Fig 3. Fig 4. Histogram of daily SO 2 concentration distribution in Urumqi. Table 2 The Statistical characteristics of variation of main pollutant concentrations in Urumqi.
Fig 5. Fig 6. Fig 7. Frequency of pollution levels and cumulative percentage changes. Table 3 Correlation coefficients between main pollutants and meteorological factors in Urumqi. Fig 8. Fig 9. Weather conditions in Urumqi and its surrounding areas from November 25 th to December 2 nd , Fig Table 4 Distribution characteristics and average pollutant concentration of all backward trajectory. Discussion Several studies have shown that meteorological conditions have great influence on the concentration of atmospheric pollutants in cities with similar climate like Urumqi [ 34 — 36 ].
Data Availability All relevant data are within the manuscript and its Supporting Information files. References 1. Weiqi Z. Beijing: Science Press, Tan Y. Cities , Guan X. Habitat International , Guilin W. Environmental Science , Bongaarts J. Population and Development Review , Han L.
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Science of the total environment , Chin M. Fang L. Indoor air , Cheng Y. Ilten N. Environmental monitoring and assessment , Cuhadaroglu B. Energy and buildings , Cogliani E. Mamtimin B. Air usually cools with increasing height in the atmosphere. However, sometimes an upper air layer is warmer than a lower one.
This is called an inversion. In the Waikato, inversions often form on clear, calm nights when the ground cools rapidly. The upper layer of warm air acts like a lid. It traps a layer of cold air beneath it, and air contaminants, such as smoke from home fires, get trapped in the bottom, colder layer. These trapped contaminants can cause health and nuisance effects. Air contaminants build up when inversion layers form close to the ground mixing depth. Inversion layers are usually dispersed by wind or by warm air rising as the ground heats up.
But if the inversion layer stays in place for a long time pollutants can build up to high levels. Some towns in the region, such as Tokoroa and Te Kuiti, are especially prone to inversion layers. Human activities have had a significant impact on the air quality in this region. Urumqi is a key city in the core area of the Silk Road and an important economic center in Northwestern China. The urban environment is playing an increasingly important role in regional development.
The results showed that: 1 From to , the annual average of PM 2. The high-value areas of the "U-shaped" mode formed around the 50th day and the th day. It showed a U-shaped change trend during the year and the value was mainly distributed between 50 and Analysis showed that the PM 2.
It was shown that the pollution was a simple sandstorm process. Backward trajectory analysis clustered the airflow trajectories reaching Urumqi into 4 categories, and the trajectories from central Asia contributed the maximum values of average PM 2. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist. The ecological protection and environmental governance work left behind, which has caused a series of ecological and environmental problems [ 5 , 6 ]. Among these environmental problems, the air pollution in urban areas is one of the most serious ones. Since the appearance of the air pollution, there have been a large number of related studies try to explain the internal mechanism of air quality changes and provide feasible guidance and related suggestions for improving urban air quality [ 7 — 10 ].
In China, urban air pollution in different urban areas has different properties, but the coarse particulate matter PM 10 and fine particulate matter PM 2. It has been proved that the air quality in Chinese cities was generally improved, and the proportion of cities that meet air quality standards is rising [ 11 ]. The Beijing-Tianjin-Hebei region three provinces around Beijing, also named Jingjinji region was classified as the poorest air quality region in China and corresponding research have shown that high PM 2.
Based on analysis of the source of air pollution, two transmission paths of pollutants has been identified by Gao, Wang [ 13 ] and they also found that the presence of a pressure equalization field, a low-level inversion layer, and the southern warm and humid airflow provided favorable conditions for the formation of PM 2. The current studies corresponding to air quality of urban area in China mainly focused PM 10 and PM 2. It should be noted that the urbanization in inland regions also witnessed severe air pollution [ 16 ], a systematic analysis on the component, source and transmission path of urban air pollution is helpful to provide decision support for the government to make reasonable and effective air pollution control measures in these regions.
This study took the Urumqi city in recent years, the air pollution has become increasingly prominent in urban areas of the city in northwest part of China as an example to analyze the spatial-temporal characteristics of air pollution of typical inland city in northwest China. Specifically, we aimed to understanding the component, source and transmission path of the pollutant of the city and quantify the relationship between the Air Quality Index AQI with meteorological data based on air quality observation data collected from to The backward trajectory analysis was used to study the temporal variation of two severe and typical air pollution events that occurred from late November to early December in The city is experiencing rapid economic development and population growth at the present.
The GDP reached According to statistics yearbook , Urumqi reached Urumqi is surrounded by mountains in the east, south and west, with high terrain in the southeast and low in the northwest Fig 1B. The elevation of the city ranges from to meters with an average of meters in the urban area. It has a temperate continental arid climate. The mean temperature is 7. Map of study area a Location and distribution of monitoring stations; b Orographic distribution in Urumqi and its surrounding areas.
The AQI is a dimensionless indicator that quantitatively describes the air quality [ 17 — 20 ]. According to new ambient air quality standard of China GB , the index is the highest concentrations of PM 2.
