scholarly journals Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 422
Author(s):  
Jérémy Gelb ◽  
Philippe Apparicio
Keyword(s):  
Statistical Models ◽  
Noise Exposure ◽  
Generalized Additive Model ◽  
Low Cost ◽  
Additive Model ◽  
Noise Pollution ◽  
Ventilation Rate ◽  
Mixed Effects ◽  
Mobile Data ◽  
Mobile Data Collection

Cyclists are particularly exposed to air and noise pollution because of their higher ventilation rate and their proximity to traffic. However, few studies have investigated their multi-exposure and have taken into account its real complexity in building statistical models (nonlinearity, pseudo replication, autocorrelation, etc.). We propose here to model cyclists’ exposure to air and noise pollution simultaneously in Paris (France). Specifically, the purpose of this study is to develop a methodology based on an extensive mobile data collection using low-cost sensors to determine which factors of the urban micro-scale environment contribute to cyclists’ multi-exposure and to what extent. To this end, we developed a conceptual framework to define cyclists’ multi-exposure and applied it to a multivariate generalized additive model with mixed effects and temporal autocorrelation. The results show that it is possible to reduce cyclists’ multi-exposure by adapting the planning and development practices of cycling infrastructure, and that this reduction can be substantial for noise exposure.

scholarly journals Ambient Sulfate Trends and the Influence of Meteorology

2005 ◽  
Vol 44 (11) ◽  
pp. 1745-1760 ◽  
Author(s):  
Stephen F. Mueller
Keyword(s):  
Statistical Models ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Total Sulfur ◽  
Eastern United States ◽  
Sulfur Species ◽  
Sulfate Sulfur ◽  
Average Change ◽  
Meteorological Influences ◽  
Local Deposition

Abstract Data on atmospheric levels of sulfur dioxide (SO2) and sulfate were examined to quantify changes since 1989. Changes in sulfur species were adjusted to account for meteorological variability. Adjustments were made using meteorological variables expressed in terms of their principal components that were used as predictors in statistical models. Several models were tested. A generalized additive model (GAM)—based in part on nonparametric, locally smoothed predictor functions—computed the greatest association between sulfate and the meteorological predictors. Sulfate trends estimated after a GAM-based adjustment for weather-related influences were found to be primarily downward across the eastern United States by as much as 6.7% per year (average of −2.6% per year), but large spatial variability was noted. The most conspicuous characteristic in the trends was over portions of the Appalachian Mountains where very small (average = −1.6% per year) and often insignificant sulfate changes were found. The Appalachian region also experienced a tendency, after removing meteorological influences, for increases in the ratio RS of sulfate sulfur to total sulfur. Before 1991, this ratio averaged 0.33 across all sites. Appalachian increases in RS were equivalent to 0.07 during 1989–2001 (significant for most sites at the 0.05 level), or nearly 2 times the average change at the other sites. This suggests that conditions over the Appalachians became notably more efficient at oxidizing SO2 into sulfate. Alternatively, subtle changes in local deposition patterns occurred, preferentially in and near mountainous monitoring sites, that changed the SO2–sulfate balance.

GAMLSS for high-variability data: an application to liver fibrosis case

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Andrea Marletta ◽  
Mariangela Sciandra
Keyword(s):  
Risk Factors ◽  
Liver Fibrosis ◽  
Statistical Models ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Finite Mixture Model ◽  
High Variability ◽  
Finite Mixture ◽  
Potential Risk Factors ◽  
Variability Data

AbstractThis article aims to provide rigorous and convenient statistical models for dealing with high-variability phenomena. The presence of discrepance in variance represents a substantial issue when it is not possible to reduce variability before analysing the data, leading to the possibility to estimate an inadequate model. In this paper, the application of Generalized Additive Model for Location, Scale and Shape (GAMLSS) and the use of finite mixture model for GAMLSS will be proposed as a solution to the problem of overdispersion. An application to Liver fibrosis data is illustrated in order to identify potential risk factors for patients, which could determine the presence of the disease but also its levels of severity.

scholarly journals CLIMATE-DRIVEN STATISTICAL MODELS AS EFECTIVE PREDICTIONS OF LOCAL DENGUE INDICENCE IN COSTA RICA: A GENERALIZED ADDITIVE MODEL AND RANDOM FOREST APPROACH

