Journal of the Air & Waste Management Association最新文献

With the acceleration of industrialization and population growth, there has been a notable surge in municipal solid waste (MSW) production globally. This necessitates the development of efficient waste management strategies that align with sustainable economic, environmental, and social goals. Implementing sorting and source separation policies serves as foundational steps toward optimizing material flow and resource utilization. In industrial areas, waste generation around a primary source may improve policy implementation and participation. Given the unique strategic context of port environments, Bahregan Port in Iran was selected as a case study to evaluate the proposed methodology. Three integrated scenarios were formulated and prioritized using the ELECTRE-I model: currently practiced collection method, and segregated collection followed by source separation of MSW into two or three groups. The analysis identified the third scenario as the most effective approach. Remarkably, when evaluating the results under optimistic and pessimistic conditions, the ranking of preferences remained consistent across scenarios in the optimal state. Under pessimistic conditions, all scenarios received identical scores, indicating significant uncertainty in criteria weights. Furthermore, sensitivity analysis revealed that criteria such as the raw material sources protection, emissions in the waste separation sector, and greenhouse gas emissions were highly influential. Interestingly, criteria with the highest weighting did not always dictate the final scenario selection. External factors, such as expert opinions on specific criteria, played a pivotal role in scenario prioritization. This research serves as a foundational study for source separation initiatives, offering practical and technically viable strategies to enhance environmental sustainability within industrial settings.Implications: Rising industrialization and population growth have led to increased municipal solid waste (MSW) production worldwide. To address this, efficient waste management strategies are essential, focusing on sustainability and resource optimization through sorting and source separation policies. By prioritizing the scenario of segregated collection followed by source separation - industrial areas can optimize material flow and resource utilization. The study highlights the influence of criteria like raw material protection, emissions, and greenhouse gases, making this research foundational for enhancing environmental sustainability in industrial settings. This study provides practical strategies for enhancing environmental sustainability in industrial settings through source separation initiatives.

Previous research on respiratory system mortality primarily focused on understanding their combined effects and have neglected the fact that air pollution mixtures are interrelated. This study used Bayesian kernel machine regression (BKMR) to analyze the relationship between air pollutant mixtures and respiratory mortality in Hangzhou, China from 2014 to 2018. The results showed a significant association between pollutant mixtures and respiratory system mortality primarily driven by PM_2.5 and SO₂. The joint exposure of air pollutants was positively correlated with respiratory system mortality at lag 01 and lag 02 days. The estimated joint effects of log-transformed mixture air pollution exposure on log-transformed respiratory system mortality increased from -0.02 (95% CI: -0.08-0.02) and -0.01 (95% CI: -0.05-0.04) at the 25th percentile to 0.06 (95% CI: 0.01-0.12) and 0.04 (95% CI: -0.001, 0.09) at the 75th percentile. Additionally, there was evidence of an interaction between O₃ and PM₁₀. This study confirms that exposure to multiple pollutants is a significant public health problem facing the Hangzhou population given the compounded effect proven with regression analysis, while furthermore, the control of PM_2.5 and SO₂ also represents a serious concern.Implications: Evidence indicates interactions between O₃ and PM₁₀. This study demonstrates that exposure to multiple pollutants exerts combined effects on the public health of the Hangzhou population, highlighting the importance of controlling PM_2.5 and SO₂.

The edible mushroom industry is the sixth largest after grain, cotton, oil, vegetables and fruits, and the annual production of edible mushrooms in China exceeds 40 million tons. Edible mushroom cultivation produces a class of by-products consisting mainly of mycelium remnants and lignocellulosic waste, known as Spent Mushroom Substrate (SMS) or Spent Mushroom Compost (SMC). SMS/SMC is rich in nutrients and active ingredients and has an extremely high recycling potential. This review paper summarizes SMS recycling strategies from the perspectives of "environmental remediation" and "circular economy", and briefly discusses the legitimacy, possible challenges and future research of SMS recycling. It is hoped that this will assist researchers in related fields and promote the development of the SMS recycling industry, thereby contributing to sustainable environmental and economic development.Implications: The efficient management of SMS is important for many countries around the world, particularly major mushroom producing countries. Traditional disposal methods (incineration, burial, piling) can cause serious damage to the environment and waste resources. The correct disposal method can protect the natural environment and provide certain economic benefits. This study presents the main methods of SMS processing from both an "environmental remediation" and "circular economy" perspective. In general, this paper emphasizes the importance of SMS processing, introduces the current mainstream processing methods and briefly discusses the legality of their processing methods.

