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Notably, clear spatial differences occur in the distribution of air pollution among cities in the Beijing-Tianjin-Hebei (BTH) Region. Clarifying the concentration distribution of PM2.5 and O3 at different time scales is helpful to formulate scientific and effective pollution prevention and control measures. Here, the concentrations of PM2.5 and O3 were decomposed using a seasonal-trend decomposition procedure based on the loess (STL) method; their long-term, seasonal, and short-term components were obtained; and their temporal and spatial distribution characteristics were studied. The results showed that the decrease in PM2.5 concentration in the BTH Region from 2017 to 2021 was higher than that of O3. There was a positive correlation between PM2.5 and O3 concentrations in spring and summer and a negative correlation in autumn and winter. The short-term component and seasonal component had the greatest contribution to PM2.5 and O3 concentrations, respectively. There were two principal components in the seasonal and short-term components of PM2.5 and the long-term and short-term components of O3, corresponding to the central and southern part of Hebei Province and the northern part of the BTH Region. Sub-regional distribution of PM2.5 and O3 in the BTH Region at different time scales were found. Compared with that in the original series, the long-term component could better reflect the evolution trend of PM2.5 and O3 concentrations, and the standard deviation (SD) of the seasonal component and short-term component could be used to measure the fluctuation in PM2.5 and O3 concentrations in various cities. The SD of the seasonal and short-term components of the PM2.5 concentration in every city in front of Taihang Mountain was higher, and the SD of the short-term component of the O3 concentration in Tangshan was the highest.
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Inorganic aerosol is the main component of haze days in winter over Tianjin. In this study, two typical high concentrations of secondary inorganic aerosol (SIA) processes, defined as CASE1 and CASE2, were selected during polluted days in January 2020 over Tianjin, and the effects of meteorological factors, regional transport, and chemical processes were comprehensively investigated combined with observations and numerical models (WRF-NAQPMS). The average SIA concentrations in CASE1 and CASE2 were 76.8 µg·m-3 and 66.0 µg·m-3, respectively, and the nitrate concentration was higher than that of sulfate and ammonium, which were typical nitrate-dominated pollution processes. Meteorological conditions played a role in inorganic aerosol formation. The temperature of approximately -6-0â and 2-4â and the relative humidity of 50%-60% and 80%-100% would be suitable conditions for the high SIA concentration (>80 µg·m-3) in CASE1, whereas the temperature of approximately 2-4â and the relative humidity of 60%-70% would be suitable in CASE2. The average contribution rates of external sources to SIA in the CASE1 and CASE2 processes were 62.3% and 22.1%, which were regional transport-dominant processes and local emission-dominant processes, respectively. The contribution of the local emission of CASE1 to nitrate and sulfate was 16.2 µg·m-3 and 8.2 µg·m-3, respectively, higher than that of external sources (31.7 µg·m-3 and 8.8 µg·m-3). the local contribution of CASE2 to nitrate and sulfate was 29.3 µg·m-3 and 25.1 µg·m-3, respectively, whereas the contribution from external sources was 8.1 µg·m-3 and 9.4 µg·m-3, respectively. The quantitative result indicated that local formation and regional transport resulted in higher nitrate concentration than sulfate in CASE1, in contrast to only local sources in CASE2. The gas phase reaction was the main source of inorganic aerosol formation, contributing 48.9% and 57.8% in CASE1 and CASE2, respectively, whereas the heterogeneous reactions were also important processes, with contribution rates of 48.1% and 42.2% to SIA. The effect of aqueous phase reaction was negligible.
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The secondary component is an important factor causing PM2.5 pollution in the Beijing-Tianjin-Hebei urban agglomeration in winter. In this study, the CO tracer method was used to estimate the secondary PM2.5 concentration of the Beijing-Tianjin-Hebei urban agglomeration in the winter of 2017-2021. The temporal and spatial distribution characteristics were analyzed, and the influencing factors of regional secondary PM2.5 were discussed. The results showed that the decreasing trend of PM2.5 concentration in the Beijing-Tianjin-Hebei Region in the winter of 2017-2021 was obvious, and the cities with the largest decline were located in the central and southern part of Hebei Province, mainly contributed by primary PM2.5. There was a good correlation between secondary PM2.5 and PM2.5 in all cities of the Beijing-Tianjin-Hebei urban agglomeration, and the proportion of secondary PM2.5 in Beijing and Tianjin was significantly higher than that in other cities. With the aggravation of pollution degree, the mass concentration of primary PM2.5 and secondary PM2.5 increased in varying degrees, and the proportion of secondary PM2.5 increased significantly. Compared with the direct measurement results, the estimated value obtained by this method was lower as a whole. The selection of appropriate primary aerosol reference value was the key to improving this method and estimating the secondary PM2.5 concentration.
