Impact of urban expansion on the air pollution landscape: A case study of Hanoi, Vietnam

Exploring the predictive ability of the CA-Markov model for urban functional area in Nanjing old city

With advancements in sustainable urban development, research on urban functional areas has garnered significant attention. In recent years, Point-of-Interest, with their large volume of information and ease of acquisition, have been widely applied in research on urban functional domains. However, scholars currently focus on the identification of urban functional areas, usually relying on data from a single period, whereas research on the prediction of functional areas has not yet been well validated. Therefore, in this study, we propose a new method based on several years of POI data to predict urban functional areas. Taking Nanjing City, Jiangsu Province, as an example, we first identified the functional area distribution of the old city of Nanjing over several years using POI data and then designed multiple sets of experiments to explore the CA-Markov model's ability to predict functional areas from various aspects, including model overall accuracy, robustness, and comparison analysis between predictions and actual situations. The results show that (1) for mixed or single functional areas, the model's predictions over several years tend to be stable, and the accuracy of the predictions over many years indicates the robustness of the model in predicting urban functional areas. (2) For mixed functional areas in cities, model predictions largely rely on the distribution of the base years used for prediction, leading to inaccurate results; thus, it is still not applicable for simulating and predicting mixed functional areas. (3) For single functional areas in cities or primary functions within an area, the model's predicted degree of change was close to the actual degree of change, making the results referable.

How urban growth dynamics impact the air quality? A case of eight Indian metropolitan cities

Air pollution is a matter of great significance that confronts the sustainable progress of urban areas. Against India's swift urbanization, several urban areas exhibit the coexistence of escalating populace and expansion in developed regions alongside extensive spatial heterogeneity. The interaction mechanism between the growth of urban areas and the expansion of cities holds immense importance for the remediation of air pollution. Henceforth, the present investigation utilizes geographically weighted regression (GWR) to examine the influence of urban expansion and population growth on air quality. The examination will use a decade of data on the variation in PM2.5 levels from 2010 to 2020 in eight Indian metropolitan cities. The study's findings demonstrate a spatial heterogeneity between urban growth dynamics and air pollution levels. Urban growth and the expansion of cities demonstrate notable positive impacts on air quality, although the growth of infilling within expanding urban areas can significantly affect air quality. Given the unique trajectories of urban development in developing countries, this research provides many suggestions for urban administrators to foster sustainable urban growth.

Assessment and mapping of noise pollution in recreation spaces using geostatistic method after COVID-19 lockdown in Turkey

Increased use of recreational areas after the lifting of COVID-19 pandemic restrictions has led to increased noise levels. This study aims to determine the level of noise pollution experienced in recreational areas with the increasing domestic and international tourism activities after the lifting of pandemic lockdowns, to produce spatial distribution maps of noise pollution, and to develop strategic planning suggestions for reducing noise pollution in line with the results obtained. Antalya-Konyaaltı Beach Recreation Area, the most important international tourism destination of Turkey, is determined as the study area. To determine the existing noise pollution, 31 measurement points were marked at 100 m intervals within the study area. Noise measurements were taken during the daytime (07:00-19:00), evening (19:00-23:00), and nighttime (23:00-07:00) on weekdays (Monday, Wednesday, Friday) and weekends (Sunday) over 2 months in the summer when the lockdown was lifted. In addition, the sound level at each measurement point was recorded for 15 min, while the number of vehicles passing through the area during the same period was determined. The database created as a result of measurements and observations was analyzed using statistical and geostatistical methods. After the analysis of the data, it was found that the co-kriging-stable model showed superior performance in noise mapping. Additionally, it was revealed that there is a high correlation between traffic density and noise intensity, with the highest equivalent noise level (Leq) on weekdays and weekend evenings due to traffic and user density. In conclusion, regions exposed to intense noise pollution were identified and strategic planning recommendations were developed to prevent/reduce noise sources in these identified regions.

