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Air quality monitoring is a significant job in our everyday life and affects the vitality of a human. It paves a better way of understanding the sources, effects and levels of pollutants in the air inhaled by the population of the region. This concept helps us in improving and developing pollution control measures to diminish the effect of air contamination. Air Quality Index (AQI) helps in understanding the level of pollution. This study briefs various state of art methods such as SVM, RF,ANN, RNN and FL in predicting air quality using machine learning. The results shows prominent outcomes which can be deployed in various cost effective hardware platforms for household and commercial purposes. The proposed model used eight parameters like NO2CO, O3, PM2.5, PM10, SO2, TEMP, PRES, DEWP, RAIN,WD, WSPM of Beijing dataset in order to predict AQI and it is tested with regional dataset. The Proposed model works based on process monitoring model. The efficient and flexible way to solve environmental issues is to combine machine learning algorithm with air quality prediction.

The air quality is generally graded into five levels in a simple way or released by the Air Pollution Index (API) which does not take the fine particulate matter (PM2.5) emission into account. The fuzzy algorithm in this paper solves the mutability aroused by the grading approach by counting in the six items of pollutants pertaining to Short-lived climate forcers (SLCFs). Firstly, six items of air pollutants as well as driving factors of human activities are introduced. Secondly, based on the relevant observation data from the China Air Quality Online Monitoring Platform (CAQOMP), 18 experimental cities covering North China, East China, Central China, and South China are selected in this paper for air quality comparison and analysis in the application of the fuzzy algorithm. Thirdly, this paper looks into the air quality ranking of experimental 18 cities from a regional perspective. North China's air quality is not optimistic owing to being in a location near the coal producer and sand-sourced Outer Mongolia. Central China's air quality is more impacted by high-speed economic development and urbanization during the last couple of years. O3 emission is not well controlled across China. It turns out that the ranking by using the fuzzy algorithmic method is more scientific and holistic than API. [ABSTRACT FROM AUTHOR]

Background: Few studies have assessed air pollution exposure association with birthweight during both preconception and gestational periods. Methods: Leveraging a preconception cohort consisting of 14220 pregnant women and newborn children in Shanghai, China during 2016–2018, we aim to assess associations of NO2 and PM2.5 exposure, derived from high-resolution spatial-temporal models, during preconception and gestational periods with outcomes including term birthweight, birthweight Z-score, small-for-gestational age (SGA) and large-for-gestational age (LGA). Linear and logistic regressions were used to estimate 3-month preconception and trimester-averaged air pollution exposure associations; and distributed lag models (DLM) were used to identify critical exposure windows at the weekly resolution from preconception to delivery. Two-pollutant models and children's sex-specific associations were explored. Results: After controlling for covariates, one standard deviation (SD) (11.5 μg/m3, equivalent to 6.1 ppb) increase in NO2 exposure during the second and the third trimester was associated with 13% (95% confidence interval: 2 – 26%) and 14% (95% CI: 1 – 29%) increase in SGA, respectively; and one SD (9.6 μg/m3) increase in PM2.5 exposure during the third trimester was associated with 15% (95% CI: 1 – 31%) increase in SGA. No association have been found for outcomes of birthweight, birthweight Z-score and LGA. DLM found that gestational weeks 22–32 were a critical window, when NO2 exposure had strongest associations with SGA. The associations of air pollution exposure tended to be stronger in female newborns than in male newborns. However, no significant associations of air pollution exposure during preconception period on birthweight outcomes were found. Conclusion: Consistent with previous studies, we found that air pollution exposure during mid-to-late pregnancy was associated with adverse birthweight outcomes. [ABSTRACT FROM AUTHOR]

The first case of COVID-19 in Iran was reported on February 25, 2020, leading in the implementation of a government-mandated lockdown as the virus gradually spread to different cities. The objective of this study was to evaluate the impact of the COVID-19 pandemic on air quality in Ahvaz city by utilizing Sentinel 5 images and the Google Earth Engine (GEE) platform. Specifically, the concentrations of air pollutants, including CO, NO2, SO2, and HCHO, during the COVID-19 pandemic from May 10 to June 01, 2021, were examined. Also, they were compared to the same period in 2019. Additionally, the influence of meteorological parameters, such as wind speed and precipitation, on pollutant concentrations during the pandemic and in the pre-pandemic year of 2019 were investigated. The results revealed a significant decrease in the concentrations of NO2 (13.7%), CO (6.1%), SO2 (28%), and HCHO (9.5%) in Ahvaz during the study period in 2021 compared to the same period in 2019. Statistical analyses indicated no significant changes in wind speed and precipitation between the COVID-19 pandemic and the pre-pandemic period in 2019. Therefore, the impact of these parameters on the observed changes in pollutant concentrations can be disregarded. It is clear that the COVID-19 epidemic and the subsequent lockdown measures, including traffic restrictions and business closures, played a crucial role in significantly reducing air pollutant concentrations in Ahvaz. [ABSTRACT FROM AUTHOR]

Background: Exposure to air pollutants promotes inflammation, cancer, and mortality in chronic diseases. Acute respiratory distress syndrome (ARDS) is a common condition among intensive care unit patients and is associated with a high mortality rate. ARDS is characterized by significant lung inflammation, which can be replicated in animal models by acute exposure to high doses of various air pollutants. Recently, several clinical studies have been conducted in different countries to investigate the role of chronic or acute air pollutant exposure in enhancing both ARDS incidence and severity. Results: Chronic exposure studies have mainly been conducted in the US and France. The results of these studies suggest that some air pollutants, notably ozone, nitrogen dioxide, and particulate matter, increase susceptibility to ARDS and associated mortality. Furthermore, their impact may differ according to the cause of ARDS. A cohort study conducted in an urbanized zone in China showed that exposure to very high levels of air pollutants in the few days preceding intensive care unit admission was associated with an increased incidence of ARDS. The effects of acute exposure are more debatable regarding ARDS incidence and severity. Conclusion: There is a likely relationship between air pollutant exposure and ARDS incidence and severity. However, further studies are required to determine which pollutants are the most involved and which patients are the most affected. Due to the prevalence of ARDS, air pollutant exposure may have a significant impact and could be a key public health issue. [ABSTRACT FROM AUTHOR]

The rapid urbanization and growing number of motor vehicles in China have led to a significant increase in NO2 emissions, posing a severe threat to the air quality in cities. Road traffic pollution has emerged as a significant environmental issue in China. Exploring the utilization of landscape plants for air pollutant mitigation and assessing the influence of various plant concentrations on reducing air pollution holds great significance in urban ecological environment protection and urban development. Through field surveys and data collection in January 2022, the objectives of this study are to explore the relationship between road meteorological factors and the reduction in air pollutant concentrations in Nanjing city's road green spaces and to investigate the influence of plant configuration in road green spaces on pollutant concentration. The findings demonstrate a distinct positive correlation between road traffic volume during winter peak hours and the concentration of NO2 pollution gas. Furthermore, meteorological factors, including temperature and light intensity, strongly correlate with air pollutant concentrations. Open green spaces with ventilated structures and high tree planting density (deciduous trees are preferred) exhibit optimal purification effects. Excessive or insufficient planting density hinders the purifying function of green belts. In conclusion, our research on plant configurations and air pollutant concentrations in Nanjing City during the winter suggests that the recommended road green space plant configuration in Nanjing is a combination of arbor (deciduous tree), shrub, and grass. [ABSTRACT FROM AUTHOR]

