Sources and aging of individual atmospheric particles in New York City: Integrating novel functional group data from optical photothermal spectroscopy with elemental and mass spectrometry data.

Air quality changes in New York City during the COVID-19 pandemic

The New York City (NYC) subway system accommodates 5.5 million daily commuters, and the environment within the subway is known to have high concentrations of fine particulate matter (PM2.5) pollution. Naturally, subway air pollution varies among individuals according to their mobility patterns, introducing the possibility of inequality in PM2.5 exposure. This study aims to evaluate individual and community-level exposure to subway PM2.5. We simulated the intracity home-to-work trip patterns using the Longitudinal Employer-Household Dynamics (LEHD) records of 3.1 million working commuters across 34,169 census blocks in four boroughs (Manhattan, Brooklyn, Queens, and the Bronx) of NYC. We incorporated the on-platform and on-train measured PM2.5 concentration data for the entire subway system. The mean underground platform concentration in the city was 139 μg/m3 with a standard deviation of 25 μg/m3, while the on-train concentration when underground was 99 μg/m3 with a standard deviation of 21 μg/m3. Using a network model, we determined the exposure of individual commuters during their daily home-work trips. We quantified the mean per capita exposure at the census block level by considering the proportion of workers within the blocks who rely on the subway for their work commute. Results indicate statistically significant weak positive correlation between elevated subway PM2.5 exposure and economically disadvantaged and racial minority groups.

Spatial and temporal variations in traffic-related particulate matter at New York City high schools

Assessment of the health benefits to children of a transportation climate policy in New York City

Fine particulate matter entering the body through breathing cause serious damage to humans. In South Korea, filter-type air purifiers are used to eliminate indoor fine particulate matter, and there has been a broad range of studies on the spread of fine particulate matter and air purifiers. However, earlier studies have not evaluated an operating method of air purifiers considering the inflow of fine particulate matter into the body or reduction performance of the concentration of fine particulate matter. There is a limit to controlling the concentration of fine particulate matter of the overall space where an air purifier is fixed in one spot as the source of indoor fine particulate matter is varied. Accordingly, this study analyzed changes in the concentration of indoor fine particulate matter through an experiment according to the discharging method and location of a fixed air purifier considering the inflow route of fine particulate matter into the body and their harmfulness. The study evaluated the purifiers’ performance in reducing the concentration of fine particulate matter in the occupants’ breathing zone according to the operation method in which a movable air purifier responds to the movement of occupants. The results showed the concentration of fine particulate matter around the breathing zone of the occupants had decreased by about 51 μg/m3 compared to the surrounding concentration in terms of the operating method in which an air purifier tracks occupants in real-time, and a decrease of about 68 μg/m3 in terms of the operating method in which an air purifier controls the zone. On the other hand, a real-time occupant tracking method may face a threshold due to the moving path of an air purifier and changes in the number of occupants. A zone controlling method is deemed suitable as an operating method of a movable air purifier to reduce the concentration of fine particulate matter in the breathing zone of occupants.

Detection and genetic characterization of community-based SARS-CoV-2 infections – New York City, March 2020

Air pollution represents the most significant environmental health risk in Europe, which significantly impacts the health of the European population, especially in urban areas. The pollutants with the most critical threat to human health in European urban areas include fine particulate matter (PM), a mixture of aerosols with an aerodynamic diameter less or equal to 2.5 μm. To better understand the composition of fine PM in any urban area of Europe, it is important to identify and quantify the sources of its components. Such knowledge can be further used to propose effective strategies for reducing this type of pollution in this urban area. One of the commonly used ways to source attribution analysis of fine PM is to use sophisticated chemical transport models that can rigorously control: (1) the evolution of primary fine PM, (2) the formation of secondary inorganic and organic fine PM from gaseous precursors and their subsequent development, and (3) aqueous aerosol chemistry (e.i., all relevant processes connected with fine PM).   In this work, we utilized an offline coupled modeling framework consisting of the Weather Research and Forecast (WRF) Model version 4.0.3 and the Comprehensive Air quality Model with Extensions (CAMx) version 7.10 on the Central European domain with a horizontal resolution of 9 km for the period covering the years 2018 and 2019 to investigate the relationships between emissions from a wide range of anthropogenic activity sectors and the total concentrations of fine PM in six large cities of this region (Berlin, Munich, Prague, Vienna, Budapest, and Warsaw) from two different approaches. First, we analyzed the contributions of emissions from anthropogenic activity sectors to the total concentrations of fine PM using the Particulate Source Apportionment Technology (PSAT) tool implemented in the used version of the CAMx model. Second, using the zero-out method, we examined the impacts of emissions from the same anthropogenic activity sectors used in the source apportionment analysis on the total concentrations of fine PM. In this case, we additionally considered a dual implementation of organic aerosol chemistry/partitioning in the CAMx model by performing two sensitivity studies determining the impacts described above, each using one of the implementations. As part of the analysis, we compared the identified contributions with the impacts and discussed cases of mutual similarity between the two approaches.

