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The Atmospheric Environment Monitoring Satellite (AEMS), also called Daqi-1 or DQ-1, was launched in April 2022; one of its main payloads is a high-spectral-resolution lidar (HSRL) system. This new system enables the accurate measurements of global aerosol optical properties, which can be used in the geoscientific community after the retirement of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. Developing a suitable retrieval algorithm and validating retrieved results are necessary. This research demonstrates a retrieval algorithm for aerosol optical properties using the DQ-1 HSRL system. This method has retrieved the aerosol linear depolarization ratio, backscatter coefficient, extinction coefficient, and optical depth. For validation purposes, we compared retrieved results with those obtained through CALIPSO. The results indicate that the profiles of the two datasets are in good agreement, with DQ-1 showing an improved signal-to-noise ratio (SNR). Optical property profiles from National Aeronautics and Space Administration (NASA) Micro-Pulse Lidar Network (MPLNET) stations were selected for validation with the DQ-1 measurements, resulting in a relative error of 25 %. Between June 2022 and December 2022, aerosol optical depth measurements using the DQ-1 satellite and the AErosol RObotic NETwork (AERONET) were correlated and yielded a value of R2 equal to 0.803. We use the DQ-1 dataset to initially investigate the transport processes of the Saharan dust and the South Atlantic volcanic aerosols. These validations and applications show that the DQ-1 HSRL system can accurately measure global aerosols and has significant potential for Earth scientific applications. [ABSTRACT FROM AUTHOR]

In this work, we extracted the near-surface CO2 concentration from the Greenhouse gases Observing SATellite (GOSAT) and the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker model datasets for a temporal period of eight years from 2010 to 2017 to study the spatiotemporal distribution of near-surface CO2 and the factors affecting it over five regions of Asia, including Central Asia, East Asia, South Asia, Southeast Asia, and West Asia. The near-surface CO2 datasets from both satellite and model were first validated against the ground-based CO2 observations obtained from the World Data Center for Greenhouse Gases (WDCGG) stations located in Asia to confirm their applicability, and the results showed a good agreement between the datasets with significant correlations. The results from the time-series analyses showed a gradual increase in the near-surface CO2 with significant monthly and seasonal variations over all the regions. To study the factors affecting the spatial distribution of near-surface CO2, we investigated the relationship of near-surface CO2 with the anthropogenic CO2 emissions, terrestrial ecosystem, and winds. The results showed that, over Asia, the anthropogenic CO2 emissions and winds primarily controlled the spatial distribution of near-surface CO2. However, in the areas where anthropogenic emissions were lower, the terrestrial ecosystem and winds affected the near-surface CO2 distribution. To study the factors controlling the temporal distribution of near-surface CO2, the relationship of near-surface CO2 with vegetation, precipitation, and relative humidity was investigated. The results showed an inverse relationship between near-surface CO2 and normalized difference vegetation index (NDVI), precipitation, and relative humidity over monsoon-influenced regions, i.e., East Asia, South Asia, and Southeast Asia. However, a positive relation of near-surface CO2 was observed with precipitation and relative humidity over arid and semiarid regions, i.e., Central Asia and West Asia. The results were also verified by determining the correlations among these variables. [ABSTRACT FROM AUTHOR]

In this study, a lidar system based on the Fizeau interferometer and photomultiplier tube array is designed to analyze the entire Rayleigh‐Brillouin spectrum aiming at obtaining the atmospheric temperature profiles. The laser wavelength emitted by the lidar is 355 nm with the pulse energy of 20 mJ, and the diameter of the receiving telescope is 0.6 m. We analyze the influence of the cumulative average of different pulse numbers on the accuracy of temperature inversion. The temperature inversion results in different height ranges are calculated and the results show that if the integration time is 100 s, the temperature deviation is less than 3 K in the altitude range below 24 km. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas, and its concentration is continuously increasing, mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and for designing mitigation strategies aimed at stabilizing CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of the column-averaged dry-air mole fraction of CO2 , i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2), and the net primary productivity (NPP) provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the anthropogenic CO2 emissions using the Generalized Regression Neural Network (GRNN) over East and West Asia. OCO-2 XCO2 , MODIS NPP, and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variability. The XCO2 anomaly, NPP, and ODIAC emission datasets from 2015 to 2018 were then used to train the GRNN model, and, finally, the anthropogenic CO2 emissions were estimated for 2019 based on the NPP and XCO2 anomalies derived for the same year. The estimated and the ODIAC CO2 emissions were compared, and the results showed good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional-scale anthropogenic CO2 emissions, and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas and its concentration is continuously increasing mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and designing mitigation strategies aimed at stabilizing the CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of column-averaged dry-air mole fraction of CO2 i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory 2 (OCO-2) to estimate the anthropogenic CO2 emissions using Generalized Regression Neural Network over East and West Asia. OCO-2 XCO2 and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015-2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variabilities. Then the XCO2 anomaly and ODIAC emission datasets from 2015 to 2018 were used to train the GRNN model, and finally, the anthropogenic CO2 emissions were estimated for 2019 based on the XCO2 anomalies derived for the same year. The XCO2-based estimated and the ODIAC actual CO2 emissions were compared and the results showed a good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional scale anthropogenic CO2 emissions and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets. [ABSTRACT FROM AUTHOR]

