Region Of Residence Research Articles

Probabilistic geo-referenced grid modeling: A Bayesian approach for integrating available system measurements

With the ongoing implementation of new climate targets, power distribution grids are increasingly integrating behind-the-meter photovoltaic (PV) systems, electric vehicle (EV) home chargers, and heat pumps (HPs). The integration of these solutions can often result in grid congestion issues, requiring appropriate mitigation measures. Designing these measures can be challenging in the absence of a digital and up-to-date model of the existing infrastructure, which is often the case at the low-voltage (LV) level. In this work, we introduce a novel two-stage Bayesian approach for establishing a probability distribution of geo-referenced power flow (PF)-ready grid models using available system measurements. We demonstrate the proposed approach in a residential region in Schutterwald, Germany. We find that integrating available system measurements can effectively enhance the quality of the distribution, yielding potential grid models that more accurately align with the existing infrastructure. Moreover, we showcase the practical utility of the proposed approach for assessing overvoltage within a specific grid segment subject to high rooftop PV adoption. While state-of-the-art baselines either fail to identify any overvoltage issues or are inconclusive, integrating available system measurements using the proposed approach offers a more reliable assessment.

Cross-Sectoral Comparisons of Process Quality Indicators of Health Care Across Residential Regions Using Restricted Mean Survival Time

Background: Practice guidelines recommend patient management based on scientific evidence. Quality indicators gauge adherence to such recommendations and assess health care quality. They are usually defined as adverse event rates, which may not fully capture guideline adherence over time. Methods: For assessing process indicators where compliance to the recommended treatment can be assessed by evaluating a patient's trace in linked routine databases, we propose using restricted mean survival time or restricted mean time lost, which are applicable even in competing risk situations. We demonstrate their application by assessing the compliance of patients with acute myocardial infarction (AMI) to high-power statins over 12 months in Austria’s political districts, using pseudo-observations and employing causal inference methods to achieve regional comparability. Results: We analyzed the compliance of 31,678 AMI patients from Austria’s 116 political districts with index AMI between 2011 and 2015. The results revealed considerable compliance variations across districts but also plausible spatial similarities. Conclusions: Restricted mean survival time and restricted mean time lost provide interpretable estimates of patients’ expected time in compliance (lost), well-suited for risk-adjusted entity comparisons in the presence of (measurable) confounding, censoring, and competing risks.

Influence of urban functional zone change on land surface temperature using multi-source geospatial data: A case study in Nanjing City, China

The urban heat island effect is a prevalent urban concern, and studies on its influencing factors are essential to mitigate its negative effects and promote sustainable urban development. Although many studies have revealed the impact of land cover change on land surface temperature (LST) during urbanization, most have focused only on built-up areas without considering the relationship between urban internal functional structure and LST. To clarify the influence of changes in urban functional zones (UFZs) on LST, focusing on the downtown area of Nanjing City, China, this study proposed an effective framework using multi-source geospatial data for qualitative and quantitative analysis. Specifically, very high spatial resolution images and point of interest data were jointly used to generate UFZ maps using an advanced deep learning approach, and LST distribution maps were retrieved from Landsat 8 images using the radiative transfer equation. The UFZ and LST maps were then overlaid and analyzed to reveal the impact of UFZ change on LST. The results showed that in 2013, 2018, and 2022, the residential region constituted the largest proportion of area, comprising 23.52%, 24.52%, and 27.28%, respectively. The areas of unused region and transport region experienced the most rapid decrease and increase of 6.08% and 4.05% from 2013 to 2022, respectively. Furthermore, the area of sub-high temperature zone decreased the most, by 3.47%, whereas that of the high-temperature zone increased the most, by 6.05%. In the study area, water and green space maintained relatively low LSTs, whereas residential region and unused region exhibited higher LSTs. From 2013 to 2022, UFZ changes contributed to a 0.71°C increase in LST. Transfers from green space, water, commercial region, transport region, and industrial region mostly resulted in a higher LST, which was associated with a decrease in fractional vegetation cover (FVC). Transfers from unused region, residential region, and public service region mostly contributed to reducing LST, which was caused by the increase in FVC. The findings and the proposed framework can provide reliable references for urban managers to optimize urban spatial layout and promote sustainable urban development.

