Time Series Of Emissions Research Articles

On the stationarity of per capita carbon dioxide emissions over a century

This paper examines the stationarity of carbon dioxide (CO2) emissions per capita for a set of 36 countries covering the period 1870–2006. We employ recently developed unit root and stationarity tests that allow for the mean reverting process to be nonlinear and take into account cross sectional dependence. By grouping countries according to their geographical proximity, the importance of cross sectional dependence in panel unit root and stationarity tests is revealed. Using a recently developed nonlinear panel unit root test, we find strong evidence that the per capita carbon dioxide emissions over the last one hundred and fifty years are stationary. Our nonlinear specification captures the dynamics of the emissions time series data more effectively and we obtain evidence supporting stationarity for all country groups under study.

Influence of Noise to Chaotic Time Series Prediction in Environment

When constructing chaotic time series prediction model involving noise, noise would influence the chaotic characteristics of the time series and lower the precision and generalization ability of the model. This paper applies wavelet transform to make de-noise on gas emission time series. It uses state space reconstruction theory to determine the embedding dimension and delay time. In the constructed phase space, build BP artificial neural network model to make prediction. Prediction model constructed after wavelet de-noises achieves good prediction performance.

Chaotic Characteristics of Workface Gas Emission Time-Series Data

The chaotic time series phase space reconstruction theory based in this paper. First, the appropriate embedding dimension and delay time are selected by minimum entropy rate. Followed the chaotic behavior are analyzed by the use of the Poincare section map and Power spectrum of time series from the qualitative point of view. Based on NLSR LLE the quantitative study of the chaotic time series characteristics indicators is proposed. Finally, the gas emission workface of Hebi 10th Mine Coal is studied. The several analytical results of the above methods show that: the gas emission time-series data of this workface has chaotic characteristics.

Ammonia emissions from cattle urine and dung excreted on pasture

Abstract. Twelve cattle were kept for three days in a circular area of 16 m radius on short pasture and fed with freshly-cut pasture. Ammonia (NH3) emissions from the urine and dung excreted by the cattle were measured with a micrometeorological mass-balance method, during the cattle presence and for 10 subsequent days. Daily-integrated emission rates peaked on Day 3 of the experiment (last day of cattle presence) and declined steadily for five days thereafter. Urine patches were the dominant sources for these emissions. On Day 9, a secondary emissions peak occurred, with dung pats likely to be the main sources. This interpretation is based on simultaneous observations of the pH evolution in urine patches and dung pats created next to the circular plot. Feed and dung samples were analysed to estimate the amounts of nitrogen (N) ingested and excreted. Total N volatilised as NH3 was 19.8 (± 0.9)% of N intake and 22.4 (± 1.3)% of N excreted. The bimodal shape of the emissions time series allowed to infer separate estimates for volatilisation from urine and dung, respectively, with the result that urine accounted for 88.6 (± 2.6)% of the total NH3 emissions. The emissions from urine represented 25.5 (± 2.0)% of the excreted urine-N, while the emissions from dung amounted to 11.6 (± 2.7)% of the deposited dung-N. Emissions from dung may have continued after Day 13 but were not resolved by the measurement technique. A simple resistance model shows that the magnitude of the emissions from dung is controlled by the resistance of the dung crust.

Temporal Variability of Nitrous Oxide from Fertilized Croplands: Hot Moment Analysis

Nitrous oxide (N2O) emissions were monitored using the micrometeorological eddy covariance technique from manure-fertilized cropland on a large dairy farm in New York State in 2006 to 2009. Nitrous oxide emissions demonstrated episodic behavior with intermittent short-duration peak fluxes up to 39.7 mg N2O-N m−2 d−1, whereas most of background fluxes during the annual agricultural cycle were below 6.5 mg N2O-N m−2 d−1. This paper discusses temporal variability of measured N2O emissions using a “hot moment” approach. To identify and quantify peak events as potential hot moments and to determine whether or not they could be treated statistically as outliers, N2O daily fluxes were analyzed by the box plot method using multiple thresholds. Peak events exceeding outlier thresholds contributed up to 51% of cumulative annual N2O emissions, although they represented <7% of the total observation time. Individual N2O peaks were also categorized by their duration, as single day spikes and multiday events. The highest contributing instances were multiday N2O peaks during summer precipitation and early spring thaw, largely enhanced by manure fertilization. These high-intensity emission events demonstrated repetitive seasonal responses to a combination of environmental factors and were therefore identified as hot moments. Abrupt rises in both temperature and soil moisture appeared to trigger major hot moments, whereas the availability of manure N controlled their magnitude. In the absence of strong correlations between time-series of individual environmental factors and N2O emissions, the hot moment approach can be a promising tool for the integrated analysis of most significant N2O events in cultivated fields receiving manure applications.