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As the problem of O3 pollution in the Beijing-Tianjin-Hebei region becomes increasingly prominent, it is of great significance to explore and analyze the ozone variation characteristics and causes of the pollution process in the Beijing-Tianjin-Hebei region for regional air pollution prevention and control. The observations in this study showed that high O3 concentration in spring and summer of the Beijing-Tianjin-Hebei region was higher in the south and lower in the north. The high O3 concentration in Beijing, Tianjin, and Shijiazhuang was often accompanied by the influence of southern wind. Based on WRF-Chem model simulation and process analysis technology, the variation characteristics and causes of O3 in The Beijing-Tianjin-Hebei region in 2019 were deeply analyzed. The diurnal variations in chemical processes, vertical mixing, and transportation in typical cities showed distinct seasonal variations. In summer afternoons, chemical processes were the main source of O3 concentration increase in each city. Vertical mixing resulted in an increase in O3 concentration in Tianjin and Shijiazhuang but a decrease in Beijing. Tianjin and Shijiazhuang had a net output, whereas Beijing had a net inflow. In the polluted O3 process, the chemical process dominated the afternoon O3 concentration increasing in Beijing and Shijiazhuang, whereas vertical mixing dominated in Tianjin. In addition, there was a net input of O3 in Beijing and Shijiazhuang and a net output of O3 in Tianjin. In the clean O3 process, vertical mixing dominated the increase in O3 concentration in Beijing and Shijiazhuang in the afternoon, whereas in Tianjin it was chemical processes. At the same time, the net output of O3 existed in all three cities.
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Contaminantes Atmosféricos , Contaminación del Aire , Ozono , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Beijing , China , Ciudades , Monitoreo del Ambiente , Ozono/análisis , Material Particulado/análisisRESUMEN
Based on real-time tracking data, PM2.5 mass concentration, and meteorological observations of the Tianjin Meteorological Bureau and the Ecological Environment Bureau, combined with the fine particle meteorological condition diffusion index constructed using the environmental model, the change and driving factors of the PM2.5 mass concentration in Tianjin from 2000 to 2020 were studied to analyze the impact of meteorology on the atmospheric environment. The study showed that change in PM2.5 mass concentration in Tianjin took place in three stages from 2000 to 2020; the first stage showed a continuous increase from 2000 to 2007. The rapid increase in emissions in this stage was the dominant factor, and its effect was four times that of the annual fluctuation in meteorological conditions. The second stage was from 2007 to 2013, in which the PM2.5 mass concentration fluctuated, with two peak years (2007 and 2013). The emissions were stable in this stage. The annual fluctuation of meteorological conditions had an important influence on the annual fluctuation in PM2.5 mass concentration. The third stage was from 2013 to 2020; the PM2.5 mass concentration decreased rapidly, and the decline in emissions was decisive, which reduced the PM2.5 mass concentration by 40% to 50%. The improvement in the meteorological diffusion conditions also provided a positive contribution, which reduced the PM2.5 mass concentration by approximately 10%. Based on the analysis of the data over the past 20 years, the annual variation in atmospheric diffusion conditions caused by the annual variation in meteorological conditions was periodic, with trough values from 2003 to 2004 and 2013 to 2015 and peaks from 2008 to 2010 and 2018 to 2020; the distance between peaks and valleys was approximately 11 years. It was estimated that the next atmospheric diffusion condition valley stage will occur circa 2025. The average intensity of the annual fluctuation in atmospheric diffusion conditions caused by the annual variation in meteorological conditions was 4%, which can explain 25%-50% of the annual variation in PM2.5 mass concentration over the past 20 years, with a difference between peaks and valleys of 16%. The periodic fluctuations in meteorological diffusion conditions have an important impact on the future PM2.5 target setting and corresponding measures design.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Monitoreo del Ambiente , Meteorología , Material Particulado/análisis , Estaciones del AñoRESUMEN
