Authorities have long proved the utility of bioindicators in monitoring the state of environmental pollution. Some biological indicators can measure environmental pollutant levels, and many tree species have been tested for suitability for monitoring purposes. The differences in morphological characteristics in the trees have demonstrated the effects of human activities on different materials. Measuring bark and wood biomass from contaminated sites was identified and directly compared with those from a clean site or areas characterized by distinct contamination sources. However, preliminary results demonstrate the approach\'s potential in the realization of strategies for disease control and promoting health to reduce environmental and health inequalities in at-risk urban areas. Picea orientalis L. and Cedrus atlantica Endl., especially their bark, can be regarded as a more robust storage of Cu (37.95 mg/kg) and Mn (188.25 mg/kg) than Pinus pinaster, Cupressus arizonica, and Pseudotsuga menziesii, which and is therefore a better bioindicator for Cu and Mn pollution. Considering the total concentrations as a result of the study, the pollution is thought to be caused by environmental problems and traffic in the region. The deposition of Cu, Mn, Ni, and Zn elements was found P. menziesii (60, 443, 58, and 258 mg/kg) and P. orientalis (76, 1684, 41, and 378 mg/kg) and seems to reflect atmospheric quite clearly compared to P. pinaster, C. arizonica, and C. atlantica. Ni and Zn concentrations have significantly increased since 1983, and P. menziesii and P. orientalis can be potentially valuable bioindicators for emphasizing polluted fields.

To evaluate the modification of allergic dermatitis on the association between PM exposure and allergic rhinitis in preschool children. This cross-sectional study was based on a questionnaire conducted between June 2019 and June 2020 to caregivers of children aged 3 to 6 years in the kindergartens of 7 Chinese cities to collect information on allergic rhinitis and allergic dermatitis. A mature machine learning-based space-time extremely randomized trees model was applied to estimate early-life, prenatal, and first-year exposure of PM1, PM2.5 and PM10 at 1 km×1 km resolution. A combination of multilevel logistic regression and restricted cubic spline functions was used to quantitatively assess whether allergic dermatitis modifies the associations between size-specific PM exposure and the risk of childhood allergic rhinitis. The results showed that out of 28 408 children, 14 803 (52.1%) were boys and 13 605 (47.9%) were girls; the age of children ranged from 3.1 to 6.8 years, with a mean age of (4.9±0.9) years, of which 3 586 (12.6%) were diagnosed with allergic rhinitis. Among all children, 17 832 (62.8%) were breastfed for more than 6 months and 769 (2.7%) had parental history of atopy. A total of 21 548 children (75.9%) had a mother with an educational level of university or above and 7 338 (29.6%) had passive household cigarette smoke exposure. The adjusted ORs for childhood allergic rhinitis among the children with allergic dermatitis as per interquartile range (IQR) increase in early-life PM1(9.8 μg/m3), PM2.5 (14.9 μg/m3) and PM10 (37.7 μg/m3) were significantly higher than the corresponding ORs among the children without allergic dermatitis [OR: 1.45, 95%CI (1.26, 1.66) vs. 1.33, 95%CI (1.20, 1.47), for PM1; OR: 1.38, 95%CI (1.23, 1.56) vs. 1.32, 95%CI (1.21, 1.45), for PM2.5; OR: 1.56, 95%CI (1.31, 1.86) vs. 1.46, 95%CI (1.28, 1.67), for PM10]. The interactions between allergic dermatitis and size-specific PM exposure on childhood allergic rhinitis were statistically significant (Z value=19.4, all P for interaction<0.001). The similar patterns were observed for both prenatal and first-year size-specific PM exposure and the results of the dose-response relationship were consistent with those of the logistic regression. In conclusion, allergic dermatitis, as an important part of the allergic disease progression, may modify the association between ambient PM exposure and the risk of childhood allergic rhinitis. Children with allergic dermatitis should pay more attention to minimize outdoor air pollutants exposure to prevent the further progression of allergic diseases.
本研究评估特应性皮炎在颗粒物暴露与学龄前儿童过敏性鼻炎发生风险关联中的效应修饰作用。采用横断面研究的设计，通过问卷调查的方式于2019年6月至2020年6月在中国7个城市的幼儿园收集了共计28 408名3~6岁学龄前儿童有关过敏性鼻炎和特应性皮炎的信息。运用一种成熟的基于机器学习的时空模型以1 km的空间分辨率水平估算不同城市儿童生命早期、孕期和出生后第1年PM1、PM2.5和PM10暴露水平。采用多水平logistic回归和暴露反应关系相结合的方法定量评估特应性皮炎作为效应修饰因子是否会改变不同粒径颗粒物暴露与儿童过敏性鼻炎发生风险的关联。结果显示，在28 408名儿童中，男孩为14 803名（52.1%），女孩为13 605名（47.9%）；年龄范围是3.1~6.8岁、（4.9±0.9）岁，其中患过敏性鼻炎的儿童为3 586名（12.6%）。在总人群中，母乳喂养持续时间大于6个月的儿童为17 832名（62.8%），父母有过敏史的为769名（2.7%）。母亲教育水平为大学及以上的儿童为21 548名（75.9%）。有被动吸烟暴露的儿童为7 338名（29.6%）。生命早期PM1（9.8 μg/m3）、PM2.5（14.9 μg/m3）和PM10（37.7 μg/m3）每增加一个四分位区间（IQR）浓度，儿童过敏性鼻炎调整后的OR值在特应性皮炎儿童中高于无特应性皮炎儿童中对应的OR值［PM1：OR=1.45，95%CI（1.26，1.66）vs. OR=1.33，95%CI（1.20，1.47）；PM2.5：OR=1.38，95%CI（1.23，1.56）vs. OR=1.32，95%CI（1.21，1.45）；PM10：OR=1.56，95%CI（1.31，1.86）vs. OR=1.46，95%CI（1.28，1.67）］。特应性皮炎与不同粒径PM暴露对儿童过敏性鼻炎的交互作用差异有显著的统计学意义（Z值=19.4，交互作用P值均<0.001）。在孕期和出生后第1年也观察到了类似的结果，且剂量反应关系的结果与logistic回归的结果具有一致性。综上，作为过敏性疾病进程重要环节的特应性皮炎可能会修饰大气颗粒物暴露与儿童过敏性鼻炎发生风险的关联。提示患特应性皮炎的儿童更应重视减少室外空气污染物的暴露，防止过敏性疾病的发生和进一步发展。.

