Ronald J. van der A

Recent reduction in NO x emissions over China: synthesis of satellite observations and emission inventories

Tropospheric nitrogen dioxide (NO2) column densities detected from space are widely used to infer trends in terrestrial nitrogen oxide (NO x ) emissions. We study changes in NO2 column densities using the Ozone Monitoring Instrument (OMI) over China from 2005 to 2015 and compare them with the bottom-up inventory to examine NO x emission trends and their driving forces. From OMI measurements we detect the peak of NO2 column densities at a national level in the year 2011, with average NO2 column densities deceasing by 32% from 2011 to 2015 and corresponding to a simultaneous decline of 21% in bottom-up emission estimates. A significant variation in the peak year of NO2 column densities over regions is observed. Because of the reasonable agreement between the peak year of NO2 columns and the start of deployment of denitration devices, we conclude that power plants are the primary contributor to the NO2 decline, which is further supported by the emission reduction of 56% from the power sector in the bottom-up emission inventory associated with the penetration of selective catalytic reduction (SCR) increasing from 18% to 86% during 2011–2015. Meanwhile, regulations for vehicles also make a significant contribution to NO x emission reductions, in particular for a few urbanized regions (e.g., Beijing and Shanghai), where they implemented strict regulations for vehicle emissions years before the national schedule for SCR installations and thus reached their NO2 peak 2–3 years ahead of the deployment of denitration devices for power plants.

ozone mini‐hole observed over Europe, influence of low stratospheric temperature on observations

A region of extreme low ozone values passed over North-western Europe during November 30, and December 1, 1999. The total ozone values were measured from the ground, with a Brewer Spectrophotometer, and from space with the GOME and TOMS satellite instruments. The ozone sonde measurement and the retrieved GOME ozone profile have shown that the main reduction in the ozone column occurred between the ozone maximum (22 km) and the tropopause. The low temperatures found in the stratosphere during this event have significant consequences for the ozone retrieval algorithm, both for satellite retrievals and for the Brewer measurements.

Ozone profile retrieval from GOME data

GOME is the first satellite instrument with the possibility to retrieve height-resolved ozone densities in both stratosphere and troposphere. The high accuracy and spectral resolution of the GOME spectrometer in the range of 240-790 nm combined with sophisticated retrieval algorithms enables the derivation of accurate ozone profiles. This paper discusses in detail the retrieval procedure of ozone profiles from the GOME observations. The resulting profiles and their calculated errors are discussed and compared to local ozone profiles form ozone sonde measurements.

Interannual variability of nitrogen oxides emissions from boreal fires in Siberia and Alaska during 1996–2011 as observed from space

Past studies suggest that forest fires contribute significantly to the formation of ozone in the troposphere. However, the emissions of ozone precursors from wildfires, and the mechanisms involved in ozone production from boreal fires, are very complicated. Moreover, an evaluation of the role of forest fires is prevented by the lack of direct observations of the ozone precursor, nitrogen oxides (NOx), and large uncertainties exist in the emissions inventories currently used for modelling. A comprehensive understanding of the important processes and factors involving wildfires has thus been unobtainable. We made 16 year consistent analyses of NOx emissions from boreal wildfires by using satellite observations of tropospheric nitrogen dioxides (NO2) from 1996 to 2011. We report substantial interannual variability of tropospheric NO2 originating from large boreal fires over Siberia in 1998, 2002, 2003, 2006, and 2008; and over Alaska in 2004, 2005, and 2009. Monthly comparisons of NO2 enhancements with fire radiative power (FRP) show reasonably strong correlation, suggesting that FRP is a better proxy than burned area for boreal fire NOx emissions. We provide space-based constraints on NOx emission factors (EFs) for Siberian and Alaskan fires. Although the associated uncertainty is relatively large, the derived EFs fall into a in reasonably agreeable range with those previously determined by in situ ground-based and airborne observations over these regions.

Space-based surface UV monitoring for Europe using SCIAMACHY and MSG

In order to characterize the solar UV radiation reaching the Earths surface it is monitored from space by means of (i) the clear-sky UV index at local solar noon, which is most relevant for operational UV forecasting, and (ii) the daily UV dose including cloud shielding effects, which is most relevant for long-term UV monitoring and assessments of health risks and biological UV effects. Optimal space- based surface UV monitoring combines information from platforms in different orbits. Space-based total ozone column products from polar orbiting platforms can be used adequately for UV monitoring because the diurnal variability in the total ozone column is limited. However, cloud cover and cloud optical thickness typically vary significantly on time scales of minutes to hours, especially over land in relation to convective activity. Because diurnal variations in cloud amount and cloud optical thickness impact dramatically on the daily-integrated UV radiation levels transmitted to the Earths surface, the time variations in (key) cloud parameters over the day need to be captured by observations. Sampling of the diurnal variations in clouds is most efficiently done from geostationary platforms. Here we demonstrate examples of calculations of the clear- sky UV index and the UV daily dose for erythema over Europe based on assimilated total ozone column data derived from observations by GOME aboard ERS-2 and its successor SCIAMACHY aboard ENVISAT, in combination with cloud information retrieved from MVIRI aboard Meteosat-7 and its successor SEVIRI aboard MSG (Meteosat-8). Some first validations with ground-based surface spectral UV data are presented.

