Sensitivity of ozone concentrations to diurnal variations of surface emissions in Mexico City: A WRF/Chem modeling study

Sensitivity of ozone (O₃) concentrations in the Mexico City area to diurnal variations of surface air pollutant emissions is investigated using the WRF/Chem model. Our analysis shows that diurnal variations of nitrogen oxides (NO_x = NO + NO₂) and volatile organic compound (VOC) emissions play an important role in controlling the O₃ concentrations in the Mexico City area. The contributions of NO_x and VOC emissions to daytime O₃ concentrations are very sensitive to the morning emissions of NO_x and VOCs. Increase in morning NO_x emissions leads to decrease in daytime O₃ concentrations as well as the afternoon O₃ maximum, while increase in morning VOC emissions tends to increase in O₃ concentrations in late morning and early afternoon, indicating that O₃ production in Mexico City is under VOC-limited regime. It is also found that the nighttime O₃ is independent of VOCs, but is sensitive to NO_x. The emissions of VOCs during other periods (early morning, evening, and night) have only small impacts on O₃ concentrations, while the emissions of NO_x have important impacts on O₃ concentrations in the evening and the early morning.This study suggests that shifting emission pattern, while keeping the total emissions unchanged, has important impacts on air quality. For example, delaying the morning emission peak from 8 am to 10 am significantly reduced the morning peaks of NO_x and VOCs, as well as the afternoon O₃ maxima. It suggests that without reduction of total emission, the daytime O₃ concentrations can be significantly reduced by changing the diurnal variations of the emissions of O₃ precursors.     

Implications of climate change for the stomatal flux of ozone: a case study for winter wheat

Climate change factors such as elevated CO2 concentrations, warming and changes in precipitation affect the stomatal flux of ozone (O3) into leaves directly or indirectly by altering the stomatal conductance, atmospheric O3 concentrations, frequency and extent of pollution episodes and length of the growing season. Results of a case study for winter wheat indicate that in a future climate the exceedance of the flux-based critical level of O3 might be reduced across Europe, even when taking into account an increase in tropospheric background O3 concentration. In contrast, the exceedance of the concentration-based critical level of O3 will increase with the projected increase in tropospheric background O3 concentration. The influence of climate change should be considered when predicting the future effects of O3 on vegetation. There is a clear need for multi-factorial, open-air experiments to provide more realistic information for O3 flux-effect modelling in a future climate.     

Analysis of ozone and VOCs measured in Shanghai: A case study

Shanghai Meteorological Administration has established a volatile organic compounds (VOCs) laboratory and an observational network for VOCs and ozone (O₃) measurements in the city of Shanghai. In this study, the measured VOCs and O₃ concentrations from 15 November (15-Nov) to 26 November (26-Nov) of 2005 in Shanghai show that there are strong day-to-day and diurnal variations. The measured O₃ and VOCs concentrations have very different characterizations between the two periods. During 15-Nov to 21-Nov (defined as the first period), VOCs and O₃ concentrations are lower than the values during 22-Nov to 28-Nov (defined as the second period). There is a strong diurnal variation of O₃ during the second period with maximum concentrations of 40–80 ppbv at noontime, and minimum concentrations at nighttime. By contrast, during the first period, the diurnal variation of O₃ is in an irregular pattern with maximum concentrations of only 20–30 ppbv. The VOC concentrations change rapidly from 30–50 ppbv during the first period to 80–100 ppbv during the second period. Two chemical models are applied to interpret the measurements. One model is a regional chemical/dynamical model (WRF-Chem) and another is a detailed chemical mechanism model (NCAR MM). Model analysis shows that the meteorological conditions are very different between the two periods, and are mainly responsible for the different chemical characterizations of O₃ and VOCs between the two periods. During the first period, meteorological conditions are characterized by cloudy sky and high-surface winds in Shanghai, resulting in a higher nighttime planetary boundary layer (PBL) and faster transport of air pollutants. By contrast, during the second period, the meteorological conditions are characterized by clear sky and weak surface winds, resulting in a lower nighttime PBL and slower transport of air pollutants. The chemical mechanism model calculation shows that different VOC species has very different contributions to the high-ozone concentrations during the second period. Alkane (40 ppbv) and aromatic (30 ppbv) are among the highest VOC concentrations observed in Shanghai. The analysis suggests that the aromatic is a main contributor for the O₃ chemical production in Shanghai, with approximately 79% of the O₃ being produced by aromatic. This analysis implies that future increase in VOC (especially aromatic) emissions could lead to significant increase in O₃ concentrations in Shanghai.     

