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Biogenic organic precursors play an important role in atmospheric new particle formation (NPF). One of the major precursor species is α-pinene, which upon oxidation can form a suite of products covering a wide range of volatilities. Highly oxygenated organic molecules (HOMs) comprise a fraction of the oxidation products formed. While it is known that HOMs contribute to secondary organic aerosol (SOA) formation, including NPF, they have not been well studied in newly formed particles due to their very low mass concentrations. Here we present gas- and particle-phase chemical composition data from experimental studies of α-pinene oxidation, including in the presence of isoprene, at temperatures (−50 and −30 ∘C) and relative humidities (20 % and 60 %) relevant in the upper free troposphere. The measurements took place at the CERN Cosmics Leaving Outdoor Droplets (CLOUD) chamber. The particle chemical composition was analyzed by a thermal desorption differential mobility analyzer (TD-DMA) coupled to a nitrate chemical ionization–atmospheric pressure interface–time-of-flight (CI-APi-TOF) mass spectrometer. CI-APi-TOF was used for particle- and gas-phase measurements, applying the same ionization and detection scheme. Our measurements revealed the presence of C8−10 monomers and C18−20 dimers as the major compounds in the particles (diameter up to ∼ 100 nm). Particularly, for the system with isoprene added, C5 (C5H10O5−7) and C15 compounds (C15H24O5−10) were detected. This observation is consistent with the previously observed formation of such compounds in the gas phase. However, although the C5 and C15 compounds do not easily nucleate, our measurements indicate that they can still contribute to the particle growth at free tropospheric conditions. For the experiments reported here, most likely isoprene oxidation products enhance the growth of particles larger than 15 nm. Additionally, we report on the nucleation rates measured at 1.7 nm (J1.7 nm) and compared with previous studies, we found lower J1.7 nm values, very likely due to the higher α-pinene and ozone mixing ratios used in the present study.
Biogenic organic precursors play an important role in atmospheric new particle formation (NPF). One of the major precursor species is α-pinene, which upon oxidation can form a suite of products covering a wide range of volatilities. Highly oxygenated organic molecules (HOMs) comprise a fraction of the oxidation products formed. While it is known that HOMs contribute to secondary organic aerosol (SOA) formation, including NPF, they have not been well studied in newly formed particles due to their very low mass concentrations. Here we present gas- and particle-phase chemical composition data from experimental studies of α-pinene oxidation, including in the presence of isoprene, at temperatures (−50 and −30 ∘C) and relative humidities (20 % and 60 %) relevant in the upper free troposphere. The measurements took place at the CERN Cosmics Leaving Outdoor Droplets (CLOUD) chamber. The particle chemical composition was analyzed by a thermal desorption differential mobility analyzer (TD-DMA) coupled to a nitrate chemical ionization–atmospheric pressure interface–time-of-flight (CI-APi-TOF) mass spectrometer. CI-APi-TOF was used for particle- and gas-phase measurements, applying the same ionization and detection scheme. Our measurements revealed the presence of C8−10 monomers and C18−20 dimers as the major compounds in the particles (diameter up to ∼ 100 nm). Particularly, for the system with isoprene added, C5 (C5H10O5−7) and C15 compounds (C15H24O5−10) were detected. This observation is consistent with the previously observed formation of such compounds in the gas phase. However, although the C5 and C15 compounds do not easily nucleate, our measurements indicate that they can still contribute to the particle growth at free tropospheric conditions. For the experiments reported here, most likely isoprene oxidation products enhance the growth of particles larger than 15 nm. Additionally, we report on the nucleation rates measured at 1.7 nm (J1.7 nm) and compared with previous studies, we found lower J1.7 nm values, very likely due to the higher α-pinene and ozone mixing ratios used in the present study.
Introduction: Clinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy. Methods and analysis: Planned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. Scope: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. Population: patients (≥18 years) with polypharmacy (≥5 prescriptions). Sample size: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. Intervention: complex intervention eMMa. Follow-up: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. Outcomes: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. Statistical analysis: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.
This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, |GE | and |GM|, using the ¯pp → μ+μ− reaction at PANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at PANDA, using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is ¯pp → π+π−,due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distribuations of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented.