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Excess atmospheric ammonia (NH 3 ) leads to deleterious effects on biodiversity, ecosystems, air quality and health, and it is therefore essential to monitor its budget and temporal evolution. Hyperspectral infrared satellite sounders provide daily NH 3 observations at global scale for over a decade. Here we use the version 3 of the Infrared Atmospheric Sounding Interferometer (IASI) NH 3 dataset to derive global, regional and national trends from 2008 to 2018. We find a worldwide increase of 12.8 ± 1.3 % over this 11-year period, driven by large increases in east Asia (5.80 ± 0.61% increase per year), western and central Africa (2.58 ± 0.23 % yr −1 ), North America (2.40 ± 0.45 % yr −1 ) and western and southern Europe (1.90 ± 0.43 % yr −1 ). These are also seen in the Indo-Gangetic Plain, while the southwestern part of India exhibits decreasing trends. Reported national trends are analyzed in the light of changing anthropogenic and pyrogenic NH 3 emissions, meteorological conditions and the impact of sulfur and nitrogen oxides emissions, which alter the atmospheric lifetime of NH 3 . We end with a short case study dedicated to the Netherlands and the ‘Dutch Nitrogen crisis’ of 2019.

Volatile organic compounds are emitted abundantly from a variety of natural and anthropogenic sources. However, in excess, they can severely degrade air quality. Their fluxes are currently poorly represented in inventories due to a lack of constraints from global measurements. Here, we track from space over 300 worldwide hotspots of ethylene, the most abundant industrially produced organic compound. We identify specific emitters associated with petrochemical clusters, steel plants, coal-related industries, and megacities. Satellite-derived fluxes reveal that the ethylene emissions of the industrial sources are underestimated or missing in the state-of-the-art Emission Database for Global Atmospheric Research (EDGAR) inventory. This work exposes global emission point-sources of a short-lived carbonated gas, complementing the ongoing large-scale efforts on the monitoring of inorganic pollutants. Combining 13 years of satellite measurements led to the discovery of 300 global hotspots of atmospheric ethylene (C 2 H 4 ). They are found to be linked to heavy industries and megacities, and are currently misrepresented in emission inventories.

Atmospheric non-methane hydrocarbon concentrations began declining in the 1970s. Surface and column measurements show that Northern Hemisphere ethane concentrations are now rising, probably due to North American oil and natural gas emissions. Non-methane hydrocarbons such as ethane are important precursors to tropospheric ozone and aerosols. Using data from a global surface network and atmospheric column observations we show that the steady decline in the ethane mole fraction that began in the 1970s 1 , 2 , 3 halted between 2005 and 2010 in most of the Northern Hemisphere and has since reversed. We calculate a yearly increase in ethane emissions in the Northern Hemisphere of 0.42 (±0.19) Tg yr −1 between mid-2009 and mid-2014. The largest increases in ethane and the shorter-lived propane are seen over the central and eastern USA, with a spatial distribution that suggests North American oil and natural gas development as the primary source of increasing emissions. By including other co-emitted oil and natural gas non-methane hydrocarbons, we estimate a Northern Hemisphere total non-methane hydrocarbon yearly emission increase of 1.2 (±0.8) Tg yr −1 . Atmospheric chemical transport modelling suggests that these emissions could augment summertime mean surface ozone by several nanomoles per mole near oil and natural gas production regions. Methane/ethane oil and natural gas emission ratios could suggest a significant increase in associated methane emissions; however, this increase is inconsistent with observed leak rates in production regions and changes in methane’s global isotopic ratio.

In social insects, alerting nestmates to the presence of a pathogen should be critical for limiting its spread and initiating social mechanisms of defense. Here we show that subterranean termites use elevated vibratory alarm behavior to help prevent fatal fungal infections. The elevated alarm leads to elevated social hygiene. This requires that termites coalesce so that they can groom each other’s cuticular surfaces of contaminating conidial spores. Groups of 12 Reticulitermes flavipes workers varied in their response when immersed in conidia solutions of nine different strains of Metarhizium. Pathogen alarm displays of short 2–7-second bursts of rapid longitudinal oscillatory movement (LOM), observed over 12 min following a fungal challenge, were positively correlated with the time that workers spent aggregated together grooming each other. The frequency of these LOMs was inversely correlated with fatal fungal infections. The variation in fatalities appeared to be largely attributable to a differential response to Metarhizium brunneum and Metarhizium robertsii in the time spent in aggregations and the frequency of allogrooming. Isolated workers challenged with conidia did not display LOMs, which suggests that the alarm is a conditional social response. LOMs appear to help signal the presence of fungal pathogens whose virulence depends on the level of this emergency alert.

