Journal of the Air & Waste Management Association最新文献

As a significant player in the global shale gas extraction industry, China has achieved a leading position in shale gas production on a worldwide scale. However, China is also facing the challenge of managing a considerable number of oil-based drill cuttings (OBDCs), which are classified as hazardous waste. Without appropriate treatment methods, these materials could cause significant environmental contamination. This review describes the distribution of shale gas in China and the characteristics of OBDCs. It also summarizes the main disposal and resource utilization methods that have been studied. Among various treatment methods, advanced technologies have demonstrated excellent treatment efficiency. However, they are costly and challenging to implement on an industrial scale. Currently, co-processing technology is gradually gaining popularity. At least two companies have adopted this technology and have achieved remarkable results. However, corresponding standards have not yet been established, and require further development. The future development prospect for OBDCs treatment is the complete utilization of resources.Implications: This paper reviews the distribution of shale gas and the characteristics of oil-based drill cuttings in China. The current state of development of traditional oil-based drill cuttings treatment technologies. Finally, we focus on the application and development of synergistic disposal technology in the resource utilization of oil-based drill cuttings. It exactly provides new ideas and references for the management of oil-based drill cuttings, and clarifies the tendency of the future.

Densification of biomass through pelletizing offers a promising approach to producing clean biofuels from renewable resources. This study, which investigates the impact of additive blends on wheat straw pellet making and upgrading the physiochemical properties, has revealed exciting possibilities. Five additives, including sawdust (SD), bentonite clay (BC), corn starch (S), crude glycerol (CG), and biochar (BioC), were chosen for this study. Pellets were made from seven different combinations using a laboratory-scale pellet mill. The resulting pellets' physical and elemental properties were assessed against ISO 17,225-8 standards. Compared to control pellets, additive blends (T₃-T₇) exhibited significant improvements in mechanical durability (80% to 99%), tensile strength (0.36 MPa to 2.09 MPa), and bulk density (244 kg/m³ to 665.21 kg/m³), all meeting ISO standards. Additionally, these blends maintained low fines content (<2%) and water absorption capacity (<2%, except T₁ and T₅). Furthermore, fixed carbon content increased from 11.1% to 30.90%, and energy content rose from 17.02 MJ/kg to 20.36 MJ/kg, which showed a significant synergistic effect of blending additives. These findings underscore the potential of wheat straw as a viable biomass source for bioenergy production through pelletization, offering a hopeful outlook for the future of renewable energy. However, further research is necessary to optimize additive mixing ratios for even greater pellet quality.Implications: The study successfully demonstrated that adding specific materials during wheat straw pelletizing significantly improves the quality of the pellets as a biofuel. Here are the key implications of the statement.Wheat straw is a promising biofuel source: Densification through pelletizing makes wheat straw a viable option for renewable energy production.Additives enhance pellet quality: Sawdust, bentonite clay, corn starch, crude glycerol, and biochar improve the pellets' durability, strength, density, and energy content.Improved pellet properties meet industry standards: The resulting pellets meet ISO standards for mechanical strength, bulk density, and fines content.Synergistic effect of blending: Combining different additives leads to a greater improvement than using them individually.Need for further research: Optimizing the ratios of these additives can potentially create even better biofuel pellets.Overall, the study highlights the potential of wheat straw pelletizing with specific additives as a sustainable and efficient biofuel option. There's room for further improvement, but the initial findings are promising.

Air pollution exposure has been found to be linked with numerous adverse human health effects. Because both air pollution concentrations and the location of human individuals change spatiotemporally, understanding the time-activity patterns (TAPs) is of utmost importance for the mitigation of adverse exposures and to improve the accuracy of air pollution and health analyses. "Time-activity patterns" outlined here broadly refer to the spatiotemporal positions of individuals. In this review paper, we briefly review past efforts on collecting individual TAP information for air pollution and health studies, with a specific focus on California efforts. We also critically summarize emerging technologies and approaches for collecting TAP data. Specifically, we critically reviewed five types of emerging TAP data sources, including call detail record, social media location data, Google Location History, iPhone Significant Location, and crowd-sourced location data. This review provides a comprehensive summary and critique of different methods to collect TAP information and offers recommendations for use in retrospective air pollution and health studies.Implications: In this review paper, we provide a comprehensive overview of approaches for collecting time-activity pattern (TAP) data from individuals, a crucial component in understanding human behavior and its implications across various fields such as urban planning, environmental science, and, particularly, public health in relation to air pollution exposures.Furthermore, our paper introduces and critically evaluates several emerging methods for TAP data collection. These novel approaches, including but not limited to Google Location History, iPhone Significant Locations, and crowdsourced smartphone location data, offer unprecedented granularity in tracking human activities. By showcasing these methodologies and their often not well-recognized weaknesses, we highlight both the potential and limitations of these tools to advance our understanding of human behavior patterns, especially in terms of how individuals interact with their environments. This discussion not only showcases the originality of our work but also sets the stage for future research directions that can benefit from these innovative data collection strategies.

