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In-cloud measurements highlight the role of aerosol hygroscopicity in cloud droplet formation

The relationship between aerosol hygroscopicity and cloud droplet activation was studied at the Puijo measurement station in Kuopio, Finland, during the autumn 2014. The hygroscopic growth of 80, 120 and 150  nm particles was measured at 90 % relative humidity with a hygroscopic tandem differential mobility analyzer. Typically, the growth factor (GF) distributions appeared bimodal with clearly distinguishable peaks around 1.0–1.1 and 1.4–1.6. However, the relative contribution of the two modes appeared highly variable reflecting the probable presence of fresh anthropogenic particle emissions. The hygroscopicity-dependent activation properties were estimated in a case study comprising four separate cloud events with varying characteristics. At 120 and 150 nm, the activation efficiencies within the low- and high-GF modes varied between 0–34 and 57–83 %, respectively, indicating that the less hygroscopic particles remained mostly non-activated, whereas the more hygroscopic mode was predominantly scavenged into cloud droplets. By modifying the measured GF distributions, it was estimated how the cloud droplet concentrations would change if all the particles belonged to the more hygroscopic group. According to κ-Köhler simulations, the cloud droplet concentrations increased up to 70 % when the possible feedback effects on effective peak supersaturation (between 0.16 and 0.29 %) were assumed negligible. This is an indirect but clear illustration of the sensitivity of cloud formation to aerosol chemical composition.
Assessing the ammonium nitrate formation regime in the Paris megacity and its representation in the CHIMERE model

Secondary inorganic compounds represent a major fraction of fine aerosol in the Paris megacity. The thermodynamics behind their formation is now relatively well constrained but, due to sparse direct measurements of their precursors (in particular NH3 and HNO3), uncertainties remain on their concentrations and variability as well as the formation regime of ammonium nitrate (in terms of limited species among NH3 and HNO3) in urban environments such as Paris. This study presents the first urban background measurements of both inorganic aerosol compounds and their gaseous precursors during several months within the city of Paris. Intense agriculture-related NH3 episodes are observed in spring/summer while HNO3 concentrations remain relatively low, even during summer, which leads to a NH3-rich regime in Paris. The local formation of ammonium nitrate within the city appears low, despite high NOx emissions. The data set also allows evaluating the CHIMERE chemistry-transport model (CTM). Interestingly, the rather good results obtained on ammonium nitrates hide significant errors on gaseous precursors (e.g., mean bias of −75 and +195 % for NH3 and HNO3, respectively). This leads to a misrepresentation of the nitrate formation regime through a highly underestimated gas ratio metric (introduced by Ansari and Pandis, 1998) and a much higher sensitivity of nitrate concentrations to ammonia changes. Several uncertainty sources are investigated, pointing out the importance of better assessing both NH3 agricultural emissions and OH concentrations in the future. These results remind us of the caution required when using of CTMs for emission scenario analysis, highlighting the importance of prior diagnostic and dynamic evaluations.
A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts

Forecasting atmospheric CO2 daily at the global scale with a good accuracy like it is done for the weather is a challenging task. However, it is also one of the key areas of development to bridge the gaps between weather, air quality and climate models. The challenge stems from the fact that atmospheric CO2 is largely controlled by the CO2 fluxes at the surface, which are difficult to constrain with observations. In particular, the biogenic fluxes simulated by land surface models show skill in detecting synoptic and regional-scale disturbances up to sub-seasonal time-scales, but they are subject to large seasonal and annual budget errors at global scale, usually requiring a posteriori adjustment. This paper presents a scheme to diagnose and mitigate model errors associated with biogenic fluxes within an atmospheric CO2 forecasting system. The scheme is an adaptive scaling procedure referred to as a biogenic flux adjustment scheme (BFAS), and it can be applied automatically in real time throughout the forecast. The BFAS method generally improves the continental budget of CO2 fluxes in the model by combining information from three sources: (1) retrospective fluxes estimated by a global flux inversion system, (2) land-use information, (3) simulated fluxes from the model. The method is shown to produce enhanced skill in the daily CO2 10-day forecasts without requiring continuous manual intervention. Therefore, it is particularly suitable for near-real-time CO2 analysis and forecasting systems.
Vertical profiles of black carbon measured by a micro-aethalometer in summer in the North China Plain