Landslide risk assessment in mining areas using hybrid machine learning methods under fuzzy environment

Landslide risk assessment in coal mining economic cities faces challenges due to inadequate knowledge of indicator systems and modeling techniques, despite its crucial significance in geological disaster management. This study addresses this gap by proposing a novel framework encompassing data preparation, susceptibility analysis, consequence analysis, and final risk assessment. The primary objective is to reduce the complexity and inherent uncertainties associated with landslide risk assessment in these specific urban environments. First, two comprehensive databases for the indication system were established. One database focuses on landslide susceptibility, considering the region’s mining disturbances and disaster-prone environments. The other evaluates the effect of consequences while accounting for the pertinent risk variables. Second, a hybrid machine learning model called Geo-FR-SVM was developed by combining the GeoDetector, Frequency Ratio method, and Support Vector Machine model to improve landslide susceptibility mapping. Integrating the susceptibility map with the consequence map created using fuzzy set theory and fuzzy analytical hierarchy process methodologies resulted in the final landslide risk map. Our analysis revealed that elevation, distance to rivers and roads, groundwater level, and coal mining subsidence were the key factors influencing landslide occurrence in the Xishan mine area. The majority of the study area exhibits low landslide risk. However, higher consequence zones were primarily concentrated in highly populated residential regions and coal mine industrial zones in the east-central and western urban areas. Additionally, they are mainly distributed along the roads in the center region. With comparatively large percentages of landslide high-risk and extremely high-risk regions (4.596%, 3.855%, 3.625%, and 3.188%, respectively) at Tunlan Mine, Xiqu Mine, Zhenchengdi Mine, and Baijiazhuang Mine, these findings highlight the need for these mines to prioritize potential landslide identification and risk mitigation strategies. This framework offers broad applicability to other coal mining economic cities, serving as a valuable foundation for landslide risk management decision-making.

Effects of acoustic environment on sleep and mental health in residential regions near railways

Noise is an important environmental risk factor for physical and mental health. Furthermore, long-term noise exposure is burdensome for the mind and body and has become a serious problem. Rail transportation is one of the main methods used to transport goods in China; however, the noise and vibrations generated by freight trains have serious impacts on residents in nearby regions. To further investigate the relationship between railway noise and road noise exposure and changes in sleep duration and mental health scores, a field study in Harbin, China, was conducted and a health risk prediction model was constructed. The results showed that for every 1 dB increase in the Equivalent continuous A-weighted sound pressure level (LAeq), the percentage of deep sleep among residents living near the railway decreased by 0.2 %. Although residents near the railway reported similar sleep evaluations compared to those living farther away, they exhibited poorer mental health. Cox risk modeling indicates that the risk of mental health problems is approximately three times higher for those living near the railway. These findings potentially provide benefits in developing strategies to reduce the risk of mental illness for people residing near railways.

Association between cognitive insight and anxiety among community-dwelling schizophrenia patients: the chain mediating effects of family cohesion and chronotype.

To investigate the effect of cognitive insight on anxiety in community-dwelling schizophrenia patients and to construct a chain mediating model to determine the underlying mechanisms of the relationship between cognitive insight and anxiety through family cohesion and chronotype. The Beck Cognitive Insight Scale, the Chinese version of the Family Adaptability and Cohesion Scale, the Morningness-Eveningness Scale, and the Generalized Anxiety Disorder Scale were used to assess cognitive insight, family cohesion, chronotype, and anxiety in a sample of 785 individuals with schizophrenia living in the community. Spearman correlation analysis, multiple linear regression and Bootstrap methods were employed to analyze the four variables. Residential region, current employment status, and family economic status impacted anxiety among community-dwelling schizophrenia patients. All variables were associated with each other, but self-certainty was not significantly associated with anxiety. Cognitive insight and self-reflection had direct effects on anxiety, as well as indirect effects on anxiety through the partial mediating effect of chronotype, the suppressing effect of family cohesion, and the chain mediating effect of family cohesion and chronotype. Family cohesion and chronotype can mediate the relationship between cognitive insight and anxiety. Improving family functioning, promoting emotional relationships within families, and correcting non-circadian sleep patterns can reduce anxiety in community-dwelling schizophrenia patients, with important implications for improving adverse mental health outcomes.

