Average Concentrations Of PM2 Research Articles

Atmospheric Air Pollution in Niamey, Niger: Assessment of Particulate Matter From Road Traffic (PM2.5 and PM10)

The aim of this study was to characterise the air based on atmospheric particles in the city of Niamey. To do this, a mass concentration detector type PCE-RCM 11 and station type Davis Pro were used as collection equipment. Particulate matter with diameters of less than 2.5 μm and 10 μm, PM2.5 and PM10, respectively, as well as meteorological parameters, temperature and humidity were determined. The study was carried out over 15 days in 5 districts of Niamey between 7.30 am and 10.10 pm at the main roundabouts in each district. According to the results obtained, the average concentrations of PM2.5 in the air measured ranged from 75.34 μg/m3 to 162.34 μg/m3, whereas the WHO recommends 15 μg/m3 for PM2.5 for daily exposure, which would cause cardiovascular or pulmonary disease in those exposed. The PM10 values recorded ranged from 100.43 μg/m3 to 221.90 μg/m3, well in excess of the WHO standards published in 2021, which recommend 45 μg/m3 for PM10, indicating a probable risk of throat and respiratory disorders. Average temperature values ranged from 23.051 °C ± 0.1 °C to 34.186 °C ± 0.1 °C. The average relative humidity measured ranged from 17.164% ± 1% to 26.910% ± 1%. The results of the correlation analysis showed a strong correlation between PM2.5 and PM10. The latter has a strong positive correlation with temperature. PM2.5 is strongly negatively correlated with relative humidity, while PM10 is moderately negatively correlated with relative humidity. Temperature and humidity show a weak negative correlation with each other. Each of the particles studied is present in the communes of Niamey at the 5 roundabouts representing the study area. It should be confirmed that these particles emitted into the air could have come from urban transport. The correlation circle obtained from the PCA explains the relationship between the variables measured (PM and meteorological parameters). The first two dimensions explain 97.55% of the total information, with 81.62% for dimension 1% and 15.93% for dimension 2.

Characteristics and Source Analysis of Carbonaceous Aerosols in PM2.5 in Huaxi District, Guiyang

Carbonaceous aerosol, as an important component of atmospheric aerosol, has a significant impact on atmospheric environmental quality, human health, and global climate change. To investigate the characteristics and sources of carbonaceous aerosol in atmospheric fine particulate matter (PM2.5) in Huaxi District of Guiyang, an in-situ observational study was conducted during different seasons in 2020, and the carbonaceous components of PM2.5 were measured using a thermal-optical carbon analyzer (DRI Model 2015). The results of the study showed that the average concentrations of PM2.5, total carbonaceous aerosol (TCA), organic carbon (OC), secondary organic carbon (SOC), and elemental carbon (EC) concentrations during the observation period were (39.7±22.3), (14.1±7.2), (7.6±3.9), (4.4±2.6), and (2.0±1.0) μg·m-3, respectively, and the mean value of OC/EC was (3.9±0.8). ρ(PM2.5), ρ(TCA), ρ(OC), ρ(SOC), and ρ(EC) showed a seasonal variation pattern with the highest in winter [(52.6±28.6), (17.0±9.6), (9.1±5.2), (6.1±3.9), and (2.4±1.2) μg·m-3, respectively] and the lowest in summer [(25.1±7.1), (11.6±3.6), (6.3±1.9), (3.7±1.2), and (1.6±0.6) μg·m-3, respectively]. The seasonal variation in OC/EC showed summer (4.2±0.8) > winter (3.8±0.9) > autumn (3.8±0.5) > spring (3.7±0.9), indicating the presence of SOC generation in all seasons in Huaxi District. SOC showed a significant correlation with OC (R2 =0.9), and the SOC concentration tended to increase with the increase in atmospheric oxidation. OC showed a good correlation with EC in all seasons, with the highest in autumn (R2 =0.9) and lower correlations in the other three seasons (R2 ranged from 0.74 to 0.75), indicating a common source. According to OC/EC ratio range, it was preliminarily determined that carbonaceous aerosol came from vehicle exhaust emissions, coal burning emissions, and biomass combustion emissions. In order to further quantify the contribution of major emission sources to carbonaceous aerosol, the results of this study using PMF to analyze the sources of carbonaceous aerosol showed that the main sources of carbonaceous aerosol in Huaxi District of Guiyang were coal combustion sources (29.3%), motor vehicle emission sources (21.5%), and biomass combustion sources (49.2%).