Allogrooming appears to be essential in many social animals for protection from routine exposure to parasites. In social insects, it appears to be critical for the removal of pathogenic propagules from the cuticle before they can start an infectious cycle. For subterranean termites, this includes fungal spores commonly encountered in the soil, such as Metarhizium conidia, that can quickly germinate and penetrate the cuticle. We investigated whether there is a difference in reliance on social and innate immunity in two closely related subterranean termites for protection from fatal infections by two locally encountered Metarhizium species. Our results indicate that relatively weak innate immunity in one termite species is compensated by more sustained allogrooming. This includes enhanced allogrooming in response to concentrations of conidia that reflect more routine contamination of the cuticle as well as to heavy cuticular contamination that elicits a networked emergency response.

Ethane is the most abundant non-methane hydrocarbon in the Earth’s atmosphere and an important precursor of tropospheric ozone through various chemical pathways. Ethane is also an indirect greenhouse gas (global warming potential), influencing the atmospheric lifetime of methane through the consumption of the hydroxyl radical (OH). Understanding the development of trends and identifying trend reversals in atmospheric ethane is therefore crucial. Our dataset consists of four series of daily ethane columns. As with many other decadal time series, our data are characterized by autocorrelation, heteroskedasticity, and seasonal effects. Additionally, missing observations due to instrument failure or unfavorable measurement conditions are common in such series. The goal of this paper is therefore to analyze trends in atmospheric ethane with statistical tools that correctly address these data features. We present selected methods designed for the analysis of time trends and trend reversals. We consider bootstrap inference on broken linear trends and smoothly varying nonlinear trends. In particular, for the broken trend model, we propose a bootstrap method for inference on the break location and the corresponding changes in slope. For the smooth trend model, we construct simultaneous confidence bands around the nonparametrically estimated trend. Our autoregressive wild bootstrap approach, combined with a seasonal filter, is able to handle all issues mentioned above (we provide R code for all proposed methods on https://www.stephansmeekes.nl/code.).

Only very few long-term records of formaldehyde (HCHO) exist that are suitable for trend analysis. Furthermore, many uncertainties remain as to its diurnal cycle, representing a large short-term variability superimposed on seasonal and inter-annual variations that should be accounted for when comparing ground-based observations to, e.g., model results. In this study, we derive a multi-decadal time series (January 1988–June 2015) of HCHO total columns from ground-based high-resolution Fourier transform infrared (FTIR) solar spectra recorded at the high-altitude station of Jungfraujoch (Swiss Alps, 46.5° N, 8.0° E, 3580 m a. s. l. ), allowing for the characterization of the mid-latitudinal atmosphere for background conditions. First we investigate the HCHO diurnal variation, peaking around noontime and mainly driven by the intra-day insolation modulation and methane (CH4) oxidation. We also characterize quantitatively the diurnal cycles by adjusting a parametric model to the observations, which links the daytime to the HCHO columns according to the monthly intra-day regimes. It is then employed to scale all the individual FTIR measurements on a given daytime in order to remove the effect of the intra-day modulation for improving the trend determination and the comparison with HCHO columns simulated by the state-of-the-art GEOS-Chem v9-02 chemical transport model. Such a parametric model will be useful to scale the Jungfraujoch HCHO columns on satellite overpass times in the framework of future calibration/validation efforts of space-borne sensors. GEOS-Chem sensitivity tests suggest then that the seasonal and inter-annual HCHO column variations above Jungfraujoch are predominantly led by the atmospheric CH4 oxidation, with a maximum contribution of 25 % from the anthropogenic non-methane volatile organic compound precursors during wintertime. Finally, trend analysis of the so-scaled 27-year FTIR time series reveals a long-term evolution of the HCHO columns in the remote troposphere to be related to the atmospheric CH4 fluctuations and the short-term OH variability: +2.9 % year−1 between 1988 and 1995, −3.7 % year−1 over 1996–2002 and +0.8 % year−1 from 2003 onwards.

