The systems designed to protect our water and reduce pollution are, paradoxically, contributing to another environmental crisis: greenhouse gas (GHG) emissions. The technologies used to upgrade wastewater treatment facilities to meet increasingly stringent nitrogen and phosphorus discharge regulations often require significant energy and chemical inputs, creating a challenging tradeoff for sustainability. Currently, U.S. water and wastewater treatment plants are already responsible for approximately 45 million tonnes of carbon dioxide equivalent (CO2e) emissions annually. While prior research has highlighted this issue, no comprehensive national evaluations exist to assess the broader implications of water policy decisions on GHG emissions. This work aims to fill that gap by developing a computational tool to quantify the climate impacts of nutrient reduction upgrades and policies at a national scale. As a case study, we assess the impact of a theoretical policy reducing effluent nutrient concentrations to 3 milligrams per liter (mg/L) for total nitrogen and 0.05 mg/L for total phosphorus within the Mississippi River Basin.

Using a life cycle assessment framework, the tool quantifies the GHG emissions associated with nutrient reduction upgrades at publicly owned treatment works in the National Pollutant Discharge Elimination System. A decision tree, informed by literature and Environmental Protection Agency reports, automatically assigns the most likely conventional treatment process required in the future based on a user-specified future effluent nutrient concentration target. The modeled conventional treatment processes include metal salts addition for phosphorus precipitation, anaerobic-anoxic-aerobic biological nutrient removal (BNR), 5-Stage Bardenpho BNR, tertiary denitrification, microfiltration, and reverse osmosis (though not all were required in the current case study). The required upgrades depend on both the future and current treatment processes. Current effluent nutrient concentrations were retrieved from the Gulf Hypoxia Task Force’s Nutrient Model, which uses Discharge Monitoring Report datasets, to identify the most likely current treatment processes at each facility. A life cycle inventory database for each treatment technology enables the tool to calculate the additional material and energy consumption due to each upgrade. Regional electrical grid profiles are incorporated based on the facility’s location.

Results indicate that assuming effluent concentration reductions to 3 milligrams per liter (mg/L) total nitrogen and 0.05 mg/L total phosphorus from their current levels, annual CO2e emissions within the Mississippi River Basin would increase by 1.1 million tonnes (0.12 kilograms of CO2e per cubic meter). With the emerging trend of transforming wastewater treatment plants into resource recovery facilities, numerous innovative technologies could drastically reduce energy consumption in the future. This tool is also capable of evaluating the national-scale impact of these technologies in comparison to conventional treatment processes. Future work will explore the adoption of such technologies including advanced ion exchange methods for nitrogen removal from anaerobic membrane digesters.

Plastic waste is a significant waste management challenge. Most plastics are currently either landfilled or mechanically recycled; however, there is considerable interest in pyrolysis or chemical recycling of plastics to recover useful chemistries. Separation of the plastics by resin type (i.e. 1-7's) is a key challenge, as co-mingled plastics cannot be effectively mechanically recycled or pyrolyzed without affecting product yield. AI-based plastic sorting is a potentially cost-effective way to separate plastics more effectively; however, the economics and environmental impacts of the technology are not yet understood. In this work, we investigate the economics and life cycle impacts of an AI-based plastics sorting system. Monte Carlo analysis is used to understand how changes in the plastics recycling market and facility siting affect both the economic viability of plastics sorting and the life cycle impacts of recycling baled plastics. The fate of different plastic waste fractions (i.e. landfilled waste, mechanically recycled plastic or pyrolyzed plastic) is investigated as a key variable. Mechanical recycling leads to the highest revenue and lowest environmental impacts for the plastics sorting company.

Nitrous oxide (N2O) is a major contributor to the climate change crisis. Wastewater treatment plants (WWTP) are a major source of N2O emissions, accounting for up to 50% of a WWTP’s carbon footprint.1 With the increasing interest in developing a nitrogen circular economy, technology development is crucial for capturing waste nitrogen and turning it into high-value products, while reducing N2O emissions.

Although N2O is a damaging environmental pollutant, it is also a powerful selective oxidant used in various chemical production pathways, including the selective oxidation of light hydrocarbons to olefins, alcohols, as well as the oxidation of benzene to phenol. Despite its potential, its industrial application is limited due to being seen as exotic and too expensive to use compared to traditional oxidants such as air or hydrogen peroxide. The Coupled Aerobic-Anoxic Nitrous Decomposition Operation (CANDO) process is an emerging technology that produces N2O on purpose from recovered nitrogen with a WWTP. Although CANDO can increase energy generation from the WWTP, it also could potentially be an N2O source that can be used for chemical production. Finding an effective pathway towards its use could potentially introduce a new oxidant that could help to expand the product portfolio of recovered nitrogen.

