High Concentrations Of Air Pollutants Research Articles

Impact of air pollution: tourists’ decision making behaviour during rural tourism

In recent years, the increasingly severe air pollution has not only posed a threat to residents’ health but also had a significant influence on tourists’ travel decision making behaviours. This study utilised empirical dynamic model–long short-term memory model to predict air pollutant concentrations in Xidi Village, China, and investigated their impact on tourists’ travel decisions. According to the results, there is a negative correlation between air quality and air quality index (AQI). The lowest AQIs were recorded in May and August 2022, with visitor numbers reaching 12 305 and 11 705, respectively. During the period from May to October, except for ozone (O3), which reached a maximum concentration of 157 μg/m3, all other pollutant concentrations remained at low levels. According to the predictions of the model, Xidi Village often experiences high concentrations of air pollutants during the spring and winter seasons, leading to hazy weather. This information provides accurate air quality data for tourists, helping them avoid periods of severe pollution at their travel destinations and reducing travel risks.

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

High concentrations of air pollutants could affect crop yield directly via influencing crop physiology and indirectly via regulating climate conditions. How multiple air pollutants affect crop yields directly and indirectly remains elusive in the North China Plain (NCP), which is the hotspot of air pollution and crop production. Here, we construct data-driven models to quantify the indirect effects of four major air pollutants on the yields of winter wheat and summer maize through modulating climate variations in the NCP during 2005–2020. Our results show that wheat has a greater negative sensitivity to absorbing aerosol optical thickness (AAOD), ozone concentration (O3), sulfur dioxide concentration (SO2) and nitrogen dioxide concentration (NO2) than maize. The indirect effects of AAOD, O3 and SO2 in November and O3 in April control wheat yield variation, while the indirect effects of AAOD and O3 in June, O3 and SO2 in July, O3 and NO2 in August, and O3 in September dominate maize yield variation. Our results emphasize the indirect effects of air pollutants on crop yield via regulating climate variations, which has great implications for improving our understanding of air pollution-climate-crop interactions and guiding targeted adaptation and mitigation efforts.

Solving the mysteries of Lahore smog: the fifth season in the country

South Asian smog is an annually recurring air pollution event that is characterized by high concentrations of air pollutants, low visibility, and severe socio-economic disruptions. It is most frequently observed across the north-western parts of the Indo-Gangetic Plains (IGP). Since 2016, it has become so frequent and pervasive that they are colloquially referred to as “the fifth season” in the region. During this season populations residing in this area including cities such as Lahore, Amritsar, Faisalabad, Multan, Delhi etc. are exposed to hazardous levels of air pollution. This study attempts to understand the reasons for the recent increase in the intensity and frequency of intense air pollution episodes by utilizing ground-based and satellite observations. Time-series analysis, seasonal and annual variations in PM2.5 and AOD were carried out. Satellite data of UVAAI, CO, and fire count were used to determine the fire incidences and aerosol characterization. The results indicate that during the last decade, there has been an increase in air pollution sources while crop residue burning, and motor vehicles have greatly contributed to the increased frequency and intensity of such events. The meteorological and topographical data analysis revealed that the IGP provides ample cloud-condensation nuclei and optimum conditions for the accumulations of pollutants, especially in the post-monsoon and winter periods. The Mann-Kendall test was performed to confirm the annual and seasonal trends of PM2.5. The major cities of South Asia such as Lahore, Delhi, Kathmandu, and Dhaka have recently shown a decreasing trend with respect to annual AOD. However, an increase has been observed for the period of post-monsoon especially for cities of Lahore and Delhi. To distinguish potential sources of air pollutants during extreme smog episodes in the region, Analytical Hierarchy Process (AHP) was conducted to estimate the most contributing factors to the annual smog episodes. According to the data, the transboundary pollution resulting from open-field agriculture fires has been assigned moderate importance over vehicular emissions. A HYSPLIT trajectory model coupled with ground observations and satellite data shows that the agricultural fires do have a profound impact on the air quality of the region. It highlights the importance of transboundary pollution and cooperation among cities, regions, and countries across the shared airshed of the Indo-Gangetic Plains.

