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Although it has been hypothesized that air pollution, particularly PM2.5 and PM10, causes depressed symptoms, their interactions with greenness have not yet been confirmed. This study examined the association between depression symptoms and air pollution, as well as the potential moderating effects of greenness.
Methods
A total of 7657 people from all around South Korea were examined using information from the Korean Longitudinal Study of Aging, for the years 2016, 2018 and 2020. Depressive symptoms were assessed using the CES-D 10 score (Center for Epidemiology Studies of Depression scale, Boston form), and annual air pollution levels (PM2.5, PM10) and greenness (NDVI, Landsat Normalized Difference Vegetation Index) at the district level (si-gun-gu) were considered for the association analysis. The investigation was primarily concerned with determining how the CES-D 10 score changed for each 10 ${\mu \text{g/}}{{\text{m}}^{\text{3}}}$ increase in PM2.5 and PM10 according to NDVI quantiles, respectively. The analysis used generalized estimating equation models that were adjusted with both minimal and complete variables. Subgroup analyses were conducted based on age groups (<65, ≥65 years old), sex and exercise status.
Results
The impact of PM10 on depression in the fourth quantile of NDVI was substantially less in the fully adjusted linear mixed model (OR for depression with a 10 ${\mu\text{ g/}}{{\text{m}}^{\text{3}}}$ increment of PM10: 1.29, 95% CI: 1.06, 1.58) than in the first quantile (OR: 1.88, 95% CI: 1.58, 2.25). In a similar vein, the effect of PM2.5 on depression was considerably reduced in the fourth quantile of NDVI (OR for depression with a 10 ${\mu\text{ g/}}{{\text{m}}^{\text{3}}}$ increment of PM2.5: 1.78, 95% CI: 1.30, 2.44) compared to the first (OR: 3.75, 95% CI: 2.75, 5.10). Subgroup analysis results demonstrated beneficial effects of greenness in the relationship between particulate matter and depression.
Conclusions
This longitudinal panel study found that a higher quantile of NDVI was associated with a significantly reduced influence of air pollution (PM10, PM2.5) on depression among older individuals in South Korea.
Emissions from unconventional oil and gas development can impact ground-level air quality. The largest impacts are on ozone (O3) and are driven by emissions of volatile organic compounds (VOCs). In the western U.S., ozone events in excess of EPA standards have been linked to VOC emissions from oil and gas operations. In Texas and the eastern U.S., ozone impacts are more modest, but may contribute to exceedances of EPA standards in some downwind cities. Some of the emitted VOCs are hazardous air pollutants that may cause cancer or other health effects. Thus, these emissions may also generate environmental injustice for communities living near oil and gas sources. Unconventional oil and gas sources also contribute to fine particulate matter (PM2.5) and nitrogen oxides (NOx). However, they are minor sources of these pollutants. Similarly, combustion associated with the oil and gas industry emits NOx, but the industry is a small contributor to overall emissions. In rural areas of the western U.S., these NOx emissions contribute to the high ozone events.
Global climate change (global warming) has been identified as the primary factor responsible for the observed increase in frequency and severity of wildfires (also known as bushfires in some countries) throughout the majority of the world’s vegetated environments. This trend is predicted to continue, causing significant adverse health effects to nearby residential populations and placing a potential strain on local emergency departments (EDs).
Study Objective:
The aim of this literature review was to identify papers relating to wildfires and their impact on EDs, specifically patient presentation characteristics, resource utilization, and patient outcomes.
Method:
This integrative literature review was guided by the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) guidelines for data collection, and Whittemore and Knafl’s framework for data analysis. Data were collected from OvidSP, MEDLINE, DARE, CINAHL, PubMed, and Scopus databases. Various Medical Subject Headings (MeSH) and keywords identified papers relevant to wildfires/bushfires and EDs.
