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Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice-nucleating particles. However, an intercomparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques.
Within the framework of INUIT (Ice Nuclei Research Unit), we distributed an illite-rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature (T), cooling rate and nucleation time. A total of 17 measurement methods were involved in the data intercomparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while 10 other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing data set was evaluated using the ice nucleation active surface-site density, ns, to develop a representative ns(T) spectrum that spans a wide temperature range (−37 °C < T < −11 °C) and covers 9 orders of magnitude in ns.
In general, the 17 immersion freezing measurement techniques deviate, within a range of about 8 °C in terms of temperature, by 3 orders of magnitude with respect to ns. In addition, we show evidence that the immersion freezing efficiency expressed in ns of illite NX particles is relatively independent of droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature dependence and weak time and size dependence of the immersion freezing efficiency of illite-rich clay mineral particles enabled the ns parameterization solely as a function of temperature. We also characterized the ns(T) spectra and identified a section with a steep slope between −20 and −27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 °C. While the agreement between different instruments was reasonable below ~ −27 °C, there seemed to be a different trend in the temperature-dependent ice nucleation activity from the suspension and dry-dispersed particle measurements for this mineral dust, in particular at higher temperatures. For instance, the ice nucleation activity expressed in ns was smaller for the average of the wet suspended samples and higher for the average of the dry-dispersed aerosol samples between about −27 and −18 °C. Only instruments making measurements with wet suspended samples were able to measure ice nucleation above −18 °C. A possible explanation for the deviation between −27 and −18 °C is discussed. Multiple exponential distribution fits in both linear and log space for both specific surface area-based ns(T) and geometric surface area-based ns(T) are provided. These new fits, constrained by using identical reference samples, will help to compare IN measurement methods that are not included in the present study and IN data from future IN instruments.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global historical irrigation data set (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arcmin resolution. We collected sub-national irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining sub-national irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to sub-national irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land as shown on historical maps for the western United States (around year 1900) and on a global map (around year 1960). Mean aridity on irrigated land increased and mean natural river discharge on irrigated land decreased from 1900 to 1950 whereas aridity decreased and river discharge remained approximately constant from 1950 to 2005. The data set and its documentation are made available in an open-data repository at https://mygeohub.org/publications/8 (doi:10.13019/M20599).
We present the characterization and application of a new gas chromatography time-of-flight mass spectrometry instrument (GC-TOFMS) for the quantitative analysis of halocarbons in air samples. The setup comprises three fundamental enhancements compared to our earlier work (Hoker et al., 2015): (1) full automation, (2) a mass resolving power R = m/Δm of the TOFMS (Tofwerk AG, Switzerland) increased up to 4000 and (3) a fully accessible data format of the mass spectrometric data. Automation in combination with the accessible data allowed an in-depth characterization of the instrument. Mass accuracy was found to be approximately 5 ppm in mean after automatic recalibration of the mass axis in each measurement. A TOFMS configuration giving R = 3500 was chosen to provide an R-to-sensitivity ratio suitable for our purpose. Calculated detection limits are as low as a few femtograms by means of the accurate mass information. The precision for substance quantification was 0.15 % at the best for an individual measurement and in general mainly determined by the signal-to-noise ratio of the chromatographic peak. Detector non-linearity was found to be insignificant up to a mixing ratio of roughly 150 ppt at 0.5 L sampled volume. At higher concentrations, non-linearities of a few percent were observed (precision level: 0.2 %) but could be attributed to a potential source within the detection system. A straightforward correction for those non-linearities was applied in data processing, again by exploiting the accurate mass information. Based on the overall characterization results, the GC-TOFMS instrument was found to be very well suited for the task of quantitative halocarbon trace gas observation and a big step forward compared to scanning, quadrupole MS with low mass resolving power and a TOFMS technique reported to be non-linear and restricted by a small dynamical range.
The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.
This study examines the urban heat island (UHI) of Brussels, for both current (2000–2009) and projected future (2060–2069) climate conditions, by employing very high resolution (250 m) modelling experiments, using the urban boundary layer climate model UrbClim. Meteorological parameters that are related to the intensity of the UHI are identified and it is investigated how these parameters and the magnitude of the UHI evolve for two plausible trajectories for future climate conditions. UHI intensity is found to be strongly correlated to the inversion strength in the lowest 100 m of the atmosphere. The results for the future scenarios indicate that the magnitude of the UHI is expected to decrease slightly due to global warming. This can be attributed to the increased incoming longwave radiation, caused by higher air temperature and humidity values. The presence of the UHI also has a significant impact on the frequency of extreme temperature events in the city area, both in present and future climates, and exacerbates the impact of climate change on the urban population as the amount of heat wave days in the city increases twice as fast as in the rural surroundings.
