Journal of the Air & Waste Management Association最新文献

This study explored the potential of electroplating sludge (ESs) as a novel and effective photocatalyst for the photodegradation of ciprofloxacin in aqueous solutions. The characterization of the ESs was evaluated using sophisticated techniques, such as XRD, SEM, TEM, EDX, FTIR, and BET. ESs-derived photocatalyst materials were found to primarily consist of various metal oxides (Ni-O, Cu-O), which can absorb ultraviolet or visible light. The effectiveness of photodegradation was assessed by measuring the decomposition of Ciprofloxacin (CIP) in aqueous solutions. The results showed that after 180 min of UVA illumination, a remarkable photodegradation effectiveness of 93.87% was achieved for a CIP concentration of 10 mg L^-1, pH = 9, catalyst dose of 1.0 g/L indicating ESs as an effective method for removing CIP from wastewater. The effect of other factors, such as other antibiotics, dyes, and phenol, were also carried out to illustrate high dominant capacity in the degradation of organic compounds. The radical scavenger demonstrated that h⁺ and O₂^●- are the main species for the degradation of CIP. This research presents an adaptable, scalable framework for sustainable electroplating sludge reuse. The easily implementable method promises widespread adoption, enhancing sustainability and resource efficiency by repurposing the treated waste as a photocatalyst for antibiotic degradation.Implications: This research investigates the potential of electroplating sludge (ESs) as a sustainable and effective photocatalyst for the degradation of ciprofloxacin (CIP) in wastewater. This study demonstrates that ESs, containing photoactive metal oxides, can effectively degrade CIP under ultraviolet light irradiation. This research suggests that ESs offer a cost-effective and environmentally friendly approach to wastewater treatment, promoting a circular economy. The findings contribute to the development of sustainable solutions for a cleaner and safer environment.

Continuous ambient sulfur measurements are routinely conducted around the globe at numerous monitoring sites impacted by industrial sources, such as gas and oil processing facilities, pulp and paper mills, smelters, sewage treatment facilities, and concentrated animal feeding operations, as well as by natural sources, such as volcanoes. Various jurisdictions have or plan to establish air ambient quality objectives, guidelines, or standards for total reduced sulfur (TRS) based on odor perception and/or health effects. A conventional TRS monitoring technique is widely used, but few studies have looked at potential biases in the resulting TRS measurements. This paper presents a novel method to quantify total sulfur (TS) concentrations to investigate odor events caused by sulfur compounds and to construct the sulfur budget for sulfur dioxide (SO₂), particle sulfate, hydrogen sulfide (H₂S), and the sum of all remaining reduced sulfur compounds (non-H₂S RSCs). This methodology was tested and improved through multi-year monitoring (2013-2017) at the Oski-ôtin site in the indigenous community of Fort McKay, in the Alberta Oil Sands Region (AOSR). Comparisons with SO₂ and conventional TRS data from two long-term monitoring sites located within five kilometers of Oski-ôtin suggest that the conventional approach for TRS is biased, being low by 20% on average. Based on this new method, SO₂ was observed to be responsible for about 40% of the TS mass in Fort McKay, whereas TRS and particle sulfate were 50% and 10%, respectively. During winter months, when SO₂ plumes emitted from stacks tend to remain elevated due to diminished vertical mixing, TRS dominated the distribution. During periods with TS below 5 ppb, which was 84% of the time, TRS (with H₂S) accounted for 55% of the sulfur mass observed in Fort McKay.Implications: Reduced sulfur compounds have a significant impact on the air quality near various types of industrial emission sources, but their accurate quantification has been hindered by technical problems inherent in standard sulfur measurement methods. We have developed, evaluated and applied a new method for measuring total sulfur. Comparisons in the Alberta Oil Sands suggest that standard methods underestimate total sulfur by typically 20% at this location. Sulfur dioxide (SO₂) was observed to be responsible for about 40% of the total sulfur mass in Fort McKay, while total reduced sulfur and particulate sulfate made up 50% and 10%, respectively.