Black carbon (BC) is a dominant absorber in the visible spectrum and a potent factor in climatic effects. Vertical profiles of BC were measured using a micro-aethalometer attached to a tethered balloon during the Vertical Observations of trace Gases and Aerosols (VOGA) field campaign, in summer 2014 at a semirural site in the North China Plain (NCP). The diurnal cycle of BC vertical distributions following the evolution of the mixing layer (ML) was investigated for the first time in the NCP region. Statistical parameters including identified mixing height (Hm) and average BC mass concentrations within the ML (Cm) and in the free troposphere (Cf) were obtained for a selected dataset of 67 vertical profiles. Hm was usually lower than 0.2 km in the early morning and rapidly rose thereafter due to strengthened turbulence. The maximum height of the ML was reached in the late afternoon. The top of a full developed ML exceeded 1 km on sunny days in summer, while it stayed much lower on cloudy days. The sunset triggered the collapse of the ML, and a stable nocturnal boundary layer (NBL) gradually formed. Accordingly, the highest level Cm was found in the early morning and the lowest was found in the afternoon. In the daytime, BC was almost uniformly distributed within the ML and significantly decreased above the ML. During the field campaign, Cm averaged about 5.16 ± 2.49 µg m−3, with a range of 1.12 to 14.49 µg m−3, comparable with observational results in many polluted urban areas such as Milan in Italy and Shanghai in China. As evening approached, BC gradually built up near the surface and exponentially declined with height. In contrast to the large variability found both in Hm and Cm, Cf stayed relatively unaffected through the day. Cf was less than 10 % of the ground level under clean conditions, while it amounted to half of the ground level in some polluted cases. In situ measurements of BC vertical profiles would hopefully have an important implication for accurately estimating direct radiative forcing by BC and improving the retrieval of aerosol optical properties by remote sensing in this region.
In situ observations of the isotopic composition of methane at the Cabauw tall tower site

High-precision analyses of the isotopic composition of methane in ambient air can potentially be used to discriminate between different source categories. Due to the complexity of isotope ratio measurements, such analyses have generally been performed in the laboratory on air samples collected in the field. This poses a limitation on the temporal resolution at which the isotopic composition can be monitored with reasonable logistical effort. Here we present the performance of a dual isotope ratio mass spectrometric system (IRMS) and a quantum cascade laser absorption spectroscopy (QCLAS)-based technique for in situ analysis of the isotopic composition of methane under field conditions. Both systems were deployed at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands and performed in situ, high-frequency (approx. hourly) measurements for a period of more than 5 months. The IRMS and QCLAS instruments were in excellent agreement with a slight systematic offset of (+0.25 ± 0.04) ‰ for δ13C and (−4.3 ± 0.4) ‰ for δD. This was corrected for, yielding a combined dataset with more than 2500 measurements of both δ13C and δD. The high-precision and high-temporal-resolution dataset not only reveals the overwhelming contribution of isotopically depleted agricultural CH4 emissions from ruminants at the Cabauw site but also allows the identification of specific events with elevated contributions from more enriched sources such as natural gas and landfills. The final dataset was compared to model calculations using the global model TM5 and the mesoscale model FLEXPART-COSMO. The results of both models agree better with the measurements when the TNO-MACC emission inventory is used in the models than when the EDGAR inventory is used. This suggests that high-resolution isotope measurements have the potential to further constrain the methane budget when they are performed at multiple sites that are representative for the entire European domain.
The natural oscillations in stratospheric ozone observed by the GROMOS microwave radiometer at the NDACC station Bern

