Consumption-based accounting of CO2 emissions in the sustainable development Goals Agenda

In 2017 the paper ‘The Sustainable Development Oxymoron: Quantifying and Modelling the Incompatibility of Sustainable Development Goals’ was published, showing that there is a conflict between socio-economic development goals and ecological sustainability goals using cross-country time-series data. The authors looked at production-based CO2 emissions to measure and model the 13^th SDG goal addressing climate change. Their models showed that production-based CO2 emissions were stalling or even decreasing in rich countries, which suggests that other countries are also likely to see stalling and decrease in their CO2 emissions once they become rich. However, this conclusion can be challenged when accounting for consumption-based CO2 emissions rather than production-based CO2 emissions. In this follow-up paper, we re-run some of the analyses performed in the original paper making use of consumption-based CO2 emissions. The analysis confirms the inherent SDG conflict between socio-economic and ecological SDGs. But, this new analysis demonstrates that from a consumption perspective the trend of stalling or decreasing CO2 emissions is reversed, with natural depletion costs being exported to poorer countries. Despite this new perspective on CO2 emissions, the conflict between SDG goals can still be avoided by making investments in public health, education and renewable energy, as suggested in the original paper.     

The challenge of managing threatened invasive species at a continental scale

The European Union's (EU) environmental legislation establishes common measures to prevent the entry and spread of invasive non-native species and to minimize their impacts. However, species that are native to at least one member state but non-native and potentially invasive in others (NPIS) are in limbo because they are neither legally regulated at the EU level nor in most member states. We used the Communication and Information Resource Centre for Administrations, Businesses and Citizens (CIRCABC) raw data on NPIS (317 taxa) to analyze their distribution across the EU and identify which biogeographical regions are the main sources of invasions. We additionally evaluated the conservation challenge posed by NPIS that are threatened within their native ranges. We performed a pairwise analysis summarizing the number of species that are native to a given member state but non-native to another and vice versa. Although distribution patterns of NPIS varied across taxa groups, overall, southern and central EU countries were both donors and recipients of NPIS. Eastern countries were mainly a source, and western and northern countries mostly received NPIS. Around 27% of NPIS were threatened in some of their EU native ranges, which is a challenge for conservation and management because some of them have serious negative effects on European biodiversity, but hitherto remain outside the scope of the EU regulation of invasive non-native species. This highlights an unresolved paradox because efforts to manage species as invasive conflict with efforts to protect them as threatened within the same territory.     

Optimal abatement of carbon emission flows

We study optimal carbon capture and storage (CCS) from point sources, taking into account damages incurred from the accumulation of carbon in the atmosphere and exhaustibility of fossil fuel reserves. High carbon concentrations call for full CCS, meaning zero net emissions. We identify conditions under which partial or no CCS is optimal. In the absence of CCS the CO2 stock might be inverted U-shaped. With CCS more complicated behavior may arise. It can be optimal to have full capture initially, yielding a decreasing stock, then partial capture while keeping the CO2 stock constant, and a final phase without capture but with an inverted U-shaped CO2 stock. We also introduce the option of adaptation and provide a unified theory regarding the optimal use of CCS and adaptation.     

施氮量及抑制剂配比对双季稻生长期温室气体排放的影响

采用静态箱-气相色谱法研究了南方稻田不同施氮量及抑制剂配比对双季稻生长期内CH4、N2O和CO2排放的影响。结果表明,双季稻田施氮与抑制剂配合施用的CH4、N2O和CO2总排放量明显低于对照（常规施肥）,其中CH4总排放量降低了7.6%～36.4%,N2O降低了25.8%～29.9%,CO2降低了17.7%～30.4%。早稻收获后各处理土壤NH4^＋-N和NO3^--N含量存在明显差异,添加抑制剂处理的土壤NH4^＋-N含量均高于对照,增幅为25.1%～77.0%,土壤NO3^--N以早稻移栽前基施N 240 kg·hm^-2配合12‰NAM和晚稻追施N 30 kg·hm^-2的处理比对照降低了61.8%（P﹤0.05）,而基施N 330 kg·hm^-2配合8‰NAM处理可能因早稻施氮过量反而高于对照。表明合理的施氮量及抑制剂添加比例能有效提高土壤中NH4^＋-N含量,减少NO3^--N残留,从而达到降低双季稻期间稻田温室气体排放的效果,为进一步利用抑制剂（NAM）与N、P、K化肥合理配比并形成复配肥,构建南方双季稻田温室气体减排的新型施肥模式提供技术支撑。     

