The contribution of soil biogenic NO emissions from a managed hyper-arid ecosystem to the regional NO 2 emissions during growing season

Introduction Conclusions References


Introduction
Atmospheric carbon monoxide, methane, and volatile organic compounds are oxidized by the hydroxyl and other radicals through various catalytic cycles (Crutzen, 1987).In these cycles, nitrogen oxides (NO x =NO+NO 2 ) are key catalysts, and their ambient concentrations determine whether ozone (O 3 ) is generated or destroyed in the troposphere (Chameides et al., 1992).Ozone is usually generated in polluted, industrialized regions, where ambient levels of NO X are high.Moreover, the intensification of agriculture is associated with increased NO emissions, which also causes an increase of available nitrogen in the atmosphere (Denman et al., 2007).NO X in the troposphere originates mostly as NO, which reaches a photo-stationary equilibrium with NO 2 within a few minutes.The current evolution of anthropogenic as well as biogenic NO x sources triggers a potential increase of global tropospheric O 3 concentrations.According to recent estimates (Kasibhatla et al., 1993;Davidson and Kingerlee 1997;Denman et al., 2007;Feig et al., 2008), anthropogenic sources amount to 45-67% of the mid 2000s total global NO X emissions (42-47 Tg a -1 , in terms of mass of N), and other globally important sources are soil biogenic NO emissions (10-40%), biomass burning (13-29%) and lightning (5-16%).The considerable uncertainty about the range of soil biogenic NO emissions stems from widely differing estimates of the NO emissions.Based on field measurements worldwide Davidson and Kingerlee (1997) estimated the global NO soil source strength to be 21 Tg a -1 (with an error margin of 4 to 10 Tg a -1 , 40% of the total), while the 4 th IPCC estimate is 8.9 Tg a -1 (Denman et al., 2007), which is higher than the 3 th IPCC estimate of 5.6 Tg a -1 (IPCC, 2001).
Moreover, the uncertainties in the NO emission data from semi-arid, arid, and hyper-arid regions are very large (mainly due to a very small number of measurements being available).In this context, one should be aware, that approximately 40% of planet Earth's total land surface consists of semi-arid, arid and hyper-arid land and more than 30% of the world's inhabitants live in arid, semiarid and hyper-arid regions (Lai 2001).
In many parts of the world's drylands land-cover is strongly changing due to the encroachment of deserts by bushy vegetation (desert →dryland farming; bushy vegetation→dryland farming).This leads and will lead to dramatic changes in soil microbial production and consumption of NO.
Consequently, it will have a strong impact on the (at least) regional budgets of those reactive trace gasses (NO x , O 3 , volatile organic compounds (VOC), etc.) which are involved in the tropospheric oxidizing capacity.For this reason, it is necessary to quantify the NO emissions from both, natural and agricultural managed soils of the drylands.
Recently, Oswald et al. (2013) pointed out, that (a) the release of odd reactive nitrogen gases from soils due to microbial activity is not confined to NO only, (b) about equal amounts of gaseous nitrous acid (HONO) are simultaneously emitted along with NO, and (c) HONO emissions from soils are one of the most relevant sources in arid areas with regard to tropospheric chemistry.In addition, daytime NO production from HONO photolysis contributes to the total production of NO X emissions.
Therefore, it is meaningful to consider HONO emissions for any estimates of biogenic total reactive nitrogen emissions from soil.
The biogenic emissions of NO (as well as HONO) depend crucially on soil temperature and soil moisture, because these factors affect the availability of organic compounds and the microbial activity in the soil (Conrad, 1996;Meixner and Yang 2006;Ludwig et al., 2001;Oswald et al., 2013).
Sufficient soil moisture, high soil temperatures, and regular supply of nutrients (N-containing fertilizer) are optimum conditions for soil biogenic NO (and HONO) emissions, particularly from arid and hyper-arid land.
An oasis is an agriculturally used area in a desert region.The intensification (economically driven) of oasis agriculture, however, needs enlargement of the arable land area, enhancement of necessary irrigation, and the increase of fertilizer use, which leads inevitably to increasing soil biogenic NO (and HONO) emissions.Microbial processes, which underlay NO production (and NO consumption) in soils (e.g., nitrification, denitrification) are confined to the uppermost soil layers (<0.05 m depth, Rudolph et al., 1996).The most direct method for the characterization of these processes and the quantification of the NO (and HONO) release from soils is usually realized by laboratory incubation of soil samples taken from top soil layers.In those laboratory incubation systems, the net release rate of NO is determined from the NO concentration difference between incoming and outgoing air.The application of this method in the past has proved that the release of NO can be described by specific and unique functions of soil moisture, soil temperature, and ambient NO concentration (Otto, et al., 1996;van Dijk et al., 2002;Meixner and Yang, 2006;Feig et al., 2008;Behrendt et al., 2014;Mamtimin et al., 2015).
Due to the industrialization of Chinese drylands and also to the intensification of their agriculture, not only significant anthropogenic NO X emissions from growing oasis cities are expected, but also the current and future land use will intensify the "hot spot" character of soil biogenic NO emissions from oases.The general aim of the present study is to determine the contributions of soil biogenic NO emissions of a selected oasis in the Taklimakan desert to the regional NO 2 emissions during the growing season.For that, we concentrate (a) on the determination of net potential biogenic NO fluxes derived from laboratory incubation measurements of soil samples, (b) on the bottom-up calculation of regional biogenic NO (and HONO) emissions for the growing season taking into account the corresponding land use, soil temperatures, gravimetric soil moistures, and fertilizer factors, (c) on the bottom-up estimation of regional anthropogenic NO 2 emissions of the oasis based on energy consumption and NO 2 emission factors of different energy sectors and fuel types, (d) on the topdown calculation of regional total NO 2 emissions from satellite observations (OMI) of the vertical NO 2 column densities and pre-scribed values of tropospheric NO 2 lifetime, and (e) on the quantitative comparison of regional total NO 2 emissions obtained by both (bottom-up (biogenic + anthropogenic) and total top-down) approaches.

Site description and soil sampling
The study area "Tohsun oasis" (Fig. 1) is a hyper-arid region located in the Xinjiang Uyghur Autonomous Region of P.R.China (Mamtimin et al., 2005).The Tohsun oasis belongs administratively to Turpan County with Turpan City as capital (50 km NE from Tohsun oasis).The Tohsun oasis has an extension of 1479 km 2 , a population of 138 thousand, and topographically constitutes the deepest point of P.R.China (154 m below sea-level; Pu, 2011).Major landform types of the Tohsun oasis are sandy-desert and Gobi-desert (stone desert), surrounded on three sides by the mountains of Bogda (north), Qoeltagh (south), and Alagou (west).Topographically, the Tohsun oasis slopes down from northwest to southeast.According to the Koeppen classification (Kottek et al., 2006), the climate of Tohsun oasis is classified as "cold desert"; i.e. hot summers (July: 33°C), cold winters (January: 6°C), and very low precipitation.Mean annual potential evaporation is about 3400 mm (see Fig. 2), while the mean annual precipitation is as low as 7 mm.
The mean monthly precipitation for Tohsun (not shown in Fig. 2) is extremely low: rainfall in June and July is about 2 mm, in January, August, and September 1 mm, respectively; and there is no rain for the rest of the year.Agriculture played and plays a significant role in Tohsun oasis; it was one of the most flourishing oases on the ancient Silk Road (Weggel, 1985).Due to the substantial lack of rainfall, regular dry-land farming is impossible without massive irrigation.Water supplies for irrigated agriculture are dependent on groundwater (pumping-wells), and on the Bai Yanggou River which originates from the Bogda Mountains.The Bai Yanggou River is temporarily, defined by the strong seasonal pattern of snow-melt and rain in the mountains (Mamtimin, 2005).
Tohsun oasis' agriculture is dominated by intensive mono-cultivation of grapes and cotton.Grapes from the Turpan county are naturally dried to raisins which are sold on the Chinese internal market and also exported to some Asian countries (Jin, 2011;Pu, 2011).Grapes from Turpan County account for 52 % of grape production in the Xinjiang Uyghur Autonomous Region, and for 20 % of entire China.There, more than 100 small and medium size companies are engaged in raisin processing (Wan, 2012).In 2008, Turpan's raisin production was 130.000 tons which accounted for more than 90 % of all raisins produced in P.R.China (Wan, 2012;Li, et al., 2012;Jin, 2011;Pu, 2009).Approximately 40% of Turpan's grape production is from the Tohsun oasis (Pu, 2009).To raise the yields of grapes and cotton, the corresponding cultivation techniques have been optimized, which resulted in the extensive application of nitrogen containing fertilizers.
Soil samples from the study area were collected in 2010 from a total of three sites of Tohsun's cotton fields, and from a total of two sites of grape fields (for sample locations, see Fig. 1).Since the primary production and consumption zones for NO are located within a very shallow layer at the soil surface (1 to 5 cm, e.g.Meixner and Yang, 2006), only soil samples 5 cm top soil were taken.At each of the sampling sites ten soil samples (approx.150 g) with stainless steel soil cores (5 cm length, 2.5 cm radius) were taken (randomly from a 10x10m 2 area); these were then combined to constitute a representative soil sample of approximately 1.5 kg in mass.These soil samples were stored at 4°C for a maximum 3 months until analysis, since the microbial alterations are not expected within storage for up to 3 months at 4° C (Stotzky et al., 1962).In this study, we also used soil samples from the (non-fertilized) desert ecosystem as reference, where the desert soil data was adapted from the study of Mamtimin et al. (2015).

