Ambient Concentrations Of PM2 Research Articles

Air quality and wheeze symptoms in a rural children's cohort near a drying saline lake

BackgroundIn California, climate change and competing water demands are intensifying the desiccation of the Salton Sea, a large land-locked “sea” situated near the southeastern rural US-Mexico border region known as the Imperial Valley. MethodsTo examine the possible effects of living near a saline lake on children's respiratory health, we analyzed the relationship between respiratory health symptoms and ambient PM concentrations among a predominantly Latino/Hispanic cohort of 722 school age children. Guardians completed a survey of their child's wheeze and respiratory health symptoms over the past 12 months, adapted from the International Study of Asthma and Allergies in Childhood (ISAAC). Exposure to dust storm hours (hourly concentrations >150 μg/m3 for PM10) was estimated using a network of regulatory monitors. ResultsBetween 2017 and 2019, children were exposed to 98 to 395 dust event hours annually. We observed disparate effects for dust events and wheeze among children living near the Salton Sea. Every additional 100 dust storm hours per year among children living near the Sea (<11 km) was associated with a 9.5 percentage point increase in wheeze (95% CI: 3.5, 15.4), a 4.6 percentage point increase in bronchitic symptoms (95% CI: 0.18, 10.2) and a 6.7 percentage point increase in sleep disturbance due to wheeze (95% CI: 0.96, 12.4). Similarly, increases in PM10 were also associated with greater reported wheeze and bronchitic symptoms among those living near the Sea, compared to children living ≥11 km from the Sea. There was no association of dust storms or PM10 with wheeze or bronchitic symptoms among the children residing farther from the Sea. ConclusionWe observed stronger adverse impacts of PM10 and dust events on respiratory health among those living closer to the drying Salton Sea, compared to children living farther away. In this community of predominantly low-income residents of color, these impacts raise environmental justice concerns about the effects of the drying Salton Sea on public health.

Impact of Warehouse Expansion on Ambient PM2.5 and Elemental Carbon Levels in Southern California's Disadvantaged Communities: A Two‐Decade Analysis

AbstractOver the past two decades, the surge in warehouse construction near seaports and in economically lower‐cost land areas has intensified product transportation and e‐commerce activities, particularly affecting air quality and health in nearby socially disadvantaged communities. This study, spanning from 2000 to 2019 in Southern California, investigated the relationship between ambient concentrations of PM2.5 and elemental carbon (EC) and the proliferation of warehouses. Utilizing satellite‐driven estimates of annual mean ambient pollution levels at the ZIP code level and linear mixed effect models, positive associations were found between warehouse characteristics such as rentable building area (RBA), number of loading docks (LD), and parking spaces (PS), and increases in PM2.5 and EC concentrations. After adjusting for demographic covariates, an Interquartile Range increase of the RBA, LD, and PS were associated with a 0.16 μg/m³ (95% CI = [0.13, 0.19], p &lt; 0.001), 0.10 μg/m³ (95% CI = [0.08, 0.12], p &lt; 0.001), and 0.21 μg/m³ (95% CI = [0.18, 0.24], p &lt; 0.001) increase in PM2.5, respectively. For EC concentrations, an IQR increase of RBA, LD, and PS were each associated with a 0.021 μg/m³ (95% CI = [0.019, 0.024], p &lt; 0.001), 0.014 μg/m³ (95% CI = [0.012, 0.015], p &lt; 0.001), and 0.021 μg/m³ (95% CI = [0.019, 0.024], p &lt; 0.001) increase. The study also highlighted that disadvantaged populations, including racial/ethnic minorities, individuals with lower education levels, and lower‐income earners, were disproportionately affected by higher pollution levels.