Acoustic, Electromagnetic, and Photon Emission from Dynamically Fracturing Granite

Laboratory samples of Westerly granite were impacted by a falling striker, and the time series of acoustic and electromagnetic emission (AE and EME) from fracturing rock were recorded with the time resolution of 10 ns. In order to determine precisely the actual instants of beginning and termination of fracturing, the fractoluminescence (FL) signal related to chemical bond ruptures on the sample surface was recorded in parallel to both AE and EME signals. Energy distributions in all three series were characterized by the function N(E > E′), where N is the number of emitted signals characterized with the energy release E exceeding a threshold value E′. The fracture dynamics was studied using both the scaling analysis and the non-extensive Tsallis statistics. The energy distributions were approximated with both the empirical Gutenberg–Richter-type relation N(E > E′) ∝ E′−b, and the analytical function Nq(E > E′) that includes the Tsallis’ parameter of non-extensivity, q, and the released energy density. A comparative consideration of information taken from the data of EME, AE and FL emission techniques was carried out in the context of the physical sense of the parameters b and q. The AE time series reflected adequately the cracking process both at microscopic and laboratory scale levels, while the photon emission did not show a direct response on the split-off formation. Time resolution of the EME method was found to be insufficient for studying the dynamic fracture of the given kind.

Nocturnal Emissions: A Failure to Replicate

A time series of nocturnal emissions was presented in The American Journal of Psychology in 1904. The anonymous author of this remarkable article provided the time series to support his contention that his nocturnal emissions exhibited a seasonal pattern of variation. Specifically, he claimed to have heightened emissions during spring and summer, with dampened emissions later. The basis for this claim was a time series graph of average emissions by month across an 8-year period. The purpose of this article is to reanalyze these data with statistical procedures developed in the past century to validate the original conclusion drawn by the author. After analyses of the data with several state-of-the-art methods, no statistical support was found for a seasonal pattern of nocturnal emissions.

Mitigation and adaptation to Climate Change in Hungary

This review paper is a brief summary of the climate change story, transforming of primary concept from a scientific idea to a threatened world, and the contribution of Hungary in solution of above mentioned problems. According to the National Inventory published in 2010 the time series of GHG emissions together with real GDP changes will be shown. The way of mitigation available for Hungary is illustrated by climate strategies on different levels. Since the most vulnerable sector of the economy is agriculture as Hungarian researchers found, mainly the increasing frequency of drought seems to be dangerous. The impact of climate change was studied on the production level of main crops and the whole agricultural sector as well as on the GDP of the country. Some possible ways for agriculture to adapt to the increasing extremities will be mentioned. Altogether climate change means a challenge to technological development in all sectors of the economy and also in social cohesions and that is a feedback to adaptation.

Mine Gas Emission Prediction based on Gaussian Process Model

Abstract For the purpose of making effective analysis and full use of gas measuring data in mines to achieve more accurate gas emission quantity prediction, studied the method for gas emission time series analysis to achieve gas emission quantity prediction based on the Gaussian process regression model. Two methods for gas emission time series analysis were proposed, the relationship between gas emission quantity and time (Q-T) model and autoregression model, considered gas emission time series as a function of time in Q-T model, while constructed the Gaussian process regression model from gas emission time series itself completely in autoregression model. The results of case study show that Gaussian process model can describe the objective laws and the developing trends of mine gas emission, its predictive results are accurate and reliable, therefore, the application of the Gaussian process regression in gas emission time series analysis is a feasible and effective method for gas emission quantity prediction, it has high practical application value.

Variations in emission rates from solvent use in the residential sector: the case of Greece

Solvent use is the second most significant source of anthropogenic non-methane volatile organic compound emissions in Europe, as well as in Greece, the residential solvent use being the second most important source of solvent emissions. The methodology used so far in Greece and other countries for estimating residential solvent emissions adopts literature-proposed average per person emission factors and population data. The methodology developed in this work involves the determination of solvent-containing product groups and the solvent content of products, along with the collection, evaluation and elaboration of a large amount of statistical data concerning the domestic supply of products consumed in the residential sector. The emission calculations are performed on the basis of the amount of the solvent-containing products consumed. Two hundred and sixty-six solvent-containing products used in the residential sector are classified into five groups and 24 sub-categories of similar products and an extensive field survey is carried out in order to determine the solvent content of the products. Time series of total emissions for the period 1995–2007 indicate that there is an increasing trend of total residential solvent emissions in Greece. Cosmetics, do it yourself and car care products are the most important emitting categories of residential solvent use. The resulted emission rates (expressed per capita and per year) are greater than those proposed in the literature and they approach in better way local characteristics, as well as their evolution. The methodology developed and the updated emissions rates could be useful in other counties of similar consumption behaviours, economic situation or climate conditions.

