Particulate Matter Pollution Levels Research Articles

Modulating phyllosphere microbiome structure and function in Loropetalum chinense and Osmanthus fragrans: The impact of foliar dust and heavy metals

Trees can effectively capture airborne particles and improve air quality. However, the specific response of phyllosphere microbiome (PMo) in different plant species to particulate matter (PM) and the heavy metals it contains are not yet fully understood. In this study, we investigated the impact of PM on the diversity and function of PMo in Loropetalum chinense and Osmanthus fragrans trees grown in industrial and clean zones with varying levels of PM pollution. Our findings revealed that leaf dust had a significant negative effect on microbial richness, with O. fragrans exhibiting higher microbial diversity than L. chinense. The dominant phylum of phyllosphere bacteria in all samples was Proteobacteria, and the dominant genera were Stenotrophomonas and Delftia. The relative abundance of these genera varied significantly among plant species and regions. Our results showed that PM had a significant impact on the community composition of PMo, with the presence of heavy metals exerting a greater effect than particle size. Moreover, the foliar microbial community of plants grown in industrial zones exhibited significantly higher metabolic functions related to stress resistance and disease resistance compared to plants in control zones. These findings highlight the structural and functional responses of PMo to PM and indicate their potential for enhancing plant adaptation to environmental stress.

The Impact of Health Status and Experienced Disutility on Air Quality Valuation

This paper examines the impact of health status, and of experienced disutility caused by air pollution, on individuals' preferences regarding the health risk reductions resulting from air quality improvement. We investigate if changes in the level of experienced disutility due to air pollution mediate the relationship between individuals' respiratory health status and their preferences regarding health risk reductions. For this purpose, we conducted a choice experiment study among inhabitants of four big Polish cities that have varying levels of particulate matter pollution. We used the modified Medical Research Council breathlessness scale, verified in clinical trials, to obtain information about respondents’ health status, except for usually applied health status measures in stated preference surveys. We do not find any direct impact of health status (apart from smoking) on willingness to pay for air quality improvement. Our results indicate, however, that individuals who self-reported a respiratory diagnosis, as well as those who scored high on the breathlessness scale, are more likely to display a latent trait indicating experienced disutility due to air pollution, and that those who experience this disutility are, in general, more in favour of air quality improvement programmes.

A Community-Based Sensor Network for Monitoring the Air Quality in Urban Romania

Air quality, especially particulate matter pollution levels in urban areas, is an essential academic and social topic due to its association with health issues and climate change. In Romania, increasing awareness of urban communities and the availability of low-cost sensors has led to the development of an independent monitoring network currently distributed in over 194 cities and towns. The uRADMonitor® network consists of 630 sensors measuring PM10 and PM2.5 concentration levels. The spatial distribution of the sensors complements the national air quality network with sensors in residential areas, intense traffic zones, and industrial areas. The data are available through a user-friendly web-based platform from uRADMonitor®. Based on data collected in 2021, we present an analysis of PM10 pollution levels in Romania’s five most populated urban areas by employing five annual statistical indicators recommended by the European Environmental Agency. For the case of Timișoara, we also compare the data measured by independent sensors with those from the national monitoring network. The results highlight the usefulness of our community-based network as it complements the national one.

PO-05-186 LEVERAGING A NATURAL EXPERIMENT TO DETERMINE THE EFFECT OF AIR POLLUTION ON VENTRICULAR ARRHYTHMIAS AND PHYSICAL ACTIVITY: THE 2020 U.S. WILDFIRES

