Quantifying effects of oxidant air pollutants on agricultural crops

Estimating risks of air pollution damage to agricultural crops requires identifying crop location and size, likely doses, models for translating dose to response, and measures of response appropriate for economic analysis. Assessment of risk requires compatible data sets for each of these variables. Analysis of air pollution mixtures suggests that oxidant crop damage is caused by three compounds: ozone, nitrogen oxides, and peroxyacetylnitrates. The phytotoxicity of ozone, the most prevalent photochemical oxidant, has been studied more extensively than the other two oxidants, and its effects on vegetation are best understood. Response of vegetation to air pollutants was first characterized by foliar or visible injury. Subsequent research indicated that foliar injury did not translate directly into reduced plant growth or yield, which can be measured. Response to air pollutants may be influenced by physical, biological, and environmental factors. Inherent genetic resistance is probably the most important single factor affecting plant response, although environmental factors influencing stomatal aperture may also be important. For several crops open-top chamber studies and cross sectional analyses of field data provide adequate information to develop dose-response functions. All of these studies have both strengths and weaknesses. Although a number of different models exist for selected crops, there is no single biological or statistical criterion which identifies the best or most accurate model.     

Future directions in air quality research: economic issues

Our challenge was to address future directions in air quality research that involve economic issues. The paper outlines the role of economics in the evaluation of air pollution impacts on environmental systems and describes existing research. We identify studies that address economic effects in the agricultural sector, in the commercial forest sector, and in unmanaged natural systems. Effects related to ozone exposure are highlighted. The summary of available research is followed by a discussion of research recommendations. Several short-term recommendations are identified that can augment some of the new research being considered by scientists. A more ambitious, long-term research project is outlined for valuing air pollution impacts in unmanaged natural environments. Specifically, the paper describes possible advantages of an 'integrated assessment' framework that more formally brings together the complex relationships that exist in both ecological and economic systems. A final section contains thoughts on the importance of education (i.e., information transfer) in the research process, especially in relation to policy. It is further noted that education should be inclusive of all members of the research team, throughout all stages of the research process.     

High-resolution spatial analysis of stomatal ozone uptake in arable crops and pastures

Ozone effects on plants depend on atmospheric transport and stomatal uptake. Thus, ozone-risk assessments should use measured ozone concentrations and account for the influence of atmospheric conditions and soil moisture on stomatal and nonstomatal ozone deposition. This requires disaggregated data for the physical input parameters and species-specific data for specific stomatal conductance (g(s)). In this study, an approach was developed based on a resistance analogue transport model. This model requires interpolated routine-measuring data for ozone concentration at 3-5 m height, wind speed, precipitation, and soil moisture content as inputs to estimate the amount of ozone taken up by wheat (Triticum aestivum) and grass/clover pastures with a 1x1-km resolution. The model was applied to the area under agricultural production in Switzerland. Using data for June 1994, the calculations revealed that the median of the distribution of stomatal ozone uptake was 88% higher in wheat compared to grassland. This was mainly due to the higher maximum stomatal conductance in wheat. Because ozone flux to soil and to external plant surfaces was comparable in both vegetation types, the difference in the stomatal fluxes was mainly responsible for distinct differences in flux partitioning. In both cases, only about 11% of the total cumulative flux was absorbed by external plant surfaces, whereas the soil was a strong sink responsible for as much as 50% of the total flux into grasslands. The higher-ozone flux to wheat resulted in clearly lower-ozone concentrations at canopy height, but no significant correlation between cumulative canopy-level ozone exposure, expressed as accumulated exposure above 40 ppb (AOT40), and stomatal uptake was found. Thus, to estimate the ozone risk for crops using a flux-based approach may lead to results that differ substantially from those obtained with a concentration-based approach.     

Significant issues in water resources policy

The difficulties in resolving water resource policy questions are analogous in many ways to the difficulties in resolving energy policy questions — technical, legal, institutional and social. Federal involvement in water resources began in 1809 and continues to the present time. The most recent comprehensive study was the Second National Water Assessment by the U.S. Water Resources Council in 1979. Conclusions reached were that water quality and quantity and surface and ground water are artificial distinctions, that water policies should reflect national needs and priorities, that flood control must be accelerated and drinking water quality protected and that more decisions should be made at a local level while integrated into national planning and development. Though the study disaggregated the U.S. into 106 subregions, its projections of a single future rather than a range of futures gives an erroneous sense of predictability to the work. To help resolve the major problems, inadequate supply and contamination and flooding and erosion, ultrasophisticated mathematical models are widely utilized without sufficient verification. A more tractable approach for policy studies would be to use simplified semi-empirical models rather than first principle models. Possibly more important, policy resolution awaits social value resolution which means that the policies adopted must be flexible, incremental, and non-divisive.     

