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Case Report

Greenhouse Gas Emissions Associated with Tree Pruning Residues of Urban Areas of Northeast Brazil

by
Yuri Rommel Vieira Araujo
1,
Bartolomeu Israel Souza
2 and
Monica Carvalho
3,*
1
Graduate Program in Development and Environment, Federal University of Paraiba, João Pessoa 58051-900, Brazil
2
Department of Geoscience, Federal University of Paraiba, João Pessoa 58051-900, Brazil
3
Department of Renewable Energy Engineering, Federal University of Paraiba, João Pessoa 58051-900, Brazil
*
Author to whom correspondence should be addressed.
Resources 2024, 13(9), 127; https://doi.org/10.3390/resources13090127
Submission received: 17 July 2024 / Revised: 6 September 2024 / Accepted: 12 September 2024 / Published: 13 September 2024
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Abstract

:
There are environmental concerns (especially regarding climate change) associated with the negative effects of some pruning waste management practices. Converting urban tree waste into valuable products can help mitigate climate change, but it is important to quantify the repercussions of tree waste scenarios in an urban context. The objective of this study was to quantify the greenhouse gas (GHG) emissions for six scenarios of urban pruning waste in urban areas. To this end, the life cycle assessment methodology was applied to real data obtained from five municipalities of the Paraíba state in 2012–2021 (northeast Brazil). The six scenarios were: sanitary landfill (current practice), sanitary landfill with methane capture, municipal incineration, reuse of wood, heat generation and electricity generation. Considering the 10-year period, the sanitary landfill emitted 1048 kt CO2e, and when methane was captured at the landfill, emissions decreased to 1033 kt CO2e. The lowest emissions were associated with electricity generation, with 854 kt CO2e. The municipality of João Pessoa presented the highest emissions, followed by Cabedelo, Santa Rita, Bayeux, and Conde. Transportation was responsible for the highest share of GHG emissions. Disposal of urban pruning waste at the sanitary landfill presented the highest emissions, and it has been demonstrated herein that pruning waste can be used for the production of bioenergy, with significant potential to mitigate GHG emissions at local levels.

1. Introduction

Climate change is one of the main threats to society nowadays. In the short-term, the solution to this problem requires a radical transformation in the energy and economic system [1]. The progressive increase in the planet’s temperature has been monitored since 1880, thus making it possible to affirm that the most recent years have been the hottest in history [2]. In 2019, atmospheric concentrations of CO2, CH4, and N2O were higher than in any other period in the last 2 million years, with the main greenhouse gases (GHGs) that cause global warming being carbon dioxide (CO2), chlorofluorocarbon (CFC), methane (CH4), nitric oxide (HNO3), and ozone (O3) [3].
In the search for solutions and alternatives to limit GHG emissions, the use of biomass, especially residues of various types, has stood out [4]. Its application in carbon sequestration is one of the promising tools in GHG recovery, being a strategy for the global reduction in emissions and acting as a gas mitigating agent, with a range of application pathways [5,6].
Electricity generation from biomass residues, when compared with fossil fuel-originated electricity, can effectively realize environmental benefits regarding the mitigation of climate change [7]. Biomass can replace coal and natural gas with a lower increase in atmospheric temperature [8]. Another way to capture CO2 is through pyrolysis for biochar production [9].
GHG emissions can be quantified by the life cycle assessment (LCA), which is a methodology used to quantify potential environmental impacts. LCA can be applied to bioenergy systems, especially in waste management and urban areas [10,11,12]. It can evaluate the environmental impacts of municipal waste management and has been proven to be useful in the planning and decision-making process. LCA has demonstrated that the disposal of waste in sanitary landfills without energy recovery was the worst alternative [13,14]. Recycling can decrease the environmental impacts associated with waste collection practices, and integrated approaches in the collection, treatment, and destination of materials can achieve even greater reductions [15,16].
As cities are responsible for the emission of 70% of CO2 [17], there is an urgency to develop plans for the adaptation and mitigation of local climate change, increasing climate resilience. This can include the promotion of urban vegetation, green infrastructure, the utilization of residues, and green roofs.
Different urban pruning destination practices can lead to different levels of GHG emissions, enhanced carbon sequestration, and support a range of environmental benefits that contribute to climate change mitigation. Therefore, the objective of this study was to quantify the GHG emissions associated with the disposal of biomass waste from urban tree pruning. The six scenarios studied were: sanitary landfill (current situation), disposal in the landfill with methane capture, municipal incineration, wood reuse, heat generation, and electricity generation. This study used actual data from five municipalities in northeast Brazil, and the overarching contribution was to build an inventory of GHG emissions for the region. Urban tree pruning practices are integral to the sustainability of cities, and this study contributes by using 10-year data and explicitly addresses urban tree pruning waste regarding its potential to serve as a local mitigating agent.

