Assessment of WRF-chem for simulating meteorology and air quality in different climatic zones over India

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ASSESSMENT OF WRF-CHEM FOR SIMULATING METEOROLOGY AND AIR QUALITY IN DIFFERENT

CLIMATIC ZONES OVER INDIA

PREETI GUNWANI

CENTRE FOR ATMOSPHERIC SCIENCES INDIAN INSTITUTE OF TECHNOLOGY DELHI

OCTOBER 2019

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© Indian Institute of Technology Delhi (IITD), New Delhi, 2019

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ASSESSMENT OF WRF-CHEM FOR SIMULATING METEOROLOGY AND AIR QUALITY IN DIFFERENT

CLIMATIC ZONES OVER INDIA

by

PREETI GUNWANI

Centre for Atmospheric Sciences

Submitted

in fulfilment of the requirements of the degree of Doctor of Philosophy

to the

INDIAN INSTITUTE OF TECHNOLOGY DELHI

OCTOBER 2019

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Dedicated to My Grandparents

& Parents

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C ERTIFICATE

This is to certify that the thesis entitled “Assessment of WRF-Chem for Simulating Meteorology and Air Quality in different Climatic Zones over India” being submitted by Ms. Preeti Gunwani to the Indian Institute of Technology Delhi for the award of the degree of Doctor of Philosophy, is a record of original bonafide research work carried out by her. She has worked under my guidance and supervision and has fulfilled the requirements for the submission of this thesis.

The results presented in this thesis have not been submitted in part or full to any other University or Institute for the award of any degree or diploma.

(PROFESSOR MANJU MOHAN) Center for Atmospheric Sciences Indian Institute of Technology Delhi Hauz Khas, New Delhi – 110016

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A CKNOWLEDGEMENTS

Firstly, I would like to express my sincere and deep sense of respect and gratitude to my supervisor Prof. Manju Mohan for her gracious support, patience and motivation during my PhD research. It has been a great learning experience to work with Prof. Mohan, which has contributed to my growth as a researcher and as a human being. I appreciate all her contributions of time, stimulating discussions and constructive criticism. Thank you for always showing me a step in the right direction. You inspire me with your genuine enthusiasm, work ethics and dedication.

I would like to thank my student research committee members: Prof. S.K. Dash, Prof.

A.D. Rao and Prof. Mukesh Khare for their guidance and insightful comments. I thank Prof. U. C. Mohanty, Prof. O.P. Sharma, Prof. Maithili Sharan, Prof. Pramila Goyal, Prof.

Krishna AchutaRao and Prof. Sagnik Dey for their guidance during the Pre-PhD course work. I am also thankful to other faculty members of Centre for Atmospheric Sciences for all the encouragement and support.

I am grateful to the staff members of Centre for Atmospheric Sciences, IIT Delhi for their help during the course of my research. I would like to acknowledge University Grants Commission (UGC) for Research Fellowship support; Centre for Atmospheric Sciences and IIT Delhi for providing vast computing resources, excellent library and other necessary facilities to conduct the research work.

I extent my heartful thanks to my seniors - Dr Swagata Payra, Dr. Lalit Dagar, Dr. Anurag Kandya, Dr. G. Senthil and Dr. Kanhu for their mentoring, motivation, words of wisdom and sense of humour. My special thanks to Dr. Shweta Bhati, for her unwavering support;

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her generosity and selflessness is inspiring and unmatched. You will always have my love, praise and gratitude.

I am indebted to my friends - Medhavi, Vivek, Tarkeshwar and Vijay Kumar for their unconditional help, and for always being there for me through thick and thin. I wish to express my hearty thanks to my friends and colleagues Ankur Sati, Rahul, Jerin, Soumyadip, Aniket, Kritika, Rati, Ragi, Ram, Sarika, Rajeev, Puneet, Pawan, Abhishek Upadhyay, Sachiko, Abhishek Anand, Popat, Tanvi, Sarita and Ankur Dixit. I also wish to thank all the other colleagues in CAS. I am grateful to have dearest buddies - Saumya, Arun, and Akhil. I am so blessed to have you in my life.

Above all I would like to thank my family - my Mother, my Mother-in-law, my Siblings Neha, Rahul and Bhavesh, my Siblings-in-law Manjit, Aditya and Sneha; and rest of my family for their love, support, patience and understanding throughout the duration of my work. Thank you for taking care of all my responsibilities when I was away from home.

Finally, of course, is my rock, my husband, Abhishek Aman, whose unconditional love and continual support over the past several years enabled me to complete this thesis.

Thank you for your constant encouragements when the tasks seemed arduous and insurmountable. Thank you for being my sounding board and keeping me sane over the past few years. But most of all, thank you for being my best friend. I owe you everything.

This accomplishment would not have been possible without you.

It is with infinite gratitude that I dedicate this thesis to my beloved late grandparents and my father. You are my constant source of inspiration and your invaluable teachings of life will always be close to my heart. Although you are not here, but I always feel your guiding presence and your blessings around me.

PREETI GUNWANI

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A BSTRACT

Aerosols can absorb or scatter light, influence the formation of clouds, affect precipitation efficiency, greenhouse gas forcing and through these affect the Earth’s radiative balance, and hence climate. But uncertainties in aerosol radiative forcings arise because of our incomplete understanding of the optical properties of the most important radiatively active species. Climate, weather and air quality directly affect the quality of our life. The study of air pollutants is very important as they have serious socioeconomic, environmental, health and welfare impacts.

