scholarly journals Basin-scale wind transport during the MILAGRO field campaign and comparison to climatology using cluster analysis

2007 ◽  
Vol 7 (5) ◽  
pp. 13035-13076 ◽  
Author(s):  
B. de Foy ◽  
J. D. Fast ◽  
S. J. Paech ◽  
D. Phillips ◽  
J. T. Walters ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Mexico City ◽  
Atmospheric Chemistry ◽  
Quality Data ◽  
Field Campaign ◽  
Urban Impacts ◽  
Basin Scale ◽  
The Impact

Abstract. The MILAGRO field campaign was a multi-agency international collaborative project to evaluate the regional impacts of the Mexico City air pollution plume as a means of understanding urban impacts on the global climate. Mexico City lies on an elevated plateau with mountains on three sides and has complex mountain and surface-driven wind flows. This paper asks what the wind transport was in the basin during the field campaign and how representative it was of the climatology. Surface meteorology and air quality data, radiosoundings and radar wind profiler data were collected at sites in the basin and its vicinity. Cluster analysis is used to identify the dominant wind patterns both during the campaign and within the past 10 years of operational data from the warm dry season. Our analysis shows that March 2006 was representative of typical flow patterns experienced in the basin. Six episode types were identified for the basin scale circulation providing a way of interpreting atmospheric chemistry and particulate data collected during the campaign. Decoupling between surface winds and those aloft had a strong influence in leading to convection and poor air quality episodes. Hourly characterisation of wind circulation during the MILAGRO, MCMA-2003 and IMADA field campaigns will enable the comparisons of similar air pollution episodes and the evaluation of the impact of wind transport on measurements of the atmospheric chemistry taking place in the basin.

scholarly journals Basin-scale wind transport during the MILAGRO field campaign and comparison to climatology using cluster analysis

2008 ◽  
Vol 8 (5) ◽  
pp. 1209-1224 ◽  
Author(s):  
B. de Foy ◽  
J. D. Fast ◽  
S. J. Paech ◽  
D. Phillips ◽  
J. T. Walters ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Mexico City ◽  
Atmospheric Chemistry ◽  
Quality Data ◽  
Field Campaign ◽  
Urban Impacts ◽  
Basin Scale ◽  
The Impact

Abstract. The MILAGRO field campaign was a multi-agency international collaborative project to evaluate the regional impacts of the Mexico City air pollution plume as a means of understanding urban impacts on the global climate. Mexico City lies on an elevated plateau with mountains on three sides and has complex mountain and surface-driven wind flows. This paper asks what the wind transport was in the basin during the field campaign and how representative it was of the climatology. Surface meteorology and air quality data, radiosondes and radar wind profiler data were collected at sites in the basin and its vicinity. Cluster analysis was used to identify the dominant wind patterns both during the campaign and within the past 10 years of operational data from the warm dry season. Our analysis shows that March 2006 was representative of typical flow patterns experienced in the basin. Six episode types were identified for the basin-scale circulation providing a way of interpreting atmospheric chemistry and particulate data collected during the campaign. Decoupling between surface winds and those aloft had a strong influence in leading to convection and poor air quality episodes. Hourly characterisation of wind circulation during the MILAGRO, MCMA-2003 and IMADA field campaigns enables the comparisons of similar air pollution episodes and the evaluation of the impact of wind transport on measurements of the atmospheric chemistry taking place in the basin.

scholarly journals Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

2021 ◽  
Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Class Imbalance ◽  
Imbalanced Data ◽  
Classification Algorithm ◽  
Quality Data ◽  
Pollution Level ◽  
Classification Problems ◽  
Chi Square ◽  
The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

A Cluster Analysis of PM2.5 Using CMAQ Model Results for Representativeness of Air Quality Monitoring Networks in Busan, Korea

2020 ◽  
Author(s):  
Woo-Sik Jung ◽  
Woo-Gon Do
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Monitoring Network ◽  
Hierarchical Cluster ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Monitoring Networks ◽  
Monitoring Stations

