**2. Instrument and system**

#### **2.1. Lidar**

addition, regional transportation contributes to combined pollution problems of atmos‐ phere, manifested by high-concentration fine particulate matter, low visibility, high-

Thus far, extensive studies using different methods have been conducted in China on atmos‐ pheric pollution [6-9]. For a better understanding of aerosol properties and their effect on environment, two major aerosol experiments were conducted in mainland China since 2004: (i) East Asian Study of Tropospheric Aerosols -An International Regional Experiment (EAST-AIRE) [10] and (ii) East Asian Study of Tropospheric Aerosols and Impact on Regional Climate (EAST-AIRC) [11]. Information on the properties of aerosols and their temporal and spatial distribution was obtained from studies using both short-term intensive field experiments and long-term operations, as well as modeling studies. Besides these filed experiments, lidar (LIght Ranging and Detection) and DOAS (Differential Absorption Spectroscopy) studies were conducted at several sites in China[12-18]. However, knowledge on the properties of aerosols and trace gases, particularly in the vertical dimension, in CCR China is rather scanty. Also, because of lack of real-time data on the quantum of pollutants discharged by major industrial parks, it is hard to resolve the task of pollution prevention. The present research was designed to take advantage of advanced environmental monitoring technical equipment (including Lidar[19,20], multi-axis DOAS[21,22], vehicle-mounted DOAS /infrared SOF[23-25], and meteorological parameter analyzer, etc.) to establish a stereoscopic observing system for key sources of regional pollution in CCR, China. The campaign was carried out from Dec 2013 to April 2014 in three key cities, namely Anyang (AY), Jiaozuo (JZ) and Sanmenxia (SMX). Continuous and automatic stereoscopic monitoring of primary pollution sources, transporta‐ tion of pollutants, emission characteristics of pollution from major industrial parks, as well as the transport conditions in the surrounding regions of pollution under specific meteorological conditions was carried out to obtain data that can help in air quality improvement and in development of forecast warning model, besides making up for the deficiency in current

concentration NO2 column, etc.

252 Current Air Quality Issues

ground monitoring system.

The scope of research resolves mainly into two parts:

FTIR and DOAS spectrum analytical methods.

**1.** Real-time monitoring of spatio-temporal distribution of regional haze pollution:

Representative monitoring points were identified in selected cities and surrounding areas along the direction of pollution transportation to measure spatial and temporal distribution characteristics of SO2, NO2 and aerosol particulate matter with lidar, MAX-DOAS, etc.

**2.** Real-time monitoring of disorganized pollutant discharge in key industrial park sources: VOC is an important precursor to the formation of photochemical smog. The type and volume of VOC discharge, as also of SO2 and NO2, play a significant role in pollution. Aiming at the key source areas of elevated discharge, vehicle-mounted DOAS and vehicle-mounted SOF-FTIR were utilized for mobile scanning measurement of discharged smoke plumes. Using the absorption characteristics of pollution gas molecules in infrared and ultraviolet spectrum, the concentration of exhaust gas was qualitatively and quantitatively determined through SOF-

The Lidar system, used for the study of spatial and temporal distribution of atmospheric particles, is shown in Fig 1; it adopts 532m Mie scattering and 532 polarization channels. Laser transmitter launches linear polarization lasers at 532nm by shooting vertically into atmosphere through beam expander, inversed mirror and quartz skylight. The laser pulse is scattered through air molecules, atmospheric aerosols or cloud, on its transmission route. The backwardscattered light firstly passes through skylight glass and then as parallel light through the diaphragm hole and convergent lens of the telescope. The converged parallel light is split into two beams by dichroic mirror: one is at 532nm, received by photomultiplier C after passing through optical filter; the other is at 355nm, whose vertical and parallel components are received respectively by A and B photomultipliers, after decomposition by an analyzer prism. After the conversion of optical signal into electrical signal by photomultiplier, the signal will be delivered to data acquisition system, where its ASCII code data file will be recorded and saved by main control computer.

**Figure 1.** System structure of lidar

#### **2.2. MAX-DOAS**

MAX-DOAS is a special type of DOAS technology, which uses characteristic absorption structure of trace gases (such as NO2, SO2, O3) in visible ultraviolet band for qualitative and quantitative analysis of gas. As a real-time and online measuring method, it is eminently suitable for remote sensing measurement of air pollution. Besides, the data on vertical column density of pollution gases acquired from this method can help in verifying satellite results [26]. MAX-DOAS receives scattered sunlight from telescopes at different elevations, as shown in Fig 2. Based on the characteristic absorption spectrums of pollution gas, it inverses the vertical column density of pollution gas and distribution profile of density. Besides, it acquires data on spatial distribution of pollution gas in atmosphere by measuring atmospheric absorption spectrums in zenith direction and several off-axis directions. During the monitoring process, the reflector orients itself to the north and is then driven by stepper motor to turn to 1°, 2°, 3°, 4°... 90° to finish one measurement cycle, thus realizing measurement of different angles. The schematic diagram of MAX-DOAS is presented below.

**Figure 2.** Schematic diagram of MAX-DOAS

#### **2.3. Vehicle-mounted DOAS**

With zenith-sky scattered light as the light source, vehicle-mounted DOAS technology is a kind of spectrum detection technology, which uses "fingerprint" absorption characteristics of optical radiation by gas molecule for qualitative and quantitative measurements of gas. The system includes mainly a spectrograph, a GPS system and a telescope [27]. As shown in Fig 3, the whole system is put on mobile platform and the telescope gathers solar spectrum along the measurement route. During operation, the band of spectrograph is fixed at 290nm~420nm (spectral region 130nm) as this band has strong SO2 and NO2 absorption structures. After the spectrograph delivers the gathered spectrum to computer for data processing, DOAS method is used to calculate the column density of pollution gas. Finally, density distribution of and NO2 absorption structures. After the spectrograph delivers the gathered spectrum to computer for

With zenith-sky scattered light as the light source, vehicle-mounted DOAS technology is a kind of spectrum detection technology, which uses "fingerprint" absorption characteristics of optical radiation by gas molecule for qualitative and quantitative measurements of gas. The system includes mainly a spectrograph, a GPS system and a telescope [27]. As shown in Fig 3, the whole system is put on mobile

pollution gas on the measuring route can be acquired by combing the information from GPS on longitude and latitude. data processing, DOAS method is used to calculate the column density of pollution gas. Finally, density distribution of pollution gas on the measuring route can be acquired by combing the

Figure 3 Structure and system of vehicle-mounted DOAS **Figure 3.** Structure and system of vehicle-mounted DOAS

information from GPS on longitude and latitude.

**2.3 Vehicle-mounted DOAS** 

#### **2.4 Satellite 2.4. Satellite**

**2.2. MAX-DOAS**

254 Current Air Quality Issues

MAX-DOAS is a special type of DOAS technology, which uses characteristic absorption structure of trace gases (such as NO2, SO2, O3) in visible ultraviolet band for qualitative and quantitative analysis of gas. As a real-time and online measuring method, it is eminently suitable for remote sensing measurement of air pollution. Besides, the data on vertical column density of pollution gases acquired from this method can help in verifying satellite results [26]. MAX-DOAS receives scattered sunlight from telescopes at different elevations, as shown in Fig 2. Based on the characteristic absorption spectrums of pollution gas, it inverses the vertical column density of pollution gas and distribution profile of density. Besides, it acquires data on spatial distribution of pollution gas in atmosphere by measuring atmospheric absorption spectrums in zenith direction and several off-axis directions. During the monitoring process, the reflector orients itself to the north and is then driven by stepper motor to turn to 1°, 2°, 3°, 4°... 90° to finish one measurement cycle, thus realizing measurement of different angles. The

**Stratosphere**

a=2° **Instrument**

With zenith-sky scattered light as the light source, vehicle-mounted DOAS technology is a kind of spectrum detection technology, which uses "fingerprint" absorption characteristics of optical radiation by gas molecule for qualitative and quantitative measurements of gas. The system includes mainly a spectrograph, a GPS system and a telescope [27]. As shown in Fig 3, the whole system is put on mobile platform and the telescope gathers solar spectrum along the measurement route. During operation, the band of spectrograph is fixed at 290nm~420nm (spectral region 130nm) as this band has strong SO2 and NO2 absorption structures. After the spectrograph delivers the gathered spectrum to computer for data processing, DOAS method is used to calculate the column density of pollution gas. Finally, density distribution of

**Boundary layer**

a=45°

a=20°

a=10° a=5°

schematic diagram of MAX-DOAS is presented below.

