Bioaerosols are relevant for public health and may play an important role in the climate system, but their atmospheric abundance, properties, and sources are not well understood. Here we show that the concentration of airborne biological particles in a North American forest ecosystem increases significantly during rain and that bioparticles are closely correlated with atmospheric ice nuclei (IN). The greatest increase of bioparticles and IN occurred in the size range of 2–6 μm, which is characteristic for bacterial aggregates and fungal spores. By DNA analysis we found high diversities of airborne bacteria and fungi, including groups containing human and plant pathogens (mildew, smut and rust fungi, molds, Enterobacteriaceae, Pseudomonadaceae). In addition to detecting known bacterial and fungal IN (Pseudomonas sp., Fusarium sporotrichioides), we discovered two species of IN-active fungi that were not previously known as biological ice nucleators (Isaria farinosa and Acremonium implicatum). Our findings suggest that atmospheric bioaerosols, IN, and rainfall are more tightly coupled than previously assumed.

Global-scale atmosphere monitoring by in-service aircraft - current achievements and future prospects of the European Research Infrastructure IAGOS

Organic matter frequently represents the single largest fraction of fine particulates in urban environments and yet the exact contributions from different sources and processes remain uncertain, owing in part to its substantial chemical complexity. Positive Matrix Factorisation (PMF) has recently proved to be a powerful tool for the purposes of source attribution and profiling when applied to ambient organic aerosol data from the Aerodyne Aerosol Mass Spectrometer (AMS). Here we present PMF analysis applied to AMS data from UK cities for the first time. Three datasets are analysed, with the focus on objectivity and consistency. The data were collected in London during the Regent's Park and Tower Environmental Experiment (REPARTEE) intensives and Manchester. These occurred during the autumn and wintertime, such that the primary fraction would be prominent. Ambiguities associated with rotationality within sets of potential solutions are explored and the most appropriate solution sets selected based on comparisons with external data. In addition to secondary organic aerosols, three candidate sources of primary organic aerosol (POA) were identified according to mass spectral and diurnal profiles; traffic emissions, cooking and solid fuel burning (for space heating). Traffic represented, on average, 40% of POA during colder conditions and exhibited a hydrocarbon-like mass spectrum similar to those previously reported. Cooking aerosols represented 34% of POA and through laboratory work, their profile was matched with that sampled from the heating of seed oils, rather than previously-published spectra derived from charbroiling. This suggests that in these locations, oil from frying may have contributed more to the particulate than the meat itself. Solid fuel aerosols represented 26% of POA during cold weather conditions but were not discernable during the first REPARTEE campaign, when conditions were warmer than the other campaigns. This factor showed features associated with biomass burning and occurred mainly at night. Grid-scale emission factors of the combustion aerosols suitable for use in chemical transport models were derived relative to CO and NO_x. The traffic aerosols were found to be 20.5 μg m⁻³ ppm⁻¹ relative to CO for Manchester and 31.6 μg m⁻³ ppm⁻¹ relative to NO_x for London. Solid fuel emissions were derived as 24.7 μg m⁻³ ppm⁻¹ relative to CO for Manchester. These correspond to mass emission ratios of 0.018, 0.026 (as NO) and 0.021 respectively and are of a similar order to previously published estimates, derived from other regions or using other approaches.

We present results of experiments at the aerosol interactions and dynamics in the atmosphere (AIDA) chamber facility looking at the freezing of water by three different types of mineral particles at temperatures between −12°C and −33°C. The three different dusts are Asia Dust-1 (AD1), Sahara Dust-2 (SD2) and Arizona test Dust (ATD). The dust samples used had particle concentrations of sizes that were log-normally distributed with mode diameters between 0.3 and 0.5 μm and standard deviations, σ_g, of 1.6–1.9. The results from the freezing experiments are consistent with the singular hypothesis of ice nucleation. The dusts showed different nucleation abilities, with ATD showing a rather sharp increase in ice-active surface site density at temperatures less than −24°C. AD1 was the next most efficient freezing nuclei and showed a more gradual increase in activity than the ATD sample. SD2 was the least active freezing nuclei. We used data taken with particle counting probes to derive the ice-active surface site density forming on the dust as a function of temperature for each of the three samples and polynomial curves are fitted to this data. The curve fits are then used independently within a bin microphysical model to simulate the ice formation rates from the experiments in order to test the validity of parameterising the data with smooth curves. Good agreement is found between the measurements and the model for AD1 and SD2; however, the curve for ATD does not yield results that agree well with the observations. The reason for this is that more experiments between −20 and −24°C are needed to quantify the rather sharp increase in ice-active surface site density on ATD in this temperature regime. The curves presented can be used as parameterisations in atmospheric cloud models where cooling rates of approximately 1°C min⁻¹ or more are present to predict the concentration of ice crystals forming by the condensation-freezing mode of ice nucleation. Finally a polynomial is fitted to all three samples together in order to have a parameterisation describing the average ice-active surface site density vs. temperature for an equal mixture of the three dust samples.

Evidence shows the importance of food systems for sustainable development: they are at the nexus that links food security, nutrition, and human health, the viability of ecosystems, climate change, and social justice. However, agricultural policies tend to focus on food supply, and sometimes, on mechanisms to address negative externalities. We propose an alternative. Our starting point is that agriculture and food systems’ policies should be aligned to the 2030 Agenda for Sustainable Development. This calls for deep changes in comparison with the paradigms that prevailed when steering the agricultural change in the XXth century. We identify the comprehensive food systems transformation that is needed. It has four parts: first, food systems should enable all people to benefit from nutritious and healthy food. Second, they should reflect sustainable agricultural production and food value chains. Third, they should mitigate climate change and build resilience. Fourth, they should encourage a renaissance of rural territories. The implementation of the transformation relies on (i) suitable metrics to aid decision-making, (ii) synergy of policies through convergence of local and global priorities, and (iii) enhancement of development approaches that focus on territories. We build on the work of the “Milano Group,” an informal group of experts convened by the UN Secretary General in Milan in 2015. Backed by a literature review, what emerges is a strategic narrative linking climate, agriculture and food, and calling for a deep transformation of food systems at scale. This is critical for achieving the Sustainable Development Goals and the Paris Agreement. The narrative highlights the needed consistency between global actions for sustainable development and numerous local-level innovations. It emphasizes the challenge of designing differentiated paths for food systems transformation responding to local and national expectations. Scientific and operational challenges are associated with the alignment and arbitration of local action within the context of global priorities.