of the system, a spore test recovery for detecting the negligible pathogens preserved on the dehydrated respirator particles is adopted to guarantee virus elimination and safety to the public. The disinfected particles are finally fed into the pyrolysis section through another conveyor.

2.2. Pyrolysis

The main goal of this section is to crack waste respirators into various hydrocarbons to be separated in the downstream processing sections, so that climate change can be mitigated by preventing GHG emissions from incinerating respirators. Respirator particles are cracked in a fluidized bed pyrolizer, which is modeled as a yield reactor (RYield) in the process simulation, under 800 °C and one bar [41]. Nitrogen gas, which is an inert fluidizing gas, is circulated in this section. Products are sent to the cyclone to separate the char, which is fed into the onsite combustion section to provide high-temperature heating energy. Gaseous products are then cooled to 200 °C and sent to the pressure swing absorption (PSA) unit, which is modeled as a separator in the process simulation, to separate nitrogen [42], [43], while the rest of the products are cooled, compressed, and split into two streams with light and heavy chemical components. The lighter stream is then sent to the light component separation section, while the heavier stream is directly fed into “C4 and C5 Separator” in the light component separation. Detailed operating conditions of key equipment units of this section are provided in Table C1 in Appendix C.

2.3. Light hydrocarbon separation

This section aims to produce ethane and propylene from waste respirators. Ethane is an important component in liquified gas, and propylene is a vital monomer used in polymerization processes. Similar to the light hydrocarbon fractionation in shale gas processing [44], this section includes several distillation processes of splitting hydrocarbons with various molecular weights. Five distillation processes, namely demethanizer, C2 splitter, C2 separator, depropylenizer, and C4 and C5 separator, are considered in this section.

The section begins with the compression of the lighter stream from the upstream pyrolysis section, which is then cooled and fed into the demethanizer, whose overhead gas is condensed under −125.89 °C and raffinate is generated under 1.76 °C and 20 bar to separate methane for producing hydrogen in the downstream hydrogen production section. Raffinate stream is then heated to 6 °C and sent to C2 splitter; the overhead stream from this distillation process is separated under −24.52 °C and 20 bar and fed into C2 separator. Ethane, whose purity is 98.26% in weight percentage, is separated as the raffinate stream of the C2 separator under −7.66 °C and 20 bar, while the stream with ethylene and CO₂ in the overhead liquid is fed into the CO₂ separation section. In the depropylenizer (30 °C, 12 bar), the precooled raffinate stream from C2 splitter is split into propylene with a purity of 94.13% as the overhead liquid stream under 26.84 °C and 12 bar, and the raffinate stream is depressurized and mixed with the heavy stream from the upstream pyrolysis section. This stream mixture is then sent to the C4 and C5 separator (138 °C, 8 bar), where the overhead stream (62.22 °C, 7.6 bar) is sent to the hydrogenation section to convert butene into butane. The raffinate stream with various aromatic components and C8 is directly sent to the gasoline mixer. Notably, the cryogenic conditions used in the condensers of demethanizer, C2 separator, C2 splitter are maintained by a cascade refrigeration cycle. Detailed operating conditions of key equipment units of this section is provided in Table C2 in Appendix C.

2.4. Hydrogenation

To convert the byproducts of butene in the overhead stream from C4 and C5 separator into butane, direct hydrogenation is considered in this section. In this hydrogenation process, the overhead stream is treated by the preheated hydrogen and NiMo catalyst in the hydrogenator (150  °C, 1.01 bar) [43], which is modeled as stoichiometry reactor (RStoic). The product stream is cooled, pressurized, and sent to product separator (81 °C, 8 bar), where the butane mixture is split in the overhead stream under 37.60 °C. Raffinate stream, which mainly includes pentane, is sent to the gasoline mixer or the hydrogen production section. Detailed chemical composition of the butane mixture is shown in Table 1 , and the operating conditions of key equipment units of this section are provided in Table C4 in Appendix C.

Table 1.

Detailed component and chemical composition of the waste respirators on a dry basis [59], [60].

	PP	PET	Polyisoprene	Al	Sum
Amount (%wt)	64%	15%	11%	10%	100%
	C	O	H	N	Al
Amount (%wt)	74%	5%	11%	0	10%

2.5. CO₂ separation

This section aims to separate CO₂ from the overhead stream of the C2 separator in the light hydrocarbon separation section, and the remaining ethylene can be sold as an important monomeric product. Owing to a high loading capacity to acid gas and high solubility in water, monoethanolamine (MEA) shows a high selectivity in the CO₂ separation process [45]. The light hydrocarbons, such as ethylene, can be separated and reduce GHG emissions via the carbon allocation to products. However, the solvent regeneration process requires much heating energy, which is provided by the saturated steam (147.7 °C, 44.61 bar).

Specifically, the overhead liquid from the C2 separator is preheated to 42 °C and sent to MEA absorber (T301) where CO₂ is effectively absorbed. The bottom stream is then split into the CO₂ rich stream at the bottom and negligible hydrocarbon stream in the flash drum under 47.27 °C and 1.1 bar. The overhead gaseous streams from MEA absorber and flash drum are mixed, depressurized, and sold as ethylene products with purity of 98.48% in weight percentage. Preheated by the lean-rich solvent heat exchanger (E302) to 102 °C, the CO2-rich stream is then sent to the acid gas stripper to separate CO₂. CO₂ is separated from the overhead gaseous stream under 97.53 °C and 1.1 bar and emits to air, while the CO₂ lean stream is generated in the raffinate stream under 107.9 °C and 20 bar. Ultimately, the CO₂ lean stream is precooled and resent to the MEA absorber, and then reused as the MEA solvent. Detailed operating conditions of key equipment units of this section are provided in Table C3 in Appendix C.

2.6. Hydrogen production

To supply the hydrogen used in the hydrogenation section, the onsite hydrogen production process is included in the waste respirator processing system. In addition, methane produced from the demethanizer can be utilized in this section to mitigate climate change via the avoidance of its direct emission to the environment.

Specifically, about 16% of the raffinate from the product separator in the upstream hydrogenation process is preheated to 550 °C, and the remaining raffinate is mixed with the raffinate from the C4 and C5 separator in the light hydrocarbon separation section to produce gasoline product from the gasoline mixer. The preheated raffinate is mixed with steam following a steam-to-carbon molar ratio of 2.3, which is close to the value of 2.5 used in the pre-reformer [46]. The pre-reformer is modeled as the stoichiometric reactor (RStoic) and equilibrium reactor (REquil). The stream mixture is sent to the pre-reformer (550 °C, 21 bar) and the heavy components are cracked into lighter components. The irreversible cracking reactions follow the stoichiometric equation given in [47]. Methane stream from the demethanizer is preheated, and 16% of this stream is mixed with saturated steam. About 84% of the preheated methane stream is directly fed into the combustor in the onsite combustion section to provide high-temperature heating energy. The stream mixture is then sent to the reformer, which is modeled as the plug flow reactor (RPlug), to produce H₂, CO, and CO₂ following the thermodynamic equilibrium given in relevant literature. Gaseous stream from the reformer is pre-cooled to 200 °C and fed into the PSA unit to separate gaseous hydrogen at 85% efficiency [42]. The separated hydrogen is then sent to the hydrogenation section, while the remaining gaseous stream from the PSA unit is cooled and split into gaseous and liquid water streams. Gaseous stream is sent to the onsite combustion section, and the water stream is mixed with makeup water and then pressurized and heated. Ultimately, the water stream is converted into the saturated steam and then reused for pre-reforming and reforming processes. Detailed operating conditions of key equipment units of this section is provided in Table C5 in Appendix C.

