Biomass Expansion Factors Research Articles

Carbon Sequestration of Common Garden Tree Species under the Carbon Neutrality Target in East China

The global warming phenomenon caused by greenhouse gas emission leads to the deterioration of the ecological environment. In urban spaces, the selection of garden tree species with high carbon sequestration rates can effectively contribute to carbon neutrality. In this study, we measured the height, diameter at breast height, and crown width of 643 ancient trees around the West Lake Scenic Spot, Hangzhou, China, and recorded their species and ages. By the biomass expansion factor method, the long-term carbon sequestration of the trees was calculated, and the corresponding statistical analysis indicated the following findings: (1) The maximum carbon sequestration of ancient trees varies with the species; the simple rational function has the best fit for the relationship between mean annual carbon sequestration and age. (2) For the five most common species in the Hangzhou area, the total individual amount of carbon sequestration per tree species can be ranked from high to low as follows: Celtis julianae, Cinnamomum camphora, Castanopsis sclerophylla, Liquidambar formosana, and Ginkgo biloba (tree age < 260 years). The ranking for trees aged above 260 years is as follows: Celtis julianae, Cinnamomum camphora, Liquidambar formosana, Castanopsis sclerophylla, and Ginkgo biloba. (3) The transient and mean annual carbon sequestration rate decreases as tree age increases; for most of the ancient trees in this research, the main growing period is 0–300 years. (4) Castanopsis sclerophylla, Liquidambar Formosana, and Osmanthus fragrans are recommended for urban landscape greening as they provide continuous long-term carbon sequestration and special landscape features.

Assessment of a probabilistic supervised machine learning method to estimate biomass expansion and conversion factors: A case study on cedar and pine trees.

Assessment of a probabilistic supervised machine learning method to estimate biomass expansion and conversion factors: A case study on cedar and pine trees.

Which Provinces Will Be the Beneficiaries of Forestry Carbon Sink Trade? A Study on the Carbon Intensity–Carbon Sink Assessment Model in China

Carbon emissions pose a significant challenge to sustainable development, particularly for China, which is the world’s largest emerging economy and is under pressure to achieve carbon neutrality and reduce emissions amid escalating human activities. The variation in economic development levels and carbon sequestration capacities among its provinces poses a significant hurdle. However, previous research has not adequately examined this dual discrepancy from the perspective of spatial heterogeneity, resulting in a lack of differentiated management of forest carbon sinks across diverse regions. Therefore, to mitigate this discrepancy, this study presents an assessment methodology that analyzes over 100 types of natural and plantation forests using forest age and biomass expansion factors. This study presents a model that can significantly support the efforts of both China and the whole world to achieve carbon neutrality through the improved management of forest carbon sinks. This approach facilitates the assessment of carbon offsets required to meet reduction targets, the development of a provincial framework for carbon intensity and sequestration, and the exploration of their potential for trading markets. Analysis is conducted using MATLAB. Key achievements of this study include the following: (1) The collection of a comprehensive carbon stock dataset for 50 natural and 57 plantation forest types in 31 provinces from 2009 to 2018, highlighting the significant role of new forests in carbon sequestration. (2) The development of a provincial carbon status scoring system that categorizes provinces as carbon-negative, carbon-balancing, or carbon-positive based on local forest sink data and carbon credit demand. (3) The formulation of the carbon intensity–carbon sink assessment (CISA) model, which suggests that provinces with middle- to upper-middle-level economies may have a prolonged need for carbon sink credits during their peak carbon phase. Furthermore, the results show that carbon trading may benefit Guangxi and Yunnan, but may also bring opportunities and risks to Hunan and Hubei. To address regional imbalances, this study advocates tailored policies: carbon-negative and carbon-balancing provinces should enhance carbon sink management, while carbon-positive provinces must focus on energy structure transformation to achieve sustainable development goals.