Monsoon Season Spatial Distribution of Particulates Concentration in the Road Intersection Area of Different Land Use in Major City in South Asian Countries

Air pollution has become one of the most significant issues in the metropolitan area of Dhaka in recent years. There are various sources of air pollution in Dhaka city, among them, unfit vehicles and industries are notable with under construction work done by Dhaka city Corporation. With regard to various land uses in the Dhaka metropolitan region, this study intends for monitoring the Particulate Matters (PM<sub>2•5</sub> and PM<sub>10</sub>) concentrations and its relationship to the various types of land use in the region. This investigation was carried out in 82 different places throughout the Dhaka metropolitan area by using instrument named Aeroqual S-500. Study found that the average concentrations of PM<sub>2•5</sub> and PM<sub>10</sub> in these locations were 31.10 and 72.03 g/m<sup>3</sup>, respectively. The average concentration of PM<sub>2•5</sub> and PM<sub>10 </sub>across all land uses was found to be 1.4148 and 1.7082 times higher than the WHO standard threshold, respectively. It is estimated that the average PM<sub>2.5</sub>/PM<sub>10</sub> was 46.32%. It also revealed that the concentrations of the parameters do not change significantly with land use as the p values are greater than 0.05. Average concentration of PM<sub>2•5</sub> & PM<sub>10 </sub>follows as mixed area > residential area > commercial area > silent area > industrial area.

Assessment of ambient particulate matter and trace gases in Istanbul: Insights from long-term and multi-monitoring stations

In this study, the long-term spatio-temporal variation, trends, and source increments of particulate matter (PM10 and PM2.5) and gaseous pollutants (SO2, NO, NO2, CO, O3) measured from 2015 to 2021 across 37 air quality monitoring stations in the European and Asian sides of Istanbul were investigated. The average PM10 concentration on the European side is higher than the Asian side. However, the average PM2.5 in both regions showed the same values. The results show that the industries near urban sites mainly affect PM10 concentrations in Istanbul. Ship emissions (from the Istanbul Strait) make the largest incremental contribution to SO2 and CO (211% and 139%, respectively) among other pollutants. PM10, PM2.5, SO2, and NO2 concentrations show significant (p < 0.01) negative temporal trends of 6.02%, 6.97%, 5.38%, and 3.28%, respectively, most notable in the winter season. However, the CO and O3 concentration trends are stable and increasing. According to the correlation coefficient (R) and the coefficient of divergence (COD) analysis, there is a heterogeneous distribution of pollutants at the intra-urban scale. PM2.5 concentrations are dominated by diverse pollution sources such as traffic, shipping and regional sources.

Transport and Potential Sources Regions of Double High Pollution in Nanjing by Different Synoptic Situations