2.7. Onsite combustion

This section primarily aims to provide high-temperature heating energy used for maintaining the high-temperature condition required for the pyrolysis section, and heating the streams in the waste respirator processing system. The secondary objective is to reduce the environmental impacts of direct emissions from the light chemical components, such as unconverted methane from the hydrogen production section, so as to mitigate climate change. The third purpose is to utilize the innate energy in the unconverted char from the pyrolysis section.

In this onsite combustion section, the mixture of oxygen, char, and gaseous chemical components, such as methane, is sent to the combustor, which is modeled as the stoichiometric reactor (RStoic) and ignited at 1000 °C. Energy released from the combustor is used for providing the high-temperature heat utility to the waste respirator processing system. The product stream is separated in a cyclone, whereas the gaseous stream is emitted to the environment and the solid stream (mainly Al₂O₃) is sold.

2.8. Heating and cooling utilities

We consider various heating utilities, namely low-pressure steam (LP), mid-pressure steam (MP), high-pressure steam (HP), and fired heat, to maintain high temperature condition in pyrolysis reactor and distillation columns. Moreover, cooling water (CW) is regarded as the only cooling utility used in the waste respirator processing system. The disposed cooling water from the processing system can be regenerated in the cooling tower with efficiency of 97.89% (%wt). The regenerated cooling water is then pumped back to the processing system and reused.

3. LCA and TEA methodologies

To quantitively assess the potential of the waste respirator processing system in mitigating climate change and other environmental impacts throughout this study, we formally state the LCA methodology for quantitively evaluating and comparing the environmental performance of the waste respirator processing system with the conventional incineration-based system for incinerating waste respirators by air in two combustion chambers under different temperatures [48]. TEA methodology is also stated so that the economic viability of establishing the waste respirator processing system can be assessed.

3.1. LCA for quantifying life cycle environmental impacts of the waste respirator processing system

LCA is a systematic approach to systematically quantify the environmental impacts from products or systems within their life cycle [49]. In this study, we consider four phases, namely goal and scope definition, inventory analysis, impact assessment, and interpretation, in this typical process-based LCA [50].

3.1.1. Goal and scope definition

The main features of the waste respirator processing system are defined in the phase of goal and scope definition, where the LCA goal, system boundary, the functional unit, and key assumptions are all set up.

The goal of the LCA is to quantify and compare the environmental impacts from the respirator processing system with those from incineration-based system, so that the potential of mitigating climate change can be assessed. The material flows and emissions from five life cycle stages, namely waste respirator transportation, waste respirator processing, offsite heat production, offsite electricity production, and offsite production for input materials, are considered in the waste respirator processing system. Owing to the absence of end-of-life phases for the final products, such as the ethane manufactured from the waste respirator processing system, we choose a “cradle-to-gate” system boundary to confine life-cycle stages [51]. The system boundary and life cycle stages are presented in Fig. 2 .

Fig. 2.

System boundary of the LCA for waste respirator processing system is confined by a dotted red box, including five life cycle stages: waste respirators processing, waste respirator transportation, offsite heat production, offsite electricity production, and offsite production for input material. Direct and indirect emissions from those life cycle stages are denoted as dark red and turquoise ticks, respectively. Major processes and material flows are represented by grey boxes and dark grey ticks, respectively. All products are presented in a navy-blue block.

The waste respirator processing system aims to sterilize the respirators and convert them into chemical products. Hence, the functional unit should be defined corresponding to the amount of waste respirators treated, or amounts of final products manufactured from the waste respirator processing system [52], [53]. Notably, the mass flow rate of each output product is proportional to the amount of waste respirators fed into the processing system. Since the mass flow rate of one product is not the same as that of another product, we adopt a functional unit defined as one thousand waste respirators treated in the recycling process system [54], [55]. Accordingly, we employ this functional unit to systematically quantify the life cycle environmental impacts.

3.1.2. Inventory analysis

The goal of the inventory analysis phase is to determine and set up life cycle inventories (LCIs) of all activities and unit processes within the system boundary of the waste respirator processing system [56]. We quantify the mass and energy balances across all life cycle stages for input materials to compile the LCIs [54]. The data of relevant LCIs are extracted from the Ecoinvent V3.6 database and high-fidelity process simulations through Aspen Plus [33], [57]. Owing to the absence of product distribution of the waste respirator pyrolysis and operating conditions for downstream processing in existing literature, relevant assumptions, and their premises are required. We mainly focus on the treatment of waste N95 respirators according to the suggestion from the Centers for Disease Control and Prevention (CDC) of wearing N95 respirators that are effective in reducing viral infection [58]. Based on similar compositions of various N95 respirators, we assume the treated N95 respirators have the same composition as the widely used 3M 8210N95 respirators. The composition data are extracted from the Material Safety Data Sheet (MSDS) and relevant patents [59], [60]. We use the average composition for each component given in the MSDS to prepare for detailed process simulations [59]. The dry-basis and atomic compositions of the waste respirators are shown in Table 1. To perform process simulation, we refer to the assumption used for pyrolyzing mixed plastics in Westcherout et al. [24], which states that the product compositions from pyrolyzing plastic mixture are the weighted average of pyrolyzing each single plastic component. The atomic composition of the unconverted char, which is shown in Table 2 , is calculated based on the mass balance relationship between waste respirators and pyrolysis products. To design and model the waste respirator processing systems with various treatment capacities, we postulate that the operating conditions, such as the reflux ratio, do not vary with the treatment capacity [61]. Meanwhile, the energy or utility consumption in the waste respirator processing system is assumed to be linearly correlated with the respirator processing rate [62].

Table 2.

Detailed chemical composition of the char on a dry basis.

	C	O	H	N	Al
Amount (%wt)	62.09%	3.74%	0.84%	0	33.33%

For the other unit processes of separating or processing products from waste respirators, we use the Peng-Robinson thermodynamic package to perform the process simulation due to its wide application in relevant literature [25], [43]. Aspen HYSYS is used for performing the process simulation for the CO₂ separation section because of the completeness of the thermodynamic parameters for the MEA absorption process [63].

