入江 仁士

Abstract In this study, we assessed air quality (AQ) and urban climate during the mobility restrictions implemented in the Greater Tokyo Area, Japan, the world’s most populated region, in response to the COVID-19 pandemic. Observations from dense surface networks were analyzed using an interpretable machine learning approach. In parallel with a ∼50% reduction in mobility and an altered lifestyle of the population, we found limited reductions in nitrogen dioxide; decreases in fine particulate matter not entirely driven by local mobility; minor variations in ozone, with a positive (negative) tendency in areas with high (low) emissions; a decrease in air temperature consistent with mobility; and pollution levels and air temperature changes with well-defined, common spatiotemporal patterns. Specifically, cooling mainly occurred in urbanized areas with an improved AQ. Overall, although reductions in mobility were moderately effective in improving the typical indicators of urban AQ, including those known to negatively impact human health, the reductions in waste heat had a stronger impact on Tokyo’s urban heat island, suggestive of a strategy to minimize exposure to heat stress. These findings can help guide urban planning strategies and policies aimed at addressing climate change.

Abstract. A horizontally pointing lidar is planned for deployment with other instruments in Fukushima, Japan, to continuously monitor and characterize the optical properties of radioactive aerosols and dust in an uninhabited area. Prior to installation, the performance of the lidar is tested at Chiba University. Data from the continuous operation of the lidar from August 2021 to February 2022 are analyzed for extinction and depolarization ratio. These are compared with the weather sensor and particulate matter (PM2.5) measurements to quantify the relationship between atmospheric conditions and optical properties of near-ground aerosols. The results show that lidar data’s extinction coefficient and depolarization ratio can have a quantifiable relationship with relative humidity (RH), absolute humidity, rain rate, wind speed, wind direction, and PM2.5 concentration. Analysis of the seven-month data shows that the optical properties of aerosol and dust depend on the combined effects of the weather parameters. An increase in RH or PM2.5 concentration does not imply an increase in radioactive aerosols. The average extinction coefficient and depolarization ratio of aerosols and dust originating from the land and ocean show different values and opposing trends which can aid in determining the occurrence of ground-based radioactive dust and aerosols. The information obtained from analyzing the interrelationship among lidar, weather parameters, and PM2.5 concentration is essential in assessing the occurrence of radioactive aerosols and characterizing local aerosol-weather relationships in a radioactive area. This result provides essential information in describing radioactive aerosols in Fukushima.

Abstract. This study investigated the spatiotemporal variabilitiesin nitrogen dioxide (NO2), formaldehyde (HCHO), ozone (O3), andlight-absorbing aerosols within the Greater Tokyo Area, Japan, which is the mostpopulous metropolitan area in the world. The analysis is based on totaltropospheric column, partial tropospheric column (within the boundarylayer), and in situ observations retrieved from multiple platforms as well as additionalinformation obtained from reanalysis and box model simulations. This studymainly covers the 2013–2020 period, focusing on 2020 when air quality wasinfluenced by the coronavirus 2019 (COVID-19) pandemic. Although total andpartial tropospheric NO2 columns were reduced by an average of about10 % in 2020, reductions exceeding 40 % occurred in some areas duringthe pandemic state of emergency. Light-absorbing aerosol levels within theboundary layer were also reduced for most of 2020, while smallerfluctuations in HCHO and O3 were observed. The significantly enhanceddegree of weekly cycling of NO2, HCHO, and light-absorbing aerosolfound in urban areas during 2020 suggests that, in contrast to othercountries, mobility in Japan also dropped on weekends. We conclude that,despite the lack of strict mobility restrictions in Japan, widespreadadherence to recommendations designed to limit the COVID-19 spread resultedin unique air quality improvements.

To mitigate tropospheric ozone (O3) pollution with proper and effective emission regulations, diagnostics for the O3-sensitive regime are critical. In this study, we analyzed the satellite-measured formaldehyde (HCHO) and nitrogen dioxide (NO2) column densities and derived the HCHO to NO2 ratio (FNR) from 2005 to 2019. Over China, there was a clear increase in the NO2 column during the first 5-year period and a subsequent decrease after 2010. Over the Republic of Korea and Japan, there was a continuous decline in the NO2 column over 15 years. Over the entire East Asia, a substantial increase in the HCHO column was identified during 2015–2019. Therefore, FNR increased over almost all of East Asia, especially during 2015–2019. This increasing trend in FNR indicated the gradual shift from a volatile organic compound (VOC)-sensitive to a nitrogen oxide (NOx)-sensitive regime. The long-term changes in HCHO and NO2 columns generally corresponded to anthropogenic non-methane VOC (NMVOC) and NOx emissions trends; however, anthropogenic sources did not explain the increasing HCHO column during 2015–2019. Because of the reduction in anthropogenic sources, the relative importance of biogenic NMVOC sources has been increasing and could have a larger impact on changing the O3-sensitive regime over East Asia.

Abstract. The Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite, launched on 23 December 2017,observes various geophysical parameters with the aim of better understanding the global climate system. As part of that aim, SGLI has greatpotential to unravel several uncertainties related to clouds by providing new cloud products along with several other atmospheric products relatedto cloud climatology, including aerosol products from polarization channels. However, very little is known about the quality of the SGLI cloudproducts. This study uses data about clouds and global irradiances observed from the Earth's surface using a sky radiometer and a pyranometer,respectively, to understand the quality of the two most fundamental cloud properties – cloud optical depth (COD) and cloud-particle effectiveradius (CER) – of both water and ice clouds. The SGLI-observed COD agrees well with values observed from the surface, although it agrees better forwater clouds than for ice clouds, while the SGLI-observed CER exhibits poorer agreement than does the COD, with SGLI values being generallyhigher than the sky radiometer values. These comparisons between the SGLI and sky radiometer cloud properties are found to differ for differentcloud types of both the water and ice cloud phases and different solar and satellite viewing angles by agreeing better for relatively uniform andflat cloud type and for relatively low solar zenith angle. Analyses of SGLI-observed reflectance functions and values calculated by assumingplane-parallel cloud layers suggest that SGLI-retrieved cloud properties can have biases in the solar and satellite viewing angles, similar to othersatellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS). Furthermore, it is found that the SGLI-observed cloudproperties reproduce global irradiances quite satisfactorily for both water and ice clouds by resembling several important features of the CODcomparison, such as better agreement for water clouds than for ice clouds and the tendency to underestimate (resp. overestimate) the COD in SGLIobservations for optically thick (resp. thin) clouds.

