Specific Geographical Locations Research Articles

Descriptive epidemiological study of coronavirus disease distribution in specific geographic location: Unique public health practice in outbreak analysis

Since the emergence of the Coronavirus disease outbreak, the world has witnessed great changes that have impacted humanity. A study of the pattern of the pandemic would be of great importance to understand the trending behavior for the spreading of the disease within any country. Visualization of the outbreak progression - through accumulated records in the datasets - using statistical tools showed that the initial fast increase rate of the affected cases in the original province in China was followed by a stability period till the end of the reporting date. Hong Kong - which was next to Hubei province in the cases – showed a different surge of slow growth curve with distinct major wave levels. The remaining territories showed a much smaller magnitude of morbidities. However, investigating the similarity levels for the daily kinetics of cases showed a clustering tendency between different political regions suggesting a significant correlation. The technique would be useful for public health authorities work.

Stability analysis of rock slope under Sujiaba overpass in Chongqing City based on kinematic and numeric methods

Rock slopes have the characteristics of complex geological conditions, weak structural surface development, steep slope, and great damage. In this study, the Sujiaba overpass slope in Chongqing was selected as the evaluation object, and the main stability evaluation methods of rock slope were analyzed. Combined with the special geological conditions and geographical location of the rock slope, through a geological survey, the slope was qualitatively analyzed based on the stereographic projection method, and the slope stability safety factor was calculated by using the finite element strength reduction method. FLAC3D was used to simulate the initial stress state of the unstable rock mass, the limit state stability of the unstable rock mass before bolt support, and the stability after bolt support. The simulation results show that the stability coefficients of selected unstable rock masses W1, W2, W6, and W7 under the limit state before bolt support are, respectively, 1.22, 1.80, 5.90, and 2.10. Unstable rock masses separate from the parent rock, causing a large displacement due to their instability and downward sliding. After bolt support, stability coefficients for those four unstable rock masses are 1.60, 2.40, 8.60, and 3.20, respectively. Under the same reduction coefficient, rock masses are stable and the displacement is small. The results show that the calculation results of the initial stress state of the rock slope are consistent with the theoretical understanding and field investigation. After the implementation of bolt support, the anti-sliding stability of unstable rock is obviously improved. The research results have important scientific guiding significance and practical value for revealing the failure mechanism of rock slope and analyzing the stability of unstable rock mass.

The Geography of Mental Health, Urbanicity, and Affluence

Residential location has been shown to significantly impact mental health, with individuals in rural communities experiencing poorer mental health compared to those in urban areas. However, the influence of an individual's social group on the relationship between residential location and mental health outcomes remains unclear. This study disaggregates the rural-urban binary and investigates how geography and social groupings interact to shape mental health outcomes. Merging data from PLACES and Claritas PRIZM, we conducted a hotspot analysis, generated bivariate choropleth maps, and applied multiscale geographically weighted regressions to examine the spatial distribution of mental health and social groupings. Our findings reveal that mental health is influenced by complex interactions, with social groups playing a critical role. Our study highlights that not all rural and urban areas are alike, and the extent to which social groups influence mental health outcomes varies within and across these areas. These results underscore the need for policies that are tailored to meet the unique mental health needs of individuals from different social groups in specific geographic locations to inform policy interventions that more effectively address mental health disparities across diverse communities.

A novel three-band macroalgae detection index (TMI) for aquatic environments

ABSTRACT Overgrowth of algae is a serious threat for aquatic ecosystems. This threat has occurred frequently in recent decades due to increased anthropogenic activities. Thus, understanding how the aquatic environment promotes algae growth by comprehensive monitoring is essential for protecting and sustaining aquatic ecosystems. We propose a novel Three band Macroalgae Index (TMI) using the green, red and near-infrared bands of Landsat-8 Operational Land Imager (OLI) as a robust remote sensing indicator for detecting and monitoring algae overgrowth in aquatic ecosystems. The proposed index has been tested in different water quality conditions in different aquatic environments. These conditions always vary between different images even if the study area is the same, e.g. atmospheric aerosols, refraction of water-leaving radiance according to sun and view angles, and sun glint on the surface which is influenced by waves and currents. Also, the six study areas were selected because of their water quality differences, including open ocean and inland lakes, e.g. Great Salt Lake being hypersaline waters, Lake St. Claire regarded as moderately eutrophic and open ocean waters in English Channel. A cross-comparison among the TMI and nine existing algal bloom indices indicated the superior performance of TMI (90%–100%), with reference to similarity to the OC2-based-TSI classifications. The performance of the existing indices was inconsistent across varying environmental and water quality conditions. This might be attributed to several factors including, uncertainty of shortwave infrared band retrievals used by some indices over turbid waters, and dependence of those indices on specific geographical location and/or sensor. The TMI overcame these issues and is therefore an alternative index for algal bloom detection in different water types, as it uses the wavebands which are commonly available on many remote sensing systems.

