Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in İstanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in İstanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in İstanbul was determined as \"poor\" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the İstanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m.

The government of India imposed a nationwide lockdown to tackle the outbreak of COVID-19 in 2020. This period witnessed record low anthropogenic activity, which had severe socio-economic impacts but also had orthogonal effects on the ambient air quality of the atmosphere. This study focuses on the variations in the atmospheric boundary layer (ABL) over a western Indian urban region in the light of COVID-19. Continuous backscatter recorded by a ceilometer, stationed at Ahmedabad, was used in this study to monitor the ABL during the national lockdown (NLD) in 2020 and state restrictions in 2021, and compared with the control year of 2019. In parallel, improvement in air quality during the NLD was observed by the SAFAR air quality station at Ahmedabad, with decreased particulate matter concentrations. The ground-based observations were substantiated by the ERA5 reanalysis dataset. A decline in the ABL height was recorded during the NLD, which showed improvement in 2021 but which was shy of the ABL in 2019. This was correlated with rain events during the observational period, recorded by an automatic weather station.

The nation-wide lockdowns imposed in India during March--May 2020 (in four phases) to curb the spread of the novel Corona virus, greatly enhanced the near-surface air-quality due to lowering of industrial, transport and human activities. The present study focuses on the changes in the vertical structure of aerosol concentration and how those changes impacted radiation balance, the planetary boundary layer (PBL) height and surface meteorological parameters. Instrumented tower and Ceilometer measurements made at Gadanki (13.45°N, 79.18°E), located in a rural environment, coupled with satellite-derived Aerosol Optical Depth (AOD) data have been used to understand the changes in lockdown period. Significant reduction in backscatter density during the lockdown compared to 2019 indicates that aerosol reduction during the lockdown is not only limited to the surface, rather observed in the entire PBL. Except for the fourth phase of lockdown during which several relaxations have been given for vehicular movement and other anthropogenic activities, the reduction in backscatter density is seen in all phases of lockdown. However, the reduction is prominently seen in the second and third phases. The AOD also reduced by 40% around Gadanki, comparable to that of in urban regions. Due to the reduction in aerosols during the lockdown period, the insolation increases by 60 Wm-2, which is expected to increase the temperature. However, the increased loss of long-wave radiation (due to reduction in trapping gases) and more rain events during the lockdown period decreased the temperature by ~1 °C. Measurements also suggest that the most of net radiation is partitioned into the latent heat flux increasing the humidity and lowering the PBL height (due to reduced strength of thermals and sensible heat flux).

Air quality models are used to assess the impact of smoke from wildland fires, both prescribed and natural, on ambient air quality and human health. However, the accuracy of these models is limited by uncertainties in the parametrisation of smoke plume injection height (PIH) and its vertical distribution. We compared PIH estimates from the plume rise method (Briggs) in the Community Multiscale Air Quality (CMAQ) modelling system with observations from the 2013 California Rim Fire and 2017 prescribed burns in Kansas. We also examined PIHs estimated using alternative plume rise algorithms, model grid resolutions and temporal burn profiles. For the Rim Fire, the Briggs method performed as well or better than the alternatives evaluated (mean bias of less than ±5-20% and root mean square error lower than 1000 m compared with the alternatives). PIH estimates for the Kansas prescribed burns improved when the burn window was reduced from the standard default of 12 h to 3 h. This analysis suggests that meteorological inputs, temporal allocation and heat release are the primary drivers for accurately modelling PIH.

Beijing\'s air quality has improved significantly since the implementation of the Air Pollution Prevention and Control Action Plan in 2013, but the local and regional contributions to this improvement have rarely been studied. Here, the vertical profile of the atmospheric backscattering coefficient (ABC) was measured by a ceilometer in Beijing from 2015 to 2020. The results show that the ABC in Beijing decreased the most at ground level from 2015 to 2020, decreasing 51.4%. Interannual variability decreased with height, and no noticeable change was found in the height range above 600 m. The most apparent declines occurred in autumn and winter, with decreases greater than 55.0%, and the minimum decrease occurred in summer, with a reduction of only 20.0%. To analyze the reasons for the autumn and winter declines, we divided the whole day into four periods according to the evolution characteristics of the atmospheric boundary layer. The significant decrease in the backscattering coefficient near the ground during the daytime confirms the effect of local emission reductions. In contrast, the considerable decreases in the backscattering coefficient measured at different heights in the midday mixing layer demonstrate the contribution of regional transport reduction. The above research results confirm the importance of regional coordinated air pollution control.

