PM10 Ratio Research Articles

Variations and Source Apportionment of PM2.5 and PM10 Before and During COVID-19 Lockdown Phases in Delhi, India

Major cities across the globe including megacity Delhi have experienced considerable lower levels of air pollutants including particulate matter (PM) during COVID-19 lockdown. This study explores pre-lockdown and during lockdown air quality changes in PM2.5, PM10, PM2.5/PM10 ratio along with meteorological effects. Selected sites with different pollution signatures in Delhi including Alipur (residential), Okhla (industrial) and Pusa Road (traffic) have experienced mean (S.D.) PM2.5 as 87.56(± 54.06), 124.45(± 73.49) and 62.14(± 58.64) µg/m3 and PM10 as 163.01(± 77.37), 217.71(± 93.94) and 135.15(± 77.90) µg/m3 before lockdown (BL), while for Lockdown 1 (L1), PM2.5 concentrations decreased drastically as 39.26(± 16.31), 38.01(± 15.16) and 31.03(± 12.79) µg/m3 and for PM10 as 100.76(± 43.71), 79.47(± 30.97) and 66.53(± 22.78) µg/m3, respectively, with gradual increase in both pollutants during successive lockdown phase—Lockdown 2, Lockdown 3, Lockdown 4 and Unlock phase 1. The percentage (%) decrease in PM2.5 (69.46%) and PM10 (63.49%) during lockdown was found well correlated with people mobility (Google and Apple mobility reports), as outdoor activities showed 70–80% decrease in L1 from BL phase. Source apportionment studies suggested both local and regional pollution contribution in Delhi. Comparison of PM2.5 and PM10 concentrations for the year 2020 with that of 2018 and 2019 and study on diurnal variations of PM2.5 and PM10 have been discussed.

Indoor and Ambient Air Pollution in Chennai, India during COVID-19 Lockdown: An Affordable Sensors Study

The Tamil Nadu Air Pollution and Health Effects study (TAPHE-2) aims to evaluate the relationship between air pollution and birth outcome in a rural-urban cohort of 300 pregnant women. Due to COVID-19 related lockdowns, some TAPHE-2 activities were delayed; however, continuous indoor and outdoor air quality data were collected in and around Chennai, India. We report here the impact of graded COVID-19 lockdown on indoor particulate matter (PM2.5 and PM10) levels based on calibrated data from affordable real-time PM sensors called atmos™ and ambient PM levels from publicly available regulatory monitors. The study period was between 11 March and 30 June 2020 (i.e., 100 days of continuous monitoring), which coincided with four phases of a nationwide graded lockdown. Field calibration coefficients for the atmos PM were derived by collocating them with reference-grade PM monitors. The normalized root mean square error (NRMSE) of the atmos hourly PM2.5 (PM10) improved from 41% to 15% (33% to 18%) after applying the field calibration coefficients. Lockdowns resulted in significant reductions in indoor and ambient PM levels, with the highest reduction observed during lockdown phase 2 (L2) and phase 3 (L3). Reductions as high as 70%, 91%, and 62% were observed in ambient PM2.5, indoor PM2.5, and indoor PM10 relative to pre-lockdown levels (PL), respectively. The indoor PM2.5/PM10 ratio decreased during the lockdown, suggesting a decline in the fine mode dominance in PM10. The indoor-to-outdoor (I/O) ratios in PM2.5 marginally increased during L1, L2, and L3 phases compared to that of PL levels, suggesting an uneven reduction in indoor and ambient PM2.5 levels during the lockdown.

Diurnal Variation of Chemical Characteristics and Source Identification of Fine Particles in the Kaohsiung Harbor