In the confined space of the underground coal mine, which is dominated by transportation lanes, explosion-proof diesel-powered trackless rubber-wheeled vehicles are becoming the main transportation equipment, and the exhaust gas produced by them is hazardous to the health of workers and pollutes the underground environment. In this experiment, a similar test platform is built to study the effects of wind speed, vehicle speed, and different wind directions on the diffusion characteristics of exhaust gas. In this paper, CO and SO2 are mainly studied. The results show that the diffusion of CO and SO2 gas is similar and the maximum SO2 concentration only accounts for 11.4% of the CO concentration. Exhaust gas is better diluted by increasing the wind speed and vehicle speed, respectively. Downwind is affected by the reverse wind flow and diffuses to the driver\'s position, which is easy to cause occupational diseases. When the wind is a headwind, the exhaust gases spread upwards and make a circumvention movement, gathering at the top. When the wind speed and vehicle speed are both 0.6 m/s, the CO concentration corresponds to the change trend of the Lorentz function when the wind is downwind and the CO concentration corresponds to the change trend of the BiDoseResp function when the wind is headwind. The study of exhaust gas diffusion characteristics is of great significance for the subsequent purification of the air in the restricted mine space and the protection of the workers\' occupational health.

BACKGROUND: Air pollution is a significant issue for a developing country like India and the air quality index (AQI) forecasting helps to predict air quality levels in advance and allows individuals to take precautionary measures to protect their health.
OBJECTIVE: The study aimed to forecast the AQI for an industrial area (SIDCUL, Haridwar City) using a time series regression model.
METHODS: Three years of existing AQI data points (post-COVID-19) were collected from the Uttarakhand Pollution Control Board for the SIDCUL area of Haridwar City and tried to know the status of AQI values for the following 12 months. Trend and seasonality components were seen through the decomposition process. Further, the augmented Dickey-Fuller test was applied to check the stationarity of the series before finalizing the best-suited time series model for forecasting the AQI values.
RESULTS: With the help of autocorrelation function (ACF)/partial ACF plots, a seasonal autoregressive integrated moving average (ARIMA) (0,1,0) (1,0,0)[12] model was selected with the minimum akaike information criterion (253.143) and mean absolute percentage error (17.42%). The AQI values have also been forecasted for this industrial area (SIDCUL) for the following year.
CONCLUSIONS: The seasonal ARIMA (0,1,0) (1,0,0)[12] model may be helpful to forecast the AQI values for a nonstationary time series dataset. Research indicates that the air of the SIDCUL area will become moderately polluted and may cause breathing discomfort to asthma patients\' health. The scientists might apply this model to other polluted regions of the country so that the public and the government can take preventive measures in advance.

Over the past two decades the Global South is witnessing unprecedented economic transformation and Asian Cities in particular have a remarkable upsurge. Coimbatore, an industrial city in Southern India with an estimated population of 2 million (in 2022) is witnessing a rapid transition in terms of infrastructure development. In this context, the present study attempts to assess the particulate matter (PM10 and PM2.5) emissions at road network construction sites and the heavy metal fractionation in the road dust/sediment samples with a core focus to quantify the bioavailable fraction of metals (Fe, Cu, Cr, Cd, Pb and Ni) and its source apportionment in the road side dust/sediment samples. About 60 composite road dust/sediment samples were collected for heavy metal fractionation analysis in the six arterial roads that undergo core developments like construction of road over bridges, additional road incorporation and street expansions. PM monitoring revealed that 24 h average