SLIDE 1
Not bugging the neighbours: building an evidence-based regulatory - - PowerPoint PPT Presentation
Not bugging the neighbours: building an evidence-based regulatory - - PowerPoint PPT Presentation
Not bugging the neighbours: building an evidence-based regulatory framework for industrial bioaerosol management Rob Kinnersley Kerry Walsh Research, Analysis and Evaluation The drivers Increased diversion of organic waste from landfill to
SLIDE 2
SLIDE 3
Are people near biowaste and intensive farming sites at increased risk of adverse health outcomes through exposure to additional bioaerosol?
- Clinical/Epidemiological evidence for harm from bioaerosol
- Standardised methods for bioaerosol monitoring to allow
intercomparison
- Sufficient standardised data to give reliable exposure
estimates What types and concentrations of additional bioaerosol might people be exposed to? Are such process contributions likely to have an adverse impact on human health? YES NO
SLIDE 4
Are such process contributions likely to have an adverse impact on human health?
- Regulatory approach to protect human
health
- Means of assessing impact of
proposed new sites/expansion
- Performance of mitigation measures
- Consistent means of monitoring site
performance at proportionate cost YES NO
SLIDE 5
Impacts 1
SLIDE 6
Impacts 1
- Impacts at high concentrations
- Insufficient data or mechanistic
understanding for lower cut-off
Precautionary position
SLIDE 7
Sampling - objectives
Collect consistent bioaerosol concentration and speciation data, with specified uncertainties
Research for use in epidemiology and clinical research and defining management practices Regulatory to set and enforce a proportionate, targeted and enforceable regulatory position
SLIDE 8
Sampling - scenarios
SLIDE 9
Sampling - scenarios
Media Sample time Extraction
SLIDE 10
Sampling - scenarios
Sample times Solutions
SLIDE 11
Sampling - scenarios
SLIDE 12
Sampling - scenarios
Work in Progress…
SLIDE 13
Exposure - waste
SLIDE 14
Exposure – intensive agriculture
SLIDE 15
Exposure – intensive agriculture
SLIDE 16
Mitigation
Distance Containment Stacks “Tech”
SLIDE 17
Mitigation
Biofilter/scrubber performance
8 sites with open or closed biofilters, some with acid scrubbers Performance variable between filters and replicates Emission concentration independent of input concentration Removal of total bacteria, gram negatives and Af not correlated. No clear link between operating conditions and efficiency
SLIDE 18
Samples were collected using pre-sterilised IOM personal sampling heads
- perated as per the AfOR (2009) protocol – not ideal but linked into agreed
sampling plan.
- Fungal primers: ITS2_KYO1 and ITS1R_Wobble (CWGYGTTCTTCATCGATG)
amended version of ITS2 (White et al. 1990).
- Bacterial primers: 16S 515F and 806rB from Earth Microbiome project (Caporaso et.
- Al. 2012).
- Bash scripts used to complete chimera checking, OTU picking, taxonomy
assignment and relative abundance calculations can be found at http://www.github.com/rachelglover/bioaerosol
Impacts 2 – this time it’s causal
Next-generation Sequencing (Illumina MiSeq) of bioaerosol samples from intensive farming facilities
SLIDE 19
5 10 15 20 25 30 35
Percentage of overall reads attributed to source
Fungal bioaerosol profile from intensive farming facilities: Family level
Broiler Layer Swine
No Taxa assigned identity Broilers: 81 Layers: 101 Swine: 156
SLIDE 20
Relative abundance (% reads in DW sample attributed to source) Taxa Identity Broilers 23.5 12 11 6.3 Aspergillus cibarius Rhodosporidium diobovatum Malassezia sp. Penicillium solitum Layer 32 20 7.4 4.3 Bjerkandera adusta Scutellinia scutellata Penicillium brevicompactum Aspergillus cibarius Swine 11 10 6.5 6.3 Sarocladium strictum Cryptococcus victoriae Unidentified Lasiosphaeriaceae Harzia acremonioides
Most common taxa attributed to source: Fungi
SLIDE 21
10 20 30 40 50 % overall reads attributed to source
Bacterial bioaerosol profile from intensive farming facilities: Phyla level
Broiler Layer Swine
No Taxa assigned identity Broilers: 228 Layers: 409 Swine: 562
SLIDE 22
Most common taxa attributed to source: Bacteria
Relative abundance (% reads in DW sample attributed to source) Taxa Identity Broilers 7.7 4.2 4 3.5 Chryseobacterium sp. Unidentified Gaiellaceae Sediminibacterium sp. Unidentified Bifidobacteriaceae Layer 5.7 5.4 5 4.9 4.9 Lactobacillus sp. Knoellia Faecalibacterium prausnitzii Carnobacterium sp. Unidentified Xanthomonadaceae Swine 6.4 5.4 4.6 3.2 Lactobacillus sp. Unidentified Aerococcaceae Unidentified Clostridiaceae Prevotella sp.
SLIDE 23