Study of the Effects of Air Pollutants on Human Health Based on Baidu Indices of Disease Symptoms and Air Quality Monitoring Data in Beijing, China

Comprehensive analysis of air pollution and the influence of meteorological factors: a case study of adiyaman province

Adıyaman, a city recently affected by an earthquake, is facing significant air pollution challenges due to both anthropogenic activities and natural events. The sources of air pollution have been investigated using meteorological variables. Elevated southerly winds, especially prominent in spring and autumn, significantly contribute to dust transport, leading to a decline in local air quality as detected by the HYSPLIT model. Furthermore, using Suomi-NPP Thermal Anomaly satellite product, it is detected and analyzed for crop burning activities. Agricultural practices, including stubble burning, contribute to the exacerbation of PM10 pollution during the summer months, particularly when coupled with winds from all directions except the north. In fall and winter months, heating is identified as the primary cause of pollution. The city center located north of the station is the dominant source of pollution throughout all seasons. The study established the connection between air pollutants and meteorological variables. Furthermore, the Spearman correlation coefficients reveal associations between PM10 and SO2, indicating moderate positive correlations under pressure conditions (r = 0.35, 0.52). Conversely, a negative correlation is observed with windspeed (r = -0.35, -0.50), and temperature also exhibits a negative correlation (r = -0.39, -0.54). During atmospheric conditions with high pressure, PM10 and SO2 concentrations are respectively 41.2% and 117.2% higher. Furthermore, pollutant concentration levels are 29.2% and 53.3% higher on days with low winds. Last, practical strategies for mitigating air pollution have been thoroughly discussed and proposed. It is imperative that decision-makers engaged in city planning and renovation give careful consideration to the profound impact of air pollution on both public health and the environment, particularly in the aftermath of a recent major earthquake.

Unveiling the health consequences of air pollution in the world's most polluted nations

Air pollution poses a persuasive threat to global health, demonstrating widespread detrimental effects on populations worldwide. Exposure to pollutants, notably particulate matter with a diameter of 2.5 µm (PM2.5), has been unequivocally linked to a spectrum of adverse health outcomes. A nuanced understanding of the relationship between them is crucial for implementing effective policies. This study employs a comprehensive investigation, utilizing the extended health production function framework alongside the system generalized method of moments (SGMM) technique, to scrutinize the interplay between air pollution and health outcomes. Focusing on a panel of the top twenty polluted nations from 2000 to 2021, the findings yield substantial insights. Notably, PM2.5 concentration emerges as a significant factor, correlating with a reduction in life expectancy by 3.69 years and an increase in infant mortality rates by 0.294%. Urbanization is found to increase life expectancy by 0.083 years while concurrently decreasing infant mortality rates by 0.00022%. An increase in real per capita gross domestic product corresponds with an improvement in life expectancy by 0.21 years and a decrease in infant mortality rates by 0.00065%. Similarly, an elevated school enrollment rate is associated with a rise in life expectancy by 0.17 years and a decline in infant mortality rates by 0.00032%. However, a higher population growth rate is found to modestly decrease life expectancy by 0.019 years and slightly elevate infant mortality rates by 0.000016%. The analysis reveals that per capita greenhouse gas emissions exert a negative impact, diminishing life expectancy by 0.486 years and elevating infant mortality rates by 0.00061%, while per capita energy consumption marginally reduces life expectancy by 0.026 years and increases infant mortality rates by 0.00004%. Additionally, economic volatility shock presents a notable decrement in life expectancy by 0.041 years and an increase in infant mortality rates by 0.000045%, with inflationary shock further exacerbating adverse health outcomes by lowering life expectancy by 0.70 years and elevating infant mortality rates by 0.00025%. Moreover, the study scrutinizes the role of institutional quality, revealing a constructive impact on health outcomes. Specifically, the institutional quality index is associated with an increase in life expectancy by 0.66% and a decrease in infant mortality rates by 0.0006%. Extending the analysis to examine the nuanced dimensions of institutional quality, the findings discern that economic institutions wield a notably stronger positive influence on health outcomes compared to political and institutional governance indices. Finally, the results underscore the pivotal moderating role of institutional quality in mitigating the deleterious impact of PM2.5 concentration on health outcomes, counterbalancing the influence of external shocks, and improving the relationships between explanatory variables and health outcome indicators. These findings offer critical insights for guiding evidence-based policy implications, with a focus on fostering resilient, sustainable, and health-conscious societies.

