A comparative assessment of air pollutants of smog in wagah border and other sites in Lahore, Pakistan / Uma avaliação comparativa de poluentes do ar do smog na fronteira de wagah e outros sites em Lahore, Paquistão

Abstract Smog has become the fifth season of Pakistan especially in Lahore city. Increased level of air pollutants (primary and secondary) are thought to be responsible for the formation of smog in Lahore. Therefore, the current study was carried out for the evaluation of air pollutants (primary and secondary) of smog in Wagah border particularly and other sites (Jail road, Gulburg) Lahore. For this purpose, baseline data on winter smog from March to December on primary and secondary air pollutants and meteorological parameters was collected from Environmental Protection Department and Pakistan Meteorological Department respectively. Devices being used in both departments for analysis of parameters were also studied. Collected data was further statistically analyzed to determine the correlation of parameters with meteorological conditions and was subjected to air quality index. According to results, PM 10 and PM 2.5 were found very high above the NEQS. NOx concentrations were also high above the permissible limits whereas SO2 and O3 were found below the NEQS thus have no roles in smog formation. Air Quality Index (AQI) of pollutants was PM 2.5(86-227), PM 10 (46-332), NOx (26-110), O3 (19-84) and SO2 (10-95). AQI of PM 2.5 remained between moderate to very unhealthy levels. AQI of PM 10 remained between good to hazardous levels. AQI of NOx remained between good to unhealthy for sensitive groups' levels. AQI of O3 and SO2 remained between good to moderate levels. Pearson correlation showed that every pollutant has a different relation with different or same parameters in different areas. It is concluded from the present study that particulate matter was much more responsible for smog formation. Although NOx also played role in smog formation. So there is need to reduce sources of particulate matter and NOx specifically in order to reduce smog formation in Lahore.

Resumo Smog tornou-se a quinta estação do Paquistão, especialmente na cidade de Lahore. Acredita-se que o aumento do nível de poluentes atmosféricos (primários e secundários) seja responsável pela formação de poluição atmosférica em Lahore. Portanto, o presente estudo foi realizado para a avaliação dos poluentes atmosféricos (primários e secundários) do smog na fronteira de Wagah em particular e em outros locais (Jail road, Gulburg) Lahore. Para este propósito, os dados de referência sobre a poluição atmosférica de inverno de março a dezembro sobre poluentes atmosféricos primários e secundários e parâmetros meteorológicos foram coletados do Departamento de Proteção Ambiental e do Departamento Meteorológico do Paquistão, respectivamente. Dispositivos sendo usados ​​em ambos os departamentos para análise de parâmetros também foram estudados. Os dados coletados foram posteriormente analisados ​​estatisticamente para determinar a correlação dos parâmetros com as condições meteorológicas e foram submetidos ao índice de qualidade do ar. De acordo com os resultados, PM 10 e PM 2,5 foram encontrados muito acima do NEQS. As concentrações de NOx também estavam muito acima dos limites permitidos, enquanto SO2 e O3 foram encontrados abaixo do NEQS, portanto, não têm papéis na formação de smog. O índice de qualidade do ar (AQI) de poluentes foi PM 2,5 (86-227), PM 10 (46-332), NOx (26-110), O3 (19-84) e SO2 (10-95). O AQI de PM 2,5 permaneceu entre níveis moderados a muito prejudiciais à saúde. O AQI de PM 10 permaneceu entre níveis bons e perigosos. AQI de NOx permaneceu entre bom e não saudável para os níveis de grupos sensíveis. O AQI de O3 e SO2 permaneceu entre níveis bons a moderados. A correlação de Pearson mostrou que cada poluente tem uma relação diferente com parâmetros diferentes ou iguais em áreas diferentes. Conclui-se do presente estudo que o material particulado foi muito mais responsável pela formação de smog. Embora o NOx também tenha desempenhado um papel na formação do smog. Portanto, é necessário reduzir as fontes de partículas e NOx, especificamente para reduzir a formação de smog em Lahore.

