Maximum Concentrations Of PM2 Research Articles

Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia.

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM2.5 and PM10 were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM10 (50 μg/m3) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area.

Spatial prediction of PM[formula omitted] concentration using hyper-parameter optimization XGBoost model in China

High-fine particulate matter (PM2.5) pollution has become the main object of damaging the atmospheric environment and endangering human health. Accurate prediction of the spatial variability of PM2.5 concentrations using high-performance models is crucial for the prevention and control of atmospheric pollution. In this paper, in order to avoid the uncertainty caused by artificially setting the parameters of the prediction model, a new hyper-parameter optimization extreme gradient boosting (HPO-XGBoost) model for spatial prediction of PM2.5 concentration was proposed. We used aerosol optical depth (AOD) data of Himawari-8 satellite combined with the HPO-XGBoost model to predict and mapping the spatial variability of PM2.5 concentrations during the COVID-19 lockdown in China. The results showed that the maximum concentration of PM2.5 exhibited a downward trend and a significant seasonal fluctuation from 2015 to 2020. Compared with grid search (GS) and random grid search (RGS) optimization algorithms, the tree-structured Parzen estimator-XGBoost (TPE-XGBoost) approach has the highest prediction accuracy (R2) of 89.37% (January), 85.58% (February), 80.02% (March), and 83.68% (April) for PM2.5 concentrations in 2020, respectively. Spatial mapping of the monthly average PM2.5 concentration from January to April using the TPE-XGBoost model showed that the regions with higher PM2.5 concentrations are concentrated in northern China, eastern China and northeastern China, where PM2.5 concentrations exceed 150 μg m−3 in January. Furthermore, the spatial correlation analysis showed that factors with the highest driving effect of PM2.5 concentrations during the COVID-19 lockdown were factory (FAC) and traffic (TRA), and the strongest contribution of the double-factor synergy (q > 0.8) for all four months included factory-residence (FAC-RES) and factory-population (FAC-POP). The contribution source of PM2.5 transport showed a long-distance channel in Taiyuan, Xi’an and Shijiazhuang, while the cluster-like distribution and mixed distribution of contribution sources were embodied in Zhengzhou, Changchun and Harbin based on concentration-weighted trajectory (CWT) analysis. The above results showed that the TPE-XGBoost has strong nonlinear explanation and effective feasibility for spatial prediction of PM2.5 concentrations, and the transport of PM2.5 was dynamic effect which should be considered into account when developing prevention and control measures of atmospheric pollution in epidemic period.

ქ. რუსთავის და მიმდებარე ტერიტორიის ატმოსფეროში PM2.5-ის გავრცელების გამოკვლევა

The distribution of PM2.5 in the atmosphere of the city of Rustavi and its environs was studied under eastern background light air, gentle and fresh breeze. It has been established that the maximum concentrations of PM2.5 in the atmosphere of Rustavi are almost always higher than the corresponding maximum allowable concentrations. The trend of hourly changes in concentrations showed that during the day the concentration of microparticles reaches its maximum in the various period of the day. Numerical modeling of the local distribution of microparticles carried out in the city of Rustavi during background easterly light air, gentle and fresh breeze showed us that the change in the daily regime of relief and temperature with eastern light air in Rustavi for 12 hours leads to a complex and significant change in the wind speed directed to land. It forms on the territory of Kvemo Kartli the opposite current of the background wind, which corresponds to the horizontal circular wind circulation. The value of circulation gradually decreases with increasing height and in the boundary layer of the atmosphere (600 m above the earth's surface) has the form of a wave disturbance. the picture obtained with an average background east wind is qualitatively similar to the field obtained with a background light air, and with a fresh breeze, in contrast to the case of a light air and gentle breeze, the pollution zone covers most of the simulation zone.

Detection of warning signal of particulate emission on the basis of fixed threshold in real-time using a lidar system

Monitoring pollutant emissions in an urban area is of primary importance in order to guarantee high levels of human health (by reducing the impact of respiratory diseases on urban inhabitants) and good preservation of objects (such as historical sites or buildings). The European Environment Agency (EEA) has established that the maximum concentration of PM2.5 concentration for long-term exposure is 10 μg/m3. By measuring the light that has been backscattered by atmospheric particulates, the lidar technique seems to be a valid method to provide a warning signal when a particulate concentration threshold is exceeded. In addition, the lidar system can also provide information about the distance at which the particulate threshold is exceeded. In this research measurements of traffic-originated particulate in the area near the University of Rome “Tor Vergata” is analysed at different times on a weekday to obtain continuous monitoring of its backscattering coefficient, values of particulate concentration and details about time and distance from the lidar system at which a warning signal is provided. The University of Rome “Tor Vergata” is in an area where traffic is very heavy, so high pollutant concentration values are to be expected.

