Jessica L. McCarty

Remote sensing estimates of stand-replacement fires in Russia, 2002?2011

The presented study quantifies the proportion of stand-replacement fires in Russian forests through the integrated analysis of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data products. We employed 30 m Landsat Enhanced Thematic Mapper Plus derived tree canopy cover and decadal (2001–2012) forest cover loss (Hansen et al 2013 High-resolution global maps of 21st-century forest cover change Science 342 850–53) to identify forest extent and disturbance. These data were overlaid with 1 km MODIS active fire (earthdata.nasa.gov/ data/near-real-time-data/firms) and 500 m regional burned area data (Loboda et al 2007 Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data Remote Sens. Environ. 109 429–42 and Loboda et al 2011 Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm Int. J. Wildl. Fire 20 487–96) to differentiate stand-replacement disturbances due to fire versus other causes. Total stand replacement forest fire area within the Russian Federation from 2002 to 2011 was estimated to be 17.6 million ha (Mha). The smallest stand-replacement fire loss occurred in 2004 (0.4 Mha) and the largest annual loss in 2003 (3.3 Mha). Of total burned area within forests, 33.6% resulted in stand-replacement. Light conifer stands comprised 65% of all nonstand-replacement and 79% of all stand-replacement fire in Russia. Stand-replacement area for the study period is estimated to be two times higher than the reported logging area. Results of this analysis can be used with historical fire regime estimations to develop effective fire management policy, increase accuracy of carbon calculations, and improve fire behavior and climate change modeling efforts.

Pollution and its Impacts on the South American Cryosphere

This article is a review of the science goals and activities initiated within the framework of the Pollution and its Impacts on the South American Cryosphere (PISAC) initiative. Air pollution associated with biomass burning and urban emissions affects extensive areas of South America. We focus on black carbon (BC) aerosol and its impacts on air quality, water availability, and climate, with an emphasis on the Andean cryosphere. BC is one of the key short-lived climate pollutants that is a topic of growing interest for near-term mitigation of these issues. Limited scientific evidence indicates that the Andean cryosphere has already responded to climate change with receding glaciers and snow cover, which directly affect water resources, agriculture, and energy production in the Andean region of South America. Despite the paucity of systematic observations along the Andes, a few studies have detected BC on snow and glaciers in the Andes. These, in addition to existing and projected emissions and weather patterns, suggest a possible contribution of BC to the observed retreat of the Andean cryosphere. Here we provide an overview of the current understanding of these issues from scientific and policy perspectives, and propose strategic expansions to the relevant measurement infrastructure in the region.

Management and climate contributions to satellite-derived active fire trends in the contiguous United States.

Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001–2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001–2010. Active fires in croplands, in contrast, increased at a rate of 3.4% per year. Cropland and prescribed/other fire types combined were responsible for 77% of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9% per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems. Key Points Wildland, cropland, and prescribed fires had different trends and patterns Sensitivity to climate varied with fire type Intensity of air quality regulation influenced cropland burning trends

Estimating black carbon emissions from agricultural burning

High sensitivity of the Arctic region to short-lived climate forcers, including black carbon (BC), makes crop residue burning an important source of emissions. A high to moderate uncertainty in cropland burning emission estimates from remote sensing-based analyses currently exists and is problematic for establishing baseline estimates of black carbon emissions from global remote sensing products. Straw burning and possible BC emissions were estimated at the oblast level for Russia for years 2003 through 2010. A study was based on 1 km Moderate Resolution Spectroradiometer (MODIS) Active Fire Product, oblast level agricultural statistics, 1:25,000–1:50,000 scale GIS vector field maps and developing algorithms for calculating the size and intensity of fires as well as testing the accuracy of the predictions in areas with contrast land use. Both Active Fire Product and statistics methods demonstrated consistent results, including increasing fire activity in the years with additional straw surplus and the highest absolute values for vast territories with quite intensive grain production, mainly in European Russia. Straw burning can be a source of at least 1/3 total BC emissions from agriculture and grassland fires and does not appear to be the main source of total BC emissions for the Russian Federation. For regions with small number of cropland fires, the accuracy of existing remote sensing-based land cover products is insufficient for reliable classification of agricultural fires from satellite products. Incorrect classification of agricultural fires may exceed 25 %, increasing for the northern part of the country where forests are the predominant land cover. An improved method would be to calculate BC emissions from burned area using high resolution field masks and ground validation of fire sources in cropland areas.

Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources

ABSTRACT Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. One component of the biomass burning inventory, crop residue burning, has been poorly characterized in the National Emissions Inventory (NEI). In the 2011 NEI, wildland fires, prescribed fires, and crop residue burning collectively were the largest source of PM2.5. This paper summarizes our 2014 NEI method to estimate crop residue burning emissions and grass/pasture burning emissions using remote sensing data and field information and literature-based, crop-specific emission factors. We focus on both the postharvest and pre-harvest burning that takes place with bluegrass, corn, cotton, rice, soybeans, sugarcane and wheat. Estimates for 2014 indicate that over the continental United States (CONUS), crop residue burning excluding all areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay occurred over approximately 1.5 million acres of land and produced 19,600 short tons of PM2.5. For areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay, biomass burning emissions occurred over approximately 1.6 million acres of land and produced 30,000 short tons of PM2.5. This estimate compares with the 2011 NEI and 2008 NEI as follows: 2008: 49,650 short tons and 2011: 141,180 short tons. Note that in the previous two NEIs rangeland burning was not well defined and so the comparison is not exact. The remote sensing data also provided verification of our existing diurnal profile for crop residue burning emissions used in chemical transport modeling. In addition, the entire database used to estimate this sector of emissions is available on EPA’s Clearinghouse for Inventories and Emission Factors (CHIEF, http://www3.epa.gov/ttn/chief/index.html).Implications: Estimates of crop residue burning and rangeland burning emissions can be improved by using satellite detections. Local information is helpful in distinguishing crop residue and rangeland burning from all other types of fires.

Agricultural Fires in European Russia, Belarus, and Lithuania and Their Impact on Air Quality, 2002–2012

This chapter describes the first research to quantify air pollution emissions at a moderate to coarse scale from agricultural burning in Belarus, Lithuania, and European Russia using MODIS and Landsat-based estimates of fire, land-cover and land-use. Agricultural burning in Belarus, Lithuania, and European Russia showed a strong and consistent seasonal geographic pattern from 2002 to 2012, with the majority of fires occurring from March to June and a smaller peak in July and August. Over this 11-year period, there was a decrease in both cropland and pasture burning throughout the region. For Smolensk Oblast, a Russian administrative region with comparable agro-environmental conditions to Belarus and Lithuania, a detailed analysis of Landsat-based burned area estimations for croplands, pastures and field data collected in summer 2014 showed that the agricultural burning area can be up to 10 times larger than the 1 km MODIS active fire estimates. Using the annual MODIS and Landsat-based burned area estimations, we identified 25 carbon, particulate matter, volatile organic carbon (VOCs), and harmful air pollutants (HAPs) emissions for all agricultural burning, including both croplands and pastures. In general, European Russia is the main source of agricultural burning emissions. Lithuania and Belarus have relatively minor contributions. Indeed, emissions from certain agricultural burning air pollutants in European Russia are so large that they are equivalent to 5 % of emissions from all sectors (industry, energy, transportation, all sources of fire) in Lithuania and likely in other neighboring Eastern European countries.

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the twenty-first century

AbstractDuring the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts.

Use of Radarsat-2 and ALOS-PALSAR SAR images for wetland mapping in New Brunswick

Our study tests the use of dual-polarized (HH, HV) RADARSAT-2 C-band and ALOS-PALSAR L-band SAR images for mapping wetland areas in New Brunswick. The study also uses LANDSAT-5 TM and DEM data. The resulting maps were compared to GPS field data as well as to two wetland maps currently in use by the Province of New Brunswick. Overall the Random Forests classifier gave better classification accuracies than the maximum likelihood classifier. The comparison with the 146 wetland truth sites shows that 73.3% are correctly identified over the LANDSAT-5 TM classified image. For the SAR-based classified images, the number of correctly identified wetland ground truth sites is higher when the image acquired during the flooding is considered, the difference being higher with the ALOS-PALSAR images than with the RADARSAT-2 images. The number of correctly identified sites is the highest when both the ALOS-PALSAR images and RADARSAT-2 images are used (98.6%). These percentages of correctly identified wetland sites are well above of those computed using the DNR wetland and forested wetland maps (44.5 %).