Spatial Distribution and Temporal Change of Carbon Storage in Timber Biomass of Two Different Forest Management Units

Forests make up large ecosystems and can play an important role in mitigating the emissions of CO₂, the most important greenhouse gas. However, they are sources of atmospheric carbon when they are disturbed by human or natural causes. Storage of carbon through expansion and adaptive management of forest ecosystems can assist in reducing carbon concentrations in atmosphere. This study proposes a methodology to produce spatially explicit estimates of the carbon storages (aboveground plus belowground) depending on land use/cover changes in two different forest ecosystems during various periods. Carbon storages for each forest ecosystem were projected according to inventory data, and carbon storages were mapped in a geographic information system (GIS). Results showed that total carbon stored in above and belowground of both forest ecosystems increased from one period to other because of especially increase of productive forest areas and decline of degraded forest areas as well as protection of spruce forests subject to insect attacks.     

Availability of disaggregated greenhouse gas emissions from beef cattle production: A systematic review

Agriculture is a significant source of anthropogenic greenhouse gas (GHG) emissions, and beef cattle are particularly emissions intensive. GHG emissions are typically expressed as a carbon dioxide equivalent (CO₂e) ‘carbon footprint’ per unit output. The 100-year Global Warming Potential (GWP₁₀₀) is the most commonly used CO₂e metric, but others have also been proposed, and there is no universal reason to prefer GWP₁₀₀ over alternative metrics. The weightings assigned to non-CO₂ GHGs can differ significantly depending on the metric used, and relying upon a single metric can obscure important differences in the climate impacts of different GHGs. This loss of detail is especially relevant to beef production systems, as the majority of GHG emissions (as conventionally reported) are in the form of methane (CH₄) and nitrous oxide (N₂O), rather than CO₂. This paper presents a systematic literature review of harmonised cradle to farm-gate beef carbon footprints from bottom-up studies on individual or representative systems, collecting the emissions data for each separate GHG, rather than a single CO₂e value. Disaggregated GHG emissions could not be obtained for the majority of studies, highlighting the loss of information resulting from the standard reporting of total GWP₁₀₀ CO₂e alone. Where individual GHG compositions were available, significant variation was found for all gases. A comparison of grass fed and non-grass fed beef production systems was used to illustrate dynamics that are not sufficiently captured through a single CO₂e footprint. Few clear trends emerged between the two dietary groups, but there was a non-significant indication that under GWP₁₀₀ non-grass fed systems generally appear more emissions efficient, but under an alternative metric, the 100-year global temperature potential (GTP₁₀₀), grass-fed beef had lower footprints. Despite recent focus on agricultural emissions, this review concludes there are insufficient data available to fully address important questions regarding the climate impacts of agricultural production, and calls for researchers to include separate GHG emissions in addition to aggregated CO₂e footprints.     

Global warming implications of facade parameters: A life cycle assessment of residential buildings in Bahrain

On a global scale, the Gulf Corporation Council Countries (GCCC), including Bahrain, are amongst the top countries in terms of carbon dioxide emissions per capita. Building authority in Bahrain has set a target of 40% reduction of electricity consumption and associated CO₂ emissions to be achieved by using facade parameters. This work evaluates how the life cycle CO₂ emissions of buildings are affected by facade parameters. The main focus is placed on direct and indirect CO₂ emissions from three contributors, namely, chemical reactions during production processes (Pco₂), embodied energy (Eco₂) and operational energy (OPco₂). By means of the life cycle assessment (LCA) methodology, it has been possible to show that the greatest environmental impact occurs during the operational phase (80–90%). However, embodied CO₂ emissions are an important factor that needs to be brought into the systems used for appraisal of projects, and hence into the design decisions made in developing projects. The assessment shows that masonry blocks are responsible for 70–90% of the total CO₂ emissions of facade construction, mainly due to their physical characteristics. The highest Pco₂ emissions factors are those of window elements, particularly aluminium frames. However, their contribution of CO₂ emissions depends largely on the number and size of windows. Each square metre of glazing is able to increase the total CO₂ emissions by almost 30% when compared with the same areas of opaque walls. The use of autoclaved aerated concrete (AAC) walls reduces the total life cycle CO₂ emissions by almost 5.2% when compared with ordinary walls, while the use of thermal insulation with concrete wall reduces CO₂ emissions by 1.2%. The outcome of this work offers to the building industry a reliable indicator of the environmental impact of residential facade parameters.     