3.1.3. Impact assessment

In the impact assessment phase, the global warming potential (GWP) indicator is first adopted to directly quantify the life cycle environmental impacts of the waste respirator processing system. The GWP indicator can be used for quantifying the life cycle environmental impacts of GHG emissions, as it is widely applied to systematically quantify the environmental impacts of the medical waste processing system [64], [65]. We use the GWP in a time horizon of 100-year to represent the relative greenhouse impact compared to CO₂ [66], which is denoted as the GWP₁₀₀. For instance, the GWP₁₀₀ of methane is 28. Hence, if we emit 1 kg of methane to the environment, the resulting greenhouse impacts are equivalent to the emission of 28 kg CO₂ over the course of 100 years.

Notably, the GWP indicator considers only one life cycle environmental impact category. Therefore, we need to examine the environmental impacts of the waste respirator processing system through a wide spectrum of impact categories. In this work, we use ReCiPe hierarchical mid-point scores to quantify the life cycle environmental impacts of the waste respirator processing system in terms of 18 mid-point impact categories, namely climate change, ozone depletion, terrestrial acidification, freshwater eutrophication, marine eutrophication, human toxicity, photochemical oxidant formation, particulate matter formation, terrestrial ecotoxicity, freshwater ecotoxicity, marine ecotoxicity, ionizing radiation, agricultural land occupation, urban land occupation, natural land transformation, water depletion, mineral resource depletion, and fossil fuel depletion [67]. System boundary presented in Fig. 2 is applied to calculate the ReCiPe mid-point scores [68] for life cycle stages within the waste respirator processing system.

As for both methodologies, the life cycle environmental impacts are divided into two categories within the system boundary, namely direct and indirect emissions, as shown in Fig. 2. Most of the characterization factors are collected from the Ecoinvent V3.6 database [33], [63]. However, since the electricity mix varies in different states, we quantify GHG emissions from offsite electricity production in each state by employing the characterization factor of the corresponding state’s electricity mix given in the U.S. e-GRID [69].

3.1.4. Interpretation

In the interpretation phase, the life cycle environmental impacts quantified by the GWP indicator are summarized to compare with those from the incineration-based system and assess the potential of the waste respirator processing system in mitigating climate change. The results of life cycle environmental impacts quantified by the ReCiPe mid-point score are presented as the absolute score for each impact category. The life cycle environmental impacts for each life cycle stage within the system boundary are also displayed as impacts breakdowns to illustrate the environmental sustainability of the waste respirator processing system.

3.2. TEA for evaluating economic performance of the waste respirator processing system

Capital expenditure (CAPEX) and operating expenditure (OPEX) are considered for calculating the economics of the waste respirator processing system. CAPEX includes the direct capital, indirect capital, working capital of all equipment units, and the land cost used for setting up the processing system [44]. OPEX includes the cost of transporting waste respirators, feedstock cost, utility cost, cost of operations and maintenance (O&M), property tax and insurance (PT&I), general expense, and income tax. The linear depreciation method is adopted to calculate the depreciation cost, and the depreciation rate (DR) is calculated by Eq. (1).

$$\mathit{DR}=\frac{1}{\mathit{yr}}$$ (1)

For the CAPEX, the procurement cost for each equipment unit (PEC) and the total equipment installation cost (TEIC) are scaled by the base case (cap) and real respirator processing rates (capr) through the power function [70], as given in Eqs. (2), (3), respectively. The inflation is evaluated by using chemical engineering indices of the base-case year and current year [71], [72], which are denoted as cepcib and cepcir, respectively. The exponential factor (scf and scft) is referred from the relevant literature [42], [73], [74], [75], [76]. The indirect capital cost (IC) and land cost (LC) are estimated by 123% and 6% of total equipment procurement cost (TPEC) [43], respectively. The working capital cost (WC) is estimated by 5% of the summation of land cost and total equipment installation cost. The total capital investment (TCI) is calculated by Eq. (4).

$$\mathit{PEC}=pecb·{\left(\left(\frac{\mathit{capr}}{\mathit{cap}}\right)\right)}^{\mathit{scf}}·\left(\left(\frac{\mathit{cepcir}}{\mathit{cepcib}}\right)\right)$$ (2)

$$\mathit{TEIC}=teicb·{\left(\left(\frac{\mathit{capr}}{\mathit{cap}}\right)\right)}^{\mathit{scft}}$$ (3)

$$\mathit{TCI}=TEIC+IC+LC+WC$$ (4)

For the OPEX, the transportation cost (TW) is calculated by Eq. (5), where the weight of waste respirators and distance is denoted as wtt and dis, respectively. We refer to the unit cost of transporting RMW (utw) as that of transporting waste respirators [77], which is assumed to remain unchanged across states. The O&M cost (OMC) is estimated by 10% of the summation of land cost and equipment installation cost [73]. The property tax and insurance denoted as PT&I (PTIC), general expense (GEC), and income tax (TAXC) are calculated by Eqs. (6), (7), (8), respectively. DPC denotes the depreciation cost, and the values of parameters ptici, geci, and txr are 0.02, 0.1, and 0.35, respectively, which come from relevant literature [43], [44].

$$\mathit{TW}=wt·dis·utw$$ (5)

$$\mathit{PTIC}=ptici·(IC+LC+TEIC)$$ (6)

$$\mathit{GEC}=geci·\sum _{i=1}^8\mathit{IN}{C}_i$$ (7)

$$\mathit{TAXC}=txr·(\sum _{i=1}^8\mathit{IN}{C}_i-OMC-GEC-DPC-PTIC)$$ (8)

The waste respirator processing system aims to treat the waste respirators and convert them into chemical products. The process system can be regarded as the combination of medical waste sterilization, solid waste disposal, and plastic pyrolysis sites. Hence, the income from the waste respirator processing system in the state i (INC_i) is the summation of incomes from products in the state i (PINC_i), the medical waste disposal income from clinical sites in the state i (CINC_i) [78], and the tipping fee in the state i (TINC_i) [79], as given in Eq. (9). The annualized revenue (AR) is calculated as Eq. (10).

$$\mathit{IN}{C}_i=PIN{C}_i+CIN{C}_i+TIN{C}_i$$ (9)

$$\mathit{AR}=\sum _{i=1}^8\mathit{IN}{C}_i-OMC-PTIC-GEC-TAXC$$ (10)

The net present value (NPV) is calculated to directly evaluate the economic profitability of the waste respirator processing system. Specifically, the NPV is calculated by the summation of discounted annual revenue subtracted by the total capital investment (TCI) during the project lifespan (yr), as given in Eq. (11). Payback time (PT) is given in the economic results by finding the year that the accumulated cash flow firstly becomes non-negative. The payback time can be obtained by solving Eq. (12). The IRR is also solved by Eqs. (13), (14), (15), (16) with iterations to reveal the economic performance [43]. Notably, the subscript n denotes the n ^th iteration.