To advance our understanding of surface and aloft nitrogen dioxide (NO2) pollution, this study extensively evaluated NO2 concentrations simulated by the regional air quality modeling system with a 1.3 km horizontal grid resolution using the Atmospheric Environmental Regional Observation System ground-based observation network and aloft measurements by multi-axis differential optical absorption spectroscopy (MAX-DOAS) over the greater Tokyo area. Observations are usually limited to the surface level, and gaps remain in our understanding of the behavior of air pollutants above the near-surface layer, particularly within the planetary boundary layer (PBL). Therefore, MAX-DOAS measurement was used, which observes scattered sunlight in the ultraviolet/visible range at several elevation angles between the horizon and zenith to determine the aloft NO2 pollution averaged over 0–1 km. In total, four MAX-DOAS measurement systems at Chiba University (35.63°N, 140.10°E) systematically covered the north, east, west, and south directions to capture the aloft NO2 pollution over the greater Tokyo area. The target period was Chiba-Campaign 2015 conducted during 9–23 November 2015. The evaluations showed that the air quality modeling system can generally capture the observed behavior of both surface and aloft NO2 pollution in terms of spatial and temporal coverage. The diurnal variation, which typically showed an increase from evening to early morning without daylight and a decrease during the daytime, was also captured by the model. During Chiba-Campaign 2015, two cases of episodic higher NO2 concentration were identified: one during the nighttime and another during the daytime as different diurnal patterns. These were related to a stagnant wind field, with the latter also connected to a lower PBL height in cloudy conditions. Comparison of the modeled daily-averaged surface and aloft NO2 concentrations showed that aloft NO2 concentration exhibited a strong linear correlation with surface NO2 concentration, with the aloft (0–1 km) value scaled to 0.4–0.5-fold the surface value, irrespective of whether the day was clean or polluted. This scaling value was lower during the nighttime and higher during the daytime. Based on this synergetic analysis of surface and aloft observation bridged by a kilometer-scale fine-resolution modeling simulation, this study contributes to fostering understanding of aloft NO2 pollution. [Figure not available: see fulltext.]

We developed look-up tables for the correlated k-distribution (CKD) method in the 940 nm water vapor absorption region (WV-CKD), with the aim of rapid and accurate computation of narrow-band radiation around 940 nm (10,000–10,900 cm^(-1)) for ground-based angular-scanning radiometer data analysis. Tables were constructed at three spectral resolutions (2, 5, and 10 cm^(-1)) with quadrature values (point and weight) and numbers optimized using simulated sky radiances at ground level, which had accuracies of ≤ 0.5% for sub-bands of 10 cm^(-1). Although high-resolution WV-CKD requires numerous quadrature points, our WV-CKD with a resolution of 2 cm^(-1) reduces the number of executions of the radiative transfer model is reducedrequired to approximately 1/46 of the number used in the line-by-line approach by our WV-CKD with a resolution of 2 cm^(-1). Furthermore, we confirmed through several simulations that WV-CKD could be used to compute radiances with various vertical profiles. The accuracy of convolved direct solar irradiance and diffuse radiance at a full width at half maximum (FWHM) of 10 nm, computed with the WV-CKD, is < 0.3%. In contrast, the accuracy of convolved normalized radiance, which is the ratio of diffuse radiance to direct solar irradiance, at an FWHM of 10 nm computed with the WV-CKD is < 0.11%. This accuracy is lower than the observational uncertainty of a ground-based angular-scanning radiometer (approximately 0.5%). Finally, we applied the SKYMAP and DSRAD algorithms (Momoi et al., 2020) to SKYNET observations (Chiba, Japan), and compared the results with microwave radiometer values. The precipitable water vapor (PWV) derived with the WV-CKD showed better agreement (correlation coefficient γ = 0.995, slope = 1.002) with observations than PWV derived with the previous CKD table (correlation coefficient γ = 0.984, slope = 0.926) by Momoi et al. (2020). Through application of the WV-CKD to actual data analysis, we found that an accurate CKD table is essential for estimating PWV from sky-radiometer observations.

We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPO-spheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the differential optical absorption spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO2 absorption. The product comes along with a full error characterization, which allows for providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1 x 10(14)-3 x 10(14) molec.cm(-2) (similar to 30 %-70 % in emission regimes) and originate mostly from a priori data uncertainties and spectral interferences with other absorbing species. The latter may be at the origin, at least partly, of an enhanced glyoxal signal over equatorial oceans, and further investigation is needed to mitigate them. Random errors are large (> 6 x 10(14) molec. cm(-2)) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail.Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and variability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appear to be biased low during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences of less than 1 x 10(14) molec.cm(-2). A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is high.

Brown carbon (BrC) aerosols have important warming effects on Earth's radiative forcing. However, information on the evolution of the light-absorption properties of BrC aerosols in the Asian outflow region is limited. In this study, we evaluated the light-absorption properties of BrC using in-situ filter measurements and sky radiometer observations of the ground-based remote sensing network SKYradiometer NETwork (SKYNET) made on Fukue Island, western Japan in 2018. The light-absorption coefficient of BrC obtained from filter measurements had a temporal trend similar to that of the ambient concentration of black carbon (BC), indicating that BrC and BC have common combustion sources. The absorption Angstrom exponent in the wavelength range of 340-870 nm derived from the SKYNET observations was 15% higher in spring (1.81 +/- 0.30) than through the whole year (1.53 +/- 0.50), suggesting that the Asian outflow carries light-absorbing aerosols to Fukue Island and the western North Pacific. After eliminating the contributions of BC, the absorption Angstrom exponent of BrC alone obtained from filter observations had a positive Spearman correlation (r(s) = 0.77, p < 0.1) with that derived from SKYNET observations but 33% higher values, indicating that the light-absorption properties of BrC were suc-cessfully captured using the two methods. Using the atmospheric transport model FLEXPART and fire hotspots obtained from the Visible Infrared Imaging Radiometer Suite product, we identified a high-BrC event related to an air mass originating from regions with consistent fossil fuel combustion and sporadic open biomass burning in central East China. The results of the study may help to clarify the dynamics and climatic effects of BrC aerosols in East Asia. (C) 2021 Elsevier B.V. All rights reserved.

