diff --git a/scripts/plot_network.py b/scripts/plot_network.py
index 2aaef6bc..edd6aba9 100644
--- a/scripts/plot_network.py
+++ b/scripts/plot_network.py
@@ -150,7 +150,7 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
     to_drop = costs.index.levels[0].symmetric_difference(n.buses.index)
     if len(to_drop) != 0:
         print("dropping non-buses", to_drop)
-        costs.drop(to_drop, level=0, inplace=True, axis=0)
+        costs.drop(to_drop, level=0, inplace=True, axis=0, errors="ignore")
 
     # make sure they are removed from index
     costs.index = pd.MultiIndex.from_tuples(costs.index.values)
@@ -251,19 +251,19 @@ def plot_h2_map(network):
     # Drop non-electric buses so they don't clutter the plot
     n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
 
-    elec = n.links.index[n.links.carrier == "H2 Electrolysis"]
+    elec = n.links[n.links.carrier.isin(["H2 Electrolysis", "H2 Fuel Cell"])].index
 
-    bus_sizes = n.links.loc[elec,"p_nom_opt"].groupby(n.links.loc[elec,"bus0"]).sum() / bus_size_factor
+    bus_sizes = n.links.loc[elec,"p_nom_opt"].groupby([n.links["bus0"], n.links.carrier]).sum() / bus_size_factor
 
     # make a fake MultiIndex so that area is correct for legend
-    bus_sizes.index = pd.MultiIndex.from_product(
-        [bus_sizes.index, ["electrolysis"]])
+    bus_sizes.rename(index=lambda x: x.replace(" H2", ""), level=0, inplace=True)
 
-    n.links.drop(n.links.index[n.links.carrier != "H2 pipeline"], inplace=True)
+    n.links.drop(n.links.index[~n.links.carrier.str.contains("H2 pipeline")], inplace=True)
 
     link_widths = n.links.p_nom_opt / linewidth_factor
     link_widths[n.links.p_nom_opt < line_lower_threshold] = 0.
 
+
     n.links.bus0 = n.links.bus0.str.replace(" H2", "")
     n.links.bus1 = n.links.bus1.str.replace(" H2", "")
 
@@ -276,7 +276,8 @@ def plot_h2_map(network):
     fig.set_size_inches(7, 6)
 
     n.plot(bus_sizes=bus_sizes,
-           bus_colors={"electrolysis": bus_color},
+           bus_colors={"H2 Electrolysis": bus_color,
+                       "H2 Fuel Cell": "slateblue"},
            link_colors=link_color,
            link_widths=link_widths,
            branch_components=["Link"],
@@ -311,6 +312,266 @@ def plot_h2_map(network):
                 bbox_inches="tight")
 