$$\mathit{NPV}=\sum _{t=1}^{\mathit{yr}}\frac{\mathit{AR}}{{(1+ir)}^t}-TCI$$ (11)

$$\mathit{PT}={log}_{(1+ir)}(\frac{\mathit{AR}}{\mathit{AR}-TCI·ir})$$ (12)

$$\begin{gathered} \mathit{IR}{R}_{n+1}=IR{R}_n-NP{V}_n(\frac{\mathit{IR}{R}_n-IR{R}_{n-1}}{\mathit{NP}{V}_n-NP{V}_{n-1}}) \\ (1-1.4\frac{\mathit{NP}{V}_{n-1}}{\mathit{NP}{V}_{n-1}-3NP{V}_n-2·TCI}) \end{gathered}$$ (13)

$$\mathit{NP}{V}_n=\sum _{t=1}^{\mathit{yr}}\frac{\mathit{AR}}{{(1+IR{R}_n)}^t}-TCI$$ (14)

$$\mathit{IR}{R}_1={(yr·AR/TCI)}^{\left(\frac{2}{\mathit{yr}+1}\right)}-1$$ (15)

$$\mathit{IR}{R}_2={(1+IR{R}_1)}^{\left(\frac{log(yr·AR/TCI)}{log(yr·AR/(NP{V}_1+TCI))}\right)}-1$$ (16)

4. Results and discussions

We employ aforementioned LCA and TEA methodologies to assess the potential of climate change mitigation and economic viability for the waste respirator processing system, which aims to treat the waste N95 respirators collected from the eight northeastern U.S. states that are near the New York Metropolitan Area, namely New York, New Jersey, Pennsylvania, Massachusetts, New Hampshire, Vermont, Rhode Island, and Connecticut. A commercialized medical waste disposal company, BioSERV, can treat RMWs from these eight states [35], which have similar legislation and tipping fee regarding to the medical waste treatment. The results from the process simulation are used for evaluating the economic and environmental performances. Notably, we assume that the amount of waste respirators to be treated in a county is proportional to its population. Hence, the total mass flow rate of the waste respirator is computed as 693 kg/h, which is calculated based on the average weight of standard 3 M 8210 N95 respirators (9.99 g per respirator) [59] and the HHS’s recommended annual production of 3.5 billion respirators nationwide [6]. For economic parameters, the equipment procurement and installation costs are extracted from Aspen Capital Cost Estimator V10.0 and relevant literature [42], [74], [75], [76], [80]. The discount rate (ir) is 10%, and the project lifespan is 20 years [44].

Two case studies are considered for establishing waste respirator processing systems to treat waste N95 respirators from eight aforementioned northeastern states in the U.S. In the first case study, only one waste respirator processing system is considered. In the second case study, two processing systems are considered for treating waste respirators from two areas. Specifically, the first area is highly populated, which locates near the New York Metropolitan Area. The second area covers the remaining area in these eight states. Economic sensitivity analysis is then performed to decipher the most influential economic parameters and the effect of the respirator processing rate on the economic profitability, while the environmental sensitivity analysis is conducted to reveal the most influential operating parameters.

4.1. Life cycle inventory analysis results

Life cycle inventories are gathered from the mass and energy balances for the waste respirator transportation, waste respirator processing, offsite heat production, offsite electricity production, and offsite production for input materials. All life cycle stages, except the one of waste respirator processing, are modeled by their corresponding predefined models in Ecoinvent V3.6 database [33] and U.S. e-GRID [69].

We first consider the mass balance relationship between the input and output mass flows. Four types of input materials are considered, namely the waste respirators treated in the pyrolysis section, the O₂ used in the onsite combustion section, the makeup N₂ applied in the pyrolysis section, and the makeup H₂O adopted in the hydrogen production section. The carbon (C) and aluminum (Al) inputs stem from the respirator flow, and the oxygen (O) input mainly derives from the O₂ flow. The hydrogen (H) is fed into the processing system by the respirator and makeup H₂O flows. However, the nitrogen (N) is introduced into the system only by the makeup N₂ flow.

The chemical elements fed into the waste respirator processing system are distributed to the output products and flue gas. As shown in the right half of Fig. 3 , the flue gas has the largest mass flow rate. As for the flows of output products, gasoline has the largest yield in the waste respirator processing system, which shares 37.98% of the total C input content and 34.04% of the total H input content. Other hydrocarbon products, namely C₄H₁₀, C₃H₆, C₂H₄, and C₂H₆, share the remaining C and H contents. Meanwhile, all input Al are converted into Al₂O₃ in the onsite combustion section. The values of hourly mass flows of the output products are presented below their corresponding blocks in Fig. 3.

Fig. 3.

Mass balance relationships between input materials and output materials. The hourly mass flows of the C, O, H, N, and Al in the input materials are presented below the red, blue, green, violet, and orange blocks, respectively. The distributions of the C, O, H, N, and Al to the output products are shown in the right half of the Sankey graph, and the hourly mass flows of the output products are presented below the dark grey blocks. The widths of the blocks and arrows are proportional to their corresponding flow rates.

The energy balance relationships between the energy input and output of the waste respirator processing system are presented in Table 3 . The major contributor to the energy input is the waste respirator feedstock, which shares a percentage of 92.20%. The utilities used in the processing system, namely LP, MP, HP, and fired heat, share a small percentage of the energy input. Moreover, the electricity input is mainly used for triggering the pumps and compressors. On the other hand, two major contributors to the energy output are from the gasoline and energy removal from the cooling water, which share 33.06% and 29.47%, respectively. The remaining energy output is mainly distributed to other products, and the negligible energy loss stems from the pumps and compressors.

Table 3.

Energy balance relationships between energy input and output. The energy input is from the waste respirators, utilities, and electricity. The energy output is from products, flue gas, energy removal from the cooling water, and the energy loss.

Input Categories	Energy Input (GJ/h)	Output Categories	Energy Output (GJ/h)
Respirator	27.42	C3H6	3.48
LP	0.12	C2H6	1.41
MP	0.06	C2H4	2.87
HP	0.00	C4H10	2.62
Fired Heat	0.02	Gasoline	9.83
Saturated Steam	0.65	Al2O3	0.20
Electricity Input	1.47	Flue gas	0.09
/	/	Cooling Water’s Energy Removal	8.76
/	/	Energy Loss	0.48
Total Energy Input	29.74	Total Energy Output	29.73

4.2. Economic and environmental performances for the waste respirator processing system

4.2.1. Case study 1: A single waste respirator processing plant for treating waste respirators from eight northeastern states in the U.S.

In the first case study, we consider a single waste respirator processing system that locates near the Citiwaste Medical Waste Disposal in New Jersey. This processing system aims to treat the respirators collected from New York, New Jersey, Pennsylvania, Massachusetts, New Hampshire, Vermont, Rhode Island, and Connecticut, which are densely populated states in the U.S. The location of the Citiwaste Medical Waste Disposal is shown in Fig. 4 . This disposal site is in a largely populated area producing a large amount of waste respirators. Notably, the transportation cost is proportional to the product of the transportation distance and loading of the truck. Hence, the transportation cost remains low if transporting many respirators in a short distance. Therefore, it is both convenient and economically viable to establish a respirator processing system that locates near the medical waste disposal site in a densely populated area.