In August 2022, China successfully launched the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS). The primary payload of this satellite is an onboard multi-beam lidar system, which is capable of observing aerosol optical parameters on a global scale. This pioneering study used the Fernald forward integration method to retrieve aerosol optical parameters based on the Level 2 data of the TECIS, including the aerosol depolarization ratio, aerosol backscatter coefficient, aerosol extinction coefficient, and aerosol optical depth (AOD). The validation of the TECIS-retrieved aerosol optical parameters was conducted using CALIPSO Level 1 and Level 2 data, with relative errors within 30%. A comparison of the AOD retrieved from the TECIS with the AERONET and MODIS AOD products yielded correlation coefficients greater than 0.7 and 0.6, respectively. The relative error of aerosol optical parameter profiles compared with ground-based measurements for CALIPSO was within 40%. Additionally, the correlation coefficients R2 with MODIS and AERONET AOD were approximately between 0.5 and 0.7, indicating the high accuracy of TECIS retrievals. Utilizing the TECIS retrieval results, combined with ground air quality monitoring data and HYSPLIT outcomes, a typical dust transport event was analyzed from 2 to 7 April 2023. The results indicate that dust was transported from the Taklamakan Desert in Xinjiang, China, to Henan and Anhui provinces, with a gradual decrease in the aerosol depolarization ratio and backscatter coefficient during the transport process, causing varying degrees of pollution in the downstream regions. This research verifies the accuracy of the retrieval algorithm through multi-source data comparison and demonstrates the potential application of the TECIS in the field of aerosol science for the first time. It enables the fine-scale regional monitoring of atmospheric aerosols and provides reliable data support for the three-dimensional distribution of global aerosols and related scientific applications. [ABSTRACT FROM AUTHOR]

The absorption characteristics of three types of trace gases (sulfur dioxide, nitrogen dioxide and nitric oxide) were simulated through line-by-line integral algorithm utilizing the HITRAN2012 database. The effect of temperature, pressure, and other interfering gases were analyzed in the mid-infrared band (2–5 μm) and suitable sets of wavelengths were proposed for the mid-infrared differential absorption lidar (MI-DIAL). The absorption spectrum of one typical trace gas was measured and it was found to be reasonably consistent with that of the simulated one. The lidar system simulated results showed that the selected sets of wavelength can be used in MI-DIAL to detect the polluted gases. [ABSTRACT FROM AUTHOR]

The CloudSat and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) are the members of satellite observation system of A-train to achieve the quasi-synchronization observation on the same orbit. With the help of active (CALIOP and CPR) and passive payloads from these two satellites, respectively, unprecedented detailed information of microphysical properties of ice cloud can be retrieved. The ice water content (IWC) is regarded as one of the most important microphysical characteristics of cirrus for its prominent role in cloud radiative forcing. In this paper, we proposed a new joint (Combination) retrieval method using the full advantages of different well established retrieval methods, namely the LIDAR method (for the region Lidar-only), the MWCR method (for the region Radar-only), and Wang method (for the region Lidar-Radar) proposed by Wang et al. (2002). In retrieval of cirrus IWC, empirical formulas of the exponential type were used for both thinner cirrus (detected by Lidar-only), thicker cirrus (detected by radar-only), and the part of cirrus detected by both, respectively. In the present study, the comparison of various methods verified that our proposed new joint method is more comprehensive, rational and reliable. Further, the retrieval information of cirrus is complete and accurate for the region that Lidar cannot penetrate and Radar is insensitive. On the whole, the retrieval results of IWC showed certain differences retrieved from the joint method, Ca&Cl, and ICARE which can be interpreted from the different hypothesis of microphysical characteristics and parameters used in the retrieval method. In addition, our joint method only uses the extinction coefficient and the radar reflectivity factor to calculate the IWC, which is simpler and reduces to some extent the accumulative error. In future studies, we will not only compare the value of IWC but also explore the detailed macrophysical and microphysical characteristics of cirrus. [ABSTRACT FROM AUTHOR]

The calibration of polarization lidar (PL) is of importance for its applications in aerosol and cloud detection. A calibration method for PL based on a Jones matrix is demonstrated in this paper. The backscattered parallel and perpendicular components are described using the Jones matrixes of optics in a transmitting and receiving system. Through rotation of the half wave plate (HWP), the Jones matrices of the optics can be retrieved by the application of a least square fitting method. These matrices may be the product of several matrices of different optical components or the matrix of a special optical component. The angle of HWP can be determined easily using retrieved matrices. The Jones matrix was employed in the receiving optics to correct the backscatter signals from the two PMTs of PL to obtain the corrected depolarization. The depolarization errors caused by the crosstalk and gain difference were analyzed, and case studies show the calibration method is effective and applicable. [ABSTRACT FROM AUTHOR]