Using life cycle assessment and techno-economic analysis, we complete a case study evaluating the impact of recovering waste nitrogen as N2O within a wastewater treatment plant to produce phenol and pure nitrogen gas. We compare these results to incumbent phenol and nitrogen gas production processes and determine the impact that this technology could have on WWTP two different WWTP configurations. Additionally, four different co-product handling methods were used to distribute the burdens between the phenol and nitrogen. We used a Monte Carlo simulation with 1,000 iterations to evaluate the impact of various technical, environmental, and economic parameters. Cumulative energy demand (CED), global warming potential (GWP), water consumption, and internal rate of return (IRR) are the metrics we included. For the produced phenol, the CED, GWP, and WC range from 38 MJ/kg phenol to 102 MJ/kg phenol, 1.6 kgCO2eq/kg phenol to 3.6 kgCO2eq/ kg phenol, and 10 L/kg phenol to 30 L/kg phenol respectively. Meanwhile, the produced nitrogen gas has a CED, GWP, and WC between 40 MJ/kg phenol to 90 MJ/kg phenol, 1.8 kgCO2eq/kg phenol to 4.0 kgCO2eq/ kg phenol, and 12 L/kg phenol to 41 L/kg phenol respectively. The size of the WWTP heavily influences the internal rate of return. 25 MGD facilities are not profitable, while 100 MGD facilities can have an IRR as high as 16%. Our results indicate that large facilities are best-suited for this technology, that phenol produced at WWTP in this manner offers GHG reductions compared to conventional routes to phenol, and highlights several opportunities to improve this technology.

(1) Maktabifard, M.; Al-Hazmi, H. E.; Szulc, P.; Mousavizadegan, M.; Xu, X.; Zaborowska, E.; Li, X.; Mąkinia, J. Net-Zero Carbon Condition in Wastewater Treatment Plants: A Systematic Review of Mitigation Strategies and Challenges. Renewable and Sustainable Energy Reviews 2023, 185, 113638. https://doi.org/10.1016/j.rser.2023.113638.

Recycling plays a crucial role in fostering a sustainable and circular economy. The U.S. Environmental Protection Agency (EPA) has established a national target to achieve a 50% recycling rate by 2030, underscoring the urgency of improving resource recovery systems. While this objective encompasses various recyclable materials—including metals, paper, glass, and polymers—this study focuses on two of the most widely used and recyclable plastics: polyethylene terephthalate (PET) and high-density polyethylene (HDPE). These materials are integral to modern recycling efforts, and understanding the current infrastructure and scalability requirements for their recovery is a vital first step toward meeting national recycling goals.

Plastics recycling is central to addressing both EPA’s targets and the growing issue of plastic pollution. Despite PET and HDPE being highly recyclable, they are not often recycled at sufficient rates, resulting in significant environmental and economic challenges. Globally, over 450 million metric tons (Mt) of plastics are produced annually, yet only 9% is recycled. In the United States, the recycling rate is even lower, ranging between 5% and 8.7%. In 2018, 50% of solid waste was landfilled, 23.6% was recycled, 11.8% was incinerated for energy recovery, and 6% was treated through alternative methods. Of the recycled materials, plastics accounted for only 4.5% (approximately 3.1 million Mt). These figures highlight the need to enhance plastic recovery systems to reduce landfilling, conserve resources, and minimize greenhouse gas emissions. Moreover, the insights gained from improving plastics recycling could inform strategies for other recyclable materials, broadening the impact of this research.

Existing studies have explored economic and environmental aspects of recycling systems; however, there is a critical gap in analyzing the infrastructure and investment required to achieve the EPA’s 50% target. This study addresses this gap through a scenario-based, policy-driven approach that incorporates logistics optimization. Specifically, it examines four key questions:

Can existing waste collection infrastructure accommodate increased recyclable volumes from higher collection rates?

If not, what capacity expansions are necessary?

Where should infrastructure investments be prioritized?

What are the incremental costs associated with scaling collection and recycling infrastructure?

This analysis centers on PET and HDPE plastics, evaluating the current capacities, identifying bottlenecks, and estimating the investments needed to increase collection and recycling rates. Multiple scenarios based on realistic, policy-driven collection rates of post-consumer plastics are assessed to determine whether existing infrastructure can support higher recycling volumes or requires expansion. The corresponding economic implications of these changes are also quantified.

The findings indicate that material recovery facilities (MRFs) are significant bottlenecks under both current and expanded recycling scenarios, requiring capacity enhancements to process the additional influx of plastic waste. Additionally, collection systems represent the largest cost investment, followed by transportation expenses, which are particularly prominent on the U.S. West Coast. Optimizing the geographic distribution of recycling facilities can minimize overall system costs. These results provide actionable insights for policymakers and stakeholders to strategically align recycling infrastructure with the EPA’s goals, fostering a more efficient and sustainable recycling supply chain.

