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Air quality have become a global issue with increasing attention. There is a growing concern in the public about both in- and outdoor air quality. In order to monitor individual air pollutants exposure in real-time, we developed several wearable air quality monitoring devices to study personal exposure to different pollutants in different environments. The devices are equipped with different type of sensors to measure NO2, aerosols, CO2, etc, in addition to environmental parameters sensor to measure temperature, relative humidity and pressure. In order to optimize the accuracy, we compared different retrieval approaches such as multiple linear regression, generalized linear model, neural network, etc. This allows us to perform the personal exposure study with a high temporal resolution in the order of seconds. We classified daily activities into different categories: different ways of commuting such as bus, tram, subway, bicycle, on foot; indoor activities like cooking, lighting candles, etc.; outdoor exercises next to busy street, in a park, etc. In this presentation, we will present our first result of this personal exposure study.

We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

The measurement accuracy of recent and future space-based imaging spectrometers with a high spectral and spatial resolution suffer from the inhomogeneity of the radiances of the observed Earth scene. The Instrument Spectral Response Function (ISRF) is distorted due to the inhomogeneous illumination from scene heterogeneity. This gives rise to a pseudo-random error on the measured spectra. In order to assess the spectral stability of the spectrograph, stringent requirements are typically defined on the ISRF such as shape knowledge and the stability of the centroid position of the spectral sample. The high level of spectral accuracy is particularly crucial for missions quantifying small variations in the total column of well-mixed trace gases like $$\hbox {CO}_{2}$$ CO 2 . In the framework of the $$\hbox {CO}_{2}$$ CO 2 Monitoring Mission (CO2M) industrial feasibility study (Phase A/B1 study), we investigated a new slit design called 2D-Slit Homogenizer (2DSH). This new concept aims to reduce the Earth scene contrast entering the instrument. The 2DSH is based on optical fibre waveguides assembled in a bundle, which scramble the light in across-track (ACT) and along-track (ALT) direction. A single fibre core dimension in ALT defines the spectral extent of the slit and the dimension in ACT represents the spatial sample of the instrument. The full swath is given by the total size of the adjoined fibres in ACT direction. In this work, we provide experimental measurement data on the stability of representative rectangular core shaped fibre as well as a preliminary pre-development of a 2DSH fibre bundle. In our study, the slit concept has demonstrated significant performance gains in the stability of the ISRF for several extreme high-contrast Earth scenes, achieving a shape stability of $$ < 0.5 % and a centroid stability of $$ < 0.25 pm (NIR). Given this unprecedented ISRF stabilization, we conclude that the 2DSH concept efficiently desensitizes the instrument for radiometric and spectral errors with respect to the heterogeneity of the Earth scene radiance.

The problem of elevated NO2 levels in cities has gained some attention in the public in recent years and has given rise to questions about the plausibility of banning diesel engines in cities, the meaning of exceedances of air quality limits and the effects of corona lock-downs on air quality to name a few. Urban air quality is typically monitored using a relatively small number of monitoring stations. Those in-situ measurements follow certain guidelines in terms of inlet height and location relative to streets, but the question remains how a limited number of point measurements can capture city-wide changes in the spatial distribution of NO2 concentrations. We utilize a combination of mobile and stationary measurements in Munich, Germany in order to estimate the fundamental drivers of urban air quality. We identified essential influencing factors like traffic volume, wind, boundary layer height, temperature, etc. and assessed for their impact on NO2 variability using a Generalized Additive Model (GAM) regression. Analyzing the impact factors separately allows us to allocate observed concentration peaks or drops, e.g. during lock down periods, to their key drivers.

We introduce the new GOME-2 daily and monthly level 3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO) and total column sulphur dioxide (SO2). The GOME-2 level 3 products are aimed to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as satisfying public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level 3 products. The GOME-2 level 3 products are produced using the overlapping area weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level 3 products is selected based on sensitivity study. The consistency of the resulting level 3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparing to ground-based observations. The verification and validation results show that the GOME-2 level 3 products are consistent with the level 2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in instrument characteristic and level 2 processor. The comparison of GOME-2 level 3 products to ground-based observations in general shows very good agreement, indicating the products are consistent and fulfil the requirements to serve the scientific community and general public.

Spatially heterogeneous Earth radiance scenes affect the atmospheric composition measurements of high-resolution Earth observation spectrometer missions. The scene heterogeneity creates a pseudo-random deformation of the instrument spectral response function (ISRF). The ISRF is the direct link between the forward radiative transfer model, used to retrieve the atmospheric state, and the spectra measured by the instrument. Hence, distortions of the ISRF owing to radiometric inhomogeneity of the imaged Earth scene will degrade the precision of the Level-2 retrievals. Therefore, the spectral requirements of an instrument are often parameterized in the knowledge of the ISRF over non-uniform scenes in terms of shape, centroid position of the spectral channel and the full width at half maximum (FWHM). The Sentinel-5/UVNS instrument is the first push-broom spectrometer that makes use of a concept referred to as a slit homogenizer (SH) for the mitigation of spatially non-uniform scenes. This is done by employing a spectrometer slit formed by two parallel mirrors scrambling the scene in the along track direction (ALT) and hence averaging the scene contrast only in the spectral direction. The flat mirrors do not affect imaging in the across track direction (ACT) and thus preserve the spatial information in that direction. The multiple reflections inside the SH act as coherent virtual light sources and the resulting interference pattern at the SH exit plane can be described by simulations using scalar diffraction theory. By homogenizing the slit illumination, the SH strongly modifies the spectrograph pupil illumination as a function of the input scene. In this work we investigate the impact and strength of the variations of the spectrograph pupil illumination for different scene cases and quantify the impact on the ISRF stability for different types of aberration present in the spectrograph optics.

