Regional spatial inventories (cadastres) of GHG emissions in the Energy sector: Accounting for uncertainty

An improvement of methods for the inventory of greenhouse gas (GHG) emissions is necessary to ensure effective control of commitments to emission reduction. The national inventory reports play an important role, but do not reflect specifics of regional processes of GHG emission and absorption for large-area countries. In this article, a GIS approach for the spatial inventory of GHG emissions in the energy sector, based on IPCC guidelines, official statistics on fuel consumption, and digital maps of the region under investigation, is presented. We include mathematical background for the spatial emission inventory of point, line and area sources, caused by fossil-fuel use for power and heat production, the residential sector, industrial and agricultural sectors, and transport. Methods for the spatial estimation of emissions from stationary and mobile sources, taking into account the specifics of fuel used and technological processes, are described. Using the developed GIS technology, the territorial distribution of GHG emissions, at the level of elementary grid cells 2 km?×?2 km for the territory of Western Ukraine, is obtained. Results of the spatial analysis are presented in the form of a geo-referenced database of emissions, and visualized as layers of digital maps. Uncertainty of inventory results is calculated using the Monte Carlo approach, and the sensitivity analysis results are described. The results achieved demonstrated that the relative uncertainties of emission estimates, for CO₂ and for total emissions (in CO₂ equivalent), depend largely on uncertainty in the statistical data and on uncertainty in fuels’ calorific values. The uncertainty of total emissions stays almost constant with the change of uncertainty of N₂O emission coefficients, and correlates strongly with an improvement in knowledge about CH₄ emission processes. The presented approach provides an opportunity to create a spatial cadastre of emissions, and to use this additional knowledge for the analysis and reduction of uncertainty. It enables us to identify territories with the highest emissions, and estimate an influence of uncertainty of the large emission sources on the uncertainty of total emissions. Ascribing emissions to the places where they actually occur helps to improve the inventory process and to reduce the overall uncertainty.     

RMAPS_Chem V1.0系统SO2排放清单优化效果评估

RMAPS_Chem V1.0系统是基于WRF_Chem模式建立的服务于华北区域雾霾等污染预报业务的模式系统,该研究着重针对系统中污染排放清单不确定性带来的SO₂浓度预报偏差较大问题,采用EnKF源反演和误差统计订正相结合的方法对排放清单进行了改进,形成了一套优化后的华北区域SO₂排放清单。通过输入初始清单和优化清单对2017年10月进行模拟,并与华北地区616个地面环境监测站观测值进行对比,结果表明:EnKF源反演结合误差统计订正的排放清单优化方法适用于SO₂排放清单的改进,有效降低了清单系统性偏差,针对主要区域及重点城市的检验显示模拟结果接近观测值;排放清单优化后模拟误差显著降低,如河北南部、山东西部至北京一带模式预报均方根误差与归一化平均绝对误差明显下降,区域内站点模拟误差呈正态分布特征,误差分布范围、最大概率出现范围均明显变窄,且最大误差概率明显上升。     

Improving resolution of a spatial air pollution inventory with a statistical inference approach

This paper presents a novel approach to allocation of spatially correlated data, such as emission inventories, to finer spatial scales, conditional on covariate information observable in a fine grid. Spatial dependence is modelled with the conditional autoregressive structure introduced into a linear model as a random effect. The maximum likelihood approach to inference is employed, and the optimal predictors are developed to assess missing values in a fine grid. An example of ammonia emission inventory is used to illustrate the potential usefulness of the proposed technique. The results indicate that inclusion of a spatial dependence structure can compensate for less adequate covariate information. For the considered ammonia inventory, the fourfold allocation benefited greatly from incorporation of the spatial component, while for the ninefold allocation this advantage was limited, but still evident. In addition, the proposed method allows correction of the prediction bias encountered for the upper range emissions in the linear regression models.     

