10 research outputs found
Modeling the Contributions of Volatile and Char-Bound Nitrogen to the Formation of NO<sub><i>x</i></sub> Species in Iron Ore Rotary Kilns
Given
that more stringent NO<sub><i>x</i></sub> emission
limits are expected in the near future, several industrial processes
are in need of NO<sub><i>x</i></sub> mitigation measures.
The Grate-Kiln process, applied in the iron ore industry, is one such
process. NO<sub><i>x</i></sub> formation is inherently high
in the process, and due to the combustion conditions, several standard
mitigation strategies are impractical. Alternative solutions are thus
needed. The current paper aims at developing a model capable of describing
the NO formation under conditions relevant in iron ore rotary kilns
and to identify governing parameters that may be modified for mitigation
purposes. The developed model uses detailed reaction modeling for
the homogeneous combustion chemistry combined with simpler modeling
with apparent kinetics for the heterogeneous chemistry. The main findings
are that thermal NO is of low significance and that the NO formation
during char combustion is the main contributor to the high NO<sub><i>x</i></sub> emissions. Attempting to control the partitioning
between the volatile nitrogen and the char-bound nitrogen is suggested
as a mitigation strategy, since the combustion of char is challenging
to control compared to the combustion of volatiles
Influence of Operating Conditions on SO<sub>3</sub> Formation during Air and Oxy-Fuel Combustion
Because SO<sub>3</sub> participates in both high- and
low-temperature
corrosion processes, there is a general concern about the SO<sub>3</sub> formation under oxy-fuel fired conditions. This work has the aim
to evaluate the influence of combustion parameters on the formation
of SO<sub>3</sub>. Experiments were conducted in oxy-fuel and air-fired
experiments with propane as fuel and injection of SO<sub>2</sub> in
the oxidizer. The SO<sub>3</sub> concentration was measured with a
controlled condensation method at the furnace outlet as well as in
the flame. The experiments show that the gas-phase is an important
contributor to SO<sub>3</sub> formation and that the SO<sub>3</sub> formation is strong during burnout of the fuel. In oxy-fuel combustion
with wet flue-gas recycle (FGR), more SO<sub>3</sub> was formed than
during dry FGR at similar temperature conditions, which indicates
that H<sub>2</sub>O enhances SO<sub>3</sub> formation. The experiments
also show that the SO<sub>3</sub> formation rises with an increase
in furnace temperature. Because temperature and residence time in
the furnace increases with reduced FGR ratio, the FGR ratio directly
influences the SO<sub>3</sub> formation in oxy-fuel combustion. This
was obvious during the experiments, and the SO<sub>3</sub> concentration
rose with a reduced FGR ratio
Modeling the Nitrogen and Sulfur Chemistry in Pressurized Flue Gas Systems
A rate-based
model is developed to elucidate the chemistry behind
the simultaneous absorption of NO<sub><i>x</i></sub> and
SO<sub><i>x</i></sub> under pressurized conditions (pressures
up to 30 bar) that are applicable to the flue gases obtained from
CO<sub>2</sub> capture systems. The studied flue gas conditions are
relevant to oxy-fuel and chemical-looping combustion systems. The
kinetics of the reactions implemented in the model is based on a thorough
review of the literature. The chemistry of nitrogen, sulfur, and N–S
interactions are evaluated in detail, and the most important reaction
pathways are discussed. The effects of pH, pressure, and flue-gas
composition on the liquid-phase chemistry are also examined and discussed.
Simulations that use existing kinetic data reveal that the pH level
has a strong influence on the reaction pathway that is followed and
the types of products that are formed in the liquid phase. In addition,
the pressure level and the presence of NO<sub><i>x</i></sub> significantly affect the removal of SO<sub>2</sub> from the flue
gas
Characteristic scale of response for <i>Elater ferrugineus</i> using two models.
<p>i) Pooled density of trees within the groups <i>Quercus</i>, Noble 1 and Noble 2, and ii) density of <i>Quercus</i> only. The grey line indicates p<0.05, corresponding to Wald value 3.9.</p
Maps of predicted occurrence of <i>Elater ferrugineus.</i>
<p>The maps show >25%, >50%, >75% and >90% probability of occurrence in the study area (<b>a,b,c,d</b>) and in the county of Östergötland (<b>e,f</b>) and the trap capture. Empty traps are presented by crosses (×) while occupied traps are marked with open circles (Ο) which size is proportional to the number of individuals caught. The first column (<b>a,c,e</b>) shows predictions based on models including the pooled density of trees within the groups <i>Quercus</i>, Noble 1 and Noble 2, while the second column (<b>b,d,f</b>) shows predictions based on models including the density of <i>Quercus</i> only. (<b>a,b</b>) shows trap captures in systematically placed traps, (<b>c,d</b>) the strategically sampled validation data and (<b>e,f</b>) the validation data set sampled in the entire Östergötland. In each map, the predictions are based on two models, one for each characteristic scales of response (blue tones represent a smaller scale: 433 m (pooled density of <i>Quercus</i>, Noble 1 and Noble 2) and 327 m (density of <i>Quercus</i> only), while orange tones represent prediction at larger scale: 4051 m (<i>Quercus</i>, Noble 1 and Noble 2) and 4658 m (<i>Quercus</i>).</p
The relationships between occurrence of <i>Elater ferrugineus</i> and density of trees in different hollow classes.
<p>The relationships are expressed as Wald-values from 63 simple binomial GLMs. The explanatory variable ‘tree density’ is measured at 31 different spatial scales and includs trees from three different tree hollow classes: hollow trees ≥1 m dbh, hollow trees <1 m dbh and non-hollow trees. All models showed positive relationship between probability of occurrence and tree density. The grey line indicates p<0.05, corresponding to Wald value 3.9.</p
Categorization of trees in the study.
<p>Deciduous trees in the study area (49.4 km × 49.4 km) categorized according to the six tree groups and three tree hollow groups: ‘hollow’, which were then divided into two groups according to the diameter at breast height (dbh), and ‘non-hollow’ >0.70 m dbh.</p
Tree density required for 25%, 50% 75% and 90% probability of occurrence of <i>Elater ferrugineus</i>, for two candidate models and for two characteristic scales of response.
<p>Tree density required for 25%, 50% 75% and 90% probability of occurrence of <i>Elater ferrugineus</i>, for two candidate models and for two characteristic scales of response.</p
Trap locations in the county of Östergötland.
<p>(<b>a</b>) Trap location for systematically placed traps. Dots (•) represent occurrence of <i>E. ferrugineus</i> and crosses (×) represent non-occurrences. Thin lines delimit municipalities. (<b>b</b>) Trap locations of the two validation data sets. Filled circles (•) represent the strategic data set, sampled within the present study area and open circles (○) represent the Östergötland data set. Distributions of deciduous trees are marked in grey.</p
Correlation between the densities of tree groups that explained the occurrence of <i>Elater ferrugineus</i>.
<p>Correlation between the densities of tree groups that explained the occurrence of <i>Elater ferrugineus</i>.</p