In this work we used the Gaussian plume model to calculate the actual maximum ground level concentration (MGLC) of air pollutant and its downwind location by using different systems of dispersion parameters and for different stack heights. An approximate formula for the prediction of downwind position that produces the MGLC of a pollutant based on the Gaussian formula was derived for different diffusion parameters. The derived formula was used to calculate the approximate MGLC. The actual and estimated values are presented in tables. The comparison between the actual and estimated values was investigated through the calculation of the relative errors. The values of the relative errors between the actual and estimated MGLC lie in the range from: 0 to 70.2 and 0 to 1.6 for Pasquill Gifford system and Klug system respectively. The errors between the actual and estimated location of the MGLC lies in the range from: 0.2 to 227 and 0.7 to 9.4 for Pasquill Gifford system and Klug system respectively.
{"title":"Relation between the Actual and Estimated Maximum Ground Level Concentration of Air Pollutant and Its Downwind Locations","authors":"K. Essa, S. Etman, M. El-Otaify","doi":"10.4236/ojap.2020.92003","DOIUrl":"https://doi.org/10.4236/ojap.2020.92003","url":null,"abstract":"In this work we used the Gaussian plume model to calculate the actual \u0000maximum ground level concentration (MGLC) of air pollutant and its downwind \u0000location by using different systems of dispersion parameters and for different \u0000stack heights. An approximate formula for the prediction of downwind position \u0000that produces the MGLC of a pollutant based on the Gaussian formula was derived \u0000for different diffusion parameters. The derived formula was used to calculate \u0000the approximate MGLC. The actual and estimated values are presented in tables. \u0000The comparison between the actual and estimated values was investigated through \u0000the calculation of the relative errors. The values of the relative errors \u0000between the actual and estimated MGLC lie in the range from: 0 to 70.2 and 0 to \u00001.6 for Pasquill Gifford system and Klug system respectively. The errors \u0000between the actual and estimated location of the MGLC lies in the range from: \u00000.2 to 227 and 0.7 to 9.4 for Pasquill Gifford system and Klug system \u0000respectively.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44786872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Senghor, E. Machu, L. Durán, G. Jenkins, A. Gaye
The Westward transport of mineral dust from the North Africa continent to Atlantic Ocean can produce poor air quality, low visibilities, and negatively impacting respiratory and cardiac health due to the optical and physical properties of aerosols. The dynamical impact of the sea-breeze on the dust vertical distribution in West Africa remains unknown. To investigate this issue, we have used in-situ measurements from lidar. We have focused on the attenuated backscatter of aerosols to study the effect of the local circulation on the vertical profile of mineral dust at land-sea transition. The results highlight a strong diurnal cycle of mineral dust associated with the nocturnal low-level jet (NLLJ). The jet is located between 500 m and 1000 m and crucially affected by the dynamic of the sea-breeze circulation.
