A land use regression for predicting NO2 and PM10 concentrations in di erent seasons in Tianjin region, China

Land use regression (LUR) model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression (MLR) equations were established based on the most significant variables for NO2 in heating season (R2 = 0.74), and non-heating season (R2 = 0.61) in the whole study area; and PM10 in heating season (R2 = 0.72), and non-heating season (R2 = 0.49). Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations (resolution is 10 km). Intercepts of MLR equations were 0.050 (NO2, heating season), 0.035 (NO2, non-heating season), 0.068 (PM10, heating season), and 0.092 (PM10, non-heating season) in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 (NO2, heating season), 0.043 (NO2, non-heating season), 0.087 (PM10, heating season), and 0.096 (PM10, non-heating season). These intercept values might imply an area’s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. R2 values increased 0.09 (heating season) and 0.18 (non-heating season) for NO2, and 0.08 (heating season) and 0.04 (non-heating season) for PM10. In terms of R2, LUR model performed more e ectively in heating season than non-heating season in the study area and gave a better result for NO2 compared with PM10.     

A land use regression model incorporating data on industrial point source pollution

Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land use regression (LUR) models for SO₂, NO₂ and PM₁₀ for Tianjin, China. Traffic volumes, road networks, land use data, population density, meteorological conditions, physical conditions and satellite-derived greenness, brightness and wetness were used for predicting SO₂, NO₂ and PM₁₀ concentrations. We incorporated data on industrial point sources to improve LUR model performance. In order to consider the impact of different sources, we calculated the PSIndex, LSIndex and area of different land use types (agricultural land, industrial land, commercial land, residential land, green space and water area) within different buffer radii (1 to 20 km). This method makes up for the lack of consideration of source impact based on the LUR model. Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO₂ and NO₂. R² values of the multiple linear regression equations for SO₂, NO₂ and PM₁₀ were 0.78, 0.89 and 0.84, respectively, and the RMSE values were 0.32, 0.18 and 0.21, respectively. Model predictions at validation monitoring sites went well with predictions generally within 15% of measured values. Compared to the relationship between dependent variables and simple variables (such as traffic variables or meteorological condition variables), the relationship between dependent variables and integrated variables was more consistent with a linear relationship. Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.     

基于土地利用回归模型的北京市2013-2019年大气污染时空变化分析

在近年来大力控制大气污染的背景下,通过历史观测数据分析污染物的时空变化特征,有助于总结以往控制的成效,并为制定下一阶段措施提供科学依据.本研究基于北京市大气环境质量监测站点2013-2019年数据,分析了 6种常规大气污染物(PM2.5、NO2、O3、PM10、SO2、CO)的时间变化趋势,并构建了 2013和2019...     

利用LUR模型模拟天津市大气污染物浓度的空间分布

针对传统监测方法无法满足对大气污染物空间分布高分辨率的要求,以Arcgis为平台,利用LUR模型模拟天津市PM10和NO2年均浓度的空间分布.选取的回归变量为1~4km半径缓冲区内的道路总长度、不同土地利用类型的面积、人口密度、风向指数及距海距离,选取3个监测点的监测数据对方程进行了验证.结果表明,对PM10年均浓度影响最大的因素是缓冲区为1km的道路总长度(R2为0.560),而对NO2年均浓度影响最大的因素是人口密度(R2为0.414).多元线性回归方程计算结果显示,PM10和NO2的R2分别达到0.946和0.691;如果考虑风向的影响,R2可分别提高到0.980和0.849.对天津市中心城区建立5km′5km网格嵌套,根据多元线性回归方程计算每个网格交点的污染物浓度模拟值.通过kriging插值得到2种污染物在天津市中心城区的空间模拟分布图.PM10年均浓度分布以研究区中心最高,向四周逐渐降低;NO2的年均浓度以研究区中心最低,向四周逐渐升高.模拟结果与实际情况相符.     

Influence of urban spatial and socioeconomic parameters on PM2.5 at subdistrict level: A land use regression study in Shenzhen, China

