Phl p 5 levels more strongly associated than grass pollen counts with allergic respiratory health.

BACKGROUND: Studies have linked daily pollen counts to respiratory allergic health outcomes, but few have considered allergen levels. OBJECTIVE: We sought to assess associations of grass pollen counts and grass allergen levels (Phl p 5) with respiratory allergic health symptoms in a panel of 93 adults with moderate-severe allergic rhinitis and daily asthma hospital admissions in London, United Kingdom. METHODS: Daily symptom and medication scores were collected from adult participants in an allergy clinical trial. Daily counts of asthma hospital admissions in the London general population were obtained from Hospital Episode Statistics data. Daily grass pollen counts were measured using a volumetric air sampler, and novel Phl p 5 levels were measured using a ChemVol High Volume Cascade Impactor and ELISA analyses (May through August). Associations between the 2 pollen variables and daily health scores (dichotomized based on within-person 75th percentiles) were assessed using generalized estimating equation logistic models and with asthma hospital admissions using Poisson regression models. RESULTS: Daily pollen counts and Phl p 5 levels were each positively associated with reporting a high combined symptom and medication health score in separate models. However, in mutually adjusted models including terms for both pollen counts and Phl p 5 levels, associations remained for Phl p 5 levels (odds ratio [95% CI]: 1.18 [1.12, 1.24]), but were heavily attenuated for pollen counts (odds ratio [95% CI]: 1.00 [0.93, 1.07]). Similar trends were not observed for asthma hospital admissions in London. CONCLUSIONS: Grass allergen (Phl p 5) levels are more consistently associated with allergic respiratory symptoms than grass pollen counts.

Detection of Microplastics in Ambient Particulate Matter Using Raman Spectral Imaging and Chemometric Analysis.

Microplastics have been observed in indoor and outdoor air. This raises concern for human exposure, especially should they occur in small enough sizes, which if inhaled, reach the central airway and distal lung. As yet, methods for their detection have not spectroscopically verified the chemical composition of microplastics in this size-range. One proposed method is an automated spectroscopic technique, Raman spectral imaging; however, this generates large and complex data sets. This study aims to optimize Raman spectral imaging for the identification of microplastics (≥2 µm) in ambient particulate matter, using different chemometric techniques. We show that Raman spectral images analyzed using chemometric statistical approaches are appropriate for the identification of both virgin and environmental microplastics ≥2 µm in size. On the basis of the sensitivity, we recommend using the developed Pearson's correlation and agglomerative hierarchical cluster analysis for the identification of microplastics in spectral data sets. Finally, we show their applicability by identifying airborne microplastics >4.7 µm in an outdoor particulate matter sample obtained at an urban sampling site in London, United Kingdom. This semiquantitative method will enable the procurement of exposure concentrations of airborne microplastics guiding future toxicological assessments.

Post-fire carbon dynamics in the tropical peat swamp forests of Brunei reveal long-term elevated CH4 flux.

Tropical peatlands hold about 15%-19% of the global peat carbon (C) pool of which 77% is stored in the peat swamp forests (PSFs) of Southeast Asia. Nonetheless, these PSFs have been drained, exploited for timber and land for agriculture, leading to frequent fires in the region. The physico-chemical characteristics of peat, as well as the hydrology of PSFs are affected after a fire, during which the ecosystem can act as a C source for decades, as C emissions to the atmosphere exceed photosynthesis. In this work, we studied the longer-term impact of fires on C cycling in tropical PSFs, hence we quantified the magnitude and patterns of C loss (CO2 , CH4 and dissolved organic carbon) and soil-water quality characteristics in an intact and a degraded burnt PSF in Brunei Darussalam affected by seven fires over the last 40 years. We used natural tracers such as 14 C to investigate the age and sources of C contributing to ecosystem respiration (Reco ) and CH4 , while we continuously monitored soil temperature and water table (WT) level from June 2017 to January 2019. Our results showed a major difference in the physico-chemical parameters, which in turn affected C dynamics, especially CH4 . Methane effluxes were higher in fire-affected areas (7.8 ± 2.2 mg CH4  m-2  hr-1 ) compared to the intact PSF (4.0 ± 2.0 mg CH4  m-2  hr-1 ) due to prolonged higher WT and more optimal methanogenesis conditions. On the other hand, we did not find significant differences in Reco between burnt (432 ± 83 mg CO2  m-2  hr-1 ) and intact PSF (359 ± 76 mg CO2  m-2  hr-1 ). Radiocarbon analysis showed overall no significant difference between intact and burnt PSF with a modern signature for both CO2 and CH4 fluxes implying a microbial preference for the more labile C fraction in the peat matrix.