Numerical Weather Prediction (NWP) models and Chemical Transport Models (CTM), are useful tools employed for studying the governing meteorological and chemical processes of the atmosphere. The models simulate the atmosphere in varying degree of detail by mathematically representing meteorological parameters such as temperature, wind, humidity, sunlight, cloud, boundary layer;

emissions, initial and boundary concentrations of chemical species; the chemical reactions of the emitted species and of their products. In the above backdrop, the main objective of this study is evaluation of the model ability to assess the model meteorology, aerosol properties and capture the temporal and spatial distribution of aerosols and gaseous species.

It is crucial to study Planetary Boundary Layer (PBL) processes which control pollutant exchanges between the surface and free atmosphere; and wind which is responsible for transport of pollutants away from the source. Firstly, model performance and sensitivity to PBL configurations are studied with the Weather Research and Forecasting (WRF) model in different climate zones over India for summer and winter period. One of the most important elements in configuring a

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model is the selection of the appropriate model inputs and physical parameterizations to be used. Thus, it is important to assess these model inputs to accurately determine the meteorology over different climatic zones, since India has varied type of climate due to its diverse topography. Best physics options suited were evaluated for surface meteorological parameters, upper air variables and planetary boundary layer height with standard statistical measures. On the whole, examining all the meteorological parameters, seasons and stations over India, Asymmetric Convective Model, Version 2 (ACM2) PBL scheme showed comparatively satisfactory performance. ACM2 is a combination of local and non-local closure and suitable for both stable and unstable atmospheric conditions.

Next, WRF model evaluation has been carried out under different Land Use Land Cover (LULC) data and initial/boundary forcing conditions over India. The model results showed improvements in simulations driven with AWiFS LULC and ERA- Interim reanalysis dataset, which highlights the significance of impact of LULC in atmospheric processes, and the need for updated accurate and comprehensive LULC and atmospheric reanalysis for meteorological modeling.

Subsequently, the best physical parameterization schemes, land use land cover and reanalysis data evaluated are used as an input to the WRF-Chem model to assess its performance in capturing the spatial and temporal resolution of aerosol optical properties, i.e. Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Asymmetry Parameter (AP) during summer and winter period. The model results are compared with satellite (MODIS) and ground based (AERONET) data over India. Further, WRF-Chem is used to evaluate PM10, PM2.5, NOx, SO2, CO and O3 to build confidence in its ability to simulate future

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air quality. It is seen that model performance improves significantly with increase in anthropogenic emission inputs and preliminary bias corrections. Overall, it is seen that WRF-Chem is capable of simulating gaseous pollutants and aerosols, with further scope for improvement in temporal and spatial resolution of emission inventory as well as the wind fields. Since air pollution has become a major environmental and public health challenge, WRF-Chem model becomes an important tool for developing and evaluating policies on air quality. In the future, necessary improvements in the simulations of meteorological variables would be undertaken through different bias correction or data assimilation techniques.

Uncertainties associated with different chemical processes and aerosol treatments will be investigated.

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सार

एरोसोल प्रकाश को अवशोषित या षिखेर सकता है, िादलोों के षिर्ााण को प्रभाषवत कर सकता है, विाा

दक्षता को प्रभाषवत कर सकता है, ग्रीिहाउस गैस forcing कर सकता है और इिके र्ाध्यर् से पृथ्वी के

षवषकरण सोंतुलि को प्रभाषवत करता है, इसषलए जलवायु को भी प्रभाषवत करता है । लेषकि एरोसोल षवषकरण forcing सोंिोंधी अषिषितता ऑषिकल गुणोों की हर्ारी अधूरी सर्झ के कारण उत्पन्न होती है।

जलवायु, र्ौसर् और हवा की गुणवत्ता हर्ारे जीवि की गुणवत्ता को सीधे प्रभाषवत करती है। वायु प्रदूिकोों

का अध्ययि िहुत र्हत्वपूणा है क्ोोंषक इिका सार्ाषजक, आषथाक, पयाावरण, स्वास्थ्य और कल्याण पर काफी गोंभीर असर पड़ता है। Numerical Weather Prediction (NWP) र्ॉडल और Chemical Transport Model (CTM), वातावरण के शाब्दिक र्ौसर् सोंिोंधी और रासायषिक प्रषियाओों का अध्ययि

करिे के षलए षियोषजत उपयोगी उपकरण हैं। र्ॉडल तापर्ाि, हवा, िर्ी, सूरज की रोशिी, िादल, सीर्ा

परत, रासायनिक प्रजानिय ों के उत्सजजि, प्रारोंनिक और सीमा साोंद्रिा; उत्सनजजि प्रजानिय ों और उिके उत्पाद ों

की रासायनिक प्रनिनियाओों का गषणतीय र्ापदोंडोों में प्रषतषिषधत्व करते हुए वातावरण को अलग-अलग षडग्री र्ें अिुकरण करिा है। उपरोक्त पृष्ठभूषर् र्ें, इस अध्ययि का र्ुख्य उद्देश्य र्ॉडल र्ौसर् षवज्ञाि, एयरोसोल गुणोों का आकलि करिे और एरोसोल और गैसीय प्रजाषतयोों के अस्थायी और स्थाषिक षवतरण को पकड़िे के षलए र्ॉडल की क्षर्ता का र्ूल्याोंकि है।