Cirrus plays an important role in the regulation of the Earth-atmosphere radiation budget. The joint observation using both the LIght Detection And Ranging (LIDAR) and Millimeter-Wave Cloud RADAR (MWCR) was implemented in this study to obtain properties of cirrus at Atmospheric Radiation Measurement (ARM) mobile facility in Shouxian (32.56°N, 116.78°E, 21 m above sea level), China during May–December 2008. We chose the simultaneous measurements of LIDAR and MWCR with effective data days, and the days must with cirrus. Hence, the cirrus properties based on 37 days of data between October 18th and December 13th, 2008 were studied in the present work. By comparing the LIDAR data with the MWCR data, we analyzed the detection capabilities of both instruments quantitatively for measuring the cirrus. The LIDAR cannot penetrate through the thicker cirrus with optical depth (τ) of more than 1.5, while the MWCR cannot sense the clouds with an optical depth of less than 0.3. Statistical analysis showed that the mean cloud base height (CBH) and cloud thickness (CT) of cirrus were 6.5±0.8 km and 2.1±1.1 km, respectively. Furthermore, we investigated three existing inversion methods for deriving the ice water content (IWC) by using the separate LIDAR, MWCR, and the combination of both, respectively. Based on the comparative analysis, a novel joint method was provided to obtain more accurate IWC. In this joint method, cirrus was divided into three different categories according to the optical depth (τ≤0.3, τ≥1.5, and 0.3<τ<1.5). Based on the joint method used in this study, the mean IWC was calculated by means of the statistics, which showed that the mean IWC of cirrus was 0.011±0.008 g m −3 . [ABSTRACT FROM AUTHOR]

Methane (CH4) is recognized as the second most important greenhouse gas. An accurate and precise monitoring of methane gas globally has a vital role in studying the carbon cycle and global warming. The spaceborne integrated path differential absorption (IPDA) lidar is one of the most effective payload for methane detection. The simulation and optimization of the lidar system parameters can create an important base for the development of spaceborne payloads. However, previous IPDA lidar simulations have mostly used standard atmospheric models at simulation conditions, and to the best of our knowledge, there is no literature yet which applies a wavelength optimization to the IPDA system. In this study, we have investigated the relationship between the IPDA lidar system, based on wavelength optimization, and error measurement for CH4 column-averaged concentration. By selecting the wavelengths with the lowest comprehensive error as on-line and off-line, the error has been minimized by 10 ppb approximately relative to before optimization. We have proposed an IPDA simulation model at real atmospheric conditions, combining with ERA-5 reanalysis data, to simulate methane concentration globally, and present the distribution of errors. Finally, after the optimization of the lidar system parameters, we have ensured that the maximum inversion error for CH4 measurement is less than 10 ppb, to provide a reference for designing spaceborne IPDA lidar systems for high-precision CH4 column-averaged concentration detection. [ABSTRACT FROM AUTHOR]

Abstract: A cloud droplet probe based on forward scattering was developed. In this probe, a single-mode 685nm laser diode with single-mode fiber coupling was used as the transmitter, uniform illumination was obtained by combination of the optical 4F system and a pinhole behind the laser. A pinhole was used to measure the depth of field and the standard particles were used to calibrate the system. The probe was installed on an airplane and field observation experiments were conducted, the results showed this probe has the ability to measure cloud droplets. [Copyright &y& Elsevier]

Satellites are an effective source of atmospheric carbon dioxide (CO2) monitoring; however, city-scale monitoring of atmospheric CO2 through space-borne observations is still a challenging task due to the trivial change in atmospheric CO2 concentration compared to its natural variability and background concentration. In this study, we attempted to evaluate the potential of space-based observations to monitor atmospheric CO2 changes at the city scale through simple data-driven analyses. We used the column-averaged dry-air mole fraction of CO2 (XCO2) from the Carbon Observatory 2 (OCO-2) and the anthropogenic CO2 emissions provided by the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product to explain the scenario of CO2 over 120 districts of Pakistan. To study the anthropogenic CO2 through space-borne observations, XCO2 anomalies (MXCO2) were estimated from OCO-2 retrievals within the spatial boundary of each district, and then the overall spatial distribution pattern of the MXCO2 was analyzed with several datasets including the ODIAC emissions, NO2 tropospheric column, fire locations, cropland, nighttime lights and population density. All the datasets showed a similarity in the spatial distribution pattern. The satellite detected higher CO2 concentrations over the cities located along the China–Pakistan Economic Corridor (CPEC) routes. The CPEC is a large-scale trading partnership between Pakistan and China and large-scale development has been carried out along the CPEC routes over the last decade. Furthermore, the cities were ranked based on mean ODIAC emissions and MXCO2 estimates. The satellite-derived estimates showed a good consistency with the ODIAC emissions at higher values; however, deviations between the two datasets were observed at lower values. To further study the relationship of MXCO2 and ODIAC emissions with each other and with some other datasets such as population density and NO2 tropospheric column, statistical analyses were carried out among the datasets. Strong and significant correlations were observed among all the datasets. [ABSTRACT FROM AUTHOR]

