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CO2 emissions from forests
Nature Geoscience
Abstract
Deforestation is the second largest anthropogenic source of carbon
dioxide to the atmosphere, after fossil fuel combustion. Following a
budget reanalysis, the contribution from deforestation is revised
downwards, but tropical peatlands emerge as a notable carbon dioxide
source.
... 9 This mainly occurs in tropical regions and is the second largest anthropogenic source of carbon dioxide in the atmosphere but has the largest relative uncertainty, namely in the order of 50%, among the components of the global carbon balance. 1,10-12 Current estimates of gross carbon emissions from deforestation in tropical forests range from 0.81 to 2.9 Pg C/year [13][14][15][16][17][18][19][20][21] in the 1990s and 2000s, and uncertainty exists regarding whether tropical forests are a net carbon sink or source. Some studies have shown that the amount of CO 2 released into the atmosphere from tropical deforestation is similar to that absorbed by growing forests, 17,22 whereas others have reported that tropical forests are a net carbon source. ...
... In early studies, the forest areas reported to the United Nations Food and Agriculture Organization by country and forest inventory plot data were used to obtain the statistics of global forest changes and carbon emissions from deforestation. 6,12,13,[15][16][17] The advent of global coverage by high-resolution optical satellite imagery led to the widespread use of satellite data to map forest loss. 3,14,[21][22][23] However, the estimation of forest carbon stock density requires different techniques. ...
The role of tropical forests in the global carbon budget remains controversial, as carbon emissions from deforestation are highly uncertain. This high uncertainty arises from the use of either fixed forest carbon stock density or maps generated from satellite-based optical reflectance with limited sensitivity to biomass to generate accurate estimates of emissions from deforestation. New space missions aiming to accurately map the carbon stock density rely on direct measurements of the spatial structures of forests using lidar and radar. We found that lost forests are special cases, and their spatial structures can be directly measured by combining archived data acquired before and after deforestation by space missions principally aimed at measuring topography. Thus, using biomass mapping, we obtained new estimates of carbon loss from deforestation ahead of forthcoming space missions. Here, using a high-resolution map of forest loss and the synergy of radar and lidar to estimate the aboveground biomass density of forests, we found that deforestation in the 2000s in Latin America, one of the severely deforested regions, mainly occurred in forests with a significantly lower carbon stock density than typical mature forests. Deforestation areas with carbon stock densities lower than 20.0, 50.0, and 100.0 Mg C/ha accounted for 42.1%, 62.0%, and 83.3% of the entire deforested area, respectively. The average carbon stock density of lost forests was only 49.13 Mg C/ha, which challenges the current knowledge on the carbon stock density of lost forests (with a default value 100 Mg C/ha according to the Intergovernmental Panel on Climate Change Tier 1 estimates, or approximately 112 Mg C/ha used in other studies). This is demonstrated over both the entire region and the footprints of the spaceborne lidar. Consequently, our estimate of carbon loss from deforestation in Latin America in the 2000s was 253.0 ± 21.5 Tg C/year, which was considerably less than existing remote-sensing-based estimates, namely 400–600 Tg C/year. This indicates that forests in Latin America were most likely not a net carbon source in the 2000s compared to established carbon sinks. In previous studies, considerable effort has been devoted to rectify the underestimation of carbon sinks; thus, the overestimation of carbon emissions should be given sufficient consideration in global carbon budgets. Our results also provide solid evidence for the necessity of renewing knowledge on the role of tropical forests in the global carbon budget in the future using observations from new space missions.
... Unfortunately, unsustainable use of this resource leads to the degradation and loss of forest resources worldwide. Deforestation and forest degradation contribute 12-20 % of greenhouse gas emissions (Saatchi et al., 2011;van der Werf et al., 2009). In response to this problem, the United Nations Framework Convention on Climate Change (UNFCCC) proposes reducing emissions from degradation and deforestation; and integrating conservation and sustainable forest management to enhance forest carbon stocks (REDD+) as a solution for developing countries (Vanderhaegen et al., 2015). ...
Forest biomass is estimated using a volume model, wood basic density (wbd), and biomass expansion factor (BEF). However, in Ethiopia, there is a shortage of volume models, hence the volume estimation was carried out using a generic model. As a result, estimation may be subject to bias when applied in areas outside its original geographic range of development. Consequently, there is a need for further research and data collection to enhance the accuracy and reliability of these equations. This study aims to develop species-specific volume models, biomass expansion factors, wood basic densities, and form factors for selected tree species in the moist evergreen Afromontane Forest of Ethiopia. A total of 59 trees were harvested for volume model, BEF, and wbd development. Nonlinear regression was employed to develop the models, and the developed models were compared with previously established models using goodness-of-fit measures. For the volume model, diameter at breast height explained 89 % - 99 % of the volume variation. Comparison with previously developed models indicates that the currently developed model yields the least error. The mean BEF for the study species was 1.58, while the mean wood basic density for all tree species was 0.58 g/cm3. The study demonstrated that species-specific volume models reduce errors in the estimation of forest volume and biomass.
... Te relentless pursuit of economic expansion, especially regarding natural resources like forests, puts signifcant pressure on them. Deforestation, a major contributor to carbon emissions after burning fossil fuels [15], has led to changes in global land use and decreased forest coverage. Practices such as wood harvesting for agriculture contribute to atmospheric carbon emissions. ...
The intricate relationship between economic growth, environmental quality, and energy consumption has been extensively debated and studied on a global scale. The impacts of ecological quality on economic growth have been observed to be both positive and negative, particularly about human health as a result of pollutant emissions. It is essential to examine the compatibility between economic growth and environmental improvement, particularly through the reduction of emissions. This study aimed to investigate the connection between economic growth in forested areas and the corresponding impact on carbon dioxide (CO2) emissions in Nepal (Rose and Fisher, 1970). The analysis utilized time series data from 1990 to 2020, employing the dynamic ordinary least squares (DOLS) method. The DOLS results demonstrated a positive and statistically significant relationship between economic growth and CO2 emissions (Shafik and Bandyopadhyay, 1992). Specifically, an increase of Rs. 10 million in gross domestic product (GDP) corresponded to a 0.6112 kiloton increase in CO2 emissions. In contrast, the long-term coefficient for forested areas exhibited a substantial association, indicating that a reduction of one square kilometer of forested area (deforestation) resulted in an increase of 68.37 kilotons in CO2 emissions in Nepal. These findings accentuate the divergent effects of economic progress and deforestation on carbon emissions in Nepal, with GDP growth contributing to a greater increase in emissions. Therefore, the implementation of effective strategies and economic measures, such as afforestation and reforestation, forest protection, sustainable forest management, and mechanisms like REDD+ (reducing emissions from deforestation and forest degradation plus), can play a vital role in mitigating carbon emissions while simultaneously addressing deforestation and ensuring long-term economic progress in Nepal.
... The concentration of atmospheric CO 2 increases mainly due to human activities, such as the burning of fossil fuels like coal, oil, and gas. Deforestation is the second-largest anthropogenic source of CO 2 to the atmosphere, after fossil fuel combustion (Van der Werf et al., 2009). Nabuurs et al. (2017) estimated that about 5.8 gigatonnes (Gt) of CO 2 are emitted worldwide annually, mostly due to deforestation. ...
Trees outside forests (ToF) play a vital role in reducing carbon from industrial activities and vehicles by sequestering and storing atmospheric Co2 generated as biomass. However, there is a scarcity of studies quantifying the biomass and carbon stock in the ToFs. To bridge this gap, we conducted a study on the potential of biomass and carbon dioxide sequestration in trees planted in Puducherry. Our findings show that the total above-ground biomass of adult trees in the city was 1926.03 Megagram (Mg), while belowground biomass was 244.47 Mg. The total carbon stored in adult trees was 966.53 Mg, while the volume of sequestered CO2 was 3547.17 Mg in the study area. To increase carbon dioxide sequestration in Puducherry town, we recommend increasing urban green cover and planting more fast-growing native species.
... Notwithstanding that it has been demonstrated that the conversion of construction land to arable land increased carbon storage [69]. Most scholars focus on forest carbon sinks and carbon emissions from urban construction land [70][71][72], but we should think about urban areas as places that can be carbon sinks as well as forest areas can be source of carbon emissions when they are disturbed, when trees burn or death to old age, even more if forest suffers deforestation [73]. ...