Particulate matter (PM) air pollution is associated with atherosclerotic cardiovascular disease. While the biological processes that link PM exposure to atherosclerotic disease may also trigger arrhythmias, there are limited data on the association of PM with ventricular arrhythmias. The high levels of PM pollution as a consequence of the 2020 U.S. wildfires provide a unique opportunity to explore the effects of air pollution on cardiac arrhythmias, physical activity, and heart failure markers using device remote monitoring data. To evaluate the association of PM exposure to ventricular arrhythmias, physical activity, and markers of heart failure. We performed a retrospective cohort study using the CERTITUDE database of patients with Biotronik CIEDs. We included patients with at least one remote data transmission on or after 1/1/2020. The primary predictors were Air Quality Index (AQI), PM < 10 μm in diameter (PM10), and PM < 2.5 μm in diameter (PM2.5). We evaluated the predictors as continuous and binary variables for values ≧ the 90th percentile for the 2020 calendar year. We determined day-level air pollutant levels using US EPA data cross-linked to patients’ Zip codes as a proxy for patient location, and we examined the outcomes of interest listed in the Table. We evaluated the association of air pollution to the outcomes of interest with (1) a case-crossover analysis using a conditional logistic regression model followed by (2) a time-varying exposure analysis using an Andersen-Gill model and day level air-pollutant levels as a time-varying exposure. The study cohort included 28349 patients (32% female, age 72.8±11.9), of whom 1822 (6.4%) had loop recorders, 17448 (61.6%) had pacemakers, and 9079 (32%) had defibrillators. In the case-crossover analysis, AQI and PM2.5 demonstrated non-significant trends toward higher ATP and shocks (Table). AQI and PM2.5 had significant but non-meaningful associations with change in heart rate, and PM2.5 with physical activity and thoracic impedance. The time-varying exposure analysis demonstrated significant but non-meaningful associations (ORs 0.99-1). In contrast to prior literature on ambient air pollution, these natural experiment analyses did not demonstrate acute or sub-acute association between AQI, PM2.5, or PM10 with ventricular arrhythmias, physical activity, or heart failure markers in CIED patients. Mediators of these findings merit further investigation to clarify causal and non-causal mechanisms.

Wood burning stoves, participatory sensing, and ‘cold, stark data’

Wood burning stoves triple levels of particulate matter pollution inside the home. Using an exploratory research design informed by coping theory, this study illustrates how sensors revealing this reality fail to influence the perceptions and behaviours of stove users. After four weeks of participatory sensing, where laypersons used sensors to identify indoor air quality during stove use, the results show how monitoring technology pulls wider preconceptions into the data interpretation process. When faced with numerical data perceived as ambiguous, users draw on preconceptions that frame stoves in a positive light and make comparisons with other indoor emission sources believed to be harmless. This influences the data interpretation process and minimises the threat indicated by sensor technology. It is recommended that participatory sensing research give greater consideration to the role of data presentation in influencing user behaviour, while being more attentive to how socio-cultural knowledges enter the process of interpretation.

NeuroSmog: Determining the Impact of Air Pollution on the Developing Brain: Project Protocol.

Exposure to airborne particulate matter (PM) may affect neurodevelopmental outcomes in children. The mechanisms underlying these relationships are not currently known. We aim to assess whether PM affects the developing brains of schoolchildren in Poland, a country characterized by high levels of PM pollution. Children aged from 10 to 13 years (n = 800) are recruited to participate in this case–control study. Cases (children with attention deficit hyperactivity disorder (ADHD)) are being recruited by field psychologists. Population-based controls are being sampled from schools. The study area comprises 18 towns in southern Poland characterized by wide-ranging levels of PM. Comprehensive psychological assessments are conducted to assess cognitive and social functioning. Participants undergo structural, diffusion-weighted, task, and resting-state magnetic resonance imaging (MRI). PM concentrations are estimated using land use regression models, incorporating information from air monitoring networks, dispersion models, and characteristics of roads and other land cover types. The estimated concentrations will be assigned to the prenatal and postnatal residential and preschool/school addresses of the study participants. We will assess whether long-term exposure to PM affects brain function, structure, and connectivity in healthy children and in those diagnosed with ADHD. This study will provide novel, in-depth understanding of the neurodevelopmental effects of PM pollution.

Exposure to PM2.5 and PM10 and COVID-19 infection rates and mortality: A one-year observational study in Poland

