Ambient Air Quality Research Articles

Monitoring and Assessing (PM10 & PM2.5) Particulate Matters within Federal University Otuoke amidst Seasonal Variation of Relative Humidity

This study examines the seasonal variation of particulate matter (PM10; PM2.5) concentrations within Federal University Otuoke, Nigeria. The study is premised on monitoring and assessing PM10 and PM2.5 in the environment of the university. Dustmate and Kane 100-1 and 3.5.1 RS-1361C-Humidity/Temperature meter were used in sampling between the hours of 8am to 5pm per day in five day per week for a period of 6month which covers both the rainy and dry season. The sampled concentration of PM10 and PM 2.5 obtained was compared with the guidelines of “The National Ambient Air Quality Standard” established by U.S. Environmental Protection Agency (EPA) for compliance and regulation. Descriptive statistically methods were used in data analysis. The Results revealed that the averages PM10 are 116.71 µg/m3 and 107.25 µg/m3, while PM 2.5 records as 27.52 µg/m3 and 32.21 µg/m3 respectively. Relative humidity was also recorded 55.53 µg/m3 and 73.74 µg/m3. Similarly the results in both seasons shows the total average of PM10 as 100.19 µg/m3 and 110.07 µg/m3, PM 2.5 records 23.88 µg/m3 and 23.37 µg/m3 while relative humidity records 55.78 µg/m3 and 68.18 µg/m3 respectively. These were significantly influenced by the relative humidity of the environment of Federal University Otuoke. The study concludes that the seasonal variation of the relative humidity has an effect on the PM10 and PM2.5 concentrations and consequently the air quality of the university, hence further research into methods that will reduce particulate matter, as well as strategic environmental management policies within the university and beyond is recommended.

Analysis of Suspended Particulate Matter in a Conventional Seed Spices Cleaning and Grading Industry: A Case Study of Unjha Vicinity in Gujarat, India

A large number of seed spices (Cumin, Fennel, Coriander, Fenugreek etc.) cleaning-grading units are situated in Gujarat and Rajasthan. In-plant study was performed in such a cleaning-grading industry located at Unjha (Gujarat) in collaboration with Centre for Research on Seed Spice (SDAU), Jagudan, Mehsana. Apprehension for wellbeing of workers of such dust/ suspended particulate matter (SPM) generating industries are growing with time. SPM samples were collected using standard High Volume Sampler and these samples were analyzed for their respirable suspended particulate matter (RSPM) and total SPM concentration (µg/m3). The highest concentration of RSPM (< 10 micron) inside the plant was found to be 20 x103 µg/m3, while the highest SPM concentration level was 168x103 µg/m3. The average particle size of SPM was 1.96 µ to 9.43 µ while that of RSPM was 1.7 µ. The Ambient air quality norms prescribed by Central Pollution Control Board (CPCB) for industrial areas limit these values to 100 µg/m3 (SPM) and 60 µg/m3 (RSPM). Such highly polluted in-plant atmosphere of seed spices cleaning-grading industry may cause severe health problems, leading to respiratory diseases among the workers. In order to protect the health of workers engaged in these industries, it is suggested to install the electrostatic precipitator (ESP) device and retrofitting of existing equipment (such that dust levels are within permissible limits) may be considered.

