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This book examines air pollution of a big city using multi-year and multi-season data from ground-based air monitoring stations and satellite sounding data, which provides more clear and detailed information on the main sources of air pollution, the long-term trend of pollution, the influence of meteorological parameters on pollution levels, and trajectories of polluted air masses. For example, the book shows that particulate matter from local sources is transported from deserts to create air quality challenges. It also analyzes the effects of desert and semi-desert landscapes on high concentrations of pollutants.



Chapter 1. Introduction

Particulate matter (PM) is a widespread air pollutant, comprising a mixture of aerosols and liquid particles of the air in a suspended state. The indicators, commonly used to characterize the PM and relevant to health, include the mass concentration of particles with a diameter of less than 10 μm (PM10) and less than 2.5 μm (PM2.5) (Pope and Dockery 2006; Shiraiwa et al. 2012). PM2.5, often called as fine suspended particles, also includes ultrafine particles with a diameter of less than 0.1 μm (Mcmurry et al. 2004; US EPA 2010; Fann and Risley 2013). Table 1.1 shows this size categorization concept. The PM with a diameter from 0.1 to 1 μm can exist in the air for many days and weeks, respectively, and also can be subjected to cross-border transport of air for long distances.
Mikalai Filonchyk, Haowen Yan

Chapter 2. Location and Methods of Investigation

Lanzhou (N36°02′ and E103°48′) is located in Northwestern China. It is the capital of Gansu Province. Its population is 3.68 million people (in 2016). The total area is 13085.6 km2. It is located in the upper reaches of the Yellow River, near the border between the Tibetan Plateau, the Loess Plateau, and the Inner Mongolia Plateau (Fig. 2.1). Lanzhou is an industrial city with a developed chemical, oil, and flower industry, manufacturing of heavy equipment and coal, and production of electricity from plants. Lanzhou has a major railroad, road, and air hub for the whole Northwestern China. For this reason, Lanzhou became an important strategic and trading center on the Silk Road in ancient times.
Mikalai Filonchyk, Haowen Yan

Chapter 3. Research of Aerosol Optical Depth and Urban Heart Island in Lanzhou City by Means of Earth Remote Sensing

This chapter contains an analysis of the aerosol optical depth (AOD) and the urban heat island (UHI) basing on the images obtained from the Landsat and MODIS satellite (Terra/Aqua), using software ENVI5.1 and ArcGis10.2 and using an algorithm of the land surface temperature (LST) and normalized difference vegetation index (NDVI), to determine the urban heat island effect and the atmospheric pollution, to estimate the environmental situation in the city of Lanzhou completely, and to perform analysis and forecasting models of aerosol according to the NAAPS (Navy Aerosol Analysis and Prediction System), as well as to determine the characteristics of the vertical distribution of aerosols and dust using CALIPSO.
Mikalai Filonchyk, Haowen Yan

Chapter 4. Study of Air Pollution in Lanzhou City in 2003–2012

The data of the air pollutants used in this chapter are the monitoring data of the three SO2, NO2, and PM10 pollutants commonly used by the EPA. They are three pollutant indicators of monitoring data. According to the Chinese National Ambient Air Quality Standard (CNAAQS) GB3095–1996, as NAAQS GB3095–2012 was adopted in 2012, the study of the period 2003–2012 was using NAAQS GB3095–1996. The daily average concentration of major air pollutants of SO2, NO2, and PM10 and the air pollution index (API) during 2003-2012 were obtained from the Lanzhou Environmental Monitoring Center. Data on dust in the period 2003-2007 were obtained on the basis of monthly averages from automatic air quality monitoring stations located in the city. In addition, along with the “Lanzhou Environmental Quality Report” (2003–2007) and Ministry of Environmental Protection of the People’s Republic of China, the data center published daily air quality data for key cities and other resources. The China Meteorological Administration Lanzhou ground weather station used meteorological data, including temperature data, air pressure data, 6 h precipitation data, wind speed data, visibility data, and dew-point temperature data, as well as it used the conventional surface meteorological observation data daily eight times at the same time.
Mikalai Filonchyk, Haowen Yan

Chapter 5. Level of Pollutants Concentration in the Atmosphere of Lanzhou

We considered the data of gross pollutants and got an overall picture of air pollutions, largely originated from the emissions of industrial enterprises. A lot of low and irregular sources (transportation, boiler, heating, etc.) weren’t taken into account. However, in our opinion, the most objective and precise criterion for the air pollution was a concentration of impurities or the mass of the pollutants in the unit volume of air (mg/m3 or μg/m3).
Mikalai Filonchyk, Haowen Yan

Chapter 6. Analysis of the Causes of Influencing Factors of Air Pollution in Lanzhou

