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The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates. It has been assumed that a better understanding of the effects of anthropogenic aerosols will greatly reduce the large uncertainties associated with our predictions of the radiative forcing effects of aerosols on climate; however, this study shows that nearly half of the uncertainty in the radiative effect of aerosols on clouds derives from uncertainties in pre-industrial natural aerosols. Natural versus anthropogenic aerosols in climate forcing Firmly establishing the influence of aerosols on cloud albedo — their forcing effect on climate in essence — is one of the greatest challenges of modern climate science. It is often tacitly assumed that the continued high uncertainties are linked mainly to anthropogenic emissions. In other words, if the anthropogenic effects could be better understood, so would the overall effect. Now Ken Carslaw and colleagues present an analysis of 28 parameters representing aerosol and precursor gas emissions and other factors that could influence cloud brightness. They find that only 34 per cent of the variance in aerosol forcing since pre-industrial times (around 1750) is associated with anthropogenic emissions, with 45 per cent of the variance linked to natural emissions of volcanic sulphur dioxide, marine dimethylsulphide and other natural sources. This work casts doubts on the degree of progress that can be made solely through advances in the understanding of anthropogenic aerosols and suggests that we need to discover more about the workings of the pre-industrial environment, when natural aerosols were predominant.

Our duty to conserve global natural ecosystems is increasingly in conflict with our need to feed an expanding population. The use of conventional pesticides not only damages the environment and vulnerable biodiversity but can also still fail to prevent crop losses of 20–40% due to pests and pathogens. There is a growing call for more ecologically sustainable pathogen control measures. RNA-based biopesticides offer an eco-friendly alternative to the use of conventional fungicides for crop protection. The genetic modification (GM) of crops remains controversial in many countries, though expression of transgenes inducing pathogen-specific RNA interference (RNAi) has been proven effective against many agronomically important fungal pathogens. The topical application of pathogen-specific RNAi-inducing sprays is a more responsive, GM-free approach to conventional RNAi transgene-based crop protection. The specific targeting of essential pathogen genes, the development of RNAi-nanoparticle carrier spray formulations, and the possible structural modifications to the RNA molecules themselves are crucial to the success of this novel technology. Here, we outline the current understanding of gene silencing pathways in plants and fungi and summarize the pioneering and recent work exploring RNA-based biopesticides for crop protection against fungal pathogens, with a focus on spray-induced gene silencing (SIGS). Further, we discuss factors that could affect the success of RNA-based control strategies, including RNA uptake, stability, amplification, and movement within and between the plant host and pathogen, as well as the cost and design of RNA pesticides.

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN). Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

We use a global aerosol microphysics model in combination with an offline radiative transfer model to quantify the radiative effect of biogenic secondary organic aerosol (SOA) in the present-day atmosphere. Through its role in particle growth and ageing, the presence of biogenic SOA increases the global annual mean concentration of cloud condensation nuclei (CCN; at 0.2% supersaturation) by 3.6–21.1%, depending upon the yield of SOA production from biogenic volatile organic compounds (BVOCs), and the nature and treatment of concurrent primary carbonaceous emissions. This increase in CCN causes a rise in global annual mean cloud droplet number concentration (CDNC) of 1.9–5.2%, and a global mean first aerosol indirect effect (AIE) of between +0.01 W m−2 and −0.12 W m−2. The radiative impact of biogenic SOA is far greater when biogenic oxidation products also contribute to the very early stages of new particle formation; using two organically mediated mechanisms for new particle formation, we simulate global annual mean first AIEs of −0.22 W m−2 and −0.77 W m−2. The inclusion of biogenic SOA substantially improves the simulated seasonal cycle in the concentration of CCN-sized particles observed at three forested sites. The best correlation is found when the organically mediated nucleation mechanisms are applied, suggesting that the first AIE of biogenic SOA could be as large as −0.77 W m−2. The radiative impact of SOA is sensitive to the presence of anthropogenic emissions. Lower background aerosol concentrations simulated with anthropogenic emissions from 1750 give rise to a greater fractional CCN increase and a more substantial first AIE from biogenic SOA. Consequently, the anthropogenic indirect radiative forcing between 1750 and the present day is sensitive to assumptions about the amount and role of biogenic SOA. We also calculate an annual global mean direct radiative effect of between −0.08 W m−2 and −0.78 W m−2 in the present day, with uncertainty in the amount of SOA produced from the oxidation of BVOCs accounting for most of this range.