The intraurban distribution of PM_2.5 concentration is influenced by various spatial, socioeconomic, and meteorological parameters. This study investigated the influence of 37 parameters on monthly average PM_2.5 concentration at the subdistrict level with Pearson correlation analysis and land-use regression (LUR) using data from a subdistrict-level air pollution monitoring network in Shenzhen, China. Performance of LUR models is evaluated with leave-one-out-cross-validation (LOOCV) and holdout cross-validation (holdout CV). Pearson correlation analysis revealed that Normalized Difference Built-up Index, artificial land fraction, land surface temperature, and point-of-interest (POI) numbers of factories and industrial parks are significantly positively correlated with monthly average PM_2.5 concentrations, while Normalized Difference Vegetation Index and Green View Factor show significant negative correlations. For the sparse national stations, robust LUR modelling may rely on a priori assumptions in direction of influence during the predictor selection process. The month-by-month spatial regression shows that RF models for both national stations and all stations show significantly inflated mean values of R² compared with cross-validation results. For MLR models, inflation of both R² and R²_CV was detected when using only national stations and may indicate the restricted ability to predict spatial distribution of PM_2.5 levels. Inflated within-sample R² also exist in the spatiotemporal LUR models developed with only national stations, although not as significant as spatial LUR models. Our results suggest that a denser subdistrict level air pollutant monitoring network may improve the accuracy and robustness in intraurban spatial/spatiotemporal prediction of PM_2.5 concentrations.     

中国土地可持续利用指标体系的理论与方法

制定土地资源可持续性指标体系是《21世纪议程》中对各国提出的科学技术优先研究领域 ,国土资源部已开始了该研究项目。论文就此对中国土地资源可持续利用指标体系的理论与方法从整体上进行了探讨。首先回顾了国内外土地可持续利用研究的进展 ,分析归纳了国外可持续发展指标体系研究状况及可借鉴之处 ;指出在土地可持续利用指标与评价的研究中 ,必须从3个方面开展深入探讨。第一是土地利用分区及制定区域性土地可持续利用指标体系 ;第二是研究制定主要土地利用系统可持续利用指标体系及其阈值 ;第三是研究制定典型区域(以县域为单位)土地可持续利用指标体系及其阈值。只有把3个方面的研究有机融合起来 ,互相反馈 ,互为依存 ,才能保证土地可持续利用指标体系的科学性、系统性和实用性。     

Ecological planning of land use in the central area of Tianjin,China

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天津PM10和NO2输送路径及潜在源区研究

利用HYSPLIT模型和全球资料同化系统(GDAS)气象数据,用聚类方法对2012年12月~2013年11月期间抵达天津的逐日72h气流后向轨迹按不同的季节进行归类.并利用相应的PM10和NO2浓度日监测数据,分析了不同季节气流轨迹对天津污染物浓度的影响.运用潜在源贡献(PSCF)因子分析法和浓度权重轨迹(CWT)分析法分别模拟了不同季节PM10和NO2潜在PSCF和CWT.结果表明,不同方向气流轨迹对天津PM10和NO2潜在源区分布的影响存在显著差异.天津PM10和NO2日均浓度最高值对应的气流轨迹均集中在冬、春和秋季等来自内陆的西北气流;夏季影响天津的气流轨迹主要来自西北和东南方向,对天津PM10和NO2的日均浓度贡献较小.天津PM10和NO2的PSCF与CWT分布特征类似,最高值主要集中在天津本地以及邻近的河北省和山东省,是天津这两种污染物主要潜在源区.     

基于GIS和LUR模型的西安市PM2.5浓度空间分布模拟研究

基于地理信息系统GIS和土地利用回归LUR模型,模拟西安市PM2.5浓度空间动态分布,结果表明:与PM2.5浓度相关性最高的分别为缓冲区为2 km的水域面积、人口密度和距离水域距离,R 2分别为0.501,0.393和0.280;与PM2.5浓度相关性最低的分别为缓冲区为4 km的水域面积、未利用地面积和耕地面积,R 2分别为0.039、0.021和0.017.未考虑风速建立的LUR模型多元回归的相关系数为0.856,R 2为0.733,考虑风速的相关系数为0.892,R 2为0.796,表明风速对于污染物的分布影响较大,LUR模型模拟效果较好.模拟的PM2.5年均浓度高风险区分布于中部,中风险区分布于中西部,低风险区分布于东南部和西部.     

太湖地区蠡河流域不同用地类型面源污染特征

以太湖上游蠡河流域为研究区,通过对面源污染为主子流域和城镇地表径流进行监测,结合GIS空间分析方法,分析了流域林地、耕地及城镇用地等土地利用类型的面源污染流失特征.结果表明,林地产出径流面源COD、TN和TP浓度分别为2.987±1.582,1.690±0.349,0.019±0.009mg/L;耕地的产出径流面源COD、TN和TP浓度分别为9.874±5.146,2.534±2.459,0.185±0.149mg/L;小城镇的产出径流面源COD、TN和TP浓度分别为7.729,1.790,0.117mg/L.蠡河流域的面源污染COD、TN和TP负荷量分别为919.9,306.0,13.5t/a.     