BackgroundAtmospheric contamination, especially particulate matter (PM), can be associated viral infections connected with respiratory failure. Literature data indicates that intensity of SARS-CoV-2 infections worldwide can be associated with PM pollution levels. ObjectivesThe aim of the study was to examine the relationship between atmospheric contamination, measured as PM2.5 and PM10 levels, and the number of COVID-19 cases and related deaths in Poland in a one-year observation study. MethodsNumber and geographical distribution of COVID-19 incidents and related deaths, as well as PM2.5 and PM10 exposure levels in Poland were obtained from publicly accessible databases. Average monthly values of these parameters for individual provinces were calculated. Multiple regression analysis was performed for the period between March 2020 and February 2021, taking into account average monthly exposure to PM2.5 and PM10, monthly COVID-19 incidence and mortality rates per 100,000 inhabitants and the population density across Polish provinces. ResultsOnly December 2020 the number of new infections was significantly related to the three analyzed factors: PM2.5, population density and the number of laboratory COVID-19 tests (R2 = 0.882). For COVID-19 mortality, a model with all three significant factors: PM10, population density and number of tests was obtained as significant only in November 2020 (R2 = 0.468). ConclusionThe distribution of COVID-19 incidents across Poland was independent from annual levels of particulate matter concentration in provinces. Exposure to PM2.5 and PM10 was associated with COVID-19 incidence and mortality in different provinces only in certain months. Other cofactors such as population density and the number of performed COVID-19 tests also corresponded with both COVID-19-related infections and deaths only in certain months. Particulate matter should not be treated as the sole determinant of the spread and severity of the COVID-19 pandemic but its importance in the incidence of infectious diseases should not be forgotten.

Gray cityscape caused by particulate matter pollution hampers human stress recovery

Air pollution has caused degraded visibility and gray cityscape in many developing countries. Though this visual change affects daily life from various aspects, there still lacks evidence on how it influences human psychological and physiological wellbeing. Based on a psychophysiological experiment, this study found that degraded cityscape caused by particulate matter (PM) pollution impeded human stress recovery and caused mental discomfort. We exposed 96 college student participants to fixed-scene images with six varied PM pollution levels during a 3-min post-stress recovery. We measured participants’ self-reported and physiological stress before the stressor, after the stressor and after the recovery. Stress recovery percentages among groups were compared. Both self-reported and physiological stress measurements showed that participants viewing clean cityscape photos recovered faster and 30–60% better than those viewing low-visibility cityscape photos. The final stress recovery percentages after 3-min recovery varied among indicators but generally followed a decreasing trend as the visibility impaired. The results convince a potentially indirect pathway through which the gray cityscape reduces well-being by hampering stress recovery. We discuss underlying mechanisms of the recovery-hampering effect of gray cityscape and call for more attention to this mild psychophysiological outcome.

Effects of short-term exposure to particulate matter air pollution on cognitive performance

This paper assesses the effect of short-term exposure to particulate matter (PM) air pollution on human cognitive performance via a double cross over experimental design. Two distinct experiments were performed, both of which exposed subjects to low and high concentrations of PM. Firstly, subjects completed a series of cognitive tests after being exposed to low ambient indoor PM concentrations and elevated PM concentrations generated via candle burning, which is a well-known source of PM. Secondly, a different cohort underwent cognitive tests after being exposed to low ambient indoor PM concentrations and elevated ambient outdoor PM concentrations via commuting on or next to roads. Three tests were used to assess cognitive performance: Mini-Mental State Examination (MMSE), the Stroop Color and Word test, and Ruff 2 & 7 test. The results from the MMSE test showed a statistically robust decline in cognitive function after exposure to both the candle burning and outdoor commuting compared to ambient indoor conditions. The similarity in the results between the two experiments suggests that PM exposure is the cause of the short-term cognitive decline observed in both. The outdoor commuting experiment also showed a statistically significant short-term cognitive decline in automatic detection speed from the Ruff 2 and 7 selective attention test. The other cognitive tests, for both the candle and commuting experiments, showed no statistically significant difference between the high and low PM exposure conditions. The findings from this study are potentially far reaching; they suggest that elevated PM pollution levels significantly affect short term cognition. This implies average human cognitive ability will vary from city to city and country to country as a function of PM air pollution exposure.

China’s clean-air efforts could hike emissions elsewhere

Regional clean-air efforts in China’s national capital region could boost air pollution in other parts of the country, according to a new study (Sci. Adv. 2019, DOI: 10.1126/sciadv.eaav4707). An international team of researchers led by Delin Fang of Beijing Normal University used computer models to examine the effects of policies to reduce particulate matter with diameter of 2.5 µm or less in the cities of Beijing and Tianjin and in Hebei Province. The three areas, considered collectively to be the national capital region, often suffer from extremely high levels of particulate matter pollution. The researchers found that emission control policies in the region would shift polluting industries and power generation out of the area and into other parts of China, especially neighboring provinces. This, in turn, would raise particulate matter pollution levels in those provinces. Wind could carry emissions from these areas to the national capital region, canceling out part

Particulate matter pollution in Chinese cities: Areal-temporal variations and their relationships with meteorological conditions (2015–2017)