Air humidity is a key meteorological factor in regulating visibility changes and haze episodes. Based on multi-year historical data of PM2.5 mass concentration, visibility, relative humidity(RH), and specific humidity(q) during winter in Tianjin, the impact of air humidity on PM2.5 mass concentration and visibility was investigated. Between 2015 and 2020, the PM2.5 mass concentration showed an overall decline of 28.0%. The frequency of visibility above 10 km significantly increased between 2015 and 2018, indicating an improvement in visibility during this period. However, the visibility deteriorated again in the winter of 2019 and 2020, with a decreased frequency of visibility above 10 km. Specifically, the mean RH in January and February in 2020 of Tianjin reached 63% and 67%, respectively, which were higher than the historical 30-year average for the same period. The frequency of extremely low visibility(lower than 2 km) rebounded to a level equivalent to that during the winter of 2016. The enhanced air humidity visually obscured the reduction effect of PM2.5. For Tianjin, the external sources of water vapor are southwestern and eastern transport. Particularly, water vapor transported from eastern Bohai Bay(59%) is significantly greater than that from southwestern direction(25%). However, the eastern air mass is generally clean, hence, although the condensed water may increase the PM2.5 mass concentration in the humid air, the eastern air mass affects visibility to a greater extent. On the other hand, the haze episodes during winter frequently occurred when the southwestern wind dominated and specific humidity was greater than 2.0 g·kg-1, with a frequency of 83.6%. In a short period of time, the variation of specific humidity is less significant than RH, therefore, the relationship between specific humidity and PM2.5 mass concentration or air quality can be utilized to predict the occurrence of haze episodes and pollution during winter. When the average RH is higher than 80% or the mean specific humidity is greater than 3.0 g·kg-1, the frequency of PM2.5 mass concentration greater than 75 µg·m-3 is 78% and 80%, respectively. For the air quality forecast during winter, weather conditions with specific humidity greater than 3.0 g·kg-1 should be carefully monitored.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Monitoreo del Ambiente , Humedad , Material Particulado/análisis , Estaciones del AñoRESUMEN
Pollution occurs in the boundary layer, and the thermal and dynamic vertical structure of the boundary layer has a significant influence on the formation of heavy pollution episodes. Based on unmanned aerial vehicle (UAV) sounding, ground-based remote sensing and numerical modeling, this paper analyzes the vertical structure of the boundary layer and the causes of pollution during the heavy pollution episode in Tianjin from January 10 to 15, 2019, with a view to strengthening the understanding of the influence law of boundary layer processes on heavy pollution in northern coastal cities and improving the accuracy of weather forecasts and heavy pollution warnings. The results show that atmospheric temperature stratification had a significant influence on the formation, persistence, and dissipation of heavy pollution episodes. During an episode, accompanied by the development and dissipation of the inversion layer, a high PM2.5 concentration area developed to the upper atmosphere with a height of over 300 m in the daytime and compressed to the ground at night with a height about 100 m. When fog appeared and continued in the daytime, the vertical structure characteristics of the boundary layer changed. A temperature inversion above the fog restrained the diffusion of pollutants to the upper air and made the contribution of turbulence vertical mixing process decrease significantly in the daytime, leading to the persistence and development of heavy pollution near the surface. Regional pollution transport accounted for 66.6% during the episode, which was closely related to regional pollution transport. Regional pollution transport mainly appeared at the top of the boundary layer and above the fog inversion layer where high wind speeds occurred. Pollutants were transported to the ground by a sinking motion as the boundary layer and fog height changed. This is how regional pollution transport occurred when Tianjin was controlled by a weak high pressure field in the north. The vertical structure of the boundary layer also affected the improvement of air quality by cold air. The strong temperature inversion at the top of the fog resulted in the failure of the cold air to transmit to the ground through turbulent shear stress in the S3 stage. There was an obvious difference in wind speed between the upper and lower air. The influence of cold air on the ground was delayed, and the effect of it was weakened. Thus, the heavy pollution episode could not be alleviated completely.
