利用气象卫星资料估算全球作物总产研究

以美国为例，利用1996～2000年每旬的全球植被指数卫星遥感资料，计算出每年耕地上作物生长季内的总NPP（Net Primary Production）。农作物总产是耕地上总NPP的一部分，根据NPP与作物总产的关系，确定作物的产量转换系数，然后利用当年耕地的总NPP值来估算当年作物的总产。通过研究表明，该方法的预测精度较高，可操作性强，能够投入业务应用。     

基于遥感沿海湿地植被生产力估算研究

植被净第一性生产力是评价地表植被状况的重要指标之一,对分析和评价全球以及区域生态环境、碳循环等变化具有重要作用.植被净第一生产力的研究方法很多,本文主要运用TM影像近红外和红光通道组成的标准化差植被指数（NDVI）,借助CASA模型机理以及气象学方法,建立盐城区域净第一性生产力（NPP）遥感估算模型,并以核心区-丹顶鹤自然保护区湿地为应用案例,分析了核心区2005年间8月份净第一性生产力的变化.分析结果表明,研究区8月份的湿地各种植被NPP分别为：人工芦苇和盐蒿为1184.863266 g/m2,芦苇为1083.435262g/m2,米草为822.766878g/m2.若以NPP为衡量标准,人工芦苇和盐蒿的净第一性生产力最高.     

近30年乌鲁木齐地区自然植被净第一性生产力变化分析

利用周广胜、张新时提出的自然植被净第一性生产力模型，估算分析了乌鲁木齐地区近30年自然植被净第一性生产力（NPP）的时空变化。结果表明，除后峡地区的NPP呈递减趋势外，其它各地的NPP总体上呈递增趋势；中山带的NPP最高，亚高山、高寒、低山和山前荒漠地带依次降低；气候变暖除对高寒地带的自然植被的NPP有一定的正效应外，对其它地区的NPP均产生较明显的负效应；年降水量的增加对提高自然植被净第一性生产力具有积极作用。     

植被净第一性生产力及其对气候变化响应研究进展

较详细地综述了近些年来，特别是近10年来，国外、国内在全球和区域陆地植被净第一性生产力研究进展，主要包括：植被净第一性生产力研究理论方法；植被净第一性生产力模型和模拟估算；全球气候变化的自然植被净第一性生产力研究和植被覆盖变化及其与气候关系的研究进展；遥感作为当今唯一一种能重复，连续获取全球环境数据信息的高新技术，近年来在植被净第一性生产力研究领域的广泛应用等。同时对今后植被净第一性生产力研究特点和趋势做了讨论，并提出了看法。     

关于吉林省玉米和水稻生产的主要气象条件及其服务指标的探讨

1 前言 玉米、水稻是我省主要的高产粮食作物,在粮食生产中占有重要地位,其中玉米每年的种植面积在200多万hm~2,约占粮食总面积的60％,产量占粮豆总产的70％左右;水稻是我省高产细粮作物,是仅次于玉米的第二大作物,从全省目前的生产状况看,粗放经营,广种薄收的现象较为普遍,大部分县(市)     

基于5种气候生产力模型的乌鲁木齐地区NPP计算分析

根据大西沟、小渠子、乌鲁木齐和达坂城等4个台站1961-2007年的气候资料,分别采用Miami模型、Thornthwaite Memorial模型、Chikugo模型、朱志辉模型和周广胜模型对乌鲁木齐地区各类草场自然植被净第一性生产力进行了计算,并以周广胜模型计算结果为标准,分析了其它模型估算不同类型天然草场NPP的误差。     

多因子权重综合评分法在水稻年景评价中的应用

1 前言 水稻是丹东地区的主要粮食作物之一,其产量占全区粮食总产的44.5％以上,平均亩产不足400kg,在省内属中低产量。充分利用本地气候资源是在当前生产力水平下,提高粮食产量的商品率的重要途径。因此,开展水稻生产年     

水稻遥感估产的一种方法

该文利用NOAA/AVHRR空间覆盖度宽、资料获取时次多的特点，寻求预测北方一季稻产区水稻产量的最佳时期，利用植被指数建立水稻单产的预报模式，遥感估算水稻种植面积。研究表明，利用卫星遥感手段对水稻进行估产的精度高于常规农业气象模式，又可提高预报时效。     