As the second largest economy in the world, China experiences severe particulate matter (PM) pollution in many of its cities. Meteorological factors are critical in determining both areal and temporal variations in PM pollution levels; understanding these factors and their interactions is critical for accurate forecasting, comprehensive analysis, and effective reduction of this pollution. This study analyzed areal and temporal variations in concentrations of PM2.5, PM10, and PMcoarse (PM10 - PM2.5) and PM2.5 to PM10 ratios (PM2.5/PM10) and their relationships with meteorological conditions in 366 Chinese cities from January 1, 2015 to December 31, 2017. On the national scale, PM2.5 and PM10 decreased from 48 to 42 μg m−³ and from 88 to 84 μg m−³, respectively, and the annual mean concentrations were 45 μg m−³ (PM2.5) and 84 μg m−³ (PM10) during the time period (2015–2017). In most regions, largest PM concentrations occurred in winter. However, in northern China, in spring PMcoarse concentrations were highest due to dust. The PM2.5/PM10 ratio was higher in southern than in northern China. There were large regional disparities in PM diurnal variations. Generally, PM concentrations were negatively correlated with precipitation, relative humidity, air temperature, and wind speed, but were positively correlated with surface pressure. The sunshine duration showed negative and positive impacts on PM in northern and southern cities, respectively. Meteorological factors impacted particulates of different size differently in different regions and over different periods of time.

Source-Specific Health Risk Analysis on Particulate Trace Elements: Coal Combustion and Traffic Emission As Major Contributors in Wintertime Beijing.

Source apportionment studies of particulate matter (PM) link chemical composition to emission sources, while health risk analyses link health outcomes and chemical composition. There are limited studies to link emission sources and health risks from ambient measurements. We show such an attempt for particulate trace elements. Elements in PM2.5 were measured in wintertime Beijing, and the total concentrations of 14 trace elements were 1.3-7.3 times higher during severe pollution days than during low pollution days. Fe, Zn, and Pb were the most abundant elements independent of the PM pollution levels. Chemical fractionation shows that Pb, Mn, Cd, As, Sr, Co, V, Cu, and Ni were present mainly in the bioavailable fraction. Positive matrix factorization was used to resolve the sources of particulate trace elements into dust, oil combustion, coal combustion, and traffic-related emissions. Traffic-related emission contributed 65% of total mass of the measured elements during low pollution days. However, coal combustion dominated (58%) during severe pollution days. By combining element-specific health risk analyses and source apportionment results, we conclude that traffic-related emission dominates the health risks by particulate trace elements during low pollution days, while coal combustion becomes equally or even more important during moderate and severe pollution days.

Transparent Nanofibrous Mesh Self-Assembled from Molecular LEGOs for High Efficiency Air Filtration with New Functionalities.

Alarming levels of particulate matter pollution in air pose a serious health threat in several countries, therefore intriguing a strong need for an economic and a viable technology of air filtration. Current air purification technology is rather expensive with certain types even having the risk of emitting hazardous by-products. The authors have developed a multifunctional air filter inspired from the nasal hairs possessing an ability to specifically trap/exhale the foreign particles and allergens while still letting the air flow. This design is achieved by introducing different functionalities at different dimensional scale employing a bottom-up approach starting with an organic molecule which is further self-organized to form nanoparticles and ultimately to a nanofibrous mesh. While the molecular building block inherently possesses the property of shielding Ultraviolet (UV) rays, the nanofibrous mesh built up from it aids in trapping the particulate matter while maintaining good air flow. By controlling the concentration of the organic molecule, the formation of fibers has been enabled in the nanoscale regime to obtain high particle-capture possibilities. The self-assembled nanofibrous filter thus designed has achieved a high filtration efficiency of ≈90% for the PM 2.5 particle in congruence with the ability to block the harmful UV radiations.