Dust weather is a kind of small probability and large hazard weather caused by the development of specific large-scale circulation background and specific weather system under specific geographical environment and underlying surface conditions, mainly in arid areas, in semi-arid areas, in desertified areas, and in farming-pastoral ecotone. Dust weather has a great destructive power, and the economic losses caused to the country and people by sand and dust weather every year are huge and incalculable (Liu et al. 2009; Qi et al. 2011). As a meteorological disaster and ecological environment problem, dust weather has already attracted the attention of scientists from all over the world. In different regions, dust weather has been studied from the aspects of synoptic, climatology, moving path, and transmission mechanism (Qian et al. 2004; Wang et al. 2005; Yin et al. 2007; Kaskaoutis et al. 2014; Dimitriou et al. 2017). Dust aerosol had a climate effect, simultaneously diffusing the incident visible light and the emergent long-wave radiation on the ground. On one hand, the dust aerosol directed scattering and absorption of radiation, resulting in direct climate effect (parasol effect). On the other hand, dust aerosol particles could change cloud microphysical processes, radiation characteristics, and precipitation, resulting in indirect climate effects (Su 2008). In addition, dust aerosols could also endanger people’s physical and mental health (Chen and Yang 2001; Meng et al. 2007) and have an impact on global ecological effects (Zhang et al. 1997; Jickells et al. 2005; Huang et al. 2007; Fan 2013; Ta et al. 2013).
Mikalai Filonchyk, Haowen Yan

Chapter 7. Conclusions and Prospects

Studies of air pollution, as well as of the way of pollutants entering the city in the period 2003–2016, were received basing on the monitoring of air quality data obtained from the Ministry of Environmental Protection of the People’s Republic of China, basing on satellite’s data of MODIS and Landsat 8, as well as on model-simulated data, which allowed us to draw the following conclusions:
In a region, average concentrations of PM exceeded the World Health Organization guideline values, which indicated a serious impact of concentrations on people and the environment of Lanzhou City. Seasonal and diurnal course of pollutants and pollution probabilities were characterized, respectively. They were characterized as the maximum in the winter and summer months in the afternoon. The annual course was largely determined by the seasonal mode of operation of the heat and power unit and vehicles. In summer months, the dependence of the increase in the concentrations of secondary pollutants on the rate of photochemical processes in the atmosphere was revealed. Daily variations in concentrations were associated with atmospheric turbulence.
Seasonal characteristic of air quality in Lanzhou had obvious differences. According to the seasonal distribution, the average concentration of PM2.5, of SO2, of NO2, and of CO quarter value had the same dynamics, i.e., winter > autumn > spring > summer. The mass concentration value of PM10 varied from heavy to light in seasons, winter > spring > autumn > summer, while difference between winter and spring concentration values was not high; spring dust weather increased concentration of PM10; however, strong wind was of importance in the removal of gaseous pollutants and PM2.5; thus the concentrations of PM2.5, of SO2, of NO2, and of CO in spring were a little lower than those in autumn.
The concentrations of all pollutants (in addition to the properties of their sources) significantly depended on the complex of meteorological quantities. It was necessary to attribute the following conditions to unfavorable meteorological conditions of dispersion of impurities in Lanzhou; on the surface of the Earth, unfavorable meteorological conditions of dispersion of impurities were the following: quiet or low wind, prevailing temperature gradients and wind direction, relative air humidity exceeding 60%, fogs and hazes at the height of the leading stream of 3 km, and speeds of west and northwest winds of 9–19 m/s. The range of increased concentrations of nitrogen oxides, maximum of sulfur, and carbon containing in urban atmosphere was mainly related to meteorological parameters. This correlation allowed us to construct a multidimensional regression model of atmospheric pollution.
Atmospheric pollution did not depend only on a complex of meteorological quantities, but it also affected the thermodynamic state of the air, creating “heat islands,” as a feedback. The data obtained from MODIS and Landsat 8 satellites revealed that microclimatic measurements allowed to register increasing air temperature in the city center and in the industrial zone by 1–3 °C comparing to its margins. “Heat island” led to an upward movement of air in the city center during the day, which helped to reduce the concentration of impurities near the surface of the Earth, to some extent. The nature of this phenomenon is related to both the direct release of heat into the atmosphere by municipal services and the radiation heating of the polluted air. The NDVI index indicated a lack of vegetation in urban area.
Aerosol optical depth data indicated that the environmental situation of the city had tended to improve, in comparison with other regions of the country, but it had still been at a level indicating the need for continuous monitoring of aerosols in the atmosphere of the city. Maximum aerosol contamination was observed in spring, due to sandstorms at the current time, indicating a high level of concentration of natural aerosols. The minimum one was registered in the summer-autumn period.
Except for local pollution sources, there are external sources of pollution located outside the study area and associated with passage of contaminants from elevated and desert regions of Western and Northern China, which are based on CALIPSO, OMI, NAAPS, and HYSPLIT and have three main trajectories. They are “north,” associated with air masses passing through the Gobi Desert, Republic of Mongolia, and Inner Mongolia; “northwest,” appearing mainly in the northwestern part of Xinjiang (Gurbantunggut Desert), where air mass go through Inner Mongolia and Ningxia to Lanzhou City; and “western,” originating in the western deserts (Taklamakan Desert in Xinjiang) and in the desert of Qaidam Вasin, where air masses pass through the Tibetan Plateau and Qinghai.
Studies of the dynamics of air pollution index (API in 2001–2012 and AQI in 2013−2016) in Lanzhou City show a tendency to reduce the level of pollution. The API value decreased continuously since 2001–2005; it increased suddenly in 2006. In 2007, the API value was the lowest in 11 years, accounting for 90, air quality achieved the best value, and then the API value increased year by year; by 2011 it fell to 95. From the API average, 2007, 2008, and 2011 were the best years of air quality in the last 11 years; the API average was 90−100. In 2006, there was the most serious pollution than in 6 years before and 6 years after, and the API standard deviation also reached the highest value. In the period of 2013–2016, the AQI gradually decreased and reached the lowest value in 16 years.
Mikalai Filonchyk, Haowen Yan


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