Search

Trace elements are essential nutrients for plant growth. An accurate prediction of soil available trace elements is necessary for scientifically based fertilization and soil environmental protection. In total, 670 surface soil samples were collected across the study area to analyze the relationship between soil properties and available trace elements (Cu, Zn, Fe, Mn, B, and Mo). Moreover, the Bayesian maximum entropy (BME) technique was employed to predict the spatial distribution of the trace elements by combining soil property information as auxiliary data. In addition, the prediction accuracy of the BME technique was compared with that of the conventional cokriging (CK) method. The results showed that soil macronutrients, especially organic matter, available P, available K and slow-release K, were significantly correlated with the content of the available trace elements. Soil texture also had great influences on trace elements and was generally represented as clay > heavy loam > medium loam > light loam. The BME technique combined with auxiliary soil property information (both categorical and numerical) performed better than the traditional CK technique, which was supported by the smaller MAE and RMSE and higher R2 from the ten-fold cross validation. By mapping the spatial prediction error difference between the BME and CK methods across the study area, in comparison to the CK method, the BME technique provided consistently more accurate spatial predictions of trace element concentrations. In conclusion, with the advantages of combining categorical and numerical auxiliary data, the BME technique is a suitable spatial prediction method, and the results obtained in local regions could provide an important reference for the scientific application of microfertilizers.

To quantitatively assess heavy metal accumulation and potential ecological and human health risks as well as analyze the sources of metals in a typical soil-rice system located on the southeast coast of China, 120 topsoil samples and corresponding rice grain samples were collected across the study area. The concentrations of As, Cd, Pb, Cr, Hg, Zn, Cu, and Ni were analyzed. The results revealed that Hg, Cd, and Cu were the main pollutants in soils. Besides, according to geo-accumulation value of Hg, 18.3% of samples were at or above moderate contamination levels. Additionally, the soil was in moderate ecological risk from combined heavy metal pollution, and 49.7% and 27.0% of this risk could be attributed to Hg and Cd pollution, respectively, due to their high toxic-response factors. For the rice samples, Cd content showed the highest biological accumulation coefficient value (40.8%) in rice grains and was slightly greater than its maximum allowable value (MAV) (0.2 mg/kg) in 7.5% of samples, whereas the other metals were all lower than their corresponding MAVs. Heavy metal exposure (especially As exposure) via rice consumption causes significant carcinogenic and non-carcinogenic risks to adults, and non-carcinogenic risk to children, while the carcinogenic risk to children was at tolerable level. Greater rice consumption might be responsible for the greater health risk to adults than children. Natural sources (loaded heavily with Cr and Ni) such as lithogenic components and soil parent materials, agricultural activities (loaded heavily with Cd, Cu, and Zn), especially excessive use of pesticides and fertilizers, and industrial activities (loaded heavily with Hg, Pb, and As) including vehicle emissions, coal combustion, and those of the textile and chemical industries were identified as the main sources. Effective regulations should be enforced to guarantee the safety of farm produce and protect ecological and human health in the study area.

Food security is essential for human survival and sustainable development. Due to rapid urbanization and industrialization, the farmland loss in Yangtze River Delta Urban Agglomeration (YRDUA) has threatened food security. Thus, this study intended to quantify the farmland loss and assess its impacts on food security in the YRDUA from 2000 to 2020 at three scales based on the Google Earth Engine platform. Our results show that the area of farmland in YRDUA is decreasing at a rather high speed in the past 20 years and the trend is getting worse. At the urban agglomeration scale, there was a farmland deficit of 0.44 million ha in 2000, followed by larger farmland deficits in 2010 and 2020. At the city scale, Shanghai had the largest scarcity of farmland. At the urban subgroup scale, Subgroup I in the west and Subgroup II in the north always maintained an oversupply of farmland, while Subgroup III in the east and Subgroup IV in the south faced serious food security problems. Our study suggests that farmland must be protected in YRDUA in order to ensure food self-sufficiency and promote regional sustainability.

