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1.
BMC Public Health ; 20(1): 1524, 2020 Oct 08.
Artigo em Inglês | MEDLINE | ID: mdl-33032561

RESUMO

BACKGROUND: Arrhythmia is a common cardiovascular event that is associated with increased cardiovascular health risks. Previous studies that have explored the association between air pollution and arrhythmia have obtained inconsistent results, and the association between the two in China is unclear. METHODS: We collected daily data on air pollutants and meteorological factors from 1st January 2014 to 31st December 2016, along with daily outpatient visits for arrhythmia in Hangzhou, China. We used a quasi-Poisson regression along with a distributed lag nonlinear model to study the association between air pollution and arrhythmia morbidity. RESULTS: The results of the single-pollutant model showed that each increase of 10 µg/m3 of Fine particulate matter (PM2.5), Coarse particulate matter (PM10), Sulphur dioxide (SO2), Nitrogen dioxide (NO2), and Ozone (O3) resulted in increases of 0.6% (- 0.9, 2.2%), 0.7% (- 0.4, 1.7%), 11.9% (4.5, 19.9%), 6.7% (3.6, 9.9%), and - 0.9% (- 2.9, 1.2%), respectively, in outpatient visits for arrhythmia; each increase of 1 mg/m3 increase of carbon monoxide (CO) resulted in increase of 11.3% (- 5.9, 31.6%) in arrhythmia. The short-term effects of air pollution on arrhythmia lasted 3 days, and the most harmful effects were observed on the same day that the pollution occurred. Results of the subgroup analyses showed that SO2 and NO2 affected both men and women, but differences between the sexes were not statistically significant. The effect of SO2 on the middle-aged population was statistically significant. The effect of NO2 was significant in both the young and middle-aged population, and no significant difference was found between them. Significant effects of air pollution on arrhythmia were only detected in the cold season. The results of the two-pollutants model and the single-pollutant model were similar. CONCLUSIONS: SO2 and NO2 may induce arrhythmia, and the harmful effects are primarily observed in the cold season. There is no evidence of PM2.5, PM10, CO and O3 increasing arrhythmia risk. Special attention should be given to sensitive populations during the high-risk period.


Assuntos
Poluição do Ar/efeitos adversos , Assistência Ambulatorial/estatística & dados numéricos , Arritmias Cardíacas/epidemiologia , Arritmias Cardíacas/terapia , Poluentes Atmosféricos/análise , Poluição do Ar/análise , China/epidemiologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estações do Ano
2.
Sci Rep ; 10(1): 16213, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-33004925

RESUMO

Italy was the first, among all the European countries, to be strongly hit by the COVID-19 pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2). The virus, proven to be very contagious, infected more than 9 million people worldwide (in June 2020). Nevertheless, it is not clear the role of air pollution and meteorological conditions on virus transmission. In this study, we quantitatively assessed how the meteorological and air quality parameters are correlated to the COVID-19 transmission in two large metropolitan areas in Northern Italy as Milan and Florence and in the autonomous province of Trento. Milan, capital of Lombardy region, it is considered the epicenter of the virus outbreak in Italy. Our main findings highlight that temperature and humidity related variables are negatively correlated to the virus transmission, whereas air pollution (PM2.5) shows a positive correlation (at lesser degree). In other words, COVID-19 pandemic transmission prefers dry and cool environmental conditions, as well as polluted air. For those reasons, the virus might easier spread in unfiltered air-conditioned indoor environments. Those results will be supporting decision makers to contain new possible outbreaks.


Assuntos
Poluição do Ar/estatística & dados numéricos , Infecções por Coronavirus/epidemiologia , Umidade , Pneumonia Viral/epidemiologia , Temperatura , Cidades/estatística & dados numéricos , Infecções por Coronavirus/transmissão , Humanos , Itália , Pandemias , Pneumonia Viral/transmissão , População Urbana/estatística & dados numéricos
3.
Environ Monit Assess ; 192(11): 719, 2020 Oct 21.
Artigo em Inglês | MEDLINE | ID: mdl-33083907

