Cleaning up the air : Effectiveness of air quality policy for SO 2 and NOx emissions in China

Air quality observations by satellite instruments are global and have a regular temporal resolution, which make them very useful in studying long-term trends in atmospheric species. To monitor air quality trends in China for the period 2005-2015 we derive SO2 columns and NOx emissions on a provincial level with improved accuracy. To put these trends 15 into perspective they are compared with public data on energy consumption and the environmental policies of China. We distinguish the effect of air quality regulations from economic growth by comparing them relatively to fossil fuel consumption. Pollutant levels, per unit of fossil fuel, are used to assess the effectiveness of air quality regulations. We note that the desulphurisation regulations enforced in 2005-2006 only had a significant effect in the years 2008-2009 when a much stricter control of the actual use of the installations began. For national NOx emissions a distinct decreasing trend is 20 only visible since 2012, but the emission peak year differs from province to province. Unlike SO2, emissions of NOx are highly related to traffic. Furthermore, regulations for NOx emissions are partly decided on a provincial level. The last three years show both a reduction in SO2 and NOx emissions per fossil fuel unit, since the authorities have implemented several new environmental regulations. Despite an increasing fossil fuel consumption and a growing transport sector, the effects of air quality policy in China are clearly visible. Without the air quality regulations the concentration of SO2 would be about 2.5 25 times higher and the NO2 concentrations would be at least 25% higher than they are today in China.


