Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Contribution of different sectors to developed countries’ fulfillment of GHG emission reduction targets under the first commitment period of the Kyoto Protocol

Greenhouse gas (GHG) data submitted in April 2014 on land use, land use change and forestry (LULUCF), energy, industrial processes, solvents and other product use, agriculture, and waste for 37 developed countries was analyzed to estimate the relative contributions of different sectors to GHG emission reductions. This GHG data from the first commitment period of the Kyoto Protocol included 35 parties to Annex B of the Kyoto Protocol, the United States and Canada. Results show that the contribution of each sector was, in order: energy (36.9%), industrial processes (12.4%), agriculture (9.9%), LULUCF (7.7%), waste (3.4%), and solvents and other product use (0.1%). The average proportion of base year emissions reduced in each sector by countries in Annex B was, in order: energy (7.4%), agriculture (2.7%), LULUCF (1.9%), industrial processes (1.2%), waste (0.5%), and solvents and other product use (0.1%). Overall, the energy sector contributed the highest GHG emission reductions, while the agriculture and LULUCF sectors also made contributions. Most countries achieved limited absolute GHG reductions from their chosen LULUCF activities, but the relative contribution of GHG emission reductions from LULUCF was significant but small. This suggests that, unless there are substantial changes to accounting rules, future emission reductions will mainly result from mitigation actions targeting fossil fuel consumption, while the agriculture and LULUCF sectors will continue to play auxiliary roles.     

Errors and uncertainties in a gridded carbon dioxide emissions inventory

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO₂), gridded EI Open-source Data Inventory for Anthropogenic CO₂ (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges.

     

广东电力生产的温室气体排放趋势和演变特征

通过文献调研收集广东电力生产最新的能源消费数据和排放因子,采用“自上而下”方法估算1995—2011年广东电力行业的直接和间接GHG(温室气体)排放量,量化直接排放量的不确定性,绘制GHG排放流向图,并且根据GHG排放特征提出减排建议. 结果表明:①虽然受经济、环境和能源政策的影响,与1995年相比,2011年广东电力生产的GHG总排放量仍增长438%,达3.44×108 t,其中直接排放量达2.78×108 t,不确定性为±11%. ②从发电能源结构角度考虑,燃煤发电是电力生产的最大GHG排放源,2011年其排放量占总排放量的76%;而从用电终端考虑,工业用电是最大的GHG排放源,2011年其排放量占电力生产GHG总排放量的66%. ③1995—2011年,用电终端总体电力GHG排放强度下降了16%,居民用电人均GHG排放量上升了260%,单位综合发电量的GHG排放系数微升了1%. ④发电能源结构和终端产业结构的低碳化以及控制居民用电的GHG排放量等措施可减排2011年广东电力生产GHG总排放量的44%.      

NOx and SOx emissions from fossil fuels: A global distribution

This paper presents a global database of annual NO_x and SO_x emissions from fossil fuel combustion at a 1° resolution. The annual emissions estimates were based on fuel consumption for individual countries and are distributed according to human population within each country. There is a large spatial variability in the distribution of these emissions with over 90% of each gas being emitted in the Northern Hemisphere. It is expected that the estimates of NO_x and SO_x emissions will be useful for global and regional chemical transport simulations. The database is available from the author for this purpose.     

Quantification of energy related industrial eco-efficiency of China

Improving eco-efficiency is propitious for saving resources and reducing emissions, and has become a popular route to sustainable development. We define two energy-related eco-efficiencies: energy efficiency (ENE) and greenhouse gas (GHG) emission-related eco-efficiency (GEE) using energy consumption and the associated GHG emissions as the environmental impacts. Using statistical data, we analyze China’s energy consumption and GHG emissions by industrial subsystem and sector, and estimate the ENE and GEE values for China in 2007 as 4.871×10⁷ US/PJ and 4.26×10 < sup > 8 < /sup > US/PJ and 4.26×10⁸ US/TgCO₂eq, respectively. Industry is the primary contributing subsystem of China’s economy, contributing 45.2% to the total economic production, using 79.6% of the energy consumed, and generating 91.4% of the total GHG emissions. We distinguish the individual contributions of the 39 industrial sectors to the national economy, overall energy consumption, and GHG emissions, and estimate their energyrelated eco-efficiencies. The results show that although ferrous metal production contributes only 3.5% to the national industrial economy, it consumes the most industrial energy (20% of total), contributes 16% to the total industrial global warming potential (GWP), and ranks third in GHG emissions. The power and heat sector ranks first in GHG emissions and contributes one-third of the total industrial GWP, although it only consumes about 8% of total industrial energy and, like ferrous metal production, contributes 3.5% to the national economy. The ENE of the ferrous metal and power and heat sectors are only 8 and 2.1×10⁷ US/PJ, while the GEE for these two sectors are 9 and 4×10 < sup > 4 < /sup > US/PJ, while the GEE for these two sectors are 9 and 4×10⁴ US/GgCO₂eq, respectively; these are nearly the lowest ENE and GEE values among all 39 industry sectors. Finally, we discuss the possibility of ecoefficiency improvement through a comparison with other countries.     

