Analytical Decision Supports System for Urban Air Quality Management in Tehran: Meteorological and Photochemical models

A new analytical air pollution modeling system is introduced in this paper to estimate concentrations of primary and secondary air pollutants and using it for further studies in order to improve the knowledge of pollutants emission and dispersion over Tehran, and developing a decision support system. For this purpose, WRF/CAMx modeling system was used to simulate the gas-phase pollutants concentrations including primary and secondary pollutants, over Tehran during a wintertime episode, which is characterized by very high concentrations of pollutants. Pollutants were triggered by meteorological conditions leading to a forced holiday imposed on citywide operations to protect the health of citizens. Based on calculated Values of NMB error, WRF performs acceptable in predicting temperature and wind speed. Generally, time series plots show that WRF performs acceptable in mild selected episode. Also, the daily trends of pollutant concentrations are greatly affected by changes in local meteorological conditions such as planetary boundary layer (PBL) height, temperature, wind, and relative humidity over the Tehran area. An underestimation in prediction of all pollutants concentrations episode at Poonak and Aghdasyeh sites show due to the insufficient emission data at the site position used for the simulation were seen. Results showed that WRF/CAMx modeling system proved to be a useful tool for analyzing urban environmental problems, investigating the impact of air quality control policies, and predicting critical conditions. However, there were weaknesses in input data and modeling system calibration that should be improved before using the system for further studies

Dynamic complex network analysis of PM2.5 concentrations in the UK, using hierarchical directed graphs (V1.0.0)

The risk of a broad range of respiratory and heart diseases can be increased by widespread exposure to fine atmospheric particles on account of their capability to have a deep penetration into the blood streams and lung. Globally, studies conducted epidemiologically in Europe and elsewhere provided the evidence base indicating the major role of PM2.5 leading to more than four million deaths annually. Conventional approaches to simulate atmospheric transportation of particles having high dimensionality from both transport and chemical reaction process make exhaustive causal inference difficult. Alternative model reduction methods were adopted, specifically a data-driven directed graph representation, to deduce causal directionality and spatial embeddedness. An undirected correlation and a directed Granger causality network were established through utilizing PM2.5 concentrations in 14 United Kingdom cities for one year. To demonstrate both reduced-order cases, the United Kingdom was split up into two southern and northern connected city communities, with notable spatial embedding in summer and spring. It continued to reach stability to disturbances through the network trophic coherence parameter and by which winter was construed as the most considerable vulnerability. Thanks to our novel graph reduced modeling, we could represent high-dimensional knowledge in a causal inference and stability framework

A Synoptic- and Remote Sensing-based Analysis of a Severe Dust Storm Event over Central Asia

Published by [Verlag nicht ermittelbar], Taina

SOIL CONTAMINATION IN AREAS IMPACTED BY MILITARY ACTIVITIES: A CRITICAL REVIEW

Military activities drastically affect soil properties mainly via physical/chemical disturbances during military training and warfare. The present paper aims to review (1) physical/chemical disturbances in soils following military activities, (2) approaches to characterization of contaminated military-impacted sites, and (3) advances in human health risk assessment for evaluating potential adverse impacts. A literature search mainly covering the period 2010–2020 but also including relevant selected papers published before 2010 was conducted. Selected studies (more than 160) were grouped as follows and then reviewed: ~40 on the presence of potentially toxic elements (PTEs), ~20 on energetic compounds (ECs) and chemical warfare agents (CWAs), ~40 on human health risk assessment, and generic limits/legislation, and ~60 supporting studies. Soil physical disturbances (e.g., compaction by military traffic) may drastically affect soil properties (e.g., hydraulic conductivity) causing environmental issues (e.g., increased erosion). Chemical disturbances are caused by the introduction of numerous PTEs, ECs, and CWAs and are of a wide nature. Available generic limits/legislation for these substances is limited, and their contents do not always overlap. Among numerous PTEs in military-impacted zones, Pb seems particularly problematic due to its high toxicity, abundance, and persistence. For ECs and CWAs, their highly variable physiochemical properties and biodegradability govern their specific distribution, environmental fate, and transport. Most site characterization includes proper spatial/vertical profiling, albeit without adequate consideration of contaminant speciation/fractionation. Human health risk assessment studies generally follow an agreed upon framework; however, the depth/adequacy of their use varies. Generic limits/legislation limited to a few countries do not always include all contaminants of concern, their content doesn’t overlap, and scientific basis is not always clear. Thus, a comprehensive scientific framework covering a range of contaminants is needed. Overall, contaminant speciation, fractionation, and mobility have not been fully considered in numerous studies. Chemical speciation and bioaccessibility, which directly affect the results for risk characterization, should be properly integrated into risk assessment processes for accurate results