The number of city residents worldwide is increasing at the same that soil consumption around cities, which can be mitigated using technosols. Urban areas need to provide a healthy environment for residents, but this is threatened by climate change. Mitigating the adverse impacts of climate change does not involve one-size-fits-all global solutions; cities face varying economic and social contexts. Cities need to offer ecosystem services in order to operate as healthy urban ecosystems. The urban soils’ environmental services are often overlooked, leading to public administrations having little to no awareness about land management policies and ecosystem services. Technosols, artificial or human altered soils, have the potential to provide the same ecosystem benefits as natural soils and do not require as much time to develop in order to perform their functions. Additionally, technosols have the potential to enhance the circular economy using waste materials. In this sense, policy makers should incorporate urban technosols as a strategy to enhance the health of cities and address climate change. Our perspective on soils in urban areas needs to be altered, as technosols should be included in urban policies, have the potential to serve as a crucial component in providing ecosystem services and acting as a carbon sink and enhance urban well-being.
... Forests play a crucial role in removing greenhouse gases directly and other ecosystem services such as climate regulation, water conservation, and biodiversity maintenance, which indirectly help mitigate climate change (Griscom et al., 2017;Cook-Patton et al., 2020). Forests also have various economic values to human production and life, and activities like deforestation become important carbon sources (van der Werf et al., 2009;Fahey et al., 2010). The numerous services and values thus also determine that the forest reserves and their distributions inevitably undergo dynamic changes when satisfying various human needs. ...
The subtropical region of China possesses abundant forest resources and features a mountainous terrain. Under the implementation of policies such as natural forest protection, the Grain for Green Project, and other initiatives since the beginning of the 21st century, coupled with climate change, the forest resources in this region have undergone significant changes compared to historical periods. In addition, forest resources distributing mainly in mountainous areas also implies that these changes may vary significantly with elevation. To explore the spatiotemporal dynamics of forest distribution in subtropical China since 2000, especially the trend of changes with elevation, we analyzed the data from two land cover products focusing on forest cover and forest types. We used a hierarchical approach, in which coarse-classification forest cover data with relatively small uncertainties impose constraints on forest type data with larger uncertainties, to achieve a reasonable balance between obtaining more details and reducing data uncertainty. We first divided the forest cover data into ‘unchanged’ and ‘changed’ categories. With the constraints by the forest cover results, we further analyzed the ‘unchanged’ and ‘changed’ forest types. The results indicated that, since the implementation of ecological engineering and management policies, 54% of the area in the subtropical region had maintained unchanged forest cover attributes over the past 20 years, which implied the good state of ecological environment. The results also showed that dynamic conversions existed in the long term between forests and lands for essential production needs like croplands. The elevational variations of forest cover suggested that the dominant changes came from the conversion between forests and croplands in low-elevation regions below 700 m, the conversion between forests and shrublands in mid-elevation regions of 700–1500 m, and the conversion between forests and grasslands in high-elevation regions above 2000 m. In the regions with unchanged forest cover, 96% exhibited unchanged forest types as well. Evergreen broad-leaved forests (EBF) were most widely distributed below 1700 m, while evergreen needle-leaved forests (ENF) dominated above 1700 m. There was still a large area of ENF and EBF undergoing dynamic conversions from/to transitional forest types such as mosaic of tree, shrub, and herbaceous cover (T-S-H) and mosaic of natural vegetation and cropland (NV-CRO). ENF almost unidirectionally transformed into T-S-H in low-elevation regions below 1000 m, and transformed from NV-CRO in mid- and high-elevation regions above 1000 m. EBF experienced an areal decrease and transformed into T-S-H in low-elevation regions, but the areal increase in mid- to low-elevation regions mainly transformed from NV-CRO. These variations with elevation may involve the impacts of specific human activities and climate change, and will provide a vertical dimension of information and perspectives for an in-depth exploration of the evolving ecosystem services of forest resources in subtropical China.
... For forest conservation efforts, the main challenge is to contain or mitigate forest disturbances, which includes both deforestation defined as "the conversion of forest to other land use independently of whether human-induced or not" [9], and forest degradation involving "the long-term reduction in the overall supply of benefits from forests, including timber, biodiversity and other products and services" [9]. Both lead to a number of environmental consequences, such as 6-17% of global CO 2 emissions [10][11][12], soil erosion, wildlife habit loss, reduction in biodiversity, etc. [1,13]. Global Forest Watch estimates that 459 Mha of forest was deforested worldwide between 2001 and 2022, equivalent to a 12% decline in tree cover since 2000 (www.globalforestwatch.org, ...
The study is part of the trend of searching for research methods to demonstrate changes in forest cover at the level of basic units of public administration with greater precision and accuracy. The purpose of the article is to present, for the first time, changes in forest cover of municipalities in Poland from 1990 to 2018 using CORINE Land Cover (CLC) data. The contributions of this study are threefold. Firstly, using GIS and CLC data (3.1. Forests), multivariate analyses of forest cover changes were carried out for 2481 municipalities for the CLC data collection years (1990, 2000, 2006, 2012, 2018), which showed the temporal and spatial dynamics of changes, with a predominance of deforestation in 1990–2000 and 2012–2018, and afforestation in 2000–2006 and 2006–2012. Secondly, the formal, legal and financial rationale for these changes was indicated. The increase in afforestation was a result of financial incentives under the National Program for Increasing Forest Cover and the EU’s Common Agricultural Policy (under Rural Development Programs—RDPs). Deforestation was related to a decrease in the supply of land for afforestation, the competitiveness of subsidies implemented under RDPs, and statutory liberalization of logging. Thirdly, the main discrepancies between the data obtained from CLC and from the public data collected by Statistics Poland (GUS) and the State Forests were indicated, which ranged from −32 kha to +310 kha, corresponding to percentage differences of 2.3% and 1.8%, respectively. This was mainly influenced by the differences in the complexity and updating of data collected for state and private forests, as well as delays in introducing changes to the land register by the public administration. This work contributes significantly to our understanding of the dynamics of forest cover changes in relation to the actual degree of forestation and deforestation, and the determinants of forest transformation in Polish municipalities, as well as demonstrating the new applicability of CLC data and their limitations related mainly to the generalization of forest cover area.
... Agronomy 2024, 14, 869 2 of 17 land to farmland, are likely to lead to SOC losses [9,10]. Despite previous extensive studies suggesting that SOC sequestration is a key measure to address global climate change [11][12][13], the current understanding of SOC stability processes under land-use changes remains limited. ...
Soil carbon content and stability are primarily influenced by the stabilization of particulate organic matter (POM) and mineral-associated organic matter (MAOM). Despite extensive research on the stabilization processes of POM and MAOM carbon components under various land-use types, the investigation into stabilization processes of soil carbon remains limited in saline–alkali soils. Therefore, we collected soil samples from different positions of saline–alkali drainage ditches at four reclamation times (the first, seventh, fifteenth, and thirtieth year) to determine their carbon content and physicochemical properties. Moreover, POM and MAOM fractions were separated from soil samples, and Fourier transform infrared spectra (FTIR) were used to investigate changes in their chemical composition. The results showed that with increasing reclamation time, the soil total carbon and soil organic carbon (SOC) contents significantly increased from 14 to 15 and 2.9 to 5.5 g kg−1, respectively. In contrast, soil inorganic carbon content significantly decreased from 11 to 9.6 g kg−1. Notably, the changes in soil carbon components following the increasing reclamation time were primarily observed in the furrow sole at a depth of 20–40 cm. While the SOC content of the POM fraction (SOCPOM) decreased significantly, the SOC content of the MAOM fraction (SOCMAOM) increased significantly. These alterations were largely dominated by drainage processes after reclamation instead of a possible conversion from SOCPOM to SOCMAOM. FTIR results revealed that MAOM was greatly influenced by the reclamation time more than POM was, but the change in both POM and MAOM contributed to an increase in soil carbon stability. Our findings will deepen the comprehension of soil carbon stabilization processes in saline–alkali drainage ditches after reclamation and offer a research framework to investigate the stability processes of soil carbon components via alterations in POM and MAOM fractions.