The long-term effects of carbon dioxide on natural systems: issues and research needs

Research on the responses of plants to increasing levels of carbon dioxide has largely assessed physiological, phenotypic, and community-level effects. Little attention has been directed to investigating the possibility that escalating levels of carbon dioxide may serve as a selection pressure altering the genetic diversity of plant populations. Plant populations exposed to elevated levels of heavy metals or ozone have been shown to undergo selection, and it is reasonable to consider that populations experiencing long-term exposure to escalating levels of carbon dioxide may show similar responses. Selection of this nature could be particularly significant because of the global extent of the effect.Genetic selection occurs when plants are subject to an agent of selection and three conditions for a property responsive to the agent are satisfied at the population level. In the population, variation must exist in the property, part of the variation must be genetically controlled, and variation in the property must affect reproductive fitness. If these conditions are satisfied, the frequency distribution of the property, and the gene frequency associated with it, will change over time in response to the agent of selection.Research on the selection pressure effects of carbon dioxide involves assessments that integrate across temporal, spatial, and biological scales, and embrace variation in the environment and genetics. To be effective, the research will have to adopt approaches that have not been commonly employed in previous air quality studies. The questions posed are biologically complex, and new research approaches and methods are required to answer them. Some of the new approaches that can be used to assess changes in gene frequency include use of natural carbon dioxide gradients, model plant systems, molecular markers, and DNA microarray technology.     

小农发展气候智慧型农业的效率与成本改进:倡导农地流转还是发展社会服务?

气候智慧型农业是联合国粮农组织所提出的积极响应气候变化、有效保障作物生产安全的新型农业发展模式。碳减排是发展气候智慧型农业的核心要义,而中国大量且长期存在的小农是发展气候智慧型农业不可背离的重要主体。基于湖北省水稻主产区气候智慧型农业发展的调研,继而利用方向性距离函数对小农发展气候智慧型农业,即低碳生产效率与碳边际减排成本进行测算,并进一步考察小农通过土地流转或农业社会化服务衔接现代农业,对低碳生产效率和碳边际减排成本的影响。结果表明:(1)基于小农发展气候智慧型农业仍处于"低效率—高成本"阶段,水稻低碳生产效率仍存在平均56%的提升空间;碳边际减排成本均值为34.13元/kgCE;(2)土地转入虽未能提升水稻低碳生产效率,但却具有碳边际减排成本优势;(3)生产雇工和农机服务对水稻低碳生产效率和碳边际减排成本均具有显著的正向影响,可见通过农业社会化服务实现低碳生产效率的提升仍面临分工与交易费用的两难之困。基于上述结论,提出促进小农发展气候智慧型农业,实现低碳生产相关政策启示。     

INSIGHT: a framework for determining impacts of changes in land and water policies.

CSIRO Sustainable Ecosystems is constructing a spatially explicit modelling system capable of exploring alternative land and water policy alternatives against plausible price, cost, and climate scenarios for the next 20 years. INSIGHT will be used to identify the likely impacts of land and water policy options on regional economies and structural adjustment. Flowcharts have been constructed for most of the major crop and pasture and associated economic models for commodities produced in the Lachlan River Catchment of New South Wales. This enabled the most important components and interrelationships within these models to be readily identified. The next step has been to construct models at the regional scale that contain the essential elements of the more-detailed point models. The paper describes the progress to date in describing these models, and how they have been integrated into a coordinated agricultural crop production evaluation system.     

Ozone and natural systems: understanding exposure,response, and risk

Research aimed at understanding the response of plants to ozone has been conducted for over four decades but little of it has addressed intact natural systems. Even so, there is sufficient scientific information at this time to support air quality standards that will protect natural terrestrial ecosystems from ozone. What is unknown is the risk associated with continued exposure of natural systems, including both above- and below-ground components, in combination with other stresses including changing temperature and precipitation, elevated carbon dioxide, pests and pathogens, invasive species, and other activities that may fragment the landscape. Research to support an assessment of the ecological risk associated with ozone as it exists, in a milieu of stresses, must include endpoints beyond those addressed in the past, primarily productivity and species composition. To estimate the risk to society of ozone impacts on natural systems, endpoints such as the integrity of soil food webs, the quantity and quality of water supplied from terrestrial ecosystems, wildlife and recreational values, and the transfer and fate of carbon, nutrients, and water within the systems must be quantified. Not only will this research provide the basis for a sound estimate of risk, but also it will improve our understanding of fundamental ecosystem processes.     

