ABSTRACT The present study investigates the potential of widely used supplementary cementitious materials (SCMs) such as fly ash (FA) and ground granulated blast furnace slag (GGBS) to improve the rheological and environmental performance of low-carbon cementitious pastes. Three binders consisting of 100% OPC, 25% FA, and 70% GGBS were tested at water-to-binder ratios of 0.4 and 0.45. The dynamic shear rheometer was employed to analyze shear-thickening behavior of various cementitious suspensions. Subsequently, the environmental life cycle assessment (LCA) was conducted within a “cradle-to-gate” framework, evaluating six environmental impact categories and proposing a novel approach to converting these impacts into a single environmental cost (USD). The results revealed that OPC suspensions exhibit the earliest and most pronounced shear-thickening onset, while 70% GGBS suspensions reduce global warming potential but increase acidification impact. In contrast, 25% FA suspensions minimize acidification impact. Moreover, the rheological behavior is significantly influenced by solid volume fraction (SVF) and particle morphology; 70% GGBS pastes demonstrate the highest yield stress (140 Pa) and plastic viscosity (1.61 Pa. s) at a w/b ratio of 0.4, attributed to their angular particle shape. The environmental cost of suspensions (100% OPC) is estimated at $13.92/m3, with OPC being the primary contributor. The findings highlight the potential of SCMs to enhance performance and reduce environmental impacts, supporting greater use of FA and GGBS for sustainable, low-carbon infrastructure development. Future research should focus on optimizing the combined use and dosage of FA and GGBS in low-carbon cementitious pastes to achieve a more effective balance among rheological performance, environmental sustainability, and economic viability. Equally important is the need to extend the assessment framework beyond the present scope by incorporating long-term performance and durability assessment, broader system boundaries, and more rigorous environmental cost evaluation should be incorporated to enable the development of robust and sustainable cementitious systems. Implication: India has set an ambitious goal of achieving carbon neutrality by 2070. In the coming years, a substantial increase in building construction is anticipated to accommodate the country’s growing population. However, this expansion threatens to hinder progress toward national sustainable development goals (SDGs) and commitments to the Paris Climate Agreement. Indian thermal power plants and steel plants produce substantial amounts of fly ash and slag, which are solid waste byproducts. To mitigate the environmental impact and reduce cement consumption, it is essential to utilize these materials in construction. By incorporating fly ash and slag as cement replacement materials, we can significantly decrease the carbon footprint of the construction industry, contributing to both sustainability and resource efficiency. The paper uniquely integrates the rheological properties of cementitious suspensions with a comprehensive environmental assessment, offering a dual perspective on performance and sustainability. A novel methodology has been proposed to consolidate environmental impacts into a single environmental cost, expressed in US dollars, providing a practical decision-making tool. We believe that this work integrating environmental assessment along with rheological properties is the first of its kind and will draw the attention of the international research fraternity working on the area of the rheology of cement-based materials and the life cycle assessment of construction materials. We believe that Journal of the Air & Waste Management Association is a highly suitable journal for this synthetic work as articles on these themes appear frequently in the journal. Being a journal with diverse readership base, I expect a huge interest from its audience for this study and a high citation impact post publication. I confirm that this article is original, unpublished, and not under consideration for publication elsewhere.