基于空气质量模拟的江苏省大气污染物排放清单比较研究

大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单，即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单"，并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明，除二氧化硫（SO₂）以外，江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较，发现两套清单对SO₂、氮氧化物（NO_x）、臭氧（O₃）和细颗粒物（PM_2.5）的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近，其中江苏省清单模拟的PM_2.5和O₃在长三角多数地区略低于长三角清单的模拟结果（1月O₃除外）.江苏省清单与长三角清单均能够用于空气质量模式模拟，可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.     

The establishment of the atmospheric emission inventories of the ESCOMPTE program

Within the frame of the ESCOMPTE program, a spatial emission inventory and an emission database aimed at tropospheric photochemistry intercomparison modeling has been developed under the scientific supervision of the LPCA with the help of the regional coordination of Air Quality network AIRMARAIX. This inventory has been established for all categories of sources (stationary, mobile and biogenic sources) over a domain of 19,600 km² centered on the cities of Marseilles–Aix-en-Provence in the southeastern part of France with a spatial resolution of 1 km². A yearly inventory for 1999 has been established, and hourly emission inventories for 23 days of June and July 2000 and 2001, corresponding to the intensive measurement periods, have been produced. The 104 chemical species in the inventory have been selected to be relevant with respect to photochemistry modeling according to available data. The entire list of species in the inventory numbers 216 which will allow other future applications of this database. This database is presently the most detailed and complete regional emission database in France. In addition, the database structure and the emission calculation modules have been designed to ensure a better sustainability and upgradeability, being provided with appropriate maintenance software. The general organization and method is summarized and the results obtained for both yearly and hourly emissions are detailed and discussed. Some comparisons have been performed with the existing results in this region to ensure the congruency of the results. This leads to confirm the relevance and the consistency of the ESCOMPTE emission inventory.     

Statistical dependence in input data of national greenhouse gas inventories: effects on the overall inventory uncertainty

An uncertainty assessment of the Austrian greenhouse gas inventory provided the basis for this analysis. We isolated the factors that were responsible for the uncertainty observed, and compared our results with those of other countries. Uncertainties of input parameters were used to derive the uncertainty of the emission estimate. Resulting uncertainty using a Monte Carlo approach was 5.2% for the emission levels of 2005 and 2.4 percentage points for the 1990–2005 emission trend. Systematic uncertainty was not assessed. This result is in the range expected from previous experience in Austria and other countries. The determining factor for the emission level uncertainty (not the trend uncertainty) is the uncertainty associated with soil nitrous oxide N₂O emissions. Uncertainty of the soil N₂O release rate is huge, and there is no agreement even on the magnitude of the uncertainty when country comparisons are made. In other words, reporting and use of N₂O release uncertainty are also different between countries; this is important, as this single factor fully determines a country’s national greenhouse gas inventory uncertainty. Inter-country comparisons of emission uncertainty are thus unable to reveal much about a country’s inventory quality. For Austria, we also compared the results of the Monte Carlo approach to those obtained from a simpler error propagation approach, and find the latter to systematically provide lower uncertainty. The difference can be explained by the ability of the Monte Carlo approach to account for statistical dependency of input parameters, again regarding soil N₂O emissions. This is in contrast to the results of other countries, which focus less on statistical dependency when performing Monte Carlo analysis. In addition, the error propagation results depend on treatment of skewed probability distributions, which need to be translated into normal distributions. The result indicates that more attention needs to be given to identifying statistically dependent input data in uncertainty assessment.     

水泥熟料生产企业CO2直接排放核算模型的建立

为快速掌握区域内全部水泥企业的碳排放情况,在部分企业实际生产数据未知时,也能建立其生产碳排放清单,文中基于熟料生产特征,构建了可根据设备设计产能和运行时长两种参数来核算企业CO2排放的数值模型.以京津冀地区59条典型水泥熟料生产线的生产数据作为统计样本,借助Eviews对生产线的实际产能、熟料烧成煤耗与设计产能间的关系...     

Investigating the Changes in Air Pollutant Emissions over the Beijing-Tianjin-Hebei Region in February from 2014 to 2019 through an Inverse Emission Method

In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei(BTH)region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ens...     

