达州市城区环境空气质量变化趋势及CMAQ模型预报分析

利用Spearman秩相关系数法、污染日历图、浓度分析法和CMAQ预测模型研究了达州市城区2015—2019年空气质量状况。结果表明:2015—2019年,达州市城区O_3浓度变化趋势为显著上升(P0.05),季度变化明显,8月易发生因O_3超标导致的轻度污染状况;CO年均值变化趋势为显著降低(P0.05);NO_2年均值呈上升趋势,但尚未达到显著水平(P0.05);SO_2、PM_(10)和PM_(2.5)年均值呈下降趋势,但变化趋势不明显(P0.05)。2019年,1月和12月污染最重,PM_(2.5)超标是主因,PM_(10)和PM_(2.5)年均值达标形势严峻,全年一半以上天数的PM_(2.5)浓度超过年均值二级标准限值,PM_(10)也近半;NO_2年均值达标形势严峻,全年212 d超过年均值二级标准限值。CMAQ模型对不同污染指标的预测准确率不同,预测PM_(2.5)浓度、首要污染物和空气质量等级时的准确率不及人工预测,预测AQI时的准确率高于人工预测,更多污染指标的预测比较还有待进一步研究。     

Methodological uncertainties in multi-regression analyses of middle-atmospheric data series

Multi-regression analyses have often been used recently to detect trends, in particular in ozone or temperature data sets in the stratosphere. The confidence in detecting trends depends on a number of factors which generate uncertainties. Part of these uncertainties comes from the random variability and these are what is usually considered. They can be statistically estimated from residual deviations between the data and the fitting model. However, interferences between different sources of variability affecting the data set, such as the Quasi-Biennal Oscillation (QBO), volcanic aerosols, solar flux variability and the trend can also be a critical source of errors. This type of error has hitherto not been well quantified. In this work an artificial data series has been generated to carry out such estimates. The sources of errors considered here are: the length of the data series, the dependence on the choice of parameters used in the fitting model and the time evolution of the trend in the data series. Curves provided here, will permit future studies to test the magnitude of the methodological bias expected for a given case, as shown in several real examples. It is found that, if the data series is shorter than a decade, the uncertainties are very large, whatever factors are chosen to identify the source of the variability. However the errors can be limited when dealing with natural variability, if a sufficient number of periods (for periodic forcings) are covered by the analysed dataset. However when analysing the trend, the response to volcanic eruption induces a bias, whatever the length of the data series. The signal to noise ratio is a key factor: doubling the noise increases the period for which data is required in order to obtain an error smaller than 10%, from 1 to 3-4 decades. Moreover, if non-linear trends are superimposed on the data, and if the length of the series is longer than five years, a non-linear function has to be used to estimate trends. When applied to real data series, and when a breakpoint in the series occurs, the study reveals that data extending over 5 years are needed to detect a significant change in the slope of the ozone trends at mid-latitudes.     

A Statistical Assessment of Changes in Precipitation Chemistry at CAPMoN Sites, Canada

The objective of this study is to decide if chemical concentrations measured during 1988-1997in precipitation by the Canadian Air and Precipitation Monitoring Network (CAPMoN) indicate changes in the annual patterns. The inference is based on SO₄, NO₃, Cl,NH₄, Na, Ca and K concentrations monitored daily with the rain water acidity pH. By pattern is understood the probability distribution of the annual sample at a particular location. Most of the annual data can be well described by means of a linear regression model with second order polynomial trend and autocorrelated noise. Statistical analysis based on the model shows luck of systematic significant year to year increases or declines of the concentrations.     

Kelp as a Bioindicator: Does it Matter Which Part of 5 M Long Plant is Used for Metal Analysis?