The variation trends and characteristics of polar mesospheric clouds (PMCs) are important for studying the evolution of atmospheric systems and understanding various atmospheric dynamic processes. Through observation and analysis of PMCs, we can gain a comprehensive understanding of the mechanisms driving atmospheric processes, providing a scientific basis and support for addressing climate change. Ultraviolet (UV) imaging technology, adopted by the Cloud Imaging and Particle Size (CIPS) instrument on board the Aeronomy of Ice in the Mesosphere (AIM) satellite, has significantly advanced the research on PMCs. Due to the retirement of the AIM satellite, there is currently no concrete plan for next-generation instruments based on the CIPS model, resulting in a discontinuity in the observation data sequence. In this study, we propose a compact and cost-effective wide-field-of-view ultraviolet imager (WFUI) that can be integrated into various satellite platforms for future PMC observation missions. A forward model was built to evaluate the detection capability and efficiency of the WFUI. CIPS and Solar Occultation for Ice Experiment (SOFIE) data were fused to reconstruct a three-dimensional PMC scene as the input background. Based on the scattering and extinction characteristics of ice particles and atmospheric molecules, the radiative transfer was calculated using the solar radiation path through the atmosphere and PMCs. The optical system and satellite platform parameters of the WFUI were selected according to CIPS, enabling the calculation of the number of photons received by the WFUI. The actual detection signal is then simulated by photoelectric conversion, and the PMC information can be obtained by removing detector noise. Subsequently, a comparison with the input background field was conducted to compute and analyze the detection efficiency. Additionally, a sensitivity analysis of the instrument and platform parameters was conducted. Simulations were performed for both individual orbits and for the entire PMC seasons. The research results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. Statistical analysis of the detection efficiency using data from 2008 to 2012 revealed an exponential relationship between the ice water content (IWC) of PMCs and detection efficiency. During the initial and final durations of the PMC season, when the IWC was relatively low, the detection efficiency remained limited. However, as the season progressed and the IWC increased, the detection efficiency significantly improved. We note that regions at lower latitudes exhibited a lower IWC and, consequently, lower detection efficiency. In contrast, regions at higher latitudes, with a greater IWC, demonstrated better detection efficiency. Additionally, the sensitivity analysis results suggest that increasing the satellite orbit altitude and expanding the field of view (FOV) of the WFUI both contribute to improving the detection efficiency. [ABSTRACT FROM AUTHOR]

Accurate monitoring of atmospheric carbon dioxide (CO2) is of great significance for studying the carbon cycle. Compared to ground observational sites, airborne observations cover a wider area, which help in effectively monitoring the distribution of CO2 sources and sinks. In this study, an airborne campaign was carried out in June and July 2021 to measure the atmospheric CO2 concentration over a desert site, Dunhuang, located in western China. The dry-air column-averaged CO2 mole fraction (XCO2) inversion results obtained from the Atmospheric Carbon Dioxide Lidar (ACDL) system were compared with the Orbiting Carbon Observatory 2 (OCO-2) retrievals, portable Fourier Transform Spectrometer (EM27/SUN) measurement results, and with the XCO2 estimates derived using the airborne Ultraportable Greenhouse Gas Analyzer (UGGA) and the Copernicus Atmosphere Monitoring Service (CAMS) model measurements. Moreover, the vertical CO2 profiles obtained from the OCO-2 and the CAMS datasets were also compared with the airborne UGGA measurements. OCO-2 and CAMS CO2 measurements showed a vertical distribution pattern similar to that of the aircraft-based measurements of atmospheric CO2. In addition, the relationship of atmospheric CO2 with the aerosol optical depth (AOD) was also determined and the results showed a strong and positive correlation between the two variables. [ABSTRACT FROM AUTHOR]

This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds. [ABSTRACT FROM AUTHOR]

In the present paper, we have analyzed the spatiotemporal distributions and trends of aerosol optical depth observed at 550 nm (AOD 550), and its relation with the optical properties of clouds over East China. For this purpose, we have used the long-term (2000–2017) data obtained from the Moderate-resolution Imaging Spectroradiometer (MODIS) Terra satellite to examine and understand the existing relationship between them. The spatial gradient of AOD 550 showed an increase from the South to the North of the study domain. However, the seasonal variation of AOD 550 was found high in summer and low during the winter. We have noticed a significant increasing trend in AOD over the northern part of the study area, especially in autumn and winter seasons. The study also investigated the spatial and temporal changes to understand the relationship between AOD and cloud properties, namely cloud fraction (CF), cloud top temperature (CTT), Cloud effective radius (CER) and cloud top pressure (CTP), respectively. Besides, the linear regression analysis was conducted to estimate the time series trend for the aerosol and cloud properties during the study period. Further, the regional correlation maps were adopted to improve our understanding of the existing relationship between aerosol and cloud properties. A positive correlation between AOD and CF and CER is evident in most of the places in East China. Image 1 • Aerosol and cloud properties exhibited substantial spatial and temporal variabilities in the recent years over East China. • Significant increasing (decreasing) trend in AOD (CTT and CTP) was found over the Shandong Province in the North of the study domain. • Moderate to high positive correlations were noticed between AOD and CER attributed to the dynamics played by the meteorology. [ABSTRACT FROM AUTHOR]

