The PhD Thesis focuses on two topics: (i) assessment of forest wood and carbon (C) stock and (ii) forestry mechanization applicable at the forest stand level for any given conditions among those found in the Italian Alpine and pre-Alpine mountainous areas. Both these topics aim to improve the use of forestry resources for climate change mitigation, starting from a bottom-up approach scaled on the information made available by Forest Management Plans (FMP). After an introduction on the topics given in chapter 1, the first topic (assessment of forest wood and C stock) is investigated in chapters 2, 3, 4 and 5, by taking the Valle Camonica District (Lombardy Region, Italy) as Case Study Area. The aim is to develop a stand-level model to estimate the mass of wood (t·yr-1 dry matter, DM) and C (t·yr-1 C) in aboveground wood biomass, belowground wood biomass and dead organic matter (i.e., deadwood and litter), quantifying, at the same time, the mass of potentially available logging residues (i.e., branches and tops; t·yr-1 DM) for energy generation and the corresponding potentially generated energy (GJ·yr-1), under the assumption that wood replaces non-renewable energy sources. Chapter 2 presents the first version of the model, called “WOody biomass and Carbon ASsessment” (WOCAS v1), aimed at the quantification of the mass of wood and C in the forest pools in a predefined reference year, by using a methodology already applied at the regional and national level. The model was tested on a dataset of 2019 public forest stands extracted from 45 FMPs (area: 37000 ha) covering the period from 1984 (year in which the oldest FMP came into force) to 2016 (most recent available data from the local FMPs). Preliminary results showed that, in 2016, the total C stock (given by the sum of C stock in aboveground wood biomass, belowground wood biomass, and dead organic matter) achieved 76.02 t·ha-1 C. The model also gives the possibility to analyze future scenarios based on the continuation of the current management practices rather than improved practices, to define a possible mitigation strategy for the activation of a local Voluntary Carbon Market. WOCAS v1 was implemented into a second version (WOCAS v2), by introducing, first of all, an improved methodology to calculate the mass of wood (t·yr-1 DM) and C (t·yr-1 C) within the forest pools from the year in which the FMPs entry into force until a predefined reference year (chapter 3). The main innovative aspect of the improved methodology is that the gross annual increment of each stand is calculated through an age-independent theoretical non-linear growth function based on the merchantable stem mass, solving the limitation of WOCAS v1 in which the gross annual increment of the stand is assumed as constant, as reported by the FMPs. This improved methodology was applied to the same dataset used for WOCAS 1 (i.e., 2019 forest stands, 45 FMPs; forest area: 37000 ha; period: 1984-2016). The total weighted average wood yield, calculated as the sum of wood yield in all the above-mentioned forest pools, ranged from 53.36±53.13 t∙ha-1∙yr-1 DM (1984) to 156.38±79.76 t∙ha-1∙yr-1 DM (2016). The total weighted average C yield ranged from 26.63±26.80 t∙ha-1∙yr-1 C (1984) to 77.45±40.19 t∙ha-1∙yr-1 C (2016). The average C yield related to the whole analyzed period (1984-2016) was 66.04 t∙ha-1 C. Of this, C yield in the aboveground wood biomass, belowground wood biomass and dead organic matter was equal to 72.0%, 15.8% and 12.2%, respectively. Validation of the results at the stand level was performed by comparing the value of the gross annual increment provided by the FMPs with the one predicted by WOCAS v2. The model caused, in some cases, an overestimation and, in other cases, an underestimation. For example, for Larix decidua Mill. and for Picea abies L., the Pearson coefficient of correlation (r2) between predicted and provided increments was r2 = 0.69 and r2 = 0.46, respectively. This was due to the fact that the methodology currently implemented into WOCAS v2 is based on average values of growth parameters valid for the whole Lombardy Region, and does not consider the productivity class of the stands since specific information was not always made available by the FMPs. WOCAS v2 also includes an innovative methodology (chapter 4 and chapter 5) to quantify – as an additional climate change mitigation strategy – the mass of potentially available residues (t·yr-1 DM) for energy generation, the potentially generated heat and electricity (GJ·yr-1) and the potentially avoided CO2 emissions into the atmosphere related to the final combustion process (t·yr-1 CO2), under