Acrylonitrile (AN) is a vinyl monomer used in the manufacture of polymers that have a wide variety of applications in the industrial, consumer, and automotive realms. Acrylonitrile was recently proposed to be designated as a high-priority substance for risk evaluation by the U.S. Environmental Protection Agency (EPA) under the Toxic Substances Control Act (TSCA). Past research has characterized worker population's exposure to acrylonitrile; however, there has been limited assessment of the general population's exposure. The objective of this study was to characterize general population exposure to acrylonitrile via the ambient air and to assess the suitability of EPA monitoring and modeled data for use in regulatory risk assessment. This study used EPA's air monitoring data from its Air Quality System (AQS) from the past 11 years and modeled data from EPA's 2020 AirToxScreen assessment. Acrylonitrile was seldom detected in ambient air samples, as only 13% of air samples from 2013 to 2023 detected acrylonitrile. Additionally, only 0.27% of samples exceeded the Agency for Toxic Substances and Disease Registry (ATSDR) Draft Minimal Risk Level (MRL) for acrylonitrile of 0.9 ppb. Most of the samples exceeding the Draft ATSDR MRL were identified as industrial-owned monitors; however, the number of exceedances has been steadily decreasing from 2013 to 2023. EPA's AirToxScreen modeled results were typically orders of magnitude lower than those measured by AQS monitors. Quantitative limitations with the air sampling methods and the potential for non-industrial sources to contribute to ambient air levels, which are not included in the AirToxScreen, may contribute to discrepancies. Given these limitations, some caution may be considered in the use of AirToxScreen exposure estimates for acrylonitrile. Overall, findings from this study suggest that general population exposure to acrylonitrile from the ambient air is low and AQS data is well suited for general population exposure evaluations.Implications: Acrylonitrile was recently proposed to be designated as a high-priority substance for risk evaluation by the U.S. EPA under TSCA. Past research has characterized the health effects of acrylonitrile and the worker population's exposure to it. However, there has been limited assessment of the general population's exposure to acrylonitrile. The objective of this study was to characterize general population exposure to acrylonitrile via the ambient air and to assess the suitability of EPA monitoring and modeled data for use in regulatory risk assessment. Overall, key findings from this study suggest that general population exposure to acrylonitrile from the ambient air is low and EPA's AQS data is well suited for general population exposure evaluations. These results benefit the general public in understanding their potential exposure to acrylonitrile, the EPA in informing their TSCA risk evaluation for acrylonitrile, and other researchers aiming to

Biogas can be used for complementary load-balancing with renewable intermittent power, thus maintaining overall energy output stability. However, biogas load balancing is typically used in small-scale distributed energy systems, constrained by factors such as technology and land requirements, making it challenging to scale up. Therefore, this study proposes a closed-loop ecological cycle system, where biogas provides load leveling support for large-scale intermittent power sources in desertified regions dominated by animal husbandry. The biogas slurry and residue produced are used for land restoration and subsequent cultivation of high-quality economic crops, with the resulting straw used for the next round of biogas production. This study conducts an economic assessment of the aforementioned system and analyzes a case study of a load-balancing biogas project in Northwest China. Accounting results indicating that the system's net present value is 0.108 million yuan/m³, internal rate of return is 0.60%, and payback period is 22 years. Additionally, sensitivity backward deduction analysis identified the reasonable value ranges for key system parameters. According to the results, we offer management recommendations to promote the proposed system, supporting innovative biomass energy utilization and enhancing renewable energy stability.Implications: This research introduces a novel closed-loop ecological cycle system that integrates large-scale peak-shaving biogas with renewable energy sources, offering a sustainable solution for enhancing energy stability and environmental sustainability in desertified areas. The study's economic evaluation reveals the critical role of ecological restoration costs in the overall viability of such systems, indicating the necessity for policy support to make them economically attractive. Our findings suggest that targeted subsidies, based on the quantified ecological benefits, are essential for incentivizing the adoption of this model. By providing specific conditions under which the system is economically feasible, this work informs policymakers on how to design effective incentive structures, thereby promoting the wider application of biogas and contributing to the goals of sustainable development and climate resilience. The research underscores the importance of integrating economic and ecological considerations to achieve long-term sustainability, making it a valuable reference for future energy policies and practices.

