A social network analysis of tourism activity patterns among domestic tourists influenced by fine particulate matter (PM2.5) concentration

2021 ◽  
Vol 30 (7) ◽  
pp. 237-252
Author(s):  
Deuk-Hee Park ◽  
Chul-Hee Lim
Keyword(s):  
Particulate Matter ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Activity Patterns ◽  
Fine Particulate Matter ◽  
Fine Particulate ◽  
Tourism Activity ◽  
Pm2.5 Concentration

scholarly journals The Combined Effects of Fine Particulate Matter and Temperature on Preterm Birth in Seoul, 2010–2016

2021 ◽  
Vol 18 (4) ◽  
pp. 1463
Author(s):  
Youngrin Kwag ◽  
Min-ho Kim ◽  
Shinhee Ye ◽  
Jongmin Oh ◽  
Gyeyoon Yim ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Preterm Birth ◽  
Pregnant Women ◽  
Low Temperatures ◽  
Fine Particulate Matter ◽  
Temperature Data ◽  
Fine Particulate ◽  
The Mean ◽  
Pm2.5 Exposure ◽  
Pm2.5 Concentration

Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM2.5) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010–2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM2.5 concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM2.5 and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM2.5 concentration was used in units of ×10 µg/m3 and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM2.5 exposure and preterm birth, as well as the combined effects of PM2.5 exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM2.5 and temperature data as exposures, which assumes an interaction between PM2.5 and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM2.5 exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061–1.213, p < 0.001). Conclusions: When we assumed the interaction between PM2.5 exposure and temperature exposure, PM2.5 exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.

scholarly journals Effect of modes of transportation on commuters' exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in Chennai, India

2019 ◽  
Vol 25 (6) ◽  
pp. 898-907 ◽  
Author(s):  
M. Gokul Raj ◽  
S. Karthikeyan
Keyword(s):  
Particulate Matter ◽  
Nitrogen Dioxide ◽  
Urban Community ◽  
Fine Particulate Matter ◽  
Exposure Concentration ◽  
Ambient Particulate Matter ◽  
Fine Particulate ◽  
The Mean ◽  
Maximum Exposure ◽  
Pm2.5 Concentration

Daily commuting increases level of contaminants inhaled by urban community and it is influenced by mode and time of commuting. In this study, the commuters’ exposure to ambient particulate matter (PM2.5) and nitrogen dioxide (NO2) was assessed during three modes of travel in six different road stretches of Chennai. The mean distance of road stretches was 25 km and the exposure to pollutants was assessed during peak hours and off-peak hours. The average travel duration was in the range of 39 to 91 min in motorbike, 83 to 140 min in car and 110 to 161 min in bus. Though there was variation on exposure to concentration in modes of transportation, the maximum exposure concentration of PM2.5 was observed as 709 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 29 μg/m<sup>3</sup> in closed car. Similarly, the maximum exposure concentration of NO2 was observed to be 312 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 21 μg/m<sup>3</sup> in car. The concentration of elements in PM2.5 was in the order of Si > Na > Ca > Al ≥ K > S ≥ Cd, with Si and Cd concentration as 60% and < 1% of the PM2.5 concentration.

scholarly journals Visualization of Correlation for Air Pollution Time Series using TAQMN Data

2019 ◽  
Vol 8 (3) ◽  
pp. 7922-7927
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Particulate Matter ◽  
Pearson Correlation ◽  
Fine Particulate Matter ◽  
Correlation Method ◽  
Well Being ◽  
Pollution Levels ◽  
Fine Particulate ◽  
Pm2.5 Concentration

In Taiwan country Annan, Chiayi, Giran, and Puzi cities are facing a serious fine particulate matter (PM2.5) issue. To date the impressive advance has been made toward understanding the PM2.5 issue, counting special temporal characterization, driving variables and well-being impacted. However, notable research as has been done on the interaction of the content between the selected cities of Taiwan country for particulate matter (PM2.5) concentration. In this paper, we purposed a visualization technique based on this principle of the visualization, cross-correlation method and also the time-series concentration with particulate matter (PM2.5) for different cities in Taiwan. The visualization also shows that the correlation between the different meteorological factors as well as the different air pollution pollutants for particular cities in Taiwan. This visualization approach helps to determine the concentration of the air pollution levels in different cities and also determine the Pearson correlation, r values of selected cities are Annan, Puzi, Giran, and Wugu.

scholarly journals Short-Term Associations of Fine Particulate Matter and Synoptic Weather Types with Cardiovascular Mortality: An Ecological Time-Series Study in Shanghai, China

2020 ◽  
Vol 17 (3) ◽  
pp. 1111 ◽  
Author(s):  
Qing Tian ◽  
Mei Li ◽  
Scott Montgomery ◽  
Bo Fang ◽  
Chunfang Wang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Cardiovascular Mortality ◽  
Fine Particulate Matter ◽  
Weather Conditions ◽  
Cold Weather ◽  
Short Term ◽  
Weather Types ◽  
Synoptic Weather ◽  
Fine Particulate ◽  
Pm2.5 Concentration

Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.

scholarly journals Variation Trends of Fine Particulate Matter Concentration in Wuhan City from 2013 to 2017

