Non-residential Locations Research Articles

Determinants of Aedes mosquito larval ecology in a heterogeneous urban environment- a longitudinal study in Bengaluru, India.

Aedes-borne disease risk is associated with contemporary urbanization practices where city developing structures function as a catalyst for creating mosquito breeding habitats. We lack better understanding on how the links between landscape ecology and urban geography contribute to the prevalence and abundance of mosquito and pathogen spread. An outdoor longitudinal study in Bengaluru (Karnataka, India) was conducted between February 2021 and June 2022 to examine the effects of macrohabitat types on the diversity and distribution of larval habitats, mosquito species composition, and body size to quantify the risk of dengue outbreak in the landscape context. A total of 8,717 container breeding sites were inspected, of these 1,316 were wet breeding habitats. A total of 1,619 mosquito larvae representing 16 species from six macrohabitats and nine microhabitats were collected. Aedes aegypti and Aedes albopictus were the dominant species and significantly higher in artificial habitats than in natural habitats. Breeding preference ratio for Aedes species was high in grinding stones and storage containers. The Aedes infestation indices were higher than the WHO threshold and showed significant linear increase from Barren habitat to High density areas. We found Ae. albopictus breeding in sympatry with Ae. aegypti had shorter wing length. A large proportion of larval habitats were man-made artificial containers. Landscape ecology drives mosquito diversity and abundance even at a small spatial scale which could be affecting the localized outbreaks. Our findings showed that sampling strategies for mosquito surveillance must include urban environments with non-residential locations and dengue transmission reduction programmes should focus on 'neighbourhood surveillance' as well to prevent and control the rising threat of Aedes-borne diseases.

Effect of location on out-of-hospital cardiac arrests involving older adults in Hong Kong: secondary analysis of a territory-wide cohort.

Most out-of-hospital cardiac arrests in Hong Kong involve older adults. The likelihood of survival varies among locations. This study investigated patient and bystander characteristics, as well as the timing of interventions, that affect the prevalences of shockable rhythm and survival outcomes among cardiac arrests involving older adults in homes, on streets, and in other public places. This secondary analysis of a territory-wide historical cohort used data collected by the Fire Services Department of Hong Kong from 1 August 2012 to 31 July 2013. Bystander cardiopulmonary resuscitation was primarily performed by relatives in homes but not in non-residential locations. The intervals in terms of receipt of emergency medical services (EMS) call, initiation of bystander cardiopulmonary resuscitation, and receipt of defibrillation were longer for cardiac arrests that occurred in homes. The median interval for EMS to reach patients was 3 minutes longer in homes than on streets (P<0.001). Forty-seven percent of patients who developed cardiac arrest on streets had a shockable rhythm within the first 5 minutes after receipt of EMS call. Defibrillation within 15 minutes after receipt of EMS call was an independent predictor of 30-day survival (odds ratio=4.07; P=0.02). Fifty percent of patients who received defibrillation within 5 minutes in non-residential locations survived. There were significant location-related differences in patient and bystander characteristics, interventions, and outcomes among cardiac arrests involving older adults. A large proportion of patients had a shockable rhythm in the early period after cardiac arrest. Good survival outcomes in out-of-hospital cardiac arrests involving older adults can be achieved through early bystander defibrillation and intervention.

Analysis of the Spatial Distribution and Associated Factors of the Transmission Locations of COVID-19 in the First Four Waves in Hong Kong