Introduction
Satellite instruments can monitor air quality from space by mapping, for example, aerosols and tropospheric ozone, but they are especially useful for emission estimates in observing the relatively short-living gases nitrogen dioxide (NO 2 ) and sulfur dioxide (SO 2 ).For these two trace gases improved data sets have recently become available, enabling analysis of air quality time series on a national or provincial level with improved accuracy.Theys et al. (2015) presented a new data set of SO 2 column densities derived from the Ozone Monitoring Instrument (OMI) satellite instrument (Levelt et al., 2006).They conclude that the SO 2 concentrations derived from OMI agree on average within 12 % with ground observations.This data set strongly improves on earlier SO 2 data sets from satellites, which motivated this study.For NO 2 , instead of using concentration data, we directly assess the emission data of nitrogen oxides (NO x = NO 2 + NO) that were derived from satellite observations by Mijling and Van der A (2012) and remove the meteorological influences.The precision of the derived NO x emissions per grid cell of 0.25 • × 0.25 • is estimated as 20 % (Ding et al., 2016a).(Kurokawa et al., 2013).The size of each dot indicates the emission of the power plants (power plants in close proximity are combined in a single dot).In addition, a list is given of the provinces mentioned in this study.
China is one of the largest emitters of SO 2 and NO 2 into the atmosphere because its large economy depends heavily on fossil fuels as an energy source.China alone is responsible for about 30 % of the total global emissions of SO 2 into the atmosphere (Klimont et al., 2013), while over 90 % of the SO 2 emissions are caused by coal consumption in China (Chen and Xu, 2010).Coal is mainly used by thermal power plants and in energy-intensive industry (e.g.steel, cement, and glass), and to a lesser extent residentially.SO 2 is also released by the use of oil and natural gas, but the sulfur content in these fuel types is much lower.Of these sources, power plants are responsible for about 30-40 % of all emissions and industry for another 50-60 % (He et al., 2012;ChinaFAQs project, 2012).According to the Multi-resolution Emission Inventory for China (MEIC) (http://www.meicmodel.org/) the source of SO 2 emissions in 2010 was 29.4 % from power plants, 57.7 % from industry, 11.7 % from residential, and 1.2 % from transport.Figure 1 shows the location of the 600 largest thermal power plants on the map of China, including a list of provinces mentioned in this study.At a global scale, volcanic activity is another important source of atmospheric SO 2 .However, plumes of active volcanoes are seldom observed over China.
NO x is released by more or less the same anthropogenic sources, i.e. the burning of coal or oil.The main difference to SO 2 is that traffic is a much more important source for NO x .NO x emission factors (i.e.emissions per fossil fuel unit) in the transport sector are generally much higher than emission factors in energy and industry, which makes traffic one of the major sources of NO x in China.According to the MEIC inventory, 25 % of NO 2 in 2010 was released by traffic, 32 % by power plants, 4 % by residential sources and 39 % by industry, with the cement industry being the largest emitter in this sector.
To reduce SO 2 in China, the authorities have implemented several environmental regulations.The most important regulation was the desulfurization of coal-fired power plants in 2005/2006(Xu, 2011)).This was later followed in the 12th five-year plan (2011)(2012)(2013)(2014)(2015) by stricter control on the implementation of the regulations; additional filtering efforts; switching to low-sulfur coal and petrol; phasing out obsolete capacity in coal-using industry; phasing out small-scale coal mining; and gradually using more oil, gas, and renewable energies instead of coal from 2011 onward.An overview of all regulations related to SO 2 is shown in Table 1, which includes the year in which the implementation began.
The regulation of NO x was started much later than for SO 2 .The 12th five-year plan mentioned the intention to reduce NO 2 by 10 % (target) (ChinaFAQs project, 2012); from 2011 onward NO x filtering systems were installed, mainly at power plants but also for heavy industry.These regulations for NO x were announced in 2013 in the Air Pollution Prevention and Control Action Plan (CAAC, 2013).According to Liu et al. (2016b) selective catalytic reduction (SCR) equipment was installed in this period and grew from a penetration of about 18 % in 2011 to 86 % in 2015.SCR equip-  ment in power plants are expected to reduce the emissions of the power plant by at least 70 % (ICAC, 2009).The SCR installation is the most significant measure taken to reduce the NO x emissions, and it largely coincides with the peak year of observed NO 2 concentrations (Liu et al., 2016b).At the same time, China has implemented several new national emission standards for cars during the time period of our study (see Table 2).The change from China 3 to China 4 standard for cars in the period 2011-2015 reduces the maximum allowed amount of NO x emissions for on-road vehicles by 50 % (Wu et al., 2017).More strict regulations for on-road vehicles (e.g. a ban on older polluting cars) were introduced on a city level, e.g. in Beijing, rather than nationwide.To our knowledge no regulations for ship emissions have been announced.Strong regulations have also been enforced during specific events like the Olympic Games in 2008, the Shanghai World Expo in 2010, the Nanjing Youth Olympic Games in 2014, and the APEC meeting in 2014, but those regulations were mostly of a temporary nature as shown by, for example, Mijling et al. (2013) for the Olympic Games in 2008.
To study the efficiency of the environmental policies, we analysed satellite observations of SO 2 and tropospheric NO 2 of the last 11 years.SO 2 satellite observations over China have been studied earlier by Lee et al. (2011), Li et al. (2011), He (2012), Yang et al. (2013), Fioletov et al. (2015), and Krotkov et al. (2016).Satellite observations are very useful for SO 2 trend studies, as recently McLinden et al. (2016) showed that bottom-up inventories are underestimating SO 2 emissions worldwide by about 0-10 %.NO 2 satellite observations over China have been evaluated by, for example, Richter et al. (2005Richter et al. ( ), van der A et al. (2006)), Zhang et al. (2012), andKrotkov et al. (2016).All these studies showed a strong increase in NO 2 over East China.On a city scale or regional level, trends are analysed and reported by Gu et al. (2013), Schneider et al. (2015), and Duncan et al. (2016).Although some cities have already showed a decreasing trend, notably in the Pearl River Delta, an overall decrease in NO 2 concentrations in China has only recently been observed by Irie et al. (2016), Liu et al. (2016b), andde Foy et al. (2016).To exclude meteorology as a factor for variability in NO 2 , several authors have evaluated NO x emissions instead.Emission estimates of NO x over China have been analysed by Stavrakou et al. (2008), Kurokawa et al. (2009), and more recently by Mijling et al. (2013) and by Liu et al. (2016a).
In these studies, whether of concentrations or emissions, linear trends of the air pollutants are often used.Here, however, we will relate changes derived on a provincial level for China to the energy consumption and the environmental policies of the country.This gives insight into the efficiency of the applied air quality policies and regulations.We apply this to NO x emissions instead of concentrations for the period 2007 until 2015.The comparison of SO 2 trends with those of NO x emissions enables us to distinguish environmental policies specifically applied on coal-based industry and power plants with general environmental measures and trends in traffic.
2 Observational data 2.1 Satellite observations of SO 2 SO 2 is observed in the UV spectral range of satellite observations of SCIAMACHY (on Envisat), GOME-2 (on METOP-A) and OMI (on EOS-AURA).SO 2 retrieval algorithms have been developed earlier for GOME-1 by Eisinger and Burrows (1998), for SCIAMACHY by Lee et al. (2008), and for GOME-2 and OMI by Krotkov et al. (2006).Recently a new retrieval algorithm has been developed (Theys et al., 2015) that improves the precision of the SO 2 data for OMI by a factor of 2, allowing us to derive more accurate trends based on OMI.The retrieval method is based on a differential optical absorption spectroscopy (DOAS) scheme to determine the slant columns from measured spectra in the 312-326 nm spectral range, which are then background-corrected and converted to vertical columns using an air mass factor (AMF).The AMF is calculated with the radiative transfer model LIDORT (LInearized Discrete Ordinate Radiative Transfer model).More details about the retrieval procedure are described in Theys et al. (2015).The operational algorithm of NASA for SO 2 from OMI has also recently been improved.This algorithm and the algorithm of Theys et al. (2015) have a very comparable performance as shown by Fioletov et al. (2016).For this study, the algorithm of Theys et al. (2015) has been applied to the observations of the OMI instrument (Levelt et al., 2006) for its whole mission from 2004 onwards.
To improve the quality of the OMI SO 2 data we exclude observations with a cloud fraction of more than 50 % or with a fitting chi-square higher than 1.The solar zenith angle is limited to 75 • and the viewing angle to 50 • .Since the OMI instrument has been suffering from the so-called row anomaly since 2007 (KNMI, 2012), we filter the affected rows (54)(55) in the same way for all years in the time series.
As we focus on anthropogenic SO 2 , the SO 2 data for 15 June-9 July 2011 have been removed because of contamination with volcanic SO 2 from the eruption of the Nabro volcano in Africa and the transport of its plume to China (Brenot et al., 2014).
As a first step in our study we have made monthly means for the whole data set by averaging and gridding the data to a resolution of 1/8 • by 1/8 • .The gridding algorithm takes into account the area of each satellite footprint overlapping the grid cell.The resulting data set is a time series of monthly means for the time period October 2004 to December 2015.
For comparison we also use the official ESA SCIA-MACHY/Envisat SO 2 version product SGP 5.02; and the standard data from the GOME-2/Metop-A version GDP 4.7, as developed within the EUMETSAT Satellite Application Facility for Atmospheric Composition and UV radiation (O3MSAF) project and distributed by http://atmos.caf.dlr.de/gome2/.The data of these instruments are noisier than the OMI data sets because of the lower spatial coverage, different fit window, and the lower signal-to-noise ratio of the SCIA-MACHY and GOME-2 instruments.Therefore, their qualitycontrolled monthly mean SO 2 data have been recalculated by spatially averaging, for each grid cell, the data from the eight surrounding neighbouring cells, hence creating a smoothed SO 2 field.For details on the methodology and findings, refer to Koukouli et al. (2016).