A quantitative assessment of natural and anthropogenic effects on the occurrence of high air pollution loading in Dhaka and neighboring cities and health consequences

Although existing studies mainly focused on the air quality status in Bangladesh, quantifying the natural and manmade effects, the frequency of high pollution levels, and the associated health risks remained beyond detailed investigation. Air quality and meteorological data from the Department of Environment for 2012-2019 were analyzed, attempting to answer those questions. Cluster analysis of PM2.5, PM10, and gaseous pollutants implied that Dhaka and neighboring cities, Narayangonj and Gazipur, are from similar sources compared to the other major cities in the country. Apart from the transboundary sources, land use types and climate parameters unevenly affected local pollution loadings across city domains. The particulate concentrations persistently remained above the national standard for almost half the year, with the peaks during the dry months. Even though nitrogen oxides remained high in all three cities, other gaseous pollutants, such as CO and O3, except SO2, showed elevated concentrations solely in Dhaka city. Concentrations of gaseous pollutants in Dhaka vary spatially, but no statistical differences could be discerned between the working days and holidays. Frequency analysis results and hazard quotients revealed the likelihood of adverse health outcomes in Narayangonj ensuing from particulate exposures surpasses the other cities for different age, gender, and occupation groups. Nonetheless, school-aged children and construction workers were most at risk from chronic exposure to gaseous pollutants mostly in Dhaka. One limitation of this study was that the routine air quality monitoring happens just from five sites, making the evidence-based study concerning health outcomes quite challenging.

Short-term effects of air pollution and noise on emergency hospital admissions in Madrid and economic assessment

INTRODUCTION

The aim of this study was to study the effect of air pollution and noise has on the population in Madrid Community (MAR) in the period 2013-2018, and its economic impact.

METHODS

Time series study analysing emergency hospital admissions in the MAR due to all causes (ICD-10: A00-R99), respiratory causes (ICD-10: J00-J99) and circulatory causes (ICD-10: I00-I99) across the period 2013-2018. The main independent variables were mean daily PM_2.5, PM₁₀, NO₂, 8-h ozone concentrations, and noise. We controlled for meteorological variables, Public Holidays, seasonality, and the trend and autoregressive nature of the series, and fitted generalised linear models with a Poisson regression link to ascertain the relative risks and attributable risks. In addition, we made an economic assessment of these hospitalisations.

RESULTS

The following associations were found: NO₂ with admissions due to natural (RR: 1.007, 95% CI: 1.004-1.011) and respiratory causes (RR: 1.012, 95% CI: 1.005-1.019); 8-h ozone with admissions due to natural (RR: 1.049, 95% CI: 1.014-1.046) and circulatory causes (RR: 1.088, 95% CI: 1.039-1.140); and diurnal noise (L_Aeq7-23h) with admissions due to natural (RR: 1.001, 95% CI: 1.001-1.002), respiratory (RR: 1.002, 95% CI: 1.001-1.003) and circulatory causes (RR: 1.003, 95% CI: 1.002-1.005). Every year, a total of 8246 (95% CI: 4580-11,905) natural-cause admissions are attributable to NO₂, with an estimated cost of close on €120 million and 5685 (95% CI: 2533-8835) attributed to L_Aeq7-23h with an estimated cost of close on €82 million.