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∘ N, 4.93∘ 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 (O4) and ozone (O3) 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 global pandemic has many negative economic, social and health impacts, but the lock-downs also led to a reduction of traffic volume which resulted in lower NO2 levels in some areas. Our study made use of different air quality measurement techniques (in-situ, on-road, satellite remote sensing) to monitor long-term NO2 levels in Munich. While comparing NO2 levels associate with traffic volume before and after a lock-down, other influences based on meteorological parameters should be considered as well. In addition to traffic data we used records of wind, mixing layer height, temperature, humidity and other meteorological parameters to analyze the impact on measured pollution levels using a Generalized Additive Model (GAM) regression. Our long-term study using data between 2018 and 2021 shows that the dominating factor is wind speed, followed by traffic volume as the main factors for impacting NO2 levels, while absolute humidity and wind direction show less effects. We utilized those findings to find best suited time periods comparable to the lockdown time in terms of meteorological conditions. In order to focus on the traffic volume factor, we applied these findings to minimize other impact factors to evaluate the NO2 variability of different years comparing to the data from the lockdown periods. A significant reduction of the ground level NO2 concentrations in Munich during the early stage of the lockdown period in March 2020 could clearly be associated with a significant reduction of traffic volume.

The problem of elevated NO2 levels in cities has gained some attention in the public in recent years and has given rise to questions about the plausibility of banning diesel engines in cities, the meaning of exceedances of air quality limits and the effects of corona lock-downs on air quality to name a few. Urban air quality is typically monitored using a relatively small number of monitoring stations. Those in-situ measurements follow certain guidelines in terms of inlet height and location relative to streets, but the question remains how a limited number of point measurements can capture the spatial variability in cities. In this talk we present two measurement campaigns in Hong Kong and Munich where we utilized a combination of mobile in-situ and stationary remote sensing differential optical absorption spectroscopy (DOAS) instruments. We developed an algorithm to separate spatial and temporal patterns in order to generate pollution maps that represent average NO2 exposure. We use those maps to identify pollution hot spots and capture the weekly cycles of on-road NO2 levels and spatial dependency of long-term changes and we analyze how on-road measurements compare to monitoring station data and how the measurement height and distance to traffic emissions have to be considered when interpreting observed concentration patterns.

We present results from the Munich NO2 imaging campaign (MuNIC) where nitrogen dioxide (NO2) near-surface concentrations (NSC) and vertical column densities (VCD) were measured with stationary, mobile and airborne in situ and remote sensing instruments. The most intensive day of the campaign was 7 July 2016, when the NO2 VCD field was mapped with the Airborne Prism Experiment (APEX) imaging spectrometer. The spatial distribution of APEX VCDs was rather smooth with a horizontal gradient between lower values upwind and higher values downwind of the city center. The NO2 map had no pronounced source signatures except for the plumes of two combined heat and power plants (CHP). The APEX VCDs agree well with mobile MAX-DOAS observations from two vehicles conducted in the same afternoon (r = 0.55). In contrast to the VCDs, mobile NSC measurements revealed high spatial and temporal variability along the roads with highest values in congested areas and tunnels. The NOx emissions of the two CHP plants were estimated from the APEX observations using a mass-balance approach. The estimates are higher than reported emissions, but uncertainties are high because the campaign day was unstable and convective, resulting in low and highly variable wind speeds. The NOx emission estimates are consistent with CO2 emissions determined from two ground-based FTIR instruments operated near one CHP plant. We conclude that airborne imaging spectrometers are well suited to map the spatial distribution of NO2 VCDs over large areas. The emission plumes of point sources can be detected in the APEX observations, but accurate flow fields are essential to estimate emissions with sufficient accuracy. The application of airborne imaging spectrometers for studying NSCs, for example as input for epidemiological studies, is less straight forward and requires to account for the non-trivial relationship between VCDs and NSCs.

A detailed analysis of springtime ozone outbreaks in South/Southwest China is presented in this paper, providing an insight into a regional photochemical and climate problem. A major ozone episode in 2013 was the first ever in April and the worst in Hong Kong up to 2018, measuring a peak ozone concentration of 293 μg m−3. This multi-day, ozone pollution was evidenced by similar conditions in the Pearl River Delta (PRD), and an even more severe episode in Kunming (Yunnan) in Southwest China. Concurrently, widespread air temperature composite anomalies of up to about +þinspace4°K were observed in the region, particularly during 6Z (14:00 local time). The global annual geopotential height anomaly implied increased atmospheric stability and inhibited dispersion---consistent with global warming impacts for the region. Backward trajectories, satellite observations, and transport model simulations characterized the biomass burning sources. Results indicated that activities in Indochina, South and Southwest China, and Africa were the main sources in South China while those in Burma dominated Southwest China. The close succession of outbreaks from west to east (Kunming, Guangzhou, and Hong Kong) suggests an eastward transport of ozone and precursors.