To achieve sustainable development in the electric vehicle (EV) industry, this study assesses the environmental impacts of retired electric vehicle batteries (EVBs) throughout the life cycle. The life cycle assessment (LCA) with the ReCiPe method is implemented with environmental impacts: CO_2eq emissions, human toxicity, terrestrial acidification, particulate matter (PM) formation, metal depletion, and fossil depletion. Four EOL management scenarios, namely the landfilling, remanufacturing, repurposing, and recycling processes, are examined with the background data obtained from the Ecoinvent database v3.6 and data collected from secondary sources. The study results reveal that the landfilling scenario is highly harmful to humans and due to its highest environmental impacts, specifically CO2 emission (2,236 kg CO_2eq) from the material extraction process. In contrast, the recycling scenario is the most environmentally friendly scenario, as it reduces the human toxicity (45,934 kg 1,4-DB_eq), terrestrial acidification (425 kg SO_2eq), and metal depletion (20,129 kg Fe_eq), achieving the lowest final impact score of -277. The study further examines the recycling scenario with different energy mixes, i.e. natural gas, coal, and renewable energy. The results suggest that the complete use of renewable energy could improve the final impact value to -281.1. The results also recommend the remanufacturing scenario as it reduces CO_2eq emission by 1,193 kg CO_2eq. The government may utilize the study results to enhance the circular economy of retired EVBs through various strategies to compete in the global market. A comprehensive evaluation of EOL management practices of retired EVBs offers valuable insights for policymakers and stakeholders to minimize the ecological footprint of the EV industry and support Thailand's sustainability goals. A future study may be performed to compare the EOL management scenarios with actual practices and suggest suitable improvements. The policy-based simulations could be implemented to examine long-term impacts of EOL management practices in Thailand.Implications: This study examines the end-of-life management of electric vehicle batteries (EVBs) through remanufacturing, repurposing, and recycling scenarios. The results show that the recycling scenario is the most effective EOL strategy for retired EVBs as it generates the lowest human toxicity, terrestrial acidification, and metal depletion. Alternatively, the remanufacturing scenario is the most suitable scenario when CO2eq emission is a major concern. The results also recommend at least half of renewable energy to be used in electricity production to improve the final impact of this study.

Bioenergy or green fuel has been considered the fuel of the future for being a type of renewable energy that contributes to the preservation of the environment as it helps to reduce greenhouse gas emissions. In this way, biogas offers a potential alternative to fossil fuels from anaerobic digestion (AD) bioprocess, which allows the action of several microorganisms in the transformation of substrates into biogas and secondary bioproducts. Over the years, researchers have discussed that low yields in AD are associated with different factors such as type of wastewater, reactor configuration, substrate concentration, temperature, organic loading rates, and biomass concentration inside of the reactor. In this way, to better conduct the AD, studies point to the reactor configuration as one of the factors in the determination of high biogas production for a long period. Understanding and knowing the type of reactor and how the parameters such as biomass accumulation and immobilization, pH, or temperature occur in the system would provide information and can help to improve the bioenergy production in different systems. Moreover, research opportunities about different technologies are essential for the anaerobic digestion of many substrates and the stability of interest production. Thus, this type of scientific study gives a broad overview of the principal systems used in the AD process and information about the circular economy in the production of biogas in the world. Important considerations are highlighted.Implications: The review paper provides information about the scenario of biogas in the world state-of-art and the biogas production from AD. Afterward, an extensive analysis of different and principal types of reactors applied to the AD process, aimed at presenting an overview of the advantages and disadvantages of each configuration intending to gain new insights to improve traditional reactors or propose novel ones. This article enables us to have a perspective about the different technologies available and about new alternatives from an operational point of view for bioenergy from AD, not only in bench studies or pilot scale studies but also at an industrial level. Thus, this type of scientific study gives a broad overview of the principal systems used in the AD process and information about the circular economy in the production of biogas in the world.