A seven-year-based characterization of aerosol light scattering properties at a rural central European site

Our study investigates the temporal variability of aerosol light scattering properties measured at three wavelengths (total scattering coefficient, backscattering coefficient, Ångström scattering exponent, hemispheric backscattering ratio and asymmetry parameter) at the rural background site of the National Atmospheric Observatory Košetice over a period of over seven years (2012–2019). The influence of fog and cloudiness on aerosol light scattering properties (ASP), together with their comparison to particle number size distribution was also investigated. The overall medians of total scattering (σsp) and backscattering coefficient (σbsp), hemispheric backscattering ratio (b) and asymmetry parameter (g) measured at 550 nm and Ångström scattering exponent (SAE_450/700) were 35.20 Mm−1, 5.07 Mm−1, 0.14 and 0.57 and 1.82, respectively. σsp and g decreased by 2.05 Mm−1/year, and 0.009/year, respectively, whereas b increased by 0.004/year. The selected aerosol properties were strongly correlated with particle number, mass, area and volume concentrations in the 200–800 nm mode. A decrease in SAE_450/700 implies a shift towards larger particle sizes, and evolutions in b and g suggest a higher backscattering portion to total scattering. The highest σsp and σbsp levels were observed in the cold seasons together with higher concentrations of air pollutants (carbonaceous aerosol, SO2 and NOx). This could be explained by enhanced emissions from human activities such as domestic heating combined with the higher stability of the atmosphere (poor atmospheric dispersion). In the summer, decreases in particle size and higher rates of backscatter fraction were attributed to secondary organic aerosol (SOA) formation. The accumulation mode showed the strongest aerosol scattering potential, with SAE_450/700 values < 2. Aerosol light scattering was significantly higher during overcast and foggy days compared to fine, cloudy, partly cloudy and no-fog days, possibly due to the particle hygroscopic growth under high relative humidity (shift of particle size towards larger sizes), which in turn can lead to a lower aerosol backscattering fraction. Source identification linked the changes in ASP to the synoptic situation over Europe rather than to specific sources of pollution.

Comorbid asthma is associated with rhinitis severity in children exposed to air pollutants.

The impact of asthma on the severity of rhinitis when children with allergic rhinitis (AR) are exposed to air pollutants has not been studied. Children with AR (65 with asthma, 208 without asthma), aged 6-13 years, were recruited from a hospital in Taichung, Taiwan, between 2007 and 2011. Correlations between Pediatric-Rhinoconjunctivitis-Quality-of-Life score, nasal peak expiratory flow, and air pollutants were compared. With the same age, research time, and form the same city, children with AR (660 with asthma, 3174 without asthma) were selected from a database. Correlations between clinical visit times for AR and air pollutants were compared. In male children with AR and asthma, both clinical and database studies revealed a correlation between higher rhinitis discomfort (quality-of-life score), higher visit times for AR, and higher PM10, PM2.5, NO2, NMHC concentrations. Correlations between higher nasal inflammation/obstruction (lower expiratory flow) and higher air pollutant concentrations were observed in male children with AR and asthma. In children with AR, comorbid asthma was associated with increased rhinitis severity when they were exposed to air pollutants, and the association was only noted in males. Increased nasal obstruction/inflammation from exposure to air pollutants may be the mechanisms underlying this association. The influence of asthma on the severity of rhinitis when children with allergic rhinitis (AR) are exposed to air pollutants has not been studied. In children with AR, the correlation between higher rhinitis discomfort, higher number of clinical visits for AR, and higher PM10, PM2.5, NO2, NMHC concentrations were only noted in those who also had asthma. The correlation was only noted in male. Comorbid asthma was associated with higher rhinitis severity when children with AR are exposed to air pollutants The association was only noted in male.

A DYNAMIC SPATIAL FILTERING APPROACH TO MITIGATE UNDERESTIMATION BIAS IN FIELD CALIBRATED LOW-COST SENSOR AIR POLLUTION DATA.