The ecosystem health of coastal metropolitan regions is changing, which will exert a negative impact on human survival and development in the future. In this case, it is a novel and effective method to evaluate the regional ecosystem health based on land use/land cover change (LUCC) and landscape ecology theories. This paper constructed an integrated ecosystem health assessment framework (top-down), including objective layer, factor layer and index layer. Comprehensive and detailed analytical methodologies (bottom-up) were employed to explore the process of ecosystem health change in Shanghai and Hangzhou Bay (SHB) at multiple scales. The results showed that, in the two periods of 2001–2007 and 2007–2013, the regional ecosystem health status continued to degrade at city scale, and this decline spread to the surrounding areas from the central cities (Shanghai and Jiaxing). Similar diffusion phenomenon was also observed at county scale (centered on Downtown Shanghai). Notably, the vigor factor was found to make the greatest contribution to the changes of ecosystem health. To conclude, integrated assessment framework and comprehensive/detailed analysis combined with LUCC and landscape patterns are meaningful exploration for ecosystem health assessment, and clustering analysis provides a foundation for government to formulate regional planning and management policies pertinently.

Metals and metalloids accumulate in soil, which not only leads to soil degradation and crop yield reduction but also poses hazards to human health. Commonly, source apportionment methods generate an overall relationship between sources and elements and, thus, lack the ability to capture important geographical variations of pollution sources. The present work uses a dataset collected by intensive sampling (1848 topsoil samples containing the metals Cd, Hg, Cr, Pb, and a metalloid of As) in the Shanghai study area and proposes a synthetic approach to source apportionment in the condition of spatial heterogeneity (non-stationarity) through the integration of absolute principal component scores with geographically weighted regression (APCA-GWR). The results showed that three main sources were detected by the APCA, i.e., natural sources, such as alluvial soil materials; agricultural activities, especially the overuse of phosphate fertilizer; and atmospheric deposition pollution from industry coal combustion and transportation activities. APCA-GWR provided more accurate and site-specific pollution source information than the mainstream APCA-MLR, which was verified by higher R2, lower AIC values, and non-spatial autocorrelation of residuals. According to APCA-GWR, natural sources were responsible for As and Cr accumulation in the northern mainland and Pb accumulation in the southern and northern mainland. Atmospheric deposition was the main source of Hg in the entire study area and Pb in the eastern mainland and Chongming Island. Agricultural activities, especially the overuse of phosphate fertilizer, were the main source of Cd across the study area and of As and Cr in the southern regions of the mainland and the middle of Chongming Island. In summary, this study highlights the use of a synthetic APCA-GWR model to efficiently handle source apportionment issues with spatial heterogeneity, which can provide more accurate and specific pollution source information and better references for pollution prevention and human health protection.

Heavy metal pollution in soils has attracted great attention worldwide in recent decades. Selecting Hangzhou as a case study location, this research proposed the synthesis application of positive matrix factorization (PMF) and GeogDetector models for quantitative analysis of pollution sources, which is the basis for subsequent soil pollution prevention and remediation. In total, 2150 surface soil samples were collected across the study area. Although the mean concentrations of As, Cd, Cr, Hg, and Pb in the soils were lower than the National Environmental Quality Standards for Soils in China, the mean contents of As and Cd were higher than their corresponding local background values by approximately 1.31 and 1.59 times, respectively, indicating that heavy metals have been enriched in topsoil. Agricultural activities, industrial activities, and soil parent materials were the main sources of heavy metal pollution in the soils, accounting for 63.4%, 19.8%, and 16.8% of the total heavy metal accumulation, respectively. Cr was derived mainly from soil parent materials (80.72%). Cd was closely associated with agricultural activities (73.68%), such as sewage irrigation and application of fertilizer. Mercury was mainly attributed to industrial activities (92.38%), such as coal mining and smelting. As was related to agricultural (57.83%) and natural (35.56%) sources, and Pb was associated with industrial (42.42%) and natural (41.83%) sources. The new synthesis models are useful for estimating the source apportionment of heavy metals in soils.