ABSTRACT Wildfire events have driven a seasonal decline in air quality in recent years. The EPA’s National Ambient Air Quality Standards are set to provide public health and welfare protection, but when a standard exceedance is outside the control of an air agency, such as in the case of many wildfires, an exceptional event demonstration can be developed to exclude data from attainment calculations. To evaluate and document probable exceptional events, we created a nationwide screening methodology to identify enhancements of PM2.5 and ozone concentrations due to wildfire emissions. The screening methodology combines widely used wildfire data and tools, including NOAA’s Hazard Mapping System data, PM2.5 and ozone monitor data, modeled smoke PM2.5 results, and generalized additive modeling results. This screening identified regional wildfire trends in the data, including the year-round influence of smoke in the southeastern part of the U.S. due to agricultural burning and the significant impact of the 2021 and 2023 Canadian wildfire seasons on the northeastern U.S. Case studies on high- and low-frequency wildfire-impacted areas confirmed the efficacy of the screening method. Results suggest that more than one-third of the days from the 2020–2022 and 2021–2023 design value periods were characterized by an ozone or PM2.5 smoke event somewhere in the country. Our results provide evidence of the scale to which wildfire smoke contributes to air pollution; this screening methodology can be used to identify probable wildfire exceptional smoke events. Implications: Wildfire events have driven a seasonal decline in air quality in recent years. The EPA’s National Ambient Air Quality Standards are set to provide public health and welfare protection, but when a standard exceedance is outside the control of an air agency, such as in the case of many wildfires, an exceptional event demonstration can be developed to exclude data from attainment calculations. We created a nationwide screening methodology to identify enhancements of PM2.5 and ozone concentrations due to wildfire emissions. Our screening methodology can be used to identify probable wildfire exceptional smoke events.

ABSTRACT Mandatory waste sorting policy in Beijing (2020) lowered mercury inputs to the representative MSWI plant by 67.7 % versus 2019 through removal of batteries and other Hg-rich articles. The front-end change propagated through the entire system, cutting stack emissions 82 % (1.35 ± 0.6 → 0.24 ± 0.05 µg m/³) and decreasing the Hg²⁺ fraction from 45.5 % to 28 %. Higher post-sorting plastic loads elevated chlorine, promoting in-furnace oxidation of Hg0; the resultant Hg²⁺ was efficiently captured by existing wet scrubbing/fabric filters. Mass-balance and speciation data show that source separation functions as a chemical pre-treatment that shifts mercury toward easily removable forms, amplifying downstream control performance without hardware retrofits. Implications: This study provides the first field-scale proof that waste-classification policy can govern mercury emission chemistry. By altering waste composition at the source, mandatory sorting oxidizes elemental mercury and enhances removal efficiency, offering decision-makers a low-cost, proactive tool to meet stringent Hg limits while advancing circular-economy goals.

ABSTRACT The rapid urbanization and industrialization in China have significantly increased municipal solid waste (MSW) generation, with incineration emerging as the dominant treatment method. However, this process produces substantial quantities of MSW incineration fly ash (MSWI-FA) and bottom ash (BA), posing environmental risks due to heavy metals, dioxins, and soluble salts. This review consolidates recent advancements in recycling these byproducts into construction materials, addressing technical feasibility, environmental impacts, and policy challenges. A systematic literature analysis (2000–2024) was conducted using Web of Science and China National Knowledge Infrastructure, supplemented by bibliometric analysis via CiteSpace. MSWI-FA is classified as hazardous waste, requiring stabilization via chemical agents (e.g. Na2HPO4/Na2S) or thermal treatments (e.g. vitrification at 1000–1500°C) to immobilize contaminants. In contrast, BA, which is generally classified as non-hazardous, is evaluated as a direct replacement for both fine and coarse natural aggregates in construction, with its geotechnical properties making it suitable for applications in concrete (≤50% substitution), road bases, and as a raw material in ceramics (20–50% substitution). Key applications include cement kiln co-processing, microcrystalline glass production, and geopolymer-stabilized road bases. Despite progress, challenges persist: compositional variability, high pretreatment costs (1,500–3,500 CNY/ton for vitrification), and insufficient long-term leaching data ( > 10 years). Policy gaps, such as outdated leaching standards (GB 5085.3-2007) and limited economic incentives, further hinder scalability. The review underscores the dual benefits of reducing landfill reliance and conserving natural resources, aligning with China’s circular economy goals. Future efforts should prioritize hybrid stabilization technologies, lifecycle assessments, and standardized protocols to enhance industrial adoption. By addressing these barriers, MSWI-FA and BA can transition from environmental liabilities to sustainable construction resources, supporting China’s waste management and decarbonization targets. Implications: Municipal solid waste incineration (MSWI) fly ash (FA) and bottom ash (BA) are environmental liabilities with resource potential in construction. Hazardous FA requires rigorous stabilization to immobilize heavy metals and dioxins, while non-hazardous BA is a viable substitute for natural aggregates. Widespread adoption is hindered by compositional variability, high pre-treatment costs (1,500–3,500 CNY/ton for FA vitrification), insufficient long-term leaching data, and outdated standards (GB 5085.3-2007). Developing hybrid stabilization technologies and lifecycle-based policies is crucial to transform these ashes into sustainable construction materials, aligning with circular economy and decarbonization goals.

