The morphological structure of leaves and the dust-retaining capability of afforested plants in urban Guangzhou, South China

Purpose

Air pollution is a serious health problem throughout the world, exacerbating a wide range of respiratory and vascular illnesses in urban areas. The mass artificial plantation is very helpful to absorb dust and reduce pollution for conservation of the urban environment. The foliar surface of plants is an important receptor of atmospheric pollutants. Therefore, selection of suitable plant species for urban environment is very important.

Methods

The dust-retaining capability of urban trees in Guangzhou was determined at four different types of urban area, and the morphological traits of their leaves such as wax, cuticle, stomata, and trichomes were observed under a scanning electron microscope.

Results

It was determined that the dust-retaining capability of any given tree species is significantly different in the same place. Of the four studied tree species in the industrial area (IA) and commercial/traffic areas (CTA) type urban areas, the highest amounts of dust removed by Mangifera indica Linn was 12.723 and 1.482?g/m², respectively. However, in contrast, the equivalent maxima for Bauhinia blakeana is only 2.682?g/m² and 0.720?g/m², respectively. Different plant species have different leaf morphology. The leaf of M. indica has deep grooves and high stomata density which are in favor of dust-retained, and thus, their dust-retained capability is stronger, while B. blakeana has the cells and epicuticular wax with its stomata arranging regularly, resulting in poor dust catching capability. Leaf size was also shown to be related to dust capture for the four studied tree species.

Conclusions

The dust removal capacity of individual tree species should be taken into account in the management of greening plantation in and around an urban area. It was also shown that temporal variation in dust accumulation occurred over the 28-day observation period and this was discussed. Furthermore, spatial contrasts in dust accumulation were evidenced by the data. This reflected the differing pollution loadings of the four urban-type areas. The highest amount of dust accumulation was associated with the industrial area in which shipyard and steelworks occurred whilst the lowest dust accumulation was associated with the grounds of the University which was the control area.     

A review on recent progress in observations,sources, classification and regulations of PM<Subscript>2.5</Subscript> in Asian environments

Natural and human activities generate a significant amount of PM_2.5 (particles ≤2.5 μm in aerodynamic diameter) into the surrounding atmospheric environments. Because of their small size, they can remain suspended for a relatively longer time in the air than coarse particles and thus can travel long distances in the atmosphere. PM_2.5 is one of the key indicators of pollution and known to cause numerous types of respiratory and lung-related diseases. Due to poor implementation of regulations and a time lag in introducing the vehicle technology, levels of PM_2.5 in most Asian cities are much worse than those in European environments. Dedicated reviews on understanding the characteristics of PM_2.5 in Asian urban environments are currently missing but much needed. In order to fill the existing gaps in the literature, the aim of this review article is to describe dominating sources and their classification, followed by current status and health impact of PM_2.5, in Asian countries. Further objectives include a critical synthesis of the topics such as secondary and tertiary aerosol formation, chemical composition, monitoring and modelling methods, source apportionment, emissions and exposure impacts. The review concludes with the synthesis of regulatory guidelines and future perspectives for PM_2.5 in Asian countries. A critical synthesis of literature suggests a lack of exposure and monitoring studies to inform personal exposure in the household and rural areas of Asian environments.     

Evaluation and application of biomagnetic monitoring of traffic-derived particulate pollution

Inhalation of particulate pollutants below 10 μm in size (PM₁₀) is associated with adverse health effects. Here we use magnetic remanence measurements of roadside tree leaves to examine levels of vehicle-derived PM around Lancaster, UK. Leaf saturation remanence (SIRM) values exhibit strong correlation with both the SIRM and particulate mass of co-located, pumped-air samples, indicating that these leaf magnetic values are an effective proxy for ambient PM₁₀ concentrations. Biomagnetic monitoring using tree leaves can thus provide high spatial resolution data sets for assessment of particulate pollution levels at pedestrian-relevant heights. Leaf SIRM values not only increase with proximity to roads with higher traffic volumes, but are also ～100% higher at 0.3 m than at ～1.5–2 m height. Magnetic and SEM data indicate that the particle populations are dominated by spherical, iron-rich particles ～0.1–1 μm in diameter, with fewer larger, more angular, silica-rich particles. Comparison of the roadside leaf-calculated PM₁₀ concentrations with PM₁₀ concentrations predicted by a widely-used atmospheric dispersion model indicates some agreement between them. However, the model under-predicts PM₁₀ concentrations at ‘urban hotspots’ such as major–minor road junctions and traffic lights. Conversely, the model over-predicts PM₁₀ concentrations with distance from the road wherever one tree is screened by another, indicating the filtering/protective effect of roadside trees in leaf.     