Destructive development of suburban areas in some metropolises has exposed suburban soils to high risk of potentially toxic trace elements (PTEs) enrichment, which also threatens human and ecosystem health. This study investigated the pollution status, sources and spatial patterns of four PTEs (Pb, Cd, Cr and As) in 1805 soil samples collected from the suburbs of Shanghai in 2015. Nineteen potential sources, including: 6 soil property factors, 10 proximity factors and 3 topography factors, were selected to help explain the PTEs aggregation using logistic regression models from global and local perspectives. The statistical results of PTEs concentration revealed that Cd showed the highest pollution risk in local soils, which was followed by As. Soil property was the primary factor affecting the PTEs (except Cr) enrichment, both identified by global models and local models. The local model particularly emphasized the significant correlation between soil property and PTEs in most parts of the outer suburbs and southeastern inner suburbs. Some proximity factors such as distance to district center and water were negatively correlated with Cd pollution and some topography factors such as elevation and slope were closely related to As pollution. It is worth noting that in the coastal areas, especially Chongming Island, there were obvious PTEs depositions in the soil near the estuary. This study helps to identify the sources of anthropogenic contamination and geogenic enrichment of the four PTEs and their spatial patterns, playing an essential role in formulating regional environmental policies for coastal cities.

The rapid expansion of urban areas and intense human activities have exerted serious impacts on the structure and service functions of ecosystems. Correspondingly, due to the limited amount of ecosystem service value (ESV), ecological environment is doomed to place restriction on disordered sprawl of urban and extensive growth of economy. A clear understanding of the interaction between urbanization and environment is of great significance for formulating regulations of future urban development and eco-environment protection. Taking terrestrial ecosystem services and urbanization as two systems, this research aims at exploring the interactive coercing relationship between urbanization and ESV in the Shanghai–Hangzhou Bay Metropolitan Region (SHB) on the system level and subsystem level. First of all, the value coefficient and information entropy methods were employed to estimate the ESV and urbanization level of each city, respectively. Then, a coupling coordination degree model (CCDM) was used to reveal the interactive coercing relationship between ESV and urbanization. The results showed that the change of land use under urbanization caused the degradation of ecosystem service functions in SHB, and the city with the highest urbanization level (Shanghai) also endured the worst ESV losses. The overall coupling coordination degree (CCD) between urbanization and ESV on the system level displayed an upward trend in SHB. However, the CCDs between several ESV subsystems and urbanization subsystems, such as food production function and demographic urbanization, had deteriorated in Shanghai, Jiaxing and Ningbo. Our study suggested that more consideration should be given to the coordinated and balanced development of different ecosystem services and urbanization, intensification of land use, and maintenance of ecosystem functions in future urban planning and decision making.

Adequate soil total nitrogen (TN) is critical to crop productivity, and soil carbon-to-nitrogen ratio (C/N) is an important indicator of soil fertility. Accurate knowledge of soil TN content and C/N ratio is essential for precision agriculture and soil biogeochemical modeling. This study aims to characterize the spatial and temporal trends of soil TN level and C/N ratio for cropland soil across Zhejiang province of East China. A total of 29,927 topsoil (0–20 cm) samples were collected during 2007–2008 for analyzing soil properties, on the basis of which we mapped the soil TN content at a 250 m resolution using a random forest model (RF). With 22 predictors covering soil properties, fertilization, meteorology, locations, and population density, the RF model showed good predictive performance with cross-validation R2 = 0.65 and RMSE = 0.43 g kg−1. The soil pH, cation exchange capacity (CEC), and fertilization played important roles in determining the spatial variations of soil TN and C/N ratio. The overall level of cropland soil TN within the study area was estimated to be 1.75 ± 0.43 g kg−1 (μ ± σ), varying from 0.25 to 3.64 g kg−1. By comparing our estimates with the previous extensive survey for 1979–1985, we found that the soil TN has slightly increase trend and the soil C/N ratio slightly decreased, which was attributed to intensified N fertilization in the last decade. This work provides up-to-date knowledge of soil TN content and soil C/N ratio in Zhejiang province of East China, indicating the importance of updating soil property databases for better regional cropland management.