Low-cost air pollution sensors, offering hyper-local characterization of pollutant concentrations, are becoming increasingly prevalent in environmental and public health research. However, low-cost air pollution data can be noisy, biased by environmental conditions, and usually need to be field-calibrated by collocating low-cost sensors with reference-grade instruments. We show, theoretically and empirically, that the common procedure of regression-based calibration using collocated data systematically underestimates high air pollution concentrations, which are critical to diagnose from a health perspective. Current calibration practices also often fail to utilize the spatial correlation in pollutant concentrations. We propose a novel spatial filtering approach to collocation-based calibration of low-cost networks that mitigates the underestimation issue by using an inverse regression. The inverse-regression also allows for incorporating spatial correlations by a second-stage model for the true pollutant concentrations using a conditional Gaussian Process. Our approach works with one or more collocated sites in the network and is dynamic, leveraging spatial correlation with the latest available reference data. Through extensive simulations, we demonstrate how the spatial filtering substantially improves estimation of pollutant concentrations, and measures peak concentrations with greater accuracy. We apply the methodology for calibration of a low-cost PM2.5 network in Baltimore, Maryland, and diagnose air pollution peaks that are missed by the regression-calibration.

Exposure to Multiple Air Pollutants and the Risk of Fractures: A Large Prospective Population-Based Study.

Atmospheric chemistry studies suggest air pollution impedes ultraviolet B photons and thus reduces cutaneous vitamin D3 synthesis. Biological evidence shows that inhaled pollutants disrupt circulating 25-hydroxyvitamin D (25[OH]D) metabolism and ultimately impact bone health. The hypothesis is that higher air pollution concentrations are associated with a higher risk of fractures, mediated by lower circulating 25(OH)D. The study included participants of the UK Biobank who were free of fracture history at enrollment (2006 to 2010) and analyzed their environmental exposure data (2007 to 2010). Air pollution measurements included the annual averages of air particulate matter (PM2.5 , PM2.5-10 , and PM10 ), nitrogen oxides (NO2 and NOx ), and a composite air pollution score. Multivariable Cox proportional hazard models were used to assess the associations of the individual pollutants and the score with fracture risks. Mediation analyses were conducted to assess the underlying role of serum 25(OH)D in such associations. Among 446,395 participants with a median of 8-year follow-up, 12,288 incident fractures were documented. Participants living in places with the highest quintile of air pollution score had a 15.3% increased risk of fractures (hazard ratio [95%CI]: 1.15[1.09,1.22]) compared to those in the lowest, and 5.49% of this association was mediated through serum 25(OH)D (pmediation  < 0.05). Pollutant-specific hazard of top-to-bottom quintiles was 16% for PM2.5 , 4% for PM2.5-10 , 5% for PM10 , 20% for NO2 , and 17% for NOx , with a 4% to 6% mediation effect of serum 25(OH)D concentrations. The associations of the air pollution score with fracture risks were weaker among female participants, those who drank less alcohol, and consumed more fresh fruit than their counterparts (pinteraction  < 0.05). © 2023 American Society for Bone and Mineral Research (ASBMR).

Towards healthy and energy-efficient buildings in the context of Egypt: Modelling demand-controlled ventilation to improve the indoor air quality in a generic office space in Cairo

Cairo is characterised by high concentrations of ambient air pollutants, especially air particulate matter of diameter less than 2.5 micrometre (PM2.5). Many studies have emphasized the impact of PM2.5 on people’s health and wellbeing including a World Bank report that has attributed 12% of the total annual deaths in Cairo to the exposure to ambient PM2.5. On one hand. improving the energy efficiency of buildings may involve implementing energy efficiency measures that aim to achieve indoor thermal comfort by maximizing the use of natural ventilation and minimizing mechanical air-conditioning. However, while natural ventilation can help reduce CO2 levels, it can also potentially lead to an increase in indoor PM2.5 levels. This study aims to investigate the impact of multiple air filtration scenarios on the energy consumption and the indoor air quality for a shoebox model that aims to represent generic offices Cairo. The study uses EnergyPlus simulations that leverage an Energy Management System script to model the demand-controlled ventilation, apply air filters when required, and simulate the increase in energy use due to the relevant pressure drops in the air system. The results for the scenarios investigated in the study highlighted that air filters can reduce the average indoor PM2.5 levels by nearly 40% during occupancy hours while causing an estimated increase of around 2-7% in the total operational energy. Given data and assumptions relevant to the study context, it was found that filtering the recirculated air while minimizing the introduction outdoor fresh air can be sufficient to minimize indoor PM2.5 levels.

