Experience in Developing Legislation to Support South Africa's Mandatory GHG Emissions Reporting Program and National Inventory Data Flow

10.1596/29120 ◽  
2016 ◽  
Author(s):  
Keyword(s):  
Data Flow ◽  
Ghg Emissions ◽  
Inventory Data ◽  
National Inventory

scholarly journals Tree Height Increment Models for National Forest Inventory Data in the Pacific Northwest, USA

Forests ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 2
Author(s):  
Hyeyoung Woo ◽  
Bianca N. I. Eskelson ◽  
Vicente J. Monleon
Keyword(s):  
Pacific Northwest ◽  
Tree Height ◽  
The United States ◽  
Tree Level ◽  
Height Increment ◽  
Inventory Data ◽  
National Inventory ◽  
Poisson Models ◽  
The Pacific ◽  
Zero Inflated Poisson Models

The United States national inventory program measures a subset of tree heights in each plot in the Pacific Northwest. Unmeasured tree heights are predicted by adding the difference between modeled tree heights at two measurements to the height observed at the first measurement. This study compared different approaches for directly modeling 10-year height increment of red alder (RA) and ponderosa pine (PP) in Washington and Oregon using national inventory data from 2001–2015. In addition to the current approach, five models were implemented: nonlinear exponential, log-transformed linear, gamma, quasi-Poisson, and zero-inflated Poisson models using both tree-level (e.g., height, diameter at breast height, and compacted crown ratio) and plot-level (e.g., basal area, elevation, and slope) measurements as predictor variables. To account for negative height increment observations in the modeling process, a constant was added to shift all response values to greater than zero (log-transformed linear and gamma models), the negative increment was set to zero (quasi-Poisson and zero-inflated Poisson models), or a nonlinear model, which allows negative observations, was used. Random plot effects were included to account for the hierarchical data structure of the inventory data. Predictive model performance was examined through cross-validation. Among the implemented models, the gamma model performed best for both species, showing the smallest root mean square error (RSME) of 2.61 and 1.33 m for RA and PP, respectively (current method: RA—3.33 m, PP—1.40 m). Among the models that did not add the constant to the response, the quasi-Poisson model exhibited the smallest RMSE of 2.74 and 1.38 m for RA and PP, respectively. Our study showed that the prediction of tree height increment in Oregon and Washington can be improved by accounting for the negative and zero height increment values that are present in inventory data, and by including random plot effects in the models.

Down scaling to regional assessment of greenhouse gas emissions to enable consistency in accounting for emissions reduction projects and national inventory accounts for northern beef production in Australia

2016 ◽  
Vol 38 (3) ◽  
pp. 219 ◽  
Author(s):  
Sandra J. Eady ◽  
Guillaume Havard ◽  
Steven G. Bray ◽  
William Holmes ◽  
Javi Navarro
Keyword(s):  
Greenhouse Gas ◽  
Production Efficiency ◽  
Ghg Emissions ◽  
Emissions Reduction ◽  
Model Parameters ◽  
Reproduction Rate ◽  
National Accounts ◽  
Beef Production ◽  
National Inventory ◽  
State Territory

This paper explores the effect of using regional data for livestock attributes on estimation of greenhouse gas (GHG) emissions for the northern beef industry in Australia, compared with using state/territory-wide values, as currently used in Australia’s national GHG inventory report. Regional GHG emissions associated with beef production are reported for 21 defined agricultural statistical regions within state/territory jurisdictions. A management scenario for reduced emissions that could qualify as an Emissions Reduction Fund (ERF) project was used to illustrate the effect of regional level model parameters on estimated abatement levels. Using regional parameters, instead of state level parameters, for liveweight (LW), LW gain and proportion of cows lactating and an expanded number of livestock classes, gives a 5.2% reduction in estimated emissions (range +12% to –34% across regions). Estimated GHG emissions intensity (emissions per kilogram of LW sold) varied across the regions by up to 2.5-fold, ranging from 10.5 kg CO2-e kg–1 LW sold for Darling Downs, Queensland, through to 25.8 kg CO2-e kg–1 LW sold for the Pindan and North Kimberley, Western Australia. This range was driven by differences in production efficiency, reproduction rate, growth rate and survival. This suggests that some regions in northern Australia are likely to have substantial opportunities for GHG abatement and higher livestock income. However, this must be coupled with the availability of management activities that can be implemented to improve production efficiency; wet season phosphorus (P) supplementation being one such practice. An ERF case study comparison showed that P supplementation of a typical-sized herd produced an estimated reduction of 622 t CO2-e year–1, or 7%, compared with a non-P supplemented herd. However, the different model parameters used by the National Inventory Report and ERF project means that there was an anomaly between the herd emissions for project cattle excised from the national accounts (13 479 t CO2-e year–1) and the baseline herd emissions estimated for the ERF project (8 896 t CO2-e year–1) before P supplementation was implemented. Regionalising livestock model parameters in both ERF projects and the national accounts offers the attraction of being able to more easily and accurately reflect emissions savings from this type of emissions reduction project in Australia’s national GHG accounts.