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Regional transport is an important factor when considering the prevention and control of air pollution. The aim of this study was to provide support for the joint prevention and control of air pollution in the Beijing-Tianjin-Hebei region. With a focus on an analysis of the relationship between regional transport and meteorological conditions based on the weather background, an atmospheric chemical model was developed to quantitatively estimate the impact of regional transport on Tianjin from October 2016 to September 2017. The results showed that the contribution percentage of regional transport in cities in plains in the Beijing-Tianjin-Hebei region was significantly higher than in cities in mountains. The local contribution of PM2.5 in the Tianjin area was 62.9% and the contribution of regional transport was 37.1%. This was mainly affected by transmissions of Chanzhou, Langfang, central and southern Hebei, Beijing, Tanshan, and Shandong. Regional transport was the most significant from April to June, the weakest from July to August, and the highest contributor to local emissions. Regional transport was closely related to weather situation, wind field, precipitation, and other meteorological conditions. Post-high pressure and pre-frontal low pressure were the two types of pollution weather with the highest proportion in regional transport, and the impact of air pollution transport under the southwest wind, westerly wind and south wind was the most apparent. Wind speed of 2-3 m·s-1 was beneficial to the regional transport of PM2.5, and precipitation above 5 mm will effectively reduce the regional transport of air pollutants. For different pollution types and heavy pollution stages, the contribution of regional transport was the most apparent in light pollution weather, being 20.5% higher than the average. The heavy pollution weather was controlled by static stable air mass, and because of the migration of high PM2.5 concentrations, pollution air mass in the surrounding area had a significant impact on the accumulation of pollution and transport in the region. The contribution ratio of PM2.5 transport in the heavy pollution period was more than the average and was approximately 10% and 15% higher. In the process of heavy pollution, the proportion of transport contribution in the initial accumulation stage and peak stage were higher than in other periods, and 14.5% and 19.5% higher than in the outbreak stage. The contribution of local emissions in the outbreak stage was more significant, being 9.9% higher than average.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Beijing , China , Ciudades , Monitoreo del Ambiente , Material Particulado/análisis , Tiempo (Meteorología)RESUMEN
Volatile organic compounds (VOCs) play an important role in the formation of ozone. The concentrations of VOCs in the Jinnan District of Tianjin were monitored by the Syntech Spectras GC955 online monitoring system, and the ozone generation potential of VOCs was calculated by the maximum incremental activity factor. The results showed that the total concentration of VOCs in the Jinnan District was (32.33±23.77) µg·m-3, in which the mass concentration of alkane was the highest, and propylene, ethylene and toluene had the highest mass concentration. During the observation period, the ozone formation potential (OFP) of TVOC was 107.81 µg·m-3, and the contribution of alkenes to OFP was the largest, which was 55.80%. Ethylene, isoprene, and toluene accounted for the first three places of OFP contribution rate. The backward trajectory analysis showed that TVOC and its OFPs were different under different trajectories. The estimation of VOCs/NOx volume fraction ratio showed that O3 formation was sensitive to VOCs, which showed that atmospheric photochemical pollution has a considerable degree of regional characteristics. The concentration ratio of ethylbenzene/m,p-xylene, and ethane/acetylene can be used to measure the progress of atmospheric chemical reaction and photochemical age in the air mass, which was proved by the aging process of VOC.
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The volume concentration of peroxyacetyl nitrate (PAN) and O3 in the atmosphere were measured at the Tianjin Meteorological Tower in summer 2017 by using the online instrument with meteorological parameters and back trajectory analysis to analyze the delivery characteristics of PAN and O3. The average volume concentrations of PAN and O3 during the observational period are (0.73±0.56)×10-9 and (53±25)×10-9, respectively. The hourly maximum concentrations of PAN and O3 are 3.49×10-9 and 137×10-9. The volume concentrations of PAN and O3 show pronounced diurnal profiles, which are both characterized by much higher values at daytime than at nighttime. In addition, the correlation coefficient between PAN and O3 at daytime (R2=0.52) is notably higher than that at nighttime (R2=0.21). The air masses originating from the south show the highest volume concentration of PAN and O3, with the lowest volume concentration originating from the east. The wind rose plot and cluster analysis of the back trajectories show that the highest concentration of pollutants mainly originates in the southwest. The air massess originating from the east and circulating through the Bohai Sea and coastal areas of the Hebei and Liaoning provinces show the lowest volume concentrations of PAN and O3. The transportation within the boundary layer plays an important role in the concentration distribution of PAN and O3.
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Based on temperature and wind speed data from the 255 meter tall meteorological tower, the characteristics of atmospheric stability were analyzed in Tianjin, with the vertical diffusion index ß and φ constructed by atmospheric chemical models. This provided information to use the vertical dispersion analysis method to forecast pollution from weather data. The results show that the comprehensive use of atmospheric stability and the vertical diffusion index can provide a better pollution forecast. When the atmospheric stability was D from 07:00-08:00 and 18:00-20:00, compared to when atmospheric stability was C, the probability of heavy pollution weather increased by 10 times. If the vertical diffusion index ß and wind speed index were used to forecast heavy pollution, the accuracy rate was 67% higher than when using the single wind speed index. The coefficient between vertical diffusion index φ and PM2.5 mass concentration was 0.8.When the vertical diffusion index φ was less than 0.52, the probability of heavy pollution was 75%, identifying 59% of heavy pollution events.