Fig. 4.

The location of the single respirator processing system. The processing system is near one corresponding disposal site, namely Citiwaste Medical Waste Disposal in New Jersey. The cyan blue color gradient denotes the county-level population densities of eight northeastern states in the U.S., namely New York, New Jersey, Pennsylvania, Massachusetts, New Hampshire, Vermont, Rhode Island, and Connecticut.

Breakdowns of CAPEX and OPEX of the proposed single waste respirator processing system are presented in Fig. 5 . The major contributor to the expenses is the total capital investment (29.02% of total expenses), which is further broken down into four categories, namely the total installation cost of all equipment units, total indirect capital, land cost, and working capital. Notably, the indirect capital is used for cost items of engineering, construction, and project contingency, as well as fees for hiring contractors to install equipment units. On this regard, the high costs for the procurement and installation for various equipment units and reactors ($9.71 million) in the downstream processing contribute to a high indirect capital ($5.82 million). The income tax shares the second-largest percentage in the total expenses (25.66%), which represents a high income so as to maintain a high economic profitability. The O&M cost, which is used for maintaining the normal operations of the waste respirator processing system, also contributes a lot to the total expense (15.43%). The transportation cost, utility cost, general expense, PT&I, feedstock cost for the waste respirator processing system are presented in the upper half of Fig. 5.

Fig. 5.

Breakdowns for the CAPEX and OPEX of establishing a single waste respirator processing system. The upper half represents the CAPEX and OPEX breakdowns. The lower half shows the breakdown of the total capital investment, namely the total installation cost, total indirect capital, land cost, and working capital.

To identify the major contributor to the high cost of the installation and procurement of equipment units, the breakdown for the total installation cost of a single waste respirator processing system is shown in the lower half of Fig. 5. Notably, the total capital investment is the summation of four categories of capital cost, namely total installed cost, total indirect capital, land cost, and working capital, which is shown in the upper right of the lower half in Fig. 5. We consider the costs of the separation unit (flash vessel, PSA, etc.), pump and compressor, distillation, refrigeration cycle, and reactor. The light hydrocarbon separation ($3.21 million) shares the largest percentage of the total installation cost, which is mainly contributed by the refrigeration cycle and distillation units. Various distillation columns are implemented in this section to separate the light hydrocarbons, namely methane, ethane, and propylene. Moreover, the cryogenic compressors are the main contributor to the installation cost of the cascade refrigeration cycle, which is applied to maintain the cryogenic conditions in the demethanizer, C2 splitter, and C2 separator. Notably, the STI-Chem Clav used for shredding, sterilizing, and drying the waste respirators has the installation cost of $1.36 million, which is not the largest contributor to the total installation cost. On this regard, the STI-Chem-Clav is economically feasible to be incorporated into the waste respirator processing system for protecting public health. The values of other installation costs, namely the total installation cost of equipment units in the onsite combustion, CO₂ separation, heat exchangers (HEX), hydrogenation, and hydrogen production, are presented in Fig. 5.

The hotspot of GHG emissions is revealed from the emissions breakdowns shown in Fig. 6 . The pie chart in the center presents the percentages of direct and indirect emissions, which are 56% and 44%, respectively. The direct emissions mainly stem from the flue gas flow, which includes CO₂ and water from the offsite combustion section.

Fig. 6.

The GHG emissions breakdown of the case of the single respirator processing system. The pie chart in the center represents the proportion of direct and indirect emissions. The middle layer on the sunburst chart denotes the breakdown of the indirect emissions. The outer layer on the sunburst chart shows the breakdown of the offsite production for different inlet materials, namely the offsite production of water, steam, O₂, and N₂.

We then analyze the life cycle stage that contributes most to GHG emissions by further breaking down the indirect emissions. The indirect emissions from the offsite production for inlet material, offsite electricity production, waste respirator transportation, and offsite heat production are presented in the middle layer on the sunburst chart. The major contributor of GHG emissions is from the offsite production for inlet material, which shares 56% of the bulk indirect emissions. As presented in the outer layer on the sunburst chart, GHG emissions from the offsite production of steam are the largest contributor (91.11%) among the offsite production for inlet materials. In the STI-Chem Clav, a large amount of steam is required to provide hydraulic force in the steam conveyor and maintain high-temperature to kill viruses on waste respirators, which aims to resist viral infection and protect public health. Owing to a large amount of consumed cooling water as the only cooling utility in various heat exchangers and condensers in the distillation columns. The percentages of GHG emissions from other life cycle stages are presented in the middle layer on the sunburst chart.

To identify the environmental hotspot of the waste respirator processing system, the ReCiPe approach considering three end-point impact categories and 18 mid-point impact categories are implemented to systematically quantify the life cycle environmental impacts. Detailed breakdown of the ReCiPe mid-point score is presented in Fig. 7 . As can be seen, climate change shares the largest percentage of life cycle environmental impacts from all life cycle stages, namely the direct emissions from waste respirator processing system, indirect emissions from waste respirator transportation, offsite heat production, offsite electricity production, and offsite production for inlet material. Notably, fossil depletion is another major contributor to life cycle environmental impacts, especially for waste respirator transportation and offsite heat production, which are typical processes consuming much energy. Additionally, waste respirator transportation, offsite electricity production, and offsite production for inlet material stages have considerable life cycle environmental impacts corresponding to the human toxicity.

Fig. 7.

ReCiPe mid-point score breakdowns of the waste respirator processing system.

To examine the environmental impacts posed by the waste respirator processing system, the profile of the ReCiPe mid-point scores is shown in Fig. 8 . It is worth mentioning that the waste respirator processing system is energy-intensive, and fossil fuels are the main source of energy generation. Consequently, key life cycle environmental impact categories lie in climate change, human toxicity, fossil depletion, and agricultural land occupation. Other important impact categories consist of ionising radiation, metal depletion, and water depletion.

Fig. 8.

Absolute ReCiPe mid-point scores of the waste respirator processing system.

4.2.2. Case study 2: two waste respirator processing plants for treating waste respirators from eight states in the U.S.

In the second case study, we consider building two waste respirator processing systems that locate near the Citiwaste Medical Waste Disposal in New Jersey and Cyntox Medical Waste Disposal in New York. Different from the first case study, the processing system near the Citiwaste Medical Waste Disposal only treats the N95 respirators collected from the region near the New York Metropolitan Area, which is a densely populated area shown in Fig. 9 . The processing system near the Cyntox Medical Waste Disposal treats the waste respirators collected from the region with a much lower population density. The locations of the Citiwaste Medical Waste Disposal and Cyntox Medical Waste Disposal are shown in Fig. 9. Notably, the waste respirator processing system near the Cyntox Medical Waste Disposal remains a low treatment capacity, while the one near the Citiwaste Medical Waste Disposal has a high treatment capacity. The results from this case study can be applied to evaluate the need of setting up branches for the waste respirator processing system with various treatment capacities in other regions.

