Carbon Balance and Management最新文献

{"title":"Integrating spaceborne LiDAR and Sentinel-2 images to estimate forest aboveground biomass in Northern China","authors":"Fugen Jiang,&nbsp;Muli Deng,&nbsp;Jie Tang,&nbsp;Liyong Fu,&nbsp;Hua Sun","doi":"10.1186/s13021-022-00212-y","DOIUrl":"10.1186/s13021-022-00212-y","url":null,"abstract":"<div><h3>Background</h3><p>Fast and accurate forest aboveground biomass (AGB) estimation and mapping is the basic work of forest management and ecosystem dynamic investigation, which is of great significance to evaluate forest quality, resource assessment, and carbon cycle and management. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), as one of the latest launched spaceborne light detection and ranging (LiDAR) sensors, can penetrate the forest canopy and has the potential to obtain accurate forest vertical structure parameters on a large scale. However, the along-track segments of canopy height provided by ICESat-2 cannot be used to obtain comprehensive AGB spatial distribution. To make up for the deficiency of spaceborne LiDAR, the Sentinel-2 images provided by google earth engine (GEE) were used as the medium to integrate with ICESat-2 for continuous AGB mapping in our study. Ensemble learning can summarize the advantages of estimation models and achieve better estimation results. A stacking algorithm consisting of four non-parametric base models which are the backpropagation (BP) neural network, k-nearest neighbor (kNN), support vector machine (SVM), and random forest (RF) was proposed for AGB modeling and estimating in Saihanba forest farm, northern China.</p><h3>Results</h3><p>The results show that stacking achieved the best AGB estimation accuracy among the models, with an R² of 0.71 and a root mean square error (RMSE) of 45.67 Mg/ha. The stacking resulted in the lowest estimation error with the decreases of RMSE by 22.6%, 27.7%, 23.4%, and 19.0% compared with those from the BP, kNN, SVM, and RF, respectively.</p><h3>Conclusion</h3><p>Compared with using Sentinel-2 alone, the estimation errors of all models have been significantly reduced after adding the LiDAR variables of ICESat-2 in AGB estimation. The research demonstrated that ICESat-2 has the potential to improve the accuracy of AGB estimation and provides a reference for dynamic forest resources management and monitoring.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9438156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40336982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GHG Monitoring Project for the Global Stocktake 2023: implications of the COP26 Japan Pavilion seminar","authors":"Tomohiro Oda","doi":"10.1186/s13021-022-00211-z","DOIUrl":"10.1186/s13021-022-00211-z","url":null,"abstract":"<div><p>During the 2021 Glasgow Climate Change Conference (COP26), a hybrid seminar event “Greenhouse gas (GHG) Monitoring Project for the Global Stocktake 2023” was held at the COP26 Japan Pavilion on 2nd of November 2011. The participants presented and discussed science-based GHG monitoring approaches in support of the Global Stocktake. This report summarizes the five research talks given at the event.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40534982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal dynamics of forest ecosystem carbon budget in Guizhou: customisation and application of the CBM-CFS3 model for China","authors":"Yuzhi Tang,&nbsp;Quanqin Shao,&nbsp;Tiezhu Shi,&nbsp;Zhensheng Lu,&nbsp;Guofeng Wu","doi":"10.1186/s13021-022-00210-0","DOIUrl":"10.1186/s13021-022-00210-0","url":null,"abstract":"<div><h3>Background</h3><p>Countries seeking to mitigate climate change through forests require suitable modelling approaches to predict carbon (C) budget dynamics in forests and their responses to disturbance and management. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is a feasible and comprehensive tool for simulating forest C stock dynamics across broad levels, but discrepancies remain to be addressed in China. Taking Guizhou as the case study, we customised the CBM-CFS3 model according to China’s context, including the modification of aboveground biomass C stock algorithm, addition of C budget accounting for bamboo forests, economic forests, and shrub forests, improvement of non-forest land belowground slow dead organic matter (DOM) pool initialisation, and other model settings.