The Impact of Taiwan’s Rugged Orography on Air Pollutant Transport and the Numerical Modeling of 20 March 2018 Case

2020 ◽  
Author(s):  
Pao K. Wang ◽  
Chuan-Yao Lin
Keyword(s):  
Air Pollutants ◽  
Great Influence ◽  
Wrf Model ◽  
Satellite Observation ◽  
Air Pollutant ◽  
Local Circulation ◽  
Pressure System ◽  
Comparison Of The Results ◽  
Cloud Patterns ◽  
The Impact

<p>Taiwan is a subtropical island with an area of only about 36,000 km<sup>2</sup> and yet packed with high density of mountains. There are 268 peaks that are taller than 3000 m in elevation and, as a result, the mountains are extremely rugged. Such rugged orography will certainly have great influence on the local circulation and consequently impact on the transport of air pollutants. It is thus necessary to understand the impact of the orography on air flow before we can interpret the measured data during the EMeRGe-Asia campaign in March-April 2018 correctly.</p><p>For the above purpose, we performed high resolution numerical simulations of the flow around Taiwan region for two cases using the Weather Research and Forecast (WRF) model. The first one is a highly stagnant case where Taiwan was under the influence of a high pressure system occurring on 10 November 2018. Two horizontal resolutions are used: 1 km and 2 km, both show very similar flow and cloud patterns as revealed by satellite images of the day. Detailed analysis of the simulated results including the flow pattern and isentropic analysis will be shown to illustrate that low level pollutants can be transported upward to at least 1 km altitude even under such calm weather.</p><p>The second one is the 20 March 2018 case which occurred during the EMeRGe-Asia campaign. Unlike the above stagnant case, this was a more turbulent situation when a typhoon was approaching from the east and a southerly flow carried air pollutants from SE Asia. The 1 km resolution simulation shows good match with satellite observation. The simulation results show a substantial concentration of VOC at ~ 3000 m altitude near Taiwan whereas the VOC was very low near the surface. The model reproduces this feature well and hence it appears that the model’s predictions are credible. More detailed analyses are being performed and comparison of the results with combined ground and aircraft observations to illustrate the impact of the orography on the transport of pollutants.  </p>

FRI0531 AIR POLLUTANTS AND DEVELOPMENT OF INTERSTITIAL LUNG DISEASE IN PATIENTS WITH AUTOIMMUNE DISEASES

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 865.1-865
Author(s):  
H. H. Chen ◽  
W. C. Chao ◽  
Y. H. Chen ◽  
D. Y. Chen ◽  
C. H. Lin
Keyword(s):  
Air Quality ◽  
Autoimmune Diseases ◽  
Air Pollutants ◽  
Air Pollutant ◽  
Air Quality Monitoring ◽  
Newly Diagnosed ◽  
Science Technology ◽  
Air Quality Monitoring Stations ◽  
The Impact ◽  
Modest Level