Results:
Literature regarding the relationship between ED presentations and wildfire events, however, is primarily limited to studies from the United States and Australia and indicates particulate matter (PM) is principally linked to adverse respiratory and cardiovascular outcomes. Observable trends in the literature principally included a significant increase in respiratory presentations, primarily with a lag of one to two days from the initial event. Respiratory and cardiovascular studies that stratified results by age indicated individuals under five, over 65, or those with pre-existing conditions formed the majority of ED presentations.
Conclusion:
Key learnings from this review included the need for effective and targeted community advisory programs/procedures, prior to and during wildfire events, as well as pre-event planning, development, and robust resilience strategies for EDs.
Congress has previously passed environmental and administrative laws that tethered the regulatory process to scientific evidence. Federal agencies were obliged to weigh scientific data, as well as dispassionate economic and legal analyses, as they developed and implemented regulations. The Trump administration sought to untether the rulemaking process from science and other forms of hard evidence and expert analysis by putting contrarian scientists in charge of science advisory boards and by sidelining the views of career scientists at federal agencies and academic scientists. That strategy paved the way for oil and gas insiders at the helm of these agencies to make decisions aligned with positions advocated by the oil and gas industry, which had shared its wish-list on deregulatory actions with the Trump administration. The administration sought to undermine the scientific basis of environmental regulations by promulgating the deceptively named Science Transparency Rule that would block federal agencies' consideration of epidemiological studies that had linked pollution to adverse public health impacts. That rule was built of the decades-long views advocated by oil- and gas-funded think tanks and pro-oil members of Congress. Fortunately for the scientific integrity of rulemaking, in January 2021 a federal court ruled that the EPA had exceeded its powers in promulgating that regulation and subsequently vacated the rule.
Almost all hospitals are equipped with air-conditioning systems to provide a comfortable environment for patients and staff. However, the accumulation of dust and moisture within these systems increases the risk of transmission of microbes and have on occasion been associated with outbreaks of infection. Nevertheless, the impact of air-conditioning on the transmission of microorganisms leading to infection remains largely uncertain. We conducted a scoping review to screen systematically the evidence for such an association in the face of the coronavirus disease 2019 epidemic. PubMed, Embase and Web of Science databases were explored for relevant studies addressing microbial contamination of the air, their transmission and association with infectious diseases. The review process yielded 21 publications, 17 of which were cross-sectional studies, three were cohort studies and one case−control study. Our analysis showed that, compared with naturally ventilated areas, microbial loads were significantly lower in air-conditioned areas, but the incidence of infections increased if not properly managed. The use of high-efficiency particulate air (HEPA) filtration not only decreased transmission of airborne bioaerosols and various microorganisms, but also reduced the risk of infections. By contrast, contaminated air-conditioning systems in hospital rooms were associated with a higher risk of patient infection. Cleaning and maintenance of such systems to recommended standards should be performed regularly and where appropriate, the installation of HEPA filters can effectively mitigate microbial contamination in the public areas of hospitals.
The purpose of the research was to investigate and identify the impact of COVID-19 lockdown on fine particulate matter (PM2.5) pollution in Dhaka, Bangladesh by using ground-based observation data.
Methods:
The research assessed air quality during the COVID-19 pandemic for PM2.5 from January 1, 2017 to August 1, 2020. The research considered pollution in pre-COVID-19 (January 1 to March 23), during COVID-19 (March 24 to May 30), and post-COVID-19 (May 31 to August 1) lockdown periods with current (2020) and historical (2017-2019) data.
Results:
PM2.5 pollution followed a similar yearly trend in year 2017-2020. The average concentration for PM2.5 was found 87.47 μg/m3 in the study period. Significant PM2.5 declines were observed in the current COVID-19 lockdown period compared with historical data: 11.31% reduction with an absolute decrease of 7.15 μg/m3.
Conclusions:
The findings of the research provide an overview of how the COVID-19 pandemic affects air pollution. The results will provide initial evidence regarding human behavioral changes and emission controls. This research will also suggest avenues for further study to link the findings with health outcomes.
