ResearchPad - aerosols Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Examination of the ocean as a source for atmospheric microplastics]]> Global plastic litter pollution has been increasing alongside demand since plastic products gained commercial popularity in the 1930’s. Current plastic pollutant research has generally assumed that once plastics enter the ocean they are there to stay, retained permanently within the ocean currents, biota or sediment until eventual deposition on the sea floor or become washed up onto the beach. In contrast to this, we suggest it appears that some plastic particles could be leaving the sea and entering the atmosphere along with sea salt, bacteria, virus’ and algae. This occurs via the process of bubble burst ejection and wave action, for example from strong wind or sea state turbulence. In this manuscript we review evidence from the existing literature which is relevant to this theory and follow this with a pilot study which analyses microplastics (MP) in sea spray. Here we show first evidence of MP particles, analysed by μRaman, in marine boundary layer air samples on the French Atlantic coast during both onshore (average of 2.9MP/m3) and offshore (average of 9.6MP/m3) winds. Notably, during sampling, the convergence of sea breeze meant our samples were dominated by sea spray, increasing our capacity to sample MPs if they were released from the sea. Our results indicate a potential for MPs to be released from the marine environment into the atmosphere by sea-spray giving a globally extrapolated figure of 136000 ton/yr blowing on shore.

<![CDATA[Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India]]> Air pollution is a major risk factor for human health in IndiaPopulation aging and growth will increase the disease burden due to exposure to particulate air pollution even under no emission changeStringent emission control reduces mortality rate in 2050 below 2015 levels although total premature mortality increases

<![CDATA[New Approaches to Identifying and Reducing the Global Burden of Disease From Pollution]]>


Pollution from multiple sources causes significant disease and death worldwide. Some sources are legacy, such as heavy metals accumulated in soils, and some are current, such as particulate matter. Because the global burden of disease from pollution is so high, it is important to identify legacy and current sources and to develop and implement effective techniques to reduce human exposure. But many limitations exist in our understanding of the distribution and transport processes of pollutants themselves, as well as the complicated overprint of human behavior and susceptibility.

New approaches are being developed to identify and eliminate pollution in multiple environments. Community‐scale detection of geogenic arsenic and fluoride in Bangladesh is helping to map the distribution of these harmful elements in drinking water. Biosensors such as bees and their honey are being used to measure heavy metal contamination in cities such as Vancouver and Sydney. Drone‐based remote sensors are being used to map metal hot spots in soils from former mining regions in Zambia and Mozambique. The explosion of low‐cost air monitors has allowed researchers to build dense air quality sensing networks to capture ephemeral and local releases of harmful materials, building on other developments in personal exposure sensing. And citizen science is helping communities without adequate resources measure their own environments and in this way gain agency in controlling local pollution exposure sources and/or alerting authorities to environmental hazards. The future of GeoHealth will depend on building on these developments and others to protect a growing population from multiple pollution exposure risks.

<![CDATA[Aerosols in the Pre-industrial Atmosphere]]>

Purpose of Review

We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate.

Recent Findings

Studies show that the magnitude of anthropogenic aerosol radiative forcing over the industrial period calculated by climate models is strongly affected by the abundance and properties of aerosols in the pre-industrial atmosphere. The low concentration of aerosol particles under relatively pristine conditions means that global mean cloud albedo may have been twice as sensitive to changes in natural aerosol emissions under pre-industrial conditions compared to present-day conditions. Consequently, the discovery of new aerosol formation processes and revisions to aerosol emissions have large effects on simulated historical aerosol radiative forcing.


We review what is known about the microphysical, chemical, and radiative properties of aerosols in the pre-industrial atmosphere and the processes that control them. Aerosol properties were controlled by a combination of natural emissions, modification of the natural emissions by human activities such as land-use change, and anthropogenic emissions from biofuel combustion and early industrial processes. Although aerosol concentrations were lower in the pre-industrial atmosphere than today, model simulations show that relatively high aerosol concentrations could have been maintained over continental regions due to biogenically controlled new particle formation and wildfires. Despite the importance of pre-industrial aerosols for historical climate change, the relevant processes and emissions are given relatively little consideration in climate models, and there have been very few attempts to evaluate them. Consequently, we have very low confidence in the ability of models to simulate the aerosol conditions that form the baseline for historical climate simulations. Nevertheless, it is clear that the 1850s should be regarded as an early industrial reference period, and the aerosol forcing calculated from this period is smaller than the forcing since 1750. Improvements in historical reconstructions of natural and early anthropogenic emissions, exploitation of new Earth system models, and a deeper understanding and evaluation of the controlling processes are key aspects to reducing uncertainties in future.

