The Impact of Urban Transportation Infrastructure on Air Quality

While previous study has confirmed significant correlation between infrastructure construction and air quality, little is known about the nature of the relationship. In this paper, we intend to fill this gap by using the Panel Smooth Transition Regression (PSTR) model to discuss the nonlinear relationship between transportation infrastructure construction and air quality. The panel data includes 280 cities in China for the period 2000-2017. We find that the transportation infrastructure investment is positively correlated to the air quality when the GDP per capita is below RMB 7151 or the number of motor vehicle population per capita is below 37 (vehicles per 10,000 persons) where the model is in the lower regime, and that the transportation infrastructure investment is negatively correlated to the air quality when the GDP per capita is greater than RMB 7151 or the number of motor vehicle population per capita is larger than 37 (vehicles per 10,000 persons) where the model is in the upper regime. The empirical results of the three sub-samples, including eastern, western and central regions, are similar to that of the national level. Furthermore, increasing transportation infrastructure investment is conducive to improving air quality. Urban bus services, green area, population density, wind speed and rainfall are also conducive to reducing air pollution, but the role of environmental regulation is not significant. After adding the instrumental variable (urban built-up area), the conclusions are further supported. Finally, relevant policy recommendations for reducing air pollution are proposed based on the empirical results.

Download Full-text

The impact of green credit on economic growth—The mediating effect of environment on labor supply

PLoS ONE ◽

10.1371/journal.pone.0257612 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0257612

Author(s):

Cai Chen ◽

Yingli Zhang ◽

Yun Bai ◽

Wenrui Li

Keyword(s):

Economic Growth ◽

Air Quality ◽

Labor Supply ◽

Industrial Structure ◽

National Level ◽

Western Region ◽

Environmental Improvement ◽

Per Capita ◽

The Western Region ◽

The Impact

Background The progress of green credit in China is accelerating, but its development is uneven and insufficient in different regions. And whether the issuance of green credit can effectively promote the improvement of the environment and economy is not well understood. Objective Previous research has found that green credit promotes economic growth through improvement of the industrial structure and green technological innovation. However, these studies have not considered the positive externality of environmental improvement even though environmental improvement and economic growth are requirements of the sustainable development concept. Methods We use the chain-mediated model to estimate the impact of green credit issuance on the economic growth of different provinces since the large-scale implementation of green credit in China with data from 2008 to 2016. Results and conclusion This paper shows that the issuance of green credit can improve labor supply rather than labor productivity through the improvement of air quality to achieve regional economic growth. Such a chain-mediated path is different from the economic growth caused by industrial structural adjustment and green technology innovation. At the national level, every 1% increase in green credit issuance relative to industrial loans will increase the per capita gross domestic product (GDP) by approximately 4.6 yuan, or 0.012%, through air quality and labor supply, accounting for 2.875% of the total effect. Heterogeneity analysis indicates that due to regional industrial structure differences and diminishing marginal effects, the impact of green credit is stronger in the western region than in the eastern and central regions. For every 1% increase in the proportion of green credit issuance relative to industrial loans, the per capita GDP growth achieved through the chain-mediated path is approximately 30.17 yuan in the western region, approximately 6.6 times greater than that at the national level. Within a 95% confidence interval of 5000 bootstrap samples, this path is found to be true, and the chain-mediated effect accounts for approximately 12.96% of the total indirect effect. Limitations The limitation of this paper is the measurement of green credit. Although green credit has a large volume, it remains underdeveloped, and there is a lack of perfect indicators. Most existing studies have adopted only alternative or reverse indicators to measure the issuance of green credit. For example, this paper takes the interest expenditure of six high-energy-consuming enterprises as the reverse indicator, which may to a certain extent lead to the overestimation of the issuance of green credit and its impact on the environment and economy. Future research can accurately explore the performance of green credit on the basis of its mature development.

Download Full-text

Effects of economic clusters, FDI and R&D on Innovation: Developing Countries in European Monetary Union Example

International Journal of Innovation ◽

10.5585/iji.v7i2.264 ◽

2019 ◽

Vol 7 (2) ◽

pp. 236-251 ◽

Cited By ~ 4

Author(s):

Durmuş Çağrı Yıldırım ◽

KORHAN ARUN

Keyword(s):

Developing Countries ◽

Developing Country ◽

Monetary Union ◽

European Monetary Union ◽

Gdp Per Capita ◽

European Monetary ◽

Moderation Effect ◽

Empirical Results ◽

Per Capita ◽

The Impact

This study investigates the impact of clusters, FDI, RD, and GDP per capita on innovation. Using a unique panel dataset obtained from eight developing countries with similar innovation levels that are in and out of economic clusters from 2001-2014. The empirical results show that dynamic (uncountable) effects of clusters are not statistically significant on innovation, but static effects (countable) are. Therefore, clusters are effective for developing countries on trade but not innovation directly that developing country should increase trade for innovation spillover by moderation effect of being in economic unions.

