Long-term analysis of the relationships between indoor and outdoor fine particulate pollution: A case study using research grade sensors

Sustainable modular biofiltration system with rainshower technology for AQI reform

India is the tenth most polluted nation in the world, according to the World Health Organization (WHO) 2022 assessment. Approximately 1.67 million deaths are caused by lung, cardiovascular, stroke, and chronic pulmonary obstruction worldwide (WHO 2024). In 2019, 1.36% of GDP was reported to be lost because of air pollution and related issues. The results presented in this article demonstrate the efficacy of UBREATHE RAIN. Ambient (outside), untested enclosure (reception), and tested enclosure (breathing lounge with 3 Ubreathe Rain) were the 3 test venues that were found based on proximity and interaction to the stubble burning site. The Air Quality Index (AQI) was recorded as the highest sub-index of pollutants involved (CO, PM, SO2, NO2, and O3) through grab sampling. Throughout the studies, the AQI in the tested enclosure was ~ 35% lower than that in the ambient environment and ~ 30% lower in the untested enclosure. Statistical analysis also supported this finding, as the p-value remains < 5% throughout (p-value ≈ 2%). Additionally, temperature and relative humidity changes were examined and demonstrated to represent significantly less of a challenge to the effectiveness of the proposed technology. The experiment's duration and demographics may have limited the given results and their importance.

Comprehensive air quality assessment including non-targeted approaches in primary schools from Spain

This work aims to establish a strategy to comprehensively assess the indoor air quality in schools including the analysis of chemical pollutants, bio-aerosols like fungi, bacteria and respiratory viruses and the identification of volatile and semi-volatile organic compounds applying non-targeted approaches. For this, a pilot study was performed in four primary schools from Spain, located in different urban and rural areas during different seasons. Common indoor pollutants, like CO2, NO2, O3, CO, particulate matter (PM10, PM2.5), ultrafine particles (UFP), total volatile organic compounds (TVOCs), and formaldehyde (HCHO), were assessed in terms of maximum recommended levels, daily variations, seasonality, and school location. Additionally, fungi and bacteria were studied indoors and they were always found at adequate levels. The most prevalent fungal genera were Aspergillus, Penicillium, and Cladosporium. Seventeen respiratory viruses were measured in the air of the assessed classrooms and none were detected. Volatile and semivolatile organic compounds were identified indoors and outdoors using non-targeted approaches based on GC-HRMS and UHPLC-HRMS. High-confidence identified compounds were classified according to their chemical and toxicological characteristics, revealing that 44% and 26% of them presented a high toxicological risk in outdoor and indoor environments, respectively. This study provides a new strategy to assess comprehensively the IAQ in schools, and expands the knowledge about contaminants present in these environments, giving rise to future research.

Exposure to indoor air pollution and angina among aging adults in India: evidence from a large-scale nationwide study

This study tried to understand the association between exposure to indoor air pollution and angina among the aging population in India. We utilized the data from the Longitudinal Ageing Study in India (LASI) Wave-1 (2017-2018), with a sample of 62,846 aging adults. We applied Chi-square and multivariate logistic regression models. The odds of angina were higher among individuals living in households that used solid fuels for cooking (aOR = 1.15, 99% CI- 1.09-1.20), had someone smoked inside the house (aOR = 1.12, 99% CI- 1.07-1.18), and households that used of incenses inside the home (aOR = 1.11, 99% CI- 1.05-1.18). In addition, it was also found that work-limiting impairment, unhealthy behaviors, and poor health status increased the odds of angina. These results indicate the need to reduce in-house air pollution by promoting clean fuel usage and changing attitudes and practices. Other implications are discussed.

