Spatio-temporal variations of carbon dioxide and its gross emission regulated by artificial operation in a typical hydropower reservoir in China

Supersaturation and excess emission of greenhouse gases in freshwater reservoirs have received a great deal of attention in recent years. Although impoundment of reservoirs has been shown to contribute to the net emission of greenhouse gases, reservoir age, geographical distribution, submerged soil type and artificial regulation also have a great impact on their emissions. To examine how large scale reservoir operation impact the water column CO₂ and its air–water interface flux, a field study was conducted in 2010 to evaluate potential ecological processes that regulate the partial pressure of CO₂ (pCO₂) in the water column in the Pengxi River backwater area (PBA), a typical tributary in the Three Gorges Reservoir, China. Measurements of total alkalinity (TA), pH and water temperature were applied to compute the pCO₂. And this approach was also validated by calculation of pCO₂ from the dissolved inorganic carbon data of samples. Partial least squares (PLS) regression was used to determine how the dynamics of the water pCO₂ were related to the available variables. The estimated pCO₂ in our sample ranged from 26 to 4,087 μatm in the surface water. During low water operation from July to early September, there was an obvious pCO₂ stratification, and pCO₂ in the surface was almost unsaturated. This phenomenon was also observed in the spring bloom during discharge period. Conversely, there was no significant pCO₂ stratification and the entire water column was supersaturated during high water operation from November to the following February. Significant correlation was observed between the magnitude of pCO₂, DO and chlorophyll a, suggesting that phytoplankton dynamics regulate pCO₂ in the PBA. The average areal rate of CO₂ emissions from the Pengxi River ranged from 18.06 to 48.09 mmol m^?2 day^?1, with an estimated gross CO₂ emission from the water surface of 14–37 t day^?1 in this area in 2010. Photosynthesis and respiration rates by phytoplankton might be the dominant processes that regulated pCO₂ in the water column. We conclude that pCO₂ values in the surface water of Pengxi River could be regarded as potential sources of CO₂ to the atmosphere were smaller or similar to those that have been reported for many other reservoirs to date.     

Estimation of green house gas emissions from Koteshwar hydropower reservoir,India

The emissions of greenhouse gas (GHG) from soils are of significant importance for global warming. The biological and physico-chemical characteristics of soil affect the GHG emissions from soils of different land use types. Methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂) production rates from six forest and agricultural soil types in the Koteshwar hydropower reservoir catchments located in the Uttarakhand, India, were estimated and their relations with physico-chemical characteristics of soils were examined. The samples of different land use types were flooded and incubated under anaerobic condition at 30 °C for 60 days. The cumulative GHG production rates in reservoir catchment are found as 1.52 ± 0.26, 0.13 ± 0.02, and 0.0004 ± 0.0001 μg g soil^?1 day^?1 for CO₂, CH₄, and N₂O, respectively, which is lower than global reservoirs located in the same eco-region. The significant positive correlation between CO₂ productions and labile organic carbon (LOC), CH₄ and C/N ratio, while N₂O and N/P ratio, while pH of soils is negatively correlated, conforms their key role in GHG emissions. Carbon available as LOC in the reservoir catchment is found as 3–14% of the total ?C” available in soils and 0–23% is retained in the soil after the completion of incubation. The key objective of this study to signify the C, N, and P ratios, LOC, and pH with GHG production rate by creating an incubation experiment (as in the case of benthic soil/sediment) in the lab for 60 days. In summary, the results suggest that carbon, as LOC were more sensitive indicators for CO₂ emissions and significant C, N, and P ratios, affects the GHG emissions. This study is useful for the hydropower industry to know the GHG production rates after the construction of reservoir so that its effect could be minimized by taking care of catchment area treatment plan.     

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%.     

北京市废弃物处理温室气体排放特征

基于《2006年IPCC国家温室气体清单指南》推荐的方法，结合《省级温室气体清单编制指南（试行）》和《城市温室气体核算工具指南》的部分数据与核算范围，针对固体废弃物填埋、焚烧和废水处理等过程，核算了北京市2005-2014年废弃物处理过程中温室气体总排放量。结果表明：2005-2014年北京市废弃物处理过程温室气体总排放量呈逐渐上升趋势，2014年温室气体总排放量比2005年增长98%。10年间，固体废弃物填埋过程一直是最主要的温室气体排放源，到2014年排放量达到最大，为416.3×10⁴t二氧化碳当量（CO₂e）。废弃物填埋、废水处理和废弃物焚烧过程占总排放量的比例分别为78.5%（CO₂e质量分数，下同）、13.5%和8%。结合已有研究，系统优化国内7个典型城市废弃物处理温室气体排放因子，核算7个城市排放情况，并对比分析了北京市排放情况。     

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.     

A comparison of emission calculations using different modeled indicators with 1-year online measurements

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm’s characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow^?1 year^?1) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow^?1 year^?1 (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between ?6.4 % and 10.5 %), compared with findings from the literature.     

Modelling and assessing inter-regional trade of CO2 emission reduction units

A cost-efficient way to allocate carbon dioxide (CO₂) emission reductions among countries or regions is to harmonise their marginal reduction costs. This could be achieved by a market of emission reduction units (ERUs). To model such a market, we use a multi-regional MARKAL-MACRO model. It gives insights into the consequences of co-ordinating CO₂ abatement on regional energy systems and economies. As a numerical application, we assess the establishment of a market of ERUs among three European countries for curbing their CO₂ emissions.     

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.     

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.     

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.     

