Verifying Fossil-Fuel Carbon Dioxide Emissions Forecasted by an Artificial Neural Network with the GEOS-Chem Model

In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions （ff） in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data （1979-2008） from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System （GEOS）-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.     

The Effects of Environmental Conditions on Concentration and Emission of Ammonia in Chicken Farms during Summer Season

This paper presents a field study conducted in northwest Turkey and characterizes the NH₃ concentration and emission measured in summer season from three chicken farms. The influence of environmental conditions on NH₃ concentration and emission was also investigated in this study. Ammonia concentration, temperature, relative humidity and airflow rate were continuously recorded for four sequential days. The environmental conditions were measured using a multifunction temperature and humidity‐meter with a hot wire probe. Portable multiple gas detectors with electro‐chemical sensors were used to measure NH₃ concentration. The NH₃ emission rates for houses were calculated by multiplying simultaneously measured NH₃ concentrations and air flow rates. The average daily mean (ADM) house concentrations of house 1 (H1), house 2 (H2), and house 3 (H3) were measured as 4.43, 3.71, and 6.20 ppm, respectively. NH₃ concentration was inversely proportional to temperature (r = ?0.279), relative humidity (r = ?0.063) and airflow rate (r = ?0.554) for all monitored houses. The ADM house NH₃ emission was 135 g/(h house) for H1, 255 g/(h house) for H2, and 117 g/(h house) for H3. The combined average emission rate in this study (0.26 g/(d bird)) was lower than the emission rate measured in chicken farms in the USA. However, our results were comparable to rates calculated in European studies because house design, ventilation system and bird diet applied in Turkish chicken farms are very similar to those employed in European countries. The NH₃ emissions were significantly correlated to NH₃ concentrations (r = 0.45, p ≤ 0.001) and airflow rates (r = 0.97, p ≤ 0.001). A clear diurnal pattern was obtained for NH₃ concentrations rather than NH₃ emissions at the end of the study.     

Reducing fugitive methane emissions from the North American oil and gas sector: a proposed science-policy framework

The shale gas boom in the United States spurred a shift in electricity generation from coal to natural gas. Natural gas combined cycle units emit half of the CO₂ to produce the same energy as a coal unit; therefore, the market trend is credited for a reduction in GHG emissions from the US power sector. However, methane that escapes the natural gas supply chain may undercut these relative climate benefits. In 2016, Canada, the United States and Mexico pledged to reduce methane emissions from the oil and natural gas sector 40–45% from 2012 levels by 2025. This article reviews the science-policy landscape of methane measurement and mitigation relevant for meeting this pledge, including changes in US policy following the 2016 presidential election. Considerable policy incoherence exists in all three countries. Reliable inventories remain elusive; despite government and private sector research efforts, the magnitude of methane emissions remains in dispute. Meanwhile, mitigation efforts vary significantly. A framework that integrates science and policy would enable actors to more effectively inform, leverage and pursue advances in methane measurement and mitigation. The framework is applied to North America, but could apply to other geographic contexts.

Key policy insights

• The oil and gas sector’s contribution to atmospheric methane concentrations is becoming an increasingly prominent issue in climate policy.

• Efforts to measure and control fugitive methane emissions do not presently proceed within a coherent framework that integrates science and policy.

• In 2016, the governments of Canada, Mexico and the United States pledged to reduce methane emissions from the oil and natural gas sector 40–45% from 2012 levels by 2025.

• The 2016 presidential election in the United States has halted American progress at the federal level, suggesting a heavier reliance on industry and subnational efforts in that country.

• Collectively or individually, the countries, individual agencies, or private stakeholders could use the proposed North American Methane Reduction framework to direct research, enhance monitoring and evaluate mitigation efforts, and improve the chances that continental methane reduction targets will be achieved.

     

Critical distances: Comparing measures of spatial accessibility in the riverine landscapes of Peruvian Amazonia

