Levels Of Particulate Matter Research Articles

Systematic Review of Air Pollution in Ethiopia: Focusing on Indoor and Outdoor Sources, Health, Environment, Economy Impacts and Regulatory Frameworks

The varied geography (Bekele, 1996) and rapid economic growth of Ethiopia (World Bank, 2020) might have impact its air pollution patterns, with topography, elevation, and climate variability (Lemma Gonfa, 1996) playing significant roles. Environmental challenges, including deforestation and climate change, also affect air quality. This study offers a systematic review of air pollution research in Ethiopia, providing a thorough analysis of its health, environmental, and economic impacts, regional variations, and policy suggestions. It addresses both indoor and outdoor air pollution, assessing their wide-ranging effects. Data were gathered through an extensive search of peer-reviewed articles, policies, and guidelines using Google Scholar and reputable sources, following PRISMA guidelines. The review highlights critical sources of air pollution in Ethiopia, including indoor biomass fuel combustion and outdoor emissions from traffic and industries. Indoor air pollution, particularly from traditional biomass fuels like wood and dung, affects rural and peri-urban areas, leading to high levels of particulate matter and carbon monoxide. Outdoor pollution, driven by urbanization, industrial expansion, and vehicle emissions, worsens health issues and environmental damage. The study identifies severe health consequences, such as respiratory infections and cardiovascular diseases, with air pollution contributing to premature deaths and rising healthcare costs. Economic analysis highlights the significant costs related to healthcare, lost productivity, and infrastructure damage. Environmental impacts include harm to plant health, soil degradation, and contributions to climate change. Despite initiatives to improve air quality monitoring and regulation, challenges persist due to outdated policies, limited infrastructure, and insufficient data. The study emphasizes the need for more comprehensive research and regulations to tackle air pollution crisis.

Cognitive Benefits of Reducing Indoor Particulate Matter Exposure During Sleep: New Evidence from a Randomized, Double-blind Crossover Trial.

There is increasing evidence that particulate matter (PM) pollution may adversely impact cognition. Considering that sleep is critical for cognitive health and occupies about one-third of human life, understanding the cognitive effects of indoor PM exposure during sleep and the potential cognitive benefits of reducing such exposure is crucial, yet currently unknown. This randomized, double-blind crossover intervention trial was conducted among 80 college students with real and sham PM filtration in their dormitories. Real-time indoor PM levels and nocturnal sleep parameters were monitored, followed by quantification of serum neurotransmitter metabolites and cognitive assessments in the mornings. We found that PM exposure during sleep, particularly PM1 and PM2.5, affected immediate and delayed memory, executive function, and global cognition. Reducing PM exposure during sleep resulted in improvements in multiple cognitive domains, with a 0.21 (95% CI: 0.05, 0.36) increase in global cognitive z-score, in which increased sleep oxygen saturation (SpO2) and alterations in dopamine metabolism and histidine metabolism played important roles. Notably, even when indoor PM2.5 levels were below the WHO air quality guidelines, further reducing PM exposure could still improve sleep SpO2 and neurotransmitter metabolism. This study provides a promising strategy to mitigate indoor PM-induced cognitive impairment.

Combined Effect of Air Pollution and Genetic Risk on Incident Cardiovascular Diseases.

Whether genetic susceptibility to cardiovascular diseases (CVDs) enhances the vulnerability to adverse cardiovascular outcomes by air pollution is unknown. We assessed the combined effect of air pollution and genetic predispositions on CVD risk. From the UK Biobank cohort, we selected genetically unrelated White British participants without CVD. Levels of ambient particulate matter with a diameter of <2.5 μm (PM2.5) and <10 μm were estimated using land use regression models. An individual's genetic predisposition to CVDs was determined by polygenic risk scores for coronary artery disease, myocardial infarction, stroke, ischemic stroke, heart failure, and atrial fibrillation. We stratified mortality and CVD risk by PM2.5 exposure across high and low genetic risk groups. A total of 249 082 participants (aged 56.9±8.0 years, 46.8% men) were followed for a median of 10.8 years. The combined effect of PM2.5 exposure and the genetic predisposition of CVD demonstrated the highest risk of cardiovascular death in the high genetic risk group with the greatest PM2.5 exposure (adjusted hazard ratios ranging from 1.73 to 2.12 across the polygenic risk score of each CVD). The combination of higher exposure to ambient PM2.5 and high genetic risk was associated with higher incidence of all CVDs, although no significant interactions were observed between genetic risk and PM2.5 exposure on cardiovascular death or CVD events. A combination of greater PM2.5 exposure and higher genetic predisposition to particular CVDs was modestly associated with elevated risks of cardiovascular death and CVDs. Not only alleviating PM2.5 exposure in the general population but also implementing individualized preventive approach for those at high genetic risk might be beneficial.

