Introduction: Indoor Air Pollution (IAP) is a serious problem, especially in enclosed environments where humans are present for a long period. Similar enclosed environments can be seen in educational Institutions, where employees and students spend much of their time. The objective of this research is to assess the Indoor Air Quality (IAQ) of engineering Institute's laboratories.
Materials and methods: The sample of Indoor Air Pollutants (IAPs) such as Particulate Matters (PM_1.0, PM_2.5, PM10), Total Volatile Organic Compounds (TVOC), Formaldehyde (HCHO), and Carbon dioxide (CO₂) were obtained by using a portable air quality meter from 12 different laboratories during July 2021 to September 2021 from 10:00 to 17:00. The statistical analysis was performed to interpret the outcomes.
Results: As a result, the higher concentration of PM_1.0, PM_2.5, PM₁₀, TVOC,
HCHO, and CO₂ was observed in ML11, ML2, ML12, ML5 and ML4. The correlation analysis shows that all laboratories, with the exception of ML4, ML5, ML9, and ML11, show good positive correlation for Particulate
Matter (PM) of all sizes (R2>0.90). Additionally, ML6 and ML9 exhibited a strong positive association (R2
>0.78) for TVOC, ML4 and ML8 for HCHO (R2>0.68), and ML3 and ML10 for CO2(R2>0.66). In addition, cluster analysis was performed on the datasets to group them into similar source categories. As a result, 3, 2, 2, 4, 3, and 3 clusters for PM_1.0, PM_2.5, PM₁₀, TVOC, HCHO, and CO₂ are extracted.
Conclusion: Overall, it appears that the presence of IAPs is caused by nearby outdoor activities, sweeping and dusting, wood furniture, paints, and poor ventilation in laboratories.

Introduction: Execution of COVID-19 lockdown measures caused variations in air pollution worldwide. This paper investigates the impact of COVID-19 stringency measures on the spatio-temporal dynamics of air pollution in Mumbai, India, using a comprehensive two-and-a-half-year pandemic period dataset.
Materials and methods: We classified the pandemic period into 7 phases and 21 sub-phases based on the severity of the Oxford COVID-19 Government Response Tracker (OxCGRT) Stringency Index (SI). Optimized Hotspot analysis (OHS) and Ordinary Least Square Regression models explored the spatio-temporal fluctuations and the effect of stringency measures on air quality.
Results: The R² value varied; with the best model R² of 0.61 for Particulate Matters (PM₁₀) and Nitrogen dioxide (NO₂) and lowest of 0.23 for Sulfur dioxide (SO₂).  A 10-point increase in SI caused a 3-7% reduction in air pollutants. Substantial reduction in average PM₁₀, PM_2.5, NO₂, and Carbon monoxide (CO) was observed throughout the COVID-19 phases. Meteorology and SI collectively caused maximum reduction of 82.6%, 72.7%, 53.8%, 52.2%, 49.1%, 28.4% for NO₂, PM_2.5, PM₁₀, NH₃, CO, and SO₂ respectively, during complete or extreme lockdown phases. Except SO₂, seasonality significantly influenced the pollutant concentrations. Winter was the worst period while monsoon was the best. OHS identified central Mumbai wards as hotspots and areas close to the national park as coldspots. 
Conclusion: PM₁₀, NO₂ and CO were more affected by SI measures than NH₃ and SO₂. For a rapid emergency response to high PM₁₀, implementation of SI, very high (≥ 80 score) and above is advised. Findings of this study have significant public health policy implications, especially among global south nations.