Based on the hourly concentration data of fine particulate matter （PM2.5） and ozone （O3） in Nanjing from 2015 to 2019， the synoptic situation that occurred in Nanjing， in which high PM2.5 and high O3 coexisted （hereinafter referred to as double high pollution （DHP））， was typed using T-mode principal component analysis. Additionally， the backward trajectory clustering analysis method， potential source contribution method （PSCF）， and concentration weight trajectory analysis method （CWT） were used to study the transport paths and potential source region distribution of the DHP of Nanjing by different synoptic situations. The synoptic situations favorable to the DHP in Nanjing were the control of weak low-pressure type （Type1） and high-pressure center （Type2）. Synoptic situations could have had an effect on the directional origin of the backward trajectory. In Type1， the Nanjing area was affected by two low pressures in the northeast and southwest， and the clustering trajectories of the Nanjing air mass mainly came from the eastern and western directions. The average concentrations of PM2.5 and O3 in the trajectory were 83.48 μg·m-3 and 106.85 μg·m-3， respectively. In Type 2， Nanjing and its surroundings were at the edge of the high-pressure center， and the air mass cluster trajectories mainly came from the north and east. The average concentrations of PM2.5 and O3 in the trajectory were 94.47 μg·m-3 and 92.32 μg·m-3， respectively. Most of the two types of backward trajectories belonged to short and medium-distance regional transportation， indicating that the pollution of neighboring provinces was one of the main factors affecting the DHP in Nanjing. PSCF and CWT analysis showed that the distribution of the most important potential sources of PM2.5 and O3 in Type1 and Type2 were not completely consistent， which indicates that the two pollutants did not come from the same area in the DHP.

PM10 increases mortality risk in rheumatoid arthritis-associated interstitial lung disease

ObjectivesThe effect of air pollution on the prognosis of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) remains poorly understood. We aimed to evaluate the effect of long-term exposure to particulate matter...

The contribution of residential wood combustion to the PM2.5 concentrations in the Helsinki metropolitan area

Abstract. This article has investigated the contribution of residential wood combustion (RWC) to the fine particulate matter (PM2.5) concentrations in the Helsinki metropolitan area (HMA) for 6 years, from 2009 to 2014. We have used the PM2.5 concentrations measured at eight air quality measurement stations. The dispersion of emissions on an urban scale was evaluated with multiple-source Gaussian dispersion models, UDM-FMI (urban dispersion model of the Finnish Meteorological Institute) and CAR-FMI (Contaminants in the Air from a Road model of the Finnish Meteorological Institute), and on a regional scale using the chemical transport model SILAM (System for Integrated modeLling of Atmospheric coMposition). The overall agreement of the predicted concentrations with measurements of PM2.5 was good or fairly good for all stations and years; e.g. at the permanent residential station the daily average values of the index of agreement ranged from 0.69 to 0.81, and the fractional bias values ranged from −0.08 to 0.11, for the considered 6 years. Both the measured and predicted daily averaged concentrations showed increasing trends towards the lower-temperature values. The highest predicted annual averaged concentrations in the region occurred in the vicinity of major roads and streets and in the suburban residential areas to the northwest, north, and northeast of the city centre. The average concentrations of PM2.5 attributed to RWC in winter were up to 10- or 15-fold, compared to the corresponding concentrations in summer. During the considered 6-yearly period, the spatially highest predicted fractions of RWC of the annual PM2.5 concentrations ranged from 12 % to 14 %. In winter, the corresponding contributions ranged from 16 % to 21 %. The RWC contribution was higher than the corresponding urban vehicular traffic contribution at all the residential stations during all years. The study has highlighted new research needs for the future, in particular (i) the modelling of the RWC emissions that would be explicitly based on the actual ambient temperatures and (ii) the modelling of the impacts of the most important holiday periods on the emissions from RWC.