2. Materials and Methods

The study area covered the urban spaces of the municipalities of Bayeux, Cabedelo, Conde, João Pessoa, and Santa Rita, all belonging to the Metropolitan Region of João Pessoa (Figure 1), the largest in Paraíba, with a population of 1,160,708 inhabitants [18]. This choice was made considering the total mass of biomass collected by the government in the five municipalities and the percentage of tree-lined streets, which ranged from 29.9% to 78.4%. In addition, together, the municipalities generated a total mass of 307 kt, over a period of 10 years [18,19].
The five municipalities are located in the Mata Paraibana mesoregion, in the Atlantic Forest biome, with a tropical hot and humid climate—As, according to Köppen’s classification, with rainfall of around 1800 mm/year [20].
The mass of solid waste collected by the municipalities and disposed of in a sanitary landfill was obtained directly from the Metropolitan Sanitary Landfill of João Pessoa [19]. Table 1 shows the amount of urban pruning waste collected, in kt (103 tons), since this disposal point started operating.
GHG quantification for the pruning waste disposal scenarios was performed by applying the life cycle assessment (LCA) methodology. The methodology was applied in four steps, following the guidelines of the Brazilian Association of Technical Standards [21,22], which are equivalent to the International Organization for Standardization (ISO) standards [23,24].
The first step began with the definition of the object and scope, with analysis of the system for pruning urban trees in the municipalities under study. This step identifies the pruning method, the biomass collection system in the urban area, and the transportation of this material to the sanitary landfill. The LCA encompassed the transportation of the pruning waste to the landfill and its final disposal scenario, and the functional unit of the study was the amount of waste collected throughout one year and transported to the landfill. The study comprised 10 years of data (2012–2021).
The pruning service is provided by the city halls and involves public collection services and autonomous entities responsible for solid waste management. This waste is collected by a specific team, without mixing with other objects, and sent to the metropolitan landfill of João Pessoa.
The second step is the construction of the life cycle inventory (LCI), considering the functional unit previously defined. The amount of waste collected was obtained directly from the cities responsible for waste management or from the Metropolitan Landfill of João Pessoa.
The transportation step was divided into two segments. The first corresponded to the route taken by the truck during waste collection within the urban perimeter, which employs a 3.5–7.5 t vehicle with EURO5 emission standard (corresponding to manufacture in the 2010s). The second segment corresponded to the route taken by the trucks from the cities to the landfill, which employs a 7.5–16 t truck with EURO3 emission standard (corresponding to manufacture in the 2000s). The trucks used are of the medium or semi-heavy diesel type, with an open bed or dump bed, coupled to a crusher. The emission standards account for efficiency improvements in newer internal combustion engines throughout time, reflecting increasingly stringent standards.
The waste transportation step comprises the distance traveled by the truck between the city and the sanitary landfill. This information was obtained by using a digital map in Google Earth, considering the route between each city center (departure) and the landfill (arrival) (Table 2). The route traveled by the collection team was recorded by the drivers in terms of kilometers traveled (km).
The scenarios for the disposal of urban tree pruning residues were established using the municipal solid waste plans (MSWPs) as a guide. The scenarios were: disposal in the sanitary landfill (current situation), disposal in the landfill with methane capture, municipal incineration, wood reuse, heat generation, and electricity generation.
The third step consisted of the life cycle impact assessment (LCIA). In this step, the inventory was analyzed based on the selected environmental impact assessment method, which in this case evaluated GHG emissions.
The LCA was performed with SimaPro 9.6.0.1 [25] software, using the Ecoinvent [26] database. Due to current concerns about climate change, the global warming potential (GWP) was used as a measure of environmental impact, expressed in carbon dioxide equivalent (CO2e), thus characterizing GHG emissions. The method adopted was IPCC 2021 GWP100 V1.00 [3], which uses the conversion factors published periodically by the IPCC to assess GHGs. The GWP quantifies how much energy a pollutant can trap in the atmosphere over a specific time period (here, 100 years was considered), compared to carbon dioxide (CO2), which is used as the reference gas with a GWP of 1.
For the scenario of waste disposal in the sanitary landfill, it was considered that the deposited wood decomposes slowly and forms methane and carbon dioxide during the first 150 years. Approximately 20% does not decompose and will remain in the landfill as stable material. The disposal of residues in the sanitary landfill without methane capture is the disposal method currently applied by the municipal government.
In methane capture, it was considered to have been used as fuel, avoiding the emissions necessary to produce natural gas. For every 1 kg of wood deposited in landfill with methane capture, 0.007 kg of natural gas does not need to be produced. Airborne emissions include unused methane (0.002 kg) and total CO2 emissions (0.5 kg) [27].
In municipal incineration, the incinerator itself is also included in the process and wood ash is considered to be deposited in sanitary landfill.
Electricity generation considers the previously described incineration process, but in this case, the energy generated is used. For electricity, 1.74 MJ/kg of residue was considered (lower heating value, LHV = 13.99 MJ/kg for urban tree pruning residues).
Heat generation also considers the incineration process, but in this case, the heat generated was used at 3.49 MJ/kg for heat.
The last step of the assessment is the interpretation of results for each proposed scenario. The GHG emission per ton of waste collected and per capita were also obtained to facilitate comparison with the existing scientific literature.