沂河流域土地利用时空变化图谱特征分析

基于沂河流域1995年、2005年和2015年土地利用空间数据,运用地学信息图谱方法构建1995-2005年和2005-2015年两个时序单元的土地利用转移图谱和涨落势图谱,分析了沂河流域近20年来的土地利用时空变化规律及发展过程。结果表明：（1）1995-2015年,沂河流域土地利用结构以耕地和林地为主,其中耕地和草地减少,林地和建设用地增加是主要变化趋势。（2）土地利用转移图谱以耕地与林地、草地之间的相互转换以及建设用地占用耕地为主,林地、草地转变为耕地主要发生在费县和平邑县中部地势平缓的山前平原,耕地转变为林地、草地则主要分布于研究区北部和西南部土壤侵蚀较为严重的山区,耕地转变为建设用地主要集中在各县市城区周边经济相对发达的区域。两个时序单元中,发生变化的主要图谱单元类型及面积存在显著差异,2005-2015年土地利用发生转换的空间进一步扩张。（3）土地利用涨势图谱中新增耕地面积最大,占新增面积的比例为33.87%;落势图谱中耕地萎缩面积最大,占萎缩面积的比例为51.38%。两个时序单元中,各县市涨落势图谱变化存在明显差异。该研究可为沂河流域土地资源的可持续利用及生态建设提供科学依据。     

Pollutant concentrations and pollution loads in stormwater runoff from different land uses in Chongqing

To investigate the distribution of pollutant concentrations and pollution loads in stormwater runoff in Chongqing,six typical land use types were selected and studied from August 2009 to September 2011.Statistical analysis on the distribution of pollutant concentrations in all water samples shows that pollutant concentrations fluctuate greatly in rainfall-runoff,and the concentrations of the same pollutant also vary greatly in different rainfall events.In addition,it indicates that the event mean concentrations (EMCs) of total suspended solids (TSS) and chemical oxygen demand (COD) from urban traffic roads (UTR) are significantly higher than those from residential roads (RR),commercial areas (CA),concrete roofs (CR),tile roofs (TRoof),and campus catchment areas (CCA);and the EMCs of total phosphorus (TP) and NH3-N from UTR and CA are 2.35-5 and 3 times of the class-III standard values specified in the Environmental Quality Standards for Surface Water (GB 3838-2002).The EMCs of Fe,Pb and Cd are also much higher than the class-III standard values.The analysis of pollution load producing coefficients (PLPC) reveals that the main pollution source of TSS,COD and TP is UTR.The analysis of correlations between rainfall factors and EMCs/PLPC indicates that rainfall duration is correlated with EMCs/PLPC of TSS for TRoof and TP for UTR,while rainfall intensity is correlated with EMCs/PLPC of TP for both CR and CCA.The results of this study provide a reference for better management of non-point source pollution in urban regions.     

我国北方沙漠化地区的土地利用结构优化研究

利用多元统计方法中的因子分析,对我国北方沙漠化地区县市级行政区的土地利用结构进行了综合评价。基于中国生态地理区域系统,对含有结构性映射综合得分值的评价单元进行了归并,从而实现了对研究区土地利用结构的综合数值分区。利用典型区土地资源遥感调查和评价结果,以及新近权威性的县市级土地利用详查结果,探讨了相应土地利用结构区内土地利用存在的问题,并提出了土地利用结构优化调整的方向。     

Seasonal variation of nitrogen-concentration in the surface water and its relationship with land use in a catchment of northern China

Surface waters can be contaminated by human activities in two ways: (1) by point sources, such as sewage treatment discharge and storm-water runoff; and (2) by non-point sources, such as runoff from urban and agricultural areas. With point-source pollution effectively controlled, non-point source pollution has become the most important environmental concem in the world. The formation of non-point source pollution is related to both the sources such as soil nutrient, the amount of fertilizer and pesticide applied, the amount of refuse, and the spatial complex combination of land uses within a heterogeneous landscape. Land-use change, dominated by human activities, has a significant impact on water resources and quality. In this study, fifteen surface water monitoring points in the Yuqiao Reservoir Basin, Zunhua, Hebei Province, northem China, were chosen to study the seasonal variation of nitrogen concentration in the surface water. Water samples were collected in low-flow period(June), high-flow period(July) and mean-flow period(October) from 1999 to 2000. The results indicated that the seasonal variation of nitrogen concentration in the surface water among the fifteen monitoring points in the rainfall-rich year is more complex than that in the rainfall-deficit year. It was found that the land use, the characteristics of the surface river system, rainfall, and human activities play an important role in the seasonal variation of N-concentration in surface water.Keywords: non-point source pollution; nitrogen concentration; seasonal variation; land use; Yuqiao Reservoir Basin, China     