Impact of COVID-19 Event on the Air Quality in Iran

The first novel coronavirus case was confirmed in Iran in mid-February 2020. This followed by the enforcement of lockdown to tackle this contagious disease. This study aims to examine the potential effects of the COVID-19 lockdown on air quality in Iran. From 21st March to 21st April in 2019 and 2020, The Data were gathered from 12 air quality stations to analyse six criteria pollutants, namely O3, NO2, SO2, CO, PM10, and PM2.5. Due to the lack of ground-level measurements, using satellite data equipped us to assess changes in air quality during the study on Iranian megacities, especially in Tehran, i.e., the capital of Iran. In this city, concentrations of primary pollutants (SO2 5–28%, NO2 1–33%, CO 5–41%, PM10 1.4–30%) decreased with spatial variations. Although, still SO2, NO2, and PM10 exceeded the WHO daily limit levels for 31 days, 31 days, and four days, respectively. Conversely, O3 and PM2.5 increased by 0.5–103% and 2–50%. In terms of the national air quality, SO2 and NO2 levels decreased while AOD increased during the lockdown. Unfavourable meteorological conditions hindered pollutant dispersion. Moreover, reductions in the height of planetary boundary layer and rainfall were observed during the lockdown period. Despite the adverse weather conditions, a decrease in primary pollutant levels, confirms the possible improvements on the air quality in Iran

Destinations frequently impacted by dust storms originating from southwest Iran

Deserts can be considered as one of the main sources of dust emissions as they are highly vulnerable to wind erosion, i.e. The lack of vegetative cover, as well as low soil wetness, contribute to the release of particles by wind erosion. The present study examines the seasonal variation in sand and dust storms (SDSs) originating from war-impacted semi-arid bare lands affected by chemical warfare located in southwest Iran for the period of 2007–2018. It employs a synthesis of satellite observations and Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model trajectories. A regression analysis between annual/seasonal absorbing aerosol index distribution and selected parameters indicated strong correlation with surface skin temperature, topsoil layer wetness, and 10-m wind speed. During both cold and warm periods, Kuwait and the Persian Gulf were highly vulnerable to episodic dust incursions as they were identified in the maximum impact zone (frequency of 100%). The Persian Gulf was affected by about 12% of the total air masses during the warm period, which increased to 74% during the cold period. Regarding the vulnerability to the high wind of war-impacted regions presumably contaminated with potentially toxic elements (PTEs) and toxic compounds, the particles of contaminated dust may have been continuously transported over by the strong winds, not only the surrounding region but also long distances including agricultural land and marine environment. The study area would possibly pose a danger to the environment and human health; therefore, a detailed site characterization to investigate the degree of contamination with PTEs and toxic compounds is warranted

ASSESSMENT OF POTENTIAL BENEFITS OF TRAFFIC AND URBAN MOBILITY REDUCTIONS DURING COVID-19 LOCKDOWNS: DOSE-RESPONSE CALCULATIONS FOR MATERIAL CORROSIONS ON BUILT CULTURAL HERITAGE