The association between residential region or socioeconomic status and dyslipidemia prevalence

The association between residential region or socioeconomic status and dyslipidemia prevalence

Canadians' experiences of alternative protein foods and their intentions to alter current dietary patterns

Despite established evidence about the environmental and health benefits of alternative protein foods (APF), considerable knowledge gaps and misconceptions remain toward APF. Drawing on a national survey (1800+ responses), the study explores Canadians' experiences of APF and intentions to alter current dietary patterns focusing on four APF – plant-based alternative proteins (PBAP) – plant-based (PB) milk, PB meat, lab-grown (LG) meat, and other alternative proteins (OAP) – and two animal-based foods (ANBF)– milk and meat. Data were collected based on a proportional stratified sampling method from all regions of Canada and analyzed using econometric models. While PB milk was the most consumed APF, followed by PB meat, LG meat was the least tried among participants. Perceived complexity of APF discouraged individuals from cutting back on ANBF, while increasing the consumption of APF. Perceived relative advantage was positively related to the adoption of APF. Perceived compatibility strongly influenced individuals’ adoption of PB meat and OAP. Likewise, perceived trialability significantly influenced the adoption of PB milk and PB meat. Despite the perception that APF may have high health related risks associated with processing, additives, calorie and sugar content, this did not prevent individuals from consuming PB milk and OAP. However, perceived risks did affect intentions to alter dietary patterns in the next 12 months. Additionally, meat attachment and sustainability orientation significantly predicted current consumption decisions of APF and intentions to alter dietary patterns. Although sustainability orientation motivates dietary changes, it did not always lead to extreme shifts. Finally, several demographic variables (age, gender, and education), dietary preferences (being omnivore), and residential area and region had influence on current consumption decisions and future intentions. In conclusion, by controlling several factors and through a comparative analysis of various protein sources, the study offers insights into the interplay of innovation-adoption characteristics, perceived risks, meat attachment and sustainability orientation in understanding dietary choices and provides some implications for industry stakeholders and policies promoting APF.

Derivation of ecotoxicologically acceptable Cu concentrations in soil from different land uses in South Korea

This study aimed to establish ecotoxicologically acceptable Cu concentrations for soil-residing species by integrating the biotic ligand model and the species sensitivity distribution. Statistical analyses were performed on 35 soil solution samples collected from four distinct land use sites: residential, agricultural, forested, and industrial regions. The environmental parameters of these samples, including pH, dissolved organic carbon (DOC), Ca2⁺, Mg2⁺, K⁺, and Na⁺ concentrations, exhibited wide variations across the four regions. Specifically, pH and the concentrations of Mg2⁺, K⁺, and Na⁺ showed significant variability. Additionally, a strong correlation was observed between pH and Ca2⁺, as well as between the DOC concentration and Mg2⁺ and Na⁺. Using the biotic ligand model, we derived the half-maximal effective activities of Cu (EC50{Cu2+}) for 10 soil organisms based on the chemical compositions of the soil solution samples. Additionally, a species sensitivity distribution approach was employed to determine the 5% hazardous concentration (HC5) for soil biota, which was closely associated with DOC and Na⁺ concentrations, with Mg2⁺ playing a secondary role. We attributed these relationships to the formation of DOC complexes that mitigate Cu toxicity, along with competitive interactions with cations. Notably, HC5 values did not differ significantly across sampling sites (p = 0.523). Clustering based on environmental factors grouped the samples into four clusters, each containing soils from different land use types. However, the third cluster included an outlier from agricultural soil due to its unusually high pH and DOC levels. These findings suggest that it is crucial to consider site-specific soil characteristics when determining ecotoxicologically acceptable Cu concentrations, and soil solution characteristics do not always align with specific land use patterns.