ग्रहीय सीर्ा परत (PBL) की प्रषियाओों का अध्ययि करिा र्हत्वपूणा है जो सतह और र्ुक्त वातावरण के

िीच प्रदूिक के आदाि-प्रदाि को षियोंषित करते हैं; और हवा जो स्रोत से दूर प्रदूिकोों के पररवहि के षलए षजम्मेदार है। सिसे पहले, र्ॉडल प्रदशाि और पीिीएल षवन्यास के प्रषत सोंवेदिशीलता का अध्ययि गर्ी

और सषदायोों की अवषध के षलए भारत के षवषभन्न जलवायु क्षेिोों र्ें Weather Research and Forecasting (WRF) र्ॉडल के साथ षकया गया है। एक र्ॉडल को कॉब्दफ़िगर करिे र्ें सिसे र्हत्वपूणा तत्व र्ॉडल र्ें

उपयोग षकए जािे वाले उपयुक्त र्ॉडल इिपुट और भौषतक र्ापदोंडोों का चयि है। इस प्रकार, षवषभन्न जलवायु क्षेिोों पर र्ौसर् षवज्ञाि को सटीक रूप से षिधााररत करिे के षलए इि र्ॉडल आदािोों का आकलि

करिा र्हत्वपूणा है, क्ोोंषक भारत र्ें षवषवध स्थलाकृषत के कारण षवषभन्न प्रकार की जलवायु है। र्ािक भौषतकी उपायोों के साथ सतह के र्ौसर् सोंिोंधी र्ापदोंडोों, ऊपरी वायु चर और ग्रहोों की सीर्ा परत की ऊोंचाई के षलए अिुकूल सवोत्तर् भौषतकी षवकल्ोों का र्ूल्याोंकि षकया गया है। कुल षर्लाकर, भारत के सभी र्ौसर्

सोंिोंधी र्ापदोंडोों, र्ौसर्ोों और स्टेशिोों की जाोंच करते हुए Asymmetric Convective Model, version 2 (ACM2) PBL योजिा िे तुलिात्मक रूप से सोंतोिजिक प्रदशाि षकया। ACM2 स्थािीय और गैरस्थािीय क्लोजर का एक सोंयोजि है और दोिोों ब्दस्थर और अब्दस्थर वायुर्ोंडलीय ब्दस्थषतयोों के षलए उपयुक्त है।

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इसके िाद, WRF र्ॉडल र्ूल्याोंकि को भारत के षवषभन्न Land Use Land Cover (LULC) डेटा और प्रारोंषभक / सीर्ा िल की प्रनिबोंधिा के तहत षकया गया है। र्ॉडल पररणार्ोों र्ें AWiFS LULC और ERA- Interim Reanalysis डेटासेट के साथ सोंचाषलत षसर्ुलेशि र्ें सुधार षदखा है, जो वायुर्ोंडलीय प्रषियाओों र्ें

LULC के प्रभाव के र्हत्व पर प्रकाश डालिा है, और र्ौसर् सोंिोंधी र्ॉडषलोंग के षलए अद्यनिि सटीक और व्यापक LULC और वायुर्ोंडलीय reanalysis की आवश्यकता क दर्ाजिा है।

इसके िाद, सिसे अच्छी भौषतक पररशोधि योजिाएों, Land Use Land Cover और Reanalysis Data का

र्ूल्याोंकि WRF-Chem र्ॉडल के इिपुट के रूप र्ें गमी और सनदजय ों की अवनध के दौराि षकया गया है, जो एरोसोल ऑषिकल गुण जैसे Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) और Asymmetry Parameter (AP) के स्थाषिक और लौषकक ररजॉल्यूशि को कैप्चर करिे र्ें इसके

प्रदशाि का आकलि करता है। र्ॉडल के पररणार्ोों की तुलिा भारत र्ें उपग्रह डेटा (MODIS) और जर्ीि

आधाररत (AERONET) डेटा के साथ िारि के नलए नकआ गया है। इसके अलावा, WRF-Chem का उपयोग PM10 , PM2.5 , NOX , SO2 , CO और O3 का र्ूल्याोंकि करिे के षलए षकया गया है ताषक भषवष्य की वायु

गुणवत्ता को अिुकरण करिे की क्षर्ता र्ें षवश्वास पैदा नकया जा सके। यह देखा जाता है षक र्ािवजषित उत्सजाि इिपुट की वृब्दि और Preliminary Bias Correction से र्ॉडल के प्रदशाि र्ें काफी सुधार होता

है। कुल षर्लाकर, यह देखा गया है षक WRF-Chem गैसीय प्रदूिकोों और एरोसोल का अिुकरण करिे र्ें

सक्षर् है, र्ॉडल र्ें उत्सजाि सूची के अस्थायी और स्थाषिक सोंकल् र्ें सुधार के साथ-साथ पवि क्षेिोों र्ें िी

सुधार की गुोंजाइश है। चूोंषक वायु प्रदूिण एक िड़ी पयाावरणीय और सावाजषिक स्वास्थ्य चुिौती िि गई है, इसषलए WRF-Chem र्ॉडल वायु गुणवत्ता की िीषतयोों के षवकास और र्ूल्याोंकि के षलए एक र्हत्वपूणा

उपकरण िि गया है। भषवष्य र्ें र्ौसर् सोंिोंधी चर के षसर्ुलेशि र्ें आवश्यक सुधार षवषभन्न Bias Correction या डेटा Assimilation तकिीकोों के र्ाध्यर् से षकया जा सकिा है। षवषभन्न रासायषिक प्रषियाओों और एयरोसोल उपचार से जुड़े अषिषितताओों की जाोंच की जाएगी।