Background:Interstitial lung disease (ILD) is characterized by progressive inflammation and fibrosis, and accumulating evidence have shown that exposure to air pollutants was associated with the development of ILD. Autoimmune diseases are highly correlated with ILD, including connective tissue disease-associated ILD (CTD-ILD) as well as interstitial pneumonia with autoimmune features (IPAF), and the development of ILD is a crucial cause of morbidity and mortality in patients with autoimmune diseases. One recent Taiwanese study reported that exposure to air pollutants was associated with incident systemic lupus erythematosus (SLE). However, the impact of air pollutants on the development of ILD among patients with autoimmune diseases remains unknown.Objectives:The study aimed to address the impact of accumulating exposure to air pollutant above moderate level, defined by Air Quality Index (AQI) value higher than 50, on the development of ILD in patients with autoimmune diseases including SLE, rheumatoid arthritis (RA) and primary Sjögren’s syndrome (SS).Methods:We used a National Health Insurance Research Database in Taiwan to enroll patients with SLE (International Classification of Diseases (ICD)-9 code 710.0, n=13,211), RA (ICD-9 code 714.0 and 714.30–714.33, n=32,373), and primary SS (ICD-9 code, 710.0, n=15,246) between 2001 and 2013. We identified newly diagnosed ILD cases (ICD-code 515) between 2012 and 2013 and selected age, sex, disease duration and index-year matched (1:4) patients as non-ILD controls. The hourly levels of air pollutants one year prior to the index-date were obtained from 60 air quality monitoring stations across Taiwan, and the air pollutants in the present study consisted of particulate matter <2.5 μm in size (PM2.5), particulate matter <10 μm in size (PM10), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2) and ozone (O3). We used a spatio-temporal model built by a deep-learning mechanism to estimate levels of air pollutants at 374 residential locations based on data of 3 air quality monitoring stations near the location (8). Notably, we used cumulative exposed hours to air pollutants higher than modest level, defined by AQI criteria, given that daily mean level of air pollutants might possibly underestimate the triggered inflammatory effect by a temporary exposure of high-level air pollutant. A conditional logistic regression was used to determine the association between exposure to air pollutant and the development of ILD, adjusting age, gender, Charlson Comorbidity Index (CCI), urbanization, family income, and medications for autoimmune diseases.Results:A total of 272 patients with newly diagnosed ILD were identified among patients with autoimmune diseases, including 39 with SLE, 135 with RA, and 98 with primary SS. We found that the duration of exposure to PM 2.5 higher than modest level was associated with the risk of ILD development in patients with SS (adjOR 1.07, 95% CI 1.01–1.13), and similar trends were also found in patients with SLE (adjOR 1.03, 95% CI 0.95–1.12) and RA (adjOR 1.03, 95% CI 0.99–1.07). Intriguingly, we observed an inverse correlation between the duration of exposure to O3 and the development of ILD in patients with SS (adjOR 0.83, 95% CI 0.70–0.99); however, the finding was not found in patients with SLE (adjOR 1.13, 95% CI 0.92–1.37) and RA (adjOR 0.98, 95% CI 0.87–1.11).Conclusion:In conclusion, we identified that longer exposure to PM2.5 higher than modest level tended to be associated with the development of ILD in patients with autoimmune diseases, mainly SS.References:[1] Araki T, Putman RK, Hatabu H, Gao W, Dupuis J, Latourelle JC, et al. Development and Progression of Interstitial Lung Abnormalities in the Framingham Heart Study. Am J Respir Crit Care Med 2016;194:1514-1522.[2] Tang KT, Tsuang BJ, Ku KC, Chen YH, Lin CH, Chen DY. Relationship between exposure to air pollutants and development of systemic autoimmune rheumatic diseases: a nationwide population-based case-control study. Ann Rheum Dis 2019;78:1288-1291.Disclosure of Interests:Hsin-Hua Chen: None declared, Wen-Cheng Chao: None declared, Yi-Hsing Chen Grant/research support from: Taiwan Ministry of Science and Technology, Taiwan Department of Health, Taichung Veterans General Hospital, National Yang-Ming University, GSK, Pfizer, BMS., Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead., Paid instructor for: Pfizer, Novartis, Johnson & Johnson, Roche, Lilly, Astra& Zeneca, Sanofi, Astellas, Agnitio Science Technology, United Biopharma., Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead., Der-Yuan Chen: None declared, Ching-Heng Lin: None declared

scholarly journals Air pollutants and outpatient visits for cardiovascular disease in a severe haze-fog city: Shijiazhuang, China

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Fengzhu Tan ◽  
Weijie Wang ◽  
Sufen Qi ◽  
Haidong Kan ◽  
Xinpei Yu ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Air Pollutants ◽  
Attributable Risk ◽  
Air Pollutant ◽  
Outpatient Visits ◽  
Pollutant Concentrations ◽  
Main Factors ◽  
High Concentrations ◽  
Air Pollutant Concentrations ◽  
The Impact

Abstract Background Many studies have reported the impact of air pollution on cardiovascular disease (CVD), but few of these studies were conducted in severe haze-fog areas. The present study focuses on the impact of different air pollutant concentrations on daily CVD outpatient visits in a severe haze-fog city. Methods Data regarding daily air pollutants and outpatient visits for CVD in 2013 were collected, and the association between six pollutants and CVD outpatient visits was explored using the least squares mean (LSmeans) and logistic regression. Adjustments were made for days of the week, months, air temperature and relative humidity. Results The daily CVD outpatient visits for particulate matter (PM10 and PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) in the 90th-quantile group were increased by 30.01, 29.42, 17.68, 14.98, 29.34%, and − 19.87%, respectively, compared to those in the <10th-quantile group. Odds ratios (ORs) and 95% confidence intervals (CIs) for the increase in daily CVD outpatient visits in PM10 300- and 500-μg/m3, PM2.5 100- and 300-μg/m3 and CO 3-mg/m3 groups were 2.538 (1.070–6.020), 7.781 (1.681–36.024), 3.298 (1.559–6.976), 8.72 (1.523–49.934), and 5.808 (1.016–33.217), respectively, and their corresponding attributable risk percentages (AR%) were 60.6, 87.15, 69.68, 88.53 and 82.78%, respectively. The strongest associations for PM10, PM2.5 and CO were found only in lag 0 and lag 1. The ORs for the increase in CVD outpatient visits per increase in different units of the six pollutants were also analysed. Conclusions All five air pollutants except O3 were positively associated with the increase in daily CVD outpatient visits in lag 0. The high concentrations of PM10, PM2.5 and CO heightened not only the percentage but also the risk of increased daily CVD outpatient visits. PM10, PM2.5 and CO may be the main factors of CVD outpatient visits.