Status of air quality in Rajshahi metropolitan area, Bangladesh

Rajshahi is well-known as a model city for clean air in Bangladesh but in recent time air pollution is increasing in metropolitan areas. This study aims to examine the concentration of Particulate Matters (PM₁, PM₂.₅, and PM₁₀) in the Rajshahi metropolitan area during March 2021, with a focus on distinct land use categories. The research was carried out in 40 different sites within the Rajshahi metropolitan area, utilizing a portable device for measuring air quality. It was found that the average concentrations of PM₂.₅ and PM₁₀ were 56.41 and 72.63 µg/m³ respectively, which is 2.25 and 1.45-fold than World Health Organizations (WHO) Standards. According to this study, the three locations with the highest levels of PM₂.₅ pollution were the Mohanonda project gate (105.750 µg/m³), Textile Mill (79.750 µg/m³), and Sarkar Cold Storage (71.750 µg/m³). The concentration of PM₂.₅ in the most polluted location was found to be 1.63 times than the standard level set by Department of Environment (DoE) and 4.23 times higher than the WHO standard. Furthermore, it was calculated that the average PM₂.₅/PM₁₀ ratio was 77.70% and the average PM₁/PM₂.₅ ratio was 60.16%. It also revealed that temperature is negatively and humidity is positively correlated with PM₁, PM₂.₅ and PM₁₀, which means any change in the concentration of PM₁, PM₂.₅ and PM₁₀ can cause a significant change in the percentage of humidity in the same direction, for humidity the change would be in opposite direction. The concentration of PM₂.₅ in ambient air with respect to land use decreases as follows: industrial area &gt; village area &gt; road intersection area &gt; sensitive area &gt; mixed area &gt; commercial area &gt; residential area.

Acidity and oxidative potential of atmospheric aerosols over a remote mangrove ecosystem during the advection of anthropogenic plumes

To investigate the acidity and the water-soluble oxidative potential of PM10, during the continental biomass-burning plume transport, a three-year (2018–2020) winter-time campaign was conducted over a pristine island (21.35°N, 88.32°E) of Sundarban mangrove ecosystem situated at the shore of Bay of Bengal. The average PM10 concentration over Sundarban was found to be 98.3 ± 22.2 μg m−3 for the entire study period with a high fraction of non-sea-salt- SO42− and water-soluble organic carbons (WSOC) that originated from the regional solid fuel burning. The thermodynamic E-AIM(IV) model had estimated that the winter-time aerosols over Sundarban were acidic (pH:2.4 ± 0.6) and mainly governed by non-sea-salt-SO42-. The volume and mass normalized oxidative potential of PM10 was found to be 1.81 ± 0.40 nmol DTT min−1 m−3 and 18.4 ± 6.1 pmol DTT min−1 μg−1 respectively which are surprisingly higher than several urban atmospheres across the world including IGP. The acid-digested water-soluble transition metals (Cu, Mn) show higher influences in the oxidative potential (under high aerosol acidity) compared to the WSOC. The study revealed that the advection of regional solid fuel burning plume and associated non-sea-salt-SO42- is enhancing aerosol acidity and oxidative stress that in turn alters the intrinsic properties of aerosols over such marine ecosystems rich in ecology and bio-geochemistry.

Characteristics and risk assessment of atmospheric PM&lt;sub&gt;2.5&lt;/sub&gt; heavy metals pollution near coal gangue sites in Huaibei, China

To study the level of atmospheric PM&lt;sub&gt;2.5&lt;/sub&gt; and its heavy metal pollution near the coal gangue mountain, this study analyzed the content of seven heavy metals (Zn, Pb, Cu, Cd, Hg, Ni, Cr) and As through the PM&lt;sub&gt;2.5&lt;/sub&gt; samples from the vicinity of a large-scale coal gangue filed of Tongting coal mine in Huaibei, and evaluated the level of pollution, sources, and health effects. The results showed that during the sampling period, the average concentration of PM&lt;sub&gt;2.5&lt;/sub&gt; near the coal gangue field was 169.83 μg·m&lt;sup&gt;-3&lt;/sup&gt;, which was 2.26 times that of the national air quality level Ⅱ daily standard. The coal gangue field may be an important source of air pollution, with the degree of heavy metal and arsenic pollution in the order of Cd, Pb, Zn, Hg (extremely heavy pollution) &gt; As, Cu (medium pollution) &gt; Ni, Cr (light pollution) and coal gangue dust and mining dust contributed more. This study provides data for atmospheric particulate matter and heavy metal and arsenic pollution levels near coal gangue fields and provides a theoretical basis for air pollution prevention and control near coal gangue hills.

The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China.