**Sun**

**Figure 2.** Schematic diagram of MAX-DOAS

**2.3. Vehicle-mounted DOAS**

Zenith

The spatial resolution of the OMI detector mounted on AURA satellite is 13 km×24 km [28]. NO2 VCD of troposphere, below the satellite orbit, can be obtained through DOAS inversion of measured spectrum. After differential and meshing treatment, NO2 VCD of each acquired orbit is integrated and then NO2 density distribution over the region obtained. Acquisition of regional density distribution data is significant for investigation of the processes of generation and transportation of pollution. For the present study, OMI Level 2 NO2 VCD data was adopted. From the weekly average between Nov and Dec, it was found that CCR pollution reached its peak in the third week. The spatial resolution of the OMI detector mounted on AURA satellite is 13 km×24 km [28]. NO2 VCD of troposphere, below the satellite orbit, can be obtained through DOAS inversion of measured spectrum. After differential and meshing treatment, NO2 VCD of each acquired orbit is integrated and then NO2 density distribution over the region is obtained. Acquisition of regional density distribution data is significant for investigation of the processes of gener‐ ation and transportation of pollution. For the present study, OMI Level 2 NO2 VCD data was adopted. From the weekly average between Nov and Dec, it was found that CCR pollution reached its peak in the third week.

#### **3.1 Stereoscopic monitoring of regular pollution gas**  (1) Comparison of areal distribution at the three sites **3. Results and discussion**

**3. Results and discussion** 

#### The average of the values obtained during measurement period at the three observation sites (AY, JZ and SMX) was taken as the areal distribution level of NO2 and SO2 in CCR (Fig 4). It can be **3.1. Stereoscopic monitoring of regular pollution gas**

observed that the average level of NO2 density at AY is 63.4\*1015molec./cm2 values at JZ and SMX. Density of NO2 in SMX is the lowest at its average level of **1.** Comparison of areal distribution at the three sites

35.3\*1015molec./cm2 . SO2, density at JZ is the highest at 149\*1015molec./cm2 , which is higher than that at AY and SMX. The average of the values obtained during measurement period at the three observation sites (AY, JZ and SMX) were taken as the areal distribution level of NO2 and SO2 in CCR (Fig 4). It can be observed that the average level of NO2 density at AY is 63.4\*1015molec./cm2 , which is higher than the values at JZ and SMX. Density of NO2 in SMX is the lowest at its average level of 35.3\*1015molec./cm2 . SO2, density at JZ is the highest at 149\*1015molec./cm2 , which is higher than that at AY and SMX.

4

, which is higher than the

**0**

**20**

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mo el c./cm2

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**150 180** SO2

vertical column density (VCD)

Figure 4 Characteristic contrasts about VCD (vertical column density) **Figure 4.** Characteristic contrasts about VCD (vertical column density) of SO2 and NO2 at the three sites of SO2 and NO2 at the three sites

#### of SO2 and NO2 at the three sites **2.** Results of monthly average variation (2) Results of monthly average variation

NO2

vertical column density (VCD)

(2) Results of monthly average variation The results obtained during the measurement period were used to calculate the averages of different months and to analyze variation trends of pollutant concentration. It can be observed from the calculation results (see Fig 5) that NO2 VCD (vertical column density) reached its peak in Dec and Jan, decreased from Feb onward, and then remained low between Mar and June. Monthly average of SO2 VCD at each station is shown in the figure below. It is obvious from the calculation results that, just as NO2, VCD of SO2 is high in winter; it reached its peak in Dec at AY, in Jan at SMX, and in Feb at JZ. It obviously decreased from Mar and thereafter remained low up to June. The results obtained during the measurement period were used to calculate the averages of different months and to analyze variation trends of pollutant concentration. It can be observed from the calculation results (see Fig 5) that NO2 VCD (vertical column density) reached its peak in Dec and Jan, decreased from Feb onward, and then remained low between Mar and June. Monthly average of SO2 VCD at each station is shown in the figure below. It is obvious from VCD of SO2 is high in winter just as NO2; it reached its peak in Dec at AY, in Jan at SMX, and in Feb at JZ. It obviously decreased from Mar and thereafter remained low up to June. The results obtained during the measurement period were used to calculate the averages of different months and to analyze variation trends of pollutant concentration. It can be observed from the calculation results (see Fig 5) that NO2 VCD (vertical column density) reached its peak in Dec and Jan, decreased from Feb onward, and then remained low between Mar and June. Monthly average of SO2 VCD at each station is shown in the figure below. It is obvious from the calculation results that, just as NO2, VCD of SO2 is high in winter; it reached its peak in Dec at AY, in Jan at SMX, and in Feb at JZ. It obviously decreased from Mar and thereafter remained low up to June.

Figure 5 Monthly average variations about VCD (vertical column density) of SO2 and NO2 in observing sites Figure 5 Monthly average variations about VCD (vertical column density) **Figure 5.** Monthly average variations about VCD (vertical column density) of SO2 and NO2 in observing sites

From an overview of the monthly averages discussed above, it can be concluded that the accumulation of pollutants had been rapid and heavy because of high discharge and unfavorable of SO2 and NO2 in observing sites From an overview of the monthly averages discussed above, it can be concluded that the accumulation of pollutants had been rapid and heavy because of high discharge and unfavorable From an overview of the monthly averages discussed above, it can be concluded that the accumulation of pollutants had been accumulated rapidly and heavily because of high discharge and unfavorable weather conditions in winter. With the end of hot season after

5

5

February, change of wind direction and increase in rainfall would start favoring diffusion and sedimentation of pollutants, and consequently reduction of pollutant concentration.

### **3.2. Stereoscopic monitoring of aerosols**

Monitoring of aerosols through lidar, from Nov 2013 to April 2014, (Fig 6) revealed that haze pollution was severe mainly from Nov. 2013 to Jan. 2014. Particularly from Dec 12 to Dec 20, and Jan 4 to Jan 17, the pollution lasted for almost half a month at AY and JZ. Overall air quality improved continuously, from Feb to June 2014, at AY, JZ and SMX. However, during wheat harvesting in June, because of straw burning, pollution levels increased at AY, JZ and SMX sites. The highest pollution levels were confined to the middle of June (14th-15th); the peak of aerosol extinction coefficients at AY, JZ and SMX sites are respectively 0.83km-1, 0.91km-1 and 0.66km-1. weather conditions in winter. With the end of hot season after February, change of wind direction and increase in rainfall would start favoring diffusion and sedimentation of pollutants, and consequently reduction of pollutant concentration. **3.2 Stereoscopic monitoring of aerosols**  Monitoring of aerosols through lidar, from Nov 2013 to April 2014, (Fig 6) revealed that haze pollution was severe mainly from Nov. 2013 to Jan. 2014. Particularly from Dec 12 to Dec 20, and Jan 4 to Jan 17, the pollution lasted for almost half a month at AY and JZ. Overall air quality improved continuously, from Feb to June 2014, at AY, JZ and SMX. However, during wheat harvesting in June, because of straw burning, pollution levels increased at AY, JZ and SMX sites. The highest pollution levels were confined to the middle of June (14th-15th); the peak of aerosol extinction

coefficients at AY, JZ and SMX sites are respectively 0.83km-1, 0.91km-1 and 0.66km-1.