Assessment of particulate matter (PM) in ambient air of different settings and its associated health risk in Haripur city, Pakistan / Avaliação de material particulado (MP) no ar ambiente de diferentes configurações e sua associação com o risco à saúde na cidade de Haripur, Paquistão

Particulate matter (PM) is a major air pollutant causing serious health problems. The aim of the present study was to find out concentration of PM in ambient air and its associated health risk in Haripur city, Pakistan. Twenty-three samples were taken at various educational institutes, hospitals, recreational areas and industries in Haripur city. Concentration of PM2.5 (µg/m3) and PM10 (µg/m3) was measured with Youngteng YT-HPC 3000A portable PM counter. The results revealed that values of both PM2.5 and PM10 were above the permissible limits (35 µg/m3 for PM2.5 and 150 µg/m3 for PM10) set by Environmental Protection Agency Pakistan (Pak-EPA) in all the educational institutes, hospitals, recreational areas and industries investigated. Furthermore, significant (p<0.05) variation was found in the concentration of both PM2.5 and PM10 in all the educational institutes, hospitals, recreational areas, and industries studied. The concentration of PM2.5 was positively correlated with the concentration of PM10 in all the sampling sites. Therefore, from 1-14 scale standard of health index, the values of PM2.5 and PM10 exhibited that the ambient air quality of Haripur city Pakistan is under high risk. If the regulatory authorities such as Environmental Protection Agency, Health Department and Local Government monitor PM pollution in different settings of Haripur city, then a decrease can be possible in the pollution level. The remedies that can be taken to overcome the problem of ambient air pollution such as PM are plantation of trees at the sites where there are higher levels of air pollutants and use of masks on personal protection basis along with implementation of pollution control system in industries of Hattar Industrial Estate Haripur city, Pakistan.

O material particulado (MP) é um importante poluente do ar que causa sérios problemas de saúde. O objetivo do presente estudo foi descobrir a concentração de MP no ar ambiente e sua associação com o risco à saúde na cidade de Haripur, Paquistão. Vinte e três amostras foram coletadas em várias instituições de ensino, hospitais, áreas recreativas e indústrias na cidade de Haripur. A concentração de MP2,5 (µg/m3) e MP10 (µg/m3) foi medida por meio do contador de MP portátil Youngteng YT-HPC 3000A. Os resultados revelaram que os valores de MP2,5 e MP10 estavam acima dos limites permitidos (35 µg/m3 para MP2,5 e 150 µg/m3 para MP10) estabelecidos pela Agência de Proteção Ambiental do Paquistão (Pak-EPA) em todas as instituições de ensino, hospitais, áreas recreativas e indústrias investigadas. Além disso, foi encontrada variação significativa (p < 0,05) na concentração de MP2,5 e MP10 em todos os locais estudados. A concentração de MP2,5 correlacionou-se positivamente com a concentração de MP10 em todos os locais de amostragem. Portanto, a partir da escala padrão 1-14 do índice de saúde, os valores de MP2,5 e MP10 mostraram que a qualidade do ar ambiente na cidade de Haripur, Paquistão, está sob alto risco. Se as autoridades reguladoras, como a Pak-EPA, o Departamento de Saúde e o governo local, monitorarem a poluição por MP em diferentes configurações da cidade de Haripur, pode ser que haja uma diminuição no nível de poluição. As medidas que podem ser tomadas para superar o problema da poluição do ar ambiente, como o MP, são o plantio de árvores nos locais onde há maiores níveis de poluentes atmosféricos, o uso de máscaras e a implantação de sistema de controle de poluição nas propriedades industriais de Hattar, na cidade Haripur, Paquistão.

Estimation of premature death attributed to short- and long-term PM2.5 exposure in Thailand.