Energy performance of passive shading and thermal insulation in multistory hotel building under different outdoor climates and geographic locations

Though energy-efficient envelope is extensively studied, there is lack of attention on incorporating appropriate passive design strategies at the design-phase of a building in a specific climate and geographic location. This study has focused on the effect of outdoor climate and geographic location on the energy-saving potential of passive shading and thermal insulation for multistory hotel building in the northern hemisphere. The building was modelled and simulated by using DesignBuilder (Version 4.5.0.148). The cities were selected in such a manner that they represent warm, moderately hot, hot, and very hot outdoor climates but different geographic locations (according to Koppen category). The proposed shading strategy was featured by the combination of solar shading devices and self-shading. As an alternative option, the envelope was provided with high-performance insulation and glazing without solar shading. The results indicated that the outdoor climate and geographic location had significant influence on the energy-saving potential of both the options; the factors identified through sensitivity analysis were cooling degree days above the cooling setpoint (CDD-base STC), share of cooling and heating energy demands, global horizontal irradiance, and solar shading effectiveness. For instance, Khamis Mushait and Athens cities have warm outdoor climate, but they represent different geographic locations; therefore, the building's cooling energy demands in these cities were significantly different (98% and 52% respectively of the total energy demand). Accordingly, the energy saving potential of passive solar shading was maximum (65.2%) for Khamis Mushait, while it was minimum (13.1%) for Athens. Conversely, the saving by high-performance insulation ranged from −11.6% in Khamis Mushait to a maximum of only 8.5% in Athens, which is consistent with their heating demands (2% and 48% respectively).

Direct and diffuse shading factors modelling for the most representative agrivoltaic system layouts

Agrivoltaic systems are becoming increasingly popular as a crucial technology for attaining multiple sustainable development goals, such as affordable and clean energy, zero hunger, clean water and sanitation, and climate action. However, a comprehensive understanding of the shading effects on crops is essential for choosing an optimal agrivoltaic system, as an incorrect choice can result in significant crop yield reductions. In this study, fixed vertical, one-axis tracking, and two-axis tracking photovoltaic arrays were developed for agrivoltaic applications to analyse the shading conditions on the ground used for crop production. The models demonstrated remarkable accuracy in comparison to commercial software such as PVsyst® and SketchUp®. These models will help to reduce crop yield uncertainty under agrivoltaic systems by providing accurate photosynthetically active radiation distribution at the crop level. The photosynthetically active radiation distribution was further analysed using a light homogeneity index, and the results showed that homogeneity and photosynthetically active radiation reduction varied significantly depending on the agrivoltaic system design, ranging from 86% to 95%, and 11% to 22%, respectively. Studying the effect of shading with distribution analysis is crucial for identifying the most suitable agrivoltaic system layout for specific crops and geographical locations.

Reckoning with Digital Inequity in Place-Based Community Revitalization

Place-based community development in America has a rich history. Practices and procedures for successful redevelopment are supported by lobbying efforts, public administration, policy, federal funding, and the efforts of non-profits dedicated to neighborhood revitalization. Community revitalization work is often centered around specific geographic locations, while in recent decades modern technology has caused social networks to become increasingly geographically disparate. Social networks have been demonstrated to support the economic mobility that community development strives to create. However, the impact of modern technology on place-based community development has not been clearly understood. Increasing digitalization has impacted the effectiveness of place-based social equity efforts such as community organizing, affordable housing and economic development, and financial capability interventions. This essay explores how place-based community organizing led to the creation of current policies that govern community development, how technology has impacted urban communities and how these changes may subsequently affect social equity objectives in public administration.