Spatiotemporal association between air pollution and stroke mortality in South Korea

BackgroundAir pollutant concentrations in South Korea vary greatly by region and time. To assess temporal and spatial associations of stroke subtypes with long-term air pollution effects on stroke mortality, we studied ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). MethodsThis was an observational study conducted in South Korea from 2001–2018. Concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter ≤10 µm in diameter (PM10) were determined from 332 stations. Average air pollutant concentrations in each district were determined by distance-weighted linear interpolation. The nationwide stroke mortality rates in 249 districts were obtained from the Korean Statistical Information Service. Time intervals were divided into three consecutive 6-year periods: 2001–2006, 2007–2012, and 2013–2018. ResultsThe concentrations of air pollutants gradually decreased from 2001–2018, along with decreases in IS and ICH mortality rates. However, mortality rates associated with SAH remained constant. From 2001–2006, NO2 (adjusted odds ratio [aOR]:1.13, 95% confidence interval: 1.08–1.19), SO2 (aOR: 1.10, 1.07–1.13), and PM10 (aOR: 1.12, 1.06–1.18) concentrations were associated with IS mortality, and SO2 (aOR: 1.07, 1.02–1.13) and PM10 (aOR:1.11,1.06–1.22) concentrations were associated with SAH-associated mortality. Air pollution was no longer associated with stroke mortality from 2007 onward, as the air pollution concentration continued to decline. Throughout the entire 18-year period, ICH-associated mortality was not associated with air pollution. ConclusionsConsidering temporal and spatial trends, high concentrations of air pollutants were most likely to be associated with IS mortality. Our results strengthen the existing evidence of the deleterious effects of air pollution on IS mortality.

Relative contributions of ambient air and internal sources to multiple air pollutants in public transportation modes

Commuters are often exposed to relatively high air pollutant concentrations in public transport microenvironments (TMEs) because of their proximity to emission sources. Previous studies have mainly focused on assessing the concentrations of air pollutants in TMEs, but few studies have distinguished between the contributions of ambient air and internal sources to the exposure of commuters to air pollutants. The main objective of this study was to quantify the contributions of ambient air and internal sources to the measured particulate matter and gaseous pollutant concentrations in selected TMEs in Hong Kong, a high-rise, high-density city in Asia. A sampling campaign was conducted to measure air pollutant concentrations in TMEs in Hong Kong in July and November 2018 using portable air quality monitors. We measured the concentrations of each pollutant in different TMEs and quantified the infiltration of particulate matter into these TMEs. The double-decker bus had the lowest particulate matter concentrations (mean PM1, PM2.5, and PM10 concentrations of 5.1, 9.5, and 13 μg/m3, respectively), but higher concentrations of CO (0.9 ppm), NO (422 ppb), and NO2 (100 ppb). For all the TMEs, about half of the PM2.5 were PM1 particles. The Mass Transit Railway (MTR) subway system had a PM2.5/PM10 ratio of about 0.90, whereas the PM2.5/PM10 ratio was about 0.60–0.70 for the other TMEs. The MTR had infiltration factor estimates <0.4 for particulate matter, lower than those of the double-decker bus and minibus. The MTR had the highest contribution from internal sources (mean PM1, PM2.5, and PM10 concentrations of 4.6, 13.4, and 15.8 μg/m3, respectively). This study will help citizens to plan commuting routes to reduce their exposure to air pollution and help policy-makers to prioritize effective exposure reduction strategies.