Soil heavy metal pollution can be a serious threat to human health and the environment. The accurate mapping of the spatial distribution of soil heavy metal pollutant concentrations enables the detection of high pollution areas and facilitates pollution source apportionment and control. To make full use of auxiliary soil properties information and show that they can improve mapping, a synthesis of the Bayesian Maximum Entropy (BME) theory and the Geographically Weighted Regression (GWR) model is proposed and implemented in the study of the Shanghai City soils (China). The results showed that, compared to traditional techniques, the proposed BME-GWR synthesis has certain important advantages: (a) it integrates heavy metal measurements and auxiliary information on a sound theoretical basis, and (b) it performs better in terms of both prediction accuracy and implementation flexibility (including the assimilation of multiple data sources). Based on the heavy metal concentration maps generated by BME-GWR, we found that the As, Cr and Pb concentration levels are high in the eastern part of Shanghai, whereas high Cd concentration levels were observed in the northwestern part of the city. Organic carbon and pH were significantly correlated with most of the heavy metals in Shanghai soils. We concluded that Cd pollution is mainly the result of agricultural activities, and that the Cr pollution is attributed to natural sources, whereas Pb and As have compound pollution sources. Future studies should investigate the implementation of BME-GWR in the case of space-time heavy metal mapping and its ability to integrate human activity information and soil category variables.

To analyze the geographic spatial patterns and risk areas of main digestive system cancers in Yiwu city.Newly diagnosed cases of esophageal, gastric and colorectal cancer during 2010-2014 were obtained from Yiwu Center for Disease Control and Prevention (CDC). The household registration population data in 2013 were obtained from public security bureau. Hierarchy clustering and partitioning regionalization method was used to generate geographic units. Global Moran's I was used to evaluate whether cancer incidence was significantly clustered in space, Anselin Local Moran's I was used to identify statistically significant hot spots, cold spots, and spatial outliers, and Spatial Scan Statistics was implemented to analyze the relative risk of cancers in different areas.The 5-year average incidence of esophageal, gastric and colorectal cancers were 9.99/100 000, 34.01/100 000 and 31.46/100 000, respectively. Males showed significantly higher incidence than females. The incidence was heterogeneous throughout the study area. Spatial Scan analysis revealed that southern Yiwu presented a significantly higher male esophageal cancer (The incidence of main digestive tract cancers shows a heterogeneous distribution in Yiwu city.

Background Incidences of thyroid cancer (TC) have been increasing worldwide in recent decades. In this research, we aimed to analyze the spatiotemporal pattern of TC and explore relevant environmental risk factors in Hangzhou (HZ), which is rapidly urbanizing and home to the highest TC incidence in China. Methods Spatial scan statistic was employed to analyze the spatiotemporal pattern of TC in HZ from 2008 to 2012. The geographically weighted regression model (GWR) was implemented to explore environmental risk factors. Its performance was compared to the traditional ordinary least squares model (OLS). Results A total of 7147 TC cases (5385 female and 1762 male) were diagnosed in HZ from 2008 to 2012. High TC clusters were detected in the northeast, urban areas and expanded outwards while low clusters were located in the southwest rural areas. The GWR model generally performed better than the OLS in analyzing the associations between TC incidence and environmental factors. The industrial density, chemical oxygen demand of wastewater (COD) and the percentage of building area had a strong positive influence on the TC in the northeastern suburb areas of HZ, while the elevation, slope and the percentage of forest area had a significant negative correlation with TC in the middle, rural areas of HZ. Meanwhile, the accessibility to health care might have an impact on the TC incidence. Conclusion High clusters were mostly located in the northeastern urban areas and showed an expansion process from the center urban area to the suburb area, especially for female TC. Intensive industrial activities and the emission of organic pollutants, which positively correlated with the high TC clusters in the northeast suburb areas of HZ, should get proper attention.

