Suping Zhao

Annual and diurnal variations of gaseous and particulate pollutants in 31 provincial capital cities based on in situ air quality monitoring data from China National Environmental Monitoring Center.

Long-term air quality data with high temporal and spatial resolutions are needed to understand some important processes affecting the air quality and corresponding environmental and health effects. The annual and diurnal variations of each criteria pollutant including PM2.5 and PM10 (particulate matter with aerodynamic diameter less than 2.5 μm and 10 μm, respectively), CO (carbon monoxide), NO2 (nitrogen dioxide), SO2 (sulfur dioxide) and O3 (ozone) in 31 provincial capital cities between April 2014 and March 2015 were investigated by cluster analysis to evaluate current air pollution situations in China, and the cities were classified as severely, moderately, and slightly polluted cities according to the variations. The concentrations of air pollutants in winter months were significantly higher than those in other months with the exception of O3, and the cities with the highest CO and SO2 concentrations were located in northern China. The annual variation of PM2.5 concentrations in northern cities was bimodal with comparable peaks in October 2014 and January 2015, while that in southern China was unobvious with slightly high PM2.5 concentrations in winter months. The concentrations of particulate matter and trace gases from primary emissions (SO2 and CO) and NO2 were low in the afternoon (~16:00), while diurnal variation of O3 concentrations was opposite to that of other pollutants with the highest values in the afternoon. The most polluted cities were mainly located in North China Plain, while slightly polluted cities mostly focus on southern China and the cities with high altitude such as Lasa. This study provides a basis for the formulation of future urban air pollution control measures in China.

Numerical Model-Based Artificial Neural Network Model and Its Application for Quantifying Impact Factors of Urban Air Quality

Knowledge of the relationship between air quality and impact factors is very important for air pollution control and urban environment management. Relationships between winter air pollutant concentrations and local meteorological parameters, synoptic-scale circulations and precipitation were investigated based on observed pollutant concentrations, high-resolution meteorological data from the Weather Research and Forecast model and gridded reanalysis data. Artificial neural network (ANN) model was developed using a combination of numerical model derived meteorological variables and variables indicating emission and circulation type variations for estimating daily SO2, NO2, and PM10 concentrations over urban Lanzhou, Northwestern China. Results indicated that the developed ANN model can satisfactorily reproduce the pollution level and their day-to-day variations, with correlation coefficients between the modeled and the observed daily SO2, NO2, and PM10 ranging from 0.71 to 0.83. The effect of four factors, i.e., synoptic-scale circulation type, local meteorological condition, pollutant emission variation, and wet removal process, on the day-to-day variations of SO2, NO2, and PM10 was quantified for winters of 2002–2007. Overall, local meteorological condition is the main factor causing the day-to-day variations of pollutant concentrations, followed by synoptic-scale circulation type, emission variation, and wet removal process. With limited data, this work provides a simple and effective method to identify the main factors causing air pollution, which could be widely used in other urban areas and regions for urban planning or air quality management purposes.

Numerical model-based relationship between meteorological conditions and air quality and its implication for urban air quality management

Relationships between winter air pollutant concentrations and ten meteorological parameters were investigated based on observed pollutant concentrations and high-resolution meteorological data from weather research and forecast model, and multiple linear regression models were developed for estimating NO2 and PM10 concentrations over urban Lanzhou, North-western China. Results indicated that pollutant concentration correlated better with boundary layer height and potential temperature lapse rate than with other meteorological parameters. There is a lag time of 3–12 hrs for meteorology conditions to have an effect on pollutant concentrations in urban and 12–17 hrs in rural areas, with longer lag time for wind than for temperature stratification. The overall performance of the multiple linear regression models is basically comparable to the widely used comprehensive air quality models and artificial neural network models. The method used here provides another way to estimate possible spatial distributions of pollutant concentrations with less computing time and input data, and could be applied to other cities for urban planning or air quality management purposes.

Effect of traffic restriction on atmospheric particle concentrations and their size distributions in urban Lanzhou, Northwestern China

During the 2012 Lanzhou International Marathon, the local government made a significant effort to improve traffic conditions and air quality by implementing traffic restriction measures. To evaluate the direct effect of these measures on urban air quality, especially particle concentrations and their size distributions, atmospheric particle size distributions (0.5-20 microm) obtained using an aerodynamic particle sizer (model 3321, TSI, USA) in June 2012 were analyzed. It was found that the particle number, surface area and volume concentrations for size range 0.5-10 microm were (15.0 +/- 2.1) cm(-3), (11.8 +/- 2.6) microm2/cm3 and (1.9 +/- 0.6) microm2/cm3, respectively, on the traffic-restricted day (Sunday), which is 63.2%, 53.0% and 47.2% lower than those on a normal Sunday. For number and surface area concentrations, the most affected size range was 0.5-0.7 and 0.5-0.8 microm, respectively, while for volume concentration, the most affected size ranges were 0.5-0.8, 1.7-2.0 and 5.0-5.4 microm. Number and volume concentrations of particles in size range 0.5-1.0 microm correlated well with the number of non-CNG (Compressed Natural Gas) powered vehicles, while their correlation with the number of CNG-powered vehicles was very low, suggesting that reasonable urban traffic controls along with vehicle technology improvements could play an important role in improving urban air quality.