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO₂, CH₄, N₂O, SO₂, NMVOC) as well as total emissions in the CO₂-equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.

     

Managing the nitrogen cycle to reduce greenhouse gas emissions from crop production and biofuel expansion

Public policies are promoting biofuels as an alternative to fossil fuel consumption in order to mitigate greenhouse gas (GHG) emissions. However, the mitigation benefit can be at least partially compromised by emissions occurring during feedstock production. One of the key sources of GHG emissions from biofuel feedstock production, as well as conventional crops, is soil nitrous oxide (N₂O), which is largely driven by nitrogen (N) management. Our objective was to determine how much GHG emissions could be reduced by encouraging alternative N management practices through application of nitrification inhibitors and a cap on N fertilization. We used the US Renewable Fuel Standards (RFS2) as the basis for a case study to evaluate technical and economic drivers influencing the N management mitigation strategies. We estimated soil N₂O emissions using the DayCent ecosystem model and applied the US Forest and Agricultural Sector Optimization Model with Greenhouse Gases (FASOMGHG) to project GHG emissions for the agricultural sector, as influenced by biofuel scenarios and N management options. Relative to the current RSF2 policy with no N management interventions, results show decreases in N₂O emissions ranging from 3 to 4 % for the agricultural sector (5.5–6.5 million metric tonnes CO₂?eq.?year^?1; 1 million metric tonnes is equivalent to a Teragram) in response to a cap that reduces N fertilizer application and even larger reductions with application of nitrification inhibitors, ranging from 9 to 10 % (15.5–16.6 million tonnes CO₂?eq.?year^?1). The results demonstrate that climate and energy policies promoting biofuel production could consider options to manage the N cycle with alternative fertilization practices for the agricultural sector and likely enhance the mitigation of GHG emissions associated with biofuels.     

Full accounting of the greenhouse gas budget in the forestry of China

Forest management to increase carbon (C) sinks and reduce C emissions and forest resource utilization to store C and substitute for fossil fuel have been identified as attractive mitigation strategies. However, the greenhouse gas (GHG) budget of carbon pools and sinks in China are not fully understood, and the forestry net C sink must be determined. The objective of this study was to analyze potential forest management mitigation strategies by evaluating the GHG emissions from forest management and resource utilization and clarify the forestry net C sink, and its driving factors in China via constructing C accounting and net mitigation of forestry methodology. The results indicated that the GHG emissions under forest management and resource utilization were 17.7 Tg Ce/year and offset 8.5% of biomass and products C sink and GHG mitigation from substitution effects from 2000 to 2014, resulting in a net C sink of 189.8 Tg Ce/year. Forest resource utilization contributed the most to the national forestry GHG emissions, whereas the main driving factor underlying regional GHG emissions varied. Afforestation dominated the GHG emissions in the southwest and northwest, whereas resource utilization contributed the most to GHG emissions in the north, northeast, east, and south. Furthermore, decreased wood production, improved product use efficiency, and forests developed for bioenergy represented important mitigation strategies and should be targeted implementation in different regions. Our study provided a forestry C accounting in China and indicated that simulations of these activities could provide novel insights for mitigation strategies and have implications for forest management in other countries.     

Energy efficiency and reduction of Co2 emissions through 2015: The Brazilian cement industry

The cement industry is characterisedby intensive energy consumption throughout itsproduction stages which, together with the calcinationof its raw materials, accounts for significant amountsof greenhouse gases (GHG) emissions. In 1996, theBrazilian cement industry consumed 4.3% of the energyrequired by the industrial sector, contributing over22 Tg (Teragrams) of CO₂. The prospects forgrowth in this sector in Brazil indicate risingdemands for fossil fuels, with a consequent upsurge inemissions. This article aims to present the prospectsfor energy conservation in the Brazilian cementindustry through to 2015, taking into account: theintroduction of new production technologies in thissector, the use of waste and low-grade fuels,cogeneration, the use of cementitious materials, andother measures, based on a technical and economicenergy demand simulation model. In all scenarios, wefound that is possible to significantly reduce energyconsumption and CO₂ emissions for BrazilianCement Industry. Under the market potential scenarios,energy savings vary between 1562.0 to 1900.6 PJ(PetaJoules), with use of cementitious materialsaccounting for around 31% of this total. Fortechnical potential scenarios, use of cementitiousmaterials could represent 51% to 52% of totalachieved energy savings, between 2374.6 to 2803.4 PJ.     