Kelp may be useful as a bioindicator because they are primary producers that are eaten by higher trophic level organisms, including people and livestock. Often when kelp or other algae species are used as bioindicators, the whole organism is homogenized. However, some kelp can be over 25 m long from their holdfast to the tip of the blade, making it important to understand how contaminant levels vary throughout the plant. We compared the levels of arsenic, cadmium, chromium, lead, manganese, mercury and selenium in five different parts of the kelp Alaria nana to examine the variability of metal distribution. To be useful as a bioindicator, it is critical to know whether levels are constant throughout the kelp, or which part is the highest accumulator. Kelp were collected on Adak Island in the Aleutian Chain of Alaska from the Adak Harbor and Clam Cove, which opens onto the Bering Sea. In addition to determining if the levels differ in different parts of the kelp, we wanted to determine whether there were locational or size-related differences. Regression models indicated that between 14% and 43% of the variation in the levels of arsenic, cadmium, chromium, manganese, mercury, and selenium was explained by total length, part of the plant, and location (but not for lead). The main contributors to variability were length (for arsenic and selenium), location (mercury), and part of the plant (for arsenic, cadmium, chromium and manganese). The higher levels of selenium occurred at Clam Cove, while mercury was higher at the harbor. Where there was a significant difference among parts, the holdfast had the highest levels, although the differences were not great. These data indicate that consistency should be applied in selecting the part of kelp (and the length) to be used as a bioindicator. While any part of Alaria could be collected for some metals, for arsenic, cadmium, chromium, and manganese a conversion should be made among parts. In the Aleutians the holdfast can be perennial while the blade, whipped to pieces by winter wave action, is regrown each year. Thus the holdfast may be used for longer-term exposure for arsenic, cadmium, chromium and manganese, while the blade can be used for short-term exposure for all metals. Cadmium, lead and selenium were at levels that suggest that predators, including people, may be at risk from consuming Alaria. More attention should be devoted to heavy metal levels in kelp and other algae from Adak, particularly where they may play a role in a subsistence diets.     

Integral assessment of climate impact on the transboundary Mesta River flow formation in Bulgaria

The present work considers the section of the Mesta River on Bulgarian territory using the integral method for evaluation of climate and anthropogenic impact on the river flow. The level of this impact is determined by the index K _i (flow module), the coefficient C _i for the deviation of the average annual water volume Q _i from the flow norm Q _o and the index h _i for the deviation of the average annual rainfall volume H _i from the average multi-annual rainfall volume H _o . The dynamics of the average annual flow Q _i at two typical hydrometric stations – Yakoruda and Khadzhidimovo, as well as the dynamics of the average annual rainfall for the Yakoruda station was examined for the period 1955–2003. The data for the considered period 1955–2003 exhibit a decreasing trend of the average annual water volumes dynamics for both stations due to the impact of climate changes in the Mesta River catchment.     

Measures of flow variability for great lakes tributaries

Design of monitoring programs for load estimation is often hampered by the lack of existing chemical data from which to determine patterns of flux variance, which determine the sampling program requirements when loads are to be calculated using flux-dependent models like the Beale Ratio Estimator. In contrast, detailed flow data are generally available for the important tributaries. For pollutants from non-point sources there is often a correlation between flow and pollutant flux. Thus, measures of flow variability might be calibrated to flux variability for well-known watersheds, after which flow variability could be used as a proxy for flux variability to estimate sampling needs for tributaries for which adequate chemical observations are lacking.Three types of measures of flow variability were explored: ratio measures, which are of the form q _x/q_y, where q _xis the flow corresponding to the percentile x, and y=100–x; spread measures, of the form (q _x–q_y)/q_m, where q _mis the median flow; and the coefficient of variation of the logs of flows. In the latter, flows are log transformed because flow distributions are often approximately log-normal. Three ratio measures were evaluated, based on the percentiles (10,90), (20,80), and (25,75). The analogous spread measures were also evaluated; the spread measure based on percentiles (25,75) is derived from the commonly used fourth spread of non-parametric statistics. The ratio measures and the spread measures are scale independent, and thus are measures only of the shape of the distribution. The coefficient of variation is also scale independent, but in log space.Values of these measures of flow variability for 120 Great Lakes tributaries are highly intercorrelated, although the relationship is often non-linear. The coefficient of variation of the log of the flows is also well correlated with the coefficient of variation of fluxes of suspended solids, total phosphorus, and chloride, for a smaller set of rivers where the existence of abundant chemical data allows comparison.Tributaries with abnormal distributions often show up as outliers when one measure of flow variability is plotted against another. Several examples are discussed.     

Temporal Trends of Young-of-Year Fishes in Lake Erie and Comparison of Diel Sampling Periods