Fig. 9.

Locations of two respirator processing systems. Two processing systems are near two corresponding disposal sites, namely Cyntox Medical Waste Disposal in New York and Citiwaste Medical Waste Disposal in New Jersey. The processing system near the Cyntox Medical Waste Disposal treats the waste respirators collected from the region on the left of the red border, while the one near the Citiwaste Medical Waste Disposal treats the respirators collected from the region on the right. The cyan blue color gradient denotes the county-level population densities of eight northeastern states in the U.S., namely New York, New Jersey, Pennsylvania, Massachusetts, New Hampshire, Vermont, Rhode Island, and Connecticut.

To better illustrate the economic competitiveness of each case study, the breakdowns of the expenses and revenues for both cases are presented together in two bar charts in Fig. 10 . The bar charts with positive values denote the revenues, while the ones with negative values are the expenses. The total profits of both case studies are presented above a bold column in shallow blue. Notably, the total expense in case 2 ($59.78 million) is higher than that in case 1 ($54.62 million). The main contributor to this result is the high capital investment. The installation and equipment procurement cost for establishing two waste respirator processing systems are higher than those for building one processing system with the same total treatment capacity. Specifically, the transportation cost in case 2 ($5.17 million) is lower than that in case 1 ($5.91 million). Moreover, the utility cost in case 2 ($2.29 million) is less than that in case 1 ($3.01 million) due to a lower statewide market price of electricity in New York State than that in New Jersey. Nevertheless, the higher revenue in case 2 ($69.28 million) due to the high gasoline market price of in New York State cannot offset its high capital investment. Hence, the total profit in the case 1 ($14.54 million) is higher than that of the case 2 ($9.50 million).

Fig. 10.

Breakdowns of expense and revenue for the two cases. The bar charts denote breakdowns of expenses and revenues, while the shallow blue bar chart represents the total profits of the two cases. Absolute values of revenues, expenses, and total profits for two cases are presented next to their corresponding bar charts.

To further illustrate the economic feasibility of establishing one waste respirator processing system, the payback times for both cases are presented in Fig. 11 . The value of x-axis of the red point A represents the payback time of case 1, while that of the green point B denotes the payback time of case 2. The payback times for cases 1 and 2 are seven and 10 years, respectively. Moreover, the IRR of establishing one waste respirator processing system (21.5%) is higher than that of building two systems (16.1%). Accordingly, the results of expenses breakdowns, revenue breakdowns, payback times, and IRRs reveal the economic viability of building one waste respirator processing system.

Fig. 11.

Relationships between the accumulated cash flow and operating year show the economic profitability of two cases. The value of x-axis of the red point A represents the payback time of setting up one waste respirator processing system, while that of the green point B denotes the payback time of establishing two waste respirator processing systems. The location of the waste respirator processing system is presented near point A. Locations of two waste respirator processing systems are shown near point B. The IRRs of two cases are presented next to their corresponding graph locations of the waste respirator processing system.

The unit GWP (unit life cycle GHG emissions) breakdowns of both cases are then performed to systematically quantify the potential of mitigating climate change. As shown in Fig. 12 , the unit life cycle GHG emissions breakdown for processing waste respirators consider GHG emissions from offsite production for inlet material, offsite electricity production, offsite heat production, waste respirator transportation, and direct emissions from the waste respirator processing system. Notably, direct emissions are one of the main contributors to GHG emissions, which share percentages of 56.00% and 56.80% for cases 1 and 2, respectively. Another major contributor is the emissions from the offsite production for inlet material, which considers the offsite production of cooling water, steam, oxygen, and nitrogen fed into the waste respirator processing system. The breakdowns and unit life cycle GHG emissions of the two cases are similar. Therefore, it is reasonable to establish one waste respirator processing system to simultaneously maintain the high economic profitability and mitigate climate change via GHG emissions reduction.

Fig. 12.

Breakdowns of unit GWPs for the waste respirator processing system and incineration-based system. The breakdown considers the unit life cycle GHG emissions from offsite production for inlet material, offsite electricity production, offsite heat production, waste respirator transportation, and direct emissions. Four stacked columns show the unit GWPs from respirators processing systems of two cases and their corresponding incineration-based systems.

The breakdowns of unit life cycle GHG emissions for the incineration-based system are displayed next to the columns of their corresponding cases. The values of unit life cycle GHG emissions are presented over their corresponding columns. As presented in Fig. 12, the unit life cycle GHG emissions of the corresponding incineration-based systems for cases 1 and 2 are 31.60 kg CO₂-eq per thousand respirators processed and 31.47 kg CO₂-eq per thousand respirators processed, respectively. Notably, the unit life cycle GHG emissions from the waste respirator processing system for cases 1 and 2 are 12.93 kg CO₂-eq per thousand respirators processed and 12.74 kg CO₂-eq per thousand respirators processed, respectively. In this way, the waste respirator processing system can reduce about 59.08% of GHG emissions compared to the corresponding incineration-based system, which validates that a single respirator processing system can mitigate climate change by GHG emissions reduction.

4.3. Sensitivity analysis

In this section, the base case economic and environmental parameters are extracted from the process simulation, which is detailly described in Section 2. The economic and environmental results of the base case are calculated based on this process simulation of the waste respirator processing system.

4.3.1. Economic sensitivity analysis for establishing one waste respirator processing system

Economic sensitivity analysis is performed to determine the most influential economic parameters. For the market-based economic parameters, the variation percentage of C₂H₄ price was calculated based on that of the US Gulf Cost from 2019 to 2020 [81], which from −64% to +12%. The variation percentage of C₂H₆ price was calculated based on the US ethane price from 2019 to 2020 [82], which is from −23% to +34%. In addition, the variation percentages of C₃H₆, C₄H₁₀, Al₂O₃, N₂, O₂, and water prices were calculated based on those prices from available prices from January 2020 to September 2020 [83], [84], [85], [86], [87], [88], [89], [90], [91], [92]. Notably, the gasoline price is largely influenced by the COVID-19 pandemic [93]. Hence, we choose the most negatively extreme gasoline price in April 2020 as the low-price, and the price of the temporary peak in August 2019 as the high-price to resemble the fluctuation of the gasoline price in the future [93], [94], [95]. The high and low values of the gasoline price are 130% and 86.1% relative to the current price, respectively. As presented in Fig. 13 , the tipping fee and gasoline price is the most influential economic parameters related to the market. The market prices of other feedstocks, namely water, N₂, and O₂, are much less effective.

Fig. 13.

