Surrounding greenness is associated with lower risk and burden of low birth weight in Iran.

The nexus between prenatal greenspace exposure and low birth weight (LBW) remains largely unstudied in low- and middle-income countries (LMICs). We investigated a nationwide retrospective cohort of 4,021,741 live births (263,728 LBW births) across 31 provinces in Iran during 2013-2018. Greenness exposure during pregnancy was assessed using satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). We estimated greenness-LBW associations using multiple logistic models, and quantified avoidable LBW cases under scenarios of improved greenspace through counterfactual analyses. Association analyses provide consistent evidence for approximately L-shaped exposure-response functions, linking 7.0-11.5% declines in the odds of LBW to each 0.1-unit rise in NDVI/EVI with multiple buffers. Assuming causality, 3931-5099 LBW births can be avoided by achieving greenness targets of mean NDVI/EVI, amounting to 4.4-5.6% of total LBW births in 2015. Our findings suggest potential health benefits of improved greenspace in lowering LBW risk and burden in LMICs.

Worldwide Evaluation of CAMS-EGG4 CO2 Data Re-Analysis at the Surface Level.

This study systematically examines the global uncertainties and biases in the carbon dioxide (CO2) mixing ratio provided by the Copernicus Atmosphere Monitoring Service (CAMS). The global greenhouse gas re-analysis (EGG4) data product from the European Centre for Medium-Range Weather Forecasts (ECMWF) was evaluated against ground-based in situ measurements from more than 160 of stations across the world. The evaluation shows that CO2 re-analysis can capture the general features in the tracer distributions, including the CO2 seasonal cycle and its strength at different latitudes, as well as the global CO2 trend. The emissions and natural fluxes of CO2 at the surface are evaluated on a wide range of scales, from diurnal to interannual. The results highlight re-analysis compliance, reproducing biogenic fluxes as well the observed CO2 patterns in remote environments. CAMS consistently reproduces observations at marine and remote regions with low CO2 fluxes and smooth variability. However, the model's weaknesses were observed in continental areas, regions with complex sources, transport circulations and large CO2 fluxes. A strong variation in the accuracy and bias are displayed among those stations with different flux profiles, with the largest uncertainties in the continental regions with high CO2 anthropogenic fluxes. Displaying biased estimation and root-mean-square error (RMSE) ranging from values below one ppmv up to 70 ppmv, the results reveal a poor response from re-analysis to high CO2 mixing ratio, showing larger uncertainty of the product in the boundaries where the CAMS system misses solving sharp flux variability. The mismatch at regions with high fluxes of anthropogenic emission indicate large uncertainties in inventories and constrained physical parameterizations in the CO2 at boundary conditions. The current study provides a broad uncertainty assessment for the CAMS CO2 product worldwide, suggesting deficiencies and methods that can be used in the future to overcome failures and uncertainties in regional CO2 mixing ratio and flux estimates.

Analysis of spatial factors, time-activity and infiltration on outdoor generated PM2.5 exposures of school children in five European cities.

Atmospheric particles are a major environmental health risk. Assessments of air pollution related health burden are often based on outdoor concentrations estimated at residential locations, ignoring spatial mobility, time-activity patterns, and indoor exposures. The aim of this work is to quantify impacts of these factors on outdoor-originated fine particle exposures of school children. We apply nested WRF-CAMx modelling of PM2.5 concentrations, gridded population, and school location data. Infiltration and enrichment factors were collected and applied to Athens, Kuopio, Lisbon, Porto, and Treviso. Exposures of school children were calculated for residential and school outdoor and indoor, other indoor, and traffic microenvironments. Combined with time-activity patterns six exposure models were created. Model complexity was increased incrementally starting from residential and school outdoor exposures. Even though levels in traffic and outdoors were considerably higher, 80-84% of the exposure to outdoor particles occurred in indoor environments. The simplest and also commonly used approach of using residential outdoor concentrations as population exposure descriptor (model 1), led on average to 26% higher estimates (15.7 µg/m3) compared with the most complex model (# 6) including home and school outdoor and indoor, other indoor and traffic microenvironments (12.5 µg/m3). These results emphasize the importance of including spatial mobility, time-activity and infiltration to reduce bias in exposure estimates.

The impact of COVID-19 on air quality levels in Portugal: A way to assess traffic contribution.

The pandemic caused by coronavirus COVID-19 is having a worldwide impact that affects health, the economy and indirectly affects the air pollution in cities. In Portugal, the number of cases increased continually (32700 confirmed cases as of May 31, 2020), which has affected the health system and caused movement restrictions which in turn affects the air pollution in the country. This article analyses the indirect effect produced by this pandemic on air pollution in Portugal, by comparison of data from a period of movement restriction of the citizens by the government - COVID lockdown period (March-May 2020) with data from baseline conditions (mean of the mirrored periods from the five previous years (March-May from 2015 to 2019)). Air quality data - in particular NO2 and PM10 hourly concentration - from more than 20 monitoring stations spread over mainland Portugal was used to perform this evaluation. The mean reduction observed on pollutant concentrations was higher for NO2 (41%) than for PM10 (18%). For NO2, mean reductions were more significant in traffic (reaching values higher than 60% in some monitoring stations) and background urban sites than in rural stations. The reduction of NO2 concentration observed in traffic sites were compared to the estimation of traffic contribution by the incremental method, suggesting that this latter approach is not consistent (lower in same sites and higher in others) and alerting to the careful use of this approach in future works.

