Particle number size distributions and concentrations in transportation environments: a review.

Ambient air ultrafine particles (UFP, particles with a diameter <100 nm) have gained significant attention in World Health Organization (WHO) air quality guidelines and European legislation. This review explores UFP concentrations and particle number size distributions (PNC-PNSD) in various transportation hotspots, including road traffic, airports, harbors, trains, and urban commuting modes (walking, cycling, bus, tram, and subway). The results highlight the lack of information on personal exposure at harbors and railway stations, inside airplanes and trains, and during various other commuting modes. The different lower particle size limits of the reviewed measurements complicate direct comparisons between them. Emphasizing the use of instruments with detection limits ≤10 nm, this review underscores the necessity of following standardized UFP measurement protocols. Road traffic sites are shown to exhibit the highest PNC within cities, with PNC and PNSD in commuting modes driven by the proximity to road traffic and weather conditions. In closed environments, such as cars, buses, and trams, increased external air infiltration for ventilation correlates with elevated PNC and a shift in PNSD toward smaller diameters. Airports exhibit particularly elevated PNCs near runways, raising potential concerns about occupational exposure. Recommendations from this study include maintaining a substantial distance between road traffic and other commuting modes, integrating air filtration into ventilation systems, implementing low-emission zones, and advocating for a general reduction in road traffic to minimize daily UFP exposure. Our findings provide important insights for policy assessments and underscore the need for additional research to address current knowledge gaps.

Multifunctional scaffolds for biomedical applications: Crafting versatile solutions with polycaprolactone enriched by graphene oxide.

The pressing need for multifunctional materials in medical settings encompasses a wide array of scenarios, necessitating specific tissue functionalities. A critical challenge is the occurrence of biofouling, particularly by contamination in surgical environments, a common cause of scaffolds impairment. Beyond the imperative to avoid infections, it is also essential to integrate scaffolds with living cells to allow for tissue regeneration, mediated by cell attachment. Here, we focus on the development of a versatile material for medical applications, driven by the diverse time-definite events after scaffold implantation. We investigate the potential of incorporating graphene oxide (GO) into polycaprolactone (PCL) and create a composite for 3D printing a scaffold with time-controlled antibacterial and anti-adhesive growth properties. Indeed, the as-produced PCL-GO scaffold displays a local hydrophobic effect, which is translated into a limitation of biological entities-attachment, including a diminished adhesion of bacteriophages and a reduction of E. coli and S. aureus adhesion of ∼81% and ∼69%, respectively. Moreover, the ability to 3D print PCL-GO scaffolds with different heights enables control over cell distribution and attachment, a feature that can be also exploited for cellular confinement, i.e., for microfluidics or wound healing applications. With time, the surface wettability increases, and the scaffold can be populated by cells. Finally, the presence of GO allows for the use of infrared light for the sterilization of scaffolds and the disruption of any bacteria cell that might adhere to the more hydrophilic surface. Overall, our results showcase the potential of PCL-GO as a versatile material for medical applications.

Aerosol source apportionment uncertainty linked to the choice of input chemical components.