3. Results and Discussion

3.1. Urban Tree Pruning Collection

The five municipalities together collected a total mass of 271.522 kt of biomass, over a period of 10 years (Table 1).
Figure 2 shows the dynamics of urban pruning waste collection throughout the study period. In Bayeux, the peak collection occurred in 2013 of 4.268 kt, but for the remainder of the period, the amounts remained stable, staying below or close to 1 kt, with an increase in 2020–2021. In the municipalities of Cabedelo and Conde, in general, there was an increase in the collected mass, and Conde stood out with a sharp increase between 2017 and 2019. In the municipality of João Pessoa, there was a reduction in the collected mass of this waste over the period, while in Santa Rita, the collected mass varied significantly during the period.
The disparity in the mass collected annually between the cities is directly related to the size, number of tree-lined streets, type of management of this waste applied by the government and/or disposal used by the population after the service is performed within the properties. João Pessoa, having a larger urbanized area, higher percentage of tree-lined streets, and larger population compared to the others, has a greater generation of waste. Conde, with 29.9% of tree-lined streets, had the lowest mass collected, so this deficit of planted trees influences the mass of waste collected, because the waste results from the urban tree pruning service. Thus, if the city is not well wooded, as is the case, there are not as many trees to be pruned.

3.2. Reference Scenario: Current Practice

Simple disposal of urban pruning waste in metropolitan landfills is the most common practice in the northeast region of Brazil. For the studied cities, this disposal practice presented overall emissions of 1048.050 kt CO2e in the studied period (Table 3).
In the period between 2012 and 2021, the city of João Pessoa emitted an overall 12,862 kt of CO2e, with the waste sector being the second largest source of emissions, after the transportation sector ([28]. When comparing the results obtained by the GHG inventory of João Pessoa [28] with the results herein obtained, it was observed that the collection and disposal of urban pruning waste in the sanitary landfill corresponded to 5.97% of the total emissions in a decade.
Using the year 2020 as a reference, João Pessoa emitted 1100 kt CO2e, with the transportation sector being the largest emitter, accounting for 40.6% (446 kt CO2e), followed by waste with 35.7% (393 kt CO2e), and stationary energy generation with 23.7% (260 kt CO2e) [28]. In the same year, the municipal pruning service emitted a total of 40.040 kt CO2e, corresponding to 3.63% of the total GHG emissions in the municipality, and 10% of the emissions came from solid waste.
GHG emissions from municipal pruning waste management can be a relatively small fraction compared to the total emissions of the municipality but are not insignificant. However, when considering only the emissions caused by overall urban waste, its contribution to GHG emissions could reach 10%. These relative values can serve as a reference for other municipalities in the region under study, although this statement is difficult to prove due to the lack of GHG inventory.
Table 4 presents the GHG emissions per capita.
For comparison with other Brazilian cities, in Fortaleza (also in Northeast Brazil), the total GHG emissions were 1.7 t CO2e/inhab./year in 2018 [29], higher than the values found for the municipalities herein investigated, when disposal was carried out in the sanitary landfill. In Curitiba (South Brazil), this value was 1.85 t CO2e/inhab./year in 2016 [30], and in Porto Alegre (South Brazil), the average was 1.67 t CO2e/inhab./year in 2019 [31]. It is worth pointing out that, in the case of the cities of Fortaleza and Curitiba, the result considered several sources of emissions: stationary, transportation, and sanitation.