The effect of fine suspended particles in the atmospheric air on the formation and course of the T2 endotype of bronchial asthma: a case-control study

The aim of the study was to investigate the effect of fine suspended particles in the atmospheric air on the formation and course of allergic and non-allergic phenotypes of the T2 endotype of bronchial asthma (BA) using the case-control study. Materials and methods. BA patients were selected in the course of seeking medical help. The groups were formed on the base of matching criteria (gender, age, body mass index, level of education), supplemented by the collection of information about potential cofounders. Based on the data on monitoring the content of fine suspended particles in the atmospheric air of Kazan, the average annual and maximum concentrations of PM2.5 and PM10 fractions were determined in the residential areas. The group of “cases” included forty patients with an allergic phenotype and 42 patients with an eosinophilic non-allergic phenotype of bronchial asthma, the control group included forty eight people. Additionally, sampling of atmospheric air was carried out using an 8-stage impactor to assess the content of bacterial endotoxin, and elemental composition. Results. Higher levels of pollution with fine suspended particles were demonstrated in the areas of residence of BA patients, comparing to the control group. An increase in the average annual concentration of the PM2.5 by 10 µg/m3 increases the odds of the eosinophilic non-allergic BA phenotype in adults by 4.76 times. The odds of the allergic phenotype of bronchial asthma increases in the presence of bacterial endotoxin - 1.32 times per 0.01 EU/m3 of endotoxin in the 3.2-18 µm size fraction. A more severe course of the eosinophilic non-allergic BA phenotype was noted at higher average annual concentrations of the PM2.5. The control of allergic asthma depends on the bacterial contamination of the aerosol. Limitations of the study are related to the use of geospatial approach to assess personalized average annual and maximum annual concentrations. Conclusion. The role of fine suspended particles in the atmospheric air in the development of bronchial asthma in adults has been shown. Various mechanisms were established to be involved in the formation of the clinical picture of the eosinophilic non-allergic and allergic phenotypes of bronchial asthma.

Impact Assessment of Aerosol Optical Depth on Rainfall in Indian Rural Areas

Aerosol significantly influences the life cycle of clouds and their formation. Many studies reported worldwide on anthropogenic aerosols and their impact on clouds and their optical properties. Atmospheric remote sensing provides the best way to estimate indirectly air quality surveillance and management in megacities of developing countries like India where many cities have elevated concentration profiles of air pollutants with inadequate coverage of spatial and temporal monitoring. The results of the study highlighted the impact on rainfall patterns due to aerosol optical depth (AOD) and fine particulate matter (PM2.5) for a total of 7 years (2015–2021) over five different Indian rural sites by using MODerate Resolution Imaging Spectroradiometer (MODIS). The AOD (550 nm) and PM2.5 were retrieved from the MODIS sensor Terra satellites and the MEERA 2 model, respectively. Also, we have analyzed in this study the relationship of AOD (550 nm) with PM2.5 and meteorological variables (temperature relative humidity and precipitation) over Indian rural sites during 2015–2021. The maximum concentration of AOD (550 nm) has been measured for Gandhi college (2.94 ± 0.44) and minimum for ARM college (0.01 ± 0.28), while the maximum concentration of PM2.5 has been measured for ARM College 296.37 (µg m−3) and minimum for Karunya University 0.02 (µg m−3). Also, the relation between AOD (550 nm) with total precipitation is measured positively for all locations except Gandhi college whereby PM2.5 associated with total precipitation is measured negatively for all locations except ARM college. Finally, the relationship between PM2.5 and AOD (550 nm) is measured positively in all selected locations except Singhad Institute. The maximum rainfall has been observed for monsoon months (June–August) and post-monsoon months (October) for all locations during the study period. The maximum total precipitation has been measured for Singhad 11,674.7 (mm) and the minimum for Karunya University 4563.41 (mm). However, the results of the study indicated that there was no direct trend observed in AOD in five different selected rural Indian sites.

