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The Fenwei Plain (FWP) remains one of the worst PM2.5-polluted regions in China, although its air quality has improved in recent years. To evaluate the regional transport characteristics of PM2.5 emitted by coal-fired power plants in the FWP in wintertime, the primary PM2.5, SO2, and NOx emissions from coal-fired power plants with large units (≥300 MW) in 11 cities of the area in January 2019 were collected based on the Continuous Emission Monitoring System (CEMS). The spatial distribution and source contribution of primary and secondary PM2.5 concentrations were investigated using the Weather Research and Forecast (WRF) model and the California Puff (CALPUFF) model. The results showed that secondary PM2.5 was transported over a larger range than primary PM2.5 and that secondary nitrate was the main component of the total PM2.5 concentration, accounting for more than 70%. High concentrations of primary, secondary, and total PM2.5 mainly occurred in the Shaanxi region of the FWP, especially in Xianyang, where the PM2.5 concentrations were the highest among the 11 cities, even though its pollutant emissions were at moderate levels. The PM2.5 concentrations in Sanmenxia and Yuncheng primarily came from regional transport, accounting for 64% and 68%, respectively, while those in other cities were dominated by local emissions, accounting for more than 63%. The results may help to understand the regional transport characteristics of pollutants emitted from elevated point sources over a complex terrain.

Aiming at the thermal attenuation problem of ground temperature field in unidirectional heat extraction and supply in buildings of deep-buried geothermal energy, we propose supplementing heat to the ground using some heat source such as solar energy that is stored during the non-heating period, thus enabling long-term operation of a buried pipe system. With the study conducted on a buried U-bend pipe project with a depth of 2505 m, a three-dimensional (3D) full-scale model was established based on the numerical modeling method which obtained by the author’s research team in the early stage. The heat extracted from the buried pipe or the heat storage capacity of ground for a constant inlet water temperature and given initial ground temperature field was analyzed and predicted. Meanwhile, the heat storage capacity after heat was taken from the buried pipe was calculated and analyzed. Finally, heat flux through the wall of the buried pipe was analyzed, and heat transfer to ground at different buried depths during the heat storage period was discussed.

As critical precursors of tropospheric ozone (O

Vehicle emissions are affected by factors such as vehicle type, fuel quality, and engine repair. Therefore, mobile source profiles should be established based on a characteristic fleet for a specific region. This study characterised the chemical composition of PM2.5 emitted from motor vehicles that are commonly used in Xi'an through dynamometer tests. The tested fleet included light duty diesel vehicles (LDDVs; eight sample sets), heavy duty diesel vehicles (HDDVs; six sample sets), light duty gasoline vehicles (LDGVs; eight sample sets), one natural gas vehicle (NGV; four sample sets) and one methanol vehicle (MV; two sample sets). Similarities and differences among the source profiles were compared and evaluated. Overall, carbon species (13.14–59.11%) were the major components of PM2.5 for each type of vehicle, and the content of organic carbon (OC) was generally higher than that of elemental carbon (EC). Moreover, NO3− (18.577–220.062 mg·g−1) was the dominant water-soluble ion and the Ca2+ (2.429–17.209 mg·g−1) and Na+ (1.966–20.798 mg·g−1) contents in PM2.5 were high. In terms of elements, the PM2.5 emitted from various types of vehicles consisted of abundant Al (2.183–94.949 mg·g−1), Fe (0.567–12.297 mg·g−1), and Zn (0.659–5.195 mg·g−11). In addition, the PM2.5 profiles were significantly affected by fuel type. In general, emissions from the LDGVs and NGV exhibited higher contents of OC (477.0–479.1 mg·g−1). The greatest fractions of water-soluble ions (32.94%) and total elements (11.74%) were observed in emissions from the NGV and MV, respectively. For the same type of vehicle, the OC/EC ratio was possibly dependent on the emission standards. The PM2.5 emitted from the LDDVs with stricter emission standards exhibited higher OC/EC ratios, whereas the OC/EC ratios displayed a decreasing trend for the LDGVs under more stringent emission standards.