PM2.5 (47 µg/m3) and PM10 (69 µg/m3) concentrations at many construction sites exceeded 24 h average recommended by WHO guidelines [PM2.5 (15 µg/m3) and PM10 (45 µg/m3), respectively]. The bioavailable fractions of Fe, Cu, Cr and Cd are notably higher in the roadside sediment samples at road construction sites. Health Risk assessment, such as carcinogenic risks (Children-4.41 × 10-2, Adult-3.598 × 10-6) and non-carcinogenic risks, inferred substantial risks at high intensity construction sites with statistical analyses, including PCA and cluster analysis, indicating considerable anthropogenic influences in the heavy metal fractions.

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UNASSIGNED: In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous.
UNASSIGNED: Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings.
UNASSIGNED: The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21.
UNASSIGNED: Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.

UNASSIGNED: Air pollution is a recognized risk factor associated with chronic diseases, including respiratory and cardiovascular conditions, which can lead to physical and cognitive impairments in later life. Although these losses of function, individually or in combination, reduce individuals\' likelihood of living independently, little is known about the association of air pollution with this critical outcome.
UNASSIGNED: To investigate associations between air pollution and loss of independence in later life.
UNASSIGNED: This cohort study was conducted as part of the Environmental Predictors Of Cognitive Health and Aging study and used 1998 to 2016 data from the Health and Retirement Study. Participants included respondents from this nationally representative, population-based cohort who were older than 50 years and had not previously reported a loss of independence. Analyses were performed from August 31 to October 15, 2023.
UNASSIGNED: Mean 10-year pollutant concentrations (particulate matter less than 2.5 μm in diameter [PM2.5] or ranging from 2.5 μm to 10 μm in diameter [PM10-2.5], nitrogen dioxide [NO2], and ozone [O3]) were estimated at respondent addresses using spatiotemporal models along with PM2.5 levels from 9 emission sources.
UNASSIGNED: Loss of independence was defined as newly receiving care for at least 1 activity of daily living or instrumental activity of daily living due to health and memory problems or moving to a nursing home. Associations were estimated with generalized estimating equation regression adjusting for potential confounders.
UNASSIGNED: Among 25 314 respondents older than 50 years (mean [SD] baseline age, 61.1 [9.4] years; 11 208 male [44.3%]), 9985 individuals (39.4%) experienced lost independence during a mean (SD) follow-up of 10.2 (5.5) years. Higher exposure levels of mean concentration were associated with increased risks of lost independence for total PM2.5 levels (risk ratio [RR] per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.10), PM2.5 levels from road traffic (RR per 1-IQR of 10-year mean, 1.09; 95% CI, 1.03-1.16) and nonroad traffic (RR per 1-IQR of 10-year mean, 1.13; 95% CI, 1.03-1.24), and NO2 levels (RR per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.08). Compared with other sources, traffic-generated pollutants were most consistently and robustly associated with loss of independence; only road traffic-related PM2.5 levels remained associated with increased risk after adjustment for PM2.5 from other sources (RR per 1-IQR increase in 10-year mean concentration, 1.10; 95% CI, 1.00-1.21). Other pollutant-outcome associations were null, except for O3 levels, which were associated with lower risks of lost independence (RR per 1-IQR increase in 10-year mean concentration, 0.94; 95% CI, 0.92-0.97).
UNASSIGNED: This study found that long-term exposure to air pollution was associated with the need for help for lost independence in later life, with especially large and consistent increases in risk for pollution generated by traffic-related sources. These findings suggest that controlling air pollution could be associated with diversion or delay of the need for care and prolonged ability to live independently.

