Respiratory hospital admission risk near large composting facilities

Safe Circular Food Systems: A Transdisciplinary Approach to Identify Emergent Risks in Food Waste Nutrient Cycling

With growing awareness of the environmental, economic, and social costs associated with food waste, there is a concerted effort on multiple scales to recover the nutrient value of discarded food. These developments are positive, but the rapid movement toward alternatives and the complexity of solving problems located at the intersection of economic, social, and environmental systems also have the potential to produce unanticipated risks. This paper draws upon long-term stakeholder-engaged research throughout New England, with a focus on Maine, to develop a transdisciplinary, systems-based model of the potential social, economic, and environmental risks of food waste nutrient cycling. Our effort is intended to help inform the creation of safe, functional, and environmentally benign circular food systems.

Assessing the health risk of living near composting facilities on lung health, fungal and bacterial disease in cystic fibrosis: a UK CF Registry study

AIM

To explore the health risk of living near permitted composting sites (PCSs) on disease severity in children and adults with cystic fibrosis (CF) across the UK.  METHODS: A semi-individual cross-sectional study was used to examine the risk of disease severity in people with CF (pwCF) within and beyond 4 km of PCSs in the UK in 2016. All pwCF registered in the UK CF Registry were eligible for this study. Linear and Poisson regressions, adjusted for age, gender, genotype, BMI, Pseudomonas aeruginosa and deprivation, were used to quantify associations between distance to a PCS and percent predicted forced expiratory volume in one second (ppFEV₁), pulmonary exacerbations (#IVdays), and fungal and bacterial infections.

RESULTS

The mean age of the 9,361 pwCF (3,931 children and 5,430 adults) studied was 20.1 (SD = 14.1) years; 53.3% were male; and 49.2% were homozygous F508del. Over 10% of pwCF (n = 1,015) lived within 4 km of a PCS. We found no statistically significant difference in ppFEV₁ and #IVdays/year in children. However, in adults, ppFEV₁ was -1.07% lower (95% confidence interval (CI): -2.29%, 0.16%) and #IVdays/year were 1.02 day higher (95%CI: 1.01, 1.04) within 4 km of a PCS. Furthermore, there were statistically significant differences in mean ppFEV₁ in CF adults with Aspergillus fumigatus (58.2.% vs 62.0%, p = 0.005) and Candida spp. (56.9% vs 59.9%, p = 0.029) residing within 4 km of a PCS. No associations were identified for allergic bronchopulmonary aspergillosis, P. aeruginosa or Staphylococcus aureus.

CONCLUSIONS

This novel national study provides evidence that adults with CF living near a PCS may experience small reductions in lung function, an increased risk of pulmonary exacerbations, and more frequent fungal infections. If confirmed by studies using refined exposure assessment methods accounting for bioaerosol dispersion, these results could have important implications for the living environment of pwCF.

Combining multi-criteria decision analysis with GIS approaches for decentralized organic wastes composting plants site selection in Tiassalé, Southern Côte d'Ivoire

In recent years, decentralized composting appeared as one of the most appropriate treatment options for organic waste valorization in low- and middle-income countries. In Cote d'Ivoire, a pilot project has proved the feasibility of organic municipal solid waste composting for the city of Tiassalé. However, numerous issues still need to be addressed for the establishment of a sustainable decentralized composting system in this city. One of the key issues is site selection. Until now, there is no clear model for such plant site selection. In this study, multi-criteria decision analysis (MCDA) and geographical information system (GIS) approaches were combined to develop an appropriate model for selecting decentralized composting sites in the city of Tiassalé. The methodology used involved two different and complementary phases. First, MCDA and GIS techniques were used to identify the most suitable site areas. Seven criteria clustered in three main factors (environmental, social and economic), and five constraints were considered in the analysis process. Second, five sites were selected within the most suitable areas after a basic field visit and ranked using the Analytic Hierarchy Process. The results showed that the most suitable spaces for decentralized composting plant siting represent only 2.6% of the study area. The investigation yielded on the selection of the two best options for decentralized composting plant siting for the city of Tiassalé. This study proved that the combination of MCDA and GIS is a practical and efficient method to identify suitable sites for decentralized composting plants.