Chemical compositions of particulate matter (PM) from traffic emissions vary by region and with time. Therefore, it is necessary to obtain local mobile source profiles of PM to support regional researches for vehicle emission control policy, source apportionment modeling, etc. In this study, PM2.5 and PM10 samples were collected from a highway tunnel in Xi’an in northwestern China. The chemical composition, specifically, the OC, EC, water-soluble ions, and elements, was analyzed in detail to (1) provide local PM profiles for a mixed vehicle fleet, (2) identify the origins of different elements in the tunnel environment, and (3) determine the associated factors influencing the profiles. The PM2.5 profiles in the tunnel were identified as OC (34.10%), EC (11.96%), water-soluble ions (18.22%), and elements (27.73%), while the PM10 profiles included OC (28.48%), EC (8.59%), water-soluble ions (14.17%), and elements (33.36%), respectively. The origins of the elements in the tunnel were classified into three categories by the receptor modeling approach: resuspended road dust and brake wear, vehicle exhaust and tire wear, and tailpipe emissions from diesel vehicles (DV). The mass fractions of OC, EC, and elements originating from resuspended road dust and brake wear were mainly affected by vehicle driving conditions (i.e., uphill/downhill and speed), whereas the mass content of bromine (Br) was influenced by the proportion of DV in the fleet.

Alternative-fueled vehicles have been introduced to solve the problem of the energy crisis and address air pollution. However, typical pollutants (e.g., methane and methanol) are emitted through combustion of the alternative fuel. In this study, the concentrations of regulated pollutants (CO, NO) and unregulated pollutants (CH4, methanol, formaldehyde, and 8 NMHC species) in the exhaust from methanol, CNG, and gasoline-fueled vehicles (MV, NGV, and GV) were measured systematically on a chassis dynamometer during an in-use vehicle driving cycle. The emission factors of these gaseous pollutants were calculated, and the ozone formation potential (OFP) of each ozone precursor measured in this work was evaluated with the MIR scale. The results showed that NO and NMHC species exhausted from the MV and NGV decreased significantly than that from the GV. However, the unburned pollutants exhausted from MV and NGV warrant attention. For the OFPs, CO was the largest contributor for all tested vehicles. Formaldehyde was ranked the second for the MV and NGV. Among the tested vehicles, the OFPs of NGV were the lowest. The results are helpful in quantitating analysis of the vehicle emissions and evaluating the impacts of alternative-fueled vehicles on atmospheric environment.

Frequent ozone and fine particulate matter (PM2.5) pollution have been occurring in the Guanzhong Plain in China. To effectively control the tropospheric ozone and PM2.5 pollution, this study performed measurements of 102 VOCs species from Sep.19-25 (autumn) and Nov.27-Dec. 8, 2017 (winter) at Weinan in the central Guanzhong Plain. The total volatile organic compounds (TVOCs) concentrations were 95.8 ± 30.6 ppbv in autumn and 74.4 ± 37.1 ppbv in winter. Alkanes were the most abundant group in both of autumn and winter, accounting for 33.5% and 39.6% of TVOCs concentrations, respectively. The levels of aromatics and oxygenated VOCs were higher in autumn than in winter, mainly due to changes in industrial activities and combustion strength. Photochemical reactivities and ozone formation potentials (OFPs) of VOCs were calculated by applying the OH radical loss rate (LOH) and maximum incremental reactivity (MIR) method, respectively. Results showed that Alkenes and aromatics were the key VOCs in term ozone formation in Weinan, which together contributed 59.6% 65.3% to the total LOH and OFP. Secondary organic aerosol formation potentials (SOAFP) of the measured VOCs were investigated by employing the fractional aerosol coefficient (FAC) method. Aromatics contributed 94.9% and 96.2% to the total SOAFP in autumn and winter, respectively. The regional transport effects on VOCs and ozone formation were investigated by using trajectory analysis and potential source contribution function (PSCF). Results showed that regional anthropogenic sources from industrial cities (Tongchuan, Xi'an city) and biogenic sources from Qinling Mountain influenced VOCs levels and OFP at Weinan. Future studies need to emphasize on meteorological factors and sources that impact on VOCs concentrations in Weinan.