Abstract. Formaldehyde (HCHO) and nitrogen dioxide (NO2) concentrations and profiles were retrieved from ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observation during January 2017 through December 2018 at three sites in Asia: (1) Phimai in Thailand (15.18° N, 102.5° E); (2) Pantnagar (29° N, 78.90° E) in the Indo Gangetic plain (IGP) in India; and (3) Chiba (35.62° N, 140.10° E) in Japan. The NO2 and HCHO partial columns (&lt; 4 km) and profiles simulated using the global chemistry transport model (CTM) and CHASER were compared to those of MAX-DOAS. The vertical sensitivity of the datasets was elucidated using the averaging kernel (AK) information from the MAX-DOAS retrievals. The NO2 and HCHO concentrations at all three sites showed consistent seasonal variation throughout the investigated period. Biomass burning affected the HCHO and NO2 variation in Phimai during the dry season and in Pantnagar during spring (March–May) and the post-monsoon (September–November) season. High NO2 concentrations in Phimai during the wet season (June–September) are attributed to soil emissions of nitrogen oxides (NOx), confirmed from satellite observations and CHASER simulations. Comparison with CHASER shows that the seasonal variations in the HCHO and NO2 abundances at Phimai and Chiba agree well, with a correlation coefficient (R) of 0.80. Results agree with the variation, ranging mainly within the one sigma standard deviation of the observations. At Phimai, pyrogenic emissions contribute to the HCHO and NO2 concentrations up to ~50 and ~35 %, respectively. CHASER showed limited skills in reproducing the NO2 and HCHO variability at Pantnagar. However, the CHASER simulations in the IGP region agreed well with the reported results. Sensitivity studies showed that anthropogenic emissions affected the seasonal variation of NO2 and HCHO concentrations in the IGP region.

The retrieval of the aerosol optical thickness (AOT) from remotely-sensed data relies on the adopted aerosol model. However, the method of this technique has been rather limited because of the high variability of the surface albedo, in addition to the spatial variability in the aerosol properties over the land surfaces. To overcome unsolved problems, we proposed a method for the visibility-derived AOT estimation from SKYNET-based measurement and daytime satellite images with a custom aerosol model over the Chiba area (35.62 degrees N, 140.10 degrees E), which is located in the greater Tokyo metropolitan area in Japan. Different from conventionally-used aerosol models for the boundary layer, we created a custom aerosol model by using sky-radiometer observation data of aerosol volume size distribution and refractive indices, coupled with spectral response functions (SPFs) of satellite visible bands to alleviate the wide range of path-scattered radiance. We utilized the radiative transfer code 6S to implement the radiative transfer calculation based on the created custom aerosol model. The concurrent data from ground-based measurement are used in the radiative analysis, namely the temporal variation of AOT from SKYNET. The radiative estimation conducted under clear-sky conditions with minimum aerosol loading is used for the determination of the surface albedo, so that the 6S simulation yields a well-defined relation between total radiance and surface albedo. We made look-up tables (LUTs) pixel-by-pixel over the Chiba area for the custom aerosol model to retrieve the satellite AOT distribution based on the surface albedo. Therefore, such a reference of surface albedo generated from clear-sky conditions, in turn, can be employed to retrieve the spatial distribution of AOT on both clear and relatively turbid days. The value for the AOTs retrieved using the custom aerosol model is found to be stable than conventionally-used typical aerosol models, indicating that our method yields substantially better performance.

Because of the increased temporal and spatial resolutions of the sensors onboard recently launched satellites, satellite-based surface aerosol concentration, which is usually estimated from the aerosol optical depth (AOD), is expected to become a strategic tool for air quality studies in the future. By further exploring the relationships of aerosol concentrations and their optical properties using ground observations, the accuracies of these products can be improved. Here, we analyzed collocated observations of surface mass concentrations of fine particulate matter (PM2.5) and black carbon (BC), as well as columnar aerosol optical properties from a sky radiometer and aerosol extinction profiles obtained by multi-axis differential optical absorption spectroscopy (MAX-DOAS), during the 2019–2020 period. We focused the analyses on a daily scale, emphasizing the role of the ultraviolet (UV) spectral region. Generally, the correlation between the AOD of the fine fraction (i.e., fAOD) and the PM2.5 surface concentration was moderately strong, regardless of considerations of boundary layer humidity and altitude. In contrast, the fAOD of the partial column below 1 km, which was obtained by combining sky radiometer and MAX-DOAS retrievals, better reproduced the variability of the PM2.5 and resulted in a linear relationship. In the same manner, we demonstrated that the absorption AOD of the fine fraction (fAAOD) of the partial column was related to the variability of the BC concentration. Analogous analyses based on aerosol products from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) confirmed these findings and highlighted the importance of the shape of the aerosol profile. Overall, our results indicated a remarkable consistency among the retrieved datasets, and between the datasets and MERRA-2 products. These results confirmed the well-known sensitivity to aerosol absorption in the UV spectral region; they also highlighted the efficacy of combined MAX-DOAS and sky radiometer observations.

The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5 x 5.5 km(2). This paper assesses the performances of the TROPOMI formaldehyde (HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30% in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns (larger than 5 x 10(15) molec.cm(-2)) the median bias between OMI and TROPOMI HCHO columns is not larger than 10% (< 0.4 x 10(15) molec.cm(-2)). For lower columns, OMI observations present a remaining positive bias of about 20% (< 0.8 x 10(15) molec.cm(-2)) compared to TROPOMI in midlatitude regions. Here, we also use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020), where a global FTIR (Fourier transform infrared) network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (25% for HCHO columns larger than 8 x 10(15) molec.cm(-2)), while no significant bias is found for medium-range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25% for individual pixels and by up to a factor of 3 when considering daily averages in 20 km radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors (5 years) and opens new perspectives to study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical interactions.