Characteristics of vertical profiles and sources of PM2.5, PM10 and carbonaceous species in Beijing

In August 2003 during the anticipated month of the 2008 Beijing Summer Olympic Games, we simultaneously collected PM₁₀ and PM_2.5 samples at 8, 100, 200 and 325 m heights up a meteorological tower and in an urban and a suburban site in Beijing. The samples were analysed for organic carbon (OC) and elemental carbon (EC) contents. Particulate matter (PM) and carbonaceous species pollution in the Beijing region were serious and widespread with 86% of PM_2.5 samples exceeding the daily National Ambient Air Quality Standard of the USA (65 μg m⁻³) and the overall daily average PM₁₀ concentrations of the three surface sites exceeding the Class II National Air Quality Standard of China (150 μg m⁻³). The maximum daily PM_2.5 and PM₁₀ concentrations reached 178.7 and 368.1 μg m⁻³, respectively, while those of OC and EC reached 22.2 and 9.1 μg m⁻³ in PM_2.5 and 30.0 and 13.0 μg m⁻³ in PM₁₀, respectively. PM, especially PM_2.5, OC and EC showed complex vertical distributions and distinct layered structures up the meteorological tower with elevated levels extending to the 100, 200 and 300 m heights. Meteorological evidence suggested that there exist fine atmospheric layers over urban Beijing. These layers were featured by strong temperature inversions close to the surface (<50 m) and more stable conditions aloft. They enhanced the accumulation of pollutants and probably caused the complex vertical distributions of PM and carbonaceous species over urban Beijing. The built-up of PM was accompanied by transport of industrial emissions from the southwest direction of the city. Emissions from road traffic and construction activities as well as secondary organic carbon (SOC) are important sources of PM. High OC/EC ratios (range of 1.8–5.1 for PM_2.5 and 2.0–4.3 for PM₁₀) were found, especially in the higher levels of the meteorological tower suggesting there were substantial productions of SOC in summer Beijing. SOC is estimated to account for at least 33.8% and 28.1% of OC in PM_2.5 and PM₁₀, respectively, with higher percentages at the higher levels of the tower.     

重庆市春季大气颗粒物浓度的对比监测分析

通过2012年春季在重庆大气超级站进行的PM10和PM2.5手工采样与自动仪器的对比监测,分析了自动监测与手工监测的一致性及造成偏差的原因,并对PM2.5与PM10浓度的比值关系进行了分析。结果表明:MP101M型颗粒物自动监测仪用于监测PM10时系统性误差偏高,仪器初始精密度存在负偏差;用于监测PM2.5时系统性误差在允许范围之内,仪器初始精密度存在较大负偏差;PM10和PM2.5的手工采样和自动仪器监测值之变化趋势具有非常高的一致性;PM2.5与PM10浓度比值范围在56.5%～90.4%,平均比值为(73.8±7.4)%。     

Characteristics and sources of PM2.5 and carbonaceous species during winter in Taiyuan,China

Continuous observation of PM_2.5 was conducted in Taiyuan, a heavily polluted city in China, during high pollution season from December 2005 to February 2006. The results of this study showed that PM_2.5 and carbonaceous species pollution were serious during winter in Taiyuan. The organic carbon (OC) and element carbon (EC) were accounted for 18.6±11.2% and 2.9±1.6% of PM_2.5, respectively, which indicated that carbonaceous aerosols were key components for control fine particles pollution in Taiyuan. Coal combustion was a dominant source of OC and EC of PM_2.5 in the urban area of Taiyuan during winter. The impact of local and remote particle sources on urban air quality was assessed using PM_2.5 concentration rose and 3-day back trajectories of air masses arriving at Taiyuan. The meteorological conditions were found to affect the ambient concentrations of PM_2.5, OC, EC and OC/EC ratio.     

Chemical characteristics and source apportionment of PM<Subscript>2.5</Subscript> using PCA/APCS,UNMIX, and PMF at an urban site of Delhi,India

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM_2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM_2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM_2.5 was recorded as 121.9 ± 93.2 μg m^?3 (range 25.1–429.8 μg m^?3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ～17% of PM_2.5. Strong seasonal variation was observed in PM_2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM_2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM_2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM_2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM_2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM_2.5 from the north-west India and Pakistan were mostly pertinent.     