Particulate matter with a diameter of less than 2.5 microns (PM2.5) has been identified as a global health concern in recent decades. Indeed, PM2.5 exposure causes detrimental health problems in the general population. Estimating the short- and long-term health impacts of PM2.5 exposure should help to shape public health policy concerning air pollution. Hence, this study sought to estimate the rate of premature death attributable to PM2.5 exposure among the Thai population if the PM2.5 concentration met the applied counterfactual factor. The PM2.5 concentration, population numbers, and numbers of health incidences were collected from secondary data sources in 2019. A health impact analysis was performed using AirQ+ software to estimate the incidences of premature deaths attributable to PM2.5 exposure. More specifically, the analysis provided the estimated proportion of attributable cases and the rate of premature death per 100,000 population aged ≥ 30 years. The annual average PM2.5 concentration in Thailand was found to be 24.15 µg per cubic meter (µg/m3) in 2019, while the natural mortality rate was around 1,107 per 100,000 population nationwide. With regard to short-term PM2.5 exposure, it was determined that 8 premature deaths per 100,000 population could be prevented if the PM2.5 concentration met the World Health Organization (WHO) short-term gold standard of 15 µg/m3. Moreover, 159 premature deaths per 100,000 population could be avoided if the PM2.5 concentration met the WHO's long-term gold standard of 5 µg/m3. This estimation of premature deaths due to the short- and long-term impacts of PM2.5 exposure can support policymakers and stakeholders in creating a roadmap to combating the adverse impacts of PM2.5 exposure and protect the health of the Thai population.

Short-term association of CO and NO2 with hospital visits for glomerulonephritis in Hefei, China: a time series study.

Objective: Recent studies suggest air pollution as an underlying factor to kidney disease. However, there is still limited knowledge about the short-term correlation between glomerulonephritis (GN) and air pollution. Thus, we aim to fill this research gap by investigating the short-term correlation between GN clinical visits and air pollution exposure. Methods: Between 2015 and 2019, daily GN visit data from two grade A tertiary hospitals in Hefei City were collected, along with corresponding air pollution and meteorological data. A generalized linear model integrated with a distributed lag nonlinear model was employed to analyze the relationship between GN visits and air pollutants. Moreover, we incorporated a dual pollutant model to account for the combined effects of multiple pollutants. Furthermore, subgroup analyses were performed to identify vulnerable populations based on gender, age, and season. Results: The association between 23,475 GN visits and air pollutants was assessed, and significant positive associations were found between CO and NO2 exposure and GN visit risk. The single-day lagged effect model for CO showed increased risks for GN visits from lag0 (RR: 1.129, 95% CI: 1.031-1.236) to lag2 (RR: 1.034, 95% CI: 1.011-1.022), with the highest risk at lag0. In contrast, NO2 displayed a more persistent impact (lag1-lag4) on GN visit risk, peaking at lag2 (RR: 1.017, 95% CI: 1.011-1.022). Within the dual-pollutant model, the significance persisted for both CO and NO2 after adjusting for each other. Subgroup analyses showed that the cumulative harm of CO was greater in the cold-season and older adult groups. Meanwhile, the female group was more vulnerable to the harmful effects of cumulative exposure to NO2. Conclusion: Our study indicated that CO and NO2 exposure can raise the risk of GN visits, and female and older adult populations exhibited greater susceptibility.

Variants in transient receptor potential channels and toll-like receptors modify airway responses to allergen and air pollution: a randomized controlled response human exposure study.