We investigated long-term observations of the tropospheric nitrogen dioxide vertical column density (NO2 TropVCD) from the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) network in Russia and ASia (MADRAS) from 2007 to 2017 at urban (Yokosuka and Gwangju) and remote (Fukue and Cape Hedo) sites in East Asia. The monthly mean in the NO2 TropVCD from MAX-DOAS measured at similar to 13:30 local time, which is the Ozone Monitoring Instrument (OMI) overpass time, shows good agreement with OMI data during summer, but differences between the two datasets increase in winter. The Theil-Sen slope of the long-term trend indicate a relatively rapid and gradual reduction in NO2 at Yokosuka and two remote sites (Fukue and Cape Hedo), respectively, regardless of the season except for fall at Fukue, but significant changes in NO2 are not observed at Gwangju, Korea. In contrast, OMI satellite data reveal an increase in the NO2 TropVCD at all sites except for Yokosuka, where a decreasing trend common to MAX-DOAS is found, suggesting that the results from satellites need to be cautiously used for investigating long-term trends in less polluted or remote areas. Using backward trajectories, potential source regions are identified for the two urban sites. The spatial distribution from OMI data shows good agreement with the potential source regions at Yokosuka. The potential source regions in Gwangju are identified as the National Industrial Complex in Yeosu and Gwangyang, while the transport route is not clearly visible with OMI data because of their low sensitivity in less polluted areas. The proposed approach is suitable for identifying potential source areas that might not be recognized by satellite observations.

Ground-based remote sensing using multi-axis differential optical absorption spectroscopy (MAX-DOAS) was used to conduct continuous simultaneous observations of ozone (O-3), nitrogen dioxide (NO2), and formaldehyde (HCHO) concentrations at Chiba (35.63 degrees N, 140.10 degrees E, 21 m a.s.l.) and Tsukuba (36.06 degrees N, 140.13 degrees E, 35 m a.s.l.), Japan, for 7 years from 2013 to 2019. These are urban and suburban sites, respectively, in the greater Tokyo metropolitan area. NO2 and HCHO are considered to be proxies for nitrogen oxides (NOx) and volatile organic compounds (VOCs), respectively, both of which are major precursors of tropospheric O-3. The mean concentrations below an altitude of 1 km were analyzed as planetary boundary layer (PBL) concentrations. For a more spatially representative analysis around the urban area of Chiba, four MAX-DOAS instruments directed at four different azimuth directions (north, east, west, and south) were operated simultaneously and their data were unified. During the 7-year period, the satellite observations indicated an abrupt decrease in the tropospheric NO2 concentration over East Asia, including China. This suggested that the transboundary transport of O-3 originating from the Asian continent was likely suppressed or almost unchanged during the period. Over this time period, the MAX-DOAS observations revealed the presence of almost-constant annual variations in the PBL O-3 concentration, whereas reductions in NO2 and HCHO concentrations occurred at rates of approximately 6-10%/year at Chiba. These changes provided clear observational evidence that a decreasing NOx concentration significantly reduced the amount of O-3 quenched through NO titration under VOC-limited conditions in the urban area. Under the dominant VOC-limited conditions, the MAX-DOAS-derived concentration ratio of HCHO/NO2 was found to be below unity in all months. Thus, the multi-component observations from MAX-DOAS provided a unique data set of O-3, NO2, and HCHO concentrations for analyzing PBL O-3 variations.

This study provides comparisons of aerosol representation methods incorporated into a regional-scale non-hydrostatic meteorology-chemistry model (NHM-Chem). Three options for aerosol representations are currently available: the five-category non-equilibrium (Aitken, soot-free accumulation, soot-containing accumulation, dust, and sea salt), three-category non-equilibrium (Aitken, accumulation, and coarse), and bulk equilibrium (submicron, dust, and sea salt) methods. The three-category method is widely used in three-dimensional air quality models. The five-category method, the standard method of NHM-Chem, is an extensional development of the three-category method and provides improved predictions of variables relating to aerosolcloud-radiation interaction processes by implementing separate treatments of light absorber and ice nuclei particles, namely, soot and dust, from the accumulation- and coarsemode categories (implementation of aerosol feedback processes to NHM-Chem is still ongoing, though). The bulk equilibrium method was developed for operational air quality forecasting with simple aerosol dynamics representations. The total CPU times of the five-category and three-category methods were 91% and 44% greater than that of the bulk method, respectively. The bulk equilibrium method was shown to be eligible for operational forecast purposes, namely, the surface mass concentrations of air pollutants such as O-3, mineral dust, and PM2.5. The simulated surface concentrations and depositions of bulk chemical species of the three-category method were not significantly different from those of the five-category method. However, the internal mixture assumption of soot/soot-free and dust/sea salt particles in the three-category method resulted in significant differences in the size distribution and hygroscopicity of the particles. The unrealistic dust/sea salt complete mixture of the three-category method induced significant errors in the prediction of the mineral dust-containing cloud condensation nuclei (CCN), which alters heterogeneous ice nucleation in cold rain processes. The overestimation of soot hygroscopicity by the three-category method induced errors in the BC-containing CCN, BC deposition, and light-absorbing aerosol optical thickness (AAOT). Nevertheless, the difference in AAOT was less pronounced with the three-category method because the overestimation of the absorption enhancement was compensated by the overestimation of hygroscopic growth and the consequent loss due to in-cloud scavenging. In terms of total properties, such as aerosol optical thickness (AOT) and CCN, the results of the three-category method were acceptable.