Modeling urban air pollutants is a challenging task not only due to the complicated, small-scale topography but also due to the complex chemical processes within the chemical regime of a city. Nitrogen oxides (NOx), particulate matter (PM) and other tracer gases, e.g. formaldehyde, hold information about which chemical regime is present in a city. As we are going to test and apply chemical models for urban pollution – especially with respect to spatial and temporally variability – measurement data with high spatial and temporal resolution are critical.Since governmental monitoring stations of air pollutants such as PM, NOx, ozone (O3) or carbon monoxide (CO) are large and costly, they are usually only sparsely distributed throughout a city. Hence, the official monitoring sites are not sufficient to investigate whether small-scale variability and its integrated effects are captured well by models. Smart networks consisting of small low-cost air pollutant sensors have the ability to provide the required grid density and are therefore the tool of choice when it comes to setting up or validating urban modeling frameworks. Such sensor networks have been established and run by several groups, achieving spatial and temporal high-resolution concentration maps [1, 2].After having conducted a measurement campaign in 2016 to create a high-resolution NO2 concentration map for Munich [3], we are currently setting up a low-cost sensor network to measure NOx, PM, O3 and CO concentrations as well as meteorological parameters [4]. The sensors are stand-alone, so that they do not demand mains supply, which gives us a high flexibility in their deployment. Validating air quality models not only requires dense but also high-accuracy measurements. Therefore, we will calibrate our sensor nodes on a weekly basis using a mobile reference instrument and apply the gathered sensor data to a Machine Learning model of the sensor nodes. This will help minimize the often occurring drawbacks of low-cost sensors such as sensor drift, environmental influences and sensor cross sensitivities. [1] Bigi, A., Mueller, M., Grange, S. K., Ghermandi, G., and Hueglin, C.: Performance of NO, NO2 low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, https://doi.org/10.5194/amt-11-3717-2018, 2018[2] Kim, J., Shusterman, A. A., Lieschke, K. J., Newman, C., and Cohen, R. C.: The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors, Atmos. Meas. Tech., 11, 1937–1946, https://doi.org/10.5194/amt-11-1937-2018, 2018[3] Zhu, Y., Chen, J., Bi, X., Kuhlmann, G., Chan, K. L., Dietrich, F., Brunner, D., Ye, S., and Wenig, M.: Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities, Atmos. Chem. Phys., 20, 13241–13251, https://doi.org/10.5194/acp-20-13241-2020, 2020[4] Zollitsch, D., Chen, J., Dietrich, F., Voggenreiter, B., Setili, L., and Wenig, M.: Low-Cost Air Quality Sensor Network in Munich, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19276, https://doi.org/10.5194/egusphere-egu2020-19276, 2020

Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2 × 1014 molec/cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5 × 1014 molec/cm2 for polluted conditions. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes are captured. For AMF calculation, the climatological surface albedo data is replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a clouds-as-layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the clouds-as-reflecting-boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the improved tropospheric NO2 data shows good correlations for nine European urban/suburban stations with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average.

The spectral accuracy of high resolution Earth observation spectrometer missions is affected by the impact of spatially heterogeneous Earth radiance scenes on the instrument spectral response function (ISRF). As the ISRF is the direct link between the forward radiative transfer model and the spectra measured by the instrument, distortions of the iSRF owing to radiometric inhomogeneity of the imaged Earth scene will degrade the precision of the Level-2 retrievals. Therefore, the spectral requirements of an instrument are often parametrized in the knowledge of the ISRF over non-uniform scenes in terms of shape, centroid position of the spectral channel and the Full Width at Half Maximum (FWHM). The Sentinel-5/UVNS instrument is the first push-broom spectrometer that makes use of a concept referred as slit homogenizer (SH) for the mitigation of spatially non-uniform scenes. This is done by employing a spectrometer slit formed by two parallel mirrors, scrambling the scene in along track direction (ALT) and hence averaging the scene contrast only in the spectral direction. The flat mirrors do not affect imaging in the across track direction (ACT) and thus preserve the spatial information in that direction. The multiple reflections inside the SH act as coherent virtual light sources and the resulting interference pattern at the SH exit plane can be described by simulations using scalar diffraction theory. By homogenizing the slit illumination, the SH moreover strongly modifies the spectrograph pupil as a function of the input scene. In this work we investigate the impact and strength of spectrograph pupil variations for different scene cases and quantify the impact on the ISRF stability for different type of aberrations present in the spectrograph optics.

Wide-field spectrometers for Earth Observation missions require inflight radiometric calibration, for which the sun can be used as a known reference. Therefor a diffuser is placed in front of the spectrometer in order to scatter the incoming light into the entrance slit and provide homogeneous illumination. The diffuser however, introduces interference patterns known as speckles into the system, yielding potentially significant intensity variations at the detector plane, called Spectral Features. There have been several approaches implemented to characterize the Spectral Features of a spectrometer, e.g. end-to-end measurements with representative instruments. Additionally, in previous publications a measurement technique was proposed, which is based on the acquisition of monochromatic speckles in the entrance slit following a numerical propagation through the disperser to the detection plane. Based on this measurement technique we present a standalone prediction model for the magnitude of Spectral Features in imaging spectrometers, requiring only few input parameters and therefor mitigating the need for expensive measurement campaigns.

Building-induced turbulence may affect aviation safety, e.g. when the aircraft is about to land at an airport. Observations of such flow have been conducted at the Hong Kong International Airport using short-range LIDAR (SRL). Statistical analysis of the radial velocity, namely, the longitudinal structure function, is described herein. It is found that the classical Kolmogorov theory for homogeneous turbulence applies to LIDAR observations of building-disrupted airflow. Some distinctive features of the turbulent flow are also discussed, notably velocity streaks and tiny anticyclones at the hectometer scale. The potential impact on a landing aircraft is examined and compared to flight data. The results in this paper could be useful for studying building-induced turbulence at other airports around the world.

We present two dimensionally scanning Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of nitrogen dioxide (NO2) and formaldehyde (HCHO) in Munich. Vertical columns and vertical distribution profiles of aerosol extinction coefficient, NO2 and HCHO are retrieved from the 2D MAX-DOAS observations. The measured surface aerosol extinction coefficients and NO2 mixing ratios derived from the retrieved profiles are compared to in-situ monitor data, and the surface NO2 mixing ratios show good agreement with in-situ monitor data with a Pearson correlation coefficient (R) of 0.91. The aerosols optical depths (AODs) show good agreement as well (R = 0.80) when compared to sun-photometer measurements. Tropospheric vertical column densities (VCDs) of NO2 and HCHO derived from the MAX-DOAS measurements are also used to validate OMI and TROPOMI satellite observations. Monthly averaged data show good correlation, however, satellite observations are on average 30 % lower than the MAX-DOAS measurements. Furthermore, the MAX-DOAS observations are used to investigate the spatio-temporal characteristic of NO2 and HCHO in Munich. Analysis of the relations among aerosol, NO2 and HCHO shows higher aerosol to HCHO ratios in winter indicating a longer atmospheric lifetime of aerosol and HCHO. The analysis also suggests that secondary aerosol formation is the major source of aerosols in Munich.