Using a high-resolution, 1.33 km by 1.33 km coupled Weather Research and Forecasting-Community Multi-scale Air Quality Model (WRF-CMAQ), we quantify the impact of emissions of nitrogen oxides (NOx) from high energy demand day (HEDD) electricity generating units (EGU) and onroad vehicles on ambient ozone air quality in the Long Island Sound Tropospheric Ozone Study (LISTOS) region covering New York City (NYC); Long Island, NY; coastal Connecticut; and neighboring areas. We test sensitivity scenarios to quantify HEDD EGU NOx contributions to ozone: (1) zero out HEDD EGU emissions, (2) dispatch HEDD EGUs starting with the lowest NOx emitting units first, (3) reduce onroad emissions by 90%, (4) combine zero out HEDD EGU emissions and reducing onroad emissions by 90%, and (5) dispatch HEDD EGUs starting with the lowest emitting units coupled with a reduction in onroad emissions by 90%. Results determine that HEDD EGUs lead to highly localized impacts on ambient concentrations of ozone while onroad emission reductions lead to large-scale regional concentration impacts. Further, reducing onroad emissions by 90% leads to spatially smaller VOC-limited regions and spatially larger transitional and NO_X-limited regions around NYC. Despite the limited scale at which the EGU emission reductions occur, modifying HEDD EGU NO_X emissions still provides substantial benefits in reducing ozone concentrations in the region, particularly at elevated ozone concentrations above 70 ppb.Implications: High-resolution coupled meteorology-chemistry modeling was used to quantify the impacts of high energy demand day (HEDD) electricity generating units (EGUs) and onroad transportation emissions changes on ozone air quality in the LISTOS region. Despite being highly localized and variable, HEDD EGUs NO_X emissions sensitivity tests led to quantifiable changes in ozone. Further, reducing onroad emissions by 90% produced large decreases in ozone concentrations and led to a more NO_X-sensitive ozone photochemical regime. With a transition to greater NO_X-sensitivity, urban NO_X-titration weakens and ozone is more likely to decline with the removal of additional NO_X from sources like HEDD EGUs.

A real-time air quality forecasting system was developed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to provide support for flight planning activities during the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) and NASA Synergistic TEMPO Air Quality Science (STAQS) 2023 field campaigns. The forecasting system operated on two separate domains centered on Chicago, IL, and New York City, NY, and provided 72-hour predictions of atmospheric composition, aerosols, and clouds. This study evaluates the Chicago-centered forecasting system's 1-, 2-, and 3-day ozone (O₃) forecast skill for Chiwaukee Prairie, WI, a rural area downwind of Chicago that often experiences high levels of O₃ pollution. Comparisons to vertical O₃ profiles collected by a Tropospheric Ozone Lidar Network (TOLNet) instrument revealed that forecast skill decreases as forecast lead time increases. When compared to surface measurements, the forecasting system tended to underestimate O₃ concentrations on high O₃ days and overestimate on low O₃ days at Chiwaukee Prairie regardless of forecast lead time. Using July 25, 2023, as a case study, analyses show that the forecasts underestimated peak O₃ levels at Chiwaukee Prairie during this regionwide bad air quality day. Wind speed and direction data indicates that this underestimation can partially be attributed to lake breeze simulation errors. Surface fine particulate matter (PM_2.5) measurements, Geostationary Operational Environmental Satellite-16 (GOES-16) aerosol optical depth (AOD) data, and back trajectories from the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model show that transported Canadian wildfire smoke impacted the Lake Michigan region on this day. Errors in the forecasted chemical composition and transport of the smoke plumes also contributed to underpredictions of O₃ levels at Chiwaukee Prairie on July 25, 2023. The results of this work help identify improvements that can be made for future iterations of the WRF-Chem forecasting system.Implications: Air quality forecasting is an important tool that can be used to inform the public about upcoming high pollution days so that individuals may plan accordingly to limit their exposure to health-damaging air pollutants. Forecasting also helps scientists make decisions about where to make observations during air quality field campaigns. A variety of observational datasets were used to evaluate the accuracy of an air quality forecasting system that was developed for NOAA and NASA field campaigns that occurred in the summer of 2023. These evaluations inform areas of improvement for future development of this air quality forecasting system.