BACKGROUND: Environmental co-exposure to allergen and traffic-related air pollution is common globally and contributes to the exacerbation of respiratory diseases. Individual responses to environmental insults remain variable due to gene-environment interactions. OBJECTIVE: This study examined whether single nucleotide polymorphisms (SNPs) in lung cell surface receptor genes modifies lung function change and immune cell recruitment in allergen-sensitized individuals exposed to diesel exhaust (DE) and allergen. METHODS: In this randomized, double-blinded, four-arm, crossover study, 13 allergen-sensitized participants underwent allergen inhalation challenge following a 2-hour exposure to DE, particle-depleted diesel exhaust (PDDE) or filtered air (FA). Lung function tests and bronchoscopic sample collection were performed up to 48 h after exposures. Transient receptor potential channel (TRPA1 and TRPV1) and toll-like receptor (TLR2 and TLR4) risk alleles were used to construct an unweighted genetic risk score (GRS). Exposure-by-GRS interactions were tested using mixed-effects models. RESULTS: In participants with high GRS, allergen exposure was associated with an increase in airway hyperresponsiveness (AHR) when co-exposed to PDDE (p = 0.03) but not FA or DE. FA and PDDE also were associated with a relative increase in macrophages and decrease in lymphocytes in bronchoalveolar lavage. CONCLUSIONS: TRPs and TLRs variants are associated with increased AHR and altered immune cellularity in allergen-exposed individuals. This effect is blunted by DE exposure, suggesting greater influence of unmeasured gene variants as primary meditators of a particulate-rich co-exposure. TRIAL REGISTRATION: The study was registered with ClinicalTrials.gov on December 20, 2013 (NCT02017431).

Virtual ecological technology: Concepts, systems, and application perspectives.

Virtual ecological technology is a new technology that builds the foundation of a digital ecological system, simulates the process of ecological evolution, and establishes a global knowledge analysis system based on a unified spatio-temporal benchmark. It is a new direction for the interdisciplinary integration and development of eco-logy, geographic information science, computer science and other subjects towards modernization, informatization, and intelligence. Research, development, and application of virtual ecological technology is of great significance for the development of ecology as a discipline, ecosystem management, and regional sustainable development. Curren-tly, research on virtual ecological technology is still in its infancy and lacks a complete and clearly defined framework, making it difficult to support systematic iterative development and scientific analysis. In this paper, starting from the main theories and objectives of modern ecology, we summarized the main contents and technical requirements of virtual ecological construction, and proposed a key technical system of virtual ecology that integrated vir-tual geography and digital twin technology. From the perspective of application scenarios, we analyzed the application capabilities of virtual ecological technology in air pollution and energy analysis. Finally, we summarized the deve-lopment potential of virtual ecological technology in the digital construction of the ecological environment, intelligent computing, and realistic expression of different levels of ecological space resources transformation under the background of new generation of information technology, both at the local computing point breakthrough and the global technology point fusion aspects. This would enrich and advance the technical capabilities that support China's ecological space resource transformation.

Effects of stubble burning and firecrackers on the air quality of Delhi.

Every year at the onset of winter season (October-November), crop residue/parali/stubble burning starts in Punjab and Haryana, leading to heavy air pollution in Delhi, and adversely affecting human and environmental health. During this time, the combination of unfavourable meteorological conditions, additional emissions from stubble burning, and firework activities in this area causes the air quality to further deteriorate. In this study, we have attempted to understand the influence of parali and firecracker incidents on air pollutants' variability over Delhi during the last three years (2020 to 2022). For this purpose, daily average particulate matter and gaseous pollutants data were fetched from the Central Pollution Control Board (CPCB), and daily total fire counts and fire radiative power (FRP) data were retrieved from NASA's Fire Information for Resource Management System (FIRMS). A bigger area of severe burning is suggested by higher FRP values and higher fire counts in the middle of November in all the years considered. Three years satellite-based FIRMS data over Punjab and Haryana show the highest number of active fire counts in 2021 (n = 80,505) followed by 2020 (n = 75,428), and 2022 (n = 49,194). More than 90% parali burning incidents were observed in Punjab state only despite the considerable variability in numbers among the years. The significant effect of parali burning was seen on pollutant concentration variability. As the number of fire count increases or decreases in Punjab and Haryana, there is a corresponding increase or decrease in the particulate matter concentration with a time lag of few days (1 to 2 days). The trend in backward air mass trajectories suggests that the variable response time of pollutants' concentration is due to local and distant sources with different air mass speeds. Our estimates suggest that stubble burning contributes 50-75% increment in PM2.5 and 40 to 45% increase in PM10 concentration between October and November. A good positive correlation between PM2.5, PM10, NOX, and CO and fire counts (up to 0.8) suggests a strong influence of stubble burning on air quality over Delhi. Furthermore, the firecracker activities significantly increase the concentration of particulate matter with ~100% increment in PM2.5 and ~55% increment in PM10 mass concentrations for a relatively shorter period (1 to 2 days).

