ENHANCING CDC AND EPA HEATRISK AND AIR QUALITY RISK RECOMMENDATIONS: A NARRATIVE REVIEW AND ACTION ALGORITHM FOR CARDIAC PATIENTS

Background: Emerging evidence suggests that air pollution is a significant but under recognized contributor to cardiovascular disease (CVD) mortality, even in middle age adults. This study evaluates the association between long term statewise air quality, as measured by median Air Quality Index (AQI) and cardiovascular mortality rates among adults aged 35–44 years across the United States over a 25-year period. Methods: We linked annual statewise median AQI data from EPA AQS (2000–2024) with CDC WONDER mortality records for non-infectious CVD in the 35–44 age group. States were ranked by mean AQI to define “Highest 10” and “Lowest 10” AQI cohorts. Mean annual cardiovascular crude death rates were compared between these groups using t-tests, and trends were visualized year-by-year. Correlation and linear regression analyses assessed the association between AQI and mortality across all state years as well. Results: States with the highest long-term AQI (poor air quality) had significantly higher mean cardiovascular mortality rates (mean 46.99 per 100,000) than states with the lowest AQI (good air quality) (mean 30.35 per 100,000; p = 0.01). Yearwise analysis showed a persistent gap in mortality rates with the highest AQI states consistently exhibiting greater CVD mortality across the study period. Linear regression confirmed a significant positive association between AQI and mortality (slope = 0.62, p < 0.001), although AQI alone explained only a modest portion of the variation (R 2 = 0.095). Conclusions: Higher long term air pollution exposure, as measured by AQI, is associated with increased cardiovascular mortality among U.S. adults aged 35–44 years. This relationship is robust at the extremes of air quality and persists over time. This highlights the need for public health policies to improve air quality as a means to reduce early onset CVD mortality. Further studies should explore mechanisms and policy interventions to mitigate this risk.

With the continuous progress of human production and life, air quality has become the focus of attention. In this paper, Beijing, Tianjin, Hebei, Shanxi, Shandong and Henan provinces were taken as the study area, where there are 58 air quality monitoring stations from which daily and monthly data are obtained. Firstly, the temporal characteristics of the air quality index (AQI) are explored. Then, the spatial distribution of the AQI is mapped by the inverse distance weighted (IDW) method, the ordinary kriging (OK) method and the Bayesian maximum entropy (BME) method. Additionally, cross-validation is utilized to evaluate the mapping results of these methods with two indexes: mean absolute error and root mean square interpolation error. Furthermore, the correlation analysis of meteorological factors, including precipitation anomaly percentage, precipitation, mean wind speed, average temperature, average water vapor pressure and average relative humidity, potentially affecting the AQI was carried out on both daily and monthly scales. In the study area and period, AQI shows a clear periodicity, although overall, it has a downward trend. The peak of AQI appeared in November, December and January. BME interpolation has a higher accuracy than OK. IDW has the maximum error. Overall, the AQI of winter (November), spring (February) is much worse than summer (May) and autumn (August). Additionally, the air quality has improved during the study period. The most polluted areas of air quality are concentrated in Beijing, the southern part of Tianjin, the central-southern part of Hebei, the central-northern part of Henan and the western part of Shandong. The average wind speed and average relative humidity have real correlation with AQI. The effect of meteorological factors such as wind, precipitation and humidity on AQI is putative to have temporal lag to different extents. AQI of cities with poor air quality will fluctuate greater than that of others when weather changes and has higher correlation with meteorological factors.

Poor air quality is implicated as a risk factor for cognitive impairment and dementia. Few studies have examined these associations longitudinally in well-characterized population-based cohorts with standardized annual assessment of both mild cognitive impairment (MCI) and dementia. We investigated the association between estimated ambient fine particulate matter (PM2.5 ) and risk of incident MCI and dementia in a post-industrial region known for historically poor air quality. Adults aged 65+ years in a population-based cohort (n=1572). Census tract level PM2.5 from Environmental Protection Agency (EPA) air quality monitors; Clinical Dementia Rating (CDR)®. We estimated ambient PM2.5 exposure (μg/m3 , single-year and 5-year averages) by geocoding participants' residential addresses to census tracts with daily EPA PM2.5 measurements from 2002 to 2014. Using Bayesian spatial regression modeling adjusted for age, sex, education, smoking history, and household income, we examined the association between estimated PM2.5 exposure and risk of incident MCI (CDR=0.5) and incident dementia (CDR ≥ 1.0). Modeling estimated single-year exposure, each 1μg/m3 higher ambient PM2.5 was associated with 67% higher adjusted risk of incident dementia (hazard ratio [HR]=1.669, 95% credible interval [CI]: 1.298, 2.136) and 75% higher adjusted risk of incident MCI (HR=1.746, 95% CI: 1.518, 2.032). Estimates were higher when modeling 5-year ambient PM2.5 exposure for incident dementia (HR=2.082, 95% CI: 1.528, 3.015) and incident MCI (HR=3.419, 95% CI: 2.806, 4.164). Higher estimated ambient PM2.5 was associated with higher risk of incident MCI and dementia, particularly when considering longer-term exposure, and independent of demographic characteristics and smoking history. Targeting poor air quality may be a reasonable population-wide intervention to reduce the risk of cognitive impairment in older adults, particularly in regions exceeding current recommendations for safe exposure to PM2.5 .

Excellent air quality is crucial for human health, safety, security, and the environment. Air quality deteriorates as cities and businesses grow, affecting the existence of numerous species as well as the service life and aesthetic appeal of materials. Measuring and evaluating surrounding air quality is the first and most significant step in minimising air toxicity. A large number of water quality surveillance does not always inform the scientific community about the state of the air quality, policymakers, regulating bodies, and, most crucially, the general population. Environmental authorities utilize air quality indexes (AQI) to communicate and interpret information widely due to the health dangers connected with poor air quality. An air quality index is a unique number that represents the air’s quality in terms of its impact on human health. In its most sophisticated version, it combines multiple contaminant amounts in some mathematical equations to obtain at a single figure for air quality. The current study examines into how the COVID-19 pandemic spread affected the quality of the surrounding air during the lockdown and recovery phases. Changes in the air quality index were detected both during phases of the winter period, which lasted from October to January, using data from Adarsh Nagar-Central Pollution Control Board (CPCB) station. The findings found that the city’s quality of air had drastically worsened following the lockdown. When compared to the previous years’ data during the same era, before to the COVID-19 epidemic, the quantity of particulate and gaseous pollution increased dramatically following the lockdown period. It was noted that, in addition to PM 10, that was the primary pollutants in the air quality index previous to the epidemic, PM 2.5, and PM 10 were all present.This study presents a quick summary of the relatively significant areas that need more focus from lawmakers in order to launch policies targeted at creating adequate air pollution reduction measures.

Air pollution is a common problem in areas with high population density such as big cities. The mega city of Tehran which is capital city of Iran is suffering from poor air quality. In Tehran, Traditional air quality assessment is realized using air quality indices which are determined as max values of selected air pollutants which is mostly base on PM2.5. Thus, air quality assessment depends on strictly describe without taking into account specific other Environmental parameters. In this paper, To demonstrate the application, common air pollutants like CO, O3, NO2, SO2, PM10 and PM2.5 are used as air pollutant parameters, also we were studied over an 2-year period (2015–2017) on daily data of the air quality index (AQI) in Tehran. The artificial intelligence based on neural network and fuzzy inferences methods allows assessing air quality parameters, providing a partial solution to this problem. Accordingly, this study proposes two fuzzy logic system for assessing accurate air quality evaluations, also proposed Seven score stages: Good, Moderate, Unhealthy for Sensitive Group, Unhealthy, Very Unhealthy, Hazardous for evaluating air quality index. Our experimental results show a good performance of the proposed air quality index against other system that those in literature.