As the number of official monitoring stations for measuring urban air pollutants such as nitrogen oxides (NOx), particulate matter (PM) or ozone (O3) in most cities is quite small, it is difficult to determine the real human exposure to those pollutants. Therefore, several groups have established spatially higher resolved monitoring networks using low-cost sensors to create a finer concentration map [1-3].We are currently establishing a low-cost, but high-accuracy network in Munich to measure the concentrations of NOx, PM, O3, CO and additional environmental parameters. For that, we developed a compact stand-alone sensor systems that requires low power, automatically measures the respective parameters every minute and sends the data to our server. There the raw data is transferred into concentration values by applying the respective sensitivity function for each sensor. These functions are determined by calibration measurements prior to the distribution of the sensors.In contrast to the other existing networks, we will apply a recurring calibration method using a mobile high precision calibration unit (reference sensor) and machine learning algorithms. The results will be used to update the sensitivity function of each single sensor twice a week. With the help of this approach, we will be able to create a calibrated real-time concentration map of air pollutants in Munich.[1] Bigi et al.: Performance of NO, NO2 low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, 2018[2] Popoola et al., “Use of networks of low cost air quality sensors to quantify air quality in urban settings,” Atmos. Environ., 194, 58–70, 2018[3] Schneider et al.: Mapping urban air quality in near real-time using observations from low-cost sensors and model information, Environ. Int., 106, 234–247, 2017

We present the Airyx 2D SkySpec Instrument: A commercially available two-dimensionally scanning Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) setup for the observations of trace gases using spectral measurements of scattered sun light and optionally also direct sun light. The waterproof design of the scanner unit is designed for long-term outdoor deployment. Temperature stabilisation of the spectrometers and automatic calibration spectra measurement are used to ensure high-quality measurement data over months and years of observations.We show 2.5 years of measurements in Munich. Vertical columns and vertical distribution profiles of aerosol extinction coefficient, NO2 and HCHO are retrieved from the 2D MAX-DOAS observations. The measured surface aerosol extinction coefficients and NO2 mixing ratios are compared to in-situ monitor data. The retrieved surface NO2 mixing ratios show good agreement with in-situ monitor data with a Pearson correlation coefficient (R) of 0.91. Good agreement (R= 0.80) is also found for AOD when compared to sun-photometer measurements. Tropospheric vertical column densities (VCDs) of NO2 and HCHO derived from the MAX-DOAS measurements are also used to validate OMI and TROPOMI satellite observations. Monthly averaged data show good correlation, however, satellite observations are on average 30% lower than the MAX-DOAS measurements. Furthermore, the 2D MAX-DOAS observations are used to investigate the spatio-temporal characteristic of NO2 and HCHO in Munich. Analysis of the relations among aerosol, NO2 and HCHO show higher aerosol to HCHO ratios in winter indicating a longer atmospheric lifetime of aerosol and HCHO. The analysis also suggests that secondary aerosol formation is the major source of aerosols in Munich.

Air pollution has been gaining increasing global attention. The public is concerned about urban pollution levels including both in- and outdoor air quality. A handheld Air Quality Inspection Box (Airquix) was developed in order to monitor air pollutants in real-time, and determine individual exposure to different pollutants in different environments. The Airquix is equipped with air quality sensors: electrical chemical NO2, O3, NO sensors, NDIR CO2 sensor, OPC-N3 PM sensor; environment sensor (T, RH, P), GPS sensor and a raspberry pi for data logging, processing and display. To achieve a relatively high accuracy, e.g. +/- 5ppb at 5 seconds time resolution for the NO2 concentration, the pre- and post- calibration for the Airquix were performed by comparison with high-end air monitoring instruments. In this study, several Airquixes were distributed to different persons to assess individual exposure. The daily activities were distinguished by different commutes, in- and outdoor behaviors, the personal habits and potential episodes. The resulting data set can be used for the assessment of health impacts.

In many cities around the world the NO2 concentration levels exceed WHO guideline limits. Urban air quality is typically monitored using a relatively small number or monitoring stations that follow certain guidelines in terms of inlet height and location relative to streets. However, the question remains how a limited number of point measurements can represent the city-wide air quality and capture spatial patterns. Measurement campaigns in Hong Kong and Munich were conducted, using a combination of mobile in-situ and stationary remote sensing differential optical absorption spectroscopy (DOAS) instruments. In order to separate spatial and temporal patterns, we developed an algorithm based on a combination of mobile and stationary data sets that corrects for the diurnal cycle in the mobile measurements. We constructed pollution maps from the corrected measurements that represent daily average NO2 exposure. The maps have been used to identify pollution hot spots, determine the spatial dependency of long-term changes, and capture the weekly cycles of on-road NO2 levels in Hong Kong and Munich. Since our method can also be used to determine the spatial representativeness of the monitoring stations in cities, it is very valuable tool for identifying suitable locations for air quality monitoring stations.

In many cities around the world the overall air quality is improving, but at the same time nitrogen dioxide (NO2) trends show stagnating values and in many cases could not be reduced below air quality standards recommended by the World Health Organization (WHO). Many large cities have built monitoring stations to continuously measure different air pollutants. While most stations follow defined rules in terms of measurement height and distance to traffic emissions, the question remains of how representative are those point measurements for the city-wide air quality. The question of the spatial coverage of a point measurement is important because it defines the area of influence and coverage of monitoring networks, determines how to assimilate monitoring data into model simulations or compare to satellite data with a coarser resolution, and is essential to assess the impact of the acquired data on public health. In order to answer this question, we combined different measurement data sets consisting of path-averaging remote sensing data and in situ point measurements in stationary and mobile setups from a measurement campaign that took place in Munich, Germany, in June and July 2016. We developed an algorithm to strip temporal from spatial patterns in order to construct a consistent NO2 pollution map for Munich. Continuous long-path differential optical absorption spectroscopy (LP DOAS) measurements were complemented with mobile cavity-enhanced (CE) DOAS, chemiluminescence (CL) and cavity attenuated phase shift (CAPS) instruments and were compared to monitoring stations and satellite data. In order to generate a consistent composite map, the LP DOAS diurnal cycle has been used to normalize for the time of the day dependency of the source patterns, so that spatial and temporal patterns can be analyzed separately. The resulting concentration map visualizes pollution hot spots at traffic junctions and tunnel exits in Munich, providing insights into the strong spatial variations. On the other hand, this database is beneficial to the urban planning and the design of control measures of environment pollution. Directly comparing on-street mobile measurements in the vicinity of monitoring stations resulted in a difference of 48 %. For the extrapolation of the monitoring station data to street level, we determined the influence of the measuring height and distance to the street. We found that a measuring height of 4 m, at which the Munich monitoring stations measure, results in 16 % lower average concentrations than a measuring height of 1.5 m, which is the height of the inlet of our mobile measurements and a typical pedestrian breathing height. The horizontal distance of most stations to the center of the street of about 6 m also results in an average reduction of 13 % compared to street level concentration. A difference of 21 % in the NO2 concentrations remained, which could be an indication that city-wide measurements are needed for capturing the full range and variability of concentrations for assessing pollutant exposure and air quality in cities.