Congenital heart disease (CHD) is the most common birth defect and one of the major causes of neonatal death, with an average prevalence of 9.4‰ worldwide. We reviewed recent epidemiological studies and found that exposure to air pollutants is associated with increased CHD risks, but the associations are inconsistent between exposure to air pollutants and different subtypes of CHD due to developmental and etiological heterogeneity among different subtypes of CHD. It has been reported that air pollutants are associated with increased risks of ventricular septal defect, patent ductus arteriosus, pulmonary stenosis, tetralogy of Fallot, and transposition of the great arteries. However, associations between maternal exposure to air pollutants and atrial septal defect (ASD) are contradictory, with significantly positive associations of inhalable particulate matter and nitrogen dioxide exposure, negative associations of fine particulate matter and carbon monoxide, and mixed associations of sulfur dioxide. Adverse effects of air pollutant on cardiac development cover a wide time window beyond 3-8 weeks during gestation; particulate matter and nitrogen oxide are more likely to affect fetal heart in early pregnancy, while the association strength of carbon monoxide shows a trough in early pregnancy, and sulfur dioxide and ozone affect cardiac health throughout pregnancy. In addition, we discussed the limitations of previous studies on the associations between maternal air pollutant exposure and CHD, and highlighted the application of precise assessment on exposure to air pollutants, the performance of prospective cohort studies and longitudinal studies, and the necessity of studies on CHD subtypes, in order to provide scientific evidence to control exposure to environmental pollutants and CHD occurrence.

Air pollution has been standing as one of the most pressing global challenges. The changing patterns of air pollutants at different spatial and temporal scales have been substantially studied all over the world, which, however, were intricately disturbed by COVID-19 and subsequent containment measures. Understanding fine-scale changing patterns of air pollutants at different stages over the epidemic’s course is necessary for better identifying region-specific drivers of air pollution and preparing for environmental decision making during future epidemics. Taking China as an example, this study developed a multi-output LightGBM approach to estimate monthly concentrations of the six major air pollutants (i.e., PM2.5, PM10, NO2, SO2, O3, and CO) in China and revealed distinct spatiotemporal patterns for each pollutant over the epidemic’s course. The 5-year period of 2019–2023 was selected to observe changes in the concentrations of air pollutants from the pre-COVID-19 era to the lifting of all containment measures. The performance of our model, assessed by cross-validation R2, demonstrated high accuracy with values of 0.92 for PM2.5, 0.95 for PM10, 0.95 for O3, 0.90 for NO2, 0.79 for SO2, and 0.82 for CO. Notably, there was an improvement in the concentrations of particulate matter, particularly for PM2.5, although PM10 exhibited a rebound in northern regions. The concentrations of SO2 and CO consistently declined across the country over the epidemic’s course (p < 0.001 and p < 0.05, respectively), while O3 concentrations in southern regions experienced a notable increase. Concentrations of air pollutants in the Beijing–Tianjin–Hebei region were effectively controlled and mitigated. The findings of this study provide critical insights into changing trends of air quality during public health emergencies, help guide the development of targeted interventions, and inform policy making aimed at reducing disease burdens associated with air pollution.

To achieve resilience goals, urban planners and decision-makers need accurate information on the benefits provided by urban trees and on the effects that management may have on them. This study investigates the impacts of management and disturbances on urban forest structure and function in Turku, Finland. Using a comprehensive urban tree database and the i-Tree software suite, we assessed the current structure and estimated the value of ecosystem services provided by Turku's urban forest. Additionally, we simulated changes in the urban forest over a 50-year period, considering different tree planting scenarios and the potential outbreak of the Asian longhorned beetle (ALB). Turku's urban forest comprised 38,438 public trees, dominated by Acer platanoides, Pinus sylvestris, Tilia × europaea, and Betula pendula. The estimated carbon storage was 12,336 t, valued at 1.98 million €, with an annual sequestration rate of 284 t (45,549 €/year). The trees also removed 8.97 t of pollutants annually, with an estimated value of 153,273 €. At the current rate of tree planting, the number of trees would decline over the course of 50 years resulting in a gradual decrease in the provision of ecosystem services. Although doubling the tree planting rate could slowly increase carbon storage and sequestration even under moderate ALB attack, it was insufficient to offset the damage caused by ALB if tree mortality rate reaches 50%. Compared to carbon storage and sequestration, changes in urban forest age structure had a more immediate impact on the removal of air pollution. These findings emphasize the importance of prioritizing investments in urban forests on grounds of their capacity to provide diverse ecosystem services. Incorporating these findings into decision-making processes would promote sustainable and resilient urban environments.

This article discusses different types of pollution from the paving process and the influence of using hot mix asphalt without and including end-of-life tyre rubber. This new composition type is one of the possible solutions to reduce the amount of used transport tyres and a new way to use less valuable raw materials. The research carried out involved analyzers applied under conditions of a mobile laboratory and handheld particle counters. Odour samples were taken using a vacuum chamber in Tedlar containers, and the level of odours was analyzed adopting the olfactometric method. Exposure to gaseous carbon, nitrogen and sulphur oxides and particulate matter up to 10 µm, fractions from 0.3 µm to 10 µm, as well as the odours emitted that cover the soil surface with the hot-mix asphalt-rubber mixture was examined. The average decrease in pollution using the asphalt-rubber mixture is about 3.8–4 % of nitrogen oxides, 10 % of particulate matter of 1.5–10, and an increase is approximately 9 % for particulate matter of 0.8–1 µm and 15 % for sulphur dioxide. The level of odour of compacted asphalt is around 2.8 times lower than that in the case of level asphalt.

Copyright of Asian Journals of Ecotoxicology is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Taxis pose a higher threat to global climate change and human health through air emissions. However, the evidence on this topic is scarce, especially, in developing countries. Therefore, this study conducted estimation of fuel consumption (FC) and emission inventories on Tabriz taxi fleet (TTF), Iran. A structured questionnaire to obtain operational data of TTF, municipality organizations, and literature review were used as data sources. Then modeling was used to estimate fuel consumption ratio (FCR), emission factors (EFs), annual FC, and emissions of TTF using uncertainty analysis. Also, the impact of COVID-19 pandemic period was considered on the studied parameters. The results showed that TTF have high FCRs of 18.68 L/100 km (95% CI=17.67–19.69 L/100 km), which are not affected by age or mileage of taxis, significantly. The estimated EFs for TTF are higher than Euro standards, but the differences are not significant. However, it is critical as can be an indication of inefficiency of periodic regulatory technical inspection tests for TTF. COVID-19 pandemic caused significant decrease in annual total FC and emissions (9.03–15.6%), but significant increase in EFs of per-passenger-kilometer traveled (47.9–57.3%). Annual vehicle-kilometer-traveled by TTF and the estimated EFs for gasoline-compressed natural gas bi-fueled TTF are the main influential parameters in the variability of annual FC and emission levels. More studies on sustainable FC and emissions mitigation strategies are needed for TTF. [ABSTRACT FROM AUTHOR]