NO x emission estimates from satellite observations
For NO x emission data we use the results of an update (version 4) of the DECSO (Daily Emission estimates Constrained by Satellite Observation) algorithm developed by Mijling and van der A (2012).DECSO calculates emissions by applying a Kalman filter for the inversion of satellite data and a regional chemical transport model (CTM) for the forward model calculation.It takes transport from the source into account with a semi-Lagrangian approach.The CTM we use is CHIMERE v2013 (Menut et al., 2013) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) with a horizontal resolution of approximately 25 km× 25 km.The DECSO algorithm is applied to OMI NO 2 observations derived by the DOMINO v.2 algorithm (Boersma et al., 2011).The latest improvements of the DECSO algorithm resulting in version 4 are described by Ding et al. (2015Ding et al. ( , 2016a)).The monthly average emission data over China we use are available at 0.25 • resolution for the period 2007-2015 on the web portal www.globemission.eu.The multi-annual mean of SO 2 for 2005-2015 is shown in Fig. 2. As the lifetime of SO 2 is relatively short (typically 4-48 h) (Lee et al., 2011;Fioletov et al., 2015); the observed SO 2 concentrations are a good proxy for the location of SO 2 emissions.Regions with large SO 2 concentrations are south Hebei, the province of Shandong (around the city of Zibo) and the region around Chongqing.South Hebei is a region with many power plants just east of the mountainous coalmining area in Shanxi.The hotspot in the Shandong province is related to a strongly industrialized area with substantial coal-using industry.Both coal mines and heavy industry are located in the Chongqing region.
Rather than located at hotspots, high NO 2 concentrations are more distributed over the east of China, mainly because traffic is an important source of NO x emissions (see Fig. 3a).The underlying NO x emissions are shown in Fig. 3b.Like the SO 2 concentrations, NO x emission spots can be found at the location of large power plants.Also clearly visible are the megacities of China, ship tracks along the coast, and sources along the large rivers.