基于积分回归法黑龙江省作物产量动态预报研究

由于积分回归法生物学意义明确,预报效果较好,已成为一种新的作物产量动态预报方法。为了完善黑龙江省主要作物的动态预报方法,提高作物单产的预报准确率,本文利用积分回归方法,随机选取以县为单元的研究对象,开展黑龙江省多种作物积分回归产量动态预报模型的适用性研究。结果表明:建立的黑龙江省6月下旬至9月下旬春玉米、大豆和水稻积分回归产量动态预报模型均通过了F的显著性检验,作物产量预报的平均差MD和相对误差RE均未通过显著性检验,表明建立的春玉米、大豆和水稻产量预报模型的预报效果较好;其中春玉米和水稻产量预报模型的预报准确率较高,模型预报的单产与实际单产的一致性较好。通过对2011—2014年黑龙江省作物单产进行试报和检验,发现春玉米、水稻和大豆单产的预报准确率平均为96%、95%和93%;表明积分回归方法对黑龙江省大豆单产预报的适宜性略差,积分回归法适用于黑龙江省水稻和春玉米单产的预报。基于积分回归法的原理,可以在黑龙江省开展春玉米和水稻单产的动态预报,并继续开展大豆产区积分回归产量动态预报的适用性研究。     

亚热带东部丘陵山区作物气候生产力研究

本文根据1983年4月—1986年3月三年山区梯度观测资料，综合考虑山区光、热、水农业的气候资源匹配关系，建立不同山区、坡向、高度的作物气候生产力估算模式。模式中对山区温度、降水、日照等气象要素进行了修正。运用模式估算了不同山区、坡向、高度的水稻、玉米、冬小麦气候生产力。计算结果:亚热带东部丘陵山区单、双季稻、夏玉米气候生产力一般南坡大于北坡，西坡大于东坡；春玉米、冬小麦一般北坡大于南坡，东坡大于西坡。双季晚稻气候生产力大于双季早稻，夏玉米大于春玉米（神农架山区除外）。应该指出，目前高产典型水稻产量可达其气候生产力的60%以上，玉米和冬小麦仅达到30%—50%左右，表明山区农业气候资源可开发潜力很大。本文为合理开发山区气候资源、调整农业布局及提高单位面积产量提供了定量的科学依据。     

Effects of the city of Moscow on the atmospheric aerosol characteristics in the environs

Absract  On the data of 13-year (1994–2006) measurements, during January to June, of the atmospheric aerosol characteristics in Dolgoprudny, Moscow region, effects of the city of Moscow on aerosol contamination of the surface air is analyzed. A relative increase is estimated of concentrations of particles of various sizes within the diameter range of 0.01 to 10 μm under conditions of airflow from the city of Moscow, along with changes in concentrations of cloud condensation nuclei and ice nuclei in the air. It is shown that percentage of the aerosol particles from Moscow in the total aerosol concentration within certain size ranges reaches 30% in winter months and 45% in summer ones. The aerosol transported from the city contains a significant amount of hygroscopic particles. The cloud nuclei concentration in June increases by a factor of 2 in the cases of airflow from the city. Original Russian Text ? N.O. Plaude, E.A. Stulov, N.A. Monakhova, M.V. Vychuzhanina, E.V. Sosnikova, N.P. Grishina, 2007, published in Meteorologiya i Gidrologiya, 2007, No. 12, pp. 35–43.     

福建省硫沉降量变化的分析与比较

应用中国科学院大气物理研究所建立的三维欧拉污染物输送模式模拟了1995、2000、2002年福建省本省排放源造成的和邻近省份排放源向其输送的硫沉降量,结果表明,福建省接收的硫沉降量有一半以上是由周围省份的远距离输送造成的。进而分析了每年4个季节硫沉降的变化特点,并结合福建省气象条件给出理论解释。最后,把这3年福建省SO2及SO42-年沉降量和各季节沉降量分别作了比较,结果显示,造成福建省SO2沉降的主要来源是本省的排放源,而SO42-沉降中外来源占很大比例,超过了50%。     

Climate Change and Rice Yields in Diverse Agro-Environments of India. I. Evaluation of Impact Assessment Models

This paper reports results of a comparison of two popular rice growth models- Ceres-Rice and ORYZA1N for the same input conditions. Both models use different approaches for simulating growth and yield, are sensitive to climate change parameters, and represent two major schools of crop modelling. A dataset of 32 experiments consisting of 98 treatments was assembled from an extensive literature search. These experiments were conducted over the period of 1980–1993 in diverse Indian locations from 11° N–33° N. The treatments varied in N management, sowing dates, varieties and seasons. The flowering duration in the dataset varied between 37 and 86 days and grain yields between 2587 kg ha^–1 and 8877 kg ha^–1. Seven treatments from this dataset, one for each variety, were selected for calibration. The genetic coefficients of different varieties used in the analysis for both models were estimated from this short-listed dataset by repeated iterations until a close match between simulated and observed phenology and yield was obtained in these treatments. Similarly 11 treatments with zero or low N applications were used for calibration of initial soil N for different locations. The remaining 80 treatments were used for validation of the models. Both models predicted satisfactorily the trends of leaf area and dry matter growth, grain number, days to flowering and grain yields. Simulated yields were within +15% of the measurements. Considering that the field measurements also generally have 10–15% error and that the treatments widely varied in weather conditions, particularly in temperature, it was concluded that both models are adequate to simulate the effects of climate change on rice yields in diverse agro-environments of India that are free from all pests.     