Download Full-text

The Adverse Impact of Air Pollution on China’s Economic Growth

Sustainability ◽

10.3390/su13169056 ◽

2021 ◽

Vol 13 (16) ◽

pp. 9056

Author(s):

Daxin Dong ◽

Boyang Xu ◽

Ning Shen ◽

Qian He

Keyword(s):

Economic Growth ◽

Air Pollution ◽

Growth Rate ◽

Instrumental Variables ◽

Gdp Per Capita ◽

Annual Growth Rate ◽

Instrumental Variables Estimation ◽

Study Results ◽

Per Capita ◽

The Impact

This study empirically evaluates the impact of air pollution on China’s economic growth, based on a province-level sample for the period 2002–2017. Air pollution is measured by the concentration of fine particulate matter (PM2.5), and economic growth is measured by the annual growth rate of gross domestic product (GDP) per capita. A panel data fixed-effects regression model is built, and the instrumental variables estimation method is utilized for quantitative analyses. The study reports a significant negative impact of air pollution on the macroeconomic growth of China. According to our instrumental variables estimation, holding other factors constant, if the concentration of PM2.5 increases by 1%, then the GDP per capita growth rate will decline by 0.05818 percentage points. In addition, it is found that the adverse effect of atmospheric pollution is heterogeneous across different regions. The effect is stronger in the eastern region and in provinces with smaller state-owned enterprise shares, fewer governmental expenditures for public health services, and fewer medical resources. The study results reveal that air pollution poses a substantial threat to the sustainable economic growth of China. Taking actions to abate air pollution will generate great economic benefits, especially for those regions which are heavily damaged by pollution.

Download Full-text

The Effect of Urbanization and Economic Performance on Metropolitan Water Consumption: Theoretic Model and Evidence from Guangzhou of China

Applied Economics and Finance ◽

10.11114/aef.v4i2.2076 ◽

2017 ◽

Vol 4 (2) ◽

pp. 163

Author(s):

Shaohui Gao ◽

Yiming He

Keyword(s):

Water Consumption ◽

Economic Performance ◽

Gdp Per Capita ◽

Theoretic Model ◽

Annual Data ◽

Empirical Results ◽

Per Capita ◽

Impact Of Urbanization ◽

The Impact

This paper examines the effect of urbanization and economic performance on metropolitan water consumption in Guangzhou of China. We develop social and individual optimal models to reveal the impact of urbanization and economic performance on metropolitan water consumption. Based on aggregated annual data from 1949 to 2014, the empirical results from OLS and ARDL suggest that previous water consumption per capita, urbanization and GDP per capita each play vital roles impacting metropolitan water consumption per capita in Guangzhou.

Download Full-text

Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China

Atmosphere ◽

10.3390/atmos12060788 ◽

2021 ◽

Vol 12 (6) ◽

pp. 788

Author(s):

Rong Feng ◽

Hongmei Xu ◽

Zexuan Wang ◽

Yunxuan Gu ◽

Zhe Liu ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Rural Areas ◽

Vehicle Emissions ◽

Motor Vehicle ◽

Northwest China ◽

Air Pollutant ◽

Capital City ◽

Air Pollution Control ◽

Motor Vehicle Emissions

In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.

Download Full-text

The Impact of Oil Price Shocks on National Income: Evidence from Azerbaijan

Energies ◽

10.3390/en14061695 ◽

2021 ◽

Vol 14 (6) ◽

pp. 1695

Author(s):

Shahriyar Mukhtarov ◽

Sugra Humbatova ◽

Mubariz Mammadli ◽

Natig Gadim‒Oglu Hajiyev

Keyword(s):

Exchange Rate ◽

Oil Price ◽

Gdp Per Capita ◽

Oil Price Shocks ◽

Price Shocks ◽

Total Trade ◽

Trade Turnover ◽

Per Capita ◽

The Exchange Rate ◽

The Impact

This study investigates the influence of oil price shocks on GDP per capita, exchange rate, and total trade turnover in Azerbaijan using the Structural Vector Autoregressive (SVAR) method to data collected from 1992 to 2019. The estimation results of the SVAR method conclude that oil price shocks (rise in oil prices) affect GDP per capita and total trade turnover positively, whereas its influence on the exchange rate is negative in the case of Azerbaijan. According to results of this study, Azerbaijan and similar oil-exporting countries should reduce the dependence of GDP per capita, the exchange rate, and total trade turnover from oil resources and its prices in the global market. Therefore, these countries should attempt to the diversification of GDP per capita, the exchange rate, and other sources of total trade turnover.

