Increased Emission Rates Research Articles

Stochastic Diffusive Modeling of CO₂ Emissions with Population and Energy Dynamics

Climate change, primarily driven by CO2 emissions from energy and non-energy sectors, necessitates effective mitigation strategies. This study develops a stochastic diffusive model to capture the complex dynamics of CO2 concentration, human population growth, and energy production. The objectives are to enhance the predictive accuracy of existing models by incorporating diffusion effects and stochastic variability, offering insights for sustainable environmental policies. A novel numerical scheme, an extension of the Euler-Maruyama algorithm, is proposed to solve stochastic time-dependent partial differential equations governing the model. The scheme's consistency and stability are rigorously analyzed in the mean square sense. Findings reveal that increasing emission rate coefficients in energy and non-energy sectors exacerbates CO2 levels, emphasizing the need for stringent controls. The proposed scheme demonstrates superior accuracy to the non-standard finite difference method, establishing its efficacy in modeling complex environmental processes. This research contributes a robust computational tool to improve existing predictive models, aiding decision-making for long-term ecological sustainability. By addressing uncertainties in the environmental process, the work advances the understanding of interactions between population growth, energy production, and CO2 emissions, offering a significant improvement over the traditional modeling approach. The novelty lies in integrating stochastic dynamics with diffusion to better inform CO2reduction strategies. Doi: 10.28991/ESJ-2025-09-01-012 Full Text: PDF

Dimethyl Sulfide Emissions From a Peatland Result More From Organic Matter Degradation Than Sulfate Reduction

AbstractVolatile sulfur compounds (VSCs) contribute to acid rain, cloud formation, and albedo, and thus influence the climate. Their global emissions are quite uncertain, especially contributions from freshwater wetlands. We investigated the processes leading to hydrogen sulfide (H2S), methanethiol (MeSH), and dimethyl sulfide (Me2S) emissions in a slightly acidic peatland and found multiple indications that organic matter degradation rather than sulfate reduction is the main driver for Me2S emissions in this system. Evidence includes: the lack of labeled Me234S production after addition of Na234SO4 despite high emissions of Me34SH and H234S, and increased emission rates when soils were amended with organic substrates containing thiol groups (H2S emissions), methylthiols (MeSH), and dimethyl sulfonio groups (Me2S). VSC precursors were identified from an Untargeted Metabolomics data set from the same soil. The abundance of sulfur cycling microbes like Acidobacteria SD 1 and Desulfosporosinus correlated with VSC emissions. We conclude that organic matter degradation is more important than sulfate reduction as a source of Me2S in our peatland system, and potentially also in other organic and wetland soils.

Digital Transformation: towards Sustainable and Smart New Cities in Upper Egypt (New Qena Case study).

Despite the ongoing development of IT and innovative technologies in all aspects of life, the transformation of cities into smart, sustainable cities is still at a starting level in developing countries. Decision-makers and planners still face numerous challenges in achieving smart, sustainable cities in Egypt. Such as rapid urbanization, increased emission rate, waste of resources, population growth, weak infrastructure, etc. This has led many countries to accelerate the harnessing of technology’s potential for transformation into smart, sustainable cities. Therefore, the research aims to investigate and highlight the significance of innovative technologies in driving and achieving digital transformation in new cities in Upper Egypt to become smart, sustainable cities. That could lead the cities to invest and build the qualifications to be autonomous cities in the future. The research studied three cases in the Arab world in order to apply the lessons acquired from their digital transformation experiences and sustainable plans. Consequently, the paper presents proposed guidelines to achieve a sustainable smart city in New Qena. These guidelines assist planners, authorities, and decision-makers in improving the quality of life, and city services, enhancing economic and social sustainability, promoting climate-friendly environments, and developing a vision for the future transformation of the city.