Effect of short-term regional traffic restriction on urban submicron particulate pollution

During the 2013 and 2015 Lanzhou International Marathon Events (LIME1 and LIME2), the local government made a significant effort to improve traffic conditions and air quality by implementing traffic restriction measures. To fill the gap in information on the effect of short-period (several hours) traffic control on urban air quality, submicron particle size distributions and meteorological data were measured simultaneously during June 2013 and June 2015 in urban Lanzhou. The number and surface area concentrations of particles in the 100-200nm range declined by 67.2% and 65.0% for LIME1 due to traffic control, while they decreased by 39.2% and 37.1% for LIME2. The impact of traffic restriction on air pollution near the sampling site lagged behind the traffic control period for LIME2. In addition, the effect of traffic restriction on air pollution near the sampling site was dependent on the distance between the relative orientation of the sampling site and traffic-restricted zones, as well as meteorological conditions such as wind direction. The influence of traffic restrictions on the particle concentrations differed for different particle sizes. The size range most affected by traffic restriction was 60-200 and 60-300nm for number and surface area concentrations in the urban environment, respectively, while for the particle volume concentration it was the 100-600nm range. This study will provide a basis for implementation of future urban traffic-induced particulate pollution control measures.

Numerical simulation of the impact of reforestation on winter meteorology and environment in a semi-arid urban valley, Northwestern China.

Since 1999 Chinese government has made great effort to reforest the south and north mountains surrounding urban Lanzhou - a city located in a river valley, Northwestern China. Until 2009 obvious land use change occurred, with 69.2% of the reforested area been changed from grasslands, croplands, barren or sparsely vegetated land to closed shrublands and 20.6% from closed shrublands, grasslands, and croplands to forests. Reforestation changes land-surface properties, with possible impact on the evolution of atmospheric variables. To understand to what extent the local meteorology and environment could be affected by reforestation in winter, and through what processes, two sets of simulations were conducted using the Weather Research and Forecasting model (WRF) and the FLEXible PARTicle (FLEXPART) dispersion model for a control case with high-resolution remotely sensed land cover data for 2009 and a scenario assuming no reforestation since 1999. Results suggested that the changes in albedo, surface exchange coefficient and surface soil heat conductivity related to reforestation led to the changes in surface net radiation and surface energy partitioning, which in turn affected the meteorological fields and enhanced the mountain-valley wind circulation. Replacement of shrublands and grassland with forest in the south mountain through reforestation play a dominant role in the enhancement of mountain-valley wind circulation. Reforestation increased the amount of air exchanged between the valley and the outside during the day, with the largest hourly increase of 10% on calm weather days and a monthly mean hourly increase of 2% for the study period (Dec. 2009). Reforestation affected the spatial distribution of pollutants and slightly improved the urban air quality, especially in the eastern valley. Results from this study provide useful information for future urban air quality management and reforestation plan, and some experience for cities with similar situations in the world.

Characteristics of aerosol particle size distributions in urban Lanzhou, north-western China

Continuous particle size data (0.5–20μm) were collected using aerodynamic particle sizer (TSI 3321) at an urban site in Lanzhou, north western China from 1 st August to 31 st October. Variations of particle concentrations and general characteristics of particle size distributions were analyzed. The hourly averaged particle number, surface area and volume concentration are 108.1±92.2cm -3 ,282.9±267.9μm 2 cm -3 and 92.2±127.3μg 3 m -3 , respectively. Fine particles (0.5–2.5μm) accounted for 98.7%, 73.8% and 37.5% of the total particle number, surface area and volume concentrations in 0.5–20μm, respectively. The size distribution of number concentrations is unimodal with a maximum at 0.54–0.58μm, while that of the surface area and volume concentrations are bimodal. The main peak of surface area concentration appears near 0.63–0.67μm with a secondary peak at 3.79–4.07μm, and the main peak of volume concentration is at 4.7–5.1μm with a secondary peak near 0.67–0.72μm. K-means cluster analysis was used to group the particle volume size distributions into 7 clusters by their dominant mode and average concentration. Particle volume size distributions observed during dust storms and under dry and clear weather conditions were characterized by a single coarse mode, while particle volume size distributions affected by fog, smog and traffic related emissions were bimodal with peaks at accumulation mode and coarse mode, respectively.

Identification Of Potential Sources AndTransport Pathways Of Atmospheric PM10 UsingHYSPLIT And Hybrid Receptor Modelling InLanzhou, China

Three-dimensional 4-day backward trajectories arriving at Lanzhou 500m above ground level were calculated every 6 h using HYSPLIT-4 trajectory model for spring (March, April and May) 2001 to 2008. The 8 years were divided into two categories: high dust years (2001, 2002, 2004 and 2006) and low dust years (2003, 2005, 2007 and 2008). Cluster analysis, potential source contribution function (PSCF) model, and concentration-weighted trajectory (CWT) method were used to evaluate the transport pathways and potential source regions affecting PM10 loadings in Lanzhou in spring season. Results indicate that the western and the northwestern pathways, accounting respectively 33% and 19.4% of all trajectories, were major pathways leading to high springtime PM10 loadings in Lanzhou during high dust years. However, the major pathways were the western and the northern pathways in low dust years, accounting for 23.6% and 18%, respectively. There were six potential source regions affecting PM10 concentration in Lanzhou, e.g. the Tarim Basin and the Turpan Basin in Xinjiang, the Qaidam Basin in Qinghai, the Hexi Corridor in Gansu province, the desert and Gobi areas in the middle and west of Inner Mongolia, and the Loess Plateau in the middle of Shaanxi province and eastern Sichuan.