394 research outputs found
Air quality in Tehran, Iran : evaluating acute health effects and modeling the long-term spatial variability
The burden of disease due to air pollution can be very large because of its acute and chronic effects. This dissertation focused on these two key challenges in the megacity of Tehran, Iran. First, it assessed short-term exposure to ambient air pollutants and their association with daily mortality. Second, it assessed long-term exposures for different air pollutants, which is a prerequisite for the investigation of their chronic health effects. The first part found that the effect of air pollutants on mortality was immediate, and that it increased steadily over a period of weeks. The second part found that concentrations of various air pollutants were very high in Tehran, comparable with those reported for other megacities in Asia. Further, spatial land-use regression (LUR) models were developed for multiple pollutants, and showed that the city center was the most polluted area. Even so, more than 80% of Tehran had benzene concentrations above air quality standard of 5 µg/m3 set by European Union and Iranian Government. The thesis also included a systematic review of the global literature on LUR models for volatile organic compounds and found that the study in Tehran has been the largest to assess all BTEX (benzene, toluene, ethylbenzene, and xylenes) species in a megacity. The methods and models developed for this PhD dissertation opened up new avenues for the next generation of air pollution monitoring, modelling, and epidemiology in Iran
Concurrent spatiotemporal daily land use regression modeling and missing data imputation of fine particulate matter using distributed space-time Expectation Maximization
In this study, a spatiotemporal land use regression (LUR) model using Distributed Space-Time Expectation Maximization (D-STEM) software was developed. We trained the model using daily mean ambient particulate matter ≤ 2.5 μm (PM2.5) data measured hourly in 2015 at 30 regulatory monitoring network stations within the megacity of Tehran, Iran. Since a substantial amount of measured data were missing (48% of the total number of daily PM2.5 observations), we used the D-STEM to impute missing data and compared the missing imputation performance between different fitted models and the mean substitution method. We used h-block cross-validation (h-block CV) method in order to account for spatial autocorrelation in the model building and validation. In the imputation of missing data, the D-STEM LUR model had a mean absolute percentage error (MAPE) of 25.3%, outperforming the mean substitution method, which resulted in MAPE of 28.3%. The spatiotemporal R-squared was 0.73 and the average CV R-squared of 2-block and 5-block cross-validations was 0.60. These values were 0.68 and 0.47 when the spatial aspect of the LUR model was assessed, and 0.995 and 0.992 when the temporal aspect of the LUR model was assessed. This study demonstrated the competence of D-STEM software in spatiotemporal modeling, missing data imputation, and mapping of daily ambient PM2.5 at a very high spatial resolution (20 m x 20 m). These estimations are available for future research, especially for epidemiological studies on short- and/or long-term health effects of ambient PM2.5. Generally, we found D-STEM as a promising tool for spatiotemporal LUR modeling of ambient air pollution, especially for those models that rely on regulatory network monitoring stations with a considerable amount of missing data
Low ambient temperature and hospitalization for cardiorespiratory diseases in Brazil
Studies have shown that larger temperature-related health impacts may be associated with cold rather than with hot temperatures. Although it remains unclear the cold-related health burden in warmer regions, in particular at the national level in Brazil. We address this gap by examining the association between low ambient temperature and daily hospital admissions for cardiovascular and respiratory diseases in Brazil between 2008 and 2018. We first applied a case time series design in combination with distributed lag non-linear modeling (DLNM) framework to assess the association of low ambient temperature with daily hospital admissions by Brazilian region. Here, we also stratified the analyses by sex, age group (15-45, 46-65, and >65 years), and cause (respiratory and cardiovascular hospital admissions). In the second stage, we performed a meta-analysis to estimate pooled effects across the Brazilian regions. Our sample included more than 23 million hospitalizations for cardiovascular and respiratory diseases nationwide between 2008 and 2018, of which 53% were admissions for respiratory diseases and 47% for cardiovascular diseases. Our findings suggest that low temperatures are associated with a relative risk of 1.17 (95% CI: 1.07; 1.27) and 1.07 (95% CI: 1.01; 1.14) for cardiovascular and respiratory admissions in Brazil, respectively. The pooled national results indicate robust positive associations for cardiovascular and respiratory hospital admissions in most of the subgroup analyses. In particular, for cardiovascular hospital admissions, men and older adults (>65 years old) were slightly more impacted by cold exposure. For respiratory admissions, the results did not indicate differences among the population groups by sex and age. This study can help decision-makers to create adaptive measures to protect public health from the effects of cold temperature