{"title":"Seasonal Behavior of Aerosol Vertical Concentration in Dakar and Role Played by the Sea-Breeze","authors":"H. Senghor, E. Machu, L. Durán, G. Jenkins, A. Gaye","doi":"10.4236/ojap.2020.91002","DOIUrl":"https://doi.org/10.4236/ojap.2020.91002","url":null,"abstract":"The \u0000Westward transport of mineral dust from the North Africa continent to Atlantic \u0000Ocean can produce poor air quality, low visibilities, and negatively impacting \u0000respiratory and cardiac health due to the optical and physical properties of \u0000aerosols. The dynamical impact of the sea-breeze on the dust vertical \u0000distribution in West Africa remains unknown. To investigate this issue, we have \u0000used in-situ measurements from lidar. We have focused on the attenuated backscatter of \u0000aerosols to study the effect of the local circulation on the vertical profile \u0000of mineral dust at land-sea transition. The results highlight a strong diurnal \u0000cycle of mineral dust associated with the nocturnal low-level jet (NLLJ). The \u0000jet is located between 500 m and 1000 m and crucially affected by the dynamic \u0000of the sea-breeze circulation.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41513263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Houngbégnon, Gloria Ayivi-Vinz, H. Lawin, K. Houessionon, Fadel Tanimomon, M. Kedote, B. Fayomi, S. Dossou-Gbété, V. Agueh
Background: Several studies have analysed the pollution issues owing to road traffic in Cotonou, Benin. Concentration levels of particles are higher on high traffic than a low traffic. The exposure of human populations to air pollution is more intense on the roads. In Benin, the density of traffic on the crossroads is indeed more important. Are traffic locations such as crossroads, areas where the level of exposure PM2.5 is increased? Methods: This study was conducted along the 5 km high-traffic road in the city of Cotonou. It is a high traffic lane with two crossroads. Sampling and measurements were carried out in dry sea-son (January and February) and rainy season (June and July). For each season the measurements were made over two months from 7 am to 9 pm. PM2.5 measurements were made at different locations at crossroads and also along the track. To compare concentrations of PM2.5 at crossroads and outside of roundabout, we used the Generalized Linear Mixed Model. Results: In the rainy season the PM2.5 hourly concentrations ranged between 400 μg/m3 and 500 μg/m3 while in the dry season 100 μg/m3 and 300 μg/m3. In the rainy season, the average of PM2.5 concentration was 463.25 ± 66.21 μg/m3 at crossroads and 264.75 ± 50.97 μg/m3 outside of crossroads. In the dry season, the average of PM2.5 concentration was 232.75 ± 97.29 μg/m3 at crossroads and 123.31 ± 63.79 μg/m3 outside of crossroads. Both in dry and rainy seasons, PM2.5 concentration level peaks are observed from 7 am to 9 am and from 7 pm to 9 pm. The Generalized Linear Mixed Model showed that there is high significant difference between concentrations of PM2.5 at crossroads compared to outside of crossroads. Occupation of the roadside (in particular crossroads) for various economic activities is common practice in Cotonou thus health risk for people working around crossroads increases. Conclusion: Locations such as crossroads are areas where the level of exposure PM2.5 is highest on road traffics.
{"title":"Exposure to PM2.5 Related to Road Traffic: Comparison between Crossroads and Outside of Crossroads at Cotonou, Benin","authors":"P. Houngbégnon, Gloria Ayivi-Vinz, H. Lawin, K. Houessionon, Fadel Tanimomon, M. Kedote, B. Fayomi, S. Dossou-Gbété, V. Agueh","doi":"10.4236/ojap.2019.84006","DOIUrl":"https://doi.org/10.4236/ojap.2019.84006","url":null,"abstract":"Background: Several studies have analysed the pollution issues owing to road traffic in Cotonou, Benin. Concentration levels of particles are higher on high traffic than a low traffic. The exposure of human populations to air pollution is more intense on the roads. In Benin, the density of traffic on the crossroads is indeed more important. Are traffic locations such as crossroads, areas where the level of exposure PM2.5 is increased? Methods: This study was conducted along the 5 km high-traffic road in the city of Cotonou. It is a high traffic lane with two crossroads. Sampling and measurements were carried out in dry sea-son (January and February) and rainy season (June and July). For each season the measurements were made over two months from 7 am to 9 pm. PM2.5 measurements were made at different locations at crossroads and also along the track. To compare concentrations of PM2.5 at crossroads and outside of roundabout, we used the Generalized Linear