... Deforestation is seen as one of the consequences of trade openness and is considered globally to be among the primary causes of climate change most especially in tropical regions. Deforestation brings about negative consequences on the environment such as soil degradation, soil erosion, desertification, loss of habitats for many animals and loss of plant species amongst others (Ajanaku & Collins, 2021;Van der Werf et al., 2009). Deforestation is of great concern as forests act as a good storage mechanism for carbon reason why they have been suggested as part of the climate change mitigation strategy (Cramer, 2004). ...
This study aimed to measure the effect of trade openness and agriculture on deforestation in Cameroon from 1980 to 2021 by using a fully modified ordinary least squares (FMOLS) approach. Data used are from the World Bank and FAO. The results obtained indicate that when trade openness increases, deforestation also increases, but when trade openness increases up to a certain threshold, deforestation decreases. This study also reveals that agriculture is one of the major causes of deforestation in Cameroon. Agricultural output and agricultural value-added both have a positive and significant impact on deforestation. There is an inverted curve relationship between economic growth and deforestation in Cameroon, this shows that the EKC is respected with deforestation as it is postulated that at higher levels of income, GDP turns to reduce deforestation meaning a unit change in GDP2 leads to a reduction of deforestation. We recommend the implementation of concrete actions and strict environmental policies focused on a green economy, to control the exploitation of natural resources with particular attention to the sustainable exploitation of wood. Sustainable agricultural practices should also be implemented, as well as more suitable liberal trade policies.
... Amidst the escalating greenhouse effect, maximizing the potential of SOC sequestration emerges as a valuable strategy to mitigate global climate change (Bai and Cotrufo, 2022;Chen et al., 2018a). However, despite numerous field studies and dozens of literature reviews, substantial disagreements persist regarding the direction and magnitude of changes in SOC stock associated with LUC (van der Werf et al., 2009). The existing knowledge remains inconclusive on both the extent and direction of SOC stock alterations linked to land use type, management practices, and other disturbances, hindering broad generalizations (IPCC, I.J.I.G, 2006). ...
Mining activities significantly contribute to forest cover loss (FCL), subsequently altering global carbon dynamics and exacerbating climate change. The present study aims to estimate the contributions of mining-induced FCL to carbon sequestration loss (CSL) and carbon dioxide (CO₂) emissions from 2000 to 2019 using the proxy datasets. For FCL analysis, the global FCL data at 30 m spatial resolution, developed by Hansen et al. (2013), was employed in the Google Earth Engine (GEE) cloud platform. Furthermore, for CSL and CO₂ emissions assessment, Moderate Resolution Imaging Spectroradiometer (MODIS)-based Net Primary Productivity (NPP) data and Zhang and Liang (2020)-developed biomass datasets were used, respectively. The outcomes of the study exhibited approximately 16,785.90 km 2 FCL globally due to mining activities, resulting in an estimated CSL of ~36,363.17 Gg CO₂/year and CO₂ emissions of ~490,525.30 Gg CO₂. Indonesia emerged as the largest contributor to mining-induced FCL, accounting for 3,622.78 km 2 of deforestation, or 21.58% of the global total. Brazil and Canada followed, with significant deforestation and CO₂ emissions. The findings revealed that mining activities are a major driver of deforestation, particularly in resource-rich regions, leading to substantial environmental degradation. The relative FCL was notably high in smaller countries like Suriname and Guyana, where mining activities constituted a significant proportion of total deforestation. The present study underscores the urgent need for robust regulatory frameworks, sustainable land management practices, and coordinated international efforts to mitigate the adverse environmental impacts of mining. The findings of this study can inform policy-makers and stakeholders, leading to more effective conservation strategies and benefiting society by promoting environmental sustainability and resilience against climate change.
The rapid increase in carbon and other greenhouse gases is likely to change the regional and global temperature, and planning of these gases is needed. The present study focused on National Highway-16 of the Srikakulam district, which was upgraded from 4 to 6 lane standards to facilitate traffic. This study intended to compute the carbon sequestration and storage capacity of above and belowground biomass. This helps in the comparison and impact of the road project on flora and its carbon pool, from where future tree stock changes can be prepared. A total of 1930 plots were constructed of criss-crosses of equal size (2 × 100 m). All woody trees with dbh ≥ 30 cm were considered and their diameters were measured. A total of 29 tree species belonging to 13 families were identified; the quantity of macrobiotic carbon sequestered as a whole, i.e., above and below ground, was 768,890.29 tC and 199,911.48 tC, respectively. The mean sequestration rate of carbon as biomass above ground was 1.19 tC/tree, and that below ground was 0.31 tC/tree. The estimated average C-Stock per tree was 1.5 tC; however, the mean C-Stock per quadrate was 250.2 tC.
Deforestation remains a significant concern regarding climate change and biodiversity conservation. At the same time, the development of new image processing techniques and wide access to high spatial and temporal resolution satellite imagery have created unique conditions for monitoring deforestation. This is particularly important in areas such as the Arasbaran Biosphere Reserve. Existing methods for monitoring deforestation rely on a combination of visual inspection, spectral profiles, statistics, and machine learning techniques. Given recent advances in image processing using Convolutional Neural Networks (CNNs), this study aims to evaluate the performance of a refined U-Net architecture for identifying forest cover to monitor deforestation in multi-temporal satellite images. In this regard, a deep learning model for monitoring deforestation in the Arasbaran Biosphere Reserve based on the classification of Landsat satellite images from 2000 to 2022 was developed. In this study, the Normalized Difference Vegetation Index (NDVI) was used to create masks, which were then visually corrected. Additionally, the refined U-Net model presented was compared with Random Forest and Artificial Neural Network (ANN) models. The results showed that the refined U-Net outperformed traditional methods in classifying images into forest or non-forest categories, resulting in an overall accuracy of 96.53%, a kappa coefficient of 91.55%, an F1 score of 94.68%, and an IoU of 90.04%. The proposed model can accurately show forest changes and estimate the amounts of forest area increase or decrease. Overall, it was observed that the forest area in Arasbaran increased during the 2000-2022 period. This research indicates that using a refined U-Net can be an effective tool for sustainable forest resource monitoring and management
Wildfire strongly influences permafrost environment and soil organic carbon (SOC) pool. In this study, we reviewed the effects of fire severity, time after a fire, and frequency on SOC in boreal permafrost regions. This review highlighted several key points: the effect of wildfires on SOC increased with an increase of fire severity, and the amount of vegetation returned and surface organic matter replenished was less in a short term, which resulted in a significantly lower SOC content compared to that of before the fire. Within a short period after fire, the SOC in near‐surface permafrost and the active layer decreased significantly due to the loss of above ground biomass, permafrost thaw, and increased microbial decomposition; as the years pass after a fire, the SOC gradually accumulates due to the contributions of litter layer accumulation and rooting systems from different stages of succession. The increase in fire frequency accelerated permafrost thawing and the formation of thermokarst, resulting in the rapid release of a large amount of soil carbon and reduced SOC storage. Therefore, the study on the effects of wildfires on SOC in the boreal permafrost region is of great significance to understanding and quantifying the carbon balance of the ecosystem.
Spaceborne lidar (light detection and ranging) instruments such as the Global Ecosystem Dynamics Investigation (GEDI) provide a unique opportunity for global forest inventory by generating broad-scale measurements sensitive to the vertical arrangement of plant matter as a supplement to in situ measurements. Lidar measurables are not directly relatable to most physical attributes of interest, including biomass, and therefore must be related through statistical models. Further, GEDI observations are not spatially complete, necessitating methods to convert the incomplete samples to predictions of area averages/totals. Such methods can face challenges in equatorial and persistently cloudy areas, such as Indonesia, where the density of quality observations is diminished. We developed and implemented a hierarchical model to produce gap-free maps of aboveground biomass density (AGBD) at various resolutions within the lowlands of Jambi province, Indonesia. A biomass model was trained between local field plots and a metric from GEDI waveforms simulated with coincident airborne laser scanning (ALS) data. After selecting a locally suitable ground-finding algorithm setting, we trained an error model depicting the discrepancies between the simulated and GEDI-observed waveforms. Finally, a geostatistical model was used to model the spatial distribution of the on-orbit GEDI observations. These three models were nested into a single hierarchical model, relating the spatial distribution of GEDI observations to field-measured AGBD. The model allows spatially complete predictions at arbitrary resolutions while accounting for uncertainties at each stage of the relationship. The model uncertainties were low relative to the predicted biomass, with a median relative standard deviation of 8% at the 1 km resolution and 26% at the 100 m resolution. The spatially consistent information on AGBD provided by our model is beneficial in support of sustainable forest management, carbon sequestration initiatives and the mitigation of climate change. This is particularly relevant in a dynamic tropical landscape like Jambi, Indonesia in order to understand the impacts of land-use transformations from forests to cash crops like oil palm and rubber. More generally, we advocate for the use of hierarchical models as a framework to account for multiple stages of relationships between field and sensor data and to provide reliable uncertainty audits for final predictions.