We explored temporal trends of young-of-year (YOY) fishes caught in bottom trawl hauls at an established offshore monitoring site in Lake Erie in fall during 1961–2001. Sampling was conducted during morning, afternoon, and night in each year. Catches per hour (CPH) of alewife (Alosa pseudoharengus) YOY were relatively low and exhibited no temporal trend. This result was consistent with the species’ intolerance to Lake Erie’s adverse winter water temperatures. Gizzard shad (Dorosoma cepedianum) YOY decreased sharply after 1991, which was consistent with recent oligotrophication of the lake. Following the establishment in 1979 and rapid increase of white perch (Morone americana) YOY, white bass (Morone chrysops) and freshwater drum (Aplodinotus grunniens) YOY decreased. Trout-perch (Percopsis omiscomaycus) YOY decreased during 1986–1991, but recovered to previous levels during 1991–2001. The recovery coincided with the resurgence of mayflies (Ephemoptera) in the lake. CPH of spottail shiner (Notropis hudsonius) and emerald shiner (N. atherinoides) YOY exhibited no temporal trend between 1961 and the late 1970s to early 1980s. CPH of yellow perch (Perca flavescens) YOY decreased during 1961–1988, and walleye (Sander vitreum) YOY increased overall during the time series. These observations were consistent with published studies of adults in the region. CPH of 4 of the 10 species of YOY considered were greatest during night. CPH for walleye YOY was higher in the morning than in the afternoon, but there was no significant difference between night and morning abundances. The results suggest that (1) CPH of YOY fishes may be a useful monitoring tool for Lake Erie, and (2) offshore monitoring programs that do not include night sampling periods may underestimate recruitment for several common species.     

Stationary and Non-stationary Extreme Value Approaches for Modelling Extreme Temperature: the Case of Riyadh City,Saudi Arabia

Climate change is one of the most fiercely debated scientific issues in recent decades, and the changes in climate extremes are estimated to have greater negative impacts on human society and the natural environment than the changes in mean climate. Extreme value theory is a well-known tool that attempts to best estimate the probability of adversarial risk events. In this paper, the focus is on the statistical behaviour of extreme maximum values of temperature. Under the framework of this theory, the methods of block maxima and threshold exceedances are employed. Due to the non-stationary characteristic of the series of temperature values, the generalized extreme value distribution and the generalized Pareto distribution were extended to the non-stationary processes by including covariates in the parameters of the models. For the purpose of obtaining an approximately independent threshold excesses, a declustering method was performed and then the de-clustered peaks were fitted to the generalized Pareto distribution. The stationary Gumbel distribution was found a reasonable model for the annual block maxima; however, a non-stationary generalized extreme value distribution with quadratic trend in the location was recommended for the half-yearly period. The findings also show that there is an improvement in modelling daily maxima temperature when it is applied to the declustered series and the given model outperforms the non-stationary generalized Pareto distribution models. Furthermore, the retained generalized Pareto distribution model proved better than the generalized extreme value distribution. Estimates of the return levels obtained from both extreme value models show that new records on maximum temperature event could appear within the next 20, 50 and 100 years.     

Identifying dissolved oxygen variability and stress in tidal freshwater streams of northern New Zealand

Tidal streams are ecologically important components of lotic network, and we identify dissolved oxygen (DO) depletion as a potentially important stressor in freshwater tidal streams of northern New Zealand. Other studies have examined temporal DO variability within rivers and we build on this by examining variability between streams as a basis for regional-scale predictors of risk for DO stress. Diel DO variability in these streams was driven by: (1) photosynthesis by aquatic plants and community respiration which produced DO maxima in the afternoon and minima early morning (range, 0.6-4.7 g/m(3)) as a product of the solar cycle and (2) tidal variability as a product of the lunar cycle, including saline intrusions with variable DO concentrations plus a small residual effect on freshwater DO for low-velocity streams. The lowest DO concentrations were observed during March (early autumn) when water temperatures and macrophyte biomass were high. Spatial comparisons indicated that low-gradient tidal streams were at greater risk of DO depletions harmful to aquatic life. Tidal influence was stronger in low-gradient streams, which typically drain more developed catchments, have lower reaeration potential and offer conditions more suitable for aquatic plant proliferation. Combined, these characteristics supported a simple method based on the extent of low-gradient channel for identifying coastal streams at risk of DO depletion. High-risk streams can then be targeted for riparian planting, nutrient limits and water allocation controls to reduce potential ecological stress.     