2018 ◽  
Vol 15 (7) ◽  
pp. 1487 ◽  
Author(s):  
Daoru Liu ◽  
Qinli Deng ◽  
Zeng Zhou ◽  
Yaolin Lin ◽  
Junwei Tao
Keyword(s):  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Wuhan City ◽  
Fine Particulate ◽  
Variation Patterns ◽  
Average Proportion ◽  
June July ◽  
Matter Concentration ◽  
Mean Concentration ◽  
Pm2.5 Concentration

Fine particulate matter (PM2.5) is directly associated with smog and has become the primary factor that threatens air quality in China. In order to investigate the variation patterns of PM2.5 concentrations in various regions of Wuhan city across different time spans, we analyzed continuous monitoring data from six monitoring sites in Wuhan city from 2013 to 2017. The results showed that the PM2.5 concentration from the various monitoring sites in the five-year period showed a decreasing trend. January, October, and December are the three months with relatively high mean monthly PM2.5 concentrations in the year, while June, July, and August are the three months with relatively low mean monthly PM2.5 concentrations in the year. The number of days with a daily mean concentration of 35–75 μg/m3 was the highest, while the number of days with a daily mean concentration of more than 250 μg/m3 was the lowest. PM2.5 accounted for a large proportion of the major pollutants and is the main source of air pollution in Wuhan city, with an average proportion of over 46%.

scholarly journals Monitoring Air Pollution Variability during Disasters

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 420
Author(s):  
Earthea Nance
Keyword(s):  
Particulate Matter ◽  
New Technologies ◽  
Fine Particulate Matter ◽  
Air Quality Management ◽  
Mobile Monitoring ◽  
Short Term ◽  
Fine Particulate ◽  
Gulf Oil Spill ◽  
National Environmental ◽  
Pm2.5 Concentration

National environmental regulations lack short-term standards for variability in fine particulate matter (PM2.5); they depend solely on concentration-based standards. Twenty-five years of research has linked short-term PM2.5, that is, increases of at least 10 μg/m3 that can occur in-between regulatory readings, to increased mortality. Even as new technologies have emerged that could readily monitor short-term PM2.5, such as real-time monitoring and mobile monitoring, their primary application has been for research, not for air quality management. The Gulf oil spill offers a strategic setting in which regulatory monitoring, computer modeling, and stationary monitoring could be directly compared to mobile monitoring. Mobile monitoring was found to best capture the variability of PM2.5 during the disaster. The research also found that each short-term increase (≥10 μg/m3) in fine particulate matter was associated with a statistically significant increase of 0.105 deaths (p < 0.001) in people aged 65 and over, which represents a 0.32% increase. This research contributes to understanding the effects of PM2.5 on mortality during a disaster and provides justification for environmental managers to monitor PM2.5 variability, not only hourly averages of PM2.5 concentration.

scholarly journals Analisis Risiko Pajanan PM2,5 di Udara Ambien Siang Hari terhadap Masyarakat di Kawasan Industri Semen

2012 ◽  
Vol 7 (4) ◽  
pp. 173
Author(s):  
Randy Novirsa ◽  
Umar Fahmi Achmadi
Keyword(s):  
Particulate Matter ◽  
Respiratory Disease ◽  
Activity Patterns ◽  
Fine Particulate Matter ◽  
Cement Industry ◽  
Fine Particulate ◽  
Increased Risk ◽  
Environmental Health Risk ◽  
Negative Impacts ◽  
Industry Risk

Salah satu dampak negatif industri pabrik semen terhadap kesehatan masyarakat adalah peningkatan risiko penyakit saluran pernapasan. Risiko tersebut banyak disebabkan oleh pajanan partikulat di udara, khususnya partikulat berukuran di bawah 2,5 mikron (PM2,5). Penelitian ini bertujuan menganalisis risiko pajanan PM2,5 di udara ambien siang hari pada masyarakat di kawasan industri semen. Risiko dihitung dengan metode Analisis Risiko Kesehatan Lingkungan berdasarkan metode Louvar yang menghasilkan nilai Intake pajanan yang diterima individu per hari berdasarkan nilai konsentrasi pajanan, pola aktivitas individu, dan nilai antropometri. Konsentrasi PM2,5 di lingkungan diukur pada 10 titik dengan radius 500 meter antartitik dari pusat pabrik, sedangkan pola aktivitas dan nilai antropometri diukur dengan menggunakan kuesioner pada 92 responden dewasa di kawasan pabrik. Hasil perhitungan risiko yang diterima seumur hidup (lifetime) menunjukkan terdapat tiga area berisiko dengan nilai RQ > 1, yaitu Ring 2 (500 – 1.000 m), Ring 4 (1.500 – 2.000 m), dan Ring 5 (2.000 – 2.500 m). Daerah paling aman yang dapat dihuni oleh masyarakat di kawasan industri semen adalah di atas 2,5 km dari pusat industri dengan konsentrasi paling aman 0,028 mg/m3.Kata kunci: Industri semen, infeksi saluran pernapasan, partikulat PM2,5AbstractOne of the negative impacts of cement industry to public health is an increased risk of respiratory disease. These risks are caused by exposure to particulate matter in air, especially fine particulate matter which is smaller than 2,5 microns (PM2,5). This study aimed to analyze the risks of PM2,5 exposure in ambien air at noon on people around cement industry. Risk was calculated using Environmental Health Risk Analysis Method that generates value of individual exposure intake received per day. This value was generated based on the concentration of exposure, individual activity patterns, and anthropometric values. PM2,5 concentrations in the environment was measured at 10 points (Ring) from the center of plant with radius of 500 meters each point. The activity patterns and anthropometric values were measured using questionnaire to 92 adult respondents around the factory. The calculation of lifetime risk showed that there are three risked area: Ring 2 (500 – 1.000 m), Ring 4 (1.500 – 2.000 m), and Ring 5 (2.000 – 2.500 m). The safest area was over 2,5 kilometers from the center of the industry with the safest concentration was 0,028 mg/m3.Keywords: Cement industry, respiratory disease, particulate PM2,5

