scholarly journals Spatio-Temporal Modeling of Small-Scale Ultrafine Particle Variability Using Generalized Additive Models

2021 ◽  
Vol 14 (1) ◽  
pp. 313
Author(s):  
Alessandra Gaeta ◽  
Gianluca Leone ◽  
Alessandro Di Menno di Bucchianico ◽  
Mariacarmela Cusano ◽  
Raffaela Gaddi ◽  
...  

High-resolution measurements of ultrafine particle concentrations in ambient air are needed for the study of health human effects of long-term exposure. This work, carried out in the framework of the VIEPI project (Integrated Evaluation of Indoor Particulate Exposure), aims to extend current knowledge on small-scale spatio-temporal variability of Particle Number Concentration (PNC, considered a proxy of the ultrafine particles) at a local scale domain (1 km × 1 km). PNC measurements were made in the university district of San Lorenzo in Rome using portable condensation particle counters for 7 consecutive days at 21 sites in November 2017 and June 2018. Generalized Additive Models (GAMs) were performed in the area for winter, summer and the overall period. The log-transformed two-hour PNC averages constitute the response variable, and covariates were grouped by urban morphology, land use, traffic and meteorology. Winter PNC values were about twice the summer ones. PNC recorded in the university area were significantly lower than those observed in the external routes. GAMs showed a rather satisfactory result in order to capture the spatial variability, in accordance with those of other previous studies: variances were equal to 71.1, 79.7 and 84%, respectively, for winter, summer and the overall period.

2019 ◽  
Vol 136 ◽  
pp. 06008
Author(s):  
SHAN Huimei ◽  
LUO Linbo ◽  
WANG Shaopei ◽  
LIAO Danxue ◽  
ZHAO Chaoran ◽  
...  

Environmental air pollution has become an important threat to human health. As one of the major air pollutants, atmospheric particulates have received attention widely. In which, ultrafine particulate matters (UPM) with diameter below 0.1μm have become the main components of ambient air particulates, posing a serious threat to the health of the organism. Therefore, this paper investigated and summarized the research on ultrafine particles at home and abroad, systematically analysed the sources of UPM in ambient air, investigated its toxicological effects of ultrafine particles on the respiratory system, cardiovascular system, and central nervous system of organisms. This study will provide a theoretical reference for environmental air protection and pollution control in China.


2010 ◽  
Vol 10 (19) ◽  
pp. 9615-9630 ◽  
Author(s):  
R. Fernández-Camacho ◽  
S. Rodríguez ◽  
J. de la Rosa ◽  
A. M. Sánchez de la Campa ◽  
M. Viana ◽  
...  

Abstract. Studies on ultrafine particles (diameter < 100nm) and air quality have mostly focused on vehicle exhaust emissions and on new particle formation in "clean" ambient air. Here we present a study focused on the processes contributing to ultrafine particle concentrations in a city (Huelva, SW Spain) placed close to a coastal area where significant anthropogenic emissions of aerosol precursors occur. The overall data analysis shows that two processes predominantly contribute to the number of particles coarser than 2.5 nm: vehicle exhaust emissions and new particle formation due to photo-chemical activity. As typically occurs in urban areas, vehicle exhaust emissions result in high concentrations of black carbon (BC) and particles coarser than 2.5 nm (N) during the morning rush hours. The highest N concentrations were recorded during the 11:00–17:00 h period, under the sea breeze regime, when low BC concentrations were registered and photochemical activity resulted in high O3 levels and in new particle formation in the aerosol precursors' rich inland airflow. In this period, it is estimated that about 80% of the number of particles are linked to sulfur dioxide emissions. The contributions to N of "carbonaceous material and those compounds nucleating/condensing immediately after emission" and of the "new particle formation processes in air masses rich gaseous precursors (e.g. SO2)" were estimated by means of a relatively novel method based on simultaneous measurements of BC and N. A comparison with two recent studies suggests that the daily cycles of "new particle formation" during the inland sea breeze is blowing period seem to be a feature of ultrafine particles in coastal areas of South-west Europe.


2010 ◽  
Vol 67 (8) ◽  
pp. 1553-1564 ◽  
Author(s):  
Juan P. Zwolinski ◽  
Paulo B. Oliveira ◽  
Victor Quintino ◽  
Yorgos Stratoudakis

Abstract Zwolinski, J. P., Oliveira, P. B., Quintino, V., and Stratoudakis, Y. 2010. Sardine potential habitat and environmental forcing off western Portugal. – ICES Journal of Marine Science, 67: 1553–1564. Relationships between sardine (Sardina pilchardus) distribution and the environment off western Portugal were explored using data from seven acoustic surveys (spring and autumn of 2000, 2001, 2005, and spring 2006). Four environmental variables (salinity, temperature, chlorophyll a, and acoustic epipelagic backscatter other than fish) were related to the acoustic presence and density of sardine. Univariate quotient analysis revealed sardine preferences for waters with high chlorophyll a content, low temperature and salinity, and low acoustic epipelagic backscatter. Generalized additive models depicted significant relationships between the environment and sardine presence but not with sardine density. Maps of sardine potential habitat (SPH) built upon the presence/absence models revealed a clear seasonal effect in the across-bathymetry and alongshelf extension of SPH off western Portugal. During autumn, SPH covered a large part of the northern Portuguese continental shelf but was almost absent from the southern region, whereas in spring SPH extended farther south but was reduced to a narrow band of shallow coastal waters in the north. This seasonal pattern agrees with the spatio-temporal variation of primary production and oceanic circulation described for the western Iberian shelf.