Comparison of the Anthropogenic Emission Inventory for CMIP6 Models with a Country-Level Inventory over China and the Simulations of the Aerosol Properties

Anthropogenic emission inventory for aerosols and reactive gases is crucial to the estimation of aerosol radiative forcing and climate effects.Here,the anthropogenic emission inventory for AerChemMIP,endorsed by CMIP6,is briefly introduced.The CMIP6 inventory is compared with a country-level inventory(i.e.,MEIC)over China from 1986 to 2015.Discrepancies are found in the yearly trends of the two inventories,especially after 2006.The yearly trends of the aerosol burdens simulated by CESM2 using the two inventories follow their emission trends and deviate after the mid-2000s,while the simulated aerosol optical depths(AODs)show similar trends.The difference between the simulated AODs is much smaller than the difference between model and observation.Although the simulated AODs agree with the MODIS satellite retrievals for country-wide average,the good agreement is an offset between the underestimation in eastern China and the overestimation in western China.Low-biased precursor gas of SO₂,overly strong convergence of the wind field,overly strong dilution and transport by summer monsoon circulation,too much wet scavenging by precipitation,and overly weak aerosol swelling due to low-biased relative humidity are suggested to be responsible for the underestimated AOD in eastern China.This indicates that the influence of the emission inventory uncertainties on simulated aerosol properties can be overwhelmed by model biases of meteorology and aerosol processes.It is necessary for climate models to perform reasonably well in the dynamical,physical,and chemical processes that would influence aerosol simulations.     

Quantitative quality assessment of the greenhouse gas inventory for agriculture in Europe

The greenhouse gas inventory of the European Communities and its estimation of the uncertainty is built from 15 individual and independent greenhouse gas inventories. This presents a particular challenge and is possible only if homogeneous information is available for all member states and if a proper evaluation of correlation between member states is performed. To this end, we present a methodology that estimates a quantitative measure for the aggregated Tier-level as well as the uncertainty for the main categories in the agriculture sector. In contrast to the approach suggested in the IPCC guidelines, which uses uncertainty estimates for activity data and emissions factors for each source category, the method presented uses quantitative information from individual parameters used in the inventory calculations, in combination with a well defined procedure to aggregate the information. Not surprisingly, N₂O emissions from agricultural soils are found to dominate the uncertainty. The results demonstrate the importance of correlation, if uncertainties are combined for the whole of Europe. The biggest challenge seems to be to conceptually harmonize the uncertainty estimates for the activity data (which tend to be underestimated) and emission factors (which tend to be overestimated).     

污染源反演对重点城市群夏季O3模拟的改进效果评估

在嵌套网格空气质量预报模式系统(NAQPMS)的基础上,采用污染源反演方法优化以中国多尺度排放清单(MEIC)为主的先验排放清单中臭氧(O₃)前体物排放量估计。分析时段为2019年6～8月,重点评估了污染源反演对我国“2+26”城市、长三角、珠三角、成渝4个重点城市群O₃模拟的改进效果。评估结果表明,污染源反演获得的“2+26”城市、长三角、珠三角的氮氧化物(NO_x)排放速率整体低于先验清单的排放速率约0.6μg m_-2 s_-1,但反演的挥发性有机物(VOCs)排放速率在“2+26”城市整体上高于先验清单的排放速率约0.5μg m_-2 s_-1。利用反演的NO_x和VOCs排放量和NAQPMS模式对4个城市群O₃进行模拟,发现反演排放数据可以显著改进夏季O₃模拟性能,使得O₃日最大8小时平均值(MDA8-O₃)模拟的均方根误差(R...     