Mixed Model. Results: In the rainy season the PM2.5 hourly concentrations ranged between 400 μg/m3 and 500 μg/m3 while in the dry season 100 μg/m3 and 300 μg/m3. In the rainy season, the average of PM2.5 concentration was 463.25 ± 66.21 μg/m3 at crossroads and 264.75 ± 50.97 μg/m3 outside of crossroads. In the dry season, the average of PM2.5 concentration was 232.75 ± 97.29 μg/m3 at crossroads and 123.31 ± 63.79 μg/m3 outside of crossroads. Both in dry and rainy seasons, PM2.5 concentration level peaks are observed from 7 am to 9 am and from 7 pm to 9 pm. The Generalized Linear Mixed Model showed that there is high significant difference between concentrations of PM2.5 at crossroads compared to outside of crossroads. Occupation of the roadside (in particular crossroads) for various economic activities is common practice in Cotonou thus health risk for people working around crossroads increases. Conclusion: Locations such as crossroads are areas where the level of exposure PM2.5 is highest on road traffics.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41911913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nébon Bado, A. Ouedraogo, H. Guengane, T. S. M. Ky, S. D. Bazyomo, B. Korgo, M. Drame, S. Sall, F. Kiéno, D. Bathiébo
This paper deals with the climatology of aerosols in West Africa based on satellite and in situ measurements between 2001 and 2016 and covers four sites in the Sahelian zone. There are indeed Banizoumbou (13.541°N, 02.665°E), Cinzana (13.278°N, 05.934°W), Dakar (14.394°N, 16.959°W) and Ouagadougou (12.20°N, 1.40°W) located respectively in Niger, Mali, Senegal and Burkina Faso. Thus, an intercomparison between the satellite observations and the in situ measurements shows a good correlation between MODIS and AERONET with a correlation coefficient R = 0.86 at Cinzana, R = 0.85 at Banizounbou, R = 0.84 at Ouagadougou and a low correlation coefficient R = 0.66 calculated on the Dakar site. Like MODIS, SeaWiFS shows a very good correspondence with measurements of the ground photometer especially for Banizoumbou (R = 0.89), Cinzana (R = 0.88) and Dakar (R = 0.75) followed by a low correlation coefficient calculated on the Ouagadougou site (R = 0.64). The performance of these airborne sensors is also corroborated by the calculation of root mean square error (RMSE) and the mean absolute error (MAE). Following this validation, a climatological analysis based on aerosol optical depth (AOD) shows the seasonality of aerosols in West Africa strongly influenced by the climate dynamics illustrated by the MERRA model reanalysis. This seasonal spatial distribution of aerosols justifies the temporal variability of the particles observed at the different sites in the Sahel. In addition, a combined analysis of AOD and Angstrom coefficient indicates the aerosol period in the Sahel in spring (March-April-May) and summer (June-July-August). However, these aerosols are strongly dominated by desert dust whose main sources are located north in the Sahara and Sahel.
{"title":"Climatological Analysis of Aerosols Optical Properties by Airborne Sensors and in Situ Measurements in West Africa: Case of the Sahelian Zone","authors":"Nébon Bado, A. Ouedraogo, H. Guengane, T. S. M. Ky, S. D. Bazyomo, B. Korgo, M. Drame, S. Sall, F. Kiéno, D. Bathiébo","doi":"10.4236/ojap.2019.84007","DOIUrl":"https://doi.org/10.4236/ojap.2019.84007","url":null,"abstract":"This paper deals with the climatology of aerosols in West Africa based on satellite and in situ measurements between 2001 and 2016 and covers four sites in the Sahelian zone. There are indeed Banizoumbou (13.541°N, 02.665°E), Cinzana (13.278°N, 05.934°W), Dakar (14.394°N, 16.959°W) and Ouagadougou (12.20°N, 1.40°W) located respectively in Niger, Mali, Senegal and Burkina Faso. Thus, an intercomparison between the satellite observations and the in situ measurements shows a good correlation between MODIS and AERONET with a correlation coefficient R = 0.86 at Cinzana, R = 0.85 at Banizounbou, R = 0.84 at Ouagadougou and a low correlation coefficient R = 0.66 calculated on the Dakar site. Like MODIS, SeaWiFS shows a very good correspondence with measurements of the ground photometer especially for Banizoumbou (R = 0.89), Cinzana (R = 0.88) and Dakar (R = 0.75) followed by a low correlation coefficient calculated on the Ouagadougou site (R = 0.64). The performance of these airborne sensors is also corroborated by the calculation of root mean square error (RMSE) and the mean absolute error (MAE). Following this validation, a climatological analysis based on aerosol optical depth (AOD) shows the seasonality of aerosols in West Africa strongly influenced by the climate dynamics illustrated by the MERRA model reanalysis. This seasonal spatial distribution of aerosols justifies the temporal variability of the particles observed at the different sites in the Sahel. In addition, a combined analysis of AOD and Angstrom coefficient indicates the aerosol period in the Sahel in spring (March-April-May) and summer (June-July-August). However, these aerosols are strongly dominated by desert dust whose main sources are located north in the Sahara and Sahel.