4.7 Article

Trend and variability of atmospheric ozone over middle Indo-Gangetic Plain: impacts of seasonality and precursor gases

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 24, Issue 1, Pages 164-179

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-016-7738-2

Keywords

Boundary layer; Meteorology; Indo-Gangetic Plain; Ozone; OMI-DOAS; Varanasi

Ask authors/readers for more resources

Ozone dynamics in two urban background atmospheres over middle Indo-Gangetic Plain (IGP) were studied in two contexts: total columnar and ground-level ozone. In terms of total columnar ozone (TCO), emphases were made to compare satellite-based retrieval with ground-based observation and existing trend in decadal and seasonal variation was also identified. Both satellite-retrieved (Aura Ozone Monitoring Instrument-Differential Optical Absorption Spectroscopy (OMI-DOAS)) and ground-based observations (IMD-O-3) revealed satisfying agreement with OMI-DOAS observation over predicting TCO with a positive bias of 7.24 % under all-sky conditions. Minor variation between daily daytime (r = 0.54; R (2) = 29 %; n = 275) and satellite overpass time-averaged TCO (r = 0.58; R (2) = 34 %; n = 208) was also recognized. A consistent and clear seasonal trend in columnar ozone (2005-2015) was noted with summertime (March-June) maxima (Varanasi, 290.9 +/- 8.8; Lucknow, 295.6 +/- 9.5 DU) and wintertime (December-February) minima (Varanasi, 257.4 +/- 10.1; Lucknow, 258.8 +/- 8.8 DU). Seasonal trend decomposition based on locally weighted regression smoothing technique identified marginally decreasing trend (Varanasi, 0.0084; Lucknow, 0.0096 DU year(-1)) especially due to reduction in monsoon time minima and summertime maxima. In continuation to TCO, variation in ground-level ozone in terms of seasonality and precursor gases were also analysed from September 2014 to August 2015. Both stations registered similar pattern of variation with Lucknow representing slightly higher annual mean (44.3 +/- 30.6; range, 1.5-309.1 mu g/m(3)) over Varanasi (38.5 +/- 17.7; range, 4.9-104.2 mu g/m(3)). Variation in ground-level ozone was further explained in terms water vapour, atmospheric boundary layer height and solar radiation. Ambient water vapour content was found to associate negatively (r = -0.28, n = 284) with ground-level ozone with considerable seasonal variation in Varanasi. Implication of solar radiation on formation of ground-level ozone was overall positive (Varanasi, 0.60; Lucknow, 0.26), while season-specific association was recorded in case of atmospheric boundary layer.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Environmental Sciences

Evaluation of Simulated AVIRIS-NG Imagery Using a Spectral Reconstruction Method for the Retrieval of Leaf Chlorophyll Content

Bhagyashree Verma, Rajendra Prasad, Prashant K. Srivastava, Prachi Singh, Anushree Badola, Jyoti Sharma

Summary: In this study, a hyperspectral image was simulated using a spectral reconstruction method, and its applicability in estimating leaf chlorophyll content was validated using ground based measurements. The simulated image achieved high accuracy when classified, indicating its usefulness for vegetation parameter retrieval.

REMOTE SENSING (2022)

Article Environmental Sciences

Highly efficient visible light active doped metal oxide photocatalyst and SERS substrate for water treatment

Samriti, Komal Shukla, Rajeev Gupta, Raju Kumar Gupta, Jai Prakash

Summary: This study reports the synthesis and characterization of highly efficient TiO2 nanorods (NRs) and Ta-doped TiO2 NRs (Ta-TiO2 NRs) for multifunctional applications. The NRs showed promising optical properties and exhibited excellent photocatalytic activities and surface-enhanced Raman scattering (SERS) performance. Ta-TiO2 NRs showed enhanced response due to the additional defects introduced by Ta doping, which resulted in improved visible light absorption and charge transfer properties.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2023)

Article Geochemistry & Geophysics

Passive Only Microwave Soil Moisture Retrieval in Indian Cropping Conditions: Model Parameterization and Validation

Dileep Kumar Gupta, Prashant K. Srivastava, Dharmendra Kumar Pandey, Sumit Kumar Chaudhary, Rajendra Prasad, Peggy E. O'Neill

Summary: The present study aims to parameterize the single channel soil moisture active passive (SMAP) passive soil moisture (SM) retrieval algorithm for Indian conditions. MODIS data products and soil texture data were used to improve the parameterization of the algorithm. The algorithm was calibrated using vegetation and roughness parameters to minimize the error between the model retrieved and ground measured SM. The performance of the new parameterized model was evaluated and compared with other SM products, showing significant improvements.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2023)

Article Engineering, Civil

Future Climate Change Impact on the Streamflow of Mahi River Basin Under Different General Circulation Model Scenarios

Swati Maurya, Prashant K. K. Srivastava, Lu Zhuo, Aradhana Yaduvanshi, R. K. Mall

Summary: Climate change significantly affects the hydrological regime, and the integration of climate models with physical based models is crucial for accurate measurement of surface water changes. The study found that the INMCM-4 and MRI-CGCM3 models, as well as their ensemble mean, performed well in predicting rainfall and temperature in the Mahi River basin, India. The findings indicate that there will be an increase in average annual streamflow in the near future.