Agroecological measures and circular economy strategies to ensure sufficient nitrogen for sustainable farming

Sustainable food systems face trade-offs between demands of low environmental pressures per unit area and requirements of increasing production. Organic farming has lower yields than conventional agriculture and requires the introduction of nitrogen (N) fixing legumes in crop rotations. Here we perform an integrated assessment of the feasibility of future food systems in terms of land and N availability and the potential for reducing greenhouse gas (GHG) emissions. Results show that switching to 100% organic farming without additional measures results in N deficiency. Dietary change towards a reduced share of animal products can aggravate N limitations, which can be overcome through the implementation of a combination of agroecological, circular economy and decarbonization strategies. These measures help to recycle and transfer N from grassland. A vegan diet from fully decarbonized conventional production performs similarly as the optimized organic scenario. Sustainable food systems hence require measures beyond the agricultural sector.     

中国七大地区“气候变化—作物产量—经济影响”综合评价

农业作为响应气候变化最敏感的领域之一,未来作物产量可能受到深刻影响。量化气候变化冲击作物产量导致的最终经济影响,需要综合“气候变化—作物产量—经济影响”开展链式研究。文中采用系统回顾和Meta回归分析方法整合了55篇文献的667项研究结果,推导出我国七大地区主要作物（水稻、玉米、小麦）产量与地区内未来温度和降水变化的定量关系,并将其作为农业部门的损失量代入改进的多区域投入产出模型,量化七大地区内与地区间遭受的经济波及影响（ERE)。结果显示：(1)气候变化对我国作物产量的影响主要体现在温度升高上,每升温1℃减产2.6%~12.7%,东北和西北地区作物受升温影响最显著;(2) 气候变化导致的作物减产将对经济产生更严重的波及影响,GDP因作物减产每下降1%将额外产生17.8%的波及影响;(3) 21世纪末,若不考虑CO₂肥效作用,作物减产导致的ERE将占GDP的-0.1%~13.6%（负值表示收益),最悲观情况下ERE与当前我国农业总产值相当（2012年为基准年);(4)不同地区受ERE影响程度的差异较大,因各区之间产业结构、贸易联系及经济发展程度存在差异,西南地区遭受本区及来自其他地区的ERE比华东地区高2.8~8.5倍。     

青藏高原臭氧低谷的加深及其可能的影响

通过分析 TOMS(1 979～ 1 992 )资料发现 :(1 )青藏高原的臭氧不仅存在递减趋势 ,而且是一个递减的强中心 ,这个递减的强中心是同纬度地区 3个递减中心之一 ;(2 )夏季青藏高原臭氧低谷有加深的趋势 ,其递减率最大值为 - 0 .336% /a;加深区域为 2 9～ 33°N,78～ 94°E。另外 ,分析 SAGE 资料的结果表明 :青藏高原臭氧递减的强中心的形成是由于其平流层下部臭氧异常减少造成的。根据研究结果的趋势估测 :从 1 992年到 2 0 0 0年 ,夏季青藏高原紫外辐射增加大约为 1 .3%～ 2 .3% ,可能引起白内障发病率上升大约 0 .8%～ 1 .4% ,皮肤癌上升大约 3.2 %～ 5.4%。     

Chemical reactions and transport of alkanes and their products in the troposphere

The product distributions have been calculated for more abundant alkanes contributing most of the carbon atoms in the alkane fraction of an ambient air hydrocarbon mixture reasonably representative of U.S. emissions. The effects of ambient temperatures on product yields has been calculated for a range of temperatures from 250 to 330 K. The sensitivity of product yields to uncertainties in alkoxy radical process rate constants has been examined with emphasis on uncertainties in decomposition reactions. Chemical lifetimes are estimated at 300 K under summertime conditions for hydrocarbons and for products of alkane photooxidation in the atmosphere. The atmospheric distribution of alkanes and products is evaluated in terms of the extent to which reaction processes are likely to occur in the planetary boundary layer compared to the free troposphere.The calculations predict a substantial effect of temperature on product yields. A large decrease in alkyl nitrate yields and a smaller decrease in ketone yields occur with increasing temperature. The yields of the short-lived, more reactive aldehydes undergo substantial increases with increasing temperature. Lower yields of ketones and higher yields of aldehydes are associated with the use of higher compared to lower decomposition process rate constants. For the type of U.S. hydrocarbon mixture available from measurements, 16 oxygenated products account for more than 60% of the total alkane carbon atoms converted to products, with most of these carbon atoms accounted for by four products. The effects of increased temperature on product reactivity and radical production may also influence O₃ production.     