RESUMO

An environmental problem which is of concern across the globe nowadays is air pollution. The extent of air pollution is often studied based on data on the observed level of air pollution. Although the analysis of air pollution data that is available in the literature is numerous, studies on the dynamics of air pollution with the allowance for spatial interaction effects through the use of the Markov chain model are very limited. Accordingly, this study aims to explore the potential impact of spatial dependence over time and space on the distribution of air pollution based on the spatial Markov chain (SMC) model using the longitudinal air pollution index (API) data. This SMC model is pertinent to be applied since the daily data of API from 2012 to 2014 that have been gathered from 37 different air quality stations in Peninsular Malaysia is found to exhibit the property of spatial autocorrelation. Based on the spatial transition probability matrices found from the SMC model, specific characteristics of air pollution are studied in the regional context. These characteristics are the long-run proportion and the mean first passage time for each state of air pollution. It is found that the probability for a particular station's state to remain good is 0.814 if its neighbors are in a good state of air pollution and 0.7082 if its neighbors are in a moderate state. For a particular station having neighbors in a good state of air pollution, the proportion of time for it to continue being in a good state is 0.6. This proportion reduces to 0.4, 0.01, and 0 for the cell of moderate, unhealthy, and very unhealthy states, respectively. In addition, there exists a significant spatial dependence of API, indicating that air pollution for a particular station is dependent on the states of the neighboring stations.


Assuntos
Poluição do Ar , Monitoramento Ambiental , Poluição do Ar/análise , Malásia , Cadeias de Markov , Análise Espacial
4.
Artigo em Inglês | MEDLINE | ID: mdl-33050278

RESUMO

At the end of 2019, the first cases of coronavirus disease (COVID-19) were reported in Wuhan, China. Thereafter, the number of infected people increased rapidly, and the outbreak turned into a national crisis, with infected individuals all over the country. The COVID-19 global pandemic produced extreme changes in human behavior that affected air quality. Human mobility and production activities decreased significantly, and many regions recorded significant reductions in air pollution. The goal of our investigation was to evaluate the impact of the COVID-19 lockdown on the concentrations of the main air pollutants in the urban area of Palermo (Italy). In this study, the trends in the average concentrations of CO, NO2, O3, and PM10 in the air from 1 January 2020 to 31 July 2020 were compared with the corresponding average values detected at the same monitoring stations in Palermo during the previous five years (2015-2019). During the lockdown period (10 March-30 April), we observed a decrease in the concentrations of CO, NO2, and particulate matter (PM)10, calculated to be about 51%, 50%, and 45%, respectively. This confirms that air pollution in an urban area is predominantly linked to vehicular traffic.


Assuntos
Poluição do Ar/estatística & dados numéricos , Infecções por Coronavirus/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Quarentena , População Urbana , Infecções por Coronavirus/epidemiologia , Humanos , Itália/epidemiologia , Pneumonia Viral/epidemiologia
5.
Environ Monit Assess ; 192(11): 693, 2020 Oct 10.
Artigo em Inglês | MEDLINE | ID: mdl-33037947

RESUMO

The subject of this paper is the possibility of using self-organizing map (SOM) in the biomonitoring studies. We used lichens as biomonitors to indicate different degrees of air quality. This research included all of 88 lichen species that was collected at 75 investigated points. These lichen species showed the different responses to air pollution. The air quality was assessed by IAP (index of atmospheric pollution) values. The IAP values were calculated for all of investigated points on the territory of four natural and one urban ecosystem. Calculated IAP values were in range of 10 to 75. On the basis of the lichen data and IAP values, we have employed SOM analysis that distinguished three clusters (A, B, and C). It presented lichen indicator species for each cluster: 16 species for cluster A, 18 species for cluster B, and two species for cluster C. This paper presents a useful method to find indicator species.


Assuntos
Poluição do Ar , Líquens , Península Balcânica , Ecossistema , Monitoramento Ambiental , Sérvia
6.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 5378-5381, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33019197

RESUMO

This paper investigates the association between consecutive ambient air pollution and Chronic Obstructive Pulmonary Disease (COPD) hospitalization in Chengdu China. The three-year (2015-2017) time series data for both ambient air pollutant concentrations and COPD hospitalizations in Chengdu are approved for the study. The big data statistic analysis shows that Air Quality Index (AQI) exceeded the lighted air polluted level in Chengdu region are mainly attributed to particulate matters (i.e., PM2.5 and PM10). The time series study for consecutive ambient air pollutant concentrations reveal that AQI, PM2.5, and PM10 are significantly positive correlated, especially when the number of consecutive polluted days is greater than nine days. The daily COPD hospitalizations for every 10 µg/m3 increase in PM2.5 and PM10 indicate that consecutive ambient air pollution can lead to an appearance of an elevation of COPD admissions, and also present that dynamic responses before and after the peak admission are different. Support Vector Regression (SVR) is then used to describe the dynamics of COPD hospitalizations to consecutive ambient air pollution. These findings will be further developed for region specific, hospital early notifications of COPD in responses to consecutive ambient air pollution.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Doença Pulmonar Obstrutiva Crônica , Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , China/epidemiologia , Hospitalização , Humanos , Doença Pulmonar Obstrutiva Crônica/epidemiologia
7.
J Infect Dev Ctries ; 14(9): 994-1000, 2020 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-33031087