Abstract 4145877: Association of heat exposure with cardiovascular and all-cause hospitalizations among elderly adults in the United States

Background: Heat exposure is associated with an increase in cardiovascular mortality, particularly among older adults. Climate change has led to an increase in days with hot temperatures. The burden of hospitalizations associated with heat exposure is not well known. Methods: Data on all hospitalizations among Medicare beneficiaries 65 years of age and older in summer months (May through September) for 2016 to 2019 were obtained from Medicare Provider Analysis and Review (MEDPAR) files. Total daily cardiovascular and all-cause hospitalizations in each US county in the contiguous United States (US) were determined and daily county-level maximum heat index levels were obtained from the gridMET dataset. Counties with &lt;100 elderly residents were excluded. The association between daily heat index and hospitalizations was quantified using the distributive lag non-linear framework, with a generalized linear regression model – assuming a quasi-Poisson distribution. The model accounted for the lagged association, for up to 10 days, for daily heat index as well as covariates (ozone, particulate matter, and precipitation levels). Estimates from this model were used to determine the number and fraction of hospitalizations attributable to high temperatures on hot days. Hot days were defined as those with a heat index level in the 90 th percentile based on a county-specific historical period (1979-2015). Results: A total of 2085 counties (out of 3108) were included. The median threshold for hot days was 90.2°F (IQR 84.8°F to 95.5°F) [32.3°C (IQR 29.3°C to 35.3°C)]. Between 2016 and 2019, hot days were associated with 3044.0 (95% CI 2641.5 to 3380.9) or 0.067% (95% CI 0.058% to 0.074%) of all cardiovascular hospitalizations. Hot days were associated with 42132.2 (95% CI 41159.9 to 43082.1) or 0.22% (95% 0.21% to 0.225%) of all hospitalizations among Medicare beneficiaries. Conclusions: Between 2016 and 2019 days with high heat index levels were associated with higher levels of cardiovascular and all-cause hospitalizations among elderly Medicare beneficiaries across the contiguous US. As the number of hot days continues to increase due to climate change, the burden of heat related hospitalizations is likely to continue to increase.

Investigation of size-segregated particulate matter and carbonaceous components in Phnom Penh, Cambodia.

This study investigated the size-segregated carbonaceous components of particulate matter (PM), including ultrafine particles (UFP or PM0.1), across three distinct urban settings in Phnom Penh, Cambodia: an educational site (University of Health Sciences, UHS), an institutional site (Ministry of Environment, MoE), and a residential area near a landfill. A cascade impactor-type sampler equipped with an inertial filter was used to collect size-segregated particles down to UFPs. Carbonaceous species, including organic carbon (OC) and elemental carbon (EC), were analyzed using a thermal/optical carbon analyzer to determine their composition and ratios. The results indicated no significant differences in mass concentration between weekdays and weekends at all sites; however, PM profiles varied across the location. The UHS site displayed higher EC levels in UFP, with concentrations suggesting significant local vehicular emissions, underscored by a lower OC/EC ratio (2.39 ± 1.13) compared to other sites. In contrast, the landfill site exhibited higher OC components in finer particles, suggesting emissions from organic sources such as waste burning and cooking activities, evidenced by higher OC/EC ratios across all particle sizes (e.g., OC/EC ratio in UFP at 3.78 ± 0.98). The MoE site presented a balanced profile with moderate levels of both OC and EC, influenced by its proximity to natural dispersion factors like the Tonle Sap River. Additionally, air mass backward trajectory analysis integrated with hotspot data indicated transboundary influences, particularly from agricultural burning in surrounding provinces, including Vietnam. Therefore, both local and transboundary emissions influenced the PM levels in Phnom Penh city.

Exploring the cooking energy biomass and its impact on women's health and quality of life in rural households: a micro-environmental study from West Bengal in India.

