Air Pollution Measurements Research Articles

Impact of the COVID-19 pandemic and lockdown measures on clinical visits and subjective symptoms in childhood allergic rhinitis induced by house dust mites in Shanghai

BackgroundEstablishing the interaction between aeroallergens and air pollution in children with house dust mite induced allergic rhinitis (HDM-AR) remains challenging, especially in urban areas. The coronavirus disease 2019 (COVID-19) pandemic and the subsequent lockdown measures provided a valuable opportunity.MethodsWe analyzed the clinical data of HDM-AR children between March and August in 2018–2020, and classified the children according to the type and the degree of HDM sensitization. The records of patients’ hospital visits, allergic rhinitis symptoms assessments, and air pollution measurements in Shanghai were used to assess the differences before (2018–2019) and during the pandemic (2020), as well as during lockdown (March-June) and unlockdown (July-August) period in 2020.ResultsThe study included 1570 HDM-AR children aged 2 to 8 years old, 815 (51.9%) were monosensitized to HDM (mono-HDM-AR), and 755 (48.1%) were polysensitized to HDM (poly-HDM-AR). There was a significant increase in the rate of clinical visits among children with HDM-AR during the COVID-19 pandemic compared to pre-pandemic (P < 0.001), particularly among older children aged 7–8 years (P = 0.01). During the unlockdown period, there was a notable decrease in clinical visits for children with poly-HDM-AR (P < 0.001). Children with high levels of HDM sensitization exhibited significant symptom improvement in unlockdown period (P < 0.001). Although the air pollutants concentration had improved during the study, there was no effect on the improvement of HDM-AR children as expected.ConclusionsThe COVID-19 pandemic and its associated lockdown measures provided a unique context to observe the dynamics of management in children with HDM-AR. The findings underscore the complexity of managing allergic conditions in pediatric populations, highlighting the influence of environmental and lifestyle changes on disease presentation and the need for tailored approaches to treatment during periods of societal disruption.

Distribution of Air pollutant Concentration and Ammonium conversion rate in Livestock Areas: Focusing on Boryeong

Objectives:The association between the generation of fine particulate matter (PM2.5) and ammonia is well-established, highlighting the importance of managing ammonia as a primary means to reduce particulate matter. However, domestic research on ammonia emissions, particularly in livestock areas, which are major sources of ammonia, is insufficient. This study aims to contribute to pollutant management on a national scale by conducting air pollutant measurements and analyses in livestock areas. Methods:Real-time analysis and monitoring of air and weather conditions were carried out in Boryeong, Chungcheongnam-do, from 2021 to 2022. Statistical analysis was then employed to investigate the correlation between observed air pollutants (ammonia, nitrogen oxides, sulfur oxides, ozone and particle matters) and PM2.5. Results and Discussion:As a result of the analysis, the concentration of air pollutants in Boryeong showed a seasonal tendancy to decrease in summer and increase after that. Most substances such as NO2, SO2, and PM10 were observed within the standard values. In the case of ammonia, domestic air environment standards are not in place, but the annual average was found to be 61.5 ± 55.3 ppb, higher than in other research results. This discrepancy is attributed to the influence of nearby livestock houses. It was also observed that PM2.5 exceeded the annual standard value of 15 μg/m3 in spring (30.1 μg/m3), summer (18.3 μg/m3), autumn (25.3 μg/m3) and winter (31.7 μg/m3), respectively. During this period, ammonium (NH4+, 32.8%), nitrate (NO3-, 35.9%), and sulfate (SO42-, 19.7%) comprised the majority of particulate pollutants in PM2.5. The ammonia-ammonium conversion rate (NHR) was 0.08 annual average, and it was found that gas/ion phase changes were affected by seasonal weather conditions (temperature and relative humidity). As a result of analyzing the NHR according to the PM2.5 concentration, it was found that the higher the PM2.5 concentration, the higher the NHR. Furthermore, although the measurement area of this study exhibited high ammonia concentration, the NHR was low. This suggests that the contribution rate of ammonia to PM2.5 was relatively low compared to the other studies.Conclusion:As a result, there is a need for measures to reduce the high concentrations of ammonia in livestock areas. Simultaneously, considering the diverse mechanisms involved in particulate matter formation, it is suggested that management of pollutants such as nitrogen oxides, sulfur oxides including ammonia should be implemented.