Since 2004, the state of Colorado in the United States of America has created multiple nonattainment State Implementation Plans (SIPs) that are supposed to comprise air pollution mitigation actions, that have so far been unsuccessful at ensuring Front Range Communities have reduced ozone levels to below the United States Environmental Protection Agency (EPA) standards. By interviewing eight stakeholders and decision-makers involved in ozone SIP rulemaking and drawing on secondary literature, this paper examines shortcomings in the SIP process in Colorado. We found that ozone precursor measurement and the modeling of attainment could be improved by better factoring in uncertainties in emissions inventories and conducting appropriate sensitivity analyses that would require more investment of state staff time and resources. Structural issues with the way the process is organized in Colorado limit optimum overlap between state: Air Pollution Control Division (APCD) and quasi-state: Regional Air Quality Council (RAQC) agencies during the SIP process. Specifically, although the RAQC is currently charged with developing and submitting SIPs to the State for approval, it does not have the power to implement control strategies for several key sources and therefore does not have the authority to propose key policies to be included in the SIP. In recent years, Colorado SIPs have largely focused on the bare minimum emissions controls to demonstrate attainment via modeling. Interviewees recommend that state political leaders take more of a leadership role to lower ground-level ozone levels and bring the Denver Metropolitan Area/North Front Range back into attainment with EPA standards.Implications: We evaluate why the State Implementation Plan (SIP) process has failed to achieve the attainment of the ozone standards in the Denver Metropolitan and North Front Range Area. Specifically, through interviewing several experts we identified several problems, namely: 1) errors in emissions inventories and modeling of ozone levels that have resulted in incorrect determinations that the ozone standards would be met with proposed emissions controls, and 2) structural problems in the way the SIP process is organized in Colorado, and the lack of political leadership.

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.

We measured organic compound emissions from a produced-water, evaporative disposal facility's oil-water separation vault in May 2022 and March-May 2023. Produced water is water pulled from the subsurface of a well along with the oil and natural gas; some produced water is disposed of by allowing it to evaporate from surface impoundments. The vault measured in this study separated residual oil from produced water before evaporative disposal. Because the vault's surface contained many potential small emission sources, we used a large plastic chamber to cover the entire vault and simultaneously capture all emissions. We also measured organic compounds in ambient air upwind and downwind of the vault and estimated emissions via a backward Lagrangian stochastic model (Windtrax). The total non-methane organic compound (TNMOC) emission rate from the vault ranged from 0.27 to 3.05 kg/h, averaging 1.99 kg/h in 2022 and 0.49 kg/h in 2023. The average TNMOC emission rate determined by the bLS method was 48% higher than the emission rate determined by the chamber method in 2023 (average of 0.73 kg/h). Still, the range of the chamber results fell within the range of TNMOC emissions from the model. Methanol emissions were much higher than the bLS method, averaging 85.3 g/hr, but were highly variable. We surmise that the water condensation on the chamber retained methanol and biased the results low. The extrapolated annual average emissions of methane, TNMOC, and methanol from the vault were 0.1, 15.5, and 1.4 U.S. tons/yr, respectively, within the range of emissions from uncontrolled oil storage tanks. The extrapolation considers bias in the chamber method and differences across the two years of measurements.Implications: The findings from our study indicate that emissions of non-methane organic compounds (TNMOC) from the oil-water separation vault at the produced-water evaporative disposal facility exhibit significant variability between years, with a notable decline in average emissions from 2022 to 2023. The higher emission rates recorded using the backward Lagrangian stochastic (bLS) model compared to the chamber method suggest that further investigation into measurement techniques is warranted to ensure accurate assessments of emissions. Additionally, the substantial variability in methanol emissions highlights the need for more controlled conditions during sampling to avoid potential biases. Overall, these results imply that while emissions from the vault are within the range of those from uncontrolled oil storage tanks, there is an ongoing necessity for improved monitoring and regulatory practices to mitigate environmental impacts associated with produced water disposal.

Dust emissions from open-pit mining pose a significant threat to environmental safety and human health. Currently, the range of dust suppressants used in coal mining is limited, often failing to account for their suitability across various stockpiles. This oversight results in poor infiltration after application, leading to insufficient crust formation and reduced durability. To explore the permeability of dust suppressant solutions in different stockpiles and develop a broader range of suppressants, numerical simulations were conducted to analyze the effects of liquid properties on infiltration rates. The results showed that increased liquid surface tension promotes infiltration, whereas higher solid-liquid contact angles and liquid viscosity inhibit it. Building on these findings, experimental work was undertaken using a water-based polyurethane with strong adhesion and low viscosity, combined with xanthan gum and polyethylene glycol, to optimize the dust suppressant formulation. The optimal binder formulation was found to contain 1.5% water-based polyurethane, 0.2% xanthan gum, and 1% polyethylene glycol. Infiltration experiments revealed distinct infiltration patterns for the dust suppressant solution in both rock and coal dust. The appropriate dosage of surfactants was also determined. The study indicated that surfactants enhance wettability and significantly reduce the solution's surface tension. For hydrophilic rock dust, moderate surfactant addition improves permeability, while excessive amounts disrupt capillary forces. In contrast, for hydrophobic coal dust, wettability governs infiltration, with surfactants enhancing this property. Based on these findings, dust suppressant solutions suitable for both rock and coal dust were formulated. The formulations demonstrated excellent permeability, consolidation effects, and water resistance, as validated by tests measuring wind erosion resistance, crust strength, and water erosion resistance.Implications: This research examines the efficacy of dust suppressants in various particulate media and the factors influencing penetration performance, offering key insights for industrial and environmental management. As industrialization accelerates, dust generation poses serious risks to health and the environment, highlighting the urgent need for effective suppressants. The study emphasizes a novel aqueous polyurethane binder with strong adhesion and low viscosity.

 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 (PM_2.5). 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%.