Investigation and modeling of the residential infiltration of fine particulate matter in Beijing,China

The objective of this study was to estimate the residential infiltration factor (Finf) of fine particulate matter (PM_2.5) and to develop models to predict PM_2.5 Finf in Beijing. Eighty-eight paired indoor–outdoor PM_2.5 samples were collected by Teflon filters for seven consecutive days during both non-heating and heating seasons (from a total of 55 families between August, 2013 and February, 2014). The mass concentrations of PM_2.5 were measured by gravimetric method, and elemental concentrations of sulfur in filter deposits were determined by energy-dispersive x-ray fluorescence (ED-XRF) spectrometry. PM_2.5 Finf was estimated as the indoor/outdoor sulfur ratio. Multiple linear regression was used to construct Finf predicting models. The residential PM_2.5 Finf in non-heating season (0.70 ± 0.21, median = 0.78, n = 43) was significantly greater than in heating season (0.54 ± 0.18, median = 0.52, n = 45, p < 0.001). Outdoor temperature, window width, frequency of window opening, and air conditioner use were the most important predictors during non-heating season, which could explain 57% variations across residences, while the outdoor temperature was the only predictor identified in heating season, which could explain 18% variations across residences. The substantial variations of PM_2.5 Finf between seasons and among residences found in this study highlight the importance of incorporating Finf into exposure assessment in epidemiological studies of air pollution and human health in Beijing. The Finf predicting models developed in this study hold promise for incorporating PM_2.5 Finf into large epidemiology studies, thereby reducing exposure misclassification.

Implications: Failure to consider the differences between indoor and outdoor PM_2.5 may contribute to exposure misclassification in epidemiological studies estimating exposure from a central site measurement. This study was conducted in Beijing to investigate residential PM_2.5 infiltration factor and to develop a localized predictive model in both nonheating and heating seasons. High variations of PM_2.5 infiltration factor between the two seasons and across homes within each season were found, highlighting the importance of including infiltration factor in the assessment of exposure to PM_2.5 of outdoor origin in epidemiological studies. Localized predictive models for PM_2.5 infiltration factor were also developed.     

Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study

Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25–55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM_2.5 and NO₂ to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM_2.5 and NO₂. A high correlation was observed between the personal 48-h PM_2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM_2.5 and the personal work time PM_2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM_2.5) and 19% (NO₂) of the variation in perceived air pollution annoyance in traffic. Compared to Helsinki, in Basel and Prague the adult participants were more annoyed by air pollution while in traffic even after taking the current home outdoor PM_2.5 and NO₂ levels into account.     

Monitoring an outdoor smoking area by means of PM<Subscript>2.5</Subscript> measurement and vegetal biomonitoring

The extension of pollutant accumulation in plant leaves associated with its genotoxicity is a common approach to predict the quality of outdoor environments. However, this approach has not been used to evaluate the environmental quality of outdoor smoking areas. This study aims to evaluate the effects of environmental tobacco smoke (ETS) by assessing particulate matter 2.5 μm (PM_2.5) levels, the pollen abortion assay, and trace elements accumulated in plant leaves in an outdoor smoking area of a hospital. For this, PM_2.5 was measured by active monitoring with a real time aerosol monitor for 10 days. Eugenia uniflora trees were used for pollen abortion and accumulated element assays. Accumulated elements were also assessed in Tradescantia pallida leaves. The median concentration of PM_2.5 in the smoking area in all days of monitoring was 66 versus 34 μg/m³ in the control area (P?<?0.001). In addition, the elements Al, Cd, Cu, Ni, Pb, Rb, Sb, Se, and V in Tradescantia pallida and Al, Ba, Cr, Cu, Fe, Mg, Pb, and Zn in Eugenia uniflora were in higher concentration in the smoking area when compared to control area. Smoking area also showed higher rate of aborted grains (26.1?±?10.7 %) compared with control (17.6?±?4.5 %) (P?=?0.003). Under the study conditions, vegetal biomonitoring proved to be an effective tool for assessing ETS exposure in outdoor areas. Therefore, vegetal biomonitoring of ETS could be a complement to conventional analyses and also proved to be a cheap and easy-handling tool to assess the risk of ETS exposure in outdoor areas.     