The purpose of the present work is to present results from a measuring campaign during February-March 2020, in Galati city, Romania, aiming the concentration of fine particulate matter (PM2.5) in air and their heavy metal concentrations, then comparing the results with the air quality determined by the national monitoring system from the same city. Results show considerable differences concerning the air quality measured in this study compared with measurements of the national monitoring system that consist in four stations placed across the city. While values recorded in this study exceeded, in some situations, the maximum target from PM2.5, the reports from the national monitoring system presented a good air quality, using a colour- and number-coding (maximum level 4 out of 6 was reported). Heavy metal concentrations of the fine particulate matters collected in this study was compared with other studies across the world, high Fe and Zn values being registered in agglomerated and industrialized cities, including the city considered in the present study, while in a study conducted in Beijing, China most higher values between all analysed heavy metals were recorded.

Version 1 of the NASA MERRA Aerosol Reanalysis (MERRAero) assimilates bias-corrected aerosol optical depth (AOD) data from MODIS-Terra and MODIS-Aqua, and simulates particulate matter (PM) concentration data to reproduce a consistent database of AOD and PM concentration around the world from 2002 to the end of 2015. The purpose of this paper is to evaluate MERRAero's simulation of fine PM concentration against surface measurements in two regions of the world with relatively high levels of PM concentration but with profoundly different PM composition, those of Israel and Taiwan. Being surrounded by major deserts, Israel's PM load is characterized by a significant contribution of mineral dust, and secondary contributions of sea salt particles, given its proximity to the Mediterranean Sea, and sulfate particles originating from Israel's own urban activities and transported from Europe. Taiwan's PM load is composed primarily of anthropogenic particles (sulfate, nitrate and carbonaceous particles) locally produced or transported from China, with an additional contribution of springtime transport of mineral dust originating from Chinese and Mongolian deserts. The evaluation in Israel produced favorable results with MERRAero slightly overestimating measurements by 6% on average and reproducing an excellent year-to-year and seasonal fluctuation. The evaluation in Taiwan was less favorable with MERRAero underestimating measurements by 42% on average. Two likely reasons explain this discrepancy: emissions of anthropogenic PM and their precursors are largely uncertain in China, and MERRAero doesn't include nitrate particles in its simulation, a pollutant of predominately anthropogenic sources. MERRAero nevertheless simulates well the concentration of fine PM during the summer, when Taiwan is least affected by the advection of pollution from China.

Impact of local traffic exclusion on near-road air quality: Findings from the New York City “Summer Streets” campaign

Ambient pollutant concentrations measured by a mobile laboratory in South Bronx, NY

Recent experience from Hurricane Sandy and high-temperature episodes has clearly demonstrated that the health of New Yorkers can be compromised by extreme coastal storms and heat events. Health impacts that can result from exposure to extreme weather events include direct loss of life, increases in respiratory and cardiovascular diseases, and compromised mental health. Other related health stressors—such as air pollution, pollen, and vector-borne, water-borne, and food-borne diseases—can also be influenced by weather and climate. Figure 5.1 illustrates the complex pathways linking extreme weather events to adverse health outcomes in New York City. New York City and the surrounding metropolitan region face potential health risks related to two principal climate hazards: (1) increasing temperatures and heat waves, and (2) coastal storms and flooding. The health impacts of these hazards depend in turn on myriad pathways, the most important of which are illustrated in the figure. Figure 5.1 Pathways linking climate hazards to health impacts in New York City. Although New York City is one of the best-prepared and most climate-resilient cities in the world, there remain significant potential vulnerabilities related to climate variability and change. As part of the NPCC2 process, a team of local climate and health specialists was mobilized to assess current vulnerabilities and to identify strategies that could enhance the resilience of New York City to adverse health impacts from climate events. The goal was to highlight some of the important climate-related health challenges that New York City is currently facing or may face in the future due to climate variability and change, based on emerging scientific understanding. As indicated in Figure 5.1, health vulnerabilities can be magnified when critical infrastructure is compromised. Critical infrastructure is a highly complex, heterogeneous, and interdependent mix of facilities, systems, and functions that are vulnerable to a wide variety of threats, including extreme weather events. For example, delivery of electricity to households depends on a multi-faceted electrical grid system that is susceptible to blackouts that can occur during heat waves. These, in turn, can expose people to greater risk of contact with exposed wires or to greater heat stress due to failure of air conditioning. Understanding and predicting the impacts that extreme weather events may have on health in New York City require careful analysis of these interactions. Two recent plans to enhance climate resiliency in New York City have been released. A Stronger, More Resilient New York (City of New York, 2013) was developed in the aftermath of Hurricane Sandy by a task force of representatives from City agencies and consultants. This plan was informed by a detailed analysis of the impacts of Hurricane Sandy on infrastructure and the built environment and by the NPCC’s updated 2013 climate projections for the New York metropolitan region. It includes more than 250 initiatives and actionable recommendations addressing 14 domains of the built environment and infrastructure including the healthcare system and several other domains relevant to protecting public health. In addition, the 2014 New York City Hazard Mitigation Plan (HMP) (City of New York, 2014), developed by the NYC Office of Emergency Management in collaboration with the Department of City Planning, updated the 2009 HMP and assesses risks from multiple hazards that threaten New York City. These include but are not limited to several climate-related hazards such as coastal storms and heat waves, and it lays out comprehensive strategies and plans to address these hazards. Many of the measures recommended by A Stronger, More Resilient New York and the HMP have already been implemented, are in progress, or are planned (City of New York, 2013; 2014). This chapter does not include a detailed review of these plans, which would be beyond the expertise and charge of the contributors. Nonetheless, the recommendations in this chapter do broadly support the plans laid out in A Stronger, More Resilient New York and the 2014 HMP, and these are referenced at several points where they are especially relevant. Here we focus on summarizing and synthesizing the emerging scientific knowledge on climate-related health hazards, knowledge that can inform ongoing preparedness planning. Key terms related to climate variability and change as they are applied in the health sector are defined in Box 5.1. This is followed by sections describing health risks, vulnerabilities, and resilience strategies for coastal storms and extreme heat events. We then briefly discuss the interactions of climate change with air pollution, pollen, vector-borne diseases, and water- and food-borne diseases. We conclude with recommendations for research and resiliency planning. Box 5.1 Definitions of key cross-cutting terms in the health context Adaptation Initiatives and measures to reduce the vulnerability of natural and human systems against actual or expected climate change effects. Various types of adaptation exist, such as anticipatory and reactive, private and public, and autonomous and planned. For health, physiological adaptation is also relevant.