The volatiles released by the volcanic structures of the world contribute to natural environmental pollution both during the passive and active degassing stages. The Island of Vulcano is characterized by solfataric degassing mainly localized in the summit part (Fossa crater) and in the peripheral part in the Levante Bay. The normal solfataric degassing (high-temperature fumarolic area of the summit and boiling fluids emitted in the Levante Bay area), established after the last explosive eruption of 1888–90, is periodically interrupted by geochemical crises characterized by anomalous degassing that are attributable to increased volcanic inputs, which determine a sharp increase in the degassing rate. In this work, we have used the data acquired from the INGV (Istituto Nazionale di Geofisica e Vulcanologia) geochemical monitoring networks to identify, evaluate, and monitor the geochemical variations of the extensive parameters, such as the SO2 flux from the volcanic plume (solfataric cloud) and the CO2 flux from the soil in the summit area outside the fumaroles areas. The increase in the flux of volatiles started in June–July 2021 and reached its maximum in November of the same year. In particular, the mean monthly flux of SO2 plume of 22 tons day−1 (t d−1) and of CO2 from the soil of 1570 grams per square meter per day (g m2 d−1) increased during this event up to 89 t d−1 and 11,596 g m2 d−1, respectively, in November 2021. The average annual baseline value of SO2 output was estimated at 7700 t d−1 during normal solfataric activity. Instead, this outgassing increased to 18,000 and 24,000 t d−1 in 2021 and 2022, respectively, indicating that the system is still in an anomalous phase of outgassing and shows no signs of returning to the pre-crisis baseline values. In fact, in the first quarter of 2023, the SO2 output shows average values comparable to those emitted in 2022. Finally, the dispersion maps of SO2 on the island of Vulcano have been produced and have indicated that the areas close to the fumarolic source are characterized by concentrations of SO2 in the atmosphere higher than those permitted by European legislation (40 μg m−3 for 24 h of exposition) on human health. [ABSTRACT FROM AUTHOR]

Recent deterioration of ambient air quality is related to anthropogenic activities, which play a significant role in atmospheric pollution. Ozone (O3) is an air pollutant that is not emitted directly from sources at the ground level. Meanwhile, anthropogenic activities, such as industrial and mobile sources, may directly produce O3 pollutant precursors. Human health, the environment, materials, and crops are negatively affected by O3 pollutants. Therefore, the present study investigated the causal relationships between O3 and particulate matter, gaseous pollutants, and meteorological conditions. Three monitoring stations, each representing a different geographical region, were selected. The three monitoring stations were in Negeri Sembilan, Kelantan, and Perlis, representing industrial, urban, and suburban areas, respectively. Sulfur dioxide (SO2), nitrogen dioxide (NO2), and wind speed (WS) were causally related to O3 in Nilai; SO2 and carbon monoxide (CO) in Kota Bharu; and NO2 and CO in Kangar. However, the causal relationship between the causative parameters and O3 was one-way. Therefore, O3 is considered to be a secondary contaminant that may require these parameters to be formed in the ambient air. However, none of the primary parameters showed a directional relationship with the other parameters, except for O3. These findings may be useful in future research to improve our understanding of air quality, particularly the status of O3 pollutants. [ABSTRACT FROM AUTHOR]

Abstract Background Worldwide, around 3 billion people rely on solid fuel for their daily energy needs. Household air pollution secondary to solid fuel burning is a major risk factor for respiratory mobility among vulnerable populations. This study aimed to investigate the respiratory symptoms associated with solid fuel usage, the level of kitchen fuel smoke exposure and its association with respiratory symptoms among reproductive-aged women in Sri Lanka, where most households exclusively use firewood as the primary cooking fuel. Methods A descriptive cross-sectional study was conducted among 403 reproductive-aged women (15 to 49 years) in the Central Province, Sri Lanka. A structured interviewer-administered questionnaire was used to collect data, and an exposure assessment was done using a breath carbon monoxide monitor. Results After adjusting for potential confounding factors by the logistic regression models, the odds ratios (OR) of the liquid petroleum gas-only users for at least one respiratory symptom relevant to cough (OR: 0.39; 95% confidence interval [CI]: 0.20–0.78), wheezing (OR: 0.47; 95% [CI]: 0.26–0.87), and dyspnea (OR: 0.44; 95% CI: 0.24–0.84) were significantly lower compared to firewood-only users. The mean of expired air carbon monoxide and estimated carboxyhemoglobin levels of liquid petroleum gas-only users (2.84 ± 2.85 ppm; 1.08 ± 0.46%) were significantly lower than those of firewood-only users (5.27 ± 4.64 ppm; 1.47 ± 0.74%). Conclusions The use of firewood increased the risk of respiratory symptoms among reproductive-aged women in Sri Lanka. Health education focused on positive behavioral changes and effective and efficient clean energy policies are recommended to mitigate the risk associated with solid fuel smoke exposure.

BackgroundAir pollutants and extreme temperature both pose significant threats to human health, but the synergistic effect between air pollutants and temperature on health is inconsistent.ObjectiveTo explore a potential synergistic effect between air pollutants and temperature on the mortality in China through literature review.MethodsWanfang Data Knowledge Service Platform, China National Knowledge Infrastructure, VIP Information Chinese Journal Service Platform, PubMed, Web of Science, Science Direct, and Embase databases were searched. "Temperature" "air pollution" "mortality" were selected as keywords to collect literature on synergistic effect between air pollutants and temperature on mortality in China. Literature was published from 2000-01-01 to 2022-07-31 in Chinese or English. Two researchers screened the literature independently according to the inclusion criteria, and the results were integrated and analyzed after data extraction. The "meta" package of R software was used for meta-analysis.ResultsTwenty-seven studies met the inclusion criteria and associated air pollutants included PM10, PM2.5, O3, SO2, NO2, and CO. The impact of PM10 and PM2.5 on mortality in high temperature days was higher than that in moderate temperature days. In high temperature days, a 10 μg·m−3 increment in PM10 concentration corresponded to pooled estimates of 2.30% (95%CI: 1.34%-3.26%), 1.23% (95%CI: 0.64%-1.82%), and 1.42% (95%CI: 0.63%-2.22%) increase in non-accidental, cardiovascular, and respiratory mortalities, respectively. A 10 μg·m−3 increment in PM2.5 concentration corresponded to pooled estimates of 2.56% (95%CI: 2.00%-3.13%), 2.37% (95%CI: 1.64%-3.12%), and 2.14% (95%CI: 1.03%-3.25%) increase in non-accidental, cardiovascular, and respiratory mortalities, respectively. The synergistic effect of SO2 and NO2 on cardiovascular and respiratory mortalities in low temperature days was higher than that in moderate temperature days.ConclusionThe synergistic effects of air pollutants and temperature on mortality in low temperature days or in high temperature days are higher than that in moderate temperature days. The health protection related to these pollutants should be strengthened in these days.

The decline in NO2 and PM2.5 pollutant levels were observed during COVID-19 around the world, especially during lockdowns. Previous studies explained such observed decline with the decrease in human mobility, overlooking the meteorological changes that could simultaneously mediate air pollution levels. This pitfall could potentially lead to over- or under-estimation of the effect of COVID-19 on air pollution. This study, thus, aims to re-evaluate the impact of COVID-19 on NO2 and PM2.5 pollutant levels in Singapore, by incorporating the effect of meteorological parameters in predicting NO2 and PM2.5 baseline in 2020 using machine learning methods. The results show that the mean NO2 and PM2.5 declined by 12% and 19%, which were less than the observed drops (i.e. 54% and 29%, respectively) without considering the effect of meteorological parameters. As two proxies for change in human mobility, taxi availability and carpark availability were found to increase and decrease by a maximum of 12.6% and 9.8%, respectively, in 2020 from 2019. Two correlation analyses were conducted to investigate how human mobility influenced air pollutant levels: one between daily PM2.5 and mobility changes at a regional scale and the other between weekly NO2 and mobility changes at a spatial resolution of 0.01°. The NO2 variation was found to be more associated with the change in human mobility and a cluster of stronger correlations was found in the South and East Coast of Singapore. Contrarily, PM2.5 and mobility had a weak correlation, which could be due to the limit of a coarse spatial resolution.