Long-term exposure to ambient particulate matter (PM2.5, mass of particles with an aerodynamic dry diameter of < 2.5 μm) is a major risk factor to the global burden of disease. Previous studies have focussed on present day or future health burdens attributed to ambient PM2.5. Few studies have estimated changes in PM2.5 and attributable health burdens over the last few decades, a period where air quality has changed rapidly. Here we used the HadGEM3-UKCA coupled chemistry-climate model, integrated exposure-response relationships, demographic and background disease data to provide the first estimate of the changes in global and regional ambient PM2.5 concentrations and attributable health burdens over the period 1960 to 2009. Over this period, global mean population-weighted PM2.5 concentrations increased by 38%, dominated by increases in China and India. Global attributable deaths increased by 89% to 124% over the period 1960 to 2009, dominated by large increases in China and India. Population growth and ageing contributed mostly to the increases in attributable deaths in China and India, highlighting the importance of demographic trends. In contrast, decreasing PM2.5 concentrations and background disease dominated the reduction in attributable health burden in Europe and the United States. Our results shed light on how future projected trends in demographics and uncertainty in the exposure-response relationship may provide challenges for future air quality policy in Asia.

The budget of atmospheric secondary organic aerosol (SOA) is very uncertain, with recent estimates suggesting a global source of between 12 and 1820 Tg (SOA) a−1. We used a dataset of aerosol mass spectrometer (AMS) observations from 34 different surface locations to evaluate the GLOMAP global chemical transport model. The standard model simulation (which included SOA from monoterpenes only) underpredicted organic aerosol (OA) observed by the AMS and had little skill reproducing the variability in the dataset. We simulated SOA formation from biogenic (monoterpenes and isoprene), lumped anthropogenic and lumped biomass burning volatile organic compounds (VOCs) and varied the SOA yield from each precursor source to produce the best overall match between model and observations. We assumed that SOA is essentially non-volatile and condenses irreversibly onto existing aerosol. Our best estimate of the SOA source is 140 Tg (SOA) a−1 but with a large uncertainty range which we estimate to be 50–380 Tg (SOA) a−1. We found the minimum in normalised mean error (NME) between model and the AMS dataset when we assumed a large SOA source (100 Tg (SOA) a−1) from sources that spatially matched anthropogenic pollution (which we term antropogenically controlled SOA). We used organic carbon observations compiled by Bahadur et al. (2009) to evaluate our estimated SOA sources. We found that the model with a large anthropogenic SOA source was the most consistent with these observations, however improvement over the model with a large biogenic SOA source (250 Tg (SOA) a−1) was small. We used a dataset of 14C observations from rural locations to evaluate our estimated SOA sources. We estimated a maximum of 10 Tg (SOA) a−1 (10 %) of the anthropogenically controlled SOA source could be from fossil (urban/industrial) sources. We suggest that an additional anthropogenic source is most likely due to an anthropogenic pollution enhancement of SOA formation from biogenic VOCs. Such an anthropogenically controlled SOA source would result in substantial climate forcing. We estimated a global mean aerosol direct effect of −0.26 ± 0.15 Wm−2 and indirect (cloud albedo) effect of −0.6+0.24−0.14 Wm−2 from anthropogenically controlled SOA. The biogenic and biomass SOA sources are not well constrained with this analysis due to the limited number of OA observations in regions and periods strongly impacted by these sources. To further improve the constraints by this method, additional OA observations are needed in the tropics and the Southern Hemisphere.