Understanding the space–time pattern of the transmission locations of COVID-19, as well as the relationship between the pattern, socioeconomic status, and environmental factors, is important for pandemic prevention. Most existing research mainly analyzes the locations resided in or visited by COVID-19 cases, while few studies have been undertaken on the space–time pattern of the locations at which the transmissions took place and its associated influencing factors. To fill this gap, this study focuses on the space–time distribution patterns of COVID-19 transmission locations and the association between such patterns and urban factors. With Hong Kong as the study area, transmission chains of the four waves of COVID-19 outbreak in Hong Kong during the time period of January 2020 to June 2021 were reconstructed from the collected case information, and then the locations of COVID-19 transmission were inferred from the transmission chains. Statistically significant clusters of COVID-19 transmission locations at the level of tertiary planning units (TPUs) were detected and compared among different waves of COVID-19 outbreak. The high-risk areas and the associated influencing factors of different waves were also investigated. The results indicate that COVID-19 transmission began with the Hong Kong Island, further moved northward towards the New Territories, and finally shifted to the south Hong Kong Island, and the transmission population shows a difference between residential locations and non-residential locations. The research results can provide health authorities and policy-makers with useful information for pandemic prevention, as well as serve as a guide to the public in the avoidance of activities and places with a high risk of contagion.

Changes in ambulance departures for assault calls during COVID-19 pandemic restrictions.

Restrictions related to COVID-19 changed the daily behavior of people, including the expression of violence. Although an increased incidence of violent behavior, especially domestic violence, was expected during the pandemic, retrospective analyses have yielded mixed results. Records of ambulance departures to address injuries caused by assaults in the Pilsen region, Czech Republic, during the restrictive measures during the national state of emergency were compared to data from 3 previous years using general linear models. The number and severity of assaults were analyzed for the whole sample and separately for patients of either sex, for residential or nonresidential locations, and for domestic violence. Controlling for the seasonal effects, the number of assaults decreased by 39% during the pandemic restrictions compared to the 3 previous years. No difference was found between the effects of restrictions on assaults resulting in an injury of a male or female patient. The decrease was specifically pronounced in the sample of assaults in nonresidential locations, while no effect of restrictions was observed in assaults in residential locations and domestic assaults. Pandemic restrictions were associated with a decreased incidence of violent assaults that required ambulance services. Although the incidence decreased especially in those assaulted outside of their homes, we found no support for an increase in domestic violence or violence against women. Pandemic restrictions may have served as a protective rather than a risk factor for assaults severe enough to warrant a call for ambulance services.

Modeling a time-differentiated policy for management of loading bays in urban areas

A model is introduced to optimally locate loading bays in an urban environment according to the demand for deliveries at various categories of non-residential locations and to assist policymakers in implementing this solution and explicitly assessing the associated costs and benefits. This model allows flexibility to consider loading bays with varying capacities, considers the capacity of each bay in terms of occupancy time including driver walking time between bay and delivery destination, and chooses from among a specified set of candidate locations for bays. The model formulation allows for selective non-allocation of loading bays in the case that the cost of urban land-use outweighs the cost of traffic disruption according to the level of ambient traffic observed, the probability of the delivery driver successfully finding on-street parking at the destination, and a baseline sensitivity factor specified by the policymaker.

Face mask mandates and risk compensation: an analysis of mobility data during the COVID-19 pandemic in Bangladesh

IntroductionConcerns have been raised about the potential for risk compensation in the context of mask mandates for mitigating the spread of COVID-19. However, the debate about the presence or absence...

Spatial Errors in Automated Geocoding of Incident Locations in Australian Suicide Mortality Data.

There is increasing interest in the spatial analysis of suicide data to identify high-risk (often public) locations likely to benefit from access restriction measures. The identification of such locations, however, relies on accurately geocoded data. This study aims to examine the extent to which common completeness and positional spatial errors are present in suicide data due to the underlying geocoding process. Using Australian suicide mortality data from the National Coronial Information System for the period of 2008-2017, we compared the custodian automated geocoding process to an alternate multiphase process. Descriptive and kernel density cluster analyses were conducted to ascertain data completeness (address matching rates) and positional accuracy (distance revised) differences between the two datasets. The alternate geocoding process initially improved address matching from 67.8% in the custodian dataset to 78.4%. Additional manual identification of nonaddress features (such as cliffs or bridges) improved overall match rates to 94.6%. Nearly half (49.2%) of nonresidential suicide locations were revised more than 1,000 m from data custodian coordinates. Spatial misattribution rates were greatest at the smallest levels of geography. Kernel density maps showed clear misidentification of hotspots relying solely on autogeocoded data. Suicide incidents that occur at nonresidential addresses are being erroneously geocoded to centralized fall-back locations in autogeocoding processes, which can lead to misidentification of suicide clusters. Our findings provide insights toward defining the nature of the problem and refining geocoding processes, so that suicide data can be used reliably for the detection of suicide hotspots. See video abstract at, http://links.lww.com/EDE/B862.

