A statistical model for spatial inventory data: a case study of N2O emissions in municipalities of southern Norway

In this paper we apply a linear regression with spatial random effect to model geographically distributed emission inventory data. The study presented is on N₂O emission assessments for municipalities of southern Norway and on activities related to emissions (proxy data). Taking advantage of the spatial dimension of the emission process, the method proposed is intended to improve inventory extension beyond its earlier coverage. For this, the proxy data are used. The conditional autoregressive model is used to account for spatial correlation between municipalities. Parameter estimation is based on the maximum likelihood method and the optimal predictor is developed. The results indicate that inclusion of a spatial dependence component lead to improvement in both representation of the observed data set and prediction.     

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.     

2006—2017年安徽省人为源氨排放清单及特征

基于排放因子法建立了2006-2017年安徽省人为源氨排放清单,估算人为源氨的排放水平、变化趋势及其分布特征。结果表明,安徽省2017年人为源氨排放量较高的两个地区是阜阳市和六安市,而氨排放总量最小的是马鞍山,占全省氨排放总量的1.83%。安徽省氨平均排放强度为5.34 t·km^-2,其中阜阳市、淮南市及蚌埠市的排放强度均超过7 t·km^-2。2006-2017年畜禽养殖源产生的氨排放量处于增加状态,尤其是肉猪、肉鸡和肉鸭的贡献分别占到畜禽源氨排放总量的34.49%~38.39%、20.31%~32.8%和10.40%~16.42%。而氮肥施用导致的氨排放量表现出先增加后下降的趋势,2017年产生的氨排放量比2013年下降了28.71 kt。生物质燃烧、人体排放和氮肥生产是非农业源氨排放的主要来源,但由机动车产生的氨的贡献呈明显增长趋势,如从2006年的1.86%增长到2017年的7.47%,这与近年来安徽省汽车保有量不断增加有关。     

Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables

The current study examines the recently proposed “bias correction and stochastic analogues” (BCSA) statistical spatial downscaling technique and attempts to improve it by conditioning coarse resolution data when generating replicates. While the BCSA method reproduces the statistical features of the observed fine data, this existing model does not replicate the observed coarse spatial pattern, and subsequently, the cross-correlation between the observed coarse data and downscaled fine data with the model cannot be preserved. To address the dissimilarity between the BCSA downscaled data and observed fine data, a new statistical spatial downscaling method, “conditional stochastic simulation with bias correction” (BCCS), which employs the conditional multivariate distribution and principal component analysis, is proposed. Gridded observed climate data of mean daily precipitation (mm/day) covering a month at 1/8° for a fine resolution and at 1° for a coarse resolution over Florida for the current and future periods were used to verify and cross-validate the proposed technique. The observed coarse and fine data cover the 50-year period from 1950 to1999, and the future RCP4.5 and RCP8.5 climate scenarios cover the 100-year period from 2000 to 2099. The verification and cross-validation results show that the proposed BCCS downscaling method serves as an effective alternative means of downscaling monthly precipitation levels to assess climate change effects on hydrological variables. The RCP4.5 and RCP8.5 GCM scenarios are successfully downscaled.     

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.     

Effects of regional temperature,wind speed and soil wetness on spatial structure of surface air temperature

Summary Climate parameters are usually collected on some grid or pattern that is supposed to represent the unobserved neighborhood. Spatial dependence is a measure of the extent to which observed data represent the unobserved neighborhood. Geostatistical analyses provide procedures for measuring spatial dependence. In this study, semivariograms were estimated from hourly observations of screen-height air temperature obtained from a dense meteorological observation network. The range and spatial component normalized by the sill were estimated from the semivariogram in order to obtain information on the spatial structure of the air temperature. Zones of spatial correlation were delineated, using the range of the semivariogram. Scales of spatial correlation depended on the regional mean air temperature and regional wetness at the ground. The range or spatial scale for data collected in winter was larger than those in summer. The range under wet conditions was larger than under dry conditions. Effects of regional wind speed on range were different, depending on the regional mean air temperature. The normalized spatial component was used as an index for measuring continuities on the interpolation surface. The normalized spatial component generally increased as the range increased.With 5 Figures     

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as ‘field’ or ‘global’ significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ^° grid resolution. Daily precipitation climatology for the 1990–2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.     

北京市高分辨率CO2排放清单研究

CO2排放清单是推动城市低碳发展的重要基础工作.文中采用自下而上和自上而下相结合的方法测算了2017年北京市CO2排放清单.自下而上方面,基于近13000座锅炉数据核算了CO2排放量.自上而下方面,利用改编后的北京市分行业分品种能源消费表对自下而上核算的分行业能源消费数据进行校验,从宏观上控制核算数据的系统误差.研究发...     