A multilinear parametric regression analysis was performed to assess the seasonal and interannual variations of stratospheric ozone profiles from the GROMOS (GROund-based Millimeter-wave Ozone Spectrometer) microwave radiometer at Bern, Switzerland (46.95° N, 7.44° E; 577 m). GROMOS takes part in the Network for the Detection of Atmospheric Composition Change (NDACC). The study covers the stratosphere from 50 to 0.5 hPa (from 21 to 53 km) and extends over the period from January 1997 to January 2015. The natural variability was fitted during the regression analysis through the annual and semi-annual oscillations (AO, SAO), the quasi-biennial oscillation (QBO), the El Niño–Southern Oscillation (ENSO) and the solar activity cycle. Seasonal ozone variations mainly appear as an annual cycle in the middle and upper stratosphere and a semi-annual cycle in the upper stratosphere. Regarding the interannual variations, they are primarily present in the lower and middle stratosphere. In the lower and middle stratosphere, ozone variations are controlled predominantly by transport processes, due to the long lifetime of ozone, whereas in the upper stratosphere its lifetime is relatively short and ozone is controlled mainly by photochemistry. The present study shows agreement in the observed naturally induced ozone signatures with other studies. Further, we present an overview of the possible causes of the effects observed in stratospheric ozone due to natural oscillations at a northern midlatitude station. For instance regarding the SAO, we find that polar winter stratopause warmings contribute to the strength of this oscillation since these temperature enhancements lead to a reduction in upper stratospheric ozone. We have detected a strong peak amplitude of about 5 % for the solar cycle in lower stratospheric ozone for our 1.5 cycles of solar activity. Though the 11-year ozone oscillation above Bern is in phase with the solar cycle, we suppose that the strong amplitude is partly due to meteorological disturbances and associated ozone anomalies in the Northern Hemisphere. Further, our observational study gave the result that ozone above Bern is anti-correlated with the ENSO phenomenon in the lower stratosphere and correlated in the middle stratosphere.
Tropospheric ozone variability during the East Asian summer monsoon as observed by satellite (IASI), aircraft (MOZAIC) and ground stations

Satellite measurements from the thermal Infrared Atmospheric Sounding Interferometer (IASI), aircraft data from the MOZAIC/IAGOS project, as well as observations from ground-based stations, are used to assess the tropospheric ozone (O3) variability during the East Asian Summer Monsoon (EASM). Six years 2008–2013 of IASI data analysis reveals the ability of the instrument to detect the onset and the progression of the monsoon seen by a decrease in the tropospheric 0–6 km O3 column due to the EASM, and to reproduce this decrease from one year to the other. The year-to-year variability is found to be mainly dependent on meteorology. Focusing on the period of May-August 2011, taken as an example year, IASI data show clear inverse relationship between tropospheric 0–6 km O3 on one hand and meteorological parameters such as cloud cover, relative humidity and wind speed, on the other hand. Aircraft data from the MOZAIC/IAGOS project for the EASM of 2008–2013 are used to validate the IASI data and to assess the effect of the monsoon on the vertical distribution of the tropospheric O3 at different locations. Results show good agreement with a correlation coefficient of 0.73 (12 %) between the 0–6 km O3 column derived from IASI and aircraft data. IASI captures very well the inter-annual variation of tropospheric O3 observed by the aircraft data over the studied domain. Analysis of vertical profiles of the aircraft data shows a decrease in the tropospheric O3 that is more important in the free troposphere than in the boundary layer and at 10–20° N than elsewhere. Ground station data at different locations in India and China show a spatiotemporal dependence on meteorology during the monsoon, with a decrease up to 22 ppbv in Hyderabad, and up to 5 ppbv in the North China Plain.
Impacts of aviation fuel sulfur content on climate and human health

Aviation emissions impact both air quality and climate. Using a coupled tropospheric chemistry-aerosol microphysics model we investigate the effects of varying aviation fuel sulfur content (FSC) on premature mortality from long-term exposure to aviation-sourced PM2.5 (particulate matter with a dry diameter of <  2.5 µm) and on the global radiation budget due to changes in aerosol and tropospheric ozone. We estimate that present-day non-CO2 aviation emissions with a typical FSC of 600 ppm result in ∼  3600 [95 % CI: 1310–5890] annual premature mortalities globally due to increases in cases of cardiopulmonary disease and lung cancer, resulting from increased surface PM2.5 concentrations. We quantify the global annual mean combined radiative effect (REcomb) of non-CO2 aviation emissions as −13.3 mW m−2; from increases in aerosols (direct radiative effect and cloud albedo effect) and tropospheric ozone. Ultra-low sulfur jet fuel (ULSJ; FSC  =  15 ppm) has been proposed as an option to reduce the adverse health impacts of aviation-induced PM2.5. We calculate that swapping the global aviation fleet to ULSJ fuel would reduce the global aviation-induced mortality rate by ∼  620 [95 % CI: 230–1020] mortalities a−1 and increase REcomb by +7.0 mW m−2. We explore the impact of varying aviation FSC between 0 and 6000 ppm. Increasing FSC increases aviation-induced mortality, while enhancing climate cooling through increasing the aerosol cloud albedo effect (CAE). We explore the relationship between the injection altitude of aviation emissions and the resulting climate and air quality impacts. Compared to the standard aviation emissions distribution, releasing aviation emissions at the ground increases global aviation-induced mortality and produces a net warming effect, primarily through a reduced CAE. Aviation emissions injected at the surface are 5 times less effective at forming cloud condensation nuclei, reducing the aviation-induced CAE by a factor of 10. Applying high FSCs at aviation cruise altitudes combined with ULSJ fuel at lower altitudes results in reduced aviation-induced mortality and increased negative RE compared to the baseline aviation scenario.
Spatial and temporal variability of urban fluxes of methane, carbon monoxide and carbon dioxide above London, UK