鄂南4种典型土地利用方式红壤CO2排放及其影响因素

以湖北省咸宁地区分布的红壤为研究对象,采用静态箱法对4种典型土地利用方式（水稻-油菜轮作田,旱地,林地,果园）土壤CO₂的排放特征及其相关影响因子进行了观测研究.结果表明,4种利用方式土壤CO₂的年排放总量从高到低分别为水稻-油菜轮作田1 129 g/(m²·a),果园828 g/(m²·a),旱地632 g/(m²·a),林地533 g/(m²·a).土壤CO₂排放通量呈现明显的季节性变异,水田夏季淹水期排放低,而其它3种土壤都是夏季最高,春秋次之,冬季最低,并与对应的大气温度、土壤温度变化趋势基本一致.其中5 cm地温与4种土壤CO₂排放通量均成极显著的相关关系,且以林地的相关性最大.除水田外,其它土壤CO₂排放通量与大气温度均呈显著正相关关系.根据5 cm地温与CO₂排放通量的相关方程计算得出,4种利用方式红壤的Q₁₀分别为水田1.51,果园1.88,林地2.08,旱地2.7.土壤CO₂排放通量与土壤WFPS之间并没有明显的相关关系.土壤可溶性有机碳（DOC）含量与CO₂排放通量的变化趋势基本一致,且DOC在降水或淹水的情况下显著增大.     

黄土丘陵区土地利用变化对深层土壤有机碳储量的影响

通过研究黄土丘陵子午岭林区5种典型土地利用类型土壤剖面有机碳分布特征,分析了天然乔木林转变为人工乔木林、天然乔木林转变为农田、天然灌木林转变为农田及撂荒后土壤有机碳变化特征.同时,以浅层(0~100 cm)土壤为对照,探讨了土地利用变化对深层(100~200cm)土壤有机碳储量的影响.结果表明,在0~200 cm剖面上,天然乔木林、天然灌木林、人工乔木林、撂荒地、农田土壤有机碳含量分别为5.85、3.96、4.98、3.09、3.20 g·kg-1,天然乔木林、人工乔木林土壤有机碳含量显著高于天然灌木林、撂荒地和农田(p0.05).各土地利用类型下浅层和深层土壤有机碳含量分别占0~200 cm土壤有机碳含量的58%~73%和27%~42%,不同土地利用类型间浅层土壤有机碳含量差异显著,但深层土壤有机碳含量差异不大.土地利用变化对土壤有机碳储量影响显著.天然乔木林转变为人工乔木林、天然乔木林转变为农田、天然灌木林转变为撂荒地、天然灌木林转变为农田4种土地利用转变方式0~200 cm土壤有机碳储量分别减少了9.68、52.90、20.20、12.49 t·hm-2,减幅为7%、39%、21%、13%,其中,浅层土壤减少了2%~48%,深层土壤减少了12%~22%.相对于林地开垦为农田而言,农田退耕还林后土壤有机碳的恢复要慢得多.研究结果揭示了浅层和深层土壤有机碳对土地利用变化的敏感性,反映了深层土壤有机碳具有较大的稳定性.     

不同利用方式对江西省农田土壤碳氮磷生态化学计量特征的影响

根据江西省2013年采集的16582个农田耕层(0～20 cm)土壤样点数据,运用实地调查、经典统计学与地统计学等相结合方法,研究了江西省耕地土壤碳氮磷生态化学计量特征的空间变异性及不同农田利用方式对其的影响.研究结果表明:江西省耕地土壤有机碳(SOC)、全氮(TN)和全磷(TP)平均含量分别为17.90、1.58和0.52 g·kg~(-1),土壤碳氮比(C∶N)、碳磷比(C∶P)和氮磷比(N∶P)平均值分别为11.72、38.29和3.38,土壤C∶N∶P比平均值为34.44∶3.03∶1,说明P是江西省耕地土壤主要的限制因素.此外,由于碳、氮、磷三者之间并不存在显著的两两相关性,表明江西省耕地土壤中不存在稳定的"Redfield ratio";半方差函数表明,江西省土壤碳、氮、磷生态化学计量特征具有中等程度的空间变异性,其空间变异特征主要受到随机性因素的影响;经ANOVA检验显示,不同农田利用方式对土壤碳氮磷生态化学计量特征影响显著(p0.05),土壤SOC和TN平均含量依次表现为:两季水田水旱轮作一季水田一季旱地两季旱地,土壤TP平均含量依次表现为:两季旱地两季水田一季水田一季旱地水旱轮作,土壤C∶N依次表现为:两季水田两季旱地一季水田水旱轮作一季旱地,土壤C∶P平均值依次表现为:水旱轮作两季水田一季水田一季旱地两季旱地,土壤N∶P平均值依次表现为:水旱轮作一季旱地两季水田一季水田两季旱地.总体而言,土壤碳、氮、磷生态化学计量比的变化特征是农田利用方式和环境因子综合作用的结果,土壤C∶N∶P比对土壤碳、氮、磷储量及养分的限制性具有重要的指示作用.     