Reversal of trends in global fine particulate matter air pollution.

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 µg/m3) to a peak in 2011 (38.9 µg/m3) and decreased steadily afterwards (34.7 µg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

AQI prediction using layer recurrent neural network model: a new approach.

The air quality index (AQI) prediction is important to evaluate the effects of air pollutants on human health. The airborne pollutants have been a major threat in Delhi both in the past and coming years. The air quality index is a figure, based on the cumulative effect of major air pollutant concentrations, used by Government agencies, for air quality assessment. Thus, the main aim of the present study is to predict the daily AQI one year in advance through three different neural network models (FF-NN, CF-NN and LR-NN) for the year 2020 and compare them. The models were trained using AQI values of previous year (2019). In addition to main air pollutants like PM10/PM2.5, O3, SO2, NOx, CO and NH3, the non-criteria pollutants and meteorological data were also included as input parameter in this study. The model performances were assessed using statistical analysis. The key air pollutants contributing to high level of daily AQI were found to be PM2.5/PM10, CO and NO2. The root mean square error (RMSE) values of 31.86 and 28.03 were obtained for the FF-NN and CF-NN models respectively whereas the LR-NN model has the minimum RMSE value of 26.79. LR-NN algorithm predicted the AQI values very closely to the actual values in almost all the seasons of the year. The LR-NN performance was also found to be the best in post-monsoon season i.e., October and November (maximum R2 = 0.94) with respect to other seasons. The study would aid air pollution control authorities to predict AQI more precisely and adopt suitable pollution control measures. Further research studies are recommended to compare the performance of LR-NN model with statistical, numerical and computational models for accurate air quality assessment.

Evaluation of air quality and health risks associated with trace elements in respirable particulates (PM2.5) from Islamabad, Pakistan.

Fine atmospheric particulates are associated with numerous environmental and health issues as they can penetrate deeply in the respiratory tract thereby adversely affecting the human health. This study aimed to investigate the concentrations of trace elements in the respirable (PM2.5) fraction of the atmospheric particulates and to understand their pollution status and health risks. The samples were collected from Islamabad, and the metals were extracted using HNO3 and HCl based extraction method. Atomic absorption spectroscopy was employed to quantify the concentrations of selected trace elements. PM2.5 exhibited considerable variations in their minimum (4.737 µg/m3) and maximum (108.1 µg/m3) levels. The significant contributors among the selected elements bound to PM2.5 were Ca (1016 ng/m3), K (759.8 ng/m3), Mg (483.0 ng/m3), Fe (469.7 ng/m3), and Zn (341.1 ng/m3), while Ag (0.578 ng/m3) was found at the lowest levels with an overall descending order: Ca > K > Mg > Fe > Zn > Cu > Pb > Ni > Cd > Mn > Sr > Cr > Co > Li > Ag. Multivariate PCA and CA identified industrial activities, combustion processes and automobile emissions as the main anthropogenic contributors to particulate pollution. Enrichment factors and geoaccumulation indices were computed to assess the pollution status. The results also revealed that among the trace elements, Cd showed extremely high contamination, followed by Ag, Zn, and Pb, which showed moderate to high contamination in the atmospheric particulates. Carcinogenic health risks from Pb and Ni were found to be within the safe limit (1.0 × 10-6); however, Cr, Co, and Cd exposure was linked to significant cancer risks. The present elemental levels in PM2.5 were also compared with the reported levels from other regions around the world.

