scholarly journals Atmospheric carbon dioxide measurement from aircraft and comparison with OCO-2 and CarbonTracker model data

2021 ◽  
Vol 14 (10) ◽  
pp. 6601-6617
Author(s):  
Qin Wang ◽  
Farhan Mustafa ◽  
Lingbing Bu ◽  
Shouzheng Zhu ◽  
Jiqiao Liu ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Optical Depth ◽  
Urban Areas ◽  
Atmospheric Carbon Dioxide ◽  
Co2 Concentration ◽  
Future Climate Change ◽  
Differential Absorption ◽  
Average Value ◽  
Pollution Levels ◽  
Atmospheric Carbon

Abstract. Accurate monitoring of atmospheric carbon dioxide (CO2) and its distribution is of great significance for studying the carbon cycle and predicting future climate change. Compared to the ground observational sites, the airborne observations cover a wider area and simultaneously observe a variety of surface types, which helps with effectively monitoring the distribution of CO2 sources and sinks. In this work, an airborne experiment was carried out in March 2019 over the Shanhaiguan area, China (39–41∘ N, 119–121∘ E). An integrated path differential absorption (IPDA) light detection and ranging (lidar) system and a commercial instrument, the ultraportable greenhouse gas analyser (UGGA), were installed on an aircraft to observe the CO2 distribution over various surface types. The pulse integration method (PIM) algorithm was used to calculate the differential absorption optical depth (DAOD) from the lidar data. The CO2 column-averaged dry-air mixing ratio (XCO2) was calculated over different types of surfaces including mountain, ocean, and urban areas. The concentrations of the XCO2 calculated from lidar measurements over ocean, mountain, and urban areas were 421.11 ± 1.24, 427.67 ± 0.58, and 432.04 ± 0.74 ppm, respectively. Moreover, through the detailed analysis of the data obtained from the UGGA, the influence of pollution levels on the CO2 concentration was also studied. During the whole flight campaign, 18 March was the most heavily polluted day with an Air Quality Index (AQI) of 175 and PM2.5 of 131 µg m−3. The aerosol optical depth (AOD) reported by a sun photometer installed at the Funing ground station was 1.28. Compared to the other days, the CO2 concentration measured by UGGA at different heights was the largest on 18 March with an average value of 422.59 ± 6.39 ppm, which was about 10 ppm higher than the measurements recorded on 16 March. Moreover, the vertical profiles of Orbiting Carbon Observatory-2 (OCO-2) and CarbonTracker were also compared with the aircraft measurements. All the datasets showed a similar variation with some differences in their CO2 concentrations, which showing a good agreement among them.

scholarly journals Atmospheric Carbon Dioxide Measurement from Aircraft and Comparison with OCO-2 and Carbon Tracker Model Data

2021 ◽  
Author(s):  
Qin Wang ◽  
Farhan Mustafa ◽  
Lingbing Bu ◽  
Shouzheng Zhu ◽  
Jiqiao Liu ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Optical Depth ◽  
Urban Areas ◽  
Atmospheric Carbon Dioxide ◽  
Co2 Concentration ◽  
Future Climate Change ◽  
Differential Absorption ◽  
Average Value ◽  
Pollution Levels ◽  
Atmospheric Carbon

Abstract. Accurate monitoring of the atmospheric carbon dioxide (CO2) and its distribution is of great significance for studying the carbon cycle and predicting the future climate change. Compared to the ground observational sites, the airborne observations cover a wider area, and simultaneously observe a variety of surface types, which help in effectively monitoring the distribution of CO2 sources and sinks. In this work, an airborne experiment was carried out in March 2019 over Shanhaiguan area, China (39–41N,119–121E). An Integrated Path Differential Absorption (IPDA) Light Detection and Ranging (LIDAR) system and a commercial instrument, the Ultraportable Greenhouse Gas Analyzer (UGGA), were used installed on an aircraft to observe the CO2 distribution over various surface types. The Pulse Integration Method (PIM) algorithm was used to calculate the Differential Absorption Optical Depth (DAOD) from the LIDAR data. The CO2 column-averaged dry-air mixing ratio (XCO2) was calculated over different types of surfaces including mountain, ocean and urban areas. The concentrations of the XCO2 calculated from LIDAR measurements over ocean, mountain, and urban areas were 421.11, 427.67, and 430 ppm, respectively. Moreover, through the detailed analysis of the data obtained from the UGGA, the influence of pollution levels on the CO2 concentration was also studied. During the whole flight campaign, March 18 was heavily polluted with an Air Quality Index (AQI) of 175 and PM2.5 of 131. The Aerosol Optical Depth (AOD) reported by a sun photometer installed at the Funning ground station was 1.28. Compared to the other days, the CO2 concentration measured by UGGA at different heights was the largest on March 18 with an average value of 422.59 ppm, that was about 10 ppm higher than the measurements recorded on March 16. Moreover, the vertical profiles of Orbiting Carbon observatory-2 (OCO-2) OCO-2 and CarbonTracker were also compared with the aircraft measurements. All the datasets showed a similar variation trend with some differences in their CO2 concentrations, which proved the existence of a good agreement among them.

