A swine production system had 3 sections located a few kilometers apart. Sections A and C contained several thousand sows and nursery and finishing pigs. Section B, located between the other 2 sections, was the smallest and had 6 finishing sites and 2 sow sites. The entire system was infected with porcine reproductive and respiratory syndrome virus, Mycoplasma hyopneumoniae, and Actinobacillus pleuropneumoniae. Section B was depopulated, cleaned, disinfected, and repopulated with negative gilts. Despite extreme measures, recontamination occurred for each pathogen, with aerosol considered the most plausible contamination source.
Transmission suspectée d’agents pathogènes porcins par aérosol : un cas de terrainUn système de production porcine comportait 3 sections situées à quelques kilomètres l’une de l’autre. Les sections A et C contenaient plusieurs milliers de truies et de porcs en maternité et en finition. La section B, située entre les 2 autres sections, était la plus petite et comptait 6 sites de finition et 2 sites de truies. L’ensemble du système était infecté par le virus du syndrome reproducteur et respiratoire porcin, Mycoplasma hyopneumoniae et Actinobacillus pleuropneumoniae. La section B a été dépeuplée, nettoyée, désinfectée et repeuplée de cochettes négatives. Malgré des mesures extrêmes, une recontamination s’est produite pour chaque agent pathogène, les aérosols étant considérés comme la source de contamination la plus plausible.(Traduit par Dr Serge Messier).

OBJECTIVE: Drug inhalation is generally accepted as the preferred administration method for treating respiratory diseases. To achieve effective inhaled drug delivery for an individual, it is necessary to use an interdisciplinary approach that can cope with inter-individual differences. The paper aims to present an individualised pulmonary drug deposition model based on Computational Fluid and Particle Dynamics simulations within a time frame acceptable for clinical use.
METHODS: We propose a model that can analyse the inhaled drug delivery efficiency based on the patient\'s airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient\'s breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied.
RESULTS: The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions.
CONCLUSIONS: The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient\'s lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient\'s changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.

The emission reduction of atmospheric pollutants during the COVID-19 caused the change in aerosol concentration. However, there is a lack of research on the impact of changes in aerosol concentration on carbon sequestration potential. To reveal the impact mechanism of aerosols on rice carbon sequestration, the spatial differentiation characteristics of aerosol optical depth (AOD), gross primary productivity (GPP), net primary productivity (NPP), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and meteorological factors were compared in the Sanjiang Plain. Pearson correlation analysis and geographic detector were used to analyze the main driving factors affecting the spatial heterogeneity of GPP and NPP. The study showed that the spatial distribution pattern of AOD in the rice-growing area during the epidemic was gradually decreasing from northeast to southwest with an overall decrease of 29.76%. Under the synergistic effect of multiple driving factors, both GPP and NPP increased by more than 5.0%, and the carbon sequestration capacity was improved. LAI and FPAR were the main driving factors for the spatial differentiation of rice GPP and NPP during the epidemic, followed by potential evapotranspiration and AOD. All interaction detection results showed a double-factor enhancement, which indicated that the effects of atmospheric environmental changes on rice primary productivity were the synergistic effect result of multiple factors, and AOD was the key factor that indirectly affected rice primary productivity. The synergistic effects between aerosol-radiation-meteorological factor-rice primary productivity in a typical temperate monsoon climate zone suitable for rice growth were studied, and the effects of changes in aerosol concentration on carbon sequestration potential were analyzed. The study can provide important references for the assessment of carbon sequestration potential in this climate zone.

Exposure to bioaerosols has been associated with the occurrence of a variety of health impacts, including infectious illnesses, acute toxic effects, allergies, and cancer. This study aimed at evaluating airborne bacteria and fungi populations at different indoor and outdoor sites on a college campus in Bengaluru, India. Bioaerosol samples were collected using a two-stage Andersen air sampler; and isolates were identified using standard procedures. Six air samples and meteorological data were collected in March and April 2014 to examine the effects of temperature and relative humidity on bioaerosol concentration using linear regression modeling. Among all sites, the canteen showed the highest bioaerosol levels both indoors and outdoors. Specific bacterial identification was not possible, but gram staining and microscopic analysis helped to identify gram positive and gram negative bacteria. The most prevalent fungal species in the samples were Cladosporium, Aspergillus niger, Penicillium, Rhizopus, Fusarium, Mucor, and Alternaria. Due to the impact of weather conditions, such as temperature and relative humidity, the bioaerosol concentration varied greatly at each site according to the regression model. The indoor bioaerosol concentrations at all sites exceeded the values established by the American Industrial Hygiene Association (< 250 CFU/m3 for total fungi and < 500 CFU/m3 for total bacteria). Higher concentrations of bioaerosols may be attributed to the transportation of microbes from the ground surface to suspended particles, the release of microbes from the respiratory tract, higher rate of shredding of human skin cells, and many other factors.

With the insidiously growing impact of urban development on the environment, the issue of air quality has attracted extensive attention nationally and globally. It is of great significance to study the influence of urbanization on air quality for the rational development of cities. MODIS-MAIAC (Moderate Resolution Imaging Spectroradiometer-Multi-Angle Implementation of Atmospheric Correction) Aerosol optical depth (AOD) product, DMSP/OLS (Defense Meteorological Satellite Program/Operational Linescan System) and NPP/VIIRS (Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite) night-light were used to explore the spatiotemporal variation and correlation between AOD and urbanization development before and after the promulgation of environmental governance policies in Jinan City from 2009 to 2018. Results show that (1) the spatial distribution of AOD in Jinan had the characteristics of high in the north and low in the south, high in the west and low in the east, and low in some parts of the central region; there was a significant seasonal variation in time, with the highest AOD in summer and the lowest in winter. During 2009-2013, the annual average variation of AOD increased by 20.6%, while during 2014-2018, it decreased by 35.3%; (2) The distribution of night-light in Jinan City has progressively expanded, mirroring the city\'s ongoing development. The spatial distribution of aerosols in urban areas was relatively low compared to the surrounding areas of the city. (3) From 2009 to 2013, there existed a significant positive correlation between the spatial and temporal distribution of AOD and night-light. However, from 2014 to 2018, with the implementation of environmental governance policies, this relationship shifted to a significant negative correlation between the spatial and temporal distribution of AOD and night-light. Through an analysis of the correlation between urban development and aerosol depth in Jinan City over the past decade, it can be concluded that urban development does not inevitably result in elevated AOD levels. Notably, the Jinan government has achieved remarkable results in controlling the atmospheric environment, as evidenced by recent years\' improvements.