This study investigated the diurnal and monthly variation of fine particle (PM2.5) concentrations and its chemical characteristics and source identification in the Kaohsiung Harbor. Three sites located in the harbor areas were selected for simultaneously sampling 12-h PM2.5 in four months with consecutive seven days in each month. Water-soluble ions (WSIs), metallic elements, carbons, anhydrosugars, and organic acids in PM2.5 were analyzed to characterize their chemical fingerprints and monthly variation. Field sampling and chemical analysis of PM2.5 showed that significant diurnal and monthly variations of PM2.5’s mass concentration and chemical composition were observed in the Kaohsiung Harbor. Prevailing wind direction highly influences the mass concentrations and chemical characteristics of PM2.5 in the port areas. PM2.5 was dominated by WSIs with the abundance of secondary inorganic aerosols (SIAs). Crustal elements dominated the metallic content of PM2.5, but trace elements mainly originated from anthropogenic sources. The V/Ni ratios of PM2.5 in the Kaohsiung Harbor were generally higher than 2.0. Organic carbon (OC) was superior to elemental carbon (EC) in PM2.5 with the dominance of secondary OC (SOC). High concentration of levoglucosan (levo) was observed in spring due to nearby biomass burning. Additionally, high mass ratios of malonic and succinic acids (M/S) in PM2.5 indicated the potential formation of SOAs. Results obtained from chemical mass balanced (CMB) receptor modeling showed that the major sources of PM2.5 resolved in the Kaohsiung Harbor were mobile sources, ship emissions and oil-fired boilers, steel plants, secondary aerosols, sea salt spray, and fugitive dust. Primary PM2.5 emitted from ship traffics accounted for 20.8% of PM2.5.

Spatiotemporal Variations of Particulate Matter and their Association with Criteria Pollutants and Meteorology in Malaysia

Fine particulate matter (PM2.5) poses a higher risk to human health than coarse particulate matter (PM10). This study aims to determine the spatiotemporal variations of PM2.5 and PM10 in Malaysia and their association with other criteria pollutants and meteorological factors. Hourly data from air quality monitoring stations for the year 2018 were retrieved from the Malaysian Department of Environment and analysed for temporal and spatial scales according to different regions in Malaysia. Further statistical analyses, such as Spearman’s Rank Correlation and Principal Component Analysis (PCA), were conducted to study the associations between PM2.5 and PM10 with other main criteria air pollutants, as well as meteorological parameters. Higher mean concentrations of PM2.5 (23 ± 8 µg/m3, range = 4.6–158 µg/m3) and PM10 (32 ± 10 µg/m3, range = 6.0–181 µg/m3) were observed in the central region of the Malaysian Peninsula. The diurnal patterns of PM2.5 and PM10 were in a bimodal pattern and influenced by traffic emissions. The highest mean PM2.5 and PM10 concentrations were recorded during the southwest monsoon season, notably in the central region. The Spearman’s Rank Correlation shows that NO2 and CO have a moderately positive correlation (p < 0.01) with PM2.5 (r = 0.47) and PM10 (r = 0.48) in the central regions while all meteorological parameters show significantly weak to very weak correlations with PM. The PCA analysis indicates that the major sources leading to the formation of particulate matter are from the contribution of secondary aerosols and combustion-related sources. The ratio of PM2.5 to PM10 ranged between 0.51 and 0.76 nationwide with the highest mean recorded in the central region (0.72). This study indicates that there is a higher abundance of fine particulate in the ambient air of the urbanised environment and thus a greater likely risk to human health in more developed areas.

Relationships between Meteorological and Particulate Matter Concentrations (PM2.5 and PM10) during the Haze Period in Urban and Rural Areas, Northern Thailand

Meteorological parameters play a crucial role in the ambient air quality of urban and rural environments. This study aims to investigate the relationship between meteorological parameters (including temperature, relative humidity, and wind speed) and the concentrations of PM2.5 and PM10 in the urban area and the rural area, northern Thailand during the haze period (January to April) from 2016 to 2020. Statistical analyses of the Spearman-Rank correlation coefficient and the multivariate gaussian regression were used to investigate the relationships. The secondary data of ambient PM2.5 and PM10 concentration and meteorological parameters were acquired from the Thai Pollution Control Department. The measurements are obtained using the Beta Ray attenuation method. The results showed that approximately 24% to 65% of daily average PM2.5 concentrations in the urban area over the study period exceeded Thailand’s National Ambient Air Quality Standards. The average PM2.5/PM10 ratios in the urban and the rural areas over the haze period were 0.69 and 0.66, respectively. Our analysis established a significant correlation between atmospheric temperature ( r = 0.624) and relative humidity ( r = −0.722) with the concentrations of PM2.5 and PM10. In both areas, PM2.5 and PM10 concentrations were also positively correlated with temperature. In contrast, relative humidity was significantly related with the decrease of PM2.5 and PM10 concentrations. However, wind speed does not affect PM2.5 and PM10 concentrations. Additionally, the daily backward trajectories using the hybrid-single particle Lagrangian integrated trajectory model also demonstrated air mass movement in March mostly came from the southwesterly direction, which moved through the highlands, the large biomass burned areas, upwind neighboring provinces, and transboundary transports before reaching the air monitoring stations. Our findings improve the understanding of particulate matter pollution and meteorological patterns during annual haze periods in the urban and rural areas. We expect the output of this study can help improve existing haze mitigation measures for improving the prediction accuracy of air pollution under variable meteorological parameters.