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatiotemporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically -23 % to -37 % in clean to slightly polluted conditions but reaching values as high as -51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about -0.2 Pmolec cm(-2), i.e. approx. -2 % in summer to -15 % in winter; and (iii) a bias ranging from zero to -50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm(-2) and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm(-2)) but exceed those for the tropospheric column data (0.7 Pmolec cm(-2)). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm(-2) and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to -34 % for GOME-2A and -24 % for OMI. These biases are further reduced to -24 % and -18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

Quantifying the spectral variation of column aerosol absorption in the ultraviolet (UV) and visible (Vis) wavelengths is required for accurate satellite-based aerosol and trace-gas retrievals. Retrievals of the column-averaged imaginary part of refractive index and single scattering albedo (SSA) in the UV-Vis range have been performed at Yonsei University, Seoul, Korea, since 2016 by combining co-located measurements from the NASA Aerosol Robotic Network (AERONET) Cimel sun-sky photometer, the Ultraviolet Multifilter Rotating Shadowband Radiometer (UV-MFRSR), the SKYNET Prede sky radiometer, and the NASA Pandora sun spectrometer. We investigated the spectral variation of column-averaged imaginary part of refractive index for UV-Vis wavelengths to refine models used in our aerosol retrieval algorithm to process measurements from the upcoming Geostationary Environment Monitoring Satellite (GEMS). The retrieved imaginary part of refractive index for highly absorbing fine pollution particles (BC), dust (DS), and non-absorbing (NA) particles in the selected UV-Vis range (380-440 nm) showed 0-20%, 30%, and 0-40% of spectral dependence, respectively. Retrievals of Ozone Monitoring Instrument (OMI) measurement data using the improved aerosol model showed improved correlation with AERONET data compared to the old algorithm that did not properly account for aerosol absorption effects. These results corroborate the advantage of using local climatology derived from ground-based UV-Vis spectral aerosol absorption measurements for satellite GEMS aerosol retrievals over East Asia. Moreover, this study reveals that spectral variations in the UV column aerosol absorption in East Asia differ from those in other regions.

The Global Change Observation Mission-Climate (GCOM-C) is currently the only satellite sensor providing aerosol optical thickness (AOT) in the ultraviolet (UV) region during the morning overpass time. The observations in the UV region are important to detect the presence of absorbing aerosols in the atmosphere. The recently available GCOM-C dataset of AOT at 380 nm for January to September 2019 were evaluated using ground-based SKYNET sky radiometer measurements at Chiba, Japan (35.62 degrees N, 140.10 degrees E) and Phimai, central Thailand (15.18 degrees N, 102.56 degrees E), representing urban and rural sites, respectively. AOT retrieved from sky radiometer observations in Chiba and Phimai was compared with coincident AERONET and multi-axis differential optical absorption spectroscopy (MAX-DOAS) AOT values, respectively. Under clear sky conditions, the datasets showed good agreement. The sky radiometer and GCOM-C AOT values showed a positive correlation (R) of similar to 0.73 for both sites, and agreement between the datasets was mostly within +/- 0.2 (the number of coincident points at both sites was less than 50 for the coincidence criterion of <= 30 km). At Chiba, greater differences in the AOT values were primarily related to cloud screening in the datasets. The mean bias error (MBE) (GCOM-C - sky radiometer) for the Chiba site was -0.02 for a coincidence criterion of <= 10 km. For a similar coincidence criterion, the MBE values were higher for observations at the Phimai site. This difference was potentially related to the strong influence of biomass burning during the dry season (Jan-Apr). The diurnal variations in AOT, inferred from the combination of GCOM-C and ozone monitoring instrument (OMI) observations, showed good agreement with the sky radiometer data, despite the differences in the absolute AOT values. Over Phimai, the AOT diurnal variations from the satellite and sky radiometer observations were different, likely due to the large differences in the AOT values during the dry season.

This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone.A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F-0 using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F-0, around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors.The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for lambda >= 500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03.Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences.It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.

Egypt experiences high rates of air pollution, which is a major threat to human health and the eco-environment and therefore needs to be tackled by defining major causes to hinder or mitigate their impacts. The major driving forces of air pollution are either of local and/or regional origin. In addition, seasonal aerosols may be natural, such as dust particles transported from the western desert, or anthropogenic aerosols which are transported from industrial areas and smoke particles from seasonal biomass burning. Monitoring the optical properties of aerosols and their pattern in the atmosphere on a daily basis requires a robust source of information and professional analytical tools. This research explored the potential of using time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) data to comprehensively investigate the aerosol optical depth (AOD) and variability for the period 2012-2018 on a daily basis. The data show that spring, summer and autumn seasons experienced the highest anomaly originating from regional and national sources. The high AOD in spring associated with a low angstrom ngstrom exponent (AE) indicates the presence of coarse particles which naturally originate from desert dust or sea spray. In contrast, the high AE in summer and autumn demonstrated the dominance of fine anthropogenic aerosols such as smoke particles from local biomass burning. The observation of a high number of fire incidents over Egypt in October and November 2018, during the months of rice crop harvesting, showed that these incidents contribute to the presence of autumn aerosols across the country. In-situ measurements of Particulate Matter (PM10) from local stations from an environmental based network as well as the AERONET AOD were used to validate the MODIS AOD, providing a high correlation coefficient of r = 0.73.

In this study, we explored the connection between anomalies in springtime Antarctic ozone and all-year precipitation in the Southern Hemisphere by using observations from 1960-2018 and coupled simulations for 1960-2050. The observations showed that this correlation was enhanced during the last several decades, when a simultaneously increased coupling between ozone and Southern Annular Mode (SAM) anomalies became broader, covering most of the following summer and part of the previous winter. For eastern Australia, the ozone-precipitation connection shows a greater persistence toward the following summer than for other regions. On the other hand, for South America, the ozone-precipitation correlation seems more robust, especially in the early summer. There, the correlation also covers part of the previous winter, suggesting that winter planetary waves could affect both parameters. Further, we estimated the sensitivity of precipitation to changes in Antarctic ozone. In both observations and simulations, we found comparable sensitivity values during the spring-summer period. Overall, our results indicate that ozone anomalies can be understood as a tracer of stratospheric circulation. However, simulations indicate that stratospheric ozone chemistry still contributes to strengthening the interannual relationship between ozone and surface climate. Because simulations reproduced most of the observed connections, we suggest that including ozone variability in seasonal forecasting systems can potentially improve predictions.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97 degrees N, 4.93 degrees E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation.The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O-4) and ozone (O-3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions.The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