Plastics, while valuable for their lightweight and durable properties, significantly contribute to environmental degradation, accounting for 4.5% of global emissions in 2015 and potentially consuming up to 13% of the remaining carbon budget by 2050. In the U.S., recycling rates for common polymers—LDPE, HDPE, PP, and PET—remain alarmingly low at 9% as of 2019. A major barrier to improving recycling rates lies in the lack of a clear understanding of the technical constraints that limit recycling, how these constraints may evolve over time, and how emerging recycling technologies could alleviate them. Without a rigorous framework for prioritizing recycling interventions or consistently evaluating emerging technologies and dynamic material systems, the U.S. struggles to implement effective strategies to enhance recycling outcomes.

This study develops a comprehensive framework to identify a temporal hierarchy of recycling constraints and corresponding recycling parameters—recycling rates, recycled content, and environmental benefits—for LDPE, HDPE, PP, and PET in the U.S. from 2020 to 2050. The methodology integrates three components: (1) a high-resolution Dynamic Material Flow Analysis (DMFA) to model polymer flows by composition and quality, accounting for evolving demand and scrap availability; (2) a consistent Recycling Technology Performance (RTP) model evaluating polymer sortation and recycling technologies across five key metrics—cost, yield, energy and emissions, throughput, and efficacy; and (3) a Python-based linear optimization model to determine active U.S. recycling constraints and assess the efficacy of recycling technologies over time. The DMFA provides a dynamic perspective on material flows, the RTP model evaluates both conventional and advanced technologies (e.g., NIR sorting, mechanical recycling, glycolysis), and the optimization model incorporates quality metrics such as melt flow rate to assess the impacts of contamination and degradation on recycling processes. This framework offers actionable guidelines for policymakers, manufacturers, and recyclers to address economic, environmental, and technical challenges in the recycling supply chain.

This presentation will showcase the DMFA and RTP model results, revealing shifts in polymer material flows over time and comparing the performance of various recycling technologies across five dimensions. A case study of PET bottle closed-loop recycling will illustrate the framework’s application, highlighting the economic, environmental, and technical impacts of emerging technologies, contamination, and multi-recycling loops on recycled content. By using PET bottles as an example, the presentation will demonstrate how the framework identifies effective recycling interventions. This study establishes a replicable framework for improving recycling systems, applicable to other polymers and products, and offers strategies for optimizing the entire plastic recycling system.

The glass industry is an interesting case study for its potential towards increased circularity and decarbonization. According to environmental protection agency, almost 31% of container glass is recycled in the United States (U.S.) as of 2018. However, post-consumer recycling of flat glass remains elusive (Figure 1). At the moment, it is a best downcycled into low-value construction aggregate or landfill cap, if not straight up landfilled. In addition to the lack of circularity analysis studies for the U.S. glass sector, there is a need for multi-scales, multi-indicators assessment capabilities. Indeed, according to the Ellen MacArthur Foundation, the circularity transition needs to occur at different scales (individual companies, economic sectors, and countries) to be successful. Otherwise, unintended consequences and impact displacements may occur. Analysis needs to account for those scaling effects. As an example, Lonca et al. (2020) showed that increased closed loop recycling of polyethylene terephthalate (PET) bottles is environmentally beneficial when the scope of the analysis is at the product level, but not when the scope is at the whole PET market level. Indeed, closed loop recycling consumes more resources and creates more environmental impacts than existing open-loop applications for recycled PET. Thus, conducting circularity only accounting for narrow system boundaries can be misleading. Moreover, to be truly beneficial, the circular economy needs to avoid any trade-offs between the economic, social and environmental dimensions of sustainability.

While several methodologies have been deployed for circularity assessments - such as Material flow analysis and Life Cycle Assessment - there are currently no multi-scales, multi-indicators methods. In this work we present how economy-wide and supply chain impact assessments can be combined. Specifically, we assess economy-wide impacts by connecting the supply chain model outputs (expressed in mass flows for different end-of-life pathways) to an hybrid input-output tables (which express economic flows between sectors in both monetary and physical units). Windows refurbishing, photovoltaics closed-loop recycling, flat glass to pozzolan-like cementitious materials, and flat glass to glass fibers are considered in the analysis. Results show that the adoption of the different circularity options depends on their level of incentives (since none are fully profitable). Windows refurbishment is the option avoiding the most greenhouse gas emissions. While the use of powdered flat glass as a replacement for Portland cement seems more economically favorable than recycling flat glass into glass fibers, there are high uncertainty on the costs parameters used in this study. Future steps will quantify such uncertainties. Moreover, more economic sectors will be added to the analysis.