Tradeoff between air pollution and economic benefits in migration dynamics: Evidence from China

This paper investigates how environmental amenity and economic benefits are balanced in migration dynamics from the individual perspective. We construct a structural model based on the dataset that combines PM2.5 concentration data from NASA and migration information from the China Migration Dynamic Survey (CMDS). Thermal inversion is used as a source of exogenous shock in air pollution to address the omitted variable bias. The results indicate that if the ambient concentration of PM2.5 at destinations increases 1 μg/m3, the probability of migration at the individual level will decrease by 0.90 %. A battery of robustness checks is implemented, including different approaches to measuring migration decision, using imputed wage instead of disposable income, using different IV and proxy variable. Heterogeneity analysis reveals that the deterrence effect of air pollution is more pronounced for the following groups: migrants who are male, move from a rural residence, or to a coastal destination, belong to working-age population, engage in a tertiary industry, have a postgraduate-level education, and support two or more elders.

Source Identification Using Principal Component Analysis and Health Risk Assessment of Heavy Metals Contamination in PM2.5 Near an Industrial Area in Thailand

AbstractIndustrialization has led to a surge in air pollution-related problems, as particulate matter (PM) containing heavy metals poses significant health risks. Understanding airborne particle chemistry, particularly the presence of heavy metals, is vital for effective air quality management and health interventions. This study analysed heavy metal levels in PM2.5 across various sites near an industrial zone in Thailand, including areas near main roads, the industrial zone, as well as indoor and outdoor areas of childcare centres. The concentrations of ambient PM2.5 were found to exceed national standards and acceptable limits during the cool dry season, particularly in the industrial zone (46.4 µg/m3), followed by areas near main roads (41.0 µg/m3) and childcare centres (31.6 µg/m3). The impact of the indoor–outdoor relationship on PM2.5 concentration within childcare centres varied. During the cool dry season, Aluminium had the highest concentration, while lead (Pb) across all sites raised environmental concerns. Remarkably, indoor childcare centres showed higher Pb levels than industrial zones and areas near the main road. Principal Component Analysis revealed the distinct factors linked to specific metals, implying contributions from industrial and transportation sources. Lead isotopic analysis indicated potential associations between lead sources and industries like smelting and refining. During the cool dry season, non-carcinogenic risks were concerning (HI &gt; 1), especially near roads and industrial areas. Vulnerabilities were also observed in students and teachers within indoor childcare centres. This study underscores the importance of monitoring and reducing heavy metal pollution in PM2.5, especially in childcare centres near industrial zones, to preserve public health and regional air quality.

Ambient PM2.5 components might exacerbate bone loss among middle-aged and elderly women: evidence from a population-based cross-sectional study.

Previous studies have primarily focused on the links between fine particulate matter (PM2.5) and bone health among the general population instead of PM2.5 components and the specific population. We aimed to investigate the associations between PM2.5 components and bone health among middle-aged and elderly women. A total of 748 middle-aged and elderly women were randomly sampled from 32 streets/villages in Hubei Province. The concentrations of ambient PM2.5 and its components were extracted across various residential areas from the Tracking Air Pollution in China (TAP) dataset. Bone mineral density measurements were obtained from dual-energy X-ray absorptiometry scans of study participants. Multivariable logistic and linear models were employed to assess the relationship between PM2.5 and its components and bone loss. Per interquartile range (IQR) increase in nitrate (NO3-) and ammonium (NH4+) concentrations were associated with 1.65 [95% confidence intervals (CI): 1.13, 2.30] and 1.77 (95% CI: 1.26, 2.49) times higher odds of osteoporosis, respectively. Long-term exposure to sulfate (SO42-), NO3-, and NH4+ was negatively associated with T-scores and bone mineral density in L1-L4 lumbar vertebrae. In addition, the elderly, women who have experienced menarche after the age of 14, and postmenopausal women were more susceptible to the water-soluble inorganic salts of PM2.5. The study emphasizes the need for comprehensive policies addressing air quality, with a specific focus on vulnerable populations such as middle-aged and elderly women. Public health interventions aimed at reducing ambient PM2.5 concentrations and minimizing exposure to its harmful components are crucial in mitigating the adverse impact on skeletal health and improving the overall well-being of communities.

