Manufacturing and mining sectors are serious pollution sources and risk factors that threaten air quality and human health. We analyzed pollutants at two study sites (Talcher and Brajrajnagar) in Odisha, an area exposed to industrial emissions, in the pre-COVID-19 year (2019) and consecutive pandemic years, including lockdowns (2020 and 2021). We observed that the annual data for pollutant concentration increased at Talcher: PM_2.5 (7–10%), CO (29–35%), NO₂ and NO_x (8–57% at Talcher and 14–19% at Brajrajnagar); while there was slight to substantial increase in PM₁₀ (up to 11%) and a significant increase in O₃ (41–88%) at both sites. At Brajrajnagar, there was a decrease in PM_2.5 (up to 15%) and CO (around half of pre-lockdown), and a decrease in SO₂ concentration was observed (30–86%) at both sites. Substantial premature mortality was recorded, which can be attributed to PM_2.5 (16–26%), PM₁₀ (31–43%), NO₂ (15–21%), SO₂ (4–7%), and O₃ (3–6%). This premature mortality caused an economic loss between 86–36 million USD to society. We found that although lockdown periods mitigated the losses, the balance of rest of the year was worse than in 2019. These findings are benchmarks to manage air quality over Asia’s largest coalmine fields and similar landscapes.

Maintaining the quality of breathing air in urban and industrial areas is one of the biggest challenges faced by humanity in the modern era. Diesel engines, as one of the main providers of energy supply for modern equipment and transport, are also unfortunately contributing highly to the deterioration of air quality. A recent research path on the limitation of diesel engine emissions is the use of alternative fuel from vegetable or animal fats or oil called biodiesel. Although the use of biodiesel has proven its efficiency in reducing emissions, it remains a problem to maintain the engine’s efficiency when shifting to biodiesel, especially due to its injection and atomization properties; most of the recent research focused on improving biodiesel fuel quality by blending it with traditional diesel fuel, but few works can be found on the regulation or control of diesel engine process when shifting to 100% biodiesel fuel (B100). This work proposes a fuel control strategy and methodology based on diesel engine operating data obtained from an experimentally designed rate of injection model (ROI) at different injection pressures and a jet and spray droplet distribution validated a two-zone model. Results show that B100 gives a higher amount of about 8% of injected fuel, a longer jet penetration of about 20 mm higher at 100 MPa injection pressure, a wider cone angle, and about a 40% increase of coarseness of the jet distribution. The experimental and numerical-based control strategy provides interacting relationships between B100 properties and specific engine features where actions shall be made to keep the engine’s efficiency when the shift is made; meanwhile, the algorithm provides a hierarchical step-by-step correcting procedure taking into account the possible degradation that could occur from the use of B100 in diesel engines.

A challenge in many Sub‐Saharan African (SSA) cities is the absence of air quality monitoring due to the high expense and technical expertise needed. Air pollution around the world is becoming a societal problem, and developed countries have all the necessary information about the levels of most air pollutants; however, underdeveloped countries have inadequate information on air quality. The problem of poor air quality in many SSA countries is due to lack of information about the hazards of poor air quality, lack of monitoring equipment, and lack of measuring stations: this is the case in Cameroon. We are avoiding these problems by using portable, low‐cost, low‐maintenance air quality monitoring equipment, including the OC 300 dust particle laser, to observe pollution levels of particle matter levels in the PK17 Douala‐Cameroon, a locality in the Central African region where no air quality data previously existed. The air quality index is very poor on the measurement days, and the color code is red. It has maximum values of about 199 for PM₁₀ and 192 for PM_2.5. The average concentration values obtained were of the order of 200.54 µg·m⁻³, 155.54 µg·m⁻³, 194.90 µg·m⁻³, and 194.03 µg·m⁻³ for PM₁₀, respectively, on Tuesday, Thursday, Saturday, and Sunday. Regarding PM_2.5, the average concentrations are 99.84 µg·m⁻³, 82.30 µg·m⁻³, 108.23 µg·m⁻³, and 112.97 µg·m⁻³, respectively, on Tuesday, Thursday, Saturday, and Sunday. A two‐dimensional Gaussian model was used to estimate the particle matter concentration along each road. The nRMSE was 9% for PM₁₀ and 12 for PM_2.5, and the index-d for both particle sizes was close to 1 (0.74 for PM₁₀ and 0.98 for PM_2.5), which allows us to conclude that the calculated concentrations are the closest to the measured concentrations. The assessment reveals that most of the particulate matter during the measurement period was generated by road traffic. The concentration measured values of the pollutants are three times for PM_2.5 and four times for PM₁₀ above the recent WHO limits for daily exposure. In addition, it provides essential information on the pollution in Douala, which can be a major source of illness in the city and must be addressed.

This study focused on the content of fine particle air pollution in the city of Douala. Several studies have analyzed pollution problems due to road traffic in Douala, Cameroon. Particle concentration levels are higher in heavy traffic than in light traffic. The populations exposure to air pollution in cities is higher near roads. Several studies have analyzed pollution problems due to road traffic in Douala, Cameroon. In this city, the traffic density at the intersections is indeed higher. Thus, the question is as follows: Are these traffic areas hotspots of increased PM exposure levels? To determine it, four particle size fractions (PM₁₀, PM_2.5, PM₅, and PM₁) were collected using an OC300 Gas and Dust Particle Laser Detector for three months at different traffic locations (roundabouts or/and crossroads). Statistical analysis of the data shows very high concentrations at most measurement sites. PM concentrations at the different measurement sites are around 35.69-68.08 µg m⁻³ for PM1, 50.72-99.13 µg m⁻³ for PM_2.5, 54.11-111.22 µg m⁻³ for PM₅, and 57.97-119.25 µg m⁻³ for PM₁₀. Exceedances of WHO daily guidelines for PM_2.5 (45 µg m⁻³) and PM₁₀ (15 µg m⁻³) were found during the measurement campaign, indicating that crossroads are the pollution hotspots in urban areas. Occupation of the roadsides for various economic activities (painting, restaurants, donut shops, etc.) is common in Cameroon, increasing health risks for people working around the roadside. Thus, crossroad locations are areas where the level of exposure to PM_x is the highest on road traffics.