Atmospheric particulate fractions from Nigerian crude oil spillage

Laboratory simulations of the spill behaviors of three different Nigerian crude oil samples over three media (fresh water, sea water and soil) were carried out with a view to determining the effect of crude oil spillage on emission of fine (PM2.5) and inhalable particulates fractions (PM10). The spillage experiments were carried out in an environmental test box fitted with equipment to regulate the micro climatic conditions (temperature and Relative humidity). The maximum concentrations of PM2.5 were 711, 689 and 680 µgm−3 while those of PM10 were 972, 946 and 940 µgm−3 for sample A, B and C respectively. These peak concentrations were obtained for spill conditions corresponding to fresh water at 45 °C and 49% relative humidity. The least concentrations of PM2.5 and PM10 emitted across all samples were 63 µgm−3 and 256 µgm−3 respectively and these corresponded to spillage over sea water at 15 °C and 80% relative humidity. These concentrations clearly exceeded the short time averaging period (24 h) standards set for PM2.5 and PM10 by the United States Environmental Protection Agency. Incessant crude oil spillages in the Nigerian oil fields are therefore predicted to cause degradation of air quality within a short duration from the spill.

Effect of PM2.5 pollution on perinatal mortality in China

Using ArcGIS to analyze satellite derived PM2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM2.5 and perinatal mortality rates. The results indicate that PM2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM2.5 increase 1% is associated with a 2.49% increase in a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. The potential mechanism is that air pollution has an impact on infant weight to impact perinatal mortality rates.

Impacts of Atmospheric Boundary Layer Vertical Structure on Haze Pollution Observed by Tethered Balloon and Lidar

In this paper, the characteristics of the atmospheric boundary layer (ABL) vertical structure over the North China Plain (NCP) during a comprehensive observation experiment conducted during 15–21 December 2018 were investigated. Observational data were obtained with a large tethered balloon, Doppler wind lidar, and ground-level instruments. The maximum concentration of PM2.5 exceeded 200 µg m−3, and the ratio of PM2.5/PM10 was approximately 0.4 (its maxi-mum was approximately 0.8) during the whole observation period, indicating the explosive growth of dominant fine-mode aerosols in the winter heating season. Elevated concentrations of pollutants decreased the solar irradiance received by the ground, resulting in lower temperature at ground level. Our results illustrate three distinct types of vertical profiles: Type 1 (convective state)—the concentration of PM2.5 decreased nearly linearly with increase of the height below approximately 600 m; Type 2 (stable state)—the PM2.5 concentration sharply decreased from the ground to approximately 200 m; and Type 3 (multilayer structure)—some pollutants were suspended aloft in the upper air layer. Diurnal evolution of the vertical profiles of PM2.5 and their relationship with the changes in meteorological factors were identified. From daytime to nighttime, the vertical profiles evolved from Type 1 to Type 2 or Type 3. All the 33 vertical PM2.5 profiles that we obtained showed a strong relationship with elements of the ABL structure, such as the distributions of winds, the inversion layer, and turbulence activities. A light-wind layer and weak turbulence activity, especially within the inversion layer, contributed greatly to the accumulation of pollutants. Vertical PM2.5 concentration patterns were also greatly affected by local ground-level emission sources and regional transport processes.

Seasonal characteristics of aerosols (PM2.5 and PM10) and their source apportionment using PMF: A four year study over Delhi, India

The present study attempts to explore and compare the seasonal variability in chemical composition and contributions of different sources of fine and coarse fractions of aerosols (PM2.5 and PM10) in Delhi, India from January 2013 to December 2016. The annual average concentrations of PM2.5 and PM10 were 131 ± 79 μg m−3 (range: 17–417 μg m−3) and 238 ± 106 μg m−3 (range: 34–537 μg m−3), respectively. PM2.5 and PM10 samples were chemically characterized to assess their chemical components [i.e. organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSICs) and heavy and trace elements] and then used for estimation of enrichment factors (EFs) and applied positive matrix factorization (PMF5) model to evaluate their prominent sources on seasonal basis in Delhi. PMF identified eight major sources i.e. Secondary nitrate (SN), secondary sulphate (SS), vehicular emissions (VE), biomass burning (BB), soil dust (SD), fossil fuel combustion (FFC), sodium and magnesium salts (SMS) and industrial emissions (IE). Total carbon contributes ∼28% to the total PM2.5 concentration and 24% to the total PM10 concentration and followed the similar seasonality pattern. SN and SS followed opposite seasonal pattern, where SN was higher during colder seasons while SS was greater during warm seasons. The seasonal differences in VE contributions were not very striking as it prevails evidently most of year. Emissions from BB is one of the major sources in Delhi with larger contribution during winter and post monsoon seasons due to stable meteorological conditions and aggrandized biomass burning (agriculture residue burning in and around the regions; mainly Punjab and Haryana) and domestic heating during the season. Conditional Bivariate Probability Function (CBPF) plots revealed that the maximum concentrations of PM2.5 and PM10 were carried by north westerly winds (north-western Indo Gangetic Plains of India).