Testing spatial cluster occurrence in maps equipped with environmentally defined structures

We propose a novel tool for testing hypotheses concerning the adequacy of environmentally defined factors for local clustering of diseases, through the comparative evaluation of the significance of the most likely clusters detected under maps whose neighborhood structures were modified according to those factors. A multi-objective genetic algorithm scan statistic is employed for finding spatial clusters in a map divided in a finite number of regions, whose adjacency is defined by a graph structure. This cluster finder maximizes two objectives, the spatial scan statistic and the regularity of cluster shape. Instead of specifying locations for the possible clusters a priori, as is currently done for cluster finders based on focused algorithms, we alter the usual adjacency induced by the common geographical boundary between regions. In our approach, the connectivity between regions is reinforced or weakened, according to certain environmental features of interest associated with the map. We build various plausible scenarios, each time modifying the adjacency structure on specific geographic areas in the map, and run the multi-objective genetic algorithm for selecting the best cluster solutions for each one of the selected scenarios. The statistical significances of the most likely clusters are estimated through Monte Carlo simulations. The clusters with the lowest estimated p-values, along with their corresponding maps of enhanced environmental features, are displayed for comparative analysis. Therefore the probability of cluster detection is increased or decreased, according to changes made in the adjacency graph structure, related to the selection of environmental features. The eventual identification of the specific environmental conditions which induce the most significant clusters enables the practitioner to accept or reject different hypotheses concerning the relevance of geographical factors. Numerical simulation studies and an application for malaria clusters in Brazil are presented.     

1999—2009年我国不同收入水平下的碳排放差异分析

碳排放差异研究对于科学合理地制定我国节能减排政策具有重要的指导意义。在利用IPCC参考方法对中国1999—2009年期间各省（市）CO2排放量计算的基础上,引入Theil指数,定量分析了中国不同收入水平下的CO2省际差异及其与人均收入水平之间的关系。结果表明,1999—2003年中国人均CO2排放量随着人均收入水平的提高而增加,2003—2009年中国各收入水平省份的人均排放量近似于不规则的＂M＂型增长趋势,中等偏低收入省份的人均排放量迅速增加,并超过中等收入省份;不同收入水平省份之间和各省份内部的人均CO2排放水平均存在较大的差距,但省份之间的排放不平等水平明显大于省份内部的不平等水平。因此,中国在制定节能减排政策时,要充分考虑经济发展和人均收入水平的条件下,兼顾区域和省域碳排放的特征,制定合理有效的减排目标和计划。     

中国燃煤电厂碳排放量计算及分析

人类活动造成的温室气体排放已经对自然生态造成了巨大的影响。如果无法有效解决气候变化问题,到2030年将有超过1亿人因此而失去生命,且全球经济增长将削减3.2%。有效地控制和减少温室气体的排放是人类急需解决的问题。目前中国温室气体排放总量已经超越美国成为全球第一大温室气体排放国,中国的能源结构决定了中国燃煤发电是中国CO2主要排放源之一,因此实现燃煤发电碳减排对降低中国碳排放总量,减少温室气体排放具有重要意义。准确地计算燃煤电厂产生的碳排放量是进行碳排放权交易、低碳火电厂在经济上具有可行性,最终实现燃煤电厂碳减排的前提条件之一。本研究根据世界资源研究所提供的计算工具首先界定了本研究对于碳排放计算的范围,其次阐述了不同电厂应针对其使用的燃煤进行工业分析的精细化程度不同而采用不同的计算方法,最后对两组不同机组类型的中国火电厂进行了碳排放量计算和对比分析。根据以上分析得出了大容量、高参数的燃煤发电机组相比小容量发电机组不仅能提高能源利用效率,同时也能相对减少因生产电能而产生的CO2排放。其次,燃煤电厂CO2排放中煤炭固定燃烧占有绝对比例,脱硫及外购电力所占比例较小,但排放的绝对总量并不小。再次,由于大容量、高参数机组与小容量发电机组相比在生产单位电能所消耗的燃煤量更少、其排放的废弃中的CO2浓度相对较高,应此更适合安装碳捕捉系统,有助于提高捕捉效率,降低捕捉CO2的成本。因此,建议在未来建设碳捕捉系统时应优先选择大容量、高参数机组。本研究的创新点在于在上述研究的基础上考虑单个燃煤电厂的煤质、考虑电厂脱硫、外购电力的因素,根据电厂对煤质不同程度的工业分析采用不同的计算方法,目的在于更?     