Exposure to household air pollutants has become a significant environmental health concern in developing nations. This study aimed to understand the growing energy consumption within households, particularly for cooking, and its impact on women's health in rural areas. We conducted real-time monitoring of ambient particulate matter (PM2.5) and carbon monoxide (CO) levels in 61 rural kitchens in the Medinipur and Jhargram districts of West Bengal, India. Additionally, we calculated the Standard Living Index (SLI) based on socio-demographic factors from 540 households. Our analyses using ANOVA and chi-square methods revealed significant effects of cooking fuel types and locations on various health indicators among women. Eye irritation was prevalent across all fuel types, followed by shortness of breath (33%), coughing (22%), and dizziness (21%). Alarmingly, nearly half (48%) of children under five consistently accompanied their mothers during cooking, exposing them to health risks. Indoor air pollution, particularly from traditional fuels like fuelwood, cow dung cakes, and leaves, poses a grave threat to families. These fuels emit considerable amounts of PM2.5 and CO, with levels reaching as high as 565µg/m3 and 12.5ppm, respectively, leading to respiratory and cardiovascular complications. Clean cooking fuel users, such as those using LPG, reported improved quality of life scores across physical, psychological, social, and environmental categories. This study highlights the urgent need to transition to cleaner cooking fuels to mitigate adverse health effects on women and children in rural households.

Effects of major air pollutants on cognitive function in middle-aged and elderly adults: Panel data evidence from China Health and Retirement Longitudinal Study.

Although numerous studies have discussed about the impact of air pollution on cognitive function, a consensus has yet to be reached, necessitating further exploration of their relationship. The aim of this study is to reveal the effects of major air pollutants on cognitive function in Chinese middle-aged and older adults, while considering the lagged effects of pollution. Panel data were constructed by integrating the air pollutants concentration (particulate matter diameter ≤1 µm (μm) (PM1), PM2.5, PM10, nitrogen dioxide (NO2), and ozone (O3)) among 28 provinces in China and the personal characteristics from China Health and Retirement Longitudinal Study participants during the period of 2011-2015. To explore the effects of single pollutants and their interactions on cognitive function, panel linear regression using ordinary least squares method was employed, and first-order lag effects (two-year interval) of air pollution were introduced into the models. Our study revealed that, after adjusting for confounding factors, higher levels of particulate matter (PM1, coefficient (Coef.) = -0.093, P = 0.001; PM2.5, Coef. = -0.051, P = 0.001; PM10, Coef. = -0.030, P = 0.001) and NO2 (Coef. = -0.094, P = 0.006) were associated with lower cognitive function scores among the participants. Moreover, the interaction between the five major pollutants exhibited a negative effect on cognitive function(Coef. = -2.89, P = 0.004). PM1, PM2.5, PM10 have detrimental effects on the cognitive function of middle-aged and elderly adults in China, where increasing particle diameter correlates with a less negative impacts, providing theoretical underpinnings for the formulation of environmental protection policies.

Ambient air pollution, urban green space and childhood overweight and obesity: A health impact assessment for Barcelona, Spain

BackgroundThe burden of childhood overweight and obesity attributable to ambient air pollution and a lack of urban green spaces (UGS) remains unknown. This study aimed to estimate the attributable cases of childhood overweight and obesity due to air pollution and insufficient UGS exposure in Barcelona, Spain. MethodsWe applied a quantitative health impact assessment approach. We collected childhood overweight and obesity prevalence levels and exposure data from 69 spatial basic health zones in Barcelona. We estimated particulate matter (PM2.5) and nitrogen dioxide (NO2) levels using land use regression models, normalized difference vegetation index (NDVI) levels using remote sensing and percentage of green area (%GA) using land use. We estimated relative risks, population attributable fractions, and preventable overweight/obesity cases in children under following scenarios: Compliance of World Health Organization (WHO) air quality guidelines (AQGs) for (1) PM2.5 and (2) NO2; achieving (3) city-target NDVI levels and (4) 25% green area (%GA) recommendations. The analyses were stratified by socioeconomic deprivation index (in quintiles). Uncertainty was quantified using Monte Carlos simulations. ResultsCompliance of WHO AQGs could prevent 0.4% [253 (95%CI, −604; 1086)] and 4.2% [3000 (95%CI, 1009; 4943)] of childhood overweight/obesity cases due to excess PM2.5 and NO2 levels in Barcelona, respectively. Compliance of NDVI and %GA targeted levels could prevent 6% [4094 (95%CI, 1698; 6379)] and 10% [6853 (95%CI, 1440; 12779)] of childhood overweight/obesity cases respectively. The preventable burdens of childhood overweight/obesity cases were slightly higher in middle-class socioeconomic areas due to the higher adverse exposure levels at baseline (high air pollution, less UGS). DiscussionCompliance with WHO AQGs and achieving UGS targets can reduce childhood overweight and obesity levels in Barcelona, and potentially in other locations as well. This underscores the need for policies that foster healthier urban environments of high environmental quality in order to protect child health.