Irrigation system and land use effect on surface water quality in river, at lake Dianchi, Yunnan, China

The surface water samples were collected in river Dahe and its tributaries, which flow into severely eutrophic lake Dianchi, Yunnan Province, China, in order to elucidate factors controlling water quality fluctuations. The temporal and spatial distribution of water quality tendency was observed. The water quality of each river is dependent on the hydrology effect such water gate and circulating irrigation system. We must consider the hydrology effect to accurately understand water quality variations of river in this study field. In river without highly circulating irrigation system or water gate effect, the downstream nitrate nitrogen (NO₃-N) concentration increase occurred in area dominated by open field cultivation, whereas the NO₃-N concentration was constant or decreased in area dominated by greenhouse land use. This result suggests that greenhouse covers the soil from precipitation, and nitrate load of greenhouse could be less than that of open field cultivation while the rainfall event. In the upper reaches of river, where is dominated by open field cultivation, there were no sharp increase dissolved molybdate reactive phosphorus and total phosphorus concentration, but P load was accumulated in the lower reaches of river, whose predominant land use is greenhouse. Although the P sources is unclear in this study, greenhouse area may have potential of P loads due to its high P content in greenhouse soil. Considering hydrology effect is necessary to determine what the major factor is influencing the water quality variation, especially in area with highly complicated irrigation system in this studying site.     

基于GIS和分形理论的土地利用空间格局分析——以闽侯县为例

以闽侯县1994年、2004年和2015年三期遥感影像为数据源,在RS、GIS和统计分析工具的支持下,运用分形理论研究时间序列上土地利用类型形态的复杂度与结构的稳定度,分析土地利用空间格局的变化,从而阐述不同土地利用类型的空间分布规律。结果表明:(1)研究期间内闽侯县的土地利用类型形态有了很大的变化,林地、耕地和未利用地面积大幅度减少,建设用地面积持续增加,水域面积变化不大;(2)整体分形维数保持下降趋势,从1994年的1.3504降到2015年的1.3333,说明空间格局总体向简单化、稳定化方向发展;(3)闽侯县各主要地类的分形维数和稳定性指数变化特点存在较大差异,耕地、林地和未利用地的分形维数持续下降,土地利用类型形态趋向规则;水域的分形维数先减后增,结构趋向稳定;建设用地的分形维数先增后减,空间结构整体趋于稳定,布局趋向合理化。土地利用的复杂性和稳定性受到人为因素的影响强烈,通过对土地利用空间格局演变的研究,可以为政府协调水土开发、区域土地合理利用以及优化土地利用结构提供支持。     

Impact of fertilization on chestnut growth, N and P concentrations in runo water on degraded slope land in South China

Growing fruit trees on the slopes of rolling hills in South China was causing serious environmental problems because of heavy application of chemical fertilizers and soil erosion. Suitable sources of fertilizers and proper rates of applications were of key importance to both crop yields and environmental protection. In this article, the impact of four fertilizers, i.e., inorganic compound fertilizer, organic compound fertilizer, pig manure compost, and peanut cake （peanut oil pressing residue）, on chestnut （Castanea mollissima Blume） growth on a slope in South China, and on the total N and total P concentrations in runoff waters have been investigated during two years of study, with an orthogonal experimental design. Results show that the organic compound fertilizer and peanut cake promote the heights of young chestnut trees compared to the control. In addition, peanut cake increases single-fruit weights and organic compound fertilizer raises single-seed weights. All the fertilizers increased the concentrations of total N and total P in runoff waters, except for organic compound fertilizer, in the first year experiment. The observed mean concentrations of total N varied from 1.6 mg/L to 3.2 mg/L and P from 0.12 mg/L to 0.22 mg/L, which were increased with the amount of fertilizer applications, with no pattern of direct proportion. On the basis of these experiment results, organic compound fertilizer at 2 kg/tree and peanut cake at 1 kg/tree are recommended to maximize chestnut growth and minimize water pollution.