“双碳”背景下中国能源消费碳排放与植被固碳的时空分异

为理解中国能源消费碳排放(ERCE)与植被固碳(VCS)的演变特征及空间差异,基于气象数据、遥感数据、土地覆盖数据及统计资料等,分别在全国尺度、省域尺度和县域尺度上,定量分析2000~2017年我国ERCE和VCS的动态变化与空间分异格局,并利用碳压力指数(CPI),表征二者之间的相互关系.结果表明:(1)我国ERCE和人均ERCE在2000~2017年间表现出显著增加趋势(P<0.01),但二者分别在2013年和2012年以后出现小幅下降;空间上,二者呈现出“北高南低、东高西低”的差异特征;(2)VCS和人均VCS均在2010年以后呈现快速增加趋势(P<0.01),幅度分别为148.09×10⁶t/a和0.04t/(人·a),东北、西南和黄土高原等区域VCS和人均VCS的增加幅度明显高于其他地区;(3)全国约有近1/3的省份CPI多年平均值在1以上(即ERCE高于VCS),其中上海、天津、江苏、山东、宁夏的CPI平均值较高,且增幅也相对较大,反映出这些区域具有较大的减排压力.研究结果可为我国不同区域碳减排政策的制定提供科学依据.     

Safety assessment of automated vehicles: how to determine whether we have collected enough field data?

Abstract

Objective: The amount of collected field data from naturalistic driving studies is quickly increasing. The data are used for, among others, developing automated driving technologies (such as crash avoidance systems), studying driver interaction with such technologies, and gaining insights into the variety of scenarios in real-world traffic. Because data collection is time consuming and requires high investments and resources, questions like “Do we have enough data?,” “How much more information can we gain when obtaining more data?,” and “How far are we from obtaining completeness?” are highly relevant. In fact, deducing safety claims based on collected data—for example, through testing scenarios based on collected data—requires knowledge about the degree of completeness of the data used. We propose a method for quantifying the completeness of the so-called activities in a data set. This enables us to partly answer the aforementioned questions.

Method: In this article, the (traffic) data are interpreted as a sequence of different so-called scenarios that can be grouped into a finite set of scenario classes. The building blocks of scenarios are the activities. For every activity, there exists a parameterization that encodes all information in the data of each recorded activity. For each type of activity, we estimate a probability density function (pdf) of the associated parameters. Our proposed method quantifies the degree of completeness of a data set using the estimated pdfs.

Results: To illustrate the proposed method, 2 different case studies are presented. First, a case study with an artificial data set, of which the underlying pdfs are known, is carried out to illustrate that the proposed method correctly quantifies the completeness of the activities. Next, a case study with real-world data is performed to quantify the degree of completeness of the acquired data for which the true pdfs are unknown.

Conclusion: The presented case studies illustrate that the proposed method is able to quantify the degree of completeness of a small set of field data and can be used to deduce whether sufficient data have been collected for the purpose of the field study. Future work will focus on applying the proposed method to larger data sets. The proposed method will be used to evaluate the level of completeness of the data collection on Singaporean roads, aimed at defining relevant test cases for the autonomous vehicle road approval procedure that is being developed in Singapore.     

Exploring the determinants for adopting water conservation measures. What is the tendency of landowners when the resource is already at risk?

In Finland, the current water conservation policy sets equal incentives for water conservation, regardless of the environmental condition. Before any policy reform, it is vital to investigate the tendency of landowners to adopt water conservation measures. In this study, we were interested in examining adoption if the soil quality implies a high leaching risk and if the water quality is already poor. By combining survey data with GIS data, we analysed the effect of farm and farmer characteristics and attitudes towards adoption. Our probit models indicated that financial variables were the key determinants of adoption for active farmers, whereas for passive owners, adoption was also explained by attitudes. In contrast to our expectations, adoption in areas under risk was weakly supported by our estimates. Environmental awareness, providing it increases with risk, is not strong enough to motivate adoption. Targeted agri-environmental measures, even though costly, cannot be avoided, and spatially tailored measures can attract adopters in hotspot areas.     