the assumption that wood substituted non-renewable energy sources. In chapter 4, since not all the required data were initially made available for the Case Study Area, the mass of residues was computed by considering only the stand’s function and the stand’s management system, covering the period from 1994 (year in which the first wood cut was performed) to 2016. The calculation was then improved (chapter 5) by taking into account also the stand’s accessibility, the forest roads’ transitability and the energy market demand. Information on topographic features, landscape morphology and characteristics of the forest roads were collected by combining the FMPs data coming from WOCAS v2 and a Digital Elevation Model (DEM) in a Geographic Information System (GIS) software. The georeferenced stands were characterized by both single contiguous areas (single stands), as well as different non-contiguous areas (sub-stands). Overall, 2157 polygons – consisting of both single and sub-stands – were analyzed, covering the period from 2009 (most recent available data on forest roads’ transitability) and 2016. The mass of potentially available residues calculated for the analyzed period was used to estimate the current sustainable supply (i.e., 1.82∙103±6.61∙102 t·yr-1 DM). Under the hypothesis that these residues were prepared into woodchips to feed the Organic Rankine Cycle (ORC) unit of the local centralized heating plant of Ponte di Legno, the potentially generated heat and electricity (GJ·yr-1) and the potentially avoided CO2 emissions into the atmosphere (t∙yr-1 CO2) for the final combustion process were estimated by assuming that: (i) heat generated by the ORC unit replaced the one produced by natural gas-based heating plants; (ii) electricity generated by the ORC unit replaced the one generated by the Italian natural gas-based plants-mix for combined heat and electricity production and distributed through the National grid. Results showed that if only the current sustainable mass of residues was used to feed the ORC unit of the plant, the potentially generated heat and electricity would represent at most 28.7% of that generated by the unit in the year 2019. The thermal and electric power would be equal to 0.70 MW and 0.17 MW, with an average power load of the ORC unit of 23.6%. Experimental tests are needed to collect information on the harvesting method, used machines and technologies – which considerably affect the mass of available resides – as well as the currently harvested mass of residues for the validation of the results, that up to now is not possible since no measured data are available yet at the stand level. The second topic (forestry mechanization) is investigated in chapter 6. The aim is to develop an innovative approach in order to: (i) select the most suitable Forestry Machinery Chain (FMC) to adopt at the stand level for wood collection (harvesting and transport) and (ii) compute the economic costs (€·h-1; €·t-1 DM; €) of the selected FMC. To make the selection feasible, a user-friendly stand-level model called “FOREstry MAchinery chain selection” (FOREMA v1) was developed. FOREMA v1 supports the user in selecting the FMC according to seven technical parameters that characterize the stand. For each FMC, the model defines the sequence of the operations and the types of machines that can be used. The economic costs of the selected FMC are then quantified by taking into account the fixed and the variable costs. The approach was applied for a Case Study concerning the collection of woodchips from a coppice stand in the Italian Alps for energy generation. The analyzed FMC was made up of the following operations: (i) felling, (ii) bunching and extraction, (iii) chipping and (iv) loading and transport. For the whole FMC, the cost per unit of time was 669.3 €·h-1; the cost per unit of product was 113.0 €·t DM, whereas the cost of production amounted to 6893.2 €. Results provided by FOREMA v1 still need to be validated; experimental tests are required to collect information on the operating conditions in which the machines are actually used and, consequently, on the corresponding economic costs. Obtained results on the costs of the operations were compared with that reported in literature and related to studies performed under similar forestry and operating conditions.

ASSESSMENT OF WOOD BIOMASS AND CARBON STOCK AND EVALUATION OF MACHINERY CHAINS PERFORMANCES IN ALPINE FORESTRY CONDITIONS: AN INNOVATIVE MODELLING APPROACH / L. Nonini ; Tutor: M. Fiala ; Coordinatore: D. Bassi. - : . Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, 2021 Jun 11. ((33. ciclo, Anno Accademico 2020.