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T ABLE OF C ONTENTS

Certificate ...i

Acknowledgements...ii

Abstract...iv

Table of Contents...vii

List of Figures...xi

List of Tables...xix

List of Abbreviations...xxiii

1 INTRODUCTION ... 1

1.1OZONE ... 1

1.2AEROSOLS ... 2

1.2.1 Aerosol Classification ... 3

1.2.2 Aerosol-Climate Interaction ... 4

1.3ATMOSPHERIC MODELLING ... 7

1.3.1 Numerical Weather Prediction models ... 7

1.3.2 Chemical Transport Models ... 9

1.4LITERATURE REVIEW ... 9

1.4.1 WRF Sensitivity Studies ... 9

1.4.2 Air Quality Modelling ... 13

1.5OBJECTIVES AND OUTLINE OF PRESENT WORK ... 25

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2 SENSITIVITY OF WRF MODEL ESTIMATES TO VARIOUS PBL PARAMETERIZATIONS IN DIFFERENT CLIMATIC ZONES OVER INDIA 28

2.1INTRODUCTION ... 28

2.2WRF MODELLING SYSTEM ... 30

2.2.1 Governing Equations in WRF (Skamarock et al., 2008) ... 31

2.3MODEL DETAILS ... 37

2.3.1 Model Simulation details ... 37

2.3.2 Model domain and data requirements ... 40

2.3.3 Performance indicators for model validation ... 45

2.4RESULTS AND DISCUSSIONS ... 47

2.4.1 Synoptic verification ... 47

2.4.2 Temperature, 2m ... 50

2.4.3 Relative Humidity, 2m ... 57

2.4.4 Wind speed, 10m and Wind Direction ... 61

2.4.5 Vertical profile of Temperature and Wind Speed... 68

2.4.6 Planetary Boundary Layer height ... 69

2.4.7 Bias Correction for Surface Parameters ... 75

2.5CONCLUSIONS ... 76

3 SENSITIVITY OF WRF MODEL TO DIFFERENT LAND USE LAND COVER AND REANALYSIS DATASET... 78

3.2.1 Model simulation details ... 80

3.2.2 Model domain, validation and data requirements ... 83

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3.3.1 Sensitivity to Reanalysis data ... 85

3.3.2 Sensitivity to Land use land cover data ... 96

4 ASSESSMENT OF AEROSOL OPTICAL PROPERTIES USING WRF-CHEM OVER INDIA ... 104

4.2AEROSOL OPTICAL PROPERTIES ... 105

4.3WRF-CHEM MODEL DESCRIPTION ... 107

4.4DATA AND METHODOLOGY ... 109

4.4.1 Study area ... 109

4.4.2 Simulation design ... 110

4.4.3 Model input data ... 115

4.4.4 Model validation ... 117

4.5RESULTS AND DISCUSSION ... 121

4.5.1 WRF-Chem vs MODIS AOD... 121

4.5.2 WRF-Chem vs AERONET ... 127

4.5.3 WRF-Chem with modified (EDGAR-HTAP) anthropogenic emissions ... 135

5 EVALUATION OF AIR QUALITY OVER INDIA USING WRF-CHEM ... 145

5.2.1 Model simulation details ... 147

5.2.2 Model validation ... 148

5.3.1 WRF-Chem with default (EDGAR-HTAP) anthropogenic emissions... 150

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5.3.2 WRF-Chem with Modified (EDGAR-HTAP) anthropogenic emissions ... 167

6 CONCLUSIONS AND FUTURE WORK ... 171

6.2SCOPE OF FUTURE WORK ... 175

REFERENCES ... 176

CURRICULUM - VITAE ... 203

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L ^{IST OF} F ^IGURES

FIGURE 1-1:DISTRIBUTION OF ATMOSPHERIC AEROSOL PARTICLES WITH THE DIFFERENT

MODES (SEINFELD AND PANDIS,2006) 4

FIGURE 1-2: SCHEMATIC DIAGRAM SHOWING THE VARIOUS RADIATIVE MECHANISMS ASSOCIATED WITH AEROSOL-CLOUD INTERACTION (IPCC,2007) 5 FIGURE 1-3:THE PROCESSES WHICH AFFECT CLOUDS.THE POLLUTED CLOUD CONTAINS AS

MANY DROPLETS OF THE HALF SIZE, TWICE THE SURFACE AREA, TWICE THE OPTICAL DEPTH AND HIGHER REFLECTIVITY THAN NATURAL CLOUD (TOON,2000) 6 FIGURE 2-1: WRF MODEL DOMAIN (SHADED REGION) OVER INDIA (GUNWANI AND

MOHAN,2017) 41

FIGURE 2-2: KOPPEN CLASSIFICATION (PEEL ET AL 2007) OF INDIA SHOWING SPATIAL DISTRIBUTION OF OBSERVATION SITES (GUNWANI AND MOHAN,2017) 43 FIGURE 2-3: SYNOPTIC WEATHER CONDITIONS OVER INDIA - WINDS (M/S) AND

GEOPOTENTIAL HEIGHT (M) AT 850 HPA DURING SUMMER PERIOD (A) YSU– ERA INTERIM (B) MYJ – ERA INTERIM (C) ACM2 – ERA INTERIM (D) QNSE – ERA INTERIM (E)MYNN–ERAINTERIM (F)ERAINTERIM OBSERVED VALUES (GUNWANI