Ongoing progress in cleaning China′s air: A novel outlook into pollution

Over the past 30 years, particulate matter (PM) air pollution has progressively worsened in many of China's urban and suburban areas. This review provides a current picture of the air pollution in China with an emphasis on the history of PM pollution, policies and reduction goals, recent improvements, and known adverse health effects of PM exposure. Several studies have provided the analyses of current PM pollution levels in cities across China using satellite data and air-monitoring stations. These analyses are consistent with the Chinese Ministry of Environmental Protection (MEP) 2015 air pollution report, which concluded that only 8 of 74 (10.8%) cities met the Chinese standards for safe annual average PM 2.5 exposure (35 μg/m 3 ). Even fewer cities met the World Health Organization PM 2.5 guideline of 10 μg/m 3 . The Government of China has acknowledged the public health threat of PM pollution and enacted higher standards and goals through the 12 th five-year plan (FYP) (2010), National Ambient Air Quality Standard (2012), the Air Pollution Prevention and Control Action Plan (2013), and the 13 th FYP (2016). A comparative analysis between 2010 and 2015 satellite data shows that PM pollution decreased by around 17% during this period. This improvement is corroborated by the MEP's report on the State of the Environment in 2014 and the global burden of disease report in 2013. Despite these changes, PM pollution remains a substantial public health challenge. In 2010, an estimated 1.235 million deaths in China were attributed to PM air pollution. Long-term exposure to PM pollution increases the rates of cardiovascular, metabolic, and respiratory mortality. In particular, PM exposure increases the morbidity of respiratory illnesses such as chronic obstructive pulmonary disease (COPD), asthma, and lower respiratory infections (LRIs). Elevated levels of PM have been found to increase the incidence of all of the top five causes of death in 2012: Ischemic heart disease, stroke, COPD, LRI, and lung cancer. In addition, higher PM pollution decreases average birth weight, raises incidence of preterm birth, and increases the prevalence of Type II diabetes mellitus across the population. With the knowledge of these serious health consequences, China must enact greater measures to reduce dangerous PM levels.

Monitoring and analysis of PM&lt;SUB align="right"&gt;10 concentration at Delhi Metro construction sites

Among all critical air pollutants, particulate matter pollution (PM10) is being awarded greater significance over the past decade. Along with vehicular traffic and meteorological phenomenon, construction works are the major source for release of PM10 in the atmosphere. It is a major source for acute, chronic and respiratory health problems. It produces short term as well as long term health problems in day-to-day lifestyle. This study aims to collect real time particulate matter data from metro construction sites to understand the gravity of the particulate matter pollution due to metro construction works. EPAM HAZ 5000 dust sampler is used to conduct the field studies and record the particulate matter (PM10) levels at Badli, Mayapuri and Najafhgarh metro construction sites of Delhi, India. The results report alarmingly high levels of particulate matter pollution, i.e., 245 ppm (during peak hours), 222 ppm (during peak hours) at Najafgarh and Mayapuri metro construction sites respectively, with time weighted average of PM10 concentration exceeding the national ambient air quality standards (24 hr) of 100 µg/m3.

Concentrations, sources and exposure risks associated with particulate matter in the Middle East Area—a review

Rapid economic expansion, industrialization, urbanisation and construction in the Middle East Area (MEA) have led to an increase in the levels of air pollution, resulting in serious effects on human health. For the first time, this article provides a comprehensive synthesis of the currently available published information which deals with atmospheric particulate matter (PM) in MEA. The focus of the article remains on the PM sources, monitoring, health impacts and source apportionment. The key objectives are to identify the levels of PM pollution and the associated exposure risks, to highlight research gaps and to discuss future research directions. The limited number of monitoring studies available for MEA indicates that dust storms augmented by the rapid increase in urban population are the key reasons for the high PM concentration levels. The findings of reviewed monitoring studies suggest that the levels of both annual mean PM10 (20 μg/m3) and PM2.5 (10 μg/m3) concentrations exceed the World Health Organization (WHO) guidelines during most of the non-dust storm episodes, and as expected, the PM pollution levels become even higher during dust storm episodes. For example, 24-h mean PM10 concentrations of over 1,000 μg/m3 were noted during a severe dust storm episode in Kuwait. The findings of the epidemiological and toxicological studies in MEA have shown that dust storm events have a significant impact on respiratory admissions and the adverse health effects of PM are particularly in the form of asthma and respiratory and cardiovascular diseases. It is concluded that PM pollution in MEA is a significant problem and quantification of PM emissions and the design of control measures to abate their impacts on public health are of primary importance. Besides, there is a need for more systematic PM data collection for source apportionment and assessment of PM levels that would enable air pollution-related health impact assessments of MEA. Furthermore, this review highlights that the release of airborne PM from major building activities such as building construction is largely unknown and emission inventories for different situations are needed.