Tropospheric Ozone levels in and around southern city Bengaluru, India

The diurnal to seasonal ozone (O3) pre-cursors (NO, NO2, CO, VOCs) trends over local climatic zones (LCZs) with the changes in weather patterns with respect to land cover classes determines the O3 trends and useful for air quality management. In this work, diurnal to seasonal patterns of O3 concentrations are analysed across the different LCZs in Bengaluru region. The Central/State Pollution Control Boards (CPCB/SPCB) operate more than 500 continuous air quality and weather monitoring stations across the India. Hourly O3 concentration data were collected from CPCB for 5 different LCZs within the Bengaluru region over a period of four years (2019-2022). Time series analyses were conducted to examine the temporal variations in O3 levels. The results showed significant fluctuations in diurnal trends of O3 due to the influence of air temperature and relative humidity variations across the five LCZs within Bengaluru region. There were distinct seasonal trends in O3 concentrations with maximum (60-65 ppb) observed during the winter and summer seasons and that of minimum concentration in the range 20-25 ppb during the monsoon months. The observed maximum ozone levels (60 -65 ppb) found to be beyond the threshold national ambient air quality standard (NAAQ) and the accumulation exposure over threshold of 40 ppb (AOT 40) during the winter and summer. The O3 concentration trends are in line with the published research on premature mortality about 1200 annually for Karnataka state for chronic obstructive pulmonary disease owing to population exposure to O3 beyond its threshold level of NAAQ. Also, the annual rice yield loss is about 2% (~0.1 Metric Tonne) with the AOT 40 to paddy crop for Karnataka state. Thus, O3 diurnal to seasonal trends serve the first-hand information to local authorities for the action plan of air quality management taking into consideration O3 precursors, wind speed, and wind direction.

Significant changes in the physicochemical properties of BC-containing particles during the cold season in Beijing

The ambient air quality has improved significantly under strict emission controls in Beijing, China over the last decade. Black carbon (BC), as a short-lived climate forcer in ambient aerosols, profoundly impacts the air quality and climate. Previous studies have demonstrated a decline in the mass concentration of BC. In this study, we characterized the chemical compositions and size distributions of BC-containing particles during the cold season of 2022 in Beijing using state-of-the-art instruments capable of exclusively measuring BC-containing particles. The optical properties of BC-containing particles were further calculated based on the Mie theory. Moreover, we compared the properties of BC-containing particles in 2022 with the results of previous studies. The results showed that the diameters of BC cores became larger while the coating thickness of BC-containing particles became thinner in 2022. For the coating materials, the mass fraction of nitrate increased obviously, and even replaced organic matter as the dominant component during the peak of the pollution period. Variations in chemical compositions and size distributions resulted in lower mass absorption cross-sections (MAC) of BC-containing particles from 10.5 ± 1.1 m2/g in 2016 to 7.3 ± 0.8 m2/g in 2022, reduced by 30.5%. Our results demonstrate the synergistic benefits of air pollution control in improving air quality and mitigating climate change. Therefore, the MAC of BC adopted in climate models should vary with the changing air pollution levels. This study emphasizes that it is imperative to conduct long-term observations of BC-containing particles to better estimate BC's climate effects.

A panel study of exposure to fine particulate matter and modeled respiratory deposition on biomarkers of inflammation, blood coagulation, and oxidative stress in healthy young adults in Hefei, China

Evidence is scarce on the acute cardiovascular health effects of fine particulate matter (PM2.5) and its respiratory tract depositions. We performed a panel study in Hefei, China to explore the relations of PM2.5 and its depositions in 3 respiratory tract regions over different lag times with a range of cardiovascular biomarkers among 40 college students and the potential mediating effects of inflammation. We found significant effects of PM2.5 exposure on the alterations of biomarkers at specific lag days, in a concentration-response manner, even at PM2.5 level below Chinese Ambient Air Quality Standard (CAAQS) Grade I (35 μg/m3). For example, per 10 μg/m3 increase in PM2.5 concentration was associated with −9.33% increase in ADAMTS13 on lag 0-1d. The corresponding increases in D-Dimer, GM-CSF, and MCP-1 for the same change in PM2.5 concentration on lag 5-6d were 30.51%, 11.43%, and 20.05%. Besides, tracheobronchial region (TB) deposition presented more evident effects on these biomarkers than that in PM2.5. Additionally, we observed greater associations of PM2.5-biomarkers among females, those with abnormal body mass index (BMI), and those with physical activity. The results indicated that short-term PM2.5 exposure and its respiratory tract depositions were concentration-responsive associated with damaged cardiovascular health via inducing blood coagulation, oxidative stress and inflammation among healthy young adults even at concentration below CAAQS Grade I. Elevated serum levels of systemic inflammation may be partly responsible for the effects of PM2.5 and its respiratory tract depositions on coagulation function.