For comparative purposes at the international level, although the following emissions are not entirely associated with pruning residues, in Latin America, Mexico City (Mexico) emitted 3.6 t CO2e/inhab./year in 2018; Medellín (Colombia) emitted 1.3 t CO2e/inhab./year in 2020; Quito (Ecuador) emitted 1.9 t CO2e/inhab./year in 2019; Lima (Peru) emitted 2.2 t CO2e/inhab./year in 2018; Santiago (Chile) emitted 3.1 t CO2e/inhab./year in 2016; and Buenos Aires (Argentina) emitted 3.4 t CO2e/inhab./year in 2016 [32].
Among European and Asian cities, Lisbon (Portugal) had GHG emissions of 3.1 t CO2e/inhab./year in 2020; Madrid (Spain), 3 t CO2e/inhab./year in 2018; Paris (France), 2.3 t CO2e/inhab./year in 2020; Amsterdam (The Netherlands), 4.5 t CO2e/inhab./year in 2020; Copenhagen (Norway), 2.4 t CO2e/inhab./year in 2018; Seoul (Republic of Korea), 4.6 t CO2e/inhab./year in 2018; Tokyo (Japan), 3.9 tCO2e/inhab./year in 2019; Mumbai (India), 2 t CO2e/inhab./year in 2019; and Dubai (United Arab Emirates), 14.6 t CO2e/inhab./year in 2019 [32].
Another parameter that can be used to compare GHG emissions between the cities is the emission per ton of waste collected (Table 5). In this case, the municipality of Cabedelo presented the highest value, with 4.120 kt CO2e/t collected, followed by João Pessoa, with 3.880 kt CO2e/t collected.
Compared with other urban areas, woody biomass residues for heat production from vegetation management in the Rhine River floodplain in the Netherlands presented negative emissions of 132 kg CO2e/t in 2018, demonstrating that its use is environmentally beneficial [33]. The results of GHG emissions per ton collected found herein were higher, ranging from 4.120 to 3.063 kt CO2e. The difference observed was related to the scope of each study: in the case of biomass from floodplain vegetation, it encompassed only the residue itself, while in the case of urban pruning, it encompassed the transportation sector, a significant GHG emitter.
When comparing the emissions per capita and per ton collected, it was observed that the municipalities of Cabedelo and João Pessoa presented the highest values. For the remaining municipalities, the parameters were a direct result of the mass collected and the number of inhabitants in each municipality.
Regarding the transportation phase only, it was the largest contributor within the management of this waste (Table 2), and of the total 1048.050 kt CO2e emitted, 882 kt CO2e was released during transportation, corresponding to 84.2% of GHGs emitted in the process. João Pessoa presented the highest emissions caused by transportation among the cities studied, followed by Cabedelo. Such high emissions are associated with the distance traveled and mainly caused by the combustion of diesel in the collection vehicles.
In a broader context, the transportation sector is also responsible for the highest GHG emissions in the municipality of João Pessoa, accounting for 40.9–45.5% of annual emissions between 2011 and 2020, according to the GHG inventory [28]. For the 10-year period of this study, the transportation sector of the pruning service in João Pessoa was responsible for the emission of 647 kt CO2e, which corresponded to 5% of the total emissions of the municipality identified by the GHG inventory.
Transportation was also the largest source of GHG emissions in 2016 in the city of Recife, corresponding to 47% of the emissions, and to 57% in 2017 [34], a result similar to that found in the inventory of João Pessoa for 2021 [28], Fortaleza [29] with 59% in 2018, Curitiba [30] with 66.6% in 2016, São Paulo [35] with 61% in 2018, and in the cities studied herein, for the pruning waste collection system.