</p><h3>Results</h3><p>The adequate linear relationship between the estimated and measured C densities (<i>R</i>² = 0.967, <i>P</i> &lt; 0.0001, <i>slope</i> = 0.904) in the model validation demonstrated the high accuracy and reliability of our customised model. We further simulated the spatiotemporal dynamics of forest C stocks and disturbance impacts in Guizhou for the period 1990–2016 using our customised model. Results shows that the total ecosystem C stock and C density, and C stocks in biomass, litter, dead wood, and soil in Guizhou increased continuously and significantly, while the soil C density decreased over the whole period, which could be attributed to deforestation history and climate change. The total ecosystem C stock increased from 1220 Tg C in 1990 to 1684 Tg C in 2016 at a rate of 18 Tg C yr⁻¹, with significant enhancement in most areas, especially in the south and northwest. The total decrease in ecosystem C stock and C expenditure caused by disturbances reached 97.6 Tg C and 120.9 Tg C, respectively, but both represented significant decreasing trends owing to the decline of disturbed forest area during 1990–2016. Regeneration logging, deforestation for agriculture, and harvest logging caused the largest C stock decrease and C expenditure, while afforestation and natural expansion of forest contributed the largest increases in C stock.</p><h3>Conclusions</h3><p>The forests in Guizhou were a net carbon sink under large-scale afforestation throughout the study period; Our customised CBM-CFS3 model can serve as a more effective and accurate method for estimating forest C stock and disturbance impacts in China and further enlightens model customisation to other areas.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40464911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil","authors":"Luis Miguel da Costa,&nbsp;Gustavo André de Araújo Santos,&nbsp;Alan Rodrigo Panosso,&nbsp;Glauco de Souza Rolim,&nbsp;Newton La Scala","doi":"10.1186/s13021-022-00209-7","DOIUrl":"10.1186/s13021-022-00209-7","url":null,"abstract":"<div><h3>Background</h3><p>The recent studies of the variations in the atmospheric column-averaged CO₂ concentration (<span>({text{X}}_{{{text{CO}}_{{2}} }})</span>) above croplands and forests show a negative correlation between <span>({text{X}}_{{{text{CO}}_{{2}} }})</span>and Sun Induced Chlorophyll Fluorescence (SIF) and confirmed that photosynthesis is the main regulator of the terrestrial uptake for atmospheric CO₂. The remote sensing techniques in this context are very important to observe this relation, however, there is still a time gap in orbital data, since the observation is not daily. Here we analyzed the effects of several variables related to the photosynthetic capacity of vegetation on <span>({text{X}}_{{{text{CO}}_{{2}} }})</span> above São Paulo state during the period from 2015 to 2019 and propose a daily model to estimate the natural changes in atmospheric CO₂.</p><h3>Results</h3><p>The data retrieved from the Orbiting Carbon Observatory-2 (OCO-2), NASA-POWER and Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) show that Global Radiation (Qg), Sun Induced Chlorophyll Fluorescence (SIF) and, Relative Humidity (RH) are the most significant factors for predicting the annual <span>({text{X}}_{{{text{CO}}_{{2}} }})</span> cycle. The daily model of <span>({text{X}}_{{{text{CO}}_{{2}} }})</span> estimated from Qg and RH predicts daily <span>({text{X}}_{{{text{CO}}_{{2}} }})</span> with root mean squared error of 0.47 ppm (the coefficient of determination is equal to 0.44, p &lt; 0.01).</p><h3>Conclusion</h3><p>The obtained results imply that a significant part of daily <span>({text{X}}_{{{text{CO}}_{{2}} }})</span> variations could be explained by meteorological factors and that further research should be done to quantify the effects of the atmospheric transport and anthropogenic emissions.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00209-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43616905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stand carbon storage and net primary production in China’s subtropical secondary forests are predicted to increase by 2060","authors":"Jia Jin,&nbsp;Wenhua Xiang,&nbsp;Yelin Zeng,&nbsp;Shuai Ouyang,&nbsp;Xiaolu Zhou,&nbsp;Yanting Hu,&nbsp;Zhonghui Zhao,&nbsp;Liang Chen,&nbsp;Pifeng Lei,&nbsp;Xiangwen Deng,&nbsp;Hui Wang,&nbsp;Shirong Liu,&nbsp;Changhui Peng","doi":"10.1186/s13021-022-00204-y","DOIUrl":"10.1186/s13021-022-00204-y","url":null,"abstract":"<div><h3>Background</h3><p>Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5).</p><h3>Results</h3><p>The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060.</p><h3>Conclusions</h3><p>The obtained results lead to conclusion that proper management of China’s subtropical secondary forests could be considered as one of the steps towards achieving China’s target to become carbon neutral by 2060.