Non-communicable diseases (NCDs) including obesity, diabetes, and allergy are chronic, multi-factorial conditions that are affected by both genetic and environmental factors. Over the last decade, the microbiome has emerged as a possible contributor to the pathogenesis of NCDs. Microbiome profiles were altered in patients with NCDs, and shift in microbial communities was associated with improvement in these health conditions. Since the genetic component of these diseases cannot be altered, the ability to manipulate the microbiome holds great promise for design of novel therapies in the prevention and treatment of NCDs. Together, the Developmental Origins of Health and Disease concept and the microbial hypothesis propose that early life exposure to environmental stimuli will alter the development and composition of the human microbiome, resulting in health consequences. Recent studies indicated that the environment we are exposed to in early life is instrumental in shaping robust immune development, possibly through modulation of the human microbiome (skin, airway, and gut). Despite much research into human microbiome, the origin of their constituent microbiota remains unclear. Dust (also known as particulate matter) is a key determinant of poor air quality in the modern urban environment. It is ubiquitous and serves as a major source and reservoir of microbial communities that modulates the human microbiome, contributing to health and disease. There are evidence that reported significant associations between environmental dust and NCDs. In this review, we will focus on the impact of dust exposure in shaping the human microbiome and its possible contribution to the development of NCDs.
Some recent studies examined the effect of ambient particulate matter (PM) pollution on depression and suicide. However, the results have been inconclusive.
Aims
To determine the overall relationship between PM exposure and depression/suicide in the general population.
Method
We conducted a systematic review and meta-analysis of case-crossover and cohort studies to assess the association between PM2.5 (particles with an aerodynamic diameter of 2.5 µm or less) or PM10 (particles with an aerodynamic diameter between 2.5 and 10 µm) exposure and depression/suicide.
Results
A total of 14 articles (7 for depression and 7 for suicide) with data from 684 859 participants were included in the meta-analysis. With a 10 µg/m3 increase in PM2.5 we found a 19% (odds ratio [95% CI] 1.19 [1.07, 1.33]) increased risk of depression and a marginally increased risk of suicide (odds ratio [95% CI] 1.05 [0.99, 1.11]) in the general population. We did not observe any significant associations between increasing exposure to PM10 and depression/suicide. Sensitivity and subgroup analyses were used to determine the robustness of results. The strongest estimated effect of depression associated with PM2.5 appeared in a long-term lag pattern (odds ratio [95% CI] 1.25 [1.07, 1.45], P < 0.01) and cumulative lag pattern (odds ratio [95% CI] 1.26 [1.07, 1.48], P < 0.01).
Conclusions
The meta-analysis suggested that an increase in ambient PM2.5 concentration was strongly associated with increased depression risk in the general population, and the association appeared stronger at long-term lag and cumulative lag patterns, suggesting a potential cumulative exposure effect over time.
The PM10 (airborne particulate matter with aerodynamic diameter <10 mm) in Beijing has a distinct seasonality, with industrial, domestic and natural sources providing a heterogeneous cocktail of airborne particulate matter (PM). Collections were made during late winter, summer and high wind dust storms to determine composition and probable sources of this PM. The concentration of the PM during winter (174 μg m–3) was approximately four times higher than summer (37 μg m–3) with dust storms raising the concentration further (200 μg m–3). During the winter the PM was dominated by combustion products (66% filter area). During the summer combustion products and loess contributed ~35% to the filter area each, but during elevated wind speeds (>10 mph) loess completely dominated the collections (96% filter area). The majority of the PM10 collected was in the respirable (PM2.5) size range (winter 99.7%, summer 96.6%, dust storms 82.3%). The loess in Beijing comprises quartz, feldspar, calcite, chlorite and mica and is in the coarse silt to sand (20–60 mm) size range. The collections are therefore likely to be made up of finer silt and clay, primarily derived from of the erosion of cultivated land. Using a plasmid assay, the Beijing particulate matter was found to have little or no surface free radical activity.