Analysis of the factors which may have influenced the incidence of congenital malformations in children born in the province of Warmia and Mazury between 1999 and 2000

<b>Introduction.</b> Congenital malformations have been known about for ages, but the reasons for their development have always been shrouded in mystery. All efforts to explain such reasons as to relating to the natural forces of God’s revenge have not stood the test of time. Still, the knowledge concerning the aetiology of malformations is not complete; we know, however, about many factors which may contribute to their development during various stages of embryogenesis. <b>Aim.</b> The aim of this paper is the analysis of specific factors which may have contributed to the development of congenital malformations in children born in the Province of Warmia and Mazury between the years 1999 and 2000. <b>Materials and methods.</b> The author of this paper, who is involved in the creation of the Polish Register of Congenital Malformations (PRCM), evaluated case records of newborns who had been reported to have been born with congenital malformations. The data recorded in this Register, maintained by the Chair and Department of Medical Genetics at the Medical Academy (at present Medical University) in Poznań, was verified by specialists, and later analysed according to the methodological principles of this work. The analysis included: fetal age and birth weight, mother’s age and education, as well as mother’s place of residence. Statistical analysis was carried out by means of Statistica v.6.1 software. <b>Results and discussion.</b> Congenital malformations were found in 276 boys, with a malformations incidence factor of 166.8/10000 for boys, and in 212 girls, the malformations incidence factor being 136.2/10000 for girls. The higher incidence of congenital malformations in boys was caused by a nearly 10 times higher incidence of urinary system defects. The incidence of congenital malformations in newborns whose mothers resided in cities amounted to 132.9/10000 of newborns born in cities. The incidence of congenital malformations in newborns of mothers residing in the country was 141.9/10 000 of newborns born in the country. It was also noted that the incidence of congenital malformations was 2–3 times higher in children with low birth weight in comparison to the general population. The highest incidence of congenital malformations was found in those children whose mothers were 35 years of age or older at the time of giving birth. Advanced maternal age was the most significant factor in the development of malformations caused by chromosome aberrations. Creating a district map presenting the incidence of malformations may be the first step to further research concerning those specific geographical regions at high risk of congenital malformations. The highest incidence, irrespective of the type of malformation, was observed in the districts of: Mrągowo, Ostróda and Braniewo, whereas the lowest was found in the districts of: Ełk, Olecko and Gołdap, and Giżycko. <b>Conclusions.</b> Having analysed all pertinent data, it was then concluded that: 1. Male sex correlates with the incidence of congenital malformations of the genitals. 2. Low birth weight correlates with an increased incidence of congenital malformations. 3. The incidence of congenital malformations in particular districts is diversified, pointing to the significance of necessary further research in order to identify those specific geographical locations having the highest malformations incidence factors.

Spatial and Temporal Changes and Driving Factors of Desertification Around Qinghai Lake, China

The area around Qinghai Lake is one of the most serious desertification areas on the Qinghai-Tibet Plateau. In this paper, combined with field investigation and indoor analysis, the classification and grading system of desertification around Qinghai Lake was established. On this basis, through remote sensing data processing and parameter inversion, the desertification monitoring index model was established. Based on the analysis of Landsat-5/TM remote sensing data from 1990 to 2020, the dynamic change characteristics of desertification land around Qinghai Lake in recent 30 years were obtained. The results show that the desertification area around Qinghai Lake was 1,359.62 km2, of which the light desertification land was the main one. The desertification spread in a belt around Qinghai Lake, concentrated in Ketu sandy area in the east, Ganzi River sandy area in the northeast, Bird Island sandy area in the northwest, and Langmashe sandy area in the southeast. From 1990 to 2000, the annual expansion rate of desertification around Qinghai Lake was 2.68%, the desertification spread rapidly, and light desertification land was the main part of desertification expansion. From 2000 to 2010, the annual expansion rate of desertification was only 0.83%, but severe desertification land and moderate desertification land developed more rapidly than in the previous period. From 2010 to 2020, the annual expansion rate of desertification was 2.66%, and the desertification was spreading rapidly, mainly with moderate desertification land and light desertification land. In the process of desertification land transfer around Qinghai Lake, the transfer of desertification land and non-desertification land was the main, accompanied by the mutual transformation of different levels of desertification land. The process of desertification around Qinghai Lake was essentially the result of natural and human factors. The special geographical location, climate changes, rodent damage, and human factors around Qinghai Lake were the main causes of desertification.