Accurate knowledge of the carbon budget on global and regional scales is critically important to design mitigation strategies aimed at stabilizing the atmospheric carbon dioxide (CO2) emissions. For a better understanding of CO2 variation trends over Asia, in this study, the column-averaged CO2 dry air mole fraction (XCO2) derived from the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker (CT) was compared with that of Greenhouse Gases Observing Satellite (GOSAT) from September 2009 to August 2019 and with Orbiting Carbon Observatory 2 (OCO-2) from September 2014 until August 2019. Moreover, monthly averaged time-series and seasonal climatology comparisons were also performed separately over the five regions of Asia; i.e., Central Asia, East Asia, South Asia, Southeast Asia, and Western Asia. The results show that XCO2 from GOSAT is higher than the XCO2 simulated by CT by an amount of 0.61 ppm, whereas, OCO-2 XCO2 is lower than CT by 0.31 ppm on average, over Asia. The mean spatial correlations of 0.93 and 0.89 and average Root Mean Square Deviations (RMSDs) of 2.61 and 2.16 ppm were found between the CT and GOSAT, and CT and OCO-2, respectively, implying the existence of a good agreement between the CT and the other two satellites datasets. The spatial distribution of the datasets shows that the larger uncertainties exist over the southwest part of China. Over Asia, NOAA CT shows a good agreement with GOSAT and OCO-2 in terms of spatial distribution, monthly averaged time series, and seasonal climatology with small biases. These results suggest that CO2 can be used from either of the datasets to understand its role in the carbon budget, climate change, and air quality at regional to global scales. [ABSTRACT FROM AUTHOR]

Developments in mid-infrared Differential Absorption Lidar (DIAL), for gas remote sensing, have received a significant amount of research in recent years. In this paper, a high repetition rate tunable mid-infrared DIAL, mounted on a mobile platform, has been built for long range remote detection of gas plumes. The lidar uses a solid-state tunable optical parametric oscillator laser, which can emit laser pulse with repetition rate of 500 Hz and between the band from 2.5 μm to 4 μm. A monitoring channel has been used to record the laser energy in real-time and correct signals. Convolution correction technology has also been incorporated to choose the laser wavelengths. Taking NO2 and SO2 as examples, lidar system calibration experiment and open field observation experiment have been carried out. The observation results show that the minimum detection sensitivity of NO2 and SO2 can reach 0.07 mg/m3, and 0.31 mg/m3, respectively. The effective temporal resolution can reach second level for the high repetition rate of the laser, which demonstrates that the system can be used for the real-time remote sensing of atmospheric pollution gas. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, west China. The average column mole fractions of CO2 (XCO2) and CH4 (XCH4) were 413.00 ± 1.09 ppm and 1876 ± 6 ppb, respectively, which were 0.90 ppm and 72 ppb lower than their surface values. Diurnal XCO2 showed a sinusoidal mode, while XCH4 appeared as a unimodal distribution. Ground observed XCO2 and XCH4 were compared with international satellites, such as GOSAT, GOSAT-2, OCO-2, OCO-3, and Sentinel-5P. The differences between satellites and EM27/SUN observations were 0.26% for XCO2 and −0.38% for XCH4, suggesting a good consistency between different satellites and ground observations in desert regions in China. Hourly XCO2 was close to surface CO2 mole fractions, but XCH4 appeared to have a large gap with CH4, probably because of the additional chemical removals of CH4 in the upper atmosphere. It is necessary to carry out a long-term observation of column mole fractions of greenhouse gases in the future to obtain their temporal distributions as well as the differences between satellites and ground observations. [ABSTRACT FROM AUTHOR]