Global impact of landscape fire emissions on surface level PM2.5 concentrations, air quality exposure and population mortality

Rationale: Outdoor air pollution causes emergency department visits and hospitalizations for childhood asthma. In the United States, the Air Quality Index (AQI) alerts the public to air quality and provides behavioral recommendations to reduce exposure and harm, yet little is known about the relationship between the AQI and childhood asthma exacerbations. Objectives: To test for association between the AQI and childhood asthma exacerbations resulting in emergency department visits and hospitalizations. Methods: This was a retrospective time-stratified case-crossover study, conducted using medical records data from 2010 through 2018 for children aged 6-17 years with a primary diagnosis of an asthma exacerbation (defined as an emergency department visit or hospitalization for asthma) at UPMC Children's Hospital of Pittsburgh. Daily AQI data was obtained for Allegheny County, Pennsylvania from the Environmental Protection Agency. Conditional logistic regression was used for analyses of the AQI (as both a continuous and categorical variable) and asthma exacerbations. Stratified analyses were conducted to explore modification of the AQI effects on asthma exacerbations by race and other covariates. Results: There were 6,573 events. Particulate matter <2.5μm (PM2.5) was the primary pollutant responsible for the AQI, followed by ozone (62% and 29% of days with events, respectively). The overall AQI was associated with asthma exacerbations (e.g., as continuous, per 10-unit increase, LagDay2: odds ratio [OR], 1.014; 95% confidence interval [CI],1.003-1.025; Lag Day 3: OR, 1.012; 95% CI, 1.001-1.023). By pollutant-specific AQI, the association was strongest for PM2.5. In stratified analyses, the AQI was associated with exacerbations in Black and younger children (6-11 yr) on LagDay 4. Conclusions: The AQI is associated with asthma exacerbations among children in Allegheny County. This is driven primarily by PM2.5, with Black and younger children particularly affected. Healthcare providers should discuss the AQI in asthma management.

Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction

The processing of limestone through the combustion process will cause air pollution at the combustion site and its surroundings. At the limestone processing site, Padalarang experiences relatively high air pollution. PM2.5 is one of the main pollutants produced by limestone burning, so it is very necessary to study the concentration of PM2.5 in the air in Padalarang and its surroundings. This study was conducted in Padalarang and its surroundings, where data collection was carried out in five locations, namely at the center of limestone burner, 1 km, 2 km, 3 km, and 4 km to the east of the burning center. Data collection was carried out for ten days, where each data collection was carried out for 12 hours, from 07.00 to 19.00. Based on the national standard of PPRI No. 22 of 2021, which is 55 µg/m3, the concentration in the limestone burning center and 1 km from burning center have exceeded the standard, which is 82.5 and 69.3 µg/m3. While PM2.5 concentrations at distances of 2 km, 3 km, and 4 km are below the national standard, namely 52.0, 51.6 and 50.2 µg/m3, respectively. Based on the Air Quality Index (AQI), the AQI at the burning center, distance of 1 km, 2 km, 3 km, and 4 km are Unhealthy, Unhealthy, Moderate, Moderate and Moderate, respectively. This means that areas less than 1 km away are not healthy places to live. The poor air quality in Padalarang is reflected in the much higher number of ARI cases compared to the surrounding sub-districts that do not have a limestone industry.

Forecasting of air quality in Delhi using principal component regression technique

Literatures shows that poor air quality index (AQI) is associated with several adverse health impacts, such as asthma, chronic obstructive pulmonary disease, diabetes mellitus, tuberculosis, cancer, pneumonia, cataracts, heart diseases, and mental health disorders. Nepal, one of the lower-middle-income countries, has become vulnerable to adverse health impacts due to poor AQI over time. The capital city of Nepal, Kathmandu, is frequently placed as one of the most polluted cities by IQAir. As such, this statement marks a caution for policymakers and the public to be aware of the future effects of prolonged exposure to air pollution and highlights its causative factors. To solve this burgeoning issue, because of the significant rise in urbanization and population growth, mitigation strategies such as creating awareness, reducing vehicular emission, reducing forest fires, creating and identifying vulnerability maps risk zones for forest fires, switching to electronic vehicles and personal interventions such as staying indoors and reducing physical outdoor activity, wearing face masks must be focused and given priority. Although our study is limited in its methodology and findings, it helps establish a policy base to underscore the need for longitudinal cohort studies to generate further evidences pertaining to not up to par air quality levels and their subsequent health impacts in the Nepalese population.

