Sulphur Emission Control Areas (SECAs), mandated by the International Maritime Organization (IMO), regulate fuel sulphur content (FSC) to mitigate the environmental and health impact of shipping emissions in coastal areas. Currently, FSC is limited to 0.1% (w/w) within and 0.5% (w/w) outside SECAs, with exceptions for ships employing wet sulphur scrubbers. These scrubbers enable vessels using non-compliant fuels such as high-sulphur heavy fuel oils (HFOs) to enter SECAs. However, while sulphur reduction via scrubbers is effective, their efficiency in capturing other potentially harmful gases remains uncertain. Moreover, emerging compliant fuels like highly aromatic fuels or low-sulphur blends lack characterisation and may pose risks. Over three years, we assessed emissions from an experimental marine engine at 25% and 75% load, representative of manoeuvring and cruising, respectively. First, characterizing emissions from five different compliant and non-compliant fuels (marine gas oil MGO, hydro-treated vegetable oil HVO, high-, low- and ultra-low sulphur HFOs), we calculated emission factors (EF). Then, the wet scrubber gas-phase capture efficiency was measured using compliant and non-compliant HFOs. NOx EF varied among fuels (5200-19700 mg/kWh), with limited scrubber reduction. CO (EF 750-13700 mg/kWh) and hydrocarbons (HC; EF 122-1851 mg/kWh) showed also insufficient abatement. Carcinogenic benzene was notably higher at 25% load and about an order of magnitude higher with HFOs compared to MGO and HVO, with no observed scrubber reduction. In contrast, carbonyls such as carcinogenic formaldehyde and acetaldehyde, acting as ozone precursors, were effectively scrubbed due to their polarity and water solubility. The ozone formation potential (OFP) of all fuels was examined. Significant EF differences between fuels and engine loads were observed, with the wet scrubber providing limited or no reduction of gaseous emissions. We suggest enhanced regulations and emission abatements in the marine sector to mitigate gaseous pollutants harmful to human health and the environment.

This paper addresses the challenges of calibrating low-cost electrochemical sensor systems for air quality monitoring. The proliferation of pollutants in the atmosphere necessitates efficient monitoring systems, and low-cost sensors offer a promising solution. However, issues such as drift, cross-sensitivity, and inter-unit consistency have raised concerns about their accuracy and reliability. The study explores the following three calibration methods for converting sensor signals to concentration measurements: utilizing manufacturer-provided equations, incorporating machine learning (ML) algorithms, and directly applying ML to voltage signals. Experiments were performed in three urban sites in Greece. High-end instrumentation provided the reference concentrations for training and evaluation of the model. The results reveal that utilizing voltage signals instead of the manufacturer\'s calibration equations diminishes variability among identical sensors. Moreover, the latter approach enhances calibration efficiency for CO, NO, NO2, and O3 sensors while incorporating voltage signals from all sensors in the ML algorithm, taking advantage of cross-sensitivity to improve calibration performance. The Random Forest ML algorithm is a promising solution for calibrating similar devices for use in urban areas.

Reliance upon fossil fuels and limited greenspace contribute to poor indoor and outdoor air quality and adverse health outcomes, particularly in communities of color. This article describes justice-informed public health and legal interventions to increase access to greenspace and accelerate the transitions to renewable energy and away from gas appliances.