Valuing transport noise impacts in public urban spaces in the UK: Gaps, opportunities and challenges

Transport noise is the dominant noise source in urban areas. Its impacts on people at their residential locations are included in economic appraisal in the UK and many other countries, and guidance and analysis tools were developed for the valuation of the impacts. However, for transport noise impacts on people in public urban spaces, e.g., urban streets, squares and parks, there is still a lack of national methodologies. This paper will discuss the gaps, opportunities and challenges in developing a national methodology for these places in the UK. Currently, evidence is lacking on pathways of transport noise impact on people and dose–response relationships at non-residential locations, and the values people place on sound environment quality at these locations. However, opportunities are emerging, with increasing attention to the urban realm in UK transport policy, and recent progress and transitions in urban sound environment research, including association between public health and urban soundscape, standardisation in soundscape research and practice, and crowdsourcing sound environment evaluations. The associated challenges, as compared to methodology for residential locations, may include calculating noise from non-free-flow traffic, defining and adding diverse receptor types, estimating dynamic affected population, accounting for diversity in level and source of background sound, and obtaining large and consistent data for dose–response or willingness-to-pay analyses.

Intergenerational photovoice perspectives of place and health in public housing: Participatory coding, theming, and mapping in/of the "structure struggle".

This paper details an intergenerational photovoice project exploring spatial and perceptual differences of "place" and health among adult and youth public housing residents in a small urban rustbelt city in the Midwestern United States. It specifically highlights the value of fully participatory photovoice processes-participatory narrative-coding and digital web-based photo-mapping-in furthering conceptual and analytical understanding of "place" and health. Results indicate the critical import of accounting for non-residential locations (i.e. activity spaces), and the significance of engaging the generationally- and spatially-specific social and physical landscapes of residents' lived "place" to improve health opportunities within place-based strategies involving public housing.

Activity spaces of men who have sex with men: An initial exploration of geographic variation in locations of routine, potential sexual risk, and prevention behaviors

Theory and research on HIV and among men who have sex with men (MSM) have long suggested the importance of non-residential locations in defining structural exposures. Despite this, most studies within these fields define place as a residential context, neglecting the potential influence of non-residential locations on HIV-related outcomes. The concept of activity spaces, defined as a set of locations to which an individual is routinely exposed, represents one theoretical basis for addressing this potential imbalance. Using a one-time online survey to collect demographic, behavioral, and spatial data from MSM, this paper describes activity spaces and examines correlates of this spatial variation. We used latent class analysis to identify categories of activity spaces using spatial data on home, routine, potential sexual risk, and HIV prevention locations. We then assessed individual and area-level covariates for their associations with these categories. Classes were distinguished by the degree of spatial variation in routine and prevention behaviors (which were the same within each class) and in sexual risk behaviors (i.e., sex locations and locations of meeting sex partners). Partner type (e.g. casual or main) represented a key correlate of the activity space. In this early examination of activity spaces in an online sample of MSM, patterns of spatial behavior represent further evidence of significant spatial variation in locations of routine, potential HIV sexual risk, and HIV prevention behaviors among MSM. Although prevention behaviors tend to have similar geographic variation as routine behaviors, locations where men engage in potentially high-risk behaviors may be more spatially focused for some MSM than for others.