For a Positive Matrix Factorization (PMF) aerosol source apportionment (SA) studies there is no standard procedure to select the most appropriate chemical components to be included in the input dataset for a given site typology, nor specific recommendations in this direction. However, these choices are crucial for the final SA outputs not only in terms of number of sources identified but also, and consequently, in the source contributions estimates. In fact, PMF tends to reproduce most of PM mass measured independently and introduced as a total variable in the input data, regardless of the percentage of PM mass which has been chemically characterized, so that the lack of some specific source tracers (e.g. levoglucosan) can potentially affect the results of the whole source apportionment study. The present study elaborates further on the same concept, evaluating quantitatively the impact of lacking specific sources' tracers on the whole source apportionment, both in terms of identified sources and source contributions. This work aims to provide first recommendations on the most suitable and critical components to be included in PMF analyses in order to reduce PMF output uncertainty as much as possible, and better represent the most commons PM sources observed in many sites in Western countries. To this aim, we performed three sensitivity analyses on three different datasets across EU, including extended sets of organic tracers, in order to cover different types of urban conditions (Mediterranean, Continental, and Alpine), source types, and PM fractions. Our findings reveal that the vehicle exhaust source resulted to be less sensitive to the choice of analytes, although source contributions estimates can deviate significantly up to 44 %. On the other hand, for the detection of the non-exhaust one is clearly necessary to analyze specific inorganic elements. The choice of not analysing non-polar organics likely causes the loss of separation of exhaust and non-exhaust factors, thus obtaining a unique road traffic source, which provokes a significant bias of total contribution. Levoglucosan was, in most cases, crucial to identify biomass burning contributions in Milan and in Barcelona, in spite of the presence of PAHs in Barcelona, while for the case of Grenoble, even discarding levoglucosan, the presence of PAHs allowed identifying the BB factor. Modifying the rest of analytes provoke a systematic underestimation of biomass burning source contributions. SIA factors resulted to be generally overestimated with respect to the base case analysis, also in the case that ions were not included in the PMF analysis. Trace elements were crucial to identify shipping emissions (V and Ni) and industrial sources (Pb, Ni, Br, Zn, Mn, Cd and As). When changing the rest of input variables, the uncertainty was narrow for shipping but large for industrial processes. Major and trace elements were also crucial to identify the mineral/soil factor at all cities. Biogenic SOA and Anthropogenic SOA factors were sensitive to the presence of their molecular tracers, since the availability of OC alone is unable to separate a SOA factor. Arabitol and sorbitol were crucial to detecting fungal spores while odd number of higher alkanes (C27 to C31) for plant debris.

Discovering oxidative potential (OP) drivers of atmospheric PM10, PM2.5, and PM1 simultaneously in North-Eastern Spain.

Ambient particulate matter (PM) is a major contributor to air pollution, leading to adverse health effects on the human population. It has been suggested that the oxidative potential (OP, as a tracer of oxidative stress) of PM is a possible determinant of its health impact. In this study, samples of PM10, PM2.5, and PM1 were collected roughly every four days from January 2018 until March 2019 at a Barcelona urban background site and Montseny rural background site in northeastern Spain. We determined the chemical composition of samples, allowing us to perform source apportionment using positive matrix factorization. The OP of PM was determined by measuring reactive oxygen species using dithiothreitol and ascorbic acid assays. Finally, to link the sources with the measured OP, both a Pearson's correlation and a multiple linear regression model were applied to the dataset. The results showed that in Barcelona, the OP of PM10 was much higher than those of PM2.5 and PM1, whereas in Montseny results for all PM sizes were in the same range, but significantly lower than in Barcelona. In Barcelona, several anthropogenic sources were the main drivers of OP in PM10 (Combustion + Road Dust + Heavy Oil + OC-rich) and PM2.5 (Road Dust + Combustion). In contrast, PM1 -associated OP was driven by Industry, with a much lower contribution to PM10 and PM2.5 mass. Meanwhile, Montseny exhibited no clear drivers for OP evolution, likely explaining the lack of a significant difference in OP between PM10, PM2.5, and PM1. Overall, this study indicates that size fraction matters for OP, as a function of the environment typology. In an urban context, OP is driven by the PM10 and PM1 size fractions, whereas only the PM1 fraction is involved in rural environments.

Glial-fibrillary-acidic-protein (GFAP) biomarker detection in serum-matrix: Functionalization strategies and detection by an ultra-high-frequency surface-acoustic-wave (UHF-SAW) lab-on-chip.

Glial-fibrillary-acidic-protein (GFAP) has recently drawn significant attention from the clinical environment as a promising biomarker. The pathologies which can be linked to the presence of GFAP in blood severely affect the human central nervous system. These pathologies are glioblastoma multiforme (GBM), traumatic brain injuries (TBIs), multiple sclerosis (MS), intracerebral hemorrhage (ICH), and neuromyelitis optica (NMO). Here, we develop three different detection strategies for GFAP, among the most popular in the biosensing field and never examined side by side within the experimental frame. We compare their capability of detecting GFAP in a clean-buffer and serum-matrix by using gold-coated quartz-crystal-microbalance (QCM) sensors. All the three detection strategies are based on antibodies, and each of them focuses on a key aspect of the biosensing process. The first is based on a polyethylene glycol (PEG) chain for antifouling, the second on a protein-G linker for controlling antibody-orientation, and the third on antibody-splitting and direct surface immobilization for high-surface coverage. Then, we select the best-performing protocol and validate its detection performance with an ultra-high-frequency (UHF) surface-acoustic-wave (SAW) based lab-on-chip (LoC). GFAP successful detection is demonstrated in a clean-buffer and serum-matrix at a concentration of 35 pM. This GFAP level is compatible with clinical diagnostics. This result suggests the use of our technology for the realization of a point-of-care biosensing platform for the detection of multiple brain-pathology biomarkers.