ASSESSMENT OF WOOD BIOMASS AND CARBON STOCK AND EVALUATION OF MACHINERY CHAINS PERFORMANCES IN ALPINE FORESTRY CONDITIONS: AN INNOVATIVE MODELLING APPROACH

L. Nonini
2021-06-11

Abstract

The PhD Thesis focuses on two topics: (i) assessment of forest wood and carbon (C) stock and (ii) forestry mechanization applicable at the forest stand level for any given conditions among those found in the Italian Alpine and pre-Alpine mountainous areas. Both these topics aim to improve the use of forestry resources for climate change mitigation, starting from a bottom-up approach scaled on the information made available by Forest Management Plans (FMP). After an introduction on the topics given in chapter 1, the first topic (assessment of forest wood and C stock) is investigated in chapters 2, 3, 4 and 5, by taking the Valle Camonica District (Lombardy Region, Italy) as Case Study Area. The aim is to develop a stand-level model to estimate the mass of wood (t·yr-1 dry matter, DM) and C (t·yr-1 C) in aboveground wood biomass, belowground wood biomass and dead organic matter (i.e., deadwood and litter), quantifying, at the same time, the mass of potentially available logging residues (i.e., branches and tops; t·yr-1 DM) for energy generation and the corresponding potentially generated energy (GJ·yr-1), under the assumption that wood replaces non-renewable energy sources. Chapter 2 presents the first version of the model, called “WOody biomass and Carbon ASsessment” (WOCAS v1), aimed at the quantification of the mass of wood and C in the forest pools in a predefined reference year, by using a methodology already applied at the regional and national level. The model was tested on a dataset of 2019 public forest stands extracted from 45 FMPs (area: 37000 ha) covering the period from 1984 (year in which the oldest FMP came into force) to 2016 (most recent available data from the local FMPs). Preliminary results showed that, in 2016, the total C stock (given by the sum of C stock in aboveground wood biomass, belowground wood biomass, and dead organic matter) achieved 76.02 t·ha-1 C. The model also gives the possibility to analyze future scenarios based on the continuation of the current management practices rather than improved practices, to define a possible mitigation strategy for the activation of a local Voluntary Carbon Market. WOCAS v1 was implemented into a second version (WOCAS v2), by introducing, first of all, an improved methodology to calculate the mass of wood (t·yr-1 DM) and C (t·yr-1 C) within the forest pools from the year in which the FMPs entry into force until a predefined reference year (chapter 3). The main innovative aspect of the improved methodology is that the gross annual increment of each stand is calculated through an age-independent theoretical non-linear growth function based on the merchantable stem mass, solving the limitation of WOCAS v1 in which the gross annual increment of the stand is assumed as constant, as reported by the FMPs. This improved methodology was applied to the same dataset used for WOCAS 1 (i.e., 2019 forest stands, 45 FMPs; forest area: 37000 ha; period: 1984-2016). The total weighted average wood yield, calculated as the sum of wood yield in all the above-mentioned forest pools, ranged from 53.36±53.13 t∙ha-1∙yr-1 DM (1984) to 156.38±79.76 t∙ha-1∙yr-1 DM (2016). The total weighted average C yield ranged from 26.63±26.80 t∙ha-1∙yr-1 C (1984) to 77.45±40.19 t∙ha-1∙yr-1 C (2016). The average C yield related to the whole analyzed period (1984-2016) was 66.04 t∙ha-1 C. Of this, C yield in the aboveground wood biomass, belowground wood biomass and dead organic matter was equal to 72.0%, 15.8% and 12.2%, respectively. Validation of the results at the stand level was performed by comparing the value of the gross annual increment provided by the FMPs with the one predicted by WOCAS v2. The model caused, in some cases, an overestimation and, in other cases, an underestimation. For example, for Larix decidua Mill. and for Picea abies L., the Pearson coefficient of correlation (r2) between predicted and provided increments was r2 = 0.69 and r2 = 0.46, respectively. This was due to the fact that the methodology currently implemented into WOCAS v2 is based on average values of growth parameters valid for the whole Lombardy Region, and does not consider the productivity class of the stands since specific information was not always made available by the FMPs. WOCAS v2 also includes an innovative methodology (chapter 4 and chapter 5) to quantify – as an additional climate change mitigation strategy – the mass of potentially available residues (t·yr-1 DM) for energy generation, the potentially generated heat and electricity (GJ·yr-1) and the potentially avoided CO2 emissions into the atmosphere related to the final combustion process (t·yr-1 CO2), under the assumption that wood substituted non-renewable energy sources. In