Air quality modeling for the city of Graz

Summary Graz, a historical grown city in the south-east of Austria, sometimes faces problems with air pollution, mainly during wintertime. The old part of the city is the largest residentially used historical downtown in Central Europe. Due to its geographical position at the southeastern edge of the Alps, Graz often has weather situations with calm winds and strong inversions between October and March. The local wind system is marked by wind shears: near the surface, cold air flows in from the south, while in higher altitudes warm air from the north flows over the basin of Graz. During these winterperiods with mighty inversions air quality values exceed the threshold limits. The reason is that the old structure of the downtown area with narrow streets and a lot of old domestic heating systems in many of the old buildings causes relatively high pollution levels. In the winter of 1988/89, the NO₂ threshold values for smog-alarm (0.8 mg/m³, 3-h mean value) were exceeded several times at three air quality monitoring stations in the city of Graz. Therefore, a research project was initiated with the aim to find out the reasons for the bad air quality. The project comprised the setting up of an emission inventory as well as meteorological measurement campaigns and numerical simulations concerning the pollution dispersion in the area of Graz. The following report will try to show the interaction of the emission inventory on one hand and the determinations of flow conditions and pollutant dispersion on the other hand in order to analyze the air quality in the city. The emission inventory contains the emissions of air pollutants in a high temporal and spatial resolution. Before determining the surface flow fields, the meteorological conditions leading to the high pollution values were analyzed. After that, the boundary conditions were defined with the help of tethered balloon measurements. With these boundary conditions, quasi-steady-state flow fields were simulated. The dispersion of pollutants was calculated in a transient form using the stored flow fields. Conversion of pollutants was determined with the help of a parameterized version of the Eschenroeder-Martinez reaction mechanism. The period of winter 1990/91 with the highest pollution concentration was simulated to validate this model. The results show that the simulated and measured values of CO, NO and NO₂ correspond well with each other in the centre of the city, while the correspondence is not as good in the outskirts of the city were lower pollution levels are observed. It turned out that the suggested methodology is well suited for analyzing winter situations with high pollution levels.With 10 Figures     

国土空间总体规划温室气体核算模型

城市的低碳发展对于应对气候变化及实现我国“碳达峰、碳中和”目标起着至关重要的作用。在新的国土空间规划体系下,国土空间总体规划对城市的低碳发展影响重大。为解决现有的城市温室气体核算中存在的问题,使总体规划促进城市低碳发展,构建了国土空间总体规划温室气体核算模型。该模型基于“空间布局—用地类型—部门划分—模型方法”的框架,采用自上而下与自下而上相结合的方法,与国土空间规划要素紧密结合;建立了市域和中心城区两个层次的碳排放核算方法,并解决了中心城区的碳排放核算问题,可进行国际间比较;解决了总体规划能源预测不完善的问题,提出了不同的核算方法供灵活选择,与完全基于用地类型的方法相比,降低了不确定性。最后基于模型提出了评估总体规划低碳发展水平的核心指标与参考指标。     

Development of Emission Models and Improvement of Emission Data for Germany

Measurements and model developments with the objective to improve the quality and resolution of estimations of anthropogenic emissions are described. Measurement results on a chassis dynamometer were used to determine VOC profiles for exhaust gas emissions of passenger cars for different vehicle and fuel types and different driving modes. Further measurements resulted in emission factors and VOC profiles for lignite burning in residential stoves. Using remote sensing techniques benzene emission factors of gas stations and the efficiency of gasoline vapour recovery systems were measured.To improve the quality and the spatial and temporal resolution of emission data, emission models were improved or modified. This was done by elaborating and applying new methods for important emission source categories (e.g., solvent use, road traffic, small combustion) as well as including new data sources in the calculation routines (e.g. emission statements, land use data, import/export indices of solvents). Simultaneously considerable progress was made improving temporal and spatial allocation functions and VOC profiles. With these improvements a large number of anthropogenic emission data sets for 14 different grid projections in Germany and Europe have been generated. An emission scenario for Germany for 2010 suggests that considering air quality directives from the EU and Germany which are in force or in pipeline, German emissions of VOC and NO_x will decrease, but still exceed the national emission ceilings of the EU-NEC directive.     