This study reported the emission factors (EFs) and detailed chemical compositions of PM

Size, morphology, and composition of airborne particles strongly affect human health and visibility, precipitation, and the kinetic characteristics of particles. In this study, the morphology and chemical composition of particles emitted from conventional (diesel and gasoline) and alternative (CNG and methanol) fuel vehicles were characterized through scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). The SEM images revealed that the size of primary particles (without agglomeration) was approximately 10 nm in the exhaust from all the tested vehicles. The particles emitted from gasoline vehicle (GV), CNG vehicle (CNGV), and methanol vehicle (MV) had the same median diameter, 62 nm, which was smaller than those from heavy diesel vehicle (HDV) and light diesel vehicle (LDV). Soot was observed in the HDV, LDV, and GV samples but not in the CNGV and MV. The fractal dimension, which was used to quantify the degree of irregularity of soot, was 1.752 ± 0.014, 1.789 ± 0.076, and 1.769 ± 0.006 in the exhaust from HDV, LDV, and GV samples, respectively. The particles discharged by all tested vehicles contained the elements C, O, Fe, and Na. The main element in the samples of HDV, LDV, and GV was C, while O was the main element in the samples of alternative fuel vehicles. The profiles of minor elements were more complex in the emissions of alternative fuel vehicles than those in the emissions of conventional fuel vehicles. The results improved our understanding of the morphology and elemental composition of particles emitted from vehicles powered by diesel, gasoline, CNG, and methanol.

Exposure to phthalates has recently become a major public health concern. The information of indoor airborne phthalates and their air-particle partition in real indoor environmental condition is still limited. In this study, the gas- and PM2.5-concentrations of 7 phthalates in 40 residences were concurrently measured in summer and winter. The major phthalates (median concentration in the summer and winter, respectively) in indoor air were DMP (2442.3 and 2403.4 ng/m3), DiBP (801.0 and 640.0 ng/m3) and DnBP (5173.2 and 1379.6 ng/m3), whereas the major phthalates in PM2.5 were DiBP (1055.1 and 585.9 ng/m3) and DnBP (1658.5 and 1517.0 ng/m3) and DEHP (215.1 and 344.9 ng/m3). Air-PM2.5 partition coefficients (Kp) of DiBP, DnBP and DEHP were calculated: the summer and winter median values (m3/μg) were 0.053 and 0.011 for DiBP, 0.010 and 0.004 for DnBP, 0.021 and 0.025 for DEHP, respectively. Air-PM2.5 partition of DiBP and DnBP approached equilibrium, while that of DEHP did not reach equilibrium in either season. The impacts of built environmental conditions on phthalate concentrations were characterized. Elevated temperature resulted in accumulation of airborne phthalates. Higher air humidity led to more water absorption of aerosols in summer, facilitated mass transfer of phthalates from air to PM2.5, and resulted in greater Kp of DiBP and DnBP in the summer. Any factors such as proximity to local traffic highway and indoor smoking activities, which can increase indoor PM2.5 concentrations, resulted in significantly higher airborne phthalate concentrations. Improving ventilation was not an effective measure to reduce indoor airborne phthalate concentrations.