中国能源消费导致的CO2排放量的差异特征分析

运用一种不产生残差的方法——对数平均迪氏指数法LMDI(logarithmicmeanDivisiaindex),对中国部分省份、区域能源消费导致的二氧化碳排放量进行了分解分析。将二氧化碳排放总量的变化分解成五个主要影响因素,即化石燃料的排放系数、能源消费结构、能源强度、人均GDP和人口总数。研究表明我国各省(地区)的二氧化碳排放量在1996年后呈现零(或负)增长趋势,主要影响因素是能源强度的提高;各省(地区)的二氧化碳排放量地区差异显著。因此,要在全国实现二氧化碳排放量的总体减排,应从提高能源利用效率,调整产业结构,消除地区发展的不平衡,逐步改善能源消费结构等方面考虑。     

Analyzing the spatial structure of a Sri Lankan tree species with multiple scales of clustering

Clustering at multiple critical scales may be common for plants since many different factors and processes may cause clustering. This is especially true for tropical rain forests for which theories explaining species coexistence and community structure rest heavily on spatial patterns. We used point pattern analysis to analyze the spatial structure of Shorea congestiflora, a dominant species in a 25-ha forest dynamics plot in a rain forest at Sinharaja World Heritage Site (Sri Lanka), which apparently shows clustering at several scales. We developed cluster processes incorporating two critical scales of clustering for exploring the spatial structure of S. congestiflora and interpret it in relation to factors such as competition, dispersal limitation, recruitment limitation, and Janzen-Connell effects. All size classes showed consistent large-scale clustering with a cluster radius of approximately 25 m. Inside the larger clusters, small-scale clusters with a radius of 8 m were evident for recruits and saplings, weak for intermediates, and disappeared for adults. The pattern of all trees could be divided into two independent patterns: a random pattern (nearest neighbor distance > 8 m) comprising approximately 12% of the trees and a nested double-cluster pattern. This finding suggests two independent recruitment and/or seed dispersal mechanisms. Saplings were several times as abundant as recruits and may accumulate several recruit generations. Recruits were only weakly associated with adults and occupied about half of the large-scale clusters, but saplings almost all. This is consistent with recruitment limitation. For approximately 70% (95%) of all juveniles the nearest adult was less than 26 m away (53 m), suggesting a dispersal limitation that may also be related to the critical large-scale clustering. Our example illustrates the manner in which the use of a specific and complex null hypothesis of spatial structure in point pattern analysis can help us better understand the biology of a species and generate specific hypotheses to be further investigated in the field.     

包膜尿素对水田土壤排放NH3、NOx、CO2影响的研究

为了研究包膜尿素对水田土壤排放NH3、NOx和CO2的影响,采用水稻盆栽的方法,探讨了在水稻不同生育期内不同种类包膜尿素对水田土壤排放NH3、NOx和CO2的影响。结果表明,包膜尿素处理对水田土壤排放NH3、NOx和CO2均具有抑制作用,与普通尿素相比,包膜尿素LP40、LPSS、BB、SC60 NH3的挥发总量降低了5.4%~19.3%,NOx的挥发总量降低了8.1%~23.4%,CO2的挥发总量降低了1.6%~13.0%;施用包膜尿素能够抑制水田土壤NH3、NOx和CO2的排放。     

Estimating the risk of insect species invasion: Kohonen self-organising maps versus k-means clustering

Previous work on the estimation of the invasiveness of insect pest species used a single Kohonen self-organising map (SOM) to quantify the invasion potential of each member of a set of species in relation to a particular geographic region. In this paper that method is critically compared to an alternative approach of calculating the invasive potential of insect pest species as an outcome of clustering of regional species assemblages. Data clustering was performed using SOM and k-means optimisation clustering and multiple trials were performed with each algorithm. The outcomes of these two approaches were evaluated and compared to the previously published results obtained from a single SOM. The results show firstly, due to the inherent variation between trials of the algorithms used, that multiple trials are necessary to determine reliable risk ratings, and secondly, that k-means clustering can be considered a more appropriate algorithm for this particular application, as it produces clusters of higher quality, as determined by objective cluster measures, and is far more computationally efficient than SOM.     