The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations - near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5^th to 95^th percentiles] = 2.08 [2.0-10.9] μg m^-3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 - 1.8] μg m^-3). Other species, including criteria pollutants ozone (O₃), carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and fine particulate matter (PM_2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles.Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source - diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems.Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.

Infectious healthcare waste (IHCW) poses a significant biohazard and public health risk. This study examines IHCW formation and influencing factors in Hungarian inpatient healthcare institutions. Factors such as hospital type, regional location, indicators related to patient traffic, educational activity, patients of certain types of medical specialties, and healthcare-associated infections (HAIs) were examined. Univariate and multivariate statistical methods identified significant predictors of IHCW occurrence. The generation rate of IHCW ranged from 0.15 to 0.81 kg/bed/day nationally, and it increased by 40.74% between 2017 and 2021, significantly impacted by the COVID-19 pandemic. The data also showed that as the number of beds increased, the IHCW production rate increased proportionally. The results indicate that IHCW generation rates vary significantly by hospital type, with university hospitals producing the most waste. The incidence of HAI multidrug-resistant (MDR) bacterial infections emerged as the primary driver of IHCW generation, along with educational activity, the number of intensive care unit patients, and regional differences. The Southern Great Plain region had the highest IHCW production (0,42 kg/bed/day) among the seven regions studied. The study highlights the critical impact of HAI MDR infections on IHCW production, emphasizing the need for targeted waste management in high-risk areas. Regional differences indicate the necessity for tailored strategies to address local waste management challenges. This study provides essential insights into IHCW formation and influencing factors in Hungary, offering valuable information for policy and practice.Implications: Nowadays, one of the main problems related to waste management is the uncontrollable amount of waste generated in the healthcare sector. Infectious healthcare waste (IHCW) represents a significant biological hazard and a high public health risk, both on an individual and a community level, so a more precise knowledge of these risks is extremely important. In the Central European region, very few studies have dealt with the infectious waste generated in the healthcare sector, and this is the first such research in Hungary. The primary aim of this study is to measure the amount of IHCW produced in various regions and hospital types in Hungary, and to examine the general and specific factors that affect the generation rate of this waste. The findings reveal that IHCW generation rates (GR) vary considerably across different hospital types and regions. This highlights the need for targeted waste management practices in individual institutions. In addition, the study emphasizes the importance of developing region-specific waste management strategies in view of regional inequalities. A crucial insight from the study is that the incidence of healthcare-associated infections (HAIs), particularly multidrug-resistant (MDR) bacterial infections, has the most significant i

Widespread North American wildfires in 2023 led to exposure to ambient wildfire smoke outside of traditionally wildfire-prone regions. The objective was to evaluate levels of indoor air pollutants in relation to ambient wildfire smoke exposure in eastern Massachusetts. Using a real-time multipollutant sensor system in five Boston area households, this study assessed indoor fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and total volatile organic compound concentrations (TVOC) two days before and during days of hazardous wildfire smoke exposure (smoke days). The relationship between ambient PM_2.5 from regulatory monitors and indoor PM_2.5 before and during smoke days was investigated by mixed effects linear regression. During smoke days and the preceding non-smoke days, median indoor PM_2.5 was 9.9 µg/m³ and 3.5 µg/m³ (p < 0.001), respectively; median NO₂ was 20.5 ppb and 18.4 ppb (p = 0.11); median TVOC was 6,715 µg/m³ and 5,361 µg/m³ (p = 0.35). A 1% increase in ambient PM_2.5 was associated with a 0.93% increase in indoor PM_2.5 on smoke days (95% CI, 0.54%-1.32%) and a 0.34% increase on non-smoke days (95% CI, 0.17%-0.66%), though interaction testing of smoke day status was not statistically significant (p = 0.14). In Northeastern US homes, indoor PM_2.5 increased significantly during ambient wildfire smoke exposure, which may reflect increased infiltration and increased indoor particle-generating activities during smoke days.Implications: This study reports on household exposure to wildfire smoke in eastern Massachusetts, finding that indoor PM_2.5 more than doubled compared to preceding non-smoke days, while indoor NO₂ and TVOC did not significantly rise. Though the generalizability of this study is limited by the small number of homes studied, the findings suggest that more investigation is needed to understand indoor air pollution during future wildfire smoke exposure in regions not traditionally wildfire-prone and to inform mitigation efforts.