Future land use and land cover influences on regional biogenic emissions and air quality in the United States

A regional modeling system was applied with inputs from global climate and chemistry models to quantify the effects of global change on future biogenic emissions and their impacts on ozone and biogenic secondary organic aerosols (BSOA) in the US. Biogenic emissions in the future are influenced by projected changes in global and regional climates and by variations in future land use and land cover (LULC). The modeling system was applied for five summer months for the present-day case (1990–1999, Case 1) and three future cases covering 2045–2054. Individual future cases were: present-day LULC (Case 2); projected-future LULC (Case 3); and future LULC with designated regions of tree planting for carbon sequestration (Case 4). Results showed changing future meteorology with present-day LULC (Case 2) increased average isoprene and monoterpene emission rates by 26% and 20% due to higher temperature and solar insolation. However when LULC was changed together with climate (Case 3), predicted isoprene and monoterpene emissions decreased by 52% and 31%, respectively, due primarily to projected cropland expansion. The reduction was less, at 31% and 14% respectively, when future LULC changes were accompanied by regions of tree planting (Case 4). Despite the large decrease in biogenic emission, future average daily maximum 8-h (DM8H) ozone was found to increase between +8 ppbv and +10 ppbv due to high future anthropogenic emissions and global chemistry conditions. Among the future cases, changing LULC resulted in spatially varying future ozone differences of ?5 ppbv to +5 ppbv when compared with present-day case. Future BSOA changed directly with the estimated monoterpene emissions. BSOA increased by 8% with current LULC (Case 2) but decreased by 45%–28% due to future LULC changes. Overall, the results demonstrated that on a regional basis, changes in LULC can offset temperature driven increases in biogenic emissions, and, thus, LULC projection is an important factor to consider in the study of future regional air quality.     

Inherent uncertainty in air quality modeling

This paper summarizes the discussions of a working group that was charged with the task of examining inherent uncertainty in air quality modeling. The major topics of the paper are:

• 1.1. Definition of inherent uncertainty in air quality models;
• 2.2. Determination of inherent uncertainty;
• 3.3. Role of inherent uncertainty in model evaluation.

The concepts introduced here are illustrated through a numerical simulation with Gifford's fluctuating plume model.     

Evaluating the use of outputs from comprehensive meteorological models in air quality modeling applications

Currently used dispersion models, such as the AMS/EPA Regulatory Model (AERMOD), process routinely available meteorological observations to construct model inputs. Thus, model estimates of concentrations depend on the availability and quality of meteorological observations, as well as the specification of surface characteristics at the observing site. We can be less reliant on these meteorological observations by using outputs from prognostic models, which are routinely run by the National Oceanic and Atmospheric Administration (NOAA). The forecast fields are available daily over a grid system that covers all of the United States. These model outputs can be readily accessed and used for dispersion applications to construct model inputs with little processing. This study examines the usefulness of these outputs through the relative performance of a dispersion model that has input requirements similar to those of AERMOD. The dispersion model was used to simulate observed tracer concentrations from a Tracer Field Study conducted in Wilmington, California in 2004 using four different sources of inputs: (1) onsite measurements; (2) National Weather Service measurements from a nearby airport; (3) readily available forecast model outputs from the Eta Model; and (4) readily available and more spatially resolved forecast model outputs from the MM5 prognostic model. The comparison of the results from these simulations indicate that comprehensive models, such as MM5 and Eta, have the potential of providing adequate meteorological inputs for currently used short-range dispersion models such as AERMOD.     

State-space modeling of the relationship between air quality and mortality

A portion of a population is assumed to be at risk, with the mortality hazard varying with atmospheric conditions including total suspended particulates (TSP). This at-risk population is not observed and the hazard function is unknown; we wish to estimate these from mortality count and atmospheric variables. Consideration of population dynamics leads to a state-space representation, allowing the Kalman Filter (KF) to be used for estimation. A harvesting effect is thus implied; high mortality is followed by lower mortality until the population is replenished by new arrivals. The model is applied to daily data for Philadelphia, PA, 1973-1990. The estimated hazard function rises with the level of TSP and at extremes of temperature and also reflects a positive interaction between TSP and temperature. The estimated at-risk population averages about 480 and varies seasonally. We find that lags of TSP are statistically significant, but the presence of negative coefficients suggests their role may be partially statistical rather than biological. In the population dynamics framework, the natural metric for health damage from air pollution is its impact on life expectancy. The range of hazard rates over the sample period is 0.07 to 0.085, corresponding to life expectancies of 14.3 and 11.8 days, respectively.     

Resolving local-scale emissions for modeling air quality near roadways

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.     