Research examining racial/ethnic disparities in pollution exposure often relies on cross-sectional data. These analyses are largely insensitive to exposure trends and rarely account for broader contextual dynamics. To provide a more comprehensive assessment of racial-environmental inequality over time, we combine the 1990 to 2009 waves of the Panel Study of Income Dynamics (PSID) with spatially- and temporally-resolved measures of nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) in respondents’ neighborhoods, as well as census data on the characteristics of respondents’ metropolitan areas. Results based on multilevel repeated measures models indicate that Blacks and Latinos are, on average, more likely to be exposed to higher levels of NO2, PM2.5, and PM10 than Whites. Despite nationwide declines in levels of pollution over time, racial and ethnic disparities persist and cannot be fully explained by individual-, household-, or metropolitan-level factors.
Research links air pollution mostly to respiratory and cardiovascular disease. The effects of air pollution on the central nervous system (CNS) are not broadly recognized. Urban outdoor pollution is a global public health problem particularly severe in megacities and in underdeveloped countries, but large and small cities in the United States and the United Kingom are not spared. Fine and ultrafine particulate matter (UFPM) defined by aerodynamic diameter (<2.5-μm fine particles, PM2.5, and <100-nm UFPM) pose a special interest for the brain effects given the capability of very small particles to reach the brain. In adults, ambient pollution is associated to stroke and depression, whereas the emerging picture in children show significant systemic inflammation, immunodysregulation at systemic, intratechal and brain levels, neuroinflammation and brain oxidative stress, along with the main hallmarks of Alzheimer and Parkinson’s diseases: hyperphosphorilated tau, amyloid plaques and misfolded α-synuclein. Animal models exposed to particulate matter components show markers of both neuroinflammation and neurodegeneration. Epidemiological, cognitive, behavioral and mechanistic studies into the association between air pollution exposures and the development of CNS damage particularly in children are of pressing importance for public health and quality of life. Primary health providers have to include a complete prenatal and postnatal environmental and occupational history to indoor and outdoor toxic hazards and measures should be taken to prevent or reduce further exposures.
This paper describes the development of a method for quantitative measurement of the elemental composition of particulate matter (PM) in seawater. This method is based on use of wavelength dispersive X-ray fluorescence (WDXRF) analysing PM harvested on various filter types. As the amount of material is less than a monolayer of cells on the filters we reduced the need for absorption correction. Given the appropriate combination of filters and elements the detection limits are low: <1 µg/filter for carbon (C), nitrogen (N), and <0.1 µg/filter for silicon (Si), phosphorus (P), calcium (Ca) and iron (Fe). The analytical range used was 90–750 µg C, 23–116 µg N and 7–30 µg P, depending on the filters applied. Calibration constants for the elements included in this study were obtained from analysis of known quantities of chemical compounds on filters or silver plates. For carbon and nitrogen we also used comparative measurements of Synechococcus sp. cultures by CHN analyser and WDXRF. We harvested PM from 150 ml to 2000 ml on each filter in three replicates, obtaining less than 5% analytical variability between the replicates. One of the challenges using WDXRF as proposed here is the absorption of X-ray signals by the filter and variability of cell/particle sizes, and, consequentlyly, the variability of harvested PM on various filters. We find that an anodisc filter is best suited for C and N, while polycarbonate filters are best for heavier elements. Here we present analytical details and some data from field experiments related to C, N, P, Si, Ca and Fe in particles from seawater.
There are still questions about the importance of different animal reservoirs and environmental factors that played a role in the large Q fever epidemic in The Netherlands. We therefore investigated the spatial association between reported Q fever cases and different livestock and environmental factors at the national level. A spatial regression analysis was performed, with four-digit postal code areas as the unit of analysis. High level of particulate matter (⩾24·5 μg/m3) with an aerodynamic diameter <10 μm (PM10) was by far the strongest risk factor for human Q fever with an odds ratio of 10·4 (95% confidence interval 7·0–15·6) using PM10 <24·5 μg/m3 as reference, in logistic regression analysis, controlling for differences in animal densities, vegetation and other risk factors. Particulate matter seems to play an important role in the transmission of Q fever from infected animals to humans and should be a focus for further studies on zoonotic infectious diseases and decision-making.
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