Impact of Open Burning Refuse on Air Quality: In the Case of "Hidar Sitaten" at Addis Ababa, Ethiopia.

Open burning of refuse is one of the key sources that causes high air pollution in Metropolitan cities. This paper identifies pollutant concentration of particulate matter (PM2.5) emission and air quality index categories with the peak hour interval on Hidar Sitaten day, and present analysis of air quality in Addis Ababa from August 2016 to November 2019. Daily records, with a 1-hour interval, of raw concentration of air pollutant and air quality index data, were obtained from the AirNow website of Addis Ababa central monitoring station. The data collected were analyzed using descriptive statistics of the mean air quality index and concentration of PM2.5. Accordingly, the study revealed that the peak hour for high pollutant concentration emission ranges between 8 pm to 11 pm hours, and the mean air quality index was more than a moderate level. Particularly, on Hidar Sitaten in 2019 at 9 pm the maximum concentration of PM2.5 was 8.6 times higher than WHO air quality guideline standard of daily allowance. The highest mean of air quality index and concentration of PM2.5 recorded was 112 and 44.2 µg/m3 on 21 November 2017, respectively, and it was found to be unhealthy for sensitive groups. This implies that the concentration of PM2.5 was harmful to people who are unusually sensitive to particulate pollution and have health problems. Therefore, public participation and strong regulations are needed on air quality management to strike a balance between a cultural practice of Hidar Sitaten and healthy air quality.

Study on Ambient Particulate Matter (PM2.5) with Different Mode of Transportation in Dhaka City, Bangladesh

Air pollution is considered a threat to the environment in developing countries. This study aims to quantify the concentration of PM2.5 in relation to the mode of transportation in the different areas of Dhaka city. For this, the concentration of PM2.5 was measured in ambient air with Ecotech Mini 2.5 Sampler and traffic volume survey was conducted in 12 sites across the city on August 2017. The study found that PM2.5 concentrations in mixed and motorized areas were on average higher than non-motorized and vehicle-free area. The maximum concentration of PM2.5 was found in Mirpur-10 (172.2 µg/m3) while minimum concentration was in B.C. das street (40 µg/m3). This study concluded that increasing the number of vehicles is one of the major sources of pollution of air in Dhaka city. Hence, well-developed public transportation service instead of the private car may contribute to reducing the air pollution in Dhaka city.

A severe fog-haze episode in Beijing-Tianjin-Hebei region: Characteristics, sources and impacts of boundary layer structure

Beijing–Tianjin–Hebei (BTH) region is recognized as one of the most polluted regions in China. In this study, characteristics, synoptic condition, boundary layer structure, and sources of a severe fog–haze episode during the December of 2016 and January of 2017 are investigated. The results show that BTH region is controlled by the uniform pressure field and southwest wind, and the average mass concentrations of PM2.5 in Beijing (BJ), Tianjin (TJ), and Shijiazhuang (SJZ) are 263.5, 192.7, and 296.1 μg/m3, respectively. Besides, the maximum hourly concentration and growth rate of PM2.5 are 578.8 μg/m3 and 13.1 μg/(m3·h), respectively for BJ. According to the wind profiler radar and L–band radar data, the maximum concentration of PM2.5 in two stages basically coincides with the minimum ventilation index (VI) value, and the minimum VI value in stage I and stage II are 5124 m2/s and 4524 m2/s. Moreover, the two stages are accompanied by significant inversion layer in the low levels. Although the maximum temperature inversion (10.8 °C) in stage I is higher that in stage II (8.3 °C) in the boundary layer, the maximum inversion strength in stage II (0.33 °C/hPa) is stronger than that in stage I (0.20 °C/hPa). Besides, weighted potential source contribution function (WPSCF) and conditional probability function analysis(CPF) are applied to investigate the potential source regions of PM2.5, the results show that southern BJ, as well as central and southern Hebei province (HB) are the main potential sources, and CPF values from the wind direction (180°–270°) are all over 0.3.