SO 2 trends over China
To construct time series of SO 2 we have averaged the data to annual means of the vertical columns derived from OMI.From these annual mean SO 2 data we constructed time se-ries for each province (see Table A1).Figure 4 shows the mean normalized time series for the 10 provinces with the highest total SO 2 column densities (i.e.Tianjin, Shandong, Hebei, Shanxi, Henan, Beijing, Jiangsu, Shanghai, Anhui, and Liaoning), together responsible for 60 % of all ambient SO 2 in China.A different trend is observed for Ningxia, a province in the mid-northern region of the country with a relative low population density and large coal resources.Here an increasing trend emerges for the years starting from 2010, when several new coal power plants were put into operation.A list of the largest power plants (with a capacity of more than 600 MW) and the start year of their operation is shown in Table 3. From 2012 onward, the more stringent SO 2 emission regulations also started to have an effect in Ningxia.

NO x emission trends over China
National NO x emission trends show a different pattern than those of SO 2 .We observe an increasing trend until about 2012, with the exception of the year 2009, which is related to regulations started at the Olympic Games in 2008 (Mijling et al., 2009) and the global economic crisis, which briefly slowed down Chinese economic growth.Total NO x emissions in East China reached their peak levels in 2012, and have stopped increasing since this year.While the economy kept growing after 2012, the emission of NO x slowly decreased again as a result of the air quality regulations described in Sect. 1.According to the DECSO emission inversion, in 2015 the NO x emissions were 4.9 Tg N yr −1 , which is 22.8 % lower than in the peak year, 2012.However, the 2015 emissions were still 14.1 % higher than in the reference year, 2007.The trends per province (see Table A2) show very similar patterns, with only the starting year (the year with maximum NO x emissions) of the decrease in emissions varying over the provinces.Events like the Olympic Games in Beijing in 2008 and the World Expo in Shanghai in 2010, when temporary strict air quality regulations were enforced, can be recognized in this table as years with significantly lower emissions for these provinces.In Fig. 5a, the normalized (to the year 2007) time series of annual NO x emissions for East China (102-132 • E, 18-50 • N) is shown in similar way to SO 2 in Fig. 4. The mean, minimum and maximum of the 10 provinces with the highest NO x emission are shown (Shandong, Hebei, Henan, Jiangsu, Guangdong, Shanxi, Zhejiang, Anhui, Sichuan, and Hubei), together responsible for 65 % of all Chinese NO x emissions.The thin grey lines show the times series for the individual 10 provinces, where the lower line represents Guangdong.
Figure 5b shows the peak year for each province.Provinces where air pollution regulations, e.g. for traffic, received a lot of attention at an early stage, like Beijing and Shanghai, reached their maximum before 2011.Most industrialized regions show their peak in the years 2011-2013.Some of the less developed and populated provinces show a maximum in 2014, which means that their decrease in NO x emissions is very recent.Regional variations are mainly due to the fact that regulations for the NO x emission reductions, for instance in traffic or power plants, are determined and implemented on a provincial level (Liu et al., 2016b).For the province of Ningxia we see a pattern occuring that is very similar to that of SO 2 , which shows for this low-populationdensity province that traffic plays a small role and the trend is determined by the operation of newly built power plants.

