Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies

The Nutrition in Early Life and Asthma (NELA) birth cohort study: Rationale, design, and methods

BACKGROUND

Primary prevention strategies for asthma are lacking. Its inception probably starts in utero and/or during the early postnatal period as the developmental origins of health and disease (DOHaD) paradigm suggests.

OBJECTIVES

The main objective of Nutrition in Early Life and Asthma (NELA) cohort study is to unravel whether the following factors contribute causally to the developmental origins of asthma: (1) maternal obesity/adiposity and foetal growth; (2) maternal and child nutrition; (3) outdoor air pollution; (4) endocrine disruptors; and (5) maternal psychological stress. Maternal and offspring biological samples are used to assess changes in offspring microbiome, immune system, epigenome and volatilome as potential mechanisms influencing disease susceptibility.

POPULATION

Randomly selected pregnant women from three health areas of Murcia, a south-eastern Mediterranean region of Spain, who fulfilled the inclusion criteria were invited to participate at the time of the follow-up visit for routine foetal anatomy scan at 19-22 weeks of gestation, at the Maternal-Fetal Medicine Unit of the "Virgen de la Arrixaca" University Clinical Hospital over a 36-month period, from March 2015 to April 2018.

DESIGN

Prospective, population-based, maternal-child, birth cohort study.

METHODS

Questionnaires on exposures and outcome variables were administered to mothers at 20-24 gestation week; 32-36 gestation week; and delivery. Children were surveyed at birth, 3 and 18 months of age and currently at 5 years. Furthermore, physical examinations were performed; and different measurements and biological samples were obtained at these time points.

PRELIMINARY RESULTS

Among the 1350 women invited to participate, 738 (54%) were finally enrolled in the study and 720 of their children were eligible at birth. The adherence was high with 612 children (83%) attending the 3 months' visit and 532 children (72%) attending the 18 months' visit.

CONCLUSION

The NELA cohort will add original and unique knowledge to the developmental origins of asthma.

Effects of air pollution on dementia over Europe for present and future climate change scenarios

The scientific literature is scarce when referring to the influence of atmospheric pollutants on neurodegenerative diseases for present and future climate change scenarios. In this sense, this contribution evaluates the incidence of dementia (Alzheimer's disease, AD, and dementia from unspecified cause, DU) occurring in Europe associated with the exposure to air pollution (essentially NO₂ and PM2.5) for the present climatic period (1991-2010) and for a future climate change scenario (RCP8.5, 2031-2050). The GEMM methodology has been applied to air pollution simulations using the chemistry/climate regional model WRF-Chem. Present population data were obtained from NASA's Center for Socioeconomic Data and Applications (SEDAC); while future population projections for the year 2050 were derived from the United Nations (UN) Department of Economic and Social Affairs-Population Dynamics. Overall, the estimated incidence rate (cases per year) of AD and DU associated with exposure to air pollution over Europe is 498,000 [95% confidence interval (95% CI) 348,600-647,400] and 314,000 (95% CI 257,500-401,900), respectively. An important increase in the future incidence rate is projected (around 72% for both types of dementia) when considering the effect of climate change together with the foreseen changes in the future population, because of the expected aging of European population. The climate penalty (impacts of future climate change alone on air quality) has a limited effect on the total changes of dementia (approx. 0.5%), because the large increase in the incidence rate over southern Europe is offset by its decrease over more northern countries, favored by an improvement of air pollution caused by the projected enhancement of rainfall.

A neural network-based method for modeling PM 2.5 measurements obtained from the surface particulate matter network

Air pollution is a global problem; hence, many countries devoted lots of resources towards its study and possible eradication. The major parameter indicator for air quality is the particulate matter (PM). These particles, especially PM_2.5, are injurious to health either under high concentration levels or after a long-term exposure. PM_2.5 particles are known to cause lung and respiratory diseases, cardiovascular diseases, and even cancer. In this research, artificial neural networks were used to train PM 2.5 measurements obtained from the Surface Particulate Matter Network (SPARTAN). The training was done using inputs that indicate time series of the measurements and the prevailing atmospheric conditions. The developed models were used to estimate PM 2.5 over a sub-Saharan site in Ilorin. Our study considered meteorological parameters and aerosol optical depth (AOD) as inputs for the neural networks. The targets are PM 2.5 measurements obtained from SPARTAN. Our models showed very high correlation with measured data. Apart from the data generated using model p which has a correlation of 0.0009, the correlation R² for other models ranges from 0.59 to 0.95) which has a good performance. The model PRB estimated both low and high PM better while others either under or over predict emission scenarios.

Vehicle emission and atmospheric pollution in China: problems, progress, and prospects

China has been the largest vehicle market in the world since 2009. The stalemate between the rapid development of the vehicle industry and delayed vehicle emission control has become increasingly prominent. Vehicle emission has become a significant source of air pollution in China's cities. Understanding the current barriers in the vehicle industry is necessary for the development of effective and sustainable measures and policy to manage vehicle-induced air pollution. This review provides insight into the circumstances and causes of vehicle-induced air pollution and outlines recent progress in policy-makers' long-term strategies and regulations. The development of an integrated mechanism of social participation, technical revolution, and regulatory innovation in vehicles, fuel, and roads is suggested to break the stalemate between air pollution and the automobile boom in China; the implications of this review extend to other countries facing the similar atmospheric pollution problems.