AND MOHAN,2017) 48

FIGURE 2-4: SYNOPTIC WEATHER CONDITIONS OVER INDIA - WINDS (M/S) AND GEOPOTENTIAL HEIGHT (M) AT 850 HPA DURING WINTER PERIOD (A) YSU – ERA INTERIM (B) MYJ – ERA INTERIM (C) ACM2 – ERA INTERIM (D) QNSE – ERA INTERIM (E)MYNN–ERAINTERIM (F)ERAINTERIM OBSERVED VALUES (GUNWANI

AND MOHAN,2017) 49

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FIGURE 2-5:DIURNAL TIME SERIES OF 2M TEMPERATURE FOR 15-31^THMAY 2008(SUMMER)

IN A)TROPICAL B)ARID C)TEMPERATE ZONE D)INDIA (GUNWANI AND MOHAN,2017) 51 FIGURE 2-6:DIURNAL TIME SERIES OF 2M TEMPERATURE FOR 25^THDEC 2008-9^THJAN 2009 (WINTER) IN A) TROPICAL B) ARID C) TEMPERATE ZONE D) INDIA (GUNWANI AND

MOHAN,2017) 51

FIGURE 2-7: Q-Q PLOTS FOR TEMPERATURE,2M FOR YSU, MYJ,ACM2,QNSE AND MYNN SCHEMES OVER (A) TEMPERATE (SUMMER), (B) TEMPERATE (WINTER), C) ARID (SUMMER), (D) ARID (WINTER), (E) TROPICAL (SUMMER), (F) TROPICAL

(WINTER), (G) INDIA (SUMMER) AND (H) INDIA (WINTER) (GUNWANI AND MOHAN,

2017) 53

FIGURE 2-8:DIURNAL TIME SERIES OF 2M RELATIVE HUMIDITY FOR 15-31^TH MAY 2008 (SUMMER) IN A) TROPICAL B)ARID C) TEMPERATE ZONE D) INDIA (GUNWANI AND

MOHAN,2017) 58

FIGURE 2-9:DIURNAL TIME SERIES OF 2M RELATIVE HUMIDITY FOR 25^THDEC 2008-9^THJAN

2009(WINTER) IN A)TROPICAL B)ARID C)TEMPERATE ZONE D)INDIA (GUNWANI AND

MOHAN,2017) 58

FIGURE 2-10: Q-Q PLOTS FOR RELATIVE HUMIDITY,2M FOR YSU,MYJ,ACM2,QNSE ANDMYNN SCHEMES OVER (A)TEMPERATE (SUMMER),(B)TEMPERATE (WINTER),

C) ARID (SUMMER), (D) ARID (WINTER), (E) TROPICAL (SUMMER), (F) TROPICAL

2017) 59

FIGURE 2-11: DIURNAL TIME SERIES OF 10M WIND SPEED FOR SUMMER PERIOD IN A) TROPICAL B)ARID C)TEMPERATE ZONE D)INDIA (GUNWANI AND MOHAN,2017) 62

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FIGURE 2-12: DIURNAL TIME SERIES OF 10M WIND SPEED FOR WINTER PERIOD IN A) TROPICAL B)ARID C)TEMPERATE ZONE D)INDIA (GUNWANI AND MOHAN,2017) 62 FIGURE 2-13: Q-Q PLOTS FOR WIND SPEED, 10M FOR YSU,MYJ, ACM2, QNSE AND MYNN SCHEMES OVER (A) TEMPERATE (SUMMER), (B) TEMPERATE (WINTER), C) ARID (SUMMER), (D) ARID (WINTER), (E) TROPICAL (SUMMER), (F) TROPICAL

2017) 64

FIGURE 2-14: WIND ROSE DIAGRAMS FOR SUMMER PERIOD- NEW DELHI (ROW 1), CHENNAI (ROW 2) AND DIBRUGARH (ROW 3)(GUNWANI AND MOHAN,2017) 66 FIGURE 2-15:WIND ROSE DIAGRAMS FOR WINTER PERIOD-NEW DELHI (ROW 1),CHENNAI

(ROW 2) AND DIBRUGARH (ROW 3)(GUNWANI AND MOHAN,2017) 67 FIGURE 2-16: VERTICAL PROFILE OF TEMPERATURE AT NEW DELHI FOR 16^THMAY 2008 0000 UTC, 1200 UTC (TOP PANEL) AND 28^TH DEC 2008 0000 UTC, 1200 UTC

(GUNWANI AND MOHAN,2017) 68

FIGURE 2-17:VERTICAL PROFILE OF WIND SPEED AT NEW DELHI FOR 16^THMAY 20080000 UTC,1200UTC(TOP PANEL) AND 28^THDEC 20080000UTC,1200UTC(GUNWANI

AND MOHAN,2017) 69

FIGURE 2-18: PBL HEIGHT OF CHENNAI DURING A) SUMMER B) WINTER PERIOD,NEW

DELHI DURING C) SUMMER D) WINTER PERIOD AND KOLKATA DURING E) SUMMER F)

WINTER PERIOD (GUNWANI AND MOHAN,2017) 71

FIGURE 2-19: HEAT FLUX AT SURFACE AT CHENNAI DURING A) SUMMER B) WINTER PERIOD,NEW DELHI DURING C) SUMMER D) WINTER PERIOD AND KOLKATA DURING E)