Introduction: Many urban cities in India, including National Capital Territory (NCT) of Delhi, have been adversely affected by air pollution since 2010s. Factors like atmospheric circulation, topography, local weather patterns, vehicular emission, industrial activities, waste burning etc. lead to extreme air pollution which is a growing threat to public health.
Materials and methods: The study was conducted to examine severity of air quality in Delhi from 2015 to 2020. For this purpose, Particulate Matters (PM_2.5 and PM₁₀) measurements were done at ITO, Mandir Marg, Punjabi Bagh, Anand Vihar, and R K Puram for a period of 2015 to 2020. Everyday data was collected to interpret and analyze the trend of air pollution both seasonally and annually.
Results: There was a significant increase in particulate matter levels at ITO, Mandir Marg, and RK Puram in the year 2016 while in the case of Anand Vihar the highest levels were measured in 2017. Also, Punjabi Bagh showed the highest PM₁₀ levels in 2017. The annual average data for all five sites indicates that PM_2.5 and PM₁₀ levels were above the air quality standard throughout the study period. Anand Vihar showed the highest level of particulate matter among all five locations during the study period of 2015 to 2020. The change in seasons is also one of the important factors affecting air quality. Overall, PM_2.5 and PM₁₀ concentration were recorded maximum during winters i.e. 218.07 μg/m³ and 358.80 μg/m³ respectively.
Conclusion: The results conclude that air quality deteriorated more during winters>autumn>summers>monsoon. Also, the air quality index (AQI) recorded for Delhi during the study period was highest in 2016, respectively. Though AQI decreased over the years, it lied in poor quality only.

Introduction: Recent climate changes and droughts have exacerbated the impact of dust sources globally, necessitating a thorough understanding of their influence on air quality. In Tehran, the interaction between internal dust sources from Iran and external sources from neighboring countries significantly affects air quality.
Materials and methods: This study spans a 20-year period (2003-2022), utilizing satellite data and advanced algorithms to analyze dust event trends and patterns. The material and methods section outlines the use of Aqua satellite MODIS sensor data alongside two algorithms to identify dust sources, focusing on Aerosol Optical Depth (AOD) data during peak dust event seasons. Statistical analysis of dust events in 2022 supplements the investigation.
Results: The analysis reveals distinct patterns in dust particle origin and transport, highlighting the predominant contribution of internal dust sources from Iran's southern Semnan province and significant input from external sources in Iraq and northern Saudi Arabia. Examining meteorological conditions during severe dust events highlights the role of synoptic conditions, particularly the presence of a tropospheric trough, in facilitating dust transport. Increased convective motions and downburst occurrences in specific regions further exacerbate the spread of dust particles, particularly those originating from external countries and provinces.
Conclusion: The conclusion emphasizes the complex interplay between internal and external dust sources and the necessity of understanding dust emission dynamics for effective mitigation strategies. It calls for proactive measures involving local and regional cooperation to mitigate dust pollution's adverse effects on air quality in Tehran and similar urban centers.

Introduction: This study investigated Polycyclic Aromatic Hydrocarbon (PAH) emissions from road traffic at the Surathkal toll plaza, in Karnataka, India. It focuses on two phases: when the toll station operated (Phase 1: January 2020 – March 2020) and when it was inactive (Phase 2: January 2023 – March 2023).

Materials and methods: The research examines Suspended Particulate Matter (SPM) concentration, its elemental analysis, and various PAH concentrations in it during both phases. Ultrasonic extraction and Gas Chromatography (GC) analysis were used to study 16 priority PAHs recommended by the United States Environmental Protection Agency (US-EPA), identifying eight in samples like SPM, soot, and green leaves. Inductively Coupled Plasma Optical Emission Spectrophotometer (ICPOES) analysed 14 elements in SPM.

Results: Results revealed higher PAH concentration during Phase 2, indicating that the presence of toll structure negatively affects air quality even when inactive. In contrast, SPM and its elements had higher mean concentrations during Phase 1, suggesting an inverse relationship between SPM and PAH levels. PAH diagnostic ratios showed different sources for each phase, including gasoline, diesel, fossil fuel, coal/biomass, and pyrogenic sources. Comprehensive health risk assessment using BaP equivalent concentration (BaP_eq) to estimate Inhalation Life-time Cancer Risk (ILCR), revealed an increased risk during both phases (0.045 during Phase 1 and 0.134 during Phase 2), higher than acceptable risk level (1×10^-6).

Conclusion: This research underscores the toll plaza's significant influence on air quality and calls for the development of mitigation measures.

