The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.
Integrated-path differential absorption (IPDA) LiDAR is a promising means of measuring the global distributions of the column weighted xCO2 (dry-air mixing ratio of CO2) with adequate accuracy and precision. Most IPDA LiDARs are incapable of discerning the vertical information of CO2 diffusion, which is of great significance for studies on the carbon cycle and climate change. Hence, we developed an inversion method using the constrained linear least-squares technique for a pulsed direct-detection multi-wavelength IPDA LiDAR to obtain sliced xCO2. In the proposed inversion method, the atmosphere is sliced into three different layers, and the xCO2 of those layers is then retrieved using the constrained linear least-squares technique. Assuming complete knowledge of the water vapor content, the accuracy of the retrieved sliced xCO2 could be as high as 99.85% when the signal-to-noise ratio of central wavelength retrievals is higher than 25 (with a log scale). Further experiments demonstrated that different carbon characteristics can be identified by the sign of the carbon gradient of the retrieved xCO2 between the ABL (atmospheric boundary layer) and FT (free troposphere). These results highlight the potential applications of multiple wavelength IPDA LiDAR.
The purpose of this study is to investigate the air quality levels of Nanyang city according to Chinese air quality standards. Therefore, in this study, fine particulate matter (PM2.5), coarse particulate matter (PM10), and total suspended particulate (TSP) were analyzed from 19 November 2021 to 19 March 2022 in Nanyang city. The results show that the average concentrations of PM2.5, PM10, and TSP were 106.47 µg/m3, 137.32 µg/m3, and 283.40 µg/m3, respectively. The numbers of days that meet the national secondary air quality standard of 24-h average concentrations were 29.75% for PM2.5, 63.64% for PM10, and 63.64% for TSP, indicating that most of the time, the air quality of Nanyang city remains polluted in winter, especially with more contributions of PM2.5 compared to PM10 and TSP. The higher concentrations were observed between 07:00 and 08:00, suggesting that vehicular emissions can be a major cause of air pollution in Nanyang city. The results also show a significant positive correlation between particulate matter and relative humidity, and a weak correlation with temperature and wind speed, which suggests that higher relative humidity increases the formation of particulate matter. This study can provide theoretical support for the local government to formulate air pollution prevention and control policies for Nanyang city.
To investigate the vertical distribution of aerosol optical characteristics in Nanyang City, a ground-based dual-wavelength (532 nm and 355 nm) lidar system was developed for aerosol observation at the Nanyang Normal University Station (NYNU) from November 2021 to December 2022. Spatio-temporal dynamics information on vertical distributions of aerosol optical properties during polluted and non-polluted days was obtained. Aerosols were characterized by low altitudes (up to 2 km), thinner layers, and high-altitude (up to 4 km) thick layers during non-polluted and polluted days, with extinction coefficient values of ~0.03 km−1 and ~0.2 km−1, respectively. The mean values of the extinction coefficient at different altitudes (0~5 km) were all about ten-times higher on polluted days (0.04~0.19 km−1) than on non-polluted days (0.004~0.02 km−1). These results indicate that aerosol loadings and variations at different altitudes (0~5 km) were much higher and more prominent on polluted days than non-polluted days. The results show ten-times larger aerosol optical depth (AOD) values (0.4~0.6) on polluted days than on non-polluted days (0.05~0.08). At the same time, AOD values on both polluted and non-polluted days slightly decreased from 19:00 to 05:00, possibly due to dry depositions at nighttime. For the first time, this study established a ground-based lidar remote sensing system to investigate the vertical distribution of atmospheric aerosol optical characteristics in Henan Province. The experimental results can provide scientific dataset support for the local government to prevent and control air pollution.
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