Vehicle exhaust standards and urban air quality in China

This study quantifies the effects of increasing the share of low-emission passenger vehicles on urban air quality in China. We estimate a two-stage least squares model, using the phased implementation of National Vehicle Emission Standards VI in 2019 as an instrumental variable for fleet composition. Our findings indicate that a 1% increase in the share of vehicles compliant with the stricter vehicle exhaust standards leads to a 0.083% reduction in the average pollutant concentration across three measures of air pollution. Furthermore, our calculation suggests that the monetized health benefits from reductions in particulate matter outweigh the costs of adhering to stricter exhaust standards by a factor of two.

Land use regression model to predict nitrogen dioxide in the greater Philadelphia area

Because of greater concern of nitrogen dioxide (NO2) pollution for urban residents, monitoring efforts are typically focused in urban areas. However, large populations in suburban areas near urban centers may also experience elevated NO2 levels. This study focuses on the application of a land use regression (LUR) model to predict NO2 pollution in the suburban and urban areas around the city of Philadelphia, Pennsylvania, USA. Air pollutant measurements used for the LUR was obtained from Ogawa™ passive samplers, which were deployed at several sites (n = 15) throughout the Greater Philadelphia area. Passive samplers were deployed for two weeks each during the fall, winter, and spring months between 2021 and 2022. Predictor data included various spatial buffers of land use, landcover, and traffic counts, as well as distances to various roadway types. The best LUR model based on regression statistics (F-statistic with 4 and 10 degrees of freedom = 5.111, p < 0.05) showed that mean NO2 concentrations increase within a 1000m buffer of annual average daily traffic. The model shows a patchwork of NO2 concentrations throughout the study area that could indicate regional and local emissions. The results highlight spatial variations of elevated concentrations influenced by a mix of land use, including roads, residential, and industrial areas.

The effect of temperature on the Emission Factor of air emissions from pyrolysis of used tyres

Used tyres pyrolysis is an efficient solid waste management strategy for used tyres and a growing method of fuel oil production. However, the impact of air emissions associated at different temperature on ambient air quality has not been determined. To solve this problem, a pyrolysis fixed bed reactor and a condensing unit for separating liquid from produced gas were designed and constructed. 0.20 kg of used tyres were pyrolysed in the reactor and air emissions from the reactor chamber was characterized for air pollutants using the E-instrument E8500. Using a combination of measured mass of pollutants, mass of tyre pyrolzed and time taken during pyrolysis, Emission Factors of the air pollutants were established from the study at 200 °C, 300 °C and 400 °C. The concentration measured between 200 °C - 400 °C were in the range of 15 -7497 mg/m3, 0 – 4680 mg/m3, 38.25 – 103, 277.76 mg/m3 and 2 – 293 mg/m3 for CO, NOx, HC and H2S respectively. The developed emission factors were in the range of 16.52 – 8370.04 g kg-1, 0 – 4470.26 g kg-1, 42.126 – 104,055.9 g kg-1 and 2.20 – 322.69 g kg-1. The designed and constructed pyrolysis reactor and condenser unit were effective for used tyre pyrolysis while the measured air pollutants concentration were higher for all pollutants except H2S using the Federal Ministry of Environment (FEPA, 1991) standard. Hence, it is necessary to carry out further studies on air pollution control from waste tyre pyrolysis at lower temperature.

Mobile laboratory measurements of air pollutants in Baltimore, MD elucidate issues of environmental justice