 
+def plot_ch4_map(network):
+
+    n = network.copy()
+
+    supply_energy = get_nodal_balance().droplevel([0,1]).sort_index()
+
+    if "Gas pipeline" not in n.links.carrier.unique():
+        return
+
+    assign_location(n)
+
+    bus_size_factor = 1e7
+    linewidth_factor = 1e4
+    # MW below which not drawn
+    line_lower_threshold = 5e3
+    bus_color = "maroon"
+    link_color = "lightcoral"
+
+    # Drop non-electric buses so they don't clutter the plot
+    n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
+
+    elec = n.generators[n.generators.carrier=="gas"].index
+    methanation_i = n.links[n.links.carrier.isin(["helmeth", "Sabatier"])].index
+
+    bus_sizes = n.generators_t.p.loc[:,elec].mul(n.snapshot_weightings, axis=0).sum().groupby(n.generators.loc[elec,"bus"]).sum() / bus_size_factor
+    bus_sizes.rename(index=lambda x: x.replace(" gas", ""), inplace=True)
+    bus_sizes = bus_sizes.reindex(n.buses.index).fillna(0)
+    bus_sizes.index = pd.MultiIndex.from_product(
+    [bus_sizes.index, ["fossil gas"]])
+
+    methanation = abs(n.links_t.p1.loc[:,methanation_i].mul(n.snapshot_weightings, axis=0)).sum().groupby(n.links.loc[methanation_i,"bus1"]).sum() / bus_size_factor
+    methanation = methanation.groupby(methanation.index).sum().rename(index=lambda x: x.replace(" gas", ""))
+    # make a fake MultiIndex so that area is correct for legend
+    methanation.index = pd.MultiIndex.from_product(
+        [methanation.index, ["methanation"]])
+
+    biogas_i = n.stores[n.stores.carrier=="biogas"].index
+    biogas = n.stores_t.p.loc[:,biogas_i].mul(n.snapshot_weightings, axis=0).sum().groupby(n.stores.loc[biogas_i,"bus"]).sum() / bus_size_factor
+    biogas = biogas.groupby(biogas.index).sum().rename(index=lambda x: x.replace(" biogas", ""))
+    # make a fake MultiIndex so that area is correct for legend
+    biogas.index = pd.MultiIndex.from_product(
+        [biogas.index, ["biogas"]])
+
+    bus_sizes = pd.concat([bus_sizes, methanation, biogas])
+    bus_sizes.sort_index(inplace=True)
+
+    n.links.drop(n.links.index[n.links.carrier != "Gas pipeline"], inplace=True)
+
+    link_widths = n.links.p_nom_opt / linewidth_factor
+    link_widths[n.links.p_nom_opt < line_lower_threshold] = 0.
+
+    n.links.bus0 = n.links.bus0.str.replace(" gas", "")
+    n.links.bus1 = n.links.bus1.str.replace(" gas", "")
+
+    print(link_widths.sort_values())
+
+    print(n.links[["bus0", "bus1"]])
+
+    fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
+
+    fig.set_size_inches(7, 6)
+
+    n.plot(bus_sizes=bus_sizes,
+           bus_colors={"fossil gas": bus_color,
+                       "methanation": "steelblue",
+                       "biogas": "seagreen"},
+           link_colors=link_color,
+           link_widths=link_widths,
+           branch_components=["Link"],
+           ax=ax,  boundaries=(-10, 30, 34, 70))
+
+    handles = make_legend_circles_for(
+        [200, 1000], scale=bus_size_factor, facecolor=bus_color)
+    labels = ["{} MW".format(s) for s in (200, 1000)]
+    l2 = ax.legend(handles, labels,
+                   loc="upper left", bbox_to_anchor=(0.01, 1.01),
+                   labelspacing=1.0,
+                   framealpha=1.,
+                   title='Biomass potential',
+                   handler_map=make_handler_map_to_scale_circles_as_in(ax))
+    ax.add_artist(l2)
+
+    handles = []
+    labels = []
+
+    for s in (50, 10):