Classifying the type of delivery from cardiotocographic signals: A machine learning approach.

BACKGROUND AND OBJECTIVE: Cardiotocography (CTG) is the most employed methodology to monitor the foetus in the prenatal phase. Since the evaluation of CTG is often visual, and hence qualitative and too subjective, some automated methods have been introduced for its assessment. METHODS: In this paper, a custom-made software is exploited to extract 17 features from the available CTG. A preliminary univariate statistical analysis is performed; then, five machine learning algorithms, exploiting ensemble learning, were implemented (J48, Random Forests (RF), Ada-boosting of decision tree (ADA-B), Gradient Boosting and Decorate) through Knime analytics platform to classify patients according to their delivery: vaginal or caesarean section. The dataset is composed by 370 signals collected between 2000 and 2009 in both public and private hospitals. The performance of the algorithms was evaluated using 10 folds cross validation with different evaluation metrics: accuracy, precision, sensitivity, specificity, area under the curve receiver operating characteristic (AUCROC). RESULTS: While only two features were significantly different (gestation week and power expressed by the high frequency band of FHR power spectrum), from the statistical point of view, machine learning results were great. The RF obtained the best results: accuracy (91.1%), sensitivity (90.0%) and AUCROC (96.7%). The ADA-B achieved the highest precision (92.6%) and specificity (93.1%). As expected, the lowest scores were obtained by J48 that was the base classifier employed in all the others empowered implementations. Excluding the J48 results, the AUCROC of all the algorithms was greater than 94.9%. CONCLUSION: In the light of the obtained results, that are greater than those ones found in the literature from comparable researches, it can be stated that the machine learning approach can actually help the physicians in their decision process when evaluating the foetal well-being.

Publisher Correction: Cortical-like mini-columns of neuronal cells on zinc oxide nanowire surfaces.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Effect of ventilation strategies and air purifiers on the children's exposure to airborne particles and gaseous pollutants in school gyms.

Indoor school gyms are environments characterized by high concentrations of different airborne particulate and gaseous pollutants. In particular, like other naturally-ventilated school environments, in addition to indoor pollutants children can be exposed to sub-micron particles and gaseous pollutants emitted by outdoor sources and penetrating the building envelope; moreover, high concentrations of super-micron particles can be reached due to the resuspension phenomena related to the physical activity performed therein. The present paper aims to evaluate the effect of different ventilation methods (natural ventilation, manual airing) and the use of air purifiers in reducing the indoor concentrations of different airborne particles and gaseous pollutants in school gyms. To this end, an experimental campaign was performed in two naturally-ventilated school gyms in Barcelona (Spain) of different volumes and different distance to major urban roads. Indoor and outdoor measurements of particle number, black carbon and PM1-10 concentrations were performed as well as indoor measurements of CO2 and NO2 concentrations. The study revealed that the use of air purifiers with windows kept closed (natural ventilation) can lead to a significant reduction in terms of indoor-to-outdoor concentration ratios. In the smaller gym (air changes per hour of the purifiers, ACH, equal to 9.2 h-1) the I/O ratios were reduced by 93% and 95% in terms of particle number and PM1-10, respectively; whereas in the larger school gym (ACH = 1.7 h-1) the corresponding reductions were 70% and 84%. For manual airing scenarios, the effect of the air purifiers on outdoor-generated sub-micron particles is reduced; in particular, for low ACH values (i.e. ACH = 1.7 h-1), the reduction is quite negligible (6%).

Impact of wood combustion on indoor air quality.