<![CDATA[WRF 1960–2014 Winter Season Simulations of Particulate Matter in the Sahel: Implications for Air Quality and Respiratory Health]]>


We use the Weather Research and Forecast model using the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) dust module (WRF‐CHEM) to simulate the particulate matter (PM) variations in the Sahel during the winter seasons (January–March) of 1960–2014. Two simulations are undertaken where the direct aerosol feedback is turned off, and only transport is considered and where the direct aerosol feedback is turned on. We find that simulated Sahelian PM10 and PM2.5 concentrations were lower in the 1960s and after 2003 and higher during the period between 1988 and 2002. Higher Sahelian PM10 concentrations are due to stronger winds between the surface and 925 hPa over the Sahara, which transport dust into the Sahel. Negative PM10 concentration anomalies are found over the Bodele Depression and associated with weaker 925 wind anomalies after 1997 through 2014. Further west, positive PM10 concentration anomalies are found across the Adrar Plateau in the Sahara and responsible for dust transport to the Western Sahel. The North Atlantic Oscillation (NAO) is positively correlated to Sahelian dust concentrations especially during the periods of 1960–1970 and 1988–2002. The temporal/spatial patterns of PM10 concentrations have significant respiratory health implications for inhabitants of the Sahel.

<![CDATA[Impact of Deadly Dust Storms (May 2018) on Air Quality, Meteorological, and Atmospheric Parameters Over the Northern Parts of India]]>


The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo‐Gangetic Plains. The dust storms that occur during the premonsoon months of March–June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and the Thar desert located in north‐western India. In the year 2018, month of May, three back‐to‐back major dust storms occurred that caused massive damage, loss of human lives, and loss to property and had an impact on air quality and human health. In this paper, we combine observations from ground stations, satellites, and radiosonde networks to assess the impact of dust events in the month of May 2018, on meteorological parameters, aerosol properties, and air quality. We observed widespread changes associated with aerosol loadings, humidity, and vertical advection patterns with displacements of major trace and greenhouse gasses. We also notice drastic changes in suspended particulate matter concentrations, all of which can have significant ramifications in terms of human health and changes in weather pattern.

<![CDATA[Regional Biases in MODIS Marine Liquid Water Cloud Drop Effective Radius Deduced Through Fusion With MISR]]>


Satellite measurements from Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) represent our longest, single‐platform, global record of the effective radius (Re) of the cloud drop size distribution. Quantifying its error characteristics has been challenging because systematic errors in retrieved Re covary with the structural characteristics of the cloud and the Sun‐view geometry. Recently, it has been shown that the bias in MODIS Re can be estimated by fusing MODIS data with data from Terra's Multi‐angle Imaging SpectroRadiometer (MISR). Here, we relate the bias to the observed underlying conditions to derive regional‐scale, bias‐corrected, monthly‐mean Re 1.6, Re 2.1, and Re 3.7 values retrieved from the 1.6, 2.1, and 3.7 μm MODIS spectral channels. Our results reveal that monthly‐mean bias in Re 2.1 exhibits large regional dependency, ranging from at least ~1 to 10 μm (15 to 60%) varying with scene heterogeneity, optical depth, and solar zenith angle. Regional bias‐corrected monthly‐mean Re 2.1 ranges from 4 to 17 μm, compared to 10 to 25 μm for uncorrected Re 2.1, with estimated uncertainties of 0.1 to 1.8 μm. The bias‐corrected monthly‐mean Re 3.7 and Re 2.1 show difference of approximately +0.6 μm in the coastal marine stratocumulus regions and down to approximately −2 μm in the cumuliform cloud regions, compared to uncorrected values of about −1 to −6 μm, respectively. Bias‐corrected Re values compare favorably to other independent data sources, including field observations, global model simulations, and satellite retrievals that do not use retrieval techniques similar to MODIS. This work changes the interpretation of global Re distributions from MODIS Re products and may further impact studies, which use the original MODIS Re products to study, for example, aerosol‐cloud interactions and cloud microphysical parameterization.