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42403297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While hydrogen fluoride (HF) and hydrogen chloride (HCl) are not considered main air-pollutants in the EU, they have the potential to contribute to acidification. Hydrofluorocarbons (HFCs), hydrofluoro-olefins (HFOs) and hydrochlorofluoro-olefins (HCFOs) are used as refrigerants and for other applications. They break down in the atmosphere to produce HF and HCl (for HCFOs) and some of these fluorocarbons also break down to produce trifluoroacetic acid (TFA). For the emissions of these fluorocarbons in the EU, a worst-case scenario estimates their theoretical potential contribution to acidification and compares it to the acidification potential for the main air pollutants contributing to acidification, which are nitrous oxides (NOx), sulphur oxides (mainly SO2), and ammonia (NH3). The Acidification Potential from these fluorocarbons in 2016 is estimated at 2, NOx, NH3, and it can be concluded that this is insignificant in the context of the main acidification air-pollutants. Assuming that the EU targets for emissions of SO2, NOx and NH3 by 2030 are achieved, the Acidification Potential from HFCs, HFOs and HCFOs in 2030 is also estimated at 2, NOx, NH3 and will remain insignificant.
{"title":"Contribution of Hydrofluorocarbons (HFCs) and Hydrofluoro-Olefins (HFOs) Atmospheric Breakdown Products to Acidification (“Acid Rain”) in the EU at Present and in the Future","authors":"A. Lindley, A. Mcculloch, Tim Vink","doi":"10.4236/ojap.2019.84004","DOIUrl":"https://doi.org/10.4236/ojap.2019.84004","url":null,"abstract":"While hydrogen fluoride (HF) and hydrogen chloride (HCl) are not considered main air-pollutants in the EU, they have the potential to contribute to acidification. Hydrofluorocarbons (HFCs), hydrofluoro-olefins (HFOs) and hydrochlorofluoro-olefins (HCFOs) are used as refrigerants and for other applications. They break down in the atmosphere to produce HF and HCl (for HCFOs) and some of these fluorocarbons also break down to produce trifluoroacetic acid (TFA). For the emissions of these fluorocarbons in the EU, a worst-case scenario estimates their theoretical potential contribution to acidification and compares it to the acidification potential for the main air pollutants contributing to acidification, which are nitrous oxides (NOx), sulphur oxides (mainly SO2), and ammonia (NH3). The Acidification Potential from these fluorocarbons in 2016 is estimated at 2, NOx, NH3, and it can be concluded that this is insignificant in the context of the main acidification air-pollutants. Assuming that the EU targets for emissions of SO2, NOx and NH3 by 2030 are achieved, the Acidification Potential from HFCs, HFOs and HCFOs in 2030 is also estimated at 2, NOx, NH3 and will remain insignificant.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46316398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bruna Marmett, R. Carvalho, Fernanda Ramos Rhoden, C. Rhoden
Traffic-related air pollution is an alarming source of pollutants exposure and consequently to the development of several adverse health effects. Otherwise, green spaces are reported to improve health status. Although, in an urban scenario most of these areas are located near air pollutants sources, as vehicle fleet. Thus, the aim of the present study was to determine, during one year, the levels of nitrogen dioxide (NO2) and ozone (O3) in the main parks from Porto Alegre—Brazil. This study focused on three urban parks: Germania, Moinhos de Vento and Marinha do Brasil Park. Nitrogen dioxide and ozone measurements were accessed by passive monitoring in four campaigns including all seasons and performed at distances of 0 m, 15 m, 30 m, 45 m, 60 m and 75 m from the main road at each park. NO2 and O3 concentration among the parks was not different (p > 0.05), as well as the mean concentration of NO2 and O3 of all parks in the six sites did not differ (p > 0.05). However, season 1 and 3 showed increased NO2 and O3 concentration. Temperature were decreased in season 1 and 3 (p p > 0.05). Traffic flow was higher in Moinhos de Vento Park and Marinha do Brasil Park compared to Germania Park (p 2 and O3 concentration in urban parks from Porto Alegre.