2019 ◽  
Vol 27 (1) ◽  
pp. 1-21
Author(s):  
PAOLA VÁSQUEZ ◽  
ANTONIO LORÍA ◽  
FABIO SÁNCHEZ ◽  
LUIS ALBERTO BARBOZA
Keyword(s):  
Public Health ◽  
Relative Risk ◽  
Costa Rica ◽  
Random Forest ◽  
Prediction Model ◽  
Statistical Models ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Climate Data ◽  
Tropical Country

Climate has been an important factor in shaping the distribution and incidence of dengue cases in tropical and subtropical countries. In Costa Rica, a tropical country with distinctive micro-climates, dengue has been endemic since its introduction in 1993, inflicting substantial economic, social, and public health repercussions. Using the number of dengue reported cases and climate data from 2007-2017, we fitted a prediction model applying a Generalized Additive Model (GAM) and Random Forest (RF) approach, which allowed us to retrospectively predict the relative risk of dengue in five climatological diverse municipalities around the country.

scholarly journals A Simulation Study to Evaluate Survey Designs and Assessment Models for Estimation of Dungeness Crab (Cancer magister) Softshell Periods

2016 ◽  
Vol 9 (1) ◽  
pp. 57-74
Author(s):  
Zane Zhang ◽  
Jason S. Dunham
Keyword(s):  
Data Collection ◽  
Hierarchical Model ◽  
Statistical Models ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Quadratic Function ◽  
Dungeness Crab ◽  
Catch Per Unit Effort ◽  
Unit Effort ◽  
Survey Designs

Softshell Dungeness Crabs have inferior meat quality and are vulnerable to handling by harvesters; therefore, knowing when softshell periods occur is important for managing Dungeness Crab fisheries. A computer simulation was used to study the effectiveness of several survey designs and statistical models for estimating softshell periods which normally would be construed from crab shell condition data obtained from trap surveys. Survey designs varied in the number of years of data collection (1, 3, 5 or 10 years) and by the number and arrangement of sampling events per year. Three statistical models, including standardized catch-per-unit-effort (SCPUE), hierarchical, and generalized additive, were tested using catch-per-unit-effort data (CPUEs) or CPUE- transformed data. CPUEs were standardised by dividing CPUE estimates by the maximum CPUE obtained in the sample year, and then transformed using the complementary log-log function. In the hierarchical model, CPUEs were modelled using a lognormal distribution, assuming the expected logarithms of CPUEs are a quadratic function of days plus a random normal error. CPUE-transformed data were modelled using a normal distribution, assuming expected values are a quadratic function of days in the SCPUE model or a spline smooth function of days in the generalized additive model. Results suggest the best survey design requires a relatively high number (6 or 11) of sampling events during several key consecutive months which contain the softshell period, and fewer sampling events during those months when softshell crab abundance is low. A minimum 3 years of data collection is required to produce reliable outputs. The hierarchical model performs best, slightly better than the SCPUE model. Use of the generalized additive model is not recommended.

Pengaruh bising lalu lintas terhadap penurunan fungsi pendengaran pada juru parkir di kota Denpasar

2013 ◽  
Vol 40 (2) ◽  
Author(s):  
Ni Ketut Susilawati ◽  
Wayan Sudana ◽  
Eka Putra Setiawan
Keyword(s):  
Hearing Impairment ◽  
Noise Exposure ◽  
Traffic Noise ◽  
Hearing Threshold ◽  
Noise Pollution ◽  
Simple Random Sampling ◽  
Cross Sectional Study ◽  
Control Group ◽  
Cross Sectional ◽  
Hearing Function

Background: Noise pollution or noise is an unwanted sound which is disturbing to human beings.However small or soft the sound, if it is undesirable it is considered as noise. Noise induced hearingloss is a sensorineural hearing loss that is commonly encountered second to presbycusis. Purpose: Toknow the effect of traffic noise exposure on hearing impairment to the employees of the Parking DistrictCompany of the Denpasar city and to improve diagnostic detection on hearing impairment caused bynoise. Method: A cross sectional study was conducted at the Parking District Company office. Thepopulations of this study were the employees of the Parking District Company. Samples of this study were the employees who were exposed to traffic noise and control samples were an employee who was unexposed. Samples were selected by simple random sampling. Results: From 40 parking attendants,27 persons (67.5%) aged above 35 years old. The parking attendants who had been working for ten to fifteen years were 36 persons (90%) and no history using ear protection when working. Seven persons(17.5%) had referred DPOAE upon examination with increase hearing threshold on audiogram result.In this study the parking attendants who had hearing deficit induced by noise were 7 persons (17.5%)and only one person (2.5%) in control group. There was a statistically significant effect of traffic noiseto hearing function deficit (p<0.05). Conclusion: Traffic noise has effect in hearing function deficit onthe parking attendants.ORLI Vol. 40 No. 2 Tahun 2010Key words: NIHL, parking attendant, audiometry, DPOAE.