The Prede sky radiometer measures direct solar irradiance and the angular distribution of diffuse radiances at the ultraviolet, visible, and near-infrared wavelengths. These data are utilized for the remote sensing of aerosols, water vapor, ozone, and clouds, but the calibration constant, which is the sensor output current of the extraterrestrial solar irradiance at the mean distance between Earth and the Sun, is needed. The aerosol channels, which are the weak gas absorption wavelengths of 340, 380, 400, 500, 675, 870, and 1020 nm, can be calibrated by an on-site self-calibration method, the Improved Langley method. This on-site self-calibration method is useful for the continuous long-term observation of aerosol properties. However, the continuous long-term observation of precipitable water vapor (PWV) by the sky radiometer remains challenging because calibrating the water vapor absorption channel of 940 nm generally relies on the standard Langley (SL) method at limited observation sites (e.g., the Mauna Loa Observatory) and the transfer of the calibration constant by a side-by-side comparison with the reference sky radiometer calibrated by the SL method. In this study, we developed the SKYMAP algorithm, a new on-site method of self-calibrating the water vapor channel of the sky radiometer using diffuse radiances normalized by direct solar irradiance (normalized radiances). Because the sky radiometer measures direct solar irradiance and diffuse radiance using the same sensor, the normalization cancels the calibration constant included in the measurements. The SKYMAP algorithm consists of three steps. First, aerosol optical and microphysical properties are retrieved using direct solar irradiances and normalized radiances at aerosol channels. The aerosol optical properties at the water vapor channel are interpolated from those at aerosol channels. Second, PWV is retrieved using the angular distribution of the normalized radiances at the water vapor channel. Third, the calibration constant at the water vapor channel is estimated from the transmittance of PWV and aerosol optical properties. Intensive sensitivity tests of the SKYMAP algorithm using simulated data of the sky radiometer showed that the calibration constant is retrieved reasonably well for PWV < 2 cm, which indicates that the SKYMAP algorithm can calibrate the water vapor channel on-site in dry conditions. Next, the SKYMAP algorithm was applied to actual measurements under the clear-sky and low-PWV (< 2 cm) conditions at two sites, Tsukuba and Chiba, Japan, and the annual mean calibration constants at the two sites were determined. The SKYMAP-derived calibration constants were 10.1% and 3.2% lower, respectively, than those determined by a side-by-side comparison with the reference sky radiometer. After determining the calibration constant, we obtained PWV from the direct solar irradiances in both the dry and wet seasons. The retrieved PWV values corresponded well to those derived from a global-navigation-satellite-system-global-positioning-system receiver, a microwave radiometer, and an AERONET (Aerosol Robotic Network) sun-sky radiometer at both sites. The correlation coefficients were greater than 0.96. We calculated the bias errors and the root mean square errors by comparing PWV between the DSRAD (direct solar irradiance) algorithm and other instruments. The magnitude of the bias error and the root mean square error were < 0.163 and < 0.251 cm for PWV < 3 cm, respectively.However, our method tended to underestimate PWV in the wet conditions, and the magnitude of the bias error and the root mean square error became large, < 0.594 and < 0.722 cm for PWV > 3 cm, respectively. This problem was mainly due to the overestimation of the aerosol optical thickness before the retrieval of PWV. These results show that the SKYMAP algorithm enables us to observe PWV over the long term, based on its unique on-site self-calibration method.

The paper presents the preliminary results of the lidar&radiometer measurement campaign (LRMC2017), estimation of statistical relations between aerosol mode concentrations retrieved from CALIOP and ground-based lidar stations and case study of fire smoke events in the Eurasian regions using combined ground-based and space lidar and radiometer observations.

Rivers play significant roles in communities, including as source of drinking water and for transportation and other daily activities. However, water pollution is a major problem in several communities, with significant negative consequences to health and well-being and socioeconomic development. This research, therefore, aimed to design and develop a system with multiple sensors to monitor river water pollution because most communities use river water in their daily activities. In the design and development of the system, multiple sensor nodes were installed for the detection of water pollution parameters such as temperature, Electrical Conductivity (EC), water pH, and Dissolved Oxygen (DO). The system was designed to monitor river water pollution parameters and send the information to the data centre (backend system). Arduino microcontroller was used to process and filter the data before sending to the backend system. Only valuable information was collected and kept in the database. Results show that the system was able to detect polluted water by showing the parameters of interest in a graph. The polluted water indicators were mostly contributed from residential waste and industries. This work has furnished progress in the development and validation of appropriate technologies for tackling river water pollution. In the future, WSNs sensors will be deployed in some areas and the results across the different areas will be compared. Furthermore, the Internet of Things (IoT) Technology will be used for data sharing and communication.

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in February 2020 to monitor air quality (AQ) at an unprecedented spatial and temporal resolution from a geostationary Earth orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O-3, NO2, SO2, HCHO, CHOCHO, and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be on board the Geostationary Korea Multi-Purpose Satellite 2 (GEO-KOMPSAT-2) satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager 2 (GOCI-2). These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA's Tropospheric Emissions: Monitoring of Pollution (TEMPO) and ESA's Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS).

Accurate aerosol optical thickness is indispensable for estimating the radiative forcing of aerosols in the atmosphere. Sun photometry is one of the most popular methods, which is simple and easy to use, but it should be noted that some errors due to forward scattering effect can be introduced in the observation of direct normal irradiance. Consequently, the estimated optical thickness of aerosols can be underestimated even if the calibration constant is correct. This possibility depends on an optical geometry of the measuring instrument as well as aerosol characteristics. This report assesses these effects by assuming several aerosol types and instrumental parameters quantitatively.Forward scattering ratio gamma(lambda),(fwd), which is defined as a ratio of the forward scattering part to the true direct normal irradiance (I-lambda), by I-lambda.obs = I-lambda,(1 + gamma(lambda),(fwd)), is approximately proportional to the product of the optical thickness (tau(lambda,aer)) and the single scattering albedo (omega(lambda)) of aerosols and the relative air mass (m), gamma(lambda),(fwd) approximate to epsilon(lambda)omega(lambda)tau(lambda aer)m. The coefficient epsilon(lambda) is a proportional constant which is dependent on the opening angle of the instrument as well as the optical characteristics of aerosols. The variation of epsilon(lambda) is tabulated for several aerosol types and opening angles. Then, the error of the estimate of tau(lambda aer) can be approximately expressed by Delta tau(lambda) approximate to -epsilon(lambda)omega(lambda)tau(lambda aer).