Characteristics of water-soluble inorganic ions in PM2.5 and PM2.5–10 in the coastal urban agglomeration along the Western Taiwan Strait Region,China

PM_2.5 and PM_2.5–10 aerosol samples were collected in four seasons during November 2010, January, April, and August 2011 at 13 urban/suburban sites and one background site in Western Taiwan Straits Region (WTSR), which is the coastal area with rapid urbanization, high population density, and deteriorating air quality. The 10 days average PM_2.5 concentrations were 92.92, 51.96, 74.48, and 89.69 μg/m³ in spring, summer, autumn, and winter, respectively, exceeding the Chinese ambient air quality standard for annual average value of PM_2.5 (grade II, 35 μg/m³). Temporal distribution of water-soluble inorganic ions (WSIIs) in PM_2.5 was coincident with PM_2.5 mass concentrations, showing highest in spring, lowest in summer, and middle in autumn and winter. WSIIs took considerable proportion (42.2～50.1 %) in PM_2.5 and PM_2.5–10. Generally, urban/suburban sites had obviously suffered severer pollution of fine particles compared with the background site. The WSIIs concentrations and characteristics were closely related to the local anthropogenic activities and natural environment, urban sites in cities with higher urbanization level, or sites with weaker diffuse condition suffered severer WSIIs pollution. Fossil fuel combustion, traffic emissions, crustal/soil dust, municipal constructions, and sea salt and biomass burnings were the major potential sources of WSIIs in PM_2.5 in WTSR according to the result of principal component analysis.     

The characteristics of PM2.5 in Beijing,China

Weekly PM_2.5 samples were simultaneously collected at a residential (Tsinghua University) and a downtown (Chegongzhuang) site in Beijing from July 1999 through September 2000. The ambient mass concentration and chemical composition of the PM_2.5 were determined. Analyses included elemental composition, water-soluble ions, and organic and elemental carbon. Weekly PM_2.5 mass concentrations ranged from 37 to 357 μg/m³, with little difference found between the two sites. Seasonal variation of PM_2.5 concentrations was significant, with the highest concentration in the winter and the lowest in the summer. Spring dust storms had a strong impact on the PM_2.5. Overall, organic carbon was the most abundant species, constituting no less than 30% of the total PM_2.5 mass at both sites. Concentrations of organic and elemental carbon were 35% and 16% higher at Tsinghua University than at Chegongzhuang. Ammonium, nitrate and sulfate were comparable at the sites, accounting for 25–30% of the PM_2.5 mass.     

Association of PM2.5 pollution with the pattern of human activity: A case study of a developed city in eastern China

Recently, air pollution has attracted a substantial amount of attention in China, which can be influenced by a variety of factors, but the association between air pollution and human activity is not quite clear. Based on real-time online data (January 1, 2014, to December 31, 2014) of air pollution and meteorology reported by official sites, and demographic, economic, and environmental reform data in a statistical yearbook, the influences of meteorological factors (temperature, relative humidity, precipitation intensity, and wind force) and human activities on PM_2.5 pollution were explored. After correlation analysis, logistic regression analysis, and a nonparametric test, weak negative correlations between temperature and PM_2.5 pollution were found. In most cases, festival and morning peak hours were protection and risk factors of PM_2.5 pollution, respectively. In addition, government actions, such as an afforestation project and increasing financial expenditure for energy saving and environmental protection, could greatly contribute to alleviating pollution of PM_2.5. The findings could help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity would be ameliorated.

Implications: Most of the time, festival and morning peak hours are protection and risk factors for PM_2.5 pollution, respectively. Increasing the percentage of afforestation area and financial expenditure for energy saving and environmental protection could significantly reduce PM_2.5 pollution. The findings can help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity, especially government action, will be ameliorated.     

Transformation of atmospheric ammonia and acid gases into components of PM<Subscript>2.5</Subscript>: an environmental chamber study

Introduction  

The kinetics of the transformation of ammonia and acid gases into components of PM_2.5 has been examined. The interactions of existing aerosols and meteorology with the transformation mechanism have also been investigated. The specific objective was to discern the kinetics for the gas-to-particle conversion processes where the reactions of NH₃ with H₂SO₄, HNO₃, and HCl take place to form (NH₄)₂SO₄, NH₄NO₃, and NH₄Cl, respectively, in PM_2.5.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses

Evaluation of health impacts arising from inhalation of pollutant particles <10 μm (PM₁₀) is an active research area. However, lack of exposure data at high spatial resolution impedes identification of causal associations between exposure and illness. Biomagnetic monitoring of PM₁₀ deposited on tree leaves may provide a means of obtaining exposure data at high spatial resolution. To calculate ambient PM₁₀ concentrations from leaf magnetic values, the relationship between the magnetic signal and total PM₁₀ mass must be quantified, and the exposure time (via magnetic deposition velocity (MV_d) calculations) known. Birches display higher MV_d (∼5 cm⁻¹) than lime trees (∼2 cm⁻¹). Leaf saturation remanence values reached ‘equilibrium’ with ambient PM₁₀ concentrations after ∼6 ‘dry’ days (<3 mm/day rainfall). Other co-located species displayed within-species consistency in MV_d; robust inter-calibration can thus be achieved, enabling magnetic PM₁₀ biomonitoring at unprecedented spatial resolution.     

