High Concentrations Of PM2 Research Articles

The Impact of Blood Lead and Its Interaction with Occupational Factors and Air Pollution on Hypertension Prevalence

Large-scale epidemiological studies on the association of blood lead levels with blood pressure and hypertension prevalence are still limited, particularly among lead-exposed workers. The evidence is even more scarce on the interaction of blood lead levels with occupational variables and ambient air pollution levels. We developed mixed-effect models based on a large group of lead-exposed workers (N = 22,002). The results were also stratified by multiple groupings. Compared to participants with blood lead < 20 μg/L, those with levels > 20 μg/L had a 26–37% higher prevalence of hypertension, as well as a 0.65–13.7mmHg higher systolic and diastolic blood pressure. Workers exposed to high PM10 levels had a 21–28% higher risk. Workers exposed to high temperatures had a 0.41–2.46 mmHg greater increase in blood pressure, and those not exposed to dust had a 1.29–1.65 mmHg greater blood pressure increase. Our findings suggested the negative impact of blood lead on blood pressure and the prevalence of hypertension, with workers exposed to high PM10 concentrations, those exposed to occupational high temperature, and those without dust exposure being more vulnerable.

Prenatal exposure to ambient fine particulate matter and child lung function in the CANDLE cohort

Background Ambient fine particulate matter (PM2.5) exposure adversely impacts child airway health; however, research on prenatal PM2.5 exposure, and child lung function is limited. We investigated these associations in the ECHO-PATHWAYS Consortium, focusing on the role of exposure timing during different phases of fetal lung development. Methods We included 675 children in the CANDLE cohort born between 2007 and 2011 in Memphis, TN, USA. Prenatal exposure to ambient PM2.5 was estimated using a spatiotemporal model based on maternal residential history and averaged over established prenatal periods of lung development. Forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) were measured by spirometry at age 8–9 years. We used linear regression and Bayesian Distributed Lag Interaction Models (BDLIM) to estimate associations between exposure and lung function z-scores, adjusting for maternal/child characteristics, prenatal/postnatal tobacco exposure, and birth year/season, and evaluating effect modification by child sex and allergic sensitization. Results The average ambient concentration of PM2.5 during pregnancy was 11.1 µg/m3 (standard deviation:1.0 µg/m3). In the adjusted linear regression and BDLIM models, adverse, but not statistically significant, associations were observed between exposure during the pseudoglandular (5–16 weeks of gestation) and saccular (24–36 weeks) phases of lung development and FEV1 and FVC. The strongest association was between a 2 μg/m3 higher concentration of PM2.5 during the saccular phase and FEV1 z-score (−0.176, 95% Confidence Interval [CI]: −0.361, 0.010). The FEV1/FVC ratio was not associated with PM2.5 in any exposure window. No effect modification by child sex or allergic sensitization was observed. Conclusions We did not find strong evidence of associations between prenatal ambient PM2.5 exposure and child lung function in a large, well-characterized study sample. However, there was a suggested adverse association between FEV1 and exposure during late pregnancy. The saccular phase of lung development might be an important window for exposure to PM2.5.

Seasonal Characteristics of Particulate Matter by Pollution Source Type and Urban Forest Type

To provide consistent air purification benefits from urban forests, it is crucial to identify common characteristics that allow for similar experimental setups. This study aimed to analyze PM10 concentrations in urban forests near pollution sources and understand their mitigation effects. Data from the Asian Initiative for Clean Air Networks, Korea, were used, focusing on three urban forests adjacent to road and industrial pollution sources in Korea, with PM10 concentrations collected during 2021. Considering high PM10 concentrations during winter and spring, these seasons were divided into two sub-periods, resulting in six seasonal periods for analysis. To address the right-skewed PM10 distribution and reduce outlier influence, the Kruskal–Wallis test was used. The results showed that “good” PM10 levels were lowest in early spring, increasing to a peak in summer before declining. High PM10 events were concentrated in spring, early spring, and early winter. The Kruskal–Wallis test indicated lower median PM10 concentrations in urban forests compared to pollution sources in the latter half of the year, while no significant median differences were found in the first half. Distribution visualizations further confirmed that even during high PM10 periods, all urban forests showed lower PM10 values compared to pollution sources. In conclusion, PM10 concentrations in urban forests were consistently lower than in pollution sources across all seasons, demonstrating their effectiveness in air purification at both road and industrial pollution sources. Future research should consider additional variables, such as PM2.5, to further explore differences between pollution sources.