The impacts of pandemic on urban housing prices: evidence from the outbreak of COVID-19 in Beijing, 2020

PurposeThe COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020.Design/methodology/approachThe authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020.FindingsThis outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were less affected.Originality/valueBy investigating the impacts of COVID-19 on housing prices in Beijing, this study illustrates that urban housing prices would be impacted by the pandemic, at least in the short term. While the rise and fall of housing prices were found spatially heterogeneous in Beijing, it suggests that urban neighbourhoods with specific socioeconomic characteristics and geographic locations would unfold different resilience when encountering pandemic. By using data scraping and rigorous statistical tools, the study is probably one of the first ones examining the consequences of COVID-19 in intra-urban housing markets.

Countermeasures for rural domestic wastewater based on ecological environment security: a case study of an MBR-integrated process based on the PVDF@ZrO2 flat membrane, China

Abstract The harmonious coexistence of humans and nature has reached a broad consensus in the world. Maintaining the health of the ecological environment is the foundation of the existence and development of human civilization, and is also the inevitable choice for human beings to deal with the global ecological environment crisis. As an important factor affecting ecological stability, rural domestic wastewater has been neglected and not treated effectively for a long time because of its special geographical location and development limitations. In this paper, an integrated process of an MBR was applied to rural domestic wastewater treatment, inside which the modified PVDF@ZrO2 membrane was used to replace the traditional PVDF membrane. A series of membrane analyses and project follow-ups have proven that the hydrophilicity, anti-fouling performance of the membrane, and the treated water quality were improved. Meanwhile, this research enlightens us to pay attention to the overall planning, the maintenance of the pipe network, and the stable investment of funds in the treatment of rural domestic wastewater.

Neighbourhood environment as a risk factor for adverse health outcomes through association with the microbiome: protocol for a scoping review

IntroductionThe connection of the microbiome to human health intersects with the physical environment of humans. Each microbiome location can be influenced by environmental conditions that relate to specific geographical locations,...

Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease.

There are over 363 customized risk models of the American College of Cardiology and the American Heart Association (ACC/AHA) pooled cohort equations (PCE) in the literature, but their gains in clinical utility are rarely evaluated. We build new risk models for patients with specific comorbidities and geographic locations and evaluate whether performance improvements translate to gains in clinical utility. We retrain a baseline PCE using the ACC/AHA PCE variables and revise it to incorporate subject-level information of geographic location and 2 comorbidity conditions. We apply fixed effects, random effects, and extreme gradient boosting (XGB) models to handle the correlation and heterogeneity induced by locations. Models are trained using 2 464 522 claims records from Optum©'s Clinformatics® Data Mart and validated in the hold-out set (N = 1 056 224). We evaluate models' performance overall and across subgroups defined by the presence or absence of chronic kidney disease (CKD) or rheumatoid arthritis (RA) and geographic locations. We evaluate models' expected utility using net benefit and models' statistical properties using several discrimination and calibration metrics. The revised fixed effects and XGB models yielded improved discrimination, compared to baseline PCE, overall and in all comorbidity subgroups. XGB improved calibration for the subgroups with CKD or RA. However, the gains in net benefit are negligible, especially under low exchange rates. Common approaches to revising risk calculators incorporating extra information or applying flexible models may enhance statistical performance; however, such improvement does not necessarily translate to higher clinical utility. Thus, we recommend future works to quantify the consequences of using risk calculators to guide clinical decisions.

A Bibliometric Analysis of Current Status on Biodeterioration of Cultural Heritage during 2018-2022

Biodeterioration occurs through the availability of biotic and abiotic factors favoring the growth of harmful fungi, bacteria and other microorganisms on cultural heritage. Thus, biodeterioration mechanism has raised a global concern since it is commonly detected on cultural heritage buildings located in specific geographical locations such as southern European countries. This study conducts a bibliometric analysis using VOSviewer and OpenRefine for data cleaning by obtaining data from Scopus database of peer-reviewed publications to provide an overview of scientific literatures on biodeterioration. A total of 537 articles were analyzed within the period of 2018 – 2022 to acquire the current status of biodeterioration issue. 537 documents on biodeterioration were published by 1451 organizations from 68 countries. The co-authorship network map generated the trend of authors in biodeterioration research that identified the most productive author from China and organization from Japan. The co-occurrence network map of the keywords presented the significant interrelations of biodeterioration research field with the development of natural biocides to cope with the colonization of fungi and bacteria on cultural heritage. These results are expected to support the understanding of the intellectual structure of biodeterioration research.