Personal Air Pollution Monitoring in the MADRES Cohort of Pregnant Women: Challenges and Lessons Learned

Introduction: Increasing rates of maternal overweight and obesity before, during and after pregnancy pose serious health concerns for both mothers and children. In California, childbearing women from disadvantaged minority and low-income groups are disproportionately exposed to multiple environmental chemicals. Urban air pollution is a ubiquitous exposure that has been implicated in the pathogenesis of obesity, diabetes and related metabolic and cardiovascular disease. Most air pollution studies assign exposures based on residential location. Methods: Given that pregnant women may regularly travel to non-residential locations, we propose to use a personal exposure assessment approach that includes time-activity patterns in key microenvironments to reduce exposure measurement error in Project 2 of the recently established “Maternal and Developmental Risks from Environmental and Social Stressors” (MADRES) pregnancy cohort. Personal PM2.5 monitoring is currently being conducted using a microPEM, along with GPS, tri-axis accelerometry and Ecological Momentary Assessment (EMA) prompts on smartphones to capture geolocation, physical activity, and context-specific information, respectively, in 60 low income, predominantly Hispanic women living in East Los Angeles. Results: Data will be presented to illustrate and describe main challenges encountered in pilot testing, in terms of developing algorithms for evaluating participant compliance using a combination of sensors and self-report tools. Lessons learned for ensuring data quality while optimizing battery life and reducing participant burden will be presented. Conclusions: Recent advances in sensor technologies are making personal exposure assessment in health studies more feasible, presenting unique opportunities for capturing key contextual information and reducing exposure measurement error in personal exposure models.

Completeness and Reliability of Location Data Collected on the Web: Assessing the Quality of Self-Reported Locations in an Internet Sample of Men Who Have Sex With Men.

BackgroundPlace is critical to our understanding of human immunodeficiency virus (HIV) infections among men who have sex with men (MSM) in the United States. However, within the scientific literature, place is almost always represented by residential location, suggesting a fundamental assumption of equivalency between neighborhood of residence, place of risk, and place of prevention. However, the locations of behaviors among MSM show significant spatial variation, and theory has posited the importance of nonresidential contextual exposures. This focus on residential locations has been at least partially necessitated by the difficulties in collecting detailed geolocated data required to explore nonresidential locations.ObjectiveUsing a Web-based map tool to collect locations, which may be relevant to the daily lives and health behaviors of MSM, this study examines the completeness and reliability of the collected data.MethodsMSM were recruited on the Web and completed a Web-based survey. Within this survey, men used a map tool embedded within a question to indicate their homes and multiple nonresidential locations, including those representing work, sex, socialization, physician, and others. We assessed data quality by examining data completeness and reliability. We used logistic regression to identify demographic, contextual, and location-specific predictors of answering all eligible map questions and answering specific map questions. We assessed data reliability by comparing selected locations with other participant-reported data.ResultsOf 247 men completing the survey, 167 (67.6%) answered the entire set of eligible map questions. Most participants (>80%) answered specific map questions, with sex locations being the least reported (80.6%). Participants with no college education were less likely than those with a college education to answer all map questions (prevalence ratio, 0.4; 95% CI, 0.2-0.8). Participants who reported sex at their partner’s home were less likely to indicate the location of that sex (prevalence ratio, 0.8; 95% CI, 0.7-1.0). Overall, 83% of participants placed their home’s location within the boundaries of their reported residential ZIP code. Of locations having a specific text description, the median distance between the participant-selected location and the location determined using the specific text description was 0.29 miles (25th and 75th percentiles, 0.06-0.88).ConclusionsUsing this Web-based map tool, this Web-based sample of MSM was generally willing and able to provide accurate data regarding both home and nonresidential locations. This tool provides a mechanism to collect data that can be used in more nuanced studies of place and sexual risk and preventive behaviors of MSM.