Remote sensing and accompanying data
Remote sensing data from both Landsat and Aura satellites (measurements by the Ozone Monitoring Instrument, OMI) were used in combination with a Geographical Information System (GIS).Landsat images, provided by United States Geological Survey, are widely applicable for purposes like our study because of their rather high spatial resolution (30-15 m).Since the aim of our study is the quantification of biogenic NO emissions from intensively managed arid soils, the consideration of the growth state of the corresponding agro-ecosystems is important.For the representation of the different seasons we selected four individual months: April (spring) for the beginning, July and, August (summer) for the middle, and September (autumn) for the end of the vegetation period.The winter season was not considered as most of the agro-ecosystems are frozen, hence any microbial activities are negligible.As proposed by many authors (Schott et al., 1985;Markham et al., 1986;Irish, 2003;Chander et al., 2003) we derived areal distributions of land surface temperature (LST), and land cover types from corresponding satellite data using remote sensing digital image processing.
For the selection of Landsat images we confined ourselves to the year 2010 when we have taken the soil samples.Six individual Landsat images of the Tohsun oasis (25 April, 28 July, 13 and 21 August, 06 and 22 September 2010) were used.
Tropospheric NO 2 column densities derived from the OMI satellite instrument (DOMINO version 2.0, Boersma et al., 2011) for the year of 2010 were used for top-down estimates of total NO 2 emissions and comparison with total bottom-up emission estimates (biogenic + anthropogenic).The long-term seasonal variability of the tropospheric NO 2 was derived from the data of 2006-2010.For the estimation of anthropogenic sources of NO X , we used fossil fuel consumption data from different economic sectors (manufacturing, electricity, transportation and domestic) which were obtained from the Xinjiang Statistical Yearbooks (Jin et al., 2009;Jin et al., 2011) and the Turpan Statistical Yearbooks (Pu, 2011).The emission-reduction coefficient for coal-fired thermal power industry was taken from "China Electric Power Yearbook" (Zhou, 2006).The land use map of Xinjiang (1:10.000.000;Ma, 2010) and the Traffic Map of Tohsun (1: 1.050.000;Ma, 2010) were involved in this study as additional tools for land use classification.
The meteorological data set  of the Tohsun County Meteorological Station (42.7833°N, 88.6500°E; +1 m a.s.l.) was supplied by the Xinjiang Meteorological Bureau.It contains monthly mean  data of air temperature, precipitation, evaporation, wind speed and direction.
Unfortunately, soil moisture content and soil temperature have not been measured routinely at Tohsun County Meteorological Station.In-situ measurements have been performed with a suitable sensor (MSR® 165 data logger; Rotronic, Switzerland) which has been buried at the site of Tohsun County Meteorological Station at 2.5 cm depth between July and September 2010.While soil temperature data was measured directly, data of gravimetric soil water content were obtained by gravimetric calibration of the sensor's signal (relative humidity of soil air).

Bottom-up calculation of biogenic NO emission estimates
Estimates of seasonal (monthly) bottom-up biogenic NO emissions for Tohsun oasis need (a) laboratory derived, land use type specific net potential NO fluxes (sect.2.3.1),(b) the areal distribution of the three land use types (cotton, grapes, and desert) of Tohsun oasis (sect.2.3.2), and (c) land use type specific and temporally high resolution data (sect.2.3.3) of soil temperature, gravimetric soil moisture content, and fertilizer (enhancement) factors.

Laboratory determination of land use type specific net potential NO fluxes
During the last two decades, the laboratory incubation method has been used to measure the net NO release from soil (Yang and Meixner, 1997;Otter et al., 1999;Kirkman et al., 2001;Feig et al., 2008;Yu et al., 2008;Ashuri, 2009;Gelfand et al., 2009;Bargsten et al., 2010;Behrendt et al., 2014;and Mamtimin et al., 2015).However, today's knowledge of soil biogenic NO emission rates from managed arid soils is still rather limited (c.f.Behrendt et al., 2014;Mamtimin et al., 2015;Delon et al., 2015).The laboratory incubation method is usually dynamic chamber system which are consists gas dilution, thermostat valve, thermostat cabinet, and analysers (Behrendt et al., 2014).The dynamic chamber was made of Plexiglas with a diameter and height of 9.2 cm and 13.6 cm (Behrendt et al., 2014), respectively.Five chambers were used for soil samples while one was kept empty as a reference and the thickness of the sample in the dynamic chamber kept the same (approx.5 cm).The wetted soil samples were placed into five chambers while one was kept empty as reference chamber.
Then, the net potential NO release rates were measured until the soil was completely dried out.
Laboratory measured NO fluxes by using the incubation method have been repeatedly shown to be in good agreement with those measured in the field (Mayer et al., 2011;van Dijk et al., 2002, Ludwig et al., 2001).The net release of NO from soil is the result of microbial production and consumption processes which occur simultaneously (Conrad, 1996).In our study, we investigated net NO releases (J NO; in terms of mass of nitric oxide per mass of dry soil and time), as well as potential NO fluxes (F NO ; in terms of mass of nitric oxide per area and time) of cotton, grapes and desert soils.The methodology for the laboratory soil measurements which is used in the frame of this study, is described in detail in Behrendt et al. (2014) and Mamtimin et al. (2015).By application of the laboratory dynamic chamber method, the net potential NO flux F NO (ng m -2 s -1 , in terms of mass of NO) is defined by    where J NO (in ng kg -1 s -1 ) is derived from the laboratory measurements, as well as the dimensionless gravimetric soil moisture g  .The soil temperature T soil (in °C), the total mass of the dry soil sample soil m (in kg), and the cross section of the dynamic chamber A (in m 2 ) were directly measured.
Soil moisture and soil temperature had been identified as the most dominant influencing factors of the net NO release; therefore, J NO is usually parameterized by these two quantities (Yang and Meixner, 1997;Otter et al., 1999;Kirkman et al., 2001;van Dijk et al., 2002;Meixner and Yang, 2006;Yu et al., 2008Yu et al., , 2010;;Feig et al., 2008;Ashuri, 2009;Gelfand et al., 2009 andBargsten et al., 2010).While the dependence of J NO on T soil is exponential, the dependence of J NO on g  has the form of an optimum curve.These dependencies are described by two explicit dimensionless functions, the so-called optimum soil moisture curve g(θ g ) and the exponential soil temperature curve h(T soil ) which are described in detail by Behrendt et al. (2014).Introducing 0 , g  , the so-called optimum gravimetric soil moisture content (i.e., where the maximum NO release has been observed), and T soil,0 = 25°C as the reference soil temperature, the net potential NO flux, specific for the soils of each land use type i (i: grape fields, cotton fields, desert) is given by The land use type specific exponential soil temperature curve   Land use type specific shape factors "a" of the corresponding optimum soil moisture curves were derived from laboratory drying-out incubation studies on the corresponding soil samples according to Behrendt et al. (2014).The land use type specific quantity Q 10,NO is the (logarithmic) slope of h(T soil ), which was also derived from the laboratory measurements; applying two different soil temperatures, T soil,0 and T soil,1 (T soil,1  T soil,0 = 10 K), the land use type specific Q 10,NO is defined by