Ecological and environmental risks of heavy metals in sediments in Dingzi Bay, South Yellow Sea

As a special geographical location between rivers and oceans, coastal estuaries always face severe heavy metal contaminations, especially in semi-closed bay. In this study, the spatial distribution, chemical fraction, ecological risks, and potential sources of heavy metals (Pb, Cr, Cu, As, Cd, Zn, and Ni) in surface sediments and sediment cores were investigated in Dingzi Bay, Shandong Peninsula. The Igeo values and modified potential ecological risk index (MRI) indicated that Cd and As presented high environmental risks in the surface and sediment cores. The high concentration sites were mainly located in the middle and the mouth of the Dingzi Bay. The source identification indicated that most heavy metals in surface sediments originated from shipping and aquaculture, while As and Ni from industrial pollution. The correlation coefficients showed that high proportion of fine particle, TN, TOC, TP, and AVS in surface sediments could significantly elevate the bioavailability of most heavy metals.

Prediction of Changes to the Suitable Distribution Area of Fritillaria przewalskii Maxim. in the Qinghai-Tibet Plateau under Shared Socioeconomic Pathways (SSPs)

The Qinghai–Tibet Plateau has given birth to many indigenous highland plants due to its special geographical location and sensitivity to climate change. Relevantly, the impact of climate change on species distribution has been a hot issue for research in biogeography. Using the maximum entropy (MaxEnt) model, the spatial distribution of habitat suitability for Fritillaria przewalskii Maxim. (FPM) on the Tibetan Plateau was predicted and ranked by combining ecological data and information on its actual current geographical distribution. The potential distribution and trends of FPM on the Tibetan Plateau from 2021 to 2040, 2041 to 2060, 2061 to 2080 and 2081 to 2100 under four current and future climate scenarios (SSP126, SSP245, SSP370 and SSP585) were also predicted. The predictions were found to be highly accurate with AUC values of 0.9645 and 0.9345 for the training and test sets, respectively. A number of conclusions could be drawn from the results. Firstly, the main ecological factors limiting the growth distribution of FPM were the Vegetation types, NPP (net primary production), Soil types, Bio7 (temperature annual range), Pop (population), Slope, GDP, Aspect, Bio1 (annual mean temperature) and Elevation, with a cumulative contribution of 97.6%. Secondly, in the recent past period of 1970–2000, the total suitable distribution area of FPM accounted for 5.55% of the plateau’s total area, which was about 14.11 × 104 km2, concentrated in its eastern and central regions. Thirdly, compared to the previous period, the aforementioned distribution area will, for the period spanning 2021–2040, increase by 14.48%, 16.23%, 16.99%, and 21.53% in the SSP126, SSP245, SSP370, and SSP585 scenarios, respectively. This comes with an overall expansion trend, and the areas predicted to be affected are concentrated in the eastern and central-western parts of the Tibetan Plateau. The other three future periods 2041–2060, 2061–2080, and 2081–2100 also show increases in these total areas to varying degrees. It is noteworthy that in the future periods 2061–2080 and 2081–2100, under the SSP370 and SSP585 scenarios, the area of high suitable distribution decreases or even disappears. Lastly, under the four climate scenarios, the FPM suitable distribution area will shift towards the western part of the Tibetan Plateau.

Computational solar energy – Ensemble learning methods for prediction of solar power generation based on meteorological parameters in Eastern India

The challenges in applications of solar energy lies in its intermittency and dependency on meteorological parameters such as; solar radiation, ambient temperature, rainfall, wind-speed etc., and many other physical parameters like dust accumulation etc. Hence, it is important to estimate the amount of solar photovoltaic (PV) power generation for a specific geographical location. Machine learning (ML) models have gained importance and are widely used for prediction of solar power plant performance. In this paper, the impact of weather parameters on solar PV power generation is estimated by several Ensemble ML (EML) models like Bagging, Boosting, Stacking, and Voting for the first time. The performance of chosen ML algorithms is validated by field dataset of a 10kWp solar PV power plant in Eastern India region. Furthermore, a complete test-bed framework has been designed for data mining as well as to select appropriate learning models. It also supports feature selection and reduction for dataset to reduce space and time complexity of the learning models. The results demonstrate greater prediction accuracy of around 96% for Stacking and Voting EML models. The proposed work is a generalized one and can be very useful for predicting the performance of large-scale solar PV power plants also.

Effect of storage time on the silage quality and microbial community of mixed maize and faba bean in the Qinghai-Tibet Plateau.