Trade‐offs among Catch,Bycatch, and Landed Value in the American Samoa Longline Fishery

The interspecific preferences of fishes for different depths and habitats suggest fishers could avoid unwanted catches of some species while still effectively targeting other species. In pelagic longline fisheries, albacore (Thunnus alalunga) are often caught in relatively cooler, deeper water (>100 m) than many species of conservation concern (e.g., sea turtles, billfishes, and some sharks) that are caught in shallower water (<100 m). From 2007 to 2011, we examined the depth distributions of hooks for 1154 longline sets (3,406,946 hooks) and recorded captures by hook position on 2642 sets (7,829,498 hooks) in the American Samoa longline fishery. Twenty‐three percent of hooks had a settled depth <100 m. Individuals captured in the 3 shallowest hook positions accounted for 18.3% of all bycatch. We analyzed hypothetical impacts for 25 of the most abundant species caught in the fishery by eliminating the 3 shallowest hook positions under scenarios with and without redistribution of these hooks to deeper depths. Distributions varied by species: 45.5% (n = 10) of green sea turtle (Chelonia mydas), 59.5% (n = 626) of shortbill spearfish (Tetrapturus angustirostris), 37.3% (n = 435) of silky shark (Carcharhinus falciformis), and 42.6% (n = 150) of oceanic whitetip shark (C. longimanus) were caught on the 3 shallowest hooks. Eleven percent (n = 20,435) of all tuna and 8.5% (n = 10,374) of albacore were caught on the 3 shallowest hooks. Hook elimination reduced landed value by 1.6–9.2%, and redistribution of hooks increased average annual landed value relative to the status quo by 5–11.7%. Based on these scenarios, redistribution of hooks to deeper depths may provide an economically feasible modification to longline gear that could substantially reduce bycatch for a suite of vulnerable species. Our results suggest that this method may be applicable to deep‐set pelagic longline fisheries worldwide. Compensaciones entre Captura, Captura Accesoria y Valores Asentados en la Pesquera de Línea Larga de Samoa Americana     

基于地理探测器和多源数据的耕地土壤重金属来源驱动因子及其交互作用识别

明确耕地土壤重金属来源对土壤健康合理管护及其可持续发展至关重要.利用正定矩阵因子分解(PMF)模型源解析结果(源成分谱和源贡献)、历史调查数据和时序遥感数据,整合地理探测器(GD)、最佳参数地理探测器(OPGD)、空间关联探测器(SPADE)和空间关联交互探测器(IDSA)模型,探讨了土壤重金属来源空间分层异质性研究中可塑性面积单元问题(MAUP),分别识别了分类变量和连续变量中控制土壤重金属来源空间分异的驱动因子及其交互作用.结果表明,中小尺度下土壤重金属来源的空间分异性研究受空间尺度影响,0.08 km²能够作为区域土壤重金属来源空间分异性探测的可选空间单元.连续变量受空间相关性与离散化水平影响,分位数法和中断数为10的离散化参数组合能够减少连续变量在土壤重金属来源空间分异性探测中所受分区效应的影响.分类变量中地层(PD 0.12～0.48)控制土壤重金属来源空间分异,地层和流域的交互作用对各来源解释力为27.28%～60.61%,各来源的高风险区域分别分布在地层中的下震旦系、上白垩系、土地利用中采矿用地和土壤种类中典型强淋溶土区域.连续变量中人口(PSD 0...     

基于MDS与TOPSIS模型的滨海滩涂围垦区土壤质量评价

评估围垦后土壤质量的变化过程可以为土壤抑盐、培肥等调控措施提供科学指导.以不同围垦年限(5、30、38和61a)滩涂围垦区和光滩为研究对象,基于最小数据集方法筛选了与土壤质量密切相关的土壤黏粒比例、土壤盐分(SSC)、土壤有机质(SOM)、全钾(TK)和土壤容重(BD)这5个指标,结合TOPSIS模型构建土壤质量指数对滨海滩涂围垦后土壤质量演变过程进行评价.结果表明,滩涂围垦后土壤粒径逐渐细化,土壤含水量和土壤容重逐渐降低,土壤脱盐脱碱活动持续进行并伴随着养分和速效养分含量的逐渐累积.研究区土壤质量指数在24. 06～63. 08之间,并呈现出:光滩(20. 04±11. 48)围垦5 a(29. 33±10. 65)围垦30 a(51. 52±8. 76)≈围垦38 a(49. 98±10. 75)围垦61 a(58. 37±3. 15),土壤质量大致经历了"初期稳定-迅速提升-相对稳定"这3个阶段.土壤质量因子障碍程度的排序为黏粒比例 SSC SOM TK BD,较低的黏粒含量和较高的盐分是围垦区土壤提升的主要障碍因子.     