SUMMER F) WINTER PERIOD (GUNWANI AND MOHAN,2017) 72

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FIGURE 2-20: STATISTICAL EVALUATION OF T2 AND WS – PRE AND POST BIAS

CORRECTION 75

FIGURE 3-1:LAND USE OVER INDIA BASED ON (A)USGS LAND USE (B)AWIFS LAND USE

(C)MODIS LAND USE DATA 83

FIGURE 3-2: FREQUENCY OF MODEL WIND SPEED – FNL AND ERA COMPARED TO

OBSERVED FOR SUMMER 2008 94

OBSERVED FOR WINTER 2008 94

OBSERVED FOR SUMMER 2010 95

OBSERVED FOR WINTER 2010 95

FIGURE 4-1:FLOWCHART OF THE WRF-CHEM MODELING SYSTEM (SOURCE:WRF-CHEM

USER GUIDE, HTTPS://RUC.NOAA.GOV/WRF/WRF-CHEM/USERS_GUIDE.PDF) 108

FIGURE 4-2:MODEL SIMULATION DOMAINS 110

FIGURE 4-3: SCHEMATIC OVERVIEW OF THE CONSIDERED AEROSOL CHEMISTRY WITHIN

MADE AND THE IMPLEMENTATION OF THE SECONDARY ORGANIC AEROSOL MODEL

(SCHELL ET AL.,2001) 113

FIGURE 4-4:AERONET STATIONS USED FOR MODEL VALIDATION 118 FIGURE 4-5: COMPARISON OF AOD550 WRF-CHEM MODEL OUTPUT (LEFT), AOD550

FROM MODIS DATA (MIDDLE) AND MODEL BIAS (RIGHT) FOR MAY 2008 123 FIGURE 4-6: COMPARISON OF AOD550 WRF-CHEM MODEL OUTPUT (LEFT), AOD550

FROM MODIS DATA (MIDDLE) AND MODEL BIAS (RIGHT) FOR DECEMBER 2008 124

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FIGURE 4-7: COMPARISON OF AOD550 WRF-CHEM MODEL OUTPUT (LEFT), AOD550

FROM MODIS DATA (MIDDLE) AND MODEL BIAS (RIGHT) FOR MAY 2010 125 FIGURE 4-8: COMPARISON OF AOD550 WRF-CHEM MODEL OUTPUT (LEFT), AOD550

FROM MODIS DATA (MIDDLE) AND MODEL BIAS (RIGHT) FOR DECEMBER 2010 126 FIGURE 4-9:TIME SERIES OF AOD(LEFT),SSA(MIDDLE) AND ASY(RIGHT) OVER KANPUR,

NAINITAL AND BAREILLY FOR MAY 2008 130

FIGURE 4-10:TIME SERIES OF AOD(LEFT),SSA(MIDDLE) AND ASY(RIGHT) OVER PUNE, GANDHI COLLEGE AND PANTNAGAR FOR MAY 2008 131 FIGURE 4-11: TIME SERIES OF AOD (LEFT), SSA (MIDDLE) AND ASY (RIGHT) OVER

PANTNAGAR,PUNE AND GUAL PAHARI FOR DECEMBER 2008 132 FIGURE 4-12: TIME SERIES OF AOD (LEFT), SSA (MIDDLE) AND ASY (RIGHT) OVER

KANPUR,PUNE,NAINITAL AND JAIPUR FOR MAY 2010 133 FIGURE 4-13: TIME SERIES OF AOD (LEFT), SSA (MIDDLE) AND ASY (RIGHT) OVER

KANPUR,PUNE AND JAIPUR FOR DECEMBER 2010 134 FIGURE 4-14: COMPARISON OF AOD550 WRF-CHEM MODEL OUTPUT WITH DEFAULT

EMISSIONS (LEFT) AND MODIFIED EMISSIONS (MIDDLE); AOD550 FROM MODIS

DATA FOR MAY 2008. 138

FIGURE 4-15:TEMPERATURE AT 2M (TOP PANEL);WIND SPEED AND DIRECTION AT 10M

(BOTTOM PANEL) SIMULATED BY THE MODEL (LEFT) AND ERA5REANALYSIS DATA

(RIGHT) FOR MAY 2008 139

FIGURE 4-16: COMPARISON OF AOD550 WRF-CHEM MODEL OUTPUT WITH DEFAULT EMISSIONS (LEFT) AND MODIFIED EMISSIONS (MIDDLE); AOD550 FROM MODIS

DATA FOR DECEMBER 2008. 140

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FIGURE 4-17:TEMPERATURE AT 2M (TOP PANEL); WIND SPEED AND DIRECTION AT 10M

(BOTTOM PANEL) SIMULATED BY THE MODEL (LEFT) AND ERA5REANALYSIS DATA

(RIGHT) FOR MAY 2008 141

FIGURE 4-18: TIME SERIES OF AOD FROM DEFAULT AND MODIFIED EMISSIONS OVER

KANPUR, NAINITAL, BAREILLY, PUNE, GANDHI COLLEGE AND PANT NAGAR FOR

MAY 2008 142

FIGURE 4-19:TIME SERIES OF AOD FROM DEFAULT AND MODIFIED EMISSIONS OVER PANT

NAGAR,PUNE AND GUAL PAHARI FOR DECEMBER 2008 143 FIGURE 5-1: COMPOSITION OF PARTICULATE MATTER (HTTP://URBANEMISSIONS.INFO) 146 FIGURE 5-2:STATIONS USED FOR MODEL VALIDATION 149 FIGURE 5-3:SCATTER PLOT OF CO OVER ITO,NEW DELHI DURING MAY 2008 AND DEC