黑龙江省“十三五”时期生态环境质量变化及趋势预测

以黑龙江省生态环境监测网监测结果为基础,总结归纳了"十三五"期间黑龙江省生态环境质量变化特征,并采用随机森林和GM(1,1)预测模型对"十四五"期间黑龙江省生态环境质量状况进行了预测。结果表明:"十三五"期间,黑龙江省环境空气、水环境和声环境质量全面好转。其中,环境空气主要污染物PM_2.5、PM₁₀、SO₂、NO₂和CO的年均质量浓度均呈现出明显下降的趋势,"哈大绥"重点区域PM₁₀、SO₂、NO₂和CO年均质量浓度呈现下降趋势。地表水水质总体呈波动变化趋势,水质状况均为轻度污染。"十四五"期间,黑龙江省生态环境质量将处于稳中向好的趋势。环境空气主要污染物及地表水主要污染指标年均质量浓度均呈现明显的下降趋势,道路交通声环境质量也将得到进一步改善。     

Evaluation of ogawa passive sampling devices as an alternative measurement method for the nitrogen dioxide annual standard in El Paso, Texas

Nitrogen Dioxide (NO₂) is a common urban air pollutant that results from the combustion of fossil fuels. It causes serious human health effects, is a precursor to the formation of ground level ozone, another serious air pollutant, and is one of the six criteria air pollutants established by the United States (U.S.) Clean Air Act (CAA). Ogawa Passive Sampling Devices (PSDs) for NO₂ were collocated and operated at six NO₂ Federal Reference Method (FRM) monitor locations in the El Paso, Texas area for the 2004 calendar year. Passive samples were taken at 2-week, 3-week, and 4-week intervals and compared against the continuously operating FRM monitors. Results showed that the collective NO₂ annual arithmetic mean for all passive monitors was identical to the NO₂ mean for all FRM monitors. Of the individual locations, three passive annual NO₂ means were identical to their corresponding FRM means, and three passive annual NO₂ means differed from their corresponding FRM means by only one part per billion (ppb). Linear correlation analysis between all readings of the individual NO₂ PSDs and FRM values showed an average absolute difference of 1.2 ppb with an r ² of 0.95. Paired comparison between high and low concentration annual NO₂ sites, seasonal considerations, and interlab quality control comparisons all showed excellent results. The ease of deployment, reliability, and the cost-savings that can be realized with NO₂ PSDs could make them an attractive alternative to FRM monitors for screening purposes, and even possibly an equivalent method for annual NO₂ monitoring. More tests of the Ogawa NO₂ PSD are recommended for different ecosystem and climate regimes.     

Duck Populations as Indicators of Landscape Condition in the Prairie Pothole Region

The Prairie Pothole Region of the northern GreatPlains is an important region for waterfowl production becauseof the abundance of shallow wetlands. The ecologicalsignificance of the region and impacts from intensiveagriculture prompted the U.S. Environmental Protection Agency to select it as one ofthe first areas for developing and evaluating ecologicalindicators of wetland condition. We examined hypothesizedrelations between indicators of landscape and wetlandconditions and waterfowl abundance on 45 40 km² study sites in North Dakota for1995–1996. Landscape condition was defined a priori as the ratio of cropland area to total upland area surroundingwetlands. Measures of waterfowl abundance included estimatednumbers of breeding pairs (by species and total numbers) and , a species-specific correction factor which effectively adjusts breedingpair estimates for annual or area-related differences in pondsize. Landscape indicators and waterfowl measures varied among regions. Results indicated that most areas in the Coteau region are ofmuch higher quality for ducks than those in the Drift Plain,and areas in the Red River Valley are of the poorest qualityfor ducks. Regression models demonstrated the impact ofagricultural development on breeding duck populations in the PrairiePothole Region. The most consistent landscape indicators ofwaterfowl abundance were percent of cropland and grassland. Models were inconsistent among years and species. Thepotential biotic indicators of landscape and wetland condition examined here wouldbe appropriate for temporal trend analyses, but because ofinherent geographic variability would not be appropriate forsingle-year geographic trend analyses without more extensiveevaluations to improve explanatory models.     

Socioeconomic Risks of Extreme El Niño Event-Related Road Damages in Peru

This study evaluates the socioeconomic risk that extreme El Niño event-related road damages present to Peru by combining an environmental modelling of events’ occurrences in the country with a quantitative modelling of their effects on its economy. The dynamic of occurrence of events is modelled as a stochastic process with a vector autoregressive representation based on historical climatic data, and simulated over a 10-year period with a non-parametric bootstrap procedure. The indirect consequences of events’ related road damages are addressed with a multiregional dynamic computable general equilibrium model through an increase in interregional transportation costs and, more originally, a negative externality effect on activities’ output, which is estimated beforehand using a firm database. We find that extreme El Niño events constitute a significant one-off disaster risk for the country, threatening shifts of???2.8% in GDP and?+?1.9% in poverty rates with an annual probability p?=?1.4%. We further show that they also present a longer-term risk, leading to average annual deviations from normal trend by???0.8% in GDP and?+?0.4% in poverty rate with a probability p?=?12.6% over a 10-year period. However, we finally show that Peru might reduce these socioeconomic risks associated with these non-frequent but recurrent climatic shocks in constructing more disaster-resilient road infrastructure.

