Carbon fluxes related to land use and land cover change in Baden-Württemberg

Spatially explicit information on carbon fluxes related to land use and land cover change (LULCC) is of value for the implementation of local climate change mitigation strategies. However, estimates of these carbon fluxes are often aggregated to larger areas. We estimated committed gross carbon fluxes related to LULCC in Baden-Württemberg, Germany, using different emission factors. In doing so, we compared four different data sources regarding their suitability for estimating the fluxes: (a) a land cover dataset derived from OpenStreetMap (OSMlanduse); (b) OSMlanduse with removal of sliver polygons (OSMlanduse cleaned), (c) OSMlanduse enhanced with a remote sensing time series analysis (OSMlanduse+); (d) the LULCC product of Landschaftsveränderungsdienst (LaVerDi) from the German Federal Agency of Cartography and Geodesy. We produced a high range of carbon flux estimates, mostly caused by differences in the area of the LULCC detected by the different change methods. Except for the OSMlanduse change method, all LULCC methods achieved results that are comparable to other gross emission estimates. The carbon flux estimates of the most plausible change methods, OSMlanduse cleaned and OSMlanduse+, were 291,710 Mg C yr^-1 and 93,591 Mg C yr^-1, respectively. Uncertainties were mainly caused by incomplete spatial coverage of OSMlanduse, false positive LULCC due to changes and corrections made in OpenStreetMap during the study period, and a high number of sliver polygons in the OSMlanduse changes. Overall, the results showed that OSM can be successfully used to estimate LULCC carbon fluxes if data preprocessing is performed with the suggested methods.

Assessing Vertical Allocation of Wildfire Smoke Emissions Using Observational Constraints From Airborne Lidar in the Western U.S

Wildfire emissions are a key contributor of carbonaceous aerosols and trace gases to the atmosphere. Induced by buoyant lifting, smoke plumes can be injected into the free troposphere and lower stratosphere, which by consequence significantly affects the magnitude and distance of their influences on air quality and radiation budget. However, the vertical allocation of emissions when smoke escapes the planetary boundary layer (PBL) and the mechanism modulating it remain unclear. We present an inverse modeling framework to estimate the wildfire emissions, with their temporal and vertical evolution being constrained by assimilating aerosol extinction profiles observed from the airborne Differential Absorption Lidar-High Spectral Resolution Lidar during the Fire Influence on Regional to Global Environments and Air Quality field campaign. Three fire events in the western U.S., which exhibit free-tropospheric injections are examined. The constrained smoke emissions indicate considerably larger fractions of smoke injected above the PBL (f _>PBL, 80%-94%) versus the column total, compared to those estimated by the WRF-Chem model using the default plume rise option (12%-52%). The updated emission profiles yield improvements for the simulated vertical structures of the downwind transported smoke, but limited refinement of regional smoke aerosol optical depth distributions due to the spatiotemporal coverage of flight observations. These results highlight the significance of improving vertical allocation of fire emissions on advancing the modeling and forecasting of the environmental impacts of smoke.

Airborne Emission Rate Measurements Validate Remote Sensing Observations and Emission Inventories of Western U.S. Wildfires

Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r² = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ^-1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

Estimating Long-Term Average Carbon Emissions from Fires in Non-Forest Ecosystems in the Temperate Belt

Research into pyrogenic carbon emissions in the temperate belt of the Russian Federation has traditionally focused on the impact of forest fires. Nevertheless, ecosystems in which wildfires also make a significant contribution to anthropogenic CO2 emissions are poorly studied. We evaluated the carbon emissions of fires in the non-forest ecosystems of the Middle Amur Lowland, in the Khabarovsk Territory of the Russian Federation. Our study is based on long-term Earth remote sensing data of medium spatial resolution (Landsat 5, 7, and 8) and expeditionary studies (2018–2021). The assessment of carbon directly emitted from wildfires in meadow and meadow–mire temperate ecosystems in the Middle Amur lowland shows that specific emissions from such ecosystems vary, from 1.09 t/ha in dwarf shrub–sphagnum and sphagnum–ledum and sedge–reed fens to 6.01 t/ha in reed–forb, forb, reed, and sedge meadows. Meanwhile, carbon emissions specifically from fires in meadow and meadow–mire ecosystems are less significant—often an order of magnitude less than carbon emissions from forest fires (which reach 37 tC/ha). However, due to their high frequency and the large areas of land burned annually, the total carbon emissions from such fires are comparable to annual emissions from fires in forested areas. The results obtained show that the inadequacy of the methods used in the automatic mapping of burns leads to a significant underestimation of the area of grassland fires and carbon emissions from non-forest fires.

