Spatial and temporal variations of soil nutrients of cropland in Northeast China from the 1980s to the 2010s

In recent years, the degradation of cropland soils in Northeast China, such as "thinned, barren, and hardened", has become increasingly serious, with consequences on sustainable development of agriculture. Based on the data from Soil Types of China (1980s) and Soil Series of China (2010s), we examined the change patterns of soil nutrient conditions across different regions and soil types in Northeast China over the past 30 years through the statistical analysis of large samples. The results showed that: 1) from the 1980s to the 2010s, soil nutrient indicators in Northeast China changed to different degrees. Soil pH decreased by 0.03. Soil organic matter (SOM) content decreasd most prominently, by 8.99 g·kg^-1 or 23.6%. Soil total N (TN), total P (TP) and total K (TK) contents showed increasing trends, with increases of 17.1%, 46.8%, and 4.9%, respectively. 2) Changes in soil nutrient indicators differed across different provinces and cities. Soil acidification in Liaoning was the most obvious, with pH decreasing by 0.32. SOM content in Liaoning decreased most significantly, by 31.0%. Soil TN, TP, and TK contents in Liaoning increased most significantly by 73.8%, 248.1% and 44.0%, respectively. 3) The changes of soil nutrients varied greatly among soil types, with brown soil and kastanozems showing the greatest decrease in pH. The SOM content of all soil types showed a decreasing trend, with 35.4%, 33.8% and 26.0% reduction in brown soil, dark brown forest soil and chernozem respectively. The greatest increase in TN, TP and TK contents were observed in brown soil by 89.1%, 232.8%, and 48.5%, respectively. In summary, declining organic matter content and soil acidification were the core problems of soil degradation in Northeast China from the 1980s to the 2010s. Reasonable tillage methods and targeted conservation strategies are critically needed to ensure the sustai-nable development of agriculture in Northeast China.

The Impact of Urban Construction Land Change on Carbon Emissions-A Case Study of Wuhan City

Urban construction land (UCL) change is a significant cause of changes in urban carbon emissions. However, as the extent of this effect is currently unclear, cities cannot easily formulate reasonable carbon reduction policies in terms of land use. Taking the city of Wuhan, China, as an example, this paper combines data on land use and carbon emissions from 1995 to 2019 and uses spatial analysis, curve estimation, and correlation evaluation to explore the direct and indirect effects of the UCL changes on carbon emissions. The results show that: (1) Between 1995 and 2019, the UCL area in Wuhan increased by 193.44%, and carbon emissions increased by 78.63%; moreover, both changes showed a gradually increasing spatial correlation, and the quantitative relationship could be better fitted with a composite function model; (2) The UCL change had mainly an indirect impact on carbon emissions via factors such as population and energy use intensity per unit of carbon emissions; (3) The maximum value of carbon emissions inside a unit area decreased during the study period, with an average annual decrease of about 2.02%. Therefore, the city of Wuhan can promote the achievement of its carbon emissions reduction targets by improving the existing land use policies, for example, by dividing the city into multiple functional zones.

Does Climate Change Increase Crop Water Requirements of Winter Wheat and Summer Maize in the Lower Reaches of the Yellow River Basin?

With increasing water resources stress under climate change, it is of great importance to deeply understand the spatio-temporal variation of crop water requirements and their response to climate change for achieving better water resources management and grain production. However, the quantitative evaluation of climate change impacts on crop water requirements and the identification of determining factors should be further explored to reveal the influencing mechanism and actual effects thoroughly. In this study, the water requirements of winter wheat and summer maize from 1981 to 2019 in the lower reaches of the Yellow River Basin were estimated based on the Penman-Monteith model and crop coefficient method using daily meteorological data. Combined with trends test, sensitivity and contribution analysis, the impacts of different meteorological factors on crop water requirement variation were explored, and the dominant factors were then identified. The results indicated that the temperature increased significantly (a significance level of 0.05 was considered), whereas the sunshine duration, relative humidity and wind speed decreased significantly from 1981 to 2019 in the study area. The total water requirements of winter wheat and summer maize presented a significant decreasing trend (-1.36 mm/a) from 1981 to 2019 with a multi-year average value of 936.7 mm. The crop water requirements of winter wheat was higher than that of summer maize, with multi-year average values of 546.6 mm and 390.1 mm, respectively. In terms of spatial distribution patterns, the crop water requirement in the north was generally higher than that in the south. The water requirements of winter wheat and summer maize were most sensitive to wind speed, and were less sensitive to the minimum temperature and relative humidity. Wind speed was the leading factor of crop water requirement variation with the highest contribution rate of 116.26% among the considered meteorological factors. The results of this study will provide important support for strengthening the capacity to cope with climate change and realizing sustainable utilization of agricultural water resources in the lower reaches of the Yellow River Basin.

