Mitigating air pollution: planetary health awaits a cosmopolitan moment

Modelling variations of emergency attendances using data on community mobility, climate and air pollution

Air pollution is associated with morbidity and mortality worldwide. We investigated the impact of improved air quality during the economic lockdown during the SARS-Cov2 pandemic on emergency room (ER) admissions in Germany. Weekly aggregated clinical data from 33 hospitals were collected in 2019 and 2020. Hourly concentrations of nitrogen and sulfur dioxide (NO2, SO2), carbon and nitrogen monoxide (CO, NO), ozone (O3) and particulate matter (PM10, PM2.5) measured by ground stations and meteorological data (ERA5) were selected from a 30 km radius around the corresponding ED. Mobility was assessed using aggregated cell phone data. A linear stepwise multiple regression model was used to predict ER admissions. The average weekly emergency numbers vary from 200 to over 1600 cases (total n = 2,216,217). The mean maximum decrease in caseload was 5 standard deviations. With the enforcement of the shutdown in March, the mobility index dropped by almost 40%. Of all air pollutants, NO2 has the strongest correlation with ER visits when averaged across all departments. Using a linear stepwise multiple regression model, 63% of the variation in ER visits is explained by the mobility index, but still 6% of the variation is explained by air quality and climate change.

Dynamics of environmental pollution, socio-economic factors, and total fertility rate in MENA, ECOWAS, and ASEAN regions

One of the critical items in the environmental agenda is managing and controlling regional haze and air pollution. These haze, emissions and air pollution are emitted into the environment, causing dangerous harm and imposing threats to public health, human wellbeing, and fertility issues, which sometimes lead to death. The researcher aims investigates broad effects of environmental pollution, socio-economic factors on total fertility rate in MENA, ECOWAS and ASEAN regions from 1970 to 2019. The Middle East and North Africa (MENA) regions consist of 21 countries, and the Economic Community of West African States (ECOWAS) comprises 15 countries. While 10 viable countries constitute the Association of Southeast Asian Nations (ASEAN). A longitudinal/panel dataset covering the regions is sourced mainly from the 2019 World Development Indicators (WDI) to examine the study objectives. In the methodology, a panel fixed-effect (FE) model are employed in estimating the objective after ascertaining the FE suitability using the Hausman Test. The results show that (i) environmental pollution (as proxied by CO₂ emissions) has a negative and statistically significant effect on total fertility rate in MENA and ECOWAS but has a significantly positive effect on TFR in ASEAN. Based on the findings, many robust policies are recommended to manage/control environmental pollution to drive down fertility and other public health threats.

Valuing burden of premature mortality attributable to air pollution in major million-plus non-attainment cities of India

Accelerating growth due to industrialization and urbanization has improved the Indian economy but simultaneously has deteriorated human health, environment, and ecosystem. In the present study, the associated health risk mortality (age > 25) and welfare loss for the year 2017 due to excess PM_2.5 concentration in ambient air for 31 major million-plus non-attainment cities (NACs) in India is assessed. The cities for the assessment are prioritised based on population and are classified as ‘X’ (> 5 million population) and ‘Y’ (1–5 million population) class cities. Ground-level PM_2.5 concentration retrieved from air quality monitoring stations for the NACs ranged from 33 to 194 µg/m³. Total PM_2.5 attributable premature mortality cases estimated using global exposure mortality model was 80,447 [95% CI 70,094–89,581]. Ischemic health disease was the leading cause of death accounting for 47% of total mortality, followed by chronic obstructive pulmonary disease (COPD-17%), stroke (14.7%), lower respiratory infection (LRI-9.9%) and lung cancer (LC-1.9%). 9.3% of total mortality is due to other non-communicable diseases (NCD-others). 7.3–18.4% of total premature mortality for the NACs is attributed to excess PM_2.5 exposure. The total economic loss of 90,185.6 [95% CI 88,016.4–92,411] million US$ (as of 2017) was assessed due to PM_2.5 mortality using the value of statistical life approach. The highest mortality (economic burden) share of 61.3% (72.7%) and 30.1% (42.7%) was reported for ‘X’ class cities and North India zone respectively. Compared to the base year 2017, an improvement of 1.01% and 0.7% is observed in premature mortality and economic loss respectively for the year 2024 as a result of policy intervention through National Clean Air Action Programme. The improvement among 31 NACs was found inconsistent, which may be due to a uniform targeted policy, which neglects other socio-economic factors such as population, the standard of living, etc. The study highlights the need for these parameters to be incorporated in the action plans to bring in a tailored solution for each NACs for better applicability and improved results of the programme facilitating solutions for the complex problem of air pollution in India.

AirKit: A Citizen-Sensing Toolkit for Monitoring Air Quality

Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility. In this paper, we present AirKit, which was developed as an integrated and open source “social IoT technology”. AirKit enables a comprehensive approach to citizen-sensing air quality through several integrated components: (1) the Dustbox 2.0, a particulate matter sensor; (2) Airsift, a data analysis platform; (3) a reliable and automatic remote firmware update system; (4) a “Data Stories” method and tool for communicating citizen data; and (5) an AirKit logbook that provides a guide for designing and running air quality projects, along with instructions for building and using AirKit components. Developed as a social technology toolkit to foster open processes of research co-creation and environmental action, Airkit has the potential to generate expanded engagements with IoT and air quality by improving the accuracy, legibility and use of sensors, data analysis and data communication.