Wildfires in the Siberian taiga

The majority of area burned by wildfire are located in Siberia. Mainly low-intensity surface fires occur in larch forests, whereas in evergreen forests both surface and crown fires are observed. Warming has led to an increase in the frequency and area of wildfires that have reached the Arctic Ocean shore. However, wildfires are the most important factor in taiga dynamics; larch and Scots pine have evolved under conditions of periodic forest fires, thereby gaining a competitive advantage over non-fire adapted species; in the permafrost zone, periodic fires are a prerequisite for the dominance of larch. Wildfires support ecosystem health, biodiversity, and conservation; periodic wildfires decrease the danger of catastrophic wildfires. With an amplified rate of increase in fires, it is necessary to focus fire suppression on areas of high social, natural, and economic value, while allowing a greater number of wildfires to burn in the vast Siberian forest landscapes.

Current Trend of Carbon Emissions from Wildfires in Siberia

Smoke from wildfires in Siberia often affects air quality over vast territories of the Northern hemisphere during the summer. Increasing fire emissions also affect regional and global carbon balance. To estimate annual carbon emissions from wildfires in Siberia from 2002–2020, we categorized levels of fire intensity for individual active fire pixels based on fire radiative power data from the standard MODIS product (MOD14/MYD14). For the last two decades, estimated annual direct carbon emissions from wildfires varied greatly, ranging from 20–220 Tg C per year. Sporadic maxima were observed in 2003 (>150 Tg C/year), in 2012 (>220 Tg C/year), in 2019 (~180 Tg C/year). However, the 2020 fire season was extraordinary in terms of fire emissions (~350 Tg C/year). The estimated average annual level of fire emissions was 80 ± 20 Tg C/year when extreme years were excluded from the analysis. For the next decade the average level of fire emissions might increase to 250 ± 30 Tg C/year for extreme fire seasons, and to 110 ± 20 Tg C/year for moderate fire seasons. However, under the extreme IPCC RPC 8.5 scenario for Siberia, wildfire emissions might increase to 1200–1500 Tg C/year by 2050 if there were no significant changes in patterns of vegetation distribution and fuel loadings.

Wildfire-Induced CO Plume Observations From NAST-I During the FIREX-AQ Field Campaign

The fire influence on regional to global environments and air quality (FIREX-AQ) field campaign was conducted during August 2019 to investigate the impact of wildfire and biomass smoke on air quality and weather in the continental United States. One of the campaign's scientific objectives was to estimate the composition of emissions from wildfires. Ultraspectrally resolved infrared radiance measurements from aircraft and/or satellite observations contain information on tropospheric carbon monoxide (CO) as well as other trace species present in fire emissions. A methodology for retrieving tropospheric CO from such remotely sensed spectral data has been developed for the National Airborne Sounder Testbed-Interferometer (NAST-I) and is applied herein. Retrievals based on NAST-I measurements are used to demonstrate CO retrieval capability and characterize fire emissions. NAST-I remotely sensed CO from ER-2 flights are evaluated with concurrent in situ measurements from the differential absorption carbon monoxide measurements flown on the NASA DC-8 aircraft. Enhanced CO emissions along with plume evolution and transport from the fire ground site locations were captured by moderate vertical and high horizontal resolution observations obtained from the NAST-I IR spectrometer; these were intercompared and verified by the cloud physics lidar and the enhanced MODIS airborne simulator also hosted on the NASA ER-2 aircraft. This study will be beneficial to the science community for studying wildfire-related topics and understanding similar remotely sensed observations from satellites, along with helping to address the broader FIREX-AQ experiment objectives of investigating the impact of fires on air quality and climate.