<p><strong>With increasing interest in air pollution, the installation of air quality monitoring networks for regular measurement is considered a very important task in many countries. However, operation of air quality monitoring networks requires much time and money. Therefore, the representativeness of the locations of air quality monitoring networks is an important issue that has been studied by many groups worldwide. Most such studies are based on statistical analysis or the use of geographic information systems (GIS) in existing air quality monitoring network data. These methods are useful for identifying the representativeness of existing measuring networks, but they cannot verify the need to add new monitoring stations. With the development of computer technology, numerical air quality models such as CMAQ have become increasingly important in analyzing and diagnosing air pollution. In this study, PM2.5 distributions in Busan were reproduced with 1-km grid spacing by the CMAQ model. The model results reflected actual PM2.5 changes relatively well. A cluster analysis, which is a statistical method that groups similar objects together, was then applied to the hourly PM2.5 concentration for all grids in the model domain. Similarities and differences between objects can be measured in several ways. K-means clustering uses a non-hierarchical cluster analysis method featuring an advantageously low calculation time for the fast processing of large amounts of data. K-means clustering was highly prevalent in existing studies that grouped air quality data according to the same characteristics. As a result of the cluster analysis, PM2.5 pollution in Busan was successfully divided into groups with the same concentration change characteristics. Finally, the redundancy of the monitoring stations and the need for additional sites were analyzed by comparing the clusters of PM2.5 with the locations of the air quality monitoring networks currently in operation.</strong></p><p><strong>This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(2017R1D1A3B03036152).</strong></p>

scholarly journals Investigating the impacts of air quality and weather indicators on the spread of SARS-COV-2 in Istanbul, Turkey

2021 ◽  
pp. 71-71
Author(s):  
Caner Taniş ◽  
Kadir Karakaya
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Positive Impact ◽  
Pearson Correlation ◽  
Quality Data ◽  
Hospital Discharges ◽  
Weather Parameters ◽  
The Impact ◽  
Quality Indexes

Background/aim: Air pollution is having a positive impact on the spread of the SARS-COV-2 virus. The effects of meteorological parameters on the spread of SARS-COV-2 are a matter of curiosity. The main purpose of this paper is to determine the association between air quality indexes (PM2.5, PM10, NO2, SO2, CO, and O3) and weather parameters (temperature, humidity, pressure, dew, wind speed) with the number of SARS-COV-2 cases, hospitalizations, hospital discharges. In this paper, we also focused on determining the impact of air pollution and weather parameters on the number of daily hospitalizations and daily discharges. Materials and methods: It is gleaned daily cases, hospitalizations, hospital discharges, meteorological, and air quality data in Istanbul from Turkey between July 15, 2020, and September 30, 2020. We performed the Pearson correlation analysis to evaluate the effects of meteorological parameters and air quality indexes on the variables related to SARS-COV-2. Results: It is determined a statistically significant positive relationship between air quality indexes such as CO, SO2, PM2.5, PM10, NO2, and the number of daily confirmed SARS-COV-2 cases. We also observed a negative association between weather parameters such as temperature and pressure and the number of daily confirmed SARS-COV-2 cases. Conclusion: Our study proposes that high air quality could reduce the number of SARS-COV-2 cases. The empirical findings of this paper might provide key input to prevent the spread of SARS-COV-2 across Turkey.

scholarly journals Impacts of the COVID-19 lockdown on air quality and its association with human mortality trends in megapolis Mexico City

2020 ◽  
Author(s):  
Gurusamy Kutralam-Muniasamy ◽  
Fermín Pérez-Guevara ◽  
Priyadarsi D. Roy ◽  
I. Elizalde-Martínez ◽  
V.C. Shruti
Keyword(s):  
Air Pollution ◽  
Latin America ◽  
Air Quality ◽  
Mexico City ◽  
Air Pollutants ◽  
Mortality Rates ◽  
Quality Data ◽  
Mortality Trends ◽  
Human Mortality ◽  
Air Quality Data

Abstract Mexico City is the second most populated city in Latin America, and it went through two partial lockdowns between April 1 and May 31, 2020 for reducing the COVID-19 propagation. The present study assessed air quality and its association with human mortality rates during the lockdown by estimating changes observed in air pollutants (CO, NO2, O3, SO2, PM10 and PM2.5) between the lockdown (April 1 - May 31) and pre-lockdown (January 1 – March 31) periods, as well as by comparing the air quality data of lockdown period with the same interval of previous five-years (2015-2019). Concentrations of NO2 (-29%), SO2 (-55%) and PM10 (-11%) declined and the contents of CO (+1.1%), PM2.5 (+19%) and O3 (+63%) increased during the lockdown compared to the pre-lockdown period. This study also estimated that NO2, SO2, CO, PM10 and PM2.5 reduced by 19-36%, and O3 enhanced by 14% compared to the average of 2015-2019. Reduction in traffic as well as less emission from vehicle exhausts led to remarkable decline in NO2, SO2 and PM10. The significant positive associations of PM2.5, CO and O3 with the numbers of COVID-19 infections and deaths, however, underscored the necessity to enforce air pollution regulations to protect human health in one of the important cities of the northern hemisphere.

scholarly journals Effects of business-as-usual anthropogenic emissions on air quality

2012 ◽  
Vol 12 (15) ◽  
pp. 6915-6937 ◽  
Author(s):  
A. Pozzer ◽  
P. Zimmermann ◽  
U.M. Doering ◽  
J. van Aardenne ◽  
H. Tost ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
East Asia ◽  
South Asia ◽  
Atmospheric Chemistry ◽  
General Circulation ◽  
Circulation Model ◽  
Business As Usual ◽  
The Impact ◽  
Very High