+        handles.append(plt.Line2D([0], [0], color=link_color,
+                                  linewidth=s * 1e3 / linewidth_factor))
+        labels.append("{} GW".format(s))
+    l1_1 = ax.legend(handles, labels,
+                     loc="upper left", bbox_to_anchor=(0.30, 1.01),
+                     framealpha=1,
+                     labelspacing=0.8, handletextpad=1.5,
+                     title='CH4 pipeline capacity')
+    ax.add_artist(l1_1)
+
+    fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_network"), transparent=True,
+                bbox_inches="tight")
+
+    ##################################################
+    supply_energy.drop("Gas pipeline", level=1, inplace=True)
+    supply_energy = supply_energy[abs(supply_energy)>5]
+    supply_energy.rename(index=lambda x: x.replace(" gas",""), level=0, inplace=True)
+
+
+    demand = supply_energy[supply_energy<0].groupby(level=[0,1]).sum()
+    supply = supply_energy[supply_energy>0].groupby(level=[0,1]).sum()
+
+    #### DEMAND #######################################
+    bus_size_factor = 2e7
+    bus_sizes = abs(demand) / bus_size_factor
+
+    fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
+
+    fig.set_size_inches(7, 6)
+
+    n.plot(bus_sizes=bus_sizes,
+           bus_colors={"CHP": "r",
+                       "OCGT": "wheat",
+                       "SMR": "darkkhaki",
+                       "SMR CC": "tan",
+                       "gas boiler": "orange",
+                       "gas for industry": "grey",
+                       'gas for industry CC': "lightgrey"},
+           link_colors=link_color,
+           link_widths=link_widths,
+           branch_components=["Link"],
+           ax=ax,  boundaries=(-10, 30, 34, 70))
+
+    handles = make_legend_circles_for(
+        [10e6, 20e6], scale=bus_size_factor, facecolor=bus_color)
+    labels = ["{} TWh".format(s) for s in (10, 20)]
+    l2 = ax.legend(handles, labels,
+                   loc="upper left", bbox_to_anchor=(0.01, 1.01),
+                   labelspacing=1.0,
+                   framealpha=1.,
+                   title='CH4 demand',
+                   handler_map=make_handler_map_to_scale_circles_as_in(ax))
+    ax.add_artist(l2)
+
+    handles = []
+    labels = []
+
+    for s in (50, 10):
+        handles.append(plt.Line2D([0], [0], color=link_color,
+                                  linewidth=s * 1e3 / linewidth_factor))
+        labels.append("{} GW".format(s))
+    l1_1 = ax.legend(handles, labels,
+                     loc="upper left", bbox_to_anchor=(0.30, 1.01),
+                     framealpha=1,
+                     labelspacing=0.8, handletextpad=1.5,
+                     title='CH4 pipeline capacity')
+    ax.add_artist(l1_1)
+
+    fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_demand"), transparent=True,
+                bbox_inches="tight")
+
+
+     #### SUPPLY #######################################
+    bus_size_factor = 2e7
+    bus_sizes = supply / bus_size_factor
+
+    fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
+
+    fig.set_size_inches(7, 6)
+
+    n.plot(bus_sizes=bus_sizes,
+           bus_colors={"gas": "maroon",
+                       "methanation": "steelblue",
+                       "helmeth": "slateblue",
+                       "biogas": "seagreen"},
+           link_colors=link_color,
+           link_widths=link_widths,
+           branch_components=["Link"],