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Forests play a crucial role in the global climate system by acting as important carbon storage sinks and controlling the flow of carbon between land and the atmosphere. They provide a wide range of ecosystem services, including the supply of resources and biodiversity conservation. Deforestation is a significant issue leading to the release of carbon dioxide and greenhouse gases. The destruction and fragmentation of existing habitats pose significant threats to biodiversity. This study examined land use/land cover (LULC) alterations in the West Singhbhum district between 1987 and 2021, specifically emphasizing the influence of mining operations on the local forest ecosystem. This study used Landsat satellite imagery to examine data from 1987 to 2021, emphasizing five primary classifications: water body, mining area, built-up areas, open/cropland, and forest/vegetation. The maps were reclassified into two categories, namely, “No-Forest" and “Forest. Forest fragmentation maps were created using Landscape Fragmentation Tool (LFT) v2.0. A regression analysis was conducted to ascertain the correlation between mining growth and the reduction in forest cover. The analysis revealed increased mining areas, developed buildings, and cultivated land accompanied by a decline in forested areas and vegetation. There were substantial changes in land use, with mining areas expanding by 31.14 km2 and open/cropland increasing by 30.39 km2. The conversion of forested areas into agricultural zones and mining regions resulted in a 1.08% reduction in forest coverage.
Land use land cover (LULC) changes hugely influence the ecological balance of an ecosystem, which adversely affects the inhabitants, making them more vulnerable to natural calamities. The LULC change studies are therefore carried out to analyze the impact of these changes on the overall ecology of an area and are very helpful in policy framing and proper management of the available natural resources. In this study, changes in the land use and land cover for a three-decade period spanning from 1992 to 2020 have been monitored in the valley of Kashmir using remotely sensed satellite data obtained from USGS/NASA’s Landsat repository. Considerable changes in the LULC patterns were observed with a significant reduction in the area covered by water (18.21%), forest (13.56%), snow/glacial cover (29.32%) and agriculture (22.37%) during the past three decades. Concurrently, expansion in the land covered by urban areas (22.33%), barren land (37.32%), plantation (14.53%) and marshes (13.21%) were noted. The calculated Normalized Difference Water Index (NDWI) confirmed an overall reduction of 51.1% in the water and glacial cover of the study area. Significant changes in the form of forest, water and glacial cover transforming into urban, marshy and barren areas can be largely accredited to increased human interference that may have serious repercussions on the environment.
This paper examines the long-term and short-run causative relationship among environmental sustainability, energy efficiency, renewable energy and carbon emissions from all over sources (coal, oil and fossil fuels) and sector wise division (heat and power, transportation, residential, manufacturing and other sectors. The empirical evidence presented in this study is derived from a balanced panel dataset spanning the annual periods from 2000 to 2021. The dataset specifically focuses on a selection of BRI Countries. The Kao test demonstrates the presence of cointegration across variables such as carbon dioxide emissions, environmental suitability, energy efficiency and renewable energy. The Panel Pooled Mean Group-Autoregressive Distributed Lag (PMG-ARDL) model indicates a statistically significant positive association between the environmental sustainability and disaggregated CO2 emissions over a long-term period. The study found a positive relationship between disaggregated CO2 emissions and environmental sustainability and energy efficiency, with renewable energy sources reducing emissions. It suggests a need for a structural transition from an energy-intensive economy to a decarbonized one, with sectors like heat and power positively impacting sustainability. Implementing measures to reduce emissions is crucial for tackling climate change.
Forest degradation and conversion to agriculture and other land uses usually leads to a reduction in soil carbon stocks and negatively impacts key soil bio-physicochemical properties. The recovery of these soil properties following reforestation has been unclear and/or has not been well studied in the tropics. We analysed the soil carbon stocks and soil physicochemical characteristics of 48 sample plots across 11 sites in 42–47 year-old tropical hardwood plantations and secondary forests of similar ages, and primary reference forests. In addition, we assessed soil microbial biomass and litter decomposition. The study was conducted in the moist and wet climatic zones of Ghana.
Climate was the main determinant of soil characteristics, while the effect of forest type was minor. After 40 years of restoration, the soil carbon stocks and key soil physicochemical properties in plantations and secondary forests reached similar levels to those in the primary forests within the respective climatic zones. We observed that forests in the wet zone had higher soil carbon stocks and higher above ground biomass with much lower soil pH. Soil carbon stocks (0–50 cm) ranged from 51.16 Mg ha− 1 to 122.84 Mg ha− 1, with the mean values for the moist and wet zones being 56.9 Mg ha− 1 and 106.8 Mg ha− 1respectively.
There were no differences in soil microbial biomass between the forest types within zones, however, it was notably much higher in the moist compared to the wet zone. The decomposition of two types of tea (green and rooibos) with contrasting decomposability was analysed using a two-component exponential decomposition model. The results indicated that the decomposition of recalcitrant material in the tea bags was slower in the wet climatic zone. Further analysis showed that soil organic carbon content was inversely related to the recalcitrant organic matter’s decomposition rate. In addition, there was a positive relation between the soil carbon stocks and above-ground biomass. Our results indicate that soil bio-physicochemical properties and carbon stocks were restored in plantations and secondary forests after 40 years of restoration. However, a number of our restoration sites were cleared and farmed for a relatively short period (≈ 3–4 years) but are representative of many recently deforested areas in the tropics.
The present study investigates the effect of land use and land cover (LULC) changes on physical and chemical properties of soil. Studying the dynamics of soil properties in different LULC classes is important for the sustainable management of agricultural resources and mitigation strategies for land degradation. Soil samples were collected and examined from different LULC classes and finds that the dynamics of LULC consequently affect soil properties in the study area. The physical properties of soil like Bulk density and Porosity change significantly. Owing to receiving a good amount of annual rainfall, the study area has slightly acidic soil in nature. The chemical properties like SOC, SOM and available N are tremendously changing their characteristics with the change of LULC. Available K and pH have moderately changed their properties and available P and EC have lower effects on the dynamics of LULC.
Indonesia has experienced rapid primary forest loss, second only to Brazil in modern history. We examined the fates of Indonesian deforested areas, immediately after clearing and over time, to quantify deforestation drivers in Indonesia. Using time-series satellite data, we tracked degradation and clearing events in intact and degraded natural forests from 1991 to 2020, as well as land use trajectories after forest loss. While an estimated 7.8 Mha (SE = 0.4) of forest cleared during this period had been planted with oil palms by 2020, another 8.8 Mha (SE = 0.4) remained unused. Of the 28.4 Mha (SE = 0.7) deforested, over half were either initially left idle or experienced crop failure before a land use could be detected, and 44% remained unused for 5 y or more. A majority (54%) of these areas were cleared mechanically (not by escaped fires), and in cases where idle lands were eventually converted to productive uses, oil palm plantations were by far the most common outcome. The apparent deliberate creation of idle deforested land in Indonesia and subsequent conversion of idle areas to oil palm plantations indicates that speculation and land banking for palm oil substantially contribute to forest loss, although failed plantations could also contribute to this dynamic. We also found that in Sumatra, few lowland forests remained, suggesting that a lack of remaining forest appropriate for palm oil production, together with an extensive area of banked deforested land, may partially explain slowing forest loss in Indonesia in recent years.