In this paper we present an investigation of the spatial and temporal variability of street-level concentrations of NO2 in Hong Kong as an example of a densely populated megacity with heavy traffic. For the study we use a combination of open-path remote sensing and in situ measurement techniques that allows us to separate temporal changes and spatial patterns and analyse them separately. Two measurement campaigns have been conducted, one in December 2010 and one in March 2017. Each campaign lasted for a week which allowed us to examine diurnal cycles, weekly patterns as well as spatially resolved long-term changes. We combined a long-path differential optical absorption spectroscopy (DOAS) instrument with a cavity-enhanced DOAS and applied several normalizations to the data sets in order to make the different measurement routes comparable. For the analysis of long-term changes we used the entire unfiltered data set and for the comparison of spatial patterns we filtered out the accumulation of NO2 when stopping at traffic lights for focusing on the changes of NO2 spatial distribution instead of comparing traffic flow patterns. For the generation of composite maps the diurnal cycle has been normalized by scaling the mobile data with coinciding citywide path-averaged measurement results. An overall descending trend from 2010 to 2017 could be observed, consistent with the observations of the Ozone Monitoring Instrument (OMI) and the Environment Protection Department (EPD) air quality monitoring network data. However, long-term difference maps show pronounced spatial structures with some areas, e.g. around subway stations, revealing an increasing trend. We could also show that the weekend effect, which for the most part of Hong Kong shows reduced NO2 concentrations on Sundays and to a lesser degree on Saturdays, is reversed around shopping malls. Our study shows that spatial differences have to be considered when discussing citywide trends and can be used to put local point measurements into perspective. The resulting data set provides a better insight into on-road NO2 characteristics in Hong Kong, which helps to identify heavily polluted areas and represents a useful database for urban planning and the design of pollution control measures.

In this paper, we present long term observations of atmospheric aerosols and nitrogen dioxide (NO2) in Hong Kong using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground based MAX-DOAS measurements were performed over 5years from December 2010 to November 2015. Vertical distribution profiles of aerosols and NO2 were derived from MAX-DOAS O4 and NO2 observations by applying the optimal estimation method. Retrieved MAX-DOAS measurements of aerosols and NO2 show good agreement with sun photometer observation of aerosol optical depths (AODs) and long path DOAS measurement of ground level NO2 mixing ratios. Tropospheric vertical column densities (VCDs) of NO2 derived from MAX-DOAS measurements are used to validate OMI satellite NO2 observations. Daily data show reasonably good agreement with each other with Pearson correlation coefficient R=0.7. However, MAX-DOAS NO2 VCDs are on average higher than OMI observations by a factor of 2. Introducing aerosols in the air mass factor calculation would enhance the OMI VCDs by 7-13%, the remaining discrepancy is mainly due to the differences in spatial coverage between the two instruments. Diurnal variation patterns of aerosols and NO2 indicated significant contributions from local anthropogenic emissions. Analysis of air mass transport shows that the enhancement of surface aerosols and NO2 concentrations mainly results from accumulation of local emissions under low wind speed conditions.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° 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 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, to discuss the performance of the various types of instruments and 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 dimer (O4) and ozone (O3) 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. 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 an unprecedented 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 reference, 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 measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

In this paper, we present long term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate OMI satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by ~ 30 % with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. We developed a new technique to assemble the source contribution map using backward trajectory analysis. The age weighted backward propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward propagated HCHO data does not show a strong spatial correlation with the OMI HCHO observations. The result shows the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %–50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants in over the Yangtze River Delta as well as the effect of emission control measures during large international event, which are important for the future design of air pollution control policies.

Model simulations and hydrological reanalysis data for 2007 are applied to investigate the impact of long-range desert dust transport on hydrometeor formation over coastal East Asia. Results are analyzed from Hong Kong and Shanghai, which are two representative coastal cities of East Asia. Long-range desert dust transport impacts mainly spring and summer clouds and precipitation over coastal East Asia. In spring, clouds and precipitation come mainly from large-scale condensation and are impacted mainly by dust from the Gobi, Sahara, and Thar deserts. These desert dusts can participate in the precipitation within and below the clouds. At lower latitudes, the dust particles act mainly as water nuclei. At higher latitudes, they act as both water nuclei and ice nuclei. The effect of Gobi, Sahara, and Thar dust on large-scale clouds and precipitation becomes stronger at higher latitudes. In summer, clouds and precipitation over coastal East Asia come mainly from convection and are impacted mainly by dust from the Taklamakan, Arabian, and Karakum-Kavir deserts. Most Taklamakan dust particles can participate in precipitation within convective clouds as ice nuclei, while Arabian and Karakum-Kavir dust particles participate only as water nuclei in precipitation below the clouds. The effect of Taklamakan dust on convective clouds and precipitation becomes stronger at lower latitudes. Of all the desert dusts, that from the Gobi and Taklamakan deserts has the relatively largest impact. Gobi dust impacts climate change in coastal East Asia by affecting spring water clouds at higher latitudes.