Size fractionation of bioaerosol emissions from green-waste composting

Particle size is a significant factor in determining the dispersal and inhalation risk from bioaerosols. Green-waste composting is a significant source of bioaerosols (including pathogens), but little is known about the distribution of specific taxa across size fractions. To characterise size fractionated bioaerosol emissions from a compost facility, we used a Spectral Intensity Bioaerosol Sensor (SIBS) to quantify total bioaerosols and qPCR and metabarcoding to quantify microbial bioaerosols. Overall, sub-micron bioaerosols predominated, but molecular analysis showed that most (>75%) of the airborne microorganisms were associated with the larger size fractions (>3.3 µm d_a). The microbial taxa varied significantly by size, with Bacilli dominating the larger, and Actinobacteria the smaller, size fractions. The human pathogen Aspergillus fumigatus dominated the intermediate size fractions (>50% d_a 1.1-4.7 µm), indicating that it has the potential to disperse widely and once inhaled may penetrate deep into the respiratory system. The abundance of Actinobacteria (>60% at d_a < 2.1 µm) and other sub-micron bioaerosols suggest that the main health effects from composting bioaerosols may come from allergenic respiratory sensitisation rather than directly via infection. These results emphasise the need to better understand the size distributions of bioaerosols across all taxa in order to model their dispersal and to inform risk assessments of human health related to composting facilities.

Assessment of airborne particles and bioaerosols concentrations in a waste recycling environment in Brazil

This study aims to assess the concentrations of size-fractioned particle mass (PM_1.0, PM_2.5, PM_4.0, PM₁₀) and number (PNC_0.3, PNC_0.5, PNC_1.0, PNC_2.5), bacteria, and fungi in a Materials Recycling Facility (MRF) in Brazil. The measurements were performed inside the waste processing shed (P1) and in the outdoor environment (P2) during working days in winter and spring of 2017, and summer of 2019. A total of 2,400 min of PM, 1,440 min of PNC, and 216 samples of bioaerosols were collected in the morning and afternoon. P1 has the strongest air contamination with mean values of 475.5 ± 563.7 µg m⁻³ for PM₁₀, 58.6 ± 36.0 cm⁻³ for PNC_0.3, 1,088.8 ± 825.2 colony-forming units per cubic meter (CFU m⁻³) for bacteria, and 2,738.3 ± 1,381.3 CFU m⁻³ for fungi. The indoor/outdoor ratios indicated the large influence of indoor sources due to the activities performed inside P1 that promote the generation and resuspension of pollutants. Gram-positive bacteria dominated with 58.6% of indoor samples. Overall, our results show a critical indoor air quality situation in a Brazilian MRF, which may cause several health risks for waste pickers. Finally, we call attention to the lack of occupational exposure limits for bioaerosols in industrial workplaces and mainly in MRFs.

Risk of respiratory hospital admission associated with modelled concentrations of Aspergillus fumigatus from composting facilities in England

Bioaerosols have been associated with adverse respiratory-related health effects and are emitted in elevated concentrations from composting facilities. We used modelled Aspergillus fumigatus concentrations, a good indicator for bioaerosol emissions, to assess associations with respiratory-related hospital admissions. Mean daily Aspergillus fumigatus concentrations were estimated for each composting site for first full year of permit issue from 2005 onwards to 2014 for Census Output Areas (COAs) within 4 km of 76 composting facilities in England, as previously described (Williams et al., 2019). We fitted a hierarchical generalized mixed model to examine the risk of hospital admission with a primary diagnosis of (i) any respiratory condition, (ii) respiratory infections, (iii) asthma, (iv) COPD, (v) diseases due to organic dust, and (vi) Cystic Fibrosis, in relation to quartiles of Aspergillus fumigatus concentrations. Models included a random intercept for each COA to account for over-dispersion, nested within composting facility, on which a random intercept was fitted to account for clustering of the data, with adjustments for age, sex, ethnicity, deprivation, tobacco sales (smoking proxy) and traffic load (as a proxy for traffic-related air pollution). We included 249,748 respiratory-related and 3163 Cystic Fibrosis hospital admissions in 9606 COAs with a population-weighted centroid within 4 km of the 76 included composting facilities. After adjustment for confounders, no statistically significant effect was observed for any respiratory-related (Relative Risk (RR) = 0.99; 95% Confidence Interval (CI) 0.96-1.01) or for Cystic Fibrosis (RR = 1.01; 95% CI 0.56-1.83) hospital admissions for COAs in the highest quartile of exposure. Similar results were observed across all respiratory disease sub-groups. This study does not provide evidence for increased risks of respiratory-related hospitalisations for those living near composting facilities. However, given the limitations in the dispersion modelling, risks cannot be completely ruled out. Hospital admissions represent severe respiratory episodes, so further study would be needed to investigate whether bioaerosols emitted from composting facilities have impacts on less severe episodes or respiratory symptoms.

