Secondary organic aerosol formation from straw burning using an oxidation flow reactor.

Herein, we use an oxidation flow reactor, Gothenburg: Potential Aerosol Mass (Go: PAM) reactor, to investigate the secondary organic aerosol (SOA) formation from wheat straw burning. Biomass burning emissions are exposed to high concentrations of hydroxyl radicals (OH) to simulate processes equivalent to atmospheric oxidation of 0-2.55 days. Primary volatile organic compounds (VOCs) were investigated, and particles were measured before and after the Go: PAM reactor. The influence of water content (i.e. 5% and 11%) in wheat straw was also explored. Two burning stages, the flaming stage, and non-flaming stages, were identified. Primary particle emission factors (EFs) at a water content of 11% (∼3.89 g/kg-fuel) are significantly higher than those at a water content of 5% (∼2.26 g/kg-fuel) during the flaming stage. However, the water content showed no significant influence at the non-flaming stage. EFs of aromatics at a non-flaming stage (321.8±46.2 mg/kg-fuel) are larger than that at a flaming stage (130.9±37.1 mg/kg-fuel). The OA enhancement ratios increased with the increase in OH exposure at first and decreased with the additional increment of OH exposure. The maximum OA enhancement ratio is ∼12 during the non-flaming stages, which is much higher than ∼ 1.7 during the flaming stages. The mass spectrum of the primary wheat burning organic aerosols closely resembles that of resolved biomass burning organic aerosols (BBOA) based on measurements in ambient air. Our results show that large gap (∼60%-90%) still remains to estimate biomass burning SOA if only the oxidation of VOCs were included.

A novel algorithm to determine the scattering coefficient of ambient organic aerosols.

In the present work, we propose a novel algorithm to determine the scattering coefficient of OA by evaluating the relationships of the MSEs for primary organic aerosol (POA) and secondary organic aerosol (SOA) with their mass concentrations at three distinct sites, i.e. an urban site, a rural site, and a background site in China. Our results showed that the MSEs for POA and SOA increased rapidly as a function of mass concentration in low mass loading. While the increasing rate declined after a threshold of mass loading of 50 µg/m3 for POA, and 15 µg/m3 for SOA, respectively. The dry scattering coefficients of submicron particles (PM1) were reconstructed based on the algorithm for POA and SOA scattering coefficient and further verified by using multi-site data. The calculated dry scattering coefficients using our reconstructing algorithm have good consistency with the measured ones, with the high correlation and small deviation in Shanghai (R2 = 0.98; deviations: 2.9%) and Dezhou (R2 = 0.90; deviations: 4.7%), indicating that our algorithms for OA and PM1 are applicable to predict the scattering coefficient of OA and Submicron particle (PM1) in China.

[An endpoint-detection algorithm of surface electromyography insensitive to electrocardiogram interference].

Surface electromyography (sEMG) has been widely used in the study of clinical medicine, rehabilitation medicine, sports, etc., and its endpoints should be detected accurately before analyzing. However, endpoint detection is vulnerable to electrocardiogram (ECG) interference when the sEMG recorders are placed near the heart. In this paper, an endpoint-detection algorithm which is insensitive to ECG interference is proposed. In the algorithm, endpoints of sEMG are detected based on the short-time energy and short-time zero-crossing rates of sEMG. The thresholds of short-time energy and short-time zero-crossing rate are set according to the statistical difference of short-time zero-crossing rate between sEMG and ECG, and the statistical difference of short-time energy between sEMG and the background noise. Experiment results on the sEMG of rectus abdominis muscle demonstrate that the algorithm detects the endpoints of the sEMG with a high accuracy rate of 95.6%.