Effect of environmental air pollutants on placental function and pregnancy outcomes: a molecular insight

Air pollution has become a major health concern, particularly for vulnerable populations such as the elderly, children, and pregnant women. Studies have reported a strong association between prenatal exposure to air pollutants and adverse pregnancy outcomes, including lower birth weight, reduced fetal growth, and an increased frequency of preterm births. This review summarizes the harmful effects of air pollutants, such as particulate matter, on pregnancy and outlines the mechanistic details associated with these adverse outcomes. Particulate pollutant matter may be able to cross the placenta barrier, and alterations in placental functions are central to the detrimental effects of these pollutants. In addition to associations with preeclampsia and gestational hypertension, air pollutants also induce oxidative stress, inflammation, and epigenetic alteration in the placenta. These pollutants can also affect placental homeostasis and endocrine function, contributing to pregnancy complications and possible transgenerational effects. Prenatal air pollution exposure has been linked to reduced cognitive and motor function in infants and newborns, increasing the predisposition to autism spectrum disorders and other neuropsychiatric disorders. This review also summarizes the use of various animal models to study the harmful effects of air pollution on pregnancy and postnatal outcomes. These findings provide valuable insight into the molecular events associated with the process and can aid in risk mitigation and adopting safety measures. Implementing effective environmental protocols and taking appropriate steps may reduce the global disease burden, particularly for developing nations with poor regulatory compliance and large populations of pregnant women.

Spatial Heterogeneity of the Respiratory Health Impacts of Wildfire Smoke PM2.5 in California

Wildfire smoke fine particles (PM2.5) are a growing public health threat as wildfire events become more common and intense under climate change, especially in the Western United States. Studies assessing the association between wildfire PM2.5 exposure and health typically summarize the effects over the study area. However, health responses to wildfire PM2.5 may vary spatially. We evaluated spatially-varying respiratory acute care utilization risks associated with short-term exposure to wildfire PM2.5 and explored community characteristics possibly driving spatial heterogeneity. Using ensemble-modeled daily wildfire PM2.5, we defined a wildfire smoke day to have wildfire-specific PM2.5 concentration ≥15 μg/m3. We included daily respiratory emergency department visits and unplanned hospitalizations in 1,396 California ZIP Code Tabulation Areas (ZCTAs) and 15 census-derived community characteristics. Employing a case-crossover design and conditional logistic regression, we observed increased odds of respiratory acute care utilization on wildfire smoke days at the state level (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.05, 1.07). Across air basins, ORs ranged from 0.88 to 1.57, with the highest effect estimate in San Diego. A within-community matching design and spatial Bayesian hierarchical model also revealed spatial heterogeneity in ZCTA-level rate differences. For example, communities with a higher percentage of Black or Pacific Islander residents had stronger wildfire PM2.5-outcome relationships, while more air conditioning and tree canopy attenuated associations. We found an important heterogeneity in wildfire smoke-related health impacts across air basins, counties, and ZCTAs, and we identified characteristics of vulnerable communities, providing evidence to guide policy development and resource allocation.

Using low-cost sensors to assess real-time comfort and air quality patterns in indoor households

People spend most of their time in indoor environments without knowing about the air quality in these spaces. In this study, indoor low-cost sensors were used (for 5 months) to assess the comfort and air quality patterns in two indoor households. To strengthen the robustness of the considered approach and build confidence in the obtained comfort and indoor air quality (IAQ) levels, the sensor measurements were also compared against information from reference monitoring equipment; in which, high correlation coefficients were obtained (> 0.85) and also low errors (on average 22%). The IAQ results were strongly influenced by the residents' activity and behaviour, the outdoor weather conditions, and indoor/outdoor air pollution sources. Overall, the recommended values of temperature and relative humidity for the occupant's comfort in indoor environments were not fulfilled. The highest particulate matter (PM) levels were recorded at the weekend (on average +14% higher), while maximum CO₂ and CO levels were obtained on the weekdays (on average +9% higher). PM daily profiles followed the outdoor concentrations with the maximum levels at the end of the night and the lowest values in the early morning/mid-afternoon. The highest and lowest CO₂ concentrations were registered in the early morning (< 1536 ppm) and mid-afternoon (< 627 ppm), respectively, while the CO daily profiles showed a high impact of outdoor emissions, with the minimum concentrations up to 0.81 mg m^-3 (at 10 a.m. or 6 p.m.), and a maximum concentration of 1.87 mg m^-3 (at 10 p.m.). Real-time comfort conditions and IAQ levels are a powerful approach to providing fast decisions to minimise human exposure and prevent negative health impacts.

Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.

K-means cluster analysis of cooperative effects of CO, NO2, O3, PM2.5, PM10, and SO2 on incidence of type 2 diabetes mellitus in the US

Air pollution (AP) has been shown to increase the risk of type 2 diabetes mellitus, as well as other cardiometabolic diseases. AP is characterized by a complex mixture of components for which the composition depends on sources and metrological factors. The US Environmental Protection Agency (EPA) monitors and regulates certain components of air pollution known to have negative consequences for human health. Research assessing the health effects of these components of AP often uses traditional regression models, which might not capture more complex and interdependent relationships. Machine learning has the capability to simultaneously assess multiple components and find complex, non-linear patterns that may not be apparent and could not be modeled by other techniques. Here we use k-means clustering to assess the patterns associating PM2.5, PM10, CO, NO2, O3, and SO2 measurements and changes in annual diabetes incidence at a US county level. The average age adjusted annual decrease in diabetes incidence for the entire US populations is -0.25 per 1000 but the change shows a significant geographic variation (range: -17.2 to 5.30 per 1000). In this paper these variations were compared with the local daily AP concentrations of the pollutants listed above from 2005 to 2015, which were matched to the annual change in diabetes incidence for the following year. A total of 134,925 daily air quality observations were included in the cluster analysis, representing 125 US counties and the District of Columbia. K-means successfully clustered AP components and indicated an association between exposure to certain AP mixtures with lower decreases on T2D incidence.

Air Quality and Behavioral Impacts of Anti-Idling Campaigns in School Drop-Off Zones

Vehicle emissions are a major source of pollution in urban communities and idling may contribute up to 34% or more to local air pollution levels. Reduced idling has been found to be an effective policy tool for improving air quality, especially around schools, where it may also improve outcomes for asthmatic children. We studied two anti-idling campaigns in Salt Lake County, Utah to understand if reduced engine idling leads to behavioral change and subsequent reduction in traffic-related air pollution exposure of the related school. We found a 38% decrease in idling time following an anti-idling campaign and an 11% decrease in the number of vehicles idling at the school drop-off zones. The air quality measurements showed improvement in the middle of the campaign, but seasonal variability as well as atmospheric inversion events had substantial effects on overall ambient pollutant concentrations. This study provides an encouraging starting point to develop more effective anti-idling campaigns to protect the health of children, school staff, and the surrounding community.

Intra-city variability of fine particulate matter during COVID-19 lockdown: A case study from Park City, Utah

Urban air quality is a growing concern due a range of social, economic, and health impacts. Since the SARS-CoV-19 pandemic began in 2020, governments have produced a range of non-medical interventions (NMIs) (e.g. lockdowns, stay-at-home orders, mask mandates) to prevent the spread of COVID-19. A co-benefit of NMI implementation has been the measurable improvement in air quality in cities around the world. Using the lockdown policy of the COVID-19 pandemic as a natural experiment, we traced the changing emissions patterns produced under the pandemic in a mid-sized, high-altitude city to isolate the effects of human behavior on air pollution. We tracked air pollution over time periods reflecting the Pre-Lockdown, Lockdown, and Reopening stages, using high quality, research grade sensors in both commercial and residential areas to better understand how each setting may be uniquely impacted by pollution downturn events. Based on this approach, we found the commercial area of the city showed a greater decrease in air pollution than residential areas during the lockdown period, while both areas experienced a similar rebound post lockdown. The easing period following the lockdown did not lead to an immediate rebound in human activity and the air pollution increase associated with reopening, took place nearly two months after the lockdown period ended. We hypothesize that differences in heating needs, travel demands, and commercial activity, are responsible for the corresponding observed changes in the spatial distribution of pollutants over the study period. This research has implications for climate policy, low-carbon energy transitions, and may even impact local policy due to changing patterns in human exposure that could lead to important public health outcomes, if left unaddressed.