The flip side of the coin:Exploring the environmental and health impacts of proof-of-work cryptocurrency mining
Blockchain technology, the backbone of cryptocurrency, is under scrutiny due to the environmental and health hazards linked to its energy-consuming Proof-of-Work (PoW) mining process. This review study provides a comprehensive analysis of the global health implications of PoW mining and cryptocurrency, with a focus on environmental sustainability and human health. The research utilized both traditional databases (PubMed and Web of Science) and additional primary sources. The study underscores the high energy consumption and carbon emissions of Bitcoin mining, despite ongoing debates comparing cryptocurrency to conventional finance. The review calls for immediate interventions, including the exploration of renewable energy sources and a transition from PoW to more sustainable consensus mechanisms. A case study on China's carbon policies highlights the necessity for effective regulatory measures. The findings reiterate the environmental and health risks associated with PoW cryptocurrency mining, including its resource-intensive procedures, reliance on non-renewable energy, and emission of air pollutants. The review emphasizes the urgent need for global regulation and a transition to more sustainable consensus mechanisms, such as Proof-of-Stake (PoS), to reduce the industry's impact on climate and human health.Blockchain technology, the backbone of cryptocurrency, is under scrutiny due to the environmental and health hazards linked to its energy-consuming Proof-of-Work (PoW) mining process. This review study provides a comprehensive analysis of the global health implications of PoW mining and cryptocurrency, with a focus on environmental sustainability and human health. The research utilized both traditional databases (PubMed and Web of Science) and additional primary sources. The study underscores the high energy consumption and carbon emissions of Bitcoin mining, despite ongoing debates comparing cryptocurrency to conventional finance. The review calls for immediate interventions, including the exploration of renewable energy sources and a transition from PoW to more sustainable consensus mechanisms. A case study on China's carbon policies highlights the necessity for effective regulatory measures. The findings reiterate the environmental and health risks associated with PoW cryptocurrency mining, including its resource-intensive procedures, reliance on non-renewable energy, and emission of air pollutants. The review emphasizes the urgent need for global regulation and a transition to more sustainable consensus mechanisms, such as Proof-of-Stake (PoS), to reduce the industry's impact on climate and human health.</p
Short-term air pollution exposure and mortality in Brazil: Investigating the susceptible population groups.
This is the first study to examine the association between ambient air pollution (PM2.5, O3, and NO2) and mortality (in different population groups by sex and age) based on a nationwide death record across Brazil over a 15-year period (2003-2017). We used a time-series analytic approach with a distributed lag model. Our study population includes 2,872,084 records of deaths in Brazil between 2003 and 2017. Men accounted for a higher proportion of deaths, with 58% for all-cause mortality, 54% for respiratory mortality, and 52% for circulatory mortality. Most individuals were over 65 years of age. Our results suggest an association between air pollution and mortality in Brazil. The direction, statistical significance, and effect size of these associations varied considerably by type of air pollutant, region, and population group (sex and age group). In particular, the older population group (>65 years) was most affected. The national meta-analysis for the entire data set (without stratification by sex and age) showed that for every 10 μg/m3 increase in PM2.5 concentration, the risk of death from respiratory diseases increased by 2.93% (95%CI: 1.42; 4.43). For every 10 ppb increase in O3, there is a 2.21% (95%CI: 0.59; 3.83) increase in the risk of all-cause mortality for the group of all people between 46 and 65 years old, and a 3.53% (95%CI: 0.34; 6.72) increase in the risk of circulatory mortality for the group of women, all ages. For every 10 ppb increase in NO2, the risk of respiratory mortality increases by 17.56% (95%CI: 4.44; 30.64) and the risk of all-cause mortality by 5.63% (95%CI: 1.83; 9.44). The results of our study provide epidemiological evidence that air pollution is associated with a higher risk of cardiorespiratory mortality in Brazil. Given the lack of nationwide studies on air pollution in Brazil, our research is an important contribution to the local and international literature that can provide better support to policymakers to improve air quality and public health
Association of high ambient temperature with daily hospitalization for cardiorespiratory diseases in Brazil: A national time-series study between 2008 and 2018.