Predicting spatio-temporal distribution of indoor multi-phase phthalates under the influence of particulate matter

Due to the complexity of phthalates spatial and temporal distribution in indoor environment, mechanistic that govern indoor phthalates concentrations and fates need to be explored. A dynamic partition model of phthalates considering the dynamic behavior and segmented emission of size-resolved particulate matter is developed to investigate the distribution of phthalates in the gas phase, airborne particles, and settled dust and on the fixed surface. The impacts of outdoor and indoor particle source on the multi-phase concentrations of phthalates are analyzed. Outdoor haze can suddenly increase indoor particle concentration and particle-phase concentration of Di-2-ethylhexyl phthalate (DEHP). However, the haze decreases gas-phase and dust-phase concentration of DEHP. The particle emission rate Sp for cooking affects the maximum concentration of indoor particle, while cooking frequency has no effect on it. When cooking frequency increases, gas-phase concentration and particle-phase peak concentration of DEHP decreases significantly, which means the particulate matter may be a good carrier for DEHP removal. Increasing emission rate Sp of particles can significantly reduce the minimum gas-phase concentration of DEHP, nevertheless it can increase particle-phase maximum concentration of DEHP. Overall, the proposed model considering interactions of particle and phthalate can improve further understanding of phthalates’ fate and transport in residential environment, which is beneficial to the implementation of control strategy.

Assessment of the link between atmospheric dispersion and chemical composition of PM10 at 2-h time resolution

The concentration of air pollutants is governed by both emission rate and atmospheric dispersion conditions. The role played by the atmospheric mixing height in determining the daily time pattern of PM components at the time resolution of 2 h was studied during 21 days of observation selected from a 2-month field campaign carried out in the urban area of Rome, Italy.Natural radioactivity was used to obtain information about the mixing properties of the lower atmosphere throughout the day and allowed the identification of advection and stability periods. PM10 composition was determined by X-ray fluorescence, ion chromatography, inductively coupled plasma-mass spectrometry and thermo-optical analysis. A satisfactory mass closure was obtained on a 2-h basis, and the time pattern of the PM10 macro-sources (soil, sea, secondary inorganics, organics, traffic exhaust) was acquired at the same time scale.After a complete quality control procedure, 27 main components and source tracers were selected for further elaboration. On this database, we identified some groups of co-varying species related to the main sources of PM. Each group showed a peculiar behaviour in relation to the mixing depth. PM components released by soil, biomass burning and traffic exhaust, and, particularly, ammonium nitrate, showed a clear dependence on the mixing properties of the lower atmosphere. Biomass burning components and organics peaked during the night hours (around midnight), following the atmospheric stabilization and increased emission rate. Traffic exhausts and non-exhausts species also peaked in the evening, but they showed a second, minor increase between 6:00 and 10:00 when the strengthening of the emission rate (morning rush hour) was counterbalanced by the dilution of the atmosphere (increasing mixing depth). In the case of ammonium nitrate, high concentrations were kept during the whole night and morning.

Data Analysis for the Aero Derivative Engines Bleed System Failure Identification and Prediction

Middle size gas/diesel aero-derivative power generation engines are widely used on various industrial plants in the oil and gas industry. Bleed of Valve (BOV) system failure is one of the failure mechanisms of these engines. The BOV is part of the critical anti-surge system and this kind of failure is almost impossible to identify while the engine is in operation. If the engine operates with BOV system impaired, this leads to the high maintenance cost during overhaul, increased emission rate, fuel consumption and loss in the efficiency. This paper proposes the use of readily available sensor data in a Supervisory Control and Data Acquisition (SCADA) system in combination with a machine learning algorithm for early identification of BOV system failure. Different machine learning algorithms and dimensionality reduction techniques are evaluated on real world engine data. The experimental results show that Bleed of Valve systems failures could be effectively predicted from readily available sensor data.

Improving the transportation system in Baghdad city

Baghdad has suffered from lack of new major infrastructure in transportation sector for many decades, compounded by a huge increase in the number of roads user. This has led to problems with out-of-date networks causing congested roads and pavement exceeding its design life, increasing travel time with negative effects on users, the economy, and the environment due to increased emission rates and massive fuel consumption. Accordingly, this study seeks to develop a sustainable transportation system to handle a large number of users with minimum effect on the environment to promote economic achievement. Based on the literature, a rail transportation system emerged is the most sustainable system, and such a system is thus proposed for Baghdad, with suggested route and station positions designed to ensure efficient interactions with the current road network. To assess the proposed system, the city was divided into fifteen zones, eight zones on the east side and seven on the west side, and travel times between zones were calculated using GIS software both with and without application of the proposed system. The results revealed that considerable savings in travel time between most zones with the system. Furthermore, the proposed system would change the land use adjacent to access points (stations), boosting investment in housing and encouraging people to leave the overcrowded city centre.