Estimating the spatiotemporal distribution of PM2.5 concentrations in Tianjin during the Chinese Spring Festival: Impact of fireworks ban

Settingoff fireworks during the Spring Festival (SF) is a traditional practice in China. However, because of its environmental impact, the Chinese government has banned this practice completely. Existing evaluations of the effectiveness of firework prohibition policies (FPPs) lack spatiotemporal perspectives, making it difficult to comprehensively assess their effects on air quality. Consequently, this study used remote sensing technology based on aerosol optical depth and multiple variables, compared nine statistical learning methods, and selected the optimal model, transformer, to estimate daily spatiotemporal continuous PM2.5 concentration datasets for Tianjin from 2016 to 2020. The overall model accuracy reached a root mean square error of 15.30 μg/m³, a mean absolute error of 9.55 μg/m³, a mean absolute percentage error of 21.07%, and an R2 of 0.88. Subsequently, we analysed the variations in PM2.5 concentrations from three time dimensions–the entire year, winter, and SF periods–to exclude the impact of interannual variations on the experimental results. Additionally, we quantitatively estimated firework-specific PM2.5 concentrations based on time-series forecasting. The results showed that during the three years following the implementation of the FPPs, firework-specific PM2.5 concentrations decreased by 52.70%, 49.76%, and 86.90%, respectively, compared to the year before the implementation of the FPPs. Spatially, the central urban area and industrial zones are more affected by FPPs than the suburbs. However, daily variations of PM2.5 concentrations during the SF showed that high concentrations of PM2.5 produced in a short period will return to normal rapidly and will not cause lasting effects. Therefore, the management of fireworks needs to consider both environmental protection and the public's emotional attachment to traditional customs, rather than simply imposing a blanket ban on fireworks. We advocate improving firework policies in four aspects–production, sales, supervision, and control–to promote sustainable development of the ecological environment and human society.

Mapping air quality trends across 336 cities in India: Insights from three decades of monitoring (1987–2019)

Over a span of 34 years (1987–2019), an in-depth analysis of PM10, SO2, and NO2 trends across India was conducted using data from the National Ambient Air Quality Monitoring Programme’s manual monitoring stations in 336 cities. The study encompassed six geographical regions over three time blocks, revealing a correlation between the expansion of monitoring networks and the nation’s economic growth. Regions like the densely populated Indo-Gangetic Plains (IGP) and Central India consistently hosted more monitoring stations, while the Himalayan and Northeast regions saw substantial increases from initial scarcity. SO2 concentrations showed a declining trend, while NO2 levels remained relatively stable with intermittent fluctuations. Conversely, national average PM10 concentrations exhibited an upward trajectory, notably spiking by 128 % between 2006 and 2009 due to economic activities, construction, network expansion, the 2009 drought, and heightened coal consumption. Spatially, pollutant concentrations across three blocks demonstrated improved SO2 levels, several cities exceeding NO2 standards, and persistently high PM10 levels in the IGP. PM10 levels in block 3 were lower than in block 2, reflecting effective policy interventions. State rankings, however, did not consistently reflect pollutant trends across blocks. Regionally, the IGP consistently had the highest PM10 concentrations, while the Northeast recorded the lowest. Population-weighted exposure levels indicated an overall increase in public exposure to PM10. Analysis of major city per region aligned with national trends, as evidenced by Delhi (IGP), Guwahati (Northeast), Vadodara (Northwest), and Bhopal (Central) showing increased PM10 concentrations since 2006, followed by intermittent declines. In contrast, Shimla (Himalayan) and Chennai (Southern) exhibited distinct patterns. Major industrial cities such as Parwanoo, Bongaigaon, Angul and Talcher, and Visakhapatnam mirrored national trends, with PM10 levels rising since 2009, highlighting the significant impact of industrial activities on air quality. This research underscores the need for targeted, effective mitigation strategies based on spatial and temporal pollutant trends.