RESUMO

Mozambique is located on the East Coast of Africa and was one of the last countries affected by COVID-19. The first case was reported on 22 March 2020 and since then the cases have increased gradually as they have in other countries worldwide. Environmental and population characteristics have been analyzed worldwide to understand their possible association with COVID-19. This article seeks to highlight the evolution and the possible contribution of risk factors for COVID-19 severity according to the available data in Mozambique. The available data highlight that COVID-19 severity can be magnified mainly by hypertension, obesity, cancer, asthma, HIV/SIDA and malnutrition conditions, and buffered by age (youthful population). Due to COVID-19 epidemic evolution, particularly in Cabo Delgado, there is the need to increase laboratory diagnosis capacity and monitor compliance of preventive measures. Particular attention should be given to Cabo Delgado, including its isolation from other provinces, to overcome local transmission and the spread of SARS-CoV-2.


Assuntos
Poluição do Ar/efeitos adversos , Betacoronavirus , Infecções por Coronavirus/etiologia , Pneumonia Viral/etiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Moçambique/epidemiologia , Pandemias/prevenção & controle , Pneumonia Viral/diagnóstico , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Prognóstico , Fatores de Proteção , Fatores de Risco , Índice de Gravidade de Doença , Adulto Jovem
9.
Allergol. immunopatol ; 48(5): 496-499, sept.-oct. 2020.
Artigo em Inglês | IBECS | ID: ibc-191742

RESUMO

In late 2019, a new infectious disease (COVID-19) was identified in Wuhan, China, which has now turned into a global pandemic. Countries around the world have implemented some type of blockade to lessen their infection and mitigate it. The blockade due to COVID-19 has drastic effects on the social and economic fronts. However, recent data released by the National Aeronautics and Space Administration (NASA), European Space Agency (ESA), Copernicus Sentinel-5P Tropomi Instrument and Center for Research on Energy and Clean Air (CREA) indicate that the pollution in some of the epicenters of COVID-19, such as Wuhan, Italy, Spain, USA, and Brazil, reduced by up to 30%. This study compiled the environmental data released by these centers and discussed the impact of the COVID-19 pandemic on environmental pollution


No disponible


Assuntos
Humanos , Poluição do Ar/efeitos adversos , Material Particulado/efeitos adversos , Infecções por Coronavirus , Pneumonia Viral , Betacoronavirus , Pandemias
10.
Chemosphere ; 258: 127310, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32947673

RESUMO

We characterized the aerosol composition and sources of particulate matter (PM) in Sanmenxia, a polluted city located in the Fen-Wei Plain region of Central China. The PM2.5 concentration decreased by 18% from 72 µg m-3 in 2014 to 59 µg m-3 in 2019. All chemical species presented pronounced seasonal variations, with their highest concentrations in winter due to enhanced emissions and the frequent stagnant meteorological conditions. Nitrate was the major fraction of PM2.5 during all seasons (35-41%) except summer (25%), while sulfate was a dominant species in summer (29%) compared to other seasons (16-18%) from July 2018 to June 2019. The detailed analysis of a wintertime severe haze episode that lasted for approximately half a month demonstrated that secondary aerosols, including secondary organic aerosol, sulfate, nitrate, and ammonium, contributed 89% to non-refractory PM1 (NR-PM1), indicating the remarkable role of secondary aerosol formation in air pollution in Sanmenxia. Positive matrix factorization analysis further showed considerably enhanced low-volatility oxygenated organic aerosol (OA) and hydrocarbon-like OA during severe haze episodes, while significant contributions in semi-volatile oxygenated OA and coal combustion OA during clean periods. Severe pollution events in the city were generally associated with air masses from the southwest, and we also found that aerosol species, especially secondary aerosol species, showed distinct forenoon increases that were caused by the subsidence of air pollutants aloft. Our results highlight that future air quality improvement would benefit substantially from a more efficient control of gaseous precursors, particularly the NOx emissions from industry and vehicle emissions.