Recent Trends in Residential Energy Use in OECD Countries and their Impact on Carbon Dioxide Emissions: A Comparative Analysis of the Period 1973–1992

In the late 1970s and for most of the 1980s, residential energy use in the OECD underwent significant changes. Many of these changes were a result of more efficient energy use in response to higher energy prices, energy efficiency programs, and the appearance of new technologies for saving energy. This study analyzes these changes and the impact of energy use on carbon emissions in the residential sector for nine OECD countries for the period from 1973 to 1992. The major findings of this analysis are:

1. CO₂ emissions per capita were lower in 1992 in almost all of the countries we studied;
2. The two primary changes were improvements in energy efficiency and a decrease in the share of fossil fuels used for electricity and district heating production;
3. The main source of growth in emissions from residential energy use was increased ownership of electric appliances, where, in spite of important improvements in energy efficiency, ownership grew so rapidly that electricity use (and subsequent emissions) increased;
4. Changes in fuel mix, including both the changes in the share of fuels used in households and the share of fuels used to generate electricity and district heating, led to a decrease in emissions in the nine countries;
5. Increasing the efficiency of electric appliances and further reductions in the intensity of space heating are probably the key elements in a strategy to improve efficiency as a means to lowering CO₂ emissions.

     

江浙沪地区能源及转化业温室气体排放及减排措施

根据ＩＰＣＣ提供的方法，对１９９０年江浙沪地区能源及转化业中能源的消耗量和温室气体的排放进行了统计计算，对数据进行了进一步的评价和分析，江浙沪地区能源及转化业能源消耗中固体燃料占８１．７％，液体燃料占１５．４％，气体燃料占２．９％，该地区该部门燃料消耗中温室气体排放为ＣＯ２：８８７３７Ｇｇ，ＣＨ４：０．８４９８Ｇｇ，Ｎ２Ｏ：５．８２４Ｇｇ。针对能源及转化业部门的具体情况提出了相应的减排措施。     

The greenhouse gas intensity of the tourism sector: The case of Switzerland

Greenhouse gas intensity is a ratio comparing the greenhouse gas (GHG) emissions of an activity or economic sector to the economic value it generates. In recent years, many countries have calculated the GHG intensity of their economic sectors as a basis for policy making. The GHG intensity of tourism, however, has not been determined since tourism is not measured as an economic sector in the national accounts. While for tourism-reliant countries it would be useful to know this quantity, a number of difficulties exist in its determination. In this study, we determine the GHG intensity of tourism's value added in Switzerland by means of a detailed bottom-up approach with the main methodological focus on how to achieve consistent system boundaries. For comparison, we calculate the tourism sector's GHG intensity for selected European countries using a simpler top-down approach. Our results show that the Swiss tourism sector is more than four times more GHG intensive than the Swiss economy on average. Of all tourism's sub-sectors, air transport stands out as the sector with by far largest emissions (80%) and highest GHG intensity. The results for other countries make similar, if not as pronounced, patterns apparent. We discuss the results and possible mitigation options against the background of the goal to prevent dangerous climate change.     

Forgotten carbon: indirect CO2 in greenhouse gas emission inventories

National governments that are Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to submit greenhouse gas (GHG) inventories accounting for the emissions and removals occurring within their geographic territories. The Intergovernmental Panel on Climate Change (IPCC) provides inventory methodology guidance to the Parties of the UNFCCC. This methodology guidance, and national inventories based on it, omits carbon dioxide (CO₂) from the atmospheric oxidation of methane, carbon monoxide, and non-methane volatile organic compounds emissions that result from several source categories. The inclusion of this category of “indirect” CO₂ in GHG inventories increases global anthropogenic emissions (excluding land use and forestry) between 0.5 and 0.7%. However, the effect of inclusion on aggregate UNFCCC Annex I Party GHG emissions would be to reduce the growth of total emissions, from 1990 to 2004, by 0.2% points. The effect on the GHG emissions and emission trends of individual countries varies. The paper includes a methodology for calculating these emissions and discusses uncertainties. Indirect CO₂ is equally relevant for GHG inventories at other scales, such as global, regional, organizational, and facility. Similarly, project-based methodologies, such as those used under the Clean Development Mechanism, may need revising to account for indirect CO₂.     

固体废物焚烧处置及其清洁发展机制

包含化石碳(如塑料等)在内的废物焚烧处置和露天燃烧是废物部门中最重要的CO₂排放来源之一. 在全国节能减排大背景下,废物焚烧发电成为温室气体减排的有效途径. 对我国固体废物焚烧处置现状及趋势进行了分析,同时研究了国内城市固体废物和危险废物焚烧的区域特征. 结果表明:随着经济发展和废物产生量的急剧增长,废物焚烧处置技术必将成为我国未来固体废物处置的主要方式;伴随着废物焚烧行业的发展,有大量项目可以注册CDM (清洁发展机制)项目,可为温室气体减排做出较大的贡献.      