Contribution to the study of possible transport of PM10 aerosols in the eastern part of the Czech Republic

The article deals with the assessment of air pollution in the eastern regions of the Czech Republic: Moravia and Silesia, where the limits for the protection of human health for PM and benzo[a]pyrene are significantly exceeded, especially in the north-eastern area. The extent to which this heavily polluted part of Moravia and Silesia affects the central, southern and south-eastern parts of Moravia, i.e. south-eastern part of the Czech Republic, has often been discussed but not proven. The assessment demonstrated the influence and extent of pollutant transport by determining the prevailing daily wind direction. The prevailing NE wind direction results in worse dispersion conditions and higher PM10 concentrations throughout the study area. Conversely, the SW wind direction is a carrier of better dispersion conditions with lower PM10 concentrations in the area. The effect of transport of PM10 pollution in the daily type from the NE direction can be observed at those sites located in the NE of the area of interest from the border with Poland to the Prerov site. In the case of more southerly sites, the methodology used does not allow to determine whether and to what extent they are affected by pollution transport from the northeastern part of Moravia or from neighbouring Poland. This methodology is particularly useful when only 24-h pollutant concentrations are available (not at more detailed, e.g. 1-hour intervals). The internal methodology of the Czech Hydrometeorological Institutefor calculating back trajectories of wind from ground stations is particularly applicable for detecting the origin of short-term episodes with high pollutant concentrations.

Preoperative Exposure to Fine Particulate Matter and Risk of Postoperative Complications: A Single Center Observational Cohort Bayesian Analysis.

While exposure to fine particulate matter air pollution (PM 2.5 ) is known to cause adverse health effects, its impact on postoperative outcomes in US adults remains understudied. Perioperative exposure to PM 2.5 may induce inflammation that insidiously interacts with the systemic inflammatory response after surgery, leading to higher postoperative complications. We conducted a single center, retrospective cohort study using data from 64,313 surgical patients living along Utah's Wasatch Front and undergoing elective surgical procedures at a single academic medical center from 2016-2018. Patients' addresses were geocoded and linked to daily Census-tract level PM 2.5 estimates preoperatively. We hypothesized that elevated PM 2.5 concentrations in the seven days prior to surgery would be associated with an increase in a bundle of major postoperative complications. A hierarchical Bayesians regression model was fit adjusting for age, sex, season, neighborhood disadvantage, and the Elixhauser index of comorbidities. Postoperative complications increased in a dose-dependent manner with higher concentrations of PM 2.5 exposure, with a relative increase of 7% in the odds of complications for every 10ug/m3 increase in the highest single-day 24-hr PM 2.5 exposure during the 7 days prior to surgery. The association persisted after controlling for comorbidities and potential confounders; our inferences were robust to modeling choices and sensitivity analysis. In this large Utah cohort, exposure to elevated PM 2.5 concentrations in the week before surgery was associated with increased postoperative complications in a dose-dependent manner, suggesting a potential impact of air pollution on surgical outcomes. These findings merit replication in larger datasets to identify populations at risk and to define the interaction and impact of different pollutants. PM 2.5 exposure is a potential perioperative risk factor and, given the unmitigated air pollution in urban areas, a global health concern.

A long-term Doppler wind LiDAR study of heavy pollution episodes in western Yangtze River Delta region, China