Constructing regional scenarios for sustainable agriculture in European Russia and Ukraine for 2000 to 2070

This study estimates the consequences of climate change on cropland with and without implementation of adaptation measures, paying special attention to the maintenance of soil organic carbon (C) stocks. We examine the possibility for regional sustainable agricultural management practice that combines both maintenance and gain in soil carbon level with profit maximization. Future scenarios of Regional Agricultural Production Systems (RAPS) were constructed for 2000–2070 based on linking the effects of global climate change, predicted change in productivity parameters for the main agricultural crops, land-use and soil database parameters. The RAPS were used to examine profitability and feasibility of alternative agricultural scenarios, based on an economic model. A number of recommendations for decision making were proposed based on an assessment of the efficiency of adaptation in animal husbandry and in the crop production sector, after analysis of current percentage of perennial grass in rotation in comparison with future economic scenarios. Figures in color are available at     

Applying mass transfer models for controlling organic compounds in ozonation process

Mass transfer plays a significant role in the ozonation process. The prediction models associated with the volumetric overall mass transfer coefficient (K_La) and initial fractional ozone absorption (FOA₀) during the ozonation process were developed through the use of dimensional analysis. It was found that the volumetric overall mass transfer coefficient is the function of diffusivity, agitation speed, and gas flow rate, and the parameters in the K_La equation are determined. Application of the prediction models for K_La and FOA₀ would yield information to choose the most practically feasible operating parameters. The removability of total organic carbon (TOC) can be estimated based on the mass balance relationship and kinetic expression of TOC oxidation, during continuous laboratory ozonation of humic acid solution. The reaction rate constant averaged 0.0291 L/mg·min. The developed model in combination with the mass transfer and reaction kinetics can be used successfully in forecasting the most efficient agitation speed to control the formation of organic compounds. Also, the critical value of ozone partial pressure to achieve the highest TOC removability can be determined through the use of the above developed model.     

农村税费改革对农业土地利用的影响:一个宏观评价

以取消农业税和加大农业补贴力度为主要特征的农村税费改革，是近年来中国农村地区的一次重大制度改革。为探讨其对农业土地利用的影响，在简要回顾农村税费改革主要历程的基础上，通过构建计量经济模型，从宏观层面分析验证了农村税费改革对农业土地利用规模和利用效率的具体影响。结果表明: 农村税费改革对农业土地利用的影响主要体现为农户行为响应产生的引致效应；无论是农业税的取消还是财政支农政策的加强都对农业土地利用规模的扩大产生了显著影响；而农村税费改革对农业土地利用效率的影响则并不明显。为此，中国政府今后仍需在农业补贴支出结构以及相关配套政策创新方面进一步优化     

中国种植业产品贸易自由化对环境影响的计量经济分析

入世后．中国将根据WTO的要求对农业贸易相关政策进行调整和改革，这将改变国内农业生产，进而影响到农村生态环境。在此背景下．本文首先界定了种檀业产品贸易自由化的涵义．并对其环境影响途径进行分析．然后利用计量经济方法着重分析了贸易自由化对国内种植业生产中化肥、农药使用的影响。研究结果表明，在种植业产品的贸易自由化中，进口渗透作用对缓解国内化肥、农药污染影响显着．而出口导向作用影响不明显。文章最后给出了减缓农产品贸易自由化的不利影响，发挥其有利影响的政策建议。     