Downscaling drivers of global environmental change: Enabling use of global SRES scenarios at the national and grid levels

Global environmental change scenarios typically distinguish between about 10–20 global regions. However, various studies need scenario information at a higher level of spatial detail. This paper presents a set of algorithms that aim to fill this gap by providing downscaled scenario data for population, gross domestic product (GDP) and emissions at the national and grid levels. The proposed methodology is based on external-input-based downscaling for population, convergence-based downscaling for GDP and emissions, and linear algorithms to go to grid levels. The algorithms are applied to the IPCC-SRES scenarios, where the results seem to provide a credible basis for global environmental change assessments.     

An advection scheme based on the combination of particle mesh method and pure Lagrangian approach

Possibility of using pure Lagrangian approach in modeling transport phenomena is described in this paper. The application of pure Lagrangian approach in real atmospheric field induces highly irregular spatial distribution of grid points, after only a few time steps. In order to avoid problems caused by that irregularity, a quasi interpolation procedure is proposed. Proposed interpolation procedure is similar to the radial basis functions interpolation and does not impose any demands about spatial distribution of the grid points or about continuity and differentiability of the field that needs to be interpolated. Besides that, proposed procedure is explicitly mass conserving. Combination of particle mesh method and pure Lagrangian approach creates efficient transport scheme that does not produce any new local maxima and minima in advected field. In proposed advection scheme motion of points are performed in Lagrangian manner while spatial derivatives are evaluated on the basis of values interpolated onto regular grid. Applicability of proposed advection scheme in an unambiguous way is proved by performing “standard” numerical tests with (i) the slotted cylinder under solid body rotation, (ii) the test with Doswell’s idealized cyclogenesis as well as (iii) integration of shallow water equations.     

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.     

Present climate simulation over Korea with a regional climate model using a one-way double-nested system

Summary This study investigates the capability of the regional climate model RegCM3 to simulate surface air temperature and precipitation over the Korean Peninsula. The model is run in one-way double nested mode, with a 60 km grid point spacing “mother” domain encompassing the eastern regions of Asia and a 20 km grid point spacing nested domain covering the Korean Peninsula. The simulation spans the three-year period of 1 October 2000 through 30 September 2003 and the boundary conditions needed to run the mother domain experiment are provided from the NCEP reanalysis of observations. The model results are compared with a high density station observation dataset to examine the fine scale structure of the surface climate signal. The model shows a good performance in capturing both the sign and magnitude of the seasonal and inter-annual variations of the surface variables both over East Asia as a whole and over the Korean Peninsula in the nested system. Some persistent biases are however present. Surface temperature is systematically underestimated, especially over mountainous regions in the warm season. This feature may be due to the relatively coarse representation of the Korean topography. The simulated precipitation over the mother domain successfully reproduces the broad spatial pattern of observed precipitation over East Asia along with its seasonal evolution. On the other hand, fine scale details from the nested results show a varying level of quality for the different individual years. Because of the better resolved topographic forcing, the increased resolution of the nested model improves the spatial agreement with the fine scale observation fields for temperature and cold season precipitation. For summer monsoon precipitation the simulation of individual monsoon convective events and tropical storms is however more important than the topographic forcing, and therefore the performance of the nested system is more case-dependent.     

Non-linear dependence and teleconnections in climate data: sources,relevance, nonstationarity

Quantification of relations between measured variables of interest by statistical measures of dependence is a common step in analysis of climate data. The choice of dependence measure is key for the results of the subsequent analysis and interpretation. The use of linear Pearson’s correlation coefficient is widespread and convenient. On the other side, as the climate is widely acknowledged to be a nonlinear system, nonlinear dependence quantification methods, such as those based on information-theoretical concepts, are increasingly used for this purpose. In this paper we outline an approach that enables well informed choice of dependence measure for a given type of data, improving the subsequent interpretation of the results. The presented multi-step approach includes statistical testing, quantification of the specific non-linear contribution to the interaction information, localization of areas with strongest nonlinear contribution and assessment of the role of specific temporal patterns, including signal nonstationarities. In detail we study the consequences of the choice of a general nonlinear dependence measure, namely mutual information, focusing on its relevance and potential alterations in the discovered dependence structure. We document the method by applying it to monthly mean temperature data from the NCEP/NCAR reanalysis dataset as well as the ERA dataset. We have been able to identify main sources of observed non-linearity in inter-node couplings. Detailed analysis suggested an important role of several sources of nonstationarity within the climate data. The quantitative role of genuine nonlinear coupling at monthly scale has proven to be almost negligible, providing quantitative support for the use of linear methods for monthly temperature data.     

