Carbon balance and fire emissions in Andean cypress (Austrocedrus chilensis) forests of Patagonia, Argentina

2020 ◽  
Vol 29 (8) ◽  
pp. 661
Author(s):  
Guillermo Emilio Defossé ◽  
María Marcela Godoy ◽  
María Lila Bertolin
Keyword(s):  
Time Lag ◽  
Growth Curves ◽  
Real Data ◽  
Austrocedrus Chilensis ◽  
Intergovernmental Panel ◽  
Fire Emissions ◽  
Uptake Rates ◽  
Ipcc Guidelines ◽  
Carbon Losses ◽  
Floristic Characteristics

Wildfires are disturbances that affect forest structure and dynamics. Forests and the atmosphere interact in different ways; one is by emitting carbon (C) through wildfires and recapturing it by photosynthesis of regrowing vegetation. Estimation of C emissions and uptake allows monitoring and inventorying C at stand, landscape, or regional levels. We indirectly estimated C and other greenhouse gas emissions and uptake following Intergovernmental Panel on Climate Change (IPCC) guidelines, and also using growth curves derived from real data, in three burned pure Andean cypress (Austrocedrus chilensis) stands in Patagonia, Argentina. The sites, termed INTA (humid), LACO (mesic) and CECE (xeric), were burned on different dates (1987, INTA; 1999, CECE; 2008, LACO). Nearby unburned stands with similar structural and floristic characteristics were used as analogues to make our estimations. Carbon losses represented 245, 225, and 215t CO2 ha−1 for CECE, INTA and LACO respectively. Amount of carbon sequestered by post-fire vegetation depended on the time-lag from fire occurrence to date of sampling, whereas C uptake rates varied in time according to differences in site environmental conditions. Andean cypress seedlings present in burned stands suggest that outside the time needed, each site may recover not only lost C but also former structure and functions.

Semiparametric approach to pharmacokinetic-pharmacodynamic data

1989 ◽  
Vol 256 (4) ◽  
pp. R1005-R1010
Author(s):  
D. Verotta ◽  
S. L. Beal ◽  
L. B. Sheiner
Keyword(s):  
Steady State ◽  
Rate Constant ◽  
Drug Concentration ◽  
Venous Blood ◽  
Time Lag ◽  
Elimination Rate ◽  
Hysteresis Loops ◽  
Real Data ◽  
Elimination Rate Constant ◽  
Arterial Blood

A semiparametric model for analysis of pharmacokinetic (PK) and pharmacodynamic (PD) data arising from non-steady-state experiments is presented. The model describes time lag between drug concentration in a sampling compartment, e.g., venous blood (Cv), and drug effect (E). If drug concentration at the effect site (Ce) equilibrates with arterial blood concentration (Ca) slower than with Cv, a non-steady-state experiment yields E vs. Cv data describing a counterclockwise hysteresis loop. If Ce equilibrates with Ca faster than with Cv, clockwise hysteresis is observed. To model hysteresis, a parametric model is proposed linking (unobserved) Ca to Cv with elimination rate constant kappa ov and also linking Ca to Ce with elimination rate constant kappa oe. When kappa oe is greater than (or less than) kappa ov clockwise (or counterclockwise) hysteresis occurs. Given kappa oe and kappa ov, numerical (constrained) deconvolution is used to obtain the disposition function of the arterial compartment (Ha), and convolution is used to calculate Ce given Ha. The values of kappa oe and kappa ov are chosen to collapse the hysteresis loops to single curves representing the Ce-E (steady-state) concentration-response curve. Simulations, and an application to real data, are reported.

Non-parametric treatment time-lag effect estimation

2021 ◽  
pp. 096228022110326
Author(s):  
Kristine Gierz ◽  
Kayoung Park ◽  
Peihua Qiu
Keyword(s):  
Survival Data ◽  
Treatment Time ◽  
Time Lag ◽  
Simulated Data ◽  
Real Data ◽  
Point Problem ◽  
Change Point Problem ◽  
Lag Effect ◽  
Effect Estimation ◽  
Non Parametric

In general, the change point problem considers inference of a change in distribution for a set of time-ordered observations. This has applications in a large variety of fields, and can also apply to survival data. In survival analysis, most existing methods compare two treatment groups for the entirety of the study period. Some treatments may take a length of time to show effects in subjects. This has been called the time-lag effect in the literature, and in cases where time-lag effect is considerable, such methods may not be appropriate to detect significant differences between two groups. In this paper, we propose a novel non-parametric approach for estimating the point of treatment time-lag effect by using an empirical divergence measure. Theoretical properties of the estimator are studied. The results from the simulated data and the applications to real data examples support our proposed method.