The G-20 countries represent a considerable percentage of the global economy and are crucial in matters to do with support for environmental sustainability. The uniqueness of this study lies in determining the effects of forests on human welfare and environmental degradation with respect to G20, offering a unique perspective regarding the efforts to battle climate change. The study analyzed the impact of income, forest extent and education on ecological and carbon intensity of wellbeing following the Environmental Kuznets Curve (EKC) hypothesis. Based on annual data from 1990 to 2022 and employing the Moment Quantile Regression Method, the results validate the presence of an inverted U-Shaped relationship between GDP and environmental well-being which refers to the existence of EKC. Our results connect enhanced ecological and carbon intensity well-being with expanding forest coverage and improving education levels. Forest management combined with educational management work as an effective mechanism reducing environmental degradation while also positively contributing to human welfare. In addition, through these informed and rational decisions, policy makers can promote the environmental stability of forests.
Understanding and accurately predicting how the sensitivity of terrestrial vegetation productivity to rising atmospheric CO2 concentration (β) is crucial for assessing carbon sink dynamics. However, the temporal characteristics and driving mechanisms of β remain uncertain. Here, observational and CMIP6 modeling evidence suggest a decreasing trend in β at the Northern Middle and High Latitudes during the historical period of 1982–2015 (−0.082 ± 0.005% 100 ppm⁻¹ year⁻¹). This decreasing trend is projected to persist until the end of the 21st century (−0.082 ± 0.005% 100 ppm⁻¹ year⁻¹ under SSP370 and −0.166 ± 0.006% 100 ppm⁻¹ year⁻¹ under SSP585). The declining β indicates a weakening capacity of vegetation to mitigate warming climates, posing challenges for achieving the temperature goals of the Paris Agreement. The rise in vapor pressure deficit (VPD), that triggers stomata closure and weakens photosynthesis, is considered as the dominated factor contributing to the historical and future decline in β, accounting for 62.3%–75.2% of the effect. Nutrient availability and water availability contribute 15.7%–21.4% and 8.5%–16.3%, respectively. These findings underscore the significant role of VPD in shaping terrestrial carbon sink dynamics, an aspect that is currently insufficiently considered in many climate and ecological models.
Global warming and climate change have increased the pollen burden and the frequency and intensity of wildfires, sand and dust storms, thunderstorms, and heatwaves—with concomitant increases in air pollution, heat stress, and flooding. These environmental stressors alter the human exposome and trigger complex immune responses. In parallel, pollutants, allergens, and other environmental factors increase the risks of skin and mucosal barrier disruption and microbial dysbiosis, while a loss of biodiversity and reduced exposure to microbial diversity impairs tolerogenic immune development. The resulting immune dysregulation is contributing to an increase in immune-mediated diseases such as asthma and other allergic diseases, autoimmune diseases, and cancer. It is now abundantly clear that multisectoral, multidisciplinary, and transborder efforts based on Planetary Health and One Health approaches (which consider the dependence of human health on the environment and natural ecosystems) are urgently needed to adapt to and mitigate the effects of climate change. Key actions include reducing emissions and improving air quality (through reduced fossil fuel use), providing safe housing (e.g., improving weatherization), improving diets (i.e., quality and diversity) and agricultural practices, and increasing environmental biodiversity and green spaces. There is also a pressing need for collaborative, multidisciplinary research to better understand the pathophysiology of immune diseases in the context of climate change. New data science techniques, biomarkers, and economic models should be used to measure the impact of climate change on immune health and disease, to inform mitigation and adaptation efforts, and to evaluate their effectiveness. Justice, equity, diversity, and inclusion (JEDI) considerations should be integral to these efforts to address disparities in the impact of climate change.
Kualitas lingkungan hidup menentukan kualitas kehidupan manusia yang tinggal di dalamnya. Sebaliknya kualitas lingkungan hidup juga ditentukan oleh aktivitas manusia yang ada di dalamnya. Segala aktivitas manusia yang dilakukan menggunakan sumber daya dari lingkungan dan sumber daya alam dan kemudian membuang sisa aktivitas tersebut kembali ke lingkungan. Penelitian ini bertujuan untuk menguji pengaruh pertumbuhan ekonomi, kepadatan penduduk, dan PDRB sektor pertanian terhadap kualitas lingkungan hidup. Kualitas lingkungan hidup dalam penelitian ini diproksi dengan sebuah indeks yaitu IKLH (Indeks Kualitas Lingkungan Hidup). Data dalam penelitian ini merupakan data panel yang terdiri atas cross section 34 provinsi di Indonesia dengan time series selama 5 tahun (2016 – 2020). Adapun sumber data yang digunakan pada penelitian ini adalah publikasi resmi Badan Pusat Statistik (BPS), Kementerian Lingkungan Hidup dan publikasi dari instansi-instansi terkait yang berhubungan dengan penelitian. Model panel yang digunakan dalamestimasi dalam penelitian ini adalah Model Random Effect, artinya terdapat perbedaan perilaku variabel Indeks Kualitas Lingkungan Hidup, Pertumbuhan Ekonomi, Kepadatan Penduduk, dan PDRB Sektor pertanian baik antar daerah (cross section) maupun antar waktu (time series). Adapun temuan penelitian ini adalah terdapat dua variabel yang signifikan terhadap kualitas lingkungan hidup yaitu pertumbuhan ekonomi yang berpengaruh negatif signifikan dan variabel kepadatan penduduk yang berpengaruh positif signifikan. Sedangkan variabel PDRB Sektor pertanian tidak berpengaruh terhadap kualitas lingkungan hidup di Indonesia.
In this study, a comprehensive evaluation of the potential of dual-polarization and full-polarization L- and S-band airborne SAR (LS-ASAR) data (ISRO's dual-frequency airborne SAR mounted on NASA's Gulfstream III aircraft) in forest above-ground biomass (AGB) estimation has been carried out. The study area comprises the temperate forests of the Lenoir landing site in Southwest Alabama, United States of America. A trunk scattering model based on Vector Radiative Transfer (VRT) theory is used in this study to estimate the AGB. Full-polarization ASAR data inversion retrieves three critical biophysical parameters: tree height, diameter at breast height (DBH), and tree count, whereas with dual-polarization ASAR data, the model is limited to retrieving only two parameters (tree height and DBH). These parameters are then employed in a suitable allometric equation to estimate the AGB over the study area. Validation of the retrieval results is performed through comparison with ground-truth measurements taken from the study site. The findings demonstrate that the inversion of L-band full-polarized data yields the highest correlation (R^2 = 0.87, RMSE = 20.37 t/ha), revealing high accuracy in AGB estimation. The L-band dual-polarized data shows a high correlation (R^2 = 0.83, RMSE = 30.66 t/ha), indicating reasonable accuracy. However, the S-band data, both full and dual-polarized, reveals weaker correlations with higher RMSE values (R^2 = 0.59, RMSE = 55.07 t/ha, and R^2 = 0.49, RMSE = 58.31 t/ha, respectively), suggesting a lower degree of reliability. This study emphasizes the pre-eminence of L-band fully polarized data inversion for reliable and accurate AGB estimation while also showing the utility of relatively ubiquitous dual-pol data (L-band) to achieve reasonable accuracy for the same.
Is there a technological way to decrease the carbon emissions caused by a devastating tropical peat land fire? This issue was addressed in this article. The objectives of this article are to (i) calculate the amount of carbon emissions that the tropical peat fire disasters in Pelalawan Regency, Sumatra Island, Indonesia, released into the atmosphere (2017-2020), and (ii) investigate the potential contributions that weather modification technology (WMT) can play to decreasing carbon emissions from these disasters. Peat fire catastrophes are especially challenging to put out because the flames may spread deeply into the peat soil layers and consume the peat soil materials. It was determined that the peat fires released 8,135 M tons of CO 2 in four years. The size of the burned regions and the amount of carbon emissions released into the atmosphere both dramatically decreased following the 2020 WMT implementation compared to the 2017-2019 periods; as there was an increase in rainfall rates in 2020. According to the Target-only technique, the application of WMT (in 2020) was considered successful in lowering carbon emissions (CHS=0.0008<1). This article can be utilized as a reference by risk mitigation experts and policymakers to decrease carbon emissions through the application of WMT.