Association between temperature and air pollutants with atrial fibrillation presentations to emergency departments.

Understanding the impact of environmental exposures on disease incidence is important for environmental guidelines, health services management, and advising patients. We aimed to assess the relationship between daily mean temperature and common pollutants with atrial fibrillation (AF) presentations to emergency departments (EDs). The study included consecutive adult patients presenting with AF to EDs from 1/1/2014 to 31/12/2020 with linkage to hospital and emergency discharge diagnosis data. A time series quasi-Poisson regression with a distributed lag nonlinear model was fitted to assess the association between AF with mean air temperature and five common pollutants, overall and according to sex and region, with adjustment for season, day of the week, long-term trend, and co-pollutants. In 82 575 AF presentations to EDs during the study period, mean (standard deviations [SD]) (SD) age was 69.6 (SD 14.7) years and 50.7% were female. AF presentations were associated with elevated levels of Particulate Matter (PM) 2.5 (≥57.7 µg/m3) and nitrous dioxide (NO2) (≥16.5 parts per billion), but not mean air temperature or other pollutants (carbon monoxide, sulphur dioxide, or ozone). The attributable fraction of AF presentations relating to above optimal NO2 and PM 2.5 levels was 7.24% and 3.81% resulting in 854 and 450 annual excess AF presentations, respectively. High levels of NO2 and PM 2.5 are associated with increased risk of AF presentations to EDs. These findings have important implications for environmental policies and advice to patients susceptible to AF presentations to EDs, especially in regions with higher baseline levels of PM 2.5 or NO2.

Ambient particulate matter and frequency of outpatient visits for chronic rhinosinusitis in the United States.

Emerging evidence has underscored the harmful effects of air pollution on the upper airway. We investigated the relationship between ambient particulate matter (PM) level and the frequency of outpatient visits for chronic rhinosinusitis (CRS). We conducted an ecological cohort study of US adults enrolled in The Merative MarketScan outpatient database from 2007 to 2020. For each geographical subunit (core-based statistical area [CBSA]), we calculated the annual rate of CRS-related outpatient visits per 1000 well-patient checkup visits (CRS-OV). Using data from the Environmental Protection Agency's Air Quality System, we mapped the rolling statistical average of daily PM2.5 and PM10 over the preceding year onto each CBSA×year combination. We employed multivariable negative binomial regression modeling to estimate the association between PM levels and subsequent CRS-OV. Across 3933 observations (CBSA×year combinations), encompassing ∼4 billion visits, the median CRS-OV was 164 (interquartile range 110-267). The mean PM2.5 level was 8.9µg/m3 (SD 2.6) and the mean PM10 level was 20.2µg/m3 (SD 7.2). Adjusting for patient demographics and respiratory comorbidities, a compounded rise in subsequent CRS-OV was observed with increasing PM levels. Each µg/m3 rise in PM2.5 independently predicted a 10% increase in CRS-OV (adjusted incidence rate ratio [aIRR]) 1.10, 95% confidence interval [CI] 1.08-1.13) and each µg/m3 rise in PM10 independently predicted a 3% increase in CRS-OV (aIRR 1.03, 95% CI 1.02-1.04). Elevated ambient PM2.5 and PM10 levels are associated with a subsequent compounded increase in the frequency of CRS-OV, with PM2.5 predicting a more pronounced rise compared to PM10.