Landsat Imagery
We used Landsat images since Landsat provides land surface information in a fine scale matrix (30x30 m²).The Landsat TM/ETM+ sensors acquire land surface information and store it as a digital number (DN) which ranges between 0 and 255.Landsat images are widely applied for the estimation of biospheric applications, such as the Normalized Differenced Vegetation Index (NDVI), Land Surface Temperature (LST), Soil Moisture Index (SMI), and fluxes of matter between different ecosystems, etc. (Goward and Williams, 1997;Liang et al., 2002;Lu et al., 2002).To perform land use classification and to derive the corresponding land use specific surface soil temperature, we have developed a tool by using ARCGIS 10.x, namely the so-called "Geoscience General Tool Package" (GGTP, see supplement, sections S1.1 -S1.7).Within GGTP model, we also calculated the 2D distributions of soil biogenic NO emissions (s.section S1.9).

Land use classification
To classify these field-specific vegetation types, pre-processing the Landsat imagery and image interpretation has to be performed.To effectively record the image data, histogram equalization and edge detector techniques (Jensen, 2005) were applied to image pre-processing.By using suitable edge detecting functions, Landsat images were enhanced and boundaries between different classes were strongly highlighted for effective subsequent image interpretation.Due to the significant requirements for the different areas of interests (AOIs) of image classification, in-situ GPS data (160 points) from the field campaigns (2010) and also from previous field investigations (2006,2008) were used.Spectral signatures of in-situ data were collected by digitizing, and were consequently used to classify all pixels.For that, image spectral analysis and the mostly used supervised classification method of maximum likelihood by Jensen (2005) was performed.This procedure ensured that (a) spectral characteristics of all AOIs were used, and (b) every pixel (both, within and outside AOIs), was assessed and associated to that land-cover of which it has the highest likelihood of being a member.

Land surface temperature T s
Knowledge of the land surface emissivity (ε) is highly indispensable to retrieve the land surface temperature (T s ) from remotely sensed data.As the land cover varies greatly from place to place, land surface emissivity widely varies from one location to another.Therefore the land surface temperature T s is defined as: The land surface emissivity (ε) can be obtained from red and near-infrared (NIR) spectral reflectance, while at-sensor brightness temperature ( B T ) can be calculated from the satellite image's thermal band of high gain mode (band 6.2); more details are given in the supplement (section S1.2 -S1.6).

Temporally high resolution data
Bottom-up calculations of this study aim for regional, seasonal (monthly), and land use specific soil biogenic NO emissions via laboratory derived net potential NO fluxes which depend on soil temperature, gravimetric soil moisture (sect.2.3.1), and fertilizer factors (i.e., amplification of NO fluxes due to the application of fertilizer).But the necessary time scale for this data must be much shorter than seasonal (monthly): (a) there is a strong non-linear response of the net potential NO flux to soil temperature and gravimetric soil moisture (eqs.( 3), ( 4)), as well as to fertilizer applications, and (b) there are large diel variations of the top soil temperature (e.g.10-60 °C in July; Tohsun oasis desert soil), and large diel to weekly variations of soil moisture and soil nutrient content caused by the applied irrigation and fertilization schedules.Consequently, seasonal (monthly), land use type specific soil NO emissions have to be averaged from data calculated on much shorter time scales (< 1 h).

Soil temperature, T soil
Due to the very low soil temperature before and after the growing season (s.Fig. 1b), most of the soil surface is expected to be frozen and biogenic emissions from any soils of the Tohsun oasis can be neglected.Thus, mean monthly soil NO emissions were only calculated for the period April to September.In-situ measurements of soil temperature (and soil moisture; 2.5 cm depth; 5 min resolution) at the Tohsun oasis have been performed only for the land use type "desert", and only for the period 01 July to 30 September, 2010 (see sect.2.2).However, soil temperature (and soil moisture; 2.5 cm depth; 5 min resolution) have also been measured at two other Taklimakan oases during the same period, namely at Kuche (41.5360°N, 82.8546°E; "cotton soils") and Minfeng (37.0534°N; 82.0760°E; "jujube soils").For this study, data from Kuche were adapted for the land use type "cotton soils" of Tohsun oasis, while data from Minfeng were chosen to substitute "grape soils" data of Tohsun oasis.The latter is justified by the fact, that both, grapes and jujube belong to the bushy agri- cultural landscape type, they have similar height, distance in rows, water requirements, and percent ground cover by their canopy.For each of the three land use type data sets, each original measured data point (5 min, July-September, 2010) of a particular day has been normalized by the mean value observed at 10:45 LT (Landsat satellite overflight, supplement Fig. S7).Then, a mean diel variation data set (30 min) has been created by averaging all respective data between 1 July-30 September constituting the representative diel variation of the (normalized) soil temperature of the respective land use type valid for the entire growing period (supplement, S3.1; Fig. S8).As described in the section S3.1 of the supplement, land use type specific surface temperatures (T S ; sect.2.3.2),derived from Landsat observations on 25 April, 28 July, 13 and 21 August, 06 and 22 September 2010 (sect. 2.2), have been temporally up-scaled for the entire growing season (01 April -30 September, 2010).
Finally, the diel variation of soil temperatures of the land use types "desert", "cotton soils", and "grape soils" for every day of the growing season 2010 was obtained by multiplying the normalized soil temperatures.

Gravimetric soil moisture  g
Evaluation of the MSR ® 165 data logger measurements (see sect.2.2) at the site of Tohsun County Meteorological station (bare desert soil) has demonstrated a temporally quite constant, very low gravimetric soil moisture content of 0.0028, which has been adapted for the entire growing season (AprilSeptember 2010) land use type "desert" of Tohsun oasis.Temporal variation of gravimetric soil moisture content of the two other land use types, "cotton soils" and "grape soils" depend strongly on irrigation amounts and schedules.Unfortunately, there is no official information on Tohsun oasis' irrigation available, neither on amounts and schedules and consequently none on the gravimetric soil moisture contents during the drying-out phases between individual irrigation events.Therefore, like for data assimilation of soil temperatures (see above), gravimetric soil moisture content data observed at Taklimakan's oases Minfeng ("cotton soils") and Kuche ("jujube soils") have been adapted for Tohsun oasis' land use types "grape soils" and "cotton soils", respectively.That consists in temporally constant irrigation schedules, starting at 1 April 2010 and repeated every 2 weeks.From the observations at Minfeng and Kuche so-called "drying-out" shape functions could be defined, which were scaled by multiples of the soil specific physical quantity "field capacity (FC)", the amount of water content held in the soil after excess (irrigation) water has drained away.The quantity FC is typically used in irrigation scheduling, calculation of plant available water, as well as water depth to be applied by irrigation (Diallo and Mariko, 2013).FC-data of soil samples from Minfeng and Kuche oases have been determined by laboratory measurements (see sect.S1.8, supplement).
Finally, for Tohsun oasis' land use types "cotton soils" and "grape soils" the following gravimetric soil moisture contents have been chosen (for details, see sect.S3.2, supplement): (a) 0.086 ("grape soils") and 0.167 ("cotton soils") before the first irrigation event (corresponding to mean gravimetric soil moisture contents at conditions of 0.25FC and 0.5FC, respectively), and (b) 0.514 ("grape soils") and 0.586 ("cotton soils") after each irrigation (corresponding to mean gravimetric soil moisture contents at conditions of 1.5FC and 1.75FC, respectively).Since for each irrigation event (every 14 days) the starting and end conditions in terms of gravimetric soil moisture content were known, as well as the functional relationship for the temporal drying-out of "cotton soils" and "grape soils" between the irrigation events, temporally high resolution data (30 min) could be calculated.
The result, the seasonal variation (01 April 2010 (DOY 90)  30 September 2010 (DOY 273)) of the gravimetric soil moisture content (at 30 min resolution) for the land use types "cotton fields" and "grape fields" of Tohsun oasis is illustrated in Fig. S9 (supplement).