WATER RESOURCES MANAGEMENT (2023)

Article Environmental Sciences

Development of High-Resolution Soil Hydraulic Parameters with Use of Earth Observations for Enhancing Root Zone Soil Moisture Product

Juby Thomas, Manika Gupta, Prashant K. Srivastava, Dharmendra K. Pandey, Rajat Bindlish

Summary: This study proposes a new method to estimate high-resolution Soil Hydraulic Parameters (SHPs) and provide high-resolution rootzone soil moisture (RZSM) products. The method consists of three phases: downsampling satellite soil moisture to estimate surface soil moisture, using downscaled soil moisture to estimate SHPs, and simulating surface soil moisture and RZSM using the derived SHPs.

REMOTE SENSING (2023)

Article Green & Sustainable Science & Technology

Potassium Simulation Using HYDRUS-1D with Satellite-Derived Meteorological Data under Boro Rice Cultivation

Ayushi Gupta, Manika Gupta, Prashant K. Srivastava, George P. Petropoulos, Ram Kumar Singh

Summary: This study compared the potassium predictions in surface and sub-surface soil layers under Boro rice cultivation using different meteorological datasets and validated the use of satellite-based meteorological data for simulating potassium concentration in soil in the absence of ground station data. The model was found most suitable for the 0-30 cm depth on all days and for all treatment variations.

SUSTAINABILITY (2023)

Article Environmental Sciences

Accounting for the aerosol type and additional satellite-borne aerosol products improves the prediction of PM2.5 concentrations

Somaya Falah, Fadi Kizel, Tirthankar Banerjee, David M. Broday

Summary: A new method is developed to predict surface PM2.5 concentrations by utilizing information on aerosol type retrieved from satellite observations. The method uses Random Forest and eXtreme Gradient Boosting models with input of widely available satellite aerosol products and surface meteorological data, resulting in improved risk assessment of PM2.5 exposure and more accurate radiative forcing calculations.

ENVIRONMENTAL POLLUTION (2023)

Article Environmental Sciences

Evaluating the Performance of PRISMA Shortwave Infrared Imaging Sensor for Mapping Hydrothermally Altered and Weathered Minerals Using the Machine Learning Paradigm

Neelam Agrawal, Himanshu Govil, Gaurav Mishra, Manika Gupta, Prashant K. Srivastava

Summary: This study evaluates the potential of the PRISMA dataset for mapping hydrothermally altered and weathered minerals using machine learning algorithms. The spectral angle mapper technique was used to generate distribution maps for minerals such as kaolinite, talc, and montmorillonite, which were verified through field validation surveys. The results demonstrate that the stochastic gradient descent and artificial neural network-based multilayer perceptron classifiers outperformed other algorithms in accuracy.

REMOTE SENSING (2023)

Article Green & Sustainable Science & Technology

Changes in Extremes Rainfall Events in Present and Future Climate Scenarios over the Teesta River Basin, India

Pawan Kumar Chaubey, Rajesh Kumar Mall, Prashant K. Srivastava

Summary: Globally, changes in hydroclimate extremes, such as extreme precipitation events, have various impacts on water resources, natural environments, and human health and safety. In recent decades, India has experienced a significant increase in rainfall extremes during the summer monsoon season. However, there is considerable uncertainty regarding future extreme rainfall events at the regional scale. Therefore, this study focuses on evaluating extreme rainfall events at a regional river basin level using observed gridded datasets and climate model projections from CMIP. The results indicate a significant rise in precipitation extremes in the first half of the 21st century, with an increase in accumulated precipitation and precipitation maxima at different return periods. Moreover, the study predicts a 23.37% increase in events exceeding the 90th percentile in the middle of the 21st century.