The variation trends and characteristics of polar mesospheric clouds (PMCs) are important for studying the evolution of atmospheric systems and understanding various atmospheric dynamic processes. Through observation and analysis of PMCs, we can gain a comprehensive understanding of the mechanisms driving atmospheric processes, providing a scientific basis and support for addressing climate change. Ultraviolet (UV) imaging technology, adopted by the Cloud Imaging and Particle Size (CIPS) instrument onboard the Aeronomy of Ice in the Mesosphere (AIM) satellite, has significantly advanced the research on PMCs. Due to the retirement of the AIM satellite, there is currently no concrete plan for next-generation instruments based on the CIPS model, resulting in a discontinuity in the observation data sequence. In this study, we propose a compact and cost-effective wide field-of-view ultraviolet imager (WFUI) that can be integrated into various satellite platforms for future PMCs observation missions. A forward model was built to evaluate the detection capability and efficiency of the WFUI. The fusion of CIPS and solar occultation for ice experiment (SOFIE) data was employed to reconstruct a three-dimensional PMCs scene as the input background. Based on the scattering and extinction characteristics of ice particles and atmospheric molecules, the radiative transfer was calculated using the solar radiation path through the atmosphere and PMCs. The optical system and satellite platform parameters of the WFUI were selected according to the CIPS, enabling the calculation of the number of photons received by the WFUI. The actual detection signal is then simulated by photoelectric conversion, and the PMCs information can be obtained by removing detector noise. Subsequently, a comparison with the input background field was conducted to compute and analyze the detection efficiency. Additionally, a sensitivity analysis of the instrument and platform parameters was conducted. Simulations were performed for both individual orbits and for the entire PMCs seasons. The research results demonstrate that using data from 2008 to 2012 revealed an exponential relationship between the ice water content (IWC) of PMCs and detection efficiency. During the initial and final durations of the PMCs season, when the IWC was relatively low, the detection efficiency the WFUI performs well in PMCs detection and has high detection efficiency. Statistical analysis of the detection efficiency remained limited. However, as the season progressed and the IWC increased, the detection efficiency significantly improved. We note that regions at lower latitudes exhibited a lower IWC and, consequently, lower detection efficiency. In contrast, regions at higher latitudes, with a greater IWC, demonstrated better detection efficiency. Additionally, the sensitivity analysis results suggest that increasing the satellite orbit altitude and expanding the field of view (FOV) of the WFUI both contribute to improving the detection efficiency. [ABSTRACT FROM AUTHOR]

Accurate monitoring of atmospheric carbon dioxide (CO 2) 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 CO 2 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 CO 2 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 CO 2 column-averaged dry-air mixing ratio (XCO 2) was calculated over different types of surfaces including mountain, ocean, and urban areas. The concentrations of the XCO 2 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 CO 2 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 PM 2.5 of 131 µ g 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 CO 2 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 CO 2 concentrations, which showing a good agreement among them. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the present study, the spatial-temporal distribution and estimation of trends of different aerosol optical properties, and related impact factors were investigated over three countries: Ghana, Togo, and Benin along the Gulf of Guinea Coast in Southern West Africa (SWA). For this purpose, long-term satellite derived aerosol optical properties (aerosol optical depth at 550 nm; AOD 550 , Ångström exponent at 470–660 nm; AE 470-660 , and absorption aerosol index; AAI) retrieved from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) during January 2005–December 2015 were utilized. The annual mean spatial distribution of AOD 550 was found to be high (>0.55) over the southern coastal area, moderate-to-high (0.35–0.55) over the central, and low (<0.35) over northern parts of the study domain. The seasonal mean variations showed high (low) values of AOD 550 and AAI during the Harmattan or dry (wet) season. Whereas, low (high) AE 470-660 values were characterized during the Harmattan (wet) season. Linear trend analysis revealed a decreasing trend in AOD 550 and AAI, and increasing trend in AE 470-660 . Further, an investigation on the potential drivers to AOD distribution over the SWA revealed that precipitation, NDVI, and terrain were negatively correlated with AOD. Finally, the HYSPLIT derived back trajectory analyses revealed diverse transport pathways originated from the North Atlantic Ocean, Sahara Desert, and Nigeria along with locally generated aerosols. [ABSTRACT FROM AUTHOR]

A planar silicon carbide/dielectric multilayer structure is investigated in Otto geometry, where surface phonon polaritons and planar waveguide mode can be coupled to realize Fano resonances under transverse magnetic polarization. The resonance coupling is analytically demonstrated using the coupled harmonic oscillator model and numerically presented through rigorous coupled-wave analysis calculations, which shows that the coupling strength between different resonances and the resonant wavelength matching condition plays an important role in the bandwidth and position of the Fano resonance (FR); the magnetic field distribution was also shown to explain the origin of FRs qualitatively. [ABSTRACT FROM AUTHOR]

One possibility of enhancing light absorption in monolayer graphene at near-infrared (NIR) wavelength region with grating structures is proposed and investigated. It is demonstrated that it is possible to achieve near-perfect absorption when a single monolayer graphene is sandwiched between two gratings with optimized geometric parameters at normal incidence for transverse electric (TE) polarization. By means of the rigorous coupled-wave analysis (RCWA), the effects of technological tolerances on the optical response of the structure by varying geometric parameters and incident angle are studied. The proposed photonic structure could be efficiently exploited as a building block for innovative optical absorbers or photodetectors in combination with active materials. [ABSTRACT FROM AUTHOR]

