Air Time Series Research Articles

Temperature Prediction for Reheating Furnace by Gated Recurrent Unit Approach

Reheating furnaces are used to homogeneously reheat the steel stock (Billets, blooms or slabs) at a temperature between 1000°C and 1250°C before hot rolling. Supply of accurate, stable, and reliable control of temperature is most important for reheating furnaces in hot-rolled steel production. The phenomenon of large time lags in temperature is an arduous problem that existed in the combustion system of furnaces, it causes control system big overshoot, continuous oscillation, and may even make the system unstable. In this paper, a prediction model based on gate recurrent unit (GRU) was established to forecast the inside temperature of the furnace by using temperature, fuel, and air time series. Moreover, this paper presents an approach which is combining a prediction model with a feedforward controller that can improve the stability of the temperature control system. Established prediction model of temperatures by collecting data from on-side, and evaluated the model and feedforward performance on the actual reheating furnace. Compared with other dynamic models (recurrent neural network and long short-term memory), the proposed models outperformed by 15.63% and 26.07% on average in terms of the mean absolute error and root mean square error, respectively. Moreover, the proposed control improve traditional PI controller by 33.43% and 19.92% on average in terms of the mean absolute error and root mean square error, respectively. The presented method can be used to reduce the temperature disturbances in the reheating furnaces.

Microbial composition in seasonal time series of free tropospheric air and precipitation reveals community separation

Primary biological aerosols are transported over large distances, are traveling in various media such as dry air masses, clouds or fog, and eventually deposited with dry deposition, especially for larger particles, or precipitation like rain, hail or snow. To investigate relative abundance and diversity of airborne bacterial and fungal communities, samples have been collected with a liquid impinger (Coriolis µ) from the top of Mount Sonnblick (3106 m asl, Austrian Alps) from the respective sources under a temporal aspect over four seasons over the year to include all climatic conditions. Bacterial and fungal samples (16S rRNA and ITS) were sequenced using Illumina MiSeq paired-end sequencing, investigated for relative abundance by qPCR(16S rRNA and 18S rRNA) and ice nucleation activity. Results show that there is no stable free tropospheric air microbial community and air mass origin was different for the four sampling periods which exerted influence on the microbial composition of the atmosphere although a core microbiome could be identified consisting of 61 bacterial OTUs and eight fungal genera. Differentiation between seasons was stronger pronounced in air than in precipitation, with rain being most different and variable of precipitation types, indicating distinct forces driving microbial fate in the air. Microorganisms precipitated with snow, hail or rain or being transported by clouds differ in their species composition from free tropospheric air masses and do not mirror the air community structure. They were more diverse, distinct in composition, 16S:18S ratio and abundance from free-floating PBA. Hence, snow or cloud samples are not suitable proxies for free tropospheric air microbiome composition, since separation processes in aerosolization, transport and scavenging occur. The microbial composition of arriving precipitation or clouds represents only a part of the microbial air composition communities of the cumulative sources of origin. Relative abundance and composition of ice nucleation-active bacteria showed a higher share of relative % reads of known ice nucleation-active bacteria present in all wet phases compared to air. Results propose a separation of IN-active reads with higher shares occurring in precipitation. This study presents the first comparison of free tropospheric bacterial and fungal abundance and diversity in time series of air over several seasons in contrast to various precipitation forms in the free troposphere.

Monte Carlo simulation of the joint non-Gaussian periodically correlated time-series of air temperature and relative humidity

In this paper a numerical stochastic model of the joint non-Gaussian periodically correlated time-series of air temperature and relative humidity is proposed. The model is based on the assumption that real weather processes are periodically correlated random processes with a period equal to 1 day. This assumption takes into account the diurnal variation of real meteorological processes, defined by the day/night alternation. The input parameters of the model (one-dimensional distributions of air temperature and relative humidity and the correlation structure of the joint time-series) are determined from long-term real observations at weather stations. On the basis of simulated trajectories, some statistical properties of rare combinations of air temperature and relative humidity are studied. In the future, the model will be expanded by the addition of a third component, atmospheric pressure, and with a model of this three-element meteorological complex, properties of enthalpy of moist air time-series will be studied.

Characterization of the Thermal Structure inside an Urban Canyon: Field Measurements and Validation of a Simple Model

AbstractThe results of measurement campaigns are analyzed to investigate the thermal structure in an urban canyon and to validate a simplified model simulating the air and surface temperatures from surface energy budgets. Starting from measurements at roof-top level, the model provides time series of air and surface temperatures, as well as surface fluxes. Two campaigns were carried out in summer 2007 and in winter 2008/09 in a street of the city of Trento (Italy). Temperature sensors were placed at various levels near the walls flanking the canyon and on a traffic light in the street center. Furthermore, the atmosphere above the mean roof-top level was monitored by a weather station on top of a tower located nearby. Air temperatures near the walls, being strongly influenced by direct solar radiation, display considerable contrasts between the opposite sides of the canyon. On the other hand, when solar radiation is weak or absent, the temperature field remains mostly homogeneous. Moreover, air temperature inside the canyon is generally higher than above roof level, with larger differences during summertime. Air temperatures from the above street measurements are well simulated by the model in both seasons. Furthermore, the modeled surface temperatures are tested against a dataset of wall surface temperatures from the Advanced Tools for Rational Energy Use Towards Sustainability–Photocatalytic Innovative Coverings Applications for Depollution (ATREUS–PICADA) experiment, and a very good agreement is found. Results suggest that the model is a reliable and convenient tool for simplified assessment of climatic conditions occurring in urban canyons under various weather situations.