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.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Marginal Abatement Costs and Marginal Welfare Costs for Greenhouse Gas Emissions Reductions: Results from the EPPA Model

Marginal abatement cost (MAC) curves, relationships between tonnes of emissions abated and the CO₂ (or greenhouse gas (GHG)) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced-form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) Are MAC relationships independent of what happens in other regions?, (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from MACs? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO₂-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. We also show that, as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated.     

Community metabolism in a deep (stratified) tropical reservoir during a period of high water-level fluctuations

As long as lakes and reservoirs are an important component of the global carbon cycle, monitoring of their metabolism is required, especially in the tropics. In particular, the response of deep reservoirs to water-level fluctuations (WLF) is an understudied field. Here, we study community metabolism through oxygen dynamics in a deep monomictic reservoir where high WLF (~10 m) have recently occurred. Simultaneous monitoring of environmental variables and zooplankton dynamics was used to assess the effects of WLF on the metabolism of the eutrophic Valle de Bravo (VB) reservoir, where cyanobacteria blooms are frequent. Mean gross primary production (P _g) was high (2.2 g C m^?2 day^?1), but temporal variation of P _g was low except for a drastic reduction during circulation attributed to zooplankton grazing. The trophogenic layer showed net autotrophy on an annual basis, but turned to net heterotrophy during mixing, and furthermore when the whole water-column oxygen balance was calculated, considering the aphotic respiration (R _aphotic). The high total respiration resulting (3.1 g C m^?2 day^?1) is considered to be partly due to mixing enhanced by WLF. Net ecosystem production was equivalent to a net export of 3.4 mg CO₂?m^?2 day^?1 to the atmosphere. Low water levels are posed to intensify boundary-mixing events driven by the wind during the stratification in VB. Long-term monitoring showed changes in the planktonic community and a strong silicon decrease that matched with low water-level periods. The effects of low water-level on metabolism and planktonic community in VB suggest that water-level manipulation could be a useful management tool to promote phytoplankton groups other than cyanobacteria.     

南通市温室气体排放估算

以2009年南通市主要领域碳排放情况为基数,采用IPCC指南中的计算方法,选取IPCC 指南明确的领域中对南通市而言具有代表性的部分内容,对2009年南通市全市碳排放量进行估算。估算结果表明,能源活动(化石燃料燃烧)为南通市主要温室气体排放源,其比例占据了主导地位。在能源活动中,原煤燃烧排放的CO₂远高于其他化石燃料燃烧的排放量。因此,南通市可在产业结构和能源结构调整、提高能源利用效率及加强能源管理等方面进行努力,以减少南通市温室气体排放量。     

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。     

The Climate Impacts of Sulfate Aerosols

Sulfate aerosols (SO₄) from anthropogenic emissions of sulfur dioxide (SO₂) generally have a cooling effect. However, if SO₂ emissions fall over time, accounting for sulfate aerosols will increase the predicted warming from greenhouse gases. This paper integrates the four marker emission scenarios for CO₂ and SO₄ from the Special Report on Emissions Scenarios (SRES), the UIUC general circulation model (GCM), and a country-specific impact model (GIM) to calculate the impacts of sulfate aerosols. By 2100, lower SO₂ emissions slightly increase warming in the temperate and polar regions causing small damages in the former and small benefits in the latter. If SO₂ emissions are also lower in tropical regions, temperatures will rise causing small damages there as well. However, if SO₂ emissions rise in tropical regions, temperatures will fall leading to small benefits. This revised version was published online in July 2006 with corrections to the Cover Date.     

Integrated Assessment of Swiss GHG Mitigation Policies After 2012

The residential sector presents a great potential for greenhouse gases (GHG) mitigation. We perform an integrated assessment of different mitigation policies for Switzerland focusing on the residential sector. We analyze the case of pure incentive taxes and technical regulations. For our analysis, we have coupled a general equilibrium model with a Swiss residential energy model. We find that a progressive GHG tax of more than 200 USD2000/tCO₂ eq is necessary to reach a target of 50% reduction of GHG emissions in 2050. Finally, we also find that efficiency-based technical regulations provide limited additional abatement incentives.     

Long-term spatiotemporal patterns of CH4 and N2O emissions from livestock and poultry production in Turkey

This study quantified spatiotemporal patterns of CH₄ and N₂O emissions from livestock and poultry production in Turkey between 1961 and 2007. CH_4(enteric) (from enteric fermentation), CH_4(manure) (from manure management), and N₂O_(AWM) (from animal waste management) emissions in Turkey were estimated at 1,164, 216, and 55 Gg in 1961 and decreased to 844, 187, and 39 Gg in 2007, contributing a share of roughly 2% to the global livestock-related CH₄ emissions and %1.5 to the global N₂O_(AWM) emissions, respectively. Total CO₂-eq emissions were estimated at 50.7 Tg in 1961 and declined from a maximum value of 60.7 Tg in 1982 to a minimum value of 34.5 Tg in 2003, with a mean emission rate of 48 Tg year^???1 due to a significant reduction in the number of ruminant livestock. The highest mean share of emissions belonged to West Black Sea (14% and 16%) for CH_4(enteric) and CH_4(manure) and to North East Anatolia (12% and %13) for N₂O_(AWM) and total CO₂-eq emissions, respectively. The highest emission density was 1.7 Mg km^???2 year^???1 for CH_4(enteric), 0.3 Mg km^???2 year^???1 for CH_4(manure), and 0.07 Mg km^???2 year^???1 for the total CO₂-eq emissions in the West and North East Anatolia regions and 0.09 Mg km^???2 year^???1 for N₂O_(AWM) in the East Marmara region. Temporal and spatial variations in CH_4(enteric), CH_4(manure), and N₂O_(AWM) emissions in Turkey were estimated using regression models and ordinary kriging at a 500-m resolution, respectively.