Transportation, as the largest source of GHG emissions, has also been observed in cities outside Brazil, such as Mexico City (Mexico), with 52.7% of the emissions in 2018, Medellín (Colombia) with 41.2% in 2020, Houston (United States) with 54.1% in 2018, Phoenix (United States) with 49.2% in 2020, and Quito (Ecuador) with 58.5% in 2019 [32].
When comparing the GHG emissions caused by transportation in João Pessoa in 2020 [28] and the management of tree pruning waste in the same year, the latter was responsible for 8.57% of the emissions associated with the transportation sector (393 kt CO2e). One of the strategies of the Climate Action Plan of João Pessoa [28] is to encourage the replacement of the public vehicle fleet with low-emission vehicles. This includes electric vehicles and those powered by biofuels, and the renewal of municipal and outsourced fleets, within a short timeframe, until 2030.
In the city of São Paulo, the municipal plan contemplates expanding the use of bicycles in the modal matrix, with a 100% reduction in atmospheric emissions by municipal buses and 100% of the fleet that provides services to the city hall with zero emissions, among others [36]. In the beverage sector, the primary hotspot of a microbrewery in northeast Brazil [37] was the distribution, which employs diesel vehicles. When a simulation substituted diesel vehicles for electric ones, the environmental impacts were three times lower. The adoption of electric mobility realized significant environmental benefits and the results of [37] can be extrapolated to other sectors with success.
With the implementation of measures to reduce emissions from the transportation sector within urban tree pruning collection, there were margins to reduce emissions by up to 8.57% in only one municipal public service.
When considering the current disposal practice (landfilling) excluding the transportation step, 166.443 kt CO2e of GHGs were emitted. These emissions are mainly generated during the decomposition of the material, corresponding to 15.8% of the overall emissions of the entire process. Regarding emissions by municipality, João Pessoa and Cabedelo were the largest emitters within the landfilling phase, with 121.409 kt CO2e and 22.400 kt CO2e, respectively (Table 3).
In the city of Fortaleza, the waste sector, which includes solid waste and effluents, corresponded to 27% of total GHG emissions in 2018 [29], and if focusing only on solid waste, the amount corresponded to 15.5% of GHG emissions in the same period. In Recife, waste accounted for 22% of the municipality’s GHG emissions in 2016 and 2017 [34]; in Belo Horizonte, it corresponded to 11% for the period from 2000 to 2013 [38]; 10.8% in Curitiba in 2018 [30]; and 8% in São Paulo (Capital) in 2016 [35].
Outside Brazil, in New York City, 4.3% of GHG emissions in 2020 came from solid waste, and this value was 0.4% in Boston, for the same year, both in the United States. In Montreal (Canada), 2.7% of GHG emissions in 2019 came from solid waste; 6.3% in Guadalajara (Mexico) in 2019; 28.4% in Lima (Peru) in 2018; 10.6% in Santiago (Chile) in 2016; and 20.5% in Buenos Aires (Argentina) in 2020 [32].
Landfilling is considered one of the main GHG emitters in Brazil, mainly due to the release of methane (CH4) in the decomposition of organic matter, which continues even after decades of disposal [30,38].
In Belo Horizonte, the disposal of municipal solid waste (MSW) in landfills including pruning waste emitted 4.586 kt CO2e in three years (2011, 2012, and 2013), resulting in an average of 1.529 kt CO2e/year [38]. This average found in Belo Horizonte was lower than the emissions caused by pruning residues in João Pessoa and higher than those found in the remaining municipalities analyzed in this study.