Early life PM2.5 exposure, childhood cognitive ability and mortality between age 11 and 86: A record-linkage life-course study from Scotland

BackgroundLiving in areas with high air pollution concentrations is associated with all-cause and cause-specific mortality. Exposure in sensitive developmental periods might be long-lasting but studies with very long follow-up are rare, and mediating pathways between early life exposure and life-course mortality are not fully understood. MethodsData were drawn from the Scottish Longitudinal Study Birth Cohort of 1936, a representative record-linkage study comprising 5% of the Scottish population born in 1936. Participants had valid age 11 cognitive ability test scores along with linked mortality data until age 86. Fine particle (PM2.5) concentrations estimated with the EMEP4UK atmospheric chemistry transport model were linked to participants’ residential address derived from the National Identity Register in 1939 (age 3). Confounder-adjusted Cox regression estimated associations between PM2.5 and mortality; regression-based causal mediation analysis explored mediation through childhood cognitive ability. ResultsThe final sample consisted of 2734 individuals with 1608 deaths registered during the 1,833,517 person-months at risk follow-up time. Higher early life PM2.5 exposure increased the risk of all-cause mortality (HR = 1.03, 95% CI: 1.01–1.04 per 10 μg m−3 increment), associations were stronger for mortality between age 65 and 86. PM2.5 increased the risk of cancer-related mortality (HR = 1.05, 95% CI: 1.02–1.08), especially for lung cancer among females (HR = 1.11, 95% CI: 1.02–1.21), but not for cardiovascular and respiratory diseases. Higher PM2.5 in early life (≥50 μg m−3) was associated with lower childhood cognitive ability, which, in turn, increased the risk of all-cause mortality and mediated 25% of the total associations. ConclusionsIn our life-course study with 75-year of continuous mortality records, we found that exposure to air pollution in early life was associated with higher mortality in late adulthood, and that childhood cognitive ability partly mediated this relationship. Findings suggest that past air pollution concentrations will likely impact health and longevity for decades to come.

Green strategies for improving urban microclimate and air quality: A case study of an Italian industrial district and facility

Densely built areas are affected by higher air-pollutant concentrations, representing a significant risk to public health. At the same time, urban settlements have a remarkable environmental impact: cities are responsible for 70% of annual carbon emissions while buildings account for 37% of global energy and process emissions. Moreover, people living in urban areas are frequently exposed to extreme micro-climate conditions caused by the urban heat island effect, related to increased external air temperature and peculiarities of the built environment. Given this framework and considering the Sustainable Development Goals, it is necessary to point out some effective and strategical mitigation measures to ameliorate micro-climate conditions, reduce pollutants concentration and enhance building performance. This paper investigates the potential advantages of green roofs as retrofitting solutions and tree planting on several micro-climate parameters and particulate matter concentration, considering an industrial district located in Italy and using ENVI-met software. The influence of the extensive green roof on energy performance is further investigated at the building level recurring to Design Builder energy models. Results showed that an extensive green roof could reduce external air temperature by up to 1.5 °C, outer surface temperature by up to 15 °C and wind speed by 50% at roof level compared to current state conditions. The application of the green roof let also to achieve energy savings of 15% for both the summer and winter seasons. Focusing on the effect on particulate matter, intensive green roof solutions proved to be more efficient in capturing air pollutants.

Cleaner air for vulnerable people – Finding better locations for essential building premises

Long-term exposure to ambient air pollution even at relatively low concentrations is associated with adverse health effects especially for children, the elderly and people with pre-existing chronic disease. Due to a variety of urban planning decisions, essential building premises attended by these vulnerable groups may be sited in locations exposed to higher levels of air pollution. Using high spatial resolution air pollution concentrations estimated by satellite-based Land Use Regression (LUR) models in Australia, we mapped and approximated the annual average concentrations of particulate matter (PM2.5) and nitrogen dioxide (NO2) at schools, child care centres, aged care facilities and hospitals across Sydney. We found that 137 (3.1 %) and 287 (6.4 %) of the total number of essential buildings assessed were exposed to annual average PM2.5 and NO2 concentrations, respectively, where: the air pollutant concentrations were greater than the median concentration of other locations in the surrounding Local Government Area (LGA), and; air pollutant levels were greater than the 90th percentile concentrations for Sydney, and; air pollution at the essential building location was at least 1 µg/m3 for PM2.5 or 2 ppb for NO2 greater than the 25th percentile concentration of other locations in the LGA. Based on these criteria, we found that many essential building premises in Sydney were in high air pollution locations and there were other meaningfully lower air pollution locations within the surrounding area. Air quality is becoming an increasingly important issue for local jurisdictions to consider as more essential amenities are required to serve denser populations in busier places exposed to more air pollution. Our study showed that high resolution maps can be used as a health-based planning tool to encourage the siting of buildings at locations better protective of health.