The use of environmental risk assessment methodologies for an indoor air quality investigation

The authors of this paper chose several target compounds that have been found in average US homes, applied the current United States Environmental Protection Agency (USEPA) Superfund risk assessment methodologies to indoor air quality, and produced risk numbers for hazard quotients and predicted increases in incidence of cancer which would be unacceptable at US hazardous waste sites. The calculations were made for the average child and adult with USEPA default exposure values. Calculations were also made for a worst case scenario using maximum concentrations and exposure estimates defined by the USEPA as describing the reasonable exposure (RME). Significant cancer risks and non-cancer hazard quotients were predicted.     

Greenhouse gas dynamics in an urbanized river system: influence of water quality and land use

Environmental Science and Pollution Research - Rivers act as a natural source of greenhouse gases (GHGs). However, anthropogenic activities can largely alter the chemical composition and microbial...     

Numerical modeling on air quality in an urban environment with changes of the aspect ratio and wind direction

Due to heavy traffic emissions within an urban environment, air quality during the last decade becomes worse year by year and hazard to public health. In the present work, numerical modeling of flow and dispersion of gaseous emissions from vehicle exhaust in a street canyon were investigated under changes of the aspect ratio and wind direction. The three-dimensional flow and dispersion of gaseous pollutants were modeled using a computational fluid dynamics (CFD) model which was numerically solved using Reynolds-averaged Navier–Stokes (RANS) equations. The diffusion flow field in the atmospheric boundary layer within the street canyon was studied for different aspect ratios (W/H?=?1/2, 3/4, and 1) and wind directions (θ?=?90°, 112.5°, 135°, and 157.5°). The numerical models were validated against wind tunnel results to optimize the turbulence model. The numerical results agreed well with the wind tunnel results. The simulation demonstrated that the minimum concentration at the human respiration height within the street canyon was on the windward side for aspect ratios W/H?=?1/2 and 1 and wind directions θ?=?112.5°, 135°, and 157.5°. The pollutant concentration level decreases as the wind direction and aspect ratio increase. The wind velocity and turbulence intensity increase as the aspect ratio and wind direction increase.     

The effect of improved nowcasting of precipitation on air quality modeling

The predictive potential of air quality models and thus their value in emergency management and public health support are critically dependent on the quality of their meteorological inputs. The atmospheric flow is the primary cause of the dispersion of airborne substances. The scavenging of pollutants by cloud particles and precipitation is an important sink of atmospheric pollution and subsequently determines the spatial distribution of the deposition of pollutants. The long-standing problem of the spin-up of clouds and precipitation in numerical weather prediction models limits the accuracy of the prediction of short-range dispersion and deposition from local sources. The resulting errors in the atmospheric concentration of pollutants also affect the initial conditions for the calculation of the long-range transport of these pollutants. Customary the spin-up problem is avoided by only using NWP (Numerical Weather Prediction) forecasts with a lead time greater than the spin-up time of the model. Due to the increase of uncertainty with forecast range this reduces the quality of the associated forecasts of the atmospheric flow.In this article recent improvements through diabatic initialization in the spin-up of large-scale precipitation in the Hirlam NWP model are discussed. In a synthetic example using a puff dispersion model the effect is demonstrated of these improvements on the deposition and dispersion of pollutants with a high scavenging coefficient, such as sulphur, and a low scavenging coefficient, such as cesium-137. The analysis presented in this article leads to the conclusion that, at least for situations where large-scale precipitation dominates, the improved model has a limited spin-up so that its full forecast range can be used. The implication for dispersion modeling is that the improved model is particularly useful for short-range forecasts and the calculation of local deposition. The sensitivity of the hydrological processes to proper initialization implies that the spin-up problem may reoccur with changes in the model and increased model resolution. Spin-up should be an ongoing concern for atmospheric modelers.     

Summer air quality over an artificial lake

In the summer of 1998, the air quality (indicators: CO, NO, NO₂, O₃) above the water surface of the Lake Balderey (Essen, Ruhr area, North Rhine-Westphalia, Germany), an artificial lake used for recreation purposes, was measured using the Fourier transform infrared spectroscopy (FTIR) and differential optical absorption spectroscopy (DOAS) remote measurement methods. The lake, with an area of 3 km² was created by damming the Ruhr and is surrounded by higher ground. In calm, bright weather conditions, this location results in a low-exchange situation (formation of temperature inversions, cold air dynamics) with a sustained impact on pollutant concentrations over the lake. The results of trace substance measurements (1/2 h mean values) were compared with values from comparison stations (suburban, high traffic and forest) located outside the area of the lake. In general, it was found that mean CO and NO concentrations over the lake were very low (0.3 ppm and 7.5 ppb, respectively). NO₂ values (15 ppb) were some 3.5 times higher than those recorded at the forest station and O₃ values, at 27 ppb, almost reached the same level as at the forest station (30 ppb). Mass flow densities as a function of wind direction, diurnal courses, differences between weekdays and weekends and comparisons with air quality standards are presented for the lake station.     