Abstract. The atmospheric chemistry general circulation model EMAC has been used to estimate the impact of anthropogenic emission changes on global and regional air quality in recent and future years (2005, 2010, 2025 and 2050). The emission scenario assumes that population and economic growth largely determine energy and food consumption and consequent pollution sources with the current technologies ("business as usual"). This scenario is chosen to show the effects of not implementing legislation to prevent additional climate change and growing air pollution, other than what is in place for the base year 2005, representing a pessimistic (but plausible) future. By comparing with recent observations, it is shown that the model reproduces the main features of regional air pollution distributions though with some imprecisions inherent to the coarse horizontal resolution (~100 km) and simplified bottom-up emission input. To identify possible future hot spots of poor air quality, a multi pollutant index (MPI), suited for global model output, has been applied. It appears that East and South Asia and the Middle East represent such hotspots due to very high pollutant concentrations, while a general increase of MPIs is observed in all populated regions in the Northern Hemisphere. In East Asia a range of pollutant gases and fine particulate matter (PM2.5) is projected to reach very high levels from 2005 onward, while in South Asia air pollution, including ozone, will grow rapidly towards the middle of the century. Around the Persian Gulf, where natural PM2.5 concentrations are already high (desert dust), ozone levels are expected to increase strongly. The population weighted MPI (PW-MPI), which combines demographic and pollutant concentration projections, shows that a rapidly increasing number of people worldwide will experience reduced air quality during the first half of the 21st century. Following this business as usual scenario, it is projected that air quality for the global average citizen in 2050 would be almost comparable to that for the average citizen in East Asia in the year 2005, which underscores the need to pursue emission reductions.

scholarly journals Effects of business-as-usual anthropogenic emissions on air quality

2012 ◽  
Vol 12 (4) ◽  
pp. 8617-8676
Author(s):  
A. Pozzer ◽  
P. Zimmermann ◽  
U.M. Doering ◽  
J. van Aardenne ◽  
H. Tost ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
East Asia ◽  
South Asia ◽  
Atmospheric Chemistry ◽  
General Circulation ◽  
Circulation Model ◽  
Business As Usual ◽  
The Impact ◽  
Very High

Abstract. The atmospheric chemistry general circulation model EMAC has been used to estimate the impact of anthropogenic emission changes on global and regional air quality in recent and future years (2005, 2010, 2025 and 2050). The emission scenario assumes that population and economic growth largely determine energy and food consumption and consequent pollution sources with the current technologies ("business as usual"). This scenario is chosen to show the effects of not implementing legislation to prevent additional climate change and growing air pollution, other than what is in place for the base year 2005, representing a pessimistic (but feasible) future. By comparing with recent observations, it is shown that the model reproduces the main features of regional air pollution distributions though with some imprecisions inherent to the coarse horizontal resolution (~100 km) and simplified bottom-up emission input. To identify possible future hot spots of poor air quality, a multi pollutant index (MPI), suited for global model output, has been applied. It appears that East and South Asia and the Middle East represent such hotspots due to very high pollutant concentrations, although a general increase of MPIs is observed in all populated regions in the Northern Hemisphere. In East Asia a range of pollutant gases and fine particulate matter (PM2.5) is projected to reach very high levels from 2005 onward, while in South Asia air pollution, including ozone, will grow rapidly towards the middle of the century. Around the Arabian Gulf, where natural PM2.5 concentrations are already high (desert dust), ozone levels are expected to increase strongly. The per capita MPI (PCMPI), which combines demographic and pollutants concentrations projections, shows that a rapidly increasing number of people worldwide will experience reduced air quality during the first half of the 21st century. Following the business as usual scenario, it is projected that air quality for the global average citizen in 2050 would be almost comparable to that for the average citizen in the East Asia in the year 2005, which underscores the need to pursue emission reductions.

scholarly journals Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

2021 ◽  
Author(s):  
Christian Acal ◽  
Ana M. Aguilera ◽  
Annalina Sarra ◽  
Adelia Evangelista ◽  
Tonio Di Battista ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Functional Data ◽  
Central Italy ◽  
Principal Component ◽  
Functional Principal Component Analysis ◽  
Area Of Interest ◽  
Pm 10 ◽  
The Impact ◽  
Monitoring Stations

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

scholarly journals The interplay between environmental exposures and COVID-19 risks in the health of children

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Peter D. Sly ◽  
Brittany A. Trottier ◽  
Catherine M. Bulka ◽  
Stephania A. Cormier ◽  
Julius Fobil ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Disease Severity ◽  
Research Effort ◽  
Severe Disease ◽  
Environmental Exposures ◽  
Research Strategy ◽  
Lessons Learned ◽  
Research Questions ◽  
The Impact