+           ax=ax,  boundaries=(-10, 30, 34, 70))
+
+    handles = make_legend_circles_for(
+        [10e6, 20e6], scale=bus_size_factor, facecolor="black")
+    labels = ["{} TWh".format(s) for s in (10, 20)]
+    l2 = ax.legend(handles, labels,
+                   loc="upper left", bbox_to_anchor=(0.01, 1.01),
+                   labelspacing=1.0,
+                   framealpha=1.,
+                   title='CH4 supply',
+                   handler_map=make_handler_map_to_scale_circles_as_in(ax))
+    ax.add_artist(l2)
+
+    handles = []
+    labels = []
+
+    for s in (50, 10):
+        handles.append(plt.Line2D([0], [0], color=link_color,
+                                  linewidth=s * 1e3 / linewidth_factor))
+        labels.append("{} GW".format(s))
+    l1_1 = ax.legend(handles, labels,
+                     loc="upper left", bbox_to_anchor=(0.30, 1.01),
+                     framealpha=1,
+                     labelspacing=0.8, handletextpad=1.5,
+                     title='CH4 pipeline capacity')
+    ax.add_artist(l1_1)
+
+    fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_supply"), transparent=True,
+                bbox_inches="tight")
+
+    ###########################################################################
+    net = pd.concat([demand.groupby(level=0).sum().rename("demand"),
+                     supply.groupby(level=0).sum().rename("supply")], axis=1).sum(axis=1)
+    mask = net>0
+    net_importer = net.mask(mask).rename("net_importer")
+    net_exporter = net.mask(~mask).rename("net_exporter")
+
+    bus_size_factor = 2e7
+    linewidth_factor = 1e-1
+    bus_sizes = pd.concat([abs(net_importer), net_exporter], axis=1).fillna(0).stack() / bus_size_factor
+
+    link_widths = abs(n.links_t.p0).max().loc[n.links.index] / n.links.p_nom_opt
+    link_widths /= linewidth_factor
+
+
+    fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
+
+    fig.set_size_inches(7, 6)
+
+    n.plot(bus_sizes=bus_sizes,
+           bus_colors={"net_importer": "r",
+                       "net_exporter": "darkgreen",
+                       },
+           link_colors="lightgrey",
+           link_widths=link_widths,
+           branch_components=["Link"],
+           ax=ax,  boundaries=(-10, 30, 34, 70))
+
+    handles = make_legend_circles_for(
+        [10e6, 20e6], scale=bus_size_factor, facecolor="black")
+    labels = ["{} TWh".format(s) for s in (10, 20)]
+    l2 = ax.legend(handles, labels,
+                   loc="upper left", bbox_to_anchor=(0.01, 1.01),
+                   labelspacing=1.0,
+                   framealpha=1.,
+                   title='Net Import/Export',
+                   handler_map=make_handler_map_to_scale_circles_as_in(ax))
+    ax.add_artist(l2)
+
+    handles = []
+    labels = []
+
+    for s in (0.5, 1):
+        handles.append(plt.Line2D([0], [0], color="lightgrey",
+                                  linewidth=s / linewidth_factor))
+        labels.append("{} per unit".format(s))
+    l1_1 = ax.legend(handles, labels,
+                     loc="upper left", bbox_to_anchor=(0.30, 1.01),
+                     framealpha=1,
+                     labelspacing=0.8, handletextpad=1.5,
+                     title='maximum used CH4 pipeline capacity')
+    ax.add_artist(l1_1)
+
+    fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_net_balance"), transparent=True,
+                bbox_inches="tight")
+
 def plot_map_without(network):
 