scholarly journals Estimation of the Inhaled Dose of Pollutants in Different Micro-Environments: A Systematic Review of the Literature

Toxics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 140
Author(s):  
Francesca Borghi ◽  
Andrea Spinazzè ◽  
Simone Mandaglio ◽  
Giacomo Fanti ◽  
Davide Campagnolo ◽  
...  
Keyword(s):  
Systematic Review ◽  
Residence Time ◽  
Low Cost ◽  
Pulmonary Ventilation ◽  
Personal Exposure ◽  
Ventilation Rate ◽  
Atmospheric Pollutants ◽  
Active Commuting ◽  
Review Of The Literature ◽  
Future Studies

Recently, the need to assess personal exposure in different micro-environments has been highlighted. Further, estimating the inhaled dose of pollutants is considerably one of the most interesting parameters to be explored to complete the fundamental information obtained through exposure assessment, especially if associated with a dose-response approach. To analyze the main results obtained from the studies related to the estimation of the inhaled dose of pollutants in different micro-environments (environments in which an individual spends a part of his day), and to identify the influence of different parameters on it, a systematic review of the literature was performed. The principal outcomes from the considered studies outlined that (i) exposure concentration and residence time are among the most important parameters to be evaluated in the estimation of the inhaled dose, especially in transport environments. Further, (ii) the pulmonary ventilation rate can be of particular interest during active commuting because of its increase, which increases the inhalation of pollutants. From a methodological point of view, the advent of increasingly miniaturized, portable and low-cost technologies could favor these kinds of studies, both for the measurement of atmospheric pollutants and the real-time evaluation of physiological parameters used for estimation of the inhaled dose. The main results of this review also show some knowledge gaps. In particular, numerous studies have been conducted for the evaluation (in terms of personal exposure and estimation of the inhaled dose) of different PM fractions: other airborne pollutants, although harmful to human health, are less represented in studies of this type: for this reason, future studies should be conducted, also considering other air pollutants, not neglecting the assessment of exposure to PM. Moreover, many studies have been conducted indoors, where the population spends most of their daily time. However, it has been highlighted how particular environments, even if characterized by a shorter residence time, can contribute significantly to the dose of inhaled pollutants. These environments are, therefore, of particular importance and should be better evaluated in future studies, as well as occupational environments, where the work results in a high pulmonary ventilation rate. The attention of future studies should also be focused on these categories of subjects and occupational studies.

scholarly journals Traffic noise disrupts vocal development and suppresses immune function

2021 ◽  
Vol 7 (20) ◽  
pp. eabe2405
Author(s):  
Henrik Brumm ◽  
Wolfgang Goymann ◽  
Sébastien Derégnaucourt ◽  
Nicole Geberzahn ◽  
Sue Anne Zollinger
Keyword(s):  
Immune Function ◽  
Noise Exposure ◽  
Traffic Noise ◽  
Vocal Learning ◽  
Noise Pollution ◽  
Experimental Models ◽  
Speech Development ◽  
Vocal Development ◽  
Learning Impairments ◽  
Cognitive Deficiencies

Noise pollution has been linked to learning and language deficits in children, but the causal mechanisms connecting noise to cognitive deficiencies remain unclear because experimental models are lacking. Here, we investigated the effects of noise on birdsong learning, the primary animal model for vocal learning and speech development in humans. We found that traffic noise exposure retarded vocal development and led to learning inaccuracies. In addition, noise suppressed immune function during the sensitive learning period, indicating that it is a potent stressor for birds, which is likely to compromise their cognitive functions. Our results provide important insights into the consequences of noise pollution and pave the way for future studies using birdsong as an experimental model for the investigation of noise-induced learning impairments.

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