农地流转与农户生计策略联合决策研究

基于中国家庭追踪调查(CFPS)2014年农村住户数据,采用多元probit模型实证检验了农户土地流转决策、农户种植经济作物决策和非农劳动力转移决策之间的相互影响。研究发现:①农户土地流转与劳动力非农转移和经济作物种植生计决策相互关联。总体而言,土地转入与种植经济作物决策正相关,与非农劳动力转移决策负相关。土地转出与非农劳动力转移决策正相关,与种植经济作物决策负相关。②土地流转与农户非农劳动力转移和经济作物种植等生计策略的关系与农地流转规模相关,小规模和中等规模的土地转入与非农劳动力转移之间未有显著关系,与经济作物种植决策具有显著正向关系,但大规模的土地转入与农户经济作物种植决策和非农就业决策显著负相关。③土地流转是否影响农户生计多样化决策还取决于地区机械化程度。机械化程度较高的平原地区土地转入决策与农户非农劳动力转移和经济作物种植决策未有显著关系,而机械化程度较低的高山、丘陵、高原等地区土地转入决策与农户种植经济作物和非农就业决策分别存在正相关和负相关关系,表明随着机械化对农业劳动力替代程度的增强,土地流转对农户劳动力配置的影响效应减弱。政策建议是:①统筹推进农村土地、劳动力市场发展,推动农户土地流转参与,促进转出户生计向非农专业化转移,促进转入户农地适度规模经营;②完善农机社会化服务市场,提高农机和农技融合使用深度和广度,提高农机对农业劳动力的替代弹性,增强转入户农业劳动力农地规模经营的能力,增加农业生产比较收益。     

作物多样性变化及其对农业产出的影响——基于期望出产和非期望产出的分析

运用中国30个省份1990～2016年的面板数据,从作物多样性视角,采用CDI和d等作物多样性指数,考察了农业种植结构对农业产值和农业面源污染的影响。研究结果表明：作物多样性与农业产值之间存在显著的“倒U型”曲线关系。当前中国非优势作物（比较优势较弱）多样性偏高,对农业产值产生抑制作用,非优势作物多样性每增加1个单位,农业产值将减少1.5%;对农业面源污染产生正向作用,非优势作物多样性每增加1个单位,农业面源污染将增加1.3%。而区域优势作物多样性的增加对农业面源污染有较大的抑制效应,优势作物多样性每增加1个单位,农业面源污染将减少1.5%;作物多样性对种植业产值和农业面源污染综合指数的提高有负面影响;在农业劳动力大量转移背景下,减少作物多样性种植有利于农业产值的提高;当自然灾害较严重时,作物多样性的增加有利于农业产值的增长。因此各区域要立足于本省的资源禀赋条件,减少比较优势较弱的农作物品种和种植面积,增加优势农产品,特色农产品种植,培育农业品牌,以提高农业收入和增强生态环境保护。同时,农业基础设施的完善以及农民防灾减灾意识的提高有利于增强抵御自然灾害的能力,促进绿色的现代化农业的发展。     

Prediction of maximum daily ozone level using combined neural network and statistical characteristics

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. As one of major pollutants, ozone, especially ground level ozone, is responsible for various adverse effects on both human being and foliage. Therefore, prediction of ambient ozone levels in certain environment, especially the ground ozone level in densely urban areas, is of great importance to urban air quality and city image. To date, though several ozone prediction models have been established, there is still a need for more accurate models to develop effective warning strategies. The development of such models is difficult because the meteorological variables and the photochemical reactions involved in ozone formation are very complex. The present work aims to develop an improved neural network model, which combines the adaptive radial basis function (ARBF) network with statistical characteristics of ozone in selected specific areas, and is used to predict the daily maximum ozone concentration level. The improved method is trained and testified by hourly time series data collected at three air pollutant-monitoring stations in Hong Kong during 1999 and 2000. The simulation results demonstrate the effectiveness and the reliability of the proposed method.     

Regionalization of climate scenarios impacts on maize production and the role of cultivar and planting date as an adaptation strategy

Understanding climate change and its impacts on crops is crucial to determine adaptation strategies. Simulations of climate change impacts on agricultural systems are often run for individual sites. Nevertheless, the scaling up of crop model results can bring a more complete picture, providing better inputs for the decision-making process. The objective of this paper was to present a procedure to assess the regional impacts of climate scenarios on maize production, as well as the effect of crop cultivars and planting dates as an adaptation strategy. The focus region is Santa Catarina State, Brazil. The identification of agricultural areas cultivated with annual crops was done for the whole state, followed by the coupling of soil and weather information necessary for the crop modeling procedure (using crop model and regional circulation models). The impact on maize yields, so as the effect of adaptation strategies, was calculated for the 2012–2040 period assuming different maize cultivars and planting dates. Results showed that the exclusion of non-agricultural areas allowed the crop model to correctly simulate local and regional production. Simulations run without adaptation strategies for the 2012–2040 period showed reductions of 11.5–13.5 % in total maize production, depending on the cultivar. By using the best cultivar for each agricultural area, total state production was increased by 6 %; when using both adaptation strategies—cultivar and best planting date—total production increased by 15 %. This analysis showed that cultivar and planting date are feasible adaptation strategies to mitigate deleterious effects of climate scenarios, and crop models can be successfully used for regional assessments.     