Climate Change and Rice Yields in Diverse Agro-Environments of India. II. Effect of Uncertainties in Scenarios and Crop Models on Impact Assessment

Estimates of impact of climate change on crop production could be biased depending upon the uncertainties in climate change scenarios, region of study, crop models used for impact assessment and the level of management. This study reports the results of a study where the impact of various climate change scenarios has been assessed on grain yields of irrigated rice with two popular crop simulation models- Ceres-Rice and ORYZA1N at different levels of N management. The results showed that the direct effect of climate change on rice crops in different agroclimatic regions in India would always be positive irrespective of the various uncertainties. Rice yields increased between 1.0 and 16.8% in pessimistic scenarios of climate change depending upon the level of management and model used. These increases were between 3.5 and 33.8% in optimistic scenarios. At current as well as improved level of management, southern and western parts of India which currently have relatively lower temperatures compared to northern and eastern regions, are likely to show greater sensitivity in rice yields under climate change. The response to climate change is small at low N management compared to optimal management. The magnitude of this impact can be biased upto 32% depending on the uncertainty in climate change scenario, level of management and crop model used. These conclusions are highly dependent on the specific thresholds of phenology and photosynthesis to change in temperature used in the models. Caution is needed in using the impact assessment results made with the average simulated grain yields and mean changes in climatic parameters.     

The impact of weather variations on maize yields and household income: Income diversification as adaptation in rural China

Climate change is threatening global food production and could potentially exacerbate food insecurity in many parts of the world. China is the second largest maize producer. Variations in maize yields in China are likely to have major implications for food security in the world. Based on longitudinal data of 4861 households collected annually between 2004 and 2010, we assess the impact of weather variations on maize yields in the two main producing regions in China, the Northern spring maize zone and the Yellow-Huai Valley summer maize zone. We also explore the role of adaptation, by estimating the response of Chinese farmers in both regions, in particular in terms of income diversification. With the use of household and time fixed effects, our estimates relate within-household variations in household outcomes (maize yields, net income, land and input use) to within-location variations in weather conditions. Temperature, drought, wet conditions, and precipitations have detrimental effects on maize yields in the two maize zones. The impact is stronger in the Northern spring maize zone where one standard deviation in temperature and drought conditions decreases maize yields by 1.4% and 2.5%, respectively. Nonetheless, such impact does not seem to translate into a significant fall in total net income. Adaptation seems to be key in explaining such a contrast in the Northern spring maize zone where the largest impact is estimated. On the contrary, we find a lower impact in the other region, the Yellow-Huai Valley summer maize zone but such impact is likely to intensify. The lack of adaptation observed in that region results into detrimental impacts on net farm and total income. Enhancing adaptative behaviors among Chinese farmers even further is likely to be key to future food security in China and in the rest of the world.     

Forage Yield-Based Carbon Storage in Grasslands of China

Forage yield-based carbon storage in 18 grasslands of China was estimated according to the detailed investigation of grassland area and forage yield (standing crop), which were derived from a 10-year national grassland survey. The total forage yield carbon in Chinese grasslands is 134.09 Tg C for ca. 299 × 10⁶ ha of grassland area and 1232 kg/ha of mean forage yield. The carbon storage is different depending on grassland types and climatic regions. Meadow, steppe and tussock occupy 93.3% (125.14 Tg C), and desert and swamp only accounts for 6.7% (8.95 Tg C) of total forage yield carbon. Forage yield carbon is stored largely in temperate (38.4%, 51.54 Tg C) and alpine regions (30.4%, 40.78 Tg C), and to less extent in tropical regions (22.1%, 29.66 Tg C). These three regions take 91% of the forage yield carbon in grasslands of China. The warm-temperate region accounts for only 9% (12.1 Tg C) of forage yields carbon. The forage yield-based carbon in grasslands of China is more accurate than the site biomass-based carbon estimate and the carbon density-based estimate. Although, forage yield carbon storage is small compared with the total carbon storage in China, carbon budgets of grasslands are often a dominant component in many regions and provide an important management opportunity to enhance terrestrial carbon sinks in vast areas of China.