Short-term exposure to air pollution on peripheral white blood cells and inflammation biomarkers: a cross-sectional study on rural residents

Effects of short-term exposure to ambient air pollution on systemic immunological and inflammatory biomarkers in rural population have not been adequately characterized. From May to July 2021, 5816 participants in rural villages of northern Henan Province, China, participated in this cross-sectional study. Blood biomarkers of systemic inflammation were determined including peripheral white blood cells (WBC), eosinophils (EOS), basophils (BAS), monocytes (MON), lymphocytes (LYM), neutrophils (NEU), neutrophil-lymphocyte ratio (NLR), and serum high-sensitivity C-reactive protein (hs-CRP). The concentrations of ambient fine particulate matter (PM2.5), PM10, nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were assessed up to 7 days prior to the blood draw. A generalized linear model was used to analyze the associations between air pollution exposure and the above-mentioned blood biomarkers. Significantly positive associations were revealed between PM2.5, CO and WBC; CO, O3 and LYM; PM2.5, PM10, SO2, CO and NEU; PM2.5, PM10, SO2, CO and NLR; PM2.5, PM10, SO2, NO2, CO, O3 and hs-CRP. Meanwhile, negative associations were found between SO2 and WBC; PM2.5, PM10, NO2, CO, or O3 and EOS; PM2.5, SO2, or CO and BAS; SO2, NO2 or O3 and MON; PM2.5, PM10, SO2, or NO2 and LYM. Moreover, men, individuals with normal body mass index (BMI), current smokers, and those older than 60 years were found vulnerable to air pollution effects. Taken together, short-term exposure to air pollution was associated with systemic inflammatory responses, providing insight into the potential mechanisms for air pollution-induced detrimental systemic effects in rural residents.

Air pollution, greenspace exposure and risk of Parkinson's disease: a prospective study of 441,462 participants.

The current understandings of the relationship between air pollution (AP), greenspace exposure and Parkinson's Disease (PD) remain inconclusive. We engaged 441,462 participants from the UK Biobank who were not diagnosed with PD. Utilizing Cox proportional hazard regression model, relationships between AP [nitrogen dioxide (NO2), and nitrogen oxides (NOX), particulate matter < 2.5μm in aerodynamic diameter(PM2.5), coarse particulate matter between 2.5μm and 10μm in aerodynamic diameter(PM2.5-10), particulate matter < 10μm in aerodynamic diameter(PM10)], greenspace exposure, and PD risk were determined independently. Our analyses comprised three models, adjusted for covariates, and affirmed through six sensitivity analyses to bolster the robustness of our findings. Moreover, mediation analysis was deployed to discern the mediating effect of AP between greenspaces and PD. During a median follow-up of 12.23years (5,574,293 person-years), there were 3,293 PD events. Each interquartile (IQR) increment in NO2 and PM10 concentrations were associated with 10% and 8% increase in PD onset risk, while the increases in NOX, PM2.5 and PM2.5-10 were not associated with PD risk. Additionally, greenspace may safeguard by reducing NO2 and PM10 levels, with the effect mediated by NO2 and PM10 in greenspace-PD relationship. Our findings indicate that an IQR increase in ambient NO2 and PM10 concentrations was associated with risk of PD development, while other pollutants (NOX, PM2.5 and PM2.5-10) were not associated with PD risk. Firstly, we find that augmented exposure to greenspace was associated with the lower PD risk by reducing NO2 and PM10 levels.

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: A nationwide test-negative case-control study in the Netherlands

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modeled ambient concentrations of PM10, PM2.5, NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017–2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5, NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health.

Exposure to ambient air pollution and cognitive function: an analysis of the English Longitudinal Study of Ageing cohort