chapter 4, since not all the required data were initially made available for the Case Study Area, the mass of residues was computed by considering only the stand’s function and the stand’s management system, covering the period from 1994 (year in which the first wood cut was performed) to 2016. The calculation was then improved (chapter 5) by taking into account also the stand’s accessibility, the forest roads’ transitability and the energy market demand. Information on topographic features, landscape morphology and characteristics of the forest roads were collected by combining the FMPs data coming from WOCAS v2 and a Digital Elevation Model (DEM) in a Geographic Information System (GIS) software. The georeferenced stands were characterized by both single contiguous areas (single stands), as well as different non-contiguous areas (sub-stands). Overall, 2157 polygons – consisting of both single and sub-stands – were analyzed, covering the period from 2009 (most recent available data on forest roads’ transitability) and 2016. The mass of potentially available residues calculated for the analyzed period was used to estimate the current sustainable supply (i.e., 1.82∙103±6.61∙102 t·yr-1 DM). Under the hypothesis that these residues were prepared into woodchips to feed the Organic Rankine Cycle (ORC) unit of the local centralized heating plant of Ponte di Legno, the potentially generated heat and electricity (GJ·yr-1) and the potentially avoided CO2 emissions into the atmosphere (t∙yr-1 CO2) for the final combustion process were estimated by assuming that: (i) heat generated by the ORC unit replaced the one produced by natural gas-based heating plants; (ii) electricity generated by the ORC unit replaced the one generated by the Italian natural gas-based plants-mix for combined heat and electricity production and distributed through the National grid. Results showed that if only the current sustainable mass of residues was used to feed the ORC unit of the plant, the potentially generated heat and electricity would represent at most 28.7% of that generated by the unit in the year 2019. The thermal and electric power would be equal to 0.70 MW and 0.17 MW, with an average power load of the ORC unit of 23.6%. Experimental tests are needed to collect information on the harvesting method, used machines and technologies – which considerably affect the mass of available resides – as well as the currently harvested mass of residues for the validation of the results, that up to now is not possible since no measured data are available yet at the stand level. The second topic (forestry mechanization) is investigated in chapter 6. The aim is to develop an innovative approach in order to: (i) select the most suitable Forestry Machinery Chain (FMC) to adopt at the stand level for wood collection (harvesting and transport) and (ii) compute the economic costs (€·h-1; €·t-1 DM; €) of the selected FMC. To make the selection feasible, a user-friendly stand-level model called “FOREstry MAchinery chain selection” (FOREMA v1) was developed. FOREMA v1 supports the user in selecting the FMC according to seven technical parameters that characterize the stand. For each FMC, the model defines the sequence of the operations and the types of machines that can be used. The economic costs of the selected FMC are then quantified by taking into account the fixed and the variable costs. The approach was applied for a Case Study concerning the collection of woodchips from a coppice stand in the Italian Alps for energy generation. The analyzed FMC was made up of the following operations: (i) felling, (ii) bunching and extraction, (iii) chipping and (iv) loading and transport. For the whole FMC, the cost per unit of time was 669.3 €·h-1; the cost per unit of product was 113.0 €·t DM, whereas the cost of production amounted to 6893.2 €. Results provided by FOREMA v1 still need to be validated; experimental tests are required to collect information on the operating conditions in which the machines are actually used and, consequently, on the corresponding economic costs. Obtained results on the costs of the operations were compared with that reported in literature and related to studies performed under similar forestry and operating conditions.
FIALA, MARCO
BASSI, DANIELE
carbon stock; climate change mitigation; empirical models; forest management plan; forestry machinery chain; forestry operations; logging residues; site-specific primary data; wood biomass
Settore AGR/09 - Meccanica Agraria
ASSESSMENT OF WOOD BIOMASS AND CARBON STOCK AND EVALUATION OF MACHINERY CHAINS PERFORMANCES IN ALPINE FORESTRY CONDITIONS: AN INNOVATIVE MODELLING APPROACH / L. Nonini ; Tutor: M. Fiala ; Coordinatore: D. Bassi. - : . Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia, 2021 Jun 11. ((33. ciclo, Anno Accademico 2020.
Doctoral Thesis
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