Figure 6 Monthly aerosol distributions from lidar observation **Figure 6.** Monthly aerosol distributions from lidar observation

5

5

Figure 5 Monthly average variations about VCD (vertical column density) of SO2 and NO2 in observing sites

Figure 5 Monthly average variations about VCD (vertical column density) of SO2 and NO2 in observing sites

**Figure 5.** Monthly average variations about VCD (vertical column density) of SO2 and NO2 in observing sites

From an overview of the monthly averages discussed above, it can be concluded that the accumulation of pollutants had been rapid and heavy because of high discharge and unfavorable

From an overview of the monthly averages discussed above, it can be concluded that the accumulation of pollutants had been rapid and heavy because of high discharge and unfavorable

From an overview of the monthly averages discussed above, it can be concluded that the accumulation of pollutants had been accumulated rapidly and heavily because of high discharge and unfavorable weather conditions in winter. With the end of hot season after

**0**

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Nov. 2013

Nov. 2013

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**50**

**SO VCD (10**

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**15molec./cm2**

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**)**

**)**

**2** **100**

**100**

**150**

**150**

**200**

**200**

**250**

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> Nov. 2013

Nov. 2013

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**NO2 VCD (1015molec./cm2**

**)**

**)**

AY

(2) Results of monthly average variation

**2.** Results of monthly average variation

(2) Results of monthly average variation

JZ SMX

JZ SMX

2014 Dec. Jan. Feb. Mar. Apr. May Jun.

2014 Dec. Jan. Feb. Mar. Apr. May Jun.

AY

AY

**VCD( 1015molec./cm2**

Figure 4 Characteristic contrasts about VCD (vertical column density) of SO2 and NO2 at the three sites

Figure 4 Characteristic contrasts about VCD (vertical column density) of SO2 and NO2 at the three sites

The results obtained during the measurement period were used to calculate the averages of different months and to analyze variation trends of pollutant concentration. It can be observed from the calculation results (see Fig 5) that NO2 VCD (vertical column density) reached its peak in Dec and Jan, decreased from Feb onward, and then remained low between Mar and June. Monthly average of SO2 VCD at each station is shown in the figure below. It is obvious from the calculation results that, just as NO2, VCD of SO2 is high in winter; it reached its peak in Dec at AY, in Jan at SMX, and in Feb

The results obtained during the measurement period were used to calculate the averages of different months and to analyze variation trends of pollutant concentration. It can be observed from the calculation results (see Fig 5) that NO2 VCD (vertical column density) reached its peak in Dec and Jan, decreased from Feb onward, and then remained low between Mar and June. Monthly average of SO2 VCD at each station is shown in the figure below. It is obvious from the calculation results that, just as NO2, VCD of SO2 is high in winter; it reached its peak in Dec at AY, in Jan at SMX, and in Feb

The results obtained during the measurement period were used to calculate the averages of different months and to analyze variation trends of pollutant concentration. It can be observed from the calculation results (see Fig 5) that NO2 VCD (vertical column density) reached its peak in Dec and Jan, decreased from Feb onward, and then remained low between Mar and June. Monthly average of SO2 VCD at each station is shown in the figure below. It is obvious from VCD of SO2 is high in winter just as NO2; it reached its peak in Dec at AY, in Jan at SMX, and in Feb at JZ. It obviously decreased from Mar and thereafter remained low up to June.

at JZ. It obviously decreased from Mar and thereafter remained low up to June.

at JZ. It obviously decreased from Mar and thereafter remained low up to June.

**Figure 4.** Characteristic contrasts about VCD (vertical column density) of SO2 and NO2 at the three sites

 AY JZ SMX

 AY JZ SMX **)**

**VCD(** 

**1015molec./cm2**

**)**

JZ SMX

JZ SMX

2014 Dec. Jan. Feb. Mar. Apri. May Jun.

2014 Dec. Jan. Feb. Mar. Apri. May Jun.

 AY JZ SMX

 AY JZ SMX

SO2

SO2

vertical column density (VCD)

vertical column density (VCD)

vertical column density (VCD)

vertical column density (VCD)

NO2

NO2

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256 Current Air Quality Issues

mo el c./cm2

)

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**100**

Pollution transportation (Nov 25, 2013-Nov 27, 2013) occurred at AY, JZ and SMX also, but the pollution characteristics and sources were different. Among these three sites, sand dust transportation in northwest direction affected SMX the most. Because of sand dust transportation, large particle concentration in air increased and RH decreased rapidly (at SMX, RH=78% on Dec 25th and RH=32% on Dec 27th). Repeated monitoring of local pollutions (Dec 12, 2013-Dec 17, 2013; Jan 8, 2014-Jan 11, 2014; Jan 27, 2014-Jan 31, 2014; Feb 16, 2014-Feb 18, 2014; Apr 10, 2014-Apr 13, 2014) reveal that near-ground pollution at these three sites came mainly from local pollution (industrial emission, motor vehicle exhaust and coal combustion) and fire coal transportation to some northern cities in the southeast direction. By the end of Jan 2014, local pollution aggravated because of discharge from firecrackers during spring festival. The pollution at higher levels in the air above 1km came mainly from the northwest. Pollution transportation (Nov 25, 2013-Nov 27, 2013) also occurred at AY, JZ and SMX, but the pollution characteristics and sources were different. Among these three sites, sand dust transportation in northwest direction affected SMX the most. Because of sand dust transportation, large particle concentration in air increased and RH decreased rapidly (at SMX, RH=78% on Dec 25 and RH=32% on Dec 27). Repeated monitoring of local pollu‐ tions (Dec 12, 2013-Dec 17, 2013; Jan 8, 2014-Jan 11, 2014; Jan 27, 2014-Jan 31, 2014; Feb 16, 2014-Feb 18, 2014; Apr 10, 2014-Apr 13, 2014) reveal that near-ground pollution at these three sites came mainly from local pollution (industrial emission, motor vehicle exhaust and coal combustion) and fire coal transportation from southern cities in the southeast

6

In conclusion, it emerges that particulate pollution occurred almost simultaneously at the three sites AY, JZ and SMX. Local pollution (local source) is typical of AY, and near-ground pollution of JZ, where higher pollution levels because of industrial emission are also common. Local pollution was direction. By the end of Jan 2014, local pollution aggravated because of discharge from firecrackers during spring festival. The pollution at higher levels in the air above 1km came mainly from the northwest.

In conclusion, it emerges that particulate pollution occurred almost simultaneously at the three sites AY, JZ and SMX. Local pollution (local source) is typical in AY, and near-ground pollution in JZ is higher due to the local industrial emission. Local pollution was relatively slighter in SMX, but it can be easily aggravated by northwest sand dust transportation. Sand dust pollution at AY manifests as superposed locally raised dust over northwest sand dust. In CCR, the ground weather conditions of uniform-pressure were conducive to pollutant diffusion. This weather had lower ground pressure field, lower ground and low-altitude wind speeds, and even calm wind sometimes. These were often accompanied by stronger radiation inversion or low-altitude temperature inversion that is difficult to eliminate. The structure of lower atmosphere layer was stable and might contribute to higher pollution.

#### **3.3. Vehicle-mounted monitoring of pollutant discharge in some representative cities and key industrial parks**

Quantitative modeling was done in some cities to evaluate the influence of key industries and industrial parks on ambient air quality, especially PM10. Vehicle-mounted DOAS system was used for monitoring industrial parks in both winter (Dec 2013) and summer (May-June, 2014) by way of acquiring data on spatial distribution of urban VOD of SO2 and NO2, emission characteristics of SO2 and NO2 in key industrial sources, as well as pollution transportation parameters under specific meteorological conditions.

At AY, the results obtained in winter and summer is similar. The concentration of SO2 and NO2 was caused mainly by the discharge from steelworks factories. However, observations during southeast/south winds in summer show that the concentration of SO2, in the southwestnorthwest section of the measurement route, was high. This indicates that sporadic small-scale industrial discharge occurred beyond southwest-northwest section (south and southwest of AY), which was not found during observations in winter. Judging from the relative geographic positions of steelworks and urban area at AY, as well as forward track model of wind field (Fig 7), it can be concluded that during northwest winds, discharge of AY steelworks had great influence on the air quality of urban area in AY.

Mean values per hour (MV/H), obtained from ground monitoring of SO2 at monitoring point of environmental protection agency in AY from May 18 to May 20 are shown in Fig 8. From these results, it can be observed that ground concentration of SO2 in urban area increased during northwest winds. At the same time, it is also found that during southeast winds, ground concentration of SO2 in urban area was high at about 11a.m. on May 18, when the observation time was just the same as that of third auxiliary chart in Figure 9. It is concluded that, under southeast wind field, sporadic pollution in the southwest and south, beyond measurement area, had great influence on the air quality of main urban area in AY.

A Comprehensive Research of Atmospheric Haze by Optical Remote Sensing in Central China Region (CCR) http://dx.doi.org/10.5772/59753 259

direction. By the end of Jan 2014, local pollution aggravated because of discharge from firecrackers during spring festival. The pollution at higher levels in the air above 1km came

In conclusion, it emerges that particulate pollution occurred almost simultaneously at the three sites AY, JZ and SMX. Local pollution (local source) is typical in AY, and near-ground pollution in JZ is higher due to the local industrial emission. Local pollution was relatively slighter in SMX, but it can be easily aggravated by northwest sand dust transportation. Sand dust pollution at AY manifests as superposed locally raised dust over northwest sand dust. In CCR, the ground weather conditions of uniform-pressure were conducive to pollutant diffusion. This weather had lower ground pressure field, lower ground and low-altitude wind speeds, and even calm wind sometimes. These were often accompanied by stronger radiation inversion or low-altitude temperature inversion that is difficult to eliminate. The structure of lower

**3.3. Vehicle-mounted monitoring of pollutant discharge in some representative cities and**

Quantitative modeling was done in some cities to evaluate the influence of key industries and industrial parks on ambient air quality, especially PM10. Vehicle-mounted DOAS system was used for monitoring industrial parks in both winter (Dec 2013) and summer (May-June, 2014) by way of acquiring data on spatial distribution of urban VOD of SO2 and NO2, emission characteristics of SO2 and NO2 in key industrial sources, as well as pollution transportation

At AY, the results obtained in winter and summer is similar. The concentration of SO2 and NO2 was caused mainly by the discharge from steelworks factories. However, observations during southeast/south winds in summer show that the concentration of SO2, in the southwestnorthwest section of the measurement route, was high. This indicates that sporadic small-scale industrial discharge occurred beyond southwest-northwest section (south and southwest of AY), which was not found during observations in winter. Judging from the relative geographic positions of steelworks and urban area at AY, as well as forward track model of wind field (Fig 7), it can be concluded that during northwest winds, discharge of AY steelworks had great

Mean values per hour (MV/H), obtained from ground monitoring of SO2 at monitoring point of environmental protection agency in AY from May 18 to May 20 are shown in Fig 8. From these results, it can be observed that ground concentration of SO2 in urban area increased during northwest winds. At the same time, it is also found that during southeast winds, ground concentration of SO2 in urban area was high at about 11a.m. on May 18, when the observation time was just the same as that of third auxiliary chart in Figure 9. It is concluded that, under southeast wind field, sporadic pollution in the southwest and south, beyond measurement

atmosphere layer was stable and might contribute to higher pollution.

parameters under specific meteorological conditions.

influence on the air quality of urban area in AY.

area, had great influence on the air quality of main urban area in AY.

mainly from the northwest.

258 Current Air Quality Issues

**key industrial parks**

**Figure 7.** Spatial distribution of SO2 and wind field track superposition at AY under northwest wind field

**Figure 8.** MV/H about ground concentration of SO2 in monitoring point at AY

**Figure 9.** Spatial distribution changes of SO2 during the wind filed transformation process at AY steelworks

#### **3.4. Analysis of the typical haze process**

Haze episode (Dec 12, 2013-Dec, 16, 2013)

From Dec 12, 2013 to Dec 16, 2013, a typical haze phenomenon was observed at AY, JZ and SMX, when the pollution was mainly local. Under the influence of regional weak wind field, the distribution range of local pollution was large and the duration long, but intermittent. Besides, the extinction coefficient of aerosol and concentration of NO2 reflect a completely accumulative, rising, sustaining and stable process. Based on the distribution range and strength, two main phases were identified: generation phase of local pollution and pollution stabilization phase.

#### **1. Aerosols**

AY city: Since the afternoon of Dec 12, 2013, the pollutants gradually rose to 1.9 km and then began descending on Dec 13 (Fig 10). In the afternoon of Dec 14, it again started rising, but this time the height was lower than that on Dec 13. During Dec 15-16, near-ground pollution intensified and lasted for a long time, with the maximum value of extinction coefficient reaching 0.87km-1 (see Fig 11).


JZ city: The height of pollutants started rising from the afternoon of Dec 12 and the average of extinction coefficient was higher than that at AY (Fig 12). The height of daytime pollutants dropped on Dec 13, but it began rising again in the morning of Dec 14; near-ground pollution continued on Dec 15-16 (Fig 13).

A Comprehensive Research of Atmospheric Haze by Optical Remote Sensing in Central China Region (CCR) http://dx.doi.org/10.5772/59753 261

**Figure 10.** Spatial distributions of aerosols from Dec 12 to Dec 14 at AY, CCR

**Figure 11.** Spatial distributions of aerosols from Dec 15 to Dec 16 at AY, CCR

**c.** Formative period of haze (Dec 12-14)

**Figure 9.** Spatial distribution changes of SO2 during the wind filed transformation process at AY steelworks

From Dec 12, 2013 to Dec 16, 2013, a typical haze phenomenon was observed at AY, JZ and SMX, when the pollution was mainly local. Under the influence of regional weak wind field, the distribution range of local pollution was large and the duration long, but intermittent. Besides, the extinction coefficient of aerosol and concentration of NO2 reflect a completely accumulative, rising, sustaining and stable process. Based on the distribution range and strength, two main phases were identified: generation phase of local pollution and pollution

AY city: Since the afternoon of Dec 12, 2013, the pollutants gradually rose to 1.9 km and then began descending on Dec 13 (Fig 10). In the afternoon of Dec 14, it again started rising, but this time the height was lower than that on Dec 13. During Dec 15-16, near-ground pollution intensified and lasted for a long time, with the maximum value of extinction coefficient

JZ city: The height of pollutants started rising from the afternoon of Dec 12 and the average of extinction coefficient was higher than that at AY (Fig 12). The height of daytime pollutants dropped on Dec 13, but it began rising again in the morning of Dec 14; near-ground pollution

**3.4. Analysis of the typical haze process**

Haze episode (Dec 12, 2013-Dec, 16, 2013)

stabilization phase.

reaching 0.87km-1 (see Fig 11).

continued on Dec 15-16 (Fig 13).

**a.** Formative period of haze (Dec 12-14)

**b.** Stable formation of pollution (Dec 15-16)

**1. Aerosols**

260 Current Air Quality Issues

**Figure 12.** Spatial distributions of aerosols from Dec 12 to Dec14 at JZ, CCR

#### **d.** Stable formation of pollution (Dec 15-16)

**Figure 13.** Spatial distributions of aerosols from Dec 15 to Dec16 at JZ, CCR

SMX city: Local pollution was noticed from the afternoon of Dec 12; the height of the pollutants rose gradually from the evening of Dec 13 and the average of extinction coefficient was 0.39km-1 (Fig 14). High concentration pollution was confined to the period from the evening of Dec 13 to evening of Dec 14. No obvious change of extinction coefficient profile is observed on Dec 15-16; the height of the pollutants was below 1.2km (Fig 15).

**e.** Formative period of local pollution (Dec 12-14)

**Figure 14.** Spatial distributions of aerosols from Dec 12 to Dec 14 at SMX, CCR

**f.** Stable formation of pollution (Dec 15-16)

#### **2. Pollution gas**

During the haze period from Dec 14 to Dec 20, the whole process of NO2 accumulation and dispersion, as observed by MAX-DOAS, is depicted in Figs 16 & 17. The changes in pollution concentration are most evident at AY, where the concentrate started rising since Dec 12 and A Comprehensive Research of Atmospheric Haze by Optical Remote Sensing in Central China Region (CCR) http://dx.doi.org/10.5772/59753 263

**Figure 15.** Spatial distributions of aerosols from Dec 15 to Dec16 at SMX, CCR

**d.** Stable formation of pollution (Dec 15-16)

262 Current Air Quality Issues

**Figure 13.** Spatial distributions of aerosols from Dec 15 to Dec16 at JZ, CCR

**e.** Formative period of local pollution (Dec 12-14)

on Dec 15-16; the height of the pollutants was below 1.2km (Fig 15).

**Figure 14.** Spatial distributions of aerosols from Dec 12 to Dec 14 at SMX, CCR

**f.** Stable formation of pollution (Dec 15-16)

**2. Pollution gas**

SMX city: Local pollution was noticed from the afternoon of Dec 12; the height of the pollutants rose gradually from the evening of Dec 13 and the average of extinction coefficient was 0.39km-1 (Fig 14). High concentration pollution was confined to the period from the evening of Dec 13 to evening of Dec 14. No obvious change of extinction coefficient profile is observed

During the haze period from Dec 14 to Dec 20, the whole process of NO2 accumulation and dispersion, as observed by MAX-DOAS, is depicted in Figs 16 & 17. The changes in pollution concentration are most evident at AY, where the concentrate started rising since Dec 12 and continued until Dec 14; thereafter, it remained at a high level. However, the increase at JZ was relatively slow. The concentration of both NO2 and SMX NO2 increased obviously on Dec 14 and again, and this time is more higher on December 18. On the contrary, the concentrations of NO2 at AY and JZ began decreasing. The haze formation was caused mainly by internal and northern atmosphere transmission; besides, the obstruction to the airflow in the north militated against pollutant diffusion and instead favored accumulation. Air humidity, coupled with the convergence of cold and hot airflows, contributed to the process of haze formation.

**Figure 16.** NO2 VCD from Dec 10 to 16 in the observing sites

#### **3. Meteorological conditions**

On Dec 15, the average wind speed was 4.1 m/s and the temperature was1.8°C at the height of 1000m. The prevailing wind was northwest wind (Fig 18). The high-altitude west wind was

**Figure 17.** NO2 profiles from Dec 12 to 16 at AY, CCR

affected by the downdraft in leeward slope terrain, leading to the convergence of the regional weak wind field pollutants, and finally to heavy pollution. downdraft in leeward slope terrain, leading to the convergence of the regional weak wind field pollutants, and finally to heavy pollution.

Figure 18 Meteorological conditions and wind rose diagram **Figure 18.** Meteorological conditions and wind rose diagram

evening of June13 the pollution became serious.

**(4) Satellite** 

From the HYSPLIT backward trajectory model in Fig 19 [29], the pollution at the three observation points was found to be mainly from the northwest. The main pollution source could be from burning of fossil fuels or bio-fuels, aided by the continental airstream. By noon on Nov 25, there was evident increase in pollutants at both AY and JZ. Subsequently, until the evening on Dec 26, at both the observation points, the pollutants decreased and then again

Figure 19 Backward trajectories from Hysplit

From the HYSPLIT backward trajectory model in Fig 19 [29], the pollution at the three observation points was found to be mainly from the northwest. The main pollution source could be from burning of fossil fuels or bio-fuels, aided by the continental airstream. By noon on Nov 25, there was evident increase in pollutants at both AY and JZ. Subsequently, until the evening on Dec 26, at both the observation points, the pollutants decreased and then again increased and stabilized. The overall aerosol extinction coefficient at AY was higher than that at JZ, the peak value at the former being 0.87km-1 and at the latter 0.51km-1. The pollution layer was below 1.9 km, corresponding to the pollutant transmission layer in a low level jet (LLJ) [30] of stable or neutral boundary layer. For two days, it was observed that the height of the mixing layer grew linearly over time. When the height of the mixing layer grows to the height of the pollutant transmission belt in the nocturnal boundary layer, the vertical mixing effect would result in rapid concentration of pollutants on the ground. Therefore, there was increase in aerosol values, as well as in local pollutants discharge during the days; the downward transmission from the higher layers was also an important factor. Compared with AY and JZ, the air at SMX was cleaner and the height of pollutants was lower at 1.2 km below, but by the

12

**Figure 19.** Backward trajectories from Hysplit

increased and stabilized. The overall aerosol extinction coefficient at AY was higher than that at JZ, and the peal values are 0.87km-1 and 0.51km-1, respectively. The pollution layer was below 1.9 km, corresponding to the pollutant transmission layer in a low level jet (LLJ) [30] of stable or neutral boundary layer. For two days, it was observed that the height of the mixing layer grew linearly over time. When the height of the mixing layer grows to the height of the pollutant transmission belt in the nocturnal boundary layer, the vertical mixing effect would result in rapid concentration of pollutants on the ground. Therefore, there was increase in aerosol values, as well as in local pollutants discharge during the days; the downward transmission from the higher layers was also an important factor. Compared with AY and JZ, the air at SMX was cleaner and the height of pollutants was lower at 1.2 km below, but by the evening of June13 the pollution became serious.

#### **4. Satellite**

affected by the downdraft in leeward slope terrain, leading to the convergence of the regional

downdraft in leeward slope terrain, leading to the convergence of the regional weak wind field

Figure 18 Meteorological conditions and wind rose diagram

From the HYSPLIT backward trajectory model in Fig 19 [29], the pollution at the three observation points was found to be mainly from the northwest. The main pollution source could be from burning of fossil fuels or bio-fuels, aided by the continental airstream. By noon on Nov 25, there was evident increase in pollutants at both AY and JZ. Subsequently, until the evening on Dec 26, at both the observation points, the pollutants decreased and then again

Figure 19 Backward trajectories from Hysplit

From the HYSPLIT backward trajectory model in Fig 19 [29], the pollution at the three observation points was found to be mainly from the northwest. The main pollution source could be from burning of fossil fuels or bio-fuels, aided by the continental airstream. By noon on Nov 25, there was evident increase in pollutants at both AY and JZ. Subsequently, until the evening on Dec 26, at both the observation points, the pollutants decreased and then again increased and stabilized. The overall aerosol extinction coefficient at AY was higher than that at JZ, the peak value at the former being 0.87km-1 and at the latter 0.51km-1. The pollution layer was below 1.9 km, corresponding to the pollutant transmission layer in a low level jet (LLJ) [30] of stable or neutral boundary layer. For two days, it was observed that the height of the mixing layer grew linearly over time. When the height of the mixing layer grows to the height of the pollutant transmission belt in the nocturnal boundary layer, the vertical mixing effect would result in rapid concentration of pollutants on the ground. Therefore, there was increase in aerosol values, as well as in local pollutants discharge during the days; the downward transmission from the higher layers was also an important factor. Compared with AY and JZ, the air at SMX was cleaner and the height of pollutants was lower at 1.2 km below, but by the

12

weak wind field pollutants, and finally to heavy pollution.

**Figure 17.** NO2 profiles from Dec 12 to 16 at AY, CCR

**Figure 18.** Meteorological conditions and wind rose diagram

evening of June13 the pollution became serious.

**(4) Satellite** 

pollutants, and finally to heavy pollution.

264 Current Air Quality Issues

From the satellite results in Fig 20, it can be observed that high NO2 VCD values existed during the haze period. From the daily variations in NO2 VCD values between Nov and Dec at AY, JZ and SMX (seen in Fig 21), it can be seen that the results at AY clearly indicate a relation between NO2 VCD values and haze. For example, at AY, the daily average value of NO2 VCD 6 0

Figure 20 NO2 VCD distribution result chart from Nov 11 to Dec 20 in CCR during haze period **Figure 20.** NO2 VCD distribution result chart from Nov 11 to Dec 20 in CCR during haze period %&?>20<\$%&?>in<\$%&?>CCR<\$%&?>during<\$%&?>haze<\$%&?>period

Figure 19. Backward<\$%&?>trajectories<\$%&?>from<\$%&?>Hysplit

From<\$%&?>the<\$%&?>HYSPLIT<\$%&?>backward<\$%&?>trajectory<\$%&?>model<\$%&?>in<\$%&?>Fig<\$%&?>19<\$% &?>[29],<\$%&?>the<\$%&?>pollution<\$%&?>at<\$%&?>the<\$%&?>three<\$%&?>observation<\$%&?>points<\$%&?>was<\$% &?>found<\$%&?>to<\$%&?>be<\$%&?>mainly<\$%&?>from<\$%&?>the<\$%&?>northwest.<\$%&?>The<\$%&?>main<\$%&? >pollution<\$%&?>source<\$%&?>could<\$%&?>be<\$%&?>from<\$%&?>burning<\$%&?>of<\$%&?>fossil<\$%&?>fuels<\$%& ?>or<\$%&?>bio-fuels,<\$%&?>aided<\$%&?>by<\$%&?>the<\$%&?>continental<\$%&?>airstream.<\$%&?>By<\$%&?>noon<\$ %&?>on<\$%&?>Nov<\$%&?>25,<\$%&?>there<\$%&?>was<\$%&?>evident<\$%&?>increase<\$%&?>in<\$%&?>pollutants<\$% &?>at<\$%&?>both<\$%&?>AY<\$%&?>and<\$%&?>JZ.<\$%&?>Subsequently,<\$%&?>until<\$%&?>the<\$%&?>evening<\$%& ?>on<\$%&?>Dec<\$%&?>26,<\$%&?>at<\$%&?>both<\$%&?>the<\$%&?>observation<\$%&?>points,<\$%&?>the<\$%&?>pollu tants<\$%&?>decreased<\$%&?>and<\$%&?>then<\$%&?>again<\$%&?>increased<\$%&?>and<\$%&?>stabilized.<\$%&?>The <\$%&?>overall<\$%&?>aerosol<\$%&?>extinction<\$%&?>coefficient<\$%&?>at<\$%&?>AY<\$%&?>was<\$%&?>higher<\$%& ?>than<\$%&?>that<\$%&?>at<\$%&?>JZ,<\$%&?>the<\$%&?>peak<\$%&?>value<\$%&?>at<\$%&?>the<\$%&?>former<\$%&? >being<\$%&?>0.87km-1<\$%&?>and<\$%&?>at<\$%&?>the<\$%&?>latter<\$%&?>0.51km-1.<\$%&?>The<\$%&?>pollution<\$%&?>l ayer<\$%&?>was<\$%&?>below<\$%&?>1.9<\$%&?>km,<\$%&?>corresponding<\$%&?>to<\$%&?>the<\$%&?>pollutant<\$%& ?>transmission<\$%&?>layer<\$%&?>in<\$%&?>a<\$%&?>low<\$%&?>level<\$%&?>jet<\$%&?>(LLJ)<\$%&?>[30]<\$%&?>of<\$%&?> stable<\$%&?>or<\$%&?>neutral<\$%&?>boundary<\$%&?>layer.<\$%&?>For<\$%&?>two<\$%&?>days,<\$%&?>it<\$%&?>was <\$%&?>observed<\$%&?>that<\$%&?>the<\$%&?>height<\$%&?>of<\$%&?>the<\$%&?>mixing<\$%&?>layer<\$%&?>grew<\$ %&?>linearly<\$%&?>over<\$%&?>time.<\$%&?>When<\$%&?>the<\$%&?>height<\$%&?>of<\$%&?>the<\$%&?>mixing<\$%& ?>layer<\$%&?>grows<\$%&?>to<\$%&?>the<\$%&?>height<\$%&?>of<\$%&?>the<\$%&?>pollutant<\$%&?>transmission<\$% &?>belt<\$%&?>in<\$%&?>the<\$%&?>nocturnal<\$%&?>boundary<\$%&?>layer,<\$%&?>the<\$%&?>vertical<\$%&?>mixing< \$%&?>effect<\$%&?>would<\$%&?>result<\$%&?>in<\$%&?>rapid<\$%&?>concentration<\$%&?>of<\$%&?>pollutants<\$%&? >on<\$%&?>the<\$%&?>ground.<\$%&?>Therefore,<\$%&?>there<\$%&?>was<\$%&?>increase<\$%&?>in<\$%&?>aerosol<\$% &?>values,<\$%&?>as<\$%&?>well<\$%&?>as<\$%&?>in<\$%&?>local<\$%&?>pollutants<\$%&?>discharge<\$%&?>during<\$ %&?>the<\$%&?>days;<\$%&?>the<\$%&?>downward<\$%&?>transmission<\$%&?>from<\$%&?>the<\$%&?>higher<\$%&?>l ayers<\$%&?>was<\$%&?>also<\$%&?>an<\$%&?>important<\$%&?>factor.<\$%&?>Compared<\$%&?>with<\$%&?>AY<\$%&

%&?>by<\$%&?>the<\$%&?>evening<\$%&?>of<\$%&?>June13<\$%&?>the<\$%&?>pollution<\$%&?>became<\$%&?>serious.

values and haze. For example, at AY, the daily average value of NO2 VCD during Nov 1-20 was 3.32×1016molec./cm2 . For the first haze period during Nov 21-23, the daily average value was Figure 21. NO2<\$%&?>VCD<\$%&?>change<\$%&?>chart<\$%&?>detected<\$%&?>by<\$%&?>OMI<\$%&?>satellite<\$%&?>from<\$%&?>No **Figure 21.** NO2 VCD change chart detected by OMI satellite from Nov 1 to Dec 20

during Nov 1-20 was 3.32×1016molec./cm2 . For the first haze period during Nov 21-23, the daily average value was 8.37×1016 molecule/cm2 , which was 2.5 times more than the normal average value. For the second haze period on Dec 8, it was 5.8×1017 molecule/cm2 , which was the highest and 18 times more than the normal average value. For the third haze period during Dec 16-17, it was 1.57×1017 molecule/cm2 , which was 4.7 times more than the average value. From the values of NO2 during these three haze periods, which were multiple times more than the average value, it clearly follows that there exists certain relation between NO2 and haze, and that high NO2 VCD values contribute to hazy weather. 8.37×1016 molecule/cm2 , which was 2.5 times more than the normal average value. For the second haze period on Dec 8, it was 5.8×1017 molecule/cm2 , which was the highest and 18 times more than the normal average value. For the third haze period during Dec 16-17, it was 1.57×1017 molecule/cm2 which was 4.7 times more than the average value. From the values of NO2 during these three haze periods, which were multiple times more than the average value, it clearly follows that there exists certain relation between NO2 and haze, and that high NO2 VCD values contribute to hazy weather. **3.5 Typical straw burning process analysis (June 12-16, 2014) (1) Aerosols**  v<\$%&?>1<\$%&?>to<\$%&?>Dec<\$%&?>20 From<\$%&?>the<\$%&?>satellite<\$%&?>results<\$%&?>in<\$%&?>Fig<\$%&?>20,<\$%&?>it<\$%&?>can<\$%&?>be<\$%&?>ob served<\$%&?>that<\$%&?>high<\$%&?>NO2<\$%&?>VCD<\$%&?>values<\$%&?>existed<\$%&?>during<\$%&?>the<\$%&?> haze<\$%&?>period.<\$%&?>From<\$%&?>the<\$%&?>daily<\$%&?>variations<\$%&?>in<\$%&?>NO2<\$%&?>VCD<\$%&?>v alues<\$%&?>between<\$%&?>Nov<\$%&?>and<\$%&?>Dec<\$%&?>at<\$%&?>AY,<\$%&?>JZ<\$%&?>and<\$%&?>SMX<\$%&

Wheat harvesting from June 12 to June 16 in early summer of 2014, straw burning contributed to

,

#### **3.5. Typical straw burning process analysis (June 12-16, 2014)** local pollution at all the three observation points in AY, JZ and SMX (Figs 22 & 23). At all these points, pollution was at its peak during June 14-15. That the burning of biomass, such as straw,

#### **1. Aerosols** releases particulate matter of small grain size is confirmed by the depolarization ratio values obtained at the three measuring points.

Wheat harvesting from June 12 to June 16 in early summer of 2014, straw burning contributed to local pollution at all the three observation points in AY, JZ and SMX (Figs 22 & 23). At all June 13, 2014-June 14, 2014 (initial phase)

13

these points, pollution was at its peak during June 14-15. And the biomass burning, such as straw burning, which releases particulate matter of small grain size, is confirmed by the depolarization ratio values from lidar observations.

June 13, 2014-June 14, 2014 (initial phase)

**Figure 22.** Spatial distribution of aerosol from June 13 to June 14, 2014 at AY, CCR

#### June 15, 2014-June 16, 2014 (serious pollution phase)

during Nov 1-20 was 3.32×1016molec./cm2

average value was 8.37×1016 molecule/cm2

haze period on Dec 8, it was 5.8×1017 molecule/cm2

v<\$%&?>1<\$%&?>to<\$%&?>Dec<\$%&?>20

2013/11/15

**Figure 21.** NO2 VCD change chart detected by OMI satellite from Nov 1 to Dec 20

that high NO2 VCD values contribute to hazy weather.

**3.5. Typical straw burning process analysis (June 12-16, 2014)**

**3.5 Typical straw burning process analysis (June 12-16, 2014)** 

it was 1.57×1017 molecule/cm2

at the three measuring points.

June 13, 2014-June 14, 2014 (initial phase)

3.32×1016molec./cm2

2013/11/1

0

1 0

2 0

**NO2 VCD(\*10**

**16**

**molecu/cm2**

**)**

3 0

4 0

5 0

6 0

266 Current Air Quality Issues

8.37×1016 molecule/cm2

2013/11/1

**NO2 VCD(\*10**

**16**

**molecu/cm2**

**)**

2013/11/8

2013/11/8

2013/11/15

A Y JZ SMX ZZ

A Y JZ SMX ZZ

4. Dummy<\$%&?>Text<\$%&?>**Satellite**

**Figure 20.** NO2 VCD distribution result chart from Nov 11 to Dec 20 in CCR during haze period

Figure 19. Backward<\$%&?>trajectories<\$%&?>from<\$%&?>Hysplit

2013/11/22

2013/11/22

2013/11/29

2013/11/29

A

Figure 21 NO2 VCD change chart detected by OMI satellite from Nov 1 to Dec 20

From the satellite results in Fig 20, it can be observed that high NO2 VCD values existed during the haze period. From the daily variations in NO2 VCD values between Nov and Dec at AY, JZ and SMX (seen in Fig 21), it can be seen that the results at AY clearly indicate a relation between NO2 VCD values and haze. For example, at AY, the daily average value of NO2 VCD during Nov 1-20 was

2013/12/6

2013/12/6

. For the first haze period during Nov 21-23, the daily average value was

, which was 2.5 times more than the normal average value. For the second

**1. Aerosols**

 **(1) Aerosols** 

value. For the second haze period on Dec 8, it was 5.8×1017 molecule/cm2

and 18 times more than the normal average value. For the third haze period during Dec 16-17,

the normal average value. For the third haze period during Dec 16-17, it was 1.57×1017 molecule/cm2

which was 4.7 times more than the average value. From the values of NO2 during these three haze periods, which were multiple times more than the average value, it clearly follows that there exists certain relation between NO2 and haze, and that high NO2 VCD values contribute to hazy weather.

Figure 20 NO2 VCD distribution result chart from Nov 11 to Dec 20 in CCR during haze period

%&?>20<\$%&?>in<\$%&?>CCR<\$%&?>during<\$%&?>haze<\$%&?>period

values of NO2 during these three haze periods, which were multiple times more than the average value, it clearly follows that there exists certain relation between NO2 and haze, and

Wheat harvesting from June 12 to June 16 in early summer of 2014, straw burning contributed to local pollution at all the three observation points in AY, JZ and SMX (Figs 22 & 23). At all these points, pollution was at its peak during June 14-15. That the burning of biomass, such as straw, releases particulate matter of small grain size is confirmed by the depolarization ratio values obtained

Wheat harvesting from June 12 to June 16 in early summer of 2014, straw burning contributed to local pollution at all the three observation points in AY, JZ and SMX (Figs 22 & 23). At all

13

. For the first haze period during Nov 21-23, the daily

2013/12/13

2013/12/20

%&?>by<\$%&?>the<\$%&?>evening<\$%&?>of<\$%&?>June13<\$%&?>the<\$%&?>pollution<\$%&?>became<\$%&?>serious.

From<\$%&?>the<\$%&?>HYSPLIT<\$%&?>backward<\$%&?>trajectory<\$%&?>model<\$%&?>in<\$%&?>Fig<\$%&?>19<\$% &?>[29],<\$%&?>the<\$%&?>pollution<\$%&?>at<\$%&?>the<\$%&?>three<\$%&?>observation<\$%&?>points<\$%&?>was<\$% &?>found<\$%&?>to<\$%&?>be<\$%&?>mainly<\$%&?>from<\$%&?>the<\$%&?>northwest.<\$%&?>The<\$%&?>main<\$%&? >pollution<\$%&?>source<\$%&?>could<\$%&?>be<\$%&?>from<\$%&?>burning<\$%&?>of<\$%&?>fossil<\$%&?>fuels<\$%& ?>or<\$%&?>bio-fuels,<\$%&?>aided<\$%&?>by<\$%&?>the<\$%&?>continental<\$%&?>airstream.<\$%&?>By<\$%&?>noon<\$ %&?>on<\$%&?>Nov<\$%&?>25,<\$%&?>there<\$%&?>was<\$%&?>evident<\$%&?>increase<\$%&?>in<\$%&?>pollutants<\$% &?>at<\$%&?>both<\$%&?>AY<\$%&?>and<\$%&?>JZ.<\$%&?>Subsequently,<\$%&?>until<\$%&?>the<\$%&?>evening<\$%& ?>on<\$%&?>Dec<\$%&?>26,<\$%&?>at<\$%&?>both<\$%&?>the<\$%&?>observation<\$%&?>points,<\$%&?>the<\$%&?>pollu tants<\$%&?>decreased<\$%&?>and<\$%&?>then<\$%&?>again<\$%&?>increased<\$%&?>and<\$%&?>stabilized.<\$%&?>The <\$%&?>overall<\$%&?>aerosol<\$%&?>extinction<\$%&?>coefficient<\$%&?>at<\$%&?>AY<\$%&?>was<\$%&?>higher<\$%& ?>than<\$%&?>that<\$%&?>at<\$%&?>JZ,<\$%&?>the<\$%&?>peak<\$%&?>value<\$%&?>at<\$%&?>the<\$%&?>former<\$%&? >being<\$%&?>0.87km-1<\$%&?>and<\$%&?>at<\$%&?>the<\$%&?>latter<\$%&?>0.51km-1.<\$%&?>The<\$%&?>pollution<\$%&?>l ayer<\$%&?>was<\$%&?>below<\$%&?>1.9<\$%&?>km,<\$%&?>corresponding<\$%&?>to<\$%&?>the<\$%&?>pollutant<\$%& ?>transmission<\$%&?>layer<\$%&?>in<\$%&?>a<\$%&?>low<\$%&?>level<\$%&?>jet<\$%&?>(LLJ)<\$%&?>[30]<\$%&?>of<\$%&?> stable<\$%&?>or<\$%&?>neutral<\$%&?>boundary<\$%&?>layer.<\$%&?>For<\$%&?>two<\$%&?>days,<\$%&?>it<\$%&?>was <\$%&?>observed<\$%&?>that<\$%&?>the<\$%&?>height<\$%&?>of<\$%&?>the<\$%&?>mixing<\$%&?>layer<\$%&?>grew<\$ %&?>linearly<\$%&?>over<\$%&?>time.<\$%&?>When<\$%&?>the<\$%&?>height<\$%&?>of<\$%&?>the<\$%&?>mixing<\$%& ?>layer<\$%&?>grows<\$%&?>to<\$%&?>the<\$%&?>height<\$%&?>of<\$%&?>the<\$%&?>pollutant<\$%&?>transmission<\$% &?>belt<\$%&?>in<\$%&?>the<\$%&?>nocturnal<\$%&?>boundary<\$%&?>layer,<\$%&?>the<\$%&?>vertical<\$%&?>mixing< \$%&?>effect<\$%&?>would<\$%&?>result<\$%&?>in<\$%&?>rapid<\$%&?>concentration<\$%&?>of<\$%&?>pollutants<\$%&? >on<\$%&?>the<\$%&?>ground.<\$%&?>Therefore,<\$%&?>there<\$%&?>was<\$%&?>increase<\$%&?>in<\$%&?>aerosol<\$% &?>values,<\$%&?>as<\$%&?>well<\$%&?>as<\$%&?>in<\$%&?>local<\$%&?>pollutants<\$%&?>discharge<\$%&?>during<\$ %&?>the<\$%&?>days;<\$%&?>the<\$%&?>downward<\$%&?>transmission<\$%&?>from<\$%&?>the<\$%&?>higher<\$%&?>l ayers<\$%&?>was<\$%&?>also<\$%&?>an<\$%&?>important<\$%&?>factor.<\$%&?>Compared<\$%&?>with<\$%&?>AY<\$%&

, which was 2.5 times more than the normal average

, which was the highest and 18 times more than

2013/12/13

, which was 4.7 times more than the average value. From the

, which was the highest

2013/12/20

,

From<\$%&?>the<\$%&?>satellite<\$%&?>results<\$%&?>in<\$%&?>Fig<\$%&?>20,<\$%&?>it<\$%&?>can<\$%&?>be<\$%&?>ob **Figure 23.** Spatial distribution of aerosol from June 15 to June16, 2014 at AY, CCR

served<\$%&?>that<\$%&?>high<\$%&?>NO2<\$%&?>VCD<\$%&?>values<\$%&?>existed<\$%&?>during<\$%&?>the<\$%&?> haze<\$%&?>period.<\$%&?>From<\$%&?>the<\$%&?>daily<\$%&?>variations<\$%&?>in<\$%&?>NO2<\$%&?>VCD<\$%&?>v alues<\$%&?>between<\$%&?>Nov<\$%&?>and<\$%&?>Dec<\$%&?>at<\$%&?>AY,<\$%&?>JZ<\$%&?>and<\$%&?>SMX<\$%& During the straw burning period in CCR, the aerosol extinction coefficient fluctuated from 0.69 to 1.23 km-1. The low depolarization peak value of 0.2 confirms the presence of fine particulates. Besides particulates, usually straw burning also releases various gaseous components such as CO2, CO, NOx, VOC, sulfuric acid gas, hydrochloric acid gas, and alkaline gas ammonia. The retention time of ammonia in the air is short, because it quickly reacts with acidic gases or acidic particulate matter, and the resulting components can be precipitated on the particle surfaces of the particulate matter leading to the generation of new condensation nucleus. The aging process will increase the amount of particulate matter, which can lead to the increase in particulate emission factors. The burning of straw near CCR, together with surrounding pollution transmission, aging of particulate matter during long distance transmission, and the emission factors such as diameter aggravated local pollution.

## **2. Pollution gas**

Figure 24 Aerosol and NO2 profiles from June 15 to June16, 2014 at AY, CCR **Figure 24.** Aerosol and NO2 profiles from June 15 to June16, 2014 at AY, CCR

NO2 and SO2 values were at low level for most of the time, but at some stages during the measurement period from the end of May to the middle of June, they were at high level. According to the results of aerosol and NO2 for the period June 12 to 17 (see Fig 24), high aerosol extinction appeared at 300 m on June 12; it reached the peak on June 14 and diffused on June 15. It appeared on June 16 again and reached the highest level on June 17. NO2 transmission process appeared at the height of 1.8 to 2.7 km on June 12; it weakened on June 13 although the transmission, close to the ground, was stronger. The transmission process appeared again at the height of 1.5 to 2.2 km on June 14, which reappeared, though as a weaker one, on June 15 and 16 at the height of 2.2 to 3 km. But, by June 17, the transmission, though remained at the same height, became stronger.  **(3) Fire spots and backward trajectory**  To identify the sources of pollution transmission, local information was taken as the reference, but NO2 and SO2 values were at low level for most of the time, but at some stages during the measurement period from the end of May to the middle of June, they were at high level. According to the results of aerosol and NO2 for the period June 12 to 17 (see Fig 24), high aerosol extinction appeared at 300 m on June 12; it reached the peak on June 14 and diffused on June 15. It appeared on June 16 again and reached the highest level on June 17. NO2 transmission process appeared at the height of 1.8 to 2.7 km on June 12; it weakened on June 13 although the transmission close to the ground was stronger. The transmission process appeared again at the height of 1.5 to 2.2 km on June 14, which reappeared, though as a weaker one, on June 15 and 16 at the height of 2.2 to 3 km. But the transmission remaining at the same height became stronger on June 17.

#### during the wheat harvesting season, the burning of straw on the surrounding farmlands was believed **3. Fire spots and backward trajectory**

to be the main cause for high values of pollution. Therefore, the analysis was made by referring to the satellite fire spots diagram of Ministry of Environmental Protection, which is shown in Fig 25. To identify the sources of pollution transmission, local information was taken as the reference. But during the wheat harvesting season, the burning of straw on the surrounding farmlands was believed to be the main cause for high values of pollution. Therefore, the analysis was made by referring to the satellite fire spots diagram of Ministry of Environmental Protection, which is shown in Fig 25.

From these fire spots [31], it was inferred that multiple fire points existed around AY and JZ since June. However, by the middle of June they increased and many more fresh points appeared in the agricultural area of south CCR in the southeast. The backward trajectories, shown in Fig 26, indicate that concentrated burning of wheat straw brought about peripheral transmission.

Figure 25 Fire spots from May 26 to June 1, June 2 to June 8, and June 9 to June 15 From the foregoing results of aerosols and pollution gas, it emerges that the transportation brought by wheat straw burning manifested mainly as rapid increase of PM10, which is related to moisture absorption and expansion of particulate matter during transportation process. NO2 and SO2 were at their peaks on June 13 and 14 respectively; so, the amplification was not

15

during the wheat harvesting season, the burning of straw on the surrounding farmlands was believed to be the main cause for high values of pollution. Therefore, the analysis was made by referring to the A Comprehensive Research of Atmospheric Haze by Optical Remote Sensing in Central China Region (CCR) http://dx.doi.org/10.5772/59753 269

To identify the sources of pollution transmission, local information was taken as the reference, but

satellite fire spots diagram of Ministry of Environmental Protection, which is shown in Fig 25.

Figure 24 Aerosol and NO2 profiles from June 15 to June16, 2014 at AY, CCR

NO2 and SO2 values were at low level for most of the time, but at some stages during the measurement period from the end of May to the middle of June, they were at high level. According to the results of aerosol and NO2 for the period June 12 to 17 (see Fig 24), high aerosol extinction appeared at 300 m on June 12; it reached the peak on June 14 and diffused on June 15. It appeared on June 16 again and reached the highest level on June 17. NO2 transmission process appeared at the height of 1.8 to 2.7 km on June 12; it weakened on June 13 although the transmission, close to the ground, was stronger. The transmission process appeared again at the height of 1.5 to 2.2 km on June 14, which reappeared, though as a weaker one, on June 15 and 16 at the height of 2.2 to 3 km.

But, by June 17, the transmission, though remained at the same height, became stronger.

 **(3) Fire spots and backward trajectory** 

Figure 25 Fire spots from May 26 to June 1, June 2 to June 8, and June 9 to June 15 **Figure 25.** Fire spots from May 26 to June 1, June 2 to June 8, and June 9 to June 15

**2. Pollution gas**

268 Current Air Quality Issues

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Figure 25 Fire spots from May 26 to June 1, June 2 to June 8, and June 9 to June 15

From the foregoing results of aerosols and pollution gas, it emerges that the transportation brought by wheat straw burning manifested mainly as rapid increase of PM10, which is related to moisture absorption and expansion of particulate matter during transportation process. NO2 and SO2 were at their peaks on June 13 and 14 respectively; so, the amplification was not

Figure 24 Aerosol and NO2 profiles from June 15 to June16, 2014 at AY, CCR

NO2 and SO2 values were at low level for most of the time, but at some stages during the measurement period from the end of May to the middle of June, they were at high level. According to the results of aerosol and NO2 for the period June 12 to 17 (see Fig 24), high aerosol extinction appeared at 300 m on June 12; it reached the peak on June 14 and diffused on June 15. It appeared on June 16 again and reached the highest level on June 17. NO2 transmission process appeared at the height of 1.8 to 2.7 km on June 12; it weakened on June 13 although the transmission, close to the ground, was stronger. The transmission process appeared again at the height of 1.5 to 2.2 km on June 14, which reappeared, though as a weaker one, on June 15 and 16 at the height of 2.2 to 3 km.

NO2 and SO2 values were at low level for most of the time, but at some stages during the measurement period from the end of May to the middle of June, they were at high level. According to the results of aerosol and NO2 for the period June 12 to 17 (see Fig 24), high aerosol extinction appeared at 300 m on June 12; it reached the peak on June 14 and diffused on June 15. It appeared on June 16 again and reached the highest level on June 17. NO2 transmission process appeared at the height of 1.8 to 2.7 km on June 12; it weakened on June 13 although the transmission close to the ground was stronger. The transmission process appeared again at the height of 1.5 to 2.2 km on June 14, which reappeared, though as a weaker one, on June 15 and 16 at the height of 2.2 to 3 km. But the transmission remaining at the same height became

To identify the sources of pollution transmission, local information was taken as the reference, but during the wheat harvesting season, the burning of straw on the surrounding farmlands was believed to be the main cause for high values of pollution. Therefore, the analysis was made by referring to the satellite fire spots diagram of Ministry of Environmental Protection, which is shown in Fig 25.

To identify the sources of pollution transmission, local information was taken as the reference. But during the wheat harvesting season, the burning of straw on the surrounding farmlands was believed to be the main cause for high values of pollution. Therefore, the analysis was made by referring to the satellite fire spots diagram of Ministry of Environmental Protection,

From these fire spots [31], it was inferred that multiple fire points existed around AY and JZ since June. However, by the middle of June they increased and many more fresh points appeared in the agricultural area of south CCR in the southeast. The backward trajectories, shown in Fig 26, indicate that concentrated burning of wheat straw brought about peripheral

But, by June 17, the transmission, though remained at the same height, became stronger.

**Figure 24.** Aerosol and NO2 profiles from June 15 to June16, 2014 at AY, CCR

 **(3) Fire spots and backward trajectory** 

**3. Fire spots and backward trajectory**

stronger on June 17.

which is shown in Fig 25.

transmission.

**Figure 26.** Backward trajectories from Hysplit

as obvious as that of PM10. For evaluating the influence of wheat straw burning on local air pollution, the values of NO2 and SO2 on June 11, before wheat straw burning, were taken as the background values. The NO2 values obtained after wheat straw burning on June 13, and again the SO2values obtained on June 14, were recorded and evaluated. From these evaluation results, it's concluded that from the end of May to the middle of June, concentration of gaseous pollutants (NO2 and SO2) and particulate matter increased obviously due to straw burning in CCR and surrounding cities.