Dominant Tree Species and Their Age Groups Drive Forest Carbon Storage in Wuyi Mountain National Park, China

Evaluating the carbon storage of forests and identifying the factors that influence it are essential in working towards the “dual carbon” goal. This assessment will facilitate research on carbon neutrality and promote regional ecological protection and development. This study utilized the “One Map” data of forest resources (2020) and the first year (2017) of the establishment of the national park in Wuyi Mountain National Park (WMNP). The continuous biomass expansion factor method, in conjunction with the vegetation carbon content coefficient, was employed to estimate the forest carbon storage within the park’s forested areas. Subsequently, the distribution of forest carbon storage was analyzed using remote sensing estimation methods, and a comparison was made between the forest carbon storage of these two years. Finally, correlation analysis and path analysis were conducted to identify the primary factors influencing forest carbon storage. The study findings reveal that in 2020, the total carbon storage in forests reached 4.851 × 106 t C, with an average carbon density of 49.55 t C·hm−2. Furthermore, the study identified positive correlations between dominant tree species, age groups, and elevation with carbon storage, whereas slope length and aspect were found to have negative correlations. Dominant tree species were observed to have the greatest impact on forest carbon storage in both 2017 and 2020, followed by age groups. These findings offer valuable scientific insights for the implementation of forest carbon storage pilot projects in WMNP.

Yield, carbon stock, and price dynamics of agroforestry tree species in district Mardan, Khyber Pakhtunkhwa, Pakistan.

A socio-economic study was conducted in district Mardan of the Khyber Pakhtunkhwa (KP) province of Pakistan to get a comprehensive knowledge of the agroforestry tree species grown on the farmlands, their yield, and carbon stock. For yield and carbon stock estimation, data were collected from 59 sample plots by measuring the diameter, height, volume, and biomass of selected agroforestry tree species through D-tape and Haga altimeter. A total of 59 sample plots were inventoried using 2.5 percent sampling intensity. Each sample plot has an area of 0.5 ha, where each tree with a Diameter at Breast Height (DBH) ≥ 5 cm was inventoried. The calculated amount of volume of each tree species was then converted to biomass by multiplying it by the density of wood and the Biomass Expansion Factor (BEF). Total yield and C stock for the selected agroforestry tree species were 11535.2 metric tons and 2102.2 metric tons, respectively. Populus euroamericana is classified as the main tree with 28% growing stock prior to Morus alba by 21%, while Melia azedarach, Eucalyptus camaldulensis, Dalbergia sissoo, Acacia nilotica, Salix tetrasperma, and Bombax ceiba consist of 15%, 12%, 8%, 6%,7% and 3% growing stock respectively. Among the species found in different sampling plots the yield of Populus euroamericana was found to be 4747.5 metric tons and it was followed by the species Morus alba found at 2027.3 metric tons. Similarly, the volume for Melia azedarach, Eucalyptus camaldulensis, Dalbergia sissoo, Salix spp, Boombox ceiba, and Acacia nilotica was 1532.2 tons,1503 ton,745.7,203.5ton, 555.4ton and 220.5ton, respectively. The carbon stock for Populus euroamericana was calculated as 777.8 ton/ha, while for Eucalyptus camaldulensis, Melia azedarach, Morus alba, Dalbergia sissoo, Acacia nilotica, Salix species, and Bombax ceiba it was calculated as 312.3ton/ha, 272.1ton/ha, 363ton/ha, 245.1ton/ha, 51.4ton/ha, 27.3ton/ha and 53.2ton/ha, respectively. The questionnaire survey conducted for price dynamics showed that the majority of respondents purchase timber from the market for construction. But they use farm trees with low-quality city construction. They dislike using local timber in the conventional building as timber from farm trees is liable to insect attack. Rs. 50,000-100000, (33.33%) of daily sales was concluded from 50% of the trader while (16.7%) of the traders have their sales between Rs.150,000-200,000. Therefore, it is concluded by the authors that both provincial and federal government should promote agroforestry in Pakistan through different incentives because it has the potential to cope with dilemma of deforestation of natural forests and improve the livelihood of local peoples. It is strongly recommended that special projects just like the Ten Billion Tree Afforestation Project (T-BTTP) should be launched for agroforestry plantation and promotion in the country to sustain the ecological harmony and uplift the socio-economic condition of the peoples of Pakistan.