Evaluation of Modeled Spatially and Temporarily Highly Resolved Emission Inventories of Photosmog Precursors for the City of Augsburg: The Experiment EVA and Its Major Results

Emission inventories of NO_x, CO, and individual volatile organic compounds (VOC), highly resolved in space and time, belong to the most important input parameters for chemistry and transport models (CTM) used for ozone prediction. Because of the decisive influence of the input quality on the outcome of CTM simulations, the quality of emission inventories has to be assessed. This paper presents an experimental evaluation of the highly resolved emission inventories for the city of Augsburg. The emissions of the city, determined in March and October 1998 using mass balance and tracer techniques, and derived from the measured receptor concentration ratios, were compared with emissions modeled from an emission inventory. The modeled CO emissions were in agreement with the measured ones within the combined experimental and model uncertainties. More detailed CO emission model simulations suggest that the tendency of calculated CO emissions being smaller than the measured ones may be due to higher traffic activity in Augsburg. Modeled NO_x emissions were in agreement with the measured ones within the combined experimental and model uncertainties. Large deviations between modeled and measured values have been found for some individual NMHC compounds. The measured NMHC emission fingerprints were dominated by mobile sources. Substantial model predicted NMHC emissions from the solvent use could not be detected by measurements suggesting that they may not be correctly represented by the emission model.     

An evaluation of air quality modeling over the Pearl River Delta during November 2006

In this paper, we evaluate the performance of several air quality models using the Pearl River Delta (PRD) region, including the Nested Air Quality Prediction Modeling System (NAQPMS), the Community Multiscale Air Quality (CMAQ) model, and the Comprehensive Air Quality Model with extensions (CAMx). All three model runs are based on the same meteorological fields generated by the Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) and the same emission inventories. The emission data are processed by the Sparse Matrix Operator Kernel Emissions (SMOKE) model, with the inventories generated from the Transport and Chemical Evolution over the Pacific/Intercontinental Chemical Transport Experiment Phase B (TRACE-P/INTEX-B) and local emission inventory data. The results show that: (1) the meteorological simulation of the MM5 model is reasonable compared with the observations at the regional background and urban stations. (2) The models have different advantages at different stations. The CAMx model has the best performance for SO₂ simulation, with the lowest mean normalized bias (MNB) and mean normalized error (MNE) at most of the Guangzhou stations, while the CMAQ model has the lowest normalized mean square error (NMSE) value for SO₂ simulation at most of the other PRD urban stations. The NAQPMS model has the best performance in the NO₂ simulation at most of the Guangzhou stations. (3) The model performance at the Guangzhou stations is better than that at the other stations, and the emissions may be underestimated in the other PRD cities. (4) The PM₁₀ simulation has the best model measures of FAC2 (fraction of predictions within a factor of two of the observations) (average 53–56%) and NMSE (0.904–1.015), while the SO₂ simulation has the best concentration distribution compared with the observations, according to the quantile–quantile (Q–Q) plots.     

Reconstruction of Quaternary temperature fields by dynamically consistent smoothing

Conventional methods of palaeoclimate reconstruction provide estimates of climatic parameters using proxy data which have originated from individual sites. These reconstructions yield information on the local environment but only limited information on spatial scales that are required for model-data intercomparisons. We present here a new approach that connects these different scales by an upscaling of the local palaeoinformation together with a dynamically consistent spatial smoothing. A probabilistic data-based method for local reconstructions is combined with a dynamic constraint on the reconstructed climate parameter which stabilises the reconstruction on the target scale. The variational analysis leads to climatological fields being optimised with respect to the proxy data and to the prescribed dynamics in a statistically consistent way. This method allows a probabilistic approach of quality control of the palaeodata in terms of their spatial consistency and homogeneity and for an estimation of reconstruction errors. The method was applied to palaeobotanical data to reconstruct near-surface temperature fields constrained by simple linear dynamics. An approximate approach was used to estimate the magnitude of reconstruction errors in terms of standard deviations. Reconstructed January and July mean temperature of the early Eemian (∼ 125,000 years bp) have errors with a median value of about 1.8°C in January and about 1.1°C in July. Reconstructions across Europe show positive temperature anomalies for Scandinavia and near the East coast of the Baltic Sea. In contrast, early Eemian temperatures were apparently quite similar to those found today in Central Europe, as no drastic differences were reconstructed between the Eemian and modern (1961–1990) climate. This implies somewhat stronger temperature gradients in the Eemian than are observed today. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