Previous studies are primarily based on surface air pollution for a single event, leaving research on the temporal characteristics of aerosols and wind fields in the atmospheric boundary layer (ABL) and their associations unclear due to a lack of long-term vertical profile data. This study was the first to conduct long-term Doppler wind LiDAR measurements from Sep. 2019 to Aug. 2022 in Hefei in western Yangtze River Delta (YRD) region, China. The spatiotemporal characteristics of retrieved aerosol backscatter coefficient (β) and wind profiles were analyzed from the perspective of long-term statistics and typical heavy pollution episodes (HPEs). The seasonal profile of β showed a peak in the near-surface layer meanwhile the overall β profile (<0.5 km) was the highest in winter but lowest in summer. Combined with ground-based meteorological and air quality observations, 12 HPEs were identified and classified into dust-related events and fog-haze episodes. The results showed a consistency between hourly variations in PM10 (particulate matter smaller than 10 μm) concentration and β retrieved at 300 m during a high PM10 concentration (>150 μg/m3) period. Different roles of horizontal wind at different altitudes and its associated time delay effect on surface PM10 pollution were evaluated based on correlation coefficients (Ф) and air pollution diffusion conditions. Significant positive Ф values were noticed below 0.5 km during the entire dust-related EP4 and EP6, indicating that the higher wind speeds could exacerbate PM10 pollution. In contrast, large negative Ф values meant the removal of PM10 pollutants by strong winds below 0.8 km during 24 h after peak in EP3. Combining with backward trajectory analysis and meteorological condition, notable transboundary pollution with positive contributions from upper winds (>1.5 km) was discovered in dust-related EP1, EP4, EP7, EP9, and EP10. Time delay effect (1-h/2-h lag) of upper winds (>0.8 km) on surface PM10 pollution was explored in EP5, EP6, EP7, EP8, and EP9. In spring dust-related HPEs, surface PM10 pollution was mostly contributed by long-range transport of aerosol particles at higher altitudes (>1.5 km) from the northwest direction, driven by the Mongolian cyclone and the cold front system. Transboundary aerosols originated from the northern part of Anhui province and the YRD region in the middle altitudes (∼0.5 km) was the main contributor to fog-haze HPEs. The findings demonstrated the ability of the real-time Doppler wind LiDAR system to monitor transboundary air pollution and provided a scientific reference for policy makers.

Drivers of High Concentration and Dispersal of PM10 and PM2.5 in the Eastern Part of Chhota Nagpur Plateau, India, Investigated Through HYSPLIT Model and Improvement of Environmental Health Quality

ABSTRACTThe ambient air quality is continuously declining especially in emerging countries because of rapid rate of urbanization, industrialization, and allied activities. Thus, the principal objective of this research is to inspect the spatiotemporal variation of particulate matters and to identify the drivers of pollutant dispersal. The month‐wise PM10 and PM2.5 data of 2022 and 2023 were obtained from the West Bengal Pollution Control Board. Meteorological datasets such as wind speed (m/s) and wind direction (degree) were collected from the NASA power access website. The HYSPLIT (Hybrid Single‐Particle Lagrangian Integrated Trajectory) model was applied to identify the pollutant's trajectories. Results showed that Purulia station stood highest in case of absolute AQI 715 (23‐1‐2022 at 7 a.m.), PM2.5 483.47 µg/m3 (23‐1‐2022 at 8 a.m.), and PM10 682.28 µg/m3 (23‐1‐2022 at 7 a.m.), respectively. During winter, the vertical expansion of particles was within the 100‐m boundary layer while during summer, it dispersed vertically and crossed 2000 m above the ground surface due to the combined effect of atmospheric conditions such as wind speed, wind direction, air pressure, and temperature. Moreover, the industrial outputs of Jharkhand and West Bengal play a significant role in elevating the pollution level. Plantation of suitable pollution‐resistant plants including Banyan (Ficus bengalensis), Mango (Mangifera indica), Peepul (Ficus religiosa), Guava (Psidium guajava), Kadam (Neolamarkia cadamba), Neem (Azadirachta indica) is a suitable management technique against pollution in this region.

Estimation of Particulate Matter (PM10) Over Middle Indo-Gangetic Plain (Patna) of India: Seasonal Variation and Source Apportionment

Despite extensive research on particulate matter (PM) pollution in India’s Indo-Gangetic Plain (IGP), source apportionment remains challenging. This study investigates the effect of particulate matter (PM10)-associated water soluble inorganic ions (WSIIs) on ambient air concentration across the middle IGP from January to December 2018. Moreover, the seasonal fluctuation and chemical characterization of PM10 were assessed for the year 2018. The results revealed a high concentration of PM10 (156 µg/m3), exceeding the WHO and National Ambient Air Quality Standard (NAAQS) limits. The highest PM10 levels were observed during autumn, winter, summer, and the rainy season. The study identified SO42− and NH4+ as the most common WSIIs, constituting 46% and 23% of the total WSIIs. Source apportionment analysis indicated that street dust, biomass burning, and vehicle and industrial emissions together with secondary formation significantly contributed to IGP’s PM pollution. Additionally, the investigation of air mass back trajectory suggests that air quality in IGP is largely influenced by eastern and western Maritime air masses originated from the Arabian Sea, the Bay of Bengal, Gujarat, Afghanistan, Pakistan, and Bangladesh.