Geological methane emissions and wildfire risk in the degraded permafrost area of the Xiao Xing'an Mountains, China

With global warming, the carbon pool in the degradation zone of permafrost around the Arctic will gradually be disturbed and may enter the atmosphere in the form of released methane gas, becoming an important factor of environmental change in permafrost areas. We selected the northwestern section of the Xiao Xing'an Mountains in China as the study area, located in the degradation zone on the southern margin of the permafrost region in Eurasia, and set up multiple study monitoring areas equipped with methane concentration sensors, air temperature sensors, pore water pressure sensors and soil temperature sensors for long-term monitoring of data changes using the high-density electrical method, ground penetrating radar and on-site drilling to survey the distribution of frozen soil and geological conditions in the study area, combined with remote sensing images of Sentinel-2 L1C and unmanned aerial vehicle photographs and three-dimensional image reconstruction, analysis of fire activities and related geological environmental factors. The results show that since 2004, the permafrost thickness of the marsh wetland in the study area has gradually reduced and the degradation rate obviously accelerated; the organic matter and methane hydrate (metastable methane hydrate and stable methane hydrate) stored in the permafrost under the marsh wetland are gradually entering the atmosphere in the form of methane gas. Methane emissions show seasonal changes, and the annual methane emissions can be divided into three main stages, including a high-concentration short-term emission stage (March to May), a higher-concentration long-term stable emission stage (June to August) and a higher-concentration short-term emission stage (September to November); there is a certain correlation between the change in atmospheric methane concentration and the change in atmospheric pressure and pore water pressure. From March to May every year (high-concentration short-term emission stage), with snow melting, the air humidity reaches an annual low value, and the surface methane concentration reaches an annual high value. The high concentration of methane gas entering the surface in this stage is expected to increase the risk of wildfire in the permafrost degradation area in two ways (increasing the regional air temperature and self-combustion), which may be an important factor that leads to a seasonal wildfire frequency difference in the permafrost zone of Northeast China and Southeast Siberia, with the peak in spring and autumn and the monthly maximum in spring. The increase in the frequency of wildfires is projected to further generate positive feedback on climate change by affecting soil microorganisms and soil structure. Southeastern Siberia and northeastern China, which are on the southern boundary of the permafrost region of Eurasia, need to be targeted to establish fire warning and management mechanisms to effectively reduce the risk of wildfires.

Low-severity fire as a mechanism of organic matter protection in global peatlands: Thermal alteration slows decomposition

Worldwide, regularly recurring wildfires shape many peatland ecosystems to the extent that fire-adapted species often dominate plant communities, suggesting that wildfire is an integral part of peatland ecology rather than an anomaly. The most destructive blazes are smoldering fires that are usually initiated in periods of drought and can combust entire peatland carbon stores. However, peatland wildfires more typically occur as low-severity surface burns that arise in the dormant season when vegetation is desiccated, and soil moisture is high. In such low-severity fires, surface layers experience flash heating, but there is little loss of underlying peat to combustion. This study examines the potential importance of such processes in several peatlands that span a gradient from hemiboreal to tropical ecozones and experience a wide range of fire return intervals. We show that low-severity fires can increase the pool of stable soil carbon by thermally altering the chemistry of soil organic matter (SOM), thereby reducing rates of microbial respiration. Using X-ray photoelectron spectroscopy and Fourier transform infrared, we demonstrate that low-severity fires significantly increase the degree of carbon condensation and aromatization of SOM functional groups, particularly on the surface of peat aggregates. Laboratory incubations show lower CO₂ emissions from peat subjected to low-severity fire and predict lower cumulative CO₂ emissions from burned peat after 1-3 years. Also, low-severity fires reduce the temperature sensitivity (Q₁₀ ) of peat, indicating that these fires can inhibit microbial access to SOM. The increased stability of thermally altered SOM may allow a greater proportion of organic matter to survive vertical migration into saturated and anaerobic zones of peatlands where environmental conditions physiochemically protect carbon stores from decomposition for thousands of years. Thus, across latitudes, low-severity fire is an overlooked factor influencing carbon cycling in peatlands, which is relevant to global carbon budgets as climate change alters fire regimes worldwide.