大气污染联合治理分区视角下的中国PM2.5关联关系时空变异特征分析

联合治理分区下PM_(2.5)关联关系时空变异特征识别对中国大气污染防治意义重大.本文主要基于2000～2016年遥感反演的中国大陆334个地级市PM_(2.5)浓度数据,利用空间单元聚合策略与地理时空加权回归技术,系统分析了大气污染联合治理分区视角下的中国PM_(2.5)关联关系时空变异特征.结果表明:①以PM_(2.5)为首要污染物,综合考虑污染程度、地理位置、气象、地形和经济等因素可将中国大陆地区划分为10个大气污染联合治理区.②地理时空加权回归能够有效刻画PM_(2.5)与关联因素间的时空非平稳关系.同时,人口规模、第二产业生产总值、SO_2排放量、年平均气温、年降水量以及年平均相对湿度被识别出对PM_(2.5)浓度的变化影响存在显著时空差异.③人口规模对PM_(2.5)浓度的影响程度各年最大的地区均为京津冀蒙区域;川渝滇黔区域中第二产业生产总值对PM_(2.5)浓度影响程度变异度最大,在黑吉辽区域之外,SO_2排放量回归系数值均先随时间逐渐减小再增大最后又减小;各治理区中年平均温度对PM_(2.5)影响程度的时间变异程度较小;而年降水量与年平均相对湿度对PM_(2.5)影响程度在各区域中呈现不同的变异特征.     

Characterization of the aerosol chemical composition during the COVID-19 lockdown period in Suzhou in the Yangtze River Delta, China

To control the spread of COVID-19, rigorous restrictions have been implemented in China, resulting in a great reduction in pollutant emissions. In this study, we evaluated the air quality in the Yangtze River Delta during the COVID-19 lockdown period using satellite and ground-based data, including particle matter (PM), trace gases, water-soluble ions (WSIs) and black carbon (BC). We found that the impacts of lockdown policy on air quality cannot be accurately assessed using MODIS aerosol optical depth (AOD) data, whereas the tropospheric nitrogen dioxide (NO₂) vertical column density can well reflect the influences of these restrictions on human activities. Compared to the pre-COVID period, the PM_2.5, PM₁₀, NO₂, carbon monoxide (CO), BC and WSIs during the lockdown in Suzhou were observed to decrease by 37.2%, 38.3%, 64.5%, 26.1%, 53.3% and 58.6%, respectively, while the sulfur dioxide (SO₂) and ozone (O₃) increased by 1.5% and 104.7%. The WSIs ranked in the order of NO₃^? > NH₄⁺ > SO₄^2- > Cl^? > Ca²⁺ > K⁺ > Mg²⁺ > Na⁺ during the lockdown period. By comparisons with the ion concentrations during the pre-COVID period, we found that the ions NO₃^?, NH₄⁺, SO₄^2?, Cl^?, Ca²⁺, K⁺ and Na⁺ decreased by 66.3%, 48.8%, 52.9%, 56.9%, 57.9% and 76.3%, respectively, during the lockdown, in contrast to Mg²⁺, which increased by 30.2%. The lockdown policy was found to have great impacts on the diurnal variations of Cl^?, SO₄^2?, Na⁺ and Ca²⁺.     

基于OMI数据的新冠疫情影响下福建省臭氧敏感性变化

基于OMI卫星数据,利用臭氧敏感性指示剂法研究了福建省及其九地市在COVID-19疫情影响下不同时间阶段大气臭氧敏感性特征以及不同情景下敏感性的变化规律.结果表明,在疫情前,福建省的大气臭氧生成控制区面积占比情况为VOC_S控制区占46.5%、协同控制区占25.0%、NO_x控制区占28.5%,以VOCs控制区为主,其中厦门市占比最高,南平市最低;在严控期,VOC_S控制区占29.5%、协同控制区占21.1%、NO_x控制区面积占49.4%,以NO_x控制区为主,其中宁德市占比最高,莆田市最低;在平稳期,VOC_S控制区占23.1%、协同控制区占29.1%、NO_x控制区占47.8%,以NO_x控制区为主,其中南平市占比最高,厦门市最低.与疫情前相比,严控期厦门市VOC_S控制区面积占比减少最多（38.1%）、最少的是三明市（7.9%）;从转化结果来看,第一类城市包括莆田市、泉州市、厦门市,敏感区变化受前体物HCHO、NO₂共同影响,而第二类城市主要受NO₂柱浓度变化影响.因此,第一类城市臭氧调控更加复杂.