The incomplete wood combustion in appliances operated in batch mode is a recognised source of both in- and outdoor airborne pollutants, especially particulate matter (PM). Data on pollutant levels and PM characteristics in households with wood burning devices in developed countries are scarce with most studies describing stove change out programmes or other intervention measures. The aim of the present study was to simultaneously evaluate indoor and outdoor concentrations of CO, CO2 and PM10 during the operation of wood burning appliances (open fireplace and woodstove) in unoccupied rural households. PM10 samples were analysed for water soluble inorganic ions, major and trace elements, organic carbon (OC), elemental carbon (EC), and detailed organic speciation. The CO 8-hour average concentrations did not exceed the protection limit despite the sharp increases observed in relation to background levels. During the open fireplace operation, PM10 levels rose up 12 times compared to background concentrations, while the airtight stove resulted in a 2-fold increase. The inhalation cancer risk of particulate bound PAHs in the room equipped with woodstove was estimated to be negligible while the long-term exposure to PAH levels measured in the fireplace room may contribute to the development of cancer. The excess lifetime cancer risk resulting from the particle-bound Cr(VI) exposure during the fireplace and woodstove operation was higher than 1.0 × 10-6 and 1.0 × 10-5, respectively. Levoglucosan was one of the most abundant individual species both indoors and outdoors. This study underlines air pollution hazards and risks arising from the operation of traditional wood burning appliances.

Monitoring the impact of desert dust outbreaks for air quality for health studies.

We review the major features of desert dust outbreaks that are relevant to the assessment of dust impacts upon human health. Our ultimate goal is to provide scientific guidance for the acquisition of relevant population exposure information for epidemiological studies tackling the short and long term health effects of desert dust. We first describe the source regions and the typical levels of dust particles in regions close and far away from the source areas, along with their size, composition, and bio-aerosol load. We then describe the processes by which dust may become mixed with anthropogenic particulate matter (PM) and/or alter its load in receptor areas. Short term health effects are found during desert dust episodes in different regions of the world, but in a number of cases the results differ when it comes to associate the effects to the bulk PM, the desert dust-PM, or non-desert dust-PM. These differences are likely due to the different monitoring strategies applied in the epidemiological studies, and to the differences on atmospheric and emission (natural and anthropogenic) patterns of desert dust around the world. We finally propose methods to allow the discrimination of health effects by PM fraction during dust outbreaks, and a strategy to implement desert dust alert and monitoring systems for health studies and air quality management.

Vertical and horizontal fall-off of black carbon and NO2 within urban blocks.

While exposure to traffic pollutants significantly decreases with distance from the curb, very dense urban architectures hamper such dispersion. Moreover, the building height reduces significantly the dispersion of pollutants. We have investigated the horizontal variability of Black Carbon (BC) and the vertical variability of NO2 and BC within the urban blocks. Increasing the distance from road BC concentrations decreased following an exponential curve reaching halving distances at 25 m (median), although with a wide variability among sites. Street canyons showed sharper fall-offs than open roads or roads next to a park. Urban background concentrations were achieved at 67 m distance on average, with higher distances found for more trafficked roads. Vertical fall-off of BC was less pronounced than the horizontal one since pollutants homogenize quickly vertically after rush traffic hours. Even shallower vertical fall-offs were found for NO2. For both pollutants, background concentrations were never reached within the building height. A street canyon effect was also found exacerbating concentrations at the lowest floors of the leeward side of the road. These inputs can be useful for assessing population exposure, air quality policies, urban planning and for models validation.

Cortical-like mini-columns of neuronal cells on zinc oxide nanowire surfaces.

A long-standing goal of neuroscience is a theory that explains the formation of the minicolumns in the cerebral cortex. Minicolumns are the elementary computational units of the mature neocortex. Here, we use zinc oxide nanowires with controlled topography as substrates for neural-cell growth. We observe that neuronal cells form networks where the networks characteristics exhibit a high sensitivity to the topography of the nanowires. For certain values of nanowires density and fractal dimension, neuronal networks express small world attributes, with enhanced information flows. We observe that neurons in these networks congregate in superclusters of approximately 200 neurons. We demonstrate that this number is not coincidental: the maximum number of cells in a supercluster is limited by the competition between the binding energy between cells, adhesion to the substrate, and the kinetic energy of the system. Since cortical minicolumns have similar size, similar anatomical and topological characteristics of neuronal superclusters on nanowires surfaces, we conjecture that the formation of cortical minicolumns is likewise guided by the interplay between energy minimization, information optimization and topology. For the first time, we provide a clear account of the mechanisms of formation of the minicolumns in the brain.

