Decoding temporal patterns and trends of PM10 pollution over Delhi: a multi-year analysis (2015-2022).

The current study delved into an extensive analysis of multi-year observations on PM10 to have trends at various time scales in Delhi, India. High-resolution ground observations from all 37 monitoring stations from 2015 to 2022 were used. This study used non-parametric generalized additive model (GAM) based smooth-trend and Theil-Sen slope estimator techniques to analyze temporal trends and variations. The long-term PM10 concentration, both in its ambient and de-seasonalized forms, exhibited a statistically significant decreasing trend. An average decrease of - 7.57 [95% confidence interval (CI) - 16.51, 0.18] µg m-3 year-1 for ambient PM10 and - 8.45 [95% CI - 11.96, - 5.58] µg m-3 year-1 for de-seasonalized PM10 mass concentration was observed. Breaking it down into seasons, we observed significant declines in PM10 concentrations during monsoon (- 10.71 µg m-3 year-1, p < 0.1) and post-monsoon (- 7.49 µg m-3 year-1, p < 0.001). On the other hand, summer and winter displayed statistically insignificant declining trends of - 5.32 µg m-3 year-1 and - 6.06 µg m-3 year-1, respectively. Remarkably, all months except March displayed declining PM10 concentrations, suggesting a gradual reduction in particle pollution across the city. Further analysis of PM10 across various wind sectors revealed a consistent decreasing trend in all wind directions. The most substantial decrease was observed from the northwest (- 10.24 µg m-3 year-1), while the minimum reduction occurred from the east (- 5.67 µg m-3 year-1). Throughout the 8-year study period, the daily average PM10 concentration remained at 228 ± 124 µg m-3, ranging from 33 to 819 µg m-3. Seasonal variations were apparent, with concentrations during winter, summer, monsoon, and post-monsoon seasons averaging 279 ± 133, 224 ± 117, 135 ± 95, and 323 ± 142 µg m-3, respectively. November had the highest and August had the lowest concentration. Weekend PM10 concentration is slightly lower than weekdays. These findings emphasize the need for more stringent government action plans.

Affective symptoms as a predictor of internet addiction among young adults.

Objectives: Mental health difficulties have been found to be associated with internet addiction, which makes it a multifaceted problem. The current study aimed to examine the relationship between internet addiction and affective states (depression, anxiety, and stress). Material and Methods: The study sample consisted of 731 individuals (403 males and 328 females) ranging in age from 18 to 25 years. We used an observational survey design to study participants with an internet addiction test and depression, anxiety, and stress scale. Results: The mean age ± standard deviation of the sample was 22.58 ± 2.80 years. Stress and depression were found to play a major role in internet addiction in the regression analysis. Conclusions: The study supports the association between internet use and stress and depression. The findings imply the need for early identification and intervention of affective states in the context of unhealthy internet use.

Catalyst-free activation of methylene chloride and alkynes by amines in a three-component coupling reaction to synthesize propargylamines.

Propargylamines are synthesized via metal-free activation of the C-halogen bond of dihalomethanes and the C-H bond of terminal alkynes in a three-component coupling without catalyst or additional base and under mild reaction conditions. The dihalomethanes are used both as solvents as well as precursors for the methylene fragment (C1) in the final product. The scope of the reaction and the influence of various reaction variables has been investigated. A plausible reaction mechanism is proposed and the involvement of various intermediates that can be generated in situ in the process is discussed. The metal-free conditions also make this protocol environmentally benign and atom economical.