An ozone climatology: relationship between meteorology and ozone in the Southeast USA

A statistical analysis of ozone (O₃) concentrations and meteorological parameters was performed to determine the relationship between meteorological changes and ambient O₃ concentrations in the Southeast United States. The correlation between average daily maximum O₃ concentration and various meteorological variables was analysed on a monthly basis from April through October during 1980-1994. The correlations were strongest during the summer months, particularly June, July, and August. Analysis of long term O₃ concentration trends indicates increasing trends during the 1980s and decreasing trends during the early 1990s.     

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.     

Assessing the risk caused by ground level ozone to European forest trees: a case study in pine, beech and oak across different climate regions

Two different indices have been proposed for estimation of the risk caused to forest trees across Europe by ground-level ozone, (i) the concentration based AOT40 index (Accumulated Over a Threshold of 40 ppb) and (ii) the recently developed flux based AFstY index (Accumulated stomatal Flux above a flux threshold Y). This paper compares the AOT40 and AFstY indices for three forest trees species at different locations in Europe. The AFstY index is estimated using the DO(3)SE (Deposition of Ozone and Stomatal Exchange) model parameterized for Scots pine (Pinus sylvestris), beech (Fagus sylvatica) and holm oak (Quercus ilex). The results show a large difference in the perceived O(3) risk when using AOT40 and AFstY indices both between species and regions. The AOT40 index shows a strong north-south gradient across Europe, whereas there is little difference between regions in the modelled values of AFstY. There are significant differences in modelled AFstY between species, which are predominantly determined by differences in the timing and length of the growing season, the periods during which soil moisture deficit limits stomatal conductance, and adaptation to soil moisture stress. This emphasizes the importance of defining species-specific flux response variables to obtain a more accurate quantification of O(3) risk.     

Increase in summer European ozone amounts due to climate change

The local and regional distribution of pollutants is significantly influenced by weather patterns and variability along with the spatial patterns of emissions. Therefore, climatic changes which affect local meteorological conditions can alter air quality. We use the regional air quality model CHIMERE driven by meteorological fields from regional climate change simulations to investigate changes in summer ozone mixing ratios over Europe under increased greenhouse gas (GHG) forcing. Using three 30-year simulation periods, we find that daily peak ozone amounts as well as average ozone concentrations substantially increase during summer in future climate conditions. This is mostly due to higher temperatures and reduced cloudiness and precipitation over Europe and it leads to a higher number of ozone events exceeding information and warning thresholds. Our results show a pronounced regional variability, with the largest effects of climate change on ozone concentrations occurring over England, Belgium, Germany and France. The temperature-driven increase in biogenic emissions appears to enhance the ozone production and isoprene was identified as the most important chemical factor in the ozone sensitivity. We also find that summer ozone levels in future climate projections are similar to those found during the exceptionally warm and dry European summer of 2003. Our simulations suggest that in future climate conditions summer ozone might pose a much more serious threat to human health, agriculture and natural ecosystems in Europe, so that the effects of climate trends on pollutant amounts should be considered in future emission control measures.     