In this present study, the association between occupational exposure to Respirable Crystalline Silica (RCS) and serum level of Clara Cell Protein (CC16) was investigated in the form of a systematic review and meta-analysis. Various databases including PubMed, Scopus, and Web of Sciences were searched until August 2022 based on Medical subject headings (MeSH) such as "CC10 protein, human" OR "Clara-cell specific 10-kD protein "OR "Clara cell phospholipid-binding protein human" AND Silicosis. Standardized Mean Difference (SMD) was used to compare the mean difference in CC16 serum levels between the silicotic and non-silicotic groups. During the initial database search until August 2022, 18 articles were found. By excluding duplicates and final screening in terms of compliance with the title and objectives, eight articles were included in our analysis. The overall effect estimate demonstrated that silicosis patients had lower serum level of CC16 (SMD:-3.58; 95% CI, from -5.14 to-2.3; I2 = 94.4% P-value<0.001) than that of the control group. Moreover, silicosis patients and exposed
individuals had lower serum level of CC16 (SMD:-3.32; 95% CI, from -4.19 to -2.45; I2 = 88.6% P-value<0.001) compared to the control group. The silica exposure had a lower CC16 level (SMD:-1.92; 95% CI, from -4.22 to 0.39; I2= 97.5% P-value<0.001) than the non-silicosis groups. The results demonstrated that occupational exposure to RCS is associated with the reduction of serum CC16 level. Therefore, the reduced serum level
 of CC16 protein can be used to monitor the maximum exposure level of workers to RCS in related workplaces.

Air pollution is one of the problems in many countries posing serious challenges the world is facing today. This is a global public health and environmental issue with multiple facets; it affects all aspects -human health, development, economy, land use and the environment. Although industrial revolution has been a great advancement in human life in terms of technology, societal development, creation and provision of multiple services, it has also resulted in the production of large quantities of unpleasant substances the atmosphere. It is no doubt that worldwide urbanization and industrialization are escalating at a high rate and reaching unprecedented proportions in many countries. In this article, we revisit the state of air pollution over southern Africa and assess the extent to which this can impact on the regional environment. The study is qualitative but also employs a blend of quantitative and qualitative evidence on the status of Air Quality (AQ) over southern Africa. The subcontinent is now a significant source of atmospheric and environmental pollution, having transformed from a rural to one of the more developing regions in the world. There is an influx of particulate and gas pollution from both local and remote sources. Prominent hotspots can be observed on satellites for Nitrogen Oxide (NO_x), Particulate Matter (PM) and Biomass Burning (BB) emissions around active areas. Depending on the nature of pollutant generation and amount, there are often differing levels of exposure to certain toxic elements, some of which are more harmful to human life. Increase in seasonal/annual pollution, in accordance with continued human development and industrial revolution can have a dire effect on the region, especially considering the growing African population. Comprehensive long-term AQ management programs are therefore needed to ensure that tolerable pollution levels are not exceeded, and that population exposure is taken care of.

Degradation of Indoor Air Quality (IAQ) due to confined spaces and insufficient ventilation has become a serious concern to human health. Published literature has established phytoremediation as an efficient removal mechanism of indoor air pollutants such as formaldehyde, Benzene, Toluene, Ethyl benzene, Xylene (BTEX), Volatile Organic Compounds (VOCs), and Particulate Matter (PM) using potted plants. This review discusses both conventional and enhanced phytoremediation for removing air pollutants and the parameters influencing the removal efficiencies. A literature review was conducted following the PRISMA guidelines to identify published literature on indoor air phytoremediation. After eliminating duplicates and reviewing articles, the articles related to indoor air phytoremediation from 2011 to the present were selected. The database was managed using Mendeley reference manager. Indoor air pollutants can be removed efficiently through phytoremediation using potted plants. Chlorophytum comosum removed the broadest range of contaminants, whereas Epipremnum aureum is the frequently used plant species for pollutant removal. Adding enhancing factors to the plant enhances their ability to remove pollutants. Inoculation of plants with soil bacteria such as Bacillus cereus ERBP is the most common enhancement method reported. The present study highlighted advancements in phytoremediation and factors affecting the pollutant removal efficiencies of plants. The findings demonstrated that enhanced phytoremediation is more effective at removing pollutants than the conventional method. Depending on the plant species used, the removal of indoor air pollutants may vary. The findings suggested that a combination of various plant species could be used to remove indoor air pollutants more efficiently.