CONCLUSIONS

Nitrogen dioxide, ozone and noise are the main pollutants to which a large number of hospitalisations in the MAR are attributed, and are thus responsible for a marked deterioration in population health and high related economic impact.

Using social media data to assess the impact of COVID-19 on mental health in China

BACKGROUND

The outbreak and rapid spread of coronavirus disease 2019 (COVID-19) not only caused an adverse impact on physical health, but also brought about mental health problems among the public.

METHODS

To assess the causal impact of COVID-19 on psychological changes in China, we constructed a city-level panel data set based on the expressed sentiment in the contents of 13 million geotagged tweets on Sina Weibo, the Chinese largest microblog platform.

RESULTS

Applying a difference-in-differences approach, we found a significant deterioration in mental health status after the occurrence of COVID-19. We also observed that this psychological effect faded out over time during our study period and was more pronounced among women, teenagers and older adults. The mental health impact was more likely to be observed in cities with low levels of initial mental health status, economic development, medical resources and social security.

CONCLUSIONS

Our findings may assist in the understanding of mental health impact of COVID-19 and yield useful insights into how to make effective psychological interventions in this kind of sudden public health event.

Effects of meteorological parameters and fuel composition on the air pollution production from motor vehicles

The aim of this study was to investigate the effect of changes in meteorological parameters and fuel composition on the emission rate of air pollutants in the vehicle fleet of the Tehran Metropolis. The results of this study can be used in management decisions to reduce the emission of air pollutants. In this paper, based on the international vehicle emission model and using mathematical equations, the effects of changing meteorological parameters and fuel composition on the emission of pollutants were modeled. The emission rates of CO, VOCs, and NOx pollutants were the most sensitive to the changes in meteorological parameters, respectively. Among all parameters studied in this research, the changes in sulfur level had the greatest effect on the emission of pollutants from the vehicle fleet of Tehran Metropolis. If the fuel was replaced with Euro 5 standard instead of Euro 3, the emission rates of CO, VOCs, NOx, PM, and SOx pollutants from the vehicle fleet of Tehran Metropolis would be reduced by 9%, 6%, 5%, 14%, and 90%, respectively. Managing and reducing the sources of production and emission of air pollution is one of the best ways to reduce the air pollution. In general, since the emission of pollutants from the fleet of Tehran Metropolis in the cold seasons of the year is greater than during hot seasons and the problem of air pollution is exacerbated by air stability, using Euro 5 fuel in cold seasons is one of the efficient ways to reduce the air pollution.

Determinants of Customer Intentions to Use Electric Vehicle in Indonesia: An Integrated Model Analysis

Electric vehicles can be a solution to certain social problems in Indonesia, such as pollution and an increase in consumption of energy from fossil fuels, which cannot be met by domestic production. The discussion of the TPB theoretical model, UTAUT2, and risk perception, using the structural equation modeling (SEM) method, in this study aims to provide an overview of the factors that drive interest in adopting electric vehicles in Indonesia. Data were collected from 526 respondents in various cities located in Indonesia. The results showed that the model can estimate the study variables adequately. The constructs of TPB such as attitude toward use (ATU), subjective norm (SBN), and perceived behavior control (PBC) positively affect interest in using electric vehicles. Meanwhile, ATU is influenced by performance and effort expectancies, hedonic motivation, price value, as well as functional, financial, and social risks. Another factor, known as PBC, is influenced by certain facilitating conditions. The ATU factor is the most influential on the use of electric vehicles, therefore factors such as performance expectancy, effort expectancy, hedonic motivation, price value, functional risk, financial risk, and social risk need to be properly analyzed.