Mortality risk and burden of aortic aneurysm and dissection attributable to low temperatures: A nationwide case-crossover analysis in Brazil, a predominantly tropical country

BackgroundLow temperatures are adverse contributors to cardiovascular diseases, but the associations between short-term exposure to cold and the risk of death from aortic dissection and aneurysm remain unclear, particularly in tropical regions. ObjectiveThis study was conducted based on 123,951 records of deaths caused by aortic dissection and aneurysms extracted from the national Mortality Information System in Brazil between 2000 and 2019. MethodsRelative risks and 95 % confidence intervals (CI) for the aortic-related deaths associated with low ambient temperatures were estimated using the conditional logistic model combined with the distributed lag nonlinear model. Subgroup analyses were performed by age group, sex, race, education level, and residential region. Furthermore, this study calculated the number and fraction of aortic-related deaths attributed to temperatures below the temperature threshold to quantify the cold-related mortality burden of aortic diseases. ResultsDuring the study period, aortic-related deaths and mortality rates in Brazil exhibited a steady increase, rising from 4419 (2.66/100,000) in 2000 to 8152 (3.88/100,000) in 2019. Under the identified temperature threshold (26 °C), per 1 °C decrease in daily mean temperature was associated with a 4.77 % (95 % CI: 4.35, 5.19) increase in mortality risk of aortic-related diseases over lag 0–3 days. Females, individuals aged 50 years or older, Asian and Black race, and northern residents were more susceptible to low temperatures. Low temperatures were responsible for 19.10 % (95 % CI: 17.71, 20.45) of aortic-related deaths in Brazil. ConclusionThis study highlights that low temperatures were associated with an increased risk of aortic-related deaths, with a remarkable burden even in this predominantly tropical country.

From Likes to Lifestyle: Predicting the Impact of Following Fitness Influencers on the Adoption of Healthy Habits in Saudi Arabia.

The increasing popularity of fitness influencers on social media has the potential to significantly impact public health by promoting healthy behaviors. Understanding how these influencers affect the adoption of healthy habits among Saudi residents can provide insights into effective public health strategies. This study aims to quantitatively assess the influence of following fitness influencers on social media on adopting healthy behaviors among Saudi residents, focusing on socio-demographic factors, characteristics of influencers, and participants' perceptions. A descriptive, cross-sectional study with an analytical component was carried out from March 25, 2023, to August 15, 2023. The study included Saudi residents aged 18 and older who actively follow fitness influencers. Data was gathered through an online questionnaire and analyzed using descriptive statistics, Pearson's chi-square test, and logistic regression analyses to identify factors associated with positive health outcomes. The study included 561 participants, revealing that marital status and residential region significantly influenced the adoption of healthy habits, with married participants and those from the Southern and Central regions more likely to report positive outcomes. Notably, engagement in physical activity more than three times a week and adherence to a healthy diet were strongly associated with positive health outcomes (p<0.05). Analysis of influencer characteristics showed that following fewer than 10 influencers and being unaware of their follower count were predictors of positive results with p<0.05. Specifically, 76.6% of participants experienced positive results after following health advice from social media, highlighting the impactful yet complex role of influencers in shaping health behaviors. Logistic regression analyses underscored the significance of socio-demographic factors, influencer characteristics, and participant perceptions in predicting the likelihood of experiencing positive health outcomes. Following fitness influencers on social media can positively impact the adoption of healthy habits, moderated by socio-demographic factors and influencer characteristics.

The differential impacts of COVID-19 mortality on mental health by residential geographic regions: The Los Angeles Pandemic Surveillance Cohort Study.

This study examines the association between changes in mental health before and during the COVID-19 pandemic and COVID-19 mortality across geographic areas and by race/ethnicity. A cross-sectional survey was conducted in Los Angeles County between April and May 2021. The study used the Patient Health Questionnaire-2 to assess major depression risk. Participants' home ZIP codes were classified into low, middle, and high COVID-19 mortality impacted areas (CMIA). While there were existing mental health disparities due to differences in demographics and social determinants of health across CMIA in 2018, the pandemic exacerbated the disparities, especially for residents living in high CMIA. Non-White residents in high CMIA reported the largest deterioration in mental health. Differences in mental health by CMIA persisted after controlling for resident characteristics. Living in an area with higher COVID-19 mortality rates may have been associated with worse mental health, with Non-White residents reporting worse mental health outcomes in the high mortality area. It is crucial to advocate for greater mental health resources in high COVID-19 mortality areas especially for racial/ethnic minorities.