Air pollution in relation to fossil fuel consumption
To relate the observed SO 2 and NO x reduction to environmental regulations we have to take into account the coal and oil consumption in the same time period.The total coal consumption in standard coal equivalent (SCE) units per year for China and the total oil consumption (also in SCE units) are shown in Fig. 6, based on data of NBSC (2015).According to Guan et al. (2012) and Hong et al. (2016) the sum of coal consumption of all provinces is more accurate than the number provided for the whole of China; thus we use the provincial totals for coal consumption.For NO x emissions the transport sector plays an important role; ships especially are one of the largest NO x emitters per fuel unit in the transport sector.The total freight transport almost doubles every 6 years in China.
Since the burning of coal and oil constitutes the dominant sources of SO 2 and NO x emissions, we can consider the total emissions of these air pollutants as the product of the national use of coal and oil (activity) and the average emission factor of one unit of coal/oil.The effectiveness of environmental regulation will be reflected in a decrease in this emission factor.Therefore, we divide the annual SO 2 column measured from satellites and the annual NO x emissions by the annual coal and oil consumption in China.In this way we get a measure of the emitted SO 2 or NO x per unit (SCE) of fossil fuel consumption reflecting the Chinese environmental policy.The results are shown in Fig. 7.One might argue that SO 2 is more related to coal than oil, but division by only coal yields the same results.In our analysis we omit gas consumption since this is very limited in China and hence does not affect the results significantly.
We focus here mainly on the results for OMI, because of the instrument's high spatial resolution and lack of instrumental degradation.However, SO 2 data of the SCIA-MACHY and GOME-2 instrument are also added in Fig. 7 to be able to further look into the past (starting in 2003) and to verify the results of OMI.The SO 2 data of SCIAMACHY and GOME-2 are averaged over the summer months (April-September).The remaining monthly means are excluded from the analysis due to a lower accuracy at higher latitudes, and a large part of the higher latitudes is missing due to snow cover.For OMI each data point is averaged over 12 months and the total area of China, which reduces the root-meansquare error to a negligible level.Biases among all instruments are removed by normalizing the values to those in reference year 2007.Up to 2009, the results agree fairly well.After 2009, we see the results of GOME-2 and OMI for SO 2 slowly diverge in time, which might be a result of the instrument degradation of the UV spectra of GOME-2 after 2009 (Munro et al., 2016).
Changing weather conditions from year to year can affect the results for SO 2 concentrations, and when the weather conditions are different during the overpass of SCIAMACHY and GOME-2 (around 09:30 LT, local time) than those at the overpass of OMI (around 13:30 LT), this can lead to differences between the instruments.The global coverage of SCIAMACHY is once every 6 days and for GOME-  ter 2009, the SO 2 content per consumed coal unit only slowly decreases until 2011.From 2012 onwards we see a stronger annual decrease in SO 2 .This coincides with the 12th fiveyear programme; when new measures were taken to upgrade the coal quality, to modernize the industry, and to put more effort on law enforcement.The enforcement of laws in the last few years concerning the prohibition of flue gas bypass and the use of desulfurization devices in the steel industry played an especially important role.
For the NO x emissions the total annual emissions are used and divided in the same way as for SO 2 by the total coal and oil consumption.Here, however, we should keep in mind that the transport sector (especially by shipping) emits much more NO x per fuel unit than the power and industrial sectors (see, e.g., Zhao et al., 2013).Thus, the percentage of the total fuel used by transport is relevant for the graph of NO x .In the early years we see, in general, a small increase in NO x  2012) and Boersma et al. (2015) showed that the economic crisis also resulted in a significant reduction in the average vessel speed to save fuel used by ship transport.This not only caused a shift in source sectors but also in general led to lower NO x per fuel values.This explains the dip in pollution per fuel unit in 2009.After 2009 the NO x per fossil fuel is slowly increasing because the transport sector is growing faster than the energy sector and has a higher emission factor.Statistics of the NBSC (2015) show that transport is growing by a factor of 2 every 5-6 years (Wu et al., 2017).After 2012 the gradual increase in NO x per fuel slowly stops, and the year 2015 shows a sharp decline in NO x per fossil fuels unit.This can be directly related to the rapidly growing installation of SCR equipment at power plants since 2012 and to a lesser extent to the introduction of new emission standards for cars, as shown by Liu et al. (2016).This strong reduction in NO x for 2015 and the equally strong reduction for SO 2 in 2014 and 2015 are a result of very effective recent environmental regulations in the last years in China.By comparing the efficiency level in 2015 with earlier levels, we can conclude from Fig. 7 that, without these air quality regulations, SO 2 concentrations would today be about 2.5 times higher.For NO x per fossil fuel we were expecting a gradual growth after 2012 because of the continuing relative growth of the transport sector.Keeping this in mind we compare the years 2015 with 2012 and conclude that without air quality regulations the NO 2 concentrations would be at least 25 % higher in China today.
On a provincial scale we can, in principle, do similar analyses, but unfortunately the provincial energy consumption related to coal and oil has a very high uncertainty due to inconsistencies in interprovincial imports and exports (Hong et al., 2016).We see this reflected in a high variability in the annual provincial data and sometimes missing data.The data have high uncertainties especially for oil consumption (Guan et al., 2012;Hong et al., 2016).Therefore, we have only analysed the five provinces with dominating coal consumption as shown in Fig. 8.In this graph we excluded Guizhou province because of its difficult-to-interpret coal consumption in 2011 as a result of large power shortages (NBSC, 2015;Sun and Zhou, 2011).For SO 2 per fossil fuel unit we see that all provinces follow the national trend.For NO x per fossil fuel we see more variation per province, depending on the role of transport.Most of these coal-consumptiondominated provinces start their decreasing trend from 2011, reflecting the national programme on SCR installations starting that same year.It is interesting to see that the commissioning of new power plants in 2011 causes a strong increase in both SO 2 and NO x in Ningxia province (see Figs. 4  and 5a).However, when compensating for fossil fuel usage, one can see that the same national air quality regulations are applied here, as the trend in Fig. 8 shows the same pattern as for other provinces.This shows the strength of the presented method to assess the efficiency of air pollution regulations.