Built environmental correlates of physical activity in China: A review

ObjectiveChina faces growing levels of physical inactivity and obesity, associated with increasing urbanization and changing lifestyles in recent years. China is expanding its cities to accommodate a growing urban population. This paper identifies built environment factors that are associated with physical activity in China. Findings can inform urban design and development in China to support increased physical activity.MethodsThis paper is modeled on a review of built environment correlates of walking by Saelens and Handy (2008). Saelens and Handy reviewed research in developed countries. The present paper reviews 42 empirical studies that were conducted in China and were published between 2006 and 2014.ResultsResults discuss the association of built environment features and physical activity for transportation, recreation and work. Studies focus on adults and on major cities. Data on the built environment is typically self-reported. Strongest evidence was found for the positive association of physical activity with proximal non-residential locations, pedestrian infrastructure, aesthetics, and non-park physical activity facilities, and for the negative association of physical activity with urban residence. In terms of physical activity for transportation, evidence is strongest for associations between physical activity for transportation and proximal non-residential locations.ConclusionMore research is needed on the built environment and physical activity, especially including research on significant features of Chinese cities, such as air pollution, high density levels, traffic safety, and others. Research on associations between built environment features and physical activity should consider the specific social and built environment contexts of Chinese cities.

Curating Transient Population in Urban Dynamics System

GIScience 2016 Short Paper Proceedings Curating Transient Population in Urban Dynamics System Gautam S. Thakur, Kevin A. Sparks, Robert N. Stewart, Marie L. Urban, Budhendra L. Bhaduri The Geographic Information Science and Technology (GIST) Group Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831 USA Email: {thakurg, sparksa, stewartrn, urbanml, bhaduribl}@ornl.gov Abstract Research efforts in population modelling has proven its efficacy in understanding the basic information about residential and commercial areas, as well as for the purposes of planning, development and improvement of the community as an eco-system. Limited by our current ability to capture the dynamics of population change at a finer resolution of space and time, more or less, such efforts assume static nature of population. Today, more and more people are becoming mobile, traveling across borders impacting the nuts and bolts of our urban fabric. Unfortunately, our current efforts are being surpassed by the need to capture such transient population. It is becoming imperative to identify and define them, as well as measure their dynamics and interconnectedness. In this work, we intend to research urban population mobility patterns, gauge their transient nature, and extend our knowledge of their visited locations. We plan to achieve this by designing and developing novel methods and using VGI data that models and characterizes transient population dynamics. 1. Introduction Over the last decade, worldwide percentages of transient population i.e. population on-the- move have grown linearly, on account of socio-economic development and rising global conflicts (Worldbank 2016). Characterizing such movement patterns are vital to understand the dynamics of an urban system. Beyond that, privacy-preserved and discrete insight into the diurnal activities of people, where they are, where they go, and how much time they spent at certain locations is vital for first responders in times of emergencies, and for urban planners to develop robust future cities. Traditionally, approaches involved in curating such information have heavily relied on census data, surveys, and simulations models. While they provide an excellent source of baseline statistics - for logistical purposes, they rarely collect the spatio-temporal distribution relating to the dynamics of population movements. Furthermore, they omit non-residential locations, such as business districts, parks, and museums. Social media(Hawelka et al. 2014; Frias-Martinez et al. 2012), cellular data(Di Lorenzo & Calabrese 2011; Calabrese et al. 2010; Calabrese et al. 2011; Calabrese et al. 2013; Isaacman et al. 2012) have proved their efficacies in representing global patterns of human mobility. However, much of the current research has not focused on curating population distribution on a temporal scale (e.g. Census data focuses on residential or night time population). This work attempts to provide a set of guidelines that help infer the change in population numbers at different temporal scales. In this work, first we propose Transient Population Dynamics Model that attempts to describe and model the mobility patterns of active population. In addition, it provides approaches to identify and estimate transient population and aid in discovering new locations and the duration of their visits. Second, we utilize this model in estimating the transient population across Australia and compare the differences against respective census data. Also, we intend to discover frequently visited locations in outback and metropolitan areas. We believe this work will generate enthusiasm among researchers and make a case for the importance of curating transient population.