Perception Matters: Perceived vs. Objective Air Quality Measures and Asthma Diagnosis among Urban Adults.

Urban air pollution is consistently linked to poorer respiratory health, particularly in communities of lower socioeconomic position (SEP), disproportionately located near highways and industrial areas and often with elevated exposures to chronic psychosocial stressors. Fewer studies, however, have considered air pollution itself as a psychosocial stressor and whether pollution may be impacting health through both direct physiologic and psychosocial pathways. We examined data on perceived air pollution exposures from a spatially representative survey of New York City adults through summer and winter 2012 (n = 1183) using residence-specific ambient nitrogen dioxide (NO2) and fine particulate matter (PM2.5) exposure estimates. We used logistic regression to compare associations for perceived and objective air quality on self-reported asthma and general health, adjusting for sociodemographics and mental health. In models including all exposure metrics, we found small but significant associations for perceived air quality (OR = 1.12, 95% CI: 1.04-1.22) but not for NO2 or PM2.5. Neither perceived nor objective pollution was significantly associated with self-reported general health. Results suggest that perceived air quality may be significantly associated with adult asthma, more so than objective air pollution and after adjusting for mental health-associations not observed for self-reported general health.

On thresholds for controlling negative particle (PM2.5) readings in air quality reporting.

Ambient PM2.5 (particles less than 2.5 µm in diameter) is monitored in many countries including Australia. Occasionally PM2.5 instruments may report negative measurements, although in realty the ambient air can never contain negative amounts of particles. Some negative readings are caused by instrument faults or procedural errors, thus can be simply invalidated from air quality reporting. There are occasions, however, when negative readings occur due to other factors including technological or procedural limitations. Treatment of such negative data requires consideration of factors such as measurement uncertainty, instrument noise and risk for significant bias in air quality reporting. There is very limited documentation on handling negative PM2.5 data in the literature. This paper demonstrates how a threshold is determined for controlling negative hourly PM2.5 readings in the New South Wales (NSW) air quality data system. The investigation involved a review of thresholds used in different data systems and an assessment of instrument measurement uncertainties, zero air test data and impacts on key reporting statistics when applying different thresholds to historical datasets. The results show that a threshold of -10.0 µg/m3 appears optimal for controlling negative PM2.5 data in public reporting. This choice is consistent with the measurement uncertainty estimates and the zero air test data statistics calculated for the NSW Air Quality Monitoring Network, and is expected not to have significant impacts on key compliance reporting statistics such as data availability and annual average pollution levels. The analysis can be useful for air quality monitoring in other Australian jurisdictions or wider context.

New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment.

BACKGROUND: Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America. OBJECTIVES: We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days. METHODS: We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations. RESULTS: The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited. DISCUSSION: The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to better characterize the causal relationship between exposures to PM2.5 and morbidity outcomes.

A pruned feed-forward neural network (pruned-FNN) approach to measure air pollution exposure.

Environmental epidemiology studies require accurate estimations of exposure intensities to air pollution. The process from air pollutant emission to individual exposure is however complex and nonlinear, which poses significant modeling challenges. This study aims to develop an exposure assessment model that can strike a balance between accuracy, complexity, and usability. In this regard, neural networks offer one possible approach. This study employed a custom-designed pruned feed-forward neural network (pruned-FNN) approach to calculate the air pollution exposure index based on emission time and rates, terrain factors, meteorological conditions, and proximity measurements. The model's performance was evaluated by cross-validating the estimated exposure indexes with ground-based monitoring records. The pruned FNN can predict pollution exposure indexes (PEIs) that are highly and stably correlated with the monitored air pollutant concentrations (Spearman's rank correlation coefficients for tenfold cross-validation (mean ± standard deviation: 0.906 ± 0.028) and for random cross-validation (0.913 ± 0.024)). The predicted values are also close to the ground truth in most cases (95.5% of the predicted PEIs have relative errors smaller than 10%) when the training datasets are sufficiently large and well-covered. The pruned-FNN method can make accurate exposure estimations using a flexible number of variables and less extensive data in a less money/time-consuming manner. Compared to other exposure assessment models, the pruned FNN is an appropriate and effective approach for exposure assessment that covers a large geographic area over a long period of time.