Air pollution, particularly in urban areas, puts human health in danger and has adverse impacts on the built environment. It can accelerate the natural corrosion rate of cultural heritages and monuments, leading to premature aging and lowering their aesthetic value. Globally, at the beginning of 2020, to tackle the spread of novel COVID-19, the lockdown was enforced in the most hardhit countries. Therefore, this study assesses, as a first time, the plausible benefits of traffic and urban mobility reductions on the natural process of deterioration of materials during COVID-19 lockdown in twenty-four major cities on five continents. The potential risk is estimated based on exceeding the tolerable degradation limits for each material. The notable impact of COVID-19 mobility restrictions on air quality was evidenced in 2020 compared to 2019. The introduced mobility restrictions in 2020 could decrease the surface recession rate of materials. Extremely randomized trees analysis showed that PM10 was the main influencing factor for corrosion of portland, copper, cast bronze, and carbon steel with a relative importance of 0.60, 0.32, 0.90, and 0.64, respectively, while SO2 and HNO3 were mainly responsible for corrosion of sandstone and zinc with a relative importance of 0.60 and 0.40, respectively. The globally adverse governed meteorological conditions in 2020 could not positively influence the movement restrictions around the world in air quality improvements. Our findings can highlight the need for additional policies and measures for reducing ambient pollution in cities and the proximity of sensitive cultural heritage to avoid further damage

ASSESSMENT OF THE ASSOCIATION BETWEEN DUST STORMS AND COVID-19 INFECTION RATE IN SOUTHWEST IRAN

This study assesses a plausible correlation between a dust intrusion episode and a daily increase in COVID-19 cases. A surge in COVID-19 cases was observed a few days after a Middle East Dust (MED) event that peaked on 25th April 2020 in south west Iran. To investigate potential causal factors for the spike in number of cases, cross-correlations between daily combined aerosol optical depths (AODs) and confrmed cases were computed for Khuzestan, Iran. Additionally, atmospheric stability data time series were assessed by covering before, during, and after dust intrusion, producing four statistically clustered distinct city groups. Groups 1 and 2 had diferent peak lag times of 10 and 4-5 days, respectively. Since there were statisti cally signifcant associations between AOD levels and confrmed cases in both groups, dust incursion may have increased population susceptibility to COVID-19 disease. Group 3 was utilized as a control group with neither a signifcant level of dust incursion during the episodic period nor any signifcant associations. Group 4 cities, which experienced high dust incur sion levels, showed no signifcant correlation with confrmed case count increases. Random Forest Analysis assessed the infuence of wind speed and AOD, showing relative importance of 0.31 and 0.23 on the daily increase percent of confrmed cases, respectively. This study may serve as a reference for better understanding and predicting factors afecting COVID-19 transmission and difusion routes, focusing on the role of MED intrusions

Exposure to particulate matter and gaseous pollutants during cab commuting in Nur-Sultan city of Kazakhstan

Exposure to particulate matter, carbon dioxide, and carbon monoxide inside a car during commuting were determined during the period October–November 2017 in Nur-Sultan, Kazakhstan. We choose to follow five bus routes (#10, 18, 19, 37 and 53) that cover the majority of the city's area. CO (ppm), CO2 (ppm) and PM1, PM2.5, PM4, and PM10 mass concentration (μg/m3) were measured in this study. PM11 was found to be the largest fraction of all sizes of PM. The mean PM1 concentrations along the forward (backward) paths for each of the five bus routes were measured as 11 ± 14 (11 ± 7), 14 ± 8 (16 ± 6), 25 ± 11 (21 ± 14), 23 ± 8 (15 ± 6) and 76 ± 26 (99 ± 55) μg/m3, respectively. Average CO concentrations among five bus routes (#10, 18, 19, 37 and 53) along the forward (backward) paths were 0.67 ± 0.16 (0.78 ± 0.17), 0.7 ± 0.16 (0.53 ± 0.32), 1.04 ± 0.01 (2.3 ± 0.95), 2.67 ± 1.3 (2.03 ± 0.41), 3.54 ± 3.57 (2.17 ± 0.37) ppm. The mean PM1/PM2.5 and PM2.5/PM10 ratios were 0.96 and 0.91, respectively. Nur-Sultan could be an example for those cities that are under major developments and candidates to be green cities by showing the exposures to atmospheric pollutants across the city. Those cities that are developing themselves as tourist attractions should create maps of PM exposures along major urban routes, and route traffic to exclude tourist areas from being hotspots