ABSTRACT The City of Baltimore, MD has a history of problems with environmental justice (EJ), air pollution, and the urban heat island (UHI) effect. Current chemical transport models lack the resolution to simulate concentrations on the scale needed, about 100 m, to identify the neighborhoods with anomalously high air pollution levels. In this paper we introduce the capabilities of a mobile laboratory and an initial survey of several pollutants in Baltimore to identify which communities are exposed to disproportionate concentrations of air pollution and to which species. High concentrations of black carbon (BC) stood out at some locations – near major highways, downtown, and in the Curtis Bay neighborhood of Baltimore. Results from the mobile lab are confirmed with longer-term, low-cost monitoring. In Curtis Bay, higher concentrations of BC were measured along Pennington Ave. (mean [5th to 95th percentiles] = 2.08 [2.0–10.9] μg m−3) than along Curtis Ave. just ~ 150 m away (0.67[0.1 – 1.8] μg m−3). Other species, including criteria pollutants ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5), showed little gradient. Observations with high spatial and temporal resolution help isolate the mechanisms leading to locally high pollutant concentrations. The difference in BC appears to result not from heavier truck traffic or slower dispersion but from the interruptions in traffic flow. Pennington Ave. has three stoplights while Curtis Ave. has none. As heavy-duty diesel-powered vehicles accelerate, they experience turbo-lag and the resulting rich air-fuel mixture exacerbates BC emissions. Immediate mediation might be achieved through smoother traffic flow, and the long-term solution through replacing heavy-duty trucks with electric vehicles. Implications: We present results documenting the locations within Baltimore of high concentrations of Black Carbon pollution and identify the likely source – diesel exhaust emissions exacerbated by stop-and-go traffic and associated turbo-lag. This suggests solutions (smoother traffic, retrofit particulate filters, replacement of diesel with electric vehicles) that would enhance Environmental Justice (EJ) and could be applied to other cities with EJ problems. Synopsis: This paper presents observations of atmospheric black carbon aerosol showing impacts on environmental justice, then identifies causes and suggests solutions.

Vehicle emission models alone are not sufficient to understand full impact of change in traffic signal timings

Few studies have considered the real-world impact of changes in traffic signal timings on air pollution and pedestrian exposure with most only drawing their conclusion from vehicle emission models alone. Here, we consider two distinct cycle timings at a junction in London, UK, model the impact using a traffic microsimulation and a NOx emissions model, and compare these results with NOx and other air pollution measurements collected during a two-week field study at the junction.Our models predict that extending the cycle time leads to a 23% decrease in NOx emissions within a 15 m radius of the junction itself. When the wind direction was such that our sensors were downwind of the junction a 21% decrease in traffic and background-adjusted NOx concentrations were seen, suggesting that the intervention was successful. However, when the sensors were upwind of the junction, we observed an increase of 23% in adjusted NOx concentrations. Similar patterns were found for the other pollutants NO2, lung deposited surface area, black carbon and CO2 we measured. This indicates that meteorology was by far the greatest determinant of roadside concentrations during our two-week study period.Looking at pedestrian exposure for pedestrians waiting to cross the road, we found that their NOx exposure increased by 46% as waiting times to cross the road increased and that potential small reductions in air pollution were offset by increases in waiting times on the main road.The study demonstrates the need to go beyond assessing the impact of hyper-local traffic interventions on vehicle emissions. Real-world trials over extended periods are required to evaluate the impact of meteorology and changes to air pollution concentrations and pedestrian exposures.

Volatile organic compounds in typical coal chemical industrial park in China and their environmental and health impacts

The coal chemical industry produces a large amount of volatile organic compounds (VOCs), and the emission characteristics and associated impact on the environment and health of the residents are still unclear. This study determined the VOC concentrations and compositions in the Jinjie Coal Chemical Industry Park which is located in northern China. The average concentrations of total measured VOCs (TVOCs) in the industrial areas in summer and winter were 231.5 and 103.2 μg/m3, which were higher than those in the residential areas (123.7 and 70.3 μg/m3), respectively. Aromatics, Oxygenated volatile organic compounds (OVOCs), and alkanes were the dominant VOC classes in the industrial areas, while halocarbons, OVOCs, and alkenes had higher compositions in the residential areas where were not only affected by industrial emissions and also other anthropogenic sources. OVOCs contributed over 43% of ozone formation potential (OFP), while aromatics contributed over 61% of secondary organic aerosol (SOA) formation in the Park in both seasons. Using the source apportionment method, biogenic emission and anthropogenic source (gasoline production, coking emission, fuel combustion, solvent coating, and vehicle exhaust) were major contributors to VOCs in residential areas. The industrial-related emissions were the main components of anthropogenic source, accounting for 53.5%–58.7% of the overall VOCs. With reliable estimations of the health aspects, exposures to acrolein (HQ: 7.4–126.6) and formaldehyde (ILCR: 5.5 × 10−3-5.7 × 10−2) posed the highest non-carcinogenic and carcinogenic risks, accounting for 94.3%–98.6% and 55.8%–93.8% of the total HQ and ILCR, respectively. The results demonstrated that substantial environmental and health co-benefits to the residents could be achieved by reducing the industrial emissions from gasoline production, coking process, and diesel-fueled vehicles in the Jinjie Coal Chemical Industry Park. Prioritizing the establishment of efficient air pollution measures and tightening industrial emission standards, especially for hazardous VOCs, are recommended according to the findings of the valuable work.