     n = network.copy()
@@ -331,7 +592,8 @@ def plot_map_without(network):
     dc_color = "m"
 
     # hack because impossible to drop buses...
-    n.buses.loc["EU gas", ["x", "y"]] = n.buses.loc["DE0 0", ["x", "y"]]
+    if "EU gas" in n.buses.index:
+        n.buses.loc["EU gas", ["x", "y"]] = n.buses.loc["DE0 0", ["x", "y"]]
 
     n.links.drop(n.links.index[(n.links.carrier != "DC") & (
         n.links.carrier != "B2B")], inplace=True)
@@ -502,35 +764,59 @@ def plot_series(network, carrier="AC", name="test"):
         transparent=True)
 
 
+def get_nodal_balance(carrier="gas"):
+
+    bus_map = (n.buses.carrier == carrier)
+    bus_map.at[""] = False
+    supply_energy = pd.Series(dtype="float64")
+
+    for c in n.iterate_components(n.one_port_components):
+
+        items = c.df.index[c.df.bus.map(bus_map).fillna(False)]
+
+        if len(items) == 0:
+            continue
+
+        s = round(c.pnl.p.multiply(n.snapshot_weightings,axis=0).sum().multiply(c.df['sign']).loc[items]
+             .groupby([c.df.bus, c.df.carrier]).sum())
+        s = pd.concat([s], keys=[c.list_name])
+        s = pd.concat([s], keys=[carrier])
+
+        supply_energy = supply_energy.reindex(s.index.union(supply_energy.index))
+        supply_energy.loc[s.index] = s
+
+
+    for c in n.iterate_components(n.branch_components):
+
+        for end in [col[3:] for col in c.df.columns if col[:3] == "bus"]:
+
+            items = c.df.index[c.df["bus" + str(end)].map(bus_map,na_action=False)]
+
+            if len(items) == 0:
+                continue
+
+            s = ((-1)*c.pnl["p"+end][items].multiply(n.snapshot_weightings,axis=0).sum()
+                .groupby([c.df.loc[items,'bus{}'.format(end)], c.df.loc[items,'carrier']]).sum())
+            s.index = s.index
+            s = pd.concat([s], keys=[c.list_name])
+            s = pd.concat([s], keys=[carrier])
+
+            supply_energy = supply_energy.reindex(s.index.union(supply_energy.index))
+
+            supply_energy.loc[s.index] = s
+
+    supply_energy = supply_energy.rename(index=lambda x: rename_techs(x), level=3)
+    return supply_energy
+
 # %%
 if __name__ == "__main__":
     # Detect running outside of snakemake and mock snakemake for testing
     if 'snakemake' not in globals():
-        from vresutils import Dict
-        import yaml
-        snakemake = Dict()
-        with open('config.yaml') as f:
-            snakemake.config = yaml.safe_load(f)
-        snakemake.config['run'] = "retro_vs_noretro"
-        snakemake.wildcards = {"lv": "1.0"}  # lv1.0, lv1.25, lvopt
-        name = "elec_s_48_lv{}__Co2L0-3H-T-H-B".format(snakemake.wildcards["lv"])
-        suffix = "_retro_tes"
-        name = name + suffix
-        snakemake.input = Dict()
-        snakemake.output = Dict(
-            map=(snakemake.config['results_dir'] + snakemake.config['run']
-                 + "/maps/{}".format(name)),
-            today=(snakemake.config['results_dir'] + snakemake.config['run']
-                   + "/maps/{}.pdf".format(name)))
-        snakemake.input.scenario = "lv" + snakemake.wildcards["lv"]
-#        snakemake.config["run"] = "bio_costs"
-        path = snakemake.config['results_dir'] + snakemake.config['run']
-        snakemake.input.network = (path +
-                                   "/postnetworks/{}.nc"
-                                   .format(name))
-        snakemake.output.network = (path +
-                                    "/maps/{}"
-                                    .format(name))
+        from helper import mock_snakemake
+        snakemake = mock_snakemake('plot_network',
+                                   network='elec', simpl='', clusters='128',
+                                   lv='1.0', opts='', planning_horizons='2030',
+                                   sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1')
 
     n = pypsa.Network(snakemake.input.network,
                       override_component_attrs=override_component_attrs)
@@ -539,6 +825,7 @@ if __name__ == "__main__":
              bus_size_factor=1.5e10, transmission=False)
 
     plot_h2_map(n)
+    plot_ch4_map(n)
     plot_map_without(n)
 
     #plot_series(n, carrier="AC", name=suffix)
diff --git a/scripts/plot_summary.py b/scripts/plot_summary.py
index 9b3a81e1..7b0200df 100644
--- a/scripts/plot_summary.py
+++ b/scripts/plot_summary.py
@@ -22,7 +22,8 @@ def rename_techs(label):
                                "retrofitting" : "building retrofitting",
                                "H2" : "hydrogen storage",
                                "battery" : "battery storage",
-                               "CC" : "CC"}
+                               #"CC" : "CC"
+                               }
 
     rename = {"solar" : "solar PV",
               "Sabatier" : "methanation",
@@ -258,7 +259,7 @@ def historical_emissions(cts):
     e["domestic navigation"] = "1.A.3.d - Domestic Navigation"
     e['international navigation'] = '1.D.1.b - International Navigation'
     e["domestic aviation"] = '1.A.3.a - Domestic Aviation'
-    e["international aviation"] = '1.D.1.a - International Aviation'   
+    e["international aviation"] = '1.D.1.a - International Aviation'
     e['total energy'] = '1 - Energy'
     e['industrial processes'] = '2 - Industrial Processes and Product Use'
     e['agriculture'] = '3 - Agriculture'
@@ -268,25 +269,25 @@ def historical_emissions(cts):
     e['indirect'] = 'ind_CO2 - Indirect CO2'
     e["total wL"] = "Total (with LULUCF)"
     e["total woL"] = "Total (without LULUCF)"
-       
-    pol = ["CO2"] # ["All greenhouse gases - (CO2 equivalent)"] 
+
+    pol = ["CO2"] # ["All greenhouse gases - (CO2 equivalent)"]
     cts
     if "GB" in cts:
         cts.remove("GB")
         cts.append("UK")
-         
+
     year = np.arange(1990,2018).tolist()
 