Estimating the benefits of electric vehicle smart charging at non-residential locations: A data-driven approach

In this paper, we use data collected from over 2000 non-residential electric vehicle supply equipments (EVSEs) located in Northern California for the year of 2013 to estimate the potential benefits of smart electric vehicle (EV) charging. We develop a smart charging framework to identify the benefits of non-residential EV charging to the load aggregators and the distribution grid. Using this extensive dataset, we aim to improve upon past studies focusing on the benefits of smart EV charging by relaxing the assumptions made in these studies regarding: (i) driving patterns, driver behavior and driver types; (ii) the scalability of a limited number of simulated vehicles to represent different load aggregation points in the power system with different customer characteristics; and (iii) the charging profile of EVs. First, we study the benefits of EV aggregations behind-the-meter, where a time-of-use pricing schema is used to understand the benefits to the owner when EV aggregations shift load from high cost periods to lower cost periods. For the year of 2013, we show a reduction of up to 24.8% in the monthly bill is possible. Then, following a similar aggregation strategy, we show that EV aggregations decrease their contribution to the system peak load by approximately 40% when charging is controlled within arrival and departure times. Our results also show that it could be expected to shift approximately 0.25kWh (~2.8%) of energy per non-residential EV charging session from peak periods (12PM-6PM) to off-peak periods (after 6PM) in Northern California for the year of 2013.

The relevance of commuter and work/school exposure in an epidemiological study on traffic-related air pollution.

Exposure during transport and at non-residential locations is ignored in most epidemiological studies of traffic-related air pollution. We investigated the impact of separately estimating NO2 long-term outdoor exposures at home, work/school, and while commuting on the association between this marker of exposure and potential health outcomes. We used spatially and temporally resolved commuter route data and model-based NO2 estimates of a population sample in Basel, Switzerland, to assign individual NO2-exposure estimates of increasing complexity, namely (1) home outdoor concentration; (2) time-weighted home and work/school concentrations; and (3) time-weighted concentration incorporating home, work/school and commute. On the basis of their covariance structure, we estimated the expectable relative differences in the regression slopes between a quantitative health outcome and our measures of individual NO2 exposure using a standard measurement error model. The traditional use of home outdoor NO2 alone indicated a 12% (95% CI: 11-14%) underestimation of related health effects as compared with integrating both home and work/school outdoor concentrations. Mean contribution of commuting to total weekly exposure was small (3.2%; range 0.1-13.5%). Thus, ignoring commute in the total population may not significantly underestimate health effects as compared with the model combining home and work/school. For individuals commuting between Basel-City and Basel-Country, ignoring commute may produce, however, a significant attenuation bias of 4% (95% CI: 4-5%). Our results illustrate the importance of including work/school locations in assessments of long-term exposures to traffic-related air pollutants such as NO2. Information on individuals' commuting behavior may further improve exposure estimates, especially for subjects having lengthy commutes along major transportation routes.

Impacts of travel activity and urbanicity on exposures to ambient oxides of nitrogen and on exposure disparities.

Daily exposures to ambient oxides of nitrogen were estimated here for residents of Hillsborough County, FL. The 2009 National Household Travel Survey provided geocoded data on fixed activity locations during each person-day sampled. Routes between activity locations were calculated from transportation network data, assuming the quickest travel path. To estimate daily exposure concentrations for each person-day, the exposure locations were matched with diurnally and spatially varying ambient pollutant concentrations derived from CALPUFF dispersion model results. The social distribution of exposures was analyzed by comparing frequency distributions of grouped daily exposure concentrations and by regression modeling. To investigate exposure error, the activity-based exposure estimates were also compared with estimates derived using residence location alone. The mean daily activity-based exposure concentration for the study sample was 17 μg/m3, with values for individual person-day records ranging from 7.0 to 43 μg/m3. The highest mean exposure concentrations were found for the following groups: black (20 μg/m3), below poverty (18 μg/m3), and urban residence location (22 μg/m3). Urban versus rural residence was associated with the largest increase in exposure concentration in the regression (8.3 μg/m3). Time in nonresidential activities, including travel, was associated with an increase of 0.2 μg/m3 per hour. Time spent travelling and at nonresidential locations contributed an average of 6 and 24 %, respectively, to the daily estimate. A mean error of 3.6 %, with range from −64 to 58 %, was found to result from using residence location alone. Exposure error was highest for those who travel most, but lowest for the sociodemographic subgroups with higher mean exposure concentrations (including blacks and those from below poverty households). This work indicates the importance of urbanicity to social disparities in activity-based air pollution exposures. It also suggests that exposure error due to using residence location may be smaller for more exposed groups.