Assessment of ambient air quality status of Amravati city using time series forecasting network in deep learning MATLAB

Assessment of ambient air quality status of Amravati city using time series forecasting network in deep learning MATLAB

Total Suspended Particulate Matter (TSP)-Bound Carbonaceous Components in a Roadside Area in Eastern Indonesia

To evaluate carbonaceous components in the ambient air in the eastern region of Indonesia, 35 Total Suspended Particulate Matter (TSP) samples were collected on four characteristic roadsides on Sultan Alauddin Street, in Makassar City, using a high-volume air sampler. The average TSP concentration was 279.7 μg/m3, which exceeded both the National Ambient Air Quality Standard (NAAQS) of Indonesia and the World Health Organization (WHO) standards. The highest concentration reached 838.6 μg/m3 in the GR (gravel) site, which had the highest number of vehicles and was near a U-turn. TSP concentration was higher during peak hours (morning and late afternoon) than off-peak hours (noon). The main component of the total carbon (TC) fraction was organic carbon (OC), which showed a strong correlation with elemental carbon (EC) (r values for the morning, noon, and late afternoon were 0.89, 0.87, and 0.97, respectively), indicating that the carbon components were derived from common sources. TSP had a strong correlation with carbon components, except for char-EC. OC vs. soot-EC and EC vs. soot-EC also correlated well, suggesting the dominant influence of vehicle exhaust emissions. Non-exhaust emissions had a slight influence during peak hours, particularly at the GR site.

Effect of COVID‐19 lockdown on ambient air quality

AbstractThe aim of this study was to evaluate the impact of pandemic‐related lockdown on Turkey's air quality throughout time and space. For this purpose, statistical techniques were used to assess daily particulate matter (PM10), sulfur dioxide (SO2), nitrogen oxides and nitrogen dioxide (NOx and NO2), ozone (O3), and carbon monoxide (CO). The study's findings showed that, while the lockdown improved air quality in terms of air pollutant emissions, the most notable reduction was in NO2 and NOx emissions. When comparing the months prior to the pandemic (November 2019 to January 2020) with the months during the pandemic (November 2020 to January 2021), the declines in NO2 were 20%, 3%, and 0.5%, respectively. NOx emissions decreased by an average of 19% and 5% in November and December, respectively, and increased by an average of 16% in January during the pandemic. When the data for the 33 days of lockdown were compared to the data for the same 33 days the previous year, significant differences were determined at several Clean Air Centers, which were two for PM10, two for SO2, seven for NOx, four for NO2, two for CO, and three for O3, respectively. In this study, pollutant concentrations were found in the following ranges from November 2019 to January 2021: PM10: 3–208 µg m–3, SO2: 1–56 µg m–3, NOx: 6–600 µg m–3, NO2: 4–155 µg m–3, CO: 1–3921 µg m–3, and O3: 2–119 µg m–3. There were days that exceeded the limit values for PM10.

COVID-19 Mitigation in a K-12 School Setting: A Case Study of Avenues: The World School in New York City.

In this case study, we describe a well-resourced private school in New York City that implemented COVID-19 mitigation measures based on public health expert guidance and the lessons learned from this process. Avenues opened in New York City in 2012 and has since expanded, becoming Avenues: The World School, with campuses in São Paulo, Brazil; Shenzhen, China; the Silicon Valley, California; and online. It offers education at 16 grade levels: 2 early learning years, followed by a prekindergarten through grade 12. We describe the mitigation measures that Avenues implemented on its New York campus. We compare COVID-19 case prevalence at the school with COVID-19 case positivity in New York City, as reported by the New York State Department of Health. We also compare the school's indoor air quality to ambient indoor air quality measures reported in the literature. The school's mitigation measures successfully reduced the prevalence of COVID-19 among its students, staff, and faculty. The school also established a consistently high level of indoor air quality safety through various ventilation mechanisms, designed to reduce common indoor air pollutants. The school received positive parent and community feedback on the policies and procedures it established, with many parents commenting on the high level of trust and quality of communication established by the school. The successful reopening provides useful data for school closure and reopening standards to prepare for future pandemic and epidemic events.