Fertilizer factor FF
To maintain the productivity of the grape and cotton fields of Tohsun oasis, the soils regularly receive considerable N-containing fertilizer amounts (see sect.2.1).The impact of the fertilizer application on the NO-fluxes from arable soils of Taklimakan oases was recently investigated by Fechner (2014) using the laboratory dynamic chamber system described by Behrendt et al. (2014).
Dependent on the applied fertilizer amount (FA), NO-fluxes from all soil samples increased considerably and immediately after fertilizer application, which was accomplished by dissolving the mineral fertilizer in that amount of water which was used to wet the soil samples (just to mirror the fertilization procedures of the Taklimakan oases).The impact of fertilization is twofold, (a) it strongly amplifies the net release (net potential flux) of NO over the entire range of gravimetric soil moisture, and (b) there is an moderate amplification of the net NO release (net NO potential flux) with soil temperature.Furthermore, the impact of fertilization has also a temporal dimension: it has been shown, that the fertilizer effect on the emission of N-containing gases is temporally declining after each fertilization event (Chen et al., 2011).Therefore, the fertilizer effect may be considered (a) by the multiplicative, FA-dependent, time dependent, dimensionless "fertilizer factor (FF)" applied to the standard net release J NO ( g,0 ,T soil,0 ) in Eq. ( 2), and (b) by the FA-dependent, time dependent, dimensionless "Q 10 factor (Q 10 F)", also multiplicatively applied to Q 10 (the logarithmic slope of the exponential soil temperature curve h(T soil )).According to Fechner (2014), initial fertilizer effects are FF = 142,179,205,226,and Q 10 F = 1.21,1.24,1.25,1.26for fertilization amounts FA= 100, 200, 300, and 400 kg (N) ha 1 , respectively.From recommendations of Tohsun oasis' local agricultural administration (personal information, 2010) and our personal communication with farmers there (2010), data for applied fertilizer amounts as well as for fertilizing schedules could be inferred.With the assumption of an exponential decay of the fertilizer effects, corresponding functional relationships for the temporal behaviour of FF and Q 10 F have been developed (see sect.S3.3, supplement) and temporally high resolution data (30 min) of FF and Q 10 F were calculated.The result, the seasonal variation (01 April 2010 (DOY 90)  30 September 2010 (DOY 273)) of the (dimensionless) factors FF and Q 10 F for the land use types "cotton fields" and "grape fields" of Tohsun oasis is illustrated in Fig. S10 (supplement).

Monthly soil biogenic bottom-up emissions of Tohsun oasis
Estimates of soil biogenic NO fluxes can be calculated from net potential NO fluxes (see sec.2.3.1)according to eqs. ( 1)-( 4), since those NO fluxes which are derived from laboratory incubations have been repeatedly shown to be in good agreement with those measured in the field (Mayer et al., 2011;van Dijk et al., 2002, Ludwig et al., 2001).Consequently, soil biogenic NO fluxes for Tohsun oasis were calculated every 30 min from land use specific net potential NO fluxes (see sec.The studies by Su et al. (2011) and Oswald et al. (2013) pointed out that the HONO and NO emissions have to feature similar dependencies on soil properties, and there exist a co-emission of HONO with NO from the soil; so it could be expected that the HONO and NO emission processes follow similar parameters (Naegele and Conrad, 1990;Skopp et al., 1990, Gödde andConrad, 2000;Oswalt et al., 2013).
The recent findings of Oswald et al. (2013), namely that a large amount of gaseous nitrous acid (HONO) is concurrently emitted along with NO, have been considered for the monthly estimation of biogenic emissions of the Tohsun oasis.They have investigated a total of 17 soil samples which have been taken from a variety of natural and agriculturally managed soils around the globe.Fortunately, five of these samples (no.S13S17 in Oswald et al., 2013) were cotton, jujube, and desert soils of the Taklimakan region, they have the same arid climate condition and irrigation regime as well as fertilizer application to those used for this study.The strong dependency of HONO emissions on soil water content and soil properties were determined by laboratory experiments with dynamic chamber systems (Oswald et al., 2013).Since the HONO emissions were not directly measured within the present study, the land use specific constant scale factor namely the ratios of HONO to NO releases for the optimum conditions to estimate the HONO emissions ((F N , opt (HONO) to F N , opt (NO)) were adapted from the study of Oswald et al. (2013).This is justified by: (a) the strong assumption that the soil from our study emits the same magnitude of HONO as the soil by Oswald et al. (2013)  In the present study, the total bottom-up biogenic emission estimates (NO and HONO) were expressed as NO 2 -partly because the reported mass of emitted nitrogen compounds becomes independent from the partitioning ratio between NO and NO 2 .Additionally, the anthropogenic and top-down emissions estimates are primarily derived for NO 2 .In this study, the mean primary NO 2 emissions were not considered and all NOx emissions are being reported as mass of NO 2 .For that purpose soil biogenic emissions of NO and HONO (given as mass) were multiplied by the respective ratios of the corresponding molecular weights (M NO2 /M NO , M NO2 /M HONO ).
For the comparison of biogenic bottom-up emissions (F biogenic ) with top-down emissions (F satellite ) only the data around the time of the satellite overpass around13:00LT was considered (bottom-up results for 12:45LT (12:30-13:00) and "13:15 LT(13:00-13:30)).To estimate the effect of the diurnal cycle of the emissions we calculated the ratio of the bottom-up emission at the satellite overpass (at 13:00 LT) and the daily average emissions.

Bottom-up anthropogenic NO 2 emission estimates
Tohsun oasis's anthropogenic NO 2 emissions predominantly originate from fossil fuel combustion of the energy and traffic sectors.To quantify the amount of an emitted substance from a source like fossil fuel consumption, specific emission factors have to be applied, which are expressed as the fraction of the substance emitted from the mass or volume of the fuel.In P.R. China, emission factors for different economic sectors and fuel types are available, but quite variable during the last decade.
Based on sparsely available statistical data, the fuel types consumed in Tohsun are ranking from coal to coke, crude oil, natural gas, diesel, and gasoline.For the calculation of bottom-up anthropogenic NO X emissions we used those NO X emission factors (in terms of NO 2 ) which are widely used in P.R. S1; supplement).According to Hao et al. (2002), Zhang et al. (2009), andShi et al. (2014) an algorithm (see eq. (S13), supplement) has been applied to calculate the emitted mass (E N ; in kg NO 2 ) from emission factors K N (in kg t -1 ), dimensionless removal efficiencies P N of corresponding emission reduction technology, and the particular fuel consumption F (in t).