A Comparison of Burned Area Time Series in the Alaskan Boreal Forests from Different Remote Sensing Products

Alaska’s boreal region stores large amounts of carbon both in its woodlands and in the grounds that sustain them. Any alteration to the fire system that has naturally regulated the region’s ecology for centuries poses a concern regarding global climate change. Satellite-based remote sensors are key to analyzing those spatial and temporal patterns of fire occurrence. This paper compiles four burned area (BA) time series based on remote sensing imagery for the Alaska region between 1982–2015: Burned Areas Boundaries Dataset-Monitoring Trends in Burn Severity (BABD-MTBS) derived from Landsat sensors, Fire Climate Change Initiative (Fire_CCI) (2001–2015) and Moderate-Resolution Imaging Spectroradiometer (MODIS) Direct Broadcast Monthly Burned Area Product (MCD64A1) (2000–2015) with MODIS data, and Burned Area-Long-Term Data Record (BA-LTDR) using Advanced Very High Resolution Radiometer LTDR (AVHRR-LTDR) dataset. All products were analyzed and compared against one another, and their accuracy was assessed through reference data obtained by the Alaskan Fire Service (AFS). The BABD-MTBS product, with the highest spatial resolution (30 m), shows the best overall estimation of BA (81%), however, for the years before 2000 (pre-MODIS era), the BA sensed by this product was only 44.3%, against the 55.5% obtained by the BA-LTDR product with a lower spatial resolution (5 km). In contrast, for the MODIS era (after 2000), BABD-MTBS virtually matches the reference data (98.5%), while the other three time series showed similar results of around 60%. Based on the theoretical limits of their corresponding Pareto boundaries, the lower resolution BA products could be improved, although those based on MODIS data are currently limited by the algorithm’s reliance on the active fire MODIS product, with a 1 km nominal spatial resolution. The large inter-annual variation found in the commission and omission errors in this study suggests that for a fair assessment of the accuracy of any BA product, all available reference data for space and time should be considered and should not be carried out by selective sampling.

A potential large and persistent black carbon forcing over Northern Pacific inferred from satellite observations

Black carbon (BC) aerosol strongly absorbs solar radiation, which warms climate. However, accurate estimation of BC's climate effect is limited by the uncertainties of its spatiotemporal distribution, especially over remote oceanic areas. The HIAPER Pole-to-Pole Observation (HIPPO) program from 2009 to 2011 intercepted multiple snapshots of BC profiles over Pacific in various seasons, and revealed a 2 to 5 times overestimate of BC by current global models. In this study, we compared the measurements from aircraft campaigns and satellites, and found a robust association between BC concentrations and satellite-retrieved CO, tropospheric NO2, and aerosol optical depth (AOD) (R2 > 0.8). This establishes a basis to construct a satellite-based column BC approximation (sBC*) over remote oceans. The inferred sBC* shows that Asian outflows in spring bring much more BC aerosols to the mid-Pacific than those occurring in other seasons. In addition, inter-annual variability of sBC* is seen over the Northern Pacific, with abundances varying consistently with the springtime Pacific/North American (PNA) index. Our sBC* dataset infers a widespread overestimation of BC loadings and BC Direct Radiative Forcing by current models over North Pacific, which further suggests that large uncertainties exist on aerosol-climate interactions over other remote oceanic areas beyond Pacific.

Understanding the Terrestrial Carbon Cycle: An Ecohydrological Perspective

The terrestrial carbon (C) cycle has a great role in influencing the climate with complex interactions that are spatially and temporally variable and scale-related. Hence, it is essential that we fully understand the scale-specific complexities of the terrestrial C-cycle towards (1) strategic design of monitoring and experimental initiatives and (2) also developing conceptualizations for modeling purposes. These complexities arise due to the nonlinear interactions of various components that govern the fluxes of mass and energy across the soil-plant-atmospheric continuum. Considering the critical role played by hydrological processes in governing the biogeochemical and plant physiological processes, a coupled representation of these three components (collectively referred to as ecohydrological approach) is critical to explain the complexity in the terrestrial C-cycling processes. In this regard, we synthesize the research works conducted in this broad area and bring them to a common platform with an ecohydrological spirit. This could aid in the development of novel concepts of nonlinear ecohydrological interactions and thereby help reduce the current uncertainties in the terrestrial C-cycling process. The usefulness of spatially explicit and process-based ecohydrological models that have tight coupling between hydrological, ecophysiological, and biogeochemical processes is also discussed.