Decision support model to select crop pattern for sustainable agricultural practices using fuzzy MCDM

The crop pattern has a significant impact on the feasibility of sustainable agricultural practices. Selected crop pattern influences environmental and economic condition and affects sustainability profoundly in agricultural practices. Hence, a careful intervention is required in the selection of an optimal crop pattern for sustainable agricultural practices. Selection of a particular set of crop pattern depends on many criteria that may vary from place to place thus pose challenges in deciding an optimum crop pattern. The present research focuses on the crop selection pattern in Indian environment that considers comprehensive criteria related to sustainable farming practices. Based on the in-depth review of the literature and experts opinion, comprehensive criteria related to sustainable farming practices for Ravi season crop are identified. Total twelve criteria covering socioeconomic conditions, soil and water conditions, environmental and climatic conditions are earmarked and taken into account for eight most commonly grown crops in Ravi season and later on modeled to determine the crop pattern for most needed sustainability. A fuzzy-based multi-criteria decision-making model has been developed considering the Indian farming system. The scarce resources availability to Indian farmers poses many challenges to practice farming with most needed sustainability. The present research will be useful in the area of Indian farming practices in particular and global farming practices in general. It will also help stakeholders in their cost effective decision making for better crop productivity leading to sustainable farming practices. Additionally, the state policy makers will be able to formulate effective state driven sustainable farming policy to enhance its stake in gross domestic product to become self-reliance.     

基于STIRPAT和GM(1,1)模型的湖南省农地投入碳排放增长机理及趋势预测

探索农地投入的碳排放特征、增长机理及趋势预测,并提出减排对策对农业发展向低碳绿色转型具有重要意义。研究采用回归分析法、STIRPAT和GM(1,1)模型解析湖南省农地投入碳排放增长机理并做出趋势预测。结果表明:2000~2014年湖南省农地投入碳排放量呈上升趋势,年均增长率为3.25%,各类碳源中化肥累计的碳排放量最大,其次是农药;此外翻耕、农药、农膜、柴油、灌溉、化肥累计碳排放年均增长量分别为0.68%、3.22%、7.47%、6.42%、2.57%、3.25%。农业人口、人均农业GDP、机械化水平、农业生产效率、农业产业结构显著影响农地碳排放,各因素每发生1%的变动会相应带来农地碳排放量约0.20%、0.95%、0.12%、0.98%和0.93%的变化。通过GM(1,1)模型对2016~2020年湖南省农地投入碳排放量进行预测,碳排放量呈持续上升趋势,2020年预计达到430.43万t。最后根据研究结果提出促进农地投入碳减排的政策建议。     

涝渍地种植制度与高效农业模式研究

采用了系统工程，生态农业，农业气象，作物栽培，技术经济等管理，通过对江汉平原涝渍地农田生态系统生产性能解析，现有种植制度与新拓高效农业模式分析评价，高效优化机理的探讨，从适应国内外市场需求，有利于农业结构调优，保护资源环境，促进农业可持续发展出发，筛选归纳了四类适宜的高效种植（养）模式，即“稳粮兴油”增值型；“稳棉机动”增值型；“粮经，粮饲兼顾”饲养型；“种地与养地”结合型。上述高效农业模式具有产品优化功能，结构优化功能，缓和大范围洪涝和自我调控补偿功能，它们既自成体系，各显特色，又互成体系，构成粮，经，饲，肥“四元”种植结构。必须实行有序高效模式自身水旱轮作，高效模式与传统耕作制度之间轮作换荐，使之动态优化，保持可持续发展。4种模式在我国南方涝渍地域具有广阔的推广前景，各地可因地制宜进行推广。     

基于ARIMA和BP神经网络组合模型的我国碳排放强度预测

预测我国碳排放强度的长期变动趋势, 对国家进行宏观经济管理和节能减排工作具有重要的参考价值。运用深入分析自回归移动平均模型和神经网络的特性,并在此基础上建立ARIMA模型和BP神经网络组合模型,将碳排放强度的时间序列的数据结构分解为线性和非线性残差部分,对我国碳排放强度的变化趋势进行了综合分析与预测。结果显示:今后10 a我国碳排放强度总体是逐步下降的,但到2020年我国碳排放强度仅比2005年下降34%,比我国政府提出碳排放强度下降40%~45%的目标还有一定的差距。因此,要在2020年实现我国碳排放强度目标,必须要调整宏观经济政策,采取各种政策措施以实现目标