Even though Southeast Asia is a hotspot of forest degradation and deforestation, thorough reviews of the drivers of forest degradation and deforestation are lacking in the literature. Here, we present a review of studies of drivers of forest degradation and deforestation in Southeast Asia, including forest conversion to plantation, shifting cultivation, fire, logging, drought, and pest damage. We calculated the number of studies by country for different drivers and identified the major drivers for each country. We reviewed global and regional datasets of forest degradation and deforestation that cover Southeast Asia, and from which the area of different drivers was calculated. We also reviewed national and local studies of the drivers by country in Southeast Asia. We found that: (1) The major drivers are conversion of forest to plantation, shifting cultivation, logging, fire, and drought; (2) The numbers of studies vary greatly from country to country (Indonesia, for example, is much more studied than the Philippines); (3) Knowledge about the different drivers is unequal (conversion of forest to plantation is more studied than other types of change); (4) Fine resolution analyses of drivers in Southeast Asia are lacking in the literature; (5) The temporal dynamics of drivers remain largely unknown; and (6) Attention to estimation of accuracy and area needs to be improved.
Carbon credits generated through jurisdictional-scale avoided deforestation projects require accurate estimates of deforestation emission baselines, but there are serious challenges to their robustness. We assessed the variability, accuracy, and uncertainty of baselining methods by applying sensitivity and variable importance analysis on a range of typically-used methods and parameters for 2,794 jurisdictions worldwide. The median jurisdiction’s deforestation emission baseline varied by 171% (90% range: 87%-440%) of its mean, with a median forecast error of 0.778 times (90% range: 0.548-3.56) the actual deforestation rate. Moreover, variable importance analysis emphasised the strong influence of the deforestation projection approach. For the median jurisdiction, 68.0% of possible methods (90% range: 61.1%-85.6%) exceeded 15% uncertainty. Tropical and polar biomes exhibited larger uncertainties in carbon estimations. The use of sensitivity analyses, multi-model, and multi-source ensemble approaches could reduce variabilities and biases. These findings provide a roadmap for improving baseline estimations to enhance carbon market integrity and trust.
Deforestation, mining, pollution and the construction of hydroelectric plants are among the main risks for biological
communities, ecosystems and indigenous peoples. In the Brazilian Amazon, historically there has been political pressure
to reduce the constitutional rights of indigenous peoples, especially regarding mining activities and the construction of
hydroelectric plants. This culminated in a law proposal allowing mining in indigenous lands (PL 191/2020), proposed during
the last presidential term in Brazil (2018-2022), which sparked a heated debate in both the legal and ethical spheres. In this
article we present objective arguments for the negative effects of mining on indigenous lands, using PL 191/2020 as a model
to debate the consequences of such policies for biodiversity, ecosystem services, increased risks for humans due to pollutants
and epidemics, and how this law violates the main objectives of the Agenda 2030 for sustainable development. Particularly
in the Brazilian Amazon, the negative effects of this law on human life quality, economy and the ecosystems are greater than
the supposed positive effects projected into the future. We suggest rethinking the feasibility of mining on indigenous lands
and reiterate the importance of conserving these lands and other protected areas in the Amazon intact as a heritage of all
Brazilians and the wider human kind.
Reducing emissions from deforestation and forest degradation, and fostering conservation, sustainable management of forests, and enhancement of forest carbon stocks (REDD+) is more than an environmental initiative for the climate system; it is a project of human rights importance to landowners, Indigenous Peoples, local communities, as well as affected individuals who may hold rights that could be adversely impacted by adverse legal framework and practices at the domestic level. The tripartite obligations to respect, protect and fulfil rights are established in human rights law and the application in implementing REDD+ is evident by its safeguards that recognise the need to respect human rights across critical phases and matters involved in its implementation. However, these obligations are rarely unpacked in the context of the success or otherwise of REDD+ at the domestic level in Africa. This chapter which foregrounds the edited volume sketches the evolution of REDD+ and its implications for state obligations under human rights law. In doing so, it offers a conceptual basis for key themes and issues in Africa addressed in the edited volume.
Reducing Emissions from Deforestation and Forest Degradation (REDD+)—the focus of this work—is a climate mechanism developed to bring about climate solutions in developing countries by exchanging carbon stored in forests for financial incentives. Global inflation and a pandemic-ruined economy have precipitated high demand for cheap food and household energy, grossly contributing to Nigeria’s high rate of deforestation. Considering the significance of the forest to forest-dependent communities, the chapter explores the importance of a human rights-based approach in implementing REDD+ in Nigeria.
The Chapter assesses the determinants of a green economy in Kazakhstan and
Uzbekistan through an empirical assessment of a 30-year (1990-2020) dataset. The
study indicates where to focus for a greener economy in the two countries. The findings provide valuable insight for decision-making in green economy strategies.
The findings from the apriori analysis of the potential impact of emerging green policies in Kazakhstan and Uzbekistan will serve as a lesson to the other countries in the region.
The energy and climate crises are driving renewable energy, but it is currently facing obstacles in leading countries. Balancing environmental, social and economic interests has become complex at the regional level due to spatial trade-offs in a contested space. To investigate stakeholder willingness to compromise on a joint ranking on wind and solar energy sites, multi-criteria decision analysis (MCDA) planning support was explored. Using a two-part stakeholder survey, four groups were identified: ‘advocates’ who were satisfied with the site ranking (66%), ‘realists’ who were willing to compromise despite previous disagreement (13%), ‘dissenters’ not accepting (35%), and ‘dogmatists’ not engaging. Planning decisions and stakeholder engagement are underpinned by distinct attitudes towards the role of (democratic) planning and sustainable development. The use of trade-off analysis can ensure transparency and trace back stakeholder interests in making planning decisions. However, decision quality factors also need to be considered to ensure a thorough planning reflection.
The dependence on fossil fuels for energy has culminated in its gradual depletion and this has generated the need to seek alternative source that will be environmentally friendly and sustainable. Hydrogen stands to be promising in this regard as energy carrier which has been proven to be efficient. Magnesium hydride (MgH2) can be used in storing hydrogen because of its availability, light weight and low cost. In this review, monoatomic, alloy, intermetallic and composite forms of Ti, Ni, V, Mo, Fe, Cr, Co, Zr and Nb as additives on MgH2 are discussed. Through ball milling, additive reacts with MgH2 to form compounds including TiH2, Mg2Ni, Mg2NiH4, V2O, VH2, MoSe, Mg2FeH6, NbH and Nb2O5which remain stable after certain de/hydrogenation cycles. Some monoatomic transition metals remain unreacted even after de/hydrogenation cycles. These formed compounds, including stable monoatomic transition metals, impart their catalytic effects by creating diffusion channels for hydrogen via weakening Mg - H bond strength. This reduces hydrogen de/sorption temperatures, activation energies and in turn, hastens hydrogen desorption kinetics of MgH2. Hydrogen storage output of MgH2/transition metal-based materials depend on additive type, ratio of MgH2/additive, ball milling time, ball –to combining materials ratio and de/hydrogenation cycle. There is a need for more investigations to be carried out on nanostructured binary and ternary transition metal-based materials as additives to enhance the hydrogen storage performance of MgH2. In addition, the already established compounds (listed above) formed after ball milling or dehydrogenation can be processed and directly doped into MgH2.
In 2004, the Joint Research Centre (JRC) of the European Commission, the Netherlands Environmental Assessment Agency (MNP) and the Max Plank Institute for Chemistry (MPIC) started a project to create fast (bi-)annual updates of the EDGAR global emission inventory system, based on the more detailed previous version 3.2. Here, the key features of the Emission Database for Global Atmospheric Research, EDGAR 3 are first summarized, and then the compilation of recent global trends having a major influence on variables and the new ‘Fast Track’ approach to estimate recent emissions of greenhouse gases and air pollutants in 2000 at a country-specific level are described. Also provided is an overview of the approaches and data sources used for this EDGAR 3.2 Fast Track 2000 dataset, the different source sectors and the accuracies achieved, with a focus on anthropogenic sources of methane and nitrous oxide. Results of global emission trends for four air pollutants are also briefly addressed. Results for various sources and greenhouse gases at regional and national scales and on 1×1 degree grid have been made available on the EDGAR website.