Seasonal Variations Assessment of Air Pollutants of Communities in the Vicinity of Scrap Metal Recycling Industries in Ogijo, Shagamu South LGA, Ogun State, SW Nigeria

This manuscript presents a thorough investigation into the seasonal variations of air pollutants in communities surrounding scrap metal recycling industries in Ogijo, Shagamu South LGA, Ogun State, Nigeria utilizing advanced Gary Wolf Environmental Sensing and Particulate Counting devices. The study meticulously measures concentrations of carbon monoxide, nitrogen dioxide, sulfur dioxide, PM2.5, and PM10 during both dry and wet seasons across 20 strategic sampling locations and control. The findings reveal significant seasonal fluctuations in pollutant levels, with some concentrations exceeding Nigerian ambient air quality standards, highlighting a pressing environmental health concern. The study not only underscores the critical need for regulatory oversight and the implementation of safer metal scrapping practices but also advocates for regular environmental monitoring to mitigate the adverse impacts of such industries on local communities and the environment.

Composition, characteristics, and treatment technologies of condensable particulate matter present in flue gas emitted by coking plants in China

To study the total particulate matter (TPM) in flue gas emitted by coking plants, a sampling system that could be used to collect filterable particulate matter (FPM) and condensable particulate matter (CPM) was designed and developed based on Method 202 recommended by the U.S. Environmental Protection Agency in 2017 and HJ 836-2017 issued by China. Using this system, FPM and CPM in flue gas emitted by four coking furnaces named A, B, C, and D were tested in China. Further, 9 water-soluble ions, 20 elements, and organic matter present in the CPM were simultaneously examined to determine their formation mechanisms. Statistical data suggested that the FPM emission level in the coking flue gas was low and the average mass concentration was less than 10 mg/m3. However, with high CPM and TPM emission levels, the TPM mass concentrations of A, B, C, and D were 130 ± 11.1, 84.4 ± 6.36, 35.1 ± 17.0, and 63.8 ± 13.0 mg/m3, respectively. The main component of TPM was CPM, and the average mass concentration of CPM accounted for 98%, 95%, 68%, and 95% of TPM in furnaces A, B, C, and D, respectively. Water-soluble ions were the important components of CPM, and the total concentration of water-soluble ions accounted for 70%, 87%, 42%, and 66% of CPM in furnaces A, B, C, and D, respectively. Toxic and harmful heavy metals, such as Mn, Cr, Ni, Cu, Zn, As, Cd, and Pb, were detected in CPM. The formation mechanism of CPM was analyzed in combination with flue-gas treatment. It was shown that the treatment process “activated carbon– flue-gas countercurrent-integrated purification technology + ammonia spraying” used in furnaces A and B was less effective in removing CPM, water-soluble ions, metals, and compounds than that of “selective catalytic reduction denitrification + limestone–gypsum wet desulfurization (spraying NaOH solution)” in furnaces C and D. Hence, different flue-gas treatment technologies and operation levels played vital roles in the formation, transformation, and removal of CPM from flue-gas. Organic components in CPM discharged from furnace A were determined via gas chromatography–mass spectrometry, and the top 15 organic components in CPM were obtained using the area normalization method. N-alkanes accounted for the highest proportion, followed by esters and phenols, and most of them were toxic and harmful to humans and ecosystems. Therefore, advanced CPM treatment technologies should be developed to reduce atmospheric PM2.5 and its precursors to improve ambient air quality in China.