scholarly journals Analysis of Spatio-Temporal Heterogeneity and Socioeconomic Driving Factors of PM2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1324
Author(s):  
Ju Wang ◽  
Ran Li ◽  
Kexin Xue ◽  
Chunsheng Fang
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Shandong Province ◽  
Temporal Heterogeneity ◽  
Pollution Levels ◽  
Fine Particulate ◽  
Spatio Temporal ◽  
Surrounding Areas ◽  
Pm2.5 Concentration

Due to rapid urbanization and socio-economic development, fine particulate matter (PM2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of “high–high” and “low–low”. The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM2.5 pollutions from a socio-economic perspective.

scholarly journals Particulate matter concentrations during winter seasons of 2016-2020 in Ulaanbaatar, Mongolia

2021 ◽  
pp. 30-39
Author(s):  
Ganzorig Byambajav ◽  
Bayarmaa Batbaatar ◽  
Ariundelger Ariunsaikhan ◽  
Sonomdagva Chonokhuu
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Single Point ◽  
Fine Particulate Matter ◽  
Measurement Data ◽  
Central Area ◽  
National Standards ◽  
Fine Particulate ◽  
The Government ◽  
Pm2.5 Concentration

In this study, we have focused on the outdoor concentration of fine particulate matter (PM2.5) during the coldest months (November-February) of 2016-2019 and January-February of 2020 and illustrated the daily, monthly and quarterly averages according to the single-point measurement data collected by the PM2.5 sensor at an air quality monitoring station located in a central area of Ulaanbaatar. The study also analyzes monthly high, low, average and median points of PM2.5 concentrations in the area that was selected. The PM2.5 sensor collects its data at an interval of every ten seconds, registers 8500 data in one day and presents the concentration of fine particulate matter in micrograms per cubic meter (μg/m3). On the basis of data collection and analysis, from November through February of 2019-2020, average PM2.5 concentration dropped noticeably by 44 per cent compared to the previous years. The Government of Mongolia took immediate action to combat air pollution of Ulaanbaatar city in May 2019 by banning the burning of raw coal in the ger districts, which account for 70 per cent of the city’s emissions, and introduced coal briquette as the only type of fuel that was allowed to be burned in metal stoves as a primary source of heating and cooking. Our study reveals that the latest government regulation had a considerable impact on air quality during winter 2019-2020 and helped in the sudden decline of the most dangerous pollutant PM2.5 concentration very close to national standards (50 µg/m3 24-hour mean) within 6 months since the enforcement of the new regulation.

scholarly journals How Do Economic Growth, Urbanization, and Industrialization Affect Fine Particulate Matter Concentrations? An Assessment in Liaoning Province, China

2020 ◽  
Vol 17 (15) ◽  
pp. 5441
Author(s):  
Tuo Shi ◽  
Yuanman Hu ◽  
Miao Liu ◽  
Chunlin Li ◽  
Chuyi Zhang ◽  
...  
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Particulate Matter ◽  
Rapid Development ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Liaoning Province ◽  
Fine Particulate ◽  
Pm2.5 Concentration

With China’s rapid development, urban air pollution problems occur frequently. As one of the principal components of haze, fine particulate matter (PM2.5) has potential negative health effects, causing widespread concern. However, the causal interactions and dynamic relationships between socioeconomic factors and ambient air pollution are still unclear, especially in specific regions. As an important industrial base in Northeast China, Liaoning Province is a representative mode of social and economic development. Panel data including PM2.5 concentration and three socio-economic indicators of Liaoning Province from 2000 to 2015 were built. The data were first-difference stationary and the variables were cointegrated. The Granger causality test was used as the main method to test the causality. In the results, in terms of the causal interactions, economic activities, industrialization and urbanization processes all showed positive long-term impacts on changes of PM2.5 concentration. Economic growth and industrialization also significantly affected the variations in PM2.5 concentration in the short term. In terms of the contributions, industrialization contributed the most to the variations of PM2.5 concentration in the sixteen years, followed by economic growth. Though Liaoning Province, an industry-oriented region, has shown characteristics of economic and industrial transformation, policy makers still need to explore more targeted policies to address the regional air pollution issue.

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