Predicting and analysing air quality in smart cities using virtual sensors

Virtual sensors have become essential in generating synthetic data to support smart city initiatives, mainly when physical sensors are absent or inaccessible. They play a crucial role in monitoring air pollutants, benefiting those with health sensitivities, and aiding city planning in the context of smart cities. This research focuses on creating reliable victual sensors for air pollutant measurement through deep learning and machine learning models, providing a cost-effective solution to address the scarcity of physical sensors and data inaccuracies. The main contribution lies in improving smart cities by providing essential health-related data to mitigate the harmful effects of air pollution on residents. Continuous monitoring empowers officials and residents to reduce pollution exposure, ultimately improving public health. The study found that gradient-boosted trees are effective for daily and hourly predictions, emphasizing the vital role of virtual sensors in advancing data-driven decision-making and improving environmental quality in smart cities. The results showed that our model was better using the boosted trees method with an RMSE of approximately 10%.

Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid Environments.

Smart cities rely on a network of sensors to gather real-time data on various environmental factors, including air quality. This paper addresses the challenges of improving the accuracy of low-cost particulate matter sensors (LCPMSs) which can be compromised by environmental conditions, such as high humidity, which is common in many urban areas. Such weather conditions often lead to the overestimation of particle counts due to hygroscopic particle growth, resulting in a potential public concern, although most of the detected particles consist of just water. The paper presents an innovative design for an indicative air-quality measuring station that integrates the particulate matter sensor with a preconditioning subsystem designed to mitigate the impact of humidity. The preconditioning subsystem works by heating the incoming air, effectively reducing the relative humidity and preventing the hygroscopic growth of particles before they reach the sensor. To validate the effectiveness of this approach, parallel measurements were conducted using both preconditioned and non-preconditioned sensors over a period of 19 weeks. The data were analyzed to compare the performance of the sensors in terms of accuracy for PM1, PM2.5, and PM10 particles. The results demonstrated a significant improvement in measurement accuracy for the preconditioned sensor, especially in environments with high relative humidity. When the conditions were too severe and both sensors started measuring incorrect values, the preconditioned sensor-measured values were closer to the actual values. Also, the period of measuring incorrect values was shorter with the preconditioned sensor. The results suggest that the implementation of air preconditioning subsystems in LCPMSs deployed in smart cities can provide a cost-effective solution to overcome humidity-related inaccuracies, thereby improving the overall quality of measured air pollution data.

Contribution of ethnicity, area level deprivation and air pollution to paediatric intensive care unit admissions in the United Kingdom 2008–2021

There is emerging evidence on the impact of social and environmental determinants of health on paediatric intensive care unit (PICU) admissions and outcomes. We analysed UK paediatric intensive care data to explore disparities in the incidence of admission according to a child's ethnicity and the degree of deprivation and pollution in the child's residential area. Data were extracted on children <16 years admitted to UK PICUs between 1st January 2008 and 31st December 2021 from the Paediatric Intensive Care Audit Network (PICANet) database. Ethnicity was categorised as White, Asian, Black, Mixed or Other. Deprivation was quantified using the 'children in low-income families' measure and outdoor air pollution was characterised using mean annual PM2.5 level at local authority level, both divided into population-weighted quintiles. UK population estimates were used to calculate crude incidence of PICU admission. Incidence rate ratios were calculated using Poisson regression models. There were 245,099 admissions, of which 60.7% were unplanned. After adjusting for age and sex, Asian and Black children had higher relative incidence of unplanned PICU admission compared to White (IRR 1.29 [95% CI: 1.25-1.33] and 1.50 [95% CI: 1.44-1.56] respectively), but there was no evidence of increased incidence of planned admission. Children living in the most deprived quintile had 1.50 times the incidence of admission in the least deprived quintile (95% CI: 1.46-1.54). There were higher crude admission levels of children living in the most polluted quintile compared to the least (157.8 vs 113.6 admissions per 100,000 child years), but after adjustment for ethnicity, deprivation, age and sex there was no association between pollution and PICU admission (IRR 1.00 [95% CI: 1.00-1.00] per 1μg/m3 increase). Ethnicity and deprivation impact the incidence of PICU admission. When restricting to unplanned respiratory admissions and ventilated patients only, increasing pollution level was associated with increased incidence of PICU admission. It is essential to act to reduce these observed disparities, further work is needed to understand mechanisms behind these findings and how they relate to outcomes. There was no direct funding for this project. HM was funded by an NIHR Academic Clinical Fellowship (ACF-2022-18-017).