Confidence intervals of difference and ratio between two means of delta-Birnbaum-Saunders distributions

During the dry season, the northern region of Thailand consistently grapples with compromised air quality, notably an excessive level of particulate matter with a diameter of less than 2.5 microns (PM2.5), which poses implications for public health. Wind speed emerges as the primary factor that diminishes the concentration of PM2.5, making the evaluation of wind speed changes crucial in understanding and potentially mitigating the impact of air pollution on public health in the region. The wind speed data contain zero and positive values. This can be estimated through the confidence intervals of the difference and ratio between two means of delta-Birnbaum-Saunders distributions using various methods, including the generalized confidence interval (GCI), bootstrap confidence interval (BCI), and generalized fiducial confidence interval (GFCI). These methods rely on variance stabilizing transformations (VST), the Wilson and Hannig methods. According to the simulation, for small sample sizes, the GCI based on the VST and Hannig was the most effective method in terms of coverage probabilities and average lengths. For medium sample sizes, it was found that the performance of GFCI based on the VST method was superior to other methods. Additionally, when confronted with a large sample size, the BCI based on the VST method becomes relevant and will be introduced. To demonstrate the efficacy of our proposed methods, we applied them to wind speed data gathered from Chiang Mai Airport station in Thailand from January to February in both 2022 and 2023.

Evaluating Indoor Air Quality in Residential Environments: A Study of PM2.5 and CO2 Dynamics Using Low-Cost Sensors

Indoor air quality (IAQ) poses a significant public health concern, and exposures to high levels of fine particulate matter (PM2.5) and carbon dioxide (CO2) could have detrimental health impacts. This study focused on assessing the indoor air pollutants in a residential house located in the town of Mission, Hidalgo County, South Texas, USA. The PM2.5 and CO2 were monitored indoors: the kitchen and the bedroom. This investigation also aimed to elucidate the effects of household activities such as cooking and human occupancy on these pollutants. Low-cost sensors (LCSs) from TSI AirAssure™ were used in this study. They were deployed within the breathing zone at approximately 1.5 m above the ground. Calibration of the low-cost sensors against Federal Equivalent Method (FEM) instruments was undertaken using a multiple linear regression method (MLR) model to improve the data accuracy. The indoor PM2.5 levels were significantly influenced by cooking activities, with the peak PM2.5 concentrations reaching up to 118.45 μg/m3. The CO2 levels in the bedroom increased during the occupant’s sleeping period, reaching as high as 1149.73 ppm. The health risk assessment was assessed through toxicity potential (TP) calculations for the PM2.5 concentrations. TP values of 0.21 and 0.20 were obtained in the kitchen and bedroom, respectively. The TP values were below the health hazard threshold (i.e., TP &lt; 1). These low TP values could be attributed to the use of electric stoves and efficient ventilation systems. This research highlights the effectiveness of low-cost sensors for continuous IAQ monitoring and helps promote better awareness of and necessary interventions for salubrious indoor microenvironments.

Opinion: How will advances in aerosol science inform our understanding of the health impacts of outdoor particulate pollution?

Abstract. Air pollution, characterized by high levels of particulate matter (PM), poses the greatest environmental threat to human health, causing an estimated 7 million deaths annually and accounting for 5 % of the global gross domestic product (GDP). While the health impacts of PM are influenced by the toxicity of its individual chemical constituents, the mortality burden of PM is solely based on its total mass concentration. This is because of a lack of large-scale, high-resolution data on PM chemical composition, needed for epidemiological assessments. Identifying which PM constituents are harmful to health has been the “holy grail” of atmospheric science since the landmark 1993 study on six US cities established a definitive link between PM and mortality. Ever since, atmospheric scientists have focused on understanding aerosol composition, emission sources, and formation pathways, while longitudinal epidemiological studies have required individual-level exposure data, employing land use regression models for the prediction of exposures at fine resolutions. In this opinion article, we argue that the time has come to shift the focus towards incorporating PM chemical composition into epidemiological health assessments, laying the foundation for the development of new regulatory metrics. This shift will enable the creation of targeted guidelines and subsequent regulations, prioritizing mitigation efforts against the most harmful anthropogenic emissions. Central to this shift is the availability of global, long-term, high-resolution data on PM chemical composition that are obtained through field observations and modelling outputs. In the article, we underscore key milestones within aerosol science that have been integral for advancing this foundational shift. Specifically, we examine emerging modelling tools for estimating exposure to individual PM components, present the type of ambient observations needed for model developments, identify key gaps in our fundamental understanding of emissions and their atmospheric transformation, and propose advancing cross-disciplinary collaboration between aerosol scientists and epidemiologists to understand the health impacts of individual PM components. We contend that aerosol science has now reached a pivotal moment in elucidating the differential health impacts of PM components, representing a first step towards their incorporation into air quality guidelines.