ABSTRACT Legislative requirements for emission limits from industrial processes are becoming increasingly stringent and therefore a lower uncertainty of measurement of emissions released to the atmosphere is needed and possible sources of measurement errors need to be reconsidered. In this paper, we investigate a measurement error of industrial emissions of particulate matter from stacks caused by the selection of sampling positions in stacks with uneven particle distribution and we determine its dependence on different flow fields inside the stacks and on the size of the particles. CFD modeling is used to analyze particle distributions in stacks with a diameter of 0.75m and with three different shapes of a supply pipe (straight, one or two bends) generating different flow fields, considering sizes of the particles from 10μm to 50μm (Stokes numbers from 0.007 to 0.18). Concentration fields in several cross-sections are compared and significant changes of the particle distribution are observed when the shape of the supply pipe or the emission particle diameter are changed. The error of the emission mass flow rate as it would be determined according to the EN 15259 standard can reach about 30% for particle diameters of 20μm. Larger particles and the presence of bends lead to stronger particle clustering and near-wall accumulation which tend to increase the error. This should be taken into account in the iso-kinetic sampling practice. Implications: This study highlights the significant impact of particulate matter distribution on the accuracy of emission measurements in industrial stacks. The findings demonstrate that uneven particle distribution, particularly in setups with bends causing stronger particle clustering and near-wall accumulation, can introduce measurement errors of up to 50% depending on flow conditions. These results suggest that current standard sampling methods (e.g., EN 15259) may not always provide accurate emission mass flow rate estimations, especially for larger particles. The study underscores the need for improved sampling strategies or mixing devices to ensure reliable regulatory compliance in emission monitoring.

ABSTRACT Indoor air quality (IAQ) is a crucial determinant of health, which is of particular concern for low-income Black children, who are disproportionately exposed to asthma triggers in their indoor housing environment and have higher rates of asthma and poorer outcomes from the disease, indicating an environmental justice issue. However, guidelines for IAQ data collection vary between organizations, making assessments and comparisons difficult. This study consolidates recommended practices into one cohesive set of guidelines for monitoring IAQ. It outlines a structured approach for defining IAQ sampling objectives, identifying the most appropriate low-cost air sensors, determining optimal sensor placement in homes, developing data collection and analysis, and presenting and interpreting results. With indoor PM2.5 as a case study, the guidelines were used to determine sampling duration, analysis, and quality assurance in five households with pediatric asthma patients. The metrics illustrate PM2.5 concentration by the 90th percentile (with average concentration level from 4 to 109 μg/m3), daily average minutes of PM2.5 concentration exceeding recommended exposure limits of 0–134 min, daily average PM2.5 concentration of 1.8–82 μg/m3, and significant temporal variation across households. This study highlights the significance of employing low-cost air sensors to provide real-time notifications of IAQ, along with simplified monitoring guidelines for researchers, healthcare providers, and parents working to improve IAQ for households with asthmatic children, potentially reducing the frequency and severity of asthma attacks. The low-cost sensors and resulting metrics can direct interventions effectively and provide a basis for determining the efficacy of environment-based air quality interventions. Implications: People spend much of their time indoors, especially at home, making indoor air quality (IAQ) monitoring crucial for guiding actions that reduce asthma exacerbations, particularly among low-income households. Although low-cost air sensors are being widely used for real-time IAQ monitoring, most existing guidelines focus on occupational settings rather than residential environments, making implementation difficult. This study develops comprehensive and unified guidelines for deploying low-cost sensors for real-time IAQ monitoring in residential settings. A case study utilizing the developed guideline in this study was applied to demonstrate and evaluate PM2.5 concentration levels in some low-income residential homes in Southeastern Louisiana.