Industrial point source CO<Subscript>2</Subscript> emission strength estimation with aircraft measurements and dispersion modelling

CO₂ remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO₂ emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO₂ industrial point source, located in Biganos, France. CO₂ density measurements were obtained by applying the mass balance method, while CO₂ emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.     

Influence of elevated carbon dioxide and temperature on belowground carbon allocation and enzyme activities in tropical flooded soil planted with rice

Changes in the soil labile carbon fractions and soil biochemical properties to elevated carbon dioxide (CO₂) and temperature reflect the changes in the functional capacity of soil ecosystems. The belowground root system and root-derived carbon products are the key factors for the rhizospheric carbon dynamics under elevated CO₂ condition. However, the relationship between interactive effects of elevated CO₂ and temperature on belowground soil carbon accrual is not very clear. To address this issue, a field experiment was laid out to study the changes of carbon allocation in tropical rice soil (Aeric Endoaquept) under elevated CO₂ and elevated CO₂ + elevated temperature conditions in open top chambers (OTCs). There were significant increase of root biomass by 39 and 44 % under elevated CO₂ and elevated CO₂ + temperature compared to ambient condition, respectively. A significant increase (55 %) of total organic carbon in the root exudates under elevated CO₂ + temperature was noticed. Carbon dioxide enrichment associated with elevated temperature significantly increased soil labile carbon, microbial biomass carbon, and activities of carbon-transforming enzyme like β-glucosidase. Highly significant correlations were noticed among the different soil enzymes and soil labile carbon fractions.     

A dynamic analysis of the global warming potential associated with air conditioning at a city scale: an empirical study in Shenzhen,China

Heating, ventilation and air conditioning (HVAC) systems are a major source of energy consumption in buildings, directly and indirectly contributing to greenhouse gas (GHG) emissions. In the urban environment, and depending on local climatic conditions, air conditioning units attribute to these high energy demands. This study analyzes the use of residential air conditioning units and their associated global warming potential (GWP) between 2005 and 2030 for the city of Shenzhen, a fast-growing megacity located in Southern China. A life cycle assessment approach was adopted to quantify the GWP impacts which arise from both direct (refrigerant release) and indirect (energy consumption) sources, in combination with a materials flow analysis approach. The results show that the total GWP (expressed as carbon dioxide equivalents, CO₂ eq.) from residential air conditioning systems increased from 2.2 ± 0.2 to 5.1 ± 0.4 million tonnes (Mt) CO₂ eq. between 2005 and 2017, with energy consumption and refrigerant release contributing to 72.5% and 27.5% of the total demands, respectively. Immediate measures are required to restrict refrigerant release and reduce the energy consumption of air conditioning units, to help mitigate the predicted additional total emissions of 36.4 Mt. CO₂ eq. potentially released between 2018 and 2030. This amount equals to approximately New Zealand's national CO₂ emissions in 2017. The findings proposed in this study targets air conditioning units to reduce the GWP emissions in cities, and provide useful data references and insights for local authorities to incentivise measures for improving building energy efficiency management and performance.     

Empirical gas emission and oxidation measurement at cover soil of dumping site: example from Malaysia

Methane (CH₄) is one of the most relevant greenhouse gases and it has a global warming potential 25 times greater than that of carbon dioxide (CO₂), risking human health and the environment. Microbial CH₄ oxidation in landfill cover soils may constitute a means of controlling CH₄ emissions. The study was intended to quantify CH₄ and CO₂ emissions rates at the Sungai Sedu open dumping landfill during the dry season, characterize their spatial and temporal variations, and measure the CH₄ oxidation associated with the landfill cover soil using a homemade static flux chamber. Concentrations of the gases were analyzed by a Micro-GC CP-4900. Two methods, kriging values and inverse distance weighting (IDW), were found almost identical. The findings of the proposed method show that the ratio of CH₄ to CO₂ emissions was 25.4 %, indicating higher CO₂ emissions than CH₄ emissions. Also, the average CH₄ oxidation in the landfill cover soil was 52.5 %. The CH₄ and CO₂ emissions did not show fixed-pattern temporal variation based on daytime measurements. Statistically, a negative relationship was found between CH₄ emissions and oxidation (R ²?=?0.46). It can be concluded that the variation in the CH₄ oxidation was mainly attributed to the properties of the landfill cover soil.     

Can buildings sector achieve the carbon mitigation ambitious goal: Case study for a low-carbon demonstration city in China?