Land use/land cover change and carbon footprint in tropical ecosystems in Benin, West Africa

Extensive research has explored land use and land cover change (LULCC) in tropical ecosystems, but more detailed carbon footprint data is essential for defining strategies to enhance carbon sinks. This study assessed LULCC and its associated carbon footprints in different natural ecosystems. It also established forest reference levels (FRL). We used Landsat images for supervised classification and conducted forest inventories in 186 plots that span moist semi-deciduous forest, swamp forest, gallery forest, woodland and savannah areas. Biomass calculations employed allometric models, biomass expansion factors, and root-to-shoot ratios. Except in Lama Forest Reserve, anthropogenic pressures led to the regressive conversion of natural forest areas to savannah, croplands, and fallows. A progressive trend was observed in semi-deciduous forest (3.18 % per year), resulting in a positive LULC carbon footprint (16.06 tCO2eq.yr−1ha−1). 41.94 % of typical swamp forest was lost, releasing -62.89 tCO2eq.yr−1ha−1. Similarly, woodland decreased by -1.48 and -5.89 % per year, according to considered site, with emissions of -12.16 and -21.83 tCO2eq.yr−1ha−1, respectively. FRL followed the gradient of canopy cover of the different vegetation types. The results highlight the need for adequate conservation and management, considering land use and cover specifics, and provide useful baselines for REDD+ activities in countries with similar ecosystems.

A Compatible Estimation Method for Biomass Factors Based on Allometric Relationship: A Case Study on Pinus densata Natural Forest in Yunnan Province of Southwest China

Using various biomass factors, such as biomass expansion factor (BEF) and biomass conversion and expansion factor (BCEF), yields different results for estimating forest biomass. Therefore, ensuring compatibility between total biomass and its components when employing different biomass factors is crucial for developing a set of rapid and efficient models for large-scale biomass calculation. In this study, allometric equations were utilized to construct independent models and the proportional values (root-to-shoot ratio (Rra), crown-to-stem ratio (Rcs), bark-to-wood ratio (Rbw), foliage-to-bark ratio (Rfb), and wood biomass-to-wood volume (ρ)) by using the mean height (Hm) and the mean diameter at breast height (Dg) of 98 Pinus densata plots in Shangri-La, Yunnan province, China. The compatible methods were applied to reveal the compatibility between the total biomass and each component’s biomass. The results showed the following: (1) Both the independent model and compatible model had a higher accuracy. The values were greater than 0.7 overall, but the foliage biomass accuracy was only 0.2. The total biomass and the component biomass showed compatibility. (2) The accuracy of BEF and BCEF exceeded 0.87 and the total error was less than 0.1 for most components. (3) The mean BEF (1.6) was greater than that of the Intergovernmental Panel on Climate Change (IPCC) (M = 1.3), and the mean BCEF was smaller than that of the IPCC; the values were 0.6 and 0.7, respectively. The range of BEF (1.4–2.1) and BCEF (0.44–0.89) were all within the range of the IPCC (1.15–3.2, 0.4–1.0). This study provides a more convenient and accurate method for calculating conversion coefficients (BEF and BCEF), especially when only Rcs data is available.

Measurement of the fair value of forest carbon sinks – Taking Yixing National Forest Park as an example

Management of forest carbon sinks can be viewed as a strategy to deal with climate change. To promote the establishment and improvement of the forest carbon market, it is important to measure the economic benefits of China’s existing forest carbon sinks with special weighting to forests along with protection of nature. Objectively measuring the value of a carbon sink is an important prerequisite to play the role of forest carbon pool and improve the efficiency of carbon sinks. This paper considers the strategy and process of forest carbon sink value accounting from two aspects of forest carbon storage and value, puts forward a set of forest carbon sink fair value accounting ideas, and considers Yixing forest farm as the research area. The following methods were used to compare the forest carbon stock of the Yixing National Forest Park. First, the economic benefits of forest carbon sink were evaluated with a market approach and carbon fair value. Next, the biomass expansion factor method and income approach were used to compute the forest carbon stock of Yixing National Forest Park, indicating a high carbon fair value.