A Two-Way Fixed Effects Estimation on the Impact of Industrial Land Supply on Environmental Pollution in Urban China

Despite the great economic growth and fast urbanization process in the past four decades, China is now suffering severely from environmental pollution. Local governments' industrial land supply behaviors have a great impact on local investment, economic growth, and environmental pollution, which has not been effectively evaluated. To fill this gap, this paper quantitatively investigates the impact of industrial land supply by local governments on environmental pollution based on a two-way fixed effects model. A comprehensive and reliable data set for 277 Chinese prefecture-level cities from 2009 to 2017 has been collected for analysis. The findings suggest that the increase of the ratio of industrial and mining storage land to total land supply significantly increases the concentration of PM2.5. The results remain significant and robust after a series of robustness tests. The negative impacts on environmental quality caused by differences in land supply behavior are greater in the central and western regions. We further explored intermediate mechanisms for the environmental impact of local governments' allocations of industrial land. The findings suggest that greater industrial land transfer by local governments leads to an expansion in the scale of regional secondary industry and increases in local fiscal deficit. Unbalanced industrial development, insufficient corporate innovation, and insufficient investment in environmental protection will increase pollution. This study provides a reference for improving regulatory measures on land transactions and for formulating regional polices for environmental protection.

Near-surface wind profile test based on accuracy verification of UAV anemometer lifting height in an urban fringe built-up area

Multirotor UAVs (unmanned aerial vehicles) have been widely used in urban vertical wind environment testing, whereas less attention has been given to the accuracy of wind speed captured by anemometers as drones fly. This paper aims to identify the ideal location of the anemometer on the UAV to obtain more accurate wind speeds and to assess the variation characteristics of wind speed in different spatial types in urban fringe areas. Accuracy verification of the lifting height of the anemometer in the UAV and wind profile test was carried out at three locations (a tennis court, a residential area, and a green park) on the iHarbour campus of Xi'an Jiaotong University. The following results were obtained: (1) the background wind speed was captured more accurately (R = 0.727, P = 0.001) when the lifting height of the anemometer was 0.00 m (as the height of the anemometer was the same as the rotors) and when the multirotor UAV was hovering in the air. However, this optimal lifting height lost 29.6% of the accuracy for capturing the background wind speed. Interestingly, when the lifting height was 0.75 m, the anemometer captured by the anemometer on the drone showed a significant negative correlation (R =  - 0.682, P = 0.005) with the background wind speed. (2) The wind speed at an altitude of 1.5 m in the residential area was significantly lower than that noted at other heights, and the wind speed at 24 m was significantly lower than that at 100 m. (3) In addition, a sudden increase in wind speeds was always observed near the surface of 12 m inside the campus, which may be due to the interaction of hot surface air in this newly built-up area with the cool rural winds around it. The study presents methods and quantitative references for the application of multirotor UAVs in urban vertical wind environment testing and the evaluation of ventilation performance at different heights inside high-rise houses in urban fringe areas.

Spatiotemporal characteristics and drivers of Chinese urban total noise pollution from 2007 to 2019

Noise pollution as a result of urbanization and socioeconomic development threatens human health and has become a major environmental problem worldwide, particularly for urban residents. Based on observed equivalent noise data of 113 major Chinese cities, a Bayesian spatiotemporal hierarchy model (BSTHM) was employed to investigate the spatiotemporal characteristics of urban noise pollution in China from 2007 to 2019. Meanwhile, the BART model was adopted to explore the drivers of urban noise pollution. The mean and medium of the equivalent noise of the 113 major cities decreased from 2007 to 2011 but increased from 2011 to 2019; the corresponding annual growth is 0.0793 dB and 0.0947 dB per year. The overall spatial pattern has a certain geographical feature. The cities located in the eastern and north-eastern coastal regions generally have a higher level of noise pollution, and the western and southwestern cities have a lower level. One hundred cities not only have greater noise pollution but also an increasing trend. Although the 52 cities located in Western China have less noise pollution, they have increasing local trends. The results indicate that economic and social factors are the main drivers of noise pollution of China; the explanatory power is 46.2%. Traffic factors are also relatively important drivers, of which bus ridership is the leading one. In terms of the natural environment, climatic factors, including temperature and relative humidity, and presence of green areas containing parkland and general green land are the main determinants.