APDB: a database onair pollutant characterization andsimilarity prediction.

The World Health Organization estimates that 9 out of 10 people worldwide breathe air containing high levels of pollutants. Long-term and chronic exposure to high concentrations of air pollutants is associated with deleterious effects on vital organs, including increased inflammation in the lungs, oxidative stress in the heart and disruption of the blood-brain barrier. For this reason, in an effort to find an association between exposure to pollutants and the toxicological effects observable on human health, an online resource collecting and characterizing in detail pollutant molecules could be helpful to investigate their properties and mechanisms of action. We developed a database, APDB, collecting air-pollutant-related data from different online resources, in particular, molecules from the US Environmental Protection Agency, their associated targets and bioassays found in the PubChem chemical repository and their computed molecular descriptors and quantum mechanics properties. A web interface allows (i) to browse data by category, (ii) to navigate the database by querying molecules and targets and (iii) to visualize and download molecule and target structures as well as computed descriptors and similarities. The desired data can be freely exported in textual/tabular format and the whole database in SQL format. Database URL http://apdb.di.univr.it.

Exposures to ambient air pollutants increase prevalence of sleep disorder in adults: Evidence from Wuhan Chronic Disease Cohort Study (WCDCS)

BackgroundSleep disorder contributes to memory dysfunction and chronic diseases. Clear evidence of environment disturbance, such as residential noise, are associated with an increased risk of sleep disorder. However, not enough studies have been conducted on association between residential air pollutants and sleep disorder. We sought to determine whether exposures to residential air pollutants associated with risk of sleep disorder among adults. MethodsUsing the dataset of the Wuhan Chronic Disease Cohort Study (WCDCS), we investigated the prevalence of sleep disorder and five sleep disorder symptoms in the study. The data of air pollutants (including PM10, PM2.5, NO2, SO2 and O3) were obtained from 10 air quality monitoring stations in Wuhan. We utilized logistic regression model to evaluate the associations of five types of air pollutants with odds ratio (OR) of sleep disorder and symptoms. The potential moderating effects of socio-demographic factors in the associations were explored using the interaction effects model. ResultsOf the study participants, 52.1 % had sleep disorder. Exposures to higher concentrations of air pollutants were associated with increased prevalence of sleep disorder. For example, per interquartile range (IQR) increases in concentrations of PM10, PM2.5 or SO2 corresponded to the increase of sleep disorder increased prevalence at 14.7 % (adjusted odds ratio (aOR) = 1.147, 95 %CI:1.062, 1.240), 8.9 % (aOR = 1.089, 95 %CI: 1.003, 1.182) and 15.8 % (aOR = 1.158, 95 %CI: 1.065, 1.260). For symptoms specific analyses, significant linkages of PM10, PM2.5, SO2 with difficulty in falling asleep, wake up after falling asleep and early awaken were observed. Moderating effects of age and place of residence on the linkages of PM10 with increased prevalence of sleep disorder were identified. ConclusionHigher level of air pollution exposure could increase the prevalence of sleep disorder. Middle-aged and elderly population, as well as the rural residents are more likely to suffer from sleep disorder.

Evaluation of the emission inventory for large point emission sources in South Korea by applying measured data from the NASA/NIER KORUS-AQ aircraft field campaign