<![CDATA[Hybrid Mass Balance/4D‐Var Joint Inversion of NO x and SO 2 Emissions in East Asia]]>


Accurate estimates of NOx and SO2 emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005–2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO2 and NO2 can provide more accurate constraints on emissions than single‐species inversions. This occurs through synergistic change of O3 and OH concentrations, particularly in conditions where satellite retrievals of the species being optimized have large uncertainties. The percentage changes of joint posterior emissions from the single‐species posterior emissions go up to 242% at grid scales, although the national average of monthly emissions, seasonality, and interannual variations are similar. In China and India, the annual budget of joint posterior SO2 emissions is lower, but joint NOx posterior emissions are higher, because NOx emissions increase to increase SO2 concentration and better match Ozone Monitoring Instrument SO2 observations in high‐NOx regions. Joint SO2 posterior emissions decrease by 16.5% from 2008 to 2012, while NOx posterior emissions increase by 24.9% from 2005 to 2011 in China—trends which are consistent with the MEIC inventory. Joint NOx and SO2 posterior emissions in India increase by 15.9% and 19.2% from 2005 to 2012, smaller than the 59.9% and 76.2% growth rate using anthropogenic emissions from EDGARv4.3.2. This work shows the benefit and limitation of joint assimilation in emission estimates and provides an efficient framework to perform the inversion.

<![CDATA[SO 2 Emission Estimates Using OMI SO 2 Retrievals for 2005–2017]]>


SO2 column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO2 retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4D‐Var/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in United States, India, and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA)–48% (BIRA) in India, but decrease in China by 23% (NASA)–33% (BIRA) since 2008. Compared to in situ measurements, the posterior GEOS‐Chem surface SO2 concentrations have reduced NMB in China, the United States, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea, and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using Ozone Monitoring Instrument observations.

<![CDATA[Characterization of an intratracheal aerosol challenge model of Brucella melitensis in guinea pigs]]>

B. melitensis is considered the most virulent of the Brucella species, and a need exists for an improved laboratory animal model of infection that mimics natural transmission and disease. Guinea pigs are highly susceptible to infection with Brucella spp. and develop a disease syndrome that mimics natural disease after aerosol inoculation. Intratracheal inoculation is a targeted means of generating aerosols that offer advantages over aerosol chamber delivery. To establish this delivery method, female, Hartley guinea pigs were infected via intratracheal inoculation with PBS or 16M B. melitensis at low dose (101 to 103) or high dose (106 to 108) and monitored for 30 days for signs of disease. Guinea pigs in the high dose groups developed fever between 12–17 days post-inoculation. Bacteria were recovered from the spleen, liver, lymph nodes, lung, and uterus at 30-days post-inoculation and demonstrated dose dependent mean increases in colonization and pathologic changes consistent with human brucellosis. To study the kinetics of extrapulmonary dissemination, guinea pigs were inoculated with 107 CFU and euthanized at 2-hours post inoculation and at weekly intervals for 3 weeks. 5.8x105 to 4.2x106 CFU were recovered from the lung 2 hours post-inoculation indicating intratracheal inoculation is an efficient means of infecting guinea pigs. Starting at 1-week post inoculation bacteria were recovered from the aforementioned organs with time dependent mean increases in colonization. This data demonstrates that guinea pigs develop a disease syndrome that models the human manifestation of brucellosis, which makes the guinea pig a valuable model for pathogenesis studies.

<![CDATA[Correlating exhaled aerosol images to small airway obstructive diseases: A study with dynamic mode decomposition and machine learning]]>


Exhaled aerosols from lungs have unique patterns, and their variation can be correlated to the underlying lung structure and associated abnormities. However, it is challenging to characterize such aerosol patterns and differentiate their difference because of their complexity. This challenge is even greater for small airway diseases, where the disturbance signals are weak.

Objectives and methods

The objective of this study is exploiting different feature extraction algorithms to develop a practical classifier to diagnose obstructive lung diseases using exhaled aerosol images. These include proper orthogonal decomposition (POD), principal component analysis (PCA), dynamic mode decomposition (DMD), and DMD with control (DMDC). Aerosol images were generated via physiology-based simulations in one normal and four diseased airway models in G7-9 bronchioles. The image data were classified using both the support vector machine (SVM) and random forest (RF) algorithms. The effectiveness of different features was evaluated by classification accuracy and misclassification rate.