Oceans are widely regarded as major offsets for anthropogenic carbon emissions, leading to an evident lower measured atmospheric CO2 concentration than expected. It is thus of great significance to develop effective means to monitor CO2 fluxes over oceans globally. In this work, we utilized observations obtained by an airborne CO2‐IPDA LIDAR to evaluate the potential of such means in estimating sea‐air CO2 flux. During a flight experiment in 2019, we have estimated the CO2 exchange rate, −1.5 ± 0.18 mmol/m2/h, between the Bohai Bay and the atmosphere using equilibrium atmospheric boundary layer theory. These findings indicated that the forthcoming space‐borne CO2‐IPDA LIDAR is capable of identifying CO2 uptakes over oceans qualitatively, which would be a novel means and a basis for monitoring CO2 fluxes over global oceans. Plain Language Summary: Oceans are regarded as important offsets to anthropogenic CO2 emissions, delaying an increase in atmospheric CO2 concentration. However, there is a lack of understanding of the intensity, distribution, and variability of marine carbon sinks. China is due to launch a space‐borne LIDAR for measuring atmospheric CO2 concentration globally in 2021. In this work, we utilized data collected during a flight test for the forthcoming satellite mission to explore the ability of such a novel means in revealing and estimating CO2 fluxes of oceans quantitatively. Results confirmed an evident CO2 uptake in the Bohai Bay and exhibited a promising prospect for the novel CO2 measuring means. Key Points: We detected XCO2 gradient during a flight campaign in ChinaRetrieve XCO2 in the atmosphere boundary layer by cloud slicing methodProvide a model to retrieve CO2 flux over ocean by CO2‐IPDA system [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important greenhouse gas and several satellites have been launched to monitor the atmospheric CO2 at regional and global scales. Evaluation of the measurements obtained from these satellites against accurate and precise instruments is crucial. In this work, aircraft measurements of CO2 were carried out over Qinhuangdao, China (39.9354°N, 119.6005°E), on 14, 16, and 19 March 2019 to validate the Greenhous gases Observing SATellite (GOSAT) and the Orbiting Carbon Observatory 2 (OCO-2) CO2 retrievals. The airborne in situ instruments were mounted on a research aircraft and the measurements were carried out between the altitudes of ~0.5 and 8.0 km to obtain the vertical profiles of CO2. The profiles captured a decrease in CO2 concentration from the surface to maximum altitude. Moreover, the vertical profiles from GEOS-Chem and the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker were also compared with in situ and satellite datasets. The satellite and the model datasets captured the vertical structure of CO2 when compared with in situ measurements, which showed good agreement among the datasets. The dry-air column-averaged CO2 mole fractions (XCO2) retrieved from OCO-2 and GOSAT showed biases of 1.33 ppm (0.32%) and −1.70 ppm (−0.41%), respectively, relative to the XCO2 derived from in situ measurements. [ABSTRACT FROM AUTHOR]

This work presents a practical spectrophotometer based on passive remote sensing, the mesospheric airglow spectrum photometer (MASP). Also presented is a detailed description of its data processing. The MASP measures the rotational temperature from nighttime airglow emission of the O 2 (0–1) band. All components of the MASP are commercial standard components, making it cost-effective and easy to maintain and update. The housing of the MASP has excellent thermal insulation and is equipped with a small semiconductor thermoelectric cooler (TEC) air conditioner that guarantees a constant temperature for the instrument. The calibration of the instrument parameters and the forward model simulation of synthetic spectra are described in detail. Moreover, the data processing is adjusted according to the characteristics of MASP, especially for the removal of background continuum. Observation results show that the MASP is capable of measuring disturbances caused by a small-scale gravity wave and by tidal waves with periods of 4 or 8 h. Comparisons with the NRLMSISE-00 atmospheric model also show a more consistent trend of averaged daily temperature variation. Accordingly, the MASP is suitable for installation at multiple stations to perform long-term and stable synchronous network observation. • MASP is cost affordable and easier to maintain and update. • The data processing is refined especially for the removal of background continuum. • MASP is capable of measuring disturbances caused by GW and tidal waves. [ABSTRACT FROM AUTHOR]

We analyzed a June 2018 Nanjing, China haze event using ground-based and spaceborne sensors, combined with sounding and HYSPLIT backward trajectory data, with the ground-based and spaceborne sensor data exhibiting good consistency. Water vapor content showed significant positive correlation with AOD (aerosol optical depth), and AOD measured in urban and industrial areas was much higher compared to other similar zones. The afternoon convection caused the aerosol uplift during the haze event. Higher aerosol concentration was detected below 2 km. Due to the summer afternoon convective movement, pollutants at high altitude were dominated by small particles, while the overall pollutant mix was dominated by mixed aerosols. During a stable period over June 11–18, a single, near-surface inversion layer, and occasional two inversion layers, stopped pollutant dispersal, with only very stable ocean air mass transport in the southeast direction available. The Air Quality Index drop which took place during June 28–30 was caused by two inversion layers, combined with the immigration of pollutants from inland air masses. [ABSTRACT FROM AUTHOR]