One of the major issues in determining a region’s air quality is the uncertainty of large point sources (LPSs) emissions, which significantly affect the local-regional air quality. In this study, the SO2 and NOx emissions of 5 major LPSs in South Korea were evaluated by comparing the emissions-based concentrations employing a Gaussian dispersion model with aircraft-based measurements from DC-8 “around-the-stack” flights through the National Aeronautics and Space Administration (NASA)/National Institute of Environmental Research (NIER) KORea-U.S. Cooperative Domestic Air Quality (KORUS-AQ) aircraft field campaign. The ratio between modeled and measured concentrations for all 5 LPSs ranged between 0.42 and 1.30 and 0.39 and 1.01 for NOx and SO2, respectively. The results for the Boryeong, Dangjin, and Seocheon power plants (PPs), where the locations and sizes of stacks are easier to specify than industrial complexes (Hyundai Steel and Hankook Glass), yielded better performance, which ranged between 0.82 and 1.30 and 0.79 and 1.01 for NOx and SO2. This level of agreement was very encouraging, considering that the modeled concentrations were based on 30-min averaged emissions compared to less-than-a-minute DC-8 around-the-stack measurements. Based on our analysis, the uncertainty of LPS emissions, at least for NOx and SO2, appears to be small, which implies that the point sources inventory emissions are reasonably accurate. The Dangjin PP’s analysis reveals that the actual measured emissions should be considered in addition to “the official” inventory amounts to reduce emission uncertainty. This detailed comparative analysis verified the method used for this study. The findings of this study are expected to enhance the performance of future LPS emission inventory assessments. In terms of recommendations, the data from the raw emission inventory should include more clear information about the locations of measured stacks to obtain more accurate emission estimates. In addition, the flight measurement duration should be long enough to fly around several times to reduce uncertainties, and the flight positions and altitudes should be varied. By improving LPS inventories through accurate evaluations, more accurate air quality forecasts and better policies could be made. As a result, it is expected that public health can be improved by reducing the time people are exposed to high concentrations of air pollutants.

PM2.5-bound trace metals in an urban area of Northern Mexico during the COVID-19 pandemic: characterization, sources, and health risk.

A field study was carried out in the Metropolitan Area of Monterrey (MAM), the second most populated city in Mexico, characterized by increasing urbanization, high traffic density, and intense industrial activity. These characteristics commonly present high concentrations of air pollutants leading to the degradation of air quality. PM2.5 was analyzed for heavy metals at two urban sites located within the MAM (Juarez and San Bernabe) in order to determine sources, health risk, morphology, and elemental content during the COVID-19 pandemic (autumn 2020 and spring 2021). Twenty-four-hour samples of PM2.5 were collected at each site during 30-day periods using high-volume equipment. Gravimetric concentrations and 11 metals were measured (Ca, Cd, Co, Cu, Fe, K, Mg, Mn, Ni, Cr, and Pb) by different analytical techniques (flame atomic absorption spectroscopy, graphite furnace atomic absorption spectroscopy, and inductively coupled plasma optical emission spectroscopy). Selected samples were analyzed by scanning electron microscopy-energy-disperse spectroscopy in order to characterize their morphology and elemental content. PM2.5 concentrations exceeded the Mexican standard and WHO guidelines in Juarez during spring 2021. Cu, Cd, and Co were highly enriched by anthropogenic sources, and Ni, K, Cr, and Pb had a moderate enrichment. Mg, Mn, and Ca were of crustal origin. Bivariate statistics and PCA confirmed that alkaline metals originated from crustal sources and that the main sources of trace metals included traffic emissions, resuspension from soil/road dust, steel industry, smelting, and non-exhaust emissions at both sites. Lifetime cancer risk coefficients did not exceed the permissible levels established by EPA and WHO, implying that local residents are not at risk of developing cancer. Non-carcinogenic risk coefficients revealed that there is a possible risk of suffering cardiovascular and respiratory diseases due to inhalation of cobalt at the study sites. The online version contains supplementary material available at 10.1007/s11869-023-01372-7.

RELATIONSHIP BETWEEN INDOOR AIR POLLUTANTS EXPOSURE AND RESPIRATORY SYMPTOMS AMONG BUS DRIVERS IN A MALAYSIAN PUBLIC UNIVERSITY