Species-Specific Allometric Equations, Biomass Expansion Factor, and Wood Density of Native Tree Species in the Dry Afromontane Forest of Ethiopia

A forest is a storehouse of carbon released from different sources when the activities of sustainable forest management, planting, and rehabilitation exist. However, few allometric equations are present to determine its contribution to carbon reduction. The target of the study was to develop species-specific allometric equations and establish a database for biomass expansion factor and wood density for five tree species grown in the dry Afromontane forest of Ethiopia. A direct or destructive sampling method was used on 62 trees from different diameter classes. The diameter at breast height and the total height of selected trees ranged from 7 to 48 cm and 6.7 to 23.4 m, respectively. Trees were felled and divided into various biomass sections. Stem and big branch discs were sampled to determine the wood density and volume of the trees. Sample wood and foliage were oven-dried for three days and two days at 105°C and 70°C, respectively, to get their dry weight. Total above-ground biomass was regressed using diameter at breast height, total height, wood density, and average crown diameter as independent variables. R software version 4.0.1 was used to fit the biomass equations. The best biomass models were determined to have lower AIC and RSE and highest adj. R2. The biomass expansion factor and wood density of five tree species ranged from 1.19 to 1.40 and 0.53 to 0.74 g/cm−3, respectively. Species-specific allometric equations were better than both mixed species and pan tropical models for the assessment of above-ground biomass in the Chilimo dry Afromontane forest of Ethiopia.

Formulating biomass allometric model for Paraserianthes falcataria (L) Nielsen (Sengon) in smallholder plantations, Central Kalimantan, Indonesia

The forests in Central Kalimantan, Indonesia have been heavily impacted by logging, mining, fires, and other degradation activities for over 30 years. To address this, the Indonesian government has promoted community-based forest management schemes. One such scheme, called Hutan Kemasyarakatan (HKm), has introduced Sengon (Paraserianthes falcataria) in smallholder plantations in Rungan Barat, Gunung Mas, Central Kalimantan. However, accurate estimation of biomass is crucial for carbon sequestration credits, but there are no specific allometric models for estimating Sengon above-ground biomass (AGB) in this area. To create a site-specific AGB allometric model for Sengon, 23 trees were felled to collect fresh biomass data. Various tree variables, such as diameter at breast height: 1.3 m (DBH), total height, merchantable height, and stem bole volume were measured for each sample tree. The average wood basic density of Sengon at the study site was also calculated. A total of nine alternative candidate regression equations were fitted and tested to select the best-fit AGB allometric model. Also, to assess the adaptedness of the identified AGB allometric model, comparisons with the models from literature, and comparisons between two interchangeable methodologies (i.e. direct biomass allometric model and biomass expansion factor (BEF)-based biomass estimation) were undertaken. This study has developed a regression function, denoted as to estimate the AGB of Sengon trees in smallholder plantations in Central Kalimantan, Indonesia. The formulated regression function demonstrated better estimation performance compared to common pantropical and regional AGB allometric models. In terms of the BEF-biomass approach, the AGB estimation derived from Smalian’s volume was relatively accurate, close to the mean AGB obtained by the formulated model in this study. In summary, this study proposes using the developed model, based solely on DBH, to accurately estimate AGB and carbon sequestration potential in Sengon trees. The accurate estimation of AGB using this model has additional advantages, including facilitating carbon credit acquisition and informing long-term management decisions.

What is meant by land-use change? Effects of mining activities on forest and climate change.

The ownership of 99.9% of forests in Turkey belongs to the State. According to the mandatory provisions of the Turkish Constitution of 1982, the ownership of State forests cannot be transferred to third parties. However, forest legislation permits several activities within the State forests, other than forestry, under certain conditions. Thus, in this study, the legal process of mining permits granted in State forests in Turkey was analyzed, and the policies implemented in mining permits were tried to be evaluated. Then, how mining activities affect forestlands and the environment has been compared by taking international studies in the literature into account. The change in the amount of carbon stored in the forests where the land use changed as a result of the given mining permit was calculated using the biomass expansion factor (BEF) method. After the mining permit was granted, 53% of the land-use change occurred in the sample area, and there was a 43% decrease in the amount of carbon stored. According to the results of the analysis, before the mining permit was granted, the amount of carbon stored by the area in 2009 was calculated as 4400.23 tons. However, with the start of mining activities in 2011, nearly half of the trees in the area were cut down, which was caused this value to drop to 1911.12 tons. As a result of the mining activities that continued after this date, it was determined by 2021 that all the trees in the area were cut down, and the amount of carbon stored in the area decreased to zero.