ABSTRACT SmokePath Explorer is a web-based decision-support tool for California, U.S.A. that quantifies smoke transport probability and population exposure risk across the state, enabling data-driven strategies to minimize impacts while advancing fire management effectiveness. SmokePath integrates the California and Nevada Smoke and Air Committee (CANSAC) high-resolution (2-km) 20-year reanalysis climatology with HYSPLIT trajectory modeling. A total of 1.3 billion transport trajectories were precomputed with initializations four times per day at four distinct height levels capturing diurnal variations and injection height influences across various prescribed fire scenarios to support probabilistic smoke projections. Within the SmokePath online dashboard, users can input fire parameters and select specific months or weeks to assess smoke transport risk. The tool generates risk-level smoke transport contours from precomputed data and summarizes key meteorological variables. The system also provides population exposure estimates, including the total affected population, the number of smoke-sensitive facilities (i.e. educational and healthcare), and impacted USPS ZIP codes. User feedback has been key to developing SmokePath, enhancing usability, data integration, and decision-making for prescribed fire planning. To assess SmokePath’s efficacy, we conducted case studies across diverse regions and validated results against independent observation datasets. These use cases assessed the accuracy of the WRF-CANSAC reanalysis dataset, which serves as the meteorological input for fire weather climatology and trajectory modeling. The fire case studies focused on identifying optimal burn windows and quantifying smoke transport patterns from (i) large multi-day prescribed fires, (ii) short duration (single-day) pile burns, and (iii) burns across diverse regions with complex topographic features. In most cases, modeled transport probability aligned with satellite-observed smoke plumes, capturing predominant dispersion patterns. Stakeholder feedback further supported the tool’s practical utility — 85% indicated they would use SmokePath for prescribed fire planning, and 62% found it useful during wildfires. Implications: With catastrophic wildfires on the rise, California is expanding fuel treatments, including prescribed fire. While essential for mitigation, prescribed burns release smoke that can harm public health if unmanaged. SmokePath addresses this challenge by providing evidence-based insights on plume behavior to guide short- and long-term planning. The tool helps land managers schedule burns to minimize community impact, especially for vulnerable populations, and supports wildfire response with rapid smoke risk information. By improving public communication and enabling protective actions, SmokePath advances both health protection and the strategic use of prescribed fire.

ABSTRACT As part of the Toxic Substances Control Act (TSCA) Risk Evaluation, the United States Environmental Protection Agency (US EPA) published a proposed screening-level methodology in January 2022 to evaluate potential chemical exposures from air pollutants in fenceline communities. In this work, we investigate the suitability of the proposed methodology for making risk determination decisions by applying its tiers to a case study facility located in Texas, which reports the release of hazardous air pollutants such as 1,3–butadiene. While 1,3–butadiene serves as a suitable example chemical due to its high-priority status under TSCA and the public availability of its emissions and ambient measurements data, the methodology presented here is broadly applicable to any chemical. The EPA’s suggested tiered methodology, including its Pre-Screening Integrated Indoor-Outdoor Air Calculator (IIOAC) and its simplified air dispersion model setup (Full-Screening AERMOD), is compared to a more detailed dispersion model setup in AERMOD (Facility-specific AERMOD) following the example provided in the EPA’s 2020 Miscellaneous Organic Chemical Manufacturing Residual Risk and Technology Review (MON RTR), for two years (2019 and 2021). Results show that the IIOAC consistently produces the highest output concentrations (10.75 µg/m3 and 9.69 µg/m3 for years 2019 and 2021, respectively), followed by the TSCA Full-Screening AERMOD (1.04 µg/m3 and 0.74 µg/m3), with the facility-specific AERMOD run producing the lowest output concentrations (0.44 µg/m3 and 0.46 µg/m3). Ambient air concentrations of 1,3–butadiene measured at various nationwide sites with automated gas chromatography (auto-GC) from 2017 to 2021 are also analyzed. All average concentrations of 1,3–butadiene, with the exception of one Texas site in 2021, are found to be below 1 ppb (2.21 µg/m3). Implications: While the TSCA Screening Level Approach provides a necessary initial framework for assessing chemical exposures, incorporating facility-specific modeling and real-world monitoring data can lead to more accurate risk management decisions. This refined approach can ensure that regulatory efforts are both protective of public health and practically feasible for regulated entities.