Assessing and Validating the Ability of Machine Learning to Handle Unrefined Particle Air Pollution Mobile Monitoring Data Randomly, Spatially, and Spatiotemporally

Many epidemiological studies have evaluated the accuracy of machine learning models in predicting levels of particulate number (PN) and black carbon (BC) pollutant concentrations. However, few studies have investigated the ability of machine learning to predict the pollutant concentration with using unrefined mobile measurement data and explore the reliability of the prediction models. Additionally, researchers are moving away from using fixed-site data in favor of using mobile monitoring data in a variety of locations to develop hourly empirical models of particulate air pollution. This study compared the differences between long-term (daily average) and short-term (hourly average and 1 s unrefined data) model performance in three different classes of cross validation: randomly, spatially, and spatially temporally. This study used secondary data describing BC and PN pollutant levels in the rural location of Blacksburg (VA). Our results show that the model based on unrefined data was able to detect the pollutant hot spot areas with similar accuracy compared to the aggregated model. Moreover, the performance was found to improve when temporal data added to the model: the 10-fold MAE for the BC and PN were 0.44 μg/m³ and 3391 pt/cm³, respectively, for the unrefined data (one second data) model. The findings detailed here will add to the literature on the correlation between data (pre)processing and the efficacy of machine learning models in predicting pollution levels while also enhancing our understanding of more reliable validation strategies.

A simple and rapid in situ method for measuring landfill gas emissions and methane oxidation rates in landfill covers

A newly developed static chamber method with a laser methane detector and a biogas analyser was proposed to measure the landfill gas emissions and methane (CH₄) oxidation rates in landfill covers. The method relied on a laser methane detector for measuring CH₄ concentration, avoiding gas samplings during test and hence the potential interference of gas compositions inside the chamber. All the measurements could be obtained on site. The method was applied to determine the landfill gas emissions and CH₄ oxidation rates in a full-scale loess gravel capillary barrier cover constructed in landfill. Both laboratory calibration and in-situ tests demonstrated that fast (i.e. <20 min) and accurate measurements could be obtained by the proposed method. The method is capable of capturing the significant spatial and temporal variations of the landfill gas emissions and CH₄ oxidation rates in landfill site.

The Response of Net Primary Production to Climate Change: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone in China

The regions in China that intersect the 400 mm annual precipitation line are especially ecologically sensitive and extremely vulnerable to anthropogenic activities. However, in the context of climate change, the response of vegetation Net Primary Production (NPP) in this region has not been scientifically studied in depth. NPP suffers from the comprehensive effect of multiple climatic factors, and how to eliminate the effect of interfering variables in the correlation analysis of NPP and target variables (temperature or precipitation) is the major challenge in the study of NPP influencing factors. The correlation coefficient between NPP and target variable was calculated by ignoring other variables that also had a large impact on NPP. This increased the uncertainty of research results. Therefore, in this study, the second-order partial correlation analysis method was used to analyze the correlation between NPP and target variables by controlling other variables. This can effectively decrease the uncertainty of analysis results. In this paper, the univariate linear regression, coefficient of variation, and Hurst index estimation were used to study the spatial and temporal variations in NPP and analyze whether the NPP seasonal and annual variability will persist into the future. The results show the following: (i) The spatial distribution of NPP correlated with precipitation and had a gradually decreasing trend from southeast to northwest. From 2000 to 2015, the NPP in the study area had a general upward trend, with a small variation in its range. (ii) Areas with negative partial correlation coefficients between NPP and precipitation are consistent with the areas with more abundant water resources. The partial correlation coefficient between the NPP and the Land Surface Temperature (LST) was positive for 52.64% of the total study area. Finally, the prediction of the persistence of NPP variation into the future showed significant differences on varying time scales. On an annual scale, NPP was predicted to persist for 46% of the study area. On a seasonal scale, NPP in autumn was predicted to account for 49.92%, followed by spring (25.67%), summer (13.40%), and winter (6.75%).

[Spatial-Temporal Variations of CO2 and CH4 Flux Through a Water-air Interface Under the Effect of Primary Productivity in Wulixia Reservoir]