The human health risk assessment of particulate air pollution (PM2.5 and PM10) in Romania

Air pollution, especially the concentration of particulate matter (PM2.5, PM10) is a major issue and is the biggest environmental risk for early death. In the present study, we aimed to estimate the human health risk and to describe the spatial and temporal variation of particulate matter in Romania between 2009 and 2018. The average concentration of PM2.5 and PM10 particulate matter in the eight studied regions varied between 17.01 and 22.91 µg m−3 and 23.02–33.29 µg m−3, while the PM2.5/PM10 ratio varied between 0.52 and 0.76, respectively. The relative risk generated by PM10 in all-cause mortality had a significant variation between the regions, a relative risk of 1.017 in case of Bucharest and1.025 for western regions, with an average of 1.020 ( ± 0.002). According to our observations, a positive relative risk was identified in the case of cardiopulmonary and lung cancer morbidity mainly attributed to PM2.5 exposure, hence the resulted risk for the country average values was 1.26 ( ± 0.023) and 1.42 ( ± 0.037), respectively. The results revealed that the excess risk and attributable fraction for cardiopulmonary mortality can be reduced by 26.7% and 21.0%. Analyzing the evolution of particulate matters and the possible health impacts of PM2.5 and PM10 in all region of Romania a strong positive correlation was observed. Since the distributions of PM in different region had significant variation, more investigation is required to understand and decipher the most important regional emission sources for each region. In order to address this issue an in-depth investigation should separately analyze the regional characteristics of air pollution.

Variations of Particulate Matter in Visakhapatnam city of Andhra Pradesh, India

This paper presents the seasonal variations of particulate matter, short and long-term variations in PM2.5/PM10 ratios for 2020-2021 in Visakhapatnam city of Andhra Pradesh, India. The season-wise analysis indicates that 92% and 78% of the time, the 24-hr average value of PM10 and PM2.5 exceeded the breakpoints in winter. A significant correlation between PM2.5 ad PM10 was observed in all seasons. The mean ratios of PM2.5/PM10 during winter and post-monsoon are higher compared to the other two seasons.

Ultra-Violet Mie Lidar Observations of Particulates Vertical Profiles in Macao during a Record High Pollution Episode

Vertical profiles of particulates were measured in Macao by using a 355 nm Mie scattering lidar during a dust event. A high energy pulse laser was employed as the light source to detect the extinction coefficient in the atmosphere. The extinction profiles showed layers of high aerosol concentrations in good agreement with both back trajectory analysis and ground-based pollution measurements in Macao, which indicate that this lidar is very useful for monitoring extinction profiles during extreme high aerosol loading and low visibility atmospheric conditions when most low energy lidar system is inefficient. The results evidenced that correlations between PM2.5 and TSP varied with the intensity of dust storm and the PM2.5/PM10 ratio was small during dust episode, which indicated that aerosols were dominated by large particles. Furthermore, results of the dust event showed high aerosol concentrations at altitudes where the wind carried the dusty aerosols from northern China, covering Shanghai and the Taiwan Channel, to the Pearl River Delta Region. This research improved the understanding of the dust properties in Macao.

Linking indoor particulate matter and black carbon with sick building syndrome symptoms in a public office building