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m-3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m-3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020-2021. Despite a 22~62% decline in NOx levels in 2020-2021, the increased O3 caused a similar NO3- concentration (20.69~23.00 μg m-3) in 2020-2021 to that (22.93 μg m-3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019-2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future.

Chemical characteristics, morphology and source apportionment of PM10 over National Capital Region (NCR) of India.

The present study frames the physico-chemical characteristics and the source apportionment of PM10 over National Capital Region(NCR) of India using the receptor model's Positive Matrix Factorization (PMF) and Principal Momponent Mnalysis/Absolute Principal Component Score-Multilinear Regression (PCA/APCS-MLR). The annual average mass concentration of PM10 over the urban siteof Faridabad, IGDTUW-Delhi and CSIR-NPL of NCR-Delhi were observed to be 195 ± 121, 275 ± 141 and 209 ± 81µgm-3, respectively. Carbonaceous species (organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC)), elemental constituents (Al, Ti, Na, Mg, Cr, Mn, Fe, Cu, Zn, Br, Ba, Mo Pb) and water-soluble ionic components (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) of PM10were entrenched to the receptor models to comprehend the possible sourcesof PM10. The PMF assorted sources over Faridabad were soil dust (SD 15%), industrial emission (IE 14%), vehicular emission (VE 19%), secondary aerosol (SA 23%) and sodium magnesium salt (SMS 17%). For IGDTUW-Delhi, the sources were SD (16%), VE (19%), SMS (18%), IE (11%), SA (27%) and VE + IE (9%). Emission sources like SD (24%), IE (8%), SMS (20%), VE + IE (12%), VE (15%) and SA + BB (21%) were extracted over CSIR-NPL, New Delhi, which are quite obvious towards the sites. PCA/APCS-MLR quantified the similar sources with varied percentage contribution. Additionally, catalogue the Conditional Bivariate Probability Function (CBPF) for directionality of the local source regions and morphology as spherical, flocculent and irregular were imaged using a Field Emission-Scanning Electron Microscope (FE-SEM).

Characterizing bioaerosols in PM2.5 in a semi-arid region experiencing desert dust events

Introduction: Fine particulate matter (PM2.5) pollution is a global public health concern, particularly in arid and semi-arid regions that experience dust events. Exposure to PM2.5 has been associated with various short- and long-term health effects, which can be attributed to the composition of the fine particles. This study aimed to assess the concentration of bacteria and fungi in PM2.5 in the air of Isfahan, Iran which experiences air pollution.Methods: A total of thirty-nine PM2.5 samples were collected over 1 year. Bacterial and fungal concentrations associated with PM2.5 were measured using both culture-based method and real-time polymerase chain reaction (PCR).Results: The average concentration of PM2.5 was found to be 56 μg m−3, with many samples exceeding the recommended limit of 15 μg m−3 set by the World Health Organization for PM2.5 in ambient air. The mean culturable bacterial and fungal concentrations were 39 and 4 CFU m−3, respectively which showed a significant difference compared to the results obtained through real-time PCR. No significant correlation was found between the levels of bacterial and fungal cells and PM2.5 concentrations. The dominant phyla found in PM2.5 were Firmicutes and Actinobacteria, while Proteobacteria as Gram-negative bacteria were rarely detected.Discussion: The findings suggest that the climate conditions in Isfahan, characterized by its semi-arid nature with low humidity content, influences the activity and viability of microbial populations, resulting in low concentrations of bioaerosols in PM2.5. Furthermore, it seems that desert dust events do not contribute to increasing the potential health risks associated with bacterial and fungal bioaerosols in PM2.5.