Escaping from Air Pollution: Exploring the Psychological Mechanism behind the Emergence of Internal Migration Intention among Urban Residents

Rapid urbanization with poor city planning has resulted in severe air pollution in urban areas of low- and middle-income countries. Given the adverse impacts of air pollution, citizens may develop ideation of averting behaviors, including migration to another region. The current study explores the psychological mechanism and demographic predictors of internal migration intention among urban people in Hanoi, Vietnam-one of the most polluted capital cities in the world. The Bayesian Mindsponge Framework (BMF) analytics was used to construct a model and perform Bayesian analysis on a stratified random sampling dataset of 475 urban people. We found that migration intention was negatively associated with an individual's satisfaction with air quality. The association was moderated by the perceived availability of a nearby alternative (i.e., a nearby province/city with better air quality). The high migration cost due to geographical distance made the moderation effect of the perceived availability of a faraway alternative negligible. These results validate the proposed psychological mechanism behind the emergence of migration intention. Moreover, it was found that male and young people were more likely to migrate. While the brain drain effect did not clearly show, it is likely due to complex underlying interactions of various related factors (e.g., age and gender). The results hint that without air pollution mitigation measures, the dislocation of economic forces might occur and hinder sustainable urban development. Therefore, collaborative actions among levels of government, with the environmental semi-conducting principle at heart, are recommended to reduce air pollution.

Urban Expansion in China: Spatiotemporal Dynamics and Determinants

China’s urbanization has attracted many scholars’ attention due to its significant impact on socioeconomic sustainability. Many studies have explored the spatial pattern and effects of the factors influencing urban expansion. However, the spatiotemporal dynamics integrating spatial and temporal dimensions and the spatial scales of the influencing factors are always ignored. This study applied the framework of exploratory space–time data analysis (ESTDA) to investigate the spatiotemporal dynamics of urban expansion across 342 cities in China from 1990 to 2017 and, further, used multiscale geographically weighted regression (MGWR) to estimate the effects of influencing factors on urban expansion. We found that urban expansion had an obvious south–north division, and yet the effects of influencing factors usually showed an east–west division. We also found that the dynamic local spatial dependency of urban expansion was accompanied by a volatile coevolution process and inclined to transfer from heterogeneity to homogeneity, and homogeneity tended to be stable. The coevolution of urban expansion between cities and other neighboring ones became stronger with increases in time and regional integration. These findings support the use of customized urban planning for specific regions in different spatial dependence to improve land-use efficiency and coordinate regional development.

Indoor Air Pollution and Susceptibility to Tuberculosis Infection in Urban Vietnamese Children

RATIONALE

The Southeast Asian tuberculosis burden is high, and it remains unclear if urban indoor air pollution in this setting is exacerbating the epidemic.

OBJECTIVES

To determine the associations of latent tuberculosis with common urban indoor air pollution sources (secondhand smoke, indoor motorcycle emissions, and cooking) in Southeast Asia.

METHODS

We enrolled child household contacts of patients with microbiologically confirmed active tuberculosis in Vietnam, July 2017-December 2019. We tested children for latent tuberculosis and evaluated air pollution exposures with questionnaires and personal aerosol sampling. We tested hypotheses using generalized estimating equations.

MEASUREMENTS AND MAIN RESULTS

We enrolled 72 tuberculosis patients (27% with cavitary disease) and 109 of their child household contacts. Of household contacts, 58 (53%) were diagnosed with latent tuberculosis at baseline visit. Children experienced a 2.56-fold increased odds of latent tuberculosis for each additional household member who smoked (95%CI 1.27-5.16). Odds were highest among children exposed to indoor smokers and children under five years old exposed to household smokers. Each residential floor above street-level pollution decreased the odds of latent tuberculosis by 36% (aOR 0.64, 95%CI 0.42-0.96). Motorcycles parked inside children's homes and cooking with liquid petroleum gas compared to electricity increased the odds of latent tuberculosis while kitchen ventilation decreased the effect, but these findings were not statistically significant.

CONCLUSION

Common urban indoor air pollution sources were associated with increased odds of latent tuberculosis infection in child household contacts of active tuberculosis patients.

The Biological Deserts Fallacy: Cities in Their Landscapes Contribute More than We Think to Regional Biodiversity

Cities are both embedded within and ecologically linked to their surrounding landscapes. Although urbanization poses a substantial threat to biodiversity, cities also support many species, some of which have larger populations, faster growth rates, and higher productivity in cities than outside of them. Despite this fact, surprisingly little attention has been paid to the potentially beneficial links between cities and their surroundings. We identify five pathways by which cities can benefit regional ecosystems by releasing species from threats in the larger landscape, increasing regional habitat heterogeneity and genetic diversity, acting as migratory stopovers, preadapting species to climate change, and enhancing public engagement and environmental stewardship. Increasing recognition of these pathways could help cities identify effective strategies for supporting regional biodiversity conservation and could provide a science-based platform for incorporating biodiversity alongside other urban greening goals.