Discussion
The current developments in data products derived from satellite observations provide high-quality time series of the air pollutants NO x and SO 2 .Although the mean of observed SO 2 columns is not linearly related to the SO 2 emissions be- cause of the influence of the weather, it can still be argued that these satellite data products, whether concentrations or emissions, provide a fair comparison over the various regions from year to year.By comparing these time series with fossil fuel energy consumption we find that the economic growth is removed from the equation and we can monitor the effectiveness of air quality policies.We foresee that this method will become a valuable tool for policy makers concerning air quality regulations.
For China we see patterns in the trends of SO 2 that are similar for all provinces.In 2006 a nationwide implementation of desulfurization installations started.However, the effects are only visible in 2008 and 2009, when a strict control by the Chinese authorities on the actual use of the desulfurization installations started.In 2009, we see the effect of the air quality regulations for SO 2 and NO x resulting from the global economic recession at the end of 2008.The increasing relative contribution of the transport sector to the NO x emission slowly increases the amount of NO x per fossil fuel unit after 2009.After 2011 we see a steadily decreasing SO 2 pollution per fossil fuel unit caused by various Chinese environmental regulations.In the last year of our time series, 2015, a clear effect becomes visible of very recent regulations for NO x emissions from power plants and heavy industry.The fit of linear trends often used in earlier studies is therefore no longer applicable to the Chinese situation.
For the first time it is shown from satellite observations that not only NO 2 concentrations in China but also NO x emissions in all Chinese provinces have been decreasing in the last two years of our study.Showing this decreasing trend for emissions of NO x rules out any meteorological influ- ences that affect concentrations.By the novel method of dividing these NO x emissions by the fossil fuel consumption and thereby showing the decreasing trend in emission factors in China, we also exclude the effect of economic changes, which has always been the driving factor in the trend of emissions in China in the past decades.We have given a complementary new overview of the main national air quality regulations in China from which changes in the emission factors of NO x and SO 2 can be understood and clarified.These trends in emission factors of NO x and SO 2 based on satellite observations might also be applied to verification of existing emission factors.
The availability of high-quality satellite data for the last 10 years is especially interesting for China, where the situation is rapidly changing.For instance, in Europe and Japan, desulfurization started much earlier, when these satellite data were not yet available.On the other hand, in India SO 2 and NO x emissions are still growing and possible new regulations can be monitored in the years to come, with even better quality, using forthcoming sensors such as TROPOMI on board Sentinel-5 Precursor.
Despite the growing use of coal and oil in the last 10 years in China we have recently seen reduced emissions per fuel unit.This decreasing trend in both SO 2 and NO x for China is likely to continue in the coming years for which the Chinese national government has announced less use of coal, more environmental regulations for SO 2 and NO x , and stricter reinforcement of control of environmental policies.