Effect of Heating Emissions on the Fractal Size Distribution of Atmospheric Particle Concentrations

Excessive particle concentrations during heating periods, which greatly affect people’s physical and mental health and their normal lives, continue to be a concern. It is more practical to understand and analyze the relationship between the fractal dimension and particle size concentration distribution of atmospheric particulate matter before and after adjusting heating energy consumption types. The data discussed and analyzed in this paper were collected by monitoring stations and measured from 2016 to 2018 in Xi’an. The data include fractal dimension and particle size concentration changes in the atmospheric particulate matter before and after adjusting the heating energy consumption types. The results indicate that adjusting the heating energy consumption types has a significant impact on particulate matter. The average concentration of PM2.5 decreased by 26.4 μg/m3. The average concentration of PM10 decreased by 31.8 μg/m3. At the same time, the different particle sizes showed a downward trend. The particles ranging from 0.265 to 0.475 μm demonstrated the maximum decrease, which was 8.80%. The heating period in Xi’an mainly involves particles ranging from 0 to 0.475 μm. The fractal dimensions of the atmospheric particulate matter before and after adjusting the heating energy consumption types were 4.809 and 3.397, respectively. After adjusting the heating energy consumption types, the fractal dimension decreased by 1.412. At that time, the proportions of particle sizes that were less than 1.0 μm, 2.0 μm, and 2.5 μm decreased by 1.467%, 0.604%, and 0.424%, respectively. This paper provides new methods and a reference value for the distribution and effective control of atmospheric particulate matter by adjusting heating energy consumption types.

Intrauterine and early postnatal exposures to submicron particulate matter and childhood allergic rhinitis: A multicity cross-sectional study in China

BackgroundAirborne particulate matter pollution has been linked to occurrence of childhood allergic rhinitis (AR). However, the relationships between exposure to particulate matter with an aerodynamic diameter ≤1 μm (PM1) during early life (in utero and first year of life) and the onset of childhood AR remain largely unknown. This study aims to investigate potential associations of in utero and first-year exposures to size-segregated PMs, including PM1, PM1–2.5, PM2.5, PM2.5–10, and PM10, with childhood AR. MethodsWe investigated 29286 preschool children aged 3–6 years in 7 Chinese major cities during 2019–2020 as the Phase II of the China Children, Families, Health Study. Machine learning-based space-time models were utilized to estimate early-life residential exposure to PM1, PM2.5, and PM10 at 1 × 1-km resolutions. The concentrations of PM1–2.5 and PM2.5–10 were calculated by subtracting PM1 from PM2.5 and PM2.5 from PM10, respectively. Multiple mixed-effects logistic models were used to assess the odds ratios (ORs) and 95% confidence intervals (CIs) of childhood AR associated with per 10-μg/m3 increase in exposure to particulate air pollution during in utero period and the first year of life. ResultsAmong the 29286 children surveyed (mean ± standard deviation, 4.9 ± 0.9 years), 3652 (12.5%) were reported to be diagnosed with AR. Average PM1 concentrations during in utero period and the first year since birth were 36.3 ± 8.6 μg/m3 and 33.1 ± 6.9 μg/m3, respectively. Exposure to PM1 and PM2.5 during pregnancy and the first year of life was associated with an increased risk of AR in children, and the OR estimates were higher for each 10-μg/m3 increase in PM1 than for PM2.5 (e.g., 1.132 [95% CI: 1.022–1.254] vs. 1.079 [95% CI: 1.014–1.149] in pregnancy; 1.151 [95% CI: 1.014–1.306] vs. 1.095 [95% CI: 1.008–1.189] in the first year of life). No associations were observed between AR and both pre- and post-natal exposure to PM1–2.5, indicating that PM1 rather than PM1–2.5 contributed to the association between PM2.5 and childhood AR. In trimester-stratified analysis, childhood AR was only found to be associated with exposure to PM1 (OR = 1.077, 95% CI: 1.027–1.128), PM2.5 (OR = 1.048, 95% CI: 1.018–1.078), and PM10 (OR = 1.032, 95% CI: 1.007–1.058) during the third trimester of pregnancy. Subgroup analysis suggested stronger PM-AR associations among younger (<5 years old) and winter-born children. ConclusionsPrenatal and postnatal exposures to ambient PM1 and PM2.5 were associated with an increased risk of childhood AR, and PM2.5-related hazards could be predominantly attributed to PM1. These findings highlighted public health significance of formulating air quality guideline for ambient PM1 in mitigating children's AR burden caused by particulate air pollution.