Status of Air Pollutant Emissions and Health Impact of LNG Cogeneration Plant in Administrative City, Republic of Korea

2020 ◽  
Author(s):  
Yumi Kim
Keyword(s):  
Power Plant ◽  
Urban Areas ◽  
Air Pollutants ◽  
Health Impact ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Risk Level ◽  
Cogeneration Plant ◽  
Impact Prediction ◽  
The Impact

&lt;p&gt;&lt;span&gt;&lt;span&gt;Along with the development of new cities, the construction of LNG cogeneration plant in urban areas is being promoted, and the facility has been pointed out as one of the major air pollution sources along with many vehicles in urban areas. For example, the construction of a new administrative city in Korea has led to the relocation of major government buildings and the influx of more than 300,000 people. The city has a 530 MW power plant + 391 Gcal/h district heating facility. The facility released 294,835 kg and 325,381 kg of NOx annually in 2017 and 2018, respectively. When examining the impact, we analyzed the impact of air pollutants (PM&lt;sub&gt;2.5&lt;/sub&gt;, O&lt;sub&gt;3&lt;/sub&gt;, NO&lt;sub&gt;2&lt;/sub&gt;, etc.) through CMAQ modeling. In addition, the impact prediction using AERMOD related to the release of carcinogenic air pollutants is estimated to be no more than 10&lt;sup&gt;-5&lt;/sup&gt; (risk level), but measurement and verification are required. In addition to concentration-based risk assessments, health impact assessments are needed that consider the number of populations exposed. In this study, QGIS was used to calculate population. In conclusion, even if the same LNG power plant is constructed, the LNG cogeneration plant located adjacent to a large residential facility requires air pollutant management measures according to the exposure population by radius of influence&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Laboratory investigation of the impact of air pollution on partial discharge inception voltage of insulators in a specific region

2021 ◽  
Vol 11 (6) ◽  
pp. 4634
Author(s):  
Y. Shafiei ◽  
F. Faghihi ◽  
H. Heydari ◽  
A. H. Salemi
Keyword(s):  
Air Pollutants ◽  
Systematic Approach ◽  
Partial Discharge ◽  
Air Pollutant ◽  
Laboratory Measurements ◽  
Discharge Performance ◽  
The Subject ◽  
The Impact ◽  
Inception Voltage ◽  
Comprehensive Study

<span lang="EN-US">Studying the discharge characteristics of transmission line insulators in the presence of pollution, particularly when the contaminated layer is wet by rain, fog or condensation, is necessary for selecting the proper insulation. Therefore, identifying the major air pollutants as well as the most effective ones on the discharge performance of outdoor insulators is mandatory. A systematic approach has been proposed to evaluate the impact of dominant air pollutants of an area on partial discharge (P.D) inception voltage of specimen insulators. Based on the suggested method, determining the pollution constituents, defining the dominant pollutant of the area, finding the most commonly used insulators for medium and above distribution voltages within the geographical boundaries of the Central Province of Iran, as well as examining the effect of dominant air pollutant of the region on partial discharge inception voltage of designated insulators by laboratory measurements, are the necessary steps toward a comprehensive study of the subject.</span>

scholarly journals Assessing the impact of long-term exposure to nine outdoor air pollutants on spatial spread of Covid-19: evidence from 107 Italian provinces

2021 ◽  
Author(s):  
Gaetano Perone
Keyword(s):  
Heavy Metals ◽  
Air Pollutants ◽  
Negative Binomial ◽  
Ordinary Least Squares ◽  
Air Pollutant ◽  
Outdoor Air ◽  
Italian Provinces ◽  
Spatial Autoregressive ◽  
The Impact