In this study we conducted air pollution monitoring using three different methods: active monitoring with the use of high volume aerosol sampler and biomonitoring with the use of lichens and spider webs. All of these monitoring tools were exposed to air pollution in Legnica city, a region of Cu-smelting in the SW Poland, which is well known for exceeding the environmental guidelines. Quantitative analysis was carried out for the particles collected by the three selected methods and concentrations of seven selected elements (Zn, Pb, Cu, Cd, Ni, As, Fe) were obtained. Concentrations found in lichens and in spider webs were directly compared and indicated significant differences between them, with higher amounts noted for spider webs. Then, in order to recognize the main pollution sources the principal component analysis was conducted and obtained results were compared. It resulted that spider webs and aerosol sampler, despite different mechanisms of accumulation, show similar sources of pollution - in this case - copper smelter. Additionally, the HYSPLIT trajectories and the correlations between metals in the aerosol samples also confirmed that this is the most probable source of pollution. This study can be considered innovative as these three air pollution monitoring methods were compared, which has never been conducted before, and their comparison gave satisfying results.

A sequence of dust intrusions occurred from the Sahara Desert to the central Mediterranean in the second half of June 2021. This event was simulated by means of the Weather Research and Forecasting coupled with chemistry (WRF-Chem) regional chemical transport model (CTM). The population exposure to the dust surface PM2.5 was evaluated with the open-source quantum geographical information system (QGIS) by combining the output of the CTM with the resident population map of Italy. WRF-Chem analyses were compared with spaceborne aerosol observations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and, for the PM2.5 surface dust concentration, with the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. Considering the full-period (17-24 June) and area-averaged statistics, the WRF-Chem simulations showed a general underestimation for both the aerosol optical depth (AOD) and the PM2.5 surface dust concentration. The comparison of exposure classes calculated for Italy and its macro-regions showed that the dust sequence exposure varies with the location and entity of the resident population amount. The lowest exposure class (up to 5 µg m-3) had the highest percentage (38%) of the population of Italy and most of the population of north Italy, whereas more than a half of the population of central, south and insular Italy had been exposed to dust PM2.5 in the range of 15-25 µg m-3. The coupling of the WRF-Chem model with QGIS is a promising tool for the management of risks posed by extreme pollution and/or severe meteorological events. Specifically, the present methodology can also be applied for operational dust forecasting purposes, to deliver safety alarm messages to areas with the most exposed population.

Mixing states of aerosol particles are crucial for understanding the role of aerosols in influencing air quality and climate. However, a fundamental understanding of the complex mixing states is still lacking because most traditional analysis techniques only reveal bulk chemical and physical properties with limited surface and 3-D information. In this research, 3-D molecular imaging enabled by ToF-SIMS was used to elucidate the mixing states of PM2.5 samples obtained from a typical Beijing winter haze event. In light pollution cases, a thin organic layer covers separated inorganic particles; while in serious pollution cases, ion exchange and an organic-inorganic mixing surface on large-area particles were observed. The new results provide key 3-D molecular information of mixing states, which is highly potential for reducing uncertainty and bias in representing aerosol-cloud interactions in current Earth System Models and improving the understanding of aerosols on air quality and human health.

Stubble burning is an emerging environmental issue in Northern India, which has severe implications for the air quality of the region. Although stubble burning occurs twice during a year, first during April-May and again in October-November due to paddy burning, the effects are severe during October-November months. This is exacerbated by the role of meteorological parameters and presence of inversion conditions in the atmosphere. The deterioration in the atmospheric quality can be attributed to the emissions from stubble burning which can be perceived from the changes observed in land use land cover (LULC) pattern, fire events, and sources of aerosol and gaseous pollutants. In addition, wind speed and wind direction also play a role in changing the concentration of pollutants and particulate matter over a specified area. The present study has been carried out for the states of Punjab, Haryana, Delhi, and western Uttar Pradesh to study the influence of stubble burning on the aerosol load of this region of Indo-Gangetic Plains (IGP). In this study, the aerosol level, smoke plume characteristics, long-range transport of pollutants, and affected areas during October-November from year 2016 to 2020 were examined over the Indo-Gangetic Plains (Northern India) region by the satellite observations. By MODIS-FIRMS (Moderate Resolution Imaging Spectroradiometer-Fire Information for Resource Management System) observations, it was revealed that there was an increase in stubble burning events with the highest number of events being observed during the year 2016 and then a decrease in the number of events in subsequent years from 2017 to 2020. MODIS observations revealed a strong AOD gradient from west to east. The prevailing north-westerly winds assist the spread of smoke plumes over Northern India during the peak burning season of October to November. The findings of this study might be used to expand on the atmospheric processes that occur over northern India during the post-monsoon season. The pollutant, smoke plume features, and impacted regions of biomass-burning aerosols in this region are critical for weather and climate research, especially given the rising trend in agricultural burning over the previous two decades.

Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.