东部沿海城市与西部半干旱地区近地层臭氧浓度观测研究

利用东部沿海城市天津大气边界层观测站(以下简称天津站)和西部兰州大学半干旱气候与环境观测站(SACOL)一年的臭氧和NOx体积浓度观测资料,对比分析了两观测站点近地层臭氧浓度的逐月变化、频率分布、日变化特征以及与NOx之间的相关关系.结果表明,两观测站点臭氧浓度月均值变化呈现出很好的一致性,均在4-7月出现高值,12月至次年2月出现低值,SACOL臭氧浓度月均值的最大值和最小值出现时间要比天津站推迟一个月.天津站臭氧体积浓度主要分布在10～50μL/m3,SACOL则集中在10～70 μL/m3,春、夏季两观测站点臭氧体积浓度低于10 μL/m3的频率均很小,秋、冬季两观测站点臭氧浓度频率分布特征类似.两观测站点臭氧浓度日变化在4个季节均呈现典型的单峰型分布,SACOL臭氧浓度日最大值出现时刻要比天津站晚2h.两观测站点臭氧浓度与NOx、NO2、NO的浓度之间均呈显著的负相关关系.天津站与臭氧浓度的相关性最强的为NO,而SACOL则是NOx.     

Forecasting summertime surface-level ozone concentrations in the Lower Fraser Valley of British Columbia: an ensemble neural network approach

Empirical models for predicting daily maximum hourly average ozone concentrations were developed for 10 monitoring stations in the Lower Fraser Valley (LFV) of British Columbia. According to data from 1991 to 1996, ensemble neural network models increased explained variance an average of 7% over multiple linear regression models using the same input variables. Without modification, all models performed poorly on days when the observed peak ozone concentration exceeded 82 parts per billion, the National Ambient Air Quality Objective. When numbers of extreme events in training data were increased using a histogram equalization process, models were able to forecast exceedances with improved accuracy. Modified generalized additive model (GAM) plots and associated measures of input variable importance and interaction were generated for a subset of the trained models and used to investigate relationships between input variables and ozone levels. The neural network models displayed a high degree of interaction among inputs, and it is likely the ability of these model types to account for interactions, rather than the nonlinearity of individual input variables, that explains their improved forecast skill. Inspection of GAM-style plots indicated that the relative importance of input variables in the ensemble neural network models varied with geographic location within the LFV. Four distinct groups of stations were identified, and rankings of inputs within the groups were generally consistent with physical intuition and results of prior studies.     

Forest responses to tropospheric ozone and global climate change: an analysis

In this paper an analysis is provided on: what we know, what we need to know, and what we need to do, to further our understanding of the relationships between tropospheric ozone (O(3)), global climate change and forest responses. The relationships between global geographic distributions of forest ecosystems and potential geographic regions of high photochemical smog by the year 2025 AD are described. While the emphasis is on the effects of tropospheric O(3) on forest ecosystems, discussion is presented to understand such effects in the context of global climate change. One particular strong point of this paper is the audit of published surface O(3) data by photochemical smog region that reveals important forest/woodland geographic regions where little or no O(3) data exist even though the potential threat to forests in those regions appears to be large. The concepts and considerations relevant to the examination of ecosystem responses as a whole, rather than simply tree stands alone are reviewed. A brief argument is provided to stimulate the modification of the concept of simple cause and effect relationships in viewing total ecosystems. Our knowledge of O(3) exposure and its effects on the energy, nutrient and hydrological flow within the ecosystem are described. Modeling strategies for such systems are reviewed. A discussion of responses of forests to potential multiple climatic changes is provided. An important concept in this paper is that changes in water exchange processes throughout the hydrological cycle can be used as early warning indicators of forest responses to O(3). Another strength of this paper is the integration of information on structural and functional processes of ecosystems and their responses to O(3). An admitted weakness of this analysis is that the information on integrated ecosystem responses is based overwhelmingly on the San Bernardino Forest ecosystem research program of the 1970s because of a lack of similar studies. In the final analysis, it is recommended that systems ecology be applied in examining the joint effects of O(3), carbon dioxide and ultraviolet-B radiation on forest ecosystems.     

Interannual variation in meteorologically adjusted ozone levels in the eastern United States: A comparison of two approaches

Assessing the influence of abatement efforts and other human activities on ozone levels is complicated by the atmosphere's changeable nature. Two statistical methods, the dynamic linear model (DLM) and the generalized additive model (GAM), are used to estimate ozone trends in the eastern United States and to adjust for meteorological effects. The techniques and resulting estimates are compared and contrasted for four monitoring locations chosen through principal components analysis to represent regional patterns of ozone concentrations. After adjustment for meteorological influence, overall downward trends are evident at all four locations from 1997 to 2004. The results indicate that the two methods’ estimates of ozone changes agree well. When such estimates are needed quickly, or when many similar, but separate analyses are required, the ease of implementation and relative simplicity of the GAMs are attractive. The DLMs are much more flexible, readily addressing such issues as autocorrelation, the presence of missing values, and estimation of long-term trends or cyclical patterns. Implementation of DLMs, however, is typically more difficult, and especially in the absence of an experienced practitioner, they may be better reserved for in-depth analyses.     