Exposure to phthalates poses adverse health impacts to human beings. In this study, we analyzed 7 phthalates in dust samples, which were collected with vacuum cleaner from 40 to 31 residences in Beijing in summer and winter, respectively. The major phthalates (median concentration in the summer and winter, respectively) were DiBP (55 and 40 ng/mg), DnBP (99 and 30 ng/mg) and DEHP (795 and 335 ng/mg). The concentrations were significantly influenced by season and residence time of house dust. The concentrations of phthalates in dust on plastic surfaces were highest, followed by those on wooden and fabric surfaces. The dust-air partition coefficients (Kd) were calculated: the median values were 0.13, 0.02 and 5.62 m3/mg in the summer and 0.06, 0.018 and 0.76 m3/mg in the winter for DiBP, DnBP and DEHP, respectively. A comparison with Kd* at equilibrium state suggested that partition between air and dust deviated from equilibrium state in both seasons. The results also revealed that dust-phthalates in the summer may completely originate from source materials via direct transfer and external physical process; while dust-phthalates in the winter may come from both air (via partition) and source material (via direct transfer and external physical process). The influence of temperature on dust-phthalate concentrations differed by season, owing to different origin of dust-phthalates in two seasons. Polar organic components in dust, which are products of reactions between O3 and unsaturated hydrocarbons in dust, likely played an important role in fate and transport of phthalates. The presence of them resulted in the significant associations between dust-phthalate concentrations and air humidity in the summer. Moreover, the impacts of indoor PM2.5 concentrations, traffic conditions surrounding residence, household lifestyle and number of occupants were also observed. The mechanisms behind those observations were discussed.

Residential indoor exposure to volatile organic compounds (VOCs) is a major public health concern. However, the relevant pollution sources have not been well characterized in China. In this study, the 24-h integrated concentrations of 55 VOC species in 27 urban residences, Beijing were measured in the summer. The sources were characterized with positive matrix factorization (PMF) and general linear model (GLM). The most abundant species in terms of geometric mean concentration were formaldehyde (55.1 μg/m3), acetaldehyde (18.7 μg/m3), acetone (14.8 μg/m3), toluene (14.1 μg/m3), hexanal (13.8 μg/m3), n-hexadecane (8.9 μg/m3) and n-pentadecane (8.5 μg/m3). PMF generated 7 factors associated with VOC sources, including aldehydes from ozone-initiated secondary reactions, butyraldehyde from hydrolysis of building materials and furniture, wood flooring emission, wooden furniture emission, wall coverings emission, mobile emission and halogenated hydrocarbons of miscellaneous outdoor origin. GLM identified leather sofa as another source of indoor terpenes and formaldehyde. GLM also found composite wood flooring had stronger emission of VOCs than solid wood flooring, except 1,4-dichlorobenzene. A comparison with multiple studies across the world suggested that: (1) more intensive ozone-initiated secondary reactions resulted in the significantly higher indoor carbonyl concentrations in Beijing than in Japan and USA in the summer; (2) the indoor concentrations of benzene and C12-C17 alkanes were much higher in Beijing, due to the traffic conditions and prevalent use of wood flooring varnishing.