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00204-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46986822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainties of soil organic carbon stock estimation caused by paleoclimate and human footprint on the Qinghai Plateau","authors":"Xia Liu,&nbsp;Tao Zhou,&nbsp;Peijun Shi,&nbsp;Yajie Zhang,&nbsp;Hui Luo,&nbsp;Peixin Yu,&nbsp;Yixin Xu,&nbsp;Peifang Zhou,&nbsp;Jingzhou Zhang","doi":"10.1186/s13021-022-00203-z","DOIUrl":"10.1186/s13021-022-00203-z","url":null,"abstract":"<div><h3>Background</h3><p>Quantifying the stock of soil organic carbon (SOC) and evaluating its potential impact factors is important to evaluating global climate change. Human disturbances and past climate are known to influence the rates of carbon fixation, soil physiochemical properties, soil microbial diversity and plant functional traits, which ultimately affect the current SOC storage. However, whether and how the paleoclimate and human disturbances affect the distribution of SOC storage on the high-altitude Tibetan Plateau remain largely unknown. Here, we took the Qinghai Plateau, the main component of the Tibetan Plateau, as our study region and applied three machine learning models (random forest, gradient boosting machine and support vector machine) to estimate the spatial and vertical distributions of the SOC stock and then evaluated the effects of the paleoclimate during the Last Glacial Maximum and the mid-Holocene periods as well as the human footprint on SOC stock at 0 to 200 cm depth by synthesizing 827 soil observations and 71 environmental factors.</p><h3>Results</h3><p>Our results indicate that the vegetation and modern climate are the determinant factors of SOC stocks, while paleoclimate (i.e., paleotemperature and paleoprecipitation) is more important than modern temperature, modern precipitation and the human footprint in shaping current SOC stock distributions. Specifically, the SOC stock was deeply underestimated in near natural ecosystems and overestimated in the strongly human disturbance ecosystems if the model did not consider the paleoclimate. Overall, the total SOC stock of the Qinghai Plateau was underestimated by 4.69%, 12.25% and 6.67% at depths of 0 to 100 cm, 100 to 200 cm and 0 to 200 cm, respectively. In addition, the human footprint had a weak influence on the distributions of the SOC stock. We finally estimated that the total and mean SOC stock at 200 cm depth by including the paleoclimate effects was 11.36 Pg C and 16.31 kg C m⁻², respectively, and nearly 40% SOC was distributed in the top 30 cm.</p><h3>Conclusion</h3><p>The paleoclimate is relatively important for the accurate modeling of current SOC stocks. Overall, our study provides a benchmark for predicting SOC stock patterns at depth and emphasizes that terrestrial carbon cycle models should incorporate information on how the paleoclimate has influenced SOC stocks.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00203-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42352960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon dioxide and particulate emissions from the 2013 Tasmanian firestorm: implications for Australian carbon accounting","authors":"Mercy N. Ndalila,&nbsp;Grant J. Williamson,&nbsp;David M. J. S. Bowman","doi":"10.1186/s13021-022-00207-9","DOIUrl":"10.1186/s13021-022-00207-9","url":null,"abstract":"<div><h3>Background</h3><p>Uncontrolled wildfires in Australian temperate <i>Eucalyptus</i> forests produce significant smoke emissions, particularly carbon dioxide (CO₂) and particulates. Emissions from fires in these ecosystems, however, have received less research attention than the fires in North American conifer forests or frequently burned Australian tropical savannas. Here, we use the 2013 Forcett–Dunalley fire that caused the first recorded pyrocumulonimbus event in Tasmania, to understand CO₂ and particulate matter (PM_2.5) emissions from a severe <i>Eucalyptus</i> forest fire. We investigate the spatial patterns of the two emissions using a fine scale mapping of vegetation and fire severity (50 m resolution), and utilising available emission factors suitable for Australian vegetation types. We compare the results with coarse-scale (28 km resolution) emissions estimates from Global Fire Emissions Database (GFED) to determine the reliability of the global model in emissions estimation.