Carbon emissions from tropical deforestation have long been recognized as a key component of the global carbon budget, and more recently of our global climate system. Tropical forest clearing accounts for roughly 20% of anthropogenic carbon emissions and destroys globally significant carbon sinks (IPCC 2007). Global climate policy initiatives are now being proposed to address these emissions and to more actively include developing countries in greenhouse gas mitigation (e.g. Santilli et al 2005, Gullison et al 2007). In 2005, at the Conference of the Parties (COP) in Montreal, the United Nations Framework Convention on Climate Change (UNFCCC) launched a new initiative to assess the scientific and technical methods and issues for developing policy approaches and incentives to reduce emissions from deforestation and degradation (REDD) in developing countries (Gullison et al 2007).
Over the last two years the methods and tools needed to estimate reductions in greenhouse gas emissions from deforestation have quickly evolved, as the scientific community responded to the UNFCCC policy needs. This focus issue highlights those advancements, covering some of the most important technical issues for measuring and monitoring emissions from deforestation and forest degradation and emphasizing immediately available methods and data, as well as future challenges.
Elements for effective long-term implementation of a REDD mechanism related to both environmental and political concerns are discussed in Mollicone et al. Herold and Johns synthesize viewpoints of national parties to the UNFCCC on REDD and expand upon key issues for linking policy requirements and forest monitoring capabilities. In response to these expressed policy needs, they discuss a remote-sensing-based observation framework to start REDD implementation activities and build historical deforestation databases on the national level. Achard et al offer an assessment of remote sensing measurements across the world's tropical forests that can provide key consistency and prioritization for national-level efforts. Gibbs et al calculate a range of national-level forest carbon stock estimates that can be used immediately, and also review ground-based and remote sensing approaches to estimate national-level tropical carbon stocks with increased accuracy.
These papers help illustrate that methodologies and tools are indeed available to estimate emissions from deforestation. Clearly, important technical challenges remain (e.g. quantifying degradation, assessing uncertainty, verification procedures, capacity building, and Landsat data continuity) but we now have a sufficient technical base to support REDD early actions and readiness mechanisms for building national monitoring systems.
Thus, we enter the COP 13 in Bali, Indonesia with great hope for a more inclusive climate policy encompassing all countries and emissions sources from both land-use and energy sectors. Our understanding of tropical deforestation and carbon emissions is improving and with that, opportunities to conserve tropical forests and the host of ecosystem services they provide while also increasing revenue streams in developing countries through economic incentives to avoid deforestation and degradation.
References
Gullison R E et al 2007 Tropical forests and climate policy Science 316 985–6 Intergovernmental Panel on Climate Change (IPCC) 2007 Climate Change 2007: The Physical Science Basis: Summary for Policymakers http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf Santilli M et al 2005 Tropical deforestation and the Kyoto Protocol: an editorial essay Clim. Change 71 267–76
Focus on Tropical Deforestation and Greenhouse Gas Emissions Contents
Pan-tropical monitoring of deforestation F Achard, R DeFries, H Eva, M Hansen, P Mayaux and H-J Stibig
Monitoring and estimating tropical forest carbon stocks: making REDD a reality Holly K Gibbs, Sandra Brown, John O Niles and Jonathan A Foley
Elements for the expected mechanisms on 'reduced emissions from deforestation and degradation, REDD' under UNFCCC D Mollicone, A Freibauer, E D Schulze, S Braatz, G Grassi and S Federici
Linking requirements with capabilities for deforestation monitoring in the context of the UNFCCC-REDD process Martin Herold and Tracy Johns
Reference scenarios for deforestation and forest degradation in support of REDD: a review of data and methods Lydia P Olander, Holly K Gibbs, Marc Steininger, Jennifer J Swenson and Brian C Murray
Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates Giacomo Grassi, Suvi Monni, Sandro Federici, Frederic Achard and Danilo Mollicone
Identifying optimal areas for REDD intervention: East Kalimantan, Indonesia as a case study Nancy L Harris, Silvia Petrova, Fred Stolle and Sandra Brown
A first map of tropical Africa's above-ground biomass derived from satellite imagery A Baccini, N Laporte, S J Goetz, M Sun and H Dong
1] Recent figures on net forest cover change rates of the world's tropical forest cover are used for the calculation of carbon fluxes in the global budget. By applying our deforestation findings in the humid tropics, complemented by published deforestation figures in the dry tropics, to refereed data on biomass, we produced new estimates of net carbon emissions. These estimates are supported by recent, independent estimations of net carbon emissions globally, over the Brazilian Amazon, and by observations of atmospheric CO 2 emissions over Southeast Asia. Our best estimate for global net emissions from land-use change in the tropics is at 1.1 ± 0.3 Gt C yr À1 . This estimate includes emissions from conversion of forests (representing 71% of budget) and loss of soil carbon after deforestation (20%), emissions from forest degradation (4.4%), emissions from the 1997–1998 Indonesian exceptional fires (8.3%), and sinks from regrowths (À3.3%). (2004), Improved estimates of net carbon emissions from land cover change in the tropics for the 1990s, Global Biogeochem. Cycles, 18, GB2008, doi:10.1029/2003GB002142.
Drainage of peatlands and deforestation have led to large-scale fires in equatorial Asia, affecting regional air quality and global concentrations of greenhouse gases. Here we used several sources of satellite data with biogeochemical and atmospheric modeling to better understand and constrain fire emissions from Indonesia, Malaysia, and Papua New Guinea during 2000-2006. We found that average fire emissions from this region [128 +/- 51 (1sigma) Tg carbon (C) year(-1), T = 10(12)] were comparable to fossil fuel emissions. In Borneo, carbon emissions from fires were highly variable, fluxes during the moderate 2006 El Niño more than 30 times greater than those during the 2000 La Niña (and with a 2000-2006 mean of 74 +/- 33 Tg C yr(-1)). Higher rates of forest loss and larger areas of peatland becoming vulnerable to fire in drought years caused a strong nonlinear relation between drought and fire emissions in southern Borneo. Fire emissions from Sumatra showed a positive linear trend, increasing at a rate of 8 Tg C year(-2) (approximately doubling during 2000-2006). These results highlight the importance of including deforestation in future climate agreements. They also imply that land manager responses to expected shifts in tropical precipitation may critically determine the strength of climate-carbon cycle feedbacks during the 21st century.
Tropical peatlands are one of the largest near-surface reserves of terrestrial organic carbon, and hence their stability has important implications for climate change. In their natural state, lowland tropical peatlands support a luxuriant growth of peat swamp forest overlying peat deposits up to 20 metres thick. Persistent environmental change-in particular, drainage and forest clearing-threatens their stability, and makes them susceptible to fire. This was demonstrated by the occurrence of widespread fires throughout the forested peatlands of Indonesia during the 1997 El Niño event. Here, using satellite images of a 2.5 million hectare study area in Central Kalimantan, Borneo, from before and after the 1997 fires, we calculate that 32% (0.79 Mha) of the area had burned, of which peatland accounted for 91.5% (0.73 Mha). Using ground measurements of the burn depth of peat, we estimate that 0.19-0.23 gigatonnes (Gt) of carbon were released to the atmosphere through peat combustion, with a further 0.05 Gt released from burning of the overlying vegetation. Extrapolating these estimates to Indonesia as a whole, we estimate that between 0.81 and 2.57 Gt of carbon were released to the atmosphere in 1997 as a result of burning peat and vegetation in Indonesia. This is equivalent to 13-40% of the mean annual global carbon emissions from fossil fuels, and contributed greatly to the largest annual increase in atmospheric CO(2) concentration detected since records began in 1957 (ref. 1).
Achard et al. ([1][1]) estimated tropical deforestation and atmospheric carbon emissions from 1990 to 1997 and concluded that both were substantially lower than had been found in previous studies. However, we believe that the evidence favors higher estimates, particularly for carbon emissions. We
Humanity already possesses the fundamental scientific, technical, and industrial know-how to solve the carbon and climate
problem for the next half-century. A portfolio of technologies now exists to meet the world's energy needs over the next 50
years and limit atmospheric CO2 to a trajectory that avoids a doubling of the preindustrial concentration. Every element in this portfolio has passed beyond
the laboratory bench and demonstration project; many are already implemented somewhere at full industrial scale. Although
no element is a credible candidate for doing the entire job (or even half the job) by itself, the portfolio as a whole is
large enough that not every element has to be used.