Backyard aerosol pollution monitors: foliar surfaces, dust enrichment, and factors influencing foliar retention.

Air pollution is one of the leading causes of death from noncommunicable diseases globally, and in Arizona, both mining activities and abandoned agriculture can generate erodible dust. This dust is transported via wind and can carry high amounts of toxic pollutants. Industry-adjacent communities, or "fenceline communities," are generally closer to the pollution sources and are disproportionally impacted by pollution, or in this case, dust. The dust transported from the mine settles into nearby rivers, gardens, and homes, and increases the concentrations of elements beyond their naturally occurring amounts (i.e., enriched). This study was built upon previous community science work in which plant leaves were observed to collect similar concentrations to an accepted dust collection method and illustrated promise for their use as low-cost air quality monitors in these communities. This work investigated the concentration of Na, Mg, Al, K, Ca, Mn, Co, Cu, Zn, Mo, and Ba in dust from the leaves of community-collected backyard and garden plants (foliar dust), as well as if certain variables affected collection efficacy. This assessment evaluated (1) foliar concentration versus surface area for 11 elements, (2) enrichment factor (EF) values and ratios, (3) comparisons of foliar, garden, and yard samples to US Geological Survey data, and (4) what variable significantly affected dust collection efficacy. The EF results indicate that many of the samples were enriched (anthropogenically contaminated) and that the foliar samples were generally more contaminated than the yard and garden soil samples. Leaf surface area was the most influential factor for leaf collection efficiency (p < 0.05) compared to plant family or sampling location. Further studies are needed that standardize the plant species and age and include multiple replicates of the same plant species across partnering communities. This study has demonstrated that foliar dust is enriched in the participating partnering communities and that plant leaf samples can serve as backyard aerosol pollution monitors. Therefore, foliar dust is a viable indicator of outdoor settled dust and aerosol contamination and this is an adoptable monitoring technique for "fenceline communities."

Fidelity and adherence to a liquefied petroleum gas stove and fuel intervention: The multi-country Household Air Pollution Intervention Network (HAPIN) trial.

BACKGROUND: Reducing household air pollution (HAP) to levels associated with health benefits requires nearly exclusive use of clean cooking fuels and abandonment of traditional biomass fuels. METHODS: The Household Air Pollution Intervention Network (HAPIN) trial randomized 3,195 pregnant women in Guatemala, India, Peru, and Rwanda to receive a liquefied petroleum gas (LPG) stove intervention (n = 1,590), with controls expected to continue cooking with biomass fuels (n = 1,605). We assessed fidelity to intervention implementation and participant adherence to the intervention starting in pregnancy through the infant's first birthday using fuel delivery and repair records, surveys, observations, and temperature-logging stove use monitors (SUMs). RESULTS: Fidelity and adherence to the HAPIN intervention were high. Median time required to refill LPG cylinders was 1 day (interquartile range 0-2). Although 26% (n = 410) of intervention participants reported running out of LPG at some point, the number of times was low (median: 1 day [Q1, Q3: 1, 2]) and mostly limited to the first four months of the COVID-19 pandemic. Most repairs were completed on the same day as problems were reported. Traditional stove use was observed in only 3% of observation visits, and 89% of these observations were followed up with behavioral reinforcement. According to SUMs data, intervention households used their traditional stove a median of 0.4% of all monitored days, and 81% used the traditional stove < 1 day per month. Traditional stove use was slightly higher post-COVID-19 (detected on a median [Q1, Q3] of 0.0% [0.0%, 3.4%] of days) than pre-COVID-19 (0.0% [0.0%, 1.6%] of days). There was no significant difference in intervention adherence pre- and post-birth. CONCLUSION: Free stoves and an unlimited supply of LPG fuel delivered to participating homes combined with timely repairs, behavioral messaging, and comprehensive stove use monitoring contributed to high intervention fidelity and near-exclusive LPG use within the HAPIN trial.