Clearing the air: A systematic review of studies on air pollution and childhood brain outcomes to mobilize policy change

Climate change, wildfires, and environmental justice concerns have drawn increased attention to the impact of air pollution on children’s health and development. Children are especially vulnerable to air pollution exposure, as their brains and bodies are still developing. The objective of this systematic review was to synthesize available empirical evidence on the associations between air pollution exposure and brain outcomes in developmental samples (ages 0–18 years old). Studies were identified by searching the PubMed and Web of Science Core Collection databases and underwent a two-phase screening process before inclusion. 40 studies were included in the review, which included measures of air pollution and brain outcomes at various points in development. Results linked air pollution to varied brain outcomes, including structural volumetric and cortical thickness differences, alterations in white matter microstructure, functional network changes, metabolic and molecular effects, as well as tumor incidence. Few studies included longitudinal changes in brain outcomes. This review also suggests methodologies for incorporating air pollution measures in developmental cognitive neuroscience studies and provides specific policy recommendations to reduce air pollution exposure and promote healthy brain development by improving access to clean air.

Assessment of the status of PM2.5 and ground-level O3 pollution variations and meteorological factor effects: A case study in Long An Province, Vietnam

Abstract Long An Province has a favorable geographical position in socio-economic development exchanges and is a fundamental bridge between the area of Ho Chi Minh City (HCMC) and the Southeast localities with the Southwestern provinces. Along with the master plan for socio-economic development with a vision for 2030, the province’s air quality issues, especially PM2.5 and surface O3 pollution, will be complex and pose many challenges to effective air pollution management and control. This study aims to investigate the effects of major meteorological characteristics (temperature–T, relative humidity–RH, surface pressure–P, and wind speed–WS) on temporal changes in the correlation between PM2.5 and surface O3 concentrations in Long An province in the 2018-2020 period (computed by a system of coupled WRF/CMAQ models) through trend evaluation using by Mann-Kendall (MK) Test and Theil-Sen Slope, and Pearson correlation analysis. The study results reported that in terms of temporal variations, both value levels of PM2.5 and O3 in the dry season tended to surpass that in the rainy season. Moreover, PM2.5 levels tended to exceed the 24-hour mean threshold (between 1.001 and 3.14 times) and the annual mean threshold (from 1.81 to 2.03 times) of the Vietnamese National Ambient Air Quality Standard. Based on the Pearson correlation analysis, significant influences of meteorological conditions on the pollution status of PM2.5 and surface O3 were also demonstrated, such as the different positive and negative correlations of each meteorological factor on concentration. These outstanding results serve as an essential reference for developing air quality targets and proposing future air pollutant control measures in Long An Province.

The Impact of Human Activities on Air Pollution in the Fallujah City, Al-Anbar Province – West Iraq

Air pollutant field study and laboratory sample analyses revealed that most of the air pollutants in Fallujah City come from various human activities. These activities: Factories, Bakeries, Private electric generators, etc represent the major sources of gaseous and particulate pollutants. Those emissions have affected the air quality of the air in study areas. This research aimed to identify air pollutant concentrations, and their effects, and develop immediate solutions to reduce their health and environmental impacts. Air pollutant measurements were taken for four sites, with each site having generators and bakeries, another five sites representing industrial activities, and another site representing the residential areas. These measurements which included total suspended particles (TSP), PM10, PM2.5, nitrogen dioxide (NO2), sulphate dioxide (SO2), methane (CH4) and (CO) were conducted in the winter and summer seasons. The plaster and asphalt factories and industrial district locations recorded the highest concentrations of particle pollutants (TSP, PM10, and PM2.5) and gases (NO2, SO2, CH4, and CO). It was also observed that there was an increase in the concentrations of total suspended particles, in addition to some gases measured at the sites of bread ovens and private electric generators, especially in the summer. Most of the sites recorded values higher than the local environmental allowable limits. The high concentrations of air pollutants measured at the study sites are due to the increased demand for electrical energy and the use of private electrical generators to compensate for the lack of electrical energy emitted by high air pollutants. In addition to the emissions of cement, plaster, and asphalt factories and the large quantities of suspended particles they release into the atmosphere resulting from crushing operations and loading operations for raw materials, in addition to the polluting gases they release resulting from the use of black oil, as well as the use of black oil as fuel in the bakeries, which leads to an increase in pollutant concentrations will, therefore, negatively affect air quality.