Population Age Structure and Greenhouse Gas Emissions from Road Transportation: A Panel Cointegration Analysis of 21 OECD Countries.

Using panel data from 21 Organization for Economic Cooperation and Development (OECD) countries collected between 2000 and 2016, this study analyzes the effect of age structure on greenhouse gas (GHG) emissions from road transportation. Previous studies have failed to reflect the driver’s behavior patterns, especially by age group. We apply the Fully-Modified Ordinary Least Squares (FMOLS) method, including the age structure effect by reorganizing 17 age groups into a polynomial structure. The age structure exhibits an asymmetric inverted U-shaped effect on GHG emissions. Initially, people emit more GHGs as they age, and reach peak emissions in their late 20s, after which emissions fall until around the age of 70, when GHG emissions remain constant because of minimum mobility demand. Factors, such as higher income, increased vehicle ownership, and raised transport volumes increase emission rates. On the other hand, fuel transition and increased fuel price, population density, urbanization rate, and fuel economy reduce GHG emissions. Furthermore, we perform a projection of GHG emissions until 2050, and conclude that the effect of age structure is limited because of the minimum mobility demand of the elderly. We conclude that various policy measures, such as increased fuel economy and urbanization, must be considered in order to achieve sustainable transport

Increase flared gas recovery and emission reduction by separator optimization

To combat the increased emission rate and energy waste, a business case for an online optimizer was established to examine the energy-saving and emission reduction figures. Prior to embarking on this study, there is a need to understand the performance of oil and gas companies in managing the continuous flared gas. From the data gathered, it was quite evident that oil and gas operators do not significantly invest in optimizing gas flaring. The survey has included 706 participants from more than 59 different countries and indicated that there is a lack of awareness where regular monitoring of flared gas is overlooked. The survey shows about 17.6% of the participants never analyzed flared gas compositions, while only 36.6% of participants do this on monthly basis. More importantly, the survey indicated that most participants don’t update their process operating conditions in response to day and night or yearly seasons thermal conditions. The optimization study is primarily focusing on having an online flared gas controller technique to continually monitor and analyze flared gas compositions with an intention to automatically manipulate separator operating conditions to increase the flared gas recovery. This approach was tested using a dynamic model developed for three real offshore and onshore oil and gas fields in Egypt and Saudi Arabia. In the three cases of study, this approach was able to adjust the operating conditions of the separator based on the flared gas analysis and the objective function identified to largely recover heavy hydrocarbons and control flared gas.

The Effect of Periodic Spatial Perturbations on the Emission Rates of Quantum Dots near Graphene Platforms.

The quenching of fluorescence (FL) at the vicinity of conductive surfaces and, in particular, near a 2-D graphene layer has become an important biochemical sensing tool. The quenching is attributed to fast non-radiative energy transfer between a chromophore (here, a Quantum Dot, QD) and the lossy graphene layer. Increased emission rate is also observed when the QD is coupled to a resonator. Here, we combine the two effects in order to control the emission lifetime of the QD. In our case, the resonator was defined by an array of nano-holes in the oxide substrate underneath a graphene surface guide. At resonance, the surface mode of the emitted radiation is concentrated at the nano-holes. Thus, the radiation of QD at or near the holes is spatially correlated through the hole-array’s symmetry. We demonstrated an emission rate change by more than 50% as the sample was azimuthally rotated with respect to the polarization of the excitation laser. In addition to an electrical control, such control over the emission lifetime could be used to control Resonance Energy Transfer (RET) between two chromophores.

Experimental determination of indoor air concentration of 5-chloro-2-methylisothiazol-3(2H)-one/ 2-methylisothiazol-3(2H)-one (CMIT/MIT) emitted by the use of humidifier disinfectant.

A mixture of 5-chloro-2-methylisothiazol-3(2H)-one/2-methylisothiazol-3(2H)-one (CMIT/MIT) had been used as an active ingredient in humidifier disinfectants (HDs). Owing to its high reactivity, the atmospheric concentration of CMIT/MIT, following its use in HD, would be lower than expected assuming that it is removed by ventilation only. In order to evaluate the exposure concentration of CMIT/MIT used as an HD, room-scale chamber studies were conducted under plausible use of three different HD doses at air change rates (ACR) of 0.3, 0.5, and 1.0 h−1. Atmospheric CMIT/MIT was sampled using two serial impingers containing deionized water after the attainment of steady state. Water samples in which CMIT/MIT was dissolved were concentrated using a cosolvent evaporation method with efficiencies of 35.5 and 77.9% for CMIT and MIT, respectively. The estimated air concentration, assuming that all the CMIT/MIT is absorbed in deionized water, increased linearly with increasing emission rate, but was independent of the ACR. This indicates that the removal rate of CMIT/MIT via chemical reactions is more than the removal rate by ventilation. Further investigations on homogeneous and heterogeneous chemical reactions of CMIT/MIT under ambient conditions are necessary to understand the actual exposure concentration of the mixture in HD.