A Study on Energy Consumption and CO2 Emissions in End-Life Cycle of Residential Buildings

2013 ◽  
Vol 689 ◽  
pp. 226-229
Author(s):  
Gi Wook Cha ◽  
Won Hwa Hong ◽  
Sung Woo Shin
Keyword(s):  
Climate Change ◽  
Life Cycle ◽  
Energy Consumption ◽  
Quantitative Analysis ◽  
Environmental Impact ◽  
Residential Buildings ◽  
Inventory Analysis ◽  
Intergovernmental Panel ◽  
Ipcc Guidelines

In recent years, demolition work in Korea has been rapidly increasing, and accordingly, its environmental impact has become significant, thus requiring quantitative analysis on energy consumption and CO2 emissions generated during demolition work. This study aims to examine energy consumption and CO2 emissions in the end-life cycle of buildings. In this study, inventory analysis was conducted and basic units of energy consumption and CO2 emissions were calculated in accordance with Intergovernmental Panel on Climate Change (IPCC) guidelines published in 1996. Major findings show that 64% of energy consumption and CO2 emissions in buildings’ end-life cycle is generated in the demolition phase, and 36% in the transportation phase.

Noise removal by migration of time-shift images

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. S105-S111 ◽  
Author(s):  
Sheng Xu ◽  
Feng Chen ◽  
Bing Tang ◽  
Gilles Lambare
Keyword(s):  
Time Lag ◽  
Real Data ◽  
Velocity Model ◽  
Noise Removal ◽  
Time Shift ◽  
Reverse Time ◽  
Coherent Noise ◽  
Data Set ◽  
Depth Migration ◽  
Time Migration

When using seismic data to image complex structures, the reverse time migration (RTM) algorithm generally provides the best results when the velocity model is accurate. With an inexact model, moveouts appear in common image gathers (CIGs), which are either in the surface offset domain or in subsurface angle domain; thus, the stacked image is not well focused. In extended image gathers, the strongest energy of a seismic event may occur at non-zero-lag in time-shift or offset-shift gathers. Based on the operation of RTM images produced by the time-shift imaging condition, the non-zero-lag time-shift images exhibit a spatial shift; we propose an approach to correct them by a second pass of migration similar to zero-offset depth migration; the proposed approach is based on the local poststack depth migration assumption. After the proposed second-pass migration, the time-shift CIGs appear to be flat and can be stacked. The stack enhances the energy of seismic events that are defocused at zero time lag due to the inaccuracy of the model, even though the new focused events stay at the previous positions, which might deviate from the true positions of seismic reflection. With the stack, our proposed approach is also able to attenuate the long-wavelength RTM artifacts. In the case of tilted transverse isotropic migration, we propose a scheme to defocus the coherent noise, such as migration artifacts from residual multiples, by applying the original migration velocity model along the symmetry axis but with different anisotropic parameters in the second pass of migration. We demonstrate that our approach is effective to attenuate the coherent noise at subsalt area with two synthetic data sets and one real data set from the Gulf of Mexico.

Comparison of Green-House Gas Emission Reduction and Cost-Effectiveness between Two Ways of Waste-to-Energy - Case Study of Tianjin, China

2013 ◽  
Vol 726-731 ◽  
pp. 2641-2644
Author(s):  
Yu He ◽  
Yuan Wang ◽  
Bei Bei Yan ◽  
Meng Han
Keyword(s):  
Cost Benefit Analysis ◽  
Landfill Gas ◽  
Cost Benefit ◽  
Waste To Energy ◽  
Ghg Emission ◽  
Intergovernmental Panel ◽  
Gas Utilization ◽  
Ghg Reduction ◽  
Ipcc Guidelines ◽  
The Cost

There are two main waste-to-energy (WtE) ways to treat municipal solid waste (MSW) in China: incineration with electricity and landfill with landfill gas utilization. And the calculation methods provided by Intergovernmental Panel on Climate Change (IPCC) Guidelines are often used for calculating greenhouse gas (GHG) reduction of WtE. This paper compared the GHG emission reductions of the two WtE methods, and made a cost-benefit analysis of them. Results show that: incineration with electricity can reduce more GHG emission than landfill with landfill gas utilization while disposing of 1 t MSW and the cost of incineration is higher than landfill while reducing 1 t CO2eq.