BACKGROUND: Short-term increases in air pollution are associated with poor asthma and COPD outcomes. Short-term elevations in fine particulate matter (PM2.5) due to wildfire smoke are becoming more common.
OBJECTIVE: Are short-term increases in PM2.5 and ozone in wildfire season and in winter inversion season associated with a composite of emergency or inpatient hospitalization for asthma and COPD?
METHODS: Case-crossover analyses evaluated 63,976 and 18,514 patients hospitalized for primary discharge diagnoses of asthma and COPD, respectively, between January 1999 and March 2022. Patients resided on Utah\'s Wasatch Front where PM2.5 and ozone were measured by Environmental Protection Agency-based monitors. ORs were calculated using Poisson regression adjusted for weather variables.
RESULTS: Asthma risk increased on the same day that PM2.5 increased during wildfire season (OR, 1.057 per + 10 μg/m3; 95% CI, 1.019-1.097; P = .003) and winter inversions (OR, 1.023 per +10 μg/m3; 95% CI, 1.010-1.037; P = .0004). Risk decreased after 1 week, but during wildfire season risk rebounded at a 4-week lag (OR, 1.098 per +10 μg/m3; 95% CI, 1.033-1.167). Asthma risk for adults during wildfire season was highest in the first 3 days after PM2.5 increases, but for children, the highest risk was delayed by 3 to 4 weeks. PM2.5 exposure was weakly associated with COPD hospitalization. Ozone exposure was not associated with elevated risks.
CONCLUSIONS: In a large urban population, short-term increases in PM2.5 during wildfire season were associated with asthma hospitalization, and the effect sizes were greater than for PM2.5 during inversion season.

Microgrids are emerging to mitigate the degradation in grid resiliency and reliability resulting from an increasing frequency of grid outages. Because microgrids incorporate a local source of power generation, the production of electricity is shifting from a centralized to distributed topology, thereby installing power generation resources and the concomitant emissions into heavily populated urban air sheds and residential communities. In this paper, the air quality and public health impacts of a mass deployment of microgrids in an urban air shed are assessed. Candidates to become microgrids are identified for both the near- and long-term deployment, and two microgrid scenarios are considered, differing by the 24/7 prime source of power: (1) combustion gas turbine (CGT)-based microgrids and (2) zero-emission FC-based microgrids complemented by solar PV and battery energy storage. Spatially and temporally resolved emissions from the microgrids are input to an air quality model and assessed for health impacts. The results show that (1) a mass deployment of CGT-based or FC-based microgrids in both the near- and long-term has a relatively small impact on air quality, (2) the health impacts are nonetheless significant for CGT-based microgrids due to the large and dense population of the area, and (3) disadvantaged communities are disproportionately impacted with the deployment of CTG-based microgrids. For example, near-term deployment of CGT-based microgrids results in an increase in the incidence of premature mortality (1 to 5 incidences per month) and an increase of $33 to $56 million per month in health costs. Deploying zero-emission FC-based microgrids mitigates the adverse health impact, prevents several incidences of premature mortality, and results in saving of ~$36M per month rather than a cost per month of ~$50M.

A significant concern in our society is the potential impact on both health and the environment of air pollutants released during the incineration of waste. Therefore, it is crucial to conduct thorough control and monitoring measures. In this context, the objective of this research was to study the evolution of particulate matter (PM2.5) and associated trace elements during the period before and after the installation of an Energy Recovery Plant (ERP). For that, a descriptive and temporal analysis of PM2.5 concentration and composition were performed on two similar areas (impact/control) using the Before-After/Control-Impact (BACI) design and two periods (before from January 01, 2018 to February 06, 2020 and after from December 10, 2020 to September 30, 2022). Results showed a decrease in the levels of PM2.5 and associated trace elements is observed in the impact zone (IZ) and in the control zone (CZ) throughout the study period. In the case of PM2.5, the most notable decrease occurred in the period of the start-up of the ERP, a period that coincides with the confinement and restrictions of COVID, with a subsequent increase in both zones, without reaching the levels observed in the period prior to the start-up of the ERP. Selenium is the only trace element that increases significantly in the IZ. In conclusion, a decrease is observed for all pollutants except selenium in both zones, although less pronounced in the IZ. Since selenium already showed an upward trend in the phase prior to the start of the ERP, it is necessary to investigate its evolution and find out the possible cause.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization.
METHODS: We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups.
RESULTS: After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 μg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 μg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064).
CONCLUSIONS: NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 μg/m3 and PM10 exceeds 55 μg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Growing environmental challenges necessitate increased focus on sustainability education. This study examines the effects of environmental education programs in China on air and water quality perception, waste reduction, and energy consumption reduction. A comparative quantitative design with 650 participants divided into four groups was employed. Data were collected using the Environmental Sustainability Assessment Survey (ESAS) instrument to assess environmental awareness and behavior changes. Statistical tests were used to identify significant differences between groups. Findings showed significant improvements in perceived air and water quality, with web-based programs demonstrating particular success. Waste reduction efforts also varied, with web-based education again proving effective. Energy consumption reduction was most evident in the corporate sector, where leadership in electric vehicles and sustainable transportation played a key role. Supportive government policies and environmental NGOs further highlighted the power of informed environmental decision-making. This study emphasizes the critical role of environmental education in addressing sustainability challenges. It empowers individuals and communities to actively engage in environmental conservation actively, fostering a harmonious relationship between humans and the environment. Our findings have global implications, highlighting education\'s vital role in shaping a sustainable future.