Features Importance Analysis of Diesel Vehicles' NOx and CO2 Emission Predictions in Real Road Driving Based on Gradient Boosting Regression Model

In order to have an accurate and fast prediction of the artificial intelligence (AI) model, the choice of input features is at least as important as the choice of model. The effect of input features selection on the emission models of light diesel vehicles driven on real roads was investigated in this paper. The gradient boosting regression (GBR) model was used to train and to predict the emissions of nitrogen oxide (NO_x), carbon dioxide (CO₂), and the fuel consumption of real driving diesel vehicles in urban scenarios, the suburbs, and on highways. A portable emissions measurement system (PEMS) system was used to collect data of vehicles as well as environmental conditions. The vehicle was run on two routes. The model was trained with the first route data and was used to predict the emissions of the second route. There were ten features related to the NO_x model and nine features associated with the CO₂ model. The importance of each feature was sorted, and a different number of features were used as input to train the models. The best NO_x model had the coefficient of determination (R²) values of 0.99, 0.99, and 0.99 in each driving pattern (urban, suburbs, and highways). Predictions of the second route had the R² values of 0.88, 0.89, and 0.96 respectively. The best CO₂ model had the R² values of 0.98, 0.99, and 0.99 in each driving pattern, respectively. Predictions of the second route had the R² values are 0.79, 0.82, and 0.83, respectively. The most important features for the NO_x model are mass air flow rate (g/s), exhaust flow rate (m³/min), and CO₂ (ppm), while the important features for the CO₂ model are exhaust flow rate (m³/min) and mass air flow rate (g/s). It is noted that the regression models based on the top three features may give predictions very close to the measured data.

Remote Tracking Gas Molecular via the Standalone-Like Nanosensor-Based Tele-Monitoring System

Highlights

A standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way is created; Metal–organic framework-derived hollow polyhedral ZnO was successfully synthesized, allowing the created smart device to be highly selective and to sensitively track the variation of NO2 concentration; A novel photoluminescence-enhanced Li-Fi telecommunication technique is proposed, offering the created smart device with the capability of long distance wireless communication.

Abstract

Remote tracking the variation of air quality in an effective way will be highly helpful to decrease the health risk of human short- and long-term exposures to air pollution. However, high power consumption and poor sensing performance remain the concerned issues, thereby limiting the scale-up in deploying air quality tracking networks. Herein, we report a standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way. Brevity, the created smart device demonstrated satisfactory selectivity (against six kinds of representative exhaust gases or air pollutants), desirable response magnitude (164–100 ppm), and acceptable response/recovery rate (52.0/50.5 s), as well as linear response relationship to NO2. After aging for 2 weeks, the created device exhibited relatively stable sensing performance more than 3 months. Moreover, a photoluminescence-enhanced light fidelity (Li-Fi) telecommunication technique is proposed and the Li-Fi communication distance is significantly extended. Conclusively, our reported standalone-like smart device would sever as a powerful sensing platform to construct high-performance and low-power consumption air quality wireless sensor networks and to prevent air pollutant-induced diseases via a more effective and low-cost approach.

Electronic supplementary material

The online version of this article (10.1007/s40820-020-00551-w) contains supplementary material, which is available to authorized users.

Changes in Air Quality during the COVID-19 Pandemic and Associated Health Benefits in Korea

The COVID-19 pandemic was caused by a highly contagious coronavirus that has triggered worldwide control actions such as social distancing and lockdowns. COVID-19 control actions have resulted in improved air quality locally and around the world in the short-term by limiting human activity. We analyzed the impacts of social distancing and transboundary pollutants on air quality changes using open data and examined the corresponding health benefits focusing on two domestic cities (Seoul and Daegu) in Korea where the spread of coronavirus was severe. During the COVID-19 pandemic, PM2.5, PM10, and NO2 concentrations decreased significantly by 31%, 61%, and 33%, respectively, compared to the previous three years. In particular, the PM2.5/PM10 ratio fell 24.5% after the implementation of social distancing, suggesting a decrease in anthropogenic emissions. Moreover, we found that the air quality index (AQI) also improved significantly, with a focus on reducing exposure to sensitive groups. In Seoul and Daegu, improved air quality prevented 250 and 78 premature deaths, and health costs were USD 884 million and USD 278 million, respectively. On the other hand, health loss due to COVID-19 deaths was in sharp contrast to USD 7.1 million and USD 543.6 million. Our findings indicate a significant association between COVID-19 prevalence patterns and health outcomes.