包膜尿素对水田土壤排放NH3、NOx、CO2影响的研究

为了研究包膜尿素对水田土壤排放NH3、Nox和CO2的影响,采用水稻盆栽的方法,探讨了在水稻不同生育期内不同种类包膜尿素对水田土壤排放NH3、Nq和CO2的影响。结果表明,包膜尿素处理对水田土壤排放NH3、Nq和CO2均具有抑制作用,与普通尿素相比,包膜尿素LP40、LPSS、BB、SC60NH3的挥发总量降低了5．4％-19．3％,Nox的挥发总量降低了8．1％-23．4％,CO2的挥发总量降低了1．6％-13．O％;施用包膜尿素能够抑制水田土壤NH3、NOx和CO2的排放。     

Evaluating greenhouse gas emissions inventories for agricultural burning using satellite observations of active fires

Fires in agricultural ecosystems emit greenhouse gases and aerosols that influence climate on multiple spatial and temporal scales. Annex 1 countries of the United Nations Framework Convention on Climate Change (UNFCCC), many of which ratified the Kyoto Protocol, are required to report emissions of CH4 and N2O from these fires annually. In this study, we evaluated several aspects of this reporting system, including the optimality of the crops targeted by the UNFCCC globally and within Annex 1 countries, and the consistency of emissions inventories among different countries. We also evaluated the success of individual countries in capturing interannual variability and long-term trends in agricultural fire activity. In our approach, we combined global high-resolution maps of crop harvest area and production, derived from satellite maps and ground-based census data, with Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) measurements of active fires. At a global scale, we found that adding ground nuts (e.g., peanuts), cocoa, cotton and oil palm, and removing potato, oats, rye, and pulse other from the list of 14 crops targeted by the UNFCCC increased the percentage of active fires covered by the reporting system by 9%. Optimization led to a different recommended list for Annex 1 countries, requiring the addition of sunflower, cotton, rapeseed, and alfalfa and the removal of beans, sugarcane, pulse others, and tuber-root others. Extending emissions reporting to all Annex 1 countries (from the current set of 19 countries) would increase the efficacy of the reporting system from 6% to 15%, and further including several non-Annex 1 countries (Argentina, Brazil, China, India, Indonesia, Thailand, Kazakhstan, Mexico, and Nigeria) would capture over 55% of active fires in croplands worldwide. Analyses of interannual trends from the United States and Australia showed the importance of both intensity of fire use and crop production in controlling year-to-year variations in agricultural fire emissions. Remote sensing provides an effective means for evaluating some aspects of the current UNFCCC emissions reporting system; and, if combined with census data, field experiments and expert opinion, has the potential to improve the robustness of the next generation inventory system.     

[CO2]和温度增加的相互作用对植物生长的影响

ＣＯ2 和温度是影响植物生长、发育和功能的两个关键因子 .在过去一个世纪中 ,[ＣＯ2 ]从 2 80 μｍｏｌ/ｍｏｌ增加到 36 0μｍｏｌ/ｍｏｌ且每年增长速率为 1～ 5 μｍｏｌ/ｍｏｌ,到 2 0世纪末达到更高的浓度[1] .最近的模型预测表明 ,到 2 10 0年 ,全球表面温度可能会增加 1～ 4 .5℃ [2 \〗.ＣＯ2 是光合作用的底物 ,而且还是初级代谢过程 (气孔反应和光合作用 )、光合同化物分配和生长的调节者 .温度几乎影响植物所有的生物学过程 .因此 ,在全球气候变化要素中 ,大气 [ＣＯ2 ]和温度升高对植物的生理过程和生物量及产量具有极为重要的…     

利用农业土壤固定有机碳——缓解全球变暖与提高土壤生产力

大气CO     

2003—2010年中国对流层CO2时空分布研究

利用2003年到2010年的美国宇航局（National Aeronautics and Space Administration,NASA）的AIRS（Atmosphere InfraRed Sounder）官方反演的对流层中层（500 hPa）左右一段气柱内的CO2体积混合比产品分析中国地区对流层的CO2体积分数分布时空变化特征。所用数据是对AIRS L3产品2°×2.5°网格数据进行处理分析得到。经过对这8年的观测数据（2003年1月—2010年12月）的数据分析研究发现：中国地区平均CO2的体积分数在空间分布上极不平衡,总体高值集中于北部。CO2对流层中层的高值区集中在35°—45°N,形成东北平原、内蒙古中西部地区、塔克拉玛干沙漠和塔里木盆地4个高值中心,而云南地区和西藏南部上空的CO2值偏低。与中国地区8年平均CO2体积分数变化特征大体一致,每月（8年平均值）分布趋势也呈北部地区和东部地区高而南方体积分数值相对低的特征。CO2月平均体积分数的最高值一般出现在每年的4月或者5月,而每年的最低值则出现在每年的1月。对流层中层CO2体积分数呈现明显季节变化,总体上来说,从2003年到2010年这8年中,平均春、夏两季对流层中CO2含量较高,而秋、冬季CO2低于春夏两季。     

