Matzen Kerr (oakcity37)

5-methylbenzotriazole (5-TTri) and 5-chlorobenzotriazole (CBT) are two benzotriazole derivatives widely used in various industrial and domestic applications. This paper reports on the photochemical behaviour of 5-TTri and CBT in aqueous solutions under UV radiation at 254 nm and the influences of pH, salinity, metal species and humic acid (HA) on their photo-transformation processes. The photolysis of 5-TTri and CBT under the exposure to UV light were found to follow the first-order reaction kinetic in all cases with half-lives ranging from 7.1 h to 24.3 h for 5-TTri and 5.1 h-20.5 h for CBT in various aqueous solutions containing metal ions and HA. The photolysis rates for both 5-TTri and CBT were strongly dependent on the solution pH value, and decreased with increasing solution pH. Salinity, metal species Cu2+ and Fe3+, and especially HA had inhibitory effects on the photolysis of 5-TTri and CBT under UV light irradiation at 254 nm. We proposed the tentative photo transformation schemes for both 5-TTri and CBT, which involved two photoproducts (4-methylaniline and N, N-diethylaniline- p-toluidine) and three photoproducts (4-chloroaniline, Aniline and 2,6-diethylaniline), respectively, via N-N and N-NH bond scission and dechlorination process.A line is a common geometry for pollution sources, e.g., outdoor traffic pollution, and is thus useful for developing a suitable source term estimation (STE) method. Most existing methods regard the source as a single point that only includes location and strength parameters; however, limited attention has been paid to the geometric information of the source. This negligence may cause errors, or even failure, in the STE. Therefore, this paper proposes a line source estimation method that combines Bayesian inference with the super-Gaussian function. This function can approximate the shape of sources with several intuitive coefficients, which are adjusted to their true value through Bayesian inference. The performance of the proposed method was evaluated through estimation of a line source in two cases an ideal urban boundary layer, via simulation, and a complex urban square, via a wind tunnel experiment. The results demonstrate that this method is capable of identifying the source information without any prior geometric information regarding the source. Moreover, it was confirmed that the conventional point-based assumption method leads to failure in estimating the line source, which implies that geometry estimation is necessary for STE. It is well known that air pollution causes respiratory morbidity and mortality by inducing airway inflammation. However, whether long-term exposure to air pollution is associated with increased incidence of chronic obstructive pulmonary disease (COPD) is controversial. We conducted a systematic review and meta-analysis with a random-effects model to calculate the pooled risk estimates of COPD development per 10μg/m increase in individual air pollutants. PubMed, Embase, and Cochrane Library were searched from the date of their inception to August 2019 to identify long-term (at least three years of observation) prospective longitudinal studies that reported the risk of COPD development due to exposure to air pollutants. The air pollutants studied included particulate matter (PM and PM ) and nitrogen dioxide (NO ). Of the 436 studies identified, seven met our eligibility criteria. Among the seven studies, six, three, and five had data on PM , PM , and NO , respectively. The meta-analysis results showed that a 10μg/m increase in PM is associated with increased incidence of COPD (pooled HR 1.18, 95% CI 1.13-1.23). We also noted that a 10μg/m increase in NO is marginally associated with increased incidence of COPD (pooled HR 1.07, 95% CI 1.00-1.16). PM seems to have no significant impact on the incidence of COPD (pooled HR 0.95, 95% CI 0.83-1.08), although t