Relating the rate of growth of metal nanoparticles to cluster size distribution in electroless deposition.

Electroless deposition on patterned silicon substrates enables the formation of metal nanomaterials with tight control over their size and shape. In the technique, metal ions are transported by diffusion from a solution to the active sites of an autocatalytic substrate where they are reduced as metals upon contact. Here, using diffusion limited aggregation models and numerical simulations, we derived relationships that correlate the cluster size distribution to the total mass of deposited particles. We found that the ratio ξ between the rates of growth of two different metals depends on the ratio γ between the rates of growth of clusters formed by those metals through the linearity law ξ = 14(γ - 1). We then validated the model using experiments. Different from other methods, the model derives k using as input the geometry of metal nanoparticle clusters, decoded by SEM or AFM images of samples, and a known reference.

Effectiveness of commercial face masks to reduce personal PM exposure.

Cycling and walking are promoted as means of transportation which can contribute to the reduction of traffic pollution in urban areas. However, cyclists and pedestrians may be exposed to high concentrations of air pollutants due to their proximity to vehicle emissions. Commercial face mask respirators are widely used, in both developing and developed countries, as an individual protective measure against particle pollution. However scientific data on the efficacy of face mask respirators in reducing airborne particle exposure is limited. In this study, a custom experimental set-up was developed in order to measure the effectiveness of nine different respirators under real environmental conditions in terms of particle mass concentration below 2.5 µm (PM2.5), particle number concentration (PNC), Lung Deposited Surface Area (LDSA) and Black Carbon concentration (BC). Face mask performances were assessed in a typical traffic affected urban background environment in the city of Barcelona under three different simulated breathing rates to investigate the influence of flow rate. Results showed a median face mask effectiveness for PM2.5 equal to 48% in a range of 14-96%, 19% in a range of 6%-61% for BC concentration, 19% in a range of 4%-63% for PNC and 22% in a range of 5%-65% for LDSA. For each pollutant under investigation, the best performance was found always with the same mask (N7) although it is not the most expensive (in a range of price of 1 to 44, its cost was 20 euros), which has a filter on the entire surface except for the 2 exhalation valves where air cannot enter but just exit and shows a good fit on the dummy head.

Superhydrophobic lab-on-chip measures secretome protonation state and provides a personalized risk assessment of sporadic tumour.

Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual's diagnosis and/or help clarify risk in healthy populations.

Aerosol sources in subway environments.

Millions of people use rail subway public transport around the world, despite the relatively high particulate matter (PM) concentrations in these underground environments, requiring the identification and quantification of the aerosol source contributions to improve the air quality. An extensive aerosol monitoring campaign was carried out in eleven subway stations in the Barcelona metro system, belonging to seven subway lines. PM2.5 samples were collected during the metro operating hours and chemically analysed to determine major and trace elements, inorganic ions, and total carbon. The chemical compositions of subway components such as brake pads, rail tracks and pantographs were also determined. The mean PM2.5 concentrations varied widely among stations, ranging from 26 µg m-3 to 86 µg m-3. Subway PM2.5 was mainly constituted by Fe2O3 (30-66%), followed by carbonaceous matter (18-37%) for the old stations, while for new stations equipped with Platform Screen Doors (PSD) these percentages go down to 21-44% and 15-30%, respectively. Both the absolute concentrations and the relative abundance of key species differed for each subway station, although with common patterns within a given subway line. This is a result of the different emission chemical profiles in different subway lines (using diverse types of brakes and/or pantographs). The co-emission of different sources poses a problem for their separation by receptor models. Nevertheless, receptor modelling (Positive Matrix Factorization) was applied resulting in ten sources, five of them subway-specific: RailWheel, RailWheel+Brake, Brake_A, Brake_B, Pb. The sum of their contributions accounted for 43-91% of bulk PM2.5 for the old stations and 21-52% for the stations with PSD. The decrease of the activity during the weekends resulted in a decrease (up to 56%) in the subway-specific sources contribution to the -already lower- bulk PM2.5 concentrations compared to weekdays. The health-related elements are mainly apportioned (> 60%) by subway sources.