3.3. Other Scenarios of Final Disposal of Urban Pruning: Comparison

Table 6 shows the emissions associated with the remaining five scenarios for urban pruning waste disposal, considering the waste collected in all five cities.
Regarding the simulation of other disposal scenarios, when considering the installation of a methane capture system in the landfill, there was a reduction of 1.5% in the overall GHG emissions (type of disposal + transportation) compared to the simple disposal in the landfill for the period. The scenarios of reuse and electricity generation resulted in the lowest GHG emissions, corresponding to reductions of 17.9% and 18.5%, respectively, when compared to the baseline.
Following the use of biomass for electricity generation, which had the best result herein, the use of biomass in the gasification process with the function of capturing and storing carbon in refineries in Europe proved to be more economical and made it possible to reduce up to 6.3 Mt CO2e/year, which corresponded to 154%, compared to non-reuse [39].
The installation of biomass plants for the use of forest and agricultural residues in the province of Anhui (China) could mitigate about 3.44 Mt CO2e, demonstrating that this material can function as a mitigating agent according to its disposal or reuse [40].
It is worth pointing out that the use of biomass in a small-scale gasification process for energy production emits less CO2, CO, and soot compared to open burning, indicating that the destination of this waste for electricity generation may be a more environmentally appropriate option [41]. In this context, the use of waste at a local or municipal level can also contribute to the reduction in GHGs, in addition to providing a more environmentally appropriate disposal.
The results of the overall GHG emissions per capita per year between the scenarios for each municipality analyzed in this study indicated that disposal in sanitary landfill had the highest value among all, and the lowest level was obtained with the scenario of disposal for electricity generation (Table 7).
The transportation phase was the same for all scenarios, so the emission of GHGs into the atmosphere was also the same, as the routes and distances did not change.
The emissions of the different scenarios excluding the transportation of waste indicated that the simple disposal in the sanitary landfill emitted 166.443 kt CO2e, and if there was methane capture, the emissions decreased to 162.329 kt CO2e, 2.5% less compared to the baseline.
When all the waste generated in the period was subjected to municipal incineration, the reduction in GHG emissions was 97.6%, from 166.443 kt CO2e to 3.991 kt CO2e. For the scenarios of heat generation, electricity generation, and reuse, they actually avoided GHG emissions (negative emissions) (Table 8).
Using biomass for energy generation is environmentally advantageous, for example, as a substitute for coal-based energy: in the city of Rajasthan/India, it resulted in annual GHG emissions of 11,412 kt CO2e, demonstrating its local potential to mitigate climate change [42]. In the United States, a 1% increase in biomass energy consumption per capita would reduce GHG emissions by 0.65% in the long-term [43].
There are many technological pathways and applications for the use of biomass that interfere positively with GHGs such as energy production. In the Canadian province of British Columbia, for example, the use of biomass waste as bioenergy has caused a reduction of 13% to 15.7% in emissions including forestry, agricultural, and urban solid biomass [44].
More generally, the utilization of woody biomass for heat generation or as raw material for small-scale gasifiers has shown positive environmental viability, with benefits in GHG capture and lower CO2, CO, and soot emissions compared to open burning [33,41].
Finally, for the scenarios analyzed herein, avoided emissions of −4138 kt CO2e could be achieved if all the waste collected in the period was destined for electricity generation. Even the simple disposal of this waste in a municipal incinerator would emit less GHGs compared to disposal in the landfill. It was observed that improvements in the transportation system and a change in the final disposal could significantly reduce the GHGs emitted, with the potential to reach net zero or even negative emissions.