scholarly journals A comparison of continuous and discrete time modeling of affective processes in terms of predictive accuracy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tim Loossens ◽  
Francis Tuerlinckx ◽  
Stijn Verdonck
Keyword(s):  
Discrete Time ◽  
Predictive Accuracy ◽  
Time Lag ◽  
Real Data ◽  
Time Intervals ◽  
Vector Autoregressive ◽  
Unequally Spaced ◽  
Time Modeling ◽  
Affective Processes ◽  
Short Time

AbstractIntra-individual processes are thought to continuously unfold across time. For equally spaced time intervals, the discrete-time lag-1 vector autoregressive (VAR(1)) model and the continuous-time Ornstein–Uhlenbeck (OU) model are equivalent. It is expected that by taking into account the unequal spacings of the time intervals in real data between observations will lead to an advantage for the OU in terms of predictive accuracy. In this paper, this is claim is being investigated by comparing the predictive accuracy of the OU model to that of the VAR(1) model on typical ESM data obtained in the context of affect research. It is shown that the VAR(1) model outperforms the OU model for the majority of the time series, even though time intervals in the data are unequally spaced. Accounting for measurement error does not change the result. Deleting large abrupt changes on short time intervals (that may be caused by externally driven events) does however lead to a significant improvement for the OU model. This suggests that processes in psychology may be continuously evolving, but that there are factors, like external events, which can disrupt the continuous flow.

scholarly journals Multi-gas and multi-source comparisons of six land use emission datasets and AFOLU estimates in the Fifth Assessment Report

2016 ◽  
Author(s):  
Rosa Maria Roman-Cuesta ◽  
Martin Herold ◽  
Mariana C. Rufino ◽  
Todd S. Rosenstock ◽  
Richard A. Houghton ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Forest Sector ◽  
Intergovernmental Panel ◽  
Enteric Fermentation ◽  
Assessment Report ◽  
Carbon Neutrality ◽  
Ipcc Guidelines ◽  
Agricultural Emissions ◽  
The Tropics

Abstract. The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20–25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates remain, however, highly uncertain, jeopardizing the mitigation effectiveness of this sector. Global comparisons of AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding on the reasons behind these differences. Here we compare a diversity of AFOLU emission datasets (e.g. FAOSTAT, EDGAR, the newly developed AFOLU "Hotspots", "Houghton", "Baccini", and EPA) and estimates given in the Fifth Assessment Report, for the tropics (2000–2005), to identify plausible explanations for the differences in: i) aggregated gross AFOLU emissions, and ii) disaggregated emissions by sources, and by gases (CO2, CH4, N2O). We also aim to iii) identify countries with low agreement among AFOLU datasets, to navigate research efforts. Aggregated gross emissions were similar for all databases for the AFOLU: 8.2 (5.5–12.2), 8.4 and 8.0 Pg CO2e. yr−1 (Hotspots, FAOSTAT and EDGAR respectively), Forests: 6.0 (3.8–10), 5.9, 5.9 and 5.4 Pg CO2e. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and Agricultural sectors: 1.9 (1.5–2.5), 2.0, 2.1, and 2.0 Pg CO2e. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating by sources, continents, and gases, particularly for the forest sector (fire leading the differences). Agricultural emissions were more homogeneous, especially livestock, while croplands were the most diverse. CO2 showed the largest differences among datasets. Cropland soils and enteric fermentation led the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (e.g. carbon-only vs multi-gas assessments, definitions, land use versus land cover, etc), in methods (Tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc) and in assumptions (e.g. carbon neutrality of certain emissions, instantaneous emissions release, etc) that call for more complete and transparent documentation for all the available datasets. Enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

scholarly journals Assessing Energy-Based CO2 Emission and Workers’ Health Risks at the Shipbreaking Industries in Bangladesh

Environments ◽  
2020 ◽  
Vol 7 (5) ◽  
pp. 35
Author(s):  
Nandita Mitra ◽  
Shihab Ahmad Shahriar ◽  
Nurunnaher Lovely ◽  
Md Shohel Khan ◽  
Aweng Eh Rak ◽  
...  
Keyword(s):  
Health Risks ◽  
Environmental Protection Agency ◽  
Co2 Emission ◽  
Electricity Consumption ◽  
Health Condition ◽  
Control Area ◽  
Intergovernmental Panel ◽  
Environmental Consequences ◽  
Ipcc Guidelines ◽  
Gwr Model