2010 ◽  
Vol 10 (7) ◽  
pp. 17753-17788 ◽  
Author(s):  
R. Fernández-Camacho ◽  
S. Rodríguez ◽  
J. de la Rosa ◽  
A. M. Sánchez de la Campa ◽  
M. Viana ◽  
...  

Abstract. Studies on ultrafine particles and air quality have mostly focused on vehicle exhaust emissions and on new particle formation in "clean" ambient air. Here we present a study of the processes contributing to ultrafine particle concentrations in an urban coastal area (Huelva, SW Spain) where significant anthropogenic emissions of aerosol precursors occur. The overall data analysis shows that two processes predominantly contribute to the number of particles coarser than 2.5 nm: vehicle exhaust emissions and new particle formation due to photo-chemical activity. As typically occurs in urban areas, vehicle exhaust emissions result in high concentrations of black carbon (BC) and particles coarser than 2.5 nm (N) during the morning rush hours. The highest N concentrations were recorded during the 11–17 h period, under the sea breeze regime, when photochemical activity resulted in high O3 levels and new particle formation in the aerosol precursors' rich inland airflow. In this period, it is estimated that about 80% of the number of particles are linked to sulfur dioxide emissions. The contributions to N of "carbonaceous material and those compounds nucleating/condensing immediately after emission" and of the "new particle formation processes in air masses rich gaseous precursors (e.g. SO2)" were estimated by means of a relatively novel method based on simultaneous measurements of BC and N. A comparison with two recent studies suggests that the daily cycles of "new particle formation" during the period when the inland sea breeze is blowing period seem to be a feature of ultrafine particles in coastal areas of South-west Europe.


2008 ◽  
Vol 14 (1) ◽  
pp. 47-49 ◽  
Author(s):  
Jasmina Jovic-Stosic ◽  
Milena Jovasevic-Stojanovic

Epidemiological and clinical studies suggested the association of the particulate matter ambient air pollution and the increased morbidity and mortality, mainly from respiratory and cardiovascular diseases. The size of particles has great influence on their toxicity, because it determines the site in the respiratory tract where they deposit. The most well established theory explaining the mechanisms behind the increased toxicity of ultrafine particles (UFP, < 0.1 ?m) is that it has to do with the increased surface area and/or the combination with the increased number of particles. Biological effects of UFP are also determined by their shape and chemical composition, so it is not possible to estimate their toxicity in a general way. General hypothesis suggested that exposure to inhaled particles induces pulmonary alveolar inflammation as a basic pathophysiological event, triggering release of various proinflammatory cytokines. Chronic inflammation is a very important underlying mechanism in the genesis of atherosclerosis and cardiovascular diseases. UFP can freely move through the circulation, but their effects on the secondary organs are not known yet, so more studies on recognizing toxicological endpoints of UFP are needed. Determination of UFP toxicity and the estimation of their internal and biologically active dose are necessary for the evidence based conclusions connecting air pollution by UFP and human diseases. .


2021 ◽  
Vol 15 (12) ◽  
pp. e0009980
Author(s):  
Weerapong Thanapongtharm ◽  
Sarin Suwanpakdee ◽  
Arun Chumkaeo ◽  
Marius Gilbert ◽  
Anuwat Wiratsudakul

The situation of human rabies in Thailand has gradually declined over the past four decades. However, the number of animal rabies cases has slightly increased in the last ten years. This study thus aimed to describe the characteristics of animal rabies between 2017 and 2018 in Thailand in which the prevalence was fairly high and to quantify the association between monthly rabies occurrences and explainable variables using the generalized additive models (GAMs) to predict the spatial risk areas for rabies spread. Our results indicate that the majority of animals affected by rabies in Thailand are dogs. Most of the affected dogs were owned, free or semi-free roaming, and unvaccinated. Clusters of rabies were highly distributed in the northeast, followed by the central and the south of the country. Temporally, the number of cases gradually increased after June and reached a peak in January. Based on our spatial models, human and cattle population density as well as the spatio-temporal history of rabies occurrences, and the distances from the cases to the secondary roads and country borders are identified as the risk factors. Our predictive maps are applicable for strengthening the surveillance system in high-risk areas. Nevertheless, the identified risk factors should be rigorously considered and integrated into the strategic plans for the prevention and control of animal rabies in Thailand.