Improved ozone profile retrieval from combined nadir/limb observations of SCIAMACHY

The spectrometer instrument SCIAMACHY is planned to be launched in 2001 to observe trace gas concentrations in the atmosphere. This instrument will alternately observe the same air mass in limb and nadir direction in the wavelength range of 240 to 2400 nm. The combination of these nadir and limb observations is likely to improve the ozone profile observations in the troposphere and stratosphere. In this sensitivity study the method of calculating the retrieval errors and covariances of the ozone profile values will be described, and the results will be presented for a few representative scenarios. It will be shown that the accuracy of ozone profile retrievals based on combined nadir/limb observations will no longer be limited by instrument noise. Therefore the accuracy of the retrieved ozone profiles in troposphere and stratosphere has the potential to be higher than of single-nadir observations from similar instruments.

Evaluation of modeling NO 2 concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope= 0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope= 1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15 % in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

A new method for deriving trace gas emission inventories from satellite observations: The case of SO2 over China

A method is developed that allows the construction of spatial emission inventories. The method is applied for anthropogenic SO2 over China (0.25°×0.25°). The Enhancement Ratio Method (ERM) allows for the calculation of SO2 emissions using relationships between gridded satellite measurements of SO2 and NO2 at low wind speeds, and satellite-based NOx emission estimates. Here, we derive SO2 emissions for five years (2007-2011). A large decrease of emissions during 2007-2009 and a modest increase between 2010 and 2011 is observed. The evolution of emissions over time calculated here is in general agreement with bottom-up inventories, although differences exist, not only between the current inventory and other inventories but also among the bottom up inventories themselves. The ERM-derived emissions are consistent, spatially and temporally, with existing inventories.

Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations. Part I: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995–2002), the Advanced ATSR (AATSR, 2002–2012) (together ATSR) and the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite (2000–2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and the MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these datasets provide an AOD time series for 23 years, from 1995 to 2017. The difference between the AOD values retrieved from ATSR-2 and AATSR is small, as shown by pixel-by-pixel and monthly aggregate comparisons as well as validation results. This allows for the combination of the ATSR-2 and AATSR AOD time series into one dataset without offset correction. ADV and MODIS AOD validation results show similar high correlations with the Aerosol Robotic Network (AERONET) AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV (− 0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90 min of each other and when both ADV and MODIS retrieve AOD around AERONET locations, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate the AERONET AOD. Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates as well as in time series. ADV–MODIS difference maps show that MODIS AOD is generally higher than that from ADV. Both ADV and MODIS show similar seasonal AOD behavior. The AOD maxima shift from spring in the south to summer along the eastern coast further north. The agreement between sensors regarding year-to-year AOD changes is quite good. During the period from 1995 to 2006 AOD increased in the southeast (SE) of China. Between 2006 and 2011 AOD did not change much, showing minor minima in 2008–2009. From 2011 onward AOD decreased in the SE of China. Similar patterns exist in year-toyear ADV and MODIS annual AOD tendencies in the overlapping period. However, regional differences between the ATSR and MODIS AODs are quite large. The consistency Published by Copernicus Publications on behalf of the European Geosciences Union. 11390 L. Sogacheva et al.: Spatial and seasonal variations of aerosols over China – Part 1 between ATSR and MODIS with regards to the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average; however, in winter and spring, when there is a difference in coverage between the two instruments, the agreement between ATSR and MODIS is lower. AOD tendencies in China during the 1995–2017 period will be discussed in more detail in Part 2 (a following paper: Sogacheva et al., 2018), where a method to combine AOD time series from ADV and MODIS is introduced, and combined AOD time series are analyzed.

Global trends in tropospheric NO 2 observed from space

Here we present results of a global trend analysis using nearly a decade of NO2 observations acquired by the SCIA-MACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) instrument onboard the Envisat satellite platform. Monthly average tropospheric NO2 column data was acquired for the period between August 2002 and August 2011. A trend analysis was subsequently performed by fitting a statistical model including a seasonal cycle and linear trend to the time series extracted at each grid cell. The linear trend component and the trend uncertainty were then mapped spatially at both regional and global scales. The results show that spatially contiguous areas of significantly increasing NO2 levels are found primarily in Eastern China. In addition, many urban agglomerations in Asia and the Middle East similarly exhibit significantly increasing trends, with Dhaka in Bangladesh being the megacity with the most rapid relative increase during the study period. In contrast, significantly decreasing trends in NO2 levels exist over large parts of Europe and the Eastern United States. The satellite-derived time series were further analysed with respect to identification of the impact of the 2008/2009 economic crisis. European trends obtained from the satellite analysis are also compared with corresponding trends computed using data of the EMEP model, as well as with NO2 trends calculated from station observations throughout Europe.