4. Conclusions

The quantification of GHG emissions in the cities in this study showed that the disposal of pruning biomass waste has caused emissions of more than 1 Mt CO2e throughout ten years, with the transportation phase being the largest source, corresponding to 84.2% of emissions. When comparing the six disposal scenarios, disposal in landfills presented the highest emissions, while the lowest emissions were achieved with the use of biomass waste for electricity production, which actually avoided GHG emissions.
Implementation of a low-carbon transportation system combined with more environmentally appropriate disposal can lead to reduced emissions for the municipal service of collecting and disposing of urban pruning waste. Depending on the amount of GHGs avoided, as pointed out in other studies, pruning residues have the potential to be a mitigating agent at the local level, with the possibility of achieving negative emissions.
The adequate management of urban pruning biomass waste falls within the scope of Goal 13 of the Sustainable Development Goals (SDGs), which addresses Action against Global Climate Change, by promoting changes in policies, strategies, and planning. Thus, this is a local action that the municipal government can implement with many environmental benefits, as demonstrated herein.

Author Contributions

Conceptualization, Y.R.V.A., B.I.S. and M.C.; methodology, M.C.; software, M.C.; validation, Y.R.V.A., B.I.S. and M.C.; formal analysis, Y.R.V.A.; investigation, Y.R.V.A. and B.I.S.; resources, Y.R.V.A., B.I.S. and M.C.; data curation, Y.R.V.A.; writing—original draft preparation, Y.R.V.A.; writing—review and editing, Y.R.V.A., B.I.S. and M.C.; visualization, Y.R.V.A., B.I.S. and M.C.; supervision, B.I.S. and M.C.; project administration, B.I.S.; funding acquisition, M.C. All authors have read and agreed to the published version of the manuscript.

Funding

The authors thank the National Council for Scientific and Technological Development (CNPq) for the support through research productivity grant 309452/2021-0 and project 424173/2021-2.

Data Availability Statement

Data available upon request.

Acknowledgments

The authors thank the Laboratory of Energy and Environmental Assessment (LAvAE) at the Federal University of Paraíba, Autarquia Especial Municipal de Limpeza Urbana de João Pessoa—EMLUR, and Foxx URE-JP Ambiental S.A. (Concessionaire), responsible for the administration of the metropolitan landfill of João Pessoa (Ecoparque João Pessoa), for providing data and being willing to collaborate. Thanks are extended to the Prefeitura Municipal de João Pessoa—PMJP, especially to the Secretaria Municipal de Meio Ambiente—SEMAM, for its collaboration and support.

Conflicts of Interest

The authors declare no conflict of interest.