南京和长三角地区CO_2与CH_4人为排放清单估算的不确定性分析

目前温室气体清单的编制主要基于IPCC方法,该方法用于特定城市或区域清单编制时可能会引起较大的不确定性,而目前对城市/区域尺度清单的不确定性的分析还存在很大的欠缺。本文通过南京市和长三角温室气体排放因子甄选,应用IPCC方法计算了2009年南京市和长三角的人为温室气体排放量,并以其为个例利用蒙特卡洛方法开展城市和区域尺度的温室气体人为排放清单不确定性的初步探究。研究结果表明:南京市CH4和CO2排放量的95%的概率分布范围分别为(1.08~1.86)×105t和(6.50~7.41)×107t,不确定性分别为-21.74%~34.78%和-7.01%~5.87%;长三角CH4和CO2排放量的95%的概率分布范围分别为(4.07~5.89)×106t和(1.62~1.82)×109t,不确定性分别为-15.60%~22.24%和-6.04%~5.34%。     

Uncertainty of forest carbon stock changes – implications to the total uncertainty of GHG inventory of Finland

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of the efforts needed for development of the inventory. This paper presents an uncertainty analysis of GHG emissions of all Kyoto sectors and gases for Finland consolidated with estimates of emissions/removals from LULUCF categories. In Finland, net GHG emissions in 2003 were around 69 Tg (±15 Tg) CO₂ equivalents. The uncertainties in forest carbon sink estimates in 2003 were larger than in most other emission categories, but of the same order of magnitude as in carbon stock change estimates in other land use, land-use change and forestry (LULUCF) categories, and in N₂O emissions from agricultural soils. Uncertainties in sink estimates of 1990 were lower, due to better availability of data. Results of this study indicate that inclusion of the forest carbon sink to GHG inventories reported to the UNFCCC increases uncertainties in net emissions notably. However, the decrease in precision is accompanied by an increase in the accuracy of the overall net GHG emissions due to improved completeness of the inventory. The results of this study can be utilised when planning future GHG mitigation protocols and emission trading schemes and when analysing environmental benefits of climate conventions.     

Determination of the uncertainties of the German emission inventories for particulate matter and aerosol precursors using Monte-Carlo analysis

This paper presents the application of a Monte-Carlo simulation for assessing the uncertainties of German 2005 emissions of particulate matter (PM₁₀ & PM_2.5) and aerosol precursors (SO₂, NO_x, NH₃ and NMVOC) carried out in the PAREST (PArticle REduction STrategies) research project. For the uncertainty analysis the German Federal Environment Agency’s emission inventory was amended and integrated with a model on the disaggregation of energy balance data. A series of algorithms was developed in order to make efficient and pragmatic use of available literature and expert judgement data for uncertainties of emission model input data. The inventories for PM₁₀ (95 %-confidence interval: ?16 %/+23 %), PM_2.5 (?15 %/+19 %) and NO_x (?10 %/+23 %) appear most uncertain, while the inventories for SO₂ (?9 %/+9 %), NMVOC (?10 %/+12 %) and NH₃ (?13 %/+13 %) show a higher accuracy. The source categories adding the most relevant contributions to overall uncertainty vary across the pollutants and comprise agriculture, mobile machinery in agriculture and forestry, construction sites, small businesses/carpentries, cigarette smoke and fireworks, road traffic, solvent use and stationary combustion. The PAREST results on relative uncertainties have been quoted in the German Informative Inventory Reports since 2012. A comparison shows that the PAREST results for Germany are within the range of (for NH₃: close below) other European countries’ results on air pollutant inventory uncertainties as reported in the 2013 Informative Inventory Reports.