区域大气环境中PM2.5/PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM_2.5/PM₁₀空间分布的方法,并在2004年12月进行了宁波市全市域PM_2.5/PM₁₀空间分布的研究。数据显示：相同路径所代表的地区PM_2.5和PM₁₀具有很好的相关性,多数路径上PM_2.5与PM₁₀数据的相关系数平方在0.95以上,而不同路径上PM_2.5与PM₁₀的比值不同。文中给出了宁波市PM_2.5/PM₁₀污染的空间分布图,直观地显示出PM_2.5/PM₁₀污染的空间分布情况,突出了污染的重点点位和地区。     

Spatio-temporal trends and influencing factors of PM2.5 concentrations in urban agglomerations in China between 2000 and 2016

An urban agglomeration (UA), similar to a megalopolis or a metropolitan area, is a region where cities and people are concentrated, and where air pollution has adversely impacted on sustainable and high quality development. Studies on the spatio-temporal trends and the factors which influence PM_2.5 concentrations may be used as a reference to support air pollution control policy for major UAs throughout the world. Nineteen UAs in China covering the years 2000–2016 were chosen as the research object, the PM_2.5 concentrations being used to reflect air pollution and being estimated from analysis of remote sensing images. The Exploratory Spatial Data Analysis method was used to study the spatio-temporal trends for PM_2.5 concentrations, and the Geodetector method was used to examine the factors influencing the PM_2.5 concentrations. The results revealed that (i) the temporal trend for the average values of the PM_2.5 concentrations in the UAs followed an inverted U-shaped curve and the inflection points of the curve occurred in 2007. (ii) The PM_2.5 concentrations in the UAs exhibited significant global spatial autocorrelation with the high–high type and the low–low type being the main categories. (iii) The rate of land urbanization and the structure of energy consumption were the main factors which influenced the PM_2.5 concentrations in the UAs.

     

An integrated MM5–CMAQ modeling approach for assessing trans-boundary PM10 contribution to the host city of 2008 Olympic summer games—Beijing,China

In this paper, an integrated MM5–CMAQ modeling approach was employed to investigate the PM₁₀ air pollution issue in Beijing, China, with a focus on assessing pollution contributions from surrounding provinces. A 2-level-nested grid domain with spatial resolutions of 36 and 12 km was designed for the study region. Seven monitoring stations across Beijing municipality were selected to provide hourly PM₁₀ measurement data. The months of January, April, July and October in 2002 were taken as target periods for model performance evaluation. Five emission scenarios were designed and run in order to quantitatively assess the trans-boundary PM₁₀ contributions. The results show that, while Beijing needs to take positive steps to reduce its own pollution emissions, much effort should also be placed on demanding more pollution reduction and better environmental performance from surrounding provinces.     

Study on ambient concentrations of PM10, PM10–2.5, PM2.5 and gaseous pollutants. Trace elements and chemical speciation of atmospheric particulates

This study provides the first comprehensive report on mass concentrations of particulate matter of various sizes, inorganic and organic gas concentrations monitored at three sampling sites in the city of Palermo (Sicily, Italy). It also provides information on the water-soluble species and trace elements. A total of 2054 PM₁₀ (1333) and PM_2.5 (721) daily measurements were collected from November 2006 to February 2008. The highest mass concentrations were observed at the urban stations, average values being about two times higher than those at the suburban (control) site. Time variations in PM₁₀ and also PM_10–2.5 were observed at the urban stations, the highest concentrations being measured in autumn and winter. CO, NOx, NO₂, benzene, toluene and o-xylene concentrations peaked in autumn and winter, a pattern similar to those recorded for PM₁₀ and PM_10–2.5 mass levels, indicating the importance of traffic emissions in urban air pollution. 91% and 51% of the benzene measurements exceeded the limit of 5 μg m^?3 at the two urban monitoring sites. Trace elements (As, Ba, Cr, Cu, Mo, Pb, Sb) suspected of being introduced into the atmosphere mainly by anthropogenic activities, were highly enriched with respect to local soil. Results indicate that a large fraction of PM₁₀ (31–47% in weight) and PM_2.5 (29% in weight) is made up of water-soluble ions. Ammonium sulphate and nitrate particles accounted for 14–29 wt% of particulate matter mass concentrations. Crustal and marine components, combined, account for 41% and 49% in PM_2.5 and PM₁₀, respectively. The calculated deficits in Cl^- and NH₄⁺ ions suggest that a proportion of these ions are lost, via the formation of gaseous NH₄Cl or HCl and NH₃.