Further research is needed to examine the nationwide impact of temperature on health in Brazil, a region with particular challenges related to climate conditions, environmental characteristics, and health equity. To address this gap, in this study, we looked at the relationship between high ambient temperature and hospital admissions for circulatory and respiratory diseases in 5572 Brazilian municipalities between 2008 and 2018. We used an extension of the two-stage design with a case time series to assess this relationship. In the first stage, we applied a distributed lag non-linear modeling framework to create a cross-basis function. We next applied quasi-Poisson regression models adjusted by PM2.5, O3, relative humidity, and time-varying confounders. We estimated relative risks (RRs) of the association of heat (percentile 99th) with hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. In the second stage, we applied meta-analysis with random effects to estimate the national RR. Our study population includes 23,791,093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. The robustness of the RR and the effect size varied significantly by region, sex, age group, and health outcome. Overall, our findings suggest that i) respiratory admissions had the highest RR, while circulatory admissions had inconsistent or null RR in several subgroup analyses; ii) there was a large difference in the cumulative risk ratio across regions; and iii) overall, women and the elderly population experienced the greatest impact from heat exposure. The pooled national results for the whole population (all ages and sex) suggest a relative risk of 1.29 (95% CI: 1.26; 1.32) associated with respiratory admissions. In contrast, national meta-analysis for circulatory admissions suggested robust positive associations only for people aged 15-45, 46-65, >65 years old; for men aged 15-45 years old; and women aged 15-45 and 46-65 years old. Our findings are essential for the body of scientific evidence that has assisted policymakers to promote health equity and to create adaptive measures and mitigations
Erratum: The role of visual preferences in architecture views
The article “The role of visual preferences in architecture views” by Ali Akbar Amini, Bahman Adibzadeh, published on 24 September 2020 in the Journal of Architecture and Urbanism, 44(2), 122–127, https://doi.org/10.3846/jau.2020.12582 contained a following errors on:
122 p. The source is incorrectly cited in the text. The correct citation is:
(de la Fuente Suárez, 2016)
126 p. The references incorrectly indicate author name, lastname and title of article. The correct citation is:
de la Fuente Suárez, L. A. (2016). Towards experiential representation in architecture. Journal of Architecture and Urbanism, 40(1), 47–58. https://doi.org/10.3846/20297955.2016.1163243
Corrected version of the article is available online.
The publisher apologises for this error
Sedimentation Processes in the Tinto and Odiel Salt Marshes in Huelva, Spain
Global warming is a key factor to take into account when a study is conducted on tidal
wetlands. Both Odiel and Tinto salt marshes are the major wetlands in Andalusia (Spain).
From the mid-1950s to date, the land use changes (LUC) have caused a great landscape
alteration that along with the effects of climatic variables and sea wave energy have given
rise to a hard impact on the environment. The advent of new image processing procedures and use of high-resolution images from satellites gave precise patterns of erosion.
In this work, a new method patented by the author is presented and used to obtain the
total cubic meters of eroded soil in both salt marshes. Moreover, the different factors that
begin this phenomenon as well as the influence of intertidal processes are discussed. The
results show how the greater integration of remote sensing and geographical information
systems (GIS) technologies, with regression model, was most useful to describe, analyze
and predict the volumetric change process in both salt marshes
Proximity of schools to roads and students' academic performance:A cross-sectional study in the Federal District, Brazil
Investigations of the educational implications of children's exposure to air pollutants at school are crucial to enhance our understanding of the hazards for children. Most of the existing literature is based on studies performed in North America and Europe. Further investigation is required in low-and middle-income countries, where there are important challenges related to public health, transportation, environment, and education sector. In response, in this present study, we studied the association between proximity of schools to roads and the academic achievement of the students in the Federal District, Brazil. We accessed academic achievement data at the student level. The data consist of 256 schools (all the public schools in the FD) and a total of 344,175 students (all the students enrolled in the public schools in the FD in 2017-2020). We analyzed the association between the length of all roads within buffers around schools and student-level academic performance using mixed-effects regression models. After adjustments for several covariates, the results of the primary analysis indicate that the presence of roads surrounding schools is negatively associated with student-level academic performance in the FD. This association varies significantly depending on the buffer size surrounding schools. We found that the highest effects occur in the first buffer, with 250 m. While in the first buffer we estimated that an increase of 1 km of length of roads around schools was associated with a statistically significant decrease of 0.011 (95%CI: 0.008; 0.013) points in students' grades (students' academic performance varies from 0 to 10), in the buffer of 1 km we found a decrease of 0.002 (95%CI: 0.002; 0.002) points in the student-level academic performance. Findings from our investigation provide support for the creation of effective health, educational and urban planning policies for local intervention in the FD. This is essential to improve the environmental quality surrounding schools to protect children from exposure to environmental hazards.</p
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