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To clarify the rapid formation and evolutionary mechanisms of an extremely severe and persistent haze and fog (HF) episode that occurred in central-eastern China from Dec 20 to 25, 2015, a novel campaign was conducted and vertical profiles of wind, temperature, light extinction coefficient (LEC) and PM2.5 concentration were used to analyze the rapid formation and evolutionary mechanisms of this HF episode. The substantial downward transportation of regional pollution from high layers and stagnant weather conditions favorable for the local pollution accumulation were the two main causes of the rapid increase in pollutant concentration. Southwest wind speeds of 4m/s between 300 and 600m and obvious downward flows were observed, whereas the southwest wind speeds were low below 300m, and strong temperature inversion with intensity of 4.5°C/100m expanded vertically to a height of 600m. Two peaks of PM2.5 concentration were observed at 200 and 700m, corresponding to 235 and 215µg/m3, respectively. The frequent change in wind direction and wind speeds resulted in the fluctuation of PM2.5 concentration. The turbulence within lower layers of the troposphere was enhanced by easterly and northerly winds which decreased the pollution level; however, the strength and stretching height of the winds were insufficient to fully clear the air of pollutants. The PM2.5 concentration revealed 2-high concentration layers in the vertical direction. The maximum concentration layer was below 100m, while the second high-concentration layer was at 400m.
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To characterize the size distribution of water-soluble inorganic ions (WSâ ¡) during a heavy pollution episode, particle samples were collected by an Andersen cascade sampler in Tianjin in January 2014, and the concentrations of eight WSâ ¡ (Na+, NH4+, K+, Mg2+, Ca2+, Cl-, NO3-, and SO42-) during a typical haze episode were analyzed by ion chromatography. The sources and formation mechanisms of WSâ ¡ were analyzed based on their size distributions. The results showed that the daily average concentrations of PM2.5 and PM10 were (138±100) µg·m-3 and (227±142) µg·m-3, respectively, and the average concentration of total WSâ ¡ concentrations (TWSâ ¡) in the coarse and fine particles were (34.07+6.16) µg·m-3 and (104.16+51.76) µg·m-3, respectively. The concentrations of SO42-, NO3-, and NH4+ in the fine particles were much higher than concentrations of the other ions, and there were strong correlations between these three ions. The TWSâ ¡ on clear days, light pollution days, and heavy pollution days were (41.55±12.41) µg·m-3, (94.46±31.19) µg·m-3, and (147.55±27.76) µg·m-3, respectively. On clear days, SO42- showed a unimodal distribution, peaking at 0.43-0.65 µm; and NO3- showed a trimodal distribution, peaking at 0.43-0.65 µm, 2.1-3.3 µm, and 5.8-9.0 µm. NH4+ had a bimodal distribution, peaking at 0.43-0.65 µm and 4.7-5.8 µm. On heavy pollution days, however, the size distributions of these three secondary inorganic ions switched to a unimodal size distribution, peaking at 0.65-1.1 µm. Unimodal NH4+ mainly coexisted with SO42- and NO3-, and the excess NH4+ was found to be combined with Cl- in the fine particles. In the coarse particles, NH4+ completely coexisted with SO42- and NO3-.
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A novel photodecomposition behavior of hemin was described. With RhB-H2O2 system a flow injection chemiluminescence method has been applied to the study of the photolytic kinetics of hemin under ultraviolet light. And the sodium dodecyl sulfonate (SDS) was added as a photostability-stabilizer. The results showed that the decomposition reaction of hemin in the presence and absence of SDS corresponded to a first-order reaction. Furthermore, the presence of SDS in the system decreased the photolytic rate of hemin by 1.8 times compared to that in the absence of SDS.