The growth rate of atmospheric carbon dioxide (CO(2)), the largest human contributor to human-induced climate change, is increasing rapidly. Three processes contribute to this rapid increase. Two of these processes concern emissions. Recent growth of the world economy combined with an increase in its carbon intensity have led to rapid growth in fossil fuel CO(2) emissions since 2000: comparing the 1990s with 2000-2006, the emissions growth rate increased from 1.3% to 3.3% y(-1). The third process is indicated by increasing evidence (P = 0.89) for a long-term (50-year) increase in the airborne fraction (AF) of CO(2) emissions, implying a decline in the efficiency of CO(2) sinks on land and oceans in absorbing anthropogenic emissions. Since 2000, the contributions of these three factors to the increase in the atmospheric CO(2) growth rate have been approximately 65 +/- 16% from increasing global economic activity, 17 +/- 6% from the increasing carbon intensity of the global economy, and 18 +/- 15% from the increase in AF. An increasing AF is consistent with results of climate-carbon cycle models, but the magnitude of the observed signal appears larger than that estimated by models. All of these changes characterize a carbon cycle that is generating stronger-than-expected and sooner-than-expected climate forcing.
Forest cover is an important input variable for assessing changes to carbon stocks, climate and hydrological systems, biodiversity richness, and other sustainability science disciplines. Despite incremental improvements in our ability to quantify rates of forest clearing, there is still no definitive understanding on global trends. Without timely and accurate forest monitoring methods, policy responses will be uninformed concerning the most basic facts of forest cover change. Results of a feasible and cost-effective monitoring strategy are presented that enable timely, precise, and internally consistent estimates of forest clearing within the humid tropics. A probability-based sampling approach that synergistically employs low and high spatial resolution satellite datasets was used to quantify humid tropical forest clearing from 2000 to 2005. Forest clearing is estimated to be 1.39% (SE 0.084%) of the total biome area. This translates to an estimated forest area cleared of 27.2 million hectares (SE 2.28 million hectares), and represents a 2.36% reduction in area of humid tropical forest. Fifty-five percent of total biome clearing occurs within only 6% of the biome area, emphasizing the presence of forest clearing “hotspots.” Forest loss in Brazil accounts for 47.8% of total biome clearing, nearly four times that of the next highest country, Indonesia, which accounts for 12.8%. Over three-fifths of clearing occurs in Latin America and over one-third in Asia. Africa contributes 5.4% to the estimated loss of humid tropical forest cover, reflecting the absence of current agro-industrial scale clearing in humid tropical Africa.
• deforestation
• humid tropics
• remote sensing
• change detection
• monitoring
Newly compiled energy statistics allow for an estimation of the complete time series of carbon dioxide (CO 2 ) emissions from fossil-fuel use for the years 1751 to the present. The time series begins with 3 × 10 6 metric tonnes carbon (C). This initial flux represents the early stages of the fossil-fuel era. The CO 2 flux increased exponentially until World War I. The time series derived here seamlessly joins the modern 1950 to present time series. Total cumulative CO 2 emissions through 1949 were 61.0 × 10 9 tonnes C from fossil-fuel use, virtually all since the beginning of the Industrial Revolution around 1860. The rate of growth continues to grow during present times, generating debate on the probability of enhanced greenhouse warming. In addition to global totals, national totals and 1° global distributions of the data have been calculated. DOI: 10.1034/j.1600-0889.1999.t01-3-00002.x
Protecting forests offers a quick and cost-effective way of reducing emissions, but agreeing a means to do so won't be easy. Mark Schrope reports.
Newly compiled energy statistics allow for an estimation of the complete time series of carbon dioxide (CO2) emissions from fossil-fuel use for the years 1751 to the present. The time series begins with 3 × 106 metric tonnes carbon (C). This initial flux represents the early stages of the fossil-fuel era. The CO2 flux increased exponentially until World War I. The time series derived here seamlessly joins the modern 1950 to present time series. Total cumulative CO2 emissions through 1949 were 61.0 × 109 tonnes C from fossil-fuel use, virtually all since the beginning of the Industrial Revolution around 1860. The rate of growth continues to grow during present times, generating debate on the probability of enhanced greenhouse warming. In addition to global totals, national totals and 1° global distributions of the data have been calculated.
abstractRecent analyses of land-use change in the US and China, together with the latest estimates of tropical deforestation and afforestation from the FAO, were used to calculate a portion of the annual flux of carbon between terrestrial ecosystems and the atmosphere. The calculated flux includes only that portion of the flux resulting from direct human activity. In most regions, activities included the conversion of natural ecosystems to cultivated lands and pastures, including shifting cultivation, harvest of wood (for timber and fuel) and the establishment of tree plantations. In the US, woody encroachment and woodland thickening as a result of fire suppression were also included. The calculated flux of carbon does not include increases or decreases in carbon storage as a result of environmental changes (e.g., increasing concentrations of CO2, N deposition, climatic change or pollution). Globally, the long-term (1850–2000) flux of carbon from changes in land use and management released 156 PgC to the atmosphere, about 60% of it from the tropics. Average annual fluxes during the 1980s and 1990s were 2.0 and 2.2 PgC yr−1, respectively, dominated by releases of carbon from the tropics. Outside the tropics, the average net flux of carbon attributable to land-use change and management decreased from a source of 0.06 PgC yr−1 during the 1980s to a sink of 0.02 PgC yr−1 during the 1990s. According to the analyses summarized here, changes in land use were responsible for sinks in North America and Europe and for small sources in other non-tropical regions. The revisions were as large as 0.3 PgC yr−1 in individual regions but were largely offsetting, so that the global estimate for the 1980s was changed little from an earlier estimate. Uncertainties and recent improvements in the data used to calculate the flux of carbon from land-use change are reviewed, and the results are compared to other estimates of flux to evaluate the extent to which processes other than land-use change and management are important in explaining changes in terrestrial carbon storage.
Carbon fluxes from tropical deforestation and regrowth are highly uncertain components of the contemporary carbon budget, due in part to the lack of spatially explicit and consistent information on changes in forest area. We estimate fluxes for the 1980s and 1990s using subpixel estimates of percent tree cover derived from coarse (National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer) satellite data in combination with a terrestrial carbon model. The satellite-derived estimates of change in forest area are lower than national reports and remote-sensing surveys from the United Nations Food and Agriculture Organization Forest Resource Assessment (FRA) in all tropical regions, especially for the 1980s. However, our results indicate that the net rate of tropical forest clearing increased approximately 10% from the 1980s to 1990s, most notably in southeast Asia, in contrast to an 11% reduction reported by the FRA. We estimate net mean annual carbon fluxes from tropical deforestation and regrowth to average 0.6 (0.3-0.8) and 0.9 (0.5-1.4) petagrams (Pg).yr(-1) for the 1980s and 1990s, respectively. Compared with previous estimates of 1.9 (0.6-2.5) Pg.yr(-1) based on FRA national statistics of changes in forest area, this alternative estimate suggests less "missing" carbon from the global carbon budget but increasing emissions from tropical land-use change.
The long-term trend in tropical forest area receives less scrutiny than the tropical deforestation rate. We show that constructing a reliable trend is difficult and evidence for decline is unclear, within the limits of errors involved in making global estimates. A time series for all tropical forest area, using data from Forest Resources Assessments (FRAs) of the United Nations Food and Agriculture Organization, is dominated by three successively corrected declining trends. Inconsistencies between these trends raise questions about their reliability, especially because differences seem to result as much from errors as from changes in statistical design and use of new data. A second time series for tropical moist forest area shows no apparent decline. The latter may be masked by the errors involved, but a “forest return” effect may also be operating, in which forest regeneration in some areas offsets deforestation (but not biodiversity loss) elsewhere. A better monitoring program is needed to give a more reliable trend. Scientists who use FRA data should check how the accuracy of their findings depends on errors in the data.
• global environmental monitoring
• sustainability indicators
• tropical deforestation
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