Street-scale dispersion modelling framework of road-traffic derived air pollution in Hanoi, Vietnam.

Traffic is an important source of air pollution in Vietnamese cities. The spatio-temporal variation of air pollution derived from traffic is poorly understood. Application of dispersion modelling can help but is hindered by the local scarcity of suitable input data. This study fills the data gap, by establishing a framework employing open-access global data to model emission from traffic activities in Hanoi. The outlined methodology explicitly defines road sources, calculates their emission, and employs background pollution profiles from Copernicus Atmospheric Monitoring Service (CAMS) to produce street-scale distribution maps for CO, PM10 and PM2.5. Pollution hotspots are found near major traffic flows with the highest hourly average CO, PM10 and PM2.5 concentrations at 1206, 87.5 and 61.5 µgm-3, respectively. The relationship between concentrations and properties of the road network is assessed. Motorcycles are the main emitters of the traffic sector. Emission from Heavy Good Vehicles dominate during the night, with contribution percentages increase as it gets further away from the city core. Modelled concentrations are underestimated mainly due to low vehicular emission factor. Adjusting emission factors according to vehicle quality in Vietnam greatly improves agreement. The presence of non-traffic emission sources contributes to the model underestimation. Results for comparisons of daily averaged PM values are broadly in agreement between models and observations; however, diurnal patters are skewed. This results partly from the uncertainties linked with background pollution levels from CAMS, and partly from non-traffic sources which are not accounted for here. Further work is needed to assess the use of CAMS's concentrations in Vietnam. Meteorological input contributes to the temporal disagreement between the model and observations. The impact is most noticeable with CO concentrations during morning traffic rush hours. This study recommends approaches to improve input for future model iterations and encourage applications of dispersion modelling studies in similar economic settings.

Predicting Aspergillus fumigatus exposure from composting facilities using a dispersion model: A conditional calibration and validation.

Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are unclear. Exposure levels are difficult to quantify as established sampling methods are costly, time-consuming and current data provide limited temporal and spatial information. Confidence in dispersion model outputs in this context would be advantageous to provide a more detailed exposure assessment. We present the calibration and validation of a recognised atmospheric dispersion model (ADMS) for bioaerosol exposure assessments. The model was calibrated by a trial and error optimisation of observed Aspergillus fumigatus concentrations at different locations around a composting site. Validation was performed using a second dataset of measured concentrations for a different site. The best fit between modelled and measured data was achieved when emissions were represented as a single area source, with a temperature of 29°C. Predicted bioaerosol concentrations were within an order of magnitude of measured values (1000-10,000CFU/m3) at the validation site, once minor adjustments were made to reflect local differences between the sites (r2>0.7 at 150, 300, 500 and 600m downwind of source). Results suggest that calibrated dispersion modelling can be applied to make reasonable predictions of bioaerosol exposures at multiple sites and may be used to inform site regulation and operational management.

A critical review of classification of organisations in relation to the voluntary implementation of environmental management systems.

The need and ability of an organisation to manage and control its impact on the environment has been hotly debated in recent times. However, the uptake of certificated environmental management systems (EMS), specifically BS EN ISO 14001 (ISO 14001) (British Standards Institution, 2004), is becoming more prevalent, even though evidence of the individual benefits is less clear. Furthermore, reports are often limited and anecdotal in their discussion of the true barriers that organisations experience during the certification and management of their EMS. Presently organisations are commonly classified simply according to size and the barriers they experience when implementing an EMS successfully. This system of classification is not sufficient to understand the multifaceted environments within which modern organisations operate. This paper reviews existing classification methodologies relevant to environmental management so as to determine whether opportunities exist for their practical application in this sector. It begins with an introduction to EMS and existing discussions regarding implementation is provided before a more detailed consideration of organisational size, the integration and development of environmental management within an organisation, then cladistics and quality management systems (QMS) are reviewed as potential opportunities for classification. This shows that whilst numerous methods are available, none function beyond the theoretical, or that the classes provided restrain the description of the complex tasks. Central to differences faced by organisations are insights to the true hurdles that each experience when implementing an EMS. It is shown here how the manipulation of techniques from the more mature field of Energy Management may offer a direction for the development of robust classes. A valuable outcome is that these methods produce classifications that are fit for purpose to better support organisations through the implementation and management of their EMS.

Temporal and spatial changes in the microbial bioaerosol communities in green-waste composting.

In this study, the microbial community within compost, emitted into the airstream, downwind and upwind from a composting facility was characterized and compared through phospholipid fatty acid analysis and 16S rRNA gene analysis using denaturing gradient gel electrophoresis and bar-coded pyrosequencing techniques. All methods used suggested that green-waste composting had a significant impact upon bioaerosol community composition. Daily variations of the on-site airborne community showed how specific site parameters such as compost process activity and meteorological conditions affect bioaerosol communities, although more data are required to qualify and quantify the causes for these variations. A notable feature was the dominance of Pseudomonas in downwind samples, suggesting that this genus can disperse downwind in elevated abundances. Thirty-nine phylotypes were homologous to plant or human phylotypes containing pathogens and were found within compost, on-site and downwind microbial communities. Although the significance of this finding in terms of potential health impact was beyond the scope of this study, it clearly illustrated the potential of molecular techniques to improve our understanding of the impact that green-waste composting emissions may have on the human health.

Endotoxin emissions from commercial composting activities.

This paper describes an exploratory study of endotoxin emissions and dispersal from a commercial composting facility. Replicated samples of air were taken by filtration at different locations around the facility on 10 occasions. Measurements were made of endotoxin and associated culturable microorganisms. The inflammatory response of cell cultures exposed to extracts from the filters was measured. Endotoxin was detected in elevated concentrations close to composting activities. A secondary peak, of lesser magnitude than the peak at source was detected at 100-150 m downwind of the site boundary. Unexpectedly high concentrations of endotoxin were measured at the most distant downwind sampling point. Extracted endotoxin was found to stimulate human monocytes and a human lung epithelial cell line to produce significant amounts of pro-inflammatory cytokines. On a weight basis, endotoxin extracted from the composting source has a greater inflammatory cytokine inducing effect than commercial E. coli endotoxin.