Comparative Evaluation of Satellite- Based Merra-2 against Ground-based Data for PM2.5 and TC Concentrations in Ghaziabad, India

Author:

Sinha Rishika,Madan Preha,Singh Rahul,Gupta Lovleen

Abstract

This study compares satellite-based observations of PM2.5 and Total Carbon (TC) concentrations derived from NASA’s MERRA-2 reanalysis dataset for the Ghaziabad region with ground-based observations at two sites (Site A and Site B) from June 2018 to May 2019. Results reveal consistent underestimation by MERRA-2, with daily mean biases of -85.34 (Site A) and -111.31 (Site B) for PM2.5, and -54.77 (Site A) to -59.08 (Site B) for TC, alongside monthly mean biases of -81.30 to -103.74 for PM2.5 and -54.77 to -59.08 for TC. The absolute error indicates a 49.01% to 53.85% underestimation for both PM2.5 and TC. Daily FAC2 values show around 39% agreement for PM2.5, reducing to 0.27 (Site A) and 0.3 (Site B) monthly, indicating reduced agreement over time. For TC, daily FAC2 is notably low at 0.04 (Site A) and 0.06 (Site B), with no monthly agreement within a factor of 2 of ground-level data. Strong correlations (R²=0.68-0.84 for PM2.5; R²=0.94-0.96 for TC) between biases and ground-level data are observed, indicating proportional relationships. However, discrepancies increase with higher PM2.5 mass concentration, highlighting MERRA-2’s limitations during elevated pollution periods. Significant monthly variations are observed in GLC-PM2.5 concentrations at Site A (F= 61.42, p= 1.68×10-11) and Site B (F=25.15, p=2.96×10-06), and For GLC-TC concentrations at Site A (F=103.85, p=4.10×10-16) and Site B (F=55.70, p=7.54×10-11). Both GLC and MERRA-2 PM2.5 and TC concentrations follow a consistent monthly pattern, with higher levels during post-monsoon and winter seasons and lower levels during monsoon and pre-monsoon periods. This study underscores MERRA-2’s limitations in estimating PM2.5 and TC concentrations compared to ground-based observations and emphasises the necessity for further refinement and validation of the MERRA-2 model to enhance accuracy across different spatial and temporal scales.

Publisher

EDP Sciences

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3