Levels of Potentially Toxic and Essential Elements in Water and Estimation of Human Health Risks in a River Located at the Interface of Brazilian Savanna and Amazon Biomes (Tocantins River).

The Tocantins-Araguaia basin is one of South America's largest river systems, across three Brazilian states (Maranhão, Tocantins, and Pará), within the Legal Amazon region. Despite draining extensive Cerrado savanna and rainforest ecosystems, it has suffered significant degradation, notably in the past 40 years. Human activities, including agricultural expansion, deforestation, and the introduction of non-native species, have worsened the environmental damage, which is alarming since many residents and villages along the middle Tocantins River rely on it for water supply, recreation, and fishing. This study assessed the concentration of potentially toxic and essential elements in water samples from four sampling sites distributed along the middle Tocantins River. The monitoring occurred throughout 2023, involving the measurement of parameters both on-site and in the laboratory. Water quality and its health implications were evaluated using the Weighted Arithmetic Water Quality Index (WAWQI), the Water Quality Index (WQI), and the health risk assessment index. The levels of aluminum, copper, iron, magnesium, and selenium exceeded legal standards. Seasonal fluctuations indicate a complex dynamic influenced by climatic or seasonal factors, with February showing the highest values. Site P1, located in urban areas, exhibited elevated mean concentrations for conductivity, total dissolved solids (TDS), and chlorophyll, indicating the need for continuous monitoring. The nitrogen concentrations at P1 raise concerns regarding drinking water quality, which is a concern for the region's residents who use untreated river water. Despite seasonal variations in element concentrations, the overall WAWQI categorized all sections as "Excellent," and the WQI rated as "Good." Human health risk assessments detected no risks, but continuous monitoring and interventions are crucial for sustained water quality improvement.

Spatial distribution of sediment dissolved organic matter in oligotrophic lakes and its binding characteristics with Pb(II) and Cu(II).

Dissolved organic matter (DOM), the most active component in interstitial waters, determines the stability of heavy metals and secondary release in sediments. However, little is known about the composition and metal-binding patterns of DOM in interstitial water from oligotrophic lakes affected by different anthropogenic perturbations. Here, 18 interstitial water samples were prepared from sediments in agricultural, residential, tourist, and forest regions in an oligotrophic lake (Shengzhong Lake in Sichuan Province, China) watershed. Interstitial water quality and DOM composition, properties, and Cu(II)- and Pb(II)-binding characteristics were measured via physicochemical analysis, UV-vis spectroscopic, fluorescence excitation-emission matrix-parallel factor analysis (EEM-PARAFAC), and fluorescence titration methods. The DOM, which was produced mainly by microbial activities, had low molecular weights, humification degrees, and aromaticity. Based on EEM-PARAFAC results, the DOM was generally composed of tryptophan- (57.7%), terrestrial humic- (18.7%), microbial humic- (15.6%), and tyrosine-like (8.0%) substances. The DOM in the metal complexes was primarily composed of tryptophan-like substances, which accounted for ~42.6% of the DOM-Cu(II) complexes and ~72.0% of the DOM-Pb(II) complexes; however, microbial humic-like substances primarily contributed to the stability of DOM-Cu(II) (logKCu = 3.7-4.6) and DOM-Pb(II) (logKPb = 4.3-4.8). Water quality parameters did not significantly affect the stability of DOM-metal complexes. We demonstrated that the metal-binding patterns of DOM in interstitial water from oligotrophic lakes are highly dependent on microbial DOM composition and are affected by anthropogenic perturbations to a lesser extent.