Silica diatom shells tailored with Au nanoparticles enable sensitive analysis of molecules for biological, safety and environment applications.

Diatom shells are a natural, theoretically unlimited material composed of silicon dioxide, with regular patterns of pores penetrating through their surface. For their characteristics, diatom shells show promise to be used as low cost, highly efficient drug carriers, sensor devices or other micro-devices. Here, we demonstrate diatom shells functionalized with gold nanoparticles for the harvesting and detection of biological analytes (bovine serum albumin-BSA) and chemical pollutants (mineral oil) in low abundance ranges, for applications in bioengineering, medicine, safety, and pollution monitoring.

Chemical profiling of PM10 from urban road dust.

Road dust resuspension is one of the main sources of particulate matter with impacts on air quality, health and climate. With the aim of characterising the thoracic fraction, a portable resuspension chamber was used to collect road dust from five main roads in Oporto and an urban tunnel in Braga, north of Portugal. The PM10 samples were analysed for: i) carbonates by acidification and quantification of the evolved CO2, ii) carbonaceous content (OC and EC) by a thermo-optical technique, iii) elemental composition by ICP-MS and ICP-AES after acid digestion, and iv) organic speciation by GC-MS. Dust loadings of 0.48±0.39mgPM10m-2 were obtained for asphalt paved roads. A much higher mean value was achieved in a cobbled pavement (50mgPM10m-2). In general, carbonates were not detected in PM10. OC and EC accounted for PM10 mass fractions up to 11% and 5%, respectively. Metal oxides accounted for 29±7.5% of the PM10 mass from the asphalt paved roads and 73% in samples from the cobbled street. Crustal and anthropogenic elements, associated with tyre and brake wear, dominated the inorganic fraction. PM10 comprised hundreds of organic constituents, including hopanoids, n-alkanes and other aliphatics, polycyclic aromatic hydrocarbons (PAH), alcohols, sterols, various types of acids, glycerol derivatives, lactones, sugars and derivatives, phenolic compounds and plasticizers. In samples from the cobbled street, these organic classes represented only 439µgg-1PM10, while for other pavements mass fractions up to 65mgg-1PM10 were obtained. Except for the cobbled street, on average, about 40% of the analysed organic fraction was composed of plasticizers. Although the risk via inhalation of PAH was found to be insignificant, the PM10 from some roads can contribute to an estimated excess of 332 to 2183 per million new cancer cases in adults exposed via ingestion and dermal contact.

Impact of the wood combustion in an open fireplace on the air quality of a living room: Estimation of the respirable fraction.

Presently, both in rural areas and in cities open fireplaces are still present and large quantities of wood are combusted every year. The present study aims to characterize aerosol size distribution, chemical composition and deposition in the human respiratory tract of particles emitted during the combustion of logs of oak in an open fireplace installed in the living room of a typical village house. CO2 and CO levels and aerosol size distribution have been continuously monitored and a PM10 sampler with two types of filters for chemical and microscopic analysis was also installed. The increment, between the operating periods and the indoor background, in the organic carbon and PM10 concentration due to the use of the fireplace is 15.7±0.6 (mean±standard deviation) and 58.5±6.2µgm-3, respectively. The two main polluting processes during the operation of the fireplace are the ignition with the subsequent refueling and the final cleaning of the residual ashes. In both phases mean values around 1800 particles cm-3 with CMD of 0.15µm were measured. However, while PM10 levels of 130±120µgm-3 were estimated for the ignition stage, values of 200±200µgm-3 were obtained during the final cleaning step. Assessment conducted according to ISO standard 7708:1995, demonstrated that a person who stays in a living room when an open fireplace is lit will inhale, on average, 217µgm-3 and 283µgm-3 during the ignition and the refueling stages, respectively. Subsequent refueling proved to be much less polluting. The ashes removal can also be very polluting and dangerous to health if there are hidden small incandescent embers among the ashes (estimated PM10 of 132µgm-3), reaching a CO2 level of 1940ppm and a dangerous level of CO of 132ppm.