Background. Wildfire smoke events are increasing in frequency and intensity due to climate change. Children are especially vulnerable to health effects even at moderate smoke levels. However, it is unclear how parents respond to Air Quality Indices (AQIs) frequently used by agencies to communicate air pollution health risks. Methods. In an experiment (3 × 2 × 2 factorial design), 2,100 parents were randomly assigned to view one of twelve adapted AQI infographics that varied by visual (table, line, gauge), index type (AQI [0-500], AQHI [1-11+]), and risk level (moderate, high). Participants were told to imagine encountering the infographic in a short-term exposure scenario. They reported worry about wildfire smoke, intentions to take risk-mitigating actions (e.g., air purifier use), and support for various exposure reduction policies. Subsequently, participants were told to imagine encountering the same infographic daily during a school week in a long-term exposure scenario and again reported worry, action intentions, and policy support. Results. Parents\' responses significantly differentiated between risk levels that both pose a threat to children\'s health; worry and action intentions were much higher in the high-risk group than the moderate-risk group in both short-exposure (F = 748.68 p<.001; F = 411.59, p<.001) and long-exposure scenarios (F = 470.51, p<.001; F = 212.01, p<.001). However, in the short-exposure scenario, when shown the AQHI [1-11+] with either the line or gauge visuals, parents\' action intentions were more similar between moderate- and high-risk level groups (3-way interaction, F = 6.03, p = .002). Conclusions. These results suggest some index formats such as the AQHI-rather than the AQI-may better attune parents to moderate levels of wildfire smoke being dangerous to children\'s health. Our research offers insights for agencies and officials seeking to improve current public education efforts during wildfire smoke events and speaks to the critical need to educate parents and help them act short-term and long-term to protect children\'s health.

One of the main factors that affect urban air quality is meteorology. The objective of this study is to understand and characterise the influence that \"Galerna\" (GL) (an abrupt westerly change over the northern coast of Spain) has on the daily variability of the air quality over Bilbao city (northern Spain). A total of 46 one-day periods from 2009 to 2019 during which GL have been analysed. Radon observations at the Bilbao city radiological station were used because radon is a suitable atmospheric tracer by which to assess and characterise air quality dynamics. The cluster analysis of these periods revealed that increases in radon concentrations, mainly in the afternoon, are associated with the occurrence of GL, but that, this increase in the daily variability of radon concentrations in Bilbao is not reflected in all these GL periods. This variability in the impact of the GL scenario on radon concentrations is associated with the location of Bilbao: along the Nervion valley and 16 km from the coast. The analysis of three GL periods using 10-min surface meteorological and radon data showed an anomalous increase in radon with the arrival of maritime winds, which is associated with the process of a progressive accumulation of radon concentrations over the coastal area in the previous days, and the displacement of these air masses inland owing to the development of the GL event. Our results consequently identify the impact of GL on urban air quality in the afternoon, along with the fact that the complex layout of this coastal area, with the presence of valleys and mountains, favours the formation of reservoir layers above the coastal and valley areas, thus influencing on daily variability of air pollution concentrations. These increases in radon concentrations do not present a significant impact on human health.