Exploring the Dynamic Spatio-Temporal Correlations between PM2.5 Emissions from Different Sources and Urban Expansion in Beijing-Tianjin-Hebei Region

Due to rapid urbanization globally more people live in urban areas and, simultaneously, more people are exposed to the threat of environmental pollution. Taking PM2.5 emission data as the intermediate link to explore the correlation between corresponding sectors behind various PM2.5 emission sources and urban expansion in the process of urbanization, and formulating effective policies, have become major issues. In this paper, based on long temporal coverage and high-quality nighttime light data seen from the top of the atmosphere and recently compiled PM2.5 emissions data from different sources (transportation, residential and commercial, industry, energy production, deforestation and wildfire, and agriculture), we built an advanced Bayesian spatio-temporal autoregressive model and a local regression model to quantitatively analyze the correlation between PM2.5 emissions from different sources and urban expansion in the Beijing-Tianjin-Hebei region. Our results suggest that the overall urban expansion in the study area maintained gradual growth from 1995 to 2014, with the fastest growth rate during 2005 to 2010; the urban expansion maintained a significant positive correlation with PM2.5 emissions from transportation, energy production, and industry; different anti-haze policies should be designated according to respective local conditions in Beijing, Tianjin, and Hebei provinces; and during the period of rapid urban expansion (2005-2010), the spatial correlations between PM2.5 emissions from different sources and urban expansion also changed, with the biggest change coming from the PM2.5 emissions from the transport sector.

Analysing the Driving Forces and Environmental Effects of Urban Expansion by Mapping the Speed and Acceleration of Built-Up Areas in China between 1978 and 2017

Abundant data sets produced from long-term series of high-resolution remote sensing data have made it possible to explore urban issues across different spatiotemporal scales. Based on a 40-year impervious area data set released by Tsinghua University, a method was developed to map the speed and acceleration of urban built-up areas. With the mapping results of the two indices, we characterised the spatiotemporal dynamics of built-up area expansion and captured different types of expansion. Combined with socioeconomic data, we examined the temporal changes and spatial heterogeneity of driving forces with an ordinary least square (OLS) model and a panel data model, as well as exploring the environmental effects of the expansion. Our results reveal that China has experienced drastic urban expansion over the last four decades. Among all cities, megacities and large cities in eastern China, as well as megacities in central and northeast China have experienced the most dramatic urban expansion. A growing number of cities are categorised as thriving, which means that they have both high expansion speed and acceleration. The overall driving force of urban expansion has significantly increased. More specifically, it was associated with population increase in the early stages; however, since 2000, it has been substantially associated with increases in GDP and fixed asset investments. The major driving factors also differ between regions and urban sizes. Urban expansion is identified as being closely associated with environmental deterioration; thus, speed and acceleration should be included as key indicators in exploring the environmental effects of urban expansion. In summary, the results of the presented case study, based on a data set of China, indicate that speed and acceleration are useful in analysing the driving forces of urban expansion and its environmental effects, and may generate more interest in related research.

COVID-19 and its relationship to particulate matter pollution - Case study from part of greater Chennai, India

It is well known that atmospheric contamination, especially the particulate matter (PM), causes severe human diseases. Yet, presently air pollution levels have dropped primarily attributable across the nation lockdown forced in the wake of the novel Coronavirus outbreak. In this study, we have attempted to establish a conceivable relationship between Covid 19 and PM10–2.5, obtained from eleven airquality monitoring stations in Chennai city, India for both Pre and during Covid situations and its influence over Covid positive cases. The observations of the materials (+ve cases, PM 10, PM 2.5) collected proved that during precovid regime less polluted areas are indicated with less than 5 infection cases reflecting the healthy people and they are less vulnerable to covid except the few occurrence of foreign source indicating no community spread whereus most polluted spots of precovid regimes are indicated with more than 90% cases and indicated that people in pollution zones are succumbed to get infected quickly. However, during Covid the lockdown has considerably reduced the particulate suspension and the results revealed that the +ve cases are of the nature of community spreading through primary and secondary contacts as reported from the media. If Covid is a visible, brutally virulent, incredibly contagious pandemic that kills rapidly and mercilessly, air pollution is its unseen evil twin. Under the radar, but even ruthlessly, if Covid and PM paired together lead to murder without delay. This is a non-communicable disease (NCD) slow-motion pandemic, equivalent-if not exceeding-the catastrophic wrath of SARS-CoV-2.

