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921.
高时空分辨率的近地面臭氧浓度分布数据对监测和防控大气臭氧污染,提高人居环境具有重要意义. 使用TROPOMI-L3 NO2、 HCHO产品和ERA5-land高分辨率数据作为估算变量,构建XGBoost-LME模型估算京津冀地区近地面臭氧浓度. 结果表明:①在估算变量中地表2 m温度(T2M)、2 m露点温度(D2M)、地表太阳向下辐射(SSRD)、对流层甲醛(HCHO)和对流层二氧化氮(NO2)是影响京津冀地区近地面臭氧浓度的重要因素,其中T2M、SSRD和D2M相关系数分别达到0.82、0.75和0.71. ②XGBoost-LME模型相较其它模型,其各项指标均为最优,十折交叉验证R2、MAE和RMSE分别为0.951、 9.27 μg·m-3和13.49 μg·m-3,同时,该模型在不同时间尺度均表现良好. ③在时间上,2019年京津冀地区近地面臭氧浓度存在显著的季节性差异,四季浓度变化为:夏季>春季>秋季>冬季,2019年该地区近地面臭氧月均浓度总体呈现出先上升后下降的倒“V”趋势,其中9月呈现小幅上升趋势,全年最大值出现在7月,最小值在12月;在空间分布上,2月和3月京津冀全域近地面臭氧浓度分布基本为同一水平,1、11和12月呈现出不显著的北高南低的空间分布趋势,其余月份该地区近地面臭氧浓度空间分布均呈现出南高北低的分布特征,高值区主要在南部海拔较低、人口密集和工业排放量较大的平原地区,低值区则主要在北部海拔较高、人口稀疏、植被覆盖率高和工业排放量低的山地地区. 相似文献
922.
重金属污染土壤的治理方法 总被引:50,自引:0,他引:50
从工程措施、生物措施、改良措施和农业措施四个方面较全面地介绍了国内外重金属污染土壤的治理方法,并就其原理、实例、优缺点和合理应用等问题做了简要阐述。 相似文献
923.
924.
Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems. 相似文献
925.
Bioavailability and toxicity of cadmium to microorganisms and their activities in soil: a review 总被引:7,自引:0,他引:7
Significant quantities of cadmium (Cd) have been added to the soils globally due to various anthropogenic activities, raising concerns for environmental health. Microorganisms play a unique role in the soil ecosystem, because of their contributions to soil fertility. Contrasting trends, reported on the toxic effects of heavy metals including Cd on soil microorganisms and their activities, are attributable to short-term studies often limited to a single soil type and conducted under controlled laboratory conditions. There is a paucity of reliable field data on Cd alone, since most field studies on Cd-microorganism interactions in soils are based on sewage sludge containing multimetals and organic substances. No single parameter can be used to generalize Cd toxicity and different parameters can provide contrasting results. A battery of relevant tests, rather than just one single assay, involving important microbial activities should therefore be included in ecotoxicity studies. The bioavailability of Cd and associated toxicity to soil biota vary with time, soil type, speciation, ageing, Cd-source, organisms and the environmental factors. The available fraction or soil solution Cd, and not the total concentration of Cd, seems to correlate well with the toxicity parameters. 相似文献
926.
通过红黄泥和紫潮泥两种土壤淹水培养和硒的价态测定结果表明:在450mV培养下,外加Se(Ⅵ)第1天有57.2%仍保持Se(Ⅵ),23.4%还原为有机Se,培养过程中Se(Ⅵ)呈稳定态,有机Se则氧化成Se(Ⅵ),反应为准一级动力学方程;在175mV培养下,外加Se(Ⅵ)第1天有81.8%还原为有机Se,8.9%还原为有机Se,8.9%为Se(Ⅵ),培养过程中有机Se呈稳定态,Se(Ⅵ)则还原为Se(Ⅵ),反应符合动力学一级方程。土壤中Se(Ⅵ)/Se(Ⅳ)体系氧化还原反应的临界电位为71.4mV-206.1mV(pH7.0),土壤pH上升1个单位,电位相应降低40.1mV.Se(Ⅵ)/Se(Ⅳ)体系在土壤氧化还原顺序中的反应次序居猛体系之后,与铁体系平行。 相似文献
927.
Simulation models are widely used to assess the impacts of management and environmental variables on soil organic matter dynamics, to address questions on ecosystem sustainability and carbon cycling under global change. We tested the Century ecosystem model for two long-term experiments in north-eastern Italy: one (SF) comparing nutrient management treatments in small confined plots containing widely contrasting soil types (i.e., sandy, clay and peat) and the other (CR) involving a field study with crop rotation, nutrient, and management intensity variables. The organic matter changes in the SF experiment, showed a strong, linear relationship with C inputs from crop residues and added manures in the sand and clay soils, which was closely mimicked by the model. There was a net loss of soil C for all treatments in the peat soil, but the rate and overall magnitude of C losses were accurately simulated by the model, which suggested that treatment effects on soil C inputs was the major determinant of SOC dynamics in all three soils. In the CR experiment the model reasonably simulated the large initial decline (averaging about 30% of initial levels) in SOC observed in all treatments, as well as mean treatment effects over the course of the experiment. The model predicted a general pattern of higher SOC in the high management intensity, high fertility treatment combinations and lower SOC in the low management intensity, low fertility treatments; however, observed soil C did not show a clear pattern related to the treatments. Simulated soil C contents were linearly related to C input levels in the different treatments while there was no significant relationship between measured soil C and C inputs based on observed data. 相似文献
928.
929.
G. Ruysschaert J. Poesen G. Verstraeten G. Govers 《Agriculture, ecosystems & environment》2007,120(2-4):153-165
Soil erosion studies on cropland usually only consider water, wind and tillage erosion. However, significant amounts of soil are also lost from the field during the harvest of crops such as sugar beet (Beta vulgaris L.), potato (Solanum tuberosum L.), chicory roots (Cichorium intybus L.), cassava (Manihot spp.) and sweet potato (Ipomoea batatas (L.) Lam). During the harvest soil adhering to the crop, loose soil or soil clods and rock fragments are exported from the field together with these crops.This soil erosion process is referred to as ‘soil losses due to crop harvesting’ (SLCH). Most of the studies investigated SLCH variability and its controlling factors for one crop type in similar agro-ecological environments and for comparable harvesting techniques. In this study, a compilation of SLCH studies was made in order to investigate the effect of crop type, agricultural systems, ecological conditions and harvesting technique on SLCH variability. SLCH rates ranged from few to tens of Mg ha−1 harvest−1 and SLCH was highly variable both in space and time. Comparison of four studies on SLCH for sugar beet revealed that harvesting technique and soil moisture content at harvesting time can be equally important for SLCH variability. The occurrence of soil clods harvested with the crop explained why SLCH was significantly larger for mechanically harvested potato in Belgium compared to manually harvested potato in China. SLCH values for manually harvested sugar beet, potato, cassava and sweet potato in China and Uganda were in general smaller than SLCH values for mechanically harvested sugar beet, potato and witloof chicory roots measured in Belgium and France. However, SLCH may also vary significantly within Europe due to differences in harvesting techniques. Soil moisture content at harvesting time was besides harvesting technique one of the key factors controlling SLCH variability. There were no systematic differences in SLCH between crop types, although the soil–crop contact area–crop mass ratio could explain more than 40% of the means from several SLCH studies. 相似文献
930.