Study on Air Pollution and Control Investment from the Perspective of the Environmental Theory Model: A Case Study in China, 2005–2014

The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China

Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 μg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.

Abundance, spatial distribution, and chemical characterization of face masks on the beaches of SE Kanyakumari, India

Personal Protective Equipment (PPE) is a new world of waste during the COVID-19 pandemic. In this baseline study, the occurrence of PPE faces masks were assessed on the eleven beaches of Kanyakumari, India concerning the abundance, spatial distribution, and chemical characterization (ATR-FTIR spectroscopy). A total of 1593 items/m² of PPE face masks and their mean density of 0.16 PPE/m², ranging from 0.02 to 0.54 PPE/m² were determined in the study area. Kanyakumari beach (n = 430 items/m²) has the highest concentration of masks (26.99 %), with a mean density of 0.54 m² due to recreational, sewage disposal, and tourism activities. This is perhaps the most important study describing the scientific data that focuses on the significant effects of communal activities and accessibility on COVID-19 PPE face mask pollution. It also highlights the need for sufficient management facilities to optimize PPE disposal.

Spatial green growth in China: exploring the positive role of investment in the treatment of industrial pollution

The industrial sector of China is critical to the country's economic growth. On the other side, industrialisation has resulted in a high rate of emissions, pushing China to spend extensively on industrial pollution remediation. As a result, this study looks at the relationship between investment completed in the treatment of industrial pollution and economic development. Initially, the study used the global Moran's I test (Queen's contiguity matrix) to find spatial autocorrelation for the 'investment completed in the treatment of industrial pollution' factor, where the study found a positive association across Chinese provinces, and suggest the existence of spatial autocorrelation. Thereafter, a time-fixed effect spatial error model was used due to the lowest Akaike information criterion and Bayesian information criterion to analyse regional data of China from 1999 to 2018. The data reveal a positive association between investment completed in the treatment of industrial pollution and regional economic growth, both in the short and long term. Furthermore, the negative consequences of urban wages and foreign investment on investment completed in the treatment of industrial pollution are having the reverse effect on regional green development, necessitating ecologically friendly actions to mitigate the negative environmental effects of both. The results highlight the need for policymakers in other countries to review their plans for economic expansion and create environmentally friendly legislation. By implementing the Chinese green economic growth model, policymakers in industrially polluting nations can reduce industrial pollution and foster green growth in their nation.

Residents’ Willingness for Centralized Biogas Production in Hebei and Shandong Provinces

Nowadays, in the North China Plain (NCP), most counties and suburban rural regions are promoting the "coal to gas" program under the situation of strong government support of large and medium-sized centralized biogas production (CBP) projects. This paper is aimed at the CBP projects, focuses on rural residents’ “willingness to use (WTU)”, “willingness to buy (WTB)” and the influencing factors for WTU/WTB. Through the analysis of rural residents from Hebei and Shandong provinces that belong to NCP in this survey, we find that 85% of respondents support the CBP program and the WTB is 63.15 CNY/year per capita, which is much lower than the cost of rural CBP in existing survey regions. The participation of rural residents is not only a manifestation of personal and family characteristics; understanding of environmental knowledge, attitudes, and household energy practices are more important. These non-economic factors seriously affect WTU/WTB. Hence, it is necessary to appropriately increase the government revenue to such projects, strengthen government guidance and publicity, improve the environmental knowledge and attitude of rural residents and guide residents’ practice. Based on a fully understanding of residents’ consumption decision mechanism, we establish a financial support mechanism due to the demand response, adopt a correct calculation for financial support, such as a reasonable subsidy rate, and seek the greatest commonality of cost, financial support, and demand.

Evaluating China’s Air Pollution Control Policy with Extended AQI Indicator System: Example of the Beijing-Tianjin-Hebei Region

This paper calculated and evaluated the air quality of 13 cities in China’s Beijing-Tianjin-Hebei (BTH) region from February 2015 to January 2018 based on the extended AQI (Air Quality Index) Indicator System. By capturing the heterogeneous information in major pollutant indicators and the standardization process, we depicted the important effect of other relevant features of pollutant indicators beyond single-point data. Based on that, we further calculated the assessment value of the air quality of different cities in the BTH region by using the Collaborative Filtering Backward Cloud Model to construct differentiated weights of different indicators. With help of the Back Propagation (BP) Neutral Network, we simulated the effect of the pollution control policies of the Chinese government targeting air pollution since March 2016. Our conclusion is: the pollution control policies have improved the air quality of Beijing by 55.74%, and improved the air quality of Tianjin by 34.38%; while the migration of polluting enterprises from Beijing and Tianjin has caused different changes in air quality in different cities of Hebei province—we saw air quality deterioration by 58.60% and 38.68% in Shijiazhuang and Handan city respectively.