The effect of temperature on cause-specific mental disorders in three subtropical cities: A case-crossover study in China

BACKGROUND

Little is known about the association between ambient temperature and cause-specific mental disorders, especially in subtropical areas.

OBJECTIVE

To investigate the effect of ambient temperature on mental disorders in subtropical cities.

METHOD

Daily morbidity data for mental disorders in three Chinese cities (Shenzhen, Zhaoqing, and Huizhou) were collected from medical record systems of local psychiatric specialist hospitals, covering patients of all ages. Case-crossover design combined with a distributed lag nonlinear model (DLNM) was used to assess the nonlinear and delayed effects of temperatures on five specific mental disorders (affective disorders, anxiety, depressive disorders, schizophrenia, and organic mental disorders), with analyses stratified by gender and age. The temperature of minimum effect was used as the reference value to calculate estimates.

RESULTS

We observed inversed J-shaped exposure-response curves between temperature and mental morbidity and observed that low temperatures had a significant and prolonged effect on most types of mental disorders in the three cities. For example, the effect of the cold (2.5th percentile) on anxiety was consistently observed in the three cities with an odds ratio (OR) of 1.29 (95% CI: 1.06-1.57) in Zhaoqing, 1.26 (95% CI: 1.18-1.34) in Shenzhen, and 1.45 (95% CI: 1.17-1.81) in Huizhou. Low temperature was also associated with an increased risk of depressive disorders and schizophrenia. For the high temperature exposure (97.5th percentile), we only observed a significant, harmful effect on anxiety [OR = 1.30 (95% CI: 1.08, 1.58) in Shenzhen, OR = 1.16 (95% CI: 1.00, 1.34) in Zhaoqing], affective disorders [OR = 1.32 (95% CI: 1.08, 1.62) in Shenzhen], and schizophrenia [OR = 1.24 (95% CI: 1.03, 1.48) in Zhaoqing, OR = 1.03 (95% CI: 1.00, 1.06) in Huizhou].

CONCLUSIONS

Our study suggests that both low and high temperatures might be important drivers of morbidity from mental disorders, and low temperature may have a more general and wide-spread effect on this cause-specific morbidity than high temperature.

Producing Urban Aerobiological Risk Map for Cupressaceae Family in the SW Iberian Peninsula from LiDAR Technology

Given the rise in the global population and the consequently high levels of pollution, urban green areas, such as those that include plants in the Cupressaceae family, are suitable to reduce the pollution levels, improving the air quality. However, some species with ornamental value are also very allergenic species whose planting should be regulated and their pollen production reduced by suitable pruning. The Aerobiological Index to create Risk maps for Ornamental Trees (AIROT), in its previous version, already included parameters that other indexes did not consider, such as the width of the streets, the height of buildings and the geographical characteristics of cities. It can be considered by working with LiDAR (Light Detection and Ranging) data from five urban areas, which were used to create the DEM and DSM (digital elevation and surface models) needed to create one of the parameters. Pollen production is proposed as a parameter (α) based on characteristics and uses in the forms of hedges or trees that will be incorporated into the index. It will allow the comparison of different species for the evaluation of the pruning effect when aerobiological risks are established. The maps for some species of Cupressaceae (Cupressus arizonica, Cupressus macrocarpa, Cupressus sempervirens, Cupressocyparis leylandii and Platycladus orientalis) generated in a GIS (geographic information system) from the study of several functions of Kriging, have been used in cities to identify aerobiological risks in areas of tourist and gastronomic interest. Thus, allergy patients can make decisions about the places to visit depending on the levels of risk near those areas. The AIROT index provides valuable information for allergy patients, tourists, urban planning councillors and restaurant owners in order to structure the vegetation, as well as planning tourism according to the surrounding environmental risks and reducing the aerobiological risk of certain areas.