The study represents the estimation of energy-based CO2 emission and the health risks of workers involved in the shipbreaking industries in Sitakunda, Bangladesh. To calculate the carbon emission (CE) from three shipbreaking activities, i.e., metal gas cutting (GC), diesel fuel (FU) and electricity consumption (EC), we used the Intergovernmental Panel on Climate Change (IPCC) guidelines and Environmental Protection Agency (EPA)’s Emission and Generation Resource Integrated Database (eGRID) emission factors. Moreover, the geographic weighted regression (GWR) model was applied to assess the contribution of influencing factors of CE throughout the sampling points. To assess the workers’ health condition and their perceptions on environmental degradation, a semi-structured questionnaire survey among 118 respondents were performed. The results showed that total CO2 emissions from GC were 0.12 megatons (MT), 11.43 MT, and 41.39 MT for daily, monthly, and yearly respectively, and the values were significantly higher than the surrounding control area. Emissions from the FU were estimated as daily: 0.85 MT, monthly: 1.92 MT, and yearly: 17.91 MT, which were significantly higher than EC. The study also revealed that workers were very susceptible to accidental hazards especially death (91%), and pollution (79%). Environmental consequences and health risks of the workers in shipbreaking industry warrant more attention nationally and internationally at the industry-level.

AIR POLLUTANT EMISSIONS IN BATAM: AN OVERVIEW

2015 ◽  
Vol 77 (23) ◽  
Author(s):  
Andy Triwinarko ◽  
Dwi Kartikasari ◽  
Didi Istardi ◽  
Syafei Ghozali ◽  
Dian Mulyaningtyas
Keyword(s):  
Large Scale ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Electronics Manufacturing ◽  
Tier 2 ◽  
Intergovernmental Panel ◽  
Policy Makers ◽  
Gas Stations ◽  
Mobile Sources ◽  
Ipcc Guidelines

This paper aims at providing high quality air pollutant emissions analysis, so that policy makers have reliable information in shaping environmental priorities. The study was conducted in Batam, a special economic zone that is packed by industries.Emissions of NOx, CO, SOx, PM10,  and HC were estimated using the 2013 EMEP/EEA methods and those of COx were estimated using the 2006 Intergovernmental Panel on Climate Change (IPCC) guidelines, both were tier 2 methods where applicable. We found that powerplants, large-scale heavy industrymetals and mobile sources were important emission sources, while area sources such ashotels, hospitals, restaurants, universities, banks, malls, vehicle repairs, housings, gas stations, facilities under constructions, landfills, and electronics manufacturing companiescontributed much less significant to the total emissions. By mapping all sources, we found that the air pollution sources densely populated along the main streets. Conclusively, this paper recommends some measures to improve the overall air quality in Batam.  

Russian Law on Climate Change

2016 ◽  
Author(s):  
Anna Korppoo ◽  
Max Gutbrod ◽  
Sergey Sitnikov
Keyword(s):  
Climate Change ◽  
Emissions Trading ◽  
Global Climate ◽  
Cost Effective ◽  
Climate Mitigation ◽  
Intergovernmental Panel ◽  
Industrial Countries ◽  
Ipcc Guidelines ◽  
Russian Law ◽  
Kyoto Mechanisms

This chapter outlines Russian legislation relevant to climate change. Russia ratified the Kyoto Protocol in 2004. The main legal elements of institutional compliance under the Protocol included requirements to submit annual greenhouse gas (GHG) inventories, following the Intergovernmental Panel on Climate Change (IPCC) guidelines, and to establish a registry to keep track of domestic emissions and implementation of the Kyoto mechanisms. The Federal Service of Russia for Hydrometeorology and Environmental Monitoring (Roshydromet), together with the Institute of Global Climate and Ecology, were designated as the entities responsible for developing Russia’s GHG inventory. Russia’s compliance was driven by its opportunity to participate in the Kyoto mechanisms. These flexibility mechanisms—Joint Implementation (JI) and International Emissions Trading—allow industrial countries to trade emission allowances in order to direct climate mitigation investments into the most cost-effective measures available.

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