2008 WITH DEFAULT EMISSIONS (TOP PANEL) AND MODIFIED EMISSIONS (BOTTOM

PANEL) 154

FIGURE 5-4:SCATTER PLOT OF SO2 OVER ITO,NEW DELHI DURING MAY 2008 AND DEC

PANEL) 155

FIGURE 5-5:SCATTER PLOT OF NO2 OVER ITO,NEW DELHI DURING MAY 2008 AND DEC

PANEL) 156

FIGURE 5-6:PERCENTAGE OF MODEL SIMULATED AND OBSERVED NO2 CONCENTRATION IN DIFFERENT RANGES OVER ITO,DELHI FOR MAY AND DECEMBER 2008 157

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FIGURE 5-7:SCATTER PLOT OF PM2.5 OVER ITO,NEW DELHI DURING MAY 2008 AND DEC

PANEL) 158

FIGURE 5-8: SCATTER PLOT OF SO2, NO2 AND PM10 OVER BANDRA, MUMBAI DURING

DECEMBER 2010 WITH DEFAULT EMISSIONS (TOP PANEL) AND MODIFIED EMISSIONS

(BOTTOM PANEL) 159

FIGURE 5-9:SCATTER PLOT OF SO2 OVER INDIA DURING MAY 2016(LEFT) AND DECEMBER

2016 (RIGHT) WITH DEFAULT EMISSIONS (TOP PANEL) AND MODIFIED EMISSIONS

(BOTTOM PANEL) 160

FIGURE 5-10: SCATTER PLOT OF NO2 OVER INDIA DURING MAY 2016 (LEFT) AND

DECEMBER 2016 (RIGHT) WITH DEFAULT EMISSIONS (TOP PANEL) AND MODIFIED

EMISSIONS (BOTTOM PANEL) 161

FIGURE 5-11:PERCENTAGE OF MODEL SIMULATED AND OBSERVED NO2 CONCENTRATION IN DIFFERENT RANGES OVER INDIA FOR MAY AND DECEMBER 2016 162 FIGURE 5-12: SCATTER PLOT OF CO OVER INDIA DURING MAY 2016 (LEFT) AND

FIGURE 5-13:SCATTER PLOT OF O3 OVER INDIA DURING MAY 2016(LEFT) AND DECEMBER

2016 (RIGHT) WITH DEFAULT EMISSIONS (TOP PANEL) AND MODIFIED EMISSIONS

(BOTTOM PANEL) 164

FIGURE 5-14: SCATTER PLOT OF PM10 OVER INDIA DURING MAY 2016 (LEFT) AND

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FIGURE 5-15: SCATTER PLOT OF PM2.5 OVER INDIA DURING MAY 2016 (LEFT) AND

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L ^{IST OF} T ^ABLES

TABLE 2-1:SIMULATION DETAILS SPECIFYING PHYSICS OPTIONS (GUNWANI AND MOHAN, 2017) ... 40 TABLE 2-2:METEOROLOGICAL STATIONS DETAILS OVER INDIA ... 44 TABLE 2-3:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING SUMMER

PERIOD (GUNWANI AND MOHAN,2017) ... 56 TABLE 2-4:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING WINTER

PERIOD (GUNWANI AND MOHAN,2017) ... 56 TABLE 2-5: STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

SUMMER PERIOD (GUNWANI AND MOHAN,2017) ... 60 TABLE 2-6: STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

WINTER PERIOD (GUNWANI AND MOHAN,2017) ... 60 TABLE 2-7:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING SUMMER

PERIOD (GUNWANI AND MOHAN,2017) ... 63 TABLE 2-8:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING WINTER

PERIOD (GUNWANI AND MOHAN,2017) ... 63 TABLE 2-9: STATISTICAL PERFORMANCE INDICES FOR PBLH DURING SUMMER PERIOD

(GUNWANI AND MOHAN,2017) ... 73 TABLE 2-10: STATISTICAL PERFORMANCE INDICES FOR PBLH DURING WINTER PERIOD

(GUNWANI AND MOHAN,2017) ... 73 TABLE 3-1:SIMULATION DETAILS ... 81 TABLE 3-2:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING SUMMER- 2008 PERIOD (FNL VS ERA)... 88

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TABLE 3-3:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING WINTER- 2008 PERIOD (FNL VS ERA) ... 88 TABLE 3-4:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING SUMMER- 2010 PERIOD (FNL VS ERA) ... 89 TABLE 3-5:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING WINTER- 2010 PERIOD (FNL VS ERA) ... 89 TABLE 3-6:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING SUMMER- 2008 PERIOD (FNL VS ERA) ... 90 TABLE 3-7:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING WINTER- 2008 PERIOD (FNL VS ERA) ... 90 TABLE 3-8:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING SUMMER- 2010 PERIOD (FNL VS ERA) ... 91 TABLE 3-9:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING WINTER- 2010 PERIOD (FNL VS ERA) ... 91 TABLE 3-10:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

SUMMER-2008 PERIOD (FNL VS ERA) ... 92 TABLE 3-11:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