Decreasing trends in PM2.5 and BC concentrations observed on central and southwestern Japanese Islands

The interannual trends in fine particulate matter (PM2.5) and black carbon (BC) concentrations at remote stations in central (Noto) and southwestern (Fukue) Japan were investigated using statistical trend analysis and the chemical transport model, Regional Air Quality Model 2 (RAQM2ver3). The concentrations of PM2.5 and BC in Noto and Fukue exhibited seasonal variations and decreased from 2013 to 2020. Higher concentrations of PM2.5 and BC were observed during the spring season (April) in both locations. The PM2.5 concentrations peaked in Fukue approximately one month earlier than in Noto, while the BC concentration peak in Noto occurred one month earlier than that of PM2.5. The total reductions in PM2.5 concentrations in Noto and Fukue were 7.5 ± 5.0 and 3.8 ± 0.95 μg m−3, corresponding to reduction rates 1.1 ± 0.7 and 0.5 ± 0.95 μg m−3year−1, respectively, compared to the concentrations in 2013. The total reduction in BC concentrations in Noto from 2013 to 2019 was estimated to be 0.13 ± 0.1 μg m−3, amounting to 0.018 ± 0.014 μg m−3year−1 reduction rate. The results of the source–receptor relationships analysis suggest that the decreases in PM2.5 and BC concentrations in Fukue and Noto were significantly influenced by reductions in amounts transported from central China (CCHN, 30–40°N), northern China (NCHN, >40°N) and Japan (JPN) after 2015/2016. The decrease in emissions from these three regions accounted for the observed reductions in particulate concentrations.

Quantitative analysis of aeolian dust incidence and diagnosis using a dynamic Bayesian network model: A case study of estuary area in central Taiwan

The presence of high concentrations of PM10 in aeolian dust within the estuary area of central Taiwan has been a focal point for air quality protection and remediation efforts over the past 15 years. This study explores the quantitative analysis of aeolian dust occurrences concerning various levels of PM10 concentration, aiming to offer early warning information to local communities and government agencies. Employing Dynamic Bayesian network (DBN) models, the research interrelates conditional probability dependencies among air quality and meteorological factors monitored in the downstream area of the Jhuoshuei River, predicting the probability distribution of aeolian dust events. The constructed DBNs demonstrate the inference of probability distributions of meteorological factors' states based on PM10 concentrations, enabling diagnostic analysis of meteorological conditions during high PM10 concentration dust events. The DBN models exhibit robust predictive ability, achieving an overall accuracy of 85.72% in validation and 85.8% in testing, with high discriminatory capacity that the area under the receiver operating characteristic curve (AUC) values of 0.924 and 0.915 during validation and testing, respectively. Sensitivity analysis highlights wind direction, wind speed, relative humidity as significant factors affecting PM10 concentrations. The probability of low PM10 concentrations was notably higher compared to higher concentrations, indicating effective aeolian dust remediation efforts. However, attention is warranted toward the 10% incidence of aeolian dust events deemed unhealthy or hazardous to human health. Diagnosis of meteorological conditions during high PM10 concentration events suggests low temperature, high wind speeds, and dry conditions, particularly with northeastern or southwestern winds, as conducive factors. This study underscores the physical relationship between meteorological factors and PM10 concentrations, employing DBNs to consider temporal relationships and uncertainties in data, aligning with human health impact standards proposed by the Ministry of Environment. Future research should incorporate soil and land surface conditions to provide a more comprehensive understanding of aeolian dust dynamics and mitigation strategies.