Abstract Rationale Studies examining the association of short-term air pollution exposure and daily deaths have typically been limited to cities and used citywide average exposures, with few using causal models. Objectives To estimate the associations between short-term exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and all-cause and cause-specific mortality in multiple US states using census tract or address exposure and including rural areas, using a double negative control analysis. Methods We conducted a time-stratified case-crossover study examining the entire population of seven US states from 2000–2015, with over 3 million non-accidental deaths. Daily predictions of PM2.5, O3, and NO2 at 1x1 km grid cells were linked to mortality based on census track or residential address. For each pollutant, we used conditional logistic regression to quantify the association between exposure and the relative risk of mortality conditioning on meteorological variables, other pollutants, and using double negative controls. Results A 10 μg/m3 increase in PM2.5 exposure at the moving average of lag 0–2 day was significantly associated with a 0.67% (95%CI: 0.34–1.01%) increase in all-cause mortality. 10 ppb increases in NO2 or O3 exposure at lag 0–2 day were marginally associated with and 0.19% (95%CI: −0.01-0.38%) and 0.20 (95% CI-0.01, 0.40), respectively. The adverse effects of PM2.5 persisted when pollution levels were restricted to below the current global air pollution standards. Negative control models indicated little likelihood of omitted confounders for PM2.5, and mixed results for the gases. PM2.5 was also significantly associated with respiratory mortality and cardiovascular mortality. Conclusions Short-term exposure to PM2.5 and possibly O3 and NO2 are associated with increased risks for all-cause mortality. Our findings delivered evidence that risks of death persisted at levels below currently permissible.

Analyzing the spatial distribution of meteorological factors and air pollutants and its correlation is of great importance for urban air pollution prevention. This study explored the spatial distribution of meteorological factors and air pollutants, analyzed the correlation between meteorological factors and air pollutants, and revealed the main meteorological factors that influence the air pollutants in 31 provincial capitals of China during 2010-2020. The results show that the spatial distribution characteristics of air pollutants and the days of air quality equal to or above grade II in 31 provincial capitals of China during 2010-2020 vary obviously. The days of air quality equal to or above grade II are negatively correlated with the annual average concentration of NO2 and annual average concentration of PM10 during 2010-2020, and annual average concentration of SO2 during 2010 to 2018. The temperature, precipitation, and relative humidity are the main meteorological factors affecting the air quality in different seasons in 31 provincial capitals of China during 2010-2020. The findings will provide a scientific basis for atmospheric environment control and urban air quality forecast. [ABSTRACT FROM AUTHOR]

Slowly adapting receptors (SARs), vagal mechanosensitive receptors located in the lung, play an important role in regulating the breathing pattern and Hering-Breuer inflation reflex (HBIR). Inhalation of high concentration of sulfur dioxide (SO2), a common environmental and occupational air pollutant, has been shown to selectively block the SAR activity in rabbits, but the mechanism underlying this inhibitory effect remained a mystery. We carried out this study to determine if inhalation of SO2 can inhibit the HBIR and change the eupneic breathing pattern, and to investigate further a possible involvement of voltage-gated K+ channels in the inhibitory effect of SO2 on these vagal reflex-mediated responses. Our results showed 1) inhalation of SO2 (600 ppm; 8 min) consistently abolished both the phasic activity of SARs and their response to lung inflation in anesthetized, artificially ventilated mice, 2) inhalation of SO2 generated a distinct inhibitory effect on the HBIR and induced slow deep breathing in anesthetized, spontaneously breathing mice, and these effects were reversible and reproducible in the same animals, 3) This inhibitory effect of SO2 was blocked by pretreatment with 4-aminopyridine (4-AP), a nonselective blocker of voltage-gated K+ channel, and unaffected by pretreatment with its vehicle. In conclusion, this study suggests that this inhibitory effect on the baseline breathing pattern and the HBIR response was primarily mediated through the SO2-induced activation of voltage-gated K+ channels located in the vagal bronchopulmonary SAR neurons. [ABSTRACT FROM AUTHOR]

Exposure to air pollution during pregnancy has been linked to birth defects. But the directions of studies on the associations between air pollutants exposure and effect on the incidence of congenital heart disease (CHDs) were inconsistent. To date, few studies were concentrated on the effects of both particulate matter and gaseous air pollutant exposure on CHDs across the full gestational week simultaneously. Our study aimed to investigate the critical exposure windows for each air pollutant throughout 40 gestational weeks. Data on CHDs, air pollution, and meteorological factors from 2013 to 2019 were collected in Lanzhou, China. A distributed lag nonlinear model combined with a quasi-Poisson regression model was applied to evaluate the weekly exposure–lag–response association between air pollutants levels and CHDs, and the subgroup analyses were conducted by gender (baby boy and baby girl). The study included 1607 mother–infant pairs. The results demonstrated that exposure of pregnant women to particulate matter ≤ 5 μm (PM2.5) at lag 1–4 weeks was significantly associated with the risk of CHDs, and the strongest effects were observed in the lag 1 week (1.150, 95%CI 1.059–1.248). For exposure to particulate matter ≤ 10 μm (PM10) at lag 1–3 weeks, the strongest effects were observed in the lag 1 week (1.075, 95% CI 1.026–1.128). For exposure to sulfur dioxide (SO2) at lag 1–4 weeks, the strongest effects were observed in the lag 1 week (1.154, 95% CI 1.025–1.299). For exposure to carbon monoxide (CO) at lag 1–3 weeks, the strongest effects were observed in the lag 1 week (1.089, 95% CI 1.002–1.183). For exposure to ozone (O3) concentration at lag 9–15 weeks, the strongest effects were observed in the lag 15 weeks (1.628, 95% CI 1.001–2.649). The cumulative effects of PM2.5, PM10, SO2, and CO along weeks with a maximum of 1.609 (95%CI 1.000–2.589), 1.286 (95%CI 1.007–1.641), 1.648 (95%CI 1.018–2.668), and 1.368 (95%CI 1.003, 1.865), respectively. The effects were obvious in the initial gestational weeks too. Through the gender stratification analysis, the air pollutants with significant effects were PM2.5 for baby boys and PM2.5, PM10, SO2, CO, NO2, and O3 for baby girl. For the relationship between CHDs and air pollution in Lanzhou, PM2.5, PM10, SO2, CO, and O3 played an important role in the initial gestational weeks, especially for baby girl. [ABSTRACT FROM AUTHOR]

Reducing air pollution is a crucial challenge in urban areas. In this regard, urban green infrastructures could play a pivotal role. In the literature, scholars analyzed both the ability of species-specific and layout-specific green infrastructures to reduce air pollution and the best location sites of new green infrastructures to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement based on vegetation species-specific performance and differentiated demand for the ecosystem services of city areas. This paper uses tree cadastre data from a medium-sized city in central Italy (Perugia) and the traffic open-layers of Gmaps to develop a spatial analysis of the urban trees' performance in PM10 dust retention, and the PM10 produced by vehicular emissions, respectively. The method generates a spatialized balance between demand (air-polluted sites by traffic) and supply (PM10 dust retention by trees) to support local decisions about the best locations for new green infrastructures and the choice between species. The paper analyzed 6710 urban trees in an area of 42.62 km2 with a linear road density of 15 km/km2. Platanus hybrida Mill. ex Münchh, Celtis australis L., Ulmus carpinifolia L., Pinus pinaster Aiton, Quercus ilex L., Quercus robur L., and Tilia cordata Mill. are the resulting optimal species to reduce PM10, with median values of 219.62, 181.47, 166.67, 154.66, 143.90, 118.61, and 118.04 g tree−1 yr−1, respectively. The paper is a first contribution in developing GIS-based tools that vary the recommended location sites and species for new green infrastructures based on the demanded ecosystem service. Urban planners are called to dynamically use and integrate numerous tools, such as the one developed here, to seek complex solutions capable of increasing the sustainability of urban systems. [ABSTRACT FROM AUTHOR]