Abstract The coronavirus (COVID-19) pandemic has dramatically changed every aspect of people’s lives around the world over the past year and a half. Although the global vaccination campaign is progressing worldwide, new variants of COVID-19 have emerged, driving many countries into a fourth wave of COVID-19 contagion. This paper investigates the air quality in 107 Italian provinces in the period 2014–2019 and the association between long-term exposure to nine outdoor air pollutants and the prevalence of COVID-19 in the same areas. The methods used were negative binomial (NB) regressions, ordinary least squares (OLS) models, and spatial autoregressive models with autoregressive disturbances (SARAR). The air pollutants examined were common air pollutants (NO2, O3, PM2.5, PM10), polycyclic aromatic hydrocarbons (PAHs) (benzene and BaP), and heavy metals (As, Cd, and Ni). The results showed that i) common air pollutants were generally highly and positively correlated with density of large firms, energy and gas consumption, public transport, and the livestock sector; and ii) long-term exposure to NO2, PM2.5, PM10, benzene, BaP, and Cd was positively and significantly correlated with the spread of COVID-19, even after controlling for cofactors and spatial effects. This outcome seems of interest and relevance because PAHs and heavy metals have not been considered at all in recent literature. It also seems to suggest the need for a national strategy to drive down air pollutant concentrations in order to cope better with possible future pandemics.

scholarly journals A numerical study of the contribution to the air pollutant in Beijing during CAREBeijing-2006

2011 ◽  
Vol 11 (2) ◽  
pp. 5271-5312 ◽  
Author(s):  
Q. Z. Wu ◽  
Z. F. Wang ◽  
A. Gbaguidi ◽  
C. Gao ◽  
L. N. Li ◽  
...  
Keyword(s):  
Surface Layer ◽  
Air Quality ◽  
Rural Areas ◽  
Air Pollutants ◽  
High Performance ◽  
Numerical Study ◽  
Air Pollutant ◽  
Air Quality Prediction ◽  
Regional Sources ◽  
The Impact

Abstract. An online air pollutant tagged module has been developed in the Nested Air Quality Prediction Model System (NAQPMS) to investigate the impact of local and regional sources on the air pollutants in Beijing during the Campaign of Air Quality Research in Beijing 2006 (CAREBeijing-2006). The NAQPMS model shows high performance in simulating sulfur dioxide (SO2), particulate matter (PM10), nitrogen dioxide (NO2), and ozone (O3) with overall better agreements with the observations at urban sites than rural areas. With the tagged module, the air pollutant contributions from local and regional sources to the surface layer (about 30 m) and the upper layer (about 1.1 km) in Beijing are differentiated and estimated. The air pollutants at the surface layer in Beijing are dominated by the contributions from local sources, accounting for 65% of SO2, 75% of PM10 and nearly 90% of NO2, respectively, comparatively, the upper layer has large source contributions from the surrounding regions (e.g., southern Beijing), accounting for more than 50% of the SO2 and PM10 concentrations. Country scale analysis is also performed and the results suggest that Tianjin is the dominant source of SO2 in Pinggu County, and Langfang, Hebei is the most important regional contributor to PM10 in Beijing. Moreover, the surrounding regions show larger impact on SO2, PM10 and NO2 in the eastern counties of Beijing (e.g., Pinggu, Tongzhou and Daxing) than those in western Beijing, which is likely due to the Beijing's semi-basin topography and the summer monsoon. Our results indicate that the efforts to control the air pollutants in Beijing should focus on controlling both local and regional emissions.

scholarly journals The Impact of Atmospheric Pollutants on Human Health and Economic Loss Assessment

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1628
Author(s):  
Houli Zhang ◽  
Shibing You ◽  
Miao Zhang ◽  
Difei Liu ◽  
Xuyan Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Human Health ◽  
Air Pollutants ◽  
Respiratory Diseases ◽  
Meteorological Data ◽  
Air Pollutant ◽  
Atmospheric Pollutants ◽  
Economic Losses ◽  
Air Pollution Control ◽  
The Impact