Assuntos
Aerossóis/análise , Poluentes Atmosféricos/análise , Poluição do Ar/estatística & dados numéricos , Poluição do Ar/análise , China , Cidades , Carvão Mineral/análise , Monitoramento Ambiental/métodos , Poluentes Ambientais/análise , Poluição Ambiental/análise , Hidrocarbonetos/química , Nitratos/análise , Óxidos de Nitrogênio/análise , Material Particulado/análise , Estações do Ano , Emissões de Veículos/análise
11.
Chemosphere ; 254: 126815, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32957269

RESUMO

A revised Community Multi-scale Air Quality (CMAQ) model with updated secondary organic aerosol (SOA) yields and a more detailed description of SOA formation from isoprene (ISOP) oxidation was applied to study the spatial distribution of SOA, its components and precursors in Shaanxi in July of 2013. The emissions of biogenic volatile organic compounds (BVOCs) were generated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN), of which ISOP and monoterpene (MONO) were the top two, with 1.73 × 109 mol and 1.82 × 108 mol, respectively. The spatial distribution of BVOCs emission was significantly correlated with the vegetation coverage distribution. ISOP and its intermediate semi-volatile gases were up to ∼7.0 and ∼1.4 ppb respectively in the ambient. SOA was generally 2-6 µg/m3, of which biogenic SOA (BSOA) accounted for as high as 84% on average. There were three main BVOCs Precursors including ISOP (58%) and MONO (8%) emit in the studied domain, and ISOP (9%) transported. The Guanzhong Plain had the highest BSOA concentrations of 3-5 µg/m3, and the North Shaanxi had the lowest of 2-3 µg/m3. More than half of BSOA was due to reactive surface uptake of ISOP epoxide (0.2-0.7 µg/m3, ∼19%), glyoxal (GLY) (0.2-0.5 µg/m3, ∼11%) and methylglyoxal (MGLY) (0.4-1.4 µg/m3, ∼32%), while the remaining was due to the traditional equilibrium partitioning of semi-volatile components (0.1-1.2 µg/m3, ∼25%) and oligomerization (0.2-0.4 µg/m3, ∼12%). Overall, SOA formed from ISOP contributed 1-3 µg/m3 (∼80%) to BSOA.


Assuntos
Aerossóis/análise , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Poluição do Ar , Butadienos , China , Hemiterpenos , Monoterpenos/análise , Compostos Orgânicos Voláteis/análise
12.
Artigo em Inglês | MEDLINE | ID: mdl-32867037

RESUMO

Seoul, the most populous city in South Korea, has been practicing social distancing to slow down the spread of coronavirus disease 2019 (COVID-19). Fine particulate matter (PM2.5) and other air pollutants measured in Seoul over the two 30 day periods before and after the start of social distancing are analyzed to assess the change in air quality during the period of social distancing. The 30 day mean PM2.5 concentration decreased by 10.4% in 2020, which is contrasted with an average increase of 23.7% over the corresponding periods in the previous 5 years. The PM2.5 concentration decrease was city-wide and more prominent during daytime than at nighttime. The concentrations of carbon monoxide (CO) and nitrogen dioxide (NO2) decreased by 16.9% and 16.4%, respectively. These results show that social distancing, a weaker forcing toward reduced human activity than a strict lockdown, can help lower pollutant emissions. At the same time, synoptic conditions and the decrease in aerosol optical depth over the regions to the west of Seoul support that the change in Seoul's air quality during the COVID-19 social distancing can be interpreted as having been affected by reductions in the long-range transport of air pollutants as well as local emission reductions.


Assuntos
Poluição do Ar/análise , Infecções por Coronavirus/epidemiologia , Monitoramento Ambiental , Pneumonia Viral/epidemiologia , Poluentes Atmosféricos/análise , Betacoronavirus , Humanos , Pandemias , Material Particulado/análise , Seul
13.
Artigo em Inglês | MEDLINE | ID: mdl-32872261

RESUMO

Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM2.5 and PM10 during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM2.5 and PM10 concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R2 of 0.711 and 0.732 for PM2.5 and PM10, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM2.5 in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM10 in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM10 drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future.