Since the haze event occurred in many areas of central and eastern China in 2013, haze pollution has become one of the most important environmental issues and has attracted more and more attention from government, industry circle, scholars and the general public in China. Haze pollution is characterized by atmospheric particular matter (PM) being one of the top pollutants. A large number of studies have been conducted to investigate the chemical components of atmospheric PM during haze pollution, while little is known about the biological components and characteristics of PM in the atmosphere, especially during haze pollution. Biological particles in the atmosphere, generally defined as bioaerosols, are airborne particles or large molecules carrying living organisms or released from living organisms (e.g., bacteria, fungi, viruses, pollen, bacterial endotoxins and mycotoxins, etc.). Bioaerosols not only pose potential risks on air quality and human health, but also have direct effects on the alteration of global climate and atmospheric physical and chemical processes. Up to now, however, the concentration and size distribution, diversity, and abundance of different types of bioaerosols as well as their temporal and spatial variability are not well characterized on hazy days. Moreover, due to the changeable community structure, flexible biological activity and comprehensive influential factors, the knowledge involving how haze pollution affects bioaerosols, to what extent it affects, and the influence mechanism is still unclear so far. Therefore, this review first has presented an overview of the state of bioaerosol research during haze pollution, including concentration level, size distribution and community structure of microorganisms in bioaerosols. Subsequently, the current understanding and open questions have been emphatically discussed concerning the characteristics of bioaerosols at different air pollution levels and effects of air pollution on airborne microbes. Finally, we suggest that the following research activities should be pursued in future studies of bioaerosols during haze pollution: (1) It is extremely urgent to develop and establish uniform standardized sampling and identification criterion to better judge and measure the numerous monitoring data from different researchers. It is also essential to develop advanced, sensitive, real-time and online detection techniques to quantify the biological properties of bioaerosols. (2) The nationwide field monitoring of bioaerosols covering more climate types and pollution levels at various time scales should be carried out to obtain more comprehensive data for fully understanding the temporal and spatial variability of bioaerosols and its influential factors. Some other meteorological influential factors (e.g., boundary-layer height, atmospheric extreme temperature, extreme wind speed, and atmospheric pressure, etc.), and pollution factors such as the concentration of heavy metal and polycyclic aromatic hydrocarbon (PAHs) in PM should be taken into account to deeply understand the effect of haze pollution on bioaerosols. (3) Current studies have shown that many gaseous and particulate pollutants are related to the concentration of bioaerosols. However, little is known about the influence mechanisms of pollutants. Therefore, in addition to field monitoring, it is also necessary to design and conduct the laboratory experiment of smog chamber to determine the influence mechanism of each single environmental factor or pollution factor on bioaerosols. (4) In addition to different degrees of haze pollution, there are different kinds of haze pollution including the formation of haze by photochemical reaction in summer and liquid phase reaction at high RH in winter. Therefore, it is also essential to examine the distribution and variation of bioaerosols during different haze formation processes in order to improve our understanding of haze pollution effects on bioaerosols. (5) It is necessary to develop a biological source-tracking technology based on the bioaerosol species and community composition to reveal the possible sources of bioaerosols during haze episodes.

Vehicle emissions are affected by factors such as vehicle type, fuel quality, and engine repair. Therefore, mobile source profiles should be established based on a characteristic fleet for a specific region. This study characterised the chemical composition of PM

Vehicular emissions contribute significantly to air pollution, and the number of vehicles in use is continuing to rise. Policymakers thus need to formulate vehicular emission reduction policies to improve urban air-quality. This study used different vehicle control scenarios to predict the associated potential of mitigating carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxide (NOx), particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), and particulate matter with an aerodynamic diameter less than 10 μm (PM10) in Xi’an China, in 2020 and 2025. One business-as-usual scenario and six control scenarios were established, and vehicular emission inventory was developed according to each scenario. The results revealed that eliminating high-emission vehicles and optimizing after-treatment devices would effectively reduce vehicular emissions. In addition, increasing the number of alternative fuel vehicles, restraining vehicle use, and restraining the growth of the vehicle population would all have certain effects on CO and VOCs emissions, but the effects would not be significant for NOx, PM2.5, and PM10. The results also indicated that if all control measures were stringently applied together, emissions of CO, VOCs, NOx, PM2.5, and PM10 would be reduced by 51.66%, 51.58%, 30.19%,71.12%, and 71.81% in 2020, and 53.55%, 51.44%, 19.09%, 54.88%, and 55.51%, in 2025, respectively.