Vertical concentration distributions of atmospheric particulates in typical seasons of winter and summer during working and non-working days: A case study of high-rise buildings

It is important to understand the vertical distribution characteristics of outdoor particulates concentration in typical seasons of winter and summer when people's living spaces are getting higher and higher above the ground. The different heights of floors (1st, 7th, 11th, 17th, and 27th) of a high-rise building in Xi'an at 8:00, 12:00, 15:00, 18:00, and 22:00, respectively, were tested and analyzed in this paper. The results showed that the concentrations on non-working days were much lower than that on working day sat different times and on different floors, and the concentrations of particulates were relatively low in summer. The particulates reached the highestat 12:00 in summer, with the average concentrations of PM10, PM2.5, and PM1.0were37.3, 31.6, and 29.4 ?g/m3.While reached the highest at 15:00 in winter, with the average concentrations of PM10, PM2.5, and PM1.0were 82.4, 64.8, and 57.7 ?g/m3. The distribution of atmospheric environment in Xi'an is mainly dominated by small particulates. The particle sizes of low floors are mainly range from 1.0 to 2.5 ?m, and the high floors are less than 1.0?m.With the increase of floors and time, PM1.0/PM2.5and PM2.5/PM10show a trend of first decreasing and then increasing on working days, while PM1.0/PM2.5and PM2.5/PM10show a trend of first increasing, then decreasing and next increasing on non-working days. In addition, outdoor meteorological parameters will also have a certain impact on particulates concentration distribution. It provides reference values for controlling the particulates concentration in high-rise buildings.

Investigating PM&lt;sub&gt;2.5&lt;/sub&gt; pollution patterns in South Africa using space-time analysis

&lt;abstract&gt; &lt;p&gt;The global concentration of fine particulate matter (PM&lt;sub&gt;2.5&lt;/sub&gt;) is experiencing an upward trend. This study investigates the utilization of space-time cubes to visualize and interpret PM&lt;sub&gt;2.5&lt;/sub&gt; data in South Africa over multiple temporal intervals spanning from 1998 to 2022. The findings indicated that the mean PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations in Gauteng Province were the highest, with a value of 53 μg/m&lt;sup&gt;3&lt;/sup&gt; in 2010, whereas the lowest mean PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations were seen in the Western Cape Province, with a value of 6.59 μg/m&lt;sup&gt;3&lt;/sup&gt; in 1999. In 2010, there was a rise in the average concentration of PM&lt;sub&gt;2.5&lt;/sub&gt; across all provinces. The increase might be attributed to South Africa being the host nation for the 2010 FIFA World Cup. In most provinces, there has been a general trend of decreasing PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations over the previous decade. Nevertheless, the issue of PM&lt;sub&gt;2.5&lt;/sub&gt; remains a large reason for apprehension. The study also forecasts South Africa's PM&lt;sub&gt;2.5&lt;/sub&gt; levels until 2029 using simple curve fitting, exponential smoothing and forest-based models. Spatial analysis revealed that different areas require distinct models for accurate forecasts. The complexity of PM&lt;sub&gt;2.5&lt;/sub&gt; trends underscores the necessity for varied models and evaluation tools.&lt;/p&gt; &lt;/abstract&gt;

Health risk analysis of heavy metal exposure bonded in PM2.5 at industrial area in Bandung Regency