Patterns of neurogenic lower urinary tract dysfunction management and associated factors among Chinese community-dwelling individuals with spinal cord injury

To identify different patterns of neurogenic lower urinary tract dysfunction management among Chinese community-dwelling individuals with spinal cord injury and explore the factors associated with latent classes. This was a cross-sectional study conducted in communities throughout China Mainland. Participants were recruited through the China Association of Persons with Physical Disability and a total of 2582 participants was included in the analysis. The data were collected by a questionnaire consisting of socio-demographic factors, disease-related factors, and a list of 8 bladder management methods. Latent class analysis was used to identify different latent classes of neurogenic lower urinary tract dysfunction management. Then the multinomial logistic regression was applied to analyze the relationship between neurogenic lower urinary tract dysfunction management patterns and socio-demographic and disease-related factors. Neurogenic lower urinary tract dysfunction management pattern among community-dwelling individuals with spinal cord injury was divided into four latent classes: “urinal collecting apparatus dominated pattern” (40.3%), “bladder compression dominated pattern” (30.7%), “intermittent catheterization dominated pattern” (19.3%) and “urethral indwelling catheterization dominated pattern” (9.6%). Multinomial logistic regression analysis found that the employment status, residential region, nursing need, payment method for catheterization products, hand function, time since spinal cord injury, urinary incontinence and concerns about social interaction affected by urination problems were significantly associated with latent classes. Only 19.3% of people used the intermittent catheterization as their main neurogenic lower urinary tract dysfunction management method. More attention needs to be paid to the promotion of the standardization process of intermittent catheterization in community-dwelling individuals with spinal cord injury. The associated factors of the four classes can be used for tailored and targeted interventions to increase the use of intermittent catheterization.

Regional differences in heart failure risk in the United Kingdom are partially explained by biological aging.

Heart failure (HF) risk is greater in rural versus urban regions in the United States (US), potentially due to differences in healthcare coverage and access. Whether this excess risk applies to countries with universal healthcare is unclear and the underlying biological mechanisms are unknown. In the prospective United Kingdom (UK) Biobank, we investigated urban-rural regional differences in HF risk and the mechanistic role of biological aging. Multivariable Cox regression was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of incident HF in relation to residential urban-rural region and a Biological Health Score (BHS) that reflects biological aging from environmental, social, or dietary stressors. We estimated the proportion of the total effect of urban-rural region on HF mediated through BHS. Among 417,441 European participants, 10,332 incident HF cases were diagnosed during the follow-up. Compared to participants in large urban regions of Scotland, those in England/Wales had significantly increased HF risk (smaller urban: HR = 1.83, 95%CI: 1.64-2.03; suburban: HR = 1.77, 95%CI: 1.56-2.01; very rural: HR = 1.61, 95%CI: 1.39-1.85). Additionally, we found a dose-response relationship between increased biological aging and HF risk (HRper 1 SD increase = 1.14 (95%CI: 1.12-1.17). Increased biological aging mediated a notable 6.6% (p < 0.001) of the total effect of urban-rural region on HF. Despite universal healthcare in the UK, disparities in HF risk by region were observed and may be partly explained by environmental, social, or dietary factors related to biological aging. Our study contributes to precision public health by informing potential biological targets for intervention.

Geomythological sites as potential geotourism destinations on the example of Lublin and Roztocze regions, SE Poland

Geomythology is an important element of the region's immaterial culture and the cultural identity of its inhabitants. Thanks to geomythology, tourists' interest in geotourist sites is increasing and their perception of these sites is changing. Geotourism is one of the forms of specialized tourism with a relatively narrow audience. To attract visitors from other groups, e.g., schoolchildren, families with children, tourists interested in the cultural heritage of a region, information on geological (or more broadly, geographic) resources can be expanded to include cultural information. One way to attract tourists and get a wider audience interested in geology is to provide geological information along with legends about the places visited. At the same time, geomythology increases the cultural identity of the region's residents.