Particle-ozone complex pollution under diverse synoptic weather patterns in the Yangtze River Delta region: Synergistic relationships and the effects of meteorology and chemical compositions

There is considerable academic interest in the particle-ozone synergistic relationship (PO) between fine particulate matter (PM2.5) and ozone (O3). Using various synoptic weather patterns (SWPs), we quantitatively assessed the variations in the PO, which is relevant to formulating policies aimed at controlling complex pollution in the air. First, based on one-year sampling data from March 2018 to February 2019, the SWPs classification of the Yangtze River Delta (YRD) was conducted using the sum-of-squares technique (SS). Five dominant SWPs can be found in the YRD region, including the Aleutian low under SWP1 (occurring 45 % of the year), a tropical cyclone under SWP2 (21 %), the tropical cyclone and western Pacific Subtropical High (WPSH) under SWP3 (15.4 %), the WPSH under SWP4 (6.9 %), and a continental high pressure under SWP5 (3.1 %). The phenomenon of a “seesaw” between PM2.5 and O3 concentrations exhibited significant spatial heterogeneity, which was influenced by meteorological mechanisms. Second, the multi-linear regression (MLR) model and the partial correlation (PCOR) analysis were employed to quantify the effects of dominant components and meteorological factors on the PO. Meteorological variables could collectively explain only 33.0 % of the PM2.5 variations, but 58.0 % for O3. O3 promoted each other with low concentrations of PM2.5 but was inhibited by high concentrations of PM2.5. High relative humidity (RH) was conducive to the generation of PM2.5 secondary components and enhanced the radiative effects of aerosols and the negative correlation of PO. In addition, attention should be paid to assessing the combined effects of precursor levels, weather, and chemical reactions on the particle-ozone complex pollution. The control of O3 pollutants should be intensified in summer, while the focus should be on reducing PM2.5 pollutants in winter. Prevention and control measures need to reflect the differences in weather conditions and pollution characteristics, with a focus on RH and secondary components of PM2.5.

Enhancing fine particle removal by electrostatic precipitation from flue gas with a high PM concentration: Effect of various electrode configurations

Particle pollution has hazardous effects on air quality and human health, especially fine particle. However, the highly efficient removal of fine particles is an unsolved problem in electrostatic precipitators (ESPs). In this study, a transparent ESP was designed to investigate the effect of fine particles on the corona discharge performance and the role of ionic wind in particle migration. And five types of typical discharge electrodes were applied. The results showed that the presence of fine particles could weaken the corona current produced by electrode discharge. Among these electrodes, the spike electrode can reduce the adverse effect of the particle space charge. The maximum ionic wind velocity around the electrode tips and within the near-plate region could reached 5.67 m/s and 5.00 m/s under an applied voltage of 30 kV, respectively. Combining the effects of corona discharge and ionic wind, the collection efficiencies of fine particles decreased in the following order: spike electrode (medium needle) > spike electrode (longest needle) > arista electrode > spike electrode (shortest needle) > sawtooth electrode. In general, spike electrode discharge has better performance for particle charging and particle collection efficiency and is suitable for fine particle removal in ESPs. In addition, electrode configuration/arrangement optimization methods were proposed to enhance fine particle removal in ESPs.

Assessing health risks from bioaccessible PM2.5-bound toxic metals in Nanchang metro: Implications for metro workers and emissions control

High concentrations of PM2.5 with enriched levels of metallic constituents could significantly affect the health and comfort of metro employees. To avoid overestimating the exposure risks, we investigated the bioaccessibility of toxic metals (TMs) bound in PM2.5 from the Nanchang metro using Gamble's solution method, and qualitatively analyzed the impact of valence state and various sources on the bioaccessibility of TMs bound to PM2.5. The results showed that the bioaccessibility of the studied TMs ranged from 2.1% to 88.1%, with As, Ba, Co and Pb being the most bioaccessible and V, Fe and Cr being the less bioaccessible. The bioaccessibility of TMs in our subway PM2.5 samples varied based on their valence and species, showing higher valence states associated with increased bioaccessibility. Vehicle traffic, secondary aerosols and wheel/rail sources were found to be significantly and positively associated with the bioaccessibility of several TMs, implying a severe potential risk from these three sources. Although both non-carcinogenic and carcinogenic risks associated with total TMs were found to be high, only As and Cr(VI) posed a considerable carcinogenic risk to metro workers based on the bioaccessible fractions and were therefore priority pollutants. In addition, potential carcinogenic risk was found to be more severe in platform than that in ticket counter. The results indicate that considerable efforts are required to control and manage PM2.5 and the associated TMs in the Nanchang subway, particularly from traffic, wheel/rail and secondary sources, to protect the health of metro staff and the public.

