scholarly journals Fostering Carbon Credits to Finance Wildfire Risk Reduction Forest Management in Mediterranean Landscapes

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1104
Author(s):  
Fermín Alcasena ◽  
Marcos Rodrigues ◽  
Pere Gelabert ◽  
Alan Ager ◽  
Michele Salis ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Cost Efficiency ◽  
Treatment Cost ◽  
Fire Regimes ◽  
Mediterranean Forest ◽  
Carbon Credits ◽  
Fuel Management ◽  
Wildfire Risk ◽  
Mediterranean Landscapes ◽  
High Emission

Despite the need for preserving the carbon pools in fire-prone southern European landscapes, emission reductions from wildfire risk mitigation are still poorly understood. In this study, we estimated expected carbon emissions and carbon credits from fuel management projects ongoing in Catalonia (Spain). The planning areas encompass about 1000 km2 and represent diverse fire regimes and Mediterranean forest ecosystems. We first modeled the burn probability assuming extreme weather conditions and historical fire ignition patterns. Stand-level wildfire exposure was then coupled with fuel consumption estimates to assess expected carbon emissions. Finally, we estimated treatment cost-efficiency and carbon credits for each fuel management plan. Landscape-scale average emissions ranged between 0.003 and 0.070 T CO2 year−1 ha−1. Fuel treatments in high emission hotspots attained reductions beyond 0.06 T CO2 year−1 per treated ha. Thus, implementing carbon credits could potentially finance up to 14% of the treatment implementation costs in high emission areas. We discuss how stand conditions, fire regimes, and treatment costs determine the treatment cost-efficiency and long-term carbon-sink capacity. Our work may serve as a preliminary step for developing a carbon-credit market and subsidizing wildfire risk management programs in low-revenue Mediterranean forest systems prone to extreme wildfires.

scholarly journals Hazards of Risk: Identifying Plausible Community Wildfire Disasters in Low-Frequency Fire Regimes

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 934
Author(s):  
Andy McEvoy ◽  
Becky K. Kerns ◽  
John B. Kim
Keyword(s):  
Risk Reduction ◽  
Low Frequency ◽  
Fire Regimes ◽  
Cascade Range ◽  
Private Land ◽  
Wildfire Risk ◽  
Location Data ◽  
Reduction Strategies ◽  
Community Exposure ◽  
Risk Reduction Strategies

Optimized wildfire risk reduction strategies are generally not resilient in the event of unanticipated, or very rare events, presenting a hazard in risk assessments which otherwise rely on actuarial, mean-based statistics to characterize risk. This hazard of actuarial approaches to wildfire risk is perhaps particularly evident for infrequent fire regimes such as those in the temperate forests west of the Cascade Range crest in Oregon and Washington, USA (“Westside”), where fire return intervals often exceed 200 years but where fires can be extremely intense and devastating. In this study, we used wildfire simulations and building location data to evaluate community wildfire exposure and identify plausible disasters that are not based on typical mean-based statistical approaches. We compared the location and magnitude of simulated disasters to historical disasters (1984–2020) in order to characterize plausible surprises which could inform future wildfire risk reduction planning. Results indicate that nearly half of communities are vulnerable to a future disaster, that the magnitude of plausible disasters exceeds any recent historical events, and that ignitions on private land are most likely to result in very high community exposure. Our methods, in combination with more typical actuarial characterizations, provide a way to support investment in and communication with communities exposed to low-probability, high-consequence wildfires.

scholarly journals Nonlinear Effects of Urbanization and Outward Foreign Direct Investment on Carbon Emissions in China

2018 ◽  
Vol 10 (12) ◽  
pp. 4411 ◽  
Author(s):  
Ming Yi ◽  
Mengqi Gong ◽  
Ting Wu ◽  
Yue Wang
Keyword(s):  
Foreign Direct Investment ◽  
Carbon Emissions ◽  
Direct Investment ◽  
Time Series Data ◽  
Series Data ◽  
Outward Foreign Direct Investment ◽  
Low Carbon ◽  
Markov Switching Model ◽  
Causality Test ◽  
High Emission