Heavy metal contents in PM2.5 particulate dust poses potential risk to the health of human beings. This study aims to measure PM2.5 dust concentrations and characterize heavy metals bound in PM2.5 to estimate health risks in both children and adult groups. PM2.5 dust was measured in Bandung Regency in industrial land uses, located in the Dayeuhkolot sub-district. Measurement of PM2.5 concentrations using a Low Volume Air Sampler (LVAS) with PTFE filters. Sample was collected for 7 days x 24 hours. Heavy metals in PM2.5 dust were characterized using ED-XRF. Calculation of non-carcinogenic and carcinogenic health risks was only performed on metals classified as Hazardous Air Pollutants (HAPs). The average concentration of PM2.5 during the measurement period was 59,10±9,10 μg/m3, exceeding the daily ambient air quality standard based on PP No.22 of 2021 which is&gt; 55μg/m3. The risk of non-carcinogenicity is expressed in Health Index (HI) values. The heavy metals considered in determining non-carcinogenic risk are As, Cd, Cr, Pb, Mn, Ni, Se, Fe, Zn, Si, and Sb as well as the crustal elements Si and Fe. Non-carcinogenic risk associated with exposure to heavy metals in PM2.5 showed HI&lt;1 for both children and adults. This indicates that the exposure to heavy metals in PM2.5 around the Dayeuhkolot industrial area is at an acceptable risk level. HI value for heavy metal exposure for children was 0.34±0.17 and 0.42±0.28 for adults. In estimating the carcinogenic risk value, elements taken into account include As, Cd, Cr, Ni and Pb. Carcinogenic risk in both children and adults showed ECR&gt;10-6 of 4.5×10-5 and 2.1×10-4, respectively. This indicates that there is an unsafe health risk that can potentially cause carcinogenic effects in the population around the Dayeuhkolot industrial area The results of this study can be used as a reference database for establishing policies related to air quality in Bandung Regency.

Unpaved road particulate matter emission rates and vehicle-induced transient plume characteristics.

Particulate matter (PM) emitted from unpaved rural roads presents a potential inhalation hazard to people living and working near them. In the absence of site-specific exposure data, plume dispersion modeling can be used to predict ambient particulate concentrations in the vicinity of the unpaved roads. Hourly averaged PM10 concentrations were measured near a gravel road using an EPA reference method resulting in a geometric mean of 50 μg m-3. With these ambient concentrations, the AERMOD plume dispersion model was used to derive a PM emission factor of 444 g/VKT (grams per vehicle kilometer travelled). This result was lower than the emission factor calculated using the EPA's AP-42 guidance for unpaved roads (795 g/VKT). The transient nature of the plume of PM concentrations due to road traffic was also evaluated using a direct-reading instrument. Vehicle speed and wind speed were found to be significant determinants of PM concentration, average PM concentration, and total PM mass for each plume. Each vehicle produced an average concentration of 4096 μg m-3 over the duration of the plume. Therefore, residents near the road are potentially exposed to substantially higher short-term concentrations from individual plumes than would be indicated by hourly averages.

Urban ambient PM10 analysis: Characterization, sources, health risk and sustainable solutions

This is the first inclusive research concerning PM10 samples collected from 3 cities of Maharashtra State of India which categorized into 9 microenvironments. This study presents insights to chemical and morphological analysis, health risks, source apportionment, with sustainable solutions to improve air quality. These samples were analyzed for elemental composition as well as morphological features. Average PM10 concentration at industrial area of Jalgaon city was found to be maximum (70.9 ± 2.7 μg/m3) while minimum at residential area of Pachora city (43.1 ± 5.2 μg/m3). The mean concentration of 8 elements followed the order of (Co < Cd < Ni < Cr < Pb < Mn < Zn < Fe). These particles showed varying morphologies such as spherical, rectangular, cluster, porous shape. Principal Component Analysis (PCA) revealed that elements mainly originate from vehicular exhaust, construction activities, coal combustion and re-suspension of crustal elements due to anthropogenic activities. Health risk assessment showed that the incremental excess lifetime cancer risk (IELCR) for Pb was below threshold limit. Nonetheless, the exposed population is highly susceptible to Cr, Ni, and Co causing high risk of cancer at all sites.