Socio-economic vulnerability to climate change in the central mountainous region of eastern Mexico

Climate change effects are expected to be more severe for some segments of society than others. In Mexico, climate variability associated with climate change has important socio-economic and environmental impacts. From the central mountainous region of eastern Veracruz, Mexico, we analyzed data of total annual precipitation and mean annual temperature from 26 meteorological stations (1922–2008) and from General Circulation Models. We developed climate change scenarios based on the observed trends with projections to 2025, 2050, 2075, and 2100, finding considerable local climate changes with reductions in precipitation of over 700 mm and increases in temperature of ~9°C for the year 2100. Deforested areas located at windward were considered more vulnerable, representing potential risk for natural environments, local communities, and the main crops cultivated (sugarcane, coffee, and corn). Socio-economic vulnerability is exacerbated in areas where temperature increases and precipitation decreases.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0690-4) contains supplementary material, which is available to authorized users.     

Threat to food security under current levels of ground level ozone: A case study for Indian cultivars of rice

A higher ozone concentration in rural agricultural region poses threat to food production in developing countries. The present study was conducted to evaluate the growth, biomass accumulation and allocation pattern, quantitative and qualitative characteristics of grains for two tropical rice cultivars (Oryza sativa L. cv NDR 97 and Saurabh 950) at ambient O₃ concentrations at a rural site in the Indo Gangetic plains of India.Percent inhibition in number of leaves was higher for NDR 97, but in leaf area for Saurabh 950 grown in non filtered chambers (NFCs) compared to filtered chambers (FCs). Higher inhibition in root biomass was recorded in Saurabh 950 and in leaf and standing dead biomass for NDR 97. During vegetative phase, relative growth rate showed more percent inhibition in Saurabh 950, but at reproductive phase in NDR 97. Net assimilation rate showed higher values for Saurabh 950 than NDR 97 in NFCs but percent inhibition in leaf area ratio was higher for former than latter cultivar in NFCs. The ozone resistance was higher in NDR 97 during vegetative phase, but in Saurabh 950 at reproductive phase. Number of grains was higher in NDR 97 than Saurabh 950, but test weight and weight of grains m^?2 showed reverse trends. Concentrations of starch, protein, P, N, Ca, Mg and K decreased, while reducing and total soluble sugar increased in grains of both the cultivars in NFCs compared to FCs. The study concluded that under ambient condition of O₃ exposure, the two cultivars responded differently. Saurabh 950 favoured biomass translocation priority towards ear in reproductive phase and hence showed higher resistivity due to maintenance of higher test weight. NDR 97, however, showed better growth during vegetative period, but could not allocate efficiently to developing ears, hence higher number of unfilled grains in NFCs led lower test weight.     

Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy,USA

Environmental Science and Pollution Research - This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In...     

A case study of contaminants on military ranges: Camp Edwards, Massachusetts, USA

An extensive investigation at the Camp Edwards, Massachusetts Military Reservation (MMR) demonstrates that assessment of groundwater and soil contamination at military ranges can be limited primarily to explosive-related compounds such as RDX, HMX, perchlorate, TNT and their transformation products. A modified analytical method is recommended to expand the list of explosives and to improve the detection limits. Analyses of metals, VOCs, SVOCs, and TICs are unnecessary. Soil samples may require the analyses of PAHs and PCNs for burn areas. Camp Edwards, as one of the few military ranges that have been exhaustively investigated for contaminants, is an ideal point of departure for evaluating other ranges. The permeable site soils promote leaching of contaminants and inhibit biotic and abiotic transformations. Moreover, the site has experienced an unusual extent of activities in its more than ninety years of active use. The recommendations in this report are based on data obtained for more than 200 analytes from more than 15,000 environmental samples.     