</p><h3>Results</h3><p>The fine scale inventory yielded total CO₂ emission of 1.125 ± 0.232 Tg and PM_2.5 emission of 0.022 ± 0.006 Tg, representing a loss of 56 t CO₂ ha⁻¹ and 1 t PM_2.5 ha⁻¹. The CO₂ emissions were comparable to GFED estimates, but GFED PM_2.5 estimates were lower by a factor of three. This study highlights the reliability of GFED for CO₂ but not PM_2.5 for estimating emissions from <i>Eucalyptus</i> forest fires. Our fine scale and GFED estimates showed that the Forcett–Dunalley fire produced 30% of 2013 fire carbon emissions in Tasmania, and 26–36% of mean annual fire emissions for the State, representing a significant single source of emissions.</p><h3>Conclusions</h3><p>Our analyses highlight the need for improved PM_2.5 emission factors specific to Australian vegetation, and better characterisation of fuel loads, particularly coarse fuel loads, to quantify wildfire particulate and greenhouse gas emissions more accurately. Current Australian carbon accountancy approach of excluding large wildfires from final GHG accounts likely exaggerates Tasmania’s claim to carbon neutrality; we therefore recommend that planned and unplanned emissions are included in the final national and state greenhouse gas accounting to international conventions. Advancing these issues is important given the trajectory of more frequent large fires driven by anthropogenic climate change.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00207-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41947202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of integrated Korean forest growth dynamics model to meet NDC target by considering forest management scenarios and budget","authors":"Mina Hong,&nbsp;Cholho Song,&nbsp;Moonil Kim,&nbsp;Jiwon Kim,&nbsp;Sle-gee Lee,&nbsp;Chul-Hee Lim,&nbsp;Kijong Cho,&nbsp;Yowhan Son,&nbsp;Woo-Kyun Lee","doi":"10.1186/s13021-022-00208-8","DOIUrl":"10.1186/s13021-022-00208-8","url":null,"abstract":"<div><h3>Background</h3><p>Forests are atmospheric carbon sinks, whose natural growth can contribute to climate change mitigation. However, they are also affected by climate change and various other phenomena, for example, the low growth of coniferous forests currently reported globally, including in the Republic of Korea. In response to the implementation of the Paris Agreement, the Korean government has proposed 2030 greenhouse gas roadmap to achieve a Nationally Determined Contribution (NDC), and the forest sector set a sequestration target of 26 million tons by 2030. In this study, the Korean forest growth model (KO-G-Dynamic model) was used to analyze various climate change and forest management scenarios and their capacity to address the NDC targets. A 2050 climate change adaptation strategy is suggested based on forest growth and CO₂ sequestration.</p><h3>Results</h3><p>Forest growth was predicted to gradually decline, and CO₂ sequestration was predicted to reach 23 million tons per year in 2050 if current climate and conditions are maintained. According to the model, sequestrations of 33 million tCO₂ year⁻¹ in 2030 and 27 million tCO₂ year⁻¹ in 2050 can be achieved if ideal forest management is implemented. It was also estimated that the current forest management budget of 317 billion KRW (264 million USD) should be twice as large at 722 billion KRW (602 million USD) in the 2030s and 618 billion KRW (516 million USD) in the 2050s to achieve NDC targets.</p><h3>Conclusions</h3><p>The growth trend in Korea's forests transitions from young-matured stands to over-mature forests. The presented model-based forest management plans are an appropriate response and can increase the capacity of Korea to achieve its NDC targets. Such a modeling can help the forestry sector develop plans and policies for climate change adaptation.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00208-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49268597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Substitution impacts of Nordic wood-based multi-story building types: influence of the decarbonization of the energy sector and increased recycling of construction materials","authors":"Tanja Myllyviita,&nbsp;Elias Hurmekoski,&nbsp;Janni Kunttu","doi":"10.1186/s13021-022-00205-x","DOIUrl":"10.1186/s13021-022-00205-x","url":null,"abstract":"<div><h3>Background</h3><p>The building and construction sectors represent a major source of greenhouse gas (GHG) emissions. Replacing concrete and steel with wood is one potential strategy to decrease emissions. On product level, the difference in fossil emissions per functional unit can be quantified with displacement factors (DFs), i.e., the amount of fossil emission reduction achieved per unit of wood use when replacing a functionally equivalent product. We developed DFs for substitution cases representative of typical wood-frame and non-wood frame multi-story buildings in the Nordic countries, considering the expected decarbonization of the energy sector and increased recycling of construction products.