     idx = pd.IndexSlice
-    co2_totals = df.loc[idx[year,e.values,cts,pol],"emissions"].unstack("Year").rename(index=pd.Series(e.index,e.values)) 
-    
+    co2_totals = df.loc[idx[year,e.values,cts,pol],"emissions"].unstack("Year").rename(index=pd.Series(e.index,e.values))
+
     co2_totals = (1/1e6)*co2_totals.groupby(level=0, axis=0).sum() #Gton CO2
 
     co2_totals.loc['industrial non-elec'] = co2_totals.loc['total energy'] - co2_totals.loc[['electricity', 'services non-elec','residential non-elec', 'road non-elec',
                                                                               'rail non-elec', 'domestic aviation', 'international aviation', 'domestic navigation',
                                                                               'international navigation']].sum()
 
-    emissions = co2_totals.loc["electricity"]   
+    emissions = co2_totals.loc["electricity"]
     if "T" in opts:
         emissions += co2_totals.loc[[i+ " non-elec" for i in ["rail","road"]]].sum()
     if "H" in opts:
@@ -294,7 +295,7 @@ def historical_emissions(cts):
     if "I" in opts:
         emissions += co2_totals.loc[["industrial non-elec","industrial processes",
                                           "domestic aviation","international aviation",
-                                          "domestic navigation","international navigation"]].sum()           
+                                          "domestic navigation","international navigation"]].sum()
     return emissions
 
 
@@ -302,8 +303,8 @@ def historical_emissions(cts):
 def plot_carbon_budget_distribution():
     """
     Plot historical carbon emissions in the EU and decarbonization path
-    """ 
-    
+    """
+
     import matplotlib.gridspec as gridspec
     import seaborn as sns; sns.set()
     sns.set_style('ticks')
@@ -311,7 +312,7 @@ def plot_carbon_budget_distribution():
     plt.rcParams['xtick.direction'] = 'in'
     plt.rcParams['ytick.direction'] = 'in'
     plt.rcParams['xtick.labelsize'] = 20
-    plt.rcParams['ytick.labelsize'] = 20   
+    plt.rcParams['ytick.labelsize'] = 20
 
     plt.figure(figsize=(10, 7))
     gs1 = gridspec.GridSpec(1, 1)
@@ -319,55 +320,55 @@ def plot_carbon_budget_distribution():
     ax1.set_ylabel('CO$_2$ emissions (Gt per year)',fontsize=22)
     ax1.set_ylim([0,5])
     ax1.set_xlim([1990,snakemake.config['scenario']['planning_horizons'][-1]+1])
-    
+
     path_cb = snakemake.config['results_dir'] + snakemake.config['run'] + '/csvs/'
-    countries=pd.read_csv(path_cb + 'countries.csv',  index_col=1) 
+    countries=pd.read_csv(path_cb + 'countries.csv',  index_col=1)
     cts=countries.index.to_list()
-    e_1990 = co2_emissions_year(cts, opts, year=1990)     
-    CO2_CAP=pd.read_csv(path_cb + 'carbon_budget_distribution.csv',  
-                        index_col=0) 
-    
-    
-    ax1.plot(e_1990*CO2_CAP[o],linewidth=3, 
+    e_1990 = co2_emissions_year(cts, opts, year=1990)
+    CO2_CAP=pd.read_csv(path_cb + 'carbon_budget_distribution.csv',
+                        index_col=0)
+
+
+    ax1.plot(e_1990*CO2_CAP[o],linewidth=3,
                          color='dodgerblue', label=None)
-            
+
     emissions = historical_emissions(cts)
 