与交通有关的空气污染是污染物暴露的一个令人担忧的来源，因此会对健康产生一些不利影响。否则，据报道，绿地可以改善健康状况。尽管如此，在城市场景中，这些区域大多位于空气污染源附近，如车队。因此，本研究的目的是在一年内确定巴西阿雷格里港主要公园的二氧化氮（NO2）和臭氧（O3）水平。这项研究的重点是三个城市公园：日耳曼尼亚，莫因霍斯德文托和马林哈巴西公园。二氧化氮和臭氧测量通过四次活动（包括所有季节）的被动监测进行，并在距离每个公园主干道0米、15米、30米、45米、60米和75米的距离处进行。公园间NO2和O3浓度无差异（p>0.05），6个地点所有公园的NO2和O3平均浓度也无差异（p>0.05）。第1季和第3季的气温有所下降（p>0.05）。与日耳曼尼亚公园相比，Moinhos de Vento公园和Marinha do Brasil公园的交通流量更高（阿雷格里港城市公园的P2和O3浓度）。
{"title":"Seasonal Influence in Traffic-Related Air Pollutants Concentrations in Urban Parks from Porto Alegre, Brazil","authors":"Bruna Marmett, R. Carvalho, Fernanda Ramos Rhoden, C. Rhoden","doi":"10.4236/ojap.2019.84005","DOIUrl":"https://doi.org/10.4236/ojap.2019.84005","url":null,"abstract":"Traffic-related air pollution is an alarming source of pollutants exposure and consequently to the development of several adverse health effects. Otherwise, green spaces are reported to improve health status. Although, in an urban scenario most of these areas are located near air pollutants sources, as vehicle fleet. Thus, the aim of the present study was to determine, during one year, the levels of nitrogen dioxide (NO2) and ozone (O3) in the main parks from Porto Alegre—Brazil. This study focused on three urban parks: Germania, Moinhos de Vento and Marinha do Brasil Park. Nitrogen dioxide and ozone measurements were accessed by passive monitoring in four campaigns including all seasons and performed at distances of 0 m, 15 m, 30 m, 45 m, 60 m and 75 m from the main road at each park. NO2 and O3 concentration among the parks was not different (p > 0.05), as well as the mean concentration of NO2 and O3 of all parks in the six sites did not differ (p > 0.05). However, season 1 and 3 showed increased NO2 and O3 concentration. Temperature were decreased in season 1 and 3 (p p > 0.05). Traffic flow was higher in Moinhos de Vento Park and Marinha do Brasil Park compared to Germania Park (p 2 and O3 concentration in urban parks from Porto Alegre.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45732862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Cancila, Irene Sabbadini, Marco Ottolenghi, M. Deserti, Sara Tessitore
The air quality survey investigated the level of perception and awareness of citizens on the air quality in the 42 cities (provincial capitals) of the Po basin in the north west of Italy. This study means that perceptions could then be compared between in the Po basin and other parts of Italy and Europe. This research was carried out as part of the Life15 IPE IT 013 PREPAIR Project (Po Regions Engaged to Policies of Air), which involves 18 national and international partners, and includes all the regions of the Po Basin. The survey involved around 7331 citizens that live in the Po basin that includes 42 cities (provincial capitals) and a total of 6.5 million inhabitants. A multivariate analysis was applied to identify the main citizens’ profiles concerning the topic of air quality and the availability to implement virtuous behaviours to reduce air pollution. Four different profiles emerge from the cluster analysis: “Committed and proactive”, “Willing but …”, “Hesitant”, “Not willing”.