BackgroundAn increasing number of studies suggest adverse effects of exposure to ambient air pollution on cognitive function, but the evidence is still limited. We investigated the associations between long-term exposure to air pollutants and cognitive function in the English Longitudinal Study of Ageing (ELSA) cohort of older adults.MethodsOur sample included 8,883 individuals from ELSA, based on a nationally representative study of people aged ≥ 50 years, followed-up from 2002 until 2017. Exposure to air pollutants was modelled by the CMAQ-urban dispersion model and assigned to the participants’ residential postcodes. Cognitive test scores of memory and executive function were collected biennially. The associations between these cognitive measures and exposure to ambient concentrations of NO2, PM10, PM2.5 and ozone were investigated using mixed-effects models adjusted for time-varying age, physical activity and smoking status, as well as baseline gender and level of education.ResultsIncreasing long-term exposure per interquartile range (IQR) of NO2 (IQR: 13.05 μg/m3), PM10 (IQR: 3.35 μg/m3) and PM2.5 (IQR: 2.7 μg/m3) were associated with decreases in test scores of composite memory by -0.10 (95% confidence interval [CI]: -0.14, -0.07), -0.02 [-0.04, -0.01] and -0.08 [-0.11, -0.05], respectively. The same increases in NO2, PM10 and PM2.5 were associated with decreases in executive function score of -0.31 [-0.38, -0.23], -0.05 [-0.08, -0.02] and -0.16 [-0.22, -0.10], respectively. The association with ozone was inverse across both tests. Similar results were reported for the London-dwelling sub-sample of participants.ConclusionsThe present study was based on a long follow-up with several repeated measurements per cohort participant and long-term air pollution exposure assessment at a fine spatial scale. Increasing long-term exposure to NO2, PM10 and PM2.5 was associated with a decrease in cognitive function in older adults in England. This evidence can inform policies related to modifiable environmental exposures linked to cognitive decline.

Long-term exposure to fine particulate matter constituents and cognitive impairment among older adults: An 18-year Chinese nationwide cohort study

BackgroundAlthough growing evidence has shown independent links of long-term exposure to fine particulate matter (PM2.5) with cognitive impairment, the effects of its constituents remain unclear. This study aims to explore the associations of long-term exposure to ambient PM2.5 constituents’ mixture with cognitive impairment in Chinese older adults, and to further identify the main contributor. Methods15,274 adults ≥ 65 years old were recruited by the Chinese Longitudinal Healthy Longevity Study (CLHLS) and followed up through 7 waves during 2000–2018. Concentrations of ambient PM2.5 and its constituents (i.e., black carbon [BC], organic matter [OM], ammonium [NH4+], sulfate [SO42-], and nitrate [NO3-]) were estimated by satellite retrievals and machine learning models. Quantile-based g-computation model was employed to assess the joint effects of a mixture of 5 PM2.5 constituents and their relative contributions to cognitive impairment. Analyses stratified by age group, sex, residence (urban vs. rural), and region (north vs. south) were performed to identify vulnerable populations. ResultsDuring the average 3.03 follow-up visits (89,296.9 person-years), 4294 (28.1%) participants had developed cognitive impairment. The adjusted hazard ratio [HR] (95% confidence interval [CI]) for cognitive impairment for every quartile increase in mixture exposure to 5 PM2.5 constituents was 1.08 (1.05–1.11). BC held the largest index weight (0.69) in the positive direction in the qg-computation model, followed by OM (0.31). Subgroup analyses suggested stronger associations in younger old adults and rural residents. ConclusionLong-term exposure to ambient PM2.5, particularly its constituents BC and OM, is associated with an elevated risk of cognitive impairment onset among Chinese older adults.

Data Gap: Air Quality Networks Miss Air Pollution from Concentrated Animal Feeding Operations.

In the U.S., the agricultural sector is the largest controllable source of several air pollutants, including ammonia (NH3), which is a key precursor to PM2.5 formation. Livestock waste is the dominant contributor to ammonia emissions. In contrast to most controllable air pollutants, satellite records show ammonia mixing ratios are rising. The number of confined animal feeding operations (CAFOs) that generate considerable livestock waste is also increasing. Spatial and temporal trends in USDA-reported animal numbers normalized by county area at medium and large CAFOs provide plausible explanations for patterns in satellite-derived NH3 over the contiguous U.S. (CONUS). The correlation between summertime ammonia derived from the European Space Agency's (ESA) Infrared Atmospheric Sounding Interferometer (IASI) and CAFO animal unit density in 2017 is positive and significant (r = 0.642; p ≈ 0). The temporal changes from 2002 to 2017 in animal unit density and NH3 derived from NASA's Atmospheric Infrared Sounder (AIRS) are spatially similar. Trends and ambient concentrations of PM2.5 mass in agricultural regions are difficult to assess relative to those of urban population centers given the sparseness of rural monitors in regulatory surface networks. Results suggest that in agricultural areas where ammonia concentrations and animal density are highest, air quality improvement lags behind the national average.