The impact of air pollution on human health is becoming increasingly severe, and economic losses are a significant impediment to economic and social development. This paper investigates the impact of air pollutants on the respiratory system and its action mechanism by using information on inpatients with respiratory diseases from two IIIA (highest) hospitals in Wuhan from 2015 to 2019, information on air pollutants, and meteorological data, as well as relevant demographic and economic data in China. This paper describes the specific conditions of air pollutant concentrations and respiratory diseases, quantifies the degree of correlation between the two, and then provides a more comprehensive assessment of the economic losses using descriptive statistical methods, the generalized additive model (GAM), cost of illness approach (COI), and scenario analysis. According to the findings, the economic losses caused by PM2.5, PM10, SO2, NO2, and CO exposure are USD 103.17 million, USD 70.54 million, USD 98.02 million, USD 40.35 million, and USD 142.38 million, for a total of USD 454.46 billion, or approximately 0.20% of Wuhan’s GDP in 2019. If the government tightens control of major air pollutants and meets the WHO-recommended criterion values, the annual evitable economic losses would be approximately USD 69.4 million or approximately 0.03% of Wuhan’s GDP in 2019. As a result, the relevant government departments must strengthen air pollution control to mitigate the impact of air pollution on population health and the associated economic losses.

scholarly journals Short-Term Effect of Air Pollution on Tuberculosis Based on Kriged Data: A Time-Series Analysis

2020 ◽  
Vol 17 (5) ◽  
pp. 1522 ◽  
Author(s):  
Shuqiong Huang ◽  
Hao Xiang ◽  
Wenwen Yang ◽  
Zhongmin Zhu ◽  
Liqiao Tian ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Pollutants ◽  
Additive Model ◽  
Ground Level ◽  
Air Pollutant ◽  
Aerodynamic Diameter ◽  
Short Term ◽  
Short Term Exposure ◽  
Incident Cases ◽  
The Impact

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015–2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ground-level ozone (O3). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May–October) and cold (November–April) seasons. In the single-pollutant model, for a 10 μg/m3 increase in PM2.5, PM10, and O3 at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

scholarly journals Numerical Study on the Effect of Urbanization and Coastal Change on Sea Breeze over Qingdao, China

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 345 ◽  
Author(s):  
Shangfei Hai ◽  
Yucong Miao ◽  
Lifang Sheng ◽  
Linbo Wei ◽  
Qing Chen
Keyword(s):  
Human Activities ◽  
Urban Areas ◽  
Numerical Study ◽  
Wrf Model ◽  
Sea Breeze ◽  
Air Pollutant ◽  
Land Breeze ◽  
Coastal Change ◽  
Conversion Time ◽  
The Impact

During the past few decades, rapid economic development occurred in Qingdao. Inevitably, human activities have caused great changes to the underlying surface, including urbanization and coastal change. Coastal change mainly refers to the expansion of the coastline to increase coastal land area. Sea-land breeze (SLB) is important for local weather and the transport of air pollutant. However, the impact of human activities on the SLB over Qingdao is not yet clear. Thus, the weather research and forecasting (WRF) model is applied to study the effect of urbanization and coastal change on SLB. The study shows that urbanization strengthens the urban heat island (UHI) effect. Due to the expansions of urban area during past decades, sea breeze is strengthened before it passes through the urban areas. When it penetrates into the city, the inland progress of sea breeze is slowed down due to the UHI effect and stronger frictional force. Besides, the expansions of coastline can delay the SLB conversion time, lead to the changes in the sea breeze penetration path and the weakening of SLB intensity.

scholarly journals Remarks on Ambient Air Pollution and Health Outcomes

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Mieczysław Szyszkowicz
Keyword(s):  
Air Pollution ◽  
Health Outcomes ◽  
Air Pollutants ◽  
Conditional Logistic Regression ◽  
Ambient Air ◽  
Air Pollutant ◽  
Ambient Air Pollution ◽  
Health Conditions ◽  
Ed Visits ◽  
The Impact

Background. Ambient air pollution is a recognized risk factor for multiple health conditions. For some health problems, the impact of air pollution is particularly evident to the patients in a specific age range. Nonsimultaneous exposures to two or more air pollutants may have different relationships with health outcomes than do simultaneous exposures. Methods. Case-crossover technique was used to analyze data on emergency department (ED) visits for ischemic heart disease (IHD), epistaxis, and upper respiratory infection (URI). Conditional logistic regression models were used to estimate odds ratios and their 95% confidence intervals corresponding to an increase in an interquartile range of air pollutant concentrations. Results. The results for IHD show that for older patients (age 60+ years), the association between sulphur dioxide (SO2) exposure and IHD is weak. For ED visits for epistaxis (O3 and SO2 in one model) and URI (O3 and NO2 in one model), air pollutants lagged differently in the common model indicated significant statistical associations but not for common lags. Conclusion. The study findings, based on analyzed examples, suggest that (i) IHD cases in older age are less related to air pollution and (ii) air pollutants may affect some health conditions by a specific sequence of exposure occurrences.

Sign in / Sign up

Export Citation Format

Share Document