Assuntos
Poluentes Atmosféricos/análise , Infecções por Coronavirus/epidemiologia , Monitoramento Ambiental , Material Particulado/análise , Pneumonia Viral/epidemiologia , Poluição do Ar/análise , Betacoronavirus , China , Cidades , Humanos , Pandemias
14.
Environ Health Perspect ; 128(9): 95001, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32902328

RESUMO

BACKGROUND: Studies have reported that ambient air pollution is associated with an increased risk of developing or dying from coronavirus-2 (COVID-19). Methodological approaches to investigate the health impacts of air pollution on epidemics should differ from those used for chronic diseases, but the methods used in these studies have not been appraised critically. OBJECTIVES: Our study aimed to identify and critique the methodological approaches of studies of air pollution on infections and mortality due to COVID-19 and to identify and critique the methodological approaches of similar studies concerning severe acute respiratory syndrome (SARS). METHODS: Published and unpublished papers of associations between air pollution and developing or dying from COVID-19 or SARS that were reported as of 10 May 2020 were identified through electronic databases, internet searches, and other sources. RESULTS: All six COVID-19 studies and two of three SARS studies reported positive associations. Two were time series studies that estimated associations between daily changes in air pollution, one was a cohort that assessed associations between air pollution and the secondary spread of SARS, and six were ecological studies that used area-wide exposures and outcomes. Common shortcomings included possible cross-level bias in ecological studies, underreporting of health outcomes, using grouped data, the lack of highly spatially resolved air pollution measures, inadequate control for confounding and evaluation of effect modification, not accounting for regional variations in the timing of outbreaks' temporal changes in at-risk populations, and not accounting for nonindependence of outcomes. DISCUSSION: Studies of air pollution and novel coronaviruses have relied mainly on ecological measures of exposures and outcomes and are susceptible to important sources of bias. Although longitudinal studies with individual-level data may be imperfect, they are needed to adequately address this topic. The complexities involved in these types of studies underscore the need for careful design and for peer review. https://doi.org/10.1289/EHP7411.


Assuntos
Poluição do Ar/efeitos adversos , Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Síndrome Respiratória Aguda Grave/epidemiologia , Poluição do Ar/análise , Viés , Surtos de Doenças , Estudos Epidemiológicos , Humanos , Pandemias , Projetos de Pesquisa , Fatores de Risco
15.
Respir Med ; 171: 106085, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32917356

RESUMO

BACKGROUND: Chronic respiratory diseases are risk factors for severe disease in coronavirus disease 2019 (COVID-19). Respiratory tract infection is one of the commonest causes of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). There has not been evidence suggesting the link between COVID-19 and AECOPD, especially in places with dramatic responses in infection control with universal masking and aggressive social distancing. METHODS: This is a retrospective study to assess the number of admissions of AECOPD in the first three months of 2020 in Queen Mary Hospital with reference to the admissions in past five years. Log-linear model was used for statistical inference of covariates, including percentage of masking, air quality health index and air temperature. RESULTS: The number of admissions for AECOPD significantly decreased by 44.0% (95% CI 36.4%-52.8%, p < 0.001) in the first three months of 2020 compared with the monthly average admission in 2015-2019. Compare to same period of previous years, AECOPD decreased by 1.0% with each percent of increased masking (p < 0.001) and decreased by 3.0% with increase in 1 °C in temperature (p = 0.045). The numbers of admissions for control diagnoses (heart failure, intestinal obstruction and iron deficiency anaemia) in the same period in 2020 were not reduced. CONCLUSIONS: The number of admissions for AECOPD decreased in first three months of 2020, compared with previous years. This was observed with increased masking percentage and social distancing in Hong Kong. We postulated universal masking and social distancing during COVID-19 pandemics both contributed in preventing respiratory tract infections hence AECOPD.


Assuntos
Infecções por Coronavirus , Pandemias , Admissão do Paciente/estatística & dados numéricos , Pneumonia Viral , Doença Pulmonar Obstrutiva Crônica , Infecções Respiratórias , Poluição do Ar/análise , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/terapia , Feminino , Hong Kong/epidemiologia , Humanos , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/epidemiologia , Pneumonia Viral/terapia , Doença Pulmonar Obstrutiva Crônica/epidemiologia , Doença Pulmonar Obstrutiva Crônica/terapia , Dispositivos de Proteção Respiratória/estatística & dados numéricos , Infecções Respiratórias/epidemiologia , Infecções Respiratórias/etiologia , Infecções Respiratórias/prevenção & controle , Estudos Retrospectivos , Fatores de Risco , Distância Social , Exacerbação dos Sintomas
16.
PLoS One ; 15(9): e0237863, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32986700