Mortality and morbidity due to exposure to ambient particulate matter

The aim of this study was to investigate spatial variation and health risk of the exposure to PM2.5 (particulate matter with a diameter of 2.5 µm or less) and PM10 (particulate matter with a diameter of 10 µm or less) in Sabzevar, Iran. PM2.5 and PM10 were measured during three campaigns from April to November 2017, in 26 sampling points. Spatial analysis was performed using kriging and autocorrelations (Moran's index) model in Arc GIS software. Relationship between exposure to the PM2.5 and PM10 and their health impacts were investigated by AirQ 2.2.3 software. The mean concentrations (and standard deviation) of PM 2.5 and PM10 over the entire study period were 32.54 (37.28) and 42.61 (47.76) μg/m3, respectively, which were higher than the guideline of World Health Organization. According to the spatial analysis, the maximum concentrations of PM2.5 and PM10 were around the main highway (beltway) which placed all over the south of Sabzevar. According to the Moran's index, the emission patterns for PM2.5 (Z-score = 2.53; P-value = 0.011) and PM10 (Z-score = 2.82; P-value = 0.004) were clustered. The attributable percentage (AP) of total mortality related to PM2.5 and PM10 were 3.544% (95% confidence interval (CI): 2.623–4.447%) and 2.055% (95% CI: 1.379–2.721%) per increasing each 10 μg/m3 of these pollutants, respectively. According to observed results, it is suggested that the beltway and other pollution sources, such as industries, should be placed at a greater distance from the city, to reduce PM amounts in residential areas.

Analysis of Atmospheric Particulate Matter Pollution Characteristics by LIDAR in Beijing During Spring Festival, 2016

Real-time aerosol extinction retrieved by Micro-pulse LIDAR and concentrations of PM2.5 and PM10 in Beijing were analyzed to investigate the air quality during the Spring Festival. The results showed that fireworks on the New Year's Eve resulted in a sharp increase in particulate matter concentrations in a short time. The maximum concentration of PM2.5 at Guanyuan station was 639.3 μg·m-3, which increased by nearly 30 times in 9 h. The maximum hourly concentration of particulate matter at Dingling and Liulihe suburban stations were significantly higher than that in Guanyuan station, the maximum values were more than 1000 μg·m-3. The particulate matter levels were continuously high on February 10-12 and the concentration of particulate matter at Dingling and Liulihe suburban stations were higher than that at Guanyuan. LIDAR results showed no obvious changes in the extinction coefficient at Dingling on the New Year's Eve. The extinction coefficient at Liulihe was greater than 1 km-1, but the particulate matter pollution was concentrated at altitudes less than 400 m. The extinction coefficient at Chegongzhuang was still higher than 0.4 km-1 at 500 m; however, the duration of pollution was shorter than that of Liulihe. The extinction coefficients at 105 m at all three stations during the New Year's Eve were significantly higher than those at 405 m. There were significant differences in the vertical extinction characteristics of the three sites. The background maximum values of Dingling, Chegongzhuang, and Liulihe were 0.09 km-1, 0.20 km-1, and 0.19 km-1 under 1.0 km, respectively. The maximum extinction coefficients at 00:00 (midnight) were 0.23 km-1, 1.36 km-1, and 1.19 km-1, which were 2.6 times, 6.8 times, and 6.0 times higher than the background value at the same time, respectively. In summary, discharge of fireworks led to a dramatic increase in the extinction coefficient of particulate matter. Temperature inversion and lower wind speeds were the main meteorological factors that contributed to this pollution event.