Poor indoor air quality is an important issue for public and occupational health worldwide. Location, air-tightness of the building, ventilation rate and resident activities play an important role on the concentration of indoor pollutants and subsequently on their effects on human health. While indoor air pollution in working environments has been widely studied, the association between specific pollutants and Sick Building Syndrome (SBS) symptoms is still not clear. The objective of this study is to explore the association between PM2.5 and BC with SBS symptoms reported by employees working in a public building in the center of Athens, Greece. Continuous indoor air quality measurements were carried out from March until May 2016 (24 h, 7 days per week), including days during a Saharan dust event in March 2016. The measurements took place in four different types of spaces, including an office, a printer room and two archiving rooms, representing both high and low exposure environments. Indoor PM2.5 and BC concentrations in the office ranged from 5.9 to 14.3 μg/m3 and 1.1–1.9 μg/m3, respectively, whereas outdoor PM2.5 and BC concentrations were in the range of 6.5–21.7 μg/m3 and 1.4–2.6 μg/m3, respectively. We observed diurnal variations in indoor/outdoor ratios of PM2.5 and BC in most rooms that were >1 during working hours, that subsequently fell to below unity after working hours. Data collected via a questionnaire to 73 employees showed that the most commonly reported SBS symptoms were irritation of the eyes, a stuffy or runny nose, headache and drowsiness. Female employees were more likely to report SBS symptoms than male employees, especially nonspecific symptoms, including “unusual tiredness or fatigue” and “feeling depressed”.

Investigation of air pollution with fine dust during repair and construction work inside premises

A study of the dispersed composition of dust for various types of repair in warehouses has been carried out. The data on the concentration of dust emissions inside the premises were obtained. The dependence of the dust concentration on the distance from the place of work, the size of the emitted particles, the area of the room and the time spent on the work is built. An assessment is given of the impact of reconstruction work in warehouses on environmental pollution by dust emissions. The concentration and ratio of PM2.5 to PM10 particles were calculated to determine dustiness and negative impact on the environment.

Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016-2017 in Lanzhou, China.

As one of the most important industrial cities in Northwest China, Lanzhou currently suffers from serious air pollution. This study analyzed the formation mechanism and potential source areas of persistent air pollution in Lanzhou during the heating period from November 1, 2016 to March 31, 2017 based on the air pollutant concentrations and relevant meteorological data. Our findings indicate that particulate pollution was extremely severe during the study period. The daily PM2.5 and PM10 concentrations had significantly negative correlations with daily temperature, wind speed, maximum daily boundary layer height, while the daily PM2.5 and PM10 concentrations showed significantly positive correlations with daily relative humidity. Five persistent pollution episodes were identified and classified as either stagnant accumulation or explosive growth types according to the mechanism of pollution formation and evolution. The PM2.5 and PM10 concentrations and PM2.5/PM10 ratio followed a growing "saw-tooth cycle" pattern during the stagnant accumulation type event. Dust storms caused abrupt peaks in PM10 and a sharp decrease in the PM2.5/PM10 ratio in explosive growth type events. The potential sources of PM10 were mainly distributed in the Kumtag Desert in Xinjiang Uygur Autonomous Region, the Qaidam Basin and Hehuang Valley in Qinghai Province, and the western and eastern Hexi Corridor in Gansu Province. The contributions to PM10 were more than 120μg/m3. The important potential sources of PM2.5 were located in Hehuang Valley in Qinghai and Linxia Hui Autonomous Prefecture in Gansu; the concentrations of PM2.5 were more than 60μg/m3.

Elemental Composition of PM2.5 and PM10 and Health Risks Assessment in the Industrial Districts of Chelyabinsk, South Ural Region, Russia.

Air pollution impacts all populations globally, indiscriminately and has site-specific variation and characteristics. Airborne particulate matter (PM) levels were monitored in a typical industrial Russian city, Chelyabinsk in three destinations, one characterized by high traffic volumes and two by industrial zone emissions. The mass concentration and trace metal content of PM2.5 and PM10 were obtained from samples collected during four distinct seasons of 2020. The mean 24-h PM10 ranged between 6 and 64 μg/m3. 24-h PM2.5 levels were reported from 5 to 56 μg/m3. About half of the 24-h PM10 and most of the PM2.5 values in Chelyabinsk were higher than the WHO recommendations. The mean PM2.5/PM10 ratio was measured at 0.85, indicative of anthropogenic input. To evaluate the Al, Fe, As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn concentration in PM2.5 and PM10, inductively coupled plasma mass spectrometry (ICP-MS) was used. Fe (337–732 ng/m3) was the most abundant component in PM2.5 and PM10 samples while Zn (77–206 ng/m3), Mn (10–96 ng/m3), and Pb (11–41 ng/m3) had the highest concentrations among trace elements. Total non-carcinogenic risks for children were found higher than 1, indicating possible health hazards. This study also presents that the carcinogenic risk for As, Cr, Co, Cd, Ni, and Pb were observed higher than the acceptable limit (1 × 10−6).