Respiratory health assessment of outdoor workers exposed to urban air pollution based on satellite observations

Human health impact assessment due to air pollution is critical for evaluating environmental hazards. In this research, levels of three air pollutants (CO, NO2, and SO2) were estimated based on satellite data (sentinel-5p) to assess the air quality over three areas (Al-Mahaad Al-Dinni, Bus Stop, and Oil Company areas) at Banha city, Qalyobia in addition to evaluating the human health risks resulting from exposure to these air pollutants. Unlike the conventional approaches for human health risk assessment, which depend on in-situ air pollution measurements, in this study, the spatial distribution of the pollutants was acquired from satellite remote sensing for the period 2021–2022. The respiratory health assessment of 151 outdoor workers, exposed to air pollution in Banha City was conducted. Results showed that the highest concentration of the pollutants was found in areas of Bus Stop and Oil Company. Consequently, the percentage of predicted pulmonary function tests was significantly lower among those working in the Oil company area than those working in the Bus Stop and Al-Mahaad Al-Dinni areas. Additionally, 47.6 % of the studied group complained of nasal congestion and 67.5 % of them complained of wheezing, 30.5% of them had obstructive airway diseases. In conclusion, remotely sensed air quality data proved its efficiency in health impact studies which could be carried out in different regions globally with less cost than traditional measurement techniques. Urban pollution can influence outdoor workers with varied percentages according to their exposure rate to pollutants and work-related factors.

P-730 A feasibility study of the impact of the level of exposure to ambient air pollutants on outcomes of assisted reproductive technologies

Abstract Study question What is the impact of air pollution exposure on outcomes for couples having IVF treatment? Summary answer Environmental exposure to high levels of air pollutants may negatively influence IVF outcomes with potential implications for fertility treatment. What is known already Air pollutants are harmful substances in the atmosphere that have adverse effects on human health. Increased levels of air pollutants have been associated with respiratory disorders, cardiovascular disease, and increased morbidity in humans across all age groups. Existing evidence suggests that increased exposure to air pollutants may adversely affect fertility. The relationship between air pollutants and IVF outcomes remains poorly understood. Study design, size, duration This was an ethically approved prospective observational feasibility study conducted over a two-year period. Ten couples due to undergo an IVF cycle were recruited from a fertility centre in the UK. Environmental exposure to ambient air pollutant for particulate matter (PM) 2.5 and 10 micron size was measured using portable AirBeam monitors over the course of two weeks from commencement of the ovarian stimulation regime. Participants/materials, setting, methods Eligible participants were those aged 18-35 years old, undergoing fresh IVF, with a good ovarian reserve and ability to provide informed consent. Data of interest included: BMI, age, parity, ethnicity, smoking status. IVF data included: number of oocytes retrieved, embryo quality and cycle outcomes. AirBeam device data was extracted, analysed and correlated with IVF outcomes. Participants feedback was sought for qualitative input for future studies. Main results and the role of chance Total of 28,269 data points of ambient air pollutant data for PM 2.5 and 10 micron size were recorded amongst the ten participants. One participant was exposed to significantly high air pollutant levels during ovarian stimulation on certain days (PM2.5 - 81.06 µg/m³ and PM10 - 154.48 µg/m³) compared to standard annual air pollution level for the UK of 25 µg/m³ for PM2.5 and 40 µg/m³ for PM10. Two women did not have embryo transfer due to embryo arrest. Of those who had transfer, 50% (n = 4) had positive pregnancy tests however three experienced early pregnancy losses. At the time of writing there was one ongoing single viable pregnancy. On correlation of air quality data with clinical outcomes, the one participant who exhibited fluctuant very high exposure levels to the measured air pollutants, had unexpected low fertilization rate (20%) with IVF and no transfer due to embryo arrest. Of the nine participants returning the questionnaire feedback, all but one rated it acceptable to most acceptable to carry the device around. The main barrier was the size of device and battery life. All respondents were willing to recommend others to participate in a future similar study confirming feasibility to recruit. Limitations, reasons for caution As a feasibility study, with a limited sample size, our findings should be interpreted cautiously. The small cohort limits the generalisability of our results. Further research with larger sample sizes is required to validate our findings. Wider implications of the findings Understanding the impact of air pollutants on IVF outcomes is important for developing evidence-based guidance and interventions to optimise fertility treatment efficacy. Our study demonstrates the feasibility of personal air quality monitoring and emphasises the necessity for larger scale research and the practicality of pollutant exposure measurements in fertility treatments. Trial registration number REC reference: 21/NE/0233 IRAS project ID: 294240. Theramex BIRTH Grant