2020 ◽  
Vol 10 (8) ◽  
pp. 3091-3110 ◽  
Author(s):  
M. E. Wigwe ◽  
E. S. Bougre ◽  
M. C. Watson ◽  
A. Giussani

Abstract Modern data analytic techniques, statistical and machine-learning algorithms have received widespread applications for solving oil and gas problems. As we face problems of parent–child well interactions, well spacing, and depletion concerns, it becomes necessary to model the effect of geology, completion design, and well parameters on production using models that can capture both spatial and temporal variability of the covariates on the response variable. We accomplish this using a well-formulated spatio-temporal (ST) model. In this paper, we present a multi-basin study of production performance evaluation and applications of ST models for oil and gas data. We analyzed dataset from 10,077 horizontal wells from 2008 to 2019 in five unconventional formations in the USA: Bakken, Marcellus, Eagleford, Wolfcamp, and Bone Spring formations. We evaluated well production performance and performance of new completions over time. Results show increased productivity of oil and gas since 2008. Also, the Bakken wells performed better for the counties evaluated. We present two methods for fitting spatio-temporal models: fixed rank kriging and ST generalized additive models using thin plate and cubic regression splines as basis functions in the spline-based smooths. Results show a significant effect on production by the smooth term, accounting for between 60 and 95% of the variability in the six-month production. Overall, we saw a better production response to completions for the gas formations compared to oil-rich plays. The results highlight the benefits of spatio-temporal models in production prediction as it implicitly accounts for geology and technological changes with time.


2021 ◽  
Author(s):  
Cervantes - Martínez Karla ◽  
Riojas - Rodríguez Horacio ◽  
Díaz - Ávalos Carlos ◽  
Moreno - Macías Hortensia ◽  
López - Ridaura Ruy ◽  
...  

Abstract Epidemiological studies on the effects of air pollution in Mexico often use the environmental concentrations of monitors closest to the home as exposure proxies, yet this approach disregards the space gradients of pollutants and assumes that individuals have no intra-city mobility. Our aim was to develop high-resolution spatial and temporal models for predicting long-term exposure to PM2.5 and NO2 in a population of ~ 16 500 participants from the Mexican Teachers’ Cohort study. We geocoded the home and work addresses of participants. Using information from secondary sources on geographic and meteorological variables as well as other pollutants, we fitted two generalized additive models to predict monthly PM2.5 and NO2 concentrations in the 2004–2019 period. The models were evaluated through 10-fold cross validation. Both showed high predictive accuracy with out-of-sample data and no overfitting (CV RMSE = 0.102 for PM2.5 and CV RMSE = 4.497 for NO2). Participants were exposed to a monthly average of 24.38 (6.78) µg/m3 of PM2.5 and 28.21 (8.00) ppb of NO2 during the study period. These models offer a solid alternative for estimating PM2.5 and NO2 exposure with high spatio-temporal resolution for epidemiological studies in the Valle de México region.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Esam Mahdi ◽  
Sana Alshamari ◽  
Maryam Khashabi ◽  
Alya Alkorbi

Over the past few years, hierarchical Bayesian models have been extensively used for modeling the joint spatial and temporal dependence of big spatio-temporal data which commonly involves a large number of missing observations. This article represented, assessed, and compared some recently proposed Bayesian and non-Bayesian models for predicting the daily average particulate matter with a diameter of less than 10 (PM10) measured in Qatar during the years 2016–2019. The disaggregating technique with a Markov chain Monte Carlo method with Gibbs sampler are used to handle the missing data. Based on the obtained results, we conclude that the Gaussian predictive processes with autoregressive terms of the latent underlying space-time process model is the best, compared with the Bayesian Gaussian processes and non-Bayesian generalized additive models.


2020 ◽  
Vol 44 (5) ◽  
pp. 591-604 ◽  
Author(s):  
Álvaro Briz-Redón ◽  
Ángel Serrano-Aroca

The new SARS-CoV-2 coronavirus has spread rapidly around the world since it was first reported in humans in Wuhan, China, in December 2019 after being contracted from a zoonotic source. This new virus produces the so-called coronavirus 2019 or COVID-19. Although several studies have supported the epidemiological hypothesis that weather patterns may affect the survival and spread of droplet-mediated viral diseases, the most recent have concluded that summer weather may offer partial or no relief of the COVID-19 pandemic to some regions of the world. Some of these studies have considered only meteorological variables, while others have included non-meteorological factors. The statistical and modelling techniques considered in this research line have included correlation analyses, generalized linear models, generalized additive models, differential equations, or spatio-temporal models, among others. In this paper we provide a systematic review of the recent literature on the effects of climate on COVID-19’s global expansion. The review focuses on both the findings and the statistical and modelling techniques used. The disparate findings reported seem to indicate that the estimated impact of hot weather on the transmission risk is not large enough to control the pandemic, although the wide range of statistical and modelling approaches considered may have partly contributed to the inconsistency of the findings. In this regard, we highlight the importance of being aware of the limitations of the different mathematical approaches, the influence of choosing geographical units and the need to analyse COVID-19 data with great caution. The review seems to indicate that governments should remain vigilant and maintain the restrictions in force against the pandemic rather than assume that warm weather and ultraviolet exposure will naturally reduce COVID-19 transmission.


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