广东货船水运的温室气体排放和低碳发展对策

作为我国港口大省和低碳试点省,广东需先行测算船舶水运的GHG(温室气体)排放量基线,以探究低碳水运对策. 通过文献调研收集适用数据和资料,基于引擎功率法,测算了广东抵港货船在2010年的GHG排放量. 结果表明:广东专属经济区海域内货船水运的GHG总排放量为2887×104t,不确定性在-36%~45%之间,其中在领海区域内的排放量为730×104t;远洋集装箱船是GHG最大排放源,占总排放量的43%;集装箱船、干散货船、油轮和其他货船的GHG排放量不确定性均介于-30%~50%之间,远洋货船的主引擎在正常航行模式下输出功率是最主要的不确定性源. 基于分析船舶水运的GHG排放特征,提出船舶减速、向远洋货船供应岸电和内河货船主引擎转用天然气共3项低碳节能措施,共可减排40%的GHG排放量.该研究结果不仅为广东低碳水运发展提供基础性的GHG排放数据,也可为其他港口地区提供估算水运业GHG排放量的技术方法参考和实践经验.      

基于LCA的北京市公交车节能及温室气体减排潜力分析

新能源公交车是未来城市公交行业节能及温室气体减排的重点发展方向.新能源公交车在行驶阶段具有良好的节能及温室气体减排效果,而汽车制造、能源生产等相关生命周期阶段的能耗及温室气体排放常被忽视,且目前新能源公交车的乘客运载功能相对较弱,可能对节能及温室气体减排的潜力造成较为显著的影响.因此,本文基于北京市公交车的运营特征,采用生命周期评价(LCA)方法,选择客运周转量作为功能单位,核算了天然气公交车、混合动力公交车和纯电动公交车等新能源公交车相对于柴油公交车的节能及温室气体减排效益.结果表明:发展新能源公交车对促进北京市公交行业及城市节能低碳发展具有积极的作用,但相对于基于运营里程的核算结果,本研究新能源公交车节能及温室气体减排潜力均较低,主要原因是新能源公交车的实际载客量相对较低;混合动力公交车和纯电动公交车在空调开启时的节能潜力与温室气体减排潜力均远低于天然气公交车;通过发展情景分析,建议北京市现阶段应优先发展天然气公交车,适当发展纯电动公交车和混合动力公交车,以减少北京市公交车的总体能耗,同时降低温室气体排放强度.     

中国区域反应性气体排放源清单

反应性气体是形成气溶胶及酸雨、光化学烟雾等环境问题的重要前体物,采用政府部门公布的基础数据(包括社会－经济数据、化石燃料和生物质燃料消耗、废物处理数据等,绝大部分为县级水平)及一些较新的、中国特有的排放因子,计算了中国大陆2007年高时空分辨率的关键反应性气体SO2、NOx、CO、NH3、VOCs的排放源清单.计算出的全国和各地区的排放量使用了0.5°×0.5°的网格来显示,结果表明,各反应性气体的估算年排放量分别为:SO2 3158.4万t,主要是燃煤所致;NOx、CO分别为2492.6,15785.2万t,均主要来源于燃煤和生物质燃烧;NH3 1601.7万t,主要源于动物排放和农田化肥的使用;VOCs 3709.8万t,主要源于溶剂挥发、废物处理、交通源等.本研究计算的排放结果比以前的清单稍高,主要是由于部分排放量以前被低估了;东部地区的排放量比西部高.反应性气体的排放具有较强的季节性,主要是由于自然因素及居民采暖、农业秸秆的露天焚烧的季节性等所致.     

基于投入产出法的北京能源消耗温室气体排放清单分析

城市是一个巨大能源物资消耗体和温室气体排放体,相关研究受到广泛关注.本文以2007年为例基于投入产出法研究北京市能源消耗的温室气体排放量,计算得出CH4和N2O这两种常规温室气体排放量.结果表明,北京市2007年能源消耗温室气体排放量为3531.72万tCO2当量,其中CO2排放量为3514.40万t,CH4排放量为1734.32t,N2O排放量为435.83t.北京市工业部门仍然是主要的温室气体排放部门,其排放的温室气体占CO2总量的98.96%,CH4总量的88.48%和N2O总量的98.99%.不同最终使用部门中,政府部门消费产生的温室气体排放量超过总量的15%,高于城镇消费和农村消费之和;调出和出口部门的碳排放量超过总量的40%,所占比例最大.贸易中,隐含在调出和出口部门中温室气体排放量是隐含在调入和进口部门的十几倍.北京市不同行业的温室气体排放强度略优于全国水平.降低北京市温室气体排放量可从进一步优化产业结构,发挥科技减排的作用,提高不同产业的能源利用率等方面采取措施.