Unveiling pollutants in Sonipat district, Haryana: Exploring seasonal, spatial and meteorological patterns

Air pollution is a serious environmental problem that aggravates climate change. Sonipat district, is a fast-urbanizing area with serious air pollution issues brought on by a variety of industry, busy traffic, and agricultural methods. Since in-situ measurements of air pollution are not feasible everywhere on Earth's surface, satellite data sets are crucial for determining trends in air pollution. This study uses several data sets, such as Sentinel-5P air pollution data, CHIRPS rainfall data, and GPWv4 population density data to investigate the spatial and temporal fluctuations of air pollution with reference to meteorological and other important socioeconomic factors. Pollutants include Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Sulphur Dioxide (SO2), Ozone (O3), and Absorbing Aerosol Index (AAI) are the main focus of the analysis during the winter, summer, and post-monsoon seasons. Findings revealed that the district's southeast portion has greater concentrations of CO and NO2, which are likely due to the intense traffic and industrial activity along National Highway 44. While O3 and SO2 exhibit seasonal fluctuations correlated with temperature and sunlight, AAI levels peak in the October in post-monsoon season as a result of regional wind patterns and agricultural burning. Rainfall during the September in post-monsoon season lowers the concentrations of pollutants because of retreating monsoon. Pollutant dispersion is greatly impacted by wind direction and speed. The study highlights the significance of weather-related elements in influencing air pollution levels and emphasizes the necessity for efficient air quality management and pollution mitigation techniques.

Reliable Air Quality Assessment in Dynamic Environments using Reward-learning Routing with Flying MANET Technology

&lt;p&gt;Air pollution poses significant threats to ecosystems, atmosphere, and the health of both humans and wildlife. It is primarily caused by industrial and chemical pollutants, leading to deterioration in air, water, and soil quality. As a result, effective air quality monitoring is crucial for environmental management. Flying Mobile Ad hoc Networks (FMANETs) offer a promising solution for intelligent air quality monitoring and assessment by employing unmanned aerial vehicles (UAVs) to measure air pollutants. However, FMANET-based systems face unique challenges, including UAVs' three-dimensional movement, high dynamism, rapid topological changes, resource constraints, and low UAV density. Therefore, routing optimization becomes a fundamental issue in these systems. In this paper, we propose a novel routing method named RFMAN (Reward-learning-based FMANET) for intelligent air quality monitoring systems. RFMAN consists of two main components: route discovery and route maintenance. In the route discovery phase, we introduce a Reward-learning-based mechanism to identify optimal routes, while also implementing a filtering parameter to refine the UAV selection process and reduce the search space. The route maintenance phase of RFMAN focuses on detecting and correcting paths nearing breakdowns, as well as promptly replacing failed paths to ensure continuous monitoring efficiency. The result section pictures that RFMAN outperforms other methods. Overall, RFMAN offers a promising solution for enhancing the effectiveness and reliability of air quality monitoring in FMANET-based systems.&lt;/p&gt;

Integrating Passive Biomonitoring and Active Monitoring: Spider Web Silk and Portable Instruments for Air Quality in Urban Areas