2003—2010年中国对流层CO2时空分布研究

利用2003年到2010年的美国宇航局(National Aeronautics and Space Administration,NASA)的AIRS(Atmosphere InfraRed Sounder)官方反演的对流层中层(500 hPa)左右一段气柱内的CO2体积混合比产品分析中国地区对流层的CO2体积分数分布时空变化特征。所用数据是对AIRS L3产品2°×2.5°网格数据进行处理分析得到。经过对这8年的观测数据(2003年1月—2010年12月)的数据分析研究发现:中国地区平均CO2的体积分数在空间分布上极不平衡,总体高值集中于北部。CO2对流层中层的高值区集中在35°—45°N,形成东北平原、内蒙古中西部地区、塔克拉玛干沙漠和塔里木盆地4个高值中心,而云南地区和西藏南部上空的CO2值偏低。与中国地区8年平均CO2体积分数变化特征大体一致,每月(8年平均值)分布趋势也呈北部地区和东部地区高而南方体积分数值相对低的特征。CO2月平均体积分数的最高值一般出现在每年的4月或者5月,而每年的最低值则出现在每年的1月。对流层中层CO2体积分数呈现明显季节变化,总体上来说,从2003年到2010年这8年中,平均春、夏两季对流层中CO2含量较高,而秋、冬季CO2低于春夏两季。     

Spatial and space-time scan statistics to detect low rate clusters of sex ratio

Whether general environmental exposures to endocrine disrupting chemicals (including pesticides and dioxin) might induce decreased sex ratios (male/female ratio at birth) is discussed. To address this issue, the authors looked for a space-time clustering test which could detect local areas of significantly low risk, assuming a Bernoulli distribution. As a matter of fact, if the endocrine disruptor hypothesis holds true, and if the sex ratio is a sentinel health event indicative of new reproductive hazards ascribed to environmental factors, then in a given region, either a cluster of low male/female ratio among newborn babies would be expected in the vicinity of polluting municipal solid waste incinerators (MSWIs) (supporting the dioxin hypothesis), or local clusters would be expected in some rural areas where large amounts of pesticides are sprayed. Among cluster detection tests, the spatial scan statistic has been widely used in various applications to scan for areas with high rates, and rarely (if ever) with low rates. Therefore, the goal of this paper was to check the properties of the scan statistics under a given scenario (Bernoulli distribution, search for clusters with low rates) and to assess its added value in addressing the sex ratio issue. This study took place in the Franche-Comté region (France), mainly rural, comprising three main MSWIs, among which only one had high dioxin emissions level in the past. The study population consisted of 192,490 boys and 182,588 girls born during the 1975–1999 period. On the whole, the authors conclude that: (i) spatial and space-time scan statistics provide attractive features to address the sex ratio issue; (ii) sex ratio is not markedly affected across space and does not provide a reliable screening measure for detecting reproductive hazards ascribed to environmental factors.     

The determinants of CO2 emissions in MENA countries: a responsiveness scores approach

This paper examines the relationship among carbon dioxide (CO₂) emissions, GDP, and energy in the Middle East and North Africa (MENA) countries by using a Responsiveness Scores (RS) approach. Empirical results over the period 1971–2013 suggest that GDP per capita and energy consumption show positive RSs, while trade and urban population negative ones. Moreover, energy consumption and urban population reveal moderate increasing returns to scale, while GDP per capita exhibits decreasing positive returns. Furthermore, three-way factors analysis sets out that most of the countries lays on regions with moderate negative Total Responsiveness Scores (TRS). This means that when all factors are jointly increased, CO₂ emissions have a moderate decrease. In addition, some GCC countries present a different pattern compared to the average pattern of MENA countries. Finally, radar plots indicate that, overall, RS pattern over factors is moderately heterogeneous within GCC countries, with larger variability appearing in the response to urban population and GDP.