Results show a significantly higher performance using dynamic feature extractions (DMD and DMDC) than static algorithms (POD and PCA). Adding the control variables to DMD further improved classification accuracy. Comparing the classification methods, RF persistently outperformed SVM for all types of features considered. While the performance of RF constantly increased with the number of features retained, the performance of SVM peaked at 50 and decreased thereafter. The 5-class classification accuracy was 94.8% using the DMDC-RF model and 93.0% using the DMD-RF model, both of which were higher than 87.0% in the previous study that used fractal dimension features.


Considering that disease progression is inherently a dynamic process, DMD(C)-based feature extraction preserves temporal information and is preferred over POD and PCA. Compared with hand-crafted features like fractals, feature extraction by DMD and DMDC is automatic and more accurate.

<![CDATA[Spores of puffball fungus Lycoperdon pyriforme as a reference standard of stable monodisperse aerosol for calibration of optical instruments]]>

Advanced air quality control requires real-time monitoring of particulate matter size and concentration, which can only be done using optical instruments. However, such techniques need regular calibration with reference samples. In this study, we suggest that puffball fungus (Lycoperdon pyriforme) spores can be utilized as a reference standard having a monodisperse size distribution. We compare the Lycoperdon pyriforme spores with the other commonly used reference samples, such as Al2O3 powder and polystyrene latex (PSL) microspheres. Here we demonstrate that the puffball spores do not coagulate and, thus, maintain the same particle size in the aerosol state for at least 15 minutes, which is enough for instrument calibration. Moreover, the puffball mushrooms can be stored for several years and no agglomeration of the spores occurs. They are also much cheaper than other calibration samples and no additional devices are needed for aerosol generation since the fungal fruiting body acts as an atomizer itself. The aforementioned features make the fungal spores a highly promising substance for calibration and validation of particle size analyzers, which outperforms the existing, artificially produced particles for aerosol sampling. Furthermore, the L. pyriforme spores are convenient for basic research and development of new optical measurement techniques, taking into account their uniform particle size and absent coagulation in the aerosol.

<![CDATA[Anthropogenic Aerosol Indirect Effects in Cirrus Clouds]]>


We have implemented a parameterization for forming ice in large‐scale cirrus clouds that accounts for the changes in updrafts associated with a spectrum of waves acting within each time step in the model. This allows us to account for the frequency of homogeneous and heterogeneous freezing events that occur within each time step of the model and helps to determine more realistic ice number concentrations as well as changes to ice number concentrations. The model is able to fit observations of ice number at the lowest temperatures in the tropical tropopause but is still somewhat high in tropical latitudes with temperatures between 195°K and 215°K. The climate forcings associated with different representations of heterogeneous ice nuclei (IN or INPs) are primarily negative unless large additions of IN are made, such as when we assumed that all aircraft soot acts as an IN. However, they can be close to zero if it is assumed that all background dust can act as an INP irrespective of how much sulfate is deposited on these particles. Our best estimate for the forcing of anthropogenic aircraft soot in this model is −0.2 ± 0.06 W/m2, while that from anthropogenic fossil/biofuel soot is −0.093 ± 0.033 W/m2. Natural and anthropogenic open biomass burning leads to a net forcing of −0.057 ± 0.05 W/m2.

<![CDATA[Disease progression in mice exposed to low-doses of aerosolized clinical isolates of Burkholderia pseudomallei]]>

Mouse models have been essential to generate supporting data for the research of infectious diseases. Burkholderia pseudomallei, the etiological agent of melioidosis, has been studied using mouse models to investigate pathogenesis and efficacy of novel medical countermeasures to include both vaccines and therapeutics. Previous characterization of mouse models of melioidosis have demonstrated that BALB/c mice present with an acute infection, whereas C57BL/6 mice have shown a tendency to be more resistant to infection and may model chronic disease. In this study, either BALB/c or C57BL/6 mice were exposed to aerosolized human clinical isolates of B. pseudomallei. The bacterial strains included HBPUB10134a (virulent isolate from Thailand), MSHR5855 (virulent isolate from Australia), and 1106a (relatively attenuated isolate from Thailand). The LD50 values were calculated and serial sample collections were performed in order to examine the bacterial burdens in tissues, histopathological features of disease, and the immune response mounted by the mice after exposure to aerosolized B. pseudomallei. These data will be important when utilizing these models for testing novel medical countermeasures. Additionally, by comparing highly virulent strains with attenuated isolates, we hope to better understand the complex disease pathogenesis associated with this bacterium.