Estimation of the biomass and carbon in Cupressus lusitanica Mill. trees in Costa Rica

[Introduction]: Forest plantations are an important carbon sinks and reservoirs while providing other important environmental goods and services. [Objective]: In this research, we developed models to estimate the biomass and carbon content of Cupressus lusitanica Mill trees and its components or fractions, in forest plantations in Costa Rica. [Methodology]: Through the destructive sampling of 43 trees, a sample of each component was obtained to determine dry matter and carbon content. The models were built through linear regression analysis and ordinary least squares, using the normal diameter as the independent variable. Models were selected through the weighted sum of the calculated statistics and the graphical analysis of the residuals. [Results]: The coefficient of determination (R2) was greater than 83.8 % and the estimation error or bias was less than 7.2 %. The leaf and root fractions were more difficult to model, given their lower fit and higher error. The stem represents 61.7 % of total tree biomass, the branches 17.1 % and the roots 9.1 %. The aerial biomass expansion factor was 1.54 (1.3 and 1.24 for branches and foliage) and 1.12 for roots. [Conclusions]: Allometric models accurately predict biomass and carbon content, are easy to use, and become useful low-cost tools to quantify the ecologic and greenhouse gas emission mitigation functions of these forests.

Models for biomass expansion factor of acacia hybrid (A. auriculiformis* A. mangium) plantations in the Southern region, Vietnam

Acacia hybrid is one of the favorably fast-growing species which is bring to potential benefits of agro-ecological and socio-economic sectors in Vietnam. The main objective of this study was to develop well-fitted models for estimating biomass expansion factor (BEF) for Acacia hybrid plantations. Fifty-four samples of Acacia hybrid trees from 2 to 10 years of age were collected from Acacia hybrid plantations in the Southern part of Vietnam. Total dry biomass including stems, branches and leaves were used to estimate an average value of BEF. The BEF value was calculated by taking the dry aboveground biomass (W) divided by the volume of merchantable tree woods over their barks (Vm). Twelve allometric equations were fitted by constructing regression models between BEF and inventory variables including diameter at breast height (DBH), height (H) and age (A). Consequently, the average value of BEF was 1.11 ton/m3. The BEF value had a strongly negative relationship with DBH, height and age in which the BEF value decreased as these three parameters increased. Two best fitted models for estimating a BEF value of Acacia hybrid (A. auriculiformis * A. mangium) plantations included: BEF = 1.99865 - 0.15400*DBH - 0.02123*H + 0.18210*A; and BEF = 3.01307 - 2.44459*ln(DBH) - 0.10171*DBH -2.06212*ln(H) + 1.54556*ln(DBH*H*A). Estimated values of above-ground biomass by utilizing the fitted BEF values from two these models were similar. Results of the study indicated that use of a fitted BEF model is fundamental to obtain reliable estimates of biomass and CO2 equivalent for Acacia hybrid plantations.

Stem volume and above ground biomass models for Sitka spruce (Picea sitchensis (Bong.) Carr.) in Iceland

The prediction of tree biomass and stem volume is necessary for monitoring and assessing of national forest biomass, carbon stock and sustainable forest management. Such predictions of biomass or carbon stocks are generated by using either allometric models or applying biomass expansion factors (BEFs), where the former is a better method. Volume models are generated by using allometric models. The data for development of the new volume and biomass models for Iceland presented in this paper were collected between years 2000-2021, from 48 locations in even aged stands that were planted between 1942-1983. Because of the young age of forest plantations in Iceland, existing biomass and volume models need to be updated regularly as trees get older and larger. The new models use the same independent variables as the previous ones for Iceland but use a wider approach and have a different form than the older ones. Using the previous Icelandic models outside their data range results in underestimation for both aboveground biomass and stem volume.