Association between living environmental quality and risk of arthritis in middle-aged and older adults: a national study in China.

The association between combined environmental factors and the risk of arthritis is still scarcely studied. The present study performed cross-sectional and cohort studies to explore the association between risk score of living environment quality and the risk of arthritis in middle-aged and older adults in China. The study was based on China Health and Retirement Longitudinal Study (CHARLS), and it recruited 17,218 participants in the cross-sectional study and 11,242 participants in the seven-year follow-up study. The living environment quality was measured by household fuel types, household water sources, room temperature, residence types, and ambient concentration of PM2.5. Logistic regression and Cox proportional hazard regression models were utilized to examine the association between the living environment quality and the risk of arthritis. Competing risk models and stratified analyses were applied to further verify our results. Compared with individuals in the suitable environment group, people who lived in moderate (OR:1.28, 95%CI: 1.14-1.43) and unfavorable environments (OR:1.49, 95%CI:1.31-1.70) showed higher risks of arthritis when considering the multiple living environmental factors (P for trend <0.001) in the cross-sectional analysis. In the follow-up study, similar results (P for trend = 0.021), moderate environment group (HR:1.26, 95%CI:1.01-1.56) and unfavorable environment group (HR: 1.36, 95%CI: 1.07-1.74), were founded. Inferior living environment might promote the development of arthritis. It is necessary for the public, especially old people, to improve the living environment, which may be the key to the primary prevention of arthritis.

Cardiovascular effects of wearing respirators against particulate matter: A randomized crossover trial

Fine particles (PM2.5) are implicated as an important risk to cardiovascular health. N95 respirators had been widely used to provide protection by filtering particles. Yet the practical effects of wearing respirators have not been fully understood. This study aimed to evaluate the cardiovascular effects of respirator wearing against PM2.5 and underpin the understanding of the mechanisms of cardiovascular responses triggered by PM2.5. We conducted a randomized, double-blind crossover trial among 52 healthy adults in Beijing, China. Participants were exposed to outdoor PM2.5 for 2 h in alterations wearing true respirators (with membranes) or sham ones (without membranes). We measured ambient PM2.5 and tested the filtration efficiency of the respirators. We compared the heart rate variability (HRV), blood pressure and arterial stiffness indicators between the true respirator group and the sham respirator group. Concentrations of ambient PM2.5 during the 2-h exposure ranged from 4.9 to 255.0 μg/m3. The filtration efficiency of true respirators was 90.1 % and that of sham ones was 18.7 %. Between-group differences varied by pollution levels. On less polluted days (PM2.5< 75 μg/m3), participants wearing true respirators showed lower levels of HRV and higher levels of heart rate compared with those wearing sham respirators. These between-group differences were inconspicuous on heavily polluted days (PM2.5≥ 75 μg/m3). We found that a 10 μg/m3 increase in PM2.5 was associated with a 2.2 % to 6.4 % decrease in HRV, prominent at 1 h after the start of exposure. N95 respirators have good performance in reducing PM2.5 exposure. Short-term exposure to PM2.5 can induce very acute responses in autonomic nervous function. However, the overall effects of wearing respirators might be not always favorable to human health in terms of their inherent adverse effects, which seem dependent on the levels of air pollution. Precise individual protection recommendations warrant to be developed.