Frequency Analysis as a Tool for Assessing Adverse Conditions During a Massive Fish Kill in the St. Lawrence River, Canada

Abstract During the summer of 2001, the largest fish kill in the recorded history of the St. Lawrence River occurred. More than 25,000 dead carp were recovered. Preliminary analyses suggested hydroclimatic factors may have triggered the fish kill. Long time series of hydroclimatic variables were available upstream and downstream from the study area. In order to investigate if hydroclimatic conditions were extreme during the summer of 2001, frequency analyses were performed on time series of air and water temperature, water level, and solar radiation. During this period, the daily maximum water temperature was abnormally high (return period of 47 years) relative to other years. Air temperature was also high (return period of 22 years) and water level was very low (return period of 67 years). Results showed that hydroclimatic forcings were acting at two different time scales. First, short-term extremes are more likely to have direct impacts on ecosystems, such as lethal stress caused by oxygen depletion in shallow areas. Long-term extremes have indirect effects, which are more difficult to detect, such as immunosuppression. These results reiterate the importance of water temperature in aquatic habitat, particularly in the present context of global warming and climate change.

A hydrographic time series station in the Wadden Sea (southern North Sea)

In the tidal inlet between the East Frisian islands of Langeoog and Spiekeroog, southern North Sea, a time-series station was set up in autumn 2002 as part of the research programme BioGeoChemistry of Tidal Flats run by the University of Oldenburg. The purpose of the station is to provide continuous data on physical, biological and chemical parameters. In addition to instruments recording basic hydrographic and meteorological parameters, the time-series station is equipped with acoustic Doppler profilers for measuring surface waves and current profiles. Compact optical spectrometers are being used for spectral measurements of seawater transmission and for daylight reflectance. Additional sensors were installed for measuring oxygen, nutrients and methane in the seawater. The data shall help to quantify the flux of dissolved and suspended matter between the backbarrier tidal flat and the open sea and to characterise the material transformation in the tidal flat area by biogeochemical processes over the tidal cycle. Due to its novel design, operation of the station is also possible during winter and under extreme weather conditions (gales, storm surges, and sea ice) when data sampling with conventional platforms such as research vessels, buoys, or smaller poles could not be performed in the past. In this way, time series of data are obtained, which include events that are most relevant to the evolution of this coastal area. The performance of the station and its equipment are presented with data covering 6 years of operation. Time series of air and water temperature as well as seawater salinity demonstrate the multiyear dynamics of these parameters in the East Frisian Wadden Sea. Hydrographic data collected under specific meteorological conditions such as gales and storm surges exemplify the all-weather capabilities of the station and its value for studying hydrographic processes in the Wadden Sea.

Beryllium‐7 and Lead‐210 in the atmosphere and surface snow over the Greenland ice sheet in the summer of 1989

The concentrations of 7Be and 210Pb were measured in surface air and fresh and aging snow samples from Summit (72°20′N, 38°45′W) and Dye 3 (65°10′N, 44°45′W) Greenland, during June and July 1989. The aerosol concentrations of these radionuclides showed rapid variations at both sites, but were nearly twice as high, on average, at Summit. Concentrations in the 16 fresh snowfall events that were sampled also showed wide variability, but the averages were the same at the two sites. The apparent difference in air‐snow fractionation and the lack of coherence in the concentration in air time series between the two sites indicate previously unsuspected complexity in atmospheric dynamics over the ice sheet. Improved understanding of atmospheric processes, and how the results of those processes are recorded in snow and ice, is crucial for full interpretation of the information about past atmospheric chemistry and climate contained in the snow and ice of glaciers around the world.

Effects of El Nino‐Southern Oscillation and North Pacific weather patterns on interannual variability in the subarctic Bering Sea

Extraordinary interannual variability in ice cover, air and sea surface temperatures (SST), and surface winds in the eastern Bering Sea have been observed over recent years. To investigate the causes of this interannual variability, long‐term (20–30 years) time series of air, ocean, and ice parameters from the Bering Sea were cross‐correlated with the southern oscillation index (SOI), an index of El Nino‐Southern Oscillation (ENSO) events in the tropical southern hemisphere, as well as with an index of Pacific/North American (PNA) events in the north Pacific. Five to thirty percent of the interannual variability (linear regression with various smoothing) in the Bering Sea data sets, with the exception of surface winds, is explained by the SOI when the Bering Sea data lags the SOI. For comparison, 29–52% of the variability in the SST off South America can be explained by the SOI. The signs of the correlations all suggest that warming in the Bering Sea follows negative anomalies in the SOI, that is, ENSO events. Positive anomalies in the SOI, which tend to precede El Nino events, were found to precede cooling in the Bering Sea. Significant correlation persists for 18–20 months. Higher‐order polynomial regressions between the SOI and Bering Sea data can explain up to 40% of the Bering Sea variability. The mechanism for the connection between ENSO events and Bering Sea interannual variability appears to be of atmospheric nature and is associated with the winter position and intensity of the Aleutian low. The Aleutian low is intensified and eastward of normal in association with El Nino, i.e., warm events but is weaker and westward of normal during cool events. It is the regional winds associated with the variable position of the Aleutian low that cause the regional warming and cooling events. This seesaw in the Aleutian low is also used to explain the out‐of‐phase ice conditions between the Bering Sea and the Sea of Okhotsk. PNA events are also associated with an intensified Aleutian low as well as 700 mbar ridging over northwestern North America causing southerly flow over Alaska. However, while correlation between ENSO events and PNA was significant, the correlation between the Bering Sea and PNA was marginal except for surface winds. Here surface winds from the north were significantly correlated with the PNA. This apparent inconsistency, as well as the lack of correlation of surface winds with the SOI, is explained by the lack of preferred site of the Aleutian low during ENSO events. This lack of preferred site helps explain why the major El Nino event of 1982–1983 had little apparent effect on the Bering Sea.