Quantitative measures of accessibility are increasingly used in land cover change modeling and in assessing human pressure on the environment. In riverine Amazonia the significance of physical accessibility for biodiversity, land use patterns and economic livelihoods is widely acknowledged, but attempts to quantify accessibility in practice have been few in number. In this study we compare different distance- and frequency-based measures of spatial accessibility and develop a quantitative model of accessibility patterns for the north-eastern Peruvian Amazonia where rivers form the core of the transportation network. We model accessibility between the rural areas of the Loreto region and the capital city of Iquitos, using different distance algorithms in a geographic information system, and complement the distance model with information on river boat frequencies and transport capacities. Patterns of accessibility are visualized in terms of potential production zones for different types of agricultural and non-timber forest products.This study demonstrates how results from different accessibility measures vary considerably. The mean Euclidean distance to Iquitos is almost 270 km, the mean network distance nearly 760 km and the mean travel time 70 h. Observed network distances from validation points to Iquitos are on average 1.6 times longer than Euclidean distances, and for the whole study area, the average ratio between modeled network distances and Euclidean distances is 3.1. The correlation between network distances and time distances is very strong, but time distances are relatively shorter along the major channels where boat traffic is considerably faster than along narrow, tightly meandering rivers. Measures of boat frequency and transport capacity show that availability of transport possibilities is highly varying across the region. These measures provide insights into the ’thickness’ of trade, indicating the level of market integration for riverine settlements. We conclude that quantifying accessibility in an environment like Peruvian Amazonia requires measures that take into account the spatial structure and dynamic nature of the riverine transportation network. Time as a unit of distance provides the most relevant measure of accessibility in the Amazonian context, where many human actions and traditional livelihoods are controlled by travel times between the regional core and the hinterland.     

Metal-residence sites in lavas and tuffs from Volcán Popocatépetl, Mexico: implications for metal mobility in the environment

 Volcan Popocatépetl is a Quaternary stratovolcano located 60 km southeast of Mexico City. The summit crater is the site of recent ash eruptions, excess degassing, and dacite dome growth. The modern cone comprises mainly pyroclastic flow deposits, airfall tephras, debris flows, and reworked deposits of andesitic composition; it is flanked by more mafic monogenetic vents. In least-degassed fallout tuffs and mafic scoria, transition metals are concentrated in phases formed before eruption, during eruption, and after eruption. Preeruptive minerals occur in both lavas and tephra, and include oxides and sulfides in glass and phenocrysts. The magmatic oxides consist of magnetite, ilmenite, and chromite; the sulfides consist of both (Fe,Ni)_1-xS (MSS) and Cu–Fe sulfide (ISS). Syn- and posteruptive phases occur in vesicles in both lavas and tephra, and on surfaces of ash and along fractures. The mineral assemblages in lavas include Cu–Fe sulfide and Fe–Ti oxide in vesicles, and Fe sulfide and Cu–Fe sulfide in segregation vesicles. Assemblages in vesicles in scoria include Fe–Ti oxide and rare Fe–Cu–Sn sulfide. Vesicle fillings of Fe–Ti oxide, Ni-rich chromite, Fe sulfide, Cu sulfide, and barite are common to two pumice samples. The most coarse-grained of the vesicle fillings are Cu–Fe sulfide and Cu sulfide, which are as large as 50 μ in diameter. The youngest Plinian pumice also contains Zn(Fe) sulfide, as well as rare Ag–Cu sulfide, Ag–Fe sulfide, Ag bromide, Ag chloride, and Au–Cu telluride. The assemblage is similar to those typically observed in high-sulfidation epithermal mineralization. The fine-grained nature and abundance of syn- and/or posteruptive phases in porous rocks makes metals susceptible to mobilization by percolating fluids. The abundance of metal compounds in vesicles indicates that volatile exsolution prior to and/or during eruption played an important role in releasing metals to the atmosphere. Received: March 1997 · Accepted: 27 May 1997     

城镇化模式与低碳发展的关联分析——以石家庄市为例

不同城镇化发展模式对城市碳排放有显著影响。以石家庄市为案例,基于历年统计数据及实地调研数据,采用情景分析方法,定量核算石家庄市不同城镇化模式下的碳排放,结果表明在不同的城镇化模式下,石家庄市能源消费和碳排放将存在显著差异。与延续目前相对高碳的城镇化模式相比,在低碳城镇化模式下,2015—2030年,在城镇化率同样提升18.7%的情景下,碳排放的年均增速将由4.3%下降至0.4%,碳减排效果非常显著。     

The population structural transition effect on rising per capita CO2 emissions: evidence from China

ABSTRACT

The per capita CO₂ emissions (PCCE) of many developing countries like China have been rising faster than total CO₂ emissions, and display spatial divergence. Such temporal growth and spatial divergence will have a significant influence on efforts to mitigate CO₂ emissions. Given the research gap on the impact of the structural transition in population on PCCE, we constructed an econometric model using the dynamic panel method. The results reveal that the population structural transition has a significant nonlinear impact on PCCE, as the rate of population growth in China decelerates. Both demographic ageing and urban-rural migration have a stronger impact on PCCE than other factors. This effect, however, decreases beyond a certain threshold. An increase in the number of households due to urbanization and family downsizing has resulted in a positive effect on PCCE, without a threshold turning point. The research also finds that an increased share of the service sector in employment can reduce PCCE only if the sector employs more than 31.56% of the total employed population. Overall, these findings indicate that policymakers should pay attention to the prominence of the demographic structural transition for effective climate policy.