Mitigation of urban particulate pollution using lightweight green roof system

As the global population becomes more concentrated in urban environments, higher numbers of people will be exposed to urban air pollution. The environmental and human health benefits of green roofs are widely recognized. The aim of this paper is to promote green roofs as an effective passive technique for pollution mitigation and adaptation to climate change. During the heating season, the ambient concentrations of PM1, PM2.5, and PM10 were measured above a green roof and a reference roof on a school building, located in New Belgrade, the second-most populous municipality and business center of Serbia’s largest city. The percent reduction of PM10, PM2.5 and PM1, in January 2020, above the green roof compared to the reference roof was 7%, 16.6%, and 17.6%, respectively. The results show that lightweight green roof improve air quality in terms of PM concentrations for all months considered. In this paper, correlation analysis and the use of Pearson’s coefficient were used in the process of analysis to determine the relationship between PM10, PM2.5, PM1, and ambient parameters: relative humidity, ambient temperature, and wind speed. It was found that the statistical correlation expressed by the Pearson coefficient between all PM particles and wind speed was statistically significant in all observed months except September. Also, the degree of significance of the correlation between PM particles and humidity and temperature of ambient air varies by month.

A Land Use Regression Model to Estimate Ambient Concentrations of PM10 and SO2 in İzmit, Turkey

A Land Use Regression Model to Estimate Ambient Concentrations of PM10 and SO2 in İzmit, Turkey

Impact of COVID-19 Restriction Measures on Ambient PM10 Concentrations during Universiti Putra Malaysia Convocation

The outbreak of COVID-19 resulted in many significant restricted social and economic activities. The pandemic provided unprecedented natural experiment in which the study was specifically conducted to investigate the impact on particulate matters with aerodynamic diameter less than 10 µm (PM10) resulting from the restriction measures taken by the university management to manage COVID-19 during convocation. PM10 and meteorological parameters (ambient temperature, relative humidity and wind speed) were monitored using TSI Dusttrak aerosol monitor and Kestrel 4500, respectively. Traffic volume was also considered as the significant source of air pollutants due to higher number of vehicles during the event. Two sets of data were collected during peak hours (7.30-9.30 a.m., 12.30-14.30 p.m. and 16.30-18.30 p.m.) on normal working days (before the outbreak in 2018) and during the convocation (after the outbreak in 2022) at two monitoring points along the major road of Persiaran Universiti 1. The results showed that ambient PM10 concentrations were remarkably reduced by ~65-84%, especially during afternoon peak hours. Parking space allocated far from the main hall area contributed to lower PM10 concentrations. From the parking space, graduands were required to either walk with guidance or take the provided university buses to go to the main hall. Pearson correlation analysis showed that PM10 concentrations have significant relationship with the meteorological parameters (p&lt;0.05). However, in terms of traffic emission, it does not necessarily influence solely by the vehicles. From the observation, walking activities by the graduands, students, visitors, etc. around the monitoring areas also contributed to the dust uplifting, hence influencing the level of PM10. The study elucidated the influence of COVID-19 restriction measures on PM10 concentrations which can be a steppingstone towards a better management in reducing the pollutant in the future convocation events.

A Study on the Distribution Characteristics and Countermeasures of Concentrations of Ambient PM10 and PM2.5 in Yangju, South Korea

A Study on the Distribution Characteristics and Countermeasures of Concentrations of Ambient PM10 and PM2.5 in Yangju, South Korea

Effect of Different Plant Communities on Fine Particle Removal in an Urban Road Greenbelt and Its Key Factors in Nanjing, China

Determining the relationships between the structure and species of plant communities and their impact on ambient particulate matter (PM) is an important topic in city road greenbelt planning and design. The correlation between the distribution of plant communities and ambient PM concentrations in a city road greenbelt has specific spatial patterns. In this study, we selected 14 plant-community-monitoring sites on seven roads in Nanjing as research targets and monitored these roads in January 2022 for various parameters such as PM with aerodynamic diameters ≤10 µm (PM10) and PM with aerodynamic diameters ≤2.5 µm (PM2.5). We used a spatial model to analyze the relationship between the concentrations of ambient PM10 and PM2.5 and the spatial heterogeneity of plant communities. The consequences revealed that the composition and species of plant communities directly affected the concentrations of ambient PM. However, upon comparing the PM concentration patterns in the green community on the urban road, we found that the ability of the plant community structures to reduce ambient PM is in the order: trees + shrubs + grasses &gt; trees + shrubs &gt; trees + grasses &gt; pure trees. Regarding the reduction in ambient PM by tree species in the plant community (conifer trees &gt; deciduous trees &gt; evergreen broad-leaved trees) and the result of the mixed forest abatement rate, coniferous + broad-leaved trees in mixed forests have the best reduction ability. The rates of reduction in PM10 and PM2.5 were 14.29% and 22.39%, respectively. We also found that the environmental climate indices of the road community, temperature, and traffic flow were positively correlated with ambient PM, but relative humidity was negatively correlated with ambient PM. Among them, PM2.5 and PM10 were significantly related to temperature and humidity, and the more open the green space on the road, the higher the correlation degree. PM10 is also related to light and atmospheric radiation. These characteristics of plant communities and the meteorological factors on urban roads are the foundation of urban greenery ecological services, and our research showed that the adjustment of plant communities could improve greenbelt ecological services by reducing the concentration of ambient PM.