Tibetan Plateau is facing serious shortage of forage in winter and spring season due to its special geographical location. Utilization of forages is useful to alleviate the forage shortage in winter and spring season. Consequently, the current study was aimed to evaluate the influence of storage time on the silage quality and microbial community of the maize (Zea mays L.) and faba bean (Vicia faba L.) mixed silage at Qinghai-Tibet Plateau. Maize and faba bean were ensiled with a fresh weight ratio of 7:3, followed by 30, 60, 90, and 120 days of ensiling. The results showed the pH value of mixed silage was below 4.2 at all fermentation days. The LA (lactic acid) content slightly fluctuated with the extension of fermentation time, with 33.76 g/kg DM at 90 days of ensiling. The AA (acetic acid) and NH3-N/TN (ammonium nitrogen/total nitrogen) contents increased with the extension of fermentation time and no significantly different between 90 and 120 days. The CP (crude protein) and WSC (water soluble carbohydrate) contents of mixed silage decreased significantly (P < 0.05) with ensiling time, but the WSC content remained stable at 90 days. The Proteobacteria was the predominant phyla in fresh maize and faba bean, and Pseudomonas and Sphingomonas were the predominant genera. After ensiling, Lactobacillus was the prevalent genus at all ensiling days. The relative abundance of Lactococcus increased rapidly at 90 days of ensiling until 120 days of fermentation. Overall, the storage time significant influenced the silage fermentation quality, nutrient content, and microbial environment, and it remained stable for 90 days of ensiling at Qinghai-Tibet Plateau. Therefore, the recommended storage time of forage is 90 days in Qinghai-Tibet Plateau and other cool areas.

Three New Species of Lactifluus (Basidiomycota, Russulaceae) from Guizhou Province, Southwest China.

Lactifluus is a distinct genus of milkcaps, well known as ectomycorrhizal fungi. The characteristics of the genus Lactifluus include grayish-yellow, orange to orange-brown, or reddish-brown pileus, white latex from the damaged lamellae, discoloring to a brownish color, reticulate spore ornamentation, lampropalisade-type pileipellis, and the presence of lamprocystidia. Guizhou Province is rich in wild mushroom resources due to its special geographical location and natural environment. In this study, three novel Lactifluus species were identified through the screening of extensive fungal resources in Suiyang County, Guizhou Province, China, sampled from host species of mostly Castanopsis spp. and Pinus spp. Based on critical morphology coupled with nuclear sequences of genes encoding large subunit rRNA, internal transcribed spacer, and RNA polymerase II, these new species, Lactifluus taibaiensis, Lactifluus qinggangtangensis, and Lactifluus jianbaensis, were found to belong to Lactifluus section Lactifluus. A comparison with closely related species, Lactifluus taibaiensis was distinguished by its lighter-colored pileus, different colors of lamellae, and more subglobose basidiospores; Lactifluus jianbaensis was identified by the height of the spore ornamentation and its subglobose basidiospores; and Lactifluus qinggangtangensis was characterized by having smaller basidiospores, ridges, and pleurolamprocystid.

Occurrence and distribution characteristics of PCBs and PBDEs in farmland soils adjacent to electronic circuit board dismantling ruins

The Nanwan village, a green ecological village in Taizhou city, is used as a recycling area (recycling for heavy metal) for electronic circuit boards and as crushing and stacking sites of waste circuit boards for nearly 20 years from 1980s to 2000s. At present, although the e-waste recycling activities in Taizhou city have been effectively controlled, and many areas polluted by the e-dismantling activities have been gradually remediated except Nanwan village. Nanwan village seems to have been forgotten for its special geographical location, which has attracted our attention because of its ecological and food safety issues. Accordingly, the content of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) in the surface soil around the ruins and four edible agricultural crops were investigated. The main conclusions are as follows: among the four dismantling ruins and surrounding soil samples investigated, the content of Σ20PCBs in vegetable field topsoil of 2(20) is 1,321.3 ± 132.1 μg kg−1; the content of Σ8PBDEs in the paddy soil of 3(1S) is 7,216.9 ± 232.0 μg kg−1; biological toxicity events are likely to occur frequently in 2(20) and 3(1S). PCBs and PBDEs have both horizontal diffusion in distance and vertical diffusion in depth. The lifetime carcinogenic and non-carcinogenic risks of PCBs and PBDEs are at a low risk level, except for the non-carcinogenic risk of PCBs for children in 3(1S). The lifetime carcinogenic and non-carcinogenic risks of PCBs and PBDEs in the edible parts of garlic, ginger, mung beans, and oranges were all at acceptable or negligible levels.