Key policy insights

• Policymakers should address rising per capita carbon emissions (PCCE) and their spatial divergence in future climate policies, not just total CO₂ emissions.

• The transitioning demographics of ageing and urbanization in China show a nonlinear, inverted U-shaped effect on PCCE instead of a continuously positive effect.

• Based on the nonlinear effect of employment structure on PCCE, policymakers should focus on the relationship between the structural transition of the economy and PCCE in future climate mitigation policies.

     

大气CO2浓度时空变化卫星遥感监测的应用潜力分析

GOSAT卫星观测反演大气CO2浓度精度已经提高到了1—2 ppm,而卫星数据能否准确地揭示全球和区域大气CO2浓度变化特征还缺乏充分的评价与分析。本文针对已经连续运行观测3年的GOSAT卫星,收集了来自美国NASA-OCO团队(ACOS)和日本环境研究所GOSAT团队(NIES)基于各自算法反演的两套大气CO2柱浓度数据,描述并分析了全球大气CO2时空变化特征。分析结果表明,从XCO2反演的绝对值结果来看ACOS总体上比NIES的高出约2 ppm左右,但从时空的相对变化上它们揭示了相近的大气CO2浓度时空变化特征。两套数据显示出全球平均大气CO2浓度在2010年—2012年的3年期间年增量分别为1.8 ppm和2.0 ppm;季节变化幅度,北半球最大4—6 ppm,南半球最大约2 ppm,这与地面观测结果基本一致。进一步将EDGAR 4.2人为排放总量格网化数据与GOSAT卫星观测反演的CO2浓度进行相关统计分析,结果指出两套数据对人为排放量有着微弱的响应。本文结果指出目前GOSAT卫星观测反演的XCO2可以检测出全球和区域大气CO2浓度的年变化、季节变化和区域空间变化的特征;GOSAT卫星10.5 km空间分辨率的观测虽难于检测出点源的浓度变化,但从区域上对人为排放的累积效应的监测显示了一定的应用潜力。     

日侧极隙纬度低频波及其与地磁扰动的关系

利用挪威斯瓦尔巴德地区的ＥＬＦ／ＶＬＦ观测资料和世界数据中心公布的Ｋｐ指数，分析了日侧极隙纬度低频波不同季节里的周日变化和１９８４年５月－１９８６年４月的年度变化及这些波与地磁扰动的某些关系．主要结果有：１．夏季ＥＬＦ波出现率极大值最大，而冬季的最小，前者约为后者的３倍，而且此极大值无论哪个季节都出现在磁正午时段．２．ＶＬＦ波出现率在夏季较小冬季较大；其极大值出现在磁午后至磁子夜前的２－４ｈ时段里．３．夏季ＥＬＦ波指数∑Ａ与地磁指数∑ＫＰ日变化较相吻合，在太阳自转周内两者相关系数约为０．６．４．冬季ＶＬＦ波指数∑Ａ与∑Ｋｐ日变化相吻合，在太阳自转周内两者相关系数可达０．８．这些结果表明日侧极隙纬度ＥＬＦ波和ＶＬＦ波各有不同的产生机制和源区．     

On the Retrieval of Volcanic Sulfur Dioxide Emissions from GOME Backscatter Measurements

We focus on the retrieval of volcanic sulfur dioxide (SO₂) emissions from an analysis of atmospheric UV backscatter spectra obtained by the Global Ozone Monitoring Experiment (GOME) spectrometer on board the ESA European Remote Sensing Satellite (ERS-2). Here, the last major eruptions of Mt. Etna on Sicily (Italy) in July/August 2001 and October/November 2002 provided an excellent opportunity to study the retrieval of SO₂ columnar amounts from ground-based, LIDAR and satellite measurements. Our study shows that the bulk of emitted SO₂ was confined in the troposphere, mainly between 700 hPa and 400 hPa which is confirmed by trajectory analysis, by LIDAR observations and AVHRR observations. The area of influence of Mt. Etna eruptions ranges from the Western Saharan Desert to Greece and the near east states and even down to the basin of Tschad, Africa. Our analysis revealed that information about the plume height of volcanic eruptions and aerosol parameters is necessary for a reliable quantitative retrieval of SO₂ from space-borne sensor data at periods perturbed by volcanic eruptions.