Spectrometers for Earth Observation require inflight radiometric calibration, for which the sun can be used as a known reference. For wide field instruments, a diffuser is placed in front of the spectrometer, scattering incoming sun light into the entrance slit and ensuring a homogenous illumination. As drawback, the diffuser induces a specific radiometric error caused by interference, so called Spectral Features. The scattering of the incident light at the diffuser induces a random path difference yielding a specific interference pattern at the entrance slit, known as a speckle pattern. These speckles are propagated through the disperser to the detector plane and further integrated by the detector pixels. The resulting intensity variation can yield a significant signal error contribution, whose spectral variation is referred to as spectral features. The magnitude of this error is evaluated in terms of the Spectral Features Amplitude (SFA), the ratio of the signal standard deviation with its mean value over a specific wavelength range. There have been several approaches implemented to characterize the SFA of a spectrometer, e.g. end-to-end measurements with representative instruments. Typically the measurement accuracy is not sufficient to isolate the SFA from other radiometric errors. As a consequence, the instrument layout can hardly be optimized to suppress Spectral Features. We describe a novel characterization technique for Spectral Features based on the direct acquisition of monochromatic speckle patterns at the entrance slit. This allows the observation of Spectral Features below the level of the spectrometer spectral and spatial resolution. The Spectral Features are derived from various observed speckle patterns by properly mimicking the real spectrometer in the data analysis. With this measurement technique we are able to gain insight into the mechanism behind speckle induced Spectral Features. This insight will be used to develop a parameterized model facilitating the design and analysis of future space based spectrometers.

In this paper we present an investigation of the spatial and temporal variability of street level concentrations of NO2 in Hong Kong as an example for a densely populated megacity with heavy traffic. For the study we use a combination of open path remote sensing and in-situ measurement techniques that allows us to separate temporal changes and spatial patterns and analyse them separately. Two measurement campaigns have been conducted, one in December 2010 and one in March 2017. Each campaign lasted for a week which allowed us to examine diurnal cycles, weekly patterns as well as spatially resolved long term changes. We combined a long-path Differential Optical Absorption Spectroscopy (DOAS) instrument with a cavity enhanced DOAS and applied several normalizations to the data sets in order to make the different measurement routes comparable. For the analysis of long term changes we used the entire unfiltered data set, for the comparison of spatial patterns we filtered out the accumulation of NO2 when stopping at traffic lights for focusing on the changes of NO2 spatial distribution instead of comparing traffic flow patterns, and for the generation of composite maps the diurnal cycle has been normalized by scaling the mobile data with coinciding citywide path-averaged measurement results. An overall descending trend from 2010 to 2017 could be observed, consistent with the observations of the ozone monitoring instrument (OMI) and the Environment Protection Department (EPD) air quality monitoring network data. However, long term difference maps show pronounced spatial structures with some areas, e.g. around subway stations, revealing an increasing trend. We could also show, that the weekend effect, which for the most part of Hong Kong shows reduced NO2 concentrations on Sundays and to a lesser degree on Saturdays, is reversed around shopping malls. Our study shows that the spatial differences have to be considered when discussing city-wide trends and can be used to put local point measurements into perspective. The resulting data set provides a better insight into on-road NO2 characteristics in Hong Kong which helps to identify heavily polluted areas and represents a useful database for urban planning and the design of pollution control measures.

In our study we developed an algorithm that combines stationary long-path Differential Optical Absorption Spectroscopy (LP DOAS) and cavity-enhanced DOAS (CE DOAS) measurements to produce consistent concentrations maps of Munich and Hong Kong.

During the Shanghai World Expo 2010 ground based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of tropospheric nitrogen dioxide (NO2) were performed to investigate the effects of emission control measures during that time. In this study we measured NO2 using four identical MAX-DOAS instruments in Shanghai from April 2009 to November 2010. We combined our MAX-DOAS data, the Ozone Monitoring Instrument (OMI) satellite observations and meteorological information from the National Centers for Environmental Prediction final reanalysis data (NCEP FNL) in order to investigate the spatial distribution of NO2 over Shanghai and the effects of emission control measures during the Expo. In general, the comparison of cloud screened MAX-DOAS data and OMI observations are in good correlation (Pearson correlation coefficient between 0.67 and 0.93 for the four measurement stations). In addition, we compared the MAX-DOAS and OMI NO2 data from the Shanghai Expo in 2010 to the same time of the year in 2009. The results show that the NO2 columns were reduced up to ∼ 30% in the area of central Shanghai during the Expo but no significant reduction of NO2 levels was found in the nearby industrial area. The overall NO2 reduction from May, July and September 2010 ranged from 7.5% to 14.5%, which is comparable to observations in previous studies. Our results revealed that the NO2 reduction was mainly achieved by emission control policies on transportation sources in the city rather than the controls from nearby provinces.