<![CDATA[Aerosol exposure to intermediate size Nipah virus particles induces neurological disease in African green monkeys]]>

Nipah virus (NiV) infection can lead to severe respiratory or neurological disease in humans. Transmission of NiV has been shown to occur through contact with virus contaminated fomites or consumption of contaminated food. Previous results using the African green monkey (AGM) model of NiV infection identified aspects of infection that, while similar to humans, don’t fully recapitulate disease. Previous studies also demonstrate near uniform lethality that is not consistent with human NiV infection. In these studies, aerosol exposure using an intermediate particle size (7μm) was used to mimic potential human exposure by facilitating virus deposition in the upper respiratory tract. Computed tomography evaluation found some animals developed pulmonary parenchymal disease including consolidations, ground-glass opacities, and reactive adenopathy. Despite the lack of neurological signs, magnetic resonance imaging identified distinct brain lesions in three animals, similar to those previously reported in NiV-infected patients. Immunological characterization of tissues collected at necropsy suggested a local pulmonary inflammatory response with increased levels of macrophages in the lung, but a limited neurologic response. These data provide the first clear evidence of neurological involvement in the AGM that recapitulates human disease. With the development of a disease model that is more representative of human disease, these data suggest that NiV infection in the AGM may be appropriate for evaluating therapeutic countermeasures directed at virus-induced neuropathogenesis.

<![CDATA[Detection of influenza A virus in aerosols of vaccinated and non-vaccinated pigs in a warm environment]]>

The 2009 influenza pandemic, the variant H3N2v viruses in agricultural fairs and the zoonotic poultry H5N9 infections in China have highlighted the constant threat that influenza A viruses (IAV) present to people and animals. In this study we evaluated the effect of IAV vaccination on aerosol shedding in pigs housed in warm environmental conditions. Thirty-six, three-week old weaned pigs were obtained from an IAV negative herd and were randomly allocated to one of 4 groups: 1) a homologous vaccine group, 2) a heterologous multivalent vaccine group, 3) a heterologous monovalent group and, 4) a non-vaccinated group. After vaccination pigs were challenged with the triple reassortant A/Sw/IA/00239/04 H1N1 virus. Environmental temperature and relative humidity were recorded throughout the study. Nasal swabs, oral fluids and air samples were collected daily. All samples were tested by RRT-PCR and virus isolation was attempted on positive samples. Average temperature and relative humidity throughout the study were 27°C (80°F) and 53%, respectively. A significantly higher proportion of infected pigs was detected in the non-vaccinated than in the vaccinated group. Lower levels of nasal virus shedding were found in vaccinated groups compared to non-vaccinated group and IAV was not detected in air samples of any of the vaccinated groups. In contrast, positive air samples were detected in the non-vaccinated group at 1, 2 and 3 days post infection although the overall levels were considered low most likely due to the elevated environmental temperature. In conclusion, both the decrease in shedding and the increase in environmental temperature may have contributed to the inability to detect airborne IAV in vaccinated pigs.

<![CDATA[Exhaled Air Dispersion during Coughing with and without Wearing a Surgical or N95 Mask]]>


We compared the expelled air dispersion distances during coughing from a human patient simulator (HPS) lying at 45° with and without wearing a surgical mask or N95 mask in a negative pressure isolation room.


Airflow was marked with intrapulmonary smoke. Coughing bouts were generated by short bursts of oxygen flow at 650, 320, and 220L/min to simulate normal, mild and poor coughing efforts, respectively. The coughing jet was revealed by laser light-sheet and images were captured by high definition video. Smoke concentration in the plume was estimated from the light scattered by smoke particles. Significant exposure was arbitrarily defined where there was ≥ 20% of normalized smoke concentration.


During normal cough, expelled air dispersion distances were 68, 30 and 15 cm along the median sagittal plane when the HPS wore no mask, a surgical mask and a N95 mask, respectively. In moderate lung injury, the corresponding air dispersion distances for mild coughing efforts were reduced to 55, 27 and 14 cm, respectively, p < 0.001. The distances were reduced to 30, 24 and 12 cm, respectively during poor coughing effort as in severe lung injury. Lateral dispersion distances during normal cough were 0, 28 and 15 cm when the HPS wore no mask, a surgical mask and a N95 mask, respectively.