Advances in mapping population and demographic characteristics at small-area levels

Temporally and spatially highly resolved information on population characteristics, including demographic profile (e.g. age and sex), ethnicity and socio-economic status (e.g. income, occupation, education), are essential for observational health studies at the small-area level. Time-relevant population data are critical as denominators for health statistics, analytics and epidemiology, to calculate rates or risks of disease. Demographic and socio-economic characteristics are key determinants of health and important confounders in the relationship between environmental contaminants and health. In many countries, census data have long been the source of small-area population denominators and confounder information. A strength of the traditional census model has been its careful design and high level of population coverage, allowing high-quality detailed data to be released for small areas periodically, e.g. every 10 years. The timeliness of data, however, becomes a challenge when temporally and spatially highly accurate annual (or even more frequent) data at high spatial resolution are needed, for example, for health surveillance and epidemiological studies. Additionally, the approach to collecting demographic population information is changing in the era of open and big data and may eventually evolve to using combinations of administrative and other data, supplemented by surveys. We discuss different approaches to address these challenges including (i) the US American Community Survey, a rolling sample of the US population census, (ii) the use of spatial analysis techniques to compile temporally and spatially high-resolution demographic data and (iii) the use of administrative and big data sources as proxies for demographic characteristics.

Monitoring of Air Microbial Contaminations in Different Bioenergy Facilities Using Cultural and Biomolecular Methods

Bioaerosol exposure linked to the bioenergy production from waste and its effects on human health in occupational and residential environments has rising interest nowadays. The health risk associated with the exposure includes mainly infective diseases, allergies, chronic bronchitis, and obstructive pulmonary disease. A risk assessment's critical point is the bioaerosol quality and quantity characterization. The aim of this study is to evaluate the application of different methods for the analysis of bioaerosol sampled in bioenergy plants. This study involved six Italian plants for the treatment of biomasses and energy production. Bioaerosol cultural evaluation was performed, by Surface Air System (SAS) sampler, and DNA was extracted from PM0.49 samples and Low Melting Agar plates. qRT-PCR followed by Denaturing Gradient Gel Electrophoresis (DGGE) and band sequencings were performed. The cultural method is able to detect less than 15% of what is evaluable with bio-molecular methods. A low sample alfa-diversity and a high beta-biodiversity in relation to feedstock and process were observed. Sequencing showed microorganisms with a hygienic-sanitary relevance such as Arcobacter, Pseudomonas, Enterobacter, Klebsiella, Enterococcus and Bacillus. Integrated cultural and biomolecular methods can be more exhaustive to evaluate bioaerosol's exposure in the occupational environment.

Estimating Aspergillus fumigatus exposure from outdoor composting activities in England between 2005 and 14

Bioaerosols, ubiquitous in ambient air, are released in elevated concentrations from composting facilities with open-air processing areas. However, spatial and temporal variability of bioaerosols, particularly in relation to meteorology, is not well understood. Here we model relative concentrations of Aspergillus fumigatus at each postcode-weighted centroid within 4 km of 217 composting facilities in England between 2005 and 2014. Facilities were geocoded with the aid of satellite imagery. Data from existing bioaerosol modelling literature were used to build emission profiles in ADMS. Variation in input parameters between each modelled facility was reduced to a minimum. Meteorological data for each composting facility was derived from the nearest SCAIL-Agriculture validated meteorological station. According to our results, modelled exposure risk was driven primarily by wind speed, direction and time-varying emissions factors incorporating seasonal fluctuations in compostable waste. Modelled A.fumigatus concentrations decreased rapidly from the facility boundary and plateaued beyond 1.5-2.0 km. Where multiple composting facilities were within 4 km of each other, complex exposure risk patterns were evident. More long-term bioaerosol monitoring near facilities is needed to help improve exposure estimation and therefore assessment of any health risks to local populations.

Scoping studies to establish the capability and utility of a real-time bioaerosol sensor to characterise emissions from environmental sources

A novel dual excitation wavelength based bioaerosol sensor with multiple fluorescence bands called Spectral Intensity Bioaerosol Sensor (SIBS) has been assessed across five contrasting outdoor environments. The mean concentrations of total and fluorescent particles across the sites were highly variable being the highest at the agricultural farm (2.6 cm^-3 and 0.48 cm^-3, respectively) and the composting site (2.32 cm^-3 and 0.46 cm^-3, respectively) and the lowest at the dairy farm (1.03 cm^-3 and 0.24 cm^-3, respectively) and the sewage treatment works (1.03 cm^-3 and 0.25 cm^-3, respectively). In contrast, the number-weighted fluorescent fraction was lowest at the agricultural site (0.18) in comparison to the other sites indicating high variability in nature and magnitude of emissions from environmental sources. The fluorescence emissions data demonstrated that the spectra at different sites were multimodal with intensity differences largely at wavelengths located in secondary emission peaks for λex 280 and λex 370. This finding suggests differences in the molecular composition of emissions at these sites which can help to identify distinct fluorescence signature of different environmental sources. Overall this study demonstrated that SIBS provides additional spectral information compared to existing instruments and capability to resolve spectrally integrated signals from relevant biological fluorophores could improve selectivity and thus enhance discrimination and classification strategies for real-time characterisation of bioaerosols from environmental sources. However, detailed lab-based measurements in conjunction with real-world studies and improved numerical methods are required to optimise and validate these highly resolved spectral signatures with respect to the diverse atmospherically relevant biological fluorophores.