It is essential to explore the relationship between China’s urbanization, outward foreign direct investment, and carbon emissions, in order to better understand China’s carbon emissions reduction target. To this end, the nonlinear Granger causality test and Markov-switching model are applied to analyze the structural effects of urbanization and outward foreign direct investment on domestic emissions, on the basis of time series data from 1984–2016. The results show that the promotion effect of outward foreign direct investment on carbon emissions is increased from low-carbon regime to high-emission regime. Specifically, 1% increase in OFDI leads to a rise in carbon emissions by 0.064% and 0.112% under the former and latter regime respectively. Unlike the effect trend of outward foreign direct investment, the effect of urbanization on carbon emissions is decreased from a high-emission regime (5.221% rise in carbon emissions with 1% increase in the level of urbanization) to a low-carbon regime (3.133% rise in carbon emissions with 1% increase in the level of urbanization).

scholarly journals Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data

2020 ◽  
Vol 12 (18) ◽  
pp. 2916
Author(s):  
Yu Sun ◽  
Sheng Zheng ◽  
Yuzhe Wu ◽  
Uwe Schlink ◽  
Ramesh P. Singh
Keyword(s):  
Carbon Emissions ◽  
Infrared Imaging ◽  
Yangtze River Delta ◽  
Chinese Government ◽  
Low Carbon ◽  
Spatiotemporal Variations ◽  
Nighttime Light Data ◽  
Low Emission ◽  
High Emission ◽  
Nighttime Light

China is one of the largest carbon emitting countries in the world. Numerous strategies have been considered by the Chinese government to mitigate carbon emissions in recent years. Accurate and timely estimation of spatiotemporal variations of city-level carbon emissions is of vital importance for planning of low-carbon strategies. For an assessment of the spatiotemporal variations of city-level carbon emissions in China during the periods 2000–2017, we used nighttime light data as a proxy from two sources: Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The results show that cities with low carbon emissions are located in the western and central parts of China. In contrast, cities with high carbon emissions are mainly located in the Beijing-Tianjin-Hebei region (BTH) and Yangtze River Delta (YRD). Half of the cities of China have been making efforts to reduce carbon emissions since 2012, and regional disparities among cities are steadily decreasing. Two clusters of high-emission cities located in the BTH and YRD followed two different paths of carbon emissions owing to the diverse political status and pillar industries. We conclude that carbon emissions in China have undergone a transformation to decline, but a very slow balancing between the spatial pattern of high-emission versus low-emission regions in China can be presumed.

Evolution of Carbon Emission of Fossil Fuel Final Consumption in China: Industrial - Spatial Perspective

2013 ◽  
Vol 734-737 ◽  
pp. 1743-1746
Author(s):  
Guo Qing Yin ◽  
Ling Li Xu ◽  
Xue Du
Keyword(s):  
Carbon Emissions ◽  
Inner Mongolia ◽  
High Speed ◽  
Carbon Emission ◽  
Fossil Fuel ◽  
Statistical Data ◽  
Rich Region ◽  
Fossil Fuel Consumption ◽  
High Emission ◽  
Very High

This paper uses Chinas statistical data by industry and by region in 1995-2010 to calculate the carbon emission caused by the fossil fuel consumption. The total amount of carbon emission in 2010 was about 1.9 billion tons and it shows an increase of 150% compared with that in 1995, which shows a rapid increase year by year.The differentiation of carbon emission by industry is significant, while the manufacturing and transportation are the major emitting sectors. The differentiation of carbon emissions by region is significant as well, while the developed region and resource-rich region are the high emission regions. Some areas like Inner Mongolia have a very high speed growth.

Predictive modelling of fire occurrences from different fire spread patterns in Mediterranean landscapes

2015 ◽  
Vol 24 (3) ◽  
pp. 407 ◽  
Author(s):  
Andrea Duane ◽  
Míriam Piqué ◽  
Marc Castellnou ◽  
Lluís Brotons
Keyword(s):  
Environmental Changes ◽  
Regional Scale ◽  
Fire Regimes ◽  
Fire Spread ◽  
Global Changes ◽  
Strong Impact ◽  
Relative Contribution ◽  
Mediterranean Landscapes ◽  
Temporal Validation ◽  
In Fire