Characteristics, sources, and health risks of volatile organic compounds in different functional regions of Shenyang

The concentration of 56 volatile organic compounds (VOCs) in the ambient air of Shenyang was continuously monitored at four sites in 2021. The characteristics, sources, secondary pollution potential and health risks of VOCs in different functional regions of Shenyang were discussed. The results indicate that the concentration of VOCs in industrial regions was significantly higher than that in non-industrial regions, with a mean of 41.09 ± 69.82 parts per billion volumes (ppbv) compared to 19.99 ± 17.86 ppbv (commercial & residential region in urban fringe), 27.51 ± 28.81 ppbv (educational & scenic region) and 29.71 ± 23.97 ppbv (commercial & residential region in urban center). The positive matrix factorization (PMF) model was utilized to assign the sources of VOCs in Shenyang, and six factors were recognized: gasoline vehicles (34.8 %), diesel vehicles (28.3 %), combustion (11.4 %), biogenic emissions (9.7 %), industrial processes (8.2 %), and fuel evaporation (7.7 %). The results of the reactivity evaluation indicated that the ozone (O3) formation potential (OFP) was primarily influenced by industrial processes (29.2 %), diesel vehicles (25.7 %), biogenic emissions (17.0 %). These three factors were also the top three contributors to secondary organic aerosol formation potential (SOAP), accounting for 44.2 %, 9.4 % and 30.3 %, respectively. At the all four sites, the non-carcinogenic and carcinogenic risks of VOCs ranged from 1.6 × 10−2 to 3.8 × 10−2 and from 2.3 × 10−6 to 3.3 × 10−6, respectively. And the main risks can be attributed to emissions from industrial processes and gasoline vehicles. These findings suggested to strengthen the control of vehicle emissions throughout all regions in Shenyang and industrial processes emissions in industrial regions.

A Multi-Feature Fusion Method for Urban Functional Regions Identification: A Case Study of Xi’an, China

Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. For this purpose, this paper proposes an urban functional region identification method called ASOE (activity–scene–object–economy), which integrates the features from multi-source data to perceive the spatial differentiation of urban human and geographic elements. First, we utilize VGG16 (Visual Geometry Group 16) to extract high-level semantic features from the remote sensing images with 1.2 m spatial resolution. Then, using scraped building footprints, we extract building object features such as area, perimeter, and structural ratios. Socioeconomic features and population activity features are extracted from Point of Interest (POI) and Weibo data, respectively. Finally, integrating the aforementioned features and using the Random Forest method for classification, the identification results of urban functional regions in the main urban area of Xi’an are obtained. After comparing with the actual land use map, our method achieves an identification accuracy of 91.74%, which is higher than other comparative methods, making it effectively identify four typical urban functional regions in the main urban area of Xi’an (e.g., residential regions, industrial regions, commercial regions, and public regions). The research indicates that the method of fusing multi-source data can fully leverage the advantages of big data, achieving high-precision identification of urban functional regions.

Influences of daily solar radiation intensity on the sea-land breeze and pollutant dispersion in coastal areas

Solar radiation plays a crucial role in the formation of sea-land breeze (SLB) circulation in coastal areas, and the SLB circulation in turn influences the atmospheric diffusion of pollutants in coastal cities. Therefore, the characteristics of the SLB and its impacts on the pollutant distributions in Shanghai, China, are numerically investigated for three (low, medium, and high) daily solar radiation intensities (DSRIs). The results show that the pollutant dispersion is affected by both the horizontal flow of SLB circulation and the vertical thermal plume (TP). The SLB only transports pollutants within the near-ground layer, while TP removes pollutants from the boundary layer and then improves near-ground air quality. Both the intensities of the SLB and TP increase with the increase of DSRI, however, the relative strength of the two are different at different DSRIs. When the DSRI is high (28.35 MJ/m2/day) or low (9.45 MJ/m2/day) during the daytime, the sea breeze (SB) is much stronger than the TP, so the prevailing flow direction on the land is horizontal, causing large amounts of pollutants to be blown inland. For the medium DSRI (18.90 MJ/m2/day), the TP is more powerful in the early stage of the SB period, so the airflow across the land is dominated by the rising TP. Pollutants are mainly transported to the upper atmosphere and the best air quality can be achieved in the residential region. At night, the worst air quality occurs at low DSRI, because when the DSRI is low, the speed of the land breeze is also low and this decelerates the diffusion of pollutants to the sea by the wind.