Abstract. An optimal estimation algorithm to retrieve the cloud optical depth (COD) and cloud particle effective radius (CER) from spectral zenith radiances observed by narrow field-of-view (FOV) ground-based sky radiometers was developed. To further address the filter degradation problem while analyzing long-term observation data, an on-site calibration procedure is proposed, which has good accuracy compared with the standard calibration transfer method. An error evaluation study conducted by assuming errors in observed transmittances and ancillary data for water vapor concentration and surface albedo suggests that the errors in input data affect retrieved CER more than COD. Except for some narrow domains that fall within a COD of &lt; 15, the retrieval errors are small for both COD and CER. The retrieved cloud properties reproduce the broadband radiances observed by a narrow FOV radiometer more precisely than broadband irradiances observed by a wide-FOV pyranometer, justifying the quality of the retrieved product (at least of COD) and indicating the important effect of the instrument FOV in cloud remote sensing. Furthermore, CODs (CERs) from sky radiometer and satellite observations show good (poor) agreement.

Abstract. The first intensive multicomponent ground-based remote-sensing observations by sky radiometer and multi-axis differential optical absorption spectroscopy (MAX-DOAS) were performed simultaneously at the SKYNET Phimai site located in central Thailand (15.18∘ N, 102.56∘ E) from January to April 2016. The period corresponds to the dry season associated with intense biomass burning (BB) activity around the site. The near-surface concentration of formaldehyde (HCHO) retrieved from MAX-DOAS was found to be a useful tracer for absorption aerosols from BB plumes, when BB was the dominant source of HCHO and absorption aerosols over other sources. As the HCHO concentration tripled from 3 to 9 ppbv, the ratio of gaseous glyoxal to HCHO concentrations in daytime decreased from ∼0.04 to ∼0.03, responding presumably to the increased contribution of volatile organic compound emissions from BB. In addition, clear increases in aerosol absorption optical depths (AAODs) retrieved from sky radiometer observations were seen with the HCHO enhancement. At a HCHO of 9 ppbv, AAOD at a wavelength of 340 nm reached as high as ∼0.15±0.03. The wavelength dependence of AAODs at 340–870 nm was quantified by the absorption Ångström exponent (AAE), providing evidence for the presence of brown carbon aerosols at an AAE of 1.5±0.2. Thus, our multicomponent observations around central Thailand are expected to provide unique constraints for understanding physical–chemical–optical properties of BB plumes.

Forest fires in Indonesia is one of big issue and disaster because of Indonesia located in tropical region, furthermore some of region consist of peat land that high risk for fire especially in dry season. Riau Province is one of region that regularly incident of forest fire with affected the length and breadth of Indonesia. This research proposes development of Wireless Sensor Networks (WSNs) for detection of forest fire hotspot in Indonesia, further case location in Riau province one of the region that high risk forest fire in dry season. WSNs technology used for ground sensor system to collect environmental data, any change by the times reporting to the data center to be analyze. Data training for fire hotspot detection is done in data center to determine and conclude of fire hotspot then potential to become big fire. The deployment of sensors will be located at several locations that has potential for fire incident in previous case and forecast location with potential fire happen. Mathematical analysis is used in this case for modelling number of sensor required to deploy and the size of forest area. The design and development of WSNs give high impact and feasibility to overcome current issues of forest fire and fire hotspot detection in Indonesia. The development of this system used WSNs highly applicable for early warning and alert system for fire hotspot detection.

We used observations recorded at Chiba University in November 2018 to examine the variability in cloud optical depth (COD) under overcast conditions. First, we conducted a careful evaluation of four COD datasets retrieved from three types of surface observations: i) zenith radiance recorded by two sky radiometers; ii) solar radiation data collected by a pyranometer; and iii) spatial distribution of radiance recorded using a sky camera system. Although the COD retrieved from the pyranometer (camera) slightly (moderately) overestimated the COD from zenith radiance, we found a satisfactory correlation among all surface estimates. This result suggests the efficacy of both pyranometer- and camera-based approaches and supports their broader use when dedicated cloud observations are not available. We then assessed satellite-based COD estimates retrieved from the recently launched Advanced Himawari Imager (AHI) aboard Himawari-8 (H-8) and Second-generation Global Imager (SGLI) on the Global Change Observation Mission for Climate (GCOM-C). Overall, we found good agreement between ground and satellite estimates; their correlation and root mean square error were virtually equivalent to values reported for co-located surface-based instruments. Nevertheless, the AHI-based COD was found to be slightly positively biased with respect to surface datasets.

The model performance of a regional-scale meteorology-chemistry model (NHM-Chem) has been evaluated for the consistent predictions of the chemical, physical, and optical properties of aerosols. These properties are essentially important for the accurate assessment of air quality and health hazards, contamination of land and ocean ecosystems, and regional climate changes due to aerosol-cloud-radiation interaction processes. Currently, three optional methods are available: the five-category non-equilibrium method, the three-category non-equilibrium method, and the bulk equilibrium method. These three methods are suitable for the predictions of regional climate, air quality, and operational forecasts, respectively. In this paper, the simulated aerosol chemical, physical, and optical properties and their consistency were evaluated using various observation data in East Asia. The simulated mass, size, and deposition of SO42− and NH4+ agreed well with the observations, whereas those of NO3−, sea salt, and dust needed improvement. The simulated surface mass concentration (PM10 and PM2.5) and spherical extinction coefficient agreed well with the observations. The simulated aerosol optical thickness (AOT) and dust extinction coefficient were significantly underestimated.