This study investigated the feasibility of using/reusing commercial activated carbon (CAC) for the capture of high molecular weight and high-boiling point volatile organic compounds (HBPVOCs). The CAC was first characterized using proximate analysis, heat value analysis, iodine value analysis, element analysis, inductively coupled plasma spectrometry, and specific surface area analysis. We then assessed the adsorption/desorption performance of a CAC-based PSA system for the removal of Butyl Cellosolve (BCS), a HBPVOC commonly used in paints, coatings, cleaners, and industrial processes. This involved deriving the BCS adsorption capacity of CAC as a function of adsorbent quantity (2.5, 5, and 10 g), flow rate (4, 6, and 8 L/min), and pressure (1.3, 2.3, and 3.4 kg/cm²). The BCS adsorption capacity of the CAC varied with pressure as follows: 1.3 kg/cm² (652.85 mg/g), 2.3 kg/cm² (817.20 mg/g) and 3.4 kg/cm² (1324.05 mg/g). The adsorption mode most closely resembled pseudo-first-order kinetics (i.e. single-layer physical adsorption). Desorption was performed using an adjustable tubular high-temperature furnace under a nitrogen atmosphere (0.93 kg/cm²). Following desorption with a set desorption duration of 1 hr, the BET values varied with temperature as follows: 350°C (75.58% of the original value) and 450°C (86.04% of the original). Desorbed CAC (DCAC) was also examined to detect changes in pore structure due to the effects of recycling. We obtained breakthrough curves and a dsorption capacity curves of CAC as functions of flow rate and pressure. We also investigated adsorption performance under pressure swing conditions from the perspective of reaction kinetics and density functional theory. Our results demonstrate the efficacy of CAC in the adsorption of BCS as well as the recyclability of this material.Implications: This study demonstrates the potential for reusing commercial activated carbon (CAC) to capture high molecular weight and high-boiling point volatile organic compounds (HBPVOCs). Through comprehensive characterization and performance evaluation, we found that CAC effectively adsorbs Butyl Cellosolve (BCS), a common industrial solvent, with adsorption capacity increasing with pressure. The adsorption process follows pseudo-first-order kinetics, indicating single-layer physical adsorption. Additionally, the study highlights the recyclability of CAC, as desorption and subsequent analysis revealed minimal changes in pore structure, maintaining a significant portion of its original BET value. These findings suggest that CAC is not only effective for BCS adsorption but also sustainable for repeated use, offering an efficient and eco-friendly solution for managing industrial HBPVOCs.

Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more effectively than traditional interpretation methods, which face challenges like high workloads and poor repeatability. In this study, we aim to enhance the inventorying of Agricultural Plastic Greenhouses (APGs) by improving the extraction accuracy of their locations and numbers through remote sensing techniques. Utilizing GF-7 satellite imagery, we propose an enhanced U-Net convolutional neural network (CNN) model that incorporates edge information expansion and a joint loss function to optimize performance. The primary objective is to provide a rapid and accurate method for mapping APGs, which is crucial for effective agricultural management and environmental monitoring. The U-Net network's accuracy was enhanced by 1.1% after expanding 3 × 3 sample edge information, and further by 1.9% by combining edge extension and loss function constraints. Our results demonstrate that the modified U-Net model significantly improves extraction accuracy compared to traditional methods, thereby facilitating better inventory management and planning for agricultural cash crops. This advancement not only supports farmers in optimizing resources but also contributes to sustainable agricultural practices by enabling precise monitoring of APG distribution.Implications: Compared to traditional interpretation methods, which suffer problems such as heavy workloads, small adaptation ranges and poor repeatability, deep learning network models can better extract target features from remote sensing images. In this study, we used GF-7 image data to improve the traditional U-Net convolutional neural network (CNN) model. The Canny operator and Gaussian kernel (GK) function were used for sample edge expansion, and the binary cross-entropy and GK functions were used to jointly constrain the loss. Finally, APGs were accurately extracted and compared to those obtained with the original model. The results indicated that the APG extraction accuracy of the U-Net network was improved through the expansion of sample edge information and adoption of joint loss function constraints.