空气质量调查调查了意大利西北部波河流域42个城市（省会）的公民对空气质量的感知和意识水平。这项研究意味着，可以将波河流域与意大利和欧洲其他地区的看法进行比较。这项研究是Life15 IPE IT 013 PREPAIR项目（参与空气政策的Po地区）的一部分，该项目涉及18个国家和国际合作伙伴，包括Po盆地的所有地区。这项调查涉及居住在Po流域的约7331名公民，该流域包括42个城市（省会）和650万居民。应用多元分析来确定主要公民关于空气质量主题的概况，以及实施良性行为以减少空气污染的可用性。聚类分析得出了四种不同的概况：“承诺和积极主动”、“愿意但…”、“犹豫不决”、“不愿意”。
{"title":"Citizens and Air Quality: The Results of the First Survey Carried Out in the Po River Basin (Northern Italy)","authors":"E. Cancila, Irene Sabbadini, Marco Ottolenghi, M. Deserti, Sara Tessitore","doi":"10.4236/ojap.2019.83003","DOIUrl":"https://doi.org/10.4236/ojap.2019.83003","url":null,"abstract":"The air quality survey investigated the level of perception and awareness of citizens on the air quality in the 42 cities (provincial capitals) of the Po basin in the north west of Italy. This study means that perceptions could then be compared between in the Po basin and other parts of Italy and Europe. This research was carried out as part of the Life15 IPE IT 013 PREPAIR Project (Po Regions Engaged to Policies of Air), which involves 18 national and international partners, and includes all the regions of the Po Basin. The survey involved around 7331 citizens that live in the Po basin that includes 42 cities (provincial capitals) and a total of 6.5 million inhabitants. A multivariate analysis was applied to identify the main citizens’ profiles concerning the topic of air quality and the availability to implement virtuous behaviours to reduce air pollution. Four different profiles emerge from the cluster analysis: “Committed and proactive”, “Willing but …”, “Hesitant”, “Not willing”.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46941249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The impacts of low and high-frequency variability from teleconnections between large scale atmospheric processes and local weather as well as emissions changes on concentrations of particulate matter of 2.5 μm or less in diameter ([PM2.5]) were examined for the Fairbanks Metropolitan Area (FMA). October to March and May to August mean [PM2.5] were 1.8 and 3.1 μg·m-3 higher for positive than negative annual mean Pacific Decadal Oscillation. Annual mean [PM2.5] were 3.8 μg·m-3 lower for positive than negative Southern Oscillation Index. On 1999-2018 average, [PM2.5] decreased 2.9 μg·m-3·decade-1. On average over October to March, decadal and inter-annual variability caused higher or similar differences in mean observed [PM2.5] and its species than emission-control measures. The 2006 implementation of Tier 2 for new vehicles decreased observed sulfate concentrations the strongest (~4.95 μg·m-3·decade-1) of all occurred emissions changes. On average, observed [PM2.5] showed elevated values at all sites when wind blew from directions of hot springs. The same was found for the sulfate, ammonium and non-metal components of PM2.5. Observations showed that these geothermal waters contain sulfate, ammonia, boric acid and non-metals. Hot springs of such composition are known to emit hydrogen sulfide and ammonia that can serve as precursors for ammonium and sulfate aerosols.
