A. Rob MacKenzie
University of Birmingham
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Publication
Featured researches published by A. Rob MacKenzie.
New Phytologist | 2016
Richard J. Norby; Martin G. De Kauwe; Tomas F. Domingues; Remko A. Duursma; David S. Ellsworth; Daniel Goll; David M. Lapola; Kristina A. Luus; A. Rob MacKenzie; Belinda E. Medlyn; Ryan Pavlick; Anja Rammig; Benjamin Smith; Rick M. Thomas; Kirsten Thonicke; Anthony P. Walker; Sönke Zaehle
The first generation of forest free-air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.
Journal of Geophysical Research | 2017
Phillip J. Blaen; Kieran Khamis; Charlotte E M Lloyd; Sophie Comer‐Warner; Francesco Ciocca; Rick M. Thomas; A. Rob MacKenzie; Stefan Krause
Storm events can drive highly variable behaviour in catchment nutrient and water fluxes, yet short-term event dynamics are frequently missed by low resolution sampling regimes. In addition, nutrient source zone contributions can vary significantly within and between storm events. Our inability to identify and characterise time-dynamic source zone contributions severely hampers the adequate design of land-use management practices in order to control nutrient exports from agricultural landscapes. Here, we utilise an 8-month high-frequency (hourly) time series of streamflow, nitrate (NO3-N), dissolved organic carbon (DOC), and hydroclimatic variables for a headwater agricultural catchment. We identified 29 distinct storm events across the monitoring period. These events represented 31% of the time series and contributed disproportionately to nutrient loads (42% of NO3-N and 43% of DOC) relative to their duration. Regression analysis identified a small subset of hydroclimatological variables (notably precipitation intensity and antecedent conditions) as key drivers of nutrient dynamics during storm events. Hysteresis analysis of nutrient concentration-discharge relationships highlighted the dynamic activation of discrete NO3-N and DOC source zones, which varied on an event-specific basis. Our results highlight the benefits of high-frequency in situ monitoring for characterising short-term nutrient fluxes and unravelling connections between hydroclimatological variability and river nutrient export and source zone activation under extreme flow conditions. These new process-based insights, which we summarise in a conceptual model, are fundamental to underpinning targeted management measures to reduce nutrient loading of surface waters.
Environmental Pollution | 2018
Jian Zhong; Irina Nikolova; Xiaoming Cai; A. Rob MacKenzie; Roy M. Harrison
This study implements a two-box model coupled with ultrafine particle (UFP) multicomponent microphysics for a compartmentalised street canyon. Canyon compartmentalisation can be described parsimoniously by three parameters relating to the features of the canyon and the atmospheric state outside the canyon, i.e. the heterogeneity coefficient, the vortex-to-vortex exchange velocity, and the box height ratio. The quasi-steady solutions for the two compartments represent a balance among emissions, microphysical aerosol dynamics (i.e. evaporation/condensation of semi-volatiles, SVOCs), and exchange processes, none of which is negligible. This coupled two-box model can capture significant contrasts in UFP number concentrations and a measure of the volatility of the multi-SVOC-particles in the lower and upper canyon. Modelled ground-level UFP number concentrations vary across nucleation, Aitken, and accumulation particle modes as well-defined monotonic functions of canyon compartmentalisation parameters. Compared with the two-box model, a classic one-box model (without canyon compartmentalisation) leads to underestimation of UFP number concentrations by several tens of percent typically. By quantifying the effects of canyon compartmentalisation, this study provides a framework for understanding how canyon geometry and the presence of street trees, street furniture, and architectural features interact with the large-scale atmospheric flow to determine ground-level pollutant concentrations.