Diesel vehicles contributed 70 % of the NOx and more than 90 % of the PM in the 2014 on-road emissions inventory in China. Attention is therefore being focused on diesel vehicles because of their significantly higher NOx and PM emission rates and vehicle miles traveled, relative to gasoline-powered cars. Xi’an city has taken many measures to reduce diesel exhaust emissions. In this present study, the main objectives were to identify potential of emission-reduction strategies—fuel-standard improvements, elimination of “yellow-brand” vehicles, increased use of alternative fuels (CNG, LNG), and installation of DPFs in older vehicles—and to quantify the relative effectiveness of each of these potential strategies. A revised MOVES model was used to estimate PM and NOx emission inventories for selected scenarios at the county scale, for Xi’an city. The results show that, for NOx reduction, the best strategy would be fuel-standard improvements (Scenario 1), followed by (in order of effectiveness) the increased use of alternative fuels (Scenario 3), elimination of “yellow-brand” diesel vehicles (Scenario 2), and retrofitting older vehicles by installing DPFs (Scenario 4), whereas for PM10 or PM2.5, the effectiveness sequence of control strategies was found to be Scenario 1, Scenario 3, Scenario 2, and Scenario 4. It was also found that medium-weight and heavy trucks have a larger potential for NOx and PM reductions than do other vehicle types. These results are of paramount importance, not only for Xi’an but also for other cities that are considering adopting possible strategies to mitigate air pollution from vehicles.

Serious air pollution events have frequently occurred in China associated with the acceleration of urbanization and industrialization in recent years. Exposure to atmospheric particulate matter (PM) of high concentration can lead to adverse effects on human health. Airborne bacteria are important constituents of microbial aerosols and contain lots of pathogens. However, variations in bacterial community structure in atmospheric PM of different sizes (PM2.5, PM10 and TSP) have not yet been explored. In this study, PM samples of different sizes were collected during the hazy days from Jul.2016 to Apr.2017 to determine bacterial diversity and community structure. Samples from soils and leaf surfaces were also collected to determine potential sources of bacterial aerosols. High-throughput sequencing technology was used generate bacterial community profiles, where we determined their diversity and abundances in the samples. Results showed that the dominant bacterial community structures in PM2.5, PM10 and TSP were strongly similar. Compared with non-haze days, the relative abundances of most bacterial pathogens on the haze days did not increase. Meanwhile, temperature, O3 and NO2 had more significant effects on bacterial community than the other environmental factors. Source tracking analysis indicated that the airborne bacteria might be not from local environment. It may come from the entire city or other regions by long distance airflow transport. Results of this study improved our understanding of the influence of bioaerosols on human health and the potential sources of airborne microbes.

Al4B2O9 whiskers on the surface of porous SiC substrates were fabricated by chemical reactions between Al(NO3)3 and H3BO3, which is a facile method to prepare cilia-like microstructure for gas–solid separation. Scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy were employed to investigate the structural morphology and phase compositions. Al4B2O9 whiskers with nanometer-sized diameters and micrometer-sized lengths grew on the surface of SiC substrates, and a self-catalytic mechanism was used to explain Al4B2O9 whisker growth.

Biomorphic silicon carbide–mullite ceramics were prepared from beech wood using liquid Si infiltration and molten salts synthesis. The resulting mullite whiskers coating, as well as the growth mechanism in molten Al 2 (SO 4 ) 3 –Na 2 SO 4 environment, have been investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR) techniques. The biomorphic SiC ceramics derived from the beech wood template have coarse pore walls consisting of β-SiC grains with diameters ranging from 5 μm to 20 μm. After the molten salts reactions between biomorphic SiC substrate and mixture molten salts (Al 2 (SO 4 ) 3 –Na 2 SO 4 ), porous Silicon carbide–mullite ceramics with cilia-like microstructure were obtained. This unique structure has potential application in hot gases filters. An oxidation–dissolution cycle was proposed to explain the mullite whiskers growth in molten salts environment.