OBJECTIVE: Snow cover serves as a unique indicator of environmental pollution in both urban and rural areas. As a seasonal cover, it accumulates various pollutants emitted into the atmosphere, thus providing insight into air pollution types and the relative contributions of different pollution sources. The aim of the study is to analyze the distribution of trace elements in snow cover to assess the anthropogenic influence on pollution levels, and better understand ecological threats.
METHODS: The study was conducted in rural areas around the village of Wólka in the Lublin Province of eastern Poland, and in urban districts of the city of Lublin, capital of the Province. Samples were analyzed using Inductively Coupled Plasma-Mass Spectrometry, the Enrichment Factor (EF), and ecological risk indices (RI), were calculated to evaluate the contamination and potential ecological risks posed by the metals.
RESULTS: The findings indicate higher concentrations of metals like sodium and iron in urban areas, likely due to road salt use and industrial activity, respectively. Enrichment factors showed significant anthropogenic contributions, particularly for metals like sodium, zinc, and cadmium, which had EF values substantially above natural levels. The potential ecological risk assessment highlighted a considerable ecological threat in urban areas compared to rural settings, primarily due to higher concentrations of metals.
CONCLUSIONS: The variation in metal concentrations between urban and rural snow covers reflects the impact of human activities on local environments. Urban areas showed higher pollution levels, suggesting the need for targeted pollution control policies to mitigate the adverse ecological impacts. This study underscores the importance of continuous monitoring and comprehensive risk assessments to effectively manage environmental pollution.

OBJECTIVE: Species of the genus Artemisia (Asteraceae) are weeds and ruderal plants growing in northern temperate regions of the world. Many of them are used in medicine and the cosmetic industry and for culinary purposes. Pollen grains of plants of this genus contain the most important aeroallergens.
METHODS: An aerobiological study conducted with the volumetric method in Lublin in 2001-2022. Trend lines for the season parameters were established. Spearman\'s correlation and stepwise regression analyses were carried out to determine relationships between various parameters of the pollen season and meteorological factors. PCA analysis was also carried out to visually compare the pollen seasons.
RESULTS: In Lublin, central-eastern Poland, the Artemisia pollen season lasted on average from the second ten days of July to the end of August, with its beginning depending on the temperature in April and May. The highest pollen concentrations were mainly recorded in the first half of August and were largely dependent on the mean temperature in June and July. The second peak in the pollen season recorded in September was associated with the presence of Artemisia annua pollen. Intense sunshine in June and the higher temperatures in June and July resulted in significant reduction in the Artemisia annual pollen sum (by 65%) over 22 years. Artemisia vulgaris is abundant in the Lublin region and contributes substantially to the amount of Artemisia pollen in the aeroplankton.
CONCLUSIONS: The downward trend in the amount of Artemisia pollen was a result of the increase in temperatures observed in the summer months, and the declining rainfall rates. The global warming effect is extremely unfavourable for plants of Artemisia vulgaris, as they require moist soil substrates for growth.