Thyroid cancer (TC) incidence in China has increased rapidly in recent years. Hangzhou is one of the areas with the highest TC incidence in China. However, the composite space–time variation and risk factors of TC are rarely investigated. We acquired 7147 TC cases from 2008 to 2012 in Hangzhou. Descriptive statistics were employed to compare the incidence disparities in different sub-populations. Geographical information systems were used to create spatial distribution maps. Hotspot analysis was applied to detect high/low incidence clusters, and the GeogDetector model was implemented to investigate the relationship between TC incidence and environmental factors. TC incidence in Hangzhou increased dramatically from 2008 to 2012: a noticeable 244.9 % increase, from 10.04 to 34.63 per 100,000 individuals, with a female to male ratio of 3.0, an urban to rural ratio of 3.2 and iodine sufficient to iodine deficient ratio of 3.5. Significantly high TC cluster was detected in the northeast area of Hangzhou. Elevation was found to be the most powerful determinant of TC distribution, followed by soil parent materials and slope. TC incidence decreased as elevation and slope increased. Concerning soil parent materials, deposited materials were generally linked to higher TC incidence than were eluvium ones. The spatial/temporal pattern of TC incidence is affected by geomorphology and soil property variations. Excessive iodine exposure may be a TC risk factor. Health research and management should pay sufficient attention to the improved understanding and prediction of the composite space–time distribution of the quickly increasing TC incidence described in this study.

Stomach cancer (SC) is a severe health burden, with nearly half of the world's cases found in China. Noticeably, the emissions of heavy metals into the environment have increased alongside rapid urbanization and industrialization in China. However, as regards carcinogenic associations, the relationship between heavy metals and SC is yet unclear. Based on 9378 newly diagnosed SC cases in Hangzhou City from 2009 to 2012, this work is concerned with the quantitative characterization of the spatial distribution pattern of SC incidence and its geographical association with soil heavy metals by means of a novel geographical model. The results show that (a) Cd is one of the severe soil pollutants in Hangzhou; (b) higher SC incidence clusters are in central Hangzhou, whereas lower clusters are found in the northeast and southwest with a male to female incidence ratio about 2.2:1; (c) although when considered separately, the heavy metals in this work do not have a considerable impact on the distribution of SC incidence in Hangzhou City, nevertheless, the joint effects of multiple heavy metals have significant impacts on SC risk. The present work calls for a rigorous quantitative assessment of the integrated heavy metal soil pollution and its effects on SC incidence.

The thyroid cancer (TC) incidence in China has increased dramatically during the last three decades. Typical in this respect is the case of Hangzhou city (China), where 7147 new TC cases were diagnosed during the period 2008-2012. Hence, the assessment of the TC incidence risk increase due to environmental exposure is an important public health matter.Correlation analysis, Analysis of Variance (ANOVA) and Poisson regression were first used to evaluate the statistical association between TC and key risk factors (industrial density and socioeconomic status). Then, the Bayesian maximum entropy (BME) theory and the integrative disease predictability (IDP) criterion were combined to quantitatively assess both the overall and the spatially distributed strength of the "exposure-disease" association.Overall, higher socioeconomic status was positively correlated with higher TC risk (Pearson correlation coefficient=0.687, P0.01). Compared to people of low socioeconomic status, people of median and high socioeconomic status showed higher TC risk: the Relative Risk (RR) and associated 95% confidence interval (CI) were found to be, respectively, RR=2.29 with 95% CI=1.99 to 2.63, and RR=3.67 with 95% CI=3.22 to 4.19. The "industrial density-TC incidence" correlation, however, was non-significant. Spatially, the "socioeconomic status-TC" association measured by the corresponding IDP coefficient was significant throughout the study area: the mean IDP value was -0.12 and the spatial IDP values were consistently negative at the township level. It was found that stronger associations were distributed among residents mainly on a stripe of land from northeast to southwest (consisting mainly of sub-district areas). The "industrial density-TC" association measured by its IDP coefficient was spatially non-consistent.Socioeconomic status is an important indicator of TC risk factor in Hangzhou (China) whose effect varies across space. Hence, socioeconomic status shows the highest TC risk effect in sub-district areas.

Thyroid cancer (TC) incidence has significantly increased worldwide in recent decades, with large differences between urban and rural areas. However, studies on Chinese TC incidence are limited. Research on the relationship between TC incidence and industry activities is also rare. In this work, data from 31 cancer registry cities in China between 2005 and 2009 were used to reveal the trend of TC incidence, compare the incidence among different cities, and analyze the relationship of TC incidence with socioeconomic factors. During the five-year period, TC incidence in China increased by 49.5 % from 3.21/100,000 to 4.80/100,000, with a female–male ratio of 3 and an urban–rural ratio of 2.5. The increase of TC incidence in more developed cities was significant, but it was not in less developed cities. People living in cities with higher secondary industry output had a higher risk of developing TC. The government and scientific community should pay sufficient attention to the rapidly increasing incidence of TC and to industry activities.