WebGIS技术在气象网格产品精细化服务中的应用

数值模式已经成为天气预报业务发展的主要方向,数值模式计算产生各种气象网格产品。气象网格产品具有数据量大、更新频次快、专业性强等特点,需要借助专业工具软件进行处理,不能很好满足企业和社会用户使用的需求,应用范围受到极大的限制。面对气象网格产品专业化与气象数据应用需求简单化之间的矛盾,文章提出针对气象网格产品,尤其是实况网格产品和预报网格产品,采用互联网服务手段,通过对网格数据离散化处理的方法,空间化管理的方式,将WebGIS技术应用到气象网格产品服务中。用户在客户端只需要进行简单文字检索或者GIS图形检索,系统便可以实现对气象网格产品中的有效数据进行精细化抽取,最终实现服务精细。文中提出的数据处理方法,对不同行业间气象网格产品的应用起到指导作用。     

Spatial GHG inventory at the regional level: accounting for uncertainty

Methodology and geo-information technology for spatial analysis of processes of greenhouse gas (GHG) emissions from mobile and stationary sources of the energy sector at the level of elementary plots are developed. The methodology, which takes into account the territorial specificity of point, line, and area sources of emissions, is based on official statistical data surveys. The spatial distribution of emissions and their structure for the main sectors of the energy sector in the territory of the Lviv region of Ukraine are analyzed. The relative uncertainties of emission estimates obtained are calculated using knowledge of the spatial location of emission sources and following the Tier 1 and Tier 2 approaches of IPCC methodologies. The sensitivity of total relative uncertainty to change of uncertainties in input data uncertainties is studied for the biggest emission point sources. A few scenarios of passing to the alternative energy generation are considered and respective structural changes in the structure of greenhouse gas emissions are analyzed. An influence of these structural changes on the total uncertainty of greenhouse gas inventory results is studied.     

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as “field” or “global” significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ^° grid resolution. Monthly temperature climatology for the 1990–2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.     

Disaggregation of screen-level variables in a numerical weather prediction model with an explicit simulation of subgrid-scale land-surface heterogeneity

The earth’s surface is characterized by small-scale heterogeneity attributable to variability in land cover, soil characteristics and orography. In atmospheric models, this small-scale variability can be partially accounted for by the so-called mosaic approach, i.e., by computing the land-surface processes on a grid with an explicit higher horizontal resolution than the atmosphere. The mosaic approach does, however, not account for the subgrid-scale variability in the screen-level atmospheric parameters, part of which might be related to land-surface heterogeneity itself. In this study, simulations with the numerical weather prediction model COSMO are shown, employing the mosaic approach together with a spatial disaggregation of the atmospheric forcing by the screen-level variables to the subgrid-scale. The atmospheric model is run with a 2.8?km horizontal grid resolution while the land surface processes are computed on a 400-m horizontal grid. The disaggregation of the driving atmospheric variables at screen-level is achieved by a three-step statistical downscaling with rules learnt from high-resolution fully coupled COSMO simulations, where both, atmosphere and surface, were simulated on a 400-m grid. The steps encompass spline interpolation of the grid scale variables, conditional regression based on the high-resolution runs, and an optional stochastic noise generator which restores the variability of the downscaled variables. Simulations for a number of case studies have been carried out, with or without mosaic surface representation and with or without atmospheric disaggregation, and evaluated with respect to the surface state variables and the turbulent surface exchange fluxes of sensible and latent heat. The results are compared with the high-resolution fully coupled COSMO simulations. The results clearly demonstrate the high importance of accounting for subgrid-scale surface heterogeneity. It is shown that the atmospheric disaggregation leads to clear additional improvements in the structures of the two-dimensional surface state variable fields, but to only marginally impacts on the simulation of the turbulent surface exchange fluxes. A detailed analysis of these results identifies strongly correlated errors in atmospheric and surface variables in the mosaic approach as the main reason for the latter. The effects of these errors largely cancel out in the flux parameterization, and thus explain the comparably good results for the fluxes in the mosaic approach without atmospheric disaggregation despite inferior performance for the surface state variables themselves. Inserting noise in the disaggregation scheme leads to a deterioration of the results.     

新一代天气雷达网资料的三维格点化及拼图方法研究

文中研究了几种把球坐标系下的雷达网反射率体扫资料插值到统一的笛卡尔坐标系下的经纬度网格上以及用多个雷达的反射率网格资料进行三维拼图的方法,并对多个雷达同步观测的反射率因子的空间一致性、系统误差以及雷达等距离线上回波的水平和垂直结构进行了分析。结果发现:在雷达资料格点化过程中,径向和方位上的最近邻居法和垂直方向的线性内插法的结合(NVI方法)是一种有效的雷达资料分析方法,它既能得到空间比较连续的反射率分析场,同时也较好地保留了体扫资料中原有的反射率结构特征;广州雷达和梅州雷达同步观测的空间一致性比较好;在多个雷达资料合成拼图的过程中,距离指数权重平均法能提供空间连续的三维反射率拼图数据,拼图也减轻了由雷达波束几何学引起的各种问题。     

城市温室气体清单研究

介绍了国际上城市温室气体清单研究进展。分析了城市清单主流方法体系、模式以及编制原则、边界、范围,并且比较了城市清单和国家清单在方法体系及模式上的差异和其自身特点。重点分析了城市清单编制的“混合模式”和3个尺度范围。最后提出国内城市清单研究面临的困难和建议。