China is committed to peaking its carbon emissions by 2030 and become a carbon-neutral society by 2060. The building sector that accounts for over one-third of the total carbon emissions is expected to face a great challenge in helping China achieve this goal. Shenzhen, as a low-carbon pilot city, whether its low-carbon work of urban buildings reaches the target is crucial. An attempt has been made in this study to assess the intensity of carbon emissions and associated reduction efficiency of urban buildings (operation stage) in Shenzhen by using the life cycle assessment method. The results show that the total carbon emissions generated from the buildings' operation stage have increased from 22 million metric tons (Mt) CO₂eq in 2005 to 42 (±13%) Mt. CO₂eq in 2019. Carbon emissions mainly result from the buildings' electricity use (79%), followed by refrigerant release emissions (12%). The energy conservation and carbon emissions reduction intensity in Shenzhen is at the middle level in China, and there is considerable space for improvement. According to scenario-based analysis, the carbon emission of the buildings sector can probably reach its peak by 2025 with the implementation of suitable policies – 5 years earlier than national target by 2030. Overall, this study makes a systemic analysis of the characteristics of urban buildings energy consumption and carbon emissions reduction, which can provide supportings for justifying the effectiveness of low-carbon activities in Shenzhen and beyond.     

Greenhouse gas emissions from forestry,land-use changes,and agriculture in Tanzania

The purpose of the study was to identify and quantify anthropogenic sources and sinks of greenhouse gases from forestry, land-use changes and agriculture in Tanzania. The 1990 inventory revealed that, in the land-use sector, methane (CH₄) and carbon dioxide (CO₂) are the primary gases emitted. Enteric fermentation in livestock production systems is the largest source of CH₄. Although deforestation results in greenhouse gas emissions, the managed forests of Tanzania are a major CO₂ sink.     

Estimation of shipping emissions in Candarli Gulf, Turkey

Ships are significant air pollution sources as their high powered main engines often use heavy fuels. The major atmospheric components emitted are nitrogen oxides, particulate matter (PM), sulfur oxide gases, carbon oxides, and toxic air pollutants. Shipping emissions cause severe impacts on health and environment. These effects of emissions are emerged especially in territorial waters, inland seas, canals, straits, bays, and port regions. Candarli Gulf is one of the major industrial regions on the Aegean side of Turkey. The marine environment of the region is affected by emissions from ships calling to ten different ports. In this study, NO _x , SO₂, CO₂, hydrocarbons (HC), and PM emissions from 7,520 ships are estimated during the year of 2007. These emissions are classified regarding operation modes and types of ships. Annual shipping emissions are estimated as 631.2 t year^???1 for NO _x , 573.6 t year^???1 for SO₂, 33,848.9 t year^???1 for CO₂, 32.3 t year^???1 for HC, and 57.4 t year^???1 for PM.     

典型燃煤电厂机组二氧化碳排放测试及核算研究

为验证二氧化碳排放量的测试技术适用性及可行性,获取燃煤电厂机组碳排放特征,系统比较不同测试方法之间碳排放量的差异,对某典型火电机组二氧化碳排放开展测试,结果表明,不同测试原理及设备二氧化碳排放实测体积分数均较为接近。测试机组CO₂实测体积分数为11.28%～14.21%,与负荷变化呈一定的正相关关系,不同负荷下基准氧含量(体积分数6%)基本无变化。测试机组排放量与负荷正相关,使用了缺省值的指南排放量最高,与其他方法排放量相对偏差均值为31.6%;使用入炉煤实测数据的指南排放量差异不大,相对偏差为0.1%;使用入炉煤实测数据的2版指南排放量高于直接测量法,相对偏差均值为4.9%;直接测量各类方法间相对偏差均值为1.0%,其中在线法与手工法间相对偏差均值为1.2%。CO₂排放强度与负荷负相关,实验条件下,机组负荷越高,碳排放强度越低。     

Modeling seasonal variations of long-term soil CO<Subscript>2</Subscript> emissions in an orchard plantation in a semiarid area,SE Turkey

