Emissions from harbour-related activities have an important impact on air quality; therefore, improved knowledge about the coastal microclimate and consequent air pollution dispersion patterns is of utmost importance. In recent years, residents of the southeast urban community of the Port of Aveiro (Portugal) have identified high levels of dust in and around their residences, which has raised their concern regarding the potential effects of air pollution on public health. The citizens’ complaints were linked to fugitive dust emissions from petroleum coke (petcoke), which is usually unloaded or temporarily stored outdoors in the port prior to transportation to a nearby manufacturing plant. Following this, the air quality measurements taken in the area have shown high levels of PM10 concentrations, especially when the wind blew from north and northwest directions. Furthermore, a numerical and physical modelling study has been performed in order to assess the impacts of the transport and storage of petcoke on the local air quality. The modelling results pointed out to a set of potential mitigation measures, namely the construction upwind of different barriers from the petcoke pile. This article presents the characterization of the problem and the management strategies adopted. It also presents the results of modelling assessment to select the most potential effective barrier in order to minimize petcoke dust impact on the surrounding population.

Particulate matter (PM) is one of the most problematic air pollutants in Ireland, and recently the associations between exposure to ambient PM and adverse health outcomes have been more firmly established. Diesel vehicles in particular are known for their significant contribution to overall emissions of PM (PM_2.5) in the atmosphere, and therefore constitute a significant threat to public health and the environment. A recent investigation of national emissions in the road transport sector in Ireland has highlighted that private diesel passenger vehicles contribute the largest proportion of total emissions in both CO₂ and PM of all vehicle categories. Owing to the recent growth in private diesel vehicles since 2008, this vehicle category represents a significant pressure on the quality of the urban environment in Ireland. Determination of the proportion of total PM concentration in urban areas, which has originated from diesel vehicle emissions using source apportionment techniques, is invaluable in assessing the impact of diesel emissions on population exposure. We are generating evidence on the impact of diesel vehicles in Ireland on the exposure of the population to PM_2.5 through field measurement of ambient PM_2.5 and direct sampling of PM_2.5 sources. Here we present a data set of chemical fingerprints of the majorsources of PM_2.5 in Dublin. These include a wide variety of vehicular exhaust emissions and solid fuels including wood, peat and coal, sea spray, mineral dust and road dust, with a particular focus on diesel vehicle emissions. A single analytical technique was employed for the chemical analysis that was carried out here; laser ablation inductively coupled mass spectrometry (LA-ICP-MS), while other PM_2.5 source apportionment studies commonly use a variety of analytical techniques for chemical analysis.

The Bay Area Air Quality Management District (District), the local air pollution control agency for the nine-county region of the San Francisco Bay Area in California, has developed the first multi-pollutant–multi-sector plan. This plan integrates measures to achieve and maintain California state and US ambient air quality standards, reduce smog pollution (ozone and particulate matter) and toxic air contaminants, eliminate disproportionate impacts on communities and reduce greenhouse gases that contribute to the earth’s changing climate. This article describes the plan, focusing on the specific strategies the District and its partner agencies will rely upon to address the threat of air pollution and climate change in the San Francisco Bay Area of California. This plan serves as a model for integrating air pollution and climate change programmes at the local level. The plan also provides a bold vision for addressing climate change by visualizing what the Bay Area may look like in a post-carbon year 2050 – where we will live, how we will travel, what we will produce, and what we will consume.

Kuwait is one of the largest oil producers in the world. However, it is also the tenth most polluted nation in the world, as per a WHO report in 2011 [1], which has created public health concerns in Kuwait. Kuwait Oil Company (KOC), which is involved in the exploration, drilling and production of oil and gas within the State of Kuwait, has undertaken a landmark project in conjunction with the Kuwait Environment Public Authority (KEPA), to develop and implement a regulatory air compliance management programme (ACMP). The ACMP is the first-ever joint venture of its type between the industry and regulators, and it includes development of a system providing real-time measurement of pollution across the country as well as a pioneering national air quality inventory with research-grade dispersion modelling techniques to determine human health risk. Subsequently, an innovative source apportion- ment study is undertaken, utilizing satellite-based techniques to define pollutant source contributions from various sources and develop abatement strategies. The ACMP is a successful demonstration of the implementation of latest technologies like hyperspectral remote imagery for surrogate estimation, remote sensing information for tracking pollutant masses during the project to provide inputs and conduct a comprehensive Human Health Risk Assessment (HHRA) based on US EPA’s Human Health Risk Assessment Protocol (HHRAP).

The purpose of this article is to analyse the correlation of air quality data with the number of emergency medical interventions and the number of patient visits to emergency clinic of the Integrated Emergency Hospital Admission (Croatian acronym: OHBP).