RESUMO

The green development of coastal urban agglomerations, which are strategic core areas of national economic growth in China, has become a major focus of both academics and government agencies. In this paper, China's coastal urban agglomeration is taken as the research area, aiming at the serious air pollution problem of coastal urban agglomeration, geographic information system (ArcGIS10.2) spatial analysis and the spatial Dubin model were applied to National Aeronautics and Space Administration atmospheric remote sensing image inversion fine particulate matter (PM2.5) data from 2010-2016 to reveal the temporal and spatial evolution characteristics and Influence mechanism of PM2.5 in China's coastal urban agglomerations, with a view to providing a reference value for coordinating air pollution in the coastal cities of the world. From 2010-2016, the PM2.5 concentration in China's coastal urban agglomerations decreased as a whole, and large spatial differences in PM2.5 concentration were observed in China's coastal urban agglomerations; the core high-pollution areas were the Beijing-Tianjin-Hebei, Shandong Peninsula, and Yangtze River Delta urban agglomerations. Large spatial differences in PM2.5 concentration were also observed within individual urban agglomerations, with higher PM2.5 concentrations found in the northern parts of the urban agglomerations. Significant spatial autocorrelation and spatial heterogeneity were observed among PM2.5-polluted cities in China's coastal urban agglomerations. The northern coastal urban agglomerations formed a relatively stable and continuous high-pollution zone. The spatial Dubin model was used to analyze the driving factors of PM2.5 pollution in coastal urban agglomerations. Together, meteorological, socioeconomic, pollution source, and ecological factors affected the spatial characteristics of PM2.5 pollution during the study period, and the overall effect was a mixed effect with significant spatial variation. Among them, meteorological factors were the greatest driver of PM2.5 pollution. In the short term, the rapid increase in population density, industrial emissions, industrial energy consumption, and total traffic emissions were the important driving factors of PM2.5 pollution in the coastal urban agglomerations of China.


Assuntos
Poluição do Ar/análise , Ecossistema , Sistemas de Informação Geográfica , Urbanização , Poluentes Atmosféricos/análise , Algoritmos , China , Análise Fatorial , Produto Interno Bruto , Modelos Teóricos , Tamanho da Partícula , Material Particulado/análise , Fatores de Tempo
17.
Environ Monit Assess ; 192(10): 646, 2020 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-32939661

RESUMO

We investigated the associations between the daily variations of coarse particulate matter (PM10) and/or sulfur dioxide (SO2) and hospital admissions for asthma and/or chronic obstructive pulmonary disease (COPD) diseases in Kirsehir, Center of Anatolia of Turkey. We analyzed the poison generalized linear model (GLM) to analyze the association between ambient air pollutants such as PM10 and SO2 and asthma and/or COPD admissions. We investigated single-lag days and multi-lag days for the risk increase in asthma, COPD, asthma, and/or COPD hospital admissions PM10, SO2, and PM10 with SO2 per 10 µg/m3. In single-lag day model a 10 µg/m3 increase in the current day (lag 0) concentrations of PM10 and SO2 corresponded to increase of 1.027 (95% CI:1.022-1.033) and 1.069 (95% CI:1.062, 1.077) for asthma. A 10 µg/m3 increase in the current day (lag 0) concentrations of PM10 and SO2 corresponded to increase of 1.029 (95% CI:1.022-1.035) and 1.065 (95% CI:1.056, 1.075) for COPD. A 10 µg/m3 increase in the current day (lag 0) concentrations of PM10 and SO2 corresponded to increase of 1.028 (95% CI:1.024-1.032) and 1.068 (95% CI:1.062, 1.074) for asthma and/or COPD. It was found that some lag structures were related with PM10 and SO2. Significant lags were detected in some lag structures from the previous first day until the previous eighth day (lag 1 to lag 7) in the asthma, COPD, and asthma and/or COPD hospital admissions in the model created with PM10 with SO2 both in the single-lag day model and in the multi-lag day model. Our study that used GLM in time series analysis showed that PM10 and/or SO2 short-term exposure in single-lag day and multi-lag day models was related with increased asthma, COPD, and asthma and/or COPD hospital admissions in the city between 2016 and 2019 until the previous-eighth day.


Assuntos
Poluentes Atmosféricos/análise , Poluição do Ar/análise , Asma , Doença Pulmonar Obstrutiva Crônica , Monitoramento Ambiental , Humanos , Dióxido de Nitrogênio/análise , Material Particulado/análise , Dióxido de Enxofre/análise , Turquia
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