The Hadley Centre Global Environmental Model (HadGEM) includes two aerosol schemes: the Coupled Large-scale Aerosol Simulator for Studies in Climate (CLASSIC), and the new Global Model of Aerosol Processes (GLOMAP-mode). GLOMAP-mode is a modal aerosol microphysics scheme that simulates not only aerosol mass but also aerosol number, represents internally-mixed particles, and includes aerosol microphysical processes such as nucleation. In this study, both schemes provide hindcast simulations of natural and anthropogenic aerosol species for the period 2000–2006. HadGEM simulations of the aerosol optical depth using GLOMAP-mode compare better than CLASSIC against a data-assimilated aerosol re-analysis and aerosol ground-based observations. Because of differences in wet deposition rates, GLOMAP-mode sulphate aerosol residence time is two days longer than CLASSIC sulphate aerosols, whereas black carbon residence time is much shorter. As a result, CLASSIC underestimates aerosol optical depths in continental regions of the Northern Hemisphere and likely overestimates absorption in remote regions. Aerosol direct and first indirect radiative forcings are computed from simulations of aerosols with emissions for the year 1850 and 2000. In 1850, GLOMAP-mode predicts lower aerosol optical depths and higher cloud droplet number concentrations than CLASSIC. Consequently, simulated clouds are much less susceptible to natural and anthropogenic aerosol changes when the microphysical scheme is used. In particular, the response of cloud condensation nuclei to an increase in dimethyl sulphide emissions becomes a factor of four smaller. The combined effect of different 1850 baselines, residence times, and abilities to affect cloud droplet number, leads to substantial differences in the aerosol forcings simulated by the two schemes. GLOMAP-mode finds a present-day direct aerosol forcing of −0.49 W m−2 on a global average, 72% stronger than the corresponding forcing from CLASSIC. This difference is compensated by changes in first indirect aerosol forcing: the forcing of −1.17 W m−2 obtained with GLOMAP-mode is 20% weaker than with CLASSIC. Results suggest that mass-based schemes such as CLASSIC lack the necessary sophistication to provide realistic input to aerosol-cloud interaction schemes. Furthermore, the importance of the 1850 baseline highlights how model skill in predicting present-day aerosol does not guarantee reliable forcing estimates. Those findings suggest that the more complex representation of aerosol processes in microphysical schemes improves the fidelity of simulated aerosol forcings.

Substantial changes in anthropogenic aerosols and precursor gas emissions have occurred over recent decades due to the implementation of air pollution control legislation and economic growth. The response of atmospheric aerosols to these changes and the impact on climate are poorly constrained, particularly in studies using detailed aerosol chemistry–climate models. Here we compare the HadGEM3-UKCA (Hadley Centre Global Environment Model-United Kingdom Chemistry and Aerosols) coupled chemistry–climate model for the period 1960–2009 against extensive ground-based observations of sulfate aerosol mass (1978–2009), total suspended particle matter (SPM, 1978–1998), PM10 (1997–2009), aerosol optical depth (AOD, 2000–2009), aerosol size distributions (2008–2009) and surface solar radiation (SSR, 1960–2009) over Europe. The model underestimates observed sulfate aerosol mass (normalised mean bias factor (NMBF) = −0.4), SPM (NMBF = −0.9), PM10 (NMBF = −0.2), aerosol number concentrations (N30 NMBF = −0.85; N50 NMBF = −0.65; and N100 NMBF = −0.96) and AOD (NMBF = −0.01) but slightly overpredicts SSR (NMBF = 0.02). Trends in aerosol over the observational period are well simulated by the model, with observed (simulated) changes in sulfate of −68 % (−78 %), SPM of −42 % (−20 %), PM10 of −9 % (−8 %) and AOD of −11 % (−14 %). Discrepancies in the magnitude of simulated aerosol mass do not affect the ability of the model to reproduce the observed SSR trends. The positive change in observed European SSR (5 %) during 1990–2009 (\"brightening\") is better reproduced by the model when aerosol radiative effects (ARE) are included (3 %), compared to simulations where ARE are excluded (0.2 %). The simulated top-of-the-atmosphere aerosol radiative forcing over Europe under all-sky conditions increased by > 3.0 W m−2 during the period 1970–2009 in response to changes in anthropogenic emissions and aerosol concentrations.

Observations and models have shown that continuously degassing volcanoes have a potentially large effect on the natural background aerosol loading and the radiative state of the atmosphere. We use a global aerosol microphysics model to quantify the impact of these volcanic emissions on the cloud albedo radiative forcing under pre-industrial (PI) and present-day (PD) conditions. We find that volcanic degassing increases global annual mean cloud droplet number concentrations by 40% under PI conditions, but by only 10% under PD conditions. Consequently, volcanic degassing causes a global annual mean cloud albedo effect of −1.06 W m−2 in the PI era but only −0.56 W m−2 in the PD era. This non-equal effect is explained partly by the lower background aerosol concentrations in the PI era, but also because more aerosol particles are produced per unit of volcanic sulphur emission in the PI atmosphere. The higher sensitivity of the PI atmosphere to volcanic emissions has an important consequence for the anthropogenic cloud radiative forcing because the large uncertainty in volcanic emissions translates into an uncertainty in the PI baseline cloud radiative state. Assuming a −50/+100% uncertainty range in the volcanic sulphur flux, we estimate the annual mean anthropogenic cloud albedo forcing to lie between −1.16 W m−2 and −0.86 W m−2. Therefore, the volcanically induced uncertainty in the PI baseline cloud radiative state substantially adds to the already large uncertainty in the magnitude of the indirect radiative forcing of climate.