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To investigate the size distributions of chemical compositions and sources of particulate matter (PM) at ground level and from the urban canopy, a study was conducted on a 255 m meteorological tower in Tianjin from December 2013 to January 2014. Thirteen sets of 8 size-segregated particles were collected with cascade impactor at 10 m and 220 m. Twelve components of particles, including water-soluble inorganic ions and carbonaceous species, were analyzed and used to apportion the sources of PM with positive matrix factorization. Our results indicated that the concentrations, size distributions of chemical compositions and sources of PM at the urban canopy were affected by regional transport due to a stable layer approximately 200 m and higher wind speed at 220 m. The concentrations of PM, Cl- and elemental carbon (EC) in fine particles at 10 m were higher than that at 220 m, while the reverse was true for NO3- and SO42-. The concentrations of Na+, Ca2+, Mg2+, Cl- and EC in coarse particles at 10 m were higher than that at 220 m. The size distributions of major primary species, such as Cl-, Na+, Ca2+, Mg2+ and EC, were similar at two different heights, indicating that there were common and dominant sources. The peaks of SO42-, NH4+, NO3- and organic carbon (OC), which were partly secondary generated species, shifted slightly to the smaller particles at 220 m, indicating that there was a different formation mechanism. Industrial pollution and coal combustion, re-suspended dust and marine salt, traffic emissions and transport, and secondary inorganic aerosols were the major sources of PM at both heights. With the increase in vertical height, the influence of traffic emissions, re-suspended dust and biomass burning on PM weakened, but the characteristics of regional transport from Hebei Province and Beijing gradually become obvious.
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Aerosoles/análisis , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/química , Atmósfera/análisis , Atmósfera/química , Tamaño de la Partícula , Material Particulado/análisis , China , Ciudades , Monitoreo del Ambiente , Industrias , Estaciones del AñoRESUMEN
In this study, PM2.5 samples were collected at four heights (10m, 40m, 120m and 220m) at a meteorological tower in the daytime and nighttime during the heating season in Tianjin, China. The vertical variation and diurnal variability of the concentrations of PM2.5 and main chemical compositions were analyzed in clear days and heavy pollution days. Generally, mass concentrations of PM2.5 and the chemical compositions showed a decreasing trend with increasing height, while mass percentages of SO4(2-), NO3(-) and OC showed an increasing trend with increasing height. Concentrations of ion species and carbon compound in PM2.5 samples in the daytime were higher than those collected at night, which was due to intense human activities and suitable meteorological condition in the daytime. The ratios of NO3(-)/SO4(2-) and OC/EC were also considered, and we have observed that their levels on heavy pollution days were higher than those on clear days. In addition, source apportionments were identified quantitatively using the CMB-iteration model. The results indicated that contributions of secondary ion species increased with increasing height, while contributions of other pollutant sources decreased, and contributions of vehicle exhaust were relatively high on clear days.
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Contaminantes Atmosféricos/análisis , Contaminación del Aire/estadística & datos numéricos , Calefacción/métodos , Material Particulado/análisis , China , Monitoreo del Ambiente/métodos , Calefacción/estadística & datos numéricos , Estaciones del AñoRESUMEN
A novel chemiluminescence method for the determination of Levofloxacin is based on its enhancement effect on thereaction of luminol with H2O2. The calibration graph is linear over the range of 5.53 x 10(-11)-2.21 x 10(-8) mol x L(-1) and the detection limit is 1.38 x 10(-11) mol x L(-1). The relative standard deviation (RSD) is 2.56% (n = 9). The method has been successfully applied to the determination of Levofloxacin in capsule samples.
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Levofloxacino , Luminiscencia , Mediciones Luminiscentes/métodos , Luminol/química , Ofloxacino/análisis , Preparaciones Farmacéuticas/análisis , Calibración , Análisis de Inyección de Flujo , Peróxido de Hidrógeno/química , Límite de DetecciónRESUMEN
To investigate the vertical characteristics of ions in PM10 as well as the contributions and possible locations of their sources, eight water-soluble ions were measured at four heights simultaneously along a meteorological tower in Tianjin, China. The total ion concentrations showed a general decreasing trend with increasing height, ranging from 64.94µgm(-3) at 10m to 44.56µgm(-3) at 220m. NH4(+), SO4(2-) and NO3(-) showed higher height-to-height correlations. In addition, relationships between ions are discussed using Pearson correlation coefficients and hierarchical clustering analysis (HCA), which implied that, for each height, the correlations among NH4(+), SO4(2-) and NO3(-) were higher. Finally, sources were identified qualitatively by the ratio of certain ions and quantitatively by principal component analysis/multiple linear regression (PCA/MLR) and positive matrix factorisation (PMF). Secondary sources played a dominant role for PM10 and water-soluble ions at four heights and became more important at greater heights (the percentage contributions were 43.04-66.41% for four heights by PCA/MLR and 46.93-67.62% by PMF). Then, the redistributed concentration field (RCF) combined with PCA/MLR and PMF was applied, which indicated the high potential source regions. The vertical characteristics of the levels, relationships, source contributions and locations would support the effective management of the water-soluble ions in particulate matter.