China (see Table
Unfortunately, data of fossil fuel consumption from the different economic sectors of Tohsun County (see sect.2.2) are only available on an annual basis.Mean monthly data of Tohsun oasis have been assimilated (down-scaled) by multiplicative consideration of known mean monthly percentages of annual NO 2 emissions of Urumqi (140 km NNW of Tohsun).This is justified by: (a) coal is the dominating fuel type of energy consumption in both areas (Mamtimin and Meixner, 2011;Pu, 2011), (b) identical arid climate conditions (resulting in identical heating periods), and (c) only from Urumqi there are known mean monthly percentages of annual NO 2 emissions.More details are given in sect.

Top-down total NO 2 emission estimates from satellite observations
Satellite retrieved tropospheric vertical column densities of NO 2 (VCD NO2 ) over the Tohsun oasis provide a daily measure for the atmospheric NO 2 concentration vertically integrated over the entire troposphere (during the time of overflight, around 13:00 LT).Only a few assumptions are necessary to derive related NO 2 fluxes (representing total NO 2 emissions) from this data: (1) the NO 2 molecules of the tropospheric vertical column originate exclusively from NO 2 emissions (anthropogenic + biogenic) from the area of the Tohsun oasis, (2) due to the surface source, the abundance of NO 2 molecules of the tropospheric vertical column is within its lowermost part, the Atmospheric Boundary Layer, (3) the depletion of NO 2 in the Atmospheric Boundary Layer is primarily due to the reaction of NO 2 with the hydroxyl radical OH (leading to the formation of gaseous nitric acid, HNO 3 ), and (4) the characteristic time (lifetime) of the depletion is approximately known.

Satellite-derived tropospheric VCD NO2
OMI satellite data of tropospheric NO 2 were chosen because of their smaller pixel size (13 x 24 km² in nadir) compared to data from SCIAMACHY (60x30 km²), or GOME (320 x 40 km²).OMI is operated in a sun-synchronous orbit such that measurements are taken at about 13:00 local time.OMI data also provides daily global coverage (Boersma, et al, 2007).For our study we used the OMI monthly mean tropospheric NO 2 data, which is calculated on the basis of the results of daily OMI overflights (around noon), and is provided by TEMIS (Tropospheric Emission Monitoring Internet Service, European Space Agency (ESA); http://www.temis.nl/).The OMI monthly mean tropospheric NO 2 data product was averaged on a 0.125° x 0.125° grid, and has been retrieved for cloud fractions < 20%.
It should be noted that the tropospheric VCDs derived from satellite measurements can be systematically affected by the a-priori assumptions needed for the calculation of the air mass factor AMF (reflecting the satellite sensitivity for tropospheric NO 2 ), such as cloud fraction, pressure at cloud level, surface albedo, and trace gas profile (Boersma et al., 2007(Boersma et al., , 2011)).Fortunately, the region of Tohsun County provides relatively favorable conditions for accurate calculation of tropospheric AMFs, since the desert region is typically only little affected by clouds and aerosols; also lightning activity, due to the predominant absence of convective rains, is rather weak, if not negligible.The AMF for OMI DOMINO v2.0 has been calculated using TM4 model NO 2 profiles with a longitudelatitude resolution of 3° x 2°, a surface reflectance climatology (0.5° x 0.5°), and cloud information (Boersma et al., 2011).To test whether the assumed surface albedo is appropriate for the Tohsun oasis, we examined the OMI surface reflectance climatology for the study area, and compared it with the high resolution MODIS surface reflectance product (0.05° x 0.05°, MOD43B).We used the MODIS albedo products from channel 3 (at 459-479 nm) because this channel is close to the spectral window (405-465 nm) used for the OMI retrieval.According to Kleipool et al. (2008) the surface albedo difference between 470 nm (center of MODIS channel) and 440 nm (OMI surface reflectance climatology) is very small for land surfaces.
To account for any background NO 2 from upwind (desert) areas, representative VCD NO2 observed over the Taklimakan desert (400 km away from the oasis, at 85.5129°E, 40.0669°N) were subtracted from the VCD NO2 observed over the Tohsun area.
To check the representativeness of satellite-derived NO 2 on the regional scale, we investigated the inter-annual variability of tropospheric VCD NO2 from 2006 to 2010.That is because a mean value of longer periods leads to significantly reduced uncertainties and it can be better demonstrate the representativeness of satellite-derived NO 2 .Evidence of clear seasonal pattern in the long-term observations can reflect the true seasonal effect on tropospheric VCD NO2 , which is of substantial importance with respect on the intended comparison "bottom-up" versus "top-down".Seasonal patterns (i.e.DecemberFebruary, MarchMay, JuneAugust, SeptemberNovember) of satellitederived NO 2 column densities were evaluated using long-term cloud-free (cloud fraction <20%) measurements from 2006 to 2010.
Satellite observations reflect contributions from different emission sources.In principle the retrieval of NO 2 emissions over a city or oases is similar.However, usually the emissions from cities are higher and the corresponding enhancements can be better identified compared to the background.In order to establish the relationship between biogenic NO 2 and satellite-derived NO 2 , it is necessary to understand their spatial patterns with respect to the locations and shapes of the potential sources.
Thus, four different areas (see Fig. 3) were selected to represent (1) typical agricultural areas (study area) as biogenic source, (2) mixed land use areas (agricultural & small urban) as biogenic and anthropogenic sources, (3) large urban areas as anthropogenic source, and (4) desert area as background source.

Monthly total NO 2 emissions of Tohsun oasis (top-down)
For the top-down inventory, the given molecular weight of NO 2 , Avogadro's number, a lifetime of NO 2 and pixel area (m 2 ) of NO 2 were considered.Top-down NO 2 emissions from Tohsun oasis (ng m -2 s -1 , in terms of NO 2 ) were calculated from all VCD NO2  whose pixels cover the area of Tohsun oasis and where each represents the particular monthly mean of 2010  as follows: (a) from each individual VCD NO2 (in NO 2 molecules cm -2 ) the representative "desert"-VCD NO2 -value was subtracted to account for any background NO 2 from upwind (desert) areas, (b) all these VCD NO2 were multiplied by their respective pixel area and summed up to obtain the mean number of (vertically integrated) NO 2 molecules for each month of 2010 over Tohsun oasis (for the area indicated in Fig. 3), (c) this value was converted to mass of NO 2 per unit area (m 2 ) and divided by the characteristic lifetime of NO 2 ,  NO2 (with respect to its reaction with the hydroxyl radical OH).The corresponding result represents the mean monthly total NO 2 emission (i.e. from anthropogenic and biogenic sources) from the area of the Tohsun oasis at the time of OMI satellite overflight (and a few hours before).Here it should be noted that meteorological information has not explicitly to be taken into account, because from the satellite observations (Fig. 9) we can conclude that most NO x (about more than 90%) is already destroyed before it is blown by winds outside the considered area.The characteristic lifetime of NO 2 can be indicated as short lifetime.It has been e.g.investigated by Beirle et al. (2011) and can be estimated to about  NO2 = 4 h for low and mid-latitudes, particularly for the dryland cities of Isfahan (32.6°N) and Riyadh (24.6°N).