A theoretical framework for the episodic-urban air quality management plan (e-UAQMP)

The present research proposes the local urban air quality management plan which combines two different modelling approaches (hybrid model) and possesses an improved predictive ability including the ‘probabilistic exceedances over norms’ and their ‘frequency of occurrences’ and so termed, herein, as episodic-urban air quality management plan (e-UAQMP). The e-UAQMP deals with the consequences of ‘extreme’ concentrations of pollutant, mainly occurring at urban ‘hotspots’ e.g. traffic junctions, intersections and signalized roadways and are also influenced by complexities of traffic generated ‘wake’ effects. The e-UAQMP (based on probabilistic approach), also acts as an efficient preventive measure to predict the ‘probability of exceedances’ so as to prepare a successful policy responses in relation to the protection of urban environment as well as disseminating information to its sensitive ‘receptors’. The e-UAQMP may be tailored to the requirements of the local area for the policy implementation programmes. The importance of such policy-making framework in the context of current air pollution ‘episodes’ in urban environments is discussed. The hybrid model that is based on both deterministic and stochastic based approaches predicting the ‘average’ as well as ‘extreme’ concentration distribution of air pollutants together in form of probability has been used at two air quality control regions (AQCRs) in the Delhi city, India, in formulating and executing the e-UAQMP—first, the income tax office (ITO), one of the busiest signalized traffic intersection and second, the Sirifort, one of the busiest signalized roadways.     

Biomarker responsiveness in different tissues of caged Ruditapes philippinarum and its use within an integrated sediment quality assessment

Biomarkers comprising activities of biotransformation enzymes (ethoxyresorufin-O-deethylase -EROD-, dibenzylfluorescein dealkylase -DBF-, glutathione S-transferase -GST), antioxidant enzymes (glutathione reductase -GR- and glutathione peroxidase -GPX), lipid peroxidation -LPO- and DNA strand breaks were analyzed in the clam Ruditapes philippinarum caged at Cádiz Bay, Santander Bay and Las Palmas de Gran Canaria (LPGC) Port (Spain). Sediments were characterized. Digestive gland was the most sensitive tissue to sediment contamination. In Cádiz Bay, changes in LPO regarding day 0 were related with metals. In LPGC Port, DBF, EROD, and GST activity responses suggested the presence of undetermined contaminants which might have led to DNA damage. In Santander Bay, PAHs were related with EROD activity, organic and metal contamination was found to be associated with GR and GST activities and DNA damage presented significant (p < 0.05) induction. R. philippinarum was sensitive to sediment contamination at biochemical level. Biomarkers allowed chemical exposure and sediment quality assessment.     

Analysis of air quality within a street canyon using statistical and dispersion modelling techniques

The dispersion model, ADMS-Urban, alongside the statistical modelling technique, generalized additive modelling, have been used to predict hourly NO_x and nitrogen dioxide (NO₂) concentrations at a busy street canyon location and the results compared with measurements. Generalized additive models (GAMs) were constructed for NO₂ and NO_x concentrations using input data required to run ADMS-Urban. Bivariate polar plots have been produced from the wind flow (speed and direction) and pollution data (measured and predicted concentrations) to provide further information regarding the complex wind-pollutant interactions in an urban street canyon. The predictions made with the GAMs show excellent agreement with measured concentrations at this location, reproducing both the magnitude of NO_x and NO₂ concentrations and also the wind speed-wind direction dependence of pollutant sources within the canyon. However, the predictions made with ADMS-Urban under-estimated the measured NO_x by 11% and NO₂ by 21% and there are clear differences in the bivariate polar plots. Several sensitivity tests were carried out with ADMS-Urban in an attempt to produce predictions in closer agreement to those measured at Gillygate. Increasing the primary NO₂ fraction in ADMS-Urban (from 10% to 20%) had a considerable effect on the predictions made with this model, increasing NO₂ predictions by ∼20%. However, the bivariate plots still showed major differences to those of the measurements. This work illustrates that generalized additive modelling is a useful tool for investigating complex wind-pollutant interactions within a street canyon.     