WINTER-2008 PERIOD (FNL VS ERA) ... 92 TABLE 3-12:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

SUMMER-2010 PERIOD (FNL VS ERA) ... 93 TABLE 3-13:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

WINTER-2010 PERIOD (FNL VS ERA) ... 93

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TABLE 3-14: STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING SUMMER-2008 PERIOD (USGS VS MODIS VS AWIFS) ... 97 TABLE 3-15:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING WINTER- 2008 PERIOD (USGS VS MODIS VS AWIFS) ... 97 TABLE 3-16: TABLE 3.16: STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE

DURING SUMMER-2010 PERIOD (USGS VS MODIS VS AWIFS) ... 98 TABLE 3-17:STATISTICAL PERFORMANCE INDICES FOR 2M TEMPERATURE DURING WINTER- 2010 PERIOD (USGS VS MODIS VS AWIFS) ... 98 TABLE 3-18:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING SUMMER- 2008 PERIOD (USGS VS MODIS VS AWIFS) ... 99 TABLE 3-19:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING WINTER- 2008 PERIOD (USGS VS MODIS VS AWIFS) ... 99 TABLE 3-20:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING SUMMER- 2010 PERIOD (USGS VS MODIS VS AWIFS) ... 100 TABLE 3-21:STATISTICAL PERFORMANCE INDICES FOR 10M WIND SPEED DURING WINTER- 2010 PERIOD (USGS VS MODIS VS AWIFS) ... 100 TABLE 3-22:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

SUMMER-2008 PERIOD (USGS VS MODIS VS AWIFS) ... 101 TABLE 3-23:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

WINTER-2008 PERIOD (USGS VS MODIS VS AWIFS)... 101 TABLE 3-24:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING

SUMMER-2010 PERIOD (USGS VS MODIS VS AWIFS) ... 102

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TABLE 3-25:STATISTICAL PERFORMANCE INDICES FOR 2M RELATIVE HUMIDITY DURING WINTER-2010 PERIOD (USGS VS MODIS VS AWIFS) ... 102 TABLE 4-1:TOTAL EDGARHTAP EMISSIONS FOR DIFFERENT SPECIES OVER INDIA FOR

2010 ... 116 TABLE 4-2:DATA AVAILABLE PERIOD OF AEROSOL PRODUCTS FOR DIFFERENT AERONET

STATIONS... 127 TABLE 4-3:MEAN BIAS FOR WRF-CHEM AOD FROM DEFAULT AND MODIFIED EMISSIONS

... 137 TABLE 5-1:DETAILS OF STATIONS USED FOR MODEL VALIDATION ... 149

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L ^{IST OF} A BBREVIATIONS

AERONET Aerosol Robotic Network AOD Aerosol Optical Depth AQM Air Quality Modelling

ARW Advanced Research WRF

ASY Asymmetry Parameter

AVHRR Advanced Very High Resolution Radiometer AWiFS Advanced Wide Field Sensor

CCN Cloud Condensation Nuclei CMAQ Community Multiscale Air Quality CTP Chemical Transport Model

ECMWF European Centre for Medium-Range Weather Forecasts EDGAR Emission Database for Global Atmospheric Research

FB Fractional Bias

GCM General Circulation Models

HTAP Hemispheric Transport of Air Pollution IGP Indo Gangetic Plains

IOA Index of Agreement

IPCC Intergovernmental Panel on Climate Change ISRO Indian Space Research Organisation

LSM Land Surface Model

LULC Land Use Land Cover

MB Mean Bias

MODIS Moderate Resolution Imaging Spectroradiometer MOZART Model for Ozone And Related chemical Tracers NCAR National Center for Atmospheric Research NCEP National Centers for Environmental Prediction NMHC Non Methane Hydro Carbons

NRSC National Remote Sensing Centre NWP Numerical Weather Prediction PBL Planetary Boundary Layer PM Particulate Matter

RMSE Root Mean Squared Error SSA Single Scattering Albedo TKE Turbulent Kinetic Energy VOC Volatile Organic Carbon

WRF Weather Research and Forecasting Model

Assessment of WRF-chem for simulating meteorology and air quality in different climatic zones over India

ASSESSMENT OF WRF-CHEM FOR SIMULATING METEOROLOGY AND AIR QUALITY IN DIFFERENT

CLIMATIC ZONES OVER INDIA

PREETI GUNWANI

CENTRE FOR ATMOSPHERIC SCIENCES INDIAN INSTITUTE OF TECHNOLOGY DELHI

OCTOBER 2019

© Indian Institute of Technology Delhi (IITD), New Delhi, 2019

ASSESSMENT OF WRF-CHEM FOR SIMULATING METEOROLOGY AND AIR QUALITY IN DIFFERENT

CLIMATIC ZONES OVER INDIA

by

PREETI GUNWANI

Centre for Atmospheric Sciences

Submitted

in fulfilment of the requirements of the degree of Doctor of Philosophy

to the

INDIAN INSTITUTE OF TECHNOLOGY DELHI

OCTOBER 2019

Dedicated to My Grandparents

& Parents

C ERTIFICATE

A CKNOWLEDGEMENTS

A BSTRACT

सार

T ABLE OF C ONTENTS

L IST OF F IGURES

L IST OF T ABLES

L IST OF A BBREVIATIONS

L ^{IST OF} F ^IGURES

L ^{IST OF} T ^ABLES

L ^{IST OF} A BBREVIATIONS