Redistributive effects of bus rapid transit (BRT) on development patterns and property values in Seoul, Korea

This study investigates the redistributive effects of Seoul's bus rapid transit (BRT) system on development patterns and property values using an urban simulation model. The Seoul Metropolitan Integrated Urban Model (SMIUM) combines the Seoul metropolitan input–output model with random utility-based location choice models and endogenous real estate markets. The major findings of this study can be highlighted as follows. First, Seoul's BRT contributes to increased development density in urban centers, acting as a centripetal force to attract firms from the suburbs into urban cores and supporting arguments for Smart Growth proponents. Second, unlike its redistributive effects on nonresidential activities, the BRT has a limited effect on the redistribution of residential activities, implying that residential locations are less sensitive to accessibility improvements made by the BRT than are nonresidential locations. Third, reflecting the transferred space demands from the suburbs to the urban cores, the CBD reaps the highest property value gains, while all of the outer ring zones suffer from reduced property values.

Prenatal Exposure to Traffic-Related Air Pollution and Ultrasound Measures of Fetal Growth in the INMA Sabadell Cohort

BackgroundFew studies have used longitudinal ultrasound measurements to assess the effect of traffic-related air pollution on fetal growth.ObjectiveWe examined the relationship between exposure to nitrogen dioxide (NO2) and aromatic hydrocarbons [benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX)] on fetal growth assessed by 1,692 ultrasound measurements among 562 pregnant women from the Sabadell cohort of the Spanish INMA (Environment and Childhood) study.MethodsWe used temporally adjusted land-use regression models to estimate exposures to NO2 and BTEX. We fitted mixed-effects models to estimate longitudinal growth curves for femur length (FL), head circumference (HC), abdominal circumference (AC), biparietal diameter (BPD), and estimated fetal weight (EFW). Unconditional and conditional SD scores were calculated at 12, 20, and 32 weeks of gestation. Sensitivity analyses were performed considering time–activity patterns during pregnancy.ResultsExposure to BTEX from early pregnancy was negatively associated with growth in BPD during weeks 20–32. None of the other fetal growth parameters were associated with exposure to air pollution during pregnancy. When considering only women who spent < 2 hr/day in nonresidential outdoor locations, effect estimates were stronger and statistically significant for the association between NO2 and growth in HC during weeks 12–20 and growth in AC, BPD, and EFW during weeks 20–32.ConclusionsOur results lend some support to an effect of exposure to traffic-related air pollutants from early pregnancy on fetal growth during mid-pregnancy.

Optimizing the benefits of urban road user charging

Traffic congestion is a feature of most modern cities but attempts to control it or limit its effects have met with only modest success. There is significant and continuing interest in the concept of charging city vehicle users, although apart from the use of parking charges actual operational schemes are few and far between. In this paper, we compare three alternative charging policies using a simplified model of travel demand and supply, which we combine with cost benefit techniques. The charging policies are area-based charging in which users pay to locate in or enter an area, terminal-charging based on supplementary parking fees in residential and non-residential locations and distance-based charging which is a charge related to how far users travel. The model allows for behavioural effects resulting from trip diversion and demand suppression, as well as capacity restraint (speed-flow feedback effects based on limited route capacity). In the case study, we parameterize the model using data and geographical dimensions based on London. We show that area based charging delivers the least benefits whilst a hybrid policy based on terminal and distance-based charges delivers the most. Because it is of topical interest, we compare our results and predictions with the Mayor's strategy for London, which is an area-based scheme. We conclude that the revenue generated using a hybrid policy would be as great as for an area based scheme whilst at the same time delivering substantially greater benefits to road users in terms of travel time and other savings.