Spatial-Temporal Variation of Air PM2.5 and PM10 within Different Types of Vegetation during Winter in an Urban Riparian Zone of Shanghai

Particulate matter (PM) in urban riparian green spaces are undesirable for human participation in outdoor activities, especially PM2.5 and PM10. The PM deposition, dispersion and modification are influenced by various factors including vegetation, water bodies and meteorological conditions. This study aimed to investigate the impact of vegetation structures and the river’s presence on PM in riparian zones. The spatial-temporal variations of PM2.5 and PM10 concentrations in three riparian vegetation communities with different structures (open grassland (G), arbor-grass (AG) and arbor-shrub-grass (ASG) woodlands) were monitored under relatively stable environment. The removal percentages (RP) and ratios of PM2.5 and PM10 were calculated and compared to identify the removal effect of vegetation structures and the river’s presence. It is found that: (1) when the wind was static (hourly wind speed &lt; 0.2 m/s), the RP was ranked as follows: G &gt; AG &gt; ASG. When the wind was mild (0.2 m/s &lt; hourly wind speed &lt; 2 m/s), the RP was ranked as follows: G &gt; ASG &gt; AG. Generally, the G had the best removal effect during the monitoring period; (2) the lowest RP occurred in the middle of the G (–3.4% for PM2.5, 1.8% for PM10) while the highest RP were found in middle of the AG and ASG, respectively (AG: 2.1% for PM2.5, 6.7% for PM10; ASG: 2.4% for PM2.5, 6.3% for PM10). Vegetation cover changed the way of natural deposition and dispersion; (3) compared with static periods, PM removal percentages were significantly reduced under mild wind conditions, and they were positively correlated with wind speed during the mild-wind period. Thus, a piecewise function was inferred between wind speed and PM removal percentage; (4) for all three communities, the 1 m-to-river PM2.5/PM10 ratio was significantly lower than that at 6 m and 11 m, even lower than that in the ambient atmosphere. The river likely promoted the hygroscopic growth of PM2.5 and the generation of larger-sized particles by coagulation effect. Based on these findings, open grassland space is preferred alongside rivers and space for outdoor activities is suggested under canopies in the middle of woodlands.

Multi‐Source Data Based Investigation of Aerosol‐Cloud Interaction Over the North China Plain and North of the Yangtze Plain

AbstractAlthough great progress has been made in the study of aerosol‐cloud interactions (ACIs), representation of ACI is still the largest uncertainty in current weather and climate models. In this study, the ACI over the North China Plain and north of the Yangtze Plain is investigated using multi‐source data including satellite, ground‐based, reanalysis, and fusion data. The effects of aerosol characteristics (PM2.5, PM10, and PM2.5/PM10 ratio), atmospheric conditions including liquid water path (LWP) and lower tropospheric stability (LTS), and drizzle on ACI are analyzed. Results suggest that both aerosol characteristics and atmospheric conditions can affect cloud effective radius (), but drizzle in clouds plays a decisive role on ACI. In the case of fixed LTS and LWP, the average cloud droplet increases first and then fluctuates for all clouds examined with the increase of PM2.5 concentration. The PM2.5 concentration corresponding to the turning point of increases with the increasing LWP due to the increased chance of collision and coalescence. In contrast, the average cloud droplet and PM2.5 concentration show a negative correlation for clouds without drizzle, which is mainly caused by competition of water vapor. The quantitative ACI results show that the values of the aerosol first indirect effect are negative for most cases when considering all clouds examined, but positive when only considering clouds without drizzle.

Appraisal of COVID-19 lockdown and unlocking effects on the air quality of North India.