SUSTAINABILITY (2023)

Article Green & Sustainable Science & Technology

Appraisal of Climate Response to Vegetation Indices over Tropical Climate Region in India

Nitesh Awasthi, Jayant Nath Tripathi, George P. Petropoulos, Dileep Kumar Gupta, Abhay Kumar Singh, Amar Kumar Kathwas, Prashant K. Srivastava

Summary: Extreme climate events are increasing due to global climate change. This study investigates the association between climate variables and vegetation dynamics in the Indian state of Haryana from 2010 to 2020. The analysis reveals a strong correlation between NDVI and LAI with climate variables during cropping months, while the relationship weakens but remains significant during non-cropping months. Rainfall and relative humidity show a positive relationship with NDVI and LAI, while other climatic variables exhibit negative trends. The findings highlight the significant usefulness of satellite-derived vegetation indices in understanding the relationship between climate variables and vegetation dynamics.

SUSTAINABILITY (2023)

Article Computer Science, Information Systems

Assessment of a Dynamic Physically Based Slope Stability Model to Evaluate Timing and Distribution of Rainfall-Induced Shallow Landslides

Juby Thomas, Manika Gupta, Prashant K. Srivastava, George P. Petropoulos

Summary: Shallow landslides have become more frequent due to changes in rainfall frequency and intensity. This study evaluated a slope stability model called TRIGRS in Idukki district, Kerala, Western Ghats. The study compared the impact of hydrogeomechanical parameters derived from different soil texture data sets on the simulation of landslide distribution and timing. The results indicate that the model simulations using parameters from either data set can identify the location of landslide events, but there is a need for high-spatial-resolution hydrogeomechanical parameter data to improve the timing of landslide event modeling.

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2023)

Article Environmental Sciences

Modeling and Analysis of Air Pollution and Environmental Justice: The Case for North Carolina's Hog Concentrated Animal Feeding Operations

Brandon M. Lewis, William H. Battye, Viney P. Aneja, Honghyok Kim, Michelle L. Bell

Summary: This study investigated the exposure to pollutants from hog farms and found disparities in exposure based on race/ethnicity, educational attainment, language proficiency, and socioeconomic status. Low-income individuals, people of color, those with low educational attainment, and the linguistically isolated are more likely to be exposed to high levels of pollutants.

ENVIRONMENTAL HEALTH PERSPECTIVES (2023)

Article Environmental Sciences

Retrieval uncertainty and consistency of Suomi-NPP VIIRS Deep Blue and Dark Target aerosol products under diverse aerosol loading scenarios over South Asia

Kumari Aditi, Abhishek Singh, Tirthankar Banerjee

Summary: The retrieval accuracy and stability of two aerosol retrieval algorithms, Deep Blue (DB) and Dark Target (DT), applied on VIIRS on-board S-NPP satellite over South Asia, were evaluated. The results showed that DB efficiently retrieved fine aerosol features over bright arid surfaces and smoke/dust dominating events, while DT was better at identifying small fire events under dark vegetated surfaces. However, both algorithms showed unsatisfactory retrieval accuracy against AERONET, with a low percentage of valid retrievals and high RMSE and bias. Further refinement is required for the accuracy of both algorithms to continue the MODIS AOD legacy over South Asia.

ENVIRONMENTAL POLLUTION (2023)

Article Environmental Sciences

Understanding the soil water dynamics during excess and deficit rainfall conditions over the core monsoon zone of India

Mangesh M. Goswami, Milind Mujumdar, Bhupendra Bahadur Singh, Madhusudan Ingale, Naresh Ganeshi, Manish Ranalkar, Trenton E. Franz, Prashant Srivastav, Dev Niyogi, R. Krishnan, S. N. Patil

Summary: This study investigates the soil water dynamics in the core monsoon zone of India by analyzing the observations of soil moisture. The research reveals that lower soil moisture is associated with depleted convective activity and higher temperatures during the pre-monsoon season, while monsoon rains increase soil moisture. The study highlights the importance of surface-subsurface soil moisture observations in unraveling the complexity of soil water dynamics.

ENVIRONMENTAL RESEARCH LETTERS (2023)

Article Environmental Sciences

Source specific health risks of size-segregated particulate bound metals in an urban environment over northern India

Nandita Singh, Abhishek Singh, Tirthankar Banerjee, Abhishek Chakraborty, Karine Deboudt, Mahesh Mohan

Summary: This study systematically investigated the health risks of exposure to particulate-bound metals of different sizes and analyzed their sources. The results showed that resuspensions of crustal and road dust were the main sources of metals, and industrial emissions and biomass/waste burning were the major contributors to health risks. Metal-contaminated food ingestion posed non-carcinogenic risks, while inhalation of carcinogenic metals increased the risk of cancer. The health risks associated with exposure to size-segregated airborne metals were within the tolerable level but exceeded the safe level of exposure.

ATMOSPHERIC ENVIRONMENT (2023)

No Data Available