Emissions of soil CO₂ under different management systems have a significant effect on the carbon balance in the atmosphere. Soil CO₂ emissions were measured from an apricot orchard at two different locations: under the crown of trees (CO₂-UC) and between tree rows (CO₂-BR). For comparison, one other measurement was performed on bare soil (CO₂-BS) located next to the orchard field. Analytical data were obtained weekly during 8 years from April 2008 to December 2016. Various environmental parameters such as air temperature, soil temperature at different depths, soil moisture, rainfall, and relative humidity were used for modeling and estimating the long-term seasonal variations in soil CO₂ emissions using two different methods: generalized linear model (GLM) and artificial neural network (ANN). Before modeling, data were randomly split into two parts, one for calibration and the second for validation, with a varying number of samples in each part. Performances of the models were compared and evaluated using means absolute of estimations (MAE), square root of mean of prediction (RMSEP), and coefficient of determination (R²) values. CO₂-UC, CO₂-BR, and CO₂-BS values ranged from 11 to 3985, from 9 to 2365, and from 8 to 1722 kg ha^?1 week^?1, respectively. Soil CO₂ emissions were significantly correlated (p?<?0.05) with some environmental variables. The results showed that GLM and ANN models provided similar accuracies in modeling and estimating soil CO₂ emissions, as the number of samples in the validation data set increased. The ANN was more advantageous than GLM models by providing a better fit between actual observations and predictions and lower RMSEP and MAE values. The results suggested that the success of environmental variables for estimations of CO₂ emissions using the two methods was moderate.     

Greenhouse gas emission inventory for Senegal, 1991

The first greenhouse gas (GHG) emission estimates for Senegal, for the year 1991, were produced according to the draft IPCC/OECD guidelines for national inventories of GHGs. Despite certain discrepancies, nonavailability of data, the quality of some of the data collected, and the methodology, the estimates provide a provisional basis for Senegal to fulfill its obligations under the UN Framework Convention on Climate Change. This inventory reveals that GHG emissions in Senegal, like those in many developing countries, can mainly be attributed to the use of biomass for energy, land-use change and forestry, and savanna burning. Taking into account the direct global warming potential of the main GHGs (CO₂, CH₄, and N₂O), Senegal's emissions are estimated at 17.6 Tg ECO₂. The major gases emitted are CO₂ (61% of GHG emissions), followed by CH₄ (35%) and N₂O (4%). Energy accounts for 45% of total emissions (12% from fossil energy and 33% from traditional biomass energy); land-use change and forests, 18%; agriculture, 24%; waste, 12%; and industry, 1%.     

The environmental Kuznets curve of CO2 emissions in the manufacturing and construction industries: A global empirical analysis

The manufacturing and construction industries have significantly contributed to the increase of carbon dioxide (CO₂) emissions. Environmental Kuznets curve (EKC) hypothesis is widely leveraged to analyze the peak of CO₂ emissions, which is considered as a pivotal step for the effective CO₂ emission reduction in previous studies. This study tests the EKC hypothesis using the data of CO₂ emissions of manufacturing and construction industries from 121 countries throughout 1960–2014, and turning points (TPs) are calculated for the countries where EKC hypothesis is validated. The results show that the EKC hypothesis was validated by 95 out of 121 countries, among which, 13 countries have not reached any of the three TPs, 11 countries have reached the first-step TP (TP_CI), 21 countries have reached the second-step TP (TP_PC), and 50 countries have reached the third-step TP (TP_TC). Moreover, the result of examination of the EKC existence at four income levels indicates the higher-income nations own a higher proportion of countries validates the EKC hypothesis and reach the TP. These findings help policy-makers analyze the TP status quo and generate step-wise strategies for national CO₂ emission reduction of manufacturing and construction industries.     

Fuel characteristics and emissions from biomass burning and land-use change in Nigeria

Nigeria is one of the 13 low-latitude countries that have significant biomass burning activities. Biomass burning occurs in moist savanna, dry forests, and forest plantations. Fires in the forest zone are associated with slash-and-burn agriculture; the areal extent of burning is estimated to be 80% of the natural savanna. In forest plantations, close to 100% of litter is burned. Current estimates of emissions from land-use change are based on a 1976 national study and extrapolations from it. The following non-carbon dioxide (CO₂) trace gas emissions were calculated from savanna burning: methane (CH₄), 145 gigagrams (Gg); carbon monoxide (CO), 3831 Gg; nitrous oxide (N₂O), 2 Gg; and nitrogen oxides (NO_x), 49 Gg. Deforestation rates in forests and woodlands are 300 × 10³ ha (kilohectare, or kha) and 200 × kha per year, respectively. Trace gas emissions from deforestation were estimated to be 300 Gg CH₄, 2.4 Gg N₂O, and 24 Gg NO_x. CO₂ emissions from burning, decay of biomass, and long-term emissions from soil totaled 125 561 Gg. These estimates should be viewed as preliminary, because greenhouse gas emission inventories from burning, deforestation, and land-use change require two components: fuel load and emission factors. Fuel load is dependent on the areal extent of various land uses, and the biomass stocking and some of these data in Nigeria are highly uncertain.     