Abstract. Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1°  ×  1° TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995–2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40 % over polluted scenes. The first validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (−2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

Observations from the new Japanese geostationary satellite Himawari-8 permit quasi-real-time estimation of global shortwave radiation at an unprecedented temporal resolution. However, accurate comparisons with ground-truthing observations are essential to assess their uncertainty. In this study, we evaluated the Himawari-8 global radiation product AMATERASS using observations recorded at four SKYNET stations in Japan and, for certain analyses, from the surface network of the Japanese Meteorological Agency in 2016. We found that the spatiotemporal variability of the satellite estimates was smaller than that of the ground observations; variability decreased with increases in the time step and spatial domain. Cloud variability was the main source of uncertainty in the satellite radiation estimates, followed by direct effects caused by aerosols and bright albedo. Under all-sky conditions, good agreement was found between satellite and ground-based data, with a mean bias in the range of 20-30 W m(-2) (i.e., AMATERASS overestimated ground observations) and a root mean square error (RMSE) of approximately 70-80 W m(-2). However, results depended on the time step used in the validation exercise, on the spatial domain, and on the different climatological regions. In particular, the validation performed at 2.5 min showed largest deviations and RMSE values ranging from about 110 W m(-2) for the mainland to a maximum of 150 W m(-2) in the subtropical region. We also detected a limited overestimation in the number of clear-sky episodes, particularly at the pixel level. Overall, satellite-based estimates were higher under overcast conditions, whereas frequent episodes of cloud-induced enhanced surface radiation (i.e., measured radiation was greater than expected clear-sky radiation) tended to reduce this difference. Finally, the total mean bias was approximately 10-15 W m(-2) under clear-sky conditions, mainly because of overall instantaneous direct aerosol forcing efficiency in the range of 120-150 W m(-2) per unit of aerosol optical depth (AOD). A seasonal anticorrelation between AOD and global radiation differences was evident at all stations and was also observed within the diurnal cycle.

Quantifying aerosol absorption at ultraviolet (UV) wavelengths is important for monitoring air pollution and aerosol amounts using current (e.g., Aura/OMI) and future (e.g., TROPOMI, TEMPO, GEMS, and Sentinel-4) satellite measurements. Measurements of column average atmospheric aerosol single scattering albedo (SSA) are performed on the ground by the NASA AERONET in the visible (VIS) and near-infrared (NIR) wavelengths and in the UV-VISNIR by the SKYNET networks. Previous comparison studies have focused on VIS and NIR wavelengths due to the lack of co-incident measurements of aerosol and gaseous absorption properties in the UV. This study compares the SKYNET-retrieved SSA in the UV with the SSA derived from a combination of AERONET, MFRSR, and Pandora (AMP) retrievals in Seoul, South Korea, in spring and summer 2016. The results show that the spectrally invariant surface albedo assumed in the SKYNET SSA retrievals leads to underestimated SSA compared to AMP values at near UV wavelengths. Re-processed SKYNET inversions using spectrally varying surface albedo, consistent with the AERONET retrieval improve agreement with AMP SSA. The combined AMP inversions allow for separating aerosol and gaseous (NO2 and O-3) absorption and provide aerosol retrievals from the shortest UVB (305 nm) through VIS to NIR wavelengths (870 nm).

We performed a feasibility study of constraining the vertical profile of the tropospheric ozone by using a synergetic retrieval method on multiple spectra, i.e., ultraviolet (UV), thermal infrared (TIR), and microwave (MW) ranges, measured from space. This work provides, for the first time, a quantitative evaluation of the retrieval sensitivity of the tropospheric ozone by adding the MW measurement to the UV and TIR measurements. Two observation points in East Asia (one in an urban area and one in an ocean area) and two observation times (one during summer and one during winter) were assumed. Geometry of line of sight was nadir down-looking for the UV and TIR measurements, and limb sounding for the MW measurement. The retrieval sensitivities of the ozone profiles in the upper troposphere (UT), middle troposphere (MT), and lowermost troposphere (LMT) were estimated using the degree of freedom for signal (DFS), the pressure of maximum sensitivity, reduction rate of error from the a priori error, and the averaging kernel matrix, derived based on the optimal estimation method. The measurement noise levels were assumed to be the same as those for currently available instruments. The weighting functions for the UV, TIR, and MW ranges were calculated using the SCIATRAN radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), and the Advanced Model for Atmospheric Terahertz Radiation Analysis and Simulation (AMATERASU), respectively. The DFS value was increased by approximately 96, 23, and 30ĝ ̄% by adding the MW measurements to the combination of UV and TIR measurements in the UT, MT, and LMT regions, respectively. The MW measurement increased the DFS value of the LMT ozone nevertheless, the MW measurement alone has no sensitivity to the LMT ozone. The pressure of maximum sensitivity value for the LMT ozone was also increased by adding the MW measurement. These findings indicate that better information on LMT ozone can be obtained by adding constraints on the UT and MT ozone from the MW measurement. The results of this study are applicable to the upcoming air-quality monitoring missions, APOLLO, GMAP-Asia, and uvSCOPE.

Since January 2017 continuous multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations have been performed for the first time at Pantnagar (29.03 degrees N, 79.47 degrees E), a semi-urban site located in the Indo-Gangetic Plain region in India. Here we report the formaldehyde (HCHO), glyoxal (CHOCHO), and nitrogen dioxide (NO2) concentrations for the lowest layer (0-1 km) of the retrieved vertical profiles. The ratio of CHOCHO to HCHO concentrations (R-GF), an important tracer indicative of changes in volatile organic compound emissions was estimated. During spring and autumn enhanced concentrations of HCHO and CHOCHO were observed wider the influence of biomass burning. The mean R-GF for the whole observation period (January-November) in Pantnagar was estimated to be 0.029 +/- 0.006. Comparing with similar MAX-DOAS observations in central Thailand and reported literature values, we found that the R-GF tends to be < similar to 0.04 under the influence of biomass burning and/or anthropogenic emissions.