Fire regimes are shifting worldwide because of global changes. The relative contribution of climate, topography and vegetation greatly determines spatial and temporal variations in fire regimes, but the interplay of these factors is not yet well understood. We introduce here a novel classification of fires according to dominant fire spread pattern, an approach considered in operational firefighting, to help understand regional-scale spatial variability in fire regimes. Here, we studied whether climate, topography and fuel variables allowed the prediction of occurrences from different fire spread patterns in Catalonia, NE Spain. We used a correlative modelling approach based on maximum entropy methods, and examined, through variation partitioning, the relative contribution of different factors on determining their occurrence. Our results accurately predicted the occurrence of different fire spread patterns, and the results were consistent when temporal validation was conducted. Although forest fuel factors made a higher contribution to the occurrence of convective fires, wind-driven fires were strongly related to topographic and climate factors. These findings may have a strong impact on investigations into how fire regimes may be projected into the future under forecast global change as they suggest that future environmental changes may affect different fire spread patterns in an idiosyncratic manner.

scholarly journals A fire model with distinct crop, pasture, and non-agricultural burning: Use of new data and a model-fitting algorithm for FINALv1

2017 ◽  
Author(s):  
Sam S. Rabin ◽  
Sergey L. Malyshev ◽  
Brian I. Magi ◽  
Elena Shevliakova ◽  
Stephen W. Pacala
Keyword(s):  
Carbon Emissions ◽  
Regional Scale ◽  
Model Fitting ◽  
Fire Regimes ◽  
Optimization Method ◽  
Sub Saharan Africa ◽  
Burned Area ◽  
Pasture Management ◽  
Fire Models ◽  
Agricultural Burning

Abstract. This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land-cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001–2009 (global totals: 0.434 × 106 and 2.02 × 106 km2 yr−1 modeled, 0.454 × 106 and 2.04 × 106 km2 yr−1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.297 PgC yr−1 and 0.712 PgC yr−1 modeled, 0.194 PgC yr−1 and 0.538 PgC yr−1 observed). The non-agricultural fire module underestimates global burned area (1.66 × 106 km2 yr−1 modeled, 2.44 × 106 km2 yr−1 observed) and carbon emissions (1.33 PgC yr−1 modeled, 1.84 PgC yr−1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, central Asia, and Australia, whereas the boreal zone suffers from underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets.

Spatial data for national fire planning and fuel management

2001 ◽  
Vol 10 (4) ◽  
pp. 353 ◽  
Author(s):  
Colin C. Hardy ◽  
Kirsten M. Schmidt ◽  
James P. Menakis ◽  
R. Neil Sampson
Keyword(s):  
Risk Assessment ◽  
Resource Management ◽  
Spatial Data ◽  
Fire Regime ◽  
National Level ◽  
Fire Regimes ◽  
Risk Assessments ◽  
Fuel Management ◽  
Data Products ◽  
Data Layers

This paper was presented at the conference ‘Integrating spatial technologies and ecological principles for a new age in fire management’, Boise, Idaho, USA, June 1999 Spatial data products are most often developed to support resource management decisions. Rarely can the data stand by themselves as spatially-explicit risk assessments. We discuss the technical aspects of true risk assessments, and the contrast between risk assessments and the underlying spatial data that an agency might use to perform one. We then present the development methodology and results from a comprehensive, national effort at creating resource data products that may be useful in agency- or geographically-specific risk assessments. We have produced a suite of spatial data layers, each a continuous coverage for the conterminous United States, to support national-level, programmatic planning efforts for fire and fuel management. This document describes the development of seven data layers: (1) Potential Natural Vegetation Groups; (2) Current Cover Types; (3) Historical Natural Fire Regimes; (4) Current Condition Classes; (5) National Fire Occurrence; (6) Potential Fire Characteristics; and (7) Population Density Groups. This paper documents the methodology used to develop the spatial products. We used a Geographic Information System (GIS) to integrate biophysical and remote sensing products with disturbance and succession processes. We then assigned attributes developed from succession diagrams to combinations of biophysical, current vegetation, and historical fire regime data layers. Regional ecologists, silviculturists, and fire managers developed the succession diagrams, reviewed and refined the data layers, and assigned condition classes. None of these data layers were developed to stand alone as an integrated risk assessment. Technically-robust risk assessments require quantification not only of the probability of an event occurring—wildland fire in this case—but also of the values at risk of damage or loss. The ‘values’ component of a risk assessment is highly dependent on the resource management policies and objectives of the responsible agency. The data presented here were developed for integration by individual agencies into agency-specific plans and risk assessments. For example, planners will use the Current Condition Class data to allocate resources for fire and fuel management. These data are posted on the national, USDA Forest Service website http://fs.fed.us/fire/fuelman.

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