Abstract Background An unusual feature of SARS-Cov-2 infection and the COVID-19 pandemic is that children are less severely affected than adults. This is especially paradoxical given the epidemiological links between poor air quality and increased COVID-19 severity in adults and that children are generally more vulnerable than adults to the adverse consequences of air pollution. Objectives To identify gaps in knowledge about the factors that protect children from severe SARS-Cov-2 infection even in the face of air pollution, and to develop a transdisciplinary research strategy to address these gaps. Methods An international group of researchers interested in children’s environmental health was invited to identify knowledge gaps and to develop research questions to close these gaps. Discussion Key research questions identified include: what are the effects of SAR-Cov-2 infection during pregnancy on the developing fetus and child; what is the impact of age at infection and genetic susceptibility on disease severity; why do some children with COVID-19 infection develop toxic shock and Kawasaki-like symptoms; what are the impacts of toxic environmental exposures including poor air quality, chemical and metal exposures on innate immunity, especially in the respiratory epithelium; what is the possible role of a “dirty” environment in conveying protection – an example of the “hygiene hypothesis”; and what are the long term health effects of SARS-Cov-2 infection in early life. Conclusion A concerted research effort by a multidisciplinary team of scientists is needed to understand the links between environmental exposures, especially air pollution and COVID-19. We call for specific research funding to encourage basic and clinical research to understand if/why exposure to environmental factors is associated with more severe disease, why children appear to be protected, and how innate immune responses may be involved. Lessons learned about SARS-Cov-2 infection in our children will help us to understand and reduce disease severity in adults, the opposite of the usual scenario.

scholarly journals Gender Differences in Association between Air Pollution and Daily Mortality in the Capital of the Green Lungs of Poland–Population-Based Study with 2,953,000 Person-Years of Follow-Up

2020 ◽  
Vol 9 (8) ◽  
pp. 2351
Author(s):  
Łukasz Kuźma ◽  
Krzysztof Struniawski ◽  
Szymon Pogorzelski ◽  
Hanna Bachórzewska-Gajewska ◽  
Sławomir Dobrzycki
Keyword(s):  
Public Health ◽  
Gender Differences ◽  
Air Pollution ◽  
Air Quality ◽  
Air Pollutant ◽  
World Health ◽  
The European Union ◽  
Daily Mortality ◽  
Male Population ◽  
The Impact

(1) Introduction: air pollution is considered to be one of the main risk factors for public health. According to the European Environment Agency (EEA), air pollution contributes to the premature deaths of approximately 500,000 citizens of the European Union (EU), including almost 5000 inhabitants of Poland every year. (2) Purpose: to assess the gender differences in the impact of air pollution on the mortality in the population of the city of Bialystok—the capital of the Green Lungs of Poland. (3) Materials and Methods: based on the data from the Central Statistical Office, the number—and causes of death—of Białystok residents in the period 2008–2017 were analyzed. The study utilized the data recorded by the Provincial Inspectorate for Environmental Protection station and the Institute of Meteorology and Water Management during the analysis period. Time series regression with Poisson distribution was used in statistical analysis. (4) Results: A total of 34,005 deaths had been recorded, in which women accounted for 47.5%. The proportion of cardiovascular-related deaths was 48% (n = 16,370). An increase of SO2 concentration by 1-µg/m3 (relative risk (RR) 1.07, 95% confidence interval (CI) 1.02–1.12; p = 0.005) and a 10 °C decrease of temperature (RR 1.03, 95% CI 1.01–1.05; p = 0.005) were related to an increase in the number of daily deaths. No gender differences in the impact of air pollution on mortality were observed. In the analysis of the subgroup of cardiovascular deaths, the main pollutant that was found to have an effect on daily mortality was particulate matter with a diameter of 2.5 μm or less (PM2.5); the RR for 10-µg/m3 increase of PM2.5 was 1.07 (95% CI 1.02–1.12; p = 0.01), and this effect was noted only in the male population. (5) Conclusions: air quality and atmospheric conditions had an impact on the mortality of Bialystok residents. The main air pollutant that influenced the mortality rate was SO2, and there were no gender differences in the impact of this pollutant. In the male population, an increased exposure to PM2.5 concentration was associated with significantly higher cardiovascular mortality. These findings suggest that improving air quality, in particular, even with lower SO2 levels than currently allowed by the World Health Organization (WHO) guidelines, may benefit public health. Further studies on this topic are needed, but our results bring questions whether the recommendations concerning acceptable concentrations of air pollutants should be stricter, or is there a safe concentration of SO2 in the air at all.

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