The COVID-19 pandemic lockdown supposedly provided a ‘window’ of reinstatement to natural resources including the air quality, but the scenario after the phased unlocking is yet to be explored. Consequently, here we evaluated the status of air quality during the 8th phase of unlocking of COVID-19 lockdown (January 2021) at three locations of North India. The first site (S1) was located at Punjab Agricultural University, Ludhiana-PPCB; the second site (S2) at Yamunapuram, Bulandshahr-UPPCB; and the third site (S3) at Okhla Phase-2, Delhi-DPCC. The levels of PM2.5 showed a significant increase of 525.2%, 281.2%, and 185.0% at sites S1, S2 and S3, respectively in the unlock 8 (January 2021), in comparison to its concentration in the lockdown phase. Coherently, the levels of PM10 also showed a prominent increase of 284.5%, 189.1%, and 103.9% at sites S3, S1, and S2, respectively during the unlock 8 as compared to its concentration in the lockdown phase. This rise in the concentration of PM2.5 and PM10 could be primarily attributed to the use of biomass fuel, industrial and vehicular emissions, stubble burning considering the agricultural activities at sites S1 and S2. Site S3 is a major industrial hub and has the highest population density among all three sites. Consequently, the maximum increase (295.7%) in the NO2 levels during the unlock 8 was witnessed at site S3. The strong correlation between PM2.5, PM10, and CO, along with the PM2.5/PM10 ratio confirmed the similar origin of these pollutants at all the three sites. The improvements in the levels of air quality during the COVID-19 lockdown were major overtaken during the various phases of unlocking consequent to the initiation of anthropogenic processes.

Spatiotemporal variation and source analysis of air pollutants in the Harbin-Changchun (HC) region of China during 2014–2020

This study analyzed the characteristics of air pollution and specific pollution periods within the Harbin-Changchun (HC) metropolitan area during 2014–2020. Regarding annual, seasonal, and monthly variations of the six pollutants, the change trend in 11 cities of HC showed strong consistency in spatial distribution. The western cities (Songyuan, Daqing, and Siping) were vulnerable to dust storms from Inner Mongolia. The concentrations of all air pollutants, except O3-8h, showed downward fluctuation trends from 2014 to 2018 and remained stable from 2018 to 2020 in terms of annual variations. The inter-annual trend of significant reductions in SO2 and SO2/PM2.5 during the heating period indicated that strict emission reduction measures posed by the government were highly successful. The ratio of PM2.5/SO2 was used to identify open biomass burning (OBB), which showed a double peak (October–November (Oct–Nov), March–April (Mar–Apr)). The burning prohibition shifted the OBB from Oct–Nov to Mar–Apr.

Three-Year Variations in Criteria Atmospheric Pollutants and Their Relationship with Rainwater Chemistry in Karst Urban Region, Southwest China

Air pollutants have been investigated in many studies, but the variations of atmospheric pollutants and their relationship with rainwater chemistry are not well studied. In the present study, the criteria atmospheric pollutants in nine monitoring stations and rainwater chemistry were analyzed in karst Guiyang city, since the time when the Chinese Ambient Air Quality Standards (CAAQS, third revision) were published. Based on the three-year daily concentration dataset of SO2, NO2, CO, PM10 and PM2.5, although most of air pollutant concentrations were within the limit of CAAQS III-Grade II standard, the significant spatial variations and relatively heavy pollution were found in downtown Guiyang. Temporally, the average concentrations of almost all air pollutants (except for CO) decreased during three years at all stations. Ratios of PM2.5/PM10 in non- and episode days reflected the different contributions of fine and coarse particles on particulate matter in Guiyang, which was influenced by the potential meteorological factors and source variations. According to the individual air quality index (IAQI), the seasonal variations of air quality level were observed, that is, IAQI values of air pollutants were higher in winter (worst air quality) and lower in summer (best air quality) due to seasonal variations in emission sources. The unique IAQI variations were found during the Chinese Spring Festival. Air pollutant concentrations are also influenced by meteorological parameters, in particular, the rainfall amount. The air pollutants are well scoured by the rainfall process and can significantly affect rainwater chemistry, such as SO42−, NO3−, Mg2+, and Ca2+, which further alters the acidification/alkalization trend of rainwater. The equivalent ratios of rainwater SO42−/NO3− and Mg2+/Ca2+ indicated the significant contribution of fixed emission sources (e.g., coal combustion) and carbonate weathering-influenced particulate matter on rainwater chemistry. These findings provide scientific support for air pollution management and rainwater chemistry-related environmental issues.