The Effects of Particulate Matter Alert on Urban Park Visitation in Seoul, Korea: Using Segmented Regression.

To reduce the health burden from particulate matter (PM), the Korean government implemented a nationwide PM10 (particles less than 10 µg/m3 in diameter) alert system in 2015. The policy was intended to reduce PM exposure by advising people to refrain from outdoor activities on highly polluted days. The present study aimed to estimate the effect of the PM10 alert system on people's daily outdoor activity patterns using urban park (specifically, Children's Grand Park) visitation data from Seoul, South Korea, from 2014-2019. Segmented regression was fitted to estimate whether the number of visitors to the park decreased on the days with PM10 alerts. PM10 concentration of 80 µg/m3, the cut-off point for a "Bad" alert, was set as a threshold, and discontinuity at the threshold and change in the relative risk after the threshold was tested. Time series regression was used to estimate the dose-response line between the ambient PM10 concentration and the daily number of park visitors. The number of park visitors decreased by 11.8% (relative risk: 0.881, 95% confidence interval: 0.808, 0.960) when a "Bad" alert was issued (PM10 level above 80 µg/m3) compared to when the alert level was "Normal" (PM10 level less than 80 µg/m3). The present study found evidence that the PM10 alert influenced people's daily outdoor activities in Seoul, Korea. As the main purpose of the PM alert is to encourage people to refrain from outdoor activities, evaluating the relationship between PM alerts and behavior patterns can help to grasp the effectiveness of the policy. Further efforts should be made to investigate whether the observed behavioral change leads to reductions in health outcomes caused by PM.

Establishing Correlation between Cruise Ship Activities and Ambient PM Concentrations in the Kotor Bay Area Using a Low-Cost Sensor Network

The analysis of cruise ships is focusing on port areas where they may represent a significant source of anthropogenic emissions. In order to determine the correlation between cruise ship activities (hoteling and maneuvering) in ports with the ambient concentration of pollutants associated with marine diesel fuel combustion, the low-cost sensors are finding their market share due to lower prices compared to the referent ones. In this study, a network of four low-cost PM sensors was used to determine the correlation between ambient PM2.5 and PM10 mass concentrations with cruise ship activities in the Kotor Bay area during 27 days in the peak summer season, with a 10-min resolution. Recorded data and the Openair model were used to investigate the potential relationship between cruise ship operations and temporal fluctuations in PM concentrations in the ambient air. Additionally, an Tier 3 methodology developed through the European Monitoring and Evaluation Programme of the European Environmental Agency (EMEP/EEA) was applied in order to estimate the total cruise ship PM emissions. The study has shown that weather conditions play a significant role in local PM concentrations, so that, with predominant ENE wind directions, the west side of the Bay experienced on average higher concentrations of both PM2.5 and PM10. Rain precipitation and higher winds tend to decrease rapidly ambient PM concentrations. Higher PM levels are associated mainly with lower wind speeds and the inflows from neighboring berths/anchorages. During the maneuvering (arrival and departure) of cruise ships, higher spikes in PM values were detected, being more visible for PM10 than PM2.5. A significant correlation between daily average PM concentrations and cruise ships’ daily estimated PM emission was not found. As a result, higher temporal resolution demonstrated a stronger correlation.