Major air pollutants seasonal variation analysis and long-range transport of PM10 in an urban environment with specific climate condition in Transylvania (Romania)

The air quality decrease, especially in urban areas, is related to local-scale conditions and to dispersion of air pollutants (regional and long-range) as well. The main objective of this study was to decipher the seasonal variation of PM10, NO, NO2, NOx, SO2, O3, and CO over a 1-year period (2017) and the possible relationships between air pollution and meteorological variables. Furthermore, trajectory cluster analysis and concentration-weighted trajectory (CWT) methods were used to assess the trajectories and the source-receptor relationship of PM10 in the Ciuc basin Transylvania, known as the "Cold Pole" of Romania. The pollutants show lower concentrations during warmer periods, especially during summer, and significantly higher concentrations were observed on heating season in winter due to seasonal variations in energy use (biomass burning) and atmospheric stability. Subsequently, in February, the highest concentration of PM10 was 132 μg/m3, which is 4 times higher than the highest recorded monthly mean. Our results indicate a negative correlation between CO/temperature (- 0.89), NOx/temperature (- 0.84) and positive between NOx/PM10 (0.95), CO/PM10 (0.9), and NOx/CO (0.98), respectively. Dominant transport pathways were identified and the results revealed that slow-moving southerly (~ 45%) and northwesterly (~ 32%) air masses represent almost 80% and mainly regional flows were discerned. During 2017, increased PM10 levels were measured at the study site when air masses arrived mostly from northwest and southeast. The CWT and polarplot models show a strong seasonal variation and significant differences were observed between weekdays and weekends, namely highest PM10 concentrations during weekends at low wind speed (2-4 m/s).

The mediating effect of air quality on the association between human mobility and COVID-19 infection in China

BACKGROUND

Previous studies have found that human mobility restrictions could not only prevent the spread of COVID-19, but also improve the air quality because of the reduction of industrial production, transportation and traffic. It is noteworthy that air quality is also closely related to the risk of COVID-19 infection. Therefore, we aimed to assess the mediating role of air quality on the association between human mobility and the infection caused by this novel coronavirus.

METHODS

We collected daily confirmed cases, human mobility data, air quality data and meteorological variables in 120 cities from China between January 23, 2020 and February 29, 2020. We applied the generalized additive model to examine the association of human mobility index with COVID-19 confirmed cases, and to assess the mediating effects of air quality index and each pollutant.

RESULTS

We observed a significant positive relationship between human mobility index and the daily counts of COVID-19 confirmed cases. A unit increase in human mobility index (lag0-14) was associated with a 6.45% increase in daily COVID-19 confirmed cases, and air quality index significantly mediated 19.47% of this association. We also observed a positive relationship between human mobility index and air quality index. In the pollutant level analyses, we found significant mediating effects of PM2.5, PM10, and NO2.

CONCLUSIONS

Our study suggests that limiting human movements could reduce COVID-19 cases by improving air quality besides decreasing social contact.

Temporal Trend of PM10 and Associated Human Health Risk over the Past Decade in Cluj-Napoca City, Romania