Laboratory derived net potential NO fluxes
Results of the laboratory derived net potential NO fluxes (F NO ) from soils of the desert and the irrigated and fertilized cotton and grape fields of are shown in Fig. 4. The highest mean net potential NO flux at 25°C occurred from the cotton soils, with a maximum net potential NO flux of 125 ng m -2 s -1 , followed by grape soils (41 ng m -2 s -1 ), and desert soils (9 ng m -2 s -1 ), respectively.Common to all net potential NO fluxes from the major land use types of the Tohsun oasis is the exponential response to soil temperature (due to strong enzymatic activities associated with microbial processes of soil NO production).During the growing period (April  September), soil temperatures of > 45°C are easily reached for the soils of the Tohsun oasis, particularly for the desert soils (see supplement, Fig. S1).
At T soil = 50°C, maximum net potential NO fluxes of 834 (cotton soils), 249 (grape soils), and 99 ng m -2 s -1 (desert soils) are reached at an optimum gravimetric soil moisture content (θ g,opt ) of 0.021, 0.146, and 0.0158, respectively.These θ g,opt -values, particularly those of the cotton and desert soils, are much lower than those of natural and agriculturally used soils of temperate latitudes (> 0.25, c.f. Oswald et al., 2013;Behrendt et al., 2014).
Emphasizing, significant net potential NO fluxes from desert soil only occurs if θ g is higher than 0.01 and less than 0.03.Since the observed θ g -value of the Tohsun desert soils is 0.0028 (see sect.2.3.3),no significant biogenic NO emissions are expected from there.As stated in sect.2.3.3, the chosen irrigation schedules of cotton and grape fields resulted in certain, pre-defined ranges of gravimetric soil moisture contents (depending on the field capacity (FC) of the respective soils).Immediately after each irrigation event θ g -values of 0.514 (grape soils) and 0.586 (cotton soils) occur; according Fig. 4, there will be no significant biogenic NO emissions at this stage.However, after 14 days (just before the next irrigation event), θ g -values as low as 0.086 (grape soils) and 0.167 (cotton soils) are found; consequently, regarding the results in Fig. 4, maximum biogenic NO emissions from grape soils have to be expected for the end of the 14 day irrigation period (θ g,opt = 0.146), while at that time biogenic NO emissions from cotton soils will be (even at T soil = 50°C) less than 10 ng m -2 s -1 , since then the θ g value for cotton soils (0.167) is far above the corresponding optimum value (θ g,opt = 0.021).This means, that despite the overwhelming potential of cotton soils to dominate the biogenic NO emissions of the Tohsun oasis (see Fig. 4), their net actual contribution is almost negligible over the full 14 days irrigation cycles (see below).It should be noted that for other oases (with other irrigation cycles) the contribution cotton soils might be much larger.

Land use type specific net NO fluxes based on soil temperature, soil moisture content, and enhancement by fertilizer application
The land-cover classification of the Tohsun oasis has been also derived from Landsat images.Based on these results, the dominant land cover types were cotton and grapes, building/residential area, other vegetation, and desert (see Fig. 5).The seasonal variation of the diel variation of the biogenic net NO flux from soils of the land use types "grape soils" and "cotton soils" are shown in Fig. 7. Results of the biogenic net NO fluxes from desert soils are not shown.Despite very high values of the soil temperature, the net NO fluxes from Tohsun oasis' desert soils are (<< 1 ng m -2 s -1 ) due to the extremely low gravimetric soil water content assumed for the Tohsun's desert soils (θ g,desert = 0.0028).Highest NO emissions were observed from grape soils (7000 ng m -2 s -1 ), while highest NO emissions from cotton soils are only 1.2 ng m -2 s -1 .Also considering the entire growing period, biogenic net NO fluxes from grape soils are dominating by far, and exceed those from cotton soils on average by a factor of 1  2 ×10 3 .In both soils, the seasonal and diel variations of the net NO fluxes clearly mirror those of the corresponding soil temperature.On the seasonal scale, there is striking evidence for the impact of the chosen irrigation schedules particularly on the net NO fluxes from cotton soils (through the assumed regular 2 weekly variation of the corresponding gravimetric soil moisture content).Immediately after (flooding) irrigation, soils might be water-logged which prevents any diffusion of gases out of the soil; but even after evaporation of the surface waters, the chosen "drying-out" curves (see supplement Fig. S9) prescribe θ g -values of 0.514 ("grape soils") and 0.586 ("cotton soils") which are well above the corresponding values at field capacity conditions.There, soil diffusivity as well as soil microbial processes are severely suppressed (c.f.Skopp et al., 1990).This is clearly reflected in the results of laboratory incubations (see Fig. 4), where the corresponding net potential NO fluxes are close to zero for θ g > 0.4.Approaching the end of the chosen 14 day irrigation period, θ g -values reach 0.086 and 0.167 for grape soils and cotton soils, respectively.Then, the soil diffusivity is no longer limited in both soils, but soil microbial processes in cotton soils are still far from their maximum activity (θ g,opt = 0.021), while soil microbial processes in grape soils have even passed their maximum activity (θ g,opt = 0.146).That is why biogenic net NO fluxes from grape soils of the Tohsun oasis are dominating those from cotton soils.Furthermore, the impact on net NO emission by fertilizer application on 01 April (DOY 91), 27 May (DOY 147), 10 June (DOY 161), 22 July (DOY 203), and 05 August (DOY 217; Fig. S10, supplement) amplifies the already higher net NO fluxes from grape fields.As a consequence, NO emissions from cotton soils can be neglected if compared with emissions from grape soils, even though the net potential emission of cotton soils is more than three times tons) of the NO 2 emission inventory.As the second largest contributor, coke combustion contributed about 10 %.Monthly anthropogenic emissions (given in terms of mass of NO 2 ) have been calculated from Tohsun County's annual NO X emission data, which were down-scaled by appropriate mean monthly percentages (see Sect. 2.4); corresponding results are also shown in Fig. 8 (black bars).As expected, the overwhelming part of anthropogenic NO 2 (600920 t NO 2 month -1 ) was emitted in the winter, when air temperatures (well below 0°C; see Fig. 2) necessitate substantial domestic heating (predominantly by coal), while in July (approx.+35°C) anthropogenic NO 2 emissions shrinked to approx.one tenth of the winter value (150 t NO 2 month -1 ) which might mainly be attributed to traffic emissions.

Soil biogenic vs. anthropogenic emissions of Tohsun oasis
On annual basis (not shown), anthropogenic sources contribute by 81.4 %, biogenic sources by 18.6 % (10.3 % NO, 8.3 % HONO) to Tohsun oasis' total emissions (7246 t, in terms of NO 2 ) of reactive nitrogen in 2010.However, if only the growing period (AprilSeptember) is considered, where 40 % (2884 t) of Tohsun oasis' total annual emissions occur, the anthropogenic emissions contribute about 53.2 %, and biogenic sources about 46.8 % (26,0% NO, 20.8 % HONO).As already mentioned in section 3.1.3,soil biogenic emissions at monthly scales seemed to be primarily controlled by soil temperature.Consequently, during June, July and August, total biogenic emissions (NO and HONO) exceed anthropogenic emissions by factors of 1.8, 2.8, and 1.5, respectively (see Fig. 8).Therefore, biogenic soil emissions of NO and HONO during the growing period are certainly much more important contributors to the regional NO 2 budget (hence to regional photochemistry) than thought before.the different seasons, it is clearly visible that for all seasons enhanced values are found over the area of Tohsun oasis (compared to the surrounding desert).Even stronger enhancements of VCD NO2values are also found for other regions, which are always dominated by anthropogenic emissions, especially the growing mega-city of Urumqi (cf.Mamtimin and Meixner, 2011).To investigate these seasonal and spatial variations in more detail, time series of monthly means are calculated for four selected areas (see Fig. 3): an exclusively agriculturally used area (A: study area), an area of mixed land use (B: agricultural and urban), a large urban area (Urumqi; C), and a desert area (D).The seasonal variation of mean tropospheric VCD NO2 of areas A  D is shown in Fig. 10.These data can distinctively be classified: highest VCD NO2 values (315 10 15 NO 2 molecules cm -2 ) over the large urban area Urumqi (C), 16.5 10 15 NO 2 molecules cm -2 over Tohsun oasis (A) and Tohsun & Turpan area (B), and less than 1 10 15 NO 2 molecules cm -2 over the chosen desert area (D).From these seasonal cycles, clear indications of the relative contributions from fossil fuel combustion and soil emissions can be drawn: Over Urumqi (C) clear maxima are found during winter indicating the dominating contribution from fossil fuel combustion, while there are evidently clear minima during the summer months.In contrast, over the desert (D), where only low VCD NO2 values prevail, small, but distinctive maxima are found during summer, which might be caused by soil emissions.Here, we have to mention that the desert VCD NO2 values are higher than in comparison to the NO emission of the GGTP model results (see supplement S1.9,Fig S6).This is indeed an interesting finding which can be attributed to the fact that in the desert region a small but still substantial diurnal variation in soil moisture is present.However, in our GGTP model we used a constant value for the soil moisture (0.0028); as a result, the diurnal cycle of soil moisture was not considered in the model calculation.It might indeed indicate that the desert soil emissions are underestimated.Alternatively, it might be partly also caused by inflow from NOx-reach air from the surrounding regions.