Context: Both frailty and multimorbidity are strong predictors of clinical endpoints for older people. In Italy, the interventions targeting chronicity are mainly based on the treatment of diseases: sufficient epidemiological literature is available about these strategies. Less is known about the territorial distribution of the frailty status. Aims: To estimate the prevalence of frailty in older people (65+) and to evaluate the relationship between frailty and multimorbidity. Methods and material: A group of general practitioners working in Veneto (Italy) was enrolled on a voluntary basis. Older individuals were both community dwelling and institutionalized patients, that is, the older people normally followed by Italian general practitioners. A centrally randomized sample was extracted from the pool of physician-assisted elderly. Each doctor evaluated the frailty status through the CSHA Clinical Frailty Scale and the multimorbidity status through the Charlson score (Frailty = CSHA Clinical Frailty Scale's score >4; serious multimorbidity = Charlson score ≥4). Prevalence and its confidence interval (CI) 95% were evaluated through the Agresti's method for proportions. The relation between frailty and multimorbidity was studied through a logistic regression model adjusted for age and sex. Results: Fifty-three physicians were enrolled, whose population of elderly individuals (N = 82919) was highly representative of the population of Veneto. The prevalence of frailty in the randomized sample of 2407 older people was 23.18% (CI 95%: 21.53%-24.91%). Sex was shown to be a strong predictor of frailty (female status OR = 1.58 p < .0001) and multimorbidity was shown to be an independent predictor only for individuals <85 years of age. Conclusions: In Veneto, more than 20% of elderly people are frail. Physicians should pay close attention to frailty and multimorbidity because both are important prognostic factors toward clinical endpoints relevant to territorial care. The CSHA Clinical Frailty Scale (easy and quick) should become part of their professional routine.

This paper studies the seasonal variation of surface and column CO at three different sites (Paris, Jungfraujoch and Wollongong), with an emphasis on establishing a link between the CO vertical distribution and the nature of CO emission sources. We find the first evidence of a time lag between surface and free tropospheric CO seasonal variations in the Northern Hemisphere. The CO seasonal variability obtained from the total columns and free tropospheric partial columns shows a maximum around March–April and a minimum around September–October in the Northern Hemisphere (Paris and Jungfraujoch). In the Southern Hemisphere (Wollongong) this seasonal variability is shifted by about 6 months. Satellite observations by the IASI–MetOp (Infrared Atmospheric Sounding Interferometer) and MOPITT (Measurements Of Pollution In The Troposphere) instruments confirm this seasonality. Ground-based FTIR (Fourier transform infrared) measurements provide useful complementary information due to good sensitivity in the boundary layer. In situ surface measurements of CO volume mixing ratios at the Paris and Jungfraujoch sites reveal a time lag of the near-surface seasonal variability of about 2 months with respect to the total column variability at the same sites. The chemical transport model GEOS-Chem (Goddard Earth Observing System chemical transport model) is employed to interpret our observations. GEOS-Chem sensitivity runs identify the emission sources influencing the seasonal variation of CO. At both Paris and Jungfraujoch, the surface seasonality is mainly driven by anthropogenic emissions, while the total column seasonality is also controlled by air masses transported from distant sources. At Wollongong, where the CO seasonality is mainly affected by biomass burning, no time shift is observed between surface measurements and total column data.

The atmosphere-ocean general circulation models (AOGCMs) used for the IPCC 4th Assessment Report (IPCC AR4) are evaluated for the Greenland ice sheet (GrIS) current climate modelling. The most suited AOGCMs for Greenland climate simulation are then selected on the basis of comparison between the 1970-1999 outputs of the Climate of the twentieth Century experiment (20C3M) and reanalyses (ECMWF, NCEP/NCAR). This comparison indicates that the representation quality of surface parameters such as temperature and precipitation are highly correlated to the atmospheric circulation (500 hPa geopotential height) and its interannual variability (North Atlantic oscillation). The outputs of the three most suitable AOGCMs for present-day climate simulation are then used to assess the changes estimated by three IPCC greenhouse gas emissions scenarios (SRES) over the GrIS for the 2070-2099 period. Future atmospheric circulation changes are projected to dampen the zonal flow, enhance the meridional fluxes and therefore provide additional heat and moisture to the GrIS, increasing temperature over the whole ice sheet and precipitation over its northeastern area. We also show that the GrIS surface mass balance anomalies from the SRES A1B scenario amount to −300 km³/year with respect to the 1970-1999 period, leading to a global sea-level rise of 5 cm by the end of the 21st century. This work can help to select the boundaries conditions for AOGCMs-based downscaled future projections.