Download Full-text

Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-021-02071-4 ◽

2021 ◽

Author(s):

Christian Acal ◽

Ana M. Aguilera ◽

Annalina Sarra ◽

Adelia Evangelista ◽

Tonio Di Battista ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Functional Data ◽

Central Italy ◽

Principal Component ◽

Functional Principal Component Analysis ◽

Area Of Interest ◽

Pm 10 ◽

The Impact ◽

Monitoring Stations

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

Download Full-text

The interplay between environmental exposures and COVID-19 risks in the health of children

Environmental Health ◽

10.1186/s12940-021-00716-z ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Peter D. Sly ◽

Brittany A. Trottier ◽

Catherine M. Bulka ◽

Stephania A. Cormier ◽

Julius Fobil ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Disease Severity ◽

Research Effort ◽

Severe Disease ◽

Environmental Exposures ◽

Research Strategy ◽

Lessons Learned ◽

Research Questions ◽

The Impact

Abstract Background An unusual feature of SARS-Cov-2 infection and the COVID-19 pandemic is that children are less severely affected than adults. This is especially paradoxical given the epidemiological links between poor air quality and increased COVID-19 severity in adults and that children are generally more vulnerable than adults to the adverse consequences of air pollution. Objectives To identify gaps in knowledge about the factors that protect children from severe SARS-Cov-2 infection even in the face of air pollution, and to develop a transdisciplinary research strategy to address these gaps. Methods An international group of researchers interested in children’s environmental health was invited to identify knowledge gaps and to develop research questions to close these gaps. Discussion Key research questions identified include: what are the effects of SAR-Cov-2 infection during pregnancy on the developing fetus and child; what is the impact of age at infection and genetic susceptibility on disease severity; why do some children with COVID-19 infection develop toxic shock and Kawasaki-like symptoms; what are the impacts of toxic environmental exposures including poor air quality, chemical and metal exposures on innate immunity, especially in the respiratory epithelium; what is the possible role of a “dirty” environment in conveying protection – an example of the “hygiene hypothesis”; and what are the long term health effects of SARS-Cov-2 infection in early life. Conclusion A concerted research effort by a multidisciplinary team of scientists is needed to understand the links between environmental exposures, especially air pollution and COVID-19. We call for specific research funding to encourage basic and clinical research to understand if/why exposure to environmental factors is associated with more severe disease, why children appear to be protected, and how innate immune responses may be involved. Lessons learned about SARS-Cov-2 infection in our children will help us to understand and reduce disease severity in adults, the opposite of the usual scenario.

Download Full-text

Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

Complex & Intelligent Systems ◽

10.1007/s40747-021-00435-5 ◽

2021 ◽

Author(s):

Shwet Ketu ◽

Pramod Kumar Mishra

Keyword(s):

Air Pollution ◽

Air Quality ◽

Class Imbalance ◽

Imbalanced Data ◽

Classification Algorithm ◽

Quality Data ◽

Pollution Level ◽

Classification Problems ◽

Chi Square ◽

The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

Download Full-text

Non-Price Criteria for the Evaluation of the Tender Offers in Public Procurement of Ukraine

International Journal of Financial Studies ◽

10.3390/ijfs8030044 ◽

2020 ◽

Vol 8 (3) ◽

pp. 44

Author(s):

Alexander Baranovsky ◽

Nataliia Tkachenko ◽

Vladimer Glonti ◽

Valentyna Levchenko ◽

Kateryna Bogatyrova ◽

...

Keyword(s):

Public Procurement ◽

Well Being ◽

Gdp Per Capita ◽

Tender Offers ◽

Product Categories ◽

Per Capita ◽

The Government ◽

The Impact ◽

Over Time ◽

The Eu

Traditionally, public procurement has been associated with the measurement of achieving savings. However, recent research shows that the economic impact of public procurement is not limited only to savings, but by measuring the impact of four capitals—natural, human, social, and economic—on sustainable well-being over time. Ukraine is a country with a very low gross domestic product (GDP) per capita, which exacerbates the problem of the impact of public procurement results on the population’s welfare. Ukrainian public procurement legislation allows customers to apply non-price criteria (the share of non-price criteria cannot be more than 70%), which, together, are taken into account in the formula of the quoted price. The studies show that the effect of the use of non-price criteria depends on the relevance of the method of the evaluation of non-price criteria. The most important non-price criteria for Ukrainian customers by product categories and the methods of their evaluation are analyzed according to the Bi.prozorro.org analytics module. Therefore, it is concluded that the quoted price method, which is used in Ukrainian practice, is not relevant in comparison with the method used in the EU. A survey of the government buyers on the practice of applying non-price criteria was conducted, and the areas of their use were identified.

Download Full-text