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Resources 13 00127 g001
Figure 1. Location map of the study area.
Figure 1. Location map of the study area.
Resources 13 00127 g001
Resources 13 00127 g002
Figure 2. Urban pruning residue collected over a period of 10 years, in kt.
Figure 2. Urban pruning residue collected over a period of 10 years, in kt.
Resources 13 00127 g002
Table 1. Urban tree pruning collected, per municipality.
Table 1. Urban tree pruning collected, per municipality.
Biomass Collected by the Municipalities (kt)
YearJoão PessoaBayeuxCabedeloCondeSanta RitaTotal
201226.2441.0430.8340.000.85528.975
201328.7104.2682.1490.0061.77236.905
201430.0240.5782.7250.3182.04235.687
201521.1840.6113.8780.2023.55229.427
201624.1710.7013.7720.0740.38629.103
201716.0391.0363.7890.1712.56923.604
201814.1720.4984.6211.1862.04522.522
201917.0910.8974.9741.9641.72126.647
202010.3190.5644.8361.5091.64618.874
202110.1031.6924.9661.3711.64619.778
Total198.05611.88936.5426.80118.234271.522
Table 2. Distances travelled by the collection trucks, per municipality.
Table 2. Distances travelled by the collection trucks, per municipality.
João PessoaBayeuxCabedeloCondeSanta Rita
Within the city7050606060
To the sorting center (landfill)1816351525
Annual distances13,72810,29614,82011,70013,260
Table 3. GHG emissions associated with the landfilling of urban pruning waste, per municipality (2012–2021).
Table 3. GHG emissions associated with the landfilling of urban pruning waste, per municipality (2012–2021).
GHG Emissions (kt CO2e)
João PessoaBayeuxCabedeloCondeSanta RitaTotal
Transportation647.10129.134128.88818.93957.544881.606
Landfill121.4097.28822.4004.16911.178166.444
Total768.51036.422151.28823.10868.7221048.050
Table 4. GHG emissions associated with the landfilling of urban pruning waste, per capita.
Table 4. GHG emissions associated with the landfilling of urban pruning waste, per capita.
João PessoaBayeuxCabedeloCondeSanta Rita
GHG emissions (t CO2e/inhab)0.0920.0420.2270.0840.046
Table 5. GHG emissions associated with the landfilling of urban pruning waste, per tonne of waste collected.
Table 5. GHG emissions associated with the landfilling of urban pruning waste, per tonne of waste collected.
João PessoaBayeuxCabedeloCondeSanta Rita
GHG emissions
(kt CO2e/t waste collected)		3.8803.0634.1203.3983.769
Table 6. GHG emissions associated with different scenarios of urban pruning waste for all waste collected.
Table 6. GHG emissions associated with different scenarios of urban pruning waste for all waste collected.
Emissions (kt CO2e)
All Cities
Landfill with methane capture1033
Incineration886
Heat generation875
Electricity generation853
Reuse860
Table 7. Overall GHG emissions per capita by type of disposal by municipality over 10 years.
Table 7. Overall GHG emissions per capita by type of disposal by municipality over 10 years.
GHG Emissions Per Capita (t CO2e/inhab./year)
OkLandfillLandfill with Methane CaptureIncinerationHeat GenerationElectricity GenerationReuse
João Pessoa0.0920.0910.0780.0770.0750.076
Bayeux0.0440.0430.0350.0350.0340.034
Cabedelo0.2270.2240.1950.1920.1880.189
Conde0.0840.0820.0690.0680.0660.067
Santa Rita0.0460.0450.0390.0380.0370.037
Table 8. GHG emissions associated only with the disposal scenario (excluding transportation) for the five municipalities studied (2012–2021).
Table 8. GHG emissions associated only with the disposal scenario (excluding transportation) for the five municipalities studied (2012–2021).
GHG Emissions (kt CO2e)
LandfillLandfill with Methane CaptureIncinerationHeat GenerationElectricity GenerationReuse
166.443162.3293.991−6.162−27.695−21.342
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Araujo, Y.R.V.; Souza, B.I.; Carvalho, M. Greenhouse Gas Emissions Associated with Tree Pruning Residues of Urban Areas of Northeast Brazil. Resources 2024, 13, 127. https://doi.org/10.3390/resources13090127

AMA Style

Araujo YRV, Souza BI, Carvalho M. Greenhouse Gas Emissions Associated with Tree Pruning Residues of Urban Areas of Northeast Brazil. Resources. 2024; 13(9):127. https://doi.org/10.3390/resources13090127

Chicago/Turabian Style

Araujo, Yuri Rommel Vieira, Bartolomeu Israel Souza, and Monica Carvalho. 2024. "Greenhouse Gas Emissions Associated with Tree Pruning Residues of Urban Areas of Northeast Brazil" Resources 13, no. 9: 127. https://doi.org/10.3390/resources13090127

APA Style

Araujo, Y. R. V., Souza, B. I., & Carvalho, M. (2024). Greenhouse Gas Emissions Associated with Tree Pruning Residues of Urban Areas of Northeast Brazil. Resources, 13(9), 127. https://doi.org/10.3390/resources13090127

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