In recent years, the effect of greenhouse gas has been a focus. In order to reveal the spatial-temporal variations of CO₂ and CH₄ flux through a water-air interface, Wulixia reservoir was selected as a typical case for measuring CO₂and CH₄ flux using a floating chamber during four study periods in 2016.The primary productivity of the water was also studied. The results indicate that surface-layer water in Wulixia reservoir is a CO₂ sink in summer, varying between -30.14 and -3.47 mg·(m²·h)^-1. However, it is the source of CO₂ in autumn and winter, varying between 15.57 mg·(m²·h)^-1 and 115.06 mg·(m²·h)^-1. The variation of methane flux is obvious in summer, but it is stable in autumn and winter. The spatial distribution of CO₂ and CH₄ show that they are higher in the typical bay area and lower in the tailing dam as well as in the drawdown zone of the reservoir. In addition, the spatial and temporal variation of CO₂ and CH₄ are negatively and positively correlated with primary productivity (r -0.477 and 0.771), respectively. Due to the high activity of photosynthetic micro- organisms in summer, CO₂ can be sequestered, allowing the surface-layer water in Wulixia reservoir to be a CO₂ sink. In addition, methanogenic bacteria can oxidize organic carbon produced by photosynthetic micro-organisms. Therefore, CH₄ has a negative correlation with primary productivity. The results provide important information for the study of microorganism functions in karst water systems.

Soil Water Measurement Using Actively Heated Fiber Optics at Field Scale

Several studies have demonstrated the potential of actively heated fiber optics (AHFO) to measure soil water content (SWC) at high spatial and temporal resolutions. This study tested the feasibility of the AHFO technique to measure soil water in the surface soil of a crop grown field over a growing season using an in-situ calibration approach. Heat pulses of five minutes duration were applied at a rate of 7.28 W m⁻¹ along eighteen fiber optic cable transects installed at three depths (0.05, 0.10 and 0.20 m) at six-hour intervals. Cumulative temperature increase (T_cum) during heat pulses was calculated at locations along the cable. While predicting commercial sensor measurements, the AHFO showed root mean square errors (RMSE) of 2.8, 3.7 and 3.7% for 0.05, 0.10 and 0.20 m depths, respectively. Further, the coefficients of determination (R²) for depth specific relationships were 0.87 (0.05 m depth), 0.46 (0.10 m depth), 0.86 (0.20 m depth) and 0.66 (all depths combined). This study showed a great potential of the AHFO technique to measure soil water at high spatial resolutions (<1 m) and to monitor soil water dynamics of surface soil in a crop grown field over a cropping season with a reasonable compromise between accuracy and practicality.

Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments

Parallel factor analysis (PARAFAC) is a useful multivariate method for decomposing three-way data that consist of three different types of entities simultaneously. This method estimates trilinear components, each of which is a low-dimensional representation of a set of entities, often called a mode, to explain the maximum variance of the data. Functional PARAFAC permits the entities in different modes to be smooth functions or curves, varying over a continuum, rather than a collection of unconnected responses. The existing functional PARAFAC methods handle functions of a one-dimensional argument (e.g., time) only. In this paper, we propose a new extension of functional PARAFAC for handling three-way data whose responses are sequenced along both a two-dimensional domain (e.g., a plane with x- and y-axis coordinates) and a one-dimensional argument. Technically, the proposed method combines PARAFAC with basis function expansion approximations, using a set of piecewise quadratic finite element basis functions for estimating two-dimensional smooth functions and a set of one-dimensional basis functions for estimating one-dimensional smooth functions. In a simulation study, the proposed method appeared to outperform the conventional PARAFAC. We apply the method to EEG data to demonstrate its empirical usefulness.

Patterns of chasmogamy and cleistogamy, a mixed-mating strategy in an endangered perennial

Cleistogamy (CL) in angiosperms historically has been understudied; however, its co-occurrence with chasmogamy (CH) across many plant species suggests a fitness advantage to maintaining this mixed-mating strategy. Maintenance of mixed-mating has been attributed to reproductive assurance, resource allocation or genetic trade-offs. Our goals were to explore patterns of CH and CL, quantify reproductive contributions measured by fruit production and determine how CL is maintained in the endangered perennial Polygala lewtonii. This species exhibits CH and both above-ground cleistogamy (CL-AG) and below-ground cleistogamy (CL-BG). In monthly censuses from 2008 to 2012, we documented flowering patterns by counting CH flowering stems, CL-AG fruits and CL-BG rhizomes per plant. Monitoring of buds on CH flowering stems in 2004 provided an estimate of CH fruits per plant. Plant excavations in 2005 of CL-BG rhizomes provided an estimate of CL-BG fruits per plant. Floral morphs were temporally separated with CH flowers observed from January to May and CL flowers from June to February. Overall, 17.5 % of plants flowered; most plants expressed CH first in spring months (63.4 %) and the rest initiated CL-AG in fall months. Reproductive output was dominated by CH (median 26 fruits) compared to combined CL (median 3.5 fruits). Annual reproductive effort of CL-AG was positively correlated with plant age while CH had no relation. Our research shows CH as the dominant form of reproductive effort with most individuals expressing CH and through greater reproductive contributions. CL appears limited by plant size or resources based on the positive relationship with plant age. CL dependency on resource availability is common in other species found in dry or low-quality habitats; however, CL contributions in this species are comparatively low. This raises more questions related to energy requirements of both floral morphs, how this affects the production of viable progeny and why CL persists.