In this paper, we present the custom Hong Kong NO2 retrieval (HKOMI) for the Ozone Monitoring Instrument (OMI) on board the Aura satellite which was used to evaluate a high-resolution chemistry transport model (CTM) (3 km × 3 km spatial resolution). The atmospheric chemistry transport was modelled in the Pearl River Delta (PRD) region in southern China by the Models-3 Community Multiscale Air Quality (CMAQ) modelling system from October 2006 to January 2007. In the HKOMI NO2 retrieval, tropospheric air mass factors (AMFs) were recalculated using high-resolution ancillary parameters of surface reflectance, a priori NO2 and aerosol profiles, of which the latter two were taken from the CMAQ simulation. We tested the influence of the ancillary parameters on the data product using four different aerosol parametrizations. Ground-level measurements by the PRD Regional Air Quality Monitoring (RAQM) network were used as additional independent measurements. The HKOMI retrieval increases estimated tropospheric NO2 vertical column densities (VCD) by (+31 ± 38)%, when compared to NASA's standard product (OMNO2-SP), and improves the normalized mean bias (NMB) between satellite and ground observations by 26 percentage points from −41 to −15%. The individual influences of the parameters are (+11.4 ± 13.4)% for NO2 profiles, (+11.0 ± 20.9)% for surface reflectance and (+6.0 ± 8.4)% for the best aerosol parametrization. The correlation coefficient r is low between ground and satellite observations (r = 0.35). The low r and the remaining NMB can be explained by the low model performance and the expected differences when comparing point measurements with area-averaged satellite observations. The correlation between CMAQ and the RAQM network is low (r ≈ 0.3) and the model underestimates the NO2 concentrations in the northwestern model domain (Foshan and Guangzhou). We compared the CMAQ NO2 time series of the two main plumes with our best OMI NO2 data set (HKOMI-4). The model overestimates the NO2 VCDs by about 15% in Hong Kong and Shenzhen, while the correlation coefficient is satisfactory (r = 0.56). In Foshan and Guangzhou, the correlation is low (r = 0.37) and the model underestimates the VCDs strongly (NMB = −40%). In addition, we estimated that the OMI VCDs are also underestimated by about 10 to 20% in Foshan and Guangzhou because of the influence of the model parameters on the AMFs. In this study, we demonstrate that the HKOMI NO2 retrieval reduces the bias of the satellite observations and how the data set can be used to study the magnitude of NO2 concentrations in a regional model at high spatial resolution of 3 × 3 km2. The low bias was achieved with recalculated AMFs using updated surface reflectance, aerosol profiles and NO2 profiles. Since unbiased concentrations are important, for example, in air pollution studies, the results of this paper can be very helpful in future model evaluation studies.

We describe the new, version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/uui/datasets/OMNO2_V003/summary). The major improvements include: (1) new spectral fitting algorithm for NO2 slant column density (SCD) retrieval; (2) higher resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry-transport model with yearly varying emissions to calculate air-mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ~ 10 %–40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over Western Europe, the eastern US and eastern China. Initial evaluation over unpolluted areas has shown that the new SPv3 products agree better with independent satellite and ground based FTIR measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hotspots.

Summertime surface ozone (O) and related secondary formation of fine particles are the major air quality concerns in the megacity of Shanghai. We performed mobile Cavity Enhanced Differential Optical Absorption Spectroscopy (CE-DOAS) measurements to investigate the spatial distribution of on-road nitrogen dioxide (NO) concentrations along the Inner Ring Elevated Road (IRER) in Shanghai. The observations show a ratio of 4 between CE-DOAS averaged on-road NO and the in-situ ambient measurements, illustrating the strong impact of vehicle emissions over the urban area. The air mass transport analysis suggests that the observed episodic ozone events arise from both the abundance of volatile organic compounds (VOCs) precursors in the sampled plume and the regional transport of ozone-rich air masses. Analysis of the sources of PM shows that the secondary heterogeneous gas-to-particle conversion of sulfate and nitrate from sulfur dioxide (SO) and nitrogen oxides (NO) is the largest source of PM contributing 44.8 ± 9.2% of the total PM. Ozone-related photochemical formation of fine particles is estimated to contribute about 22.5 ± 11.9% of the total PM, which is strongly facilitated by solar radiation in summer. According to our results, nitrous acid (HONO) is the major precursor of hydroxyl radicals (OH) accounting for 40% to 80% of the total OH production during daytime. A significant correlation is found between the HONO levels in the early morning and the daily O and PM levels. The summertime measurements indicate that the photolytic reaction of HONO after sunrise increased the abundance of daytime OH and oxidative capacity, resulting in an enhancement of ground level ozone and secondary organic aerosol formation. This study provides quantitative information to better understand photochemical formation of ozone and fine particles in Shanghai during summertime, which is useful for designing collaborative strategies to mitigate emissions of precursor pollutants.

Concerns have been raised about the possible connections between the local and regional photochemical problem and global warming. The current study assesses the trend of ozone in Hong Kong and the Pearl River Delta (PRD) in South China and investigates the interannual changes of sensitivity of ozone to air temperature, as well as the trends in regional precursors. Results reveal, at the three monitoring sites from the mid-1990s to 2010, an increase in the mean ozone concentrations from 1.0 to 1.6 µg m −3 per year. The increase occurred in all seasons, with the highest rate in autumn. This is consistent with trends and temperature anomalies in the region. The increase in the sensitivity of ozone to temperature is clearly evident from the correlation between ozone (OMI [Ozone Monitoring Instrument] column amount) and surface air temperature (from the Atmospheric Infrared Sounder) displayed in the correlation maps for the PRD during the prominently high ozone period of July–September. It is observed to have increased from 2005 to 2010, the latter being the hottest year on record globally. To verify this temporal change in sensitivity, the ground-level trends of correlation coefficients/regression slopes are analysed. As expected, results reveal a statistically significant upward trend over a 14-year period (1997–2010). While the correlation revealed in the correlation maps is in agreement with the corresponding OMI ozone maps when juxtaposed, temperature sensitivity of surface ozone also shows an association with ozone concentration, with R =0.5. These characteristics of ozone sensitivity are believed to have adverse implications for the region. As shown by ground measurements and/or satellite analyses, the decrease in nitrogen oxides (NO 2 ) and NO x in Hong Kong is not statistically significant while NO 2 of the PRD has only very slightly changed. However, carbon dioxide has remarkably declined in the whole region. While these observations concerning precursors do not seem to adequately support an increasing ozone trend, measured surface levels of formaldehyde, a proxy for volatile organic compound (VOC) emissions, have risen significantly in the PRD (2004–2010). Hence, the reactive VOCs in the PRD are likely to be the main culprit for the increase of ozone, as far as precursors are concerned. Despite the prevailing problem, model simulations suggest prospects for improvement in the future. Keywords: ozone trends, temperature sensitivity of ozone, sensitivity and concentration, ozone precursors, future ozone, South China (Published: 11 August 2014) Citation: Tellus B 2014, 66 , 23455, http://dx.doi.org/10.3402/tellusb.v66.23455

The recent increase in spatial resolution for satellite instruments has made it feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (level 2) onto a longitude–latitude grid (level 3). The algorithm is designed for the Ozone Monitoring Instrument (OMI) and can easily be employed for similar instruments – for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI). Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrisation of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly developed gridding algorithm improves regional trace gas maps; its application could be very helpful for the study of satellite-derived trace gas distributions.