Human Ammonia Emission Rates under Various Indoor Environmental Conditions.

Ammonia (NH3) is typically present at higher concentrations in indoor air (∼10-70 ppb) than in outdoor air (∼50 ppt to 5 ppb). It is the dominant neutralizer of acidic species in indoor environments, strongly influencing the partitioning of gaseous acidic and basic species to aerosols, surface films, and bulk water. We have measured NH3 emissions from humans in an environmentally controlled chamber. A series of experiments, each with four volunteers, quantified NH3 emissions as a function of temperature (25.1-32.6 °C), clothing (long-sleeved shirts/pants or T-shirts/shorts), age (teenagers, adults, and seniors), relative humidity (low or high), and ozone (<2 ppb or ∼35 ppb). Higher temperature and more skin exposure (T-shirts/shorts) significantly increased emission rates. For adults and seniors (long clothing), NH3 emissions are estimated to be 0.4 mg h-1 person-1 at 25 °C, 0.8 mg h-1 person-1 at 27 °C, and 1.4 mg h-1 person-1 at 29 °C, based on the temperature relationship observed in this study. Human NH3 emissions are sufficient to neutralize the acidifying impacts of human CO2 emissions. Results from this study can be used to more accurately model indoor and inner-city outdoor NH3 concentrations and associated chemistry.

Estimating Emissions from Static Traffic Models: Problems and Solutions

In large urban areas, the estimation of vehicular traffic emissions is commonly based on the outputs of transport planning models, such as Static Traffic Assignment (STA) models. However, such models, being used in a strategic context, imply some important simplifications regarding the variation of traffic conditions, and their outputs are heavily aggregated in time. In addition, dynamic traffic flow phenomena, such as queue spillback, cannot be captured, leading to inaccurate modelling of congestion. As congestion is strongly correlated with increased emission rates, using STA may lead to unreliable emission estimations. The first objective of this paper is to identify the errors that STA models introduce into an emission estimation. Then, considering the type and the nature of the errors, our aim is to suggest potential solutions. According to our findings, the main errors are related to STA inability of accurately modelling the level and the location of congestion. For this reason, we suggest and evaluate the postprocessing of STA outputs through quasidynamic network loading. Then, we evaluate our suggested approach using the HBEFA emission factors and a 19 km long motorway segment in Stockholm as a case study. Although, in terms of total emissions, the differences compared to the simple static case are not so vital, the postprocessor performs better regarding the spatial distribution of emissions. Considering the location-specific effects of traffic emissions, the latter may lead to substantial improvements in applications of emission modelling such as dispersion, air quality, and exposure modelling.

Utilization of inorganic mineral filler material as partial replacement for wood fiber in medium density fiberboard (MDF) and its effect on material properties

The influence of inorganic mineral filler addition on the material properties of medium density fiberboard (MDF) was investigated at varying densities. Fibreboards with 10, 20 and 30% fibers replaced by calcium carbonate weight basis (dry/dry) and with target densities of 550, 700 and 850 kgm−3, respectively, were manufactured in a laboratory scale environment. The fiberboards were prepared by adding the mineral filler in dry powder form to the wood fibers to which urea formaldehyde UF resin in liquid state had previously been added. The obtained fiber-filler furnish, with the filler distributed uniformly by sticking to the UF resin on the fibers, was then pressed into panel forms. The effect of inorganic filler on elastic and strength properties, thickness swelling, permeability, as well as formaldehyde and volatile organic compound (VOC) emissions was quantified. The results demonstrate that the addition of mineral filler to MDF up to levels of 10 wt.% only have a small effect, if at all, on the material properties. The addition of calcium carbonate, and the associated increase in pH, does not have any effect on the strength development in the cured MDF, even though the results clearly demonstrate the negative effect on the curing kinetics of urea formaldehyde (UF) resin. Likewise, thickness swelling and formaldehyde and volatile organic compounds (VOC’s) emissions are not affected by filler addition levels of up to 10 wt.%. However, exceeding this level leads to a significant decline in strength, which is believed to be caused mainly by a reduction in the number of fiber-to-fiber stress transfer points. Further, increased emissions in VOC’s are expected due to a combination of the catalytic effect of the calcium carbonate that causes a breakdown of fatty acids to VOC’s and also increased emission rates due to a higher permeability of the MDF with filler addition levels above 10 wt.%.