The human health risk associated with PM10 exposure was assessed for the residents of Cluj-Napoca city, Romania, for a best case-scenario based on the monthly average PM10 and for a worst-case scenario based on the monthly 90th percentile of PM10 concentration. As no toxicity value for PM10 was available, for the calculation of the hazard quotient, the toxicity value was considered to be equal to the annual limit value (40 µm/m3) set in the European Union (EU), and to air quality guidelines (20 µm/m3) set by the World Health Organization (WHO). The daily PM10 concentrations for the period 2009–2019, at the four monitoring stations existing in Cluj-Napoca, were obtained from the National Air Quality Monitoring Network. The annual PM10 values ranged between 20.3 and 29.5 µg/m3, and were below the annual limit value (40 µg/m3) set by European and national legislation, but above the annual air quality guideline (20 µg/m3) set by WHO. Generally, the monthly PM10 concentrations were higher from October to March than in the rest of the year. The monthly air quality index (AQI) showed the good to moderate quality of the air during the whole decade; however, there were days when the air quality was unhealthy for sensitive population groups. The air quality was more or less constant during the warm months, and improved significantly for the cold months from 2009 to 2019. In the best-case scenario, calculated using the EU annual limit value for PM10, the potential non-carcinogenic chronic health risk was present only in 2009 and 2010, but in the worst-case scenario, in each year there were periods, especially in the cold months, in which health risk was present. When considering the WHO air quality guidelines in the calculation of the health risk, the potential non-carcinogenic chronic health risk was present between October and March in each year in the best-case scenario, and in most of the months in the worst-case scenario.

Air emissions and health risk assessment around abattoir facility

The study assessed the impacts of abattoir activities on ambient air quality and health risk associated with exposure to PM2.5 and PM10, H2S, SO2 and NH3. Air samplings were done simultaneously around the abattoir at three points for sixty consecutive days (October to November) and standard methods adopted for the samplings and analysis. Health risks associated with exposure to PM10 and PM2.5 were estimated, using attributable fractions, relative risk and the excess lifetime cancer risk. The non-carcinogenic risks induced by the inhalation of H2S, SO2 and NH3 were also evaluated using hazard quotient (HQ). The results indicated that the average concentrations of 18.75 μg/m3, 89.17 μg/m3 and 0.1ppm for PM2.5, PM10 and NO2 respectively, were higher than the World Health Organization (WHO), National Ambient Air Quality Standard (NAAQS) and Federal Ministry of Environment (FMEnv) permissible limits. Air Quality Index showed that the ambient air quality in respect of CO and NH3 was very good, moderate for PM10 and was very poor for NO2 and SO2. It was also shown that 0.32% of deaths from lung cancer, and 0.23% from cardiopulmonary could be avoided if PM2.5 is reduced to 3 μg/m3 and while about 0.14% of all-cause mortality could be avoided if PM10 is reduced to 10 μg/m3. In similar manner, at least 0.45% likelihood that an individual in a group of people exposed to PM2.5 100m away from the burning point may have health issue (lung cancer) than an individual from another set of people that is exposed to baseline concentration of 3 μg/m3. All the HQ values exceeded the threshold value, set at the unity, implying that H2S, SO2 and NH3 are likely to cause adverse health effects in the area. Conclusively, continuous operation of this abattoir within the residential area can constitute a great environmental menace to the residents of the area and can result in complication to those with existing health challenge.

Air-Pollution Control in an Emergent Market: Does It Work? Evidence from Romania

Economic development in a national and international context must be based on a sustainability strategy established on the systemic interaction between the economic, sociocultural, and ecological environments. Today, the world is confronted by many challenges related to climate change and natural-resource flows, including waste streams resulting from economic activity. The need for national and European environmental standards and the work of an environment monitoring authority to reduce air pollution are highlighted by economic and industrial activities. Thus, our research focused on determining if emissions of sulfur dioxide (SO₂), nitrogen (NO₂), and particulate matter 10 (PM₁₀) are influenced by planned and unplanned inspections made by competent authorities from Romania. We built a regression model that estimates the influence of economic measures imposed by the authorities on reducing industrial air pollution. Preliminary results showed that the number of inspections negatively influences air pollution, indicating that national and local authorities in Romania are striving to maintain air quality and are conducting more inspections when air pollution is high.

