Ultrafine particles and PM2.5 in the air of cities around the world: Are they representative of each other?

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM2.5 (mass concentration of particles with aerodynamic diameter < 2.5 µm) and factors that influence their concentrations. Hourly average PNC and PM2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 103 to 19.5 × 103 particles·cm-3 and from 7.0 to 65.8 µg·m-3 for PNC and PM2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM2.5 demonstrated that a high PNC level does not lead to a high PM2.5, and vice versa. The particle number-to-mass ratio (in units of 109 particles·µg-1) ranged from 0.14 to 2.2, >1 for roadside sites and <1 for urban background sites with lower values for more polluted cities. The Pearson's r ranged from 0.09 to 0.64 for the log-transformed data, indicating generally poor linear correlation between PNC and PM2.5. Therefore, PNC and PM2.5 measurements are not representative of each other; and regulating PM2.5 does little to reduce PNC. This highlights the need to establish regulatory approaches and control measures to address the impacts of elevated UFP concentrations, especially in urban areas, considering their potential health risks.

Study on the Method of Voigt Profiles Two Wings Fitting Non-Uniform Flow Field Absorbance.

In the field of the absorption spectrum, especially for direct tunable diode laser absorption spectroscopy (dTDLAS) technology, the integrated area of the absorption spectrum is needed to be measured accurately for calculating the temperature and the component concentration of the flow field. Doing single optical path absorption spectroscopic measurement in the non-uniform flow field, spectral lineshape broadening is varied with the flow changes, in previous research reports, researchers mainly use single Voigt or Lorentz profile to fit absorbance curve or use directly integral to obtain the integrated area of the absorption spectrum. There are some shortcomings in these methods, resulting in certain error between the fitting result and the actual area, which is not conducive to the accurate measurement of flow field parameters. Firstly, the error is analyzed theoretically, and then, we adopt the simulation method to obtain the error size of the method. Finally, we proposed the Voigt wings fitting absorbance method to reduce the fitting error. The operation of Voigt wings fitting method is to Select the wings of the spectral line, and then use Voigt profile fitting, The difference between the two wings was used the numerical integral method to calculate area, the integrated area is sum of Voigt profile fitting area and numerical integral area. We have used water vapor as the target gas, with eight absorption lines which have different low-level states energy from HITRAN 2012 database being selected-, building two kinds of non-uniform flow field model base on the flat flame furnace, and through the method of segmentation to equivalent processing the no uniformity of flow field. Using Voigt profile fitting method, numerical integral method and Voigt profile wings fitting method to obtain the integral area of models, the error size is obtained by comparing with the theoretical value. As the result of contrast, the fitting error of Voigt profile fitting method is large and related to the different absorption line, the error of numerical integral method is biggest but it is nothing to do with absorption line, the fitting error of Voigt profile wings fitting method is least and stable. By force of contrast, we determined the appropriate method to obtain integral area in the different non-uniform flow field, which is beneficial to obtain accurate integrated area and flow field parameters.

Frequency analysis of the fibrillatory activity from surface ECG lead V1 and intracardiac recordings: implications for mapping of AF.

AIMS: Fibrillatory waves observed in the surface electrograms may be a direct reflection of the electrophysiologic mechanism of the atrial fibrillation (AF). This study compared the fibrillatory waves in the surface ECG and the individual intracardiac mapping sites in different types of paroxysmal AF. METHODS AND RESULTS: Thirty patients with paroxysmal AF originating from the pulmonary veins (PVs) or superior vena cava (SVC) were enrolled. Frequency analysis was performed on the intracardiac electrograms recorded from various mapping sites in both atria sequentially with simultaneous surface electrogram recordings. The SVC-AF patients had a trend toward a higher DF in ECG lead V1 when compared with the PV-AF patients (7.35 +/- 2.09 vs. 5.89 +/- 0.79 Hz, P = 0.018). The mean dominant frequency (DF) of the LA mapping sites in the PV-AF patients was higher than that in the SVC-AF patients (7.06 +/- 0.66 vs. 6.13 +/- 0.96 Hz, P = 0.009), whereas the mean DF of the RA mapping sites was similar between the two groups (5.84 +/- 0.80 vs. 6.26 +/- 1.11 Hz, P = NS). The intra-class correlation coefficient (ICC) between the mean DF of the RA sites and V1 was higher (r = 0.21, P = 0.02) when compared with the mean DF of the LA sites (r = -0.007, P > 0.05). Furthermore, the maximal ICC was observed in the anterolateral RA free wall (r = 0.84, P < 0.001) and not the other anatomic sites of the RA and LA. CONCLUSION: The fibrillatory activity observed in ECG lead V1 correlated primarily with the activity of the anterolateral RA free wall and thus may be useful for detecting the AF source if it is close to that area.