Air quality and particulate matter speciation in a beauty salon and surrounding outdoor environment: Exploratory study

Beauty salons are considered occupational environments where the staff personnel and clients are exposed to high levels of airborne pollutants. In this study, air quality monitoring was carried out in Léon, Spain. Temperature, relative humidity, CO2, CO and particulate matter were continuously monitored inside and outside areas of the salon. PM10 was simultaneously collected onto filters. Volatile organic compounds and carbonyls were sampled inside the salon. Indoor PM10 concentrations exceeded the recommended 24-h guideline of 50 μg m−3. A detailed PM10 chemical characterisation included organic and elemental carbon, trace elements, water-soluble ions and organic speciation. Indoor vs outdoor ratios of PM10, as well as the majority of PM10-bound organic compounds, were >1. During work periods, organic carbon accounted for 29.5 ± 1.8 and 16.2 ± 4.5 %wt. of PM10 indoors and outdoors, respectively. More than 200 individual organic compounds were detected in the PM10, including aliphatic alcohols, fatty acids, phthalates, glycerol derivatives, fatty acid alkyl esters, phenolic compounds, alkanes and polycyclic aromatic hydrocarbons, among others. Many of them are part of formulations widely used in hair cosmetics, personal care and cleaning products. Inadequate ventilation, working activities and the use of specific products can greatly contribute to high indoor levels of organic air pollutants. Formaldehyde revealed a cancer risk of 4.6 × 10−6, higher than the guideline level, suggesting a “possible risk” for workers. The total excess lifetime cancer risk from exposure to multiple compounds was 9.3 × 10−6, which is lower than the acceptable risk, but not negligible.

Long-Term Proactive Treatment of Plaque Psoriasis with Calcipotriene/Betamethasone Dipropionate Foam Prolongs Remission and Reduces Relapses Irrespective of Patient Baseline Characteristics.

IntroductionThe phase 3 PSO LONG study (NCT02899962) demonstrated superior efficacy of proactive (PM) versus reactive management (RM) using calcipotriene 0.005%/betamethasone dipropionate 0.064% (Cal/BD) foam in adults with psoriasis. Here, we evaluated whether certain baseline parameters had an effect on time to first relapse (TTFR), number of relapses, and assessed interactions between treatment effect.MethodsPSO LONG included an initial 4-week open-label phase (once-daily Cal/BD foam) and a 52-week maintenance phase where patients were randomized to twice-weekly Cal/BD (PM) or vehicle foam (RM), with a 4-week once-daily Cal/BD foam rescue treatment for relapse. Baseline parameters analyzed using a stepwise variable selection procedure included body surface area, modified Psoriasis Area Severity Index (mPASI), Physician Global Assessment (PGA), body mass index, age, sex, Dermatology Life Quality Index, and duration of psoriasis. Continuous variables were divided into groups based on standard criteria.ResultsOverall, the effect of treatment on TTFR did not vary across any baseline parameters. Variables with a statistically significant effect on TTFR were: treatment group (PM vs. RM hazard ratio [HR]: 0.56; p < 0.001); PGA (moderate vs. mild HR: 1.42; severe vs. mild HR: 2.32; overall p = 0.009); mPASI (moderate vs. mild HR: 1.19; severe vs. mild HR: 1.77; overall p = 0.009); and sex (women vs. men HR: 1.26; p = 0.030). Variables with a significant effect on the number of relapses were: treatment group (PM vs. RM, rate ratio [RR] 0.52; p < 0.001); PGA at baseline (moderate vs. mild, RR 1.38; severe vs. mild, RR 2.22; overall p < 0.001); and mPASI (moderate vs. mild, RR 1.25; severe vs. mild, HR 1.70; overall p = 0.002).ConclusionAll patients benefitted from long-term PM versus RM with Cal/BD foam regardless of baseline characteristics, and the benefit of treatment increased with greater disease severity.Trial RegistrationClinicalTrials.gov identifier, NCT02899962.

Analysis of weather condition on thermal behavior utilization in solar device

This article investigates the seasonal changes of particulate matter (PM) attentions, their connection by meteorological in 2020 at a rural location in South India called Amaravati. PM2.5, PM10 absorptions have main winter (54.6727.87 g/m3; 86.269.79 g/m3), lowermost monsoon (9.673.97 g/m3; 24.889.54 g/m3). In addition, the estimated PM2.5/PM10 ratio was 0.49, with a low contribution (0.39) in the monsoon and a high contribution (0.63) in the winter, indicating coarse and fine particle dominance, respectively. With a Pearson correlation coefficient of 0.96, the association between PM concentrations was determined to be strongly positive. However, the impact of PM concentrations on meteorological parameters found a negative correlation during the period of study. The polar bivariate plots exposed considerable influence on PM2.5, breezes blew since the north-westerly as well as southeasterly directions.