Phenomenology of the Composition of PM2.5 at an Urban Site in Northern France

In this work, PM2.5 was sampled at Dunkerque, a medium-sized city located in northern France. The mean concentration of PM2.5 during the sampling period was 12.6 ± 9.5 μg·m−3. Samples were analyzed for elemental and organic carbon (EC/OC), water-soluble organic carbon (WSOC), humic-like substances (HULIS-C), water-soluble inorganic ions, and major and trace elements. The origin and the variations of species concentrations were examined using elemental enrichment factors, bivariate polar plot representations, and diagnostic concentration ratios. Secondary inorganic ions were the most abundant species (36% of PM2.5), followed by OC (12.5% of PM2.5). Secondary organic carbon (SOC) concentrations were estimated to account for 52% of OC. A good correlation between SOC and WSOC indicated that secondary formation processes significantly contribute to the WSOC concentrations. HULIS-C also represents almost 50% of WSOC. The determination of diagnostic ratios revealed the influence of anthropogenic emission sources such as integrated steelworks and fuel oil combustion. The clustering of 72 h air masses backward trajectories data evidenced that higher concentrations of PM2.5, OC, and secondary inorganic aerosols were recorded when air masses came from north-eastern Europe and the French continental sector, showing the considerable impact of long-range transport on the air quality in northern France.

Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China.

The evidence on the effects of extreme meteorological conditions and high air pollution levels on incidence of hand, foot and mouth disease (HFMD) is limited. Moreover, results of the available studies are inconsistent. Further investigations are imperative to elucidate the specific issue. Data on the daily cases of HFMD, meteorological factors and air pollution were obtained from 2017 to 2022 in Jining City. We employed distributed lag nonlinear model (DLNM) incorporated with Poisson regression to explore the impacts of extreme meteorological conditions and air pollution on HFMD incidence. We found that there were nonlinear relationships between temperature, wind speed, PM2.5, SO2, O3 and HFMD. The cumulative risk of extreme high temperature was higher at the 95th percentile (P95th) than at the 90th percentile(P90th), and the RR values for both reached their maximum at 10-day lag (P95th RR = 1.880 (1.261-2.804), P90th RR = 1.787 (1.244-2.569)), the hazardous effect of extreme low temperatures on HFMD is faster than that of extreme high temperatures. The cumulative effect of extreme low wind speeds reached its maximum at 14-day lag (P95th RR = 1.702 (1.389-2.085), P90th RR = 1.498(1.283-1.750)). The cumulative effect of PM2.5 concentration at the P90th was largest at 14-day lag (RR = 1.637 (1.069-2.506)), and the cumulative effect at the P95th was largest at 10-day lag (RR = 1.569 (1.021-2.411)). High SO2 concentration at the P95th at 14-day lag was associated with higher risk for HFMD (RR: 1.425 (1.001-2.030)). Our findings suggest that high temperature, low wind speed, and high concentrations of PM2.5 and SO2 are associated with an increased risk of HFMD. This study not only adds insights to the understanding of the impact of extreme meteorological conditions and high levels of air pollutants on HFMD incidence but also holds practical significance for the development and enhancement of an early warning system for HFMD.