Volatile emissions from thawing permafrost soils are influenced by meltwater drainage conditions.

Vast amounts of carbon are bound in both active layer and permafrost soils in the Arctic. As a consequence of climate warming, the depth of the active layer is increasing in size and permafrost soils are thawing. We hypothesize that pulses of biogenic volatile organic compounds are released from the near-surface active layer during spring, and during late summer season from thawing permafrost, while the subsequent biogeochemical processes occurring in thawed soils also lead to emissions. Biogenic volatile organic compounds are reactive gases that have both negative and positive climate forcing impacts when introduced to the Arctic atmosphere, and the knowledge of their emission magnitude and pattern is necessary to construct reliable climate models. However, it is unclear how different ecosystems and environmental factors such as drainage conditions upon permafrost thaw affect the emission and compound composition. Here we show that incubations of frozen B horizon of the active layer and permafrost soils collected from a High Arctic heath and fen release a range of biogenic volatile organic compounds upon thaw and during subsequent incubation experiments at temperatures of 10°C and 20°C. Meltwater drainage in the fen soils increased emission rates nine times, while having no effect in the drier heath soils. Emissions generally increased with temperature, and emission profiles for the fen soils were dominated by benzenoids and alkanes, while benzenoids, ketones, and alcohols dominated in heath soils. Our results emphasize that future changes affecting the drainage conditions of the Arctic tundra will have a large influence on volatile emissions from thawing permafrost soils - particularly in wetland/fen areas.

Endangered species management and climate change: When habitat conservation becomes a moving target

ABSTRACTAs climate conditions continue to shift, species assemblages and composition within ecological communities may be reshuffled in unpredictable ways. Some habitat types may cease to exist while others may expand in size; protecting ecosystems and species in their current locations will become increasingly difficult. Threatened and endangered species are likely to be disproportionately affected by climate change because they are often habitat specialists and relatively rare. In the United States, the 1973 Endangered Species Act has prevented the extinction of many species. The identification and conservation of critical habitat is an important tool for species preservation. But how do we designate and preserve habitat for protected species when we are unsure about future habitat conditions? We address this question based upon the concept of managing for anticipated change, rather than focusing on the maintenance of existing conditions. We used an ecological niche modeling program (MaxEnt) to model current and future climatic niche for an endangered mammal endemic to southern California, USA; the Stephens’ kangaroo rat (SKR, Dipodomys stephensi). Our results indicate that the climatic niche of SKR was governed primarily by precipitation during the dry season, precipitation seasonality, annual mean temperature, and mean summer temperature. Projecting current species‐presence relationships to different scenarios predicted for the future revealed substantial loss in climatic niche with increased emission rates. Areas of future suitable climatic niche were evaluated in relation to land ownership and identified as potential reserves or translocation sites, which can aid in conservation planning for this species. Additionally, species vulnerability assessments and a climate‐change analysis tool were utilized to demonstrate how overall understanding of climate change effects can be enhanced. Information presented here can serve as guiding principles for the inclusion of climate change considerations into management plans, and can better inform overall decision‐making related to endangered species management. © 2019 The Wildlife Society.