Acarological Risk of Borrelia burgdorferi Sensu Lato Infections Across Space and Time in The Netherlands

A longitudinal investigation on tick populations and their Borrelia infections in the Netherlands was undertaken between 2006 and 2011 with the aim to assess spatial and temporal patterns of the acarological risk in forested sites across the country and to assess variations in Borrelia genospecies diversity. Ticks were collected monthly in 11 sites and nymphs were examined for Borrelia infections. Tick populations expressed strong seasonal variations, with consistent and significant differences in mean tick densities between sites. Borrelia infections were present in all study sites, with a site-specific mean prevalence per month ranging from 7% to 26%. Prevalence was location-dependent and was not associated with tick densities. Mean Borrelia prevalence was lowest in January (4%), gradually increasing to reach a maximum (24%) in August. Borrelia afzelii represented 70% of all infections, with Borrelia burgdorferi sensu stricto, Borrelia garinii, and Borrelia valaisiana represented with 4%, 8%, and 10%, respectively. The density of infected nymphs and the proportional distribution of the four Borrelia genospecies, were significantly different between sites. The results show a consistent and significant spatial and temporal difference in acarological risk across the Netherlands.

Spatial and temporal variation of heavy metal risk and source in sediments of Dongting Lake wetland, mid-south China

Surface sediments of Dongting Lake wetland were collected from ten sites to investigate variation trend, risk and sources of heavy metal distribution in dry seasons of 2011∼2013. The three-year mean concentrations (mg/kg) of Cr, Cu, Pb, Cd, Hg and As were 91.33, 36.27, 54.82, 4.39, 0.19 and 25.67, respectively, which were all higher than the corresponding background values. Sediment quality guidelines (SQGs) and Geo-accumulation index (Igeo) were used for the assessment of pollution level of heavy metals. The pollution risk of Cd, Hg and As were great and that of Cr needed urgent attention because of its obvious increase. Pollution load index (PLI) and geographic information system (GIS) methods were conducted to assess spatial and temporal variation of heavy metal contamination. Results confirmed an increased contamination contribution inflow from Xiang River. Multivariate statistical analyses were applied to identify contribution sources of heavy metal, which showed anthropogenic origin mainly from mining, smelting, chemical industry and agricultural activity.

Evaluation of changes in effluent quality from industrial complexes on the Korean nationwide scale using a self-organizing map

One of the major issues related to the environment in the 21st century is sustainable development. The innovative economic growth policy has supported relatively successful economic development, but poor environmental conservation efforts, have consequently resulted in serious water quality pollution issues. Hence, assessments of water quality and health are fundamental processes towards conserving and restoring aquatic ecosystems. In this study, we characterized spatial and temporal changes in water quality (specifically physico-chemical variables plus priority and non-priority pollutants) of discharges from industrial complexes on a national scale in Korea. The data were provided by the Water Quality Monitoring Program operated by the Ministry of Environment, Korea and were measured from 1989 to 2008 on a monthly basis at 61 effluent monitoring sites located at industrial complexes. Analysis of monthly and annual changes in water quality, using the seasonal Mann-Kendall test, indicated an improvement in water quality, which was inferred from a continuous increase in dissolved oxygen and decrease in other water quality factors. A Self-Organizing Map, which is an unsupervised artificial neural network, also indicated an improvement of effluent water quality, by showing spatial and temporal differences in the effluent water quality as well as in the occurrence of priority pollutants. Finally, our results suggested that continued long-term monitoring is necessary to establish plans and policies for wastewater management and health assessment.

Spatial and temporal variations and mobile source emissions of polycyclic aromatic hydrocarbons in Quito, Ecuador

Motor vehicles are a major source of air pollution in Quito, Ecuador; however, little work has been done to characterize spatial and temporal variations in traffic-related pollutants, or to measure pollutants in vehicle emissions. We measured PAH continuously for one year at two residential sites in Quito, and PAH and traffic patterns for one week near a busy roadway. Morning rush-hour traffic and temperature inversions caused daily PAH maxima between 06:00 and 08:00. SO2, NOx, CO, and PM(2.5) behaved similarly. At the residential sites PAH levels during inversions were 2-3-fold higher than during the afternoon, and 10-16-fold higher than 02:00-03:00 when levels were lowest. In contrast, at the near-roadway site, PAH concentrations were 3-6-fold higher than at the residential sites, and the effects of inversions were less pronounced. Cars and buses accounted for >95% of PAH at the near-roadway site. Near-roadway PAH concentrations were comparable to other polluted cities.