Estimating crop net primary production using national inventory data and MODIS-derived parameters

2013 ◽  
Vol 80 ◽  
pp. 61-71 ◽  
Author(s):  
Varaprasad Bandaru ◽  
Tristram O. West ◽  
Daniel M. Ricciuto ◽  
R. César Izaurralde
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Inventory Data ◽  
National Inventory

scholarly journals National Greenhouse Gas Emissions Inventory – Romania

2010 ◽  
Vol 67 (2) ◽  
Author(s):  
Marian PROOROCU ◽  
Sorin DEACONU ◽  
Mihaela SMARANDACHE
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gas ◽  
Kyoto Protocol ◽  
Fossil Fuels ◽  
Ghg Emissions ◽  
Great Probability ◽  
Emissions Inventory ◽  
National Inventory ◽  
Commitment Period ◽  
Carbon Dioxide Co2

As a Party to the United Nations Framework Convention on Climate Change (UNFCCC), and its Kyoto Protocol, Romania is required to elaborate, regularly update and submit the national GHG Inventory. In compliance with the reporting requirements, Romania submitted in 2010 its ninth version of the National Inventory Report (NIR) covering the national inventories of GHG emissions/removals for the period 1989-2008. The inventories cover all sectors: Energy, Industrial Processes, Solvent and other product use, Agriculture, LULUCF and Waste. The direct GHGs included in the national inventory are: Carbon dioxide (CO2); Methane (CH4); Nitrous oxide (N2O); Hydrofluorocarbons (HFCs); Perfluorocarbons (PFCs); Sulphur hexafluoride (SF6). The emissions trend over the 1989-2008 period reflects the changes characterized by a process of transition to a market economy. With the entire economy in transition, some energy intensive industries reduced their activities and this is reflected in the GHG emissions reduction. Energy represents the most important sector in Romania, accounting for about 69% of the total national GHG emissions in 2008. The most significant anthropogenic greenhouse gas is the carbon dioxide. The decrease of CO2 emissions is caused by the decline of the amount of fossil fuels burnt in the energy sector, as a consequence of activity decline. According to the figures, there is a great probability for Romania to meet the Kyoto Protocol commitments on the limitation of the GHG emissions in the 2008-2012 commitment period.

scholarly journals Case study

2021 ◽  
Vol 9 (8) ◽  
pp. 252-262
Author(s):  
Thaisa Calvo Fugineri Moreti ◽  
Alexandre Garbosa ◽  
Ricardo Alan Verdú Ramos ◽  
Paulo Sérgio Barbosa dos Santos
Keyword(s):  
Ghg Emissions ◽  
The Other ◽  
Raw Material ◽  
Inventory Data ◽  
Technical Parameters ◽  
Production Models ◽  
National Office ◽  
The One ◽  
Biofuels Policy

The Brazilian National Biofuels Policy (RenovaBio) has as its main purpose to promote the growth of the biofuels chain in Brazil, from more efficient and sustainable production models, culminating in the reduction of greenhouse gas (GHG) emissions, as well as contributing to the fulfillment of the commitments assumed by the country at COP-21. RenovaCalc is a tool from RenovaBio that is capable of analyzing lifecycle inventory data of background processes, added to the technical parameters of agricultural and industrial production that is informed by the biofuel producer. The final product is given through an Energy-Environmental Efficiency Grade (NEEA). In this context, NEEA, together with raw material eligibility values, will serve as the basis for the calculation of decarbonization credits (CBios). Given this context, the present study sought to investigate three scenarios: S1: excluded agricultural phase; S2: 100% eligible soy combined with the use of beef tallow, and S3: production of biodiesel with 100% soybean oil. The study compared two biodiesel producing national industries to NEEA certified by the Brazilian National Office of Petroleum, Natural Gas and Biofuels (ANP). It can be concluded that NEEA does not have a direct influence on the quantity of CBios to be traded, that is, the highest ratio is given from the eligibility (%) of the raw material chosen for the production of the fuel. Thus, scenario 2, which relied on the use of waste, proved to be 10 times more profitable compared to the other scenarios, in both analyses, due to its high eligibility. However, in terms of NEEA, it was noted that the exclusion of the agricultural phase (scenario 1) was the one that was most efficient in terms of gCO2 eq./MJ. It is relevant to emphasize the importance of proper handling and practices that guarantee the traceability of the grain so that the eligibility indexes are optimized.

scholarly journals SISTEM INFORMASI INVENTORY DATA BARANG PADA UD. MUTIARA MEUBEL BERBASIS WEB

2019 ◽  
Vol 1 (1) ◽  
pp. 19-28
Author(s):  
Guslan ◽  
Rodianto
Keyword(s):  
Input Data ◽  
Data Flow ◽  
Flow Diagram ◽  
Input Output ◽  
Inventory Data ◽  
Data Flow Diagram

Sistem Informasi Inventory Data Barang Pada UD. Mutiara Meubel, yang bertujuan untuk memudahkan dalam proses meng-input data barang dan proses teransaksi yang tidak lagi dilakukan secara manual yang dapat berlangsung dengan lebih cepat dan efisien serta dapat mengurangi tingkat kesalahan yang mungkin terjadi. Metode penelitian yang dilakukan adalah kualitatif dengan melakukan pengumpulan data,observasi pengamatan secara langsung wawancara, dan dokumentasi.Data yang digunakan meliputi data stok barang data proses transaksi. Analisis data, serta metode perancangan sistem yang digunakan dibuat melalui tahapan-tahapan definisi alur kerja sistem yang berjalan, Data Flow Diagram, perancangan database, serta desain Input-Output sistem. Dari pengamatan serta penelitian yang dilakukan dapat diketahui. UD Mutiara Meubel memerlukan pengolahan data berupa sitem Informasi Inventory yang memudahkan dalam proses meng-input Barang dan mencari barang yang telah di-input, sehingga diharapkan akan menhasilkan Sistem Informasi Inventory Data Barang yang lebih baik dari sistem manual.

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