Background and Objective: Air pollution affects clinical course and prognosis of idiopathic pulmonary fibrosis (IPF). However, the effect of individual exposure to air pollutants on disease progression is unclear. We aimed to identify the effect of individual exposure to nitrogen dioxide (NO2) and particulate matter (aerodynamic diameter ≤ 10 μm [PM10]) on disease progression in patients with IPF. Methods: The serial lung function data of 946 IPF patients (mean age: 65.4 years, male: 80.9%) were analysed. Individual‐level long‐term exposures to NO2 and PM10 at the residential addresses of patients were estimated using a national‐scale exposure prediction model, constructed based on air quality regulatory monitoring data. Progression was defined as a relative decline (≥10%) in forced vital capacity. Individual‐ and area‐level covariates were adjusted in the primary analysis model. Results: Overall, 547 patients (57.8%) experienced progression during a median follow‐up of 1.0 year (interquartile range: 0.4–2.6 years). In the primary model, a 10‐ppb increase in NO2 concentration was associated with a 10.5% increase in the risk of progression (hazard ratio [HR] = 1.105; 95% CI = 1.000–1.219) in patients with IPF. There was also an increasing trend of progression in patients with IPF according to the second to fourth quartiles of NO2 (Q2 [HR = 1.299; 95% CI = 0.972–1.735], Q3 [1.409; 1.001–1.984], Q4 [1.598; 1.106–2.310]) compared to the first quartile. We found no association between PM10 and progression in IPF patients. Conclusion: Our data suggest that increased individual exposure to NO2 can increase the risk of progression in patients with IPF. In a nationwide population‐based study using estimated long‐term personal air pollutant levels, an increase in NO2 level was associated with increased risk of disease progression of IPF in a model adjusted by individual‐ and area‐level covariates. Our data suggest that avoiding exposure to NO2 might prevent disease progression in IPF. See relatedEditorial [ABSTRACT FROM AUTHOR]

Accurate monitoring of air pollution is crucial to human health and the global environment. In this research, the various multispectral satellite data, including MODIS AOD/SR, Landsat 8 OLI, and Sentinel-2, together with the two most commonly used machine-learning models, viz. multi-layer backpropagation neural network (MLBPN) and random forest (RF), have been employed to analyze the spatiotemporal distributions of the primary air pollutant from 2019 to 2022 in Guanzhong Region, China. In the conducted experiments, the RF-based model, using the MODIS AOD data, has generally demonstrated the “optimal” estimation performance for the ground-surface concentrations of the primary air-pollutants. Then, the “optimal” estimation model has been employed to analyze the spatiotemporal distribution of the various air pollutants—in terms of temporal distribution, the annual average concentrations of PM2.5, PM10, NO2, and SO2 in the research area showed a decreasing trend from 2019 to 2022, while the annual average concentration of CO remained relatively stable and the annual average concentration of O3 slightly increased; in terms of the spatial distribution, the air pollution presents a gradual increase from west to east in the research area, with the distribution of higher concentrations in the center of the built-up areas and lower in the surrounding rural areas. The proposed estimation model and spatiotemporal analysis can provide reliable methodologies and data support for the further study of the air pollution characteristics in the research area.

Introduction: Indonesia ranks 8th globally in the air pollution index, with poor air quality causing premature deaths from lung ailments such as interstitial lung diseases. Krebs von den Lungen-6 (KL 6) can be used to detect lung disease caused by air pollution. However, the number of studies investigating the link between air pollutant exposure and KL-6 levels is inadequate. The present study explores the association between air pollutant exposure and KL-6 levels in workers in different settings. Methods: This cross-sectional study recruited 70 individuals who were divided into two groups. Dust levels were measured using a particle counter as a proxy for air pollutant levels. KL-6 levels were measured with ELISA. The Spearman correlation test, Mann-Whitney test, and generalized linear model were used in statistical analyses. Results and Discussion: Air pollutant exposure differed significantly between outdoor and indoor settings (p = 0.000). A significant difference was found in KL-6 serum levels between outdoor and indoor workers (p = 0.000). Air pollutant levels were inversely associated with KL-6 serum levels in outdoor (r = -0.557, p < 0.05) and indoor workers (r = -0.360, p < 0.05). Working duration did not significantly correlate with KL-6 serum levels in either group. A tendency of linear association among air pollutant exposure, overall working duration, and KL-6 serum levels was found in the multivariable model. Conclusion: Work settings were associated with varying exposures to air pollutants and KL-6 serum levels. Higher exposure to pollutants may be associated with an increase in KL-6 serum levels.

PurposeTo reveal relationship between air pollution exposure and osteoporosis (OP) risk.MethodsBased on large-scale data from the UK Biobank, we evaluated the relationship between OP risk and several air pollutants. Then air pollution scores (APS) were constructed to assess the combined effects of multiple air pollutants on OP risk. Finally, we constructed a genetic risk score (GRS) based on a large genome-wide association study of femoral neck bone mineral density and assessed whether single or combined exposure to air pollutants modifies the effect of genetic risk on OP and fracture risk.ResultsPM2.5, NO2, NOx, and APS were significantly associated with an increased risk of OP/fracture. OP and fracture risk raised with increasing concentrations of air pollutants: compared to the lowest APS quintile group, subjects in the highest quintile group had a hazard ratio (HR) (95% CI) estimated at 1.140 (1.072–1.213) for OP and 1.080 (1.026–1.136) for fracture. Moreover, participants with low GRS and the highest air pollutant concentration had the highest risk of OP, the HRs (95% CI) of OP were 1.706 (1.483–1.964), 1.658 (1.434–1.916), 1.696 (1.478–1.947), 1.740 (1.506–2.001) and 1.659 (1.442–1.908), respectively, for PM2.5, PM10, PM2.5−10, NO2, and NOx. Similar results were also observed for fractures. Finally, we assessed the joint effect of APS and GRS on the risk of OP. Participants with higher APS and lower GRS had a higher risk of developing OP. Similar results were observed in the joint effect of GRS and APS on fracture.ConclusionsWe found that exposure to air pollution, individually or jointly, could improve the risk of developing OP and fractures, and increased the risk by interacting with genetic factors.

Copyright of Chinese Journal of Contemporary Pediatrics is the property of Xiangya Medical Periodical Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Worldwide, around 3 billion people rely on solid fuel for their daily energy needs. Household air pollution secondary to solid fuel burning is a major risk factor for respiratory mobility among vulnerable populations. This study aimed to investigate the respiratory symptoms associated with solid fuel usage, the level of kitchen fuel smoke exposure and its association with respiratory symptoms among reproductive-aged women in Sri Lanka, where most households exclusively use firewood as the primary cooking fuel.Methods: A descriptive cross-sectional study was conducted among 403 reproductive-aged women (15 to 49 years) in the Central Province, Sri Lanka. A structured interviewer-administered questionnaire was used to collect data, and an exposure assessment was done using a breath carbon monoxide monitor.Results: After adjusting for potential confounding factors by the logistic regression models, the odds ratios (OR) of the liquid petroleum gas-only users for at least one respiratory symptom relevant to cough (OR: 0.39; 95% confidence interval [CI]: 0.20-0.78), wheezing (OR: 0.47; 95% [CI]: 0.26-0.87), and dyspnea (OR: 0.44; 95% CI: 0.24-0.84) were significantly lower compared to firewood-only users. The mean of expired air carbon monoxide and estimated carboxyhemoglobin levels of liquid petroleum gas-only users (2.84 ± 2.85 ppm; 1.08 ± 0.46%) were significantly lower than those of firewood-only users (5.27 ± 4.64 ppm; 1.47 ± 0.74%).Conclusions: The use of firewood increased the risk of respiratory symptoms among reproductive-aged women in Sri Lanka. Health education focused on positive behavioral changes and effective and efficient clean energy policies are recommended to mitigate the risk associated with solid fuel smoke exposure. [ABSTRACT FROM AUTHOR]