Does the high–tech industry consistently reduce CO2 emissions? Results from nonparametric additive regression model

China is currently the world's largest carbon dioxide (CO₂) emitter. Moreover, total energy consumption and CO₂ emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO₂ emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO₂ emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Based on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO₂ emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO₂ emissions in the three regions should be given adequate attention in developing effective abatement policies.     

大气14CO2的加速器质谱分析技术研究进展

利用加速器质谱技术测定大气¹⁴CO₂以示踪大气化石源CO₂成为当前减污降碳工作的热点。该文从加速器质谱¹⁴C分析基础出发,系统介绍了加速器质谱的工作原理、大气样品的采集及纯化、石墨化样品的制备和测定,阐述了大气碳监测领域14 CO₂测试的研究进展。随着加速器质谱技术的不断发展,大气¹⁴CO₂的研究将会更加广泛和深入,有助于进一步认识大气化石源CO₂的来源,更有针对性地开展减污降碳工作。未来应统一制定¹⁴CO₂监测方法标准,规范操作流程和质控手段,完善实验仪器配套设施,加快提升监测能力和水平。     

Decadal emission estimates of carbon dioxide,sulfur dioxide,and nitric oxide emissions from coal burning in electric power generation plants in India

This study aims to estimate the emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitric oxide (NO) for coal combustion in thermal power plants in India using plant-specific emission factors during the period of 2001/02 to 2009/10. The mass emission factors have been theoretically calculated using the basic principles of combustion under representative prevailing operating conditions in the plants and fuel composition. The results show that from 2001/02 to 2009/10 period, total CO₂ emissions have increased from 324 to 499 Mt/year; SO₂ emissions have increased from 2,519 to 3,840 kt/year; and NO emissions have increased from 948 to 1,539 kt/year from the Indian coal-fired power plants. National average emissions per unit of electricity from the power plants do not show a noticeable improvement during this period. Emission efficiencies for new plants that use improved technology are found to be better than those of old plants. As per these estimates, the national average of CO₂ emissions per unit of electricity varies between 0.91 and 0.95 kg/kWh while SO₂ and NO emissions vary in the range of 6.9 to 7.3 and 2.8 to 2.9 g/kWh, respectively. Yamunagar plant in Haryana state showed the highest emission efficiencies with CO₂ emissions as 0.58 kg/kWh, SO₂ emissions as 3.87 g/kWh, and NO emissions as 1.78 g/kWh, while the Faridabad plant has the lowest emission efficiencies with CO₂ emissions as 1.5 kg/kWh, SO₂ emissions as 10.56 g/kWh, and NO emissions as 4.85 g/kWh. Emission values at other plants vary between the values of these two plants.     

Effect of national-level spatial distribution of cities on national transport CO2 emissions

Most research regarding the relationship between cities and transportation carbon emission is focused on intra-city travel, and it has been found that compact patterns tend to emit less carbon. Yet, little is known about the impact of national-level spatial distribution of cities and inter-city transportation on transportation CO₂ emissions. Further, most studies regarding the impact of urbanization on CO₂ emission directly examine the relationship between urbanization rate and CO₂ emission with little consideration of the national spatial pattern of urbanization. This study hypothesizes that the national-level spatial distribution of cities – in a dispersed or polarized pattern – affects national transport CO₂ emissions due to the varying intensity of inter-city transportation. This study uses the Gridded Population of the World v3 and v4 from Socioeconomic Data and Applications Center (SEDAC) of NASA to examine the national-level spatial distribution of urban agglomerations. It applies the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The analysis shows that, among 60–90% of urbanized countries, spatially dispersed urbanized countries (e.g., countries with many medium-sized cities scattered over the territory) show a lower national transportation CO₂ emission than spatially polarized urbanized countries (e.g., there are only a few large cities). The urban system elasticity of transportation CO₂ emissions is 0.4 or 0.6. That is, if the degree of polarization decreases by 1%, national transportation CO₂ emissions decrease by approximately 0.4–0.6%. This effect is similar to the effect of GDP per capita of around 0.5%. Because it is particularly difficult to disperse people and economic activities across a country once spatial polarization is set, this study's findings have the most significant implications for urbanizing countries. If urbanizing countries adopt national urban policy and territorial plans to form dispersed cities, it could reduce transportation carbon emissions and promote sustainable development. For already urbanized countries, national urban policy development is recommended to promote spatially dispersed rather than polarized national urban systems.