Deep energy renovations’ impact on indoor air quality and thermal comfort of residential dwellings in Ireland – ARDEN project

As Europe's residential energy renovation programmes accelerate, field studies assessing their impact on indoor environmental quality are required to ensure maximum co-benefits to occupants' health and wellbeing. In this work, we evaluated the impact of deep energy renovation (DER) on indoor air quality (IAQ), ventilation, and thermal comfort in a sample of Irish homes (n = 12). Indoor air pollutants (IAPs), including particulate matter (PM2.5), carbon dioxide (CO2), carbon monoxide (CO), formaldehyde, radon, nitrogen dioxide (NO2), and BTEX, were measured pre and post DER. Performance of the newly installed mechanical ventilation systems was also assessed. Questionnaires and diaries were used to collect feedback regarding the retrofit and occupant activities. All occupants reported high levels of satisfaction with thermal comfort, and homes were significantly warmer post-retrofit (p < 0.0001). The DER improved indoor CO2 concentrations, indicating a positive impact on residential ventilation. However, many bedrooms were still under ventilated. PM2.5 (p < 0.0001) and formaldehyde (p < 0.05) concentrations increased post-retrofit. Higher concentrations of PM2.5 were most likely due to a combination of factors including inadequate ventilation, ingress from outdoors via open windows or doors, presence of a wood burning stove and other occupant activities. Retrofits were observed to have poor compliance with ventilation recommendations. Greater emphasis on pollutant source control along with proper installation and maintenance of mechanical ventilation systems is required to ensure DERs lead to sustainable and healthy homes.

European air quality in view of the WHO 2021 guideline levels: Effect of emission reductions on air pollution exposure

Although anthropogenic emissions have decreased during the last 2 decades, air pollution is still problematic in Europe. This study analyzes the air quality in Europe using simulations by EURopean Air pollution Dispersion—Inverse Model for the year 2016 with updated emissions in view of the annual guideline levels for particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) released in 2021 by the World Health Organization (WHO). Three different emission scenarios are applied, including a scenario for the committed emission reductions from the European Union (EU), a scenario including additional reductions to specifically mitigate PM2.5, and a scenario in which all anthropogenic emissions are eliminated. Model results show that in Europe, the concentrations of PM2.5 and NO2 exceed the annual WHO guideline levels by up to a factor of 5.6 and 5.2, respectively, in the main polluted regions and by up to a factor of 2 for O3 in Southern Europe. High concentrations of PM2.5 and O3 are homogeneously distributed across Europe with 99% and 100% of the European population exposed to concentrations above the WHO guideline levels, respectively. NO2 concentrations above the annual WHO guideline level are primarily found in populated areas, affecting 323 million inhabitants in 2016. Although the emission scenario designed to mitigate PM2.5 shows a decrease of the highest annual mean concentrations of PM2.5 from 28 µgm−3 to 12 µgm−3, 527 million European inhabitants remain affected by PM2.5 annual mean concentrations above the WHO guideline level. Seasonal mean O3 concentrations after eliminating all anthropogenic emissions (between 60 and 82 µgm−3) are found to be above the WHO guideline level for the entire European continent. The mortality attributable to air pollution is reduced by 47% in the emission scenario for committed emissions by the EU. In the more aggressive scenario designed to mitigate PM2.5, the mortality is reduced by 72%. The study reveals that the emission scenarios and, therefore, the reduction in premature deaths are subject to sectoral emission reductions between 41% and 79%.

Nitrate formation mechanisms causing high concentration of PM2.5 in a residential city with low anthropogenic emissions during cold season

During the cold season in South Korea, NO3− concentrations are known to significantly increase, often causing PM2.5 to exceed air quality standards. This study investigated the formation mechanisms of NO3− in a suburban area with low anthropogenic emissions. The average PM2.5 was 25.3 μg m−3, with NO3− identified as the largest contributor. Ammonium-rich conditions prevailed throughout the study period, coupled with low atmospheric temperature facilitating the transfer of gaseous HNO3 into the particulate phase. This result indicates that the formation of HNO3 played a crucial role in determining particulate NO3− concentration. Nocturnal increases in NO3− were observed alongside increasing ozone (O3) and relative humidity (RH), emphasizing the significance of heterogeneous reactions involving N2O5. NO3− concentrations at the study site were notably higher than in Seoul, the upwind metropolitan area, during a high concentration episode. This difference could potentially attributed to lower local NO concentrations, which enhanced the reaction between O3 and NO2, to produce NO3 radicals. High concentrations of Cl− and dust were also identified as contributors to the elevated NO3− concentrations.