A Hazardous Duty: Occupational Health Challenges for Traffic Police at Koshi Province

Abstract Background: Traffic police officers are integral to maintaining urban traffic flow and safety, yet their occupational roles expose them to a variety of health hazards. This study investigates the spectrum of occupational health hazards faced by traffic police officers in Koshi Province. Methods: A cross-sectional study was conducted involving 175 traffic police officers in Koshi Province. Data were collected through structured questionnaires, physical examinations, and environmental assessments. The study evaluated the prevalence of various health issues and their association with identified occupational hazards. Results: Findings reveal high prevalence rates of respiratory ailments (35%), musculoskeletal disorders (28%), stress and anxiety (40%), hearing impairments (15%), and exposure to vehicular pollutants. Environmental assessments indicated significant levels of noise, particulate matter, and exhaust fumes in traffic hotspots. Statistical analysis identified prolonged exposure duration as significant predictors of adverse health outcomes. Conclusion: Traffic police officers in Koshi Province are susceptible to multiple occupational health hazards, necessitating comprehensive intervention strategies include enhancing protective measures, implementing regular health screenings, and establishing mental health support systems. Keywords: Occupational health hazard, traffic police, Koshi Province

Residential wood heat in the US: Results of a survey investigating user behavior and operation of wood heating appliances

Wood is used as a source of primary and secondary heat by millions of people in the US, but many wood stoves emit levels of particulate matter that negatively impact human health and the environment. Modern wood stoves are designed to pass emissions testing required by regulatory bodies and manufacturers may be hindered in their ability to design for the variability of real-world use. User behavior can strongly impact wood heater emissions, and learning about how they are used in real life could inform the future design of cleaner-burning wood heaters. In this study a survey was performed to investigate the habits, needs, and challenges surrounding residential wood heating in the US. Common user characteristics and behaviors are investigated in categories covering heating technology, fuel use and preference, user behavior, and operation. The data collected from 210 completed survey responses can be used to support and refute anecdotal understandings of wood stove use. Results from this study cover wood heater ages and the presence or lack of catalysts. Fuel provenance, type, seasoning, and storage practices are discussed, along with the ways that respondents learned how to use their stoves and their operational practices including reloading, cold start behavior, and use of air controls. The information presented in this paper can be used to inform industry and regulatory groups as to how people use their wood heaters and highlights areas for potential future research.

Impact of metals exposure on lung function and serum club cell secretory protein among schoolchildren: A mixture and mediation analysis

Particulate matter (PM) and its harmful components are significant contributors to respiratory diseases and impaired lung function, especially in children. Club cell secretory protein (CC16) is a maker of lung epithelium or club cell injuries. To date, the relationship between metals related with PM and CC16 and lung function impairment has been overlooked in children. We enrolled 603 schoolchildren exposed to different levels of PM in China. We found per doubling increase, urinary thallium, and iron was associated with a 3.42 % (95 % CI: 0.01, 6.72) and 3.09 % (95 % CI: 0.55, 5.56) decrease of serum CC16, respectively, whereas urinary cadmium was associated with a 4.74 % (95 % CI: 1.29, 8.31) increase of serum CC16. The Bayesian kernel machine regression (BKMR) model confirmed these associations and showed a potential synergistic interaction between thallium and cadmium. Urinary metal mixtures were associated with lower CC16 when they were below the 35th percentile compared with their median. Serum CC16 mediated 11.47 % (95 % CI: 0.06, 45.00) of the association between urinary thallium and FEV1/FVC decline. The inverted U-shaped association with CC16 and the mediation role of CC16 on associations with lung function provide insight into the mechanisms underlying lung injury induced by metals related with PM.

Evolution Characteristics and Typical Pollution Episodes of PM2.5 and O3 Complex Pollution in Bozhou City from 2017 to 2022