The analysis was conducted on data regarding Slavonski Brod (Croatia) from 1 January to 31 August 2016, obtained from:

(1) System eHitna – emergency medical services interventions

(2) Patients’ visit to OHBP-General Hospital Slavonski Brod

(3) Environmental Protection Agency data regarding air quality for PM2.5, PM10 and H₂S per day.

The number of interventions ranged from 103 to 260 (M = 151), and the number of patients from 90 to 250 per day (M = 133). Overall the number of interventions was 37,482, and overall number of patients 32,757. The values of PM2.5 ranged from 1.73 to 500.11 µg/m³ (M = 18.70), values of PM10 ranged from 3.17 to 520.21 µg/m³ (M = 25.55), and values of H2S ranged from 0.62 to 12.43 µg/m³ (M = 1.49). The values of PM2.5, PM10 and H2S have been analysed also depending on the limit values (25 µg/m3 for PM2.5, 50 µg/m³ for PM10 and 5 µg/m³ for H2S).

The values were within the limit values for PM2.5 in 64% of days, in 80% of days for PM10 and in 93% of days for H2S.

There was a statistically significant weak correlation (r_s = 0.333, p < 0.05) between PM2.5 and the number of patients per day, weak correlation (r_s = 0.334, p < 0.05) between PM10 and the number of patients per day and a weak correlation (r_s = 0.171, p < 0.05) between H2S and the number of patients per day.

There was a statistically significant difference in the number of patients who were provided with medical assistance in the day depending on the values of PM2.5 (p < 0.001) and PM10 (p < 0.001), while for H2S the significance was borderline (p = 0.051).

Prevalence of asthma is quite high in health care settings due to exposure to a wide variety of substances, including cleaning products, latex, medicines, ammonia and solvents. In this cross-sectional study, participants completed a validated questionnaire about their occupation, asthma diagnosis, variability of asthma symptoms at and away from work, and exposure to individual substances in the workplace. Work-related asthma symptoms (WRAS) were defined based on a set of criteria. Principal component analysis (PCA) was conducted to classify different substances into exposure patterns. Multivariable logistic regression analysis was used to evaluate the association between self-reported exposures to substances and asthma outcomes among health care workers. PCA revealed two factors: factor 1 (metal dust, metal fumes, solvents, cleaning agents, ammonia, glues) and factor 2 (disinfectants, latex, medicines). Exposure to factor 1 agents was associated with increased risk of WRAS (crude odds ratio (OR) 5.52, 95% confidence intervals (CI) 2.72–11.19), while exposure to factor 2 agents was associated with non-significant lower risk of WRAS (crude OR 0.58, 95% CI 0.3–1.14). Adjusting by confounders such as parent’s allergy and history of asthma, or smoking, did not appreciably change the ORs. Some agents were associated with increased risk of WRAS, while the lack of association with the exposure to other set of chemicals may be attributed to a number of factors, including healthy worker effect.

Nowadays air pollution is increasing due to anthropogenic activity. Among all air pollutants, nitrogen oxides (NOx) such as NO are predominant. It is well known that those compounds exhibit direct toxic effects on human health. However, microorganisms are also exposed to them, but the effect of NOx on the virulence of air microbiota is still poorly understood. In this study, we evaluated the impact of NO on the adaptability and virulence of an airborne strain of P. fluorescens, MFA76a, by exposition of this strain to 45 ppm of NO₂. The growth kinetics and cultivability were analysed. A decrease of cultivability coupled with an increase of the lag phase was observed suggesting a potential toxicity of NO₂. Since NOx particularly target lipids, the membrane permeability was assessed thanks to Live Dead tests and confocal microscopy. A significant alteration of membrane permeability was observed. Furthermore, more abundant bacterial aggregates were detected compared to the control. Thus, a lipidomic study was performed using MALDI-TOF MS Imaging coupled to HPTLC. Interestingly, bacteria exposed to NO were lacking one putative glycerophospholipid molecule. In agreement with a previous study from Kondakova et al., these data demonstrate the adaptation potential of P. fluorescens MFAF76a to an air pollutant such as NO.

Indoor air quality in subterranean train stations is a concern in many places around the globe. However, because of the specificity of each case, numerous parameters of the problem remain unknown, such as the braking disc particle emission rate, the ventilation rate of the station or the complete particle size distribution of the emitted particles. In this study the problem of modelling PM10 concentration evolution is hence addressed with a particle-mass conservation model which parameters are fitted using a genetic algorithm. The parameters of the model allow to reproduce the dynamics and amplitude of the measured data and comply with realistic bounds in terms of emissions, deposition and ventilation rate.