The present study considered the AQI and the level of classification are shown in Table 1. AQI is widely used in China due to its simple definition [ 23 , 24 ]. The air quality monitoring data concentrations of PM 2.
Seven automatic air quality monitoring stations Training base, Toll station, Monitoring station, No. These seven air quality monitoring stations were classified according to functional areas, representing clean areas Training base and Farm of Xinjiang Academy of Agricultural Sciences , residential areas Toll station, Monitoring station and Railway Bureau , industrial areas Midong District Environmental Protection Bureau , and cultural and educational areas No.
When calculating the AQI, we used the daily average of these seven monitoring stations in Urumqi. The data was collected from January 1, to December 31, China Air Quality Monitoring and Analysis Platform is an automatic air quality monitoring system consists of monitoring stations, quality control laboratories and system support laboratories.
The quality control laboratories are responsible for the standardization, calibration and audit of monitoring equipment, ensuring the accurate transmission and storage of data. In addition, these laboratories also responsible for correcting and eliminating of the abnormal data missing data and errors caused by non-human factors such as instrument failure and power failure.
With the help of the laboratory, the system could provide accurate, reliable, continuous and timely environmental monitoring data including AQI, PM 2. In the system, all data are updated hourly and automatically. In addition, the MeteoInfo [ 26 ] software was used to analyze the backward trajectory and related statistical analysis. TrajStat trajectory model, a plug-in of MeteoInfo, is used for backward trajectory analysis, which is a professional model for calculating air mass trajectory and was widely used in the study of air pollutant transport and diffusion.
In this paper, we analyzed the backward trajectory of the air flow that affected two air pollution events in Urumqi the first one appeared in November 25 th and the second one started at 1 st and ended at 2 nd in December of In addition, the trajectory estimation time is 24h. Based on the simulation results, the air flow trajectories gathered in Urumqi were classified into four categories.
Furthermore, the different transport trajectories of PM 2. From to , the annual average concentrations of PM 2.
The concentrations of PM 10 and SO 2 showed a downward trend and reached the lowest values The inter-annual variation of NO 2 concentration fluctuated from to and the highest The inter-annual variations of PM 2.
The Urumqi is the remotest city from any ocean in the word and the feather of climate is short warm summers and long cold winters [ 27 ]. It determined that Urumqi has very high demands and consumption rates of fossil fuels for wintertime heating. Moreover, lots of industries and people were attracted to Urumqi from all parts of China with the strongly developing economy, enhanced the increasing consumption of energy by fossil fuels and the steady growing fleet of motor vehicles.
It is likely to explain the characteristics of pollutants PM 2. The monthly average concentrations of PM 2. During the study period from January, to December, , monthly concentration of PM 2. For CO, the highest concentration value 3.
In February , the concentrations of PM 10 reached its monthly highest value in five years with The monthly average concentration of SO 2 was obviously higher in than in other years especially in December. NO 2 concentration reached its highest value During our study period, the interannual and seasonal variations of PM 2. Additionally, the histogram Fig 4 demonstrated that the variation range of SO 2 concentration is shrinking, decreasing yearly and the concentration tends to be stable CV from It should be noted that coal combustion is one of the main sources of urban air pollution in most of cities at western of China [ 29 , 30 ].
In , aimed to reduce the degree of air pollution and improve the quality of human settlements, Urumqi launched 22 projects including energy conservation, air pollution prevention, and water pollution prevention, etc.
In terms of air pollution control, the corresponding projects including coal-to-gas a measure to change the energy structure , grid-connected boiler network compare to independent heating unit and relocation of polluting enterprises [ 31 ]. Due to these effective measures along with air pollution prevention measures implemented in the steel industries and enhancement of transformation and obsolescence of high-emission equipment , the concentration of SO 2 significantly declined from to , as shows in the present study and elsewhere [ 32 ].
Additionally, the meteorological condition also contributed to the high concentration of SO 2 , since when temperature is low, an inversion layer is easy to generate for a city located in valley, and the layer could hinder the diffusion of pollutants [ 33 ].
It is important to note although the concentrations of PM 2. This might be due to the measures primarily aimed at reducing pollutants emitted by industry and energy use that currently the local government enacted [ 32 ].
Since the air pollution is dominated by particulate pollutants PM 2. The daily concentration of PM 2. Among these six pollutants, PM 2. Interestingly, for concentrations of PM 2. AQI was relatively higher from November of first year to March of the following year and lower from April to October with a unimodal trend.
Majority of AQI value ranged between 51—, which denoted good air quality Fig 6. The proportion of days with good air quality AQI value ranged between 51— was Overall, number of days with excellent air quality AQI value less than 51 increased from to Moreover, number of days with severe air quality AQI value higher than was fewest among six air quality levels.
The light, moderate and heavy pollution the range of AQI value are —, — and —, respectively days may appear in any time of the year, but the possibility was relatively higher from November to May of next year.
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