Meteorological Variables and Synoptic Patterns Associated with Air Pollutions in Eastern China during 2013-2018

Steady meteorological conditions are important external factors affecting air pollution. In order to analyze how adverse meteorological variables affect air pollution, surface synoptic situation patterns and meteorological conditions during heavy pollution episodes are discussed. The results showed that there were 78 RPHPDs (regional PM_2.5 pollution days) in Jiangsu, with a decreasing trend year by year. Winter had the most stable meteorological conditions, thus most RPHPDs appeared in winter, followed by autumn and summer, with the least days in spring. RPHPDs were classified into three patterns, respectively, as equalized pressure (EQP), advancing edge of a cold front (ACF) and inverted trough of low pressure (INT) according to the SLP (sea level pressure). RPHPDs under EQP were the most (51%), followed by ACF (37%); INT was the minimum (12%). Using statistical methods and meteorological condition data on RPHPDs from 2013 to 2017 to deduce the thresholds and 2018 as an independent dataset to validate the proposed thresholds, the threshold values of meteorological elements are summarized as follows. The probability of RPHPDs without rain was above 92% with the daily and hourly precipitation of all RPHPDs below 2.1 mm and 0.8 mm. Wind speed, RHs, inversion intensity(ITI), height difference in the temperature inversion(ITK), the lower height of temperature inversion (LHTI) and mixed-layer height (MLH) in terms of 25%–75% high probability range were respectively within 0.5–3.6 m s⁻¹, 55%–92%, 0.7–4.0 °C 100 m ⁻¹, 42–576 m, 3–570 m, 200–1200 m. Two conditions should be considered: whether the pattern was EQP, ACF or INT and whether the eight meteorological elements are within the thresholds. If both criteria are met, PM_2.5 particles tend to accumulate and air pollution diffusion conditions are poor. Unfavorable meteorological conditions are the necessary, but not sufficient condition for RPHPDs.

Urban Form, Air Quality, and Cardiorespiratory Mortality: A Path Analysis

With the unprecedented urbanization during the past three decades, air quality in many Chinese cities has been a serious issue which poses great challenges for urban sustainability. This study examines the health consequences of development patterns in China by establishing the linkage between urban form, air pollution level, and cardiorespiratory mortality rate. We assembled a dataset by compiling a series of variables from multiple sources, including China's Disease Surveillance Points (DSP) system, which forms a nationally representative sample of mortality for the year 2005, Chinese census, satellite imagery, and the Chinese National Land Use Database. After controlling for local climate, demography, socioeconomics, and other pollution factors, this study finds that urban form elements (e.g., urban density, fragmentation level, forest/green space ratio) have significant influences on PM_2.5 (atmospheric particulate matter with a diameter of less than 2.5 micrometers) concentration, thus influencing the incidence of cardiorespiratory mortality at the county level. These results may help explain how the type and pattern of development shape public health by influencing air quality and form an evidence-based land use policy to improve environmental quality and public health.

The Relationship Between the Actual Level of Air Pollution and Residents' Concern about Air Pollution: Evidence from Shanghai, China

This study explored the relationship between the actual level of air pollution and residents’ concern about air pollution. The actual air pollution level was measured by the air quality index (AQI) reported by environmental monitoring stations, while residents’ concern about air pollution was reflected by the Baidu index using the Internet search engine keywords “Shanghai air quality”. On the basis of the daily data of 2068 days for the city of Shanghai in China over the period between 2 December 2013 and 31 July 2019, a vector autoregression (VAR) model was built for empirical analysis. Estimation results provided three interesting findings. (1) Local residents perceived the deprivation of air quality and expressed their concern on air pollution quickly, within the day on which the air quality index rose. (2) A decline in air quality in another major city, such as Beijing, also raised the concern of Shanghai residents about local air quality. (3) A rise in Shanghai residents’ concern had a beneficial impact on air quality improvement. This study implied that people really cared much about local air quality, and it was beneficial to inform more residents about the situation of local air quality and the risks associated with air pollution.