Knowledge about mass discrimination effects in a chemical ionization mass spectrometer (CIMS) is crucial for quantifying, e.g., the recently discovered extremely low volatile organic compounds (ELVOCs) and other compounds for which no calibration standard exists so far. Here, we present a simple way of estimating mass discrimination effects of a nitrate-based chemical ionization atmospheric pressure interface time-of-flight (CI-APi-TOF) mass spectrometer. Characterization of the mass discrimination is achieved by adding different perfluorinated acids to the mass spectrometer in amounts sufficient to deplete the primary ions significantly. The relative transmission efficiency can then be determined by comparing the decrease of signals from the primary ions and the increase of signals from the perfluorinated acids at higher masses. This method is in use already for PTR-MS; however, its application to a CI-APi-TOF brings additional difficulties, namely clustering and fragmentation of the measured compounds, which can be treated with statistical analysis of the measured data, leading to self-consistent results. We also compare this method to a transmission estimation obtained with a setup using an electrospray ion source, a high-resolution differential mobility analyzer and an electrometer, which estimates the transmission of the instrument without the CI source. Both methods give different transmission curves, indicating non-negligible mass discrimination effects of the CI source. The absolute transmission of the instrument without the CI source was estimated with the HR-DMA method to plateau between the m∕z range of 127 and 568 Th at around 1.5 %; however, for the CI source included, the depletion method showed a steady increase in relative transmission efficiency from the m∕z range of the primary ion (mainly at 62 Th) to around 550 Th by a factor of around 5. The main advantages of the depletion method are that the instrument is used in the same operation mode as during standard measurements and no knowledge of the absolute amount of the measured substance is necessary, which results in a simple setup.
Background: Despite its largely mountainous terrain for which this Himalayan country is a popular tourist destination, Nepal is now endemic for five major vector-borne diseases (VBDs), namely malaria, lymphatic filariasis, Japanese encephalitis, visceral leishmaniasis and dengue fever. There is increasing evidence about the impacts of climate change on VBDs especially in tropical highlands and temperate regions. Our aim is to explore whether the observed spatiotemporal distributions of VBDs in Nepal can be related to climate change.
Methodology: A systematic literature search was performed and summarized information on climate change and the spatiotemporal distribution of VBDs in Nepal from the published literature until December 2014 following providing items for systematic review and meta-analysis (PRISMA) guidelines.
Principal findings: We found 12 studies that analysed the trend of climatic data and are relevant for the study of VBDs, 38 studies that dealt with the spatial and temporal distribution of disease vectors and disease transmission. Among 38 studies, only eight studies assessed the association of VBDs with climatic variables. Our review highlights a pronounced warming in the mountains and an expansion of autochthonous cases of VBDs to non-endemic areas including mountain regions (i.e., at least 2,000 m above sea level). Furthermore, significant relationships between climatic variables and VBDs and their vectors are found in short-term studies.
Conclusion: Taking into account the weak health care systems and difficult geographic terrain of Nepal, increasing trade and movements of people, a lack of vector control interventions, observed relationships between climatic variables and VBDs and their vectors and the establishment of relevant disease vectors already at least 2,000 m above sea level, we conclude that climate change can intensify the risk of VBD epidemics in the mountain regions of Nepal if other non-climatic drivers of VBDs remain constant.
We present the application of time-of-flight mass spectrometry (TOF MS) for the analysis of halocarbons in the atmosphere after cryogenic sample preconcentration and gas chromatographic separation. For the described field of application, the quadrupole mass spectrometer (QP MS) is a state-of-the-art detector. This work aims at comparing two commercially available instruments, a QP MS and a TOF MS, with respect to mass resolution, mass accuracy, stability of the mass axis and instrument sensitivity, detector sensitivity, measurement precision and detector linearity. Both mass spectrometers are operated on the same gas chromatographic system by splitting the column effluent to both detectors. The QP MS had to be operated in optimised single ion monitoring (SIM) mode to achieve a sensitivity which could compete with the TOF MS. The TOF MS provided full mass range information in any acquired mass spectrum without losing sensitivity. Whilst the QP MS showed the performance already achieved in earlier tests, the sensitivity of the TOF MS was on average higher than that of the QP MS in the "operational" SIM mode by a factor of up to 3, reaching detection limits of less than 0.2 pg. Measurement precision determined for the whole analytical system was up to 0.2% depending on substance and sampled volume. The TOF MS instrument used for this study displayed significant non-linearities of up to 10% for two-thirds of all analysed substances.