Subsurface emission effects in AMSR-E measurements: Implications for land surface microwave emissivity retrieval

An analysis of land surface microwave emission time series shows that the characteristic diurnal signature associated with subsurface emission in sandy deserts carry over to arid and semi-arid region worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (AMSR-E) measurements. The AMSR-E orbit has equator crossing times near 01:30 and 13 :30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. AMSR-E measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from AMSR-E, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions

Time Series of Combustion Characteristics and Particulate Emission during Combustion of Thai Lignite in a Fixed Bed

Time Series of Combustion Characteristics and Particulate Emission during Combustion of Thai Lignite in a Fixed Bed

Experimental Study on Time Series Characteristics of Rock Acoustic Emission in Complete Stress-Strain Process under Uniaxial Compression

Analysis of rock acoustic emission characteristics in complete stress-strain process under uniaxial compression shows that the evolution process of rock deformation and damage can be divided into five stages—compaction, linear elastic deformation, accelerate inelastic deformation, damage and development, plastic flow. Acoustic emission characteristics of rock can well reflect its compressive deformation and damage evolution process. Acoustic emission time series of typical plastic coal is comparatively dispersed and presents group shock type. The acoustic emission frequency events and their energy of coal are bigger around the damage point, but the maximum amplitude and the secondary maximum amplitude have not much difference. The acoustic emission events and their energy of very uniform and dense fragile limestone are mainly concentrated in a very short period of time before its damage and the acoustic emission time series manifests as isolated shock type. For sandstone whose homogeneous degree lies between typical plastic coal and very uniform and dense fragile limestone, its acoustic emission time series manifest as main shock type.

Deriving emissions time series from sparse atmospheric mole fractions

[1] A growth-based Bayesian inverse method is presented for deriving emissions of atmospheric trace species from temporally sparse measurements of their mole fractions. This work is motivated by many recent studies that have deduced emissions using archived air samples with measurement intervals of the order of a year or longer in the early part of the record. Several techniques have been used to make this underdetermined problem invertible. These include the incorporation of prior emissions estimates, the smoothing of observations or derived emissions, the approximation of emissions time series by polynomials, or the application of regularization schemes. However, these methods often suffer from limitations, such as the unavailability of independent, unbiased priors, the emergence of unrealistic emissions fluctuations due to measurement outliers, or the subjective choice of measurement or emissions smoothing time scales. This paper presents an alternative solution that reduces the influence of potentially biased priors or measurement outliers by constraining the emissions growth rate around some growth estimate, in conjunction with the model-measurement mismatch.

Monthly, global emissions of carbon dioxide from fossil fuel consumption

This paper examines available data, develops a strategy and presents a monthly, global time series of fossil-fuel carbon dioxide emissions for the years 1950-2006. This monthly time series was constructed from detailed study of monthly data from the 21 countries that account for approximately 80% of global total emissions. These data were then used in a Monte Carlo approach to proxy for all remaining countries. The proportional-proxy methodology estimates by fuel group the fraction of annual emissions emitted in each country and month. Emissions from solid, liquid and gas fuels are explicitly modelled by the proportional-proxy method. The primary conclusion from this study is the global monthly time series is statistically significantly different from a uniform distribution throughout the year. Uncertainty analysis of the data presented show that the proportional-proxy method used faithfully reproduces monthly patterns in the data and the global monthly pattern of emissions is relatively insensitive to the exact proxy assignments used. The data and results presented here should lead to a better understanding of global and regional carbon cycles, especially when the mass data are combined with the stable carbon isotope data in atmospheric transport models.

On chromospheric variations modeling for main-sequence stars of G and K spectral classes

We present a method of 13 late-type main-sequence stars chromospheric flux observation data calculations. These Sun-like stars have well-determined cyclic flux variations similar to the 11-year solar activity cycle. Our flux prediction is based on chromospheric HK emission time series measurements from the Mount Wilson Observatory and comparable solar data. We show that solar three - component modeling explains well the stellar observations. We find that the 10 - 20% of K - stars disc’s surfaces are occupied by bright active regions.

Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)

Abstract. New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

A statistical analysis of the SOT-Hinode observations of solar spicules and their wave-like behavior

Spicules are an important very dynamical and rather cool structure extending between the solar surface and the corona. They are partly filling the space inside the chromosphere and they are surrounded by a transition thin layer. New space observations taken with the SOT of the Hinode mission shed some light on their still mysterious formation and dynamics. Here we restrict the analysis to the most radial and the most interesting polar spicules situated at the base of the fast solar wind of coronal holes. We consider a first important parameter of spicules as observed above the solar visible limb: their apparent diameter as a function of the height above the limb which determines their aspect ratio and leads to the discussion of their magnetic origin using the flux tube approximation. We found that indeed spicules show a whole range of diameters, including unresolved “interacting spicules” (I-S), depending of the definition chosen to characterize this ubiquitous dynamical phenomenon occurring into a low coronal surrounding. Superposition effects along the line of sight have to be taken into account in order to correctly measure individual spicules and look at I-S. We take advantage of the so-called mad-max operator to reduce these effects and improve the visibility of these hair-like features. An excellent time sequence of images obtained above a polar region with the Hinode SOT through the HCaII filter with a cadence of 8 s was selected for analysis. 1-D Fourier amplitude spectra (AS) made at different heights above the limb are shown for the first time. A definite signature in the 0.18–0.25 Mm range exists, corresponding to the occurrence of the newly discovered type II spicules and, even more impressively, large Fourier amplitudes are observed in the 0.3–1.2 Mm range of diameters and spacing, in rough agreement with what historical works were reporting. Additionally, some statistically significant behavior, based on AS computed for different heights above the limb, is discussed. “Time slice or x– t diagrams” revealing the dynamical behavior of spicules are also analyzed. They show that most of spicules have multiple structures (similarly to the doublet spicules) and they show impressive transverse periodic fluctuations which were interpreted as upward kink or Alfven waves. Evidence of the helical motion in spicules is now well evidenced, the typical periods of the apparent oscillation being around 120 s. A fine analysis of the time-slice diagram as a function of the effective heights shows an interesting new feature near the 2 Mm height. We speculate on the interpretation of this feature as being a result of the dynamical specificities of the spicule helical motion as seen in these unprecedented high resolution HCaII line emission time series.

Do biomass burning aerosols intensify drought in equatorial Asia during El Niño?

Abstract. During El Niño years, fires in tropical forests and peatlands in equatorial Asia create large regional smoke clouds. We characterized the sensitivity of these clouds to regional drought, and we investigated their effects on climate by using an atmospheric general circulation model. Satellite observations during 2000–2006 indicated that El Niño-induced regional drought led to increases in fire emissions and, consequently, increases in aerosol optical depths over Sumatra, Borneo and the surrounding ocean. Next, we used the Community Atmosphere Model (CAM) to investigate how climate responded to this forcing. We conducted two 30 year simulations in which monthly fire emissions were prescribed for either a high (El Niño, 1997) or low (La Niña, 2000) fire year using a satellite-derived time series of fire emissions. Our simulations included the direct and semi-direct effects of aerosols on the radiation budget within the model. We assessed the radiative and climate effects of anthropogenic fire by analyzing the differences between the high and low fire simulations. Fire aerosols reduced net shortwave radiation at the surface during August–October by 19.1±12.9 W m−2 (10%) in a region that encompassed most of Sumatra and Borneo (90° E–120° E, 5° S–5° N). The reductions in net shortwave radiation cooled sea surface temperatures (SSTs) and land surface temperatures by 0.5±0.3 and 0.4±0.2 °C during these months. Tropospheric heating from black carbon (BC) absorption averaged 20.5±9.3 W m−2 and was balanced by a reduction in latent heating. The combination of decreased SSTs and increased atmospheric heating reduced regional precipitation by 0.9±0.6 mm d−1 (10%). The vulnerability of ecosystems to fire was enhanced because the decreases in precipitation exceeded those for evapotranspiration. Together, the satellite and modeling results imply a possible positive feedback loop in which anthropogenic burning in the region intensifies drought stress during El Niño.

An emission time series generator for pollutant release modelling in urban areas

Dynamic priority pollutant (PP) fate models are being developed to assess appropriate strategies for limiting the release of PPs from urban sources and for treating PPs on a variety of spatial scales. Different possible sources of PP releases were mapped and both their release pattern and release factors were quantified as detailed as possible. This paper focuses on the link between the gathered PP sources data and the dynamic models of the urban environment. This link consists of (1) a method for the quantitative and structured storage of temporal emission pattern information, (2) the retrieval of spatial emission source data from a GIS covering the studied urban area, (3) the coupling of the (GIS-based) spatial emission source data with temporal emission pattern information and (4) the generation of PP release time series to feed the dynamic sewer catchment model. Steps 3 and 4 were included as the main features of a dedicated software tool. Finally, this paper also illustrates the method's applicability to generate model input time series for generic pollutants (N, P and COD/BOD) in addition to priority pollutants.