Increased methane concentration alters soil prokaryotic community structure along an artificial pH gradient

Global climate change may have a large impact on increased emission rates of carbon dioxide and methane to total greenhouse gas emissions from terrestrial wetlands. Methane consumption by soil microbiota in alpine wet meadows serves as a biofilter for the methane produced in the waterlogged soil below. Altered pH regimes change microbial community composition and structure by exerting selection pressure on soil microorganisms with different ecological strategies and thus affect greenhouse gas emissions resulting from the metabolic activity of soil microorganisms. However, responses of prokaryotic communities to artificial pH shift under elevated methane concentration remain unclear. In this study, we assessed diversity and relative abundance of soil prokaryotes in an alpine meadow under elevated methane concentration along an artificial pH gradient using laboratory incubation experiments. We established an incubation experiment treated with artificial pH gradient (pH 4.5–8.5). After 3 months of incubation, 300 ml of methane at a concentration of 20,000 ppm was added to stimulate potential methanothrophs in topsoil. Sequencing of 16S rRNA gene indicated increasing of relative abundances of Crenarchaeota, Chloroflexi, Bacteroidetes, and Planctomycetes in soil after addition of methane, while the relative abundances of Actinobacteria and Gemmatimonadetes did not significant change before and after methane treatment. Results of phylogenetic relatedness of soil prokaryotes showed that microbial community is mostly shaped by deterministic factors. Species indicator analysis revealed distinct OTUs among various pH and methane treatments. Network analysis revealed distinct co-occurrence patterns of soil prokaryotic community before and after methane addition, and different correlation patterns among various prokaryotic taxa. Linear regression model revealed significant decrease of methane oxidation along elevated pH gradient. Soil pH constituted a strong environmental filter in species assembly of soil prokaryotic community. Methane oxidation rates decreased significantly with elevated pH. The interactive effects of elevated methane concentration and pH are therefore promising topic for future research.

Cavity-Enhanced Single-Photon Source Based on the Silicon-Vacancy Center in Diamond

Single photon sources are an integral part of various quantum technologies, and solid state quantum emitters at room temperature appear as a promising implementation. We couple the fluorescence of individual silicon vacancy centers in nanodiamonds to a tunable optical microcavity to demonstrate a single photon source with high efficiency, increased emission rate, and improved spectral purity compared to the intrinsic emitter properties. We use a fiber-based microcavity with a mode volume as small as $3.4~\lambda^3$ and a quality factor of $1.9\times 10^4$ and observe an effective Purcell factor of up to 9.2. We furthermore study modifications of the internal rate dynamics and propose a rate model that closely agrees with the measurements. We observe lifetime changes of up to 31%, limited by the finite quantum efficiency of the emitters studied here. With improved materials, our achieved parameters predict single photon rates beyond 1 GHz.

Deconstructing Methane Emissions from a Small Northern European River: Hydrodynamics and Temperature as Key Drivers.

Methane (CH4) emissions from small rivers and streams, particularly via ebullition, are currently under-represented in the literature. Here, we quantify the methane effluxes and drivers in a small, Northern European river. Methane fluxes are comparable to those from tropical aquatic systems, with average emissions of 320 mg CH4 m-2 d-1. Two important drivers of methane flux variations were identified in the studied system: 1) temperature-driven sediment methane ebullition and 2) flow-dependent contribution suspected to be hydraulic exchange with adjacent wetlands and small side-bays. This flow-dependent contribution to river methane loading is shown to be negligible for flows less than 4 m3 s-1 and greater than 50% as flows exceed 7 m3 s-1. While the temperature-ebullition relationship is comparable to other systems, the flow rate dependency has not been previously demonstrated. In general, we found that about 80% of the total emissions were due to methane bubbles. Applying ebullition rates to global estimates for fluvial systems, which currently are not considered, could dramatically increase emission rates to ranges from lakes or wetlands. This work illustrates that small rivers can emit significant methane and highlights the need for further studies on the link between hydrodynamics and connected wetlands.

First principles pulse pile-up balance equation and fast deterministic solution

Pulse pile-up (PPU) is an always present effect which introduces a distortion into the spectrum measured with radiation detectors and that worsen with the increasing emission rate of the radiation source. It is fully ascribable to the pulse handling circuitry of the detector and it is not comprised in the detector response function which is well explained by a physical model. The PPU changes both the number and the height of the recorded pulses, which are related, respectively, with the number of detected particles and their energy. In the present work, it is derived a first principles balance equation for second order PPU to obtain a post-processing correction to apply to X-ray measurements. The balance equation is solved for the particular case of rectangular pulse shape using a deterministic iterative procedure for which it will be shown the convergence. The proposed method, deterministic rectangular PPU (DRPPU), requires minimum amount of information and, as example, it is applied to a solid state Si detector with active or off-line PPU suppression circuitry. A comparison shows that the results obtained with this fast and simple approach are comparable to those from the more sophisticated procedure using precise detector pulse shapes.