Normal cough produced a turbulent jet about 0.7 m towards the end of the bed from the recumbent subject. N95 mask was more effective than surgical mask in preventing expelled air leakage during coughing but there was still significant sideway leakage.

<![CDATA[Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments]]>

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods.

<![CDATA[Exhaled Aerosol Transmission of Pandemic and Seasonal H1N1 Influenza Viruses in the Ferret]]>

Person-to-person transmission of influenza viruses occurs by contact (direct and fomites) and non-contact (droplet and small particle aerosol) routes, but the quantitative dynamics and relative contributions of these routes are incompletely understood. The transmissibility of influenza strains estimated from secondary attack rates in closed human populations is confounded by large variations in population susceptibilities. An experimental method to phenotype strains for transmissibility in an animal model could provide relative efficiencies of transmission. We developed an experimental method to detect exhaled viral aerosol transmission between unanesthetized infected and susceptible ferrets, measured aerosol particle size and number, and quantified the viral genomic RNA in the exhaled aerosol. During brief 3-hour exposures to exhaled viral aerosols in airflow-controlled chambers, three strains of pandemic 2009 H1N1 strains were frequently transmitted to susceptible ferrets. In contrast one seasonal H1N1 strain was not transmitted in spite of higher levels of viral RNA in the exhaled aerosol. Among three pandemic strains, the two strains causing weight loss and illness in the intranasally infected ‘donor’ ferrets were transmitted less efficiently from the donor than the strain causing no detectable illness, suggesting that the mucosal inflammatory response may attenuate viable exhaled virus. Although exhaled viral RNA remained constant, transmission efficiency diminished from day 1 to day 5 after donor infection. Thus, aerosol transmission between ferrets may be dependent on at least four characteristics of virus-host relationships including the level of exhaled virus, infectious particle size, mucosal inflammation, and viral replication efficiency in susceptible mucosa.

<![CDATA[Emissions and Char Quality of Flame-Curtain "Kon Tiki" Kilns for Farmer-Scale Charcoal/Biochar Production]]>

Flame Curtain Biochar Kilns

Pyrolysis of organic waste or woody materials yields charcoal, a stable carbonaceous product that can be used for cooking or mixed into soil, in the latter case often termed "biochar". Traditional kiln technologies for charcoal production are slow and without treatment of the pyrolysis gases, resulting in emissions of gases (mainly methane and carbon monoxide) and aerosols that are both toxic and contribute to greenhouse gas emissions. In retort kilns pyrolysis gases are led back to a combustion chamber. This can reduce emissions substantially, but is costly and consumes a considerable amount of valuable ignition material such as wood during start-up. To overcome these problems, a novel type of technology, the Kon-Tiki flame curtain pyrolysis, is proposed. This technology combines the simplicity of the traditional kiln with the combustion of pyrolysis gases in the flame curtain (similar to retort kilns), also avoiding use of external fuel for start-up.

Biochar Characteristics

A field study in Nepal using various feedstocks showed char yields of 22 ± 5% on a dry weight basis and 40 ± 11% on a C basis. Biochars with high C contents (76 ± 9%; n = 57), average surface areas (11 to 215 m2 g-1), low EPA16—PAHs (2.3 to 6.6 mg kg-1) and high CECs (43 to 217 cmolc/kg)(average for all feedstocks, mainly woody shrubs) were obtained, in compliance with the European Biochar Certificate (EBC).

Gas Emission Factors

Mean emission factors for the flame curtain kilns were (g kg-1 biochar for all feedstocks); CO2 = 4300 ± 1700, CO = 54 ± 35, non-methane volatile organic compounds (NMVOC) = 6 ± 3, CH4 = 30 ± 60, aerosols (PM10) = 11 ± 15, total products of incomplete combustion (PIC) = 100 ± 83 and NOx = 0.4 ± 0.3. The flame curtain kilns emitted statistically significantly (p<0.05) lower amounts of CO, PIC and NOx than retort and traditional kilns, and higher amounts of CO2.


With benefits such as high quality biochar, low emission, no need for start-up fuel, fast pyrolysis time and, importantly, easy and cheap construction and operation the flame curtain technology represent a promising possibility for sustainable rural biochar production.