In China, atmospheric pollution exhibits a complex pattern, with simultaneous exceedances of fine particulate matter （PM2.5） and ozone （O3） levels becoming evident. To understand the complex pollution characteristics and evolution patterns of PM2.5 and O3 in Bozhou City, various methods such as weather classification, analysis of typical pollution processes, and investigation of precursor sources were employed to explore the pollution and variations of PM2.5 and O3 in Bozhou City from 2017 to 2022 and subsequently analyze their causes and precursor sources. The results indicated that： ① PM2.5-O3 complex pollution in Bozhou City mostly occurred under high-pressure weather conditions, with daytime high temperatures and low humidity promoting the formation of O3 pollution, whereas nighttime high humidity and atmospheric oxidative conditions promoted the generation of secondary components such as nitrates and ammonium salts in PM2.5. ② During the pollution process, PM2.5 in Bozhou City mainly originated from biomass burning, secondary generation, traffic pollution, coal combustion, and dust sources. Volatile organic compounds （VOCs） primarily emerged from plant sources, traffic pollution, oil and gas evaporation, solvent use, fossil fuel combustion, residential emissions, and industrial emissions. Biomass burning and traffic pollution made significant contributions to the pollution process. ③ Analysis of air mass trajectories and regional pollution situations indicated that the overlay of northern and southern air masses, along with local generation, were the main causes of the PM2.5-O3 complex pollution in Bozhou from October 18th to 27th, 2022.

Problem-driven visualization design of health and pollution big data

We present the design of a big data visualization application aimed at investigating the potential relationships between air pollution and perinatal health. We integrated data from singleton pregnancies in Brazil over a seven-year period and records of fine particulate matter (PM2.5) levels. Our methodology combines Design by Immersion and co-design, engaging specialists from various domains in problem-driven visualization design. The interactive visualization allows exploratory queries and comparative analyses based on medical birth certificate data restructured according to estimated conception dates. The collaboration of various domain experts was essential for leveraging complex data for an informed decision-making visualization.

Seasonal anomaly of particulate matter concentration in an equatorial climate: Evaluating the transboundary impact from neighboring provinces on Padang City, Indonesia.

This study investigated the anomalous seasonal variations in particulate matter (PM) concentrations-specifically PM2.5 and PM10-in Padang City, Indonesia, situated within the Equatorial climate zone. A one-year dataset of half-hourly PM measurements from January to December 2023, collected by the Air Quality Monitoring System (AQMS) managed by the Environmental Agency of West Sumatra (DLH), was utilized. Maps of hotspots and air mass backward trajectories were used to identify possible transboundary emissions affecting Padang City. Despite the region experiencing nearly continuous rainfall, significant elevations in PM levels were observed during the typically drier months of August to October. Specifically, PM2.5 levels peaked at 36.57µg/m3 and PM10 at 39.58µg/m3 in October, significantly higher than in other months and indicating a substantial deviation from the typical expectations for equatorial climates. These results suggest that the high PM concentrations are not solely due to local urban emissions or normal seasonal variations but are also significantly influenced by transboundary smoke from peatland fires and agricultural burning in neighboring provinces such as Bengkulu, Riau, Jambi, and South Sumatra. Backward trajectory analysis further confirmed the substantial impact of regional activities on degradation of air quality in Padang City. The study underscores the need for integrated air quality management that includes both local and transboundary pollution sources. Enhanced monitoring, public engagement, and inter-regional collaboration are emphasized as crucial strategies for mitigating the adverse effects of PM pollution in equatorial regions like Padang City.

Estimation of human airway deposition of size-segregated particulate and their health impact in monsoon and post-monsoon season in semi-urban area of northern India

Numerous studies have shown the negative association between Particulate Matter (PM) exposure and health impact, understanding this risks associated with PM exposure for generating appropriate risk-control strategies, an accurate evaluation of PM concentration and respiratory deposition is necessary. So, the present study aims to describe the temporal and diurnal variation of Particulate Matter and Black Carbon concentrations, as well as their health risks. Real-time monitoring of PM and BC was conducted near a national highway (NH-19) in the semi-urban area. Our findings indicated that the washout effect played its role in reducing the PM level in monsoon season while meteorological parameters, local anthropogenic activities, and stubble-burning influenced the high PM concentration in the post-monsoon season. The current study also estimates the particle deposition in the human respiratory tract using Multiple Path Dosimetry Model (MPPD) for understanding the health effects of particle inhalation. The results revealed that different seasons exhibit different deposition patterns. For example, during the monsoon season, the trend was PM10>PM2.5>PM1.0 while in post-monsoon season PM2.5 >PM10 > PM1.0 respectively. The findings indicate that small particles easily deposited deeper into the lungs have a significant impact on various age groups, particularly children, who are the most affected. Furthermore, the health risks of PM and BC exceeded the safer limit (HQ = 1) and ELCR≥10−6, suggesting prolonged inhalation exposure to particulate could lead to cancer. The present study will give an insight into designing interventions and policies to control PM pollution in smaller cities, where a significant portion of the population resides.