Chemical composition of indoor and outdoor PM2.5 in the eastern Arabian Peninsula.

Water-soluble and trace metal species in fine particulate matter (PM2.5) were determined for indoor and outdoor environments in Doha, Qatar. During the study period, PM2.5 concentrations showed significant variability across several indoor locations ranging from 7.1 to 75.8 µg m-3, while the outdoor mass concentration range was 34.7-154.4 µg m-3. The indoor and outdoor PM2.5 levels did not exhibit statistically significant correlation, suggesting efficient building envelope protection against outdoor PM2.5 pollution. Rather than outdoor sources, human activities such as cooking, cleaning, and smoking were the most significant influence on chemical composition of indoor PM2.5. NH4+ concentration was insufficient to neutralize SO42- indoors and outdoors, indicating the predominant presence of NH4HSO4. The enrichment factors indicated that outdoor Fe, Mn, Co, Cr, and Ni in PM2.5 mostly originated from crustal sources. In contrast, the remaining outdoor trace metals (Cu, Zn, As, Cd, Pb, and V) were mainly derived from anthropogenic sources. The indoor/outdoor concentration ratios revealed significant indoor sources for NH4+ and Cu. The crustal matter, water-soluble ions, and sea salt explained 42%, 21%, and 1% of the indoor PM2.5 mass, respectively. The same groups sequentially constituted 41%, 16%, and 1% of the outdoor PM2.5 mass.

Carbon based sensors for air quality monitoring networks; middle east perspective.

IoT-based Sensors networks play a pivotal role in improving air quality monitoring in the Middle East. They provide real-time data, enabling precise tracking of pollution trends, informed decision-making, and increased public awareness. Air quality and dust pollution in the Middle East region may leads to various health issues, particularly among vulnerable populations. IoT-based Sensors networks help mitigate health risks by offering timely and accurate air quality data. Air pollution affects not only human health but also the region's ecosystems and contributes to climate change. The economic implications of deteriorated air quality include healthcare costs and decreased productivity, underscore the need for effective monitoring and mitigation. IoT-based data can guide policymakers to align with Sustainable Development Goals (SDGs) related to health, clean water, and climate action. The conventional monitor based standard air quality instruments provide limited spatial coverage so there is strong need to continue research integrated with low-cost sensor technologies to make air quality monitoring more accessible, even in resource-constrained regions. IoT-based Sensors networks monitoring helps in understanding these environmental impacts. Among these IoT-based Sensors networks, sensors are of vital importance. With the evolution of sensors technologies, different types of sensors materials are available. Among this carbon based sensors are widely used for air quality monitoring. Carbon nanomaterial-based sensors (CNS) and carbon nanotubes (CNTs) as adsorbents exhibit unique capabilities in the measurement of air pollutants. These sensors are used to detect gaseous pollutants that includes oxides of nitrogen and Sulphur, and ozone, and volatile organic compounds (VOCs). This study provides comprehensive review of integration of carbon nanomaterials based sensors in IoT based network for better air quality monitoring and exploring the potential of machine learning and artificial intelligence for advanced data analysis, pollution source identification, integration of satellite and ground-based networks and future forecasting to design effective mitigation strategies. By prioritizing these recommendations, the Middle East and other regions, can further leverage IoT-based systems to improve air quality monitoring, safeguard public health, protect the environment, and contribute to sustainable development in the region.

High time-resolved measurements of water-soluble sulfate, nitrate and ammonium in PM2.5 and their precursor gases over the Eastern Mediterranean.

High time-resolved measurements of aerosol SO42-, NO3-, NH4+ and their precursor gases HNO3, SO2, NH3 between 27 and 02 January/February and 19-01 August/September 2015 were carried out by applying AIM-IC at a rural site located on the coast of the Eastern Mediterranean, Erdemli, Turkey. The comparison between online and offline techniques revealed better correlation coefficients for SO42- and NH4+ (r > 0.90) than that of NO3- (0.63). Mean concentrations of water-soluble species were found in decreasing order SO42- (2814 ng m-3) > NH4+ (1371 ng m-3) > NO3- (495 ng m-3). NH3 (3390 ng m-3) concentration was more than enough to neutralize SO2 (879 ng m-3) and HNO3 (346 ng m-3). The gas-to-particle conversion ratios (>0.3) implied that SO42-, NO3- and NH4+ were mainly influenced by non-local sources. SO42-, NO3-, NH4+, HNO3, SO2 exhibited remarkable decrease (leastways 40%) in the atmosphere over the Eastern Mediterranean throughout fifteen years. In winter, day time NH3 concentrations illustrated significant relationship with temperature (positive) and humidity (negative), implying evaporation of dew or emission from plant stoma. Whereas, diurnal cycle of SO42- and SO2 was considerably influenced by populated City of Mersin in winter. During summer, HNO3 and SO2 (r = 0.74) demonstrated similar diurnal cycle, suggesting a common source for these precursor gases whilst NH3 was considerably affected by biomass burning emissions. Variability of all species was governed by local or nearly mesoscale transport in winter possibly due to frequent rain events. In summer, air flow from Eastern Mediterranean denoted aged air masses (GPC > 0.65) containing rather uniform concentrations of SO42- (~65 nmol m-3) and NH4+ (~140 nmol m-3). The highest NH3 along with the greatest % KBB contribution to PM2.5 mass was observed under the influence of Northerly airflow, exhibiting significance of biomass burning emissions as a source of NH3 in summer.