Formulation of the problem. Air pollution is one of the biggest modern ecological problem, which aggravates with process of urbanization, industrial development, increasing number of vehicles, etc. So that, the article is devoted to the study the of air pollution in the largest cities of the Volyn region: Lutsk, Kowel, Novovolynsk and Volodymyr-Volynskyi. The purpose of the article is to estimate state and quality of the air in the largest cities of the Volyn region, discover the main sources of air pollution, characterize the effects of pollution on people health and environment, propose measures for solving this problem. Review of previous publications and studies. State of the air pollution in the urban areas of the Volyn region became the subject of scientific interest of many scientists. Hulai L. D., Karaim O. A. and Syniuk, A. Yu. researched ecological state of air basin and structure of sources of air pollution in the Novovolynsk City. Panasiuk M. V. and Hulai L. D. analyzed air quality in the Kovel district and Kovel City. Problems of air pollution were investigated in the studies of Kiptenko Ye. M., Kozlenko T. V. and Molchak Ya. O., Fesiuk V. O., Kartava O. F. Moreover, Poruchynska, I. V. in her publication explored ways of reducing air pollution by vehicle in the Volyn region. Methods. The most common methods in the research were analysis and synthesis, correlations and regressions, generalization and comparison. Moreover, to study the quality of air basin in the largest urban area – Lutsk City, the authors calculated index of air pollution. Results. The study defined that the main source of air pollution in the urban systems are automobiles, which produce into the atmosphere 85-95 % of all emissions. Furthermore, stationary sources such as industrial enterprises and utility companies also pollute air basin of cities with hazardous substances. However, the amount of pollutants from these sources in the Lutsk City and Volodymyr-Volynskyi City slowly decreases. The authors researched that the air basin in Lutsk City is exposed to the greatest anthropogenic loading. According to the calculation of the air pollution index, city’s air basin belongs to the quality class «polluted air». Consequences of air pollution are quite different and have impact on environment and economic complex. Besides, poor air quality can cause different diseases. To solve this problem the authors propose to reconstruct and modernize enterprises’ treatment systems, to increase the number of environmental friendly public transport, to increase the areas with greenery, to introduce green logistics in transportation. The authors concluded that air basin in the most urbanized areas of the Volyn region is quite polluted, which caused by using vehicles and functioning of manufacture. So that, it is suggested measures to reduce the amount of emission from different source of pollution. Scientific novelty and practical significance. The main preconditions and trends of modern changes in air quality of the largest cities in the Volyn region was researched for the first time. Furthermore, the authors identified the main sources of air pollution, which have affected the quality of urban air basins during recent years. In addition, index of air pollution in the Lutsk City was calculated for the period 2015-2020. The article proposes measures to improve air quality and reduce emissions from stationary and mobile sources of pollution.

Know where you stand.The odds are African Americans are twice as likely to suffer a stroke as white Americans.Beating the odds isn't about winning, it's about living.You have the power to end stroke.1-888-4-STROKE / StrokeAssociation.org

Excessive environmental noise and poor air quality can be adverse to human health, living comfort and the environment itself. Measurement of sound pressure levels and air quality in critical areas including libraries, campus areas, public parks and hospitals thus becomes necessary to monitor and mitigate existing noise levels. In a university environment, student activities will be less disrupted if the locations of the activities are sufficiently away from noise sources. The present study is intended to measure sound levels and air quality around the Engineering Complex, Universiti Teknologi Mara, Shah Alam. The measured data is compared with to acceptable sound pressure levels and air quality index specified by the Department of Environment (DOE), Malaysia. Sound pressure levels are measured using the Castle Sound Level Meter Type 6224 and air quality measurement was done by using the BW Gas Alert MicroClip XT device. Both measurements were conducted at five selected stations around the Engineering Complex for three times each weekday for five weeks. Results obtained indicated that sound levels at some locations and time zones are above the thresholds recommended by the DOE. The air quality is acceptable in most locations except the vicinity of a bus stop. With the growing number of students in the university and other factors like construction and redevelopment of existing roads, a continuously increasing noise situations and air pollution proportional to the traffic flow is inevitable.

Air Quality Index prediction using an effective hybrid deep learning model