Hygienic aspects of mortality of the population of an industrial city

Introduction. The target indicators of the Federal Project “Clean Air” include a reduction in emissions of chemical pollutants by at least 20%. However, the main socially significant goal remains to improve the medical and demographic situation by reducing environmental and hygienic health risks.
 The purpose of the study was to preliminary assess the reserves for reducing mortality in the city of Omsk by identifying the most unfavourable territories in terms 
 of atmospheric air quality and identify priority chemicals, presumably causing negative trend in mortality.
 Materials and methods. To assess the quality of atmospheric air in the city of Omsk, the results of social and hygienic monitoring, environmental monitoring 
 of Federal Service of Russia on Hydrometeorology and Monitoring of the Environment (RosGidromet) for the multi-year period over 2009–2022 were used. 
 An analysis of the mortality rate of the population of Omsk for 2017–2022 was carried out. The data were studied in the context of municipal districts of the city of Omsk and in dynamics. Statistical methods were used in the study: ANOVA, correlation analysis, assessment of relative mortality risks. 
 Results. The relative risk (RR) of mortality for persons living in the most polluted areas of the city is 23–25% higher than in conditionally clean areas. Strong positive associations have been established: between the levels of actual total mortality and the specific gravity of atmospheric air samples exceeding the maximum single limit concentrations (R = 0.86; p < 0.05); between perennial average annual carbon monoxide concentrations and standardized rates of total mortality 
 (R = 0.93; p<0.05) and male mortality rates from all natural causes (R = 0.89; p<0.05).
 Limitations. The study is limited to the statistical research methods used. 
 Conclusion. The results of the study can become the basis for more efficient use of administrative resources in municipal districts of the city. As additional reserves for reducing mortality, the development of primary prevention measures at the outpatient level is important. It is necessary to optimize methodological approaches in the health control system of the population living in risk areas with developed industry.

Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India

Abstract. This paper discusses the newly developed Decision Support System version 1.0 (DSS v1.0) for air quality management activities in Delhi, India. In addition to standard air quality forecasts, DSS provides the contribution of Delhi, its surrounding districts, and stubble-burning fires in the neighboring states of Punjab and Haryana to the PM2.5 load in Delhi. DSS also quantifies the effects of local and neighborhood emission-source-level interventions on the pollution load in Delhi. The DSS-simulated Air Quality Index for the post-monsoon and winter seasons of 2021–2022 shows high accuracy (up to 80 %) and a very low false alarm ratio (∼ 20 %) from day 1 to day 5 of the forecasts, especially when the ambient air quality index (AQI) is > 300. During the post-monsoon season (winter season), emissions from Delhi, the rest of the National Capital Region (NCR)'s districts, biomass-burning activities, and all other remaining regions on average contribute 34.4 % (33.4 %), 31 % (40.2 %), 7.3 % (0.1 %), and 27.3 % (26.4 %), respectively, to the PM2.5 load in Delhi. During peak pollution events (stubble-burning periods or wintertime), however, the contribution from the main sources (farm fires in Punjab–Haryana or local sources within Delhi) could reach 65 %–69 %. According to DSS, a 20 % (40 %) reduction in anthropogenic emissions across all NCR districts would result in a 12 % (24 %) reduction in PM2.5 in Delhi on a seasonal mean basis. DSS is a critical tool for policymakers because it provides such information daily through a single simulation with a plethora of emission reduction scenarios.

Integrated Portable and Stationary Health Impact-Monitoring System for Firefighters.

The multi-layered negative effects caused by pollutants released into the atmosphere as a result of fires served as the stimulus for the development of a system that protects the health of firefighters operating in the affected area. A collaborative network comprising mobile and stationary Internet of Things (IoT) devices that are furnished with gas sensors, along with a remote server, constructs a resilient framework that monitors the concentrations of harmful emissions, characterizes the ambient air quality of the vicinity where the fire transpires, adopting European Air Quality levels, and communicates the outcomes via suitable applications (RESTful APIs and visualizations) to the stakeholders responsible for fire management decision making. Different experimental evaluations adopting separate contexts illustrate the operation of the infrastructure.

