Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

Issues with ozone attainment methodology for Houston, TX

To comply with the federal 8-hr ozone standard, the state of Texas is creating a plan for Houston that strictly follows the U.S. Environmental Protection Agency's (EPA) guidance for demonstrating attainment. EPA's attainment guidance methodology has several key assumptions that are demonstrated to not be completely appropriate for the unique observed ozone conditions found in Houston. Houston's ozone violations at monitoring sites are realized as gradual hour-to-hour increases in ozone concentrations, or by large hourly ozone increases that exceed up to 100 parts per billion/hr. Given the time profiles at the violating monitors and those of nearby monitors, these large increases appear to be associated with small parcels of spatially limited plumes of high ozone in a lower background of urban ozone. Some of these high ozone parcels and plumes have been linked to a combination of unique wind conditions and episodic hydrocarbon emission events from the Houston Ship Channel. However, the regulatory air quality model (AQM) does not predict these sharp ozone gradients. Instead, the AQM predicts gradual hourly increases with broad regions of high ozone covering the entire Houston urban core. The AQM model performance can be partly attributed to EPA attainment guidance that prescribes the removal in the baseline model simulation of any episodic hydrocarbon emissions, thereby potentially removing any nontypical causes of ozone exceedances. This paper shows that attainment of all monitors is achieved when days with observed large hourly variability in ozone concentrations are filtered from attainment metrics. Thus, the modeling and observational data support a second unique cause for how ozone is formed in Houston, and the current EPA methodology addresses only one of these two causes.     

Temporal analysis of PM10 in Metropolitan Monterrey, México

The Monterrey Metropolitan Area (MMA) is the third largest city in Mexico. Few studies have been carried out regarding its air pollution. The aim of this study was to analyze the temporal behavior of PM10 (particulate matter < or =10 microm in aerodynamic diameter). Data reported by the "Sistema Integral de Monitoreo Ambiental" (Integrated Environmental Monitoring System) network from 2006 to 2008 were used. PM10 levels were compared among the stations by year, season, and day of week. A bootstrap technique was used to obtain subsamples to which Student's t test and ANOVA were applied. PM10 levels were high and exceeded the annual limit of 50 microg/m3 set up by the Mexican standard Norma Oficial Mexicana NOM-025-SSA1-1993. These levels could have serious health effects. The southwest zone of MMA had the highest levels of PM10 during the period studied. Winter was the most polluted season, and summer was the least polluted season. Thursday and Friday were the most polluted days, and Sunday was the least polluted day. The hours with the highest levels of PM10 were 8:00 to 10:00 a.m., whereas nighttime hours were the cleanest.     

Effect of fresh green waste and green waste compost on mineral nitrogen, nitrous oxide and carbon dioxide from a Vertisol

Incorporation of organic waste amendments to a horticultural soil, prior to expected risk periods, could immobilise mineral N, ultimately reducing nitrogen (N) losses as nitrous oxide (N₂O) and leaching. Two organic waste amendments were selected, a fresh green waste (FGW) and green waste compost (GWC) as they had suitable biochemical attributes to initiate N immobilisation into the microbial biomass and organic N forms. These characteristics include a high C:N ratio (FGW 44:1, GWC 35:1), low total N (<1%), and high lignin content (>14%). Both products were applied at 3 t C/ha to a high N (plus N fertiliser) or low N (no fertiliser addition) Vertisol soil in PVC columns. Cumulative N₂O production over the 28 day incubation from the control soil was 1.5 mg/N₂O/m², and 11 mg/N₂O/m² from the control + N. The N₂O emission decreased with GWC addition (P < 0.05) for the high N soil, reducing cumulative N₂O emissions by 38% by the conclusion of the incubation. Analysis of mineral N concentrations at 7, 14 and 28 days identified that both FGW and GWC induced microbial immobilisation of N in the first 7 days of incubation regardless of whether the soil environment was initially high or low in N; with the FGW immobilising up to 30% of available N. It is likely that the reduced mineral N due to N immobilisation led to a reduced substrate for N₂O production during the first week of the trial, when soil N₂O emissions peaked. An additional finding was that FGW + N did not decrease cumulative N₂O emissions compared to the control + N, potentially due to the fact that it stimulated microbial respiration resulting in anaerobic micro sites in the soil and ultimately N₂O production via denitrification. Therefore, both materials could be used as post harvest amendments in horticulture to minimise N loss through nitrate-N leaching in the risk periods between crop rotations. The mature GWC has potential to reduce N₂O, an important greenhouse gas.     

Targeted intervention strategies to optimise diversion of BMW in the Dublin, Ireland region

Urgent transformation is required in Ireland to divert biodegradable municipal waste (BMW) from landfill and prevent increases in overall waste generation. When BMW is optimally managed, it becomes a resource with value instead of an unwanted by-product requiring disposal. An analysis of survey responses from commercial and residential sectors for the Dublin region in previous research by the authors proved that attitudes towards and behaviour regarding municipal solid waste is spatially variable. This finding indicates that targeted intervention strategies designed for specific geographic areas should lead to improved diversion rates of BMW from landfill, a requirement of the Landfill Directive 1999/31/EC. In the research described in this paper, survey responses and GIS model predictions from previous research were the basis for goal setting, after which logic modelling and behavioural research were employed to develop site-specific waste management intervention strategies. The main strategies devised include (a) roll out of the Brown Bin (Organics) Collection and Community Workshops in Dún Laoghaire Rathdown, (b) initiation of a Community Composting Project in Dublin City (c) implementation of a Waste Promotion and Motivation Scheme in South Dublin (d) development and distribution of a Waste Booklet to promote waste reduction activities in Fingal (e) region wide distribution of a Waste Booklet to the commercial sector and (f) Greening Irish Pubs Initiative. Each of these strategies was devised after interviews with both the residential and commercial sectors to help make optimal waste management the norm for both sectors. Strategy (b), (e) and (f) are detailed in this paper. By integrating a human element into accepted waste management approaches, these strategies will make optimal waste behaviour easier to achieve. Ultimately this will help divert waste from landfill and improve waste management practice as a whole for the region. This method of devising targeted intervention strategies can be adapted for many other regions.     

Altered feeding preference of beech weevil Rhynchaenus fagi L. for beech foliage under ambient air pollution

The effect of ambient air pollution with increased ozone concentrations on the feeding behaviour of the beech weevil Rhynchaenus fagi L. was studied. In a dual choice feeding test the beech weevil preferred leaf disks from beech saplings exposed to ambient air against those from filtered air in 65.5% of all cases.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

How Good? Ethical Criteria for a ‘Good Life’ for Farm Animals

The Farm Animal Welfare Council’s concept of a Good Life gives an idea of an animal’s quality of life that is over and above that of a mere life worth living. The concept needs explanation and clarification, in order to be meaningful, particularly for consumers who purchase farm animal produce. The concept could allow assurance schemes to apply the label to assessments of both the potential of each method of production, conceptualised in ways expected to enhance consumers’ engagement such as ‘naturalness’ and ‘freedom’; and the concept of a life worth living as a safeguard threshold below which no animal’s actual welfare should fall, based on each animal’s overall affective states. This may provide a framework for development of the Good Life concept, within scientific and sociological fields, in order to allow reliable and influential use by assessors, consumers and retailers.