It is imperative to conduct collaborative planning for greenhouse gas and air pollutant control in China. At present, although the country has certain policies, laws, standards, institutions, and theoretical research as the basis for such planning, there are still deficiencies such as insufficient strategic coordination and a lack of effective connections of relevant plans, and the goals and requirements of collaborative control of greenhouse gases and air pollutants have not been fully incorporated into the territorial space planning, regional planning, and industrial development planning. In these circumstances, this study carries out text analysis and normative analysis and finds that the idea of improving the collaborative planning of greenhouse gas and air pollutant control mainly includes two aspects. The first is to strategically coordinate the collaborative control of greenhouse gases and air pollutants and determine its direction and long-term goal. Second, the collaborative control of greenhouse gases and air pollutants should be specifically deployed and arranged through the coordination of relevant plans. However, in order to fully realize the collaborative control of greenhouse gases and air pollutants by relevant plans, the following four aspects need to be guaranteed: ① We should further strengthen the coordination among the main bodies and strengthen unified supervision so as to provide the main body guarantee and supervision guarantee for the collaboration of related planners. ② We should strengthen theoretical research and further expand the scope of research to explore the relation⁃ ship between greenhouse gases (other than carbon dioxide) and air pollutants (including new pollutants). ③ We should formulate and re⁃ vise relevant policies, laws, and standards in a timely manner to assist collaborative planning. ④ We should actively carry out the pilot practice of collaborative control of greenhouse gases and air pollutants to explore the collaborative control mode that can be replicated and promoted and to accumulate practical experience for collaborative control planning. [ABSTRACT FROM AUTHOR]

The decline in NO2 and PM2.5 pollutant levels were observed during COVID-19 around the world, especially during lockdowns. Previous studies explained such observed decline with the decrease in human mobility, overlooking the meteorological changes that could simultaneously mediate air pollution levels. This pitfall could potentially lead to over- or under-estimation of the effect of COVID-19 on air pollution. This study, thus, aims to re-evaluate the impact of COVID-19 on NO2 and PM2.5 pollutant levels in Singapore, by incorporating the effect of meteorological parameters in predicting NO2 and PM2.5 baseline in 2020 using machine learning methods. The results show that the mean NO2 and PM2.5 declined by 12% and 19%, which were less than the observed drops (i.e. 54% and 29%, respectively) without considering the effect of meteorological parameters. As two proxies for change in human mobility, taxi availability and carpark availability were found to increase and decrease by a maximum of 12.6% and 9.8%, respectively, in 2020 from 2019. Two correlation analyses were conducted to investigate how human mobility influenced air pollutant levels: one between daily PM2.5 and mobility changes at a regional scale and the other between weekly NO2 and mobility changes at a spatial resolution of 0.01°. The NO2 variation was found to be more associated with the change in human mobility and a cluster of stronger correlations was found in the South and East Coast of Singapore. Contrarily, PM2.5 and mobility had a weak correlation, which could be due to the limit of a coarse spatial resolution. [ABSTRACT FROM AUTHOR]

Copyright of Refractories / Naihuo Cailiao is the property of Naihuo Cailia (Refractories) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • Cooking oil fume (COF) quantification method was developed. • Triglycerides in COFs were derivatized via non-catalytic transesterification. • The yield of non-catalytic transesterification was 97.2 %, showing high reliability. • This analytical method contributes to indoor air quality control. Cooking oil fumes (COFs), which are aerosols formed via the interaction of water and oil (triglycerides, TGs), contribute to the incidence of lung cancer. Control of indoor COF concentrations has not yet been established, as reliable methods for quantifying COFs have not been developed. This study aimed to quantify COFs based on the derivatization of TGs via a non-catalytic transesterification reaction. Our investigation into the thermolytic behaviors of oil confirmed that COFs generated at ≤ 200 °C primarily consisted of oil and water vapor. Alkali-catalyzed transesterification is commonly used for the derivatization of TGs. However, it is sensitive to impurities such as free fatty acids and water, leading to side reactions. Furthermore, this reaction requires additional purification steps to separate the catalyst and has long reaction times (≥120 min). In contrast, non-catalytic transesterification is not sensitive to impurities and can achieve a conversion yield of over 97 wt% within 1 min. The conversion yield of non-catalytic transesterification was higher than that of the alkali-catalyzed method, indicating that non-catalytic transesterification could be a more reliable method for quantifying COFs. Additionally, the concentration of COFs determined using non-catalytic derivatization was higher than that obtained using the conventional aerosol analysis method (PM gravimetric method). This approach addresses a critical gap in current practices, offering a valuable tool for assessing and regulating COF levels in indoor spaces. Consequently, this contributes to broader efforts aimed at mitigating potential adverse health effects associated with exposure to COFs. [ABSTRACT FROM AUTHOR]

Hyderabad, similar to many cities worldwide, has experienced accelerated urbanization, leading to increased surface temperature and air pollution. The present study investigated the relationship between land surface temperature (LST) and various air pollutants, urbanization, surface indices, and meteorological parameters, which are associated with Sustainable Development Goals (SDGs), especially Goal 13 (Climate Action) and Goal 11 (Sustainable Cities and Communities). The effect of air pollution on LST across seasons was also examined for five years (2018–2022). LST images collected from MODIS satellite. Data on air pollutants and meteorological parameters were collected from air quality monitoring stations. The results showed that PM 2.5 exceeded the WHO guidelines. A weak or moderate relationship was observed between LST and individual air pollutants. However, the association significantly improved when all air pollutants were considered simultaneously. The relationship improved even further when additional parameters such as Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), road line density (RLD), and global population density (GPD), were also included. The resulting relationship was very strong (R2 > 0.80) during the summer and winter seasons. The study identified that NH 3 had a prominent influence on LST during winter, while PM 2.5 and NH 3 exhibited a higher influence during summer. The research findings emphasized that LST variations were influenced by both air pollutants and meteorological conditions, along with urbanization factors represented by various parameters and indices. The research underscores the importance of considering these findings in future studies. It suggests the need to explore efficient approaches to address the combined problem of rising LST and concentration of air pollutants in urban areas. [Display omitted] • Relationship of land surface temperature (LST) with air pollutants was investigated. • LST was highly affected by air pollutants and meteorological parameters. • Strong relationship of LST was observed with all parameters in summer (R2 = 0.87) & winter (R2 = 0.85). • PM 2.5 & NH 3 in summer and NH 3 in winter were main contributors to changes in LST. [ABSTRACT FROM AUTHOR]

Currently, Tangshan confronts the dual challenge of elevated carbon emissions and substantial pollution discharge from the iron and steel industries (ISIs). While significant efforts have been made to mitigate air pollutants and carbon emissions within the ISIs, there remains a gap in comprehending the control of carbon emissions, air pollutant emissions, and their contributions to air pollutant concentrations at the enterprise level. In this study, we devised the Air Pollutant and Carbon Emission and Air Quality (ACEA) model to identify enterprises with noteworthy air pollution and carbon emissions, as well as substantial contributions to air pollutant concentrations. We constructed a detailed inventory of air pollutants and CO2 emissions from the iron and steel industry in Tangshan for the year 2019. The findings reveal that in 2019, Tangshan emitted 5.75 × 104 t of SO2, 13.47 × 104 t of NOx, 3.55 × 104 t of PM10, 1.80 × 104 t of PM2.5, 5.79 × 106 t of CO and 219.62 Mt of CO2. The ACEA model effectively pinpointed key links between ISI enterprises emitting air pollutants and carbon dioxide, notably in pre-iron-making processes (coking, sintering, pelletizing) and the Blast furnace. By utilizing the developed air pollutant emission inventory, the CALPUFF model assessed the impact of ISI enterprises on air quality in the Tangshan region. Subsequently, we graded the performance of air pollutant and CO2 emissions following established criteria. The ACEA model successfully identified eight enterprises with significant air pollution and carbon emissions, exerting notable influence on air pollutant concentrations. Furthermore, the ACEA outcomes offer the potential for enhancing regional air quality in Tangshan and provide a scientific instrument for mitigating air pollutants and carbon emissions. The effective application of the ACEA model in Tangshan’s steel industry holds promise for supporting carbon reduction initiatives and elevating environmental standards in other industrial cities across China.