Identification and quantification of shipping emissions in Bohai Rim, China

Rapid development of port and shipbuilding industry in China has badly affected the ambient air quality of coastal zone due to shipping emissions. A total of 60 ambient air samples were collected from background site of Tuoji Island in Bohai Sea strait. The air samples were analyzed for PM2.5, organic carbon (OC), element carbon (EC), inorganic elements, and water-soluble ions. The maximum concentration of PM2.5 was observed during spring (73.6μg·m−3) compared to winter (39.0μg·m−3) with mean of 54.6μg·m−3. Back trajectory air mass analysis together with temporal distribution of vanadium (V) showed that V could be the typical tracer of shipping emissions at Tuoji Island. Furthermore, the ratios of vanadium to nickel (V/Ni), vanadium to lead (V/Pb) and vanadium to zinc (V/Zn) also suggest shipping emissions at Tuoji Island. The annual average primary PM2.5 estimate of shipping emissions was 0.65μg·m−3 at Tuoji Island, accounting for 2.94% of the total primary PM2.5, with a maximum of 3.16% in summer and a minimum of 2.39% in autumn.

A Modeling Study of a Typical Winter PM2.5 Pollution Episode in a City in Eastern China

A PM2.5 pollution episode over Hangzhou, China during 8 to 16 December 2011 was simulated using the Models-3 Community Multiscale Air Quality (CMAQ). Relative contributions from local and regional emission sources to the pollution event were also investigated through numerical sensitivity tests. Comparisons between simulations and measurements at six meteorological sites over the Yangtze River Delta Region (YRDR) and four air monitoring stations at Hangzhou were satisfactory. The temporal mean of the PM2.5 mass concentration in Hangzhou was lower than those at most areas of Jiangsu province and Shanghai during the episode. Process analysis of the four air monitoring stations at Hangzhou shows that emissions and aerosol processes contributed to the primary and secondary PM2.5 concentrations, with the mean accumulated rates of 1.2–25.5 µg/m 3 /hr and 0.5–1.2 µg/m 3 /hr, respectively. The process of advection also increased the PM2.5 mass concentration (1.2–3.4 µg/m 3 /hr). Diffusion was the dominant removal process at most air monitoring stations, with the removal rates of 4.1–20.7 µg/m 3 /hr. The dry (–3.0 to –3.6 µg/m 3 /hr) and wet deposition and heterogeneous processes (–0.4 to –1.8 µg/m 3 /hr) contributed to the loss of PM2.5. Process analysis also indicates that the maximum concentrations of PM2.5 that occurred during 13–14 December were mainly due to ineffective removal through diffusion. Results of the sensitivity tests suggest that non-Hangzhou pollutants made significant contributions to the PM2.5 pollution in Hangzhou, reaching up to 70% during the focal episode. Under certain meteorological conditions, pollutants transported from outside of Hangzhou not only increased the PM2.5 concentration, but also extended the pollution episode period in Hangzhou by one day. Nevertheless Hangzhou’s local emissions were not negligible, because they had important impacts on PM2.5 peak values.

Fine and Coarse Particulate Matter Chemical Characterization in a Heavily Industrialized City in Central Mexico during Winter 2003

This paper presents the results of the first reported study on fine particulate matter (PM) chemical composition at Salamanca, a highly industrialized urban area of Central Mexico. Samples were collected at six sites within the urban area during February and March 2003. Several trace elements, organic carbon (OC), elemental carbon (EC), and six ions were analyzed to characterize aerosols. Average concentrations of PM with aerodynamic diameter of less than 10 μm (PM10) and fine PM with aerodynamic diameter of less than 2.5 μm (PM2.5) ranged from 32.2 to 76.6 μg m-3 and 11.1 to 23.7 μg m-3, respectively. OC (34%), SO4 = (25.1%), EC (12.9%), and geological material (12.5%) were the major components of PM2.5. For PM10, geological material (57.9%), OC (17.3%), and SO4 = (9.7%) were the major components. Coarse fraction (PM10 –PM2.5), geological material (81.7%), and OC (8.6%) were the dominant species, which amounted to 90.4%. Correlation analysis showed that sulfate in PM2.5 was present as ammonium sulfate. Sulfate showed a significant spatial variation with higher concentrations to the north resulting from predominantly southwesterly winds above the surface layer and by major SO2 sources that include a power plant and refinery. At the urban site of Cruz Roja it was observed that PM2.5 mass concentrations were similar to the submicron fraction concentrations. Furthermore, the correlation between EC in PM2.5 and EC measured from an aethalometer was r2 = 0.710. Temporal variations of SO2 and nitrogen oxide were observed during a day when the maximum concentration of PM2.5 was measured, which was associated with emissions from the nearby refinery and power plant. From cascade impactor measurements, the three measured modes of airborne particles corresponded with diameters of 0.32, 1.8, and 5.6 μm.