Comprehensive Impact of Changing Siberian Wildfire Severities on Air Quality, Climate, and Economy: MIROC5 Global Climate Model’s Sensitivity Assessments

AbstractWildfires emit atmospheric aerosols, affecting climate and air quality. Siberia is a known source region of wildfires. However, comprehensive knowledge regarding the impact associated with particulate matter pollution due to Siberian wildfires on climate and air quality and their effects on mortality and the economy under present and near‐future warmer atmospheric conditions remains poor. Thus, we performed model sensitivity experiments (atmospheric model and coupled atmosphere‐ocean model settings) simulating the effects of changing Siberian wildfire emissions under the present and near‐future climate conditions, using the Model for Interdisciplinary Research on Climate version 5 (MIROC5). Increased Siberian wildfire smoke likely caused a cooling effect in broad areas of the Northern Hemisphere and worsened the air quality near the source and in the downwind region (i.e., East Asia). The more Siberian wildfires occur, the more air pollution is present in those regions, which likely increases mortality and welfare losses there. However, the total impact of changing temperature on the gross domestic product under present and near‐future climate conditions is ambiguous. Our comprehensive results on the air quality changes due to Siberian wildfires under present and near‐future climate conditions suggest that increased efforts to limit the aerosol impact of Siberian wildfires are crucial to prevent possible excess mortality and economic losses.

Insights into civil aviation emissions in China: Analysis of an emission inventory of air pollutants and the ChinaHighAirPollutants (CHAP) dataset

The emissions from the civil aviation sector are a significant source of CO2 and air pollutants, which represent a serious threat to ambient air quality and public health. To gain a deeper understanding of civil aviation airport emissions, it is imperative to develop a precise and comprehensive emission inventory of China's civil aviation airports. However, there are limited studies dedicated to analyzing and verifying the accuracy and completeness of China's civil aviation emission inventory. Here, this study explored pollution characteristics from temporal trends and spatial distribution perspectives based on a previously developed 2019–2020 high-resolution air pollution and CO2 emission inventory of the landing and take-off (LTO) cycle of civil aviation airports in China and the ChinaHighAirPollutants (CHAP) dataset. Besides, this study established an empirical model to evaluate the relationship between the air pollutant emissions of China's civil aviation sector in 2019–2020 and the pollutant concentration from the CHAP dataset. Compared to those in 2019, the total NOx, CO, PM, and SO2 emissions during the LTO phase in China's civil aviation sector in 2020 decreased by 14.29%–24.32%, and the average concentrations of NO2, CO, PM10, and SO2 in 2020 decreased by 6.33%–9.45%. The eastern, central, and southern regions of China are characterized by high emissions of pollutants, a phenomenon closely related to the economic prosperity and tourism development in these areas. They tend to boast higher route densities, increasing air transport activity and consequently resulting in elevated emissions. In addition, NOx had the highest correlation coefficient in the empirical model, with a correlation coefficient of 0.603 in 2019. Our findings provide new insights into civil aviation emissions in China from the analysis of the emission inventory of air pollutants and the CHAP dataset and provide a new method for verifying the accuracy and completeness of China's civil aviation emission inventory.

Exposure to Smoke From Wildfire, Prescribed, and Agricultural Burns Among At-Risk Populations Across Washington, Oregon, and California.

Wildfires, prescribed burns, and agricultural burns all impact ambient air quality across the Western U.S.; however, little is known about how communities across the region are differentially exposed to smoke from each of these fire types. To address this gap, we quantify smoke exposure stemming from wildfire, prescribed, and agricultural burns across Washington, Oregon, and California from 2014 to 2020 using a fire type-specific biomass burning emissions inventory and the GEOS-Chem chemical transport model. We examine fire type-specific PM2.5 concentration by race/ethnicity, socioeconomic status, and in relation to the Center for Disease Control's Social Vulnerability Index. Overall, population-weightedPM2.5 concentrations are greater from wildfires than from prescribed and from agricultural burns. While we found limited evidence of exposure disparities among sub-groups across the full study area, we did observe disproportionately higher exposures to wildfire-specific PM2.5 exposures among Native communities in all three states and, in California, higher agricultural burn-specific PM2.5 exposures among lower socioeconomic groups. We also identified, for all three states, areas of significant spatial clustering of smoke exposures from all fire types and increased social vulnerability. These results provide a first look at the differential contributions of smoke from wildfires, prescribed burns, and agricultural burns to PM2.5 exposures among demographic subgroups, which can be used to inform more tailored exposure reduction strategies across sources.