The rapid urbanization and growing number of motor vehicles in China have led to a significant increase in NO2 emissions, posing a severe threat to the air quality in cities. Road traffic pollution has emerged as a significant environmental issue in China. Exploring the utilization of landscape plants for air pollutant mitigation and assessing the influence of various plant concentrations on reducing air pollution holds great significance in urban ecological environment protection and urban development. Through field surveys and data collection in January 2022, the objectives of this study are to explore the relationship between road meteorological factors and the reduction in air pollutant concentrations in Nanjing city’s road green spaces and to investigate the influence of plant configuration in road green spaces on pollutant concentration. The findings demonstrate a distinct positive correlation between road traffic volume during winter peak hours and the concentration of NO2 pollution gas. Furthermore, meteorological factors, including temperature and light intensity, strongly correlate with air pollutant concentrations. Open green spaces with ventilated structures and high tree planting density (deciduous trees are preferred) exhibit optimal purification effects. Excessive or insufficient planting density hinders the purifying function of green belts. In conclusion, our research on plant configurations and air pollutant concentrations in Nanjing City during the winter suggests that the recommended road green space plant configuration in Nanjing is a combination of arbor (deciduous tree), shrub, and grass.

Parkinson's disease (PD) is a progressive neurodegenerative disorder, and its global incidence is on the rise. There is increasing interest in understanding the role of air pollution in the development of human disease. Although the precise mechanisms are not understood, several epidemiological studies have reported a positive association between air pollution and the risk of PD. However, the various pollutants studied, endpoints measured, and differences in study design yield conflicting results. This review summarizes recent evidence regarding the relationship between particulate matter, ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide and PD. Limitations and challenges are also discussed, with suggestions for future work to understand the true effects of air pollution on PD.

Air pollution is a significant contributor of cardiovascular diseases, including ischaemic stroke (IS), with substantial mortality and morbidity. However, associations between air pollution and IS remain unclear. Limited data are available on the relationship between IS and individual air pollutants. In this systematic review, we present an overview of the current literature about various individual ambient air pollutants that are believed to contribute towards incidence of hospitalization and mortality related to IS.

BackgroundPhosphatase and tensin homolog (Pten) is capable of mediating microbe-induced immune responses in the gut. Thus, Pten deficiency in the intestine accelerates colitis development in Il10-/- mice. As some ambient pollutants inhibit Pten function and exposure to ambient pollutants may increase inflammatory bowel disease (IBD) incidence, it is of interest to examine how Pten inhibition could affect colitis development in genetically susceptible hosts.MethodsWith human colonic mucosa biopsies from pediatric ulcerative colitis and non-IBD control subjects, we assessed the mRNA levels of the PTEN gene and the gene involved in IL10 responses. The data from the human tissues were corroborated by treating Il10-/-, Il10rb-/-, and wild-type C57BL/6 mice with Pten-specific inhibitor VO-OHpic. We evaluated the severity of mouse colitis by investigating the tissue histology and cytokine production. The gut microbiome was investigated by analyzing the 16S ribosomal RNA gene sequence with mouse fecal samples.ResultsPTEN and IL10RB mRNA levels were reduced in the human colonic mucosa of pediatric ulcerative colitis compared with non-IBD subjects. Intracolonic treatment of the Pten inhibitor induced colitis in Il10-/- mice, characterized by reduced body weight, marked colonic damage, and increased production of inflammatory cytokines, whereas Il10rb-/- and wild-type C57BL/6 mice treated with the inhibitor did not develop colitis. Pten inhibitor treatment changed the fecal microbiome, with increased abundance of colitogenic bacteria Bacteroides and Akkermansia in Il10-/- mice.ConclusionsLoss of Pten function increases the levels of colitogenic bacteria in the gut, thereby inducing deleterious colitis in an Il10-deficient condition.

With a growing economy, the living standard of people has improved which has led to increased use of urban motor vehicles globally. Consequently, the concentration of nitrogen dioxide (NO2) has increased in the ambient air, becoming a major pollutant in urban areas. Plant leaves can absorb, adsorb and fix nitrogen oxides to some extent. Interestingly, NO2 has been recognized as a positive/negative regulator of plant growth. To comprehensively understand the effect of NO2-induced pollution on plants, Bougainvillea spectabilis seedlings were fumigated with different concentrations of nitrogen dioxide (NO2) for a short period in the current study. Further, the induced morphological, physiological, and biochemical changes were measured in the treated as well as untreated seedlings. NO2 exposure caused yellow-brown spotting on the leaf blades in B. spectabilis, which could be the symptoms of oxidative damage. Our findings also reflected the changes in antioxidant enzyme activity and peroxidation of membrane lipids. In addition, the levels of osmotic regulatory substances were also found to be altered to different degrees. In addition, the activities of nitrogen metabolism-related enzymes varied, mainly affecting amino acid metabolism. Overall, the current study would provide a theoretical and scientific basis for selecting and allocating plants in NO2-contaminated areas to manage the pollutants level.

L-Selenomethionine is one of the important organic selenium sources. The supplementation of L-selenomethionine in diets is significant to improve the health of pigs. Ammonia is a major pollutant in the atmosphere and piggery, posing a threat to human and animal health. Although ammonia exposure can damage the heart, the mechanism of cardiac toxicity by ammonia is still unknown. In this study, we investigated the mechanism of cardiac injury induced by ammonia exposure in pigs and the protective effect of L-selenomethionine on its cardiotoxicity. The results showed that the blood ammonia content of pig increased significantly in ammonia group, the expressions of energy metabolism-related genes (LDHA, PDK4, HK2, and CPTIB) and the oxidative stress indexes were significantly changed (P < 0.05), the AMPK/PPAR-γ/NF-κB signaling pathways were activated, the chromatin edge aggregation and nuclear pyknosis were observed in ultrastructure, the apoptotic cells were significantly increased (P < 0.05), and the mRNA and protein expressions of apoptosis-related genes (Bcl-2, Bax, Cyt-c, caspase-3, and caspase-9) were significantly affected (P < 0.05). The above changes were significantly alleviated in ammonia + L-selenomethionine group, but there were still significant differences compared with the C group (P < 0.05). Our results indicated that ammonia exposure could cause energy metabolism disorder and oxidative stress and induce apoptosis of cardiomyocytes through AMPK/PPAR-γ/NF-κB pathways, which could lead to cardiac injury and affect cardiac function. L-Selenomethionine could effectively alleviate the cardiac damage caused by ammonia and antagonize the cardiotoxicity of ammonia. [ABSTRACT FROM AUTHOR]