ABSTRACT The IMPROVE program (Interagency Monitoring of PROtected Visual Environments) tracks long-term trends in the composition and optics of regional haze aerosols in the United States. The absorptance of red (633-nm) light is monitored by filter photometry of 24 h-integrated samples of fine particulate matter (PM2.5). These are collected every third day at about 150 rural and often remote locations. Systematic reanalyses of archived samples have established the reproducibility of the optical absorption measurements across decades and rebuilt instrument systems, with a consistent calibration that is traceable back to 2003. IMPROVE samples for nondestructive sequential analyses by photometry, gravimetry, and X-ray fluorescence are all collected on ring-mounted membranes of expanded PTFE (polytetrafluoroethylene). Although chemically inert, low in blank mass, and optically thin, these collection media yield visibly nonuniform deposits that do not admit direct interpretation according to a naïve “Beer-Lambert” formulation of optical absorption. Most IMPROVE PTFE deposits exhibit fine-scale “pixelation,” a pattern shaped by the perforated metal screen that supports the membrane during sample collection. This paper extends the traditional Beer-Lambert interpretive model to accommodate the patterned deposits generated on PTFE filters by IMPROVE and similar sampling protocols. Implications: The ambient absorption coefficients historically reported from IMPROVE filter samples are based on the conventional Beer-Lambert interpretation of measured transmittance by filter deposits assumed to be uniform. The neglect of observed patterning in actual deposits yields predictable underestimates for the summed absorption cross-sections of the collected particles. This pixelation bias can be substantial for individual samples that are taken from elevated concentrations of absorbing aerosols, near wildfires or urban centers. Over the regional-haze-tracking scale of the predominantly rural IMPROVE network, the aggregate bias relevant to radiative forcing is more moderate, estimated at roughly 10%.

ABSTRACT The R-LINE model, which was released in 2013 as a stand-alone model for roadway-type applications and was based on a set of newly developed dispersion curves, exhibited favorable model performance in a limited set of evaluations. In 2019, the R-LINE model was incorporated as the RLINE source type in EPA’s preferred near-field dispersion model AERMOD. Since its inclusion in AERMOD, the RLINE source type has been tested and compared to other AERMOD source types using multiple data sets and transportation studies. The outcome of these tests is a need to revisit the dispersion parameters used in the original RLINE dispersion curves to address performance issues suggested by comparisons to AREA and VOLUME source types in AERMOD. The work presented here includes corrections to the RLINE vertical wind profiling, harmonization of several aspects of the RLINE formulation with AERMOD’s AREA and VOLUME source types (i.e. the addition of terrain and meander weighting), and updates to the RLINE dispersion parameterization based on a computational optimization routine. The updated RLINE source type is compared with AREA and VOLUME estimates for two hot-spot transportation studies. RLINE modeled estimates are also reevaluated with two of the previous evaluation studies and two additional tracer studies. The updated RLINE formulation leads to improved performance in most cases and closer comparison with the AREA and VOLUME sources. Implications: The RLINE source type was recently added by the EPA to the AERMOD model as a “preferred” model option. Thus, the RLINE source type is now available to the air quality modeling community as a modeling option without any approval required. This paper explains recent changes to the model formulation and provides both an updated and expanded model evaluation. For the updated evaluation, we compare the three AERMOD source types (RLINE, AREA, and VOLUME) for two tracer databases used when the RLINE source was initially created (Caltrans 99 and Idaho Falls). We also add model evaluations for two “new” databases (GM Sulfate and Berkeley Freeway Experiment) to expand the assessments of model performance. Additionally, two model intercomparisons are examined, comparing design concentrations for two real-world highway hot-spot projects for RLINE against the AREA and VOLUME sources, which show much better agreement between the three source types with the updated RLINE model. The work is essential for dispersion model practitioners to understand the specifics of RLINE’s model formulation as well as its performance against the other two AERMOD source types typically used for modeling roadway emissions.