Figure 1 .
Figure 1.Location of power plants in China according to REAS v.2(Kurokawa et al., 2013).The size of each dot indicates the emission of the power plants (power plants in close proximity are combined in a single dot).In addition, a list is given of the provinces mentioned in this study.

Figure 2 .
Figure 2. Average SO 2 concentrations for the period 2005 to 2015 as observed by the OMI satellite instrument.Data below 0.1 DU are masked (grey).

3
Temporal analysis over China 3.1 Sources of SO 2 and NO x in China The individual time series are drawn as thin grey lines.The minimum and maximum of these time series for each year are shown in the grey shaded area to indicate the variability.The time series of Shanghai is the lowest grey line of the 10 series; thus the reductions have been strongest in this province since 2005.Apart from Ningxia province, all provincial time series show very similar patterns.In general, the SO 2 concentrations were at a maximum in the year 2007, when the start of a decreasing trend is visible in China.Despite some fluctuations the SO 2 concentrations remain relatively constant from 2010 until 2013, whereafter they are decrease again.

Figure 3 .
Figure 3. (a) The averaged tropospheric NO 2 concentrations over China measured by OMI in the period 2005-2014.(b) The NO x emissions in the year 2010 derived from OMI satellite observations.

Figure 4 .
Figure 4. Time series (red line) of the annual mean of the 10 provinces with the highest SO 2 concentrations derived from the OMI satellite observations.The time series are normalized to their value in 2005.The grey area indicates the maximum range of the individual values of the times series of each of the 10 provinces.The thin grey lines show the individual time series of those provinces.The province of Ningxia has a distinct deviating trend, here shown in blue.

Figure 5 .
Figure 5. (a) The annual total NO x emission estimates for the last 9 years for the top 10 highest NO x -emitting provinces in East China.Emissions are derived with DECSO V4 using OMI observations.The thin grey lines show the individual time series of those provinces.(b) Peak year of the NO x emissions per province.

Figure 6 .
Figure 6.In black the annual coal consumption.In red the annual oil consumption for China.

Figure 7 .
Figure 7. Time series of the ratio of the mean SO 2 columns and the fossil fuel consumption in China based on observations of OMI (black), SCIAMACHY (green), and GOME-2 (blue).The ratios of the annual NO x emissions and the fossil fuel consumption are based on observations of OMI (red).All time series are normalized to the year 2007.

Figure 8 .
Figure 8. Same graph as Fig. 7 but with time series for the provinces Hebei, Henan, Nei Mongol, Ningxia, and Shanxi included.Time series per province of the ratio of the mean SO 2 columns and the fossil fuel consumption are drawn in blue.The ratios of the annual NO x emissions and the fossil fuel consumption per province are shown in red.All time series are normalized to the year 2007 and based on OMI observations.

Table 1 .
Environmental regulations of the Chinese national government to reduce SO 2 in the air.

Table 2 .
Environmental regulations of the Chinese national government to reduce NO x emissions.

Table A2 .
Annual NO x emissions (Gg N year −1 ) per province in the domain of DECSO (in parentheses the fraction of provincial area considered) derived from OMI observations.