Breast cancer (BC) is the main cause of death of female cancer patients in China. Mainstream mapping techniques, like spatiotemporal ordinary kriging (STOK), generate disease incidence maps that improve our understanding of disease distribution. Yet, the implementation of these techniques experiences substantive and technical complications (due mainly to the different characteristics of space and time). A new spatiotemporal projection (STP) technique that is free of the above complications was implemented to model the space-time distribution of BC incidence in Hangzhou city and to estimate incidence values at locations-times for which no BC data exist. For comparison, both the STP and the STOK techniques were used to generate BC incidence maps in Hangzhou. STP performed considerably better than STOK in terms of generating more accurate incidence maps showing a closer similarity to the observed incidence distribution, and providing an improved assessment of the space-time BC correlation structure. In sum, the inter-connections between space, time, BC incidence and spread velocity established by STP allow a more realistic representation of the actual incidence distribution, and generate incidence maps that are more accurate and more informative, at a lower computational cost and involving fewer approximations than the incidence maps produced by mainstream space-time techniques.

For the purpose of pollution assessment and source apportionment of heavy metals in agricultural soils with different fertility levels, an intensive sampling (1848 samples) was conducted in Shanghai city. Various indices, including the pollution index ( PI ), Nemerow integrated pollution index ( NIPI ), geoaccumulation index ( GI ) and potential ecological risk index ( RI ), were employed to assess the pollution status caused by heavy metals. In view of the spatial heterogeneity of heavy metal concentrations, in this work a synthesis of principal component analysis (PCA) with spatial lag modeling (SLM) is proposed to explore quantitatively the sources of heavy metals and the contributions of each component. The results showed that the mean heavy metal concentrations followed a decreasing order: Cr (72.02 ± 8.90 mg/kg) > Pb (25.57 ± 7.38 mg/kg) > As (6.98 ± 1.97 mg/kg) > Cd (0.19 ± 0.10 mg/kg) > Hg (0.12 ± 0.08 mg/kg). Although the mean heavy metal concentrations did not exceed the corresponding national standards, the percentages of sampling locations exhibiting higher concentrations relative to the background values were found to be equal to 43.29% for Pb, 32.63% for Cd, 27.54% for Hg, 11.26% for Cr, and 10.93% for As, which indicate significant local accumulation of heavy metal pollutants within the study area. Industrial activities, natural sources and agricultural activities are the main pollution sources that account for 27.92%, 27.48% and 20.64% of the total pollution, respectively. Industrial activities with high Pb and Hg loadings have a large contribution to good fertility soils (39.38%). It was found that agricultural activity is the main contributor of Cd pollution, having a large contribution (33.46%) to low fertility soils. Cr and As pollution comes mainly from natural sources, with relatively equal contribution to soils with various fertility levels. The present study improves understanding of the pollution status of heavy metals in Shanghai agricultural soils, and also serves as reference for pollution source apportionment in other regions.

Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008–2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008–2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

Sporadic cases occurring in mall geographic unit could lead to extreme value of incidence due to the small population bases, which would influence the analysis of actual incidence.This study introduced a method of hierarchy clustering and partitioning regionalization, which integrates areas with small population into larger areas with enough population by using Geographic Information System (GIS) based on the principles of spatial continuity and geographical similarity (homogeneity test). This method was applied in spatial epidemiology by using a data set of thyroid cancer incidence in Yiwu, Zhejiang province, between 2010 and 2013.Thyroid cancer incidence data were more reliable and stable in the new regionalized areas. Hotspot analysis (Getis-Ord) on the incidence in new areas indicated that there was obvious case clustering in the central area of Yiwu.This method can effectively solve the problem of small population base in small geographic units in spatial epidemiological analysis of thyroid cancer incidence and can be used for other diseases and in other areas.