     

Variable-source flood pulsing in a semi-arid transboundary watershed: the Chobe River, Botswana and Namibia

The Chobe River, characterized by an unusual flood pulsing regime and shared between Botswana and Namibia, lies at the heart of the world’s largest transfrontier conservation area (the Kavango–Zambezi Transfrontier Conservation Area). Significant ecological changes and vegetation conversions are occurring along its floodplains. Various scenarios for agricultural and urban water use are currently being proposed by the government of Botswana. However, the understanding of the river’s annual flow regime and timing of the relative contributions of water from three different sources is relatively poor. In light of past and future climate change and variability, this means that allocating water between ecological flows and economic and domestic uses will become increasingly challenging. We reconstruct the inundation history in this basin to help ease this challenge. This paper presents a spatiotemporal approach to estimate the contribution of water from various sources and the magnitude of changes in the flooding extent in the basin between 1985 and 2010. We used time series analysis of bimonthly NOAA AVHRR and NASA MODIS data and climatologic and hydrologic records to determine the flooding timing and extent. The results indicate that between 12 and 62 % of the basin is flooded on an annual basis and that the spatial extent of the flooding varies throughout the year as a function of the timing of peak discharge in two larger basins. A 30-year trend analysis indicates a consistent decline in the average monthly flooded area in the basin. The results may prove useful in future water utilization feasibility studies, in determining measures for protecting ecological flows and levels, and in ecosystem dynamics studies in the context of current and future climate change and variability.     

Response of non-point source pollutant loads to climate change in the Shitoukoumen reservoir catchment

The impacts of climate change on streamflow and non-point source pollutant loads in the Shitoukoumen reservoir catchment are predicted by combining a general circulation model (HadCM3) with the Soil and Water Assessment Tool (SWAT) hydrological model. A statistical downscaling model was used to generate future local scenarios of meteorological variables such as temperature and precipitation. Then, the downscaled meteorological variables were used as input to the SWAT hydrological model calibrated and validated with observations, and the corresponding changes of future streamflow and non-point source pollutant loads in Shitoukoumen reservoir catchment were simulated and analyzed. Results show that daily temperature increases in three future periods (2010–2039, 2040–2069, and 2070–2099) relative to a baseline of 1961–1990, and the rate of increase is 0.63°C per decade. Annual precipitation also shows an apparent increase of 11 mm per decade. The calibration and validation results showed that the SWAT model was able to simulate well the streamflow and non-point source pollutant loads, with a coefficient of determination of 0.7 and a Nash–Sutcliffe efficiency of about 0.7 for both the calibration and validation periods. The future climate change has a significant impact on streamflow and non-point source pollutant loads. The annual streamflow shows a fluctuating upward trend from 2010 to 2099, with an increase rate of 1.1 m³ s⁻¹ per decade, and a significant upward trend in summer, with an increase rate of 1.32 m³ s⁻¹ per decade. The increase in summer contributes the most to the increase of annual load compared with other seasons. The annual NH₄⁺-N load into Shitoukoumen reservoir shows a significant downward trend with a decrease rate of 40.6 t per decade. The annual TP load shows an insignificant increasing trend, and its change rate is 3.77 t per decade. The results of this analysis provide a scientific basis for effective support of decision makers and strategies of adaptation to climate change.     

Estimation of Ozone Trend in Central Greece, Based on Meteorologically Adjusted Time Series

Data referring to an approximately 8-year period (1999–2007) are analyzed in order to estimate the trend of the daily maximum hourly value of ozone concentration at the east coast of central Greece, where the summer background ozone concentration is high. A Kolmogorov–Zurbenko filter is applied to remove the short-term component from the raw time series of ozone and meteorological variables. Regression models are developed in order to produce meteorologically adjusted ozone time series, involving the noise-free temperature, relative humidity, and wind speed as independent variables. The analysis verifies that the meteorological adjustment provides better results on estimating ozone’s trend, which is found to be increasing (α?=?0.001) with an annual rate of 1.34?±?0.07?μg/m³. This trend could mainly be attributed to policy and changes in the emissions of ozone’s precursors. Additionally, the short-term component of ozone concentration is also meteorologically adjusted and its impact on the trend is examined. The analysis shows that its contribution is of minor importance when the ozone trend is adjusted by temperature, relative humidity, and wind speed. Moreover, the sea breeze circulation system that is frequently developed in the area influences the short-term and seasonal ozone variation, and therefore, it should be taken into account when producing meteorologically adjusted time series. The study’s conclusions could be exploited by environmental and agricultural authorities in order to develop their long-term strategies towards the air quality management.     