Urban areas worldwide face significant challenges from increasing air pollution, posing health risks and environmental concerns. Lahore, a major city in Pakistan, is particularly affected by severe air pollution due to rapid industrial growth, high vehicle emissions, and various human activities. Traditional air quality monitoring methods, while effective, are often costly and complex, limiting their widespread use. This study investigates a dual monitoring system combining passive biomonitoring with spider web silk and active measurements using portable instruments to assess airborne pollutants in urban environments. Spider webs, collected from various sites in Lahore, were analyzed for heavy metals, while portable instruments simultaneously measured PM2.5, PM10, total volatile organic contents, formaldehyde, and carbon monoxide at the same locations. A spatial distribution analysis using GIS and statistical analysis revealed a pattern with significant changes as per land use in the urban environment related to anthropogenic activities. The Principal Component Analysis revealed three distinct clusters of pollutants origins consisting of: I) effluent drains and landfills, II) construction sites, and III) residential areas. The concentrations of Hg in spider silk (average ~ 2.66 mg/kg) were found to be significantly higher in the northeastern part of Lahore, with a similar trend observed in Cd, Cu, Ni, and As levels (average ~ 15.45, 102.87, 31.72, and 6.64, respectively). Several-fold changes in levels and spatial distribution of Pb (15.12 to 356.41 mg/kg) showed a higher concentration in the northern and northeastern parts of Lahore. The spatial variation pattern of Cr (average~ 57.04 mg/kg) registered a higher concentration in southwestern Lahore. Ambient air levels of measured pollutants followed almost similar patterns in spatial distribution. PM2.5 and PM10 measured higher levels (195 and 226 μg/m3, respectively) in the southwestern and northwestern areas, with a similar pattern of variation observed in TVOC (average ~ 0.14 μg/m3). The concentration of HCHO (average ~ 0.003 μg/m3) was higher in the southwest of Lahore. All measured pollutants registered higher values than air quality standards. Particulate matter is the most dominant pollutant contributing to air pollution (up to 20x higher than WHO guidelines). The findings support the use of a dual monitoring system, integrating passive spider web silk biomonitoring and active portable instruments, as a scalable and sustainable solution for air quality management. This approach holds potential for global application in diverse urban environments, with future research focusing on further validation and integration with advanced remote sensing technologies to enhance air quality monitoring and contribute to improved public health and environmental management worldwide. Hence, this research work points to the potential use of spider silk as a biomonitoring tool in combination with instrumental measurement of ambient air pollutants.

Characterization of PM2.5 Carbonaceous Components in a Typical Industrial City in China under Continuous Mitigation Measures.

The goals of the "dual carbon" program in China are to implement a series of air pollution policies to reduce the emission of carbon-bearing particulate matter (PM). Following improvements in the reduction in carbon emissions in Handan City, China, fine particulate matter (PM2.5) was collected in the winters from 2016 to 2020 to characterize the concentrations and sources of carbonaceous components in PM2.5. Trend analysis revealed that both organic carbon (OC) and elemental carbon (EC) concentrations significantly decreased. The proportion of total carbon aerosol (TCA) in PM2.5 decreased by 47.0%, highlighting the effective reduction in carbon emissions. Secondary organic carbon (SOC) concentrations increased from 2016 (12.86 ± 14.10 μg·m-3) to 2018 (36.76 ± 21.59 μg·m-3) and then declined gradually. SOC/OC was larger than 67.0% from 2018 to 2020, implying that more effective synergistic emission reduction measures for carbonaceous aerosol and volatile organic compounds (VOCs) were needed. In the winters from 2016 to 2020, primary organic carbon (POC) concentrations reduced by 76.1% and 87.6% under a light/moderate pollution period (LP) and heavy/severe pollution periods (HPs), respectively. The TCA/PM2.5 showed a decreasing trend under LP and HP conditions, decreasing by 42.1% and 54.7%, respectively. Source analysis revealed that carbonaceous components were mainly from biomass burning, coal combustion and automotive exhaust emissions in the winters of 2016 and 2020. OC/EC and K+/EC analysis pointed out that air pollutant reduction measurements should focus on rectification biomass fuels in the next stage. Compared with 2016, the contributions of automotive exhaust emissions decreased in 2020. OC and EC concentrations decreased due to control measures on automotive exhaust emissions.