Carbon dioxide (CO2) emissions from the service industry, traffic, and secondary industry as revealed by the remotely sensed nighttime light data
- 30 June 2021
- journal article
- research article
- Published by Taylor & Francis Ltd in International Journal of Digital Earth
- Vol. 14 (11), 1514-1527
- https://doi.org/10.1080/17538947.2021.1946605
Abstract
Exploring carbon dioxide (CO2) emissions from human activities is essential for urban energy conservation and resource management. Remotely sensed nighttime lights from the Suomi NPP-VIIRS provide spatial consistency in and a low-cost way of revealing CO2 emissions. Although many researches have documented the feasibility of the Suomi NPP-VIIRS data for assessing CO2 emissions, few have systematically revealed the ability of nighttime lights for evaluating CO2 emissions from different industries, such as service industry CO2 emissions (SC), traffic CO2 emissions (TC), and secondary industry CO2 emissions (IC). Here, China was selected as the experimental subject, and we comprehensively explored the relationships between the nighttime lights and SC, TC, and IC, and investigated the factors mediating these relationships. We found that without considering other factors, the nighttime lights only revealed up to 51.2% of TC, followed by 41.7% of IC and 22.7% of SC. When controlling for city characteristic variables, the models showed that there were positive correlations between the Suomi NPP-VIIRS data and SC, IC, and TC, and that nighttime lights have an Inverted-U relationship with SC. The Suomi NPP-VIIRS data are more suitable for revealing SC, TC, and IC in medium-sized and large-sized cities than in small-sized cities and megacities.Keywords
Funding Information
- Key Research Program of Frontier Sciences, CAS (QYZDB-SSW-DQC011)
- MOE (Ministry of Education in China) Project of Humanities and Social Sciences (18XJC790011)
- Fundamental Research Founds for the Central Universities (XDJK2020B008)
This publication has 38 references indexed in Scilit:
- Generating the Nighttime Light of the Human Settlements by Identifying Periodic Components from DMSP/OLS Satellite ImageryEnvironmental Science & Technology, 2015
- Modeling and mapping total freight traffic in China using NPP-VIIRS nighttime light composite dataGIScience & Remote Sensing, 2015
- Regional-Scale Estimation of Electric Power and Power Plant CO2 Emissions Using Defense Meteorological Satellite Program Operational Linescan System Nighttime Satellite DataEnvironmental Science & Technology Letters, 2014
- Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areasRemote Sensing Letters, 2014
- Urban CO2 emissions in China: Spatial boundary and performance comparisonEnergy Policy, 2014
- Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS DataRemote Sensing, 2014
- Modeling the spatiotemporal dynamics of electric power consumption in Mainland China using saturation-corrected DMSP/OLS nighttime stable light dataInternational Journal of Digital Earth, 2013
- The Vegetation Adjusted NTL Urban Index: A new approach to reduce saturation and increase variation in nighttime luminosityRemote Sensing of Environment, 2013
- Night-time Imagery as a Tool for Global Mapping of Socioeconomic Parameters and Greenhouse Gas EmissionsAMBIO, 2000
- Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumptionInternational Journal of Remote Sensing, 1997