The contribution of major aerosol components emitted from local and remote regions to Hong Kong's Aerosol Optical Depth (AOD) in 2007 is quantitatively determined using the chemical transport model GOCART (Global Ozone Chemistry Aerosol Radiation and Transport). Of the major aerosol components, sulphur has the largest influence (68%) on Hong Kong, followed by organic carbon (OC, 13%) and dust (11%), and the influences of black carbon (BC, 5%) and sea salt (3%) are the lowest. The highest AOD is seen in September 2007 and is composed mainly of sulphur aerosols (85%). The high AOD values in March and April 2007 are caused by sulphur and OC. OC has a relative contribution of 39% in March and 30% in April. The anthropogenic sulphur, BC, and OC emitted from every continent, as well as from China and South China, are considered respectively. In summer, South China's contribution of sulphur aerosols from anthropogenic SO 2 emissions to the total sulphur AOD in Hong Kong is more than 20%. In other seasons, sulphur aerosols from anthropogenic SO 2 emissions in Rest China (all of China except South China) accounts for more than 25%. Anthropogenic BC from South China accounts for more than 20% of total BC AOD in Hong Kong in summer. The contribution of anthropogenic BC from Rest China exceeds 40% in autumn and winter. Anthropogenic BC from Rest Asia (all of Asia except China) accounts for more than 30% in summer and autumn. The contribution of anthropogenic OC from Rest China is more than 35% in autumn and winter. The contribution of anthropogenic OC from Rest Asia exceeds 20% in summer. Gobi dust accounts for more than 40% of the total dust AOD in winter, and its impact appears mainly in the Atmospheric Boundary Layer (ABL), where it is responsible for 50% of the dust concentration. The contribution of Sahara dust to the dust AOD in spring exceeds 35%, and its contribution to the dust concentration in the free atmosphere (40%) is larger than that in the ABL (10%). More than 35% of the dust AOD in summer and autumn comes from Taklamakan dust, which exists mainly in the free atmosphere, where it accounts for 40% of the dust concentration.

In this paper, we present the first dispersive infrared spectroscopic (DIRS) measurement of atmospheric carbon dioxide (CO2) using a new scanning Fabry-Perot interferometer (FPI) sensor. The sensor measures the optical spectra in the mid infrared (3,900 nm to 5,220 nm) wavelength range with full width half maximum (FWHM) spectral resolution of 78.8 nm at the CO2 absorption band (~4,280 nm) and sampling resolution of 20 nm. The CO2 concentration is determined from the measured optical absorption spectra by fitting it to the CO2 reference spectrum. Interference from other major absorbers in the same wavelength range, e.g., carbon monoxide (CO) and water vapor (H2O), was taken out by including their reference spectra in the fit as well. The detailed descriptions of the instrumental setup, the retrieval procedure, a modeling study for error analysis as well as laboratory validation using standard gas concentrations are presented. An iterative algorithm to account for the non-linear response of the fit function to the absorption cross sections due to the broad instrument function was developed and tested. A modeling study of the retrieval algorithm showed that errors due to instrument noise can be considerably reduced by using the dispersive spectral information in the retrieval. The mean measurement error of the prototype DIRS CO2 measurement for 1 minute averaged data is about ±2.5 ppmv, and down to ± 0.8ppmv for 10 minute averaged data. A field test of atmospheric CO2 measurements were carried out in an urban site in Hong Kong for a month and compared to a commercial non-dispersive infrared (NDIR) CO2 analyzer. 10 minute averaged data shows good agreement between the DIRS and NDIR measurements with Pearson correlation coefficient (R) of 0.99. This new method offers an alternative approach of atmospheric CO2 measurement featuring high accuracy, correction of non-linear absorption and interference of water vapor.

Biomass burning is the largest source of primary fine carbonaceous particles and globally the second largest source of trace gases, contributing to climate change and regional air pollution. This study investigates the most serious black carbon (BC) episodes in Hong Kong in 2010, which occurred on 22 February, 18 March, 6, 20 and 21 December. The contributing sources were identified using an integrated approach of ground-based measurement, satellite data analyses and model simulations. Hourly maximum BC concentrations from continuous monitoring ranged from 15.6 to 18.9 μg m −3 . The correlation coefficients between hourly BC and carbon monoxide (CO) concentrations (CO as an indicator of biomass burning) varied from 0.88 to 0.97 during episodic/high BC days whereas daily ΔBC/ΔCO ratios for the episodes were between 9.05 and 13.1 ng m −3 ppbv −1 , significantly higher than the seasonal averages. Non-sea-salt (nss)-K + (daily), another indicator of biomass burning, correlated moderately with BC ( r = 0.52) for concentrations above the 80th percentile. The area-averaged statistics for fire pixel counts from satellite measurement showed the intensity of biomass burning in 2010 was strongest in Africa, Southwest China and Indochina, followed by North/Central, South China and India. Except for North/Central China, all sources are upwind of Hong Kong when the northeast monsoon and the mid/upper-tropospheric westerlies (subtropical jet) prevail. GEOS-Chem simulations indicate that biomass burning contributed most significantly from Indochina (southwest China included) in the spring of 2010. This model sensitivity analysis complements the MODIS-based fire map(s), the high-level vector wind plots, the AIRS CO and backward trajectory analyses. Results suggest that other contributors of BC include not only South China, but also the Indian subcontinent (in spring) and Africa in winter. The latter's influence is evident in the February and December episodes.