Economic sensitivity analysis results for the single waste respirator processing system. High and low values of the total capital investment, tipping fee, C₄H₁₀, C₃H₆, Al₂O₃, C₂H₄, C₂H₆, water, N₂, O₂, gasoline price, project contingency, and discount rate are presented in the graph. The incremental market prices of final products (from C₄H₁₀ to C₂H₆), and the tipping fee enhance the NPV. The effects are shown in a series of red bars while the opposite effects are presented in blue bars. The incremental prices of makeup chemicals (water, N₂, and O₂), values of project contingency, total capital investment, and discount rate decrease the NPV. The effects are shown in a series of red bars and the opposite effects are presented in blue bars.

For the parameters related to CAPEX and OPEX calculation, we consider the variation of the project contingency, total capital investment, and discount rate, which are stressed in relevant literature corresponding to pyrolysis [43], [61], [76]. The discount rate is the most influential parameter. If the discount rate raises from 10% to 15%, the NPV would be reduced to less than 10% of its original value. Conversely, the NPV would double if the discount rate is reduced to 5% [61].

It is necessary to illustrate the economic feasibility of the novel waste respirator processing system for the plant to handle the growing number of respirators due to the further prevention of the COVID-19 pandemic in the aforementioned eight northeastern U.S. states. We display the variation of the unit NPV of the waste respirator processing system with the respirator processing rate in Fig. 14 . Specifically, the respirator processing rate of the base-case is calculated corresponding to the HHS’s recommended annual production rate, which is 3.5 billion respirators nationwide [6]. Results show that the unit NPV of the waste respirator processing system would increase if the respirator processing rate grows. Hence, it would be economically viable to establish a single waste respirator processing system to support the fight for COVID-19 in these eight northeastern states.

Fig. 14.

The relationship between the unit NPV and the respirator processing rate in the plant. The yellow point shows the unit NPV of the waste respirator processing system when treating the respirators in the base-case processing rate. The location of the single waste respirator processing system is shown near the yellow point.

4.3.2. Environmental sensitivity analysis for establishing one waste respirator processing system

It is worth mentioning that operating parameters, such as the conversion rate of pyrolyzing respirators, can influence GHG emissions of the waste respirator processing system. As presented in Fig. 15 , the unit GWP of the single waste respirator processing system will increase to 15.57 kg CO₂-eq per thousand respirators treated, if the pyrolysis conversion rate decreases to 0.85. In addition, the unit GWP enhances to 13.65 kg CO₂-eq per thousand respirators treated when the steam consumption for the STI-Chem Clav increases from 0.4 kg per kg waste respirators processed (267.6 kg/h) to 0.5 kg per kg waste respirators processed (334.5 kg/h). On the other hand, the electricity requirement is the least influential operating parameter, which would decrease the unit GWP to 12.78 kg CO₂-eq per thousand respirators treated if the electricity requirement is reduced by 11%.

Fig. 15.

Environmental sensitivity analysis results for the single waste respirator processing system. High and low values of the steam generation, electricity requirement, and pyrolysis conversion are presented in the graph. The incremental values of steam generation amount and electricity requirement, as well as the decremental value of waste respirators pyrolysis conversion rate increase the unit GWP. The effects are shown in a series of red bars while the opposite effects are presented in blue bars.

5. Conclusion

In this work, we developed a novel and effective waste respirator processing system that could reduce the risk of COVID-19 infection to protect public health and mitigate climate change. The waste respirator processing system included seven sections, namely respirator preprocessing, pyrolysis, light hydrocarbon separation, CO₂ separation, hydrogenation, hydrogen production, and onsite combustion. High-fidelity process simulations and detailed LCA were conducted to evaluate the environmental performance. Two case studies were considered for establishing waste respirator processing systems to treat waste N95 respirators from eight northeastern states in the U.S., namely New York, New Jersey, Pennsylvania, Massachusetts, New Hampshire, Vermont, Rhode Island, and Connecticut, which were former epicenters of COVID-19 [96]. The consumption of respirators remained high in these states to further fight for and prevent the new wave of coronavirus infection [97], [98]. TEA results revealed the economic viability for setting up the single respirator processing system in terms of the payback time (7 years) and IRR (21.5%), which were significantly influenced by the tipping fee and discount rate. On the other hand, this processing system could mitigate climate change via reducing GHG emissions by 59.08% compared to the incineration-based system. It was worth noting that the increasing waste respirator processing rate, which was due to the growing consumption of respirators to reduce viral infection in aforementioned eight northeastern states, could enhance the economic effectiveness.

CRediT authorship contribution statement

Xiang Zhao: Data curation, Formal analysis, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing. Fengqi You: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing.

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.

Appendix A. Product distribution of pyrolyzing waste respirators

See Table A1 .

Table A1.

Product distribution of pyrolyzing waste respirators [36], [99], [100].

Chemicals	Composition
CO	3.11%
CO2	3.66%
Methane	9.54%
Ethylene	8.56%
Ethane	4.15%
Propene	10.20%
Propane	1.04%
n-Butane	3.89%
1-Butene	1.17%
Isobutylene	0.79%
2-Butene	0.20%
Butadiene	1.22%
1,3-Pentadiene	7.29%
2-Methyl-1-Pentene	0.65%
Cyclohexene	0.19%
1-Heptene	0.19%
1-Octene	12.79%
Benzene	4.40%
Toluene	2.85%
m-Xylene	1.04%
Ethylbenzene	0.27%
Styrene	0.52%
Indene	0.22%
Naphthalene	2.02%
Char	9.89%

Appendix B. Chemical composition of products

See Table B1 .

Table B1.

Chemical compositions of products from pyrolyzing waste respirators.

Chemicals	Ethane	Ethylene	Propylene	Butane Mixture	Gasoline
CO	0.00%	0.00%	0.00%	0.00%	0.00%
CO2	0.00%	0.00%	0.00%	0.03%	0.00%
Methane	0.00%	0.06%	0.00%	0.33%	0.00%
Ethylene	1.36%	98.48%	0.00%	0.22%	0.00%
Ethane	98.26%	1.46%	0.01%	0.00%	0.00%
Propylene	0.38%	0.00%	94.13%	1.31%	0.00%
Propane	0.00%	0.00%	5.86%	0.01%	0.00%
n-Butane	0.00%	0.00%	0.00%	9.38%	1.26%
Isobutene	0.00%	0.00%	0.00%	78.21%	0.00%
Isobutane	0.00%	0.00%	0.00%	0.03%	0.01%
Butadiene	0.00%	0.00%	0.00%	0.02%	0.00%
1,3-Pentadiene	0.00%	0.00%	0.00%	0.00%	0.05%
n-Pentane	0.00%	0.00%	0.00%	0.00%	20.25%
2-Methyl-1-Pentene	0.00%	0.00%	0.00%	0.00%	0.04%
2-Methyl-Pentane	0.00%	0.00%	0.00%	0.00%	1.72%
Cyclohexene	0.00%	0.00%	0.00%	0.00%	0.62%
Cyclohexane	0.00%	0.00%	0.00%	0.00%	0.52%
1-Heptene	0.00%	0.00%	0.00%	0.00%	0.63%
1-Octene	0.00%	0.00%	0.00%	0.00%	40.11%
Benzene	0.00%	0.00%	0.00%	0.00%	13.13%
Toluene	0.00%	0.00%	0.00%	0.00%	8.92%
m-Xylene	0.00%	0.00%	0.00%	0.00%	3.26%
Ethylbenzene	0.00%	0.00%	0.00%	0.00%	0.85%
Styrene	0.00%	0.00%	0.00%	0.00%	1.63%
Indene	0.00%	0.00%	0.00%	0.00%	0.69%
Naphthalene	0.00%	0.00%	0.00%	0.00%	6.33%

Appendix C. Operating parameters for key equipment units

See Table C1, Table C2, Table C3, Table C4, Table C5 .