Atmospheric Chemistry and Physics | 2018
Irina Nikolova; Xiaoming Cai; Mohammed S. Alam; Soheil Zeraati-Rezaei; Jian Zhong; A. Rob MacKenzie; Roy M. Harrison
Abstract. A recent study demonstrated that diesel particles in urban air undergo evaporative shrinkage when advected to a cleaner atmosphere (Harrison et al., 2016). We explore, in a structured and systematic way, the sensitivity of nucleation-mode diesel particles to changes in particle composition and saturation vapour pressure. We use a multi-component aerosol microphysics model based on surrogate molecule (C 16 -C 32 n-alkane) volatilities. For standard atmospheric conditions (298 K, 1013.25 hPa), and over timescales (ca. 100 s) relevant for dispersion on the neighbourhood scale (up to 1 km), the choice of a particular vapour pressure dataset changes the range of compounds that are appreciably volatile by 2–6 carbon numbers. The nucleation-mode peak diameter, after 100 s of model runtime, is sensitive to the vapour pressure parameterisations for particles with compositions centred on surrogate molecules between C 22 H 46 and C 24 H 50 . The vapour pressures of components in this range are therefore critical for the modelling of nucleation-mode aerosol dynamics on the neighbourhood scale and need to be better constrained. Laboratory studies have shown this carbon number fraction to derive predominantly from engine lubricating oil. The accuracy of vapour pressure data for other (more and less volatile) components from laboratory experiments, is less critical. The influence of a core of involatile material is also considered. The new findings of this study may also be used to identify the Semi-Volatile Organic Compound (SVOC) compositions that play dominating roles in the evaporative shrinkage of the nucleation mode observed in field measurements (e.g. Dall’Osto et al., 2011). As well as reconciling model and observations, identifying the most significant vapour pressure regime for nucleation-mode dynamics offers a way to improve the computing efficiency of urban aerosol models by adopting simplified schemes for those less important components: e.g., an equilibrium scheme for low-carbon-number components and a linear scheme for high-carbon-number components.
Bulletin of the American Meteorological Society | 2017
Rick M. Thomas; A. Rob MacKenzie; S. James Reynolds; Jonathan P. Sadler; Ford Cropley; Simon Bell; Stephen J. Dugdale; Lee Chapman; Andrew Quinn; Xiaoming Cai
AbstractThe increasing miniaturization of accurate, reliable meteorological sensors and logging systems allows the deployment of sensor packages on lightweight airborne platforms. Here, we demonstr...
Sustainability | 2012
Dexter Hunt; D. Rachel Lombardi; Stuart Atkinson; Austin R. G. Barber; Matthew Barnes; Christopher T. Boyko; Julie Brown; John Bryson; David Butler; Silvio Caputo; Maria Caserio; Richard Coles; Rachel Cooper; Raziyeh Farmani; Mark Gaterell; James Hale; Chantal Hales; C. Nicholas Hewitt; Lubo Jankovic; I. Jefferson; Joanne M. Leach; A. Rob MacKenzie; Fayyaz A. Memon; Jon Sadler; Carina Weingaertner; J. Duncan Whyatt; C. D. F. Rogers
Sustainability | 2015
James D. Hale; Thomas A. M. Pugh; Jon P. Sadler; Christopher T. Boyko; Julie Brown; Silvio Caputo; Maria Caserio; Richard Coles; Raziyeh Farmani; Chantal Hales; Russell Horsey; Dexter Hunt; Joanne M. Leach; C. D. F. Rogers; A. Rob MacKenzie
Faraday Discussions | 2016
Irina Nikolova; A. Rob MacKenzie; Xiaoming Cai; Mohammed S. Alam; Roy M. Harrison
Journal of Geophysical Research | 2017
Phillip J. Blaen; Kieran Khamis; Charlotte E M Lloyd; Sophie Comer‐Warner; Francesco Ciocca; Rick M. Thomas; A. Rob MacKenzie; Stefan Krause
Atmospheric Measurement Techniques | 2018
Mohammed S. Alam; Soheil Zeraati-Rezaei; Zhirong Liang; Christopher Stark; Hongming Xu; A. Rob MacKenzie; Roy M. Harrison