Air pollution and suicide in rural and urban America: Evidence from wildfire smoke.

Air pollution poses well-established risks to physical health, but little is known about its effects on mental health. We study the relationship between wildfire smoke exposure and suicide risk in the United States in 2007 to 2019 using data on all deaths by suicide and satellite-based measures of wildfire smoke and ambient fine particulate matter (PM2.5) concentrations. We identify the causal effects of wildfire smoke pollution on suicide by relating year-over-year fluctuations in county-level monthly smoke exposure to fluctuations in suicide rates and compare the effects across local areas and demographic groups that differ considerably in their baseline suicide risk. In rural counties, an additional day of smoke increases monthly mean PM2.5 by 0.41 µg/m3 and suicide deaths by 0.11 per million residents, such that a 1-µg/m3 (13%) increase in monthly wildfire-derived fine particulate matter leads to 0.27 additional suicide deaths per million residents (a 2.0% increase). These effects are concentrated among demographic groups with both high baseline suicide risk and high exposure to outdoor air: men, working-age adults, non-Hispanic Whites, and adults with no college education. By contrast, we find no evidence that smoke pollution increases suicide risk among any urban demographic group. This study provides large-scale evidence that air pollution elevates the risk of suicide, disproportionately so among rural populations.

Comparison of Pneumotachometer and Portable Digital Turbine Spirometry for Field-Based Assessment: An Air Quality, Environment, and Respiratory Outcomes in Bronchopulmonary Dysplasia Study.

Introduction: Data on the use of remote spirometry are limited in the pediatric population. We sought to assess the feasibility and accuracy of a digital turbine spirometer, Medical International Research (MIR) Spirobank Smart (MIR, New Berlin, WI, USA), compared with a pneumotachography spirometer, Pneumotrac (Vitalograph Inc., Lenexa, KS, USA), in field-based clinical research. Methods: This is a cross-sectional study of a subgroup of school-aged participants enrolled in the Air quality, Environment, and Respiratory Outcomes in Bronchopulmonary Dysplasia (BPD) study, who performed same-day paired coached baseline spirometry measurements from the Pneumotrac and MIR devices. Proportion of successful tests was estimated for each device and compared using McNemar's test. Correlation between devices forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) was analyzed by Lin's concordance correlation, and Bland-Altman plots were generated. Results: Twenty-one participants with history of BPD completed home spirometry maneuvers on both devices. The mean age of participants was 8.7 years. The mean FEV1 and FVC measurement was 81% predicted and 90.4% predicted, respectively. The proportion of acceptable tests appeared higher using Pneumotrac (81%) than when using MIR (67%), although without evidence of discordance (P = 0.317). Among subjects with successful tests on both devices, Lin's concordance correlation demonstrated moderate agreement (FEV1 r = 0.955, 95% confidence interval [CI]: 0.87-0.98; FVC r = 0.971, CI: 0.91-0.99). The mean difference in FEV1 between Pneumotrac and MIR was 0.079 L (95% limits of agreement were -0.141 to 0.298 L) and FVC was 0.075 L (95% limits of agreement were -0.171 to 0.322 L). These were relatively small and without evidence of systematic or volume-dependent bias. Conclusions: Utilizing turbine spirometers may be a promising and feasible way to perform pulmonary function testing for field research in children.