We report on more than 3 years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Mean annual emissions of CO2 in the period 2012–2014 (39.1 ± 2.4 ktons km−2 yr−1) and CO (89 ± 16 tons km−2 yr−1) were consistent (within 1 and 5 % respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 emissions (72 ± 3 tons km−2 yr−1) were over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69 %, and monthly fluxes were strongly anti-correlated with mean air temperature. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33 % higher in winter than in summer and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. CH4 fluxes exhibited moderate seasonality (21 % larger in winter), and a spatially variable linear anti-correlation with air temperature. Differences in resident population within the flux footprint explained up to 90 % of the spatial variability of the annual CO2 fluxes and up to 99 % for CH4. Furthermore, we suggest that biogenic sources of CH4, such as wastewater, which is unaccounted for by the atmospheric emissions inventories, make a substantial contribution to the overall budget and that commuting dynamics in and out of central business districts could explain some of the spatial and temporal variability of CO2 and CH4 emissions. To our knowledge, this study is unique given the length of the data sets presented, especially for CO and CH4 fluxes. This study offers an independent assessment of "bottom-up" emissions inventories and demonstrates that the urban sources of CO and CO2 are well characterized in London. This is however not the case for CH4 emissions which are heavily underestimated by the inventory approach. Our results and others point to opportunities in the UK and abroad to identify and quantify the "missing" sources of urban methane, revise the methodologies of the emission inventories and devise emission reduction strategies for this potent greenhouse gas.
Boundary layer evolution over the central Himalayas from radio wind profiler and model simulations

We investigate the time evolution of the Local Boundary Layer (LBL) for the first time over a mountain ridge at Nainital (79.5° E, 29.4° N, 1958 m a.m.s.l.) in the central Himalayan region, using a radar wind profiler (RWP) during November 2011 to March 2012, as a part of the Ganges Valley Aerosol Experiment (GVAX). We restrict our analysis to clear–sunny days, resulting in a total of 78 days of observations. The standard criterion of the peak in the signal-to-noise ratio (S ∕ N) profile was found to be inadequate in the characterization of mixed layer (ML) top at this site. Therefore, we implemented a criterion of S ∕ N > 6 dB for the characterization of the ML and the resulting estimations are shown to be in agreement with radiosonde measurements over this site. The daytime average (05:00–10:00 UTC) observed boundary layer height ranges from 440 ± 197 m in November (late autumn) to 766 ± 317 m above ground level (a.g.l.) in March (early spring). The observations revealed a pronounced impact of mountain topography on the LBL dynamics during March, when strong winds (> 5.6 m s−1) lead to LBL heights of 650 m during nighttime. The measurements are further utilized to evaluate simulations from the Weather Research and Forecasting (WRF) model. WRF simulations captured the day-to-day variations up to an extent (r2 = 0.5), as well as the mean diurnal variations (within 1σ variability). The mean biases in the daytime average LBL height vary from −7 % (January) to +30 % (February) between model and observations, except during March (+76 %). Sensitivity simulations using a mixed layer model (MXL/MESSy) indicated that the springtime overestimation of LBL would lead to a minor uncertainty in simulated surface ozone concentrations. However, it would lead to a significant overestimation of the dilution of black carbon aerosols at this site. Our work fills a gap in observations of local boundary layer over this complex terrain in the Himalayas, and highlights the need for year-long simultaneous measurements of boundary layer dynamics and air quality to better understand the role of lower tropospheric dynamics in pollution transport.