Highlights • Evaluation of vertical feature type and aerosol sub-type of V3 and V4.1 observed from the CALIPSO. • Investigate the impact of dust aerosol on cirrus properties combining the CloudSat with CALIPSO. • Analyze the differences in microphysical properties observed during dust and dust-free cirrus. Abstract The present study elucidates on the evaluation of two versions (V3 and V4.10) of vertical feature mask (VFM) and aerosol sub-types data derived from the Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations (CALIPSO), and its utilization to analyze the impact of dust aerosol on the microphysical properties of cirrus over the Tibetan Plateau (TP). In conjunction to the CALIPSO, we have also used the CloudSat data to study the same during the summer season for the years 2007–2010 over the study area 25–40°N and 75–100°E. Compared to V3 of CALIPSO, V4.10 was found to have undergone substantial changes in the code, algorithm, and data products. Intercomparison of both versions of data products in the selected grid between 30–31°N and 83–84°E within the study area during 2007–2017 revealed that the VFM and aerosol sub-types are in good agreement of ∼95.27% and ∼82.80%, respectively. Dusty cirrus is defined as the clouds mixed with dust aerosols or existing in dust aerosol conditions, while the pure cirrus is that in a dust-free environment. The obtained results illustrated that the various microphysical properties of cirrus, namely ice water content (IWC), ice water path (IWP), ice distribution width (IDW), ice effective radius (IER), and ice number concentration (INC) noticed a decrease of 17%, 18%, 4%, 19%, and 10%, respectively due to the existence of dust aerosol, consistent with the classical "Twomey effect" for liquid clouds. Moreover, the aerosol optical depth (AOD) showed moderate negative correlations between −0.4 and −0.6 with the microphysical characteristics of cirrus. As our future studies, in addition to the present work undertaken, we planned to gain knowledge and interested to explore the impact of a variety of aerosols apart from the dust aerosol on the microphysical properties of cirrus in different regions of China. [ABSTRACT FROM AUTHOR]

This article presents a new method for retrieving the Ice Water Path (IWP), the median volume equivalent sphere diameter (Dme) of thin ice clouds (IWP < 100 g/m2, Dme < 80 μm) in the Terahertz band. The upwelling brightness temperature depressions caused by the ice clouds at 325.15, 448.0, 664.0 and 874.0 GHz channels are simulated by the Atmospheric Radiative Transfer Simulator (ARTS). The simulated forward radiative transfer models are taken as historical data for the M5 model tree algorithm to construct a set of piecewise functions which represent the relation of simulated brightness temperature depressions and IWP. The inversion results are optimized by an empirical relation of the IWP and the Dme for thin ice clouds which is summarized by previous studies. We inverse IWP and Dme with the simulated brightness temperature and analyze the inversion performance of selected channels. The 874.4 ± 6.0 GHz channel provides the most accurate results, because of the strong brightness temperature response to the change of IWP in the forward radiative transfer model. In order to improve the thin ice clouds IWP and Dme retrieval accuracy at the middle-high frequency channels in Terahertz band, a dual-channel inversion method was proposed that combines the 448.0± 3.0 GHz and 664.0 ± 4.2 GHz channel. The error analysis shows that the results of the 874.4 ± 6.0 GHz channel and the dual-channel inversion are reliable, and the IWP inversion results meet the error requirement range proposed by previous studies. [ABSTRACT FROM AUTHOR]

The demand for greenhouse gas measurement has increased dramatically due to global warming. A 1.57-μm airborne double-pulse integrated-path differential absorption (IPDA) light detection and ranging (LIDAR) system for CO2 concentration measurement was developed. The airborne field experiments of this IPDA LIDAR system were conducted at a flight altitude of approximately 7 km, and the weak echo signal of the ocean area was successfully received. The matched filter algorithm was applied to the retrieval of the weak signals, and the pulse integration method was used to improve the signal-to-noise ratio. The inversion results of the CO2 column-averaged dry-air mixing ratio (XCO2) by the scheme of averaging after log (AVD) and the scheme of averaging signals before log were compared. The AVD method was found more effective for the experiment. The long-term correlation between the changing trends of XCO2 retrieved by the IPDA LIDAR system and CO2 dry-air volume mixing ratio measured by the in-situ instrument reached 92%. In the steady stage of the open area (30 km away from the coast), which is almost unaffected by the residential areas, the mean value of XCO2 retrieved by the IPDA LIDAR system was 414.69 ppm, with the standard deviation being 1.02 ppm. Compared with the CO2 concentration measured by the in-situ instrument in the same period, bias was 1.30 ppm. The flight path passed across the ocean, residential, and mountainous areas, with the mean value of XCO2 of the three areas being 419.35, 429.29, and 422.52 ppm, respectively. The gradient of the residential and ocean areas was 9.94 ppm, with that of the residential and mountainous areas being 6.77 ppm. Obvious gradients were found in different regions. [ABSTRACT FROM AUTHOR]