Bus drivers are continuously exposed to air pollutants such as particulate matter while working; hence, they have a high risk for respiratory diseases. This study aimed to investigate the associations of exposure to particulate matter (PM2.5, PM10) and nitrogen dioxide (NO2) inside campus transit buses with respiratory symptoms among bus drivers. A cross-sectional comparative study was conducted among 38 bus drivers as the exposed group and 38 office workers as the comparative group at a Malaysian public university. Indoor air monitoring was performed for 8 hours using SidePak Personal Aerosol Monitor, DustTrak II Aerosol Monitor, and Air Quality Monitor, while background information and self-reported respiratory symptoms were obtained using an adapted American Thoracic Society (ATS-DLD-78-A) questionnaire. Air pollutants (PM2.5, PM10 and NO2) exposure between both groups was significantly different at p&lt;0.05. The exposed group had higher odds of getting cough (OR=2.5), chronic cough (OR=2.2) and chronic phlegm (OR=4.6) than the comparative group. Moreover, there were significant associations between PM10 and PM2.5 concentrations with cough (OR=2.2), chronic cough (OR=2.2), and chronic phlegm (OR=2.2). Meanwhile, only cough was significantly associated with NO2 (OR=2.4). Multiple logistic regression showed that the main predictor for cough was PM2.5 (OR=3.2), for chronic cough was PM10 (OR=5.0), and for chronic phlegm was work duration (OR=1.3). In short, the exposed group was exposed to higher concentrations of air pollutants than the comparative group, leading to a higher prevalence of respiratory symptoms among the bus drivers. These findings provide important evidence for future programs to improve the air quality in buses. It is recommended that the indoor air quality inside the bus should be monitored periodically to ensure the drivers and the passengers are not exposed to air pollutants above the permissible limit.

Association of long-term ambient fine particulate matter (PM2.5) and incident non-alcoholic fatty liver disease in Chinese adults

Air pollution is increasingly recognized as an important environmental risk factor for non-alcoholic fatty liver disease (NAFLD). However, epidemiologic evidence on long-term exposure to high air pollution concentrations with incident NAFLD is still very limited. Here, we constructed a population-based dynamic cohort involving 17,106 subjects who were enrolled between 2005 and 2013 and subsequently followed until 2017, combined with a high-resolution ambient fine particulate matter ≤2.5 μm (PM2.5) dataset, to investigate the association of long-term PM2.5 exposure (cumulative annual average levels ranged from 36.67 to 111.16 μg/m3) with NAFLD incidence (N = 4,640). We estimated the adjusted hazard ratio (HR) for incident NAFLD among those exposed to the highest quartile of PM2.5 was 2.04 [95% confidence interval (CI), 1.80–2.30] compared with individuals exposed to the lowest quartile of PM2.5. The dose-response relationships for PM2.5 are non-linear for NAFLD across the exposure distribution. Further stratified analyses revealed that lean (<23 kg/m2), younger (<40-year-old), and women individuals appeared more vulnerable to the harmful effects of PM2.5 exposure. Our study suggests a greater long-term high ambient PM2.5 exposure is associated with an increased risk of NAFLD in Chinese adults, particularly in specific groups, including lean, women, and younger people.

Explainable prediction of daily hospitalizations for cerebrovascular disease using stacked ensemble learning

BackgroundWith the prevalence of cerebrovascular disease (CD) and the increasing strain on healthcare resources, forecasting the healthcare demands of cerebrovascular patients has significant implications for optimizing medical resources.MethodsIn this study, a stacking ensemble model comprised of four base learners (ridge regression, random forest, gradient boosting decision tree, and artificial neural network) and a meta learner (elastic net) was proposed for predicting the daily number of hospital admissions (HAs) for CD using the historical HAs data, air quality data, and meteorological data in Chengdu, China from 2015 to 2018. To solve the label imbalance problem, a re-weighting method based on label distribution smoothing was integrated into the meta learner. We trained the model using the data from 2015 to 2017 and evaluated its predictive ability using the data in 2018 based on four metrics, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). In addition, the SHapley Additive exPlanations (SHAP) framework was applied to provide explanation for the prediction of our stacking model.ResultsOur proposed model outperformed all the base learners and long short-term memory (LSTM) on two datasets. Particularly, compared with the optimal results obtained by individual models, the MAE, RMSE, and MAPE of the stacking model decreased by 13.9%, 12.7%, and 5.8%, respectively, and the R2 improved by 6.8% on CD dataset. The model explanation demonstrated that environmental features played a role in further improving the model performance and identified that high temperature and high concentrations of gaseous air pollutants might strongly associate with an increased risk of CD.ConclusionsOur stacking model considering environmental exposure is efficient in predicting daily HAs for CD and has practical value in early warning and healthcare resource allocation.