Spatio-temporal prediction of atmospheric benzene (Part I)

Benzene is a carcinogenic and genotoxic pollutant which mainly affects the people health through the inhalation. Nevertheless, this pollutant is not frequently measured by air-quality networks. To solve this problem, some models have been published to estimate benzene concentrations in the atmosphere. However, the lack of measures makes difficult the application of complex models in order to get a detailed spatio-temporal analysis, namely in urban areas. In this work was developed a simple semi-empirical model to predict benzene concentrations based on the ratio of benzene and carbon monoxide concentrations in order to predict the concentrations of this pollutant in large areas and periods with lack of benzene measurements but with higher impact in the human health. The model was applied to an urban area, the Metropolitan Area of Oporto, for a period of 12 years (1995–2006). Monthly correlations between benzene and carbon monoxide concentrations at Custóias air-quality station are significant (p = 0.01) and higher in winter (r _s > 0.7) than in summer (0.3 > r _s > 0.7). Estimate of the monthly ratio of the concentration of these two pollutants range between 199 and 305. The methodology validation shows good results (r _s = 0.81) which allow, assuming the availability of carbon monoxide data, the use of this tool for areas with low benzene recorded data. The application of this methodology in the study area shows an annual average trend decrease of benzene concentrations during the study period, which may be linked to a general trend decrease of benzene emissions in European urban areas, including the study domain.     

Annual and Seasonal Rainfall Trends in an Equatorial Tropical River Basin in Malaysian Borneo

Annual and seasonal rainfall trends in the Limbang River Basin (LRB), located in the equatorial tropics of Malaysian Borneo, have been characterised through Mann-Kendall and Spearman’s Rho non-parametric tests. Rainfall from 13 rain gauge stations in the LRB for the period 1948–2016 was examined in the present study. Basic statistical analysis of rainfall in the region indicates normal distribution, low missing percentage and homogenous characteristics of precipitation. Annual and seasonal rainfall in the LRB shows spatial variation while considering different rain gauge stations. In annual rainfall, eight stations showed a decreasing trend and five stations showed an increasing trend. Rain gauge stations which showed a statistically significant increase in annual rainfall were Limbang DID (2.77 and 2.85 mm/year) and Long Napir (3.65 and 3.77 mm/year). In recognising the two annual monsoon seasons in this area, a significant increase in rainfall was noticed in Long Napir (2.79 and 2.88 mm/year) during the Southwest monsoon (SWM) period. During the Northeast monsoon (NEM), along with Long Napir (3.90 and 3.95 mm/year), Limbang DID (2.86 and 3.02 mm/year), Pandaruan (1.82 and 1.87 mm/year) and Medamit Nanga (1.93 and 2.00 mm/year) also showed a significant increase in rainfall. At the same time, a distinct trend was noticed in rainfall amounts during the inter-monsoon (IM) periods. During the first inter-monsoon month (April), seven rain gauge stations showed an increasing trend in rainfall, whereas in the second inter-monsoon month (October), nine stations showed a decreasing rainfall trend. In April, Long Napir (1.86 and 1.95 mm/year) indicated a significant increasing trend, whereas in the month of October, the rain gauge station at Ukong showed a significant decreasing trend (− 2.45 and − 2.37 mm/year). Though minor spatial changes in trend characteristics were observed among the rain gauge stations, the LRB as a whole showed a consistent increasing (significant and non-significant) trend in annual and seasonal rainfall.

     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

Tree-ring analysis for the assessment of anthropogenic changes and trends

Investigation of Pine (Pinus sylvestris L.)annual radial increment (width of annual tree rings) was carriedout in the surroundings of one of the largest pollution sources inLithuania – Jonava Nitrogen Fertilizers Plant. The main objectiveof investigation was to analyse different sides of anthropogenictransformations of tree-ring series in the polluted environment:changes in tree growth intensity; variance changes in tree-ringseries; changes in the relations with natural external factors.Three different periods of tree reaction to the environmentalpollution were singled out – fertilization period, depressionperiod and recovery period since annual emissions were essentiallyreduced. The variance of tree-ring series has increased severaltimes in the polluted environment. Reaction of trees to the impactof climatic factors (temperature, precipitation) has changedsignificantly in the polluted environment and their sensitivity hasalso increased.