Measuring the Health Co-Benefits of Air Pollution Interventions on Premature Deaths in Canadian Cities

Background: Climate change has significant consequences on human health. Cities are especially vulnerable, where air pollution is a major environmental health risk. Premature mortality (i.e., deaths before age 75) is a robust population health outcome amenable to targeted policy and programmatic interventions. We used the Premature Mortality Population Risk Tool augmented with environmental data (PreMPoRT-ENV) to predict the 5-year incidence of premature deaths under air pollution reduction policies. Methods: PreMPoRT-ENV is a sex-specific Weibull accelerated failure time survival model that uses the Canadian Community Health Survey (CCHS) linked to the Canadian Vital Statistics Death Database and environmental data. We applied PreMPoRT-ENV to the 2016–2017 CCHS cycles and simulated Canadian Ambient Air Quality Standards targets to predict their impact on premature mortality across Canadian census metropolitan areas. We simulated capping annual mean particulate matter 2.5 microns or less in diameter (PM2.5) and nitrogen dioxide (NO2), as well as reducing air pollutants by 10% and 25% plus capping. Results: The weighted sample included 9,240,000 females and 9,260,000 males. Capping PM2.5 to 8.8 μg/m3 and NO2 to 12.0 ppb resulted in 12 per 100,000 fewer predicted premature deaths than observed exposures over 5 years (1,110 fewer absolute premature deaths). Reducing air pollutants by 10% and 25% plus capping resulted in even fewer predicted premature deaths. Conclusion: Our study highlights how to use a model that predicts premature mortality to provide estimates of the health impacts of environmental vulnerabilities. Results suggest that more aggressive targets may be needed to further realize population health benefits.

Ambient Air Quality Assessment in the Limestone Mining Area of Ponjong District, Gunung Kidul, Indonesia

Limestone, a non-metallic industrial mineral, is abundantly found across Indonesia. The extraction process involves overburden removal, limestone breaking using rock breakers, loading onto dump trucks with excavators, stockpiling, and subsequent processing. These activities can negatively impact the environment, particularly air quality. To evaluate the ambient air quality in the mining area, measurements were taken focusing on hazardous substances such as SO2, CO, NO2, O3, and Total Suspended Particles (TSP). This study aims to assess the ambient air quality within the limestone mining area. Results indicate that the ambient air quality in the mining area is relatively good, with no parameters exceeding established quality standards. Specifically, SO2 levels were 9.39 µg/m³, NO2 levels were 4.19 µg/m³, CO levels were 69.74 µg/m³, O3 levels were 24.90 µg/m³, and TSP levels were 133.26 µg/m³. For a more comprehensive assessment, it is recommended to conduct extended monitoring of these parameters to ensure the long-term air quality status for both the environment and the mine workers

Air and noise pollution analyses near oil and gas fields in the Mahakam Delta, Kalimantan, Indonesia

The Mahakam Delta is a strategic industrial area in East Kalimantan, Indonesia, in which oil and gas industries reduce ambient air quality and generate excessive noise. This research aimed to analyze the ambient air and noise pollution attributed to oil and gas production activities in the delta. Relevant parameters at five sampling points (UA-02 to UA-06) were measured and further analyzed in the laboratory, including total suspended particulate (TSP), SO2, Pb CO, NO2, O3, temperature, humidity, wind direction, wind speed, and noise. Indonesia’s air pollutant standard index (locally abbreviated as ISPU) with four parameters (CO, NO2, SO2, and O3) was used to determine the ambient air quality, and provisions written in the Decree of the Minister of Environment No. 50 Kep-48/MENLH/11/1996 were consulted for the noise quality assessment. Results showed ISPU values in the range of 0–50 at the five sampling points, suggesting good ambient air quality and compliance with Government Regulation No. 22 of 2021. In addition, it was revealed that the noise parameter was lower than the upper threshold set in the Ministerial Decree, namely 65 dB. Nevertheless, monitoring air and noise quality at the main pollutant sources should be regulated through policies and implemented to protect the public from exposure to potential pollutants.