A Controlled Study on the Characterisation of Bioaerosols Emissions from Compost

Bioaerosol emissions arising from biowaste treatment are an issue of public concern. To better characterise the bioaerosols, and to assess a range of measurement methods, we aerosolised green waste compost under controlled conditions. Viable and non-viable Andersen samplers, cyclone samplers and a real time bioaerosol detection system (Spectral Intensity Bioaerosol Sensor (SIBS)) were deployed simultaneously. The number-weighted fraction of fluorescent particles was in the range 22–26% of all particles for low and high emission scenarios. Overall fluorescence spectral profiles seen by the SIBS exhibited several peaks across the 16 wavelength bands from 298 to 735 nm. The size-fractionated endotoxin profile showed most endotoxin resided in the 2.1–9 μm aerodynamic diameter fraction, though up to 27% was found in a finer size fraction. A range of microorganisms were detected through culture, Matrix Assisted Laser Desorption and Ionisation Time of Flight Mass Spectrometry (MALDI-TOF) and quantitative polymerase chain reaction (qPCR), including Legionella pneumophila serogroup 1. These findings contribute to our knowledge of the physico-chemical and biological characteristics of bioaerosols from composting sites, as well as informing future monitoring approaches and data interpretation for bioaerosol measurement.

Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study

Objective To investigate the relation between exposure to both air and noise pollution from road traffic and birth weight outcomes.Design Retrospective population based cohort study.Setting Greater London and surrounding counties up to the M25 motorway (2317 km²), UK, from 2006 to 2010.Participants 540 365 singleton term live births.Main outcome measures Term low birth weight (LBW), small for gestational age (SGA) at term, and term birth weight.Results Average air pollutant exposures across pregnancy were 41 μg/m³ nitrogen dioxide (NO₂), 73 μg/m³ nitrogen oxides (NO_x), 14 μg/m³ particulate matter with aerodynamic diameter <2.5 μm (PM_2.5), 23 μg/m³ particulate matter with aerodynamic diameter <10 μm (PM₁₀), and 32 μg/m³ ozone (O₃). Average daytime (L_Aeq,16hr) and night-time (L_night) road traffic A-weighted noise levels were 58 dB and 53 dB respectively. Interquartile range increases in NO₂, NO_x, PM_2.5, PM₁₀, and source specific PM_2.5 from traffic exhaust (PM_{2.5 traffic exhaust}) and traffic non-exhaust (brake or tyre wear and resuspension) (PM_{2.5 traffic non-exhaust}) were associated with 2% to 6% increased odds of term LBW, and 1% to 3% increased odds of term SGA. Air pollutant associations were robust to adjustment for road traffic noise. Trends of decreasing birth weight across increasing road traffic noise categories were observed, but were strongly attenuated when adjusted for primary traffic related air pollutants. Only PM_{2.5 traffic exhaust} and PM_2.5 were consistently associated with increased risk of term LBW after adjustment for each of the other air pollutants. It was estimated that 3% of term LBW cases in London are directly attributable to residential exposure to PM_2.5>13.8 μg/m³during pregnancy.Conclusions The findings suggest that air pollution from road traffic in London is adversely affecting fetal growth. The results suggest little evidence for an independent exposure-response effect of traffic related noise on birth weight outcomes.

Use of dispersion modelling for Environmental Impact Assessment of biological air pollution from composting: Progress, problems and prospects

With the increase in composting asa sustainable waste management option, biological air pollution (bioaerosols) from composting facilities have become a cause of increasing concern due to their potential health impacts. Estimating community exposure to bioaerosols is problematic due to limitations in current monitoring methods. Atmospheric dispersion modelling can be used to estimate exposure concentrations, however several issues arise from the lack of appropriate bioaerosol data to use as inputs into models, and the complexity of the emission sources at composting facilities. This paper analyses current progress in using dispersion models for bioaerosols, examines the remaining problems and provides recommendations for future prospects in this area. A key finding is the urgent need for guidance for model users to ensure consistent bioaerosol modelling practices.

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.