Carbon Storage of Shelterbelts in Yunnan Province and Countermeasures for Increasing Carbon Sinks

Based on the data of seven national forest inventory and the fourth second-class forest inventory in Yunnan Province, the biomass expansion factor method was used to calculate the carbon storage dynamics of shelterbelts in Yunnan Province. The results show that: 1) the carbon storage of shelterbelts in Yunnan Province increased from 8868.03×104 tons in 1988 to 37635.01×104 tons in 2018, with an average annual growth of 821.91×104 tons. The contribution rate of shelterbelts carbon storage to the total forest carbon storage in Yunnan Province increased from 17.59% to 41.63%, and the total average carbon density of shelterbelts showed an upward trend in fluctuation. 2) the contribution rate of carbon storage of middle-aged forest (20.20%-27.44%) was the largest, the mature forest and overmature forest was the second and third, and the contribution rate of carbon storage of young forest was the lowest. The total average carbon density of shelterbelts increased with the age classes. 3) The natural shelterbelts had been the main contributor to the carbon storage in Yunnan, and its contribution rate (between 95.80% and 99.53%) decreases gradually, while the carbon density of natural shelterbelts increases with the increase of age. Compared with natural shelterbelts, the carbon storage and density of artificial shelterbelts were at a lower level, and the total average carbon density of artificial shelterbelts is on the rise. The carbon density of artificial shelterbelts of different ages is mature forest > near mature forest > over mature forest > middle aged forest > young forest. 4) Diqing Prefecture was the main contributor of carbon storage of shelterbelts in Yunnan Province (the contribution rate is 17.65%), and the carbon storage of shelterbelts in northwest Yunnan accounts for 44.19% of the total carbon storage of shelterbelts in Yunnan Province. Yunnan province should pay attention to the maturity of middle-aged and young shelterbelts, strengthen the management of artificial shelterbelts to enhance the carbon storage capacity of Yunnan shelterbelts.

Forest Carbon Reserve Calculation and Comprehensive Economic Value Evaluation: A Forest Management Model Based on Both Biomass Expansion Factor Method and Total Forest Value

With the continuous intensification of global climate warming, the carbon cycle has become the focus of global climate change, and the calculation and value evaluation of forest carbon reserves is a key link in promoting the global carbon cycle system. Considering the climatic factors, the biomass expansion factor method (BEF) is used to calculate the forest carbon reserves, selecting the best Gompertz model, adding the time change to the forecast model to predict the growth of forest stock, and the four key indexes of total forest value (TEV) are selected for comprehensive evaluation of forest value. The results show that the carbon fixation efficiency and prediction of forest farms depend largely on the trees, and products can provide more value. Accordingly, it is suggested that broad-leaved trees and younger trees should be planted, and broad-leaved trees should be planted to increase forest stock, increase the vertical distribution of forests to increase carbon reserves, and make trees into wood products with longer retention time to achieve higher total forest value.

Allometry, Biomass and Productivity in Pinus massoniana Forests of China: An Updated Review of Published Data

Field measurements of forest biomass are labor-consuming and usually destructive, but such direct datasets are the foundation for further developing indirect estimation such as biomass equation and biomass expansion factors that were used to scale biomass estimation or carbon storage from site or local surveys up to regional or national level. Pinus massoniana is widely distributed throughout 17 provinces of China and has a high economic value. This study is an updated review of the allometric equations, biomass allocation data and productivity estimations in Pinus massoniana forests of China published in articles during the period from 1982 to 2019. Different allometric equations of Pinus massoniana showed site-specific dependences. The aboveground and total tree biomass were expressed as power equations of mean age for Pinus massoniana forests. The mean value of aboveground tree biomass, total tree biomass and ecosystem biomass across all ages for Masson pine forests was 109.81, 127.65 and 138.76 Mg/ha, respectively. The mean proportion of stem, branch and foliage to aboveground tree biomass for Pinus massoniana was 77.1%, 15.9% and 7%, respectively. The tree root biomass continuously increased with the aboveground tree biomass and a power relationship was found between the tree root biomass and aboveground tree biomass for Pinus massoniana forests. The tree net primary productivity increased with aboveground tree biomass for Pinus massoniana forests, and the relationship was expressed as a linear equation. The mean tree, litter and ecosystem net primary productivity was 7.04, 4.88 and 8.30 Mg/ha/year, respectively. These findings provide key parameters for the biomass estimation and carbon accounting studies of widely planted Pinus massoniana forests in China.