Soil sealing (loss of soil resources due to extensive land covering for the purpose of house building, road construction etc.) and subsequent soil landscape pattern changes constitute typical environmental problems in many places worldwide. Previous studies concentrated on soil sealing in urbanized regions, whereas rural areas have not been given sufficient attention. Accordingly, this paper studies soil landscape pattern dynamics (i.e., landscape pattern changes in response to rural anthropogenic activities) in the Tiaoxi watershed (Zhejiang province, eastern China), in which surface sealing is by far the predominant component of human forcing with respect to environmental change. A novel approach of quantifying the impacts of rural anthropogenic activities on soil resources is presented. Specifically, quantitative relationships were derived between five soil landscape pattern metrics (patch density, edge density, shape index, Shannon's diversity index and aggregation index) and three rural anthropogenic activity indicators (anthropogenic activity intensity, distance to towns, and distance to roads) at two landscape block scales (3 and 5 km) between 1985 and 2010. The results showed that the Tiaoxi watershed experienced extensive rural settlement expansion and high rates of soil sealing. Soil landscapes became more fragmented, more irregular, more isolated, and less diverse. Relationships between soil landscape pattern changes and rural anthropogenic activities differed with the scale (spatial and temporal) and variable considered. In particular, the anthropogenic activity intensity was found to be the most important indicator explaining social development intensity, whereas the other two proximity indicators had a significant impact at certain temporal interval. In combination with scale effects, spatial dependency (correlation) was shown to play a key role that should be carefully taken into consideration in any relevant environmental study. Overall, the findings of this work suggest that soil sealing can be a critical human forcing issue with considerable consequences deserving serious attention by the experts, the public and the government alike.

Soil erosion, as a serious environmental problem worldwide, poses a great threat to human sustainability. Spatiotemporal information on soil erosion is of vital importance to finding a solution for this problem. A case study was conducted to characterize the dynamics of soil erosion risk in 1985, 1994, 2003 and 2008 for Anji County, China, a region with seemingly high ecological quality. Remote sensing and geographic information systems were integrated to parameterize soil erosion-controlling factors. By using the Revised Universal Soil Loss Equation, we estimated annual soil loss, and generated categorical maps of soil erosion risk in the County for the 4 years. Results showed that, while appearing to improve in some areas, soil erosion risk increased and eroded area expanded from 1985 to 2008. Spatial analysis revealed that the most vulnerable hotspots were erosion-free forests, where newly eroded areas were most likely to occur. These results implied that, similar to findings in many parts of the world, soil erosion is an important issue in the study area, which could be closely associated with local eutrophication and algal blooms. Our research indicated that there should be more focus on this issue. From a methodological point of view, we believe that the approach used to estimate soil loss in the study area has the potential to be applied in other similar regions.

Background Breast cancer (BC) is the most common female malignant tumor. Previous studies have suggested a big incidence disparity among different cities in China. The present work selected a typical city, Hangzhou, to study BC incidence disparity within the city. Methods Totally, 8784 female breast cancer cases were obtained from the Hangzhou Center for Disease Control and Prevention during the period 2008–2012. Analysis of Variance and Poisson Regression were the statistical tools implemented to compare incidence disparity in the space-time domain (reference group: township residents during 2008, area: subdistrict, town, and township, time frame: 2008–2012), space-time scan statistics was employed to detect significant spatiotemporal clusters of BC compared to the null hypothesis that the probability of cases diagnosed at a particular location was equal to the probability of cases diagnosed in the whole study area. Geographical Information System (GIS) was used to generate BC spatial distribution and cluster maps at the township level. Results The subdistrict populations were found to have the highest and most stable BC incidence. Although town and township populations had a relatively low incidence, it displayed a significant increasing trend from 2008 to 2012. The BC incidence distribution was spatially heterogeneous and clustered with a trend-surface from the southwest low area to the northeast high area. High clusters were located in the northeastern Hangzhou area, whereas low clusters were observed in the southwestern area during the time considered. Conclusions Better healthcare service and lifestyle changes may be responsible for the increasing BC incidence observed in towns and townships. One high incidence cluster (Linping subdistrict) and two low incidence clusters (middle Hangzhou) were detected. The low clusters may be attributable mainly to developmental level disparity, whereas the high cluster could be associated with other risk factors, such as environmental pollution.