We estimate methane emissions for urban waste treatment facilities from mobile in situ atmospheric concentration measurements using an inverse Gaussian plume methodology at facilities in Southern Ontario, Canada. We use these emission rates to assess and improve the existing high-resolution methane inventories for waste sources throughout Southwestern Ontario. Our measurements encompass tens of thousands of kilometres worth of mobile survey data collected over 7 years, including more than 650 downwind transects where we surveyed 14 active landfills, 11 closed landfills, 2 organic waste processing facilities, 3 open-air windrow compost facilities, and 11 water resource recovery facilities. These sources account for 77% of the active landfills within Southern Ontario, which is estimated in inventories to be the largest source of methane emissions in the region. Within the Greater Toronto Area (GTA) megacity, the measured facilities represent about 52% of the total inventoried non-wetland methane emissions. We find that emissions from closed landfills are lower than inventory estimates, with significant implications for the methane budget in the GTA. We update the Facility Level and Area Methane Emissions for the GTA inventory with our measured emissions rates, which results in a 54% decline in the solid waste emissions, effecting a 35% lower estimate for the total anthropogenic methane emissions in the region. We attribute the bulk of this difference to a single facility: the Keele Valley landfill. Our atmospheric measurements serve as a metric for evaluating the discrepancies between four facility level and two high resolution gridded methane emission inventories. We find that the facility level first-order decay model maintained by Environment and Climate Change Canada (ECCC) to be the most consistent with our measured emission rates at landfills, and the self-reported emissions to the Greenhouse Gas Reporting Program of ECCC to be the least consistent with our measurements.Implications: We present estimates of atmospheric measurement derived methane emissions for multiple waste processing facilities in Canada. We investigate six emission inventories and models. Based on our atmospheric observations of landfills, we show that the self-reported methane emissions are not well correlated with our measured emissions, and that the first order decay models used in official emissions reporting are much better correlated. One of the most critical findings in this work is that methane emissions from the Keele Valley Landfill, assumed in some inventories to be the second largest anthropogenic source of methane in the country, are significantly less than predicted.

Urbanization and infrastructure projects generate huge amount of construction and demolition waste (CDW), posing significant challenges for the environment and human health. In order to reduce the environment and safety risks caused by the CDW landfills, this study was amid to utilize plant roots to develop a root-CDW-soil system for strengthening the CDW and enhancing the slope stability of CDW landfills. A series of experimental analyses were conducted, focusing on shear tests of root-soil composites under various moisture conditions and root content ratios. The results indicate that the inclusion of ryegrass roots plays a critical role in significantly enhancing the shear strength of the soil, and the soil samples reinforced with 0.6 g of ryegrass roots exhibited a shear strength increase of up to 35% compared to the unreinforced samples. The slope stability treated by the plant roots was evaluated by finite element simulations under different rainfall conditions. The factor of safety (FoS) for reinforced slopes increased from 1.18 to 1.59 after five days of heavy rainfall (480 mm/d), highlighting the significant improvement in stability provided by the root systems. These findings suggest that the root-soil system offers a sustainable solution for slope management, reducing risks associated with construction waste and extreme weather conditions.Implications: Urbanization and infrastructure projects generate significant waste, posing environmental and safety challenges. This study investigates the enhancement of slope stability through the integration of ryegrass root systems. The findings indicate that ryegrass roots substantially improve soil shear strength and overall slope stability. Furthermore, the study demonstrates that these root systems enhance resilience to heavy rainfall, thereby mitigating the risk of slope failure. These results suggest that plant root systems offer a sustainable solution for slope management, effectively addressing environmental concerns related to construction waste and extreme weather conditions. This research provides a comprehensive understanding of the physical and mechanical properties of root-soil composites, thereby promoting their practical application in slope stabilization.