</p><h3>Results</h3><p>Most of the DFs were positive, implying lower fossil emissions, if wood construction is favored. However, variation in the DFs was substantial and negative DFs implying higher emissions were also detected. All DFs showed a decreasing trend, i.e., the GHG mitigation potential of wood construction significantly decreases under future decarbonization and increased recycling assumptions. If only the decarbonization of the energy sector was considered, the decrease was less dramatic compared to the isolated impact of the recycling of construction materials. The mitigation potential of wood construction appears to be the most sensitive to the GHG emissions of concrete, whereas the emissions of steel seem less influential, and the emissions of wood have only minor influence.</p><h3>Conclusions</h3><p>The emission reduction due to the decarbonization of the energy sector and the recycling of construction materials is a favorable outcome but one that reduces the relative environmental benefit of wood construction, which ought to be considered in forest-based mitigation strategies. Broadening the system boundary is required to assess the overall substitution impacts of increased use of wood in construction, including biogenic carbon stock changes in forest ecosystems and in wood products over time, as well as price-mediated market responses.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00205-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43365814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal variations in urban CO2 flux with land-use types in Seoul","authors":"Chaerin Park,&nbsp;Sujong Jeong,&nbsp;Moon-Soo Park,&nbsp;Hoonyoung Park,&nbsp;Jeongmin Yun,&nbsp;Sang-Sam Lee,&nbsp;Sung-Hwa Park","doi":"10.1186/s13021-022-00206-w","DOIUrl":"10.1186/s13021-022-00206-w","url":null,"abstract":"<div><h3>Background</h3><p>Cities are a major source of atmospheric CO₂; however, understanding the surface CO₂ exchange processes that determine the net CO₂ flux emitted from each city is challenging owing to the high heterogeneity of urban land use. Therefore, this study investigates the spatiotemporal variations of urban CO₂ flux over the Seoul Capital Area, South Korea from 2017 to 2018, using CO₂ flux measurements at nine sites with different urban land-use types (baseline, residential, old town residential, commercial, and vegetation areas).</p><h3>Results</h3><p>Annual CO₂ flux significantly varied from 1.09 kg C m^− 2 year^− 1 at the baseline site to 16.28 kg C m^− 2 year^− 1 at the old town residential site in the Seoul Capital Area. Monthly CO₂ flux variations were closely correlated with the vegetation activity (r = − 0.61) at all sites; however, its correlation with building energy usage differed for each land-use type (r = 0.72 at residential sites and r = 0.34 at commercial sites). Diurnal CO₂ flux variations were mostly correlated with traffic volume at all sites (r = 0.8); however, its correlation with the floating population was the opposite at residential (r = − 0.44) and commercial (r = 0.80) sites. Additionally, the hourly CO₂ flux was highly related to temperature. At the vegetation site, as the temperature exceeded 24 ℃, the sensitivity of CO₂ absorption to temperature increased 7.44-fold than that at the previous temperature. Conversely, the CO₂ flux of non-vegetation sites increased when the temperature was less than or exceeded the 18 ℃ baseline, being three-times more sensitive to cold temperatures than hot ones. On average, non-vegetation urban sites emitted 0.45 g C m^− 2 h^− 1 of CO₂ throughout the year, regardless of the temperature.</p><h3>Conclusions</h3><p>Our results demonstrated that most urban areas acted as CO₂ emission sources in all time zones; however, the CO₂ flux characteristics varied extensively based on urban land-use types, even within cities. Therefore, multiple observations from various land-use types are essential for identifying the comprehensive CO₂ cycle of each city to develop effective urban CO₂ reduction policies.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"17 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-022-00206-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41753963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}