scholarly journals Marine biodiversity–ecosystem functions under uncertain environmental futures

2010 ◽  
Vol 365 (1549) ◽  
pp. 2107-2116 ◽  
Author(s):  
Mark T. Bulling ◽  
Natalie Hicks ◽  
Leigh Murray ◽  
David M. Paterson ◽  
Dave Raffaelli ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Species Richness ◽  
Ecosystem Functioning ◽  
Atmospheric Carbon Dioxide ◽  
Nutrient Release ◽  
Future Climate Change ◽  
Marine Biodiversity ◽  
Invertebrate Species ◽  
Atmospheric Carbon

Anthropogenic activity is currently leading to dramatic transformations of ecosystems and losses of biodiversity. The recognition that these ecosystems provide services that are essential for human well-being has led to a major interest in the forms of the biodiversity–ecosystem functioning relationship. However, there is a lack of studies examining the impact of climate change on these relationships and it remains unclear how multiple climatic drivers may affect levels of ecosystem functioning. Here, we examine the roles of two important climate change variables, temperature and concentration of atmospheric carbon dioxide, on the relationship between invertebrate species richness and nutrient release in a model benthic estuarine system. We found a positive relationship between invertebrate species richness and the levels of release of NH 4 -N into the water column, but no effect of species richness on the release of PO 4 -P. Higher temperatures and greater concentrations of atmospheric carbon dioxide had a negative impact on nutrient release. Importantly, we found significant interactions between the climate variables, indicating that reliably predicting the effects of future climate change will not be straightforward as multiple drivers are unlikely to have purely additive effects, resulting in increased levels of uncertainty.

scholarly journals INVESTIGATING THE HISTORICAL CORRELATION BETWEEN ATMOSPHERIC CARBON DIOXIDE CONCENTRATION AND GLOBAL TEMPERATURE CHANGE

2021 ◽  
pp. 5-16
Author(s):  
Kneev Sharma ◽  
Dimitre Karamanev
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Temperature Rise ◽  
Atmospheric Carbon Dioxide ◽  
Carbon Dioxide Concentration ◽  
Co2 Concentration ◽  
Global Temperature ◽  
Atmospheric Carbon Dioxide Concentration ◽  
Important Relationship ◽  
Atmospheric Carbon

Understanding the fundamental relationship between atmospheric carbon dioxide concentration and temperature rise is essential for tackling the problem of climate change that faces us today. Misconceptions regarding the relationship are widespread due to media and political influences. This investigation aims to address the popular misconception that CO2 concentration directly and naturally leads to global temperature rise. While anthropogenic CO2 emissions seem to affect the rising global atmospheric temperature with a confidence of 95%, it falters when the historical relationship using ice core data is studied. This investigation uses two statistical approaches to determine an accurate range and direction for this important relationship. Through a combined approach, it was found that historically CO2 concentration in the last 650 000 years lags global temperature rise by 1020-1080 years with a maximum correlation coefficient of 0.8371-0.8372. This result is important for the investigation of climate change.

scholarly journals Atmospheric Carbon Dioxide and Electricity Production Due to Lockdown

2020 ◽  
Vol 12 (22) ◽  
pp. 9397
Author(s):  
Yusri Yusup ◽  
Nur Kamila Ramli ◽  
John Stephen Kayode ◽  
Chee Su Yin ◽  
Sabiq Hisham ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Energy Demand ◽  
Atmospheric Carbon Dioxide ◽  
Phase 1 ◽  
Co2 Concentration ◽  
The United States ◽  
Atmospheric Co2 ◽  
Electricity Production ◽  
Atmospheric Carbon ◽  
The Impact

We analyzed real-time measurements of atmospheric carbon dioxide (CO2), with total electricity production and nationwide restrictions phases in China, the United States of America, Europe, and India due to the novel coronavirus COVID-19 pandemic and its effects on atmospheric CO2. A decline of 3.7% in the global energy demand at about 150 million tonnes of oil equivalent (Mtoe) in the first quarter (Q1) of 2020 was recorded compared to Q1 2019 due to the cutback on international economic activities. Our results showed that: (1) electricity production for the same period in 2018, 2019, and 2020 shrunk at an offset of 9.20%, which resulted in a modest reduction (−1.79%) of atmospheric CO2 to the 2017–2018 CO2 level; (2) a non-seasonal, abrupt, and brief atmospheric CO2 decrease by 0.85% in mid-February 2020 could be due to Phase 1 restrictions in China. The results indicate that electricity production reduction is significant to the short-term variability of atmospheric CO2. It also highlights China’s significant contribution to atmospheric CO2, which suggests that, without the national restriction of activities, CO2 concentration is set to exceed 2019 by 1.79%. Due to the lockdown, it quickly decreased and sustained for two months. The results underscore atmospheric CO2 reductions on the monthly time scale that can be achieved if electricity production from combustible sources was slashed. The result could be useful for cost-benefit analyses on the decrease in electricity production of combustible sources and the impact of this reduction on atmospheric CO2.

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