The aim of this study is (i) to reveal the bioclimatic comfort zones depending on the Discomfort Index (DI) in Şanlıurfa province with the help of geographic information system (GIS), and (ii) to determine the relationship between bioclimatic comfort levels and Air Quality Index (AQI) levels in the Şanlıurfa city. For all analyzes made in the study, annual and monthly average values of meteorological (temperature, relative humidity, wind speed) and air pollutant parameters (for PM10 and SO2) between the years 2006–2021 were used. In this context, meteorological parameters, air pollutant parameters, temporal changes of DI and AQI (for PM10 and SO2) parameters were determined by Mann-Kendal (MK) trend analysis and the relationships between all these parameters were determined by Pearson correlation analysis. The most suitable (21 ≤ DI < 24) months in terms of bioclimatic comfort in Şanlıurfa province were June and September. In the Şanlıurfa city, annual and monthly average AQIPM10 values were generally in the "good" and "moderate" class, while AQISO2 values were in the "good" class in all years and all months. While the annual average temperature values showed a statistically significant increase, the annual average wind speed and PM10 and AQIPM10 values showed a statistically significant decrease. There was a negative "weak" correlation (r = − 0.028) between DI and AQIPM10, and a positive "moderate" correlation between DI and AQISO2 (r = 0.449; p < 0.05). In addition, correlations between DI, PM10, and SO2 were significant at the p < 0.05 level. [ABSTRACT FROM AUTHOR]

Objective: Increasing evidence suggested that gaseous pollutants were associated with the development of autoimmune diseases, while there were few studies on the association between gaseous pollutants and Sjögren's syndrome (SS). This study sought to assess the relationship between exposure to several gaseous pollutants and the hospitalizations for SS. Methods: The data regarding SS hospitalizations, gaseous pollutants, and meteorological factors in Hefei from 2016 to 2021 were collected. A distributed lag non-linear model combined with a generalized linear model were adopted to analyze the association between gaseous pollutants and SS hospitalizations, and stratified analyses were also conducted. Results: We detected significant associations between gaseous pollutants (NO2, SO2, O3, CO) and SS hospitalizations. Exposure to NO2 was linked with the elevated risk of hospitalizations for SS (RR=1.026, lag1 day). A positive correlation between CO exposure and hospitalizations for SS was found (RR=1.144, lag2 day). In contrast, exposure to SO2, O3 was respectively related to the decreased risk of hospitalizations for SS (SO2: RR=0.897, lag14 day; O3: RR=0.992, lag9 day). Stratified analyses found that female patients were more vulnerable to these gaseous pollutants. SS patients = 65 years were more susceptible to NO2, CO exposure, and younger patients were more vulnerable to O3 exposure. In addition, exposure to O3, CO in cold season were more likely to affect hospitalizations for SS. Conclusion: Our results demonstrated a significant association between exposure to NO2, CO and elevated risk of hospitalizations for SS, and SO2, O3 exposure might be linked to reduced risk of SS hospitalizations. [ABSTRACT FROM AUTHOR]

Vehicle air pollution is a significant problem for health and climate change that can be solved by several approaches. The route is one of the many components to be considered. In this work, we propose a statistical analysis of a large FCD database in November 2017 in Lyon (France) in order to find alternative sustainable trips and evaluate potential emission reductions (CO2, NOx, PM10). To this end, an innovative framework was built. First, we assessed vehicle speeds for each network section and the fifteen-minute period, when this information was reachable. Then, we used a regression random forest (RF) algorithm to fill in the missing data. This dynamical speed map allowed us to search for fewer pollutant trips, for the first ten days of November. By using COPERT emission factors (EFs) and the time-dependent Dijkstra algorithm, we successfully identified between 51% and 72% of alternative sustainable paths, depending on the engine technology and the pollutant. We investigated the influence of vehicle technology. In all cases, the number of alternative trips found tends to be the same as soon as the emission savings exceed 5%. Moreover, about 400 trips out of 11,000 have the potential to mitigate about 20% of emissions. [ABSTRACT FROM AUTHOR]

A key challenge in building machine learning models for time series prediction is the incompleteness of the datasets. Missing data can arise for a variety of reasons, including sensor failure and network outages, resulting in datasets that can be missing significant periods of measurements. Models built using these datasets can therefore be biased. Although various methods have been proposed to handle missing data in many application areas, more air quality missing data prediction requires additional investigation. This study proposes an autoencoder model with spatiotemporal considerations to estimate missing values in air quality data. The model consists of one-dimensional convolution layers, making it flexible to cover spatial and temporal behaviours of air contaminants. This model exploits data from nearby stations to enhance predictions at the target station with missing data. This method does not require additional external features, such as weather and climate data. The results show that the proposed method effectively imputes missing data for discontinuous and long-interval interrupted datasets. Compared to univariate imputation techniques (most frequent, median and mean imputations), our model achieves up to 65% RMSE improvement and 20–40% against multivariate imputation techniques (decision tree, extra-trees, k-nearest neighbours and Bayesian ridge regressors). Imputation performance degrades when neighbouring stations are negatively correlated or weakly correlated. [ABSTRACT FROM AUTHOR]

Rationale: Studies examining the association of short-term air pollution exposure and daily deaths have typically been limited to cities and used citywide average exposures, with few using causal models.Objectives: To estimate the associations between short-term exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and all-cause and cause-specific mortality in multiple US states using census tract or address exposure and including rural areas, using a double negative control analysis.Methods: We conducted a time-stratified case-crossover study examining the entire population of seven US states from 2000-2015, with over 3 million non-accidental deaths. Daily predictions of PM2.5, O3, and NO2 at 1x1 km grid cells were linked to mortality based on census track or residential address. For each pollutant, we used conditional logistic regression to quantify the association between exposure and the relative risk of mortality conditioning on meteorological variables, other pollutants, and using double negative controls.Results: A 10 μg/m3 increase in PM2.5 exposure at the moving average of lag 0-2 day was significantly associated with a 0.67% (95%CI: 0.34-1.01%) increase in all-cause mortality. 10 ppb increases in NO2 or O3 exposure at lag 0-2 day were marginally associated with and 0.19% (95%CI: -0.01-0.38%) and 0.20 (95% CI-0.01, 0.40), respectively. The adverse effects of PM2.5 persisted when pollution levels were restricted to below the current global air pollution standards. Negative control models indicated little likelihood of omitted confounders for PM2.5, and mixed results for the gases. PM2.5 was also significantly associated with respiratory mortality and cardiovascular mortality.Conclusions: Short-term exposure to PM2.5 and possibly O3 and NO2 are associated with increased risks for all-cause mortality. Our findings delivered evidence that risks of death persisted at levels below currently permissible. [ABSTRACT FROM AUTHOR]

Air pollution is one of the severe environmental issues in Chongqing. Many measures made by the government for improving air quality have been put into use these past few years, while the influence of these measures remains unknown. This study analyzed the changes in the air quality of the urban area of Chongqing between 2015 and 2021 using a complete in situ observation dataset that all missing data were filled by the interpolation of a low-rank tensor completion model with truncate nuclear norm minimization (LRTC-TNN). The results include: (1) the LRTC-TNN model robustly performs to reconstruct missing data of pollutant concentrations with an R2 of 0.93 and an RMSE of 7.78; (2) the air quality index (AQI) decreases by 15.96%, and the total polluted days decrease by 21.05% from 2015 to 2021, showing an obvious promotion in air quality; and (3) the changing air quality is attributed to decreasing concentrations of PM2.5 (34.10%), PM10 (25.03%), and NO2 (5.53%) from 2015 to 2021, whereas an increasing concentration of O3 (10.49%) is observed. The processing method for missing data, intact AQI datasets, and analysis of changes are beneficial to policy-making for environmental improvement and fill the gap in the field of data interpolation for air quality datasets in mountainous areas. [ABSTRACT FROM AUTHOR]