Table C1.

Operating conditions for key equipment units in the respirator pyrolysis section.

	T/°C	P/bar
R101 (RYield)	700	1
R102 (RStoic)	1000	1
V101	40	3
PSA	200	1

Table C2.

Operating conditions for the key equipment units in the light hydrocarbon separation section.

	Ttop/°C	Tbot./°C	P/bar
T201	−125.89	1.76	20
T202	−24.52	81.50	20
T203	−29.77	−7.66	20
T204	26.84	109.03	12
T205	62.22	199.57	7.6

Table C3.

Operating conditions for key equipment units in the CO₂ separation section.

	Ttop/°C	Tbot./°C	P/bar
T301	40.78	47.01	20
V301	47.27		1.1
T302	97.53	107.9	1.1

Table C4.

Operating conditions for key equipment units in the hydrogenation section.

	Ttop/°C	Tbot./°C
R401	150
T401	37.60	109.35

Table C5.

Operating conditions for key equipment units in the hydrogen production section.

	T/°C	P/bar
R501	450	21
R502	950 (Tin), 670 (Tout)	21
PSA	200	20
V501	30	1

Appendix D. . Input parameters for the Techno-economic analysis

See Table D1 .

Table D1.

Input parameters for the techno-economic analysis [42], [44], [74], [75], [76], [80], [83], [84], [85], [86], [87], [88].

Items	Values	Items	Values
Ethylene ($/kg)	0.51	HP Steam ($/klb)	11.71
Ethane ($/kg)	0.18	MP Steam ($/klb)	8.14
Propylene ($/kg)	0.73	Electricity ($/kWh)	0.052
Butane ($/kg)	1.2	Transportation Cost ($/mile·ton)	1.013
Gasoline ($/kg)	0.84	Steam ($/ton)	8.2
Al2O3 ($/kg)	0.334	yr	20
N2 ($/m3)	0.18	cepcib	607.5
TINC ($/t)	790	scft	0.6093
CINC ($/t)	75.45	ptici	0.02
O2 ($/t)	40	geci	0.1
Water ($/t)	1.41	txr	0.35
LP Steam ($/mmBTU)	2.11	ir	0.1

Appendix E. . Input parameters for the life cycle assessment

See Table E1, Table E2 .

Table E1.

GWP-based characterization factor for the life cycle assessment [33].

Items	Characterization Factor Value	Unit
Transportation	0.547	kg CO2-eq/(km·ton)
Heat	0.036	kg CO2-eq/MJ
Makeup Water	0.0005	kg CO2-eq/kg
Electricity for NY	0.228	kg CO2-eq/kWh
Electricity for NJ	0.190	kg CO2-eq/kWh
Electricity for PA	0.358	kg CO2-eq/kWh
O2	0.038	kg CO2-eq/kg
N2	0.015	kg CO2-eq/kg
Steam	0.334	kg CO2-eq/kg
CO2	1.000	kg CO2-eq/kg

Table E2.

Data for ReCiPe mid-point score of each life cycle inventories, where the m denotes impact categories. For m = 1–18, the categories are Agriculture Land Occupation, Climate Change, Fossil Depletion, Freshwater Ecotoxicity, Freshwater Eutrophication, Human Toxicity, Ionizing Radiation, Marine Ecotoxicity, Marine Eutrophication, Metal Depletion, Natural Land Transformation, Ozone Depletion, Particulate matter formation, Photochemical Oxidant Formation, Terrestrial Acidification, Terrestrial Ecotoxicity, Urban Land Occupation, Water Depletion, respectively. For the numbers shown in the first row, the 1–8 denote life cycle inventories of transportation, heat, makeup water, electricity, O₂, N₂, steam, CO₂[33], [68].

m	1	2	3	4	5	6	7	8
1	0.007436	7.89E−05	0.025445	3.01E−05	0.21073	0.083612	0.002445	0.007436
2	0.54154	0.035539	0.42388	0.000492	0.037853	0.015019	0.32985	0.54154
3	0.18777	0.018177	0.13727	0.000145	0.004356	0.001728	0.11272	0.18777
4	0.007758	0.000176	0.009299	1.82E−05	0.00452	0.001793	0.0018	0.007758
5	6.09E−05	5.75E−07	0.000475	3.71E−07	6.31E−06	2.50E−06	4.00E−05	6.09E−05
6	0.13204	0.001378	0.29395	0.000279	0.011275	0.004474	0.044806	0.13204
7	0.03703	0.000116	0.077932	0.000131	0.025166	0.009985	0.008646	0.03703
8	0.00778	0.000114	0.008062	1.60E−05	0.003931	0.00156	0.001541	0.00778
9	5.15E−05	1.70E−06	0.00013	1.38E−07	5.73E−06	2.27E−06	2.69E−05	5.15E−05
10	0.040516	0.000198	0.00384	2.67E−05	0.003946	0.001566	0.000948	0.040516
11	−3.03E−05	−3.75E−07	−1.30E−05	−3.18E−08	−0.00102	−0.0004	−6.54E−06	−3.03E−05
12	8.70E−08	3.11E−09	2.64E−08	2.11E−10	1.70E−09	6.76E−10	2.72E−08	8.70E−08
13	0.000689	1.49E−05	0.001716	1.48E−06	4.52E−05	1.79E−05	0.000344	0.000689
14	0.001242	5.56E−05	0.000674	9.92E−07	7.71E−05	3.06E−05	0.000592	0.001242
15	0.001277	4.45E−05	0.000789	1.53E−06	0.000103	4.09E−05	0.000972	0.001277
16	0.000162	1.31E−06	2.63E−05	6.26E−08	7.71E−06	3.06E−06	4.35E−05	0.000162
17	0.097149	0.000399	0.050501	9.53E−05	0.014326	0.005684	0.013869	0.097149
18	0.001058	5.23E−05	0.003062	1.90E−05	0.049978	0.01983	0.000269	0.001058