Intercity bus terminals are hotspots of air pollution due to concentrated activities of diesel buses. In order to evaluate the bus terminals’ impact on air quality, it is necessary to estimate the associated mobile emission inventories. Since the vehicles’ operating condition at the bus terminal varies significantly, conventional calculation of the emissions based on average emission factors suffers the loss of accuracy. In this study, we examined a typical intercity bus terminal—the Southern City Bus Station of Xi’an, China—using a multi-scale emission model—(US EPA’s MOVES model)—to quantity the vehicle emission inventory. A representative operating cycle for buses within the station is constructed. The emission inventory was then estimated using detailed inputs including vehicle ages, operating speeds, operating schedules, and operating mode distribution, as well as meteorological data (temperature and humidity). Five functional areas (bus yard, platforms, disembarking area, bus travel routes within the station, and bus entrance/exit routes) at the terminal were identified, and the bus operation cycle was established using the micro-trip cycle construction method. Results of our case study showed that switching to compressed natural gas (CNG) from diesel fuel could reduce PM2.5 and CO emissions by 85.64 and 6.21 %, respectively, in the microenvironment of the bus terminal. When CNG is used, tail pipe exhaust PM2.5 emission is significantly reduced, even less than brake wear PM2.5. The estimated bus operating cycles can also offer researchers and policy makers important information for emission evaluation in the planning and design of any typical intercity bus terminals of a similar scale.

The paper analyzed the three-year (from 2006 to 2008) concentration data of SO 2 , NO 2 and PM 10 with routine monitoring in Xi'an, and selected several common statistical distribution models to fit the observational data. The results showed that the most appropriate distribution models representing the daily average concentration of SO 2 (0.0514 ± 0.0390 mg/m3, n=1096), NO 2 (0.0416 ± 0.0135 mg/m3, n=1096) and PM 10 (0.1268 ± 0.0574 mg/m3, n=1095) were Pearson 6, Extreme Value and Log-Logistic distribution, respectively. According to the rollback equation, the emission source reduction of SO 2 , NO 2 and PM 10 to meet the secondary standards of ambient air quality standard (AAQS) is also estimated, i.e. −16.7%, 3.8% and 21.1%, respectively. Therefore, in order to improve the air quality in Xi'an, the average concentration of PM 10 and NO 2 should be reduced to meet the AAQS while the SO 2 concentration meet to the AAQS with the environmental capacity of 16.7% in future. It can offer some referenced suggestions to develop effective air pollution control strategies for environmental protection departments.

The current study was based on annual ambient air quality monitoring data and corresponding meteorological observation data of Xi'an in 2011. Distribution models on hourly concentrations of PM10, SO2, and NO2 were studied, and the results showed that statistical distribution functions varied from seasons and from pollutants. The optimal distribution models of PM10 concentrations in the four seasons (spring, summer, autumn, and winter) were generalized extreme value distribution (GEVD), Weibull, Weibull, and GEVD, respectively; those of SO2 were lognormal, log-logistic, log-logistic, and GEVD, respectively; and those of NO2 were Weibull, lognormal, GEVD, and GEVD, respectively. The concentrations ranges were 0.03 ∼ 0.20 mg/m3 for PM10, 0.008 ∼ 0.17 mg/m3 for SO2, and 0.01 ∼ 0.12 mg/m3 for NO2, and the probabilities of concentrations in the ranges for accordingly pollutants were up to 85 %. Effects of the meteorological parameters on concentrations of PM10, SO2, and NO2 were studied with linear correlation analysis method for Xi'an city. The results indicated that pollutant concentrations had a negative correlation with wind speed, temperature, and mixing height (MH), whereas it had a positive correlation with atmospheric pressure and atmospheric stability. Both temperature and atmospheric pressure were the most obvious correlation with SO2 concentration with r value of −0.7916 and 0.7032, respectively. Wind speed and MH had the most obvious correlation with NO2 concentration with r value of −0.4423 and −0.3997, respectively. SO2 had the best correlation with meteorological parameters. Analyzing the statistical characteristics of urban air pollution concentration and their relationships with meteorological parameters are of great importance to study urban air pollution problems and corresponding prevention measure.