In this study, first, air pollution that is caused by the air pollutants\' concentration exceeding the limit value in Istanbul between 2017 and 2020 were analysed. In addition to this analysis, the effects of meteorological parameters on pollution were also examined within the same period of time. Second, for a 14-day period during which the concentration values of the air pollutants were calculated higher than the standards, therefore, were selected as an episode. In that respect, measurements of both pollutant and meteorological parameters were obtained from air quality monitoring stations. The Weather Research and Forecasting (WRF) model was used to examine the changes of meteorological parameters in the surface and upper atmospheric levels. The cross-correlation function (CCF) was performed together with both air quality monitoring station and the WRF model output data to examine the effects of temporal changes in meteorological parameters on air pollutant concentrations on a temporal scale. In addition, some meteorological parameters were obtained from remote sensing systems (SODAR and Ceilometer). Finally, with the help of the trajectory analysis model, it was determined whether the pollutant parameters were transported or not. Consequently, within a 3-year period, the most critical parameters in terms of pollution throughout the city were assessed as NO2 and PM10. Moreover, low wind speeds and high pressure values during the episode prevented the dispersion of pollutants and caused air pollution in Istanbul.

Aerosol-cloud interactions and feedbacks play an important role in modulating cloud development, microphysical and optical properties thus enhancing or reducing precipitation over polluted/pristine regions. The lockdown enforced on account of Covid-19 pandemic is a unique opportunity to verify the influence of drastic reduction in aerosols on cloud development and its vertical distribution embedded in identical synoptic conditions. Cloud bases measured by ceilometer in Delhi, the capital of India, are observed to propagate from low level to higher levels as the lockdown progresses. It is explained in terms of trends in temporal variation of cloud condensation nuclei (CCN) and precursor gases to secondary hygroscopic aerosols. The large reduction (47%) in CCN estimated from aerosol extinction coefficient during the lockdown results in upward shift of cloud bases. Low clouds with bases located below 3 km are found to have reduced significantly from 63% (of total clouds distributed in the vertical) during pre-lockdown to 12% in lockdown period (less polluted). Cloud base height is found to have an inverse correlation with CCN (r = -0.64) and NO2/NH3 concentrations (r = -0.7). The role of meteorology and CCN in modulating the cloud vertical profiles is discussed in terms of anomalies of various controlling factors like lifting condensation level (LCL), precipitable water content (PWC) and mixing layer height (MLH).

The thermal internal boundary layer (TIBL) is associated with coastal pollution dispersion, which can result in high concentrations of air pollutants near the surface of the Earth. In this study, boundary layer height data which were obtained using a ceilometer were used to assess the effect of the TIBL on atmospheric pollutants in Qinhuangdao, a coastal city in North China. A TIBL formed on 33% of summer days. When a TIBL formed, the sunshine duration was 2.4hr longer, the wind speed was higher, the wind direction reflected a typical sea breeze, and the boundary layer height was lower from 9:00 LT to 20:00 LT compared to days without a TIBL. If no TIBL formed, the average concentrations of PM2.5 and PM10 decreased with increasing boundary layer height. However, when a TIBL was observed, the average concentrations of PM2.5 and PM10 increased with increasing boundary layer height. Because the air from the sea is clean, PM2.5 and PM10 concentrations reached minimums in the daytime at 16:00 LT. After 16:00 LT, the PM2.5 and PM10 concentrations increased rapidly on days when a TIBL formed, which indicated that the TIBL leads to the rapid accumulation of atmospheric pollutants in the evening. Therefore, the maximum concentrations of particulate matters were larger when a TIBL formed compared to when no TIBL was present during the night. These results indicate that it is suitable for outdoor activities in the daytime on days with a TIBL in coastal cities.

The adoption of embedded systems, mobile devices and other smart devices keeps rising globally, and the scope of their involvement broadens, for instance, in smart city-like scenarios. In light of this, a pressing need emerges to tame such complexity and reuse as much tooling as possible without resorting to vertical ad hoc solutions, while at the same time taking into account valid options with regard to infrastructure management and other more advanced functionalities. Existing solutions mainly focus on core mechanisms and do not allow one to scale by leveraging infrastructure or adapt to a variety of scenarios, especially if actuators are involved in the loop. A new, more flexible, cloud-based approach, able to provide device-focused workflows, is required. In this sense, a widely-used and competitive framework for infrastructure as a service, such as OpenStack, with its breadth in terms of feature coverage and expanded scope, looks to fit the bill, replacing current application-specific approaches with an innovative application-agnostic one. This work thus describes the rationale, efforts and results so far achieved for an integration of IoT paradigms and resource ecosystems with such a kind of cloud-oriented device-centric environment, by focusing on a smart city scenario, namely a park smart lighting example, and featuring data collection, data visualization, event detection and coordinated reaction, as example use cases of such integration.