{"title":"Geothermal, Oceanic, Wildfire, Meteorological and Anthropogenic Impacts on PM2.5 Concentrations in the Fairbanks Metropolitan Area","authors":"N. Mölders, G. Fochesatto, S. Edwin, G. Kramm","doi":"10.4236/OJAP.2019.82002","DOIUrl":"https://doi.org/10.4236/OJAP.2019.82002","url":null,"abstract":"The impacts of low and high-frequency variability from teleconnections between large scale atmospheric processes and local weather as well as emissions changes on concentrations of particulate matter of 2.5 μm or less in diameter ([PM2.5]) were examined for the Fairbanks Metropolitan Area (FMA). October to March and May to August mean [PM2.5] were 1.8 and 3.1 μg·m-3 higher for positive than negative annual mean Pacific Decadal Oscillation. Annual mean [PM2.5] were 3.8 μg·m-3 lower for positive than negative Southern Oscillation Index. On 1999-2018 average, [PM2.5] decreased 2.9 μg·m-3·decade-1. On average over October to March, decadal and inter-annual variability caused higher or similar differences in mean observed [PM2.5] and its species than emission-control measures. The 2006 implementation of Tier 2 for new vehicles decreased observed sulfate concentrations the strongest (~4.95 μg·m-3·decade-1) of all occurred emissions changes. On average, observed [PM2.5] showed elevated values at all sites when wind blew from directions of hot springs. The same was found for the sulfate, ammonium and non-metal components of PM2.5. Observations showed that these geothermal waters contain sulfate, ammonia, boric acid and non-metals. Hot springs of such composition are known to emit hydrogen sulfide and ammonia that can serve as precursors for ammonium and sulfate aerosols.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45694163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since 1991, air pollution has gained special attention in Taiwan after a petrochemical complex was constructed in Mailiao Township, Yunlin County. We explored the association between the magnitude of PM2.5 and meteorological factors during 2012-2016. Our findings revealed that 1) mean PM2.5 levels gradually decreased from 30.70 μg/m3 in 2013 to 25.36 μg/m3 in 2016; 2) wind speed is the main determinant of air quality—air quality significantly improved when it was faster than 4 m/sec; and 3) wind direction is another determinant of air quality—when the wind direction was southerly, air quality improved. Elevated PM2.5 levels were defined as those hourly levels higher than the third quartile (36 μg/m3). The significantly negative predictive factors for elevated PM2.5 levels were the summer or autumn seasons, rainfall, increased wind speed, and wind direction from 150° to 230° from the north. The significantly positive predictive factors for elevated PM2.5 levels were working hours from 6 a.m. to 2 p.m., a temperature between 11°C and 25°C, relative humidity between 40% and 68%, and wind direction (e.g., northerly wind, northeasterly wind, and easterly wind). The predictive formula is attached in the Appendix. Therefore, people should protect themselves on these high-risk days.
{"title":"Predictive Meteorological Factors for Elevated PM2.5 Levels at an Air Monitoring Station Near a Petrochemical Complex in Yunlin County, Taiwan","authors":"Yee-Hsin Kao, Chih-Wen Lin, J. Chiang","doi":"10.4236/OJAP.2019.81001","DOIUrl":"https://doi.org/10.4236/OJAP.2019.81001","url":null,"abstract":"Since 1991, air pollution has gained special attention in Taiwan after a petrochemical complex was constructed in Mailiao Township, Yunlin County. We explored the association between the magnitude of PM2.5 and meteorological factors during 2012-2016. Our findings revealed that 1) mean PM2.5 levels gradually decreased from 30.70 μg/m3 in 2013 to 25.36 μg/m3 in 2016; 2) wind speed is the main determinant of air quality—air quality significantly improved when it was faster than 4 m/sec; and 3) wind direction is another determinant of air quality—when the wind direction was southerly, air quality improved. Elevated PM2.5 levels were defined as those hourly levels higher than the third quartile (36 μg/m3). The significantly negative predictive factors for elevated PM2.5 levels were the summer or autumn seasons, rainfall, increased wind speed, and wind direction from 150° to 230° from the north. The significantly positive predictive factors for elevated PM2.5 levels were working hours from 6 a.m. to 2 p.m., a temperature between 11°C and 25°C, relative humidity between 40% and 68%, and wind direction (e.g., northerly wind, northeasterly wind, and easterly wind). The predictive formula is attached in the Appendix. Therefore, people should protect themselves on these high-risk days.","PeriodicalId":93802,"journal":{"name":"Open journal of air pollution","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48571005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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