Error Analysis on the Five Stand Biomass Growth Estimation Methods for a Sub-Alpine Natural Pine Forest in Yunnan, Southwestern China

Forest biomass measurement or estimation is critical for forest monitoring at the stand scale, but errors among different estimations in stand investigation are unclear. Thus, the Pinus densata natural forest in Shangri-La City, southwestern China, was selected as the research object to investigate the biomass of 84 plots and 100 samples of P. densata. The stand biomass was calculated using five methods: stand biomass growth with age (SBA), stem biomass combined with the biomass expansion factors (SB+BEF), stand volume combined with biomass conversion and expansion factors (SV+BCEF), individual tree biomass combined with stand diameter structure (IB+SDS), and individual tree biomass combined with stand density (IB+SD). The estimation errors of the five methods were then analyzed. The results showed that the suitable methods for estimating stand biomass are SB+BEF, M+BCEF, and IB+SDS. When using these three methods (SB+BEF, SV+BCEF, and IB+SDS) to estimate the biomass of different components, wood biomass estimation using SB+BEF is unsuitable, and root biomass estimation employing the IB+SDS method was not preferred. The SV+BCEF method was better for biomass estimation. Except for the branches, the mean relative error (MRE) of the other components presented minor errors in the estimation, while MRE was lower than other components in the range from −0.11%–28.93%. The SB+BEF was more appealing for branches biomass estimation, and its MRE is only 0.31% lower than SV+BCEF. The stand biomass strongly correlated with BEF, BCEF, stand structure, stand age, and other factors. Hence, the stand biomass growth model system established in this study effectively predicted the stand biomass dynamics and provided a theoretical basis and practical support for accurately estimating forest biomass growth.

Estimating Carbon Stocks and Biomass Expansion Factors of Urban Greening Trees Using Terrestrial Laser Scanning

Urban forest carbon sequestration represents an important component of the global forest carbon pool; however, accurate measurements are limited by the inability of existing field stand models to match the specificity of urban greening species. Herein, canopy volume, carbon stock, and the biomass expansion factor (BEF) of 30 Koelreuteria paniculate trees were measured based on terrestrial laser scanning (TLS) and compared to the results of existing wood volume and carbon stock model measurements. The findings revealed that (1) TLS point cloud data were highly reproducible and accurate (root mean square error of tree height and diameter at breast height were ±0.35 m and ±0.33 cm, respectively). (2) Owing to human interference and cluttered urban environments, the BEF of urban greening tree species fluctuated irregularly, considerably different from that of natural forest stands. (3) Leaf carbon stocks were influenced by the size of the voxel. (4) Different tree measurement factors maintained variable degrees of influence on BEF (height under branch, volume of thick branch, crown width, and projected areas of tree-crown produced correlation coefficients of −0.64, 0.54, 0.45, and 0.43, respectively). Accordingly, the carbon stock and BEF of urban greening tree species can be accurately calculated via TLS without damage.

Assessing logging residues availability for energy production by using forest management plans data and geographic information system (GIS)

The aim of the work was to quantify the mass of logging residues (branches and tops; t yr−1 dry matter, DM) for energy generation starting from Forest Management Plans (FMP) data. The methodology was applied to public stands of an Italian district (area: 3.60 × 104 ha; period: 2009–2018). Compared to the previous preliminary analysis, the potentially available residues were computed considering forest accessibility and road traversability, by combining FMPs data with a geographic information system (GIS). New issues that were assessed here were: (i) representation of stands consisting of multiple disconnected parts; (ii) calculation of producible residues by using different values of biomass expansion factors (Scenario 1, S1; Scenario 2, S2). The potentially available residues computed for the analyzed period were used to quantify the current sustainable supply. Then, the potentially generated heat (thermal energy, TE; GJ yr−1) and electricity (EE; GJ yr−1), and the potentially avoided CO2 emissions into the atmosphere (EM; t yr−1 CO2) related to the final combustion process were computed by assuming that the current supply of residues was used as woodchips in a local centralized heating plant currently operating. For both S1 and S2, the large difference between the potentially producible and the potentially available residues demonstrated that geodata are essential for reliable estimations. Moreover, as the required information for the GIS analysis can be easily found in databases made available by forestry authorities, the proposed approach can be applied also to other areas; this could be helpful to support local decision-makers in defining sustainable practices for residues recovery.