-    ax1.plot(emissions, color='black', linewidth=3, label=None) 
-    
-    #plot commited and uder-discussion targets  
+    ax1.plot(emissions, color='black', linewidth=3, label=None)
+
+    #plot commited and uder-discussion targets
     #(notice that historical emissions include all countries in the
     # network, but targets refer to EU)
     ax1.plot([2020],[0.8*emissions[1990]],
                      marker='*', markersize=12, markerfacecolor='black',
-                     markeredgecolor='black')    
-            
+                     markeredgecolor='black')
+
     ax1.plot([2030],[0.45*emissions[1990]],
                      marker='*', markersize=12, markerfacecolor='white',
-                     markeredgecolor='black')    
-            
+                     markeredgecolor='black')
+
     ax1.plot([2030],[0.6*emissions[1990]],
                      marker='*', markersize=12, markerfacecolor='black',
                      markeredgecolor='black')
-            
+
     ax1.plot([2050, 2050],[x*emissions[1990] for x in [0.2, 0.05]],
-                  color='gray', linewidth=2, marker='_', alpha=0.5) 
-            
+                  color='gray', linewidth=2, marker='_', alpha=0.5)
+
     ax1.plot([2050],[0.01*emissions[1990]],
-                     marker='*', markersize=12, markerfacecolor='white', 
-                     linewidth=0, markeredgecolor='black', 
-                     label='EU under-discussion target', zorder=10, 
-                     clip_on=False) 
-            
+                     marker='*', markersize=12, markerfacecolor='white',
+                     linewidth=0, markeredgecolor='black',
+                     label='EU under-discussion target', zorder=10,
+                     clip_on=False)
+
     ax1.plot([2050],[0.125*emissions[1990]],'ro',
                      marker='*', markersize=12, markerfacecolor='black',
                      markeredgecolor='black', label='EU commited target')
-            
-    ax1.legend(fancybox=True, fontsize=18, loc=(0.01,0.01), 
-                       facecolor='white', frameon=True) 
-            
-    path_cb_plot = snakemake.config['results_dir'] + snakemake.config['run'] + '/graphs/'             
-    plt.savefig(path_cb_plot+'carbon_budget_plot.pdf', dpi=300) 
+
+    ax1.legend(fancybox=True, fontsize=18, loc=(0.01,0.01),
+                       facecolor='white', frameon=True)
+
+    path_cb_plot = snakemake.config['results_dir'] + snakemake.config['run'] + '/graphs/'
+    plt.savefig(path_cb_plot+'carbon_budget_plot.pdf', dpi=300)
 
 if __name__ == "__main__":
     # Detect running outside of snakemake and mock snakemake for testing
@@ -380,15 +381,15 @@ if __name__ == "__main__":
         snakemake.input = Dict()
         snakemake.output = Dict()
         snakemake.wildcards = Dict()
-        #snakemake.wildcards['sector_opts']='3H-T-H-B-I-solar3-dist1-cb48be3'        
-        
+        #snakemake.wildcards['sector_opts']='3H-T-H-B-I-solar3-dist1-cb48be3'
+
         for item in ["costs", "energy"]:
             snakemake.input[item] = snakemake.config['summary_dir'] + '/{name}/csvs/{item}.csv'.format(name=snakemake.config['run'],item=item)
             snakemake.output[item] = snakemake.config['summary_dir'] + '/{name}/graphs/{item}.pdf'.format(name=snakemake.config['run'],item=item)
         snakemake.input["balances"] = snakemake.config['summary_dir'] + '/{name}/csvs/supply_energy.csv'.format(name=snakemake.config['run'],item=item)
         snakemake.output["balances"] = snakemake.config['summary_dir'] + '/{name}/graphs/balances-energy.csv'.format(name=snakemake.config['run'],item=item)
-        
-        
+
+
     n_header = 4
 
     plot_costs()
@@ -396,7 +397,7 @@ if __name__ == "__main__":
     plot_energy()
 
     plot_balances()
-    
+
     for sector_opts in snakemake.config['scenario']['sector_opts']:
         opts=sector_opts.split('-')
         for o in opts: