Spatio Temporal.docx

Abstract In recent years, smog has been one of the main concerns in heavily populated urban areas like Lahore and Kanpur. Atmospheric pollutants like aerosols play an important role in smog. In this paper, aerosol types in smog episode are identified, based on AERONET data, for 4-year period i.e. 2015-2018. For winters we take four months January, October, November, December and May, June, July August for Summer Duration. The data is then classified in different aerosol types on the basis of Fine Mode Fraction (FMF) and Single Scattering Albedo (SSA). One of the main aerosol types which is abundant in every smog episode is Black Carbon (BC) aerosol while other types such as dust, were present throughout the year. Black Carbon is responsible for radiation imbalance, so considered as main component in climate changes at regional and global level. Furthermore, Aerosol Optical Depth (AOD) time series in smog episodes is used to make sure the presence of smog as AOD evaluates total burden of aerosol in atmosphere. Backward trajectories from HYSPLIT model are used to trace the origin of aerosols in maximum AOD days of smog episodes.

Introduction Aerosols plays a vital role in smog. In this paper, aerosol types in smog episode are identified, based on AERONET data, for 4-year period i.e. 2015-2018. For winters we take four months January, October, November, December and May, June, July August for Summer Duration. Atmospheric pollutants like aerosols are an insistent concern because of their increasing percentage and prominent effect on global and regional climate change. Aerosols have a nature and can affect atmosphere both directly and indirectly. They can disturb the radiation balance causing either heating or cooling effect depending upon the optical properties of aerosols and their concentration and vertical extent (Novakov, Tica 2013). Aerosol is considered as one of the biggest uncertainties in assessment of climate forcing because of lack of detailed knowledge of their optical properties. (Heintzenberg et al. 1997) In atmosphere, aerosols are originated from natural and different anthropogenic activities. Aerosols originated from natural emissions are mostly primary aerosols (e.g. dust). On the other hand, secondary aerosols, mainly fine particles, are originated from anthropogenic activities (Hansson et.al 2015). Incomplete combustion of fossil fuels, biofuels and biomass generates Black Carbon (BC) which is considered as one of the main component responsible for climate change. It is suggested in recent researches that BC is responsible for both regional and global changes in climates (Jacobson MZ.2002). A rapid increase in concentration of BC in the atmosphere is due to the emissions of vehicle exhaust, biological, fossil fuels and agricultural burning (Zhang, H., and Z. Wang, 2011). In urban environment, severe smog can occur due to BC aerosols along with suitable weather conditions (Mira-Salama, D., et al.). Soot emission associated with coal burning was responsible for London smog, having both BC and organic compounds as main constituents. (Brimblecombe, Peter 1978). By the utilization of

other fuels such as gasoline instead of coal, another view of air pollution arose in US and California. This type of air pollution caused LA smog with the symptoms of visibility reduction and severe irritation in eyes. An explanation of the formation of LA smog is proposed as nitrogen oxides and hydrocarbons from automobile exhaust form visibility reducing aerosols and ozone when get in contact with UV radiations from sun. From this explanation two conclusions are derived  

Photochemical conversion of gasses to particles form smog particles in atmosphere. Reduction of primary particles like dust, smoke or soot caused LA air pollution. (HaagenSmit, Arie J.1952)

To study the main reasons of smog in Lahore, Aerosol Robotic Network (AERONET) data is used. To classify aerosols FMF and SSA is used and aerosols are classified in 6 types over the study area. Month of November is considered as smog episode for 4 years data i.e. 2014-2018. The most abundant aerosol type in winter is BC, whereas in summer other types are observed such as dust and mixture. BC is found to be the main constituent in Lahore smog. BC also alters weather conditions so in smog episodes, meteorological data is observed. Wind velocity is strongly influenced by BC aerosols (M. Z. Jacobson 2002). Average monthly temperature decreases in the month of November up to over Lahore and over Kanpur. High aerosol deposition occurs as a result of decrease in both temperature and relative humidity which provides unfavorable conditions for the dispersion of aerosols (Tiwari et al., 2018) HYSPLIT, a computer model, can calculate forward and backward trajectories at different heights for any ground location. This model is used to know the origin BC aerosols in smog episodes. Three heights are chosen for trajectories in this case i.e. 500m, 1000m and 1500m.

Study Area As a second most populous city of Pakistan, Lahore (31.56°N 74.35°E) is located on the Ravi River, in the upper Indus plain, in the northwest of country, with a population density of over 7 billion. Climate of Lahore is classified as BSh according to Köppen and Geiger. 5 seasons of Lahore are foggy winter (NDJ), spring (FMA), summer (MJ), monsoon (JAS); and autumn (SN) with June as a hottest month (33.9°C average), January as a coldest (average 12.3 °C). November experiences least precipitation (average 4mm) and maximum precipitation in July (average 189mm). Study site is affected form heavy aerosol emission including fine mode particles in winter due to fossil fuel combustion and different anthropogenic activities and dust throughout the year. Kanpur is a large city famous for its industry, located in state of Uttar Perdesh, northern India with --- million population. According to Köppen and Geiger, climate of Kanpur is Cwa. Seasons are winter (DJF), pre monsoon or summer (MAM), monsoon (JJAS) and post monsoon

(OND). Area is affected by dense smoky conditions in post monsoon due to massive crop burning. (Chen et al 2016)

Figure 1: Lahore and Kanpur

Materials and methods 1- AERONET (AErosol RObotic NETwork) AERONET is a ground based project for the remote sensing of aerosols founded by NASA and PHOTONS (Photométrie pour le Traitement Opérationnel de Normalisation Satellitaire) that offers a calibration for a ground-based aerosol monitoring on regional to global level and characterization network (Holben, Brent N., et al, 1998). For more than 400 sites over the entier globe, AERONET provides the data of Aerosol Optical Depth, Aerosol Inversion Products and Precipitable water in 3 Levels. Level 1.0 data is unscreened, Level 1.5 data is cloud screened and quality controlled, Level 2.0 data is quality assured. AOD, precipitable water and inversion produts are all derived from these three Levels, although some additional checks for quality may be implemented. At our study site, the AERONET instrument is placed at IST (Institute of Space and Technology), Lahore Pakistan. Daily average data is used for 4 summer months (MJJA) and 4 winter months (ONDJ) for 4 years i-e 20152018. From spectral AOD parameters, fine mode fraction data is used, And from various derived inversion products, SSA data is used in order to classify aerosols in different types. Level 2.0 data is prefered, however when level 2.0 data is unavailable, level 1.5 data is taken. Data can be downloaded directly from AERONET website. (https://aeronet.gsfc.nasa.gov/new_web/index.html)

2- HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) The National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory’s (ARL) Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) (Draxler, R.and G. D. Hess, 1998) is a complete system to compute the trajectory of air parcel and distribution of pollutants in atmosphere. The common applications of this model is a back-trajectory analysis used to verify air masses origin (Fleming et al. 2012). In order to predict the backward trajectory, HYSPLIT model is used

with the archived data in this study. Upon requirement, HYSPLIT can calculate up to 40 backward or forward trajectories at altered heights, with 500 x 500m resolution and 1.5 ° x 1.5 ° horizontal grid (Alam, Khan, et al, 2010). In this study, the height of backward trajectories from to ground is chosen to be 500m, 1000m and 1500m. This model can be used from the HYSPLIT official website (http://ready.arl.noaa.gov/HYSPLIT.php).

Methodology: The classification of Aerosols is based on size and radiation absorptivity, thus producing four unique categories which are    

Absorbing fine-mode Absorbing course-mode Non-absorbing fine-mode Non-absorbing course-mode

Absorbing fine-mode aerosols are classified as Black Carbon (BC) as its optical properties are well known. Black Carbons are further classified into Moderately Absorbing (MA), Slightly Absorbing (SA) and Highly Absorbing (HA) (Higurashi and Nakajima 2002), during this analysis daily average level 1.5 inversion products are used. In order to classify aerosols, to differentiate absorbing from non-absorbing Single Scattering Albedo (SSA) is used and to conclude size of aerosols Fine Mode Fraction (FMF) at 550nm is used. Threshold of FMF determines the dominant size mode of Aerosols. AERONET inversion algorithm has a slightly issue in determining the size mode of aerosols as it used the threshold of 0.6 micro meters. The issue is that it overestimates fine-mode AOD of fine-mode aerosols -and underestimate coarse-mode AOD of coarse mode aerosols. To tackle this estimation problem 0.2 safety margin in the threshold of FMF is adopted. As a result aerosol having FMF >0.6 are distinguished as fine-mode aerosols whereas to classify the aerosol as Coarse-mode aerosol the FMF should be <0.4. The aerosols lying within the margin of 0.2 that is from 0.4 to 0.6 inclusive, are classified as Mixture of both modes. The SSA used to determine the absorptivity of aerosol is provided by AEONET channel and for the particular study the shortest wavelength is selected which was 440nm. Hence, SSA determines whether an aerosol is absorbing or non-absorbing. Those aerosols which have FMF threshold greater than 0.6 are further classified as non-absorbing if SSA is greater than 0.95 and as BC if not. Black Carbons are further distributed into three categories with respect to SSA which are 

Slightly Absorbing Aerosols

 

Moderately Absorbing Aerosols Highly Absorbing Aerosols

On contrary, course-mode aerosols having SSA greater than 0.95 are classified as “Uncertain” and those with SSA less than 0.95 are classified as “Dust”. The performance of classifying aerosol algorithm is dependent on FMF threshold although this algorithm is simple and robust (Lee et al. 2010)

Results and Discussions 1-Classification of Aerosols over Lahore and Kanpur: Aerosols over Lahore and Kanpur are divided into 5 classes i.e. uncertain, dust, mixture, NA and BC. BC is further divided into 3 classes as SA, MA and HA on the basis of SSA at 440nm and FMF at 500nm. Percentage of overall data represented by each class in Lahore and Kanpur is shown in figure 2 Figure 2 (a) shows aerosol spatial distribution over Kanpur, the most dominant type of aerosol is Dust 52% which is found throughout the year, followed by NA mostly found in winters. Then comes all types of BC which are HA>SA>MA and least concentration of mixtures is present. For Lahore, Figure 2 (b), the most dominant type of the aerosol is Moderately Absorbing Aerosols (MA), accounting for 33% of all the second dominant type of aerosol is Slightly Absorbing Aerosols (SA) which is 21%. Then comes the Mixture whose concentration is 18%, Highly Absorbing (HA) and Dust which are 11%. The rare concentration of aerosol type Mixture detected is Non-Absorbing Aerosols (NA) which 1% is 6%. SA 12% NA 18%

NA 6%

Dust 52% MA 3%

HA 14%

Uncertain 0% Dust 11% Mixture 18%

MA 33%

HA 11%

SA 21%

Figure 2(a) and (b) shows spatial distribution of aerosols over Kanpur and Lahore respectively.

2- Single Scattering Albedo: The absorption and scattering properties of aerosols particles are revealed by single scattering albedo (Chen et al.2016). Single scattering albedo (SSA) is defined as the ratio of the scattering coefficient to the extinction coefficient. It is a vital parameter that defines the consequence of aerosols on radiative forcing. It depends upon the size and refractive index of aerosols. There are several ways in which SSA can be calculated for column as well as surface and layered aerosols (Soni et al., 2010). In the current work, SSA has been attained using sun/sky radiance measurements for column aerosols in the atmosphere (Nakajima et al., 1996; Dubovik et al., 2000) and is derived from almucantar retrieved aerosol properties. The SSA displays diverse spectral behavior for different types of aerosols. It decreases with wavelength for biomass and urban/industrial aerosols and increases for desert dust aerosols (Dubovik et al., 2002). Figure 3 shows the spectral divergences of single scattering albedo (Ali et al.2014) for the month of November from year 2014 to 2018 over Lahore. There is a reasonable dependence of Single Scattering Albedo over different Wavelengths. In winter, SSA decreases with increase in wavelength beyond 675 nm, which can be qualified to the dominance of absorbing industrial/urban aerosols over Lahore, because lower SSA values at longer wavelength are obtained due to minimum chance for contact between absorbing aerosols and solar radiation (Singh et al., 2004; Yu et al. 2009). Over Lahore, NA shows highest value of SSA among all types of aerosols with mean values ranging from 0.93-0.95 over the wavelength ranging from 440-1020nm. And for Kanpur, this range is from 0.94-0.91 for NA. This aerosol type is more dominant over winter and post monsoon season (ONDJ), when the relative humidity is relatively greater than other seasons. (Chen et al 2016). SA comes next with the values ranging from 0.92-0.93 over Lahore, MA and mixture show almost same behavior with the values between 0.84-0.90. HA shows least SSA values having strong absorbing properties. Aerosols over Kanpur show almost same SSA trends with dust showing highest SSA and SA with the least values.

Lahore

1

Kanpur 0.96

0.95

0.94

SSA

SSA

0.9 0.85

0.92 0.9 0.88

0.8

0.86 440nm

0.75 [440nm]

675nm

870nm

HA

MA

Mixture

Non-absorbing (NA)

SA

870nm

1020nm

Wavelength

1020nm

Wavelength

675nm

Dust

HA

MA

Non-absorbing (NA)

SA

Figure3(a) showing SSA over Lahore and 3(b) over Kanpur

3-Fine mode Fraction: FMF of aerosol optical depth is the fraction of fine mode AOD (AOD fine mode) to the total AOD (AOD total) at 500nm, where fine mode and coarse mode aerosols are defined as their effective radii range from 0.1 to 0.25 μm and 1.0 to 2.5 μm respectively (Aloysius et al., 2009). The value of FMF is in the range of 0 (single coarse mode particle) to 1 (single fine mode particle) and gives the quantitative information about the size distribution of atmospheric aerosols (Kim et al., 2007; Kedia and Ramachandran 2008). It also relates the absorption spectral dependence of particle to particle size as well as it has the potential to characterize the dominant absorbing types of aerosol or optical mixture (Giles et al., 2011)

4- Temporal distribution of aerosols: The yearly classification of aerosols from the year 2015 -2018 is shown in figure 4. Every year shows different concentration of different particles over Lahore in Figure 4 (a). In 2015 the most often identified aerosol type is MA and Mixture followed by Black Carbon, whereas Dust and NA are rarely identified. In 2016 the most frequently detected aerosol type is MA, whereas the rarely identified aerosol is Dust. In 2017 the frequently occurring aerosol type is MA same as previous years while the rear particle is SA followed by Black Carbon. In 2018 the most often identified aerosol type is Dust and Mixture, whereas HA and NA followed by Black Carbon are rarely identified. From these results we can conclude that Lahore is mainly affected by aerosols primarily by Black Carbons. Black carbons are due to natural and anthropogenic activities. The anthropogenic sources mainly consist of the combustion of coal, oil, and other fossil fuels, biomass burning, and car exhaust emissions (Bond et al. 2007). Burning of Crops is also a main source of Black Carbon aerosols. 50

Percentage %

Percentage %

40 30 20 10

70 60 50 40 30 20 10 0 2015

0 2015

2016

2017

Years Dust

Mixture

SA

HA

MA

Non-absorbing (NA)

2016

2018 Uncertain

2017

2018

Years Dust

HA

MA

NA

SA

Figure 4(a) and (b) showing temporal aerosol distribution over Lahore and Kanpur respectively

Mix

Figure 4(b) shows that dust this the most dominant aerosol type over Kanpur during all time period. Then NA and SA values are prominent in the all years. Whereas very less concentration of MA is observed. Mixture is present only in 2016.

Kanpur

100 90 80 70

60 50 40 30 20 10 0 S 2015

S 2016

S 2017

S 2018

Dust

HA

MA

N 2015 NA

SA

N 2016

N 2017

N 2018

MIX

Figure 5(a) showing concentration of different aerosol types in smog periods and normal days over Kanpur

Lahore

90 80 70

60 50 40 30 20

10 0 S 2015

S 2016 Dust

S 2017 Mixture SA

S 2018 HA MA

N 2015 N 2016 Non-absorbing (NA)

N 2017 Uncertain

N 2018

Figure 6 showing concentration of different aerosol types in smog periods and normal days over Lahore Aerosol distribution in smog periods and normal days over Kanpur Figure 5. Shows that dust is present mostly all year long. During smog episodes, mostly NA and BC are observed, although concentration of

different types of BC differs. During the years of 2015 and 2016, all three types of BC are present in almost same concentration. But during 2017 and 2018, SA is maximum and MA is minimum from BC aerosol types. When normal days are observed, maximum dust is present followed by HA with least concentration of SA, MA and mixture. Figure 6 presenting distribution of aerosol over Lahore during smog episodes and normal days. During smog episodes most dominant aerosol type is MA then comes SA and HA. This shows that BC aerosol is main component during smog episodes. Mixture is also present in every year except 2017. Small concentration of NA is present in 2015 and 2016. But no general trend for normal days is observed. In 2015 NA is dominant with small concentration of dust and SA is also present. In 2016 almost same concentration of all types is present except HA and uncertain aerosols. No data was available for 2017. And for 2018, most dominant aerosol type is dust followed by mixture with small concentration of others. 1.2 1

AOD

0.8 0.6 0.4 0.2 0 July

August

October

November

December

Months

Figure 7 variation of AOD at 500nm over Lahore

January

Aerosol optical depth is the significant parameter used to evaluate total aerosol burden in the atmosphere (Tariq, Salman, and Muhammad Ali.2015). Variation of monthly average AOD at 500 nm during the year 2015 to 2018 over Lahore are showed in figure 7. It is obvious from the figure that the peak AOD occurred in the month of November of taken four years. (Ali et al. 2014). To examine the variations of Single Scattering Albedo with regard to Total Precipitable water, time series between Single Scattering Albedo and Total Precipitable water is plotted over Lahore as shown in Fig 8. The trend between Single Scattering Albedo and Total Precipitable water is linear. It means as Single Scattering Albedo increase to Total Precipitable water also increases. The Pearson correlation coefficients between Single Scattering Albedo and Total Precipitable Water is calculated. The value of Pearson correlation (R) is 0.04.

Figure 8 time series of SSA and TPW

Conclusions: AERONET sun photometer data were used to classify Aerosol types. For absorbing aerosols, we deduct a relationship between Absorption Characteristic Single Scattering Albedo (SSA) and size parameter Fine Mode Fraction (FMF) (Rupakhet et al 2019). On the smog episodes which occurred in November have maximum Aerosol Optical Depth (AOD). In the month of November from 2015 to 2018 the aerosols which were detected are Black Carbons. In the atmospheric Aerosols Black Carbon plays a significant and complex role in the climate.The aerosols detected over the city Lahore are mainly from biomass burning and urban activities. It is concluded that Black Carbons are the main constituents of the smog.

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