Sensitivity of a forest ecosystem model to climate parametrization schemes

An analysis of the climate parametrization scheme adopted by conventional forest gap models revealed that most models assume a constant climate and are difficult to calibrate consistently. Tree growth showed unrealistically sensitive threshold effects along ecological gradients of temperature and precipitation. A new parametrization was compared with its predecessors in terms of the model's capability to predict realistic steady state species compositions at three test sites in the Alps. Applying the new model variant ForClim to some climate-change scenarios suggests that forest gap models are highly sensitive to climate pametrizations, regardless of the realism with which they simulate forests for the current climate. Moreover, the precision of climate scenarios based on General Circulation Models (GCM), for example, falls short of ForClim's sensitivity. Climate-dependent processes in forest gap models should be rehearsed before these models are used in impact studies of climatic change.     

Temperature modeling in activated sludge systems: a case study.

A model of temperature dynamics was developed as part of a general model of activated-sludge reactors. Transport of heat was described by the one-dimensional, advection-dispersion equation, with a source term based on a theoretical heat balance over the reactor. The model was compared to several reference models, including a tanks-in-series model and the dispersion model with heat components neglecting biochemical-energy inputs and other activated-sludge, heat-balance terms. All the models were tested under steady-state and dynamic conditions at a full-scale facility, the Rock Creek wastewater treatment plant in Hillsboro, Oregon, using meteorological data from a station located 16 km from the plant. The dispersion model and tanks-in-series model matched in situ temperature data with absolute-mean errors less than 0.1 degrees C. Neglecting biochemical-heat-energy inputs in the activated-sludge reactor underestimated temperatures by up to 0.5 degrees C. The biochemical-heat-energy inputs accounted for 30 to 40% of the total heat flux throughout the year.     

Evaluation of ozone exposure indices in exposure-response modeling

In exposure-response modeling, a major concern is the numerical definition of exposure in relating crop loss to O3, yet few indices have been considered. This paper addresses research in which plant growth was regressed for soybean, wheat, cotton, corn, and sorghum against 613 numerical exposure indices using the Box-Tidwell model. When the minimum sum of squared errors criterion was used, optimum performance was not attained for any single index; however, near optimum performances were achieved by two censored cumulative indices and from a class of indices called the generalized, phenologically weighted, cumulative impact indices (GPWCIs). The top-performing GPWCIs accumulated concentrations, used sigmoid weighting schemes emphasizing O3 concentrations of 0.06 ppm (118 microg m(-3)) or higher, and had phenological weighting schemes with greatest weight occurring 20 to 40 days prior to crop maturity. These findings indicate that (1) peak concentrations are important, but lower concentrations should be included in the calculations, (2) increased plant sensitivity occurs between flowering and maturity, and (3) plants respond to cumulative exposure impact.     

Degradation of macrolide antibiotics by ozone: a mechanistic case study with clarithromycin

Macrolide antibiotics are widely used (in the order of 1g per person per year). They pass the body largely unchanged and are also not degraded in wastewater treatment plants. With not too much effort, they may be eliminated from their effluents by ozonation. The macrolide antibiotics have all a dimethylamino group at one of the carbohydrate residues in common. This functional group is the target of the ozone reaction, and clarithromycin has been selected here for a more detailed study. Since only the free amine reacts with ozone, the rate of reaction is pH dependent (at pH 7: k = 4 x 10(4) M(-1) s(-1)). In analogy to the ozonolysis of trimethylamine, the main reaction is a transfer of an O-atom yielding the N-oxide (identified by HPLC/MS-MS). A minor product (10%, based on formaldehyde yields) is demethylated clarithromycin (identified by HPLC/MS-MS). The dimethylamino group is thought to be essential for the binding of the macrolide antibiotics to their target. As a consequence, chemical changes of this functional group, notably the formation of the N-oxide that is no longer a proton acceptor, inactivates these drugs as assayed by the suppression of the growth of Pseudomonas putida. This is most important for wastewater treatment, as mineralization of clarithromycin by ozone would require 100 times as much ozone.