Spatio-temporal assessment of land use dynamics and urbanization: linking with environmental aspects and DPSIR framework approach

Environmental Science and Pollution Research - Urbanization is the main force of the global environmental as well as land use land cover changes (LULC). Urbanization is caused by prompt increase in...     

浦阳江干流河流生态缓冲带土地利用类型对水质和底栖动物的影响

为揭示河流生态缓冲带土地利用变化对水质和水生生物多样性的影响,以浦阳江干流为研究对象,通过底栖动物野外采集、水质分析和河岸带土地利用解译,分析其干流河流生态缓冲带土地利用类型与河流水质和底栖动物多样性之间的关系。结果表明,高锰酸盐指数(COD_Mn)、氨氮(NH₃-N)和总磷(TP)与林业用地呈负相关,但与农业用地显著正相关。底栖动物群落多样性与农业用地呈显著正相关,但与城镇用地显著负相关。冗余分析结果显示,浦阳江上游浦江段河流生态缓冲带中农业用地对底栖动物影响最大,中下游的诸暨段建设用地对底栖动物的影响最大。这表明同一条河流的上下游,河流生态缓冲带中农业和建设用地对底栖动物多样性的影响可能不同。河流生态缓冲带修复实践中,增加林地面积和自然岸线比例对河流水生生物多样性恢复与保护有促进作用。     

免疫粒子群算法优化的环境空气质量评价方法

为了提高免疫算法的收敛速度,将粒子群优化思想引入到免疫算法中,设计了一种免疫粒子群优化算法。采用该算法对大气污染损害公式的参数进行寻优,得到了适用于臭氧、PM2．5等6种大气污染物的环境空气质量评价的污染损害指数公式及环境空气质量评价模型。为了使评价结果更准确,采用了国家环保部最新发布的空气质量标准中给出的大气污染物种类、数目及各级浓度限值。将该评价方法应用于大气质量评价领域,实验结果表明,该方法评价结果准确,具有较好的灵活性、实用性和应用前景。     

The impact of frequency and duration of air quality monitoring: Atlanta, GA, data modeling of air pollution and mortality

The purpose of this analysis is threefold. We first examine the extent to which a longer series of data improves our understanding of air pollution on human mortality in the Atlanta, GA, area by updating the findings presented in Klemm and Mason (J. Air Waste Manage. Assoc. 2000, 50, 1433-1439) and Klemm et al. (Inhal. Toxicol. 2004, 16 (Suppl 1), 131-141) with 7.5 additional years of data. We explore estimated effects on two age groups (<65 and 65+) and four categories of cause of death. Second, we investigate how enlarging the geographic area of inquiry influences the estimated effects. Third, because some air quality (AQ) measures are monitored less frequently than daily, we investigate the extent to which AQ measurement frequency can influence estimates of relationships with human mortality. Our analytical approach employs a Poisson regression model using generalized linear modeling in S-Plus to estimate the relationship between daily AQ measures and daily mortality counts. We show that the estimated effects and their associated t values vary by year for nine AQ measures (particulate matter with aerodynamic diameter < or =2.5 microm [PM2.5], elemental carbon [EC], organic carbon [OC], NO3, SO4, O3, NO2, CO, and SO2). Several of the estimated AQ effects show downward trends during the 9-year period of study. The estimated effects tend to be strongest for the AQ measurement during the day of death and tend to decrease with additional lags. Enlarging the geographic area from two to four counties in the metropolitan area decreased the estimated effects, perhaps partly due to the fact that the measurement site is located in one of the two original counties. Estimated effects utilizing data as if the AQ were only measured every 3rd or every 6th day each week or twice per week vary from lower to higher than that estimated with daily measurements, although the t values are lower, as expected.     

Scale-dependence of land use effects on water quality of streams in agricultural catchments

The influence of land use on water quality in streams is scale-dependent and varies in time and space. In this study, land cover patterns and stocking rates were used as measures of agricultural development in two pasture and one native grassland catchment in New Zealand and were related to water quality in streams of various orders. The amount of pasture per subcatchment correlated well to total nitrogen and nitrate in one catchment and turbidity and total phosphorous in the other catchment. Stocking rates were only correlated to total phosphorous in one pasture catchment but showed stronger correlations to ammonium, total phosphorous and total nitrogen in the other pasture catchment. Winter and spring floods were significant sources of nutrients and faecal coliforms from one of the pasture catchments into a wetland complex. Nutrient and faecal coliform concentrations were better predicted by pastural land cover in fourth-order than in second-order streams. This suggests that upstream land use is more influential in larger streams, while local land use and other factors may be more important in smaller streams. These temporal and spatial scale effects indicate that water-monitoring schemes need to be scale-sensitive.