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land-atmosphere carbon exchange. Previous forest recovery assessments using satellite optical-infrared normalized difference vegetation index (NDVI) and tower CO(2) eddy covariance techniques indicate rapid vegetation recovery within 5-10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post-fire vegetation response to inform regional recovery assessments. We analyzed a multi-year (2003-2010) satellite VOD record from the NASA AMSR-E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post-fire canopy biomass recovery within 3-7 years, lagging NDVI recovery by 1-5 years. The VOD lag was attributed to slower non-photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre-burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical-infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.

Spatial relationship between climatologies and changes in global vegetation activity

Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982-2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate-associated effects and a spatially correlated field representing the combined influence of other factors, including land-use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large-scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land-cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology).

Peat bog wildfire smoke exposure in rural North Carolina is associated with cardiopulmonary emergency department visits assessed through syndromic surveillance

BACKGROUND

In June 2008, burning peat deposits produced haze and air pollution far in excess of National Ambient Air Quality Standards, encroaching on rural communities of eastern North Carolina. Although the association of mortality and morbidity with exposure to urban air pollution is well established, the health effects associated with exposure to wildfire emissions are less well understood.

OBJECTIVE

We investigated the effects of exposure on cardiorespiratory outcomes in the population affected by the fire.

METHODS

We performed a population-based study using emergency department (ED) visits reported through the syndromic surveillance program NC DETECT (North Carolina Disease Event Tracking and Epidemiologic Collection Tool). We used aerosol optical depth measured by a satellite to determine a high-exposure window and distinguish counties most impacted by the dense smoke plume from surrounding referent counties. Poisson log-linear regression with a 5-day distributed lag was used to estimate changes in the cumulative relative risk (RR).

RESULTS

In the exposed counties, significant increases in cumulative RR for asthma [1.65 (95% confidence interval, 1.25-2.1)], chronic obstructive pulmonary disease [1.73 (1.06-2.83)], and pneumonia and acute bronchitis [1.59 (1.07-2.34)] were observed. ED visits associated with cardiopulmonary symptoms [1.23 (1.06-1.43)] and heart failure [1.37 (1.01-1.85)] were also significantly increased.

CONCLUSIONS

Satellite data and syndromic surveillance were combined to assess the health impacts of wildfire smoke in rural counties with sparse air-quality monitoring. This is the first study to demonstrate both respiratory and cardiac effects after brief exposure to peat wildfire smoke.

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.

Increase in carbon emissions from forest fires after intensive reforestation and forest management programs

This paper shows an example of substantial increase in carbon emissions from forest fires after reforestation on a national scale. It is the first estimation of historical carbon emissions from forest fires in Korea during the last 40 years. Investigation was focused on the recent increase in large forest fires and its closely related factors. A simple modeling approach to estimate carbon emission was applied. The direct carbon emission from forest fires in 2000, ranging from 115 to 300 Gg C, corresponds to 1-3% of the annual carbon uptake by forests. The influence of forest fires on the carbon cycle in Korea is not so significant, but Korean forests have a large potential for generating severe local fires due to increasing forest carbon density and a high forest area ratio (forest area/total land area) of 65%. The carbon emission per area burned (Mg C ha(-1)) clearly reflects the trend toward increases in the number of severe fires. Statistical analyses and the trends of annual temperature and precipitation show that the recent large increase in carbon emissions may be the negative consequences of intensive forest regrowth that is the product of successful reforestation and forest management programs rather than the effect of climate change. These results imply a need for further studies in other countries, where large-scale plantation has been conducted, to evaluate the role of plantation and forest fires on the global carbon cycle.