The purpose of this study was to survey the seasonal variation of fine particulate matter (PM2.5) concentration and determine spatial distribution in Darkhan city. Air pollution research and reports have been few and far between in most of parts in Mongolia, especially in Darkhan with respect to quantitative aerosol particle concentration. In this study, we utilized “PM2.5sensor” to measure spatial and seasonal variation of particulate matter concentrations in the study area. The monitoring points were chosen by basing on their specific features and set up directly at ambience outdoor. In each season, we carried out measurement at 3 points, which covered the ger district and apartment district areas for one day. Whereas, at one point the ger district was sampled for 4 days in summer. Fine particulate matter concentrations were the highest in the ger district area because there are many households that use coal for their daily heating and cooking, and at the bared surface. As for seasonal variation, in winter pollution reached 400 times higher than other seasons. Furthermore, at the ger district area, PM2.5 concentration was as much as 20 times greater than other points and it was observed that this too had its impact on the apartment district as well. As regards the air quality index, the level of particulate matter in the ger district area is extremely unhealthy to hazardous in winter. While, good and moderate indexes were mostly identified at monitoring points during the springtime.

WM2-O-06 Introduction: Few studies have investigated the composition of particulate matter (PM) in indoor microenvieonments and for personal exposures. Two COPD panel studies were conducted in New York City (NYC) and Seattle to characterize the interrelationship among outdoor, indoor and personal PM concentrations. Methods: In the NYC panel, subjects were followed for 12 consecutive days both in a summer and a winter season (July 2000 to January 2001), while in the Seattle panel, subjects were followed in a winter season (October 2002 to March 2003). Concentrations of PM10 and PM2.5 at their residential outdoor, their residential indoor, a central-monitoring-site, and at their personal breathing zones were measured during 24 hours each day. Elemental composition of the PM samples were measured using x-ray fluorescence (XRF), and elemental carbon contents were estimated using reflectance measurements. Indoor-outdoor-personal concentration correlations were investigated. Multivariate factor analysis-based source apportionment techniques were applied to identify contributing sources each day. Results: For NYC, 176 personal and 366 indoor-outdoor paired PM samples were collected from 9 subjects; for Seattle, 142 personal and 320 indoor-outdoor paired PM samples were collected from 15 subjects. Personal PM10 mass concentrations were 2 times higher for the NYC cohort than for the Seattle cohort (71.4, 52.9, and 23.3 μg/m3, for NYC summer, NYC winter and Seattle winter, respectively). Considerable intersubject variability of the indoor-outdoor correlations were found by season and by geographic locations (r = −0.4 to 0.9, r = 0.1 to 0.7, and r = 0 to 0.9, for NYC summer, NYC winter, and Seattle winter, respectively). In NYC, the identified outdoor sources included soil, oil combustion, transported aerosol, and incineration. In Seattle, soil, marine aerosol, and wood combustion were identified outdoors. In both cities, indoor PM was influenced by outdoor sources, such as oil combustion, and by personal activity sources, such as aerosol generated from inhalation therapy. Discussion: We found different outdoor sources in NYC and Seattle, and indoor PM was associated with outdoor sources and personal activities. The preliminary results suggest that using elemental contents data can provide better characterization of interrelationships of outdoor, indoor, and personal PM concentrations. The detailed quantitative contribution of each source to total PM mass and the contribution of outdoor and indoor sources to personal exposure, and their interrelationships at each city, will be presented at the meeting.

The 2015 New York City Legionnaires' Disease Outbreak: A Case Study on a History-Making Outbreak.