Spatio-temporal variation of the tropospheric VCD NO2 measured from satellite
Over Tohsun oasis (A) and Tohsun & Turpan area (B) a clear maximum, however 23 fold lower than that over (C), is also found in every winter certainly related to fossil fuel combustion during the heating period.Unique for all seasonal cycles are secondary maxima found in over (A) and (B) during the summer months, which amount approx.half of the winter maxima and indicate that during summer soil emissions substantially contribute to total NO x emissions.

Monthly total NO 2 emissions from Tohsun oasis (top-down)
As described in sect.2.5.2, top-down monthly total NO 2 emissions (particularly from anthropogenic and biogenic sources) of Tohsun oasis were calculated from satellite-derived, background-corrected VCD NO2 .overTohsun oasis and the characteristic lifetime of NO x ,  NOx (with respect to its reaction with the hydroxyl radical OH).In addition, a correction for the partitioning between NO and NO 2 in the atmosphere has to be made.For that purpose we multiply the NO 2 values by typical ratios between NOx and NO 2 of about 1.3 (see e.g.Seinfeld and Pandis, 2012).Results are shown in Fig. 11.Since a prescribed and constant value for  NOx (4.h) has been applied, the seasonal course of monthly total NO 2 emissions is directly proportional to that of VCD NO2 over the area of Tohsun oasis (A) in Fig. 10.In 2010, highest total NO 2 emissions were observed in January and December (343308 ng m -2 s -2 , in terms of NO 2 ), and lowest, 100110 ng m -2 s -2 , in May, September, and October.Between July and August, there is the already mentioned secondary maximum of total NO 2 emissions (177 ng m -2 s -2 ), approximately half of the value in January and December, and approximately twofold of the values in May, September, and October.

NO X emissions of Tohsun oasis: bottom-up vs. top-down
Finally, we compare the satellite-derived (top-down) total NO 2 emissions of the Tohsun oasis with the bottom-up total emission estimates (anthropogenic+biogenic) for the year of 2010.As mentioned before (see sec.2.3.4),we calculated the ratio of bottom-up emission at the satellite overpass (13:00 LT) and the daily average emissions to estimate the effect of the diurnal cycle of the emissions.The highest ratios are found for July and August (2.4) while it is only 1.01 for April (see Fig S12).
Monthly means of bottom-up biogenic emissions at satellite overpass (13:00 LT) with the considering the diurnal cycle of the bottom-up estimates from the Tohsun oasis are also shown in The seasonal course of the bottom-up total emissions (anthropogenic+biogenic; in terms of NO 2 ) qualitatively exhibits nearly the indentical shape as the seasonal course of the top-down total NO 2 emissions.Interestingly, the second maximum in summer is only found, if the soil emissions are taken into account.This finding confirms that during summer soil emissions play an important (if not the dominant) role for Tohsun oasis' total emissions.However, quantitative agreement of bottom-up and top-down total emissions is only perfect for the months April, May and October.For the months of March, June, July, and August, total bottom-up emissions are always higher than the top-down ones between 1062%.The finding seems to confirm that the soil biogenic emission's evidence for the tropospheric NO 2 through the impact of the monthly variation of soil temperature, irrigation schedules, and fertilizer application.Especially the quantitative agreement was better than expected taking into account the uncertainties of the bottom-up and top down emission estimates.The most important error sources are discussed in the following:

Top-down emission estimates:
(a) satellite retrieval: air mass factor (AMF) has to be calculated for the conversion of the retrieved slant column densities into the vertical column densities.Mainly uncertainties of the AMF leading to uncertainties of the derived NO 2 VCD of about 50%.Here particular assumptions on the trace gas profile and the surface albedo have to be made.For NO 2 vertical profiles from a global model (TM4, s. sect.2.5.1) with a rather coarse spatial resolution are used.Probably the derived NO 2 VCDs underestimate the true NO 2 VCDs because the true NO 2 profile is peaked more closely to the ground than the profile used in the satellite retrieval.Here it should be noted that the uncertainties of the spectral retrieval are much smaller because many measurements are averaged.As a consequence, the true AMF is probably smaller than the one used in the OMI retrieval, and thus the VCD NO2 from the operational product probably underestimates the true tropospheric VCD NO2 .In contrast, the surface albedo used in the operational product is very similar to those from other data sets (MODIS and MERIS).Here it is interesting to note that the spatial patterns of the surface albedo and the tropospheric VCD NO2 show no similarities.
(b) assumption of the NOx lifetime of 4 hours: The life time of NO 2 in the troposphere depends on season and altitude and varies from hour to days.Due to the winterly lower OH concentration, lifetime in winter is longer than corresponding values in summer.However, to keep the estimation of the top-down inventory simple, we used a temporally constant mean lifetime of 4 hours; that leads to a certain overestimation of the emissions in winter.Nevertheless, the considered lifetime within study is a good approximation for the growing season.Thereby, the potential uncertainties might be neglected if one considers the uncertainties which may be caused by the Air Mass Factor (AMF).(c) satellite overpass time period: top-down emission estimates are only valid for the time of the satellite overpass (around 13:00 LT) and a few hours before.Thus we compared the top-down emissions to the results from the bottom-up emissions during the time of the satellite overlap (Fig. 11).Fortunately, the soil emissions during the satellite overpass time are strongest because of the high temperatures around noon.

Bottom-up emission estimates:
(a) soil biogenic NO: The soil temperature at 30-minute resolution are calculated by using of satellite-derived surface temperature and in-situ measurements.The interpolation of the satellitederived data was done by a 3 rd order polynomial.From sensitivity analyses we found that the uncertainties of the derived temperatures are up to about 6°C.Substantial deviations of soil temperatures (from the interpolated values) between Day 115 and Day 225 might be unlikely since surface temperatures in (hyper-) arid regions (even with (sparse) vegetation covering) are predominantly controlled by insolation only as long there is no impact of (convective) precipitation (indeed, Turpan's Meteorological Station has not reported any precipitation events during the entire growing period).The soil moisture contents were adapted from in-situ measurements of Minfeng and Kuche oases (see.S1.8).Thus, the bottom-up NO estimates might be prone of systematic uncertainties which are inevitably due to the assumptions and adaptions of the data assimilation for soil temperatures, gravimetric soil moisture contents, and fertilizer factors (s.sect.S3.1S3.3,supplement).
(b) soil biogenic HONO: Since the NO and HONO emissions have the similar dependence on soil moisture for soil properties in arid climate conditions (Oswald et al. ( 2013)), we used the land use specific constant scale factor namely the ratio of HONO and NO releases for the optimum conditions to estimate the HONO emissions ((F N , opt (HONO) to F N , opt (NO)).Nevertheless, the optimum soil water content (SWC opt ) has a strong influence on the ratio of F N , opt (HONO) to F N , opt (NO).We used this ratio for the calculation of monthly HONO emissions by scaling corresponding NO emissions.
However, particularly for cotton soil, the value of the optimum gravimetric soil water content for NO (2.1 %) is slightly lower than the corresponding value for HONO (3.6 %, s.Oswald et al., 2013).This may result in a certain error of the calculated HONO emissions, which unfortunately can not be quantified more precisely at the moment.Nevertheless, these uncertainties do not question for the basic massage of the study.
(c) anthropogenic NO 2 : Furthermore, one should keep in mind, that the percentage factors for temporal down-scaling annual anthropogenic NO 2 emissions of Tohsun oasis to monthly have to be adapted from the growing mega-city of Urumqi.
Because of these uncertainties, the good agreement between top-down and bottom-up emission estimates should be treated with caution.Nevertheless, the qualitative and, in particular, the quantitative agreement between bottom-up and top-down estimates indicates that our assumptions are largely justified.The combination of independent methods applied in our present study was the first attempt to prove the comparison of soil NO emissions of different scales, ranging from the size of a soil sample to the size of a satellite pixel.However, the following improvements in these methods for the future work might be necessary:

Summary
This study is focusing on the investigation and quantification of the biogenic NO emission from agriculturally managed soils of the Tohsun oasis (i.e. from soils of grape and cotton cultivation).Biogenic emissions of nitrous acid (HONO, concurrently emitted with NO) were also estimated using scaling factors applied to the calculated NO emissions.The following methodology was applied: Firstly, the Geoscience General Tool Package (GGTP) has been developed to obtain the soil temperatures and classification of land use types of the oasis from Landsat satellite data.Secondly, mean diel and land use specific variations of the normalized soil temperature, gravimetric soil moisture content, and fertilizer factors were assimilated from (sparsely) available data sources (of different spatial and temporal scales as well as data quality).These have been used to calculate the mean monthly land use specific bottom-up biogenic NO emissions from so-called net potential NO fluxes which in turn have been derived from laboratory incubation of soil samples from the three considered land use types (cotton, grape, and desert soils).Thirdly, land use specific factors of HONO to biogenic NO emissions from grape and cotton soils were applied to calculate the monthly biogenic bottom-up HONO emissions during the growing period.Fourthly, data of the anthropogenic NO 2 emissions (down-scaled from annual to monthly values) were estimated and compared to the mean monthly soil biogenic emissions (NO+HONO).Fifthly, top-down total NO 2 emissions from the Tohsun oasis have been derived from satellite observations (monthly means of Vertical Column Densities of NO 2 , VCD NO2 ) and prescribed values of the characteristic lifetime of NO 2 ,  NO2 (with respect to its reaction with the hydroxyl radical OH).Finally, we compared the biogenic bottom-up emissions at around noon time (13:00 LT) to that of the top-down emissions with the consideration of the diurnal cycle of bottom-up estimates.
The importance of soil biogenic emissions to the regional NO 2 budget of Tohsun oasis has been demonstrated by the comparison between monthly biogenic soil emissions (NO and HONO, expressed in terms of NO 2 ) and the corresponding anthropogenic NO 2 emissions.During the growing period, particularly between June and August, biogenic emissions are up to twofold of the anthropogenic emissions.From the three considered land use types of the Tohsun oasis (desert, grape, and cotton soils), the soil biogenic emissions from grape soils (fertilized and irrigated) dominated summertime soil biogenic emissions of the oasis; emissions from cotton soils (fertilized and irrigated) were orders of magnitude lower (particularly because of its soil physical nature and the chosen irrigation schedule); soil biogenic emissions from desert soils could be completely neglected.It should be noted, that the contribution from cotton soils might be considerably higher for other oases.During winter, Tohsun oasis' soils are frozen, and biogenic emissions are virtually zero; thus total NO x emissions of the Tohsun oasis during that season are exclusively due to anthropogenic emissions.As a consequence of both, anthropogenic and biogenic contributions, the seasonal (monthly) variation of total emission is characterized by two peaks (a strong peak in winter and a weaker, secondary peak in summer).The monthly variation of the top-down total emissions (derived from satellite observations) reveals the identical two-peak shape and agrees qualitatively truly satisfactory to that of bottom-up emissions.Also good quantitative agreement between the top-down and the bottom-up estimates is found.Here it should be noted that the emissions around noon (the satellite overpass time) are up to about two times higher than the daily averaged emissions during the growing season.Therefore, these results provide strong evidence that the biogenic emissions from soils of managed drylands (irrigated, fertilized) in the growing period exceed local anthropogenic emissions, hence contributing substantially to the local tropospheric NO x levels.Summarizing, it is concluded, that soil biogenic emissions of NO and HONO during the vegetation period could be much more important contributors to the regional NO X budget (hence to regional photochemistry) of dryland regions than thought before.).The biogenic bottom-up emissions around 13:00LT (at satellite overpass) are selected.They are systematically higher than the daily averages (see Fig. S12).
2.3.1)using land use specific data of soil temperature (see sec.2.3.3),gravimetric soil moisture contents (see 2.3.3), and fertilizer factors (see sec.2.3.3).Monthly, bottom-up soil biogenic NO emissions for the entire region of Tohsun oasis were calculated by (a) averaging temporally high resolution data (30 min) of the three land use specific soil biogenic net NO fluxes for each month of the growing period (AprilSeptember 2010), (b) weighing by the areal contribution of each of the three land use types (1117, 80, and 150 km 2 for desert, grape, and cotton soils; see sect.2.3.2), and (c) summing up for each month of 2010.
because they have the same soil properties, and they experienced the same irrigation regimes and fertilizer applications, and (b) the soil release of HONO and NO byOswald et al. (2013) has been measured also in the Max Planck Institute for Chemistry by a next-laboratory version of that dynamic chamber system which was used to measure the soil release of NO in the present study.Consequently, corresponding ratios for optimum condition of HONO and NO emissions (i.e., F N , opt (HONO) to F N , opt (NO)) have been used to calculate monthly HONO emissions from Tohsun oasis from the measured NO emissions.Monthly land use type specific contributions of HONO emission for the Tohsun oasis during the growing period 2010 were estimated by multiplying the corresponding NO emissions with the mean, land use type specific factors (0.8 for grape and desert soils, and 1.6 for cotton soils); these were calculated from individual values provided byOswald et al. (2013) which are derived from the ratio for the optimum condition F N , opt (HONO) to F N , opt (NO).
Fig. S10 (supplement), clearly demonstrating regular temporal patterns due to the chosen irrigation and fertilization schedules.

Fig. 9
Fig. 9 shows the seasonal means for spring, summer, autumn and winter (from 2006 to 2010) of the tropospheric NO 2 VCD around the Tohsun oasis.Comparing the mean distribution (2006-2010) of

Fig. 11 .
Fig. 11.Bottom-up anthropogenic NO 2 emissions are shown individually to emphasize the contribution of soil biogenic emissions (NO+HONO).
(a) bottom-up biogenic emissions: derivation of individual NO and HONO net release rates from a series of simultaneous incubation experiments in the laboratory under well-defined conditions (full soil temperature and gravimetric soil moisture scales), (b) temporally high resolution in-situ measurements of top soil temperature and gravimetric soil moisture by suitable (and simple) sensors at representative sites of all considered land use types (at least during the growing period), (c) top-down emission estimates: temporally resolved consideration of the NO 2 lifetime.
analyzed the data and performed the bottom-up estimates; B. Mamtimin and T. Behrendt carried out the field experiments; T. Behrendt performed laboratory experiments; B. Mamtimin and T. Wagner performed the top-down estimates; B. Mamtimin and M. Badawy developed the GGTP model; B. Mamtimin, F.X. Meixner and T. Wagner wrote the paper and all Authors contributed to the discussion of the paper.

Fig. 8 :Fig. 10 :
Fig. 8: Anthropogenic NO x emissions vs. soil biogenic NO 2 emissions from NO and HONO emissions of the Tohsun oasis in 2010; biogenic emissions of nitrous acid (HONO) have been estimated according to Oswald et al. (2013).All data are given in terms of mass of NO 2 .5