Impact of traffic emissions on air quality in Cabo Verde.

Air quality degradation due to road traffic emissions is one of the topics of major interest for the scientific community and urban planners worldwide. Cabo Verde does not have regulations for traffic emission control or air quality guidelines, although the number of road vehicles has grown steadily over the past decade. Moreover, studies focusing on the impact of road transport on air quality in this archipelago are sparse. In this study, we present a first detailed air pollutant inventory of road traffic emissions through a bottom-up methodology, along with snapshots of the state of air quality on the islands of Santiago, São Vicente, and Sal. For the year 2017, emission estimates for the main island (Santiago) are 654 tons of CO, 35 tons of PM10, 562 tons of NOx, and 84 tons of NMVOCs. The air quality assessment was carried out using the TAPM model for a period of 6 months from January to July 2017. The results showed that the mean concentration values for Sao Vicente, Sal, and Santiago Islands ranged between 2.0 and 18 µg m-3 for NO2 and 3.8 and 5.6 µg m-3 for PM10. NO2 concentrations show an increasing trend from January to July in Santiago and Sal, and no clear trend in São Vicente Island. The simulated PM10 concentrations showed values in the same range over the year, even though they appeared slightly higher in July than in January. It was observed that both NO2 and PM10 average concentrations have been consistently above healthful levels, according to air quality guidelines fixed by the WHO.

Modelling air quality levels of regulated metals: limitations and challenges.

Toxic metals as arsenic (As), cadmium (Cd), nickel (Ni), and lead (Pb) exist in the atmosphere as particulate matter components. Their concentration levels in the European Union (EU) are regulated by European legislation, which sets target and limit values as annual means, and by the World Health Organization (WHO) that defines guidelines and reference values for those metal elements. Modelling tools are recommended to support air quality assessment regarding the toxic metals; however, few studies have been performed and those assessments rely on discrete measurements or field campaigns. This study aims to evaluate the capability of air quality modelling tools to verify the legislation compliance concerning the atmospheric levels of toxic elements and to identify the main challenges and limitations of using a modelling assessment approach for regulatory purposes, as a complement to monitoring. The CAMx air quality model was adapted and applied over Porto and Lisbon urban regions in Portugal at 5 × 5-km2 and 1 × 1-km2 horizontal resolution for the year 2015, and the results were analysed and compared with the few measurements available in three locations. The comparison between modelled and measured data revealed an overestimation of the model, although annual averages are much lower than the regulated standards. The comparison of the 5-km and 1-km resolutions' results indicates that a higher resolution does not necessarily imply a better performance, pointing out uncertainties in emissions and the need to better describe the magnitude and spatial allocation of toxic metal emissions. This work highlighted that an increase of the spatial and temporal coverage of monitoring sites would allow to improve the model design, contribute to a better knowledge on toxic metals atmospheric emission sources and to increase the capacity of models to simulate atmospheric particulate species of health concern.

Optimal air quality policies and health: a multi-objective nonlinear approach.

The use of modelling tools to support decision-makers to plan air quality policies is now quite widespread in Europe. In this paper, the Regional Integrated Assessment Tool (RIAT+), which was designed to support policy-maker decision on optimal emission reduction measures to improve air quality at minimum costs, is applied to the Porto Urban Area (Portugal). In addition to technological measures, some local measures were included in the optimization process. Case study results are presented for a multi-objective approach focused on both NO2 and PM10 control measures, assuming equivalent importance in the optimization process. The optimal set of air quality measures is capable to reduce simultaneously the annual average concentrations values of PM10 and NO2 in 1.7 and 1.0 µg/m3, respectively. This paper illustrates how the tool could be used to prioritize policy objectives and help making informed decisions about reducing air pollution and improving public health.

Integrating health on air quality assessment--review report on health risks of two major European outdoor air pollutants: PM and NO2.

Quantifying the impact of air pollution on the public's health has become an increasingly critical component in policy discussion. Recent data indicate that more than 70% of the world population lives in cities. Several studies reported that current levels of air pollutants in urban areas are associated with adverse health risks, namely, cardiovascular diseases and lung cancer. IARC recently classified outdoor air pollution and related particulate matter (PM) as carcinogenic to humans. Despite the air quality improvements observed over the last few years, there is still continued widespread exceedance within Europe, particularly regarding PM and nitrogen oxides (NOx). The European Air Quality Directive 2008/50/EC requires Member States to design appropriate air quality plans for zones where air quality does not comply with established limit values. However, in most cases, air quality is only quantified using a combination of monitored and modeled data and no health impact assessment is carried out. An integrated approach combining the effects of several emission abatement measures on air quality, impacts on human health, and associated implementation costs enables an effective cost-benefit analysis and an added value to the decision-making process. Hence, this review describes the basic steps and tools for integrating health into air quality assessment (health indicators, exposure-response functions). In addition, consideration is given to two major outdoor pollutants: PM and NO2. A summary of the health metrics used to assess the health impact of PM and NO2 and recent epidemiologic data are also described.