Particulate Matter 2.5 concentration prediction system based on uncertainty analysis and multi-model integration DOI
Yamei Chen, Jianzhou Wang, Runze Li

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 958, P. 177924 - 177924

Published: Dec. 9, 2024

Language: Английский

Prediction of land surface temperature using spectral indices, air pollutants, and urbanization parameters for Hyderabad city of India using six machine learning approaches DOI
Gourav Suthar, Saurabh Singh,

Nivedita Kaul

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 35, P. 101265 - 101265

Published: June 2, 2024

Language: Английский

Citations

10
Machine Learning Approach for Predicting Perfluorooctanesulfonate Rejection in Efficient Nanofiltration Treatment and Removal DOI
Saurabh Singh, Gourav Suthar, Akhilendra Bhushan Gupta

et al.

ACS ES&T Water, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Language: Английский

Citations

1
Understanding the multifaceted influence of urbanization, spectral indices, and air pollutants on land surface temperature variability in Hyderabad, India DOI
Gourav Suthar, Saurabh Singh,

Nivedita Kaul

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 470, P. 143284 - 143284

Published: Aug. 1, 2024

Language: Английский

Citations

4
Application of machine learning models for PM2.5 prediction in bengaluru using precursor air pollutants and meteorological data DOI
Gourav Suthar,

Saurabh Singh

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(3)

Published: March 1, 2025

Language: Английский

Citations

0
The infiltration, morphology and sources of indoor and outdoor fine particulate matter and metals at the urban residences of Agra, India DOI

Kirti Singh,

Neelam Baghel,

K. Maharaj Kumari

et al.

Indoor and Built Environment, Journal Year: 2025, Volume and Issue: unknown

Published: April 16, 2025

The United Nations proposed Sustainable Development Goals to promote healthy, safe and resilient lives. In recent years, indoor air pollution has been attracting increasing consideration listed as one of the prime environmental hazards. Thus, it is vital investigate influence outdoor on quality. To fill this lacuna, study conducted simultaneous indoor–outdoor measurements particulate matter with a diameter ≤2.5 μm (PM 2.5 ) their metallic composition (Zn, Na, Cr, Cu, Ba, Ni, Ca, Al, Mg, Fe, K Pb) in urban residential buildings Agra. Results showed higher PM concentrations indoors (83.2±15.8 μg/m 3 compared outdoors (73.5±12.2 an indoor/outdoor ratio 1.13, indicating dominance emission sources (cooking building materials). Infiltration analysis was applied transport particles. Zn, Ba Ni were high (I/O > 1) while Pb dominant < 1). This identified four potential source factors both outdoor. Field scanning electron microscope revealed difference morphologies (mostly spheroidal particles C, S, Cl indoors). These findings will help develop strategies control metals , reducing adverse health effects.

Language: Английский

Citations

0
Analyzing methane emissions in five Indian cities using TROPOMI data from sentinel-5 precursor satellite DOI
Gourav Suthar, Saurabh Singh,

Nivedita Kaul

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 58, P. 102174 - 102174

Published: Oct. 19, 2024

Language: Английский

Citations

3
A UAV-based method for efficiently measuring the spatial pattern of multiple air pollutants in street canyons DOI
Peng Ren,

Wentong Hu,

Sainan Lin

et al.

Building and Environment, Journal Year: 2024, Volume and Issue: 266, P. 112068 - 112068

Published: Sept. 8, 2024

Language: Английский

Citations

2
Synergistic effects of carbon and heat under disturbance of human activities: Evidence from a resource-based city of China DOI
Yaping Zhang, Jianjun Zhang, Wei Chen

et al.

Environmental Pollution, Journal Year: 2024, Volume and Issue: unknown, P. 125424 - 125424

Published: Dec. 1, 2024

Language: Английский

Citations

2
Relationship of Rice Farming Income with Socio-Economic Characteristics of Farmers DOI Open Access
Syamsu Qamar Badu, Mohamad Ikbal Bahua,

Sarson W. Pomalato

et al.

Journal of Economics Finance and Management Studies, Journal Year: 2024, Volume and Issue: 07(05)

Published: May 31, 2024

Characteristics are ways of thinking and behavior that characterize each individual to live work together in a family environment social community. The purpose the study was analyze relationship between rice farming income socio-economic characteristics farmers. research method used is survey method. Data this primary data sourced from respondents obtained through interviews using questionnaires, which consists on factors, namely; age farmers, farmers ' education, experience, number dependents, as well economic namely: land area capital. While secondary supporting Department Agriculture other stakeholders. Determination location purposive sampling for simple random many 30 analysis Pearson Correlation analysis. results showed that: has positive not significant with income, level Education experience dependents very capital farming.

Language: Английский

Citations

1
Impact of vegetation cover and land surface temperature